Antienshittification

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Referee #3

Evidence, reproducibility and clarity

Summary

In this manuscript, the authors investigate the role of the tubulin polyglutamylase TTLL6 in maintaining colonic epithelial homeostasis and its potential role in colorectal cancer (CRC). Using transcriptomic analyses, mouse genetics, histology, and proteomics, the authors report that TTLL6 is highly expressed in colonic epithelial cells and decreases during CRC progression. Constitutive and epithelial-specific deletion of Ttll6 in mice leads to elongated colonic crypts, expansion of proliferative and stem cell compartments, and increased susceptibility to chemically induced colitis-associated carcinogenesis. Mechanistically, the authors identify the nucleic acid-binding protein PurA as a potential non-tubulin substrate of TTLL6. They propose that TTLL6-mediated polyglutamylation of PurA regulates its nuclear localization, thereby contributing to epithelial homeostasis in the colon. Together, the study suggests a TTLL6-PurA axis that may restrain early colorectal tumorigenesis.

Major comments

1. Evidence that PurA is a physiologically relevant TTLL6 substrate remains incomplete. A central conclusion of the manuscript is that PurA is a substrate of TTLL6 whose polyglutamylation regulates nuclear localization. While the authors present several lines of evidence (PolyE immunoprecipitation, co-transfection experiments, and mutagenesis of the PurA C-terminal glutamate residues), the physiological relevance of this modification remains somewhat indirect. For example, polyglutamylation of endogenous PurA in colonic epithelial cells is inferred but not directly demonstrated. The PolyE antibody detects glutamate chains but does not identify the specific modified protein in tissue. Direct evidence that PurA is polyglutamylated in vivo (e.g., MS identification of the modification site on PurA or PurA immunoprecipitation followed by PolyE detection) would strengthen the mechanistic claim. At present, the data convincingly show that TTLL6 can glutamylate PurA in an overexpression system, but the endogenous modification remains less clearly demonstrated.
2. Mechanistic link between PurA localization and the epithelial phenotype is not established. The authors propose that loss of TTLL6 disrupts PurA nuclear localization and thereby alters epithelial homeostasis. However, the manuscript does not establish a causal relationship between PurA localization and the observed crypt phenotypes. Specifically, it is not shown whether PurA loss phenocopies Ttll6 deficiency in the colon. No experiments test whether restoring nuclear PurA rescues the Ttll6 phenotype. Downstream transcriptional or signaling pathways regulated by PurA are not explored. Thus, while the TTLL6-PurA relationship is intriguing, the study remains largely correlative with respect to functional consequences.
3. Interpretation of the tumorigenesis data should be tempered. The authors conclude that Ttll6 deficiency promotes colon carcinogenesis. However, the tumor data appear somewhat limited. Increased tumor numbers are reported only at an early time point (day 40) and are described as a trend toward significance. By day 70, tumor numbers and sizes appear comparable between groups. The increased incidence of vimentin-positive crypts is interesting but does not clearly establish increased tumor burden. Given these results, the conclusion that TTLL6 restrains tumorigenesis may be stronger than supported by the data. The authors may wish to frame this as enhanced early tumor development or altered tumor progression rather than increased tumorigenesis per se.
4. Expansion of multiple epithelial cell populations requires clarification. The authors report that Ttll6-deficient colons exhibit expansion of stem/progenitor compartments as well as increased numbers of differentiated cells (e.g., goblet cells and enterocytes). While these findings are interesting, the biological interpretation is somewhat unclear. For example, expansion of stem/progenitor compartments typically accompanies reduced differentiation rather than increased differentiation. It is not clear whether the increased numbers of differentiated cells reflect overall crypt enlargement or altered lineage allocation. Quantification of cell-type proportions rather than absolute cell numbers would help clarify whether differentiation programs are altered.
5. Nuclear polyglutamylation requires further clarification The authors report nuclear PolyE staining in colonic epithelial cells and propose that this reflects polyglutamylation of non-tubulin substrates such as PurA. However, it is not clear whether other nuclear proteins could account for this signal. The specificity of the nuclear PolyE signal should be better validated. Additional controls (e.g., peptide competition or validation with alternative approaches) would strengthen the interpretation.

Minor comments

1. The manuscript would benefit from clearer distinction between tubulin vs non-tubulin glutamylation throughout the text.
2. Some conclusions in the Discussion appear slightly overstated relative to the data (e.g., the role of the TTLL6-PurA axis in tumor suppression).
3. The description of the Ttll6 mouse models (constitutive vs conditional deletion) could be clarified earlier in the Results section.
4. Quantification methods for histological analyses (crypt length, cell counts, marker-positive cells) should be described in greater detail in the Methods.
5. It would be useful to include representative images of PurA localization in control vs Ttll6-deficient colon tissue in the main figures.
6. Several minor typographical issues appear throughout the manuscript and should be corrected during revision.

Significance

General assessment

This study investigates the role of the polyglutamylase TTLL6 in intestinal epithelial biology and colorectal cancer. The identification of a potential non-tubulin substrate (PurA) is conceptually interesting and expands the emerging view that tubulin-modifying enzymes can regulate additional cellular proteins. The study combines mouse genetics, histological analysis, transcriptomic datasets, and proteomics, which together provide a substantial dataset supporting a role for TTLL6 in regulating crypt architecture and epithelial proliferation. However, the mechanistic link between TTLL6 activity, PurA modification, and epithelial homeostasis remains incompletely resolved. The tumorigenesis data also suggest only modest effects on carcinogenesis.

Advance relative to previous literature

Previous studies have linked members of the TTLL family primarily to microtubule regulation and ciliary biology. This work extends these findings by suggesting a tissue-specific function of TTLL6 in the colon, and the existence of non-tubulin substrates regulating epithelial biology. If further validated, the identification of PurA polyglutamylation could represent an interesting conceptual advance.

The manuscript will likely be of interest to researchers working in cytoskeletal post-translational modifications, intestinal epithelial biology, colorectal cancer biology

My expertise lies in cytoskeletal regulation, epithelial biology, and intestinal tissue organization, which are directly relevant to the central themes of this manuscript.

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Referee #2

Evidence, reproducibility and clarity

Summary: In this study, the authors investigate novel functions of the tubulin typrosine ligase-like protein 6 (TTLL6), which covalently adds glutamate residues to the C-terminus of a given protein. The authors have already published previously on this topic. In the current study, the role of TTLL6 in colon function and pathologies was investigated. The study consists of two major parts. In the first part, a mouse model is used to show that TTLL6 is expressed at elevated levels and activity in epithelial cells of the colon. A database search indicated that TTL6 expression positively correlates with prognosis of patients with colorectal cancer. The authors generated a TTLL6 KO mouse and showed that induced tumor growth at 40 days was more positive for vimentin in the crypts of these mice, which should correlate with tumor aggressiveness. This difference was not observed anymore after 70 days. Morphological analyses of the crypts showed that in TTLL6 KO mice the crypts increased in length, a difference in proliferation markers, and a change of cell types in the crypts was observed.<br /> In the second part, the authors used a modification-specific antibody to immunoprecipitate (IP) proteins modified by TTLLs. To identify TTLL6-dependently modified target proteins, they compared these results with IPs from TTLL6 KO mice. A total of 43 proteins were identified this way. Because of their similarity to the tubuline tail sequence, two of the enriched proteins, PurA and PurB, were further analyzed. The authors provide evidence that PurA but not PurB is modified by TTLL6, which as a result changes its subcellular localization. While the first part of this work provides convincing novel insights into TTLL6's function with potential pathological relevance, the second part raises some concerns. I would therefore tend to rate the quality of the first part significantly higher than the second part.

Major comments:

1) When considering the results of the induced colorectal cancer test, the only significant difference between WT and KO was the moderately higher expression of Vimentin (figure 5E-F). Since this is the main evidence for a pathological relevance of TTLL6 in cancer, it is important to understand how the quantification of Vimentin in the complex tissue shown in figure 5E was done. A detailed description of how these images were analysed and perhaps a table with raw data would be essential to convince the reader of the conclusions. In the currently presented form, I find the analyses not too convincing.

2) Figure 7A: It was somewhat surprising that two of the least significant (PurA is just below the cutoff) were used for further analyses. Although the authors explain that both proteins have strong sequence similarity to the know TTLL6 target, tubuline, the C-terminal, genomically encoded protein sequence of PurA and PurB already contain several glutamates. This raises the concern that the polyE antibody in the IP possibly detected the non-modified C-terminal tail of PurA and PurB and that both proteins may not be modified by TTLL6. Because of this and the lower significance than other candidates, the authors should consider focussing on other hits (OPTIONAL). Besides being much more significant, they lack an accumulation of glutamates in their C-terminus (at least the ones I looked at). Alternatively, the concern of having potentially IP-ed unmodified proteins should be addressed.

3) Figure 8A: this figure compares PurA with a modified PurA that lacks the C-terminal EEE stretch. The authors conclude that the subcellular localization is different between both and that the nuclear localization of WT PURA must be due to modification by the co-expressed TTLL6. There are two major concerns with this conclusion: Firstly, the expression of PurA without TTLL6 co-expression is a missing essential control. This would show if PurA itself is already predominantly located in the nucleus regardless of potential modifications (PurA seems to have different nucleocytoplasmic localization in different cell types). Secondly, both depicted cells look very different. In PurA the nuclei are much smaller and the cytoplasm seems also much smaller than in the PurA DDD-expressing cells. Furthermore, IF staining without proper quantification of several cells seem less than ideal for such conclusions. In case, the authors want to convincingly validate this conclusion such a quantification with several cells would be required. OPTIONAL: an alternative approach would be a nucleo-cytoplasmic fractionation experiment followed by a western blot.

Figure 8B: it seems that the contrast between the images of the upper and lower panel is very different. For this reason, I find it difficult to follow the conclusions. However, even when ignoring this aspect, I have great problems coming to the same conclusions as the authors.

Minor comments:

1) In figure 3A it would help if the legend describes what exactly "Control (+ or -)" means.

2) In figure 3E-F, a label inside of the figure (what is the red bar, what the blue) would help the reader to faster grasp the subfigures.

3) Figure 7C-D: these experiments are based on strong overexpression of TTLLs, which might result in unphysiological modifications of PurA. I would suggest to include a note of caution in the discussion that this is a possibility.

4) In the discussion (page 9, last paragraph), it is stated: "Our findings suggest that the polyglutamylation of PurA is essential for maintaining colonic homeostasis". I do not understand this statement, as this study does not provide any evidence that modification of PurA does play a functional role in the colon (expression itself is not an evidence for function importance or even being "essential"). I recommend to remove this statement.

5) Not all abbreviations are introduced properly (like CRC).

Significance

In general, this study addresses a very interesting aspect - i.e. the covalent addition of multiple glutamate residues to the C-terminus of a target gene by the enzyme TTLL6. The authors convincingly show that this protein regulates the morphology and composition of crypts in subregions of the colon. This is certainly a new and important finding that expands our knowledge about the functional breadth of this class of enzymes. If convincingly validated (see major concerns), also the pathological relevance of this enzyme for cancer progression would be of general interest. However, this statement has to be considered with a note of caution as this is not my area of expertise.

The validation of novel targets of TTLL6 after IP is - at this stage of the manuscript - not very convincing to me. In particular the claim that PurA does play a functional role in the TTLL6-dependent regulation (of crypts) is not justified by the data. However, given that the list of other candidates contains several important gene regulators, this work might have the potential to open up to open up the field for new research directions.

The reviewer's areas of expertise: cell biology, biochemistry, histology.

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Referee #1

Evidence, reproducibility and clarity

Summary:

This study shows that loss of TTLL6 affects colonic epithelial homeostasis (crypt architecture and proliferation/differentiation markers) and proposes that TTLL6 contributes to a nuclear glutamylation signal, with PurA presented as a candidate non-tubulin substrate. The authors also connect TTLL6 mRNA levels to human CRC progression and outcome. Overall, the observations are potentially interesting, but the manuscript currently does not establish a clear mechanistic link between TTLL6 activity, PurA, and the in vivo phenotype.

Major comments:

1. The "TTLL6-PurA link" framing is currently too strong. The pull-down data indicate multiple candidate substrates, and the study does not show that PurA is the key functional mediator of the epithelial phenotype. As written, the manuscript reads as though PurA is the central downstream effector, which is not yet supported. Requested change: Either add substrate-specific functional evidence (additional KO/rescue-type experiments) or soften the language throughout (title/abstract/discussion) to reflect that PurA is one candidate among several.
2. PurA glutamylation should be demonstrated directly by MS. PolyE/GT335 immunoblotting and enrichment in PolyE pull-downs are suggestive, but they do not conclusively establish glutamylation of PurA at the C-terminal end (antibody specificity and/or co-precipitating glutamylated proteins remain possible explanations). Essential experiment: MS/MS identification of glutamylated residue(s) on PurA, ideally with evidence that the modification is TTLL6-dependent (WT vs KO or epithelial-inducible KO).
3. Regional TTLL6 expression vs phenotype needs to be reconciled. TTLL6 expression is reported to be highest in distal colon, yet the strongest crypt-length phenotype appears in transverse colon (as presented). Proximal colon data are not shown in the main text. Requested revision: Provide complete regional analyses (proximal/transverse/distal) with consistent quantification and statistics, and discuss explicitly why TTLL6 expression levels and phenotype do (or do not) align.
4. Several internal inconsistencies and missing statistics.
   • Fig. 1A vs 1B: CEC enrichment appears ~80-fold in panel A and ~4-fold in the panel B; if these reflect the same enrichment workflow, this discrepancy needs a clear explanation (normalization, starting material, ....).
   • Fig. 2A: statistics are missing.
   • Fig. 5D: the effects appear borderline; the conclusions should match the statistical support/significance. Requested revision: Ensure complete statistical reporting in the manuscript (n, definition of replicates, test used, p-values/thresholds) and avoid interpretive language where differences are not significant.
5. PurA Localization claims would benefit from stronger imaging and quantification. For nuclear localization/redistribution conclusions (main Fig. 8 and related supplement), confocal imaging with Z-stacks (and orthogonal views) would be more convincing than representative single-plane images. In addition, conditions with PurA-only expression need a clear baseline description and quantification. Requested additions: confocal Z-stacks + blinded quantification of nuclear/cytosolic localization across replicates; ideally support with subcellular fractionation and quantitative immunoblotting.
6. Overexpression artifacts should be considered more carefully. If TTLL6 has been described as an elongase in prior work (Mahalingan, NSMB, 2020, DOI: 10.1038/s41594-020-0462-0) high-level overexpression may generate non-physiological modifications or localization patterns. Requested revision: Soften conclusions drawn from overexpression experiments and provide appropriate expression controls and/or supportive evidence in more physiological settings.
7. Mouse tumor data should be interpreted more cautiously relative to the human correlations. The human datasets suggest a correlation between TTLL6 mRNA levels and clinical features/outcome (including recurrence-free survival), which is potentially interesting. In contrast, the mouse CAC results appear modest/borderline and, in places, are interpreted as stronger evidence than the data support. Requested change: Avoid strong claims about TTLL6 promoting or suppressing tumor growth unless supported by robust, clearly significant differences and comprehensive burden metrics.

Minor comments:

• Every figure should clearly state n (biological vs technical), statistical test, and multiple-comparison correction where applicable.
• Where effects are segment-specific, the text should reflect that specificity and avoid global statements.
• The Discussion would benefit from a clearer separation of what is directly shown versus what is proposed (especially near the end).
• TTLL6 expression is largely presented at the transcript level; it would help to make this explicit throughout and avoid wording that implies protein-level validation where it is not shown.

Significance

The manuscript has the potential to be of interest because it points to a possible role for TTLL6 in non-tubulin, nuclear glutamylation in the intestinal epithelium, and it links TTLL6 expression to human CRC datasets. At present, however, the broader impact is limited by (i) insufficient direct evidence that PurA is glutamylated in vivo and (ii) the lack of a causal connection between PurA and the epithelial phenotype. In addition, while the human data show correlations between TTLL6 expression and clinical parameters/outcome, the mouse CAC phenotype appears comparatively modest/borderline and should be interpreted with appropriate caution. With stronger biochemical validation (MS), improved localization quantification, and more restrained framing (or additional functional data), the work could appeal to readers in intestinal epithelial biology, post-translational modification biology, and CRC research.

Expertise: enzymology; post-translational modifications; microscopy; cancer mechanisms.

Rapport de Synthèse : Le Traitement Judiciaire de l’Inceste Parental sur Mineurs

Résumé Exécutif

Ce document synthétise les témoignages et analyses de Mme Hélène Romano (psychologue et docteure en droit) et de Mme Eugénie Izard (pédopsychiatre) lors de leur audition par la commission d'enquête sur l'inceste.

Le constat est celui d'un échec structurel du système français : seuls 8 % des enfants ayant révélé des faits d'inceste sont effectivement protégés, tandis que 95 % des procédures sont classées sans suite.

Les points critiques identifiés sont :

• L'institutionnalisation du doute : Un basculement idéologique post-affaire d'Outreau qui érige l'enfant en menteur de principe et le parent protecteur en manipulateur.

• L'absence de méthodologie scientifique : L'inexistence d'outils standardisés (comme le protocole SVA) pour évaluer la crédibilité de la parole de l'enfant.

• Le rôle délétère de l'Ordre des Médecins : Une institution accusée de réduire les médecins au silence et de sanctionner ceux qui signalent des maltraitances.

• La primauté de la famille sur l'enfant : Une sacralisation de la "coparentalité" et du lien biologique qui contraint les enfants à maintenir des liens avec leurs agresseurs présumés.

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1. Un Système Structurellement Défaillant

L'inceste n'est pas une accumulation de faits divers conjoncturels, mais un phénomène systémique et organisé.

Malgré une libération de la parole médiatique, les statistiques révèlent une impunité persistante.

Chiffres clés du traitement de l'inceste en France

| Indicateur | Donnée | | --- | --- | | Enfants victimes de violences sexuelles par an | 160 000 | | Part des violences étant d'ordre incestueux | 80 % | | Taux de protection des enfants après révélation | 8 % | | Taux de procédures classées sans suite | 95 % | | Condamnations annuelles | Environ 1 000 |

Le système actuel est décrit comme une "inversion perverse" où l'enfant qui parle n'est pas entendu et se voit souvent remis à la garde du parent désigné comme agresseur.

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2. L'Idéologie du Doute et l'Inversion de la Culpabilité

Depuis l'affaire d'Outreau, une "idéologie du mensonge" imprègne les institutions judiciaires et médico-sociales.

La disqualification du parent protecteur

Majoritairement des mères (95 % des auteurs d'inceste étant des hommes), les parents protecteurs subissent un processus de disqualification en plusieurs étapes :

• Disqualification psychologique : Mère jugée "trop fusionnelle", fatiguée ou déprimée.

• Biais de confirmation : L'épuisement de la mère face au système est utilisé pour confirmer son instabilité psychique.

• Accusations de pathologie : Recours au Syndrome d'Aliénation Parentale (SAP) ou au Syndrome de Münchhausen par procuration pour accuser la mère de manipuler l'enfant.

Note : Le SAP n'est pas reconnu par le DSM et son usage est proscrit par plusieurs instances internationales, mais il reste largement utilisé pour discréditer les signalements.

Les conséquences pour l'enfant

L'enfant est souvent réduit à l'état d'objet.

S'il ne parle pas (contexte de terreur, handicap, bas âge), son silence est utilisé contre lui.

S'il parle, il subit une "sur-violence" institutionnelle : répétition épuisante des récits (parfois plus de 20 fois), confrontations traumatisantes et absence de protection.

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3. Défaillances de l'Expertise et Absence de Méthodologie

La France souffre d'un manque criant de professionnels formés spécifiquement au psychotrauma de l'enfant et à l'évaluation de sa parole.

• Le "Chifoumi" judiciaire : En l'absence de méthodes validées, les décisions sont souvent le fruit de biais cognitifs et de stéréotypes (ex: "les enfants mentent", "l'inceste n'existe pas").

• L'outil SVA (State Validity Assessment) : Cette méthode, utilisée à l'étranger mais proscrite en France après Outreau, repose sur 19 critères permettant de distinguer un récit vécu d'un récit fabriqué (cohérence, détails atypiques, dialogues rapportés).

• Incompétence des experts : Des experts psychiatres d'adultes sont parfois mandatés pour des enfants sans avoir de pratique clinique pédiatrique, rendant des rapports basés sur des entretiens de quelques minutes.

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4. L'Ordre des Médecins : Un Obstacle à la Protection

Le témoignage du Dr Izard met en lumière une "silenciation" des médecins par leur propre institution.

• Pressions et sanctions : Des médecins sont interdits d'exercer pour avoir signalé des enfants en danger, l'Ordre invoquant souvent "l'immixtion dans les affaires de famille".

• Entrave à la loi : Bien que la loi de 2015 dégage les médecins de leur responsabilité en cas de signalement de bonne foi, l'Ordre est accusé d'ignorer la loi pénale pour sanctionner disciplinairement les praticiens.

• Résultat : Seul 1 % des signalements de violences sexuelles incestueuses proviennent de médecins, par crainte de représailles ordinales.

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5. La Sacralisation du Lien Familial et de la Coparentalité

Le système français privilégie le maintien du lien familial au détriment de la sécurité de l'enfant.

• Le paradigme de la réparation : L'enfant est souvent utilisé comme un "outil de réparation" pour le parent agresseur via des visites médiatisées forcées, au nom de la coparentalité.

• Le conflit vs la violence : Le terme "conflit parental" est abusivement utilisé pour invisibiliser les violences sexuelles.

Or, il ne peut y avoir de coparentalité dans une situation d'inceste.

• La violence judiciaire : Le cas de Mme Romano illustre l'extrême violence subie par les parents protecteurs : gardes à vue humiliantes, perquisitions, ruine financière (frais d'avocats s'élevant à plusieurs centaines de milliers d'euros) et condamnations pour "non-représentation d'enfant" même face à des preuves médicales de violences.

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6. Pistes de Réformes et Recommandations

Les intervenantes proposent plusieurs leviers pour transformer radicalement la prise en charge :

Réformes Procédurales et Judiciaires

• Création d'un crime d'inceste spécifique dans le code pénal, intégrant la notion de domination et de crime contre l'humanité de l'enfant.

• Reconnaissance de l'imprescriptibilité pour les crimes sexuels sur mineurs.

• Priorisation de l'ordonnance de protection immédiate dès la révélation.

• Saisine directe du Juge aux Affaires Familiales (JAF) par le procureur pour suspendre les droits du parent mis en cause pendant l'enquête.

• Suppression du délit de non-représentation d'enfant en cas de suspicion de violences.

Évaluation et Santé

• Usage de méthodologies standardisées (SVA, protocole NICHD) pour l'audition et l'expertise.

• Enregistrement audiovisuel systématique de toutes les expertises.

• Création de collèges d'experts spécialisés en psychotraumatologie infantile.

• Immunité disciplinaire effective pour les médecins signalant des maltraitances de bonne foi.

• Anonymat possible pour les professionnels signalant des faits graves.

Transformation Sociétale

• Sortir du déni de la domination masculine et patriarcale au sein de la famille.

• Former massivement tous les professionnels au contact des enfants (école, santé, social) au repérage des troubles spécifiques.

• Protéger l'enfant avant de protéger la famille, en cessant de considérer le lien biologique comme sacré au-delà de la sécurité physique et psychique.

DOI: 10.1038/s41419-026-08605-4

Resource: (Proteintech Cat# 10176-2-AP, RRID:AB_2224574)

Curator: @scibot

SciCrunch record: RRID:AB_2224574

What is this?

freundlish吸附线和其他等温吸附线判断吸附类型

Annotating this to keep the prompt handy. I am going to test this to see how the opinion is swayed.

By what measurement? I would expect them to be No 1 or 2 by BIP

Claude: Resources page shortening suggestions:

1. Remove duplicate tool cards — the Dashboard + Learn page cards are identical to what's on the About page. Replace with a compact one-liner: 'Interactive tools: Dashboard · How CM is Made · TEA Comparison · Technical Docs'

2. Add TEA Comparison link — the new compare.html page systematically compares Pasitka, Humbird, CE Delft, GFI, and Goodwin. This is directly relevant to the reading list context.

3. Keep the Shared Reading Collection — it serves a unique purpose (downloadable PDFs) not available elsewhere.

4. Keep the PQ Database section — it's the canonical link set.

Claude: Content trimming plan for this page (1,147 lines → ~700 target)

Proposed changes in priority order: 1. Fold FBS/serum-free section — historical context, no longer reflects current practice. One visible sentence + collapsed detail. 2. Move jurisdiction & 'Which market?' discussions to workshop — these are workshop topics, not dashboard content. Replace with one-line links. 3. Fold GF signaling diagram — educational but not cost-relevant. Keep the price/solutions tables visible. 4. Bold audit — reduce bold to headings + key numbers only (addresses multiple reviewer comments). 5. Trim Further Resources — link to workshop resources page for full list. 6. CSS fixes — larger diagrams, less whitespace around SVGs.

Optional: fold 2-3 SVG diagrams (cell banking, seed train) to reduce scroll length — the text already explains these steps.

Full plan at .private/content_trimming_plan.md. Feedback welcome here or in chat.

I find this description of translanguaging to be a very good one because translanguaging does not limit or isolate language and rather it sees it as a collection of linguistic abilities that can be used in unison to express meaning and feeling. Being worded as an "active negotiation of language" is such an interesting way to put it because as somebody who translanguages every single day, it sounds like a good way to express the idea that the two languages aren't competing, but are instead flowing in our brains and bargaining depending on the situation or circumstance that we find ourselves in.

Author Response:

The following is the authors’ response to the original reviews.

Public Reviews:

Reviewer #1 (Public review):

(1) The sample size for the ex vivo electrophysiology is small. Given the difficulty and complexity of the preparation, this is understandable. However, a larger sample size would have strengthened the authors' conclusions.

We appreciate that the sample size is small, but this was limited by the technical difficulty and relatively low yield with this preparation. From a total of 16 experiments, we were able to obtain successful recordings in 6 cases, and these provided the characterisation of the 11 cells reported in Figure 4. We believe that this is sufficient to “strongly suggest” that the cells with dense Trpm8 input correspond to cold-selective cells. We have toned down the statements in the abstract (line 23) and the Results section (line 246).

(2) The authors used tdTomato expression to identify brain targets innervated by these coldselective lamina I projection neurons. Since tdTomato is a soluble fluorescent protein that fills the entire cell, using synaptophysin reporters (e.g., synaptophysin-GFP) would have been more convincing in revealing the synaptic targets of these projection neurons.

As the Reviewer says, tdTomato labelling fills the entire cell. However, examination at high magnification reveals numerous varicosities along the labelled axons, presumably corresponding to synaptic boutons. We now illustrate this in Figure 6–figure supplement 2F.

In addition, we have provided further evidence that these varicosities correspond to (glutamatergic) synaptic boutons by immunostaining sections through the LPB for the postsynaptic density protein Homer1, and showing Homer1 puncta apposed to varicosities (Figure 6–figure supplement 2 G,H). This new information now appears in the Results section (lines 374-380).

(3) The summary cartoon shown in Figure 7 can be misleading because this study did not determine whether these cold - selective lamina I projection neurons have collateral branches to multiple brain targets or if there are anatomical subtypes that may project exclusively to specific targets. For example, a recent study (Ding et al., Neuron, 2025) demonstrated that there are PBN-projecting spinal neurons that do not project to other rostral brain areas. Furthermore, based on the authors' bulk labeling experiments, the three main brain targets are NTS, PBNrel, and cPAG. The VPL projection is very sparse and almost negligible.

We agree that branches to different brain nuclei may originate from specific subsets of ALS3 neurons and this is now stated in the figure legend. It is true that there are projections to other brain regions (including NTS). These are not included in the diagram, because their circuitry in relation to cold-sensing is less well understood. Although the projection to VPL from lumbar cord is sparse, this is likely to be explained by the very low proportion of lamina I projection neurons with axons that reach the thalamus. Our retrograde tracing data (e.g. Figure 6-figure supplement 4) had already revealed many cells in the C7 segment that were densely coated with Trpm8 afferents and retrogradely labelled from the lateral thalamus. We have carried out additional experiments in which AAV1.Cre^ON.td Tomato was injected into the cervical enlargement of Calb1^Cre mice.This resulted in much denser labelling in the VPL and PoT thalamic nuclei, supporting the suggestion that cold-selective lamina I neurons in the cervical enlargement project to these nuclei. This is now described in lines 381-387 and illustrated in Figure 6–figure supplement 3.

Reviewer #2 (Public review):

(1) In the characterization of recorded neurons in close contact or in the absence of this contact with TRPM8 afferents, the number of recorded neurons is relatively low. In addition, the strength of thermal stimuli is not very well controlled, preventing a more precise characterization of the connectivity.

We fully accept that the sample size is small (please see response to Reviewer 1 above). We also accept that the thermal stimulation was not that well controlled. Unfortunately, commercially available probes for controlling skin temperature are too large to apply to the skin in this preparation. For this reason, we have used application of hot and cold saline, as in our previous studies with this preparation.

(2) The authors could provide some sense of the effort needed to record from the 6 coldactivated neurons described. How many preparations were needed, etc?

We now state that 6 out of 16 experiments resulted in successful recordings for this part of the study (lines 858-861).

Reviewer #3 (Public review):

(1) While anatomical evidence for direct synaptic connectivity between Trpm8+ afferents and lamina I projection neurons is compelling, a physiological demonstration of strict monosynaptic transmission is not shown. The conclusion that these inputs are exclusively monosynaptic should be toned down. Similarly, the statement that "Lamina I ALS neurons that are surrounded by Trpm8 afferents are cold-selective" should also be toned down as only a few neurons have been tested and it cannot be excluded that other neurons with similar characteristics may be polymodal.

We have now carried out optogenetic experiments by expressing channelrhodopsin in Trpm8 afferents and retrogradely labelling ALS neurons with tdTomato. This has allowed us to directly demonstrate monosynaptic input. This is described in the Results section (lines 180-202) and the Methods section has been updated. As noted above, we have toned down the statement about lamina I neurons surrounded by Trpm8 afferents being coldselective (line 246).

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

(1) The patch innervation of Trpm8+ sensory neurons in lamina I of the spinal cord dorsal horn is interesting. Do they occupy specific areas within lamina I along the mediolateral axis, or are their placements random? Quantifying the distribution of these terminals in lamina I might be worthwhile.

Although we have not studied the mediolateral distribution systematically, it appears that the locations of the patches in the mediolateral axis is random, and they could be seen in medial, central and lateral parts of lamina I (as shown in Figure 2). We have added a comment to this effect in the Results section (lines 114-116). Quantifying Trpm8 terminals would be very labour-intensive, and we do not feel that this would be of great benefit.

(2) Quantification for the percentage of Trpm8+ boutons contacting Phox2a+ neurons that are vGlut3+

The main purpose of this part of the study was to provide a possible explanation for the finding by Li et al (2015) that some lamina I cells were associated with Vglut3-

immunoreactive boutons. We found that the percentages of Trpm8+ boutons that contained Vglut3 varied considerably from cell to cell, and this is now stated in the text (lines 133134). However, knowing exact proportions was not an important aspect of the study, we have therefore not carried out a detailed analysis.

(3) Quantification for the percentage of PBN projections neurons densely innervated by Trpm8+ axons that are calb1+.

As requested, we have carried out immunohistochemistry to determine the proportion of lamina I ALS neurons with dense Trpm8 input that are calbindin-immunoreactive. We examined 31 neurons from 3 different mice and found that all but 4 (i.e. 87%) were immunoreactive. This is now described (lines 287-293) and illustrated (Figure 5–figure supplement 1). We have now put the electrophysiological characterisation that was in this figure into a separate supplement (Figure 5–figure supplement 2).

(4) It might be helpful to confirm the brain projection targets of Cal1b+ lamina 1 projection neurons using AAV1-CreON-Synaptophysin-GFP (or other fluorescent proteins) injections

Please see our response to Public review Reviewer 1 comment 2 above. We have provided further evidence that the brain regions that received input from the Calb1+ cells contain axonal boutons (lines 374-380 and Figure 6–figure supplement 2F-H).

(5) Figure 6 - Figure Supplements 3 and 4 are duplicated

We apologise for this duplication, which was made in error in the version originally submitted to eLife. This has now been corrected.

Reviewer #2 (Recommendations for the authors):

(1) As mentioned, in the characterization of recorded neurons in close contact or in the absence of this contact with TRPM8 afferents, the number of recorded neurons is relatively low, some recorded in current clamp, a few in voltage clamp. This prevents any solid statistical evaluation of the findings

Please see response to response to the first point made by Reviewer 1 in the Public reviews. As stated above, we have toned down the statement about the relationship between cells with dense Trpm8 input and cold-selective cells (line 246).

(2) In addition, the strength of thermal stimuli is not very well controlled, preventing a more precise characterization of the synaptic connection between afferents and ALS projection neurons.

Please see our response to the Public review comment made by this Reviewer.

(3) Line 35. In the description of the anterolateral system and the effects of lesions, the species(s) should be specified since rodents and humans have a different anatomical distribution of spinal tracts.

We now state that while ALS axons ascend in the anterolateral quadrant in humans, they are located in the dorsolateral white matter in rodents (lines 40-42)

(4) To describe the semi-intact preparation used for recording and stimulation from the periphery, the authors cite a study by Julien Allard (reference 25). However, that study describes an in vivo preparation. I believe there is an error in the citation.

We thank the Reviewer for pointing this out – it has now been corrected.

(5) Line 726. Dorsal horn recordings were performed at 25 ºC. What is the temperature of the skin? How would this low temperature affect the excitability of cold afferents and their axons? Perhaps a comment about this issue would be appropriate.

The skin temperature in this preparation is the same as that of the spinal cord (25 °C). At this temperature, Trpm8 afferents would be active, but are likely to have adapted during the course of the experiment. Since this temperature is below 37 °C, it is likely that the conduction velocity of these afferents will be slower than in the in vivo situation. We have added a comment to this effect (lines 818-821).

(6) Line 401. The authors could not detect Trpv1-immunoreactivity in the central terminals of Trpm8Flp;RCE:FRT mice. Could they detect Trpv1 immunoreactivity in any central terminal? Do they have positive evidence that their immunostaining worked?

Trpv1 was readily detected in central terminals with the Trpv1 antibody. An example showing lack of detectable Trpv1-immunoreactivity in GFP-labelled (Trpm8-expressing) afferents is now shown in Figure 2–figure supplement 1K-M.

(7) Line 437. What is the expected anterograde transport time for YFP from the lumbar cord to the brainstem? Are 2-3 weeks not sufficient based on the literature? I noticed the authors are using longer survival times after intraspinal injections

In preliminary experiments for a previous study Substance P-expressing excitatory interneurons in the mouse superficial dorsal horn provide a propriospinal input to the lateral spinal nucleus | Brain Structure and Function we had found that a 2 week survival time after injection of AAV1.Cre^ON.GFP into the lumbar spinal cord of Tac1^Cre mice was not sufficient to label axons in the brain, although at 4 weeks we saw brain labelling. We have also found that extending survival times from 4 to 6 weeks gives greatly improved labelling, especially in the thalamus.

(8) Figure 5A. Many of the labelled cells appear to have the somas in the white matter, which makes little sense. It seems the reference section to plot the cells is not optimal

The placement of cells is accurate. Many spinal projection neurons are present outside the main region of grey matter (i.e. laminae I-X). These cells are found in 2 main regions – the lateral spinal nucleus (LSN) and the lateral reticulated part of lamina V. These two regions are intermediate between grey and white matter – i.e. they contain scattered cell bodies amongst a dense collection of axons. For this reason they appear outside the grey/white border as it is conventionally shown on diagrams of this type. This has been reported in numerous studies, e.g. see Figure 2 in The cells of origin of the spinothalamic tract of the rat: a quantitative reexamination - PubMed.

(9) Recent transcriptomic studies suggest the presence of more than one subpopulation of Trpm8-expressing DRG or trigeminal neurons. It is unclear to what extent the Trpm8-Flp line is capturing this diversity.

We are aware that there are at least 3 transcriptomic subsets of Trpm8-expressing primary sensory neurons. However, we are not aware of any suitable molecular markers that would allow us to discriminate between them, and therefore address this point.

(10) Could the patchy distribution of Trpm8 afferents in lamina I reflect incomplete recombination; the empty spaces could be occupied by unmarked afferents?

In theory it could, but this seems unlikely. The Trpm8^Flp line (crossed with RCE:FRT) captures ~83% of Trpm8-positive cell bodies, and it seems very unlikely that the remaining 17% of Trpm8-expressing afferents would fill the spaces between GFP bundles that we see in lamina I. This is now stated in the Results section (lines 116-120).

Reviewer #3 (Recommendations for the authors):

(1) It would be a nice addition to the validation of the Trpm8-Flp line to specify what ages (if multiple) have been analysed and whether there are any differences. In addition, is labelling different at different levels of the spinal cord, and is there any labeling in supraspinal regions?

The tissue used for this part of the study was obtained from mice aged 5-9 weeks and this is now stated (lines 78-79). We did not observe any differences with age, but we did not look at this in detail. Labelling was similar at different levels of the spinal cord, and this is stated (lines 108-109). We have added a brief account of the distribution of GFP labelling in the brain (lines 140-144).

(2) Line 169. It is not clear how ALS neurons are labeled. It is explained in the material and methods (I believe it is AAV9.mCherry into the LPB or CVLM). Although I could not find a mention of a tdTomato AAV, maybe I missed it. In any case, it would be great to have the experimental strategy briefly explained in the text. For the same reason, I would recommend moving Figure 4 Supplement 1A and 1B schematics to the main figure, very helpful for understanding the experiment.

We thank the Reviewer for this suggestion. We now explain in the Results section how the ALS neurons were labelled (lines 209-212), and as the Reviewer recommends we have put the schematic diagrams from Figure 4–figure supplement 1 into the main Figure. As noted in the text, the tdTomato labelling resulted from injection of an AAV coding for Cre into mice that contained the Ai9 allele. We have also updated the descriptions of brain injections in the Methods section to cover the new experiments (optogenetics, and calbindin immunohistochemistry).

(3) Line 184. "Figure 4" would be good to specify the panels; I believe it should be 4A-C. Same for line 194, 4D-F?

We apologise that this was omitted from the original version – we have now specified the panels.

(4) Line 179. It would be great to specifiy in the text and figures the temperature used for hot and warm water. In addition, would the responses be different using different temperatures? Can you test ramps? These would go a great way to compare with responses shown in vivo by Ran and colleagues.

We now specify the hot and cold saline temperatures used to stimulate the skin in the semiintact preparation in the legend for Figure 4 and in the Results section (lines 222-223). As noted above, it is difficult to use more accurate thermal stimuli in this preparation. Please see response to Reviewer 2 public comment 1.

(5) Figure 4-Figure supplement 1F. It looks like these are very slow responses (1 sec?) for monosynaptic connectivity.

In this figure (now part 1D) the action potential frequency was determined from counts of APs in 1 sec bins, and this is now stated in the legend. This might have given the impression of slow responses.

(6) Line 203. I would tone down the statement, as only 6 cells "that were clearly associated with numerous GFP-labelled afferents" have been tested. Thus, it cannot be excluded that other cells with similar anatomical characteristics may also respond to other stimuli

As requested, we have toned down this statement (line 246).

(7) Line 230. Here AAV11.CreON.td Tomato is used, in previous retrograde experiments, AAV9 has been used (Figure 4), why the switch to 11? Is the tropism the same? Is it possible that because you are using a different serotype, you are targeting different neurons?

We have found that although AAV9 coding for fluorescent proteins is very good for retrograde labelling, AAV9 coding for Cre-dependent constructs (e.g. AAV.Cre^ON.tdTomato) gives very poor recombination in spinal projection neurons, for reasons that we do not understand. We recently became aware of the AAV11 serotype, which was recommended as being suitable for retrograde transport AAV11 enables efficient retrograde targeting of projection neurons and enhances astrocyte-directed transduction | Nature Communications. We have found that this works very well for labelling ALS cells throughout the spinal cord when using Cre-dependent constructs. We have added a reference to this paper at this point in the text. We are not able to say whether tropism is the same or different, but in each case many ALS neurons (including many of those in lamina I) are captured.

(8) Line 234. Is there any positional organization for the "tdTomato-labelled cells densely innervated byTrpm8 afferents", do they preferentially cluster in some position of lamina I?

These cells are found throughout the mediolateral extent of the dorsal horn, and this is now stated (lines 279-280).

(9) Line 237. The actual number of cells/mm would be informative.

This would be difficult to estimate, as the sections were cut in the horizontal plane, which means that lamina I can appear on a variable number of sections.

(10) Line 249. From the figures, the action potentials of the Calb+ neurons seem to have a delayed onset (at the end of cold saline treatment, Figure 5, Supplement 1l) compared to lamina I ALS neurons recorded in Figure 4, Supplement 1f. If real, it is an interesting difference in the time-course of response that could indicate different coding properties e.g., response to cooling (general neurons) vs. response to absolute temperature (calb + neurons).

As for Fig 4-figure supplement 4 (see response to point #5 above), action potential frequency was determined from APs counted in 1 sec bins, and this is now stated in the legend.

(11) Figure 7. In the model, the disynaptic pathway should also be shown

We have added a comment to the legend stating that there may also be indirect (“polysynaptic”) input from Trpm8 afferents to ALS3 neurons.

Reviewer #2 (Public review):

Summary:

This article addresses a very pertinent question - what are the computational mechanisms underlying risky behaviour in patients having attempted suicide. In particular, it is impressive how the authors find a broad behavioral effect whose mechanisms they can then explain and refine through computational modeling. This work is important because currently, beyond previous suicide attempts, there has been a lack of predictive measures. This study is the first step towards that: understanding the cognition on a group level. Before then being able to include it in future predictive studies (based on the cross-sectional data, this study by itself cannot assess the predictive validity of the measure).

Strengths:

- Large sample size<br /> - Replication of their own findings<br /> - Well-controlled task with measures of behaviour and mood + precise and well-validated computational modeling

Questions, based on revised manuscript and replies to other reviewers:

(1) Replies to reviewers in general: Bayes Factors have been added, it would be good to also use common verbal terms to describe them (e.g. 'anecdotal', 'moderate' etc). For example, my reading of table S8 would be that for gambling rate there is only anecdotal evidence that it does not relate to PSWQ, BDI, and moderate evidence it does not relate to TAI.

(2) Reply to reviewer 1 Q2 (Predicting STB):<br /> For the regression predicting suicidal ideation, it seems to me that what you did was a regression STB ~ gambling behaviour + approach + mood? Could you clarify? I had expected as a test of whether the task can predict STB risk something slightly different - a cross-validation (LOO or maybe 5-fold in the large sample): STB ~ gambling behaviour + approach [parameter from model] + mood [parameter from model]; and then computing in the left out participants: predicted STB. Then checking correlation between STB and predicted STB. This would allow testing whether the diverse task measures together predict STB (with the caveat, that it's cross-validated, rather than hold-out sample, unless you could train on one sample (in lab) and test on the other (online).

(3) Reply to reviewer 2 Q1 (parameter recovery): I'm looking at S3, it seems to still show only the scatter plots and not the correlation matrices, which are now added as text notes. Can you actually show these matrices? An off-diagonal correlation of 0.63 appears quite high. I think it needs to be discussed exactly which parameters those are, and whether that impacts the interpretation of the results.

(4) Reply to reviewer 3 Q3 (mood model): I would have imagined that the response would involve changing the mood equations (equation 8 main text) to include a term for whether the participant gambled or not, independent of the gamble value.

Author response:

The following is the authors’ response to the original reviews

eLife Assessment

This valuable study combined careful computational modeling, a large patient sample, and replication in an independent general population sample to provide a computational account of a difference in risk-taking between people who have attempted suicide and those who have not. It is proposed that this difference reflects a general change in the approach to risky (high-reward) options and a lower emotional response to certain rewards. Evidence for the specificity of the effect to suicide, however, is incomplete, which would require additional analyses.

We thank the editors and reviewers for this important assessment. Based on clinical interviews, we included patients with and without suicidality (S⁺ and S^- groups). However, in line with suicidal-related literature (e.g., Tsypes et al., 2024), two groups also differed substantially in the severity of symptoms (see Table 1). To address the request for evidence on specificity to suicidality beyond general symptom severity, we performed separate linear regressions to explain in gambling behaviour, value-insensitive approach parameter (β_gain), and mood sensitivity to certain rewards (β_CR) with group as a predictor (1 for S⁺ group and 0 for S^- group) and scores for anxiety and depression as covariates. Results remained significant after controlling anxiety and depression (ps < 0.027; Table S8). Given high correlations among anxiety and depression questionnaires (rs > 0.753, ps < 0.001), we performed Principal Components Analysis (PCA) on the clinical questionnaire to extract the orthogonal components, where each component explained 86.95%, 7.09%, 3.27%, and 2.68% variance, respectively. We then performed linear regressions using these components as covariates to control for anxiety and depression. Our main results remained significant (ps < 0.027; Table S9). We believe that these analyses provide evidence that the main effects on gambling and on mood were specific to suicide.

Moreover, as Reviewer 3 pointed out, these “absence of evidence” cannot provide insights of “evidence of absence”. Although we median-split patients by the scores of general symptoms (e.g., depression and anxiety-related questionnaires) and verified no significant differences in these severities (Figure S11), we additionally conducted Bayesian statistics in gambling behavior, value-insensitive approach parameter, and mood sensitivity to certain rewards. BF₀₁ is a Bayes factor comparing the null model (M₀) to the alternative model (M₁), where M₀ assumes no group difference. BF₀₁ > 1 indicates that evidence favors M₀. As can be seen in Table S7, most results supported null hypothesis, suggesting that general symptoms of anxiety and depression overall did not influence our main results. Overall, we believe that these analyses provide compelling evidence for the specificity of the effect to suicide, above and beyond depression and anxiety.

Beyond these specific findings, this work highlights the broader utility of computational modelling and mood to better understand behavioral effect, showing how to use both mood and choice data to better comprehend a psychiatric issue. 

Public Reviews:

Reviewer #1 (Public review):

Summary:

The authors use a gambling task with momentary mood ratings from Rutledge et al. and compare computational models of choice and mood to identify markers of decisional and affective impairments underlying risk-prone behavior in adolescents with suicidal thoughts and behaviors (STB). The results show that adolescents with STB show enhanced gambling behavior (choosing the gamble rather than the sure amount), and this is driven by a bias towards the largest possible win rather than insensitivity to possible losses. Moreover, this group shows a diminished effect of receiving a certain reward (in the non-gambling trials) on mood. The results were replicated in an undifferentiated online sample where participants were divided into groups with or without STB based on their self-report of suicidal ideation on one question in the Beck Depression Inventory self-report instrument. The authors suggest, therefore, that adolescents with decreased sensitivity to certain rewards may need to be monitored more closely for STB due to their increased propensity to take risky decisions aimed at (expected) gains (such as relief from an unbearable situation through suicide), regardless of the potential losses.

Strengths:

(1) The study uses a previously validated task design and replicates previously found results through well-explained model-free and model-based analyses.

(2) Sampling choice is optimal, with adolescents at high risk; an ideal cohort to target early preventative diagnoses and treatments for suicide.

(3) Replication of the results in an online cohort increases confidence in the findings.

(4) The models considered for comparison are thorough and well-motivated. The chosen models allow for teasing apart which decision and mood sensitivity parameters relate to risky decision-making across groups based on their hypotheses.

(5) Novel finding of mood (in)sensitivity to non-risky rewards and its relationship with risk behavior in STB.

Weaknesses:

(1) The sample size of 25 for the S- group was justified based on previous studies (lines 181-183); however, all three papers cited mention that their sample was low powered as a study limitation.

We thank the Reviewer for rising this concern. We agree that the sample size for S^- group (n=25) is modest, and the prior studies we cited also acknowledged limited power. We wanted to point out that we obtained a comparable sample size to a prior study. In the revision, we therefore updated the section to justify this sample size in which we acknowledge the limited power of our study in the limitation section. Please see our clarification below:

Page 32:

“Third, despite replicating our main results in an independent dataset (n=747), the modest S^- subgroup size (n=25) has a limited statistical power.”

(2) Modeling in the mediation analysis focused on predicting risk behavior in this task from the model-derived bias for gains and suicidal symptom scores. However, the prediction of clinical interest is of suicidal behaviors from task parameters/behavior - as a psychiatrist or psychologist, I would want to use this task to potentially determine who is at higher risk of attempting suicide and therefore needs to be more closely watched rather than the other way around (predicting behavior in the task from their symptom profile). Unfortunately, the analyses presented do not show that this prediction can be made using the current task. I was left wondering: is there a correlation between beta_gain and STB? It is also important to test for the same relationships between task parameters and behavior in the healthy control group, or to clarify that the recommendations for potential clinical relevance of these findings apply exclusively to people with a diagnosis of depression or anxiety disorder. Indeed, in line 672, the authors claim their results provide "computational markers for general suicidal tendency among adolescents", but this was not shown here, as there were no models predicting STB within patient groups or across patients and healthy controls.

Thank you for these thoughtful comments. Our study focuses on why adolescent patients with suicidality have increased risk behavior, aiming to provide a mechanism-based target for suicide prevention. Therefore, our dependent variable in the mediation model was gambling behavior. We also agree that the clinically relevant question is whether suicidality can be predicted from task-derived behavior/parameters. We thus used risky behavior and the potential mental parameters to predict STB. Linear regressions showed that gambling behavior, as well as the value-insensitive approach parameter, can predict suicidal symptom scores among patients (former: β = 9.189, t = 2.004, p = 0.048; latter: β = 5.587, t = 2.890, p = 0.005). In healthy controls, these predictions failed (gambling behavior: β = 1.471, t = 0.825, p = 0.411; approach: β = 0.874, t = 1.178, p = 0.241). These results suggest that clinical relevance of these findings apply exclusively to people with a diagnosis of depression or anxiety disorder. We found same patterns for the mood parameter (mood sensitivity to certain rewards: patients: β = -28.706, t = -2.801, p = 0.006; healthy controls: β = -2.204, t = -0.528, p = 0.599). In sum, we believe that our statement of “computational markers for general suicidal tendency among adolescents” is reasonable now. Please see our revisions below:

Page 17:

“Furthermore, linear regression showed that gambling rate can predict the current suicidal ideation score (BSI-C, β = 9.189, t = 2.004, p = 0.048) among patients, but not among HC (β = 1.471, t = 0.825, p = 0.411), suggesting that gambling behavior has patient-specific predictive utility for suicidal symptoms.”

Page 19:

“Furthermore, linear regression showed that approach parameter can predict the current suicidal ideation score (β = 5.587, t = 2.890, p = 0.005) among patients, but not among HC (β = 0.874, t = 1.178, p = 0.241), suggesting that value-insensitive approach parameter has patient-specific predictive utility for suicidal symptoms.”

Page 21:

“Furthermore, linear regression showed that mood sensitivity to CR can predict the current suicidal ideation score (β = -28.706, t = -2.801, p = 0.006) among patients, but not among HC (β = -2.204, t = 0.528, p = 0.599), suggesting that mood sensitivity to CR has patient-specific predictive utility for suicidal symptoms.”

(3) The FDR correction for multiple comparisons mentioned briefly in lines 536-538 was not clear. Which analyses were included in the FDR correction? In particular, did the correlations between gambling rate and BSI-C/BSI-W survive such correction? Were there other correlations tested here (e.g., with the TAI score or ERQ-R and ERQ-S) that should be corrected for? Did the mediation model survive FDR correction? Was there a correction for other mediation models (e.g., with BSI-W as a predictor), or was this specific model hypothesized and pre-registered, and therefore no other models were considered? Did the differences in beta_gain across groups survive FDR when including comparisons of all other parameters across groups? Because the results were replicated in the online dataset, it is ok if they did not survive FDR in the patient dataset, but it is important to be clear about this in presenting the findings in the patient dataset.

Thank you for raising the important issue of multiple testing and for asking us to clarify exactly which tests were covered by the FDR procedure. In the clinical dataset we conducted a large number of inferential tests (χ², t-tests, ANOVAs, regressions) spanning: (i) group differences in demographic/clinical characteristics; (ii) sanity checks (e.g., anxiety/depression questionnaires); (iii) primary hypotheses (e.g., group differences in risky behavior); (iv) model-based analyses (parameter checks and between-group contrasts); and (v) control/sensitivity analyses. Post-hoc t-tests were performed only when the three-group ANOVA was significant. This yielded >150 p-values. FDR was applied using all these p-values. Please see our clarification below:

Supplementary Page 4:

“Supplementary Note 8: Clarification for FDR correction.

In the clinical dataset we conducted a large number of inferential tests (χ<sup2\</sup>, t-tests, ANOVAs, regressions) spanning: (i) group differences in demographic/clinical characteristics; (ii) sanity checks (e.g., anxiety/depression questionnaires); (iii) primary hypotheses (e.g., group differences in risky behavior); (iv) model-based analyses (parameter checks and between-group contrasts); and (v) control/sensitivity analyses. Post-hoc t-tests were performed only when the three-group ANOVA was significant. This yielded >150 p-values. FDR was applied using all these p-values.”

(4) There is a lack of explicit mention when replication analyses differ from the analyses in the patient sample. For instance, the mediation model is different in the two samples: in the patient sample, it is only tested in S+ and S- groups, but not in healthy controls, and the model relates a dimensional measure of suicidal symptoms to gambling in the task, whereas in the online sample, the model includes all participants (including those who are presumably equivalent to healthy controls) and the predictor is a binary measure of S+ versus S- rather than the response to item 9 in the BDI. Indeed, some results did not replicate at all and this needs to be emphasized more as the lack of replication can be interpreted not only as "the link between mood sensitivity to CR and gambling behavior may be specifically observable in suicidal patients" (lines 582-585) - it may also be that this link is not truly there, and without a replication it needs to be interpreted with caution.

Thank you for these important comments. This study focused on cognitive and affective computational mechanisms underlying increased risky behavior in STB. Accordingly, we compared patients with STB (S⁺) with patients without STB (S^-) and healthy controls (HC) to examine the effects of STB on risky behavior. Therefore, group comparison, instead of dimensional measure of suicidal symptoms by Beck Scale for Suicidal Ideation, can answer our research questions directly.

To enhance consistency between the clinical and replication datasets, we included all participants in each dataset when performing the mediation analysis. Given that S^- and HC did not differ in gambling behavior or the approach parameter in the clinical dataset, we merged these two groups. In the replication dataset, to mirror the S⁺ vs. S^- contrast used clinically, we categorized the general sample into S+ and S^- based on BDI item 9. The mediation results remained significant in both datasets (the clinical dataset: a×b = 0.321, 95% CI = [0.070, 0.549], p = 0.016; the replication dataset: a×b = 0.143, 95% CI = [0.016, 0.288], p = 0.031), suggesting that STB is associated with increased risk behavior via stronger approach motivation.

We also acknowledge the non-replication of the correlation between gambling behavior and mood sensitivity to certain rewards in the online sample. While this pattern might indicate that the link is specific to suicidal patients, it may also reflect sample-specific or unstable effects; thus, we now state this explicitly and interpret the finding with caution. Please see our revisions below:

Page 15:

“We next verified our results in an independent dataset, including the same task and BDI questionnaire in 747 general participants (500 females; age: 20.90±2.41) (46). One item in BDI involves the measurement of STB. In item 9 of BDI, participants chose one option that describes them best: Option 1, “I don't have any thoughts of killing myself.”; Option 2, “I have thoughts of killing myself, but I would not carry them out.”; Option 3, “I would like to kill myself.”; Option 4, “I would kill myself if I had the chance.”. In line with the current definition of S⁺/S^- in the clinical dataset, we identified S⁺ group as choosing Option 2, 3, or 4, while participants selecting Option 1 were categorized as S^- group.”

Page 19:

“Given significant correlations between group, approach parameter, and gambling rate for gain trials (ps < 0.017), we further conducted a mediation analysis with the assumption of the mediating effect of approach motivation of suicidality on the risk behavior. Given that we aimed to test the effect of STB, with S^- and HC as controls, and given that S^- and HC did not differ in gambling behavior or in the approach parameter, we merged these two groups for the mediation analysis. Results supported our hypothesis (a×b = 0.321, 95% CI = [0.070, 0.549], p = 0.016; Figure 2C), confirming that suicidal thoughts and behavior increase risk behavior through stronger approach motivation.”

Page 26:

“However, we did not observe any significant correlation between mood sensitivity to CR and gambling behavior (ps > 0.389), which suggests that the link between mood sensitivity to CR and gambling behavior may be specifically observable in suicidal patients. Alternatively, this non-replicated result may also reflect sample-specific or unstable effects, which needs to be interpreted with caution.”

(5) In interpreting their results, the authors use terms such as "motivation" (line 594) or "risk attitude" (line 606) that are not clear. In particular, how was risk attitude operationalized in this task? Is a bias for risky rewards not indicative of risk attitude? I ask because the claim is that "we did not observe a difference in risk attitude per se between STB and controls". However, it seems that participants with STB chose the risky option more often, so why is there no difference in risk attitude between the groups?

Thank you for pointing out the ambiguity. In our manuscript, “motivation” and “risk attitude” are defined at the computational level. Following prior work with this task Rutledge et al., (2015, 2016), we decompose observed gambling into (i) value-dependent valuation parameters that capture risk attitude (e.g., risk aversion and loss aversion, which scale the subjective value of outcomes), and (ii) value-insensitive, valence-dependent biases that capture approach/avoidance motivation. Accordingly, a higher gambling rate does not imply a change in risk attitude per se: it can arise from an increased value-insensitive approach bias even when risk-attitude parameters are comparable between groups—which is what we observe for S⁺ vs. controls. We have clarified this point in the computational modeling section.

Pages 12-13:

“Please note that a higher gambling rate does not imply a change in risk attitude per se: it can arise from an increased value-insensitive approach bias even when risk-attitude parameters are comparable between groups. Risk attitude is indeed conceptualized in economics as the curvature of the utility function (i.e., the subjective value) of the objective outcomes, with concave curves associated with risk aversion, and convex curves associated with risk seeking (54,56). By contrast, the approach or avoidance bias apply to all the value. A possible interpretation of the approach bias is that participant approach the option with the highest possible gain (the lottery) in the gain frame; the avoidance bias would then reflect a tendency to systematically avoid the highest potential losses (the lottery) in the loss frame.”

Reviewer #2 (Public review):

Summary:

This article addresses a very pertinent question: what are the computational mechanisms underlying risky behaviour in patients who have attempted suicide? In particular, it is impressive how the authors find a broad behavioural effect whose mechanisms they can then explain and refine through computational modeling. This work is important because, currently, beyond previous suicide attempts, there has been a lack of predictive measures. This study is the first step towards that: understanding the cognition on a group level. This is before being able to include it in future predictive studies (based on the cross-sectional data, this study by itself cannot assess the predictive validity of the measure).

Strengths:

(1) Large sample size.

(2) Replication of their own findings.

(3) Well-controlled task with measures of behaviour and mood + precise and well-validated computational modeling.

Weaknesses:

I can't really see any major weakness, but I have a few questions:

(1) I can see from the parameter recovery that the parameters are very well identified. Is it surprising that this is the case, given how many parameters there are for 90 trials? Could the authors show cross-correlations? I.e., make a correlation matrix with all real parameters and all fitted parameters to show that not only the diagonal (i.e., same data is the scatter plots in S3) are high, but that the off-diagonals are low.

Thank you for raising these thoughtful concerns. The current task consisted of 90 choices and 36 mood ratings. There were 5 choice parameters and 4 mood parameters. The apparently strong identifiability is not unexpected, as 90 choice trials and 36 mood ratings are comparable to those in prior computational modeling literature (Blain & Rutledge, 2022).

As suggested, we computed cross-correlations between all generating (“true”) and recovered (“fitted”) parameters. The resulting matrix showed high diagonal (choice winning model: rs > 0.91; mood winning model: rs > 0.90) and low off-diagonal (choice winning model: abs(rs) < 0.63; mood winning model: abs(rs) > 0.40) correlations, further supporting parameter recovery. Please see our clarifications below:

Supplementary Pages 2-3:

“Parameter recovery: Figure S3 shows good parameter recovery for both choice and mood winning model (choice: rs > 0.91, ps < 0.001; intraclass coefficients > 0.78; mood: rs > 0.90, ps < 0.001; intraclass coefficients > 0.86). Moreover, we computed cross-correlations between all generating (“true”) and recovered (“fitted”) parameters. The resulting matrix showed high diagonal (choice winning model: rs > 0.91; mood winning model: rs > 0.90) and low off-diagonal (choice winning model: abs(rs) < 0.63; mood winning model: abs(rs) > 0.40) correlations, further supporting parameter recovery.”

Page 10：

“The numbers of choice trials and mood ratings were comparable to those in prior computational modeling studies (34,35).”

(2) Could the authors clarify the result in Figure 2B of a correlation between gambling rate and suicidal ideation score, is that a different result than they had before with the group main effect? I.e., is your analysis like this: gambling rate ~ suicide ideation + group assignment? (or a partial correlation)? I'm asking because BSI-C is also different between the groups. [same comment for later analyses, e.g. on approach parameter].

Thank you for pointing out the lack of clarity. We performed group difference analysis and correlation of suicidal ideation analysis, separately. We first performed group difference analysis to test our hypothesis of STB effects. We then conducted correlational analysis to further specify our findings.

(3) The authors correlate the impact of certain rewards on mood with the % gambling variable. Could there not be a more direct analysis by including mood directly in the choice model?

Thank you for this insightful suggestion. As suggested, we tried to integrate mood into choice models by adding mood bias component(s) in line with previous literature (Vinckier et al., 2018). The first model (mcM1) assumes that mood biases choice, building on cM3 (the winning choice model). cmM2 further separated the mood bias parameter into two components according to participants’ choices.

However, model comparison using BIC supported cM3 (Table S6), that is, without consideration of mood in choice modeling. This can be due to the lack of block design in our experimental design unlike e.g., Vinckier et al., (2018) and Eldar & Niv, (2015). Please see our clarifications below:

Supplementary Pages 3-4:

“Supplementary Note 6: integration of mood into choice models

Although we modeled choice and mood separately to examine cognitive and affective mechanisms underlying increased risk behavior in adolescent suicidal patients, one interesting question was whether mood responses influence subsequent gambling choices and how to model them. First, we median-split mood responses (except the final rating) to compare gambling rate. Results showed a trend for less gambling rate in higher mood (t = -1.971, p = 0.050). However, there was no significant group difference (F = 0.680, p = 0.507). Second, with the assumption that mood biases choice, we constructed mcM1 based on cM3 (the winning choice model).

Based on our finding of the negative correlation between mood sensitivity to certain rewards and gambling rate in S⁺, we separated β_Mood parameter into β_Mood-CR and β_Mood-GR (cmM2).

Model comparison using BIC supported cM3 (Table S6), that is, without consideration of mood in choice modeling. The mood bias parameters in neither cM2 nor cM3 reached significance (ps > 0.091), which may be due to the absence of a blocked design in our experiment, unlike in Vinckier et al. (2018) and Eldar and Niv (2015).”

(4) In the large online sample, you split all participants into S+ and S-. I would have imagined that instead, you would do analyses that control for other clinical traits. Or, for example, you have in the S- group only participants who also have high depression scores, but low suicide items.

Thank you for this insightful suggestion. Following prior suicide-related literature (Tsypes et al., 2024), we controlled for depression by including them as covariates. Note that depression scores were derived from our established bifactor model (Wang et al., 2025), which decomposed depression from the anxiety. These results remained largely significant (ps ≤ 0.050), except a marginally significant effect of group on gambling behavior (p = 0.059). Despite a trend, this effect with covariates of depression-related questionnaires is strong in our clinical cohort (p = 0.024; Table S8). This suggests that the link between suicidality and risky behavior persists above and beyond general depressive symptoms.

Please see our clarifications below:

Page 26:

“After controlling for depression severity using our established bifactor model (see ref 60 for details), these results remained significant (ps ≤ 0.050), except a marginally significant effect of group on gambling behavior (p = 0.059). Despite a trend, this effect with covariates of depression-related questionnaires is strong in our clinical cohort (p = 0.024; Table S8). This suggests that the link between suicidality and risky behavior persists above and beyond general depressive symptoms.”

Reviewer #3 (Public review):

This manuscript investigates computational mechanisms underlying increased risk-taking behavior in adolescent patients with suicidal thoughts and behaviors. Using a well-established gambling task that incorporates momentary mood ratings and previously established computational modeling approaches, the authors identify particular aspects of choice behavior (which they term approach bias) and mood responsivity (to certain rewards) that differ as a function of suicidality. The authors replicate their findings on both clinical and large-scale non-clinical samples.

(1) The main problem, however, is that the results do not seem to support a specific conclusion with regard to suicidality. The S+ and S- groups differ substantially in the severity of symptoms, as can be seen by all symptom questionnaires and the baseline and mean mood, where S- is closer to HC than it is to S+. The main analyses control for illness duration and medication but not for symptom severity. The supplementary analysis in Figure S11 is insufficient as it mistakes the absence of evidence (i.e., p > 0.05) for evidence of absence. Therefore, the results do not adequately deconfound suicidality from general symptom severity.

Thank you for this important comment. Based on clinical interviews, we included patients with and without suicidality (S⁺ and S^- groups). However, in line with suicidal-related literature (e.g., Tsypes et al., 2024), two groups also differed substantially in the severity of symptoms (see Table 1). To address the request for evidence on specificity to suicidality beyond general symptom severity, we performed separate linear regressions to explain in gambling behaviour, value-insensitive approach parameter (β_gain), and mood sensitivity to certain rewards (β_CR) with group as a predictor (1 for S⁺ group and 0 for S^- group) and scores for anxiety and depression as covariates. Results remained significant after controlling anxiety and depression (ps < 0.027; Table S8). Given high correlations among anxiety and depression questionnaires (rs > 0.753, ps < 0.001), we performed Principal Components Analysis (PCA) on the clinical questionnaire to extract the orthogonal components, where each component explained 86.95%, 7.09%, 3.27%, and 2.68% variance, respectively. We then performed linear regressions using these components as covariates to control for anxiety and depression. Our main results remained significant (ps < 0.027; Table S9). We believe that these analyses provide evidence that the main effects on gambling and on mood were specific to suicide.

As pointed out, these “absence of evidence” cannot provide insights of “evidence of absence”. Although we median-split patients by the scores of general symptoms (e.g., depression and anxiety-related questionnaires) and verified no significant differences in these severities (Figure S11), we additionally conducted Bayesian statistics in gambling behavior, value-insensitive approach parameter, and mood sensitivity to certain rewards. BF₀₁ is a Bayes factor comparing the null model (M₀) to the alternative model (M₁), where M₀ assumes no group difference. BF₀₁ > 1 indicates that evidence favors M₀. As can be seen in Table S7, most results supported null hypothesis, suggesting that general symptoms of anxiety and depression overall did not influence our main results. Overall, we believe that these analyses provide compelling evidence for the specificity of the effect to suicide, above and beyond depression and anxiety.

Please see our revisions below:

Page 17:

“Within patients, this group effect on gambling rate remained significant after controlling for sex, illness duration, family history, diagnosis, and various medications use (ps < 0.05), as well as general symptoms (e.g., depression and anxiety; p = 0.024; also see Figure S11, Table S7 and Table S8). Given high correlations among anxiety and depression questionnaires (rs > 0.753, ps < 0.001), we performed Principal Components Analysis (PCA) to extract main components, where each component explained 86.95%, 7.09%, 3.27%, and 2.68% variance, respectively. To further control for anxiety and depression, linear regression using these components as covariates revealed that the group effect on gambling rate remained significant (p = 0.024; Table S9).”

Pages 18-19:

“Within patients, this group effect on the approach parameter remained significant after controlling for sex, illness duration, family history, diagnosis, and various medications use (ps < 0.05), as well as general symptoms (e.g., depression and anxiety; p = 0.027; also see Figure S11, Table S7 and Table S8). Linear regression using PCA components as covariates revealed that the group effect on approach parameter remained significant (p = 0.027; Table S9).”

Page 21:

“Within patients, this group effect on βCR remained significant after controlling for gambling rate, earnings, mood-related outcome effect, mood drift effect, sex, illness duration, family history, diagnosis, and various medications use (ps < 0.032), as well as general symptoms (e.g., depression and anxiety; p = 0.001; also see Figure S11, Table S7 and Table S8). Linear regression using PCA components as covariates revealed that the group effect on this mood parameter remained significant (p = 0.001; Table S9).”

(2) The second main issue is that the relationship between an increased approach bias and decreased mood response to CR is conceptually unclear. In this respect, it would be natural to test whether mood responses influence subsequent gambling choices. This could be done either within the model by having mood moderate the approach bias or outside the model using model-agnostic analyses.

Thank you for this important suggestion. As suggested, one interesting question was whether mood responses influence subsequent gambling choices and how to model them. First, we median-split mood responses (except the final rating) to compare gambling rate. Results showed a trend for less gambling rate in higher mood (t = -1.971, p = 0.050). However, there was no significant group difference (F = 0.680, p = 0.507). Second, with the assumption that mood biases choice, we constructed mcM1 based on cM3 (the winning choice model). Based on our finding of the negative correlation between mood sensitivity to certain rewards and gambling rate in S⁺, we separated β_Mood parameter into β_Mood-CR and β_Mood-GR (cmM2). Model comparison using BIC supported cM3 (Table S6), that is, without consideration of mood in choice modeling. This can be due to the lack of block design in our experimental design unlike e.g., Vinckier et al., (2018) and Eldar & Niv, (2015). Please see Supplementary Pages 3-4:

(3) Additionally, there is a conceptual inconsistency between the choice and mood findings that partly results from the analytic strategy. The approach bias is implemented in choice as a categorical value-independent effect, whereas the mood responses always scale linearly with the magnitude of outcomes. One way to make the models more conceptually related would be to include a categorical value-independent mood response to choosing to gamble/not to gamble.

We apologise for the unclear statement. The approach bias is implemented in choice as a continuous value-independent effect, ranging from -1 to 1.

It was true that the mood responses always scale with the magnitude of outcomes, since mood ratings were request after the outcomes. Therefore, mood parameters and the approach bias were both continuous.

We also attempted to integrate mood into choice modelling. See Response 2 for Reviewer 3 for details.

(4) The manuscript requires editing to improve clarity and precision. The use of terms such as "mood" and "approach motivation" is often inaccurate or not sufficiently specific. There are also many grammatical errors throughout the text.

Thank you for this important suggestion. We have now explained motivation and mood in the Introduction section and the computational modeling section. Please see our clarifications below:

Pages 3-4:

“A growing literature indeed shows that risky behavior can be far better explained after adding value-insensitive approach and avoidance components to prospect theory(18,19), that is by including a decision bias in favor of the highest gain (approach) and another decision bias against the lowest loss (avoidance), above and beyond options value difference. This class of models highlights the important role of value-insensitive motivational components in decision making in addition to risk attitude-driven valuation (e.g., loss/risk aversion)(20).”

Page 5:

“Although mood is thought to persist for hours, days, or even weeks(30-33), momentary mood, measured over the timescale in the laboratory setting, represents the accumulation of the impact of multiple events at the scale of minutes(30,32,34-38). Momentary mood external validity is demonstrated e.g., through its association with depression symptoms(37). Mood is different from emotions, which reflect immediate affective reactivity and is more transient (e.g., from surprise to fear)(31-33,39).”

We have corrected grammatical errors throughout the manuscript.

5) Claims of clinical relevance should be toned down, given that the findings are based on noisy parameter estimates whose clinical utility for the treatment of an individual patient is doubtful at best.

Thank you for this comment. We agree that we did not evaluate the noise in our estimate e.g., by assessing the test-retest reliability on the task parameters, which is outside the scope of the study, and it is indeed possible that parameter estimate is somehow noisy. Therefore, we tone down the clinical relevance of our results. Please see our revision below:

Page 32:

“Next, we did not evaluate the noise in our estimate e.g., by assessing the test-retest reliability on the task parameters and it is indeed possible that parameter estimate is somehow noisy.”

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

(1) Title: I believe "aberrant mood dynamics" is both too general and overstating the results of this study, which did not measure mood dynamics longitudinally. "Aberrant" is also overly pathologizing. I would suggest sticking more directly to the results, for instance, "Insensitivity of momentary mood to non-risky rewards in adolescent suicidal patients".

Thank you for this suggestion. We have now corrected it.

(2) Abstract: in line 61, "Our study uncovers the cognitive and affective mechanisms" suggests that these are the only ones, and you uncovered them. Of course, there could be more mechanisms contributing to risk behavior in STB, so I would suggest removing the word "the" or adding "one of the".

Thank you for this suggestion. We have now corrected it.

(3) One major weakness of this study is that suicidal thoughts and behaviors were not assessed via a clinical instrument such as the Columbia Suicide Severity Rating Scale - this should be mentioned upfront.

Thank you for this comment. According to medical records and information from family and friends by the researcher and psychiatrists, patients with suicidal thoughts and behaviors were categorized as suicidal group (S⁺), while patients without suicidal thoughts and behaviors were identified as control group (S^-). Note that medical records and information were recorded from clinical interviews where the psychiatrists were vigilant for signs of suicidal ideation and inquired about suicidal-related thoughts and behaviors from both the patients and their families. Therefore, the current group operation was possibly comparable to Columbia Suicide Severity Rating Scale.

(4) Table 1: female/male are sex, not gender (gender is man/woman/transgender/non-binary).

Thank you for this suggestion. We have now corrected it.

(5) Equation 1: It would be good to clarify what happens in gain-only or loss-only trials (the other value is then 0, but this can be clarified as it is not technically a loss or a gain).

Thank you for this suggestion. We have now corrected it. Please see below for our revision:

Page 12:

“Please note that V_gain is 0 in gain trials and V_loss is 0 in loss trials.”

(6) Figure 1E: The model prediction is not informative here. Given the linear regression model, there is no other option except that the mean prediction would overlap with the mean empirical measurement (unless the model was specified incorrectly). The same is true in Figure 2A.

Thank you for this suggestion. We have now removed plots for model prediction.

(7) Figure 1G: There was no analysis of the differences between groups in terms of earnings, given that the ANOVA was not significant. Still, if the claim is that risky behavior is sometimes suboptimal in this task, it would be good to show that there is a correlation between, say, symptoms of STB across groups and 1) risky behavior and 2) earnings.

Thank you for this insightful comment. In the patient cohort, risky behavior (gambling rate)—but not earnings—predicted the current suicidal ideation score (BSI-C, β = 9.189, t = 2.004, p = 0.048; earnings, β = 0.001, t = 0.582, p = 0.562). The lack of association for earnings is consistent with the task design, in which there is no stable optimal policy and payouts are only a coarse proxy for decision quality. Future work in learning paradigms, where optimality is well defined, may be better suited to test earnings-based links to STB. We have clarified this point below:

Page 32:

“Second, although we assumed that increased risky behavior in STB was suboptimal, the current task was not suited to test this, given the task design of random feedback for gambling option. Future work in learning paradigms, where optimality is well defined, may be better suited to test earnings-based links to STB.”

(8) Line 290: "beta_gain: -1-1" is unclear. I believe you meant beta_gain \in [-1,1].

Thank you for this suggestion. We have now corrected it to make it clear.

(9) The gain and loss biases are modeled as minimum and maximum probabilities for choosing the gamble. This is a legitimate choice for value-agnostic biases, but it is not the traditional choice (as far as I know). I wonder if the same results would hold with the more traditional formulation of the bias as an added constant to the utility of the gamble, i.e., p(gamble) = 1/(1+ exp(-mu(U_gamble + beta_gain - U_certain)). I believe in this case, you would also not have to specify different equations for positive or negative biases, or to limit the bias to the range of [-1,1] (indeed, the bias would be in reward-equivalent units).

Thank you for this suggestion. The winning choice model we used here was consistent with previous literature (Rutledge et al., 2015 & 2016), which decomposed the decision process into risk-attitude-driven valuation (e.g., loss and risk aversion) and value-insensitive motivational components. These approach/avoidance parameters are a decision bias in favor of the highest gain (approach) and another decision bias against the lowest loss (avoidance), above and beyond options value difference.

As suggested, we also compared the traditional bias choice model. Model comparison did not support this. Please see our revision below:

Supplementary Page 4:

“We also considered the traditional bias parameter (cM4), rather than approach/avoidance parameters. We limited the bias to the range of [-100, 100], which was in reward-equivalent units.

However, model comparison did not support cM4 (Table S6).”

(10) Also, for equations 5-8, it seems that 5-6 are identical to 7-8 except for the use of beta_gain versus beta_loss. You might want to consider simplifying by putting beta in the equations and specifying in the text that, depending on the trial type (loss or gain), the relevant beta is used.

Thank you for this suggestion. We have now simplified it. Please see response to Reviewer 2, point 3.

(11) It is not clear what equations are applied to mixed trials in cM3.

Sorry for the confusion. We have now clarified this point.

Page 12:

“Approach/avoidance parameters are not applied to in mixed trials.”

(12) Model comparison: the mood models are nested within each other (e.g., mM3 can be derived from mM1 by setting beta_EV = beta_RPE). In this case, model comparison can use the likelihood ratio test instead of BIC, which can be too conservative (and therefore does not support the extra beta parameter for RPE, different from previous results in the literature). I wonder if a likelihood ratio test would lead to results more in line with previous findings with this task?

Thanks for this suggestion. We agree that mM1 (CR+EV+RPE) and mM3 (CR+GR) are nested. However, our model space also included unnested models, such as mM5 (CR+GR_better+GR_worse). Therefore, it was not reasonable in our model space to use likelihood ratio tests.

(13) Line 346: The replication sample is described as "healthy participants," however, their health (or mental health) status was not assessed, and they may as well have mental health concerns. I would suggest calling this a general sample or an undifferentiated sample - but not a healthy sample.

Sorry for the confusion. We have now corrected this phrase.

(14) Line 363: "in addition to the replication of previous findings in the validation dataset" is unclear. Are those tests not two-tailed?

Sorry for the unclear statement. In the replication analyses, we used one-tailed t-tests because the direction of the effect was revealed on the clinical dataset. Please see our clarification below:

Page 15:

“For the replication of previous findings in the validation dataset, we used one-tailed tests in line with our clinically motivated directional hypothesis.”

(15) Line 372: "validating our group manipulation" - the presented work does not have a manipulation. Maybe you meant "validating our grouping of participants"?

Thank you for this suggestion. We have now corrected it to make it clear.

(16) Figure 2B: It is not clear how the data were binned for illustration purposes only, and why this binning is necessary (I have not seen it in other papers) - presenting the data from each subject and the correlation line with error margins (as is done here) should be sufficient.

Thank you for flagging this. For illustration only, we binned the data proportional to group sizes: in the patient sample (S^- n = 25; S⁺ n = 58; ≈1:2), we displayed 3 bins for S^- and 6 bins for S⁺. We agree that binning is not necessary; all statistics were computed on raw, unbinned data. The binned panel was included solely for visualization, consistent with our prior work (Blain et al., 2023).

(17) Table 2: delta BIC should be presented per subject (that is, divided by the number of subjects in each group), as the groups are of different sizes, so as presented now, the columns are not comparable across groups.

Thank you for the helpful suggestion. Our goal in Table 2 is not to compare ΔBIC magnitudes across groups, but to identify the winning model within each group. The ΔBICs are aggregated at the group level solely to rank models for that group. Dividing by the number of participants would rescale each group’s column by a constant and would therefore not affect the within-group ranking or the conclusion that cM3 is the best model in all groups. For this reason, we retain the current presentation and interpret each column within group rather than across groups.

(18) Line 640 - the effect of expectations and prediction errors on mood was not only shown in healthy people, but also in people with depression (Rutledge et al., 2007, https://pubmed.ncbi.nlm.nih.gov/28678984/)

Thank you for this comment. Indeed, Rutledge et al., (2017) showed evidence for CR+EV+RPE mood model in adult people with depression. However, our study recruited adolescents with depression or anxiety, given that adolescent period might provide a developmental window for opportunities for early intervention of suicidality. Therefore, it is also possible that the current winning model was specific to adolescents. Please see our clarifications below:

Page 28:

“It is also possible that the current winning model was specific to adolescents. Given that Rutledge et al., (2017) supported the “CR-EV-RPE model” in adults with depression, our study with adolescent populations may suggest a developmental change for mood sensitivities.”

(19) Supplemental material: Is the R2 section about R-squared? Perhaps you can use superscript on the 2 to make that clearer? For Figure S2, how was model recovery determined? Should I interpret the confusion matrix as suggesting that the winning model for each and every simulated subject was the generating model, or was the winning model determined for the whole simulated population in each of the 100 simulations? Traditionally, confusion matrices use the former measure, but the results of 100% recoverability make me suspect the latter was used here. In Figure S3, should we not be looking at simulated parameters and recovered parameters? What are "real parameters" here?

Thank you for these important comments. We now consistently denote the coefficient of determination as R² (with a superscript 2) throughout the manuscript and Supplementary Materials.

For the model recovery analysis in Figure S2, we have clarified that the confusion matrix is computed at the population level. Specifically, for each of the 100 simulations we generated a full dataset under each candidate model, fit all models to that dataset, and selected the winning model based on group-level model evidence (BIC). Each cell in the confusion matrix therefore reflects the proportion of simulations in which model j was selected as the best-fitting model when the data were generated by model i. This operation was reasonable because the decision of the winning model is made on the population-level dataset rather than on individual subjects.

In Figure S3, the term “real parameters” referred to the parameters used to generate the simulated data. To avoid confusion, we now relabel these as “simulated (generating) parameters” and explicitly describe the figure as showing the relationship between simulated (generating) parameters and recovered parameters. Please see our revisions below:

Supplementary Pages 2-3:

“Model recovery: We generated 100 simulated datasets for each model (3 choice models and 8 mood models) using the fitted parameters of each model as the ground truth. Each dataset contained 201 trials and included 3 (or 8) sets of simulated data corresponding to the respective models. For each simulated dataset, we then fit all models and determined the winning model at the population level based on group-level BIC, yielding a confusion matrix in which each entry represents the proportion of simulations in which model j was selected as the best-fitting model when the data were generated by model i. As shown in Figure S2, all models are highly identifiable, indicating excellent recovery performance for both the choice and mood models.”

“Parameter recovery: Figure S3 shows good parameter recovery for both choice and mood winning model (choice: rs > 0.91, ps < 0.001; intraclass coefficients > 0.78; mood: rs > 0.90, ps < 0.001; intraclass coefficients > 0.86). Moreover, we computed cross-correlations between all generating (“generating”) and recovered (“fitted”) parameters. The resulting matrix showed high diagonal (choice winning model: rs > 0.91; mood winning model: rs > 0.90) and low off-diagonal (choice winning model: abs(rs) < 0.63; mood winning model: abs(rs) > 0.40) correlations, further supporting parameter recovery.”

Typos:

(1) Line 90: original → originate

(2) Line 596-598 - the same phrase is repeated twice.

(3) Line 616: on the other word → hand.

Sorry for the mistakes. We have now corrected them throughout the manuscript.

Reviewer #2 (Recommendations for the authors):

For people unfamiliar with interpersonal theory or motivational-volitional model, or three-step theory (lines 105-106), could you briefly explain the key idea of mood and suicide before going to the decision-making tasks? And from this, maybe motivate the predictions in your task? In particular, in the abstract and introduction, the phrasing could be a bit more concise and simpler. In the abstract, sentences were sometimes quite long. In the introduction, some paragraphs are somewhat repetitive. In the discussion, there were some typos.

Thank you for these suggestions. We have now explained the key idea of mood and suicide before going to the decision-making tasks in the introduction, which can be seen below:

Pages 4-5:

“Contemporary theories of suicide converge on the idea that STB is initially caused by low mood experience. The interpersonal theory of suicide proposes that suicidal desire arises when people simultaneously feel socially disconnected (“thwarted belongingness”) and like a burden on others (“perceived burdensomeness”), experiences that are tightly linked to chronically low mood(25). The motivational–volitional model(26) and the three-step theory(27,28) similarly emphasize that when negative mood and feelings of defeat or entrapment are experienced as inescapable, they can give rise to suicidal ideation, and that the progression from ideation to suicide attempts depends on additional factors such as reduced fear of death, increased pain tolerance, and a tendency to act impulsively under intense affect. Some official organizations, e.g., National Institute of Mental Health, have also listed mood problems as warning signals(8). Interestingly, within the framework of decision making under uncertainty, gambling on lotteries with a revealed outcome has been found to induce high mood variance(29), providing an opportunity to assess the relationship between deficient mood and increased gambling decisions in STB.”

We have also refined the wording and corrected typos throughout the manuscript.

Reviewer #3 (Recommendations for the authors):

(1) Since many readers might only read the abstract, it is important that it is both informative and accurate. I have two suggestions in this respect. First, for the abstract to be more informative, it may be helpful to indicate already there that these are value-insensitive approach-avoidance parameters, in the sense that they favor/disfavor the gamble regardless of the potential outcomes' magnitude or probability. This issue is also present throughout the text, where the phrases "approach and avoidance motivation" are referred to as if they have established and precise computational definitions. In my view, these terms could just as easily be interpreted as parameters that multiply the value of potential gains or losses, which is not what the authors mean. It would be helpful to clarify this terminology.

Thank you for these suggestions. In line with previous literature (Rutledge et al., 2015 & 2016), approach and avoidance motivation are indeed defined at the computational level, referring to a decision bias in favor of the highest gain (approach) and another decision bias against the lowest loss (avoidance), above and beyond options value difference. We have cited these papers in the manuscript. We also make it clear to further clarify approach and avoidance parameters in the abstract and introduction. Please see our revisions below:

Page 2 (Abstract):

“Using a prospect theory model enhanced with value-insensitive approach-avoidance parameters revealed that this rise in risky behavior resulted only from a heightened approach parameter in S⁺.Altogether, model-based choice data analysis indicated dysfunction in the approach system in S⁺, leading to greater propensity for gambling in the gain domain regardless of the lottery expected value.”

Page 3 (Introduction):

“A growing literature indeed shows that risky behavior can be far better explained after adding value-insensitive approach and avoidance components to prospect theory(18,19), that is by including a decision bias in favor of the highest gain (approach) and another decision bias against the lowest loss (avoidance), above and beyond options value difference. This class of models highlights the important role of value-insensitive motivational components in decision making in addition to risk attitude-driven valuation (e.g., loss/risk aversion)(20).”

(2) The statement "our study uncovers the cognitive and affective mechanisms contributing to increased risk behavior in STB" is overstating the findings, as the study may have uncovered some contributing mechanisms, but likely not all of them. Removing the word "the" would fix this issue.

Thank you for this suggestion. We have now corrected it.

(3) Since mood is typically defined as lasting hours, it's inappropriate to refer to ratings that only reflect the last few trials as self-reports of mood. To be sure, I view the distinction between emotions and moods as quantitative, not qualitative, so I do not think there is a problem studying the former to understand the latter, but to avoid confusion, the terminology should follow common usage.

Thank you for this suggestion. We follow previous work and operational definitions regarding mood (Rutledge et al., 2014, Eldar & Niv, 2015, Vinckier et al., 2018). Emotion is usually a very brief response to a specific stimulus (Emanuel & Eldar, 2023), e.g., leading to rapid changes like surprise then fear. In contrast, mood is defined as a diffuse state that is not specific to one stimulus. Here, we operationally and computationally define mood as an affective state reflecting the recent history of safe and gamble outcomes. We now clarify that point in the main text. Please see our revision below:

Page 5:

“Although mood is thought to persist for hours, days, or even weeks(30-33), momentary mood, measured over the timescale in the laboratory setting, represents the accumulation of the impact of multiple events at the scale of minutes(30,32,34-38). Momentary mood external validity is demonstrated e.g., through its association with depression symptoms(37). Mood is different from emotions, which reflect immediate affective reactivity and is more transient (e.g. from surprise to fear)(31-33,39).”

(4) Line 78: The phrases "increase in risk attitude", "decrease in loss attitude", and "decrease in value-independent choice biases" are unclear to me in terms of their directionality. An attitude might be avoidant or embracing. If it is the former then increasing it would decrease risk-taking.

Thank you for pointing out the ambiguity. We have now corrected them throughout the manuscript. Please see our revision below:

Page 4:

“We therefore hypothesized that heightened approach motivation, or weakened avoidance motivation, would account for increased risk behavior in STB.”

(5) Line 125: I was not sure why one would expect the mood response to gamble-related quantities (EV and RPE) to be lower in STB and not higher.

Sorry for the typo. We hypothesized that mood would respond more strongly to gambling-related quantities—expected value (EV) and reward prediction error (RPE)—in adolescents with STB than in controls, given prior evidence that STB is associated with greater risk-taking.

(6) The text could use proofreading, as there are many typos. These are from the first 100 lines alone:

a) Abstract: regardless the lotteries -> regardless of the lotteries'.

b) Line 78: it remains whether.

c) Line 80: can each -> each can.

d) Line 90: may original from.

Sorry for the mistakes. We have now corrected them throughout the manuscript.

(7) The rationale for focusing on the S+ group for mood model comparison is incorrect. The purpose is to identify parameters that vary as a function of suicidality, and for that, the S- group is just as important.

Thank you for this comment. We agree that the S^- group is as important as the S⁺ group. A direct comparison was complicated because the winning mood models differed (S⁺: mM3; S^-: mM5; Table 3). To ensure comparability, we checked results from both model specifications (mM3 and mM5). The conclusions were convergent: mood sensitivity to certain rewards (CR) was lower in S⁺ than in S^- (see Fig. 3 for mM3 and Fig. S8 for mM5).

(8) There appears to be a contradiction between the inclusion criteria, which include having experienced suicidal thoughts and behaviors, and the definition of the S- group as not having suicidality.

Thank you for pointing out this mistake. The corrected version of inclusion criteria can be seen on Page 7:

“Patients were included if they met the following criteria: 1) both the researcher and psychiatrists agreed on their group classification; 2) they had a current diagnosis of major depressive disorder (MDD; unipolar depression), generalized anxiety disorder (GAD), or bipolar disorder with depressive episodes (BD), confirmed by two experienced psychiatrists using the Structured Clinical Interview for DSM-IV-TR-Patient Edition (SCID-P, 2/2001 revision; see Supplementary Note 1 for details); 3) they were between 10 and 19 years of age; 4) they had no organic brain disorders, intellectual disability, or head trauma; 5) they had no history of substance abuse; 6) they had no experience of electroconvulsive therapy.”

(9) It would be helpful to specify whether mood modeling was based on objective or subjective values, and why.

Thank you for this helpful suggestion. We have now clarified whether mood modeling was based on objective or subjective values, and why. Specifically, we constructed two model families: one in which mood was driven by objective monetary outcomes (objective values) and one in which mood was driven by subjective values derived from each participant’s fitted choice model (subjective values). We then used the VBA_groupBMC function in the VBA toolbox to perform family-wise model comparison, with 8 candidate mood models within each family. Consistent with previous literature, the objective-value family provided a clearly superior fit to the data (exceedance probability, EP = 1.000). Based on this result and for parsimony, we report and interpret the mood modeling results from the objective-value family in the main text. We have clarified this point below:

Supplement Pages 4-5:

“Supplementary Note 9: Mood model comparison using subjective values.

To identify whether mood modeling was based on objective or subjective values, we constructed two model families: one in which mood was driven by objective monetary outcomes (objective values) and one in which mood was driven by subjective values derived from each participant’s fitted choice model (subjective values). We then used the VBA_groupBMC function in the VBA toolbox (Daunizeau et al., 2014) to perform family-wise model comparison, with 8 candidate mood models within each family. Consistent with previous literature, the objective-value family provided a clearly superior fit to the data (exceedance probability, EP = 1.000).”

Author response:

The following is the authors’ response to the original reviews.

Public Reviews:

Reviewer #1 (Public review):

Summary:

CCK is the most abundant neuropeptide in the brain, and many studies have investigated the role of CCK and inhibitory CCK interneurons in modulating neural circuits, especially in the hippocampus. The manuscript presents interesting questions regarding the role of excitatory CCK+ neurons in the hippocampus, which has been much less studied compared to the well-known roles of inhibitory CCK neurons in regulating network function. The authors adopt several methods, including transgenic mice and viruses, optogenetics, chemogenetics, RNAi, and behavioral tasks to explore these less-studied roles of excitatory CCK neurons in CA3. They find that the excitatory CCK neurons are involved in hippocampal-dependent tasks such as spatial learning and memory formation, and that CCK-knockdown impairs these tasks.

However, these questions are very dependent on ensuring that the study is properly targeting excitatory CCK neurons (and thus their specific contributions to behavior). There needs to be much more characterization of the CCK transgenic mice and viruses to confirm the targeting. Without this, it is unclear whether the study is looking at excitatory CCK neurons or a more general heterogeneous CCK neuron population.

Strengths:

This field has focused mainly on inhibitory CCK+ interneurons and their role in network function and activity, and thus, this manuscript raises interesting questions regarding the role of excitatory CCK+ neurons, which have been much less studied.

Weaknesses:

(1a) This manuscript is dependent on ensuring that the study is indeed investigating the role of excitatory CCK-expressing neurons themselves and their specific contribution to behavior. There needs to be much more characterization of the CCK-expressing mice (crossed with Ai14 or transduced with various viruses) to confirm the excitatory-cell targeting. Without this, it is unclear whether the study is looking at excitatory CCK neurons or a more general heterogeneous CCK neuron population.

Thank you for this constructive comment. Indeed, the current study lacks comprehensive strategies to unequivocally distinguish excitatory CCK neurons from heterogeneous CCK neuronal populations. Nevertheless, we provide multiple lines of evidence supporting the distribution of CaMKIIα/Vglut1-expressing CCK⁺ neurons in the hippocampus (Figure 1F), using complementary approaches including transgenic mouse models as well as viral and antibody-based labeling (Figure 1A, Figure 1H-I). In addition, we demonstrate that 635 nm light reliably evokes field excitatory postsynaptic potentials (fEPSPs) at CA3-Schaffer collateral synapses expressing DIO-CaMKIIα-ChrimsonR in vitro (Figure 2A-F). Importantly, these light-evoked excitatory synaptic responses are abolished by AMPA and NMDA receptor antagonists (CNQX and APV), confirming the excitatory nature of the DIO-CaMKIIα-ChrimsonR-expressing synapses. To demonstrate the future works that can further support our findings and conclusions, we have added the strategies that can be conducted in the Discussion section in the revision:

“Due to technical limitations at the current stage, we were unable to perform whole-cell recordings or pharmacological manipulations using CCK receptor antagonists. In future studies, the application of these approaches to directly record and selectively block EPSPs from excitatory CCK neurons in the hippocampus will further strengthen and validate our conclusions.” (Line 265 - line 269 in the revision).

(1b) For the experiments that use a virus with the CCK-IRES-Cre mouse, there is no information or characterization on how well the virus targets excitatory CCK-expressing neurons. (Additionally, it has been reported that with CaMKIIa-driven protein expression, using viruses, can be seen in both pyramidal and inhibitory cells.

We thank the reviewer for this insightful comment regarding the specificity of viral targeting in CCK-IRES-Cre mice.

To address this concern, we performed additional characterization of viral expression in CA3. We found that DIO-CaMKIIα-mCherry expression showed a high degree of colocalization with CaMKIIα immunoreactivity, indicating preferential targeting of excitatory neurons (sFigure 1A-B; sFigure 2A-B; sFigure 3A-B). We showed an example to confirmed the high specificity of the AAV for infecting the excitatory CCK neurons in CA3 area.

Besides, we acknowledge prior reports showing that CaMKIIα-driven viral expression can, in some cases, be detected in a small subset of inhibitory neurons. However, because CA3-Schaffer collateral projections to CA1 arise exclusively from excitatory CA3 pyramidal neurons, any potential expression in inhibitory CCK⁺ interneurons are unlikely to directly contribute to the recorded CA1 synaptic responses in our electrophysiological experiments. That said, we cannot fully exclude the possibility that a minor population of inhibitory CCK⁺ neurons could indirectly modulate CA3 pyramidal neuron activity via local circuit mechanisms, particularly in experiments involving optogenetic manipulation or shRNA expression. We now explicitly acknowledge this limitation in the revised manuscript:

“Importantly, to further improve cell-type specificity, we propose an intersectional genetic strategy using CCK-IRES-Cre × VGlut1-Flp mice combined with a Cre-On/Flp-On (Con/Fon) AAV, which would restrict expression exclusively to excitatory CCK-expressing neurons and eliminate potential contributions from inhibitory CCK⁺ cells. This approach will be implemented in future studies to refine circuit specificity.” (Line 269 - line 273 in the revision).

(2) The methods and figure legends are extremely sparse, leading to many questions regarding methodology and accuracy. More details would be useful in evaluating the tools and data. More details would be useful in evaluating the tools and data. Additionally, further quantification would be useful-e.g. in some places, only % values are noted, or only images are presented.

Thank you for these constructive comments. We have expanded the methodological descriptions in both the Methods section and the figure legends to provide sufficient detail for evaluating the experimental tools and data accuracy. In addition, we have added quantitative analyses where previously only representative images or percentage values were shown. Specifically, quantification has now been included for each AAV condition in the corresponding figures in the revised manuscript.

(3) It is unclear whether the reduced CCK expression is correlated, or directly causing the impairments in hippocampal function. Does the CCK-shRNA have any additional detrimental effects besides affecting CCK-expression (e.g., is the CCK-shRNA also affecting some other essential (but not CCK-related) aspect of the neuron itself?)? Is there any histology comparison between the shRNA and the scrambled shRNA?

Recent studies from our lab demonstrated that knockout the CCK gene expression significantly attenuates the hippocampal-dependent spatial learning and CA3-CA1 LTP, indicating CCK plays a critical role in modulating the hippocampal functions[1,2]. Additionally, CCK-shRNA or CCK-scramble did not significantly affect the excitatory synaptic transmission in the CA3-CA1 projections, hinting that CCK-shRNA may exhibits no obvious adverse effect on other neural components.

Finally, we have provided the histology comparison between the shRNA and the scrambled shRNA regrading the expression level of the CCK protein (Pro-CCK) in the revision. Our result shows that CCK-shRNA (left panel) significantly reduced CCK expression in CA3^CCK-positive neurons compared with the CCK-Scramble group (right panel).

Citation:

(1) Wang, J. L., Sha, X. Y., Shao, Y., Zhang, Z. H., Huang, S. M., Lin, H., ... & Sun, J. P. (2025). Elucidating pathway-selective biased CCKBR agonism for Alzheimer’s disease treatment. Cell.

(2) Zhang, N., Sui, Y., Jendrichovsky, P., Feng, H., Shi, H., Zhang, X., ... & He, J. (2024). Cholecystokinin B receptor agonists alleviates anterograde amnesia in cholecystokinin-deficient and aged Alzheimer's disease mice. Alzheimer's research & therapy, 16(1), 109.

https://doi.org/10.7554/eLife.109001.1.sa2

Reviewer #2 (Public review):

Summary:

In this study, the authors have demonstrated, through a comprehensive approach combining electrophysiology, chemogenetics, fiber photometry, RNA interference, and multiple behavioral tasks, the necessity of projections from CCK+ CAMKIIergic neurons in the hippocampal CA3 region to the CA1 region for regulating spatial memory in mice. Specifically, authors have shown that CA3-CCK CAMKIIergic neurons are selectively activated by novel locations during a spatial memory task. Furthermore, authors have identified the CA3-CA1 pathway as crucial for this spatial working memory function, thereby suggesting a pivotal role for CA3 excitatory CCK neurons in influencing CA1 LTP. The data presented appear to be well-organized and comprehensive.

Strengths:

(1) This work combined various methods to validate the excitatory CCK neurons in the CA3 area; these data are convincing and solid.

(2) This study demonstrated that the CA3-CCK CAMKIIergic neurons are involved in the spatial memory tasks; these are interesting findings, which suggest that these neurons are important targets for manipulating the memory-related diseases.

(3) This manuscript also measured the endogenous CCK from the CA3-CCK CAMKIIergic neurons; this means that CCK can be released under certain conditions.

Weaknesses:

(1) The authors do not mention which receptors of the CCK modulate these processes.

We appreciate the reviewer for raising this important question. Based on our recent work, CCK-B receptors are the primary neural components mediating CCK functions in the hippocampus at both the synaptic plasticity and behavioral levels (Su et al., 2023; Zhang et al., 2024; Wang et al., 2025). To clarify this mechanism, we have added the following content to the revised manuscript:

“Based on our recent work, CCK signaling in the hippocampus is predominantly mediated by CCK-B receptors, which play a critical role in regulating synaptic plasticity and spatial memory-related behaviors.” (Line 105 - line 106 in the revision).

(2) This author does not test the CCK gene knockout mice or the CCK receptor knockout mice in these neural processes.

Thank you for this insightful comment. We previously tested these experiments in an earlier study. Our results showed that high-frequency electrical stimulation failed to induce significant LTP in the CA3-CA1 pathway in both CCK gene knockout (CCK-KO) mice and CCK-B receptor knockout (CCK-BR-KO) mice in vitro (Su et al., 2023; Zhang et al., 2024; Wang et al., 2025). These findings indicate that CCK mediates its synaptic effects predominantly through CCK-B receptors in the CA3-CA1 pathway. Accordingly, we have added this description to the revised manuscript.

“Additionally, high-frequency electrical stimulation fails to induce LTP in the CA3-CA1 pathway in both CCK-KO and CCK-BR-KO mice, indicating that CCK-dependent synaptic plasticity in this circuit is primarily mediated by CCK-B receptors.” (Line 170 - line 173 in the revision).

(3) The author does not test the source of CCK release during the behavioral tasks.

We thank the reviewer for raising this important point. In our previous work, we directly monitored CCK release in the hippocampus during an object-exploration task using a GPCR-based CCK-BR sensor combined with fiber photometry (Su et al., 2023). During object exploration, we observed a rapid and robust increase in CCK-BR sensor fluorescence, indicating activity-dependent CCK release in the hippocampus. Based on these findings, we deduced that hippocampal CCK release plays a critical role in hippocampus-dependent behavioral tasks.

We acknowledge that hippocampal neurons receive CCK-positive projections from multiple brain regions, making it technically challenging to isolate and monitor the precise source of CCK release in the CA1 area during behavioral tasks in vivo. One potential strategy to address this limitation is selective overexpression of CCK in CA3 neurons (e.g., AAV-CCK delivery), followed by assessment of CCK-BR sensor responses during hippocampal-dependent behaviors. We have added this discussion to the revised manuscript to clarify the source and functional relevance of CCK release during behavioral tasks.

“Besides, using a GPCR-based CCK-BR sensor combined with fiber photometry, our previous work demonstrated rapid, activity-dependent CCK release in the hippocampus during object-exploratory behavior, supporting a functional role for hippocampal CCK signaling in cognitive tasks (Su et al., 2023). Given that hippocampal neurons receive CCK-positive projections from multiple brain regions, it remains technically challenging to precisely identify the cellular source of CCK release in CA1 during behavior. Future studies employing selective CCK overexpression in CA3 neurons, together with CCK-BR sensor recordings, may help further delineate the contribution of CA3-derived CCK to hippocampal-dependent behaviors.” (Line 313 - line 321 in the revision).

Citation:

(1) Wang, J. L., Sha, X. Y., Shao, Y., Zhang, Z. H., Huang, S. M., Lin, H., ... & Sun, J. P. (2025). Elucidating pathway-selective biased CCKBR agonism for Alzheimer’s disease treatment. Cell.

(2) Zhang, N., Sui, Y., Jendrichovsky, P., Feng, H., Shi, H., Zhang, X., ... & He, J. (2024). Cholecystokinin B receptor agonists alleviates anterograde amnesia in cholecystokinin-deficient and aged Alzheimer's disease mice. Alzheimer's research & therapy, 16(1), 109.

(3) Su, J., Huang, F., Tian, Y., Tian, R., Qianqian, G., Bello, S. T., ... & He, J. (2023). Entorhinohippocampal cholecystokinin modulates spatial learning by facilitating neuroplasticity of hippocampal CA3-CA1 synapses. Cell Reports, 42(12).

https://doi.org/10.7554/eLife.109001.1.sa1

Reviewer #3 (Public review):

Summary:

Fengwen Huang et al. used multiple neuroscience techniques (transgenetic mouse, immunochemistry, bulk calcium recording, neural sensor, hippocampal-dependent task, optogenetics, chemogenetics, and interfer RNA technique) to elucidate the role of the excitatory cholecystokinin-positive pyramidal neurons in the hippocampus in regulating the hippocampal functions, including navigation and neuroplasticity.

Strengths:

(1) The authors provided the distribution profiles of excitatory cholecystokinin in the dorsal hippocampus via the transgenetic mice (Ai14::CCK Cre mice), immunochemistry, and retrograde AAV.

(2) The authors used the neural sensor and light stimulation to monitor the CCK release from the CA3 area, indicating that CCK can be secreted by activation of the excitatory CCK neurons.

(3) The authors showed that the activity of the excitatory CCK neurons in CA3 is necessary for navigation learning.

(4) The authors demonstrated that inhibition of the excitatory CCK neurons and knockdown of the CCK gene expression in CA3 impaired the navigation learning and the neuroplasticity of CA3-CA1 projections.

Weaknesses:

(1) The causal relationship between navigation learning and CCK secretion?

Thank you for pointing out this important issue. Previous studies have shown that CCK can be rapidly secreted during exploratory behaviors, as detected by the CCK-BR sensor. In parallel, CCK-positive neurons have been demonstrated to play a critical role in the precise execution of hippocampus-dependent spatial learning. Together, these findings suggest that exploratory behavior induces CCK secretion, which in turn contributes to the accuracy of hippocampal-dependent learning and memory processes. Based on this evidence, we propose that CCK secretion serves as a functional link between behavioral exploration and spatial learning. We have added these explanations in the revised manuscript to better clarify the causal relationship between behavioral exploration and CCK secretion:

“Besides, using a GPCR-based CCK-BR sensor combined with fiber photometry, our previous work demonstrated rapid, activity-dependent CCK release in the hippocampus during object-exploratory behavior, supporting a functional role for hippocampal CCK signaling in cognitive tasks (Su et al., 2023). Given that hippocampal neurons receive CCK-positive projections from multiple brain regions, it remains technically challenging to precisely identify the cellular source of CCK release in CA1 during behavior. Future studies employing selective CCK overexpression in CA3 neurons, together with CCK-BR sensor recordings, may help further delineate the contribution of CA3-derived CCK to hippocampal-dependent behaviors.” (Line 313 - line 321 in the revision)

(2) The effect of overexpression of the CCK gene on hippocampal functions?

We thank the reviewer for this comment. In fact, an earlier study from our laboratory demonstrated that intraperitoneal injection of exogenous CCK-4 significantly improved performance in hippocampus-dependent spatial learning tasks in both CCK gene knockout (CCK-KO) mice and Alzheimer’s disease (AD) mouse models. These findings suggest that enhancing CCK signaling can ameliorate hippocampal dysfunction at both the behavioral and synaptic plasticity levels (Zhang et al., 2024; Wang et al., 2025). Accordingly, although direct genetic overexpression of CCK in the hippocampus has not yet been extensively characterized, the observed benefits of exogenous CCK delivery support the notion that increased CCK availability positively modulates hippocampal function and spatial learning. We have cited this study in the revised manuscript to support this interpretation.

“Interestingly, an earlier study demonstrated that intraperitoneal injection of exogenous CCK-4 significantly improved performance in hippocampus-dependent spatial learning tasks in both CCK gene knockout (CCK-KO) mice and Alzheimer’s disease (AD) mouse models (Zhang et al., 2024). These findings suggest that enhancing CCK signaling can ameliorate hippocampal dysfunction at both the behavioral and synaptic plasticity levels.” (Line 291 - line 297 in the revision)

(3) What are the functional differences between the excitatory and inhibitory CCK neurons in the hippocampus?

In the hippocampus, CCK-expressing neurons consist of two major populations with distinct functions: excitatory (glutamatergic) and inhibitory (GABAergic) neurons. Excitatory CCK neurons are relatively sparse and intermingled with pyramidal cells. By releasing glutamate, they directly contribute to excitatory transmission and are thought to participate in synaptic plasticity and information processing related to learning and memory. In contrast, inhibitory CCK neurons are more abundant and include well-characterized interneuron subtypes such as CCK-positive basket cells. These neurons release GABA and primarily target the perisomatic region of pyramidal neurons, providing strong control over neuronal firing. Notably, inhibitory CCK interneurons are highly sensitive to neuromodulatory signals, particularly endocannabinoids via CB1 receptors, enabling dynamic regulation of inhibitory tone and network activity. Together, excitatory CCK neurons mainly support hippocampal excitation and plasticity, whereas inhibitory CCK neurons regulate network dynamics and spike timing. As the focus of the present study is on excitatory CCK neurons, a detailed comparison between these two populations was not included in the original manuscript.

(4) Do CCK sources come from the local CA3 or entorhinal cortex (EC) during the high-frequency electrical stimulation?

Thank you for this insightful comment. Our data indicate that the CCK detected during high-frequency stimulation originates from CA3 neurons rather than the entorhinal cortex (EC). As shown in Figure 2, we used an optogenetic approach combined with a GPCR-based CCK sensor to selectively examine CCK release from the CA3-CA1 pathway. ChrimsonR was specifically expressed in CA3 neurons projecting to CA1, restricting light stimulation to CA3 axon terminals. In parallel, the CCK sensor was locally expressed in CA1, allowing real-time detection of CCK release at CA3 presynaptic sites. High-frequency light stimulation robustly evoked CCK signals in CA1, demonstrating activity-dependent CCK release from CA3 terminals. Importantly, EC inputs were neither genetically targeted nor optically stimulated in this experiment, excluding the EC as a source of the detected CCK. Together, these results support the conclusion that CCK released during high-frequency stimulation is derived from local CA3 projections to CA1. Similarly, as the focus of the present study is on excitatory CCK neurons in the CA3 area, a detailed comparison between these two CCK sources was not included in the original manuscript.

Citation:

(4) Wang, J. L., Sha, X. Y., Shao, Y., Zhang, Z. H., Huang, S. M., Lin, H., ... & Sun, J. P. (2025). Elucidating pathway-selective biased CCKBR agonism for Alzheimer’s disease treatment. Cell.

(5) Zhang, N., Sui, Y., Jendrichovsky, P., Feng, H., Shi, H., Zhang, X., ... & He, J. (2024). Cholecystokinin B receptor agonists alleviates anterograde amnesia in cholecystokinin-deficient and aged Alzheimer's disease mice. Alzheimer's research & therapy, 16(1), 109.

(6) Su, J., Huang, F., Tian, Y., Tian, R., Qianqian, G., Bello, S. T., ... & He, J. (2023). Entorhinohippocampal cholecystokinin modulates spatial learning by facilitating neuroplasticity of hippocampal CA3-CA1 synapses. Cell Reports, 42(12).

Reviewer #1 (Public review):

Summary:

The authors test whether the frog buccal ventilatory rhythm generator behaves as a discrete, anatomically localized oscillator or as a distributed, state-dependent network. They combine reduced preparations (segment/subsegment work), systematic extracellular unit surveys over a defined grid, and local AMPA/GABA microinjections in a hemisected brainstem preparation. Based on these approaches, the authors conclude that mild global excitation (bath AMPA) broadens the distribution of rhythmically active units and renders a previously defined "buccal area" functionally non-identifiable as a unique necessary/sufficient locus.

The central idea is plausible, and the overall experimental strategy is appropriate for the question being asked. However, in its current form, the manuscript overstates the strength of inference supporting the "expansion" and "loss of necessity/sufficiency" conclusions. This is primarily due to (a) statistical treatment of unit-mapping data that does not respect clustering by preparation/animal, (b) inconsistent statistical reporting across sections, and (c) limited interpretability of focal inhibitory perturbations under a globally excited state.

Strengths:

(1) The manuscript addresses a clear mechanistic question with broader relevance: whether rhythm generation is best conceptualized as a localized kernel or as an emergent distributed property that changes with excitatory state.

(2) The authors use convergent approaches (reduced preparations, mapping, and necessity/sufficiency-style pharmacological perturbations), which is appropriate for circuit-level inference.

(3) A strong element is the within-unit analysis supporting state-dependent changes in phase coupling for a subset of units ("lung" units adopting a buccal-like pattern). The authors' offline PCA-based spike sorting (with cluster-quality selection via silhouette score) provides some reassurance that the reported pre/post injection changes are not simply driven by unit misidentification.

Weaknesses:

(1) Pseudoreplication in unit-survey statistics undermines the main mapping inference. The Methods state that "Units were pooled from multiple preparations" and that chi-squared tests were used to compare proportions across conditions (baseline vs 60 nM AMPA). The Results similarly report proportion changes (e.g., 110 units pooled from three preparations vs 137 units pooled from three additional animals) analyzed with chi-squared tests. Because many units come from the same preparation/animal, independence is unlikely to hold; therefore, inference about state-dependent reorganization at the systems level should be made at the preparation/animal level or via hierarchical models that explicitly account for clustering.

(2) Statistical methods are inconsistently described and need harmonization. In the segment dose-response "Analysis," values are described as compared to zero using a "One-sample t-test." Yet Table 1 is titled as using a "Wilcoxon One-sample Test." These discrepancies must be resolved throughout (Methods, Results, figure legends, and tables), including clear reporting of the unit of n and exact test statistics.

(3) Unit classification and operational definitions raise interpretational concerns. The unit classification scheme defines "buccal units" as those firing during buccal bursts as well as lung bursts, and explicitly notes that "no units were found which fired only during buccal bursts." This is a consequential result, and it currently reads more like a limitation of detection/classification (or state-space sampled) than a robust biological conclusion. Without additional evidence, it weakens claims about a distinct buccal rhythmogenic module and complicates the interpretation of "buccal identity" changes under excitation.

(4) Microinjection mapping: high exclusion rate and alternative explanations for 'loss of necessity' under excitation. The manuscript reports that 15 experiments were conducted, but 9 were excluded because the buccal area was not found or the preparation was "overdriven." This exclusion rate is too high to leave implicit; it raises concerns about selection bias and demands transparent accounting. Moreover, under baseline conditions, GABA (or AMPA-GABA) microinjections reliably reduce/abolish buccal bursts, but under bath 60 nM AMPA, the same injections produce no significant change in instantaneous frequency. This pattern can be interpreted as network redistribution, but it can also reflect state-dependent changes in gain, dynamic range, or local pharmacological impact (e.g., inhibition being comparatively underpowered in the globally excited state). Additional controls/analyses are required to distinguish these explanations.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors investigate the response of the amphibian respiratory rhythm generator under varying excitability conditions. They use pharmacological agents to increase and/ or decrease synaptic excitability and demonstrate the resilience of buccal rhythms under different conditions. They employ these results to formulate their primary thesis, that there is no obligatory locus of the buccal respiratory rhythm in the frog, and that their respiratory rhythmogenic mechanisms should be considered diffuse and anatomically distributed across a larger brainstem region.

Strengths:

This manuscript is well written, with a sufficiently large number of experiments, for which the authors should be congratulated.

Weaknesses:

The presented results don't support the authors' main conclusions, and the interpretation of the data is heavily biased toward their hypothesis. This impregnates an unsubstantiated narrative in the Abstract, Introduction, and Discussion of this manuscript, which must be reexamined with the following points in consideration:

(1) The authors seem to confuse degeneracy with redundancy. For instance, at line 54, they state, "These findings support the broader hypothesis that respiratory rhythm-generating circuits can switch to being diffuse and redundant, with discrete oscillators quickly drowning in a sea of excitations."

Redundancy means having the same component repeated multiple times to buffer the failure of any single component, whereas degeneracy means different functional components that compensate for one another under perturbations (Goaillard and Marder, ARN 2021)

Since the premotor-lung units get converted to buccal units under high excitability, this suggests a degenerate mechanism for respiratory rhythm generation- rather than a redundant mechanism, where there should be multiple buccal units that get recruited under different excitability conditions.

(2) Line 83, "but the essential requirement for a discrete, rudimentary buccal oscillator is also lost".

This statement is not supported by the data presented in this study. How does the expansion of the buccal unit imply that the essential requirement for discreteness is lost? Under increased excitability, does the burst/rhythm initiation zone also expand? Or does it still remain centered around the location of buccal units under physiological conditions? Increased excitability can lead to recruitment of a larger area, without a change in the location of the rhythmogenic kernel.

(3) Line 86, "... oscillators should be viewed as promiscuous flexible functional entities that expand or contract...".

Oscillators can be regarded as promiscuous only if, under physiological conditions, they switch positions. Under high excitability, only the flexibility argument holds, which has been established in mammals before (e.g., CA Del Negro, K Kam, JA Hayes, JL Feldman, The Journal of physiology 587 (6), 1217-1231; CA Del Negro, C Morgado-Valle, JL Feldman,Neuron 34 (5), 821-830; NA Baertsch, LJ Severs, TM Anderson, JM Ramirez, Proceedings of the National Academy of Sciences 116 (15), 7493-7502; NA Baertsch, HC Baertsch, JM Ramirez Nature communications 9 (1), 843).

Results:

(4) Interpretation of data in Figure 6.

How does the Buccal activity and L2 Power stroke change with 60nm AMPA (in CN5)? Does the increase in the Buccal neurons and decrease in power stroke neurons also reflect in the CN5 activity? Also see comments on Figure 9 data below.

(5) Interpretation of data in Figure 7.

Here, classifying buccal neurons solely by spiking may obscure the fact that the 'silent' neurons under baseline conditions were part of the rhythmic network but could not spike due to subthreshold inputs. 60 nM AMPA increased their firing in response to previously subthreshold synchronous inputs during the buccal burst. Intracellular recordings are required to negate this possibility and establish that the neuronal classification is robust.

(6) Interpretation of data in Figure 8.

"Lung units can transform into buccal units under excitation".<br /> CN5 buccal and lung bursts need to be compared before and after AMPA injection. From Figure 8 A-D, it is apparent that the example Unit2's activity increases during the buccal bursts, after AMPA injection. However, they are also present in buccal burst pre-AMPA, albeit with less frequency.

It is striking that the pre-AMPA epoch (panel A) is less than half of the post-AMPA epoch. This would, in itself, lead to a biased estimate of lung units that are active under the baseline condition during the buccal bursts.

Figure 8G, meta-analysis of lung units spiking during the baseline buccal bursts is warranted to interpret the main claim of this figure. Similarly, analysis of spiking per lung burst for the post-AMPA condition is essential for comparing the lung unit's contribution under high excitability.

(7) Interpretation of data in Figure 9

"Buccal area loses importance under increased excitation."

This interpretation is not fully supported by the data presented in this manuscript. Under 60 nm AMPA, does the ratio of lung burst to buccal burst change in CN5? This analysis is crucial for determining whether the lung units are indeed converted into buccal bursts at the expense of lung activity or whether their appearance during buccal bursts is incidental due to increased excitability. In the baseline, there are 4-5 buccal bursts per lung burst, whereas under high excitability, there are 2-3 buccal bursts per lung burst (Figure 9 A-B). This seems inconsistent with the conclusion that increased excitability converts lung units into buccal units (Figures 6 &7).

Could the authors comment on the connectivity between the lung and the buccal units? Results in Figure 9A-B indicate that lung units may receive an efference copy of buccal units, and under high excitability, their spikes may generate negative feedback onto the buccal units, terminating their bursts. This could explain the decrease in the buccal-to-lung burst in high-AMPA conditions. This type of circuit interaction resembles the mammalian breathing CPG, in which the parafacial/RTN (which controls the abdominal muscles) and preBötC (which controls the diaphragm) interact and cross-inhibit each other.

(8) Line 382.

"Buccal-like bursting produced from two independent slices".

The two "independent" slices have portions of the same anatomical kernel, the buccal rhythm generator. This experiment is like the sandwich slice preparation of preBötC (Del Negro Lab), in which two thinner slices exhibit rhythmic activity. Thus, the two slices are not independent; they are anatomically adjacent and functionally overlapping.

Author response:

Reviewer #1 (Public review):

Hierarchical Inference (Unit Survey)

We agree that pooling units across preparations can overstate the strength of inference if preparation-level clustering is ignored. We will therefore reanalyze the unit-survey dataset using a hierarchical approach in which the preparation/animal is treated as the unit of inference. Our pooled dataset was derived from three chunk preparations exposed to AMPA and three baseline preparations, allowing us to report per-preparation proportions and variability as requested.

A preliminary reanalysis of the buccal segment preparations is summarized below. In this analysis, the unit of inference is shifted from individual recorded units to the preparation level (n = 3 baseline; n = 3 at 60 nM AMPA), thereby accounting for potential within-preparation dependence.

Author response table 1.

The distribution of units for each of the three preparations per condition is as follows:

Using the proportion of buccal units per preparation as the dependent variable:

Baseline (n = 3): mean proportion of buccal units = 6.5% (SD 5.7%).

60 nM AMPA (n = 3): mean proportion of buccal units = 53.2% (SD 6.0%).

Absolute difference in proportions = 46.7% (95% CI 33.4% to 59.8%).

Independent-samples t-test on per-preparation proportions: t(4) = 9.77, p = 0.0006.

Thus, this preliminary hierarchical reanalysis indicates that the observed recruitment is consistent across preparations and is not driven by outlier data from a single animal. These results support substantial expansion of the buccal oscillator with excitation.

Statistical Standardization: In the revision, we will better justify our use of parametric and non-parametric versions of the one-sample tests and review usage in the Methods, Table 1, and figure legends for consistency.

Exclusion criteria for microinjection experiments: We will extend the description of these experiments by including a flow diagram summarizing the 15 attempted microinjection experiments and documenting the technical reasons for the 9 exclusions. These exclusions reflected the technical requirements of the preparation: (a) the buccal area had to be localized before AMPA excitation so that the effects of buccal-area manipulation during excitation could be interpreted reliably, which was not always possible; and (b) preparations had to exhibit sufficiently sustained periods of consecutive buccal bursting to permit quantification of buccal burst frequency, whereas some preparations expressed motor patterns dominated by lung bursts.

Pharmacological Potency and Necessity: We will revise the wording of this section to make the causal interpretation more precise. Our data already show that local GABA microinjections can reverse the excitatory effects of local AMPA microinjections, providing an internal control for local pharmacological efficacy of GABA when the local network is excited. Notably, the local AMPA concentration used in these experiments (5 µM) is nearly two orders of magnitude greater than the 60 nM concentration used in bath application. We therefore interpret the failure of focal GABA inhibition to abolish rhythm during global excitation as being consistent with expansion of rhythmogenic capacity beyond the spatial reach of the local injection, rather than with failure of the GABA manipulation itself.

Finding an inhibitory site that remains sensitive in bath applied AMPA is an interesting experiment but this would require identifying the anatomical substrate of a brainstem circuit for a non-ventilatory circuit in Rana that is guaranteed not to undergo reconfiguration with AMPA. This is beyond the scope of the current manuscript; based on our work to identify the neuronal substrate for ventilation in Rana, this would take at least five years to complete. In addition, having identified such a circuit there would be no guarantee that AMPA would not cause reconfiguration in this case too. With regards to transection boundaries and location of injections, we agree these would be useful refinements. We used the location of nerves as reliable landmarks to guide transections and located the buccal area using stereotactic coordinates to guide micropipette insertion and functional criteria (AMPA and GABA sufficiency and necessity tests) to locate the exact position based on our previous work.

Unit Classification: We will review the nomenclature we use to define units to ensure it does not cause confusion and provide more explicit criteria for unit classes. This will include clarification of the absence of “buccal-only” units as currently defined. Specifically, when both buccal and lung rhythms are present, units active during buccal bursts are also active during lung bursts in our preparation. This does not conflict with the multiple interacting oscillator model we have proposed previously. Rather, recruitment of buccal-area neurons during lung bursts is consistent with a model in which the lung oscillator excites the buccal oscillator. It is also consistent with prior evidence that lung bursts persist after buccal-area ablation. In addition, burst frequency during lung episodes exceeds buccal burst frequency during intervening buccal periods. We will revise the text to make this logic clearer.

Reviewer #2 (Public review):

(1) Degeneracy vs. Redundancy

We agree that degeneracy is the more precise term for the phenomenon our data demonstrate, in which structurally and functionally distinct neurons (lung units) acquire the capacity to participate in buccal rhythm generation under excitation. The Discussion already uses this language (e.g., "necessity and sufficiency may not work in a large degenerate network where rhythm generation is distributed across many elements"), but we used the word "redundant" in the Key Points Summary and Abstract in the broader sense of distributed robustness that a wider readership could grasp. Nonetheless, we recognize the distinction drawn by Goaillard and Marder (2021) and, considering the reviewers concerns, we will revise the Abstract and Key Points to adopt the degeneracy framework consistently.

(2) Loss of Essential Requirement for a Discrete Oscillator

The reviewer asks whether expansion of the rhythmically active region necessarily implies loss of the rhythmogenic kernel. We believe our necessity and sufficiency experiments (Figure 9) directly address this. Under baseline conditions, GABA microinjection into the buccal area reliably abolishes buccal bursting; under 60 nM bath AMPA, the same injection at the same location and volume has no significant effect on buccal frequency. If the kernel remained essential and the surrounding recruitment were merely supplementary, local inhibition of the kernel should still slow or abolish the rhythm. It does not. We interpret this as evidence that the essential requirement for the discrete buccal area is lost under excitation, not merely that a larger area has been recruited around a still-critical core. We acknowledge, however, that the word "lost" could be read as implying permanent elimination rather than state-dependent suspension, and we will temper this language in the revision.

(3) Novelty Relative to Mammalian Studies

We appreciate the reviewer drawing attention to the cited mammalian literature (Del Negro et al., 2002, 2009; Baertsch et al., 2018, 2019), which we discuss in detail in the manuscript. However, we respectfully note that our findings extend this literature in several ways that the public review does not acknowledge. First, Baertsch et al. demonstrated recruitment of tonic or silent neurons to become phasically active during inspiration; we show that neurons already assigned to one oscillator phase (lung) can be dynamically reassigned to another (buccal), which represents a qualitatively different form of reconfiguration. Second, we developed a novel approach to functionally ablate motor neuron pools using high-frequency nerve stimulation, enabling the unit survey to be interpreted at the premotor level which was not achieved in the mammalian studies cited. Third, our data provide the first demonstration of state-dependent oscillator expansion in a non-mammalian tetrapod, offering evolutionary context that strengthens the generality of the principle. We will revise the term "promiscuous" if it overstates the claim, but we maintain that our data support the conclusion that oscillator boundaries are flexible, which goes beyond what has been shown in mammals.

(4) Figure 6, CN5 Output Under AMPA

The reviewer asks whether the shift in premotor unit composition is reflected in CN5 motor output. This is a reasonable question. As noted in the manuscript, 60 nM AMPA produces only minor changes in the overt motor pattern as recorded from CN5, which is precisely why we interpret the premotor changes as a reorganization of the network's internal architecture that is not readily apparent from motor output alone. This is in sharp contrast to observations of substantive network reconfiguration in mammals in which eupnea is replaced by the pathological condition of gasping. We will add quantification of CN5 burst parameters (amplitude, duration, frequency) under baseline and 60 nM AMPA to make this point explicit.

(5) Subthreshold Recruitment vs. Network Expansion

The reviewer suggests that neurons classified as newly rhythmic under AMPA may have been part of the rhythmic network all along, receiving subthreshold inputs at baseline. We are grateful to the reviewer for highlighting this and hope they would agree that the literature clearly demonstrates that all respiratory neurons receive subthreshold phasic inputs of one kind or another, perhaps providing a clue that reconfiguration is a common feature of respiratory networks generally. Regardless of the implications for other animals, we agree this is likely the mechanism at work in the frog, and indeed our manuscript states that "this increase in the number and proportion of premotor buccal units is due in part to recruitment of sub-threshold buccal neurons that, under low excitability, only fire during lung bursts," citing intracellular evidence from Kogo and Remmers (1994) that lung neurons in this region receive subthreshold buccal-timed input. We note that this observation does not diminish our conclusion and likely explains the mechanism by which network expansion occurs. Whether one calls these neurons "newly recruited" or "pushed above threshold," the functional consequence is the same: a larger population of neurons is now rhythmically active during buccal bursts, and the necessity of the original buccal area is lost. We will clarify this reasoning in the revision and acknowledge the limitation that additional intracellular recordings from our preparation would be needed to fully characterize the subthreshold dynamics.

(6) Figure 8, Epoch Length and Meta-analysis

The reviewer notes that the pre-AMPA epoch appears shorter than the post-AMPA epoch in Figure 8A, which could bias unit classification. We will address this in the revision by reporting epoch durations explicitly and addressing its implication on spike counts where appropriate. Regarding the request for meta-analysis of lung unit spiking during baseline buccal bursts: this analysis is part of the rationale for the phase-recruitment panels, and we will expand Figure 8 to include the requested cross-condition comparisons (lung unit activity during baseline buccal bursts, and during post-AMPA lung bursts) as also suggested by Reviewer 3.

(7) Figure 9, Buccal-to-Lung Burst Ratio

The reviewer observes that the ratio of buccal to lung bursts decreases from approximately 4-5:1 under baseline to 2-3:1 under 60 nM AMPA, and suggests this is inconsistent with conversion of lung units into buccal units. We do not believe this is inconsistent. The buccal-to-lung burst ratio reflects the overt motor pattern, which is determined by the interaction of multiple oscillators and is influenced by AMPA at both buccal and lung levels. A change in this ratio does not speak to whether individual premotor units have acquired buccal-timed activity; the unit survey and the single-unit transformation data (Figure 8) address that question directly. Regarding the alternative model involving efference copy and cross-inhibition: this is an interesting hypothesis, but it is speculative and not tested by the current dataset. We are happy to discuss lung-buccal interactions more fully in the revision, including the parallels to parafacial/preBötC interactions in mammals, but we note that our data on unit transformation are better explained by network reconfiguration than by a feedback model that remains to be tested.

(8) "Independent" Slices

The reviewer compares our Level 2 transection to the preBötC sandwich slice preparation and argues the two resulting slices are not independent. We take the reviewer's point that "independent" may be read as implying no shared developmental or functional origin, which is not our intent. By "independent" we mean that the two physically separated slices can each generate rhythmic output without being synaptically connected to each other. This is, in fact, our central point: rhythmogenic capacity is distributed across a region broad enough to endow two separated slices with independent rhythm-generating capability when excited. We note that the analogy to the sandwich slice is imperfect because in our Level 1 cuts, only the rostral slice containing the buccal area generates rhythm -- the caudal slice does not -- whereas Level 2 cuts that bisect the buccal area produce rhythmicity in both halves, consistent with distributed capacity specifically within the buccal region. We will revise the wording to clarify what we mean by "independent" in this context.

Reviewer #3 (Public review):

Physiological Parallels: We will expand the Discussion to place these findings in a broader comparative context, including the eupnea-to-gasping transition in mammals as an example of state-dependent reconfiguration of respiratory networks. This will also allow us to clarify two advances that may otherwise be missed when comparing our work to that in mammals: (a) we developed a novel approach to functionally eliminate motor neurons, allowing mapped units to be interpreted as premotor; and (b) the state-dependent reconfiguration of the buccal oscillator occurred without qualitative changes in the overt lung-buccal motor pattern.

Unit Transformation Analysis: We will revise Figure 8 to improve clarity around the observed lung-to-buccal transformation by expanding the phase-recruitment panels as suggested and will revisit the operational definitions of lung and buccal unit identity to reduce ambiguity. The central observation is that some units active only during lung bursts under one condition become active during buccal bursts when network excitation is increased.

Saturation vs. Network Expansion: We will directly address the possibility that 60 nM bath-applied AMPA simply pushes the network toward a frequency ceiling. Two observations strongly argue against this interpretation: (a) 60 nM global AMPA produced only mild changes in buccal frequency, whereas local AMPA injection at much higher concentrations produced larger effects; and (b) local GABA was sufficient to reverse the effects of high-concentration local AMPA microinjections but insufficient to abolish rhythm during low-concentration global AMPA application. Together, these findings are more consistent with global AMPA endowing the network with distributed rhythm-generating capacity than with simple saturation of a discrete local oscillator. Notwithstanding these arguments, we will attempt to extend AMPA/GABA dose response experiment as suggested or add the lack of such experiments as a caveat to our interpretation.

Figure 9C Correction: We will correct the statistical markings in Figure 9C to align with the text in the Results regarding the significance of frequency changes under 60 nM AMPA.

In total, we believe these revisions will improve the rigor and clarity of the manuscript while preserving the central conclusion supported by the data: that the organization of the frog respiratory rhythmogenic network is state dependent and becomes more distributed under excitation.

Reviewer #1 (Public review):

This manuscript investigates how dentate gyrus (DG) granule cell subregions, specifically suprapyramidal (SB) and infrapyramidal (IB) blades, are differentially recruited during a high cognitive demand pattern separation task. The authors combine TRAP2 activity labeling, touchscreen-based TUNL behavior, and chemogenetic inhibition of adult-born dentate granule cells (abDGCs) or mature granule cells (mGCs) to dissect circuit contributions.

This manuscript presents an interesting and well-designed investigation into DG activity patterns under varying cognitive demands and the role of abDGCs in shaping mGC activity. The integration of TRAP2-based activity labeling, chemogenetic manipulation, and behavioral assays provides valuable insight into DG subregional organization and functional recruitment. However, several methodological and quantitative issues limit the interpretability of the findings. Addressing the concerns below will greatly strengthen the rigor and clarity of the study.

Major points:

(1) Quantification methods for TRAP+ cells are not applied consistently across panels in Figure 1, making interpretation difficult. Specifically, Figure 1F reports TRAP+ mGCs as density, whereas Figure 1G reports TRAP+ abDGCs as a percentage, hindering direct comparison. Additionally, Figure 1H presents reactivation analysis only for mGCs; a parallel analysis for abDGCs is needed for comparison across cell types.

(2) The anatomical distribution of TRAP+ cells is different between low- and high-cognitive demand conditions (Figure 2). Are these sections from dorsal or ventral DG? Is this specific to dorsal DG, as itis preferentially involved in cognitive function? What happens in ventral DG?

(3) The activity manipulation using chemogenetic inhibition of abDGCs in AsclCreER; hM4 mice was performed; however, because tamoxifen chow was administered for 4 or 7 weeks, the labeled abDGC population was not properly birth-dated. Instead, it consisted of a heterogeneous cohort of cells ranging from 0 to 5-7 weeks old. Thus, caution should be taken when interpreting these results, and the limitations of this approach should be acknowledged.

(4) There is a major issue related to the quantification of the DREADD experiments in Figure 4, Figure 5, Figure 6, and Figure 7. The hM4 mouse line used in this study should be quantified using HA, rather than mCitrine, to reliably identify cells derived from the Ascl lineage. mCitrine expression in this mouse line is not specific to adult-born neurons (off-targets), and its expression does not accurately reflect hM4 expression.

(5) Key markers needed to assess the maturation state of abDGCs are missing from the quantification. Incorporating DCX and NeuN into the analysis would provide essential information about the developmental stage of these cells.

Minor points:

(1) The labeling (Distance from the hilus) in Figure 2B is misleading. Is that the same location as the subgranular zone (SGZ)? If so, it's better to use the term SGZ to avoid confusion.

(2) Cell number information is missing from Figures 2B and 2C; please include this data.

(3) Sample DG images should clearly delineate the borders between the dentate gyrus and the hilus. In several images, this boundary is difficult to discern.

(4) In Figure 6, it is not clear how tamoxifen was administered to selectively inhibit the more mature 6-7-week-old abDGC population, nor how this paradigm differs from the chow-based approach. Please clarify the tamoxifen administration protocol and the rationale for its specificity.

Comments on revisions:

I appreciate the authors' careful and thorough revisions. They have addressed all of my previous concerns satisfactorily, and the manuscript is now significantly strengthened. I have no further concerns.

Reviewer #3 (Public review):

This study examines the role of dentate gyrus neuronal populations, reflecting neurogenesis and anatomical location (suprapyramidal vs infrapyramidal blade), in a mnemonic discrimination task that taxes the pattern separation functions of the dentate. The authors measure dentate gyrus activity resulting from cognitive training and test whether adult neurogenesis is required for both the anatomical patterns of activity and performance in the cognitive task. The authors find that more cognitively challenging variants of the task evoked more dentate activity, but also distinct patterns of activity (more activity in the suprapyramidal blade, less in the infdrapyramidal blade). Using chemogenetic approaches they silence mature vs immature dentate gyrus neurons and find that only mature neurons (either the general population or specifically mature adult-born neurons), and not immature adult-born neurons, are required for the difficult version of the task. Inhibition of mature adult-born neurons furthermore increased overall activity in the dentate and reduced the biased pattern of activity across the blades, consistent with evidence that adult-born neurons broadly regulate dentate gyrus activity.

Comments on revisions:

I appreciate the efforts the authors have taken to revise this manuscript. I have only minor concerns with this revised version of the manuscript:

Methods state that significance is defined as P<0.05 but some results are interpreted as significant when P=0.05. Either the alpha value needs to change or the interpretation needs to change.

I believe the statistical results for group and blade effects for the ANOVAs, in Figs 2,3 & 4, appear to be switched (blade should be significant, not group).

I appreciate that sometimes there is not a perfect overlap between immunohistochemical signals, but I continue to believe that the spatially-non-overlapping TRAP and EDU signals in Fig 3 is caused by these 2 markers being in different cells. A Z-stack or orthogonal projection could verify/disprove this concern.

Author Response:

The following is the authors’ response to the original reviews.

Public Reviews:

Reviewer #1 (Public review):

This manuscript investigates how dentate gyrus (DG) granule cell subregions, specifically suprapyramidal (SB) and infrapyramidal (IB) blades, are differentially recruited during a high cognitive demand pattern separation task. The authors combine TRAP2 activity labeling, touchscreen-based TUNL behavior, and chemogenetic inhibition of adult-born dentate granule cells (abDGCs) or mature granule cells (mGCs) to dissect circuit contributions.

This manuscript presents an interesting and well-designed investigation into DG activity patterns under varying cognitive demands and the role of abDGCs in shaping mGC activity. The integration of TRAP2-based activity labeling, chemogenetic manipulation, and behavioral assays provides valuable insight into DG subregional organization and functional recruitment. However, several methodological and quantitative issues limit the interpretability of the findings. Addressing the concerns below will greatly strengthen the rigor and clarity of the study.

Major points:

(1) Quantification methods for TRAP+ cells are not applied consistently across panels in Figure 1, making interpretation difficult. Specifically, Figure 1F reports TRAP+ mGCs as density, whereas Figure 1G reports TRAP+ abDGCs as a percentage, hindering direct comparison. Additionally, Figure 1H presents reactivation analysis only for mGCs; a parallel analysis for abDGCs is needed for comparison across cell types.

In Figure 1G and 1H we report TRAP+ abDGCs as a percentage rather than density because we are analyzing colocalization of the two markers, which are very sparse in this population. Given the very low number of double-labeled abDGCs, calculating density would not be practical. In the revised manuscript we have clarified the rationale for using these measures. As noted in the current text, we did not observe abDGCs co-expressing TRAP and c-Fos; we have made this point more explicit to guide interpretation of these data.

(2) The anatomical distribution of TRAP+ cells is different between low- and high-cognitive demand conditions (Figure 2). Are these sections from dorsal or ventral DG? Is this specific to dorsal DG, as it is preferentially involved in cognitive function? What happens in ventral DG?

The sections shown in Figure 2 were obtained from the dorsal dentate gyrus (see Methods, “Histology and imaging”: stereotaxic coordinates −1.20 to −2.30 mm relative to bregma, Paxinos atlas). From a feasibility standpoint, it is not possible to analyze the entire longitudinal extent of the hippocampus with these low-throughput histological approaches. We therefore focused on the dorsal DG, for which there is a strong functional rationale. A large body of work indicates that the dorsal hippocampus, and specifically the dorsal DG, is preferentially involved in spatial memory and in the fine contextual discrimination that underlies pattern separation. The dorsal hippocampus is critical for encoding and distinguishing similar spatial representations, a core component of the high-cognitive demand task used here. In contrast, the ventral DG is more strongly associated with emotional regulation and affective memory processing and is less implicated in high-resolution spatial encoding. For these reasons, the present study was designed to assess TRAP+ cell distributions specifically in the dorsal DG.

(3) The activity manipulation using chemogenetic inhibition of abDGCs in AsclCreER; hM4 mice was performed; however, because tamoxifen chow was administered for 4 or 7 weeks, the labeled abDGC population was not properly birth-dated. Instead, it consisted of a heterogeneous cohort of cells ranging from 0 to 5-7 weeks old. Thus, caution should be taken when interpreting these results, and the limitations of this approach should be acknowledged.

We agree that prolonged tamoxifen administration results in labeling a heterogeneous population of abDGCs spanning approximately 0 to 5–7 weeks of age, rather than a precisely birth-dated cohort. This is a limitation of this approach and we have included discussion of this in more detail in the revised manuscript.

(4) There is a major issue related to the quantification of the DREADD experiments in Figure 4, Figure 5, Figure 6, and Figure 7. The hM4 mouse line used in this study should be quantified using HA, rather than mCitrine, to reliably identify cells derived from the Ascl lineage. mCitrine expression in this mouse line is not specific to adult-born neurons (off-targets), and its expression does not accurately reflect hM4 expression.

We agree that mCitrine is not a marker that allows localization of hM4Di as it is well known that the mCitrine can be independently expressed in a Cre independent manner in this mouse. As suggested, we have removed the figure that showed the mCitrine and have performed immunohistochemical localization of the DREADD with an antibody against the HA tag. This is now shown in Figure 5.

(5) Key markers needed to assess the maturation state of abDGCs are missing from the quantification. Incorporating DCX and NeuN into the analysis would provide essential information about the developmental stage of these cells.

The goal of this study was to examine activity patterns of adult-born versus mature granule cells, rather than to assess maturation state. The adult-born neurons analyzed were 25–39 days old, an age at which point most cells have progressed beyond the DCX⁺ stage and are expected to express NeuN based on prior work. We therefore do not think that including DCX or NeuN quantification would provide additional information relevant to the aims or interpretation of this study.

Minor points:

(1) The labeling (Distance from the hilus) in Figure 2B is misleading. Is that the same location as the subgranular zone (SGZ)? If so, it's better to use the term SGZ to avoid confusion.

We have updated Figure 2B, the Methods, and the main text to more explicitly localize this which it the boundary between the subgranular zone (SGZ) and the hilus.

(2) Cell number information is missing from Figures 2B and 2C; please include this data.

We have now added the cell number information to the figure legends. In Figures 2B and 2C, each point corresponds to a single cell, with an equal number of mice per group. The total number of TRAP⁺ cells per mouse is shown in Figure 1F, which reports TRAP⁺ cell densities by group.

(3) Sample DG images should clearly delineate the borders between the dentate gyrus and the hilus. In several images, this boundary is difficult to discern.

We made the DG-hilus boundaries clearer in the sample images to improve visualization and interpretation.

(4) In Figure 6, it is not clear how tamoxifen was administered to selectively inhibit the more mature 6-7-week-old abDGC population, nor how this paradigm differs from the chow-based approach. Please clarify the tamoxifen administration protocol and the rationale for its specificity.

We apologize for the confusion here. The protocol used in Figure 6 is the same tamoxifen chow–based approach as in Figure 5, differing only in the duration of tamoxifen exposure. Mice in Figure 5 received tamoxifen chow for 7 weeks, whereas mice in Figure 6 received it for 4 weeks, restricting labeling to a younger and narrower cohort of adult-born DGCs. Thus, the population targeted in Figure 6 is younger than that in Figure 5 and does not correspond to mature 6–7-week-old neurons. By contrast, the experiment in Figure 4 targets a more mature population, consisting predominantly of ~5-week-old adult-born neurons as well as mature granule cells, which are Dock10-positive and express Cre endogenously, allowing selective manipulation of this later-stage population.

We have corrected the paragraph accordingly and clarified the age range of the labeled populations in the revised manuscript.

Reviewer #2 (Public review):

Summary

In this manuscript, the authors combine an automated touchscreen-based trial-unique nonmatching-to-location (TUNL) task with activity-dependent labeling (TRAP/c-Fos) and birth-dating of adult-born dentate granule cells (abDGCs) to examine how cognitive demand modulates dentate gyrus (DG) activity patterns. By varying spatial separation between sample and choice locations, the authors operationally increase task difficulty and show that higher demand is associated with increased mature granule cell (mGC) activity and an amplified suprapyramidal (SB) versus infrapyramidal (IB) blade bias. Using chemogenetic inhibition, they further demonstrate dissociable contributions of abDGCs and mGCs to task performance and DG activation patterns.

The combination of behavioral manipulation, spatially resolved activity tagging, and temporally defined abDGC perturbations is a strength of the study and provides a novel circuit-level perspective on how adult neurogenesis modulates DG function. In particular, the comparison across different abDGC maturation windows is well designed and narrows the functionally relevant population to neurons within the critical period (~4-7 weeks). The finding that overall mGC activity levels, in addition to spatially biased activation patterns, are required for successful performance under high cognitive demand is intriguing.

Major Comments

(1) Individual variability and the relationship between performance and DG activation.

The manuscript reports substantial inter-animal variability in the number of days required to reach the criterion, particularly during large-separation training. Given this variability, it would be informative to examine whether individual differences in performance correlate with TRAP+ or c-Fos+ density and/or spatial bias metrics. While the authors report no correlation between success and TRAP+ density in some analyses, a more systematic correlation across learning rate, final performance, and DG activation patterns (mGC vs abDGC, SB vs IB) could strengthen the interpretation that DG activity reflects task engagement rather than performance only.

As mentioned, we previously reported no correlation between task success and TRAP+ density. We have now performed additional analyses examining correlations with learning rate, final performance, and DG activation patterns (mGC vs abDGC, SB vs IB), and found no significant relationships. Therefore, as we did not find any positive correlations the original interpretation that DG activity primarily reflects task engagement rather than performance level seems the most parsimonious.

(2) Operational definition of "cognitive demand".

The distinction between low (large separation) and high (small separation) cognitive demand is central to the manuscript, yet the definition remains somewhat broad. Reduced spatial separation likely alters multiple behavioral variables beyond cognitive load, including reward expectation, attentional demands, confidence, engagement, and potentially motivation. The authors should more explicitly acknowledge these alternative interpretations and clarify whether "cognitive demand" is intended as a composite construct rather than a strictly defined cognitive operation.

We agree that reducing spatial separation between stimuli likely engages multiple behavioral and cognitive processes beyond a single, strictly defined operation. We have now clarified this point in the manuscript and explicitly state that our use of the term “cognitive demand” reflects a multidimensional behavioral challenge rather than a singular cognitive process (see Discussion).

(3) Potential effects of task engagement on neurogenesis.

Given the extensive behavioral training and known effects of experience on adult neurogenesis, it remains unclear whether the task itself alters the size or maturation state of the abDGC population. Although the focus is on activity and function rather than cell number, it would be useful to clarify whether neurogenesis rates were assessed or controlled for, or to explicitly state this as a limitation.

While the primary goal of this study was to examine activity and functional recruitment of adult-born granule cells, we also quantified the survival of birth-dated neurons at the end of behavioral training. Density measurements of BrdU⁺ and EdU⁺ cells revealed no differences across experimental groups, indicating that engagement in the pattern separation task, across low to high cognitive demand conditions, did not significantly alter survival of adult-born neurons. In addition, we examined the spatial distribution of BrdU⁺ and EdU⁺ neurons between the suprapyramidal and infrapyramidal blades of the dentate gyrus. The proportion of newborn neurons was consistent across all groups, with approximately 60% located in the suprapyramidal blade and 40% in the infrapyramidal blade. These findings indicate that behavioral training did not alter the baseline distribution of adult-born neurons. We have now clarified these points in the manuscript (See Results).

(4) Temporal resolution of activity tagging.

TRAP and c-Fos labeling provide a snapshot of neural activity integrated over a temporal window, making it difficult to determine which task epochs or trial types drive the observed activation patterns. This limitation is partially acknowledged, but the conclusions occasionally imply trial-specific or demand-specific encoding. The authors should more clearly distinguish between sustained task engagement and moment-to-moment trial processing, and temper interpretations accordingly. While beyond the scope of the current study, this also motivates future experiments using in vivo recording approaches.

We agree and have made changes to the manuscript to discuss these points (see Discussion and Limitations).

(5) Interpretation of altered spatial patterns following abDGC inhibition.

In the abDGC inhibition experiments, Cre+ DCZ animals show delayed learning relative to controls. As a result, when animals are sacrificed, they may be at an intermediate learning stage rather than at an equivalent behavioral endpoint. This raises the possibility that altered DG activation patterns reflect the learning stage rather than a direct circuit effect of abDGC inhibition. Additional clarification or analysis controlling for the learning stage would strengthen the causal interpretation.

We agree that differences in learning stage could in principle confound the interpretation of DG activation patterns. However, although Cre+ DCZ-treated mice exhibited delayed learning, they ultimately reached the same performance criterion as control animals. Thus, adult-born DGC inhibition did not prevent learning but increased the time required to reach criterion, indicating that these neurons are beneficial for learning efficiency rather than strictly necessary for task acquisition. Importantly, all animals were sacrificed only after reaching the predefined success criterion. Therefore, the immunohistochemical analyses were performed at the same behavioral endpoint for Cre+ DCZ and control groups, even though the number of training days differed. Consequently, the observed differences in DG activation reflect circuit recruitment at equivalent task mastery rather than differences in learning stage.

(6) Relationship between c-Fos density and behavioral performance.

The study reports that abDGC inhibition increases c-Fos density while impairing performance, whereas mGC inhibition decreases c-Fos density and also impairs performance. This raises an important conceptual question regarding the relationship between overall activity levels and task success. The authors suggest that both sufficient activity and appropriate spatial patterning are required, but the manuscript would benefit from a more explicit discussion of how different perturbations may shift the identity, composition, or coordination of the active neuronal ensemble rather than simply altering total activity levels.

We agree that our findings highlight that successful performance is not determined solely by the overall level of dentate gyrus activity, but rather by the composition and spatial organization of the active neuronal ensemble. In our study, inhibition of abDGCs increased overall mGC activity while disrupting the spatially organized, blade-biased activation pattern and impaired performance. In contrast, direct inhibition of mGCs reduced global excitability but preserved the relative spatial organization of active neurons in animals that continued to perform the task. These findings suggest that different perturbations alter task performance by shifting the identity and coordination of the active neuronal ensemble, rather than simply increasing or decreasing total activity levels. We have now expanded the Discussion to more explicitly address how dentate gyrus computations may depend on the structured recruitment of granule cell ensembles and how distinct manipulations differentially disrupt this organization.

Reviewer #3 (Public review):

Summary:

The authors used genetic models and immunohistochemistry to identify how training in a spatial discrimination working memory task influences activity in the dentate gyrus subregion of the hippocampus. Finding that more cognitively challenging variants of the task evoked more and distinct patterns of activity, they then investigated whether newborn neurons in particular were important for learning this task and regulating the spatial activity patterns.

Strengths:

The focus on precise anatomical locations of activity is relatively novel and potentially important, given that little is known about how DG subregions contribute to behavior. The authors also use a task that is known to depend on this memory-related part of the brain.

Weaknesses:

Statistical rigor is insufficient. Many statistical results are not stated, inappropriate tests are used, and sample sizes differ across experiments (which appear to potentially underlie null results). The chemogenetic approach to inhibit adult-born neurons also does not appear to be targeting these neurons, as judged by their location in the DG.

Please refer to the updated statistical analyses in response to the recommendations below.

Recommendations for the authors:

Reviewing Editor Comments

Please note that reviewers agreed that appropriate revisions are needed to increase the strength of evidence for the paper's claims. Concerns were raised about a lack of statistical rigor in the statistical analyses used. Results of statistical tests were not consistently provided (i.e., statistic applied, value of statistic, degrees of freedom, p-value), and seemingly inappropriate statistical tests were used in some instances. Also, some comparisons had lower statistical power than others. When clarifying the statistical approaches used in the manuscript, we also encourage you to consider reading this article that outlines common statistical mistakes (Makin TR, Orban de Xivry JJ. Ten common statistical mistakes to watch out for when writing or reviewing a manuscript. Elife. 2019 Oct 9;8:e48175. doi: 10.7554/eLife.48175.), such as the importance of not basing conclusions on a significant p-value for one pair-wise comparison vs a non-significant p-value for another pairwise comparison (i.e., groups that are being compared should be included in the same statistical analysis, and interaction effects should be reported when appropriate). We hope that you find this information to be helpful should you decide to submit a revised manuscript to eLife.

Reviewer #1 (Recommendations for the authors):

(1) Standardize TRAP+ quantification across Figure 1.

Please report TRAP+ cell numbers using consistent metrics (e.g., density or percentage) to enable comparison across cell types. In addition, extend the TRAP+ reactivation analysis in Figure 1H to include abDGCs so that reactivation dynamics can be compared directly between mGCs and abDGCs.

Reply in Public Review

(2) Clarify whether dorsal or ventral DG was analyzed in Figure 2.

The differing anatomical distributions of TRAP+ cells under low- and high-demand conditions raise important questions about DG axis specificity. Please indicate whether analyses were performed in dorsal DG, ventral DG, or both, and provide data or justification accordingly.

Reply in Public Review

(3) Acknowledge limitations of the tamoxifen-chow labeling strategy in AsclCreER; hM4 experiments.

Since tamoxifen chow administered over 4-7 weeks labels a heterogeneous abDGC population spanning a broad age range, this approach does not generate birth-dated cohorts. This limitation should be clearly addressed in the text and interpretations, particularly related to cell age-dependent effects, should be tempered.

Reply in Public Review

(4) Revise DREADD quantification using HA rather than mCitrine.

The hM4 mouse line requires HA immunostaining to accurately identify Ascl-lineage cells expressing the DREADD receptor. Because mCitrine is not specific to adult-born neurons and does not reliably reflect hM4 expression, quantification based on mCitrine should be revised.

Reply in Public Review

(5) Include markers to assess abDGC maturation state.

Adding quantification of DCX and NeuN would help define the developmental stage of abDGCs in key experiments and improve the interpretation of cell-age-dependent effects.

Reply in Public Review

(6) Clarify DG layer boundaries and terminology in Figure 2.

If the metric labeled "Distance from the hilus" corresponds to the subgranular zone (SGZ), using SGZ terminology would prevent confusion. Additionally, please provide clearer delineation of DG and hilus borders in sample images.

Reply in Public Review

(7) Provide missing cell number data for Figures 2B and 2C.

Reply in Public Review

(8) Clarify the tamoxifen administration protocol in Figure 6.

Please describe how the protocol selectively targets 6-7-week-old abDGCs and how it differs from the chow-based approach. This will help readers understand the intended specificity of the manipulation.

Reply in Public Review

Reviewer #2 (Recommendations for the authors):

(1) EdU birth-dating timeline

The manuscript would benefit from a clearer description of the EdU birth-dating timeline, ideally with a schematic similar to that provided for BrdU in Supplementary Figure 1.

We appreciate the suggestion. However, we did not include a separate schematic for EdU because its use and birth-dating logic are identical to BrdU (both are thymidine analogs administered systemically and incorporated during S-phase). Therefore, the timeline shown in Supplementary Figure 1 applies equally to both markers. We have clarified this point in the Methods section to avoid confusion.

(2) Clarity of TUNL task description.

The description of the TUNL task, particularly for readers unfamiliar with touchscreen-based paradigms, is difficult to follow without consulting prior literature. A simplified schematic or a clearer step-by-step explanation in the main text or supplementary material would improve accessibility.

We note that the main steps of the TUNL protocol are illustrated in Figure 1A, Supplementary Figure 2A and 2B. Nevertheless, we agree that the description in the text can be made clearer for readers less familiar with touchscreen-based tasks. Thus , we have now revised the Methods section to provide a clearer step-by-step description of the TUNL.

(3) Influence of outliers in Figure 1G.

In Figure 1G, the reported trend that ~1% of 25-39-day-old abDGCs are TRAP+ during LS trials appears to be driven by a small number of outliers. This should be acknowledged, and the wording of the conclusion moderated to reflect the variability in the data.

We agree with the reviewer that the apparent outliers reflect the inherent sparsity of TRAP labeling in this population. In absolute terms, this corresponds to between 0 and 2 TRAP⁺ 25–39-day-old abDGCs per mouse, such that the presence or absence of a small number of labeled cells can appear as outliers when expressed as a percentage. We have revised the text to acknowledge this (see Results).

(4) Presentation of learning curves.

Rather than focusing primarily on "days before criterion" (DBC), it would be helpful to show full learning curves across the entire training period. This would provide a clearer picture of acquisition dynamics and inter-animal variability.

We agree that learning curves can be informative in many behavioral paradigms. However, in our protocol, mice do not undergo the same number of training days because training stops individually once each animal reaches criterion. As a result, plotting full learning curves would produce trajectories of different lengths, making group comparisons difficult and visually cluttered. For this reason, we aligned animals based on days before criterion (DBC), which allows direct comparison of learning dynamics relative to task acquisition. We also consider the cumulative probability representation to be the most appropriate way to summarize learning progression across animals in this context which are also included in the figures.

(5) Clarification of Figure 3B labeling

In Figure 3B, the identity of the orange-labeled group above the LS condition is unclear. Clarification in the figure legend would improve interoperability.

Figure 3B includes two experimental groups. One group performed both the large- and small-separation conditions; this group is shown in orange and labeled LS. Within this group, the upper orange trace corresponds to performance in the large-separation condition, while the lower orange trace corresponds to performance in the small-separation condition. The second group is a control group that performed only the large-separation configuration, and therefore only a single green trace is shown. We agree that this distinction was not sufficiently clear and have revised the figure legend and text to clarify the identity of each trace.

Reviewer #3 (Recommendations for the authors):

(1) Please label figures and, even better, put the legends on the same page.

(2) Just to confirm, in establishing the task, mice performed above 70% for the small separation trials in one of the sessions on 2 consecutive days, for each criterion? Performance seems to be below 70%.

Yes. To meet the criterion, each mouse had to reach ≥70% correct performance in at least one of the two daily sessions on two consecutive days. We then averaged the performance across both sessions for each of those days. As a result, if one session was ≥70% but the other was lower, the daily average could fall below 70%. The values shown in the figure correspond to these daily averages, further averaged across mice.

(3) mGC needs to be explicitly defined. Am I assuming any non-birthdated GC is an mGC according to the authors? (which means it is unknown whether they are in fact mature, though likely most of them are).

In this study, “mature granule cells” (mGCs) refer operationally to granule cells that are not birth-dated with BrdU or EdU and therefore are not classified as adult-born neurons within the defined labeling window. We agree that this population is not directly age-defined, and that while the majority are expected to be mature based on their birth timing relative to the labeling period, we cannot exclude the possibility that a small fraction may include younger, unlabeled neurons. We have now explicitly defined this usage of mGCs in the Methods and clarified this point in the text to avoid ambiguity.

(4) Methods state that Kruskal-Wallis tests were used when more than 3 groups were compared, but I don't see these stats presented (e.g., for trap data in Figure 1, blade x task TRAP expt in Figure 3 (should be 2-way RM anova here and elsewhere), etc) or any corrections for multiple comparisons. I appreciate that the mean rates of TRAPed abGCs are higher in the S and LS groups than in the shaping group, but most mice do not have any BrdU+ cells that are also TRAPed, and there are no statistics here to support the claim. I don't think there is enough sampling to accurately quantify activation of abGCs. Also, no stats to support the claim that TRAPing increases at the "tip of the SB after the more demanding LS task".

We agree with this comment. We have now systematically tested all datasets for normality (by group) and applied parametric tests when the data met normality assumptions, and non-parametric tests otherwise. The statistical analyses have been revised accordingly. We added the appropriate tests (including two-way ANOVA where relevant, such as for blade × group comparisons) and now report full statistics in the figure legends and results sections. For the TRAP analyses in adult-born DGCs, we explicitly acknowledge the very low number of BrdU⁺/TRAP⁺ cells, which limits statistical power and, in some cases, precludes robust statistical testing. These limitations are now clearly stated in the Results and Discussion, and the corresponding interpretations have been tempered. For all Kruskal–Wallis tests, post hoc pairwise comparisons were performed using Dunn’s test, with Bonferroni correction for multiple comparisons, as now specified in the Methods section. We also expanded the Methods to describe the statistical workflow in detail. In addition, we have added the previously missing statistical analysis for Figure 2C. Comparisons were performed between the 0–50% and 50–100% portions of the blade, where 0% corresponds to the apex and 100% corresponds to the distal tip of the blade.

(5) Figure 3I: I can't figure out which effect is statistically significant here (what does the asterisk signify?). Why no individual data points in this graph?

We agree that the absence of individual data points reduced interpretability, and we have now updated the figure to include individual data points to better illustrate data distribution and variability.

(6) The gradient of activity (shap < S < LS) could be due to how long they've been trained on a given stage (e.g. less activity during shaping because they have habituated, and neurons encoding that task phase have already been selected)

We agree that task duration and habituation could, in principle, influence activity levels. Under this interpretation, higher activity would primarily reflect task novelty rather than cognitive demand. However, our data do not support this explanation. Specifically, we found no correlation between the number of training days required to reach criterion and c-Fos–positive or TRAP-positive cell density within a given stage. Thus, animals that reached criterion rapidly did not show higher activity levels than animals that required more days of training and were presumably more habituated to the task demands. This suggests that the observed activity gradient (shaping < S < LS) is not driven by exposure duration or habituation, but rather reflects differences in cognitive demand across task stages.

(7) The TRAP+ EDU+ cell in Figure 3 looks odd because the BrdU signal is (a lot) larger than the TRAP signal, but BrdU is in the nucleus and should be smaller.

We agree that the example in Figure 3 is not optimal. In dividing cells, BrdU/EdU signals can sometimes appear broader or closely apposed, which may affect their apparent size.

(8) For the Ascl-HM4Di experiment, HM4Di appears to be expressed in all of the areas of the granule cell layer where abGCs are NOT located (i.e. no expression in the deep cell layer, near the sgz). This is problematic because it suggests perhaps abGCs are not inhibited as expected.

As noted in our response to Reviewer #1, we did not use the mCitrine to localize the DREADD receptor as it has been demonstrated that mCitrine expression is expressed in a Cre-independent manner and not correlated with hM4Di expression. In the revised manuscript we include a representative image were we performed immunostaining using an HA antibody to directly visualize hM4Di and confirm its expression in adult-born granule cells (Figure 5).

(9) Line 267: "6-7 week old neurons by themselves do not influence either the performance of mice in the task". I don't think this is fair because this experiment wasn't designed with as much power to detect an effect. The group trends are in the same direction, but there are many fewer mice in this experiment (n=6/group) than in the =<7w experiment (n=11/group), where the effect just reached statistical significance.

We are sorry for this confusion which came from an incorrect version. The experiment shown in Figure 6 does not target 6–7-week-old neurons specifically. It uses the same tamoxifen chow–based protocol as Figure 5, but with a shorter exposure (4 weeks vs. 7 weeks), thereby labeling a younger and more restricted cohort of adult-born DGCs. By contrast, Figure 4 targets a more mature population, consisting predominantly of ~5-week-old adult-born neurons as well as mature granule cells (Dock10+).

We have corrected the paragraph accordingly and clarified the age range of the labeled populations in the revised manuscript.

Author Response:

The following is the authors’ response to the original reviews.

We thank the reviewers for their constructive comments. A central concern raised is the comparison of performance with existing motion-correction methods. In response, we performed motion correction using several widely used approaches and compared results using the number of particles detected by 2DTM and their associated SNR. To minimize potential bias, we selected parameters to give each method a comparable level of model flexibility so that the results are as directly comparable as possible. Overall, Unbend performs the best. We note that extensive, method-specific parameter optimization could further affect absolute performance, and a comprehensive benchmarking study is therefore beyond the scope of this work

Public Reviews:

Reviewer #1 (Public review):

Kong et al.'s work describes a new approach that does exactly what the title states: "Correction of local beam-induced sample motion in cryo-EM images using a 3D spline model." I find the method appropriate, logical, and well-explained. Additionally, the work suggests using 2DTM-related measurements to quantify the improvement of the new method compared to the old one in cisTEM, Unblur. I find this part engaging; it is straightforward, accurate, and, of course, the group has a strong command of 2DTM, presenting a thorough study.

However, everything in the paper (except some correct general references) refers to comparisons with the full-frame approach, Unblur. Still, we have known for more than a decade that local correction approaches perform better than global ones, so I do not find anything truly novel in their proposal of using local methods (the method itself- Unbend- is new, but many others have been described previously). In fact, the use of 2DTM is perhaps a more interesting novelty of the work, and here, a more systematic study comparing different methods with these proposed well-defined metrics would be very valuable. As currently presented, there is no doubt that it is better than an older, well-established approach, and the way to measure "better" is very interesting, but there is no indication of how the situation stands regarding newer methods.

Regarding practical aspects, it seems that the current implementation of the method is significantly slower than other patch-based approaches. If its results are shown to exceed those of existing local methods, then exploring the use of Unbend, possibly optimizing its code first, could be a valuable task. However, without more recent comparisons, the impact of Unbend remains unclear.

We thank the reviewer for this important point. We agree that comparing against modern local motion-correction approaches is a valuable task. To address this, we added a new benchmarking section (pp. 17–18, lines 444–492, Fig. 8, Fig. 8—figure supplement 1) that compares Unbend against widely used patch-based local correction methods, including MotionCor2, MotionCor3, Warp, and CryoSPARC. Using the same 2DTM-based metrics described in the manuscript (detections per micrograph and SNR distributions for commonly detected particles), we find that Unbend provides the most stable performance across the tested datasets and, in most cases, yields higher detection counts and higher SNR than the alternative methods.

Regarding runtime, the current implementation is CPU-based and is therefore slower than some optimized GPU-accelerated packages. We now clarify this limitation in the manuscript (line 498–499). Our primary goal in this study is to improve motion-correction accuracy and quantify its impact using 2DTM-based measures. Importantly, higher-quality motion-corrected micrographs can reduce downstream processing cost (e.g., by increasing particle detection efficiency and reducing ambiguous candidates), so modest additional compute times at the motion-correction stage can be offset later in the workflow. We also note that GPU acceleration and additional code-level optimizations are planned for future releases (line 501-503); however, they are not required to evaluate the methodological contribution and the benchmarking results presented here.

Reviewer #2 (Public review):

Summary:

The authors present a new method, Unbend, for measuring motion in cryo-EM images, with a particular emphasis on more challenging in situ samples such as lamella and whole cells (that can be more prone to overall motion and/or variability in motion across a field of view). Building on their previous approach of full-frame alignment (Unblur), they now perform full-frame alignment followed by patch alignment, and then use these outputs to generate a 3D cubic spline model of the motion. This model allows them to estimate a continuous, per-pixel shift field for each movie frame that aims to better describe complex motions and so ultimately generate improved motion-corrected micrographs. Performance of Unbend is evaluated using the 2D template matching (2DTM) method developed previously by the lab, and results are compared to using full-frame correction alone. Several different in situ samples are used for evaluation, covering a broad range that will be of interest to the rapidly growing in situ cryo-EM community.

Strengths:

The method appears to be an elegant way of describing complex motions in cryo-EM samples, and the authors present convincing data that Unbend generally improves SNR of aligned micrographs as well as increases detection of particles matching the 60S ribosome template when compared to using full-frame correction alone. The authors also give interesting insights into how different areas of a lamella behave with respect to motion by using Unbend on a montage dataset collected previously by the group. There is growing interest in imaging larger areas of in situ samples at high resolution, and these insights contribute valuable knowledge. Additionally, the availability of data collected in this study through the EMPIAR repository will be much appreciated by the field.

Thank you for this positive assessment.

Weaknesses:

While the improvements with Unbend vs. Unblur appear clear, it is less obvious whether Unbend provides substantial gains over patch motion correction alone (the current norm in the field). It might be helpful for readers if this comparison were investigated for the in situ datasets. Additionally, the authors are open that in cases where full motion correction already does a good job, the extra degrees of freedom in Unbend can perhaps overfit the motions, making the corrections ultimately worse. I wonder if an adaptive approach could be explored, for example, using the readout from full-frame or patch correction to decide whether a movie should proceed to the full Unbend pipeline, or whether correction should stop at the patch estimation stage.

We thank the reviewer for suggesting an adaptive criterion to decide whether to proceed patch alignment or not. We agree that such an approach could be valuable for efficiency and for avoiding unnecessary model flexibility. However, our results indicate that a simple criterion based on the magnitude of estimated local patch motion is unlikely to be sufficient. For example, in the BS-C-1 cell lysate dataset, (see line 412-417 on page 16), we observe minimal local motion (Figure 4b) with mean patch shifts of only 0.7Å and full-frame alignment already yields comparable detection counts, yet local correction still produces a measurable SNR gain (13.84 ± 0.04 to 14.25 ± 0.04, 3%) and improves SNR for ~70% of the commonly detected targets (Figure 6c). This suggests that residual local distortion can remain even when overall local motion appears small. Establishing a robust, dataset-agnostic stopping rule would therefore require a dedicated, systematic benchmarking study across many samples and acquisition conditions.

Reviewer #3 (Public review):

Summary

Kong and coauthors describe and implement a method to correct local deformations due to beam-induced motion in cryo-EM movie frames. This is done by fitting a 3D spline model to a stack of micrograph frames using cross-correlation-based local patch alignment to describe the deformations across the micrograph in each frame, and then computing the value of the deformed micrograph at each pixel by interpolating the undeformed micrograph at the displacement positions given by the spline model. A graphical interface in cisTEM allows the user to visualise the deformations in the sample, and the method has been proven to be successful by showing improvements in 2D template matching (2DTM) results on the corrected micrographs using five in situ samples.

Impact

This method has great potential to further streamline the cryo-EM single particle analysis pipeline by shortening the required processing time as a result of obtaining higher quality particles early in the pipeline, and is applicable to both old and new datasets, therefore being relevant to all cryo-EM users.

Strengths

(1) One key idea of the paper is that local beam induced motion affects frames continuously in space (in the image plane) as well as in time (along the frame stack), so one can obtain improvements in the image quality by correcting such deformations in a continuous way (deformations vary continuously from pixel to pixel and from frame to frame) rather than based on local discrete patches only. 3D splines are used to model the deformations: they are initialised using local patch alignments and further refined using cross-correlation between individual patch frames and the average of the other frames in the same patch stack.

(2) Another strength of the paper is using 2DTM to show that correcting such deformations continuously using the proposed method does indeed lead to improvements. This is shown using five in situ datasets, where local motion is quantified using statistics based on the estimated motions of ribosomes.

Thank you for this positive assessment.

Weaknesses

(1) While very interesting, it is not clear how the proposed method using 3D splines for estimating local deformations compares with other existing methods that also aim to correct local beam-induced motion by approximating the deformations throughout the frames using other types of approximation, such as polynomials, as done, for example MotionCor2.

We thank the reviewer for this suggestion. We agree that positioning Unbend relative to existing local motion-correction methods is important. In the revised manuscript, we added a dedicated benchmarking section comparing Unbend with widely used local correction approaches, including MotionCor2, MotionCor3, Warp, and CryoSPARC, using the same 2DTM-based metrics (Fig. 8, Fig. 8—figure supplement 1). This section is included on pp. 17–18, lines 444–492. To make the comparison as fair as possible, we matched nominal model flexibility across methods and otherwise used default parameters to reduce method-specific tuning. This expanded comparison provides a direct baseline against current patch-/spline-based approaches and shows that Unbend performs consistently across the in situ datasets evaluated here, with improvements in detection counts and/or SNR in multiple cases.

(2) The use of 2DTM is appropriate, and the results of the analysis are enlightening, but one shortcoming is that some relevant technical details are missing. For example, the 2DTM SNR is not defined in the article, and it is not clear how the authors ensured that no false positives were included in the particles counted before and after deformation correction. The Jupyter notebooks where this analysis was performed have not been made publicly available.

We agree that these technical details improve clarity and reproducibility. We have therefore made three changes.

(1) Definition of 2DTM SNR. We added an explicit definition of the 2DTM SNR in Section “2DTM provides a one-step verification for motion correction”, pp. 11, lines 277–287). Briefly, at each image location we compute cross-correlation values over the searched orientation space and define the 2DTM SNR as the maximum per location z-score across orientations.

(2) False-positive control / detection threshold. We clarified how detection thresholds were set to control false positives (pp. 11, lines 285–287). Specifically, we used the standard 2DTM statistical framework in which the threshold  is chosen using the one-false-positive (1-FP) criterion (or equivalently, a specified expected false-positive rate). We applied the same thresholding procedure consistently across all motion-corrected micrographs. This ensures that particle counts before/after correction reflect changes in signal recovery.

(3) Reproducibility of the analysis. We have made the script used for the benchmarking and figure generation publicly available (pp. 24 line 622-623), and we provide a link in the Data Availability statement (pp. 25 line 650). The repository includes sample .star files and a python package that computes detections per micrograph, commonly detected particles, and SNR comparisons.

(3) It is also not clear how the proposed deformation correction method is affected by CTF defocus in the different samples (are the defocus values used in the different datasets similar or significantly different?) or if there is any effect at all.

We thank the reviewer for raising this point. In the revised manuscript, we now report the defocus ranges used for each dataset (Table 1) and clarify that all motion-correction comparisons were performed within each dataset using the same CTF estimation and 2DTM settings (pp. 23 line 615-618). Across the five datasets, four were collected at similar defocus ranges (1.0 µm to 1.5µm), whereas one dataset includes near-focus (0.4 µm) micrographs (Table 1). Because Unbend operates on frame alignment/warping rather than CTF modeling, we do not expect a defocus specific effect beyond indirect influences through image SNR and reliability of cross-correlation-based alignment.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

The obvious recommendation would be to use their 2DTM approach for a comparison of their new method with other currently used ones

We agree and added a new comparison section (pp. 17–18, lines 444–492). Addressed above in Response to Reviewer #1 Public Review.

Reviewer #2 (Recommendations for the authors):

(1) Line 29, typo. 3 ~ 8% > 3 - 8%.

Corrected.

(2) Lines 220 and 226. Should this be e-/Angstrom squared for the exposure?

Corrected to e^-/Ų (Now pp. 9 lines 230, 236).

(3) Figure 2 c-d. These are good for instinctively seeing the movement, but I found the legend confusing, as a 10 x 10 pixel array is mentioned, yet the schematics show a higher sampling (30 x 30 pixels? in c-e).

Thank you for pointing this out. The “10×10” annotation refers to the physical scale, whereas the grid represents pixel sampling. We removed the “10×10” label and now show only the pixel grid to avoid confusion. The caption has been updated to state that the grid corresponds to a 30×30 pixel sampling. (Fig. 2c, d; pp. 31, line 766)

(4) Figure 4. It would be good if the n of movies analyzed was given in the figure legend.

Thank you for noticing this. We report the number of movies per dataset in the corresponding summary table (Table 1).

(5) Figure 5. X/Y axes labels missing (assume pixels). Also, suggest changing the strain scale to % to match the main text description of this figure.

We added X/Y axis labels, changed the strain scale to % (Figure 5), and specified that the strains are per pixel on pp. 14 line 367. Correspondingly, the X/Y labels and strain scale in strain plots in Figure 4—figure supplementary 1 to 5 are also changed.

(6) Unify labelling of Figure 4 and 6 (i.e., Bacteria vs. M. pneumoniae, etc.).

Corrected. Sample labels are now consistent across figures. (Figures 4 and 6)

Reviewer #3 (Recommendations for the authors):

Some recommendations related to the points mentioned in the 'Weaknesses' section in the public review:

(1) If feasible, it would be useful to see a comparison with other existing methods that estimate local deformations (e.g., MotionCor2), at least on some of the datasets. For example, does the proposed method lead to better 2DTM SNR in the detected particles compared to other methods, or higher detection numbers? Alternatively, if such a comparison would require too much additional work and the authors have good reasons to believe that the results are evident, it would be helpful to include a discussion about why the proposed method is expected to perform better, both in terms of the general approach and specific implementation details.

We agree that this comparison is important. (pp. 17–18, lines 444–492). Addressed above in Response to Reviewer #3 Public Review (1).

(2) It would be useful to define the 2DTM SNR in the main text of the paper, as well as to address the point about false positives in the picked particles.

We added an explicit definition of 2DTM SNR and clarified the detection thresholding/false-positive control used in our analysis (pp. 11, lines 277–287). Addressed above in Response to Reviewer #3 Public Review (2.1 and 2.2).

(3) Regarding the results shown in Figures 4 and 6: do the authors have any insight about how the CTF defocus affects the deformation estimation and correction across the different sample types?

We now report the defocus ranges used for each dataset (Table 1). We have addressed this problem in Response to Reviewer #3 Public Review (3).

(4) Will the Jupyter notebooks used for the 2DTM analysis be made publicly available?

Yes. We have deposited a python script used for the 2DTM benchmarking and figure generation in a public repository and added the link in Data Availability statement. (pp. 23 line 622, pp. 25 line 650). Addressed above in Response to Reviewer #3 Public Review (2.3).

(5) I would also appreciate a few words about the implementation details of the 3D spline model (e.g., what libraries have been used, if any, or if the authors have implemented their own code for this).

The 3D spline model and warping code were implemented by us (no external spline library was used) and the relevant implementation details are described in the “Sample distortion modeling and correction” section (pp. 7–10, lines 174–246). For optimization, we used the L-BFGS implementation provided by the dlib library, which is now explicitly cited (pp. 10, line 264).

Some comments regarding the presentation of the work:

(1) I found the mathematical background on splines on pages 7-9 a little distracting from the main ideas of the paper, and I believe it could be moved to the methods section. A short description of this in the main text of the paper would suffice, and it would be useful to state clearly when this is background material and when it is the authors' contribution.

We appreciate the suggestion. Because Unbend includes an in-house spline implementation (no external spline library) and it is the central part of this work, we retained the spline description to support reproducibility. (pp. 7–10, lines 174–246).

(2) More generally, I found the whole method very interesting, but understanding exactly what all the steps involved were was a bit cumbersome, as they are spread across different sections of the main text. I think it would be useful to have a dedicated section giving the exact steps taken in the algorithm, possibly pointing to the relevant section in the text for more details about each step. This could be, for example, in the form of an 'Algorithm' box or a flowchart.

We added an Algorithm box as Figure 2 supplement summarizing the end-to-end workflow and pointing to the relevant sections for details (Figure 2—figure supplement 1 Algorithm, pp. 4, line 96–103, pp. 32 line 799). This is intended to make the sequence of steps easier to follow.

(3) In Figure 3, panels (b) and (c), the difference between the two micrographs, before and after correction, is not very noticeable, particularly the Thon rings in the spectra. I don't know if this is due to the image quality in the paper or if a better example could be shown. For example, the differences are clear in some of the supplementary figures.

Thank you for the suggestion. We revised the figure by adding annotations to show the recovered Thon rings. This figure shows a vertex motion and is intended not only to show improvement but also to illustrate complex, spatially varying deformation patterns that motivate the 3D spline model (pp. 12, lines 304–308). The supplementary figures display those with highest motions in each sample type, thus the Thon rings for the motion corrected micrograph in higher frequency space look more obvious. We also refer readers to the supplementary examples where the differences are more pronounced (pp. 12, lines 310–312).

Author Response:

The following is the authors’ response to the previous reviews

Public Reviews:

Reviewer #1 (Public review):

Summary:

Here Bansal et al., present a study on the fundamental blood and nectar feeding behaviors of the critical disease vector, Anopheles stephensi. The study encompasses not just the fundamental changes in blood feeding behaviors of the crucially understudied vector, but then use a transcriptomic approach to identify candidate neuromodulation path ways which influence blood feeding behavior in this mosquito species. The authors then provide evidence through RNAi knockdown of candidate pathways that the neuromodulators sNPF and Rya modulate feeding either via their physiological activity in the brain alone or through joint physiological activity along the brain-gut axis (but critically not the gut alone). Overall, I found this study to be built on tractable, well-designed behavioral experiments.

Their study begins with a well-structured experiment to assess how the feeding behaviors of A. stephensi changes over the course of its life history and in response to its age, mating and oviposition status. The authors are careful and validate their experimental paradigm in the more well-studied Ae. aegypti, and are able to recapitulate the results of prior studies which show that mating is pre-requisite for blood feeding behaviors in Ae. aegypt. Here they find A. stephensi like another Anopheline mosquitoes has a more nuanced regulation of its blood and nectar feeding behaviors.

The authors then go on to show in a Y- maze olfactometer that to some degree, changes in blood feeding status depend on behavioral modulation to host-cues, and this is not likely to be a simple change to the biting behaviors alone. I was especially struck by the swap in valence of the host-cues for the blood-fed and mated individuals which had not yet oviposited. This indicates that there is a change in behavior that is not simply desensitization to host-cues while navigating in flight, but something much more exciting happening.

The authors then use a transcriptomic approach to identify candidate genes in the blood feeding stages of the mosquito's life cycle to identify a list of 9 candidates which have a role in regulating the host-seeking status of A. stephensi. Then through investigations of gene knockdown of candidates they identify the dual action of RYa and sNPF and candidate neuromodulators of host-seeking in this species. Overrall, I found the experiments to be welldesigned. I found the molecular approach to be sound. While I do not think the molecular approach is necessarily an all-encompassing mechanism identification (owing mostly to the fact that genetic resources are not yet available in A. stephensi as they are in other dipteran models), I think it sets up a rich lines of research questions for the neurobiology of mosquito behavioral plasticity and comparative evolution of neuromodulator action.

Strengths:

I am especially impressed by the authors' attention to small details in the course of this article. As I read and evaluated this article I continued to think how many crucial details I may have missed if I were the scientist conducting these experiments. That attention to detail paid off in spades and allowed the authors to carefully tease apart molecular candidates of blood-seeking stages. The authors top down approach to identifying RYamide and sNPF starting from first principles behavioral experiments is especially comprehensive. The results from both the behavioral and molecular target studies will have broad implications for the vectorial capacity of this species and comparative evolution of neural circuit modulation.

I believe the authors have adequately addressed all of my concerns; however, I think an accompanying figure to match the explained methods of the tissue-specific knockdown would help readers. The methods are now explicitly written for the timing and concentrations required to achieve tissue-specific knockdown, but seeing the data as a supplement would be especially reassuring given the critical nature of tissue-specific knockdown to the final interpretations of this paper.

We thank the reviewer for the suggestion and have now incorporated a schematic in the supplementary figure S9B, explaining our methodology for achieving tissue-specific knockdowns.

Reviewer #2 (Public review):

Summary:

In this manuscript, Bansal et al examine and characterize feeding behaviour in Anopheles stephensi mosquitoes. While sharing some similarities to the well-studied Aedes aegypti mosquito, the authors demonstrate that mated-females, but not unmated (virgin) females, exhibit suppression in their blood-feeding behaviour. Using brain transcriptomic analysis comparing sugar fed, blood fed and starved mosquitoes, several candidate genes potentially responsible for influencing blood-feeding behaviour were identified, including two neuropeptides (short NPF and RYamide) that are known to modulate feeding behaviour in other mosquito species. Using molecular tools including in situ hybridization, the authors map the distribution of cells producing these neuropeptides in the nervous system and in the gut. Further, by implementing systemic RNA interference (RNAi), the study suggests that both neuropeptides appear to promote blood-feeding (but do not impact sugar feeding) although the impact was observed only after both neuropeptide genes underwent knockdown.

While the authors have addressed most of the concerns of the original manuscript, a few issues remain. Particularly, the following two points:

(5) Figure 4

The authors state that there is more efficient knockdown in the head of unfed females; however, this is not accurate since they only get knockdown in unfed animals, and no evidence of any knockdown in fed animals (panel D). This point should be revised in the results test as well.

Perhaps we do not understand the reviewer's point or there has been a misunderstanding. In Figure 4D, we show that while there is more robust gene knockdown in unfed females, bloodfed females also showed modest but measurable knockdowns ranging from 5-40% for RYamide and 2-21% for sNPF.

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In both the dsRNA treatments where animals were fed, neither was significantly different from control. Therefore, there is no change, and indeed this is confirmed by the author's labelling of the figure stats in panel 4D.

We agree with the reviewer and thank them for pointing it out. We have now revised the figure legend and the text to reflect these results (see lines 351-354).

In addition, do the uninjected and dsGFP-injected relative mRNA expression data reflect combined RYa and sNPF levels? Why is there no variation in these data,...

In these qPCRs, we calculated relative mRNA expression using the delta-delta Ct method (see line 975). For each neuropeptide its respective control was used. For simplicity, we combined the RYa and sNPF control data into a single representation. The value of this control is invariant because this method sets the control baseline to a value of 1.

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The authors are claiming that there is no variation between individual qPCR experiments (particularly in their controls)? Normally, one uses a known standard value (or calibrator) across multiple experiments/plates so that variation across biological replicates can be assessed. This has an impact on statistical analyses since there is no variation in the control data. Indeed, this impacts all figures/datasets in the manuscript where qPCR data is presented. All the controls have zero variation!

We are truly thankful to this reviewer for insisting on this point. It has made us revisit what we thought we understood and now realise were doing wrong (though many in literature do it this way!). We were – incorrectly – setting each control to 1 and calculating relative fold changes for each replicate independently. While this is often seen in literature, we now realise that it is incorrect. We have revisited all our analyses and normalized all samples to the mean ΔCt of the control group, which captures biological variation in both control and experimental groups. All data are now re-plotted to show individual data points for both control and experimental groups, and the error bars on controls represent the biological variation across replicates (Figure 4D, 4F, 4G, S8, S9). Statistical analyses were also revised accordingly, and, importantly, they do not change any conclusions. Please note that the abdominal expression of sNPF and RYa are so low that the controls show very variable baseline expression values.

Reviewer #3 (Public review):

Summary:

This manuscript investigates the regulation of host-seeking behavior in Anopheles stephensi females across different life stages and mating states. Through transcriptomic profiling, the authors identify differential gene expression between "blood-hungry" and "blood-sated" states. Two neuropeptides, sNPF and RYamide, are highlighted as potential mediators of host-seeking behavior. RNAi knockdown of these peptides alters host-seeking activity, and their expression is anatomically mapped in the mosquito brain (sNPF and RYamide) and midgut (sNPF only).

Strengths:

(1) The study addresses an important question in mosquito biology, with relevance to vector control and disease transmission.

Transcriptomic profiling is used to uncover gene expression changes linked to behavioral states.

(2) The identification of sNPF and RYamide as candidate regulators provides a clear focus for downstream mechanistic work.

(3) RNAi experiments demonstrate that these neuropeptides are necessary for normal hostseeking behavior.

(4) Anatomical localization of neuropeptide expression adds depth to the functional findings.

Weaknesses:

(1) The title implies that the neuropeptides promote host-seeking, but sufficiency is not demonstrated and some conclusions appear premature based on the current data. The support for this conclusion would be strengthened with functional validation using peptide injection or genetic manipulation.

(2) The identification of candidate receptors is promising, but the manuscript would be significantly strengthened by testing whether receptor knockdowns phenocopy peptide knockdowns. Without this, it is difficult to conclude that the identified receptors mediate the behavioral effects.

(3) Some important caveats, such as variation in knockdown efficiency and the possibility of offtarget effects, are not adequately discussed.

These comments were addressed in the previous round.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

Awesome paper everyone. A delight to read and review.

Thank you very much! We appreciated your comments too!

Reviewer #1 (Public review):

Summary:

The authors aimed to investigate how short-term visual deprivation influences tactile processing in the primary somatosensory cortex (S1) of sighted rats. They justify the study based on previous studies that have shown that long-term blindness can enhance tactile perception, and aim to investigate the change in neural representations underlying rapid, short-term cross-modal effects. The authors recorded local field potentials from S1 as rats encountered different tactile textures (smooth and rough sandpaper) under light and dark conditions. They used deep learning techniques to decode the neural signals and assess how tactile representations changed across the four different conditions. Their goal was to uncover whether the absence of visual cues leads to a rapid reorganization of tactile encoding in the brain.

Strengths:

The study effectively integrates high-density local field potential (LFP) recordings with convolutional neural network (CNN) analysis. This combination allows for decoding high-dimensional population-level signals, revealing changes in neural representations that traditional analyses (e.g., amplitude measures) failed to detect. The custom treadmill paradigm permits independent manipulation of visual and tactile inputs under stable locomotion conditions. Gait analysis confirms that motor behavior was consistent across conditions, strengthening the conclusion that neural changes are due to sensory input rather than movement artifacts.

Weaknesses:

(1) While the study interprets the emergence of more distinct texture representations in the dark as evidence of rapid cross-modal plasticity, the claim rests on correlational data from a short-term manipulation and decoding analysis. The authors show that CNN-derived feature embeddings cluster more clearly by texture in the dark, but this does not directly demonstrate plasticity in the classical sense (e.g., synaptic or circuit-level reorganization). The authors have noted this as a limitation and have clarified that the observed changes reflect functional reorganization rather than structural plasticity.

(2) Although gait was controlled, changes in arousal or exploratory behavior in light versus dark conditions might play a role in the observed neural differences. The authors have controlled for various factors in relation to locomotion, but future studies would benefit from more direct behavioural readouts of arousal states (e.g., via pupillometry or cortical state indicators).

(3) It should be noted that the time course of the observed changes (within 10 minutes) is quite rapid, and while intriguing, the study does not include direct evidence that the underlying circuits were reorganized-only that population-level signals become more discriminable. The authors have adequately discussed this as an avenue for more mechanistic future research.

(4) The authors have adequately discussed that, while these findings are consistent with somatotopy and context-dependent dynamics, they do not provide strong independent evidence for novel spatial or temporal organization.

(5) The authors have also discussed that, while the neural data suggest enhanced tactile representations, the study does not assess whether rats' actual tactile perception improved. Future studies including an assessment of a behavioral readout (e.g., discrimination accuracy), would be insightful.

(6) The authors' discussion about the implications for sensory rehabilitation, including Braille training and haptic feedback enhancement was a bit premature, but they have amended this, and it remains an interesting translational potential to be explored in future studies.

(7) While the CNN showed good performance, more transparent models (e.g., linear classifiers or dimensionality reduction) appear to not exceed chance level. The implications of this are that there is an underlying complex structure in the LFPs that has yet to be fully uncovered, on the mechanistic level. This would be important to push the findings forward in future studies.

Therefore, while the authors raise interesting hypotheses around rapid plasticity, somatotopic dynamics, and rehabilitation, the evidence for each is indirect. Stronger claims will require future causal experiments, behavioral readouts, and mechanistic specificity beyond what the current data provides. However, the work represents an interesting starting point to a more mechanistic understanding in the future.

Author Response:

The following is the authors’ response to the original reviews.

Public Reviews:

Reviewer #1 (Public review):

(1) While the study interprets the emergence of more distinct texture representations in the dark as evidence of rapid cross-modal plasticity, the claim rests on correlational data from a short-term manipulation and decoding analysis. The authors show that CNN-derived feature embeddings cluster more clearly by texture in the dark, but this does not directly demonstrate plasticity in the classical sense (e.g., synaptic or circuit-level reorganization).

Thank you for this insightful comment. We acknowledge that our claim of “rapid cross-modal plasticity” is based on correlational evidence and does not directly address synaptic or circuit-level reorganization, which would require more invasive methods. Our study instead focuses on changes in the representational structure of tactile stimuli when visual input is temporarily removed, highlighting the adaptability of sensory coding to environmental context. We agree that this distinction is important and have revised the manuscript to clarify that the observed changes reflect functional reorganization rather than structural plasticity, as indicated by the enhanced separability of texture representations in S1 during darkness.

(2) Although gait was controlled, changes in arousal or exploratory behavior in light versus dark conditions might contribute to the observed neural differences. These factors are acknowledged but not directly measured (e.g., via pupillometry or cortical state indicators).

Thank you for your insightful comment. We agree that arousal and exploratory behavior could influence neural differences and have considered these factors in our study. While gait was controlled, we did not directly measure arousal (e.g., via pupillometry or cortical indicators).

To partially address this, we reviewed locomotor-speed traces (Supplementary Figure 1), which showed no significant differences between light and dark conditions, suggesting movement speed did not drive the neural differences. We also reversed the order of light and dark conditions, and although the separability of textures was not significantly different, it further supports that motivation did not confound our results.

However, we acknowledge that arousal may still affect cortical dynamics, especially in the dark condition, where the lack of visual input might alter exploratory behavior. Due to technical limitations, we could not directly measure arousal states, and this is now discussed in the revised manuscript. While we cannot rule out the influence of arousal, the enhanced separability of texture representations suggests that sensory reorganization due to visual deprivation likely played a substantial role.

(3) Moreover, the time course of the observed changes (within 10 minutes) is quite rapid, and while intriguing, the study does not include direct evidence that the underlying circuits were reorganized - only that population-level signals become more discriminable. As such, the term "plasticity" may overstate the conclusions and should be interpreted with caution unless validated by additional causal or longitudinal data.

Thank you for your important comment. We agree that the term "plasticity" may overstate our conclusions, as our study focuses on population-level signal changes rather than direct evidence of circuit-level reorganization.

To address this, we have revised the manuscript to clarify that while the observed changes in neural separability suggest functional reorganization of sensory representations, they do not confirm structural plasticity. We have updated the wording throughout the manuscript to emphasize that these findings reflect functional reorganization in response to short-term visual input loss, rather than structural or long-term plasticity.

We also updated the discussion to highlight the need for future research with more invasive approaches to validate the causal mechanisms behind these rapid changes in neural dynamics.

(4) The study highlights the forelimb region of S1 and a post-contact temporal window as particularly important for decoding texture, based on occlusion and integrated gradient analyses. However, this finding may be somewhat circular: The LFPs were aligned to forelimb contact, and the floor textures were sensed primarily via the forelimbs, making it unsurprising that forelimb electrodes were most informative. The observed temporal window corresponds directly to the event-aligned epoch, and while it may shift slightly in duration in the dark, this could reflect general differences in sensory gain or arousal, rather than changes in stimulus-specific encoding. Thus, while these findings are consistent with somatotopy and context-dependent dynamics, they do not provide strong independent evidence for novel spatial or temporal organization.

Thank you for your insightful comment. We understand your concern that the finding of forelimb electrodes being most informative might seem circular, given that the LFPs were aligned to forelimb contact, and the floor textures were primarily sensed by the forelimbs. This design choice was intentional, as the task focused on texture perception through the forelimb, and the forelimb subregion of S1 is naturally expected to play a dominant role in this process. While this somatotopic specificity may make the results predictable, our aim was to emphasize the changes in temporal dynamics of neural processing under visual deprivation.

We observed a shift in the temporal window's duration in the dark condition, which we interpret as a change in how texture information is processed without visual input. While this could reflect sensory gain or arousal differences, the lack of significant differences in locomotor speed or other behavioral measures (Supplementary Figure 1) suggests that these changes are more likely due to functional reorganization of sensory processing.

We have clarified in the discussion that the shift in the temporal window is consistent with previous research on sensory reorganization involving both spatial and temporal cortical adjustments. While we do not claim novel spatial or temporal organization, we emphasize that the shift in temporal dynamics suggests adaptation in encoding strategy for texture perception in the absence of visual input. Future studies measuring arousal states (e.g., pupil diameter or cortical state markers) would help distinguish the contributions of arousal versus sensory reorganization to these dynamics.

(5) While the neural data suggest enhanced tactile representations, the study does not assess whether rats' actual tactile perception improved. Without a behavioral readout (e.g., discrimination accuracy), claims about perceptual enhancement remain speculative.

Thank you for raising this important point. We agree that while the neural data suggest enhanced separability of tactile representations in the dark condition, we do not directly assess whether these changes translate into improved tactile perception behaviorally.

However, the primary aim of our study is not to claim perceptual enhancement, but to demonstrate that neural representations in the somatosensory cortex can rapidly reorganize in response to visual deprivation. To clarify this distinction, we have revised the manuscript to emphasize that the observed neural changes in S1 are consistent with functional reorganization of tactile representations, rather than a direct indication of perceptual improvement.

Future studies will be crucial to directly test whether the enhanced separability of tactile representations in S1 correlates with improved tactile perception in a behavioral task. We have highlighted this as an avenue for future research to better understand the link between neural changes and perceptual outcomes.

(6) In addition to point 4, the authors discuss implications for sensory rehabilitation, including Braille training and haptic feedback enhancement. However, the lack of actual chronic or even more acute pathological sensory deprivation, behavioral data, or subsequent intervention in this study limits the ability to draw translational conclusions. It remains unknown whether the more distinct neural representations observed actually translate into better tactile performance, discriminability, or perception. Additionally, extrapolating from rats walking on sandpaper in the dark to human rehabilitative contexts is speculative without a clearer behavioral or mechanistic bridge. The potential is certainly there, but the claim is currently aspirational rather than empirically grounded.

Thank you for raising this important point. Upon careful consideration, we have decided to remove the discussion of sensory rehabilitation implications from the revised manuscript. We have refocused the manuscript to concentrate solely on the neural findings related to tactile encoding reorganization in response to short-term sensory deprivation, avoiding speculative extrapolation to human rehabilitative contexts. This revised approach ensures that the manuscript emphasizes the empirical findings without overstating the translational potential.

(7) While the CNN showed good performance, details on generalization robustness and validation (e.g., cross-validation folds, variance across animals) are not deeply discussed. Also, while explainability tools were used, interpretability of CNNs remains limited, and more transparent models (e.g., linear classifiers or dimensionality reduction) could offer complementary insights.

We appreciate the reviewer’s valuable feedback. In response to the concern about generalization robustness and validation, we have now conducted 5-fold cross-validation to assess the model's performance within animals (Figure 6C). We also have added supplementary information on the average silhouette scores across the different folds and animals (Supplementary Table 1, 2). These details are provided in the methods section and discussed in the results to offer a clearer picture of the model's robustness and consistency across rats.

Regarding the interpretability of CNNs, we acknowledge that deep learning models can lack transparency. We also attempted classification using more transparent models such as PCA and SVM, but their performance did not exceed chance level (Supplementary Figure 2). This indicates that while these simpler models are more interpretable, they cannot capture the complex representations in the LFPs, making deep learning models like CNNs necessary for extracting these insights.

Reviewer #2 (Public review):

(1) Despite applying explainability techniques to the CNN-based decoder, the study does not clearly demonstrate the precise "subtle, high-dimensional patterns" exploited by the CNN for surface roughness decoding, limiting the physiological interpretability of the results. Additional analyses (e.g., detailed waveform morphology analysis on grand averages, time-frequency decompositions, or further use of explainability methods) are necessary to clarify the exact nature of the discriminative activity features enabling the CNN to decode surface roughness and how these change with the sensory context (i.e., in light or darkness).

Thank you for your insightful comment. We recognize the importance of clarifying the exact nature of the high-dimensional neural patterns that the CNN exploits for surface roughness decoding. In response, we have performed additional analyses to provide a more detailed explanation of the CNN's decision-making process and the discriminative features it learned:

Grand-Average LFP Waveforms Analysis: We calculated the grand-average LFP waveforms for each texture × lighting condition (Figure 4A). While visual inspection did not reveal distinct features in the averaged waveforms, we explored the channel-wise correlations between textures under both light and dark conditions (Figure 4B). We found that the correlation between textures was lower in the dark condition, suggesting that LFPs become more distinct between textures when visual input is absent, which aligns with the CNN’s output.

Time-Frequency Decomposition (Wavelet Analysis): We also performed time-frequency decomposition of the LFPs using wavelet transforms (Figure 4D). No prominent differences emerged across texture × lighting conditions in the spectral domain. However, upon computing differences in wavelet features between light and dark conditions and analyzing the relationship with the CNN's attribution scores (Supplementary Figures 5A-C), we observed a negative correlation in the 50-60 Hz range and a positive correlation in the 80-90 Hz range. This suggests frequency-specific modulation in LFP activity that may contribute to texture representations, providing further support for the CNN’s learned features.

(2) The claim regarding cross-modal representation reorganization heavily relies on a silhouette analysis (Figure 5C), which shows a modest effect size and borderline statistical significance (p≈0.05 with n=9+2). More rigorous statistical quantification, such as permutation tests and reporting underlying cluster distances for all animals, would strengthen confidence in this finding.

Thank you for your thoughtful comment. We appreciate your suggestion to strengthen the statistical rigor of our analysis regarding the cross-modal representation reorganization. In response, we have implemented several additional analyses to more rigorously quantify the separability of neural representations between light and dark conditions:

(1) Permutation Test for Cluster Separability: We performed a permutation test to assess whether the observed differences in cluster separability between light and dark conditions were statistically significant or could have arisen by chance. The results showed that the silhouette scores for the dark condition consistently exceeded the 95th percentile of the null distribution (Supplementary Figure 4). This permutation test strengthens the validity of our findings, indicating that the enhanced separability in darkness is a systematic reorganization of neural representations, not due to random fluctuations.

(2) Reporting Cluster Distances: To address concerns about the modest effect size and borderline significance, we have explicitly reported the underlying cluster distances in the form of silhouette scores for each individual animal (Supplementary Table 1, 2). These values reflect the Euclidean distance between clusters within each rat, providing a clearer understanding of the separability observed.

(3) Additional Statistical Analysis on Silhouette Scores: To further enhance the rigor of our statistical analysis, we recalculated the silhouette scores using 5-fold cross-validation within each animal, ensuring that our results are robust across multiple data splits (Figure 6C).

By incorporating these additional analyses and reporting detailed cluster distances, we believe we have significantly strengthened the confidence in our claim of cross-modal reorganization.

(3) While the authors recorded in the somatosensory cortex, primarily known for its tactile responsivity, I would be cautious not to rule out a priori the presence of crossmodal (visual) responses in the area. In this case, the stronger texture separation in darkness might be explained by the absence of some visually-evoked potentials (VEPs) rather than genuine cross-modal reorganization. Clarification is needed to rule out visual interference and this would strengthen the claim.

Thank you for raising this important point. In response to your concern, we carefully examined whether visually-evoked potentials (VEPs) could be present in the S1 recordings, particularly under the light condition. However, we observed that this experiment did not involve any cue-guided visual stimulation, such as flashing lights or visual cues aligned with the LFP recordings. Without such external visual stimuli, it is unlikely that VEPs would be reliably evoked in the S1. Therefore, we believe the stronger texture separation observed in the dark condition is not due to visual interference, but rather reflects a genuine sensory reorganization in response to the absence of visual input.

(4) Behavioural controls are limited to gross gait parameters; more detailed analyses of locomotor behavior and additional metrics (e.g., pupil size or locomotor variance) would robustly rule out potential arousal or motor confounds.

Thank you for your insightful comment regarding behavioral controls. In response, we have added locomotor speed traces aligned with corresponding LFPs (Supplementary Figure 1) to demonstrate that locomotion remained consistent across trials, irrespective of environmental condition (light vs. dark). Additionally, we report locomotor speed variance over 10-minute blocks to confirm no significant motor changes affecting neural recordings. These analyses indicate that LFP differences are unlikely due to locomotor confounds.

While measuring pupil size could be useful for assessing arousal, the camera resolution in our study was insufficient for reliable measurements. We have noted this limitation in the Discussion and recommend that future studies with high-resolution eye-tracking explore arousal's role in sensory processing in S1.

(5) The consistent ordering of trials (10 minutes of light then 10 minutes of dark) could introduce confounds such as fatigue or satiation (and also related arousal state), which should be controlled by analyzing sessions with reversed condition ordering.

Thank you for highlighting the potential confounds due to trial ordering. To address this, we reversed the condition order (dark before light) in a subset of sessions from six rats and reanalyzed the data (Supplementary Figure 3). The results showed not significant, but increase separability in the dark condition, suggesting that the enhanced separability in the dark condition is not due to trial order effects like fatigue or satiation. While order effects may contribute to trial-to-trial variability, the consistent pattern of enhanced separability in the dark further supports the interpretation that visual deprivation directly influences the reorganization of tactile representations in S1.

(6) The focus on forelimb-aligned LFP analyses raises the possibility that hindlimb-aligned data might yield different conclusions, suggesting alignment effects might bias the results.

Thank you for your insightful comment on the potential bias of forelimb-aligned LFP analyses. We acknowledge that the choice of alignment event can influence the results and appreciate the suggestion to consider hindlimb-aligned data. However, our experimental design specifically focused on forelimb S1. The forelimb region of S1 was oversampled in our array, and as expected, we observed larger responses there, consistent with the known somatotopic organization of S1.

While hindlimb-aligned data could provide additional insights, it is not directly relevant to the primary question of how forelimb S1 codes tactile information under visual deprivation. We do not believe the forelimb alignment introduces a bias, as it aligns with the sensory task being investigated. However, we recognize the value of exploring alternative alignments and have now included a discussion in the Methods section regarding the rationale for our design choices.

(7) The authors' dismissal of amplitude-based metrics as ineffective is inadequately substantiated. A clearer demonstration (e.g., event-related waveforms averaged by conditions, presented both spatially and temporally) would support this claim.

Thank you for your constructive comment. In response, we have added a more detailed analysis of event-related waveforms, averaged across conditions (light vs. dark, smooth vs. rough textures), and presented them spatially and temporally aligned to forelimb contact (Figure 4A). These waveforms did not show clear, distinct features that could differentiate conditions, which highlights the limitations of traditional amplitude-based metrics in detecting subtle neural activity changes related to visual deprivation.

We further performed channel-wise correlation analyses (Figure 4B), revealing stronger texture correlations in the light condition, indicating that averaged waveforms do not capture the nuanced differences in neural dynamics. Additionally, time-frequency spectrograms and channel–channel correlation matrices (Figures 4C and 4D) did not show distinct condition differences, reinforcing the limitations of amplitude-based metrics.

These findings, along with the superior performance of machine learning-based decoding methods (e.g., CNN), support our claim that amplitude-based approaches are insufficient for fully capturing the complexity of the neural data.

(8) Wording ambiguity regarding "attribution score" versus "activation amplitude" (Figure 5) complicates the interpretation of key findings. This distinction must be clarified for proper assessment of the results.

Thank you for pointing out the ambiguity between "attribution score" and "activation amplitude." To address this, we have revised the manuscript to use "attribution score" only.

(9) Generalization across animals remains unaddressed. The current within-subject decoding setup limits conclusions regarding shared neural representations across individuals. Adopting cross-validation strategies and exploring between-animal analyses would add significant value to the manuscript.

Thank you for highlighting the importance of generalization across animals. While our study focused on within-subject decoding, we acknowledge that this limits conclusions about shared neural representations across individuals. We expect that inter-animal generalization would be challenging, as models trained on data from a single rat may not perform well on data from others due to differences in electrode placement, brain anatomy, and neural representations. We recognize the value of cross-validation strategies and between-animal analyses and will consider them in future work to address this limitation.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

(1) I would strongly recommend that the authors refine their introduction to be more concise. Many concepts and study aims are repeated many times and, therefore, present as highly redundant text. The introduction may be half the length and still contain the important concepts to set up the justification for the study. I would also suggest refining to be less about sensory deprivation (e.g., with blindness) and more in relation to context, as the acute nature of the study allows one to conclude more about the latter than the former.

Thank you for your feedback on the introduction. We have revised the section to reduce redundancy and present the key concepts more concisely. We also streamlined the study aims and focused more on the context of the acute nature of the study, as you suggested, rather than emphasizing sensory deprivation. This revision better aligns with the main focus of the research and improves clarity. We believe the updated introduction provides a more direct justification for the study.

(2) I am not sure if Figures 1-3 are meant to be in grey-scale for some reason (perhaps to represent light and dark), but I would encourage the authors to examine if this is necessary, as the use of color generally helps one more easily follow Figures.

Thank you for this suggestion. Upon review, we agree that the use of color would enhance the clarity and readability of our figures. We have revised the figures including the newly added supplementary figures to incorporate color.

(3) Figure 5, Figure legend title - check wording.

Thank you for pointing this out. The title has been adjusted for consistency with the other figure legends.

Reviewer #2 (Recommendations for the authors):

(1) Analyses that would strengthen the main claims (major):

(a) Identify the features exploited by the CNN.

(i) Provide grand-average LFP waveforms for each texture × lighting condition (fore- and hind-limb channels shown separately, spatially arranged as in Figure 3C) and try to relate them to the decoding strategy learned by the CNN.

Thank you for your helpful suggestion. We have calculated the grand-average LFP waveforms for each texture × lighting condition and included them in Figure 4A, with fore- and hind-limb channels shown separately and spatially arranged as in Figure 3C. Upon visual inspection, the mean waveforms did not reveal clear, distinct features. To further investigate, we computed the channel-wise correlation between different textures under both dark and light conditions. By subtracting the correlation coefficients for the dark environment from those in the light, we observed that the correlation between textures was lower in the dark environment (Figure 4B). This suggests that LFPs are more distinct between textures in the dark, supporting the CNN model's output. However, this also indicates that the CNN has captured more complex, nuanced information, as it is able to discriminate between LFPs on a single-trial basis, rather than relying on mean traces.

To assess how the correlation between average LFP waveforms varied across channels, we also calculated the channel-channel correlation matrix for all 32 channels in each condition. While we found stronger correlations within each S1 subregion, we did not observe clear differences of correlation matrix between light and dark conditions, nor between different textures (Figure 4C).

(ii) Add channel-wise and time-frequency maps (e.g., wavelet or spectrograms) for each texture × lighting condition and try to relate them to the decoding strategy learned by the CNN.

Thank you for the valuable suggestion. We calculated wavelet features for each LFP segment and averaged them across trials to assess differences in LFP between light and dark conditions, as well as across textures (Figure 4D). However, no distinct differences were observed in the spectral map. To investigate further, we computed the differences in spectral maps for LFPs in light and dark trials. We then calculated the difference in attribution scores derived from the integrated gradient map (Supplementary Figure 4A). Subsequently, we calculated the correlation coefficients between the differences in integrated gradients and the differences in power across each frequency band in the spectral map (Supplementary Figures 4B and 4C). A negative correlation was found in the 50-60 Hz range, while a positive correlation was observed in the 80-90 Hz range. These findings suggest that frequency-specific patterns of LFP activity in different conditions may be linked to the texture representations captured by the CNN model. We have included a discussion of these findings in [lines 463-468].

(b) Quantify the "enhanced separability in darkness" more rigorously.

(i) Report cluster-distances (e.g. Euclidean) for each individual animal.

We thank the reviewer for this helpful comment. When calculating the silhouette score, we used Euclidean distance as the distance metric. The silhouette score is defined for each data point as the difference between the average distance to points within its assigned cluster and the average distance to points in the nearest other cluster, normalized by the larger of the two values. Thus, the silhouette score inherently reflects the relative cluster distances both within and across conditions for each individual animal. Because we report and statistically analyze silhouette scores (Figure 6C), these values already quantify and compare the Euclidean cluster distances across conditions at the animal level. For clarity, we have now added a definition of the silhouette score in the Methods section of the main text [lines 269-278]. We also included the calculated silhouette scores in Supplementary Table 1.

(ii) Run a permutation or bootstrap test (shuffling darkness/light labels within animals) to obtain an empirical null distribution for cluster separability in the network embedding space.

We thank the reviewer for this important suggestion. In response, we implemented a permutation test to assess the robustness of our cluster separability results. Specifically, we shuffled the darkness/light labels within each animal and recalculated silhouette scores across 1000 resamples to generate an empirical null distribution. The observed separability between light and dark conditions consistently exceeded the 95th percentile of the null distribution (Supplementary Figure 3). This confirms that the enhanced cluster separability in darkness was not attributable to random fluctuations in labeling but instead reflected a systematic reorganization of neural representations.

(c) Control for possible visually-evoked potentials (VEPs).

(i) Search the LFPs recorded in light for stereotyped VEP components and/or comment on this possible confound (i.e., VEPs in S1?).

Thank you for raising this point. Although it would be interesting to observe if a VEP is present in the S1 of rats, this experiment did not involve cue-guided visual stimulation. Additionally, there was no environmental visual cue that could serve as an external trigger to align the LFPs for VEP analysis in S1. Furthermore, since even the somatosensory evoked potential was not clearly visible in the S1 LFP without averaging the aligned LFPs, it is unlikely that we would be able to observe VEPs in single trials.

(d) Address behavioral and arousal confounds.

(i) Provide example locomotor-speed traces (aligned with corresponding LFPs) and report locomotor-speed variance across the 10-min blocks.

Thank you for your comment. We had speedometer installed for the recording of the last two rats. We have now provided example speed traces and the speed variance across blocks in Supplementary Figure 1. The traces show that the locomotor-speed was stable in each trial.

(ii) If available from the camera recordings, include pupil diameter as a proxy for arousal; otherwise, discuss explicitly how arousal changes might affect S1 LFPs.

Thank you for this suggestion. We strongly agree that measuring pupil diameters should be incorporated into future studies. However, because our camera did not have sufficient resolution to capture pupil diameters, we have addressed this limitation in the discussion section [lines 525-537].

(e) Address order effects (and motivation/satiety confounds)

(i) Present at least a subset of sessions in which the dark block precedes the light block; re-analyze the silhouette score/discriminability with block order as a factor.

Thank you for this helpful suggestion. We conducted additional analyses using sessions from 6 rats in which the dark block preceded the light block (Supplementary Figure 5A). Using the same model architecture, we calculated the silhouette score for each rat (Supplementary Figure 5B). However, when the order was reversed (dark preceding light), this discriminability effect disappeared. Thus, while we observed a trend toward higher scores in the dark condition, no statistically significant differences in texture discriminability were observed.

If trial order alone accounted for the increase in discriminability, reversing the order would be expected to yield higher silhouette scores in the light condition. Our findings suggest that factors related to order (e.g., thirst or motivation, as you proposed) are not the sole contributors. Furthermore, previous studies in human participants have shown that brief blindfolding can produce lingering increases in tactile sensitivity, indicating a lasting effect of visual deprivation. Thus, the absence of significant differences in texture representation when the dark condition preceded the light condition may reflect such lasting effects. We have included a discussion in [lines 441-452].

(ii) Discuss explicitly the potential confounding effect of motivational state/thirst.

We appreciate the reviewer’s insightful comment. In the revised manuscript, we now explicitly address the potential confounding role of motivational state and thirst in shaping our results. Because animals were water-restricted to maintain task engagement, it is possible that increasing thirst or fluctuating motivation over the course of a session could alter arousal or attentional state, thereby influencing neural separability. However, when the trial order was reversed (dark condition preceding light), silhouette scores did not show a significant increase in the second (light) trial. Thus, while we acknowledge that motivational state may contribute to trial-to-trial variability, the systematic increase in separability during darkness cannot be fully explained by thirst or motivational confounds. This addition has been incorporated into the discussion section [lines 441-452].

(f) Alignment control and the role of forelimb S1.

(i) Repeat the decoding analysis with LFPs aligned to hind-limb strike; report whether the fore-limb dominance persists.

Thank you for your thoughtful suggestion. We appreciate the opportunity to clarify. Our study was designed to ask a different question: how the absence of visual input reorganizes tactile encoding for the body part that actually initiates texture contact in our paradigm (the forepaw). Accordingly, all analyses were aligned to forelimb strike and our array intentionally oversampled S1-forelimb relative to S1-hindlimb (18 vs. 14 electrodes; Fig. 1F–G), yielding clear topographic forelimb-locked event-related responses (Fig. 3B–D) and forelimb-channel dominance in the decoding explainability analyses (Fig. 5D–E). Repeating the full decoding locked to hind-limb strike would test a different hypothesis and would be difficult to interpret for three reasons:

Design/measurement alignment. Our kinematic detection was built to identify forelimb foot strikes. Extending the detector to hindlimb would require new model training/validation and introduces uncertainty in the exact contact timing relative to the LFP segments we analyze.

Sampling asymmetry. The array and cortical magnification are not balanced across subregions (18 forelimb vs. 14 hindlimb electrodes; Fig. 1G), so a hind-limb–aligned comparison would be confounded by unequal coverage and signal-to-noise across S1 subdivisions rather than reflecting true “dominance.”

Scope of the claim. We do not claim that the forelimb is globally more informative about texture; we show the intuitive and topographically specific result that “forelimb S1 codes textures touching the forelimb,” and that these representations become more separable in darkness (silhouette increase; Fig. 5C). A hind-limb–locked re-analysis would likely reveal hindlimb contributions when the hindpaw is the alignment event — but that would not change the central conclusion about darkness enhancing tactile representational separability.

To address the underlying concern about generality without introducing the above confounds, we have clarified these design choices and limitations in the revised Methods [lines 194-197].

(g) Amplitude-based baseline.

(i) Show that a simple linear discriminant or logistic-regression model on peak amplitudes (and/or other simple features like trough width/slope) cannot reach the CNN's accuracy. This kind of "baseline" analysis could also be useful to pinpoint the discriminative features learned by the CNN.

Thank you for your insightful suggestion. We agree that performing a baseline comparison with a simpler model could help highlight the advantage of using a CNN. However, in our dataset, individual LFP traces do not exhibit clear peaks or well-defined features such as peak amplitude, width, or energy, which makes feature extraction using traditional methods like linear discriminants or logistic regression challenging.

To address this, we performed principal component analysis (PCA) on the raw LFP traces to reduce the dimensionality and applied a support vector machine (SVM) classifier on the reduced features, in line with the approach used for the CNN models (Supplementary Figure 2A). The results of this analysis, demonstrate that the SVM model struggles to effectively discriminate between conditions, further reinforcing the necessity of the CNN model. The CNN’s ability to automatically learn complex features from the raw LFP data appears to be a crucial factor in achieving superior classification performance (Supplementary Figure 2B).

(h) Cross-validation and inter-animal generalization.

(i) Consider replacing the single 80/20 split with k-fold cross-validation within animals.

Thank you for this suggestion. Instead of using an 80/20 split, we performed 5-fold cross-validation on all rats. The silhouette scores were averaged within each animal across the five folds, and Figure 6C was updated accordingly. After performing a paired t-test, we still observed a significant difference in silhouette scores between the light and dark conditions.

(ii) Comment on inter-animal generalization.

Thank you for this valuable feedback. Although we did not explicitly test inter-animal generalization, it is unlikely that a model trained on data from one rat would perform equally well when classifying data recorded from another animal. This limitation arises from two main factors. First, despite careful efforts to implant electrodes in the same brain region and cortical layer across experiments, it is impossible to align all 32 electrodes to identical coordinates. Consequently, the recorded LFPs are obtained from slightly different locations, which may reflect distinct neural processing. Second, even within the same species, individual animals differ in brain size and neural circuit organization. Thus, even if electrodes could be placed at identical anatomical locations, inter-individual variability in brain structure would still lead to differences in the recorded signals. Because deep learning models are often sensitive to small perturbations in their input data, we believe that robust inter-animal generalization is unlikely without fine-tuning the model using data from the target animal. This comment has been inserted in the Discussion [lines 494-507].

(2) Writing, figure and terminology improvements (minor):

(a) Figure 5F-G axis label. Decide on either "attribution score" or "activation amplitude" and use that term consistently in panels, legend, and text (currently, I believe it could be confused with raw signal amplitude).

We have unified the terminology to "attribution score" and applied this consistently across the panels, legend, and text.

(b) Throughout the manuscript, use "population-level activity" or "average population dynamics" when discussing LFPs (I believe it is more correct to reserve "population code" for multiple single-unit datasets).

We agree with the reviewer’s point and have adapted the term "population dynamics" to describe LFP information consistently throughout the manuscript.

(c) Lines 219-221, state down-sampling to 2 kHz, whereas line 289 mentions 10 kHz. Reconcile these numbers.

We apologize for the confusion and thank the reviewer for thoroughly reading the manuscript. Our original sampling rate was 30 kHz, and all analyses were performed on data resampled to 10 kHz. The reference to 2 kHz was an error, and we have corrected it.

(d) Specify the tail of each statistical test mentioned in the manuscript and any multiple-comparison correction used.

We have specified the tail of each statistical test and any multiple-comparison corrections used in the "Data Analysis" section of the Methods.

(e) Line 244: "variables (He et al., 2015)" → "variables (He et al., 2015)".

We have corrected this formatting issue and revised it to "variables (He et al., 2015)".

(f) Line 253: "one-dimentional" → "one-dimensional".

We have corrected the spelling error and revised it to "one-dimensional".

(3) Data and code sharing:

(a) Consider depositing data and code for the analysis in public open repositories.

Thank you for your suggestion. We have set up a public GitHub repository to share the code. Since the full dataset is quite large (~400GB), we have uploaded a smaller example dataset for the analysis.

Reviewer #2 (Public review):

Summary:

An abundant literature documents molecular changes in the rodent hypothalamus that occur during the transition from prepubertal to mature reproductive physiology. Equally well documented is the role of sex steroids and their receptors during this important period of reproductive development, as well as the importance of GABAergic and glutamatergic neurons. The medial preoptic area (MPOA) is known to play a central role in expression of sexually dimorphic reproductive function and previously reported sexually dimorphic patterns of gene expression are consistent with this role. The present manuscript extends this knowledge base and reports the results of a detailed evaluation of transcriptional dynamics in the MPOA during the adolescent transition to maturity with a particular focus on the role of the estrogen receptor gene (Esr1). Both single cell RNA sequencing (scRNseq) and multiplex in situ hybridization methods were employed and the results subjected to detailed computational analyses to demonstrate that the transcriptomic structure of MPOA neurons displays both sex and cell type specific expression profiles. In addition, both hormonal and genetic manipulations of Esr1 signaling during puberty altered the transcriptional profiles of MPOA neurons, and these changes aligned with maturation of hormone-dependent reproductive function. The authors provide this evidence to illustrate Esr1-dependent control of gene regulatory networks required for normal expression of reproductive behaviors expressed during the transition from adolescence to adulthood. The results presented in this manuscript are extensive and represent the most comprehensive evaluation of transcriptomic changes during reproductive maturation to date. The methods appear strong and the results provide a rich data set that will support a good deal of future analysis.

Strengths:

(1) The major strength of this manuscript is the extensive set of images and graphs that illustrate molecular changes that occur in MPOA neurons during adolescence, although additional spatial detail as to locations of the source neurons would be welcome in order to place the changes in the proper circuitry context.

(2) Targeting Esr1 deletion to MPOA GABA neurons is a good choice, given how these cells have been implicated in sexual differentiation of reproductive behavior previously, and the lack of comparable responses in glutamatergic neurons is convincing. The AAV-frtFlex-Cre virus created by the investigators is a most useful tool for such studies. Profiling distinct transcriptomic trajectories in GABA and glutamatergic neurons during reproductive maturation is impressive and leads to some of the best supported conclusions in this paper.

(3) Cellular and molecular resolution of the transcriptomics data appears excellent, however, because the source tissue for the scRNAseq analysis was obtained by bulk dissection of the MPOA anatomical resolution is limited. This problem is addressed to some extent by careful comparison of scRNAseq results with previously published spatial transcriptomics data. The HM-HCR-FISH analysis clearly documents spatially restricted changes in gene expression, but it is hard to discern where these changes occur based on the images presented or the descriptions included in the Results. The anatomical schematic included in Figure 4 suggests that investigators are not familiar with components of the MPOA (see Allen Mouse Brain Atlas).

Weaknesses:

(1) A major conceptual flaw is that the authors do not distinguish between genetically determined sex differences in patterns of gene expression and differences caused by the fact that MPOA neurons are exposed to different endocrine environments in adolescent males and females, which can cause different transcriptional trajectories independent of genetic sex. This issue does not render their results invalid, but their terminology should address the issue in the discussion and "limitations" section. At the very least the endocrine status of "intact females" should be included.

(2) A major technical flaw is that the MPOA is treated as a functionally distinct brain region (block dissections) with uniform distribution of cell types (FISH data are not illustrated or reported with sufficient spatial detail). Thus, an enormous amount of molecular data is provided that cannot be mapped to distinct neural circuits, thereby limiting the neurobiological impact. This is also a weakness of the FISH data, which is presented with only small regions illustrated without anatomical detail. In fact, some images are compared that appear to illustrate different MPOA structures, although it is impossible to be certain of this due to the lack of morphological landmarks. The analysis of how Esr1 orchestrates regulatory gene networks is impressive and interesting, but the fact that many of the observed transcriptional events occur in neural circuits that do not overlap confounds interpretation.

(3) The locations of the AAV injections should be characterized because deleting Esr1 in multiple distinct parts of the MPOA will likely confound interpretation. This is especially problematic given the limited number of mice used for parts of the RNAscope analysis.

(4) Although the focus of these experiments on adolescence is welcome, neither the Introduction nor the Discussion do a good job of placing these studies in the context of what is already known about brain maturation during puberty. It is true that this is very much a results-focused manuscript, but the scholarship can be improved. Simply stating that your results are consistent with previous reports places an undue burden on the reader to go figure out what is new.

(5) Throughout the manuscript, the authors utilize obscure abbreviations, which often makes reading their text overly cumbersome. This is certainly justified in certain instances where complex names of analytical methods are used repeatedly, but the authors are encouraged to try and simply their use of non-standard abbreviations.

Comments on revisions:

The authors have considered issues raised during the initial review. Although there do not appear to be significant changes to analyses, figures or conclusions, the authors have added important revisions listing limitations in study design and methodology that impact interpretation.

Author Response:

The following is the authors’ response to the original reviews.

Public review:

Reviewer #1 (Public review):

Weaknesses:

Two minor comments

(1) Fig 4 (hormone treatment): In this experiment, testosterone is given to males, yet in Sup Fig 6 it is argued that Esr1 is more influential in driving transcriptional changes compared to AR. Does DHT treatment have the same outcome as testosterone? Or, does estrogen treatment in males have the same outcome as testosterone?

We agree that to distinguish AR and Esr1 activation by testosterone and converted estrogen respectively is a limitation in our study. We added discussion in the “limitation of the study” section.

Although HM-HCR experiments showed the bidirectional control of transcriptional progression during adolescence, it is unclear if the facilitation in male by testosterone supplement is via activation of AR or Esr1 or both because testosterone will likely be converted to estrogen in the brain. Future studies using dihydrotestosterone (DHT) and estrogen to males may address this issue.

(2) Fig 3i: There appears to be an age-dependent transcriptional change in male Vgat HR-low cells. Can the authors comment on age-dependent (hormone-independent) transcriptional changes in males versus females.

We agree that it is important to clarify hormone dependent changes and age dependent changes. We added pair-wise DE results in Vgat HR low population in the main text. As consistent with trajectory analysis, the number of age-dependent genes were fewer than hormonally associated genes.

“Pair-wise DEG analysis consistently showed that larger number of DEGs between P35 and P23 in Vgat+Esr1+ (male: 146 genes; female: 162 genes) than Vgat+ hormone R^Low (male: 26 genes; female: 1 gene).”

Reviewer #2 (Public review):

Weaknesses:

(1) A major conceptual flaw is that the authors do not distinguish between genetically determined sex differences in patterns of gene expression and differences caused by the fact that MPOA neurons are exposed to different endocrine environments in adolescent males and females, which can cause different transcriptional trajectories independent of genetic sex. This issue does not render their results invalid, but their terminology should address the issue in the discussion and "limitations" section. At the very least the endocrine status of "intact females" should be included.

We agree that this was ideal if perinatal and pubertal dynamics are analyzed within the same study to distinguish these two processes. We added discussion in the “limitation section”.

“2. Although we have identified hormone/Esr1 dependent transcriptional trajectories during adolescence, the relations and interplay with genetically determined perinatal event, which is earlier and robust, are unclear. Some sex differences during adolescence might be an extension of perinatally established sex differences while others might be unique adolescent changes.”

(2) A major technical flaw is that the MPOA is treated as a functionally distinct brain region (block dissections) with uniform distribution of cell types (FISH data are not illustrated or reported with sufficient spatial detail). Thus, an enormous amount of molecular data is provided that cannot be mapped to distinct neural circuits, thereby limiting the neurobiological impact. This is also a weakness of the FISH data, which is presented with only small regions illustrated without anatomical detail. In fact, some images are compared that appear to illustrate different MPOA structures, although it is impossible to be certain of this due to the lack of morphological landmarks. The analysis of how Esr1 orchestrates regulatory gene networks is impressive and interesting, but the fact that many of the observed transcriptional events occur in neural circuits that do not overlap confounds interpretation.

We agree that while MPOA is defined based on brain atlas consistently across samples, the boundary is somewhat less obvious compared to other nuclei (e.g. hippocampus, VHM etc). To minimize the contaminations from adjacent areas, we have restricted quantitative analysis to mostly Vgat+ Esr1+ population which are densely located within the MPOA but not in immediately adjacent areas, except posterior BNST which is readily distinguishable. We added clarification in the method as well as added technical limitation in the discussion below.

Method

“To disambiguate the MPOA and adjacent brain regions, quantitative analysis is restricted to Vgat+ Esr1+ neurons and is devoid of posterior BNST.”

Discussion

“3. While we have observed robust effect of Esr1-KO in scRNAseq experiment which was further validated with FISH experiment, it is possible that there are further heterogeneous Vgat-Esr1 populations in the MPOA which might be differentially targeted in each virally injected sample. To mitigate this, 3-4 mice were pooled for each sample in scRNAseq experiment and in HCR-FISH experiment, in addition to confirming recombinase RNA expression within the MPOA, we included samples with robust Esr1 deletion in the MPOA. Interestingly, due to the technical challenge, Esr1 deletion tends to be more robust than weakly detected recombinase RNA expression (data not shown).”

(3) The locations of the AAV injections should be characterized because deleting Esr1 in multiple distinct parts of the MPOA will likely confound interpretation. This is especially problematic given the limited number of mice used for parts of the RNAscope analysis.

We agree that similar to #2, this is an important matter. For HCR experiment, we only included animal with recombinase RNA (Cre or Flp) expression within MPOA. Although the recombinase expression was sufficient enough to qualitatively determine the hit or miss, the detection was weak and it was challenging to determine the extent of viral spread. Thus, we also used successful Esr1 deletion as an additional inclusion criteria for AAV-Cre-YFP group. We have added inclusion criteria in the method and technical consideration in discussion.

Method

“For HCR2, AAV was injected unilaterally so that successful targeting of the MPOA with AAVCre-YFP (detection of recombinase RNA within the MPOA) and the deletion of Esr1 were confirmed for inclusion of samples.”

Discussion

“3. While we have observed robust effect of Esr1-KO in scRNAseq experiment which was further validated with FISH experiment, it is possible that there are further heterogeneous Vgat-Esr1 populations in the MPOA which might be differentially targeted in each virally injected sample. To mitigate this, 3-4 mice were pooled for each sample in scRNAseq experiment and in HCR-FISH experiment, in addition to confirming recombinase RNA expression within the MPOA, we included samples with robust Esr1 deletion in the MPOA. Interestingly, due to the technical challenge, Esr1 deletion tends to be more robust than weakly detected recombinase RNA expression (data not shown).”

(4) Although the focus of these experiments on adolescence is welcome, neither the Introduction nor the Discussion do a good job of placing these studies in the context of what is already known about brain maturation during puberty. It is true that this is very much a results focused manuscript, but the scholarship can be improved. Simply stating that your results are consistent with previous reports places an undue burden on the reader to go figure out what is new.

We agree that contextualizing our study in the scholarship will clarify the novelty and impacts that this study provides to the community. We have updated the introduction adding a review highlighting puberty associated genomic studies in the brain, which are all bulk (brain region level) as well as the very first puberty scRNAseq study in Human testis.

“Despite the well-established role of these hormones in shaping behavior, the molecular mechanisms underlying their influence on brain development during adolescence are still limited to brain-region level (bulk)[8]in humans and model organisms and adolescent transcriptional dynamics at single cell resolution in the brain remain poorly understood (but see a pioneering study in the human testis[9]).”

(5) Throughout the manuscript the authors utilize obscure abbreviations, which often makes reading their text overly cumbersome. This is certainly justified in certain instances where complex names of analytical methods are used repeatedly, but the authors are encouraged to try and simplify their use of non-standard abbreviations.

We agree that this is helpful for readers to have the reference of abbreviations in handy at single location. We added an “abbreviation” section as a reference for readers.

Medial preoptic area (MPOA)

Single-cell RNA sequencing (scRNAseq)

Estrogen receptor 1 (Esr1)

GABAergic neurons (Vgat+)

Glutamatergic neurons (Vglut2+)

Hybridized chain reaction fluorescent in situ hybridization (HCR-FISH)

Gonadectomized (GDX)

Partition-based graph abstraction (PAGA)

Hormone-associated differentially expressed genes (HA-DEGs)

Multiplexed error-robust fluorescence in situ hybridization (MERFISH) differential gene expression (DE)

Differentially expressed genes (DEGs)

Support vector machine (SVM)

Manifold Enhancement Latent Dimension (MELD)

Potential of Heat-diffusion for Affinity-based Trajectory Embedding (PHATE)

Androgen receptor (AR)

single-cell regulatory network inference (SCENIC)

Reviewer #3 (Public review):

We appreciate reviewer for the constructive comments to improve our manuscript.

Weaknesses:

We already know that Esr1 is important within GABAergic but not glutamatergic neurons for mating behavior. However, there is not enough data to support the claim that disrupting Esr1 in glutamatergic MPOA neurons "had no observable effect." The MPOA is involved in many behaviors and physiologies that were not investigated. More assays would be required to report "no observable effect."

The small number of cells included in the transcriptional studies is a general concern, as noted by the authors. This is a particular concern for conclusions related to the role of adolescence in glutamatergic MPOA neurons. The paper reports 24,627 neurons across all treatment groups, which include 3 time points, 2 sexes, and GDX conditions. It seems likely that not much was detected in the glutamatergic neurons because of insufficient power.

Esr1 knockout is initiated in adolescence, not restricted to adolescence. Do we know that the effects on mating behavior are due to what is happening in adolescence vs. the function of Esr1 in adults? Are the effects different if Esr1 is knocked out in mature adults? This comparison would be important to demonstrate that adolescence is a critical time window for Esr1 function.

We agree that 1. the relatively mild effects observed in Glutamatergic neurons may be partially due to the scale of the study, and 2. Esr1 deletion is permanent once induced and it is challenging to distinguish adolescent and adult transcriptional dynamics using existing viral strategies.

We added discussion in the “limitation” section.

“4. While we have observed robust transcriptional progression in Vgat⁺ Esr1⁺ neurons during adolescence, we observed more mild alternations in VgluT2⁺ neurons. Although the scale of our study is comparable or exceeds prior scRNAseq studies in MPOA[22,29], future larger studies may have more sensitivity to detect adolescent transcriptional dynamics in VgluT2⁺ neurons.”

“5. Although we demonstrated adolescent transcriptional changes were observed as early as P35, and either hormonal deprivation or Esr1 KO in prior to adolescence prevented the transcriptional progression (arrested transcriptional state even at adult), given the viral incubation time and permanent deletion of Esr1 after viral injection, it is challenging to disambiguate the role of Esr1 during adolescence and adult. Future studies injecting the virus at adult may provide additional insights on the similarity and difference between transcriptional changes during puberty and maintained transcriptional states at adult.”

Reviewer #1 (Public review):

Summary:

Overall, this is an interesting and well-written manuscript on a fascinating question in a "charismatic" model system.

Strengths:

1) The Introduction is concise, though it might be helpful to the non-specialist reader to learn a bit more about what is known about the social control of somatic growth across diverse species (including humans), which would help to make this work more generally interesting.

(2) The experiment is well-designed.

(3) The data collected are comprehensive.

(4) The complementary analysis of both feeding and aggression/submission data with and without known social roles is a neat idea and compelling!

Weaknesses:

(1) I was surprised that the HPA/stress axis was not considered here at all. Wouldn't we expect that subordinates have increased stress axis activation, which in turn could inhibit their growth and aggressive behavior?

(2) To what extent are growth, food intake, agonistic behavior, and/or gene expression patterns coordinated across P1 vs P2 pairs? The lack of such an analysis seems like a missed opportunity.

(3) What was the rationale for using whole bodies for the transcriptome analysis? Given the hypotheses, the forebrain or hypothalamus and certain other organ systems (e.g., liver, gonads, skin, etc.) would have been obvious candidate tissues here. I realize that cost is always a consideration, but maybe a focus on the fore-/midbrain could have been prioritized.

(4) Given the preceding point, why was a fold-change threshold used for assessing DEGs (supplementary Figure 3)? There is no biological justification to ever use a fold-change threshold, especially in bulk RNA-seq analysis. This is particularly true here, where whole bodies were used for RNA-seq analysis, which is a bit unusual. Relatively small cell populations (such as hypothalamic neurons that regulate growth or food intake) may show substantial gene expression variation across social types, yet will be masked by the masses of other cells in the whole body sample. However, gene expression may still vary significantly, albeit the fold-difference may be small. I therefore suggest a reanalysis that omits any fold-change threshold.

(5) Why is the analysis of color (hue, saturation) buried in the supplementary materials? Based on the hypotheses that motivated the study, color seems just as relevant as food intake, growth, and agonistic behavior, so even if the results are negative, they should be presented in the main paper.

(6) The Discussion is sometimes difficult to follow. The authors may want to consider including a conceptual graphic that integrates the different aspects of growth and satiety regulation, etc., into a work-in-progress model of sorts, which would also facilitate clearer hypotheses for future research.

Reviewer #2 (Public review):

In this manuscript, the authors test growth, behavior, and gene expression in pairs of clownfish as they establish social dominance hierarchies, examining patterns of gene expression in these pairs after dominance has been established. The authors show solid evidence that emerging dominant clownfish show increased growth, aggression, and food consumption compared to their submissive or solitary counterparts, eventually adopting distinct gene expression profiles.

Major Comments:

(1) The Introduction is comprehensive, but it could be condensed. Likewise, the discussion could be condensed. There is considerable redundancy between the methods, the results, and the legend in Figure 1. The authors should consolidate and remove the redundancy.

(2) For Figure 3, the authors are showing PC2 and PC3; why is PC1 not shown? There is so much overlap between the three groups in PC2 vs PC3; it seems unlikely that researchers could conclusively identify any individual as belonging to a group based on the expression profile. The ovals shown do not capture all the points within each of the groups, and particularly the grey S oval seems misaligned with the datapoints shown.

(3) The authors indicate that the 15 replicates exhibiting the greatest size difference between P1 and P2 were selected for gene profiling. Does this mean that each of the P1 and P2 were pairs with each other? Have the authors tried examining the gene expression patterns in a paired manner? E.g., for the pairs that showed the greatest size differences, do they also show the greatest differences in gene expression? Do the P1s show the most extreme differences from P2s that also show the most extreme P2 differences? Perhaps lines on Figure 3A connecting datapoints from the P1 and P2 pairs would be informative.

(4) For the specific target pathways that are up- and downregulated in the different backgrounds, I recommend that the authors include boxplots (or heatmaps) showing the actual expression values for these targets. Figure 6 shows a heatmap for appetite-related genes, and it would be great to see a similar graph for the metabolism and glycolysis genes; it would also be informative to see similar graphs for hormonal and sexual maturation pathways as well.

(5) Particularly given that there is a relatively small number of genes enriched in the different rank conditions, I did not understand the need to do the WGCNA module analysis. I thought that an analysis of GO terms across the dataset would have been more meaningful than the GO term analysis shown in Figure 4, which considers only genes assigned to the "brown WGCNA module". This should be simplified or clarified.

(6) The authors say that they have identified coordinated changes in behaviors and the "underlying gene expression, leading to the emergence" of social roles. This is a little bit misleading, since the gene expression analysis occurred well after the behavioral and phenotypic differences emerged. Presumably, the hormonal and genetic shifts that actually caused the behavioral and phenotypic difference occurred during the weeks during which the experiment was underway, and earlier capture of the transcriptome would presumably reveal different patterns, and ones that would be considered more causative. The authors acknowledge this in 434-435, but it could be emphasized further.

(7) The authors have measured a number of differences between the different dominance classes of fish. All these differences were measured relative to the other classes, but in my view, the Solitary group was the closest to a baseline control. So I'm not sure that it is fair to say that "P2 and S individuals showed consistent downregulation of these genes and pathways" (line 401). I encourage the authors to emphasize the differences in gene expression from the "perspective" of the P1 individuals compared to the baseline of P2 and S individuals. Line 474 says that "P2 fish showed significant upregulation" of a number of pathways. It should be very clear what that is compared to (compared to P1, presumably?)

(8) Along the same lines, the authors say in line 514 that subordinates and solitaries strategically downregulate their growth. I'm not convinced that this is the case: I would consider this growth trajectory to be the default and the baseline. I would interpret that under certain social conditions, a P1 dominant pattern of growth, behavior, and gene expression is allowed to emerge.

Author Response:

Public Reviews:

Reviewer #1 (Public review):

Summary:

Overall, this is an interesting and well-written manuscript on a fascinating question in a"charismatic" model system.

Strengths:

(1) The Introduction is concise, though it might be helpful to the non-specialist reader to learn a bit more about what is known about the social control of somatic growth across diverse species (including humans), which would help to make this work more generally interesting.

(2) The experiment is well-designed.

(3) The data collected are comprehensive.

(4) The complementary analysis of both feeding and aggression/submission data with and without known social roles is a neat idea and compelling!

Thank you for the positive feedback!

Here, we investigate phenotypic plasticity associated with the adoption of social roles in the clown anemonefish, with strategic growth being just one aspect of that plasticity. Strategic growth, also known as social control of growth, is a fascinating form of adaptive phenotypic plasticity, whereby individuals modify their growth and size in response to fine-scale changes in social conditions (Buston & Clutton-Brock, 2022). In cooperative breeding systems with high reproductive skew, particularly fishes and mammals (possibly including humans), individuals have been shown to i) increase growth/size on the acquisition of dominant status (Dengler-Crish & Catania, 2007; Johnston et al., 2021; Thorley et al., 2018; Van Schaik & Van Hooff, 1996; Walker & McCormick, 2009), ii) increase growth/size when paired with size matched reproductive rivals (Huchard et al., 2016; Reed et al., 2019; this study), and iii) decrease growth/size to avoid conflict (Buston, 2003; Heg et al., 2004; Wong et al., 2007). While strategic growth is fascinating and clearly occurring in this study, we show coordinated changes of multiple aspects of the phenotype as fish adopt social roles. Therefore, we deliberately framed the Introduction broadly to avoid biasing the reader toward viewing growth as the sole or main driver.

Weaknesses:

(1) I was surprised that the HPA/stress axis was not considered here at all. Wouldn't we expect that subordinates have increased stress axis activation, which in turn could inhibit their growth and aggressive behavior?

We also expected to see the HPA/stress axis activated in subordinates, which is why we carried out a targeted exploration of genes known to play a role in this axis. We did not find any genes that were significantly differentially expressed. We believe that there could be two explanations for this. First, from a methodological perspective, it could be due to our use of a whole-body RNA-seq, which may have masked this signal. Alternatively, the stress axis might play a more complex role than just acting as a simple on/off switch for reduced growth. Its activation may peak when competition over size is at its highest (during week one) or, conversely, it may peak later and help maintain reduced growth once hierarchies are firmly established (particularly after the dominant individual reaches its maximum size). To understand the role of the stress axis, future studies should observe how its activation varies over time. We acknowledge that the absence of a stress‑axis signal and its potential explanations were not clearly discussed in the original manuscript, in the revised version, we will address this issue.

(2) To what extent are growth, food intake, agonistic behavior, and/or gene expression patterns coordinated across P1 vs P2 pairs? The lack of such an analysis seems like a missed opportunity.

We had a similar thought. Specifically, we were interested in testing the hypothesis that the final size ratio of pairs, which is indicative of the amount of conflict remaining, would predict gene expression. We examined gene expression within pairs to test for coordinated changes and repeated the analysis, accounting for the pair size ratio. In both cases, we found no clear or consistent pattern within pairs. We will consider including these figures in the Supplementary Materials document.

(3) What was the rationale for using whole bodies for the transcriptome analysis? Given the hypotheses, the forebrain or hypothalamus and certain other organ systems (e.g.,liver, gonads, skin, etc.) would have been obvious candidate tissues here. I realize that cost is always a consideration, but maybe a focus on the fore-/midbrain could have been prioritized.

We decided to use whole-body samples for this initial transcriptomic analysis to capture a broad view of gene-expression differences while keeping sequencing costs and sample requirements manageable. We agree with the reviewer that future work should explore specific tissues sampled from individuals at multiple time points to disentangle transcriptomic differences across tissue types.

(4) Given the preceding point, why was a fold-change threshold used for assessing DEGs (supplementary Figure 3)? There is no biological justification to ever use a fold-change threshold, especially in bulk RNA-seq analysis. This is particularly true here, where wholebodies were used for RNA-seq analysis, which is a bit unusual. Relatively small cell populations (such as hypothalamic neurons that regulate growth or food intake) may show substantial gene expression variation across social types, yet will be masked by the masses of other cells in the whole body sample. However, gene expression may still vary significantly, albeit the fold-difference may be small. I therefore suggest a reanalysis that omits any fold-change threshold.

We thank the reviewer for this important point, and agree that an arbitrary fold‑change cutoff is inappropriate/unnecessary. It should be noted that this fold-change cut-off was only used in this single figure, and all other analyses used p-values from the entire dataset. We will remove the fold‑change threshold cutoff and correct Supplementary Figure 3, and any corresponding text.

(5) Why is the analysis of color (hue, saturation) buried in the supplementary materials?Based on the hypotheses that motivated the study, color seems just as relevant as food intake, growth, and agonistic behavior, so even if the results are negative, they should be presented in the main paper.

We agree that color can be an important social signal, so we included color measurements in our experimental design. However, after careful consideration of the color results, we decided that our experimental timing and husbandry changes introduced multiple confounding factors, preventing us from drawing confident conclusions. Specifically, our fish were ≈1 month old at the transfer from larval to experimental tanks and had already begun to deepen their orange hue, before our experiment. (In the wild, they would settle at two weeks of age, prior to the deepening of the orange hue). Once individuals attain a certain hue, it seems that color development can be halted, but not reversed. The transfer also involved changes in lighting, tank background, and diet, factors known to strongly affect coloration. Our results show a uniform shift in orange hue and saturation across social groups, suggesting that these confounding factors might have dominated changes in hue.

For transparency, we report the color data in the Supplementary Materials, but we caution against drawing any strong conclusions. In the revised manuscript, we will recommend that future work include a targeted experiment to robustly test for the effect of the adoption of social roles on coloration or the effect of coloration on the adoption of social roles.

(6) The Discussion is sometimes difficult to follow. The authors may want to consider including a conceptual graphic that integrates the different aspects of growth and satiety regulation, etc., into a work-in-progress model of sorts, which would also facilitate clearer hypotheses for future research.

Thank you for flagging that parts of the Discussion are a bit difficult to follow. In the revised manuscript, we will work to improve readability of the Discussion. We also appreciate the suggestion of including a conceptual schematic. We will consider whether adding such a graphic will add value to this manuscript or future manuscripts.

Reviewer #2 (Public review):

In this manuscript, the authors test growth, behavior, and gene expression in pairs of clownfish as they establish social dominance hierarchies, examining patterns of gene expression in these pairs after dominance has been established. The authors show solid evidence that emerging dominant clownfish show increased growth, aggression, and food consumption compared to their submissive or solitary counterparts, eventually adopting distinct gene expression profiles.

Major Comments:

(1) The Introduction is comprehensive, but it could be condensed. Likewise, the discussion could be condensed. There is considerable redundancy between the methods, the results,and the legend in Figure 1. The authors should consolidate and remove the redundancy.

Thank you for flagging that parts of the manuscript could be condensed, we will work on this as we revise the manuscript.

(2) For Figure 3, the authors are showing PC2 and PC3; why is PC1 not shown? There is so much overlap between the three groups in PC2 vs PC3; it seems unlikely that researchers could conclusively identify any individual as belonging to a group based on the expression profile. The ovals shown do not capture all the points within each of the groups, and particularly the grey S oval seems misaligned with the datapoints shown.

We understand the concern raised by the reviewer about the overlap among points in the PCA. We have explored PC1-PC3 and found that PC2 and PC3 showed the clearest, statistically significant clustering by social position, while PC1 did not capture any variation due to social position. We have explored whether other factors might be masking differences, such as genetic relatedness, tank effects, total read count per sample, and found that none of these factors explained sample clustering. Regarding the ellipses shown around the points, they were not intended to capture all points, but rather they show the estimated 95% multivariate t-distribution for that given social group. We will make sure this is clearly explained in the figure legend, and Methods section. In addition, in the revised version, we will show PC1 and PC2, and PC1 and PC3, in the Supplements for transparency.

(3) The authors indicate that the 15 replicates exhibiting the greatest size difference between P1 and P2 were selected for gene profiling. Does this mean that each of the P1and P2 were pairs with each other? Have the authors tried examining the gene expression patterns in a paired manner? E.g., for the pairs that showed the greatest size differences,do they also show the greatest differences in gene expression? Do the P1s show the most extreme differences from P2s that also show the most extreme P2 differences? Perhaps lines on Figure 3A connecting datapoints from the P1 and P2 pairs would be informative.

Yes, “15 replicates exhibiting the greatest size difference between P1 and P2 were selected for gene profiling” refers to pairs of P1 and P2, we will make sure this is clearly stated in the revised Methods. Yes, we have explored gene expression data considering the size difference between pairs, and found that it showed no clear differences in gene expression patterns (see earlier response to Reviewer #1). We will consider including these figures in the Supplementary Materials document, as well as adding a version of Figure 3A that clearly shows information on pairs, as suggested by the reviewer.

(4) For the specific target pathways that are up- and downregulated in the different backgrounds, I recommend that the authors include boxplots (or heatmaps) showing the actual expression values for these targets. Figure 6 shows a heatmap for appetite-related genes, and it would be great to see a similar graph for the metabolism and glycolytic genes; it would also be informative to see similar graphs for hormonal and sexual maturation pathways as well.

We have explored genes across a broad set of metabolic pathways (glycolysis, TCA cycle, lactic fermentation, PDH complex, cholesterol biosynthesis, fatty-acid synthesis, and beta-oxidation) and show all metabolic genes that showed significant differential expression between P1, P2, and S in Figure 6. Overall, very few metabolism-associated genes were significantly differentially expressed, which is why we decided to combine appetite-regulation and metabolism-associated genes into a single figure (Figure 6). In the revised version, we will ensure that Figure 6 clearly shows the gene sets associated with appetite and metabolism.

We also examined hormonal pathways (glucocorticoid and thyroid signaling), but did not find genes in these pathways that were significantly differentially expressed. Finally, we would like to clarify that our samples consist of two-month-old juvenile individuals that are sexually immature —under ideal conditions, clown anemonefish can mature in one to two years, but they can also remain sexually immature for a decade or more (Buston & García, 2007) — which is why we did not observe distinct molecular signatures of sexual maturation. We recognize that the sentence at line 520 may be misleading, as we did not identify any gene expression signature that we could confidently associate with signs of sexual maturation. We will make sure that these are clearly stated in the revised version of the manuscript.

(5) Particularly given that there is a relatively small number of genes enriched in the different rank conditions, I did not understand the need to do the WGCNA module analysis. I thought that an analysis of GO terms across the dataset would have been more meaningful than the GO term analysis shown in Figure 4, which considers only genes assigned to the "brown WGCNA module". This should be simplified or clarified.

To clarify, GO enrichment analysis does not establish correlations with traits, it only describes which functions or pathways are over-represented in a given gene set. That is why we began by using WGCNA to define gene sets (modules) that are correlated to phenotypes. Our primary rationale for WGCNA was to identify modules of co-expressed genes that show significant statistical correlation with the phenotypes of interest (social role: P1, P2, S; growth; and food intake). Pairwise differential expression analysis (Figure 3B) identified a few hundred significantly differentially expressed genes, but those tests treat genes independently and are not able to help us link coordinated changes of co-expressed genes to phenotypes of interest. Because WGCNA is blind to traits, it first identifies groups of co-expressed genes, which can help resolve gene expression patterns.

We therefore ran WGCNA on the rlog-transformed dataset to identify modules of co-expressed genes that show significant correlation with phenotypes of interests. For every module that showed such a correlation, we performed GO enrichment and carefully evaluated the resulting GO enrichment trees (see Supplementary Figs. 4–5). The brown module was highlighted in the main text because it was one of the modules with a significant correlation to growth, and its associated GO enrichment showed clear growth-related signals that were not identified in the pairwise differential expression analysis results.

(6) The authors say that they have identified coordinated changes in behaviors and the"underlying gene expression, leading to the emergence" of social roles. This is a little bit misleading, since the gene expression analysis occurred well after the behavioral and phenotypic differences emerged. Presumably, the hormonal and genetic shifts that actually caused the behavioral and phenotypic difference occurred during the weeks during which the experiment was underway, and earlier capture of the transcriptome would presumably reveal different patterns, and ones that would be considered more causative.The authors acknowledge this in 434-435, but it could be emphasized further.

We appreciate the reviewer raising this point. In the updated version of the manuscript, we will revise wording to convey that food intake, agonistic behavior, size and growth, and gene expression are all changing continuously, in response to each other and in response to social feedback. An underappreciated aspect of this system (and likely many other systems) is that phenotype (including transcriptome) influences the outcome of social interactions, and the outcome of social interactions influences the phenotype (including the transcriptome). Earlier capture of the transcriptome would reveal different levels of gene expression, reflecting the state of the system at that moment in time.

(7) The authors have measured a number of differences between the different dominance classes of fish. All these differences were measured relative to the other classes, but in my view, the Solitary group was the closest to a baseline control. So I'm not sure that it is fair to say that "P2 and S individuals showed consistent downregulation of these genes and pathways" (line 401). I encourage the authors to emphasize the differences in gene expression from the "perspective" of the P1 individuals compared to the baseline of P2and S individuals. Line 474 says that "P2 fish showed significant upregulation" of a number of pathways. It should be very clear what that is compared to (compared to P1, presumably?)

We agree with the reviewer that solitary individuals are the most intuitive baseline. Indeed, the experimental design included solitary fish because we expected they would serve as a useful control. Without social restraint, we anticipated they would show unrestricted growth, feeding, behavior, and associated gene‑expression patterns, similar to dominants.

We initially ran analyses using solitaries as the baseline, but after examining the results, which showed subordinate‑like characteristics for the solitary individuals, we concluded that solitary individuals are not an ecologically appropriate control for this context. Removing juveniles from a social context and housing them in isolation may be stressful and can affect physiology and behavior in ways that do not reflect a natural baseline. From a life‑history standpoint, solitary living is not the typical state for A. percula.

For these reasons, we reanalysed the dataset using the dominant (P1) as the reference to enable more ecologically meaningful comparisons (this choice was somewhat arbitrary, subordinates could also have been used as the reference). Given that gene expression is relative, we interpret results from both the dominant (P1) and subordinate (P2) perspectives in the Discussion to provide a complete view. We will clarify wording throughout the manuscript to make it clear that everything is relative (e.g., revising Line 474).

(8) Along the same lines, the authors say in line 514 that subordinates and solitaries strategically downregulate their growth. I'm not convinced that this is the case: I would consider this growth trajectory to be the default and the baseline. I would interpret that under certain social conditions, a P1 dominant pattern of growth, behavior, and gene expression is allowed to emerge.

We respectfully disagree with the idea that a single baseline/reference growth trajectory exists for any individual of this species. Growth of individuals is entirely social context-dependent: neither fast nor slow growth represents an inherent baseline. When two size‑matched juveniles meet and compete to establish dominance, accelerated growth is the expected trajectory. By contrast, juveniles joining an existing hierarchy are expected to exhibit reduced growth, which minimizes conflict and facilitates their social integration. Unlike species that show non socially mediated growth trajectories, clown anemonefish do not have a context‑independent growth rate, rather, individuals constantly readjust their growth according to their immediate social environment.

Therefore, growth trajectories must be considered from the perspective of all group members, because they emerge from interactions among individuals rather than reflecting an intrinsic baseline. In this study, we were interested in the establishment of dominance hierarchy and how individuals adjust their phenotypes during this process. By experimentally pairing size‑matched rivals, both individuals are initially expected to pursue the dominant trajectory, and thus neither individual represents a default state. Instead, the outcome reflects a social decision, after which both individuals reinforce their emerging social roles through coordinated changes.

Reviewer #3 (Public review):

Summary:

The authors tested the hypothesis that interactions among size- and age-matched rivals will lead to the emergence of social roles, accompanied by divergence in four aspects of individual phenotypes: growth, feeding behavior, fighting behaviors, and gene expression in clownfish.

Strengths:

The data on growth, feeding rate, and fighting behaviors support the authors' claims.

Thank you for the positive feedback!

Weaknesses:

Gene analysis conducted in this study is not sufficient to clarify how the relevant genes actually regulate growth and behavior.

The information obtained from whole-body gene expression analysis is very limited.Various gene expression is associated with the regulation of fighting behaviors, food intake, growth, and metabolism, and these genes are regulated differently across tissues,even within a single individual. Gene expression analysis should be performed separately for each tissue.

We understand the reviewer’s concern about whole‑body transcriptomes and agree that tissue‑specific sampling would provide greater resolution of the mechanisms linking gene expression to growth, agonistic behaviors, and food intake. For this initial study, however, we deliberately chose whole‑body samples to capture a broad, unbiased view of gene expression differences while keeping sequencing costs and sample requirements manageable. We explicitly acknowledge the resulting interpretational limits in the Discussion (lines 464; 529–533), and suggest in the last paragraph that the patterns reported here should be used to build on in future studies exploring targeted, tissue‑specific hypotheses.

Clownfish undergo sex change depending on social status and body size, as the authors mention in the manuscript. Numerous gene expressions are affected by sex change. It is unclear how this issue was addressed.

We thank the reviewer for raising this point. Sex change and sexual maturation can indeed drive major transcriptional shifts in clown anemonefish, but our experiment did not encompass such a life‑history transition. All individuals in this experiment were juveniles (≈1 month old at the start, ≈2 months old at the end) and were sexually immature at these ages. Clown anemonefish reach sexual maturation around one to two years under ideal conditions, can delay sexual maturation for years under normal conditions (Buston & García, 2007), and sex change in the genus Amphiprion is known to take over ~5 months (Moyer & Nakazono, 1978). Accordingly, individuals in this study were not sexually mature, and sex change was not biologically plausible over the five-week experimental period of our study. We recognize that the sentence at line 520 may be misleading, as we did not identify any gene expression signature that we could confidently associate with signs of sexual maturation. We will make sure that it is clearly stated that the fish in this study were sexually immature in the revised version.

References:

Buston, P. (2003). Forcible eviction and prevention of recruitment in the clown anemonefish. Behavioral Ecology, 14(4), 576–582. https://doi.org/10.1093/beheco/arg036

Buston, P. M., & García, M. B. (2007). An extraordinary life span estimate for the clown anemonefish Amphiprion percula. Journal of Fish Biology, 70(6), 1710–1719. https://doi.org/10.1111/j.1095-8649.2007.01445.x

Buston, P., & Clutton-Brock, Tim. (2022). Strategic growth in social vertebrates (WITH REVIEWER COMMENTS). Trends in Ecology & Evolution, 37(8), 694–705. https://doi.org/10.1016/j.tree.2022.03.010

Dengler-Crish, C. M., & Catania, K. C. (2007). Phenotypic plasticity in female naked mole-rats after removal from reproductive suppression. THE JOURNAL OF EXPERIMENTAL BIOLOGY.

Heg, D, Bender, N, & Hamilton, I. (2004). Strategic growth decisions in helper cichlids. Proceedings of the Royal Society of London. Series B: Biological Sciences, 271(suppl_6). https://doi.org/10.1098/rsbl.2004.0232

Huchard, E, English, S, Bell, M B. V., Thavarajah, N, & Clutton-Brock, T. (2016). Competitive growth in a cooperative mammal. Nature, 533(7604), 532–534. https://doi.org/10.1038/nature17986

Johnston, R A., Vullioud, P, Thorley, J, Kirveslahti, H., Shen, L., Mukherjee, S., Karner, C. M., Clutton-Brock, T, & Tung, J (2021). Morphological and genomic shifts in mole-rat ‘queens’ increase fecundity but reduce skeletal integrity. eLife, 10, e65760. https://doi.org/10.7554/eLife.65760

Moyer, J. T., & Nakazono, A. (1978). Protandrous Hermaphroditism in Six Species of the Anemonefish Genus Amphiprion in Japan (No. 2). The Ichthyological Society of Japan. https://doi.org/10.11369/jji1950.25.101

Reed, C., Branconi, R., Majoris, J., Johnson, C., & Buston, P. (2019). Competitive growth in a social fish. Biology Letters, 15(2), 20180737. https://doi.org/10.1098/rsbl.2018.0737

Thorley, J, Katlein, N, Goddard, K, Zöttl, M, & Clutton-Brock, T. (2018). Reproduction triggers adaptive increases in body size in female mole-rats. Proceedings of the Royal Society B: Biological Sciences, 285(1880), 20180897. https://doi.org/10.1098/rspb.2018.0897

Van Schaik, C P., & Van Hooff, J A. R. A. M. (1996). Toward an understanding of the orangutan’s social system. In Linda F. Marchant, Toshisada Nishida, & William C. McGrew (Eds.), Great Ape Societies (pp. 3–15). Cambridge University Press. https://doi.org/10.1017/CBO9780511752414.003

Walker, S P. W., & McCormick, M I. (2009). Sexual selection explains sex-specific growth plasticity and positive allometry for sexual size dimorphism in a reef fish. Proceedings of the Royal Society B: Biological Sciences, 276(1671), 3335–3343. https://doi.org/10.1098/rspb.2009.0767

Wong, M. Y. L., Buston, P. M., Munday, Philip L., & Jones, Geoffrey P. (2007). The threat of punishment enforces peaceful cooperation and stabilizes queues in a coral-reef fish. Proceedings of the Royal Society B: Biological Sciences, 274(1613), 1093–1099. https://doi.org/10.1098/rspb.2006.0284

Author response:

The following is the authors’ response to the previous reviews

Public Reviews:

Reviewer #1 (Public review):

Summary:

In this paper, the authors investigate the effects of Miro1 on VSMC biology after injury. Using conditional knockout animals, they provide the important observation that Miro1 is required for neointima formation. They also confirm that Miro1 is expressed in human coronary arteries. Specifically, in conditions of coronary diseases, it is localized in both media and neointima and, in atherosclerotic plaque, Miro1 is expressed in proliferating cells.

However, the role of Miro1 in VSMC in CV diseases is poorly studied and the data available are limited; therefore, the authors decided to deepen this aspect. The evidence that Miro-/- VSMCs show impaired proliferation and an arrest in S phase is solid and further sustained by restoring Miro1 to control levels, normalizing proliferation. Miro1 also affects mitochondrial distribution, which is strikingly changed after Miro1 deletion. Both effects are associated with impaired energy metabolism due to the ability of Miro1 to participate in MICOS/MIB complex assembly, influencing mitochondrial cristae folding. Interestingly, the authors also show the interaction of Miro1 with NDUFA9, globally affecting super complex 2 assembly and complex I activity.<br /> Finally, these important findings also apply to human cells and can be partially replicated using a pharmacological approach, proposing Miro1 as a target for vasoproliferative diseases.

Strengths:

The discovery of Miro1 relevance in neointima information is compelling, as well as the evidence in VSMC that MIRO1 loss impairs mitochondrial cristae formation, expanding observations previously obtained in embryonic fibroblasts.

The identification of MIRO1 interaction with NDUFA9 is novel and adds value to this paper. Similarly, the findings that VSMC proliferation requires mitochondrial ATP support the new idea that these cells do not rely mostly on glycolysis.

The revised manuscript includes additional data supporting mitochondrial bioenergetic impairment in MIRO1 knockout VSMCs. Measurements of oxygen consumption rate (OCR), along with Complex I (ETC-CI) and Complex V activity, have been added and analyzed across multiple experimental conditions. Collectively, these findings provide a more comprehensive characterization of the mitochondrial functional state. Following revision, the association between MIRO1 deficiency and impaired Complex I activity is more robust.

Although the precise molecular mechanism of action remains to be fully elucidated, in this updated version, experiments using a MIRO1 reducing agent are presented with improved clarity

Although some limitations remain, the authors have addressed nearly all the concerns raised, and the manuscript has substantially improved

Weaknesses:

Figure 6: The authors do not address the concern regarding the cristae shape; however, characterization of the cristae phenotype with MIRO1 ΔTM would have strengthened the mechanistic link between MIRO1 and the MIB/MICOS complex

Although the authors clarified their reasoning, they did not explore in vivo validation of key biochemical findings, which represents a limitation of the current study. While their justification is acknowledged, at least a preliminary exploratory effort could have been evaluated to reinforce the translational relevance of the study.

Finally, in line with the explanations outlined in the rebuttal, the Discussion section should mention the limits of MIRO1 reducer treatment.

Reviewer #2 (Public review):

Summary:

This study identifies the outer‑mitochondrial GTPase MIRO1 as a central regulator of vascular smooth muscle cell (VSMC) proliferation and neointima formation after carotid injury in vivo and PDGF-stimulation ex vivo. Using smooth muscle-specific knockout male mice, complementary in vitro murine and human VSMC cell models, and analyses of mitochondrial positioning, cristae architecture and respirometry, the authors provide solid evidence that MIRO1 couples mitochondrial motility with ATP production to meet the energetic demands of the G1/S cell cycle transition. However, a component of the metabolic analyses are suboptimal and would benefit from more robust methodologies. The work is valuable because it links mitochondrial dynamics to vascular remodelling and suggests MIRO1 as a therapeutic target for vasoproliferative diseases, although whether pharmacological targeting of MIRO1 in vivo can effectively reduce neointima after carotid injury has not been explored. This paper will be of interest to those working on VSMCs and mitochondrial biology.

Strengths:

The strength of the study lies in its comprehensive approach assessing the role of MIRO1 in VSMC proliferation in vivo, ex vivo and importantly in human cells. The subject provides mechanistic links between MIRO1-mediated regulation of mitochondrial mobility and optimal respiratory chain function to cell cycle progression and proliferation. Finally, the findings are potentially clinically relevant given the presence of MIRO1 in human atherosclerotic plaques and the available small molecule MIRO1.

Weaknesses:

(1) High-resolution respirometry (Oroboros) to determine mitochondrial ETC activity in permeabilized VSMCs would be informative.

(2) Therapeutic targeting of MIRO1 failed to prevent neointima formation, however, the technical difficulties of such an experiment is appreciated.

Reviewer #3 (Public review):

Summary:

This study addresses the role of MIRO1 in vascular smooth muscle cell proliferation, proposing a link between MIRO1 loss and altered growth due to disrupted mitochondrial dynamics and function. While the findings are useful for understanding the importance of mitochondrial positioning and function in this specific cell type, the main bioenergetic and mechanistic claims are not strongly supported.

Strengths:

This study focuses on an important regulatory protein, MIRO1, and its role in vascular smooth muscle cell (VSMC) proliferation, a relatively underexplored context.

This study explores the link between smooth muscle cell growth, mitochondrial dynamics, and bioenergetics, which is a significant area for both basic and translational biology.

The use of both in vivo and in vitro systems provides a useful experimental framework to interrogate MIRO1 function in this context.

Weaknesses:

The proposed link between MIRO1 and respiratory supercomplex biogenesis or function is not clearly defined.

Completeness and integration of mitochondrial assays is marginal, undermining the strength of the conclusions regarding oxidative phosphorylation.

We thank the reviewers for their thoughtful and constructive feedback. We appreciate their recognition of our work’s value and the improvements made in this revised version.

We are particularly grateful to Reviewer 3 for their detailed and insightful comments, which identified errors we (and other reviewers) had unfortunately overlooked. To address these concerns and ensure the manuscript meets the high standards of clarity and rigor we aim for, we have made additional corrections and refinements.

As part of this process, we conducted a thorough review of the original source files. This was especially important given that the project spanned from 2018 to 2025, and many co-authors have since left their previous positions.

We appreciate the opportunity to resubmit this manuscript and are confident that these updates fully address the concerns raised by the reviewer and the editorial team.

Reviewer #3 (Recommendations for the authors):

(1) I still do not see the data in WB 2G reflecting the quantification in 2H and 2I. Moreover, the authors state they performed 1 additional experiment, but it appears not to have been included in the analysis of 2H and 2I since the graphs remained the same from the last version of the manuscript.

We apologize for this oversight. The additional experiment has now been incorporated into the analysis for Figures 2H and 2I, and the graphs have been updated accordingly. While we had uploaded the new blot, we inadvertently forgot to update the analysis graphs. Thank you for bringing this to our attention.

(2) The authors talk several times about "supercomplexes 1 and 2" without testing their precise composition (there is a ton of literature about SC species in several mouse cell types, and separate BN-PAGE immunoblotting of individual MRC complexes would precisely define them in this context)

We agree with the reviewer that this is an important point. However, structural differences between supercomplexes were outside the scope of this paper, and we did not perform such analyses. That said, examining the precise composition of supercomplexes could be a valuable direction for future work.

(3) Steady-state levels of MRC subunits do not match the observations from BN-PAGE results. That might be potentially interpreted and explained by the possible accumulation of intermediates but this is not explored.

We appreciate the reviewer’s observation. There is indeed a strong possibility that differences in the expression of structural components of mitochondrial complexes exist between WT and Miro1 -/- cells. However, in this study, we chose to focus on assessing potential differences in the enzymatic activities of the complexes rather than examining their structural composition. Exploring the accumulation of intermediates and structural differences could be an interesting avenue for future investigations.

(4) Citrate synthase normalization of kinetic enzyme activities is claimed, yet it is not shown in any graph and no description of the method is provided.

We sincerely thank the reviewer for pointing out this discrepancy. Upon careful review, we realized that our statement regarding citrate synthase normalization of kinetic enzyme activities in the last revised version was made in error. This was a miscommunication between co-authors, and we did not perform citrate synthase normalization. Instead, the normalization was performed against protein concentration, determined by the BCA assay as described in the manuscript. We regret this oversight and appreciate the opportunity to clarify this.

(5) Complex I activity is still wrongfully described as NADPH oxidation in the methods

We corrected this error.

(6) The authors state 'Thank you for this comment. We believe this is due to a technical issue. Complex IV can be challenging to detect consistently, as its visibility is highly dependent on sample preparation conditions. In this specific case, we suspect that the buffer used during the isolation process may have influenced the detection of Complex IV'. I do not understand this, I find this justification insufficient and not substantiated by any experimental evidence. What buffer has been used for isolation? There are hundreds of protocols for isolation of intact mitochondria and MRC complexes. Also, DDM and digitonin are the gold-standard detergents for MRC complexes isolation and separation via BN-PAGE.

We thank the reviewer for raising this important point. We have revised the response to clarify the exact experimental conditions and to provide supporting data.

For BN-PAGE, mitochondrial fractions purified from cultured VSMCs or aortic tissue were prepared using a standard protocol (now explicitly detailed in the Methods). Briefly, mitochondria were resuspended in 6-aminocaproic acid (ACA) buffer containing 750 mM ACA, 50 mM Bis-Tris (pH 7.0), and protease inhibitors. Forty micrograms of mitochondrial protein were solubilized with 1.5% digitonin, using a final detergent-to-protein ratio of 8:1, and incubated on ice for 20 minutes prior to clarification by centrifugation at 16,000 g for 30 minutes at 4°C. Thus, consistent with established standards, digitonin—one of the gold-standard detergents for MRC complex solubilization and BN-PAGE—was used throughout.

Despite using these widely accepted conditions, we found that detection of fully assembled Complex IV by BN-PAGE was inconsistent, a limitation that has been reported by others and is known to be sensitive to mitochondrial source, tissue type, and solubilization efficiency. To address this directly and avoid over-interpretation, we assessed Complex IV integrity by examining core subunits. As shown in Figure 6—figure supplement 1 (panels B and C), expression levels of MTCO1 and MTCO2, both essential core components of Complex IV, do not differ significantly between WT and Miro1-/- cells, supporting the conclusion that Complex IV abundance is not altered.

We have revised the manuscript to clarify these methodological details and to explicitly state that conclusions regarding Complex IV are based on subunit analysis rather than BN-PAGE visualization alone.

(7) Complex V IGA also does not seem to reflect its quantification.

Thank you for highlighting this concern. To address it, we will include the numerical data alongside the figures to ensure clarity and alignment with our findings. We hope this will provide a more comprehensive understanding and resolve any ambiguity.

(8) Figure 6 supplement 1, the authors state 'we concentrated on ETC1 and 5 and performed experiments in cells after expression of MIRO1 WT and MIRO1 mutants'. I do not understand, what background is being used? what mutants are being expressed? all the figures refer to Miro1 -/- which is, according to standard genetic nomenclature, a loss-of-function allele (KO).

Thank you for your comment. To clarify, we first infected MIRO1fl/fl VSMCs with an adenovirus expressing the DNA recombinase Cre or a control adenovirus. Cells infected with the adenovirus expressing Cre are labeled as MIRO1-/- cells. In these MIRO1-/- cells, we then introduced MIRO1 wild type (WT) and MIRO1 mutants via adenoviral expression.

The mutants include one lacking the transmembrane domain (MIRO1-ΔTM), and another in which the two EF hands of MIRO1 were point-mutated (MIRO1-KK). MIRO1-WT is denoted as Ad WT, the mutant MIRO1-KK as Ad KK, and MIRO1-ΔTM as Ad ΔTM in the figures. We hope this explanation clarifies the experimental background and nomenclature used.

(9) Figure 6 supplement 1B, no normalization is provided (e.g. VDAC, TOM20 etc.). Interestingly, VDAC is then used to normalize the data in C-D-E-F-G. Also, why is MIRO1 detected in lane 4? Is the mutant stable or not? There is zero signal in A.

Thank you very much for pointing out that the immunoblot for VDAC1 was missing in Figure 6—Supplement 1B. This figure has been reviewed several times, and unfortunately, this error was not detected. We sincerely apologize for this oversight. We have now revised the figure to include the immunoblot for VDAC1 to address this issue.

Regarding the detection of MIRO1 in lane 4, we confirm that the "mutant" is not stable. To generate MIRO1 knockout cells, aortic smooth muscle cells from MIRO1fl/fl mice were isolated and cultured, followed by infection with an adenovirus expressing Cre. As these are primary cells and the deletion was induced by Cre expression, the recombination efficiency can vary, which is reflected in the variability observed in lanes 2 and 4 of the immunoblot.

(10) Why are COX4 levels so low in the 2nd replicate in 7A? the authors 'We also performed anti-VDAC immunoblots on the same membranes as alternative loading control (see image below)'. I could not find the image.

Thank you for your comment. The second pair of samples in Figure 7A is from a different preparation of mitochondria. In our experimental design, a control sample and a MIRO1 knockdown sample were processed side by side and run next to each other on the immunoblot.

Regarding the anti-VDAC immunoblot, the image was included in our response to reviewers during the previous revision, as we did not believe it altered the message conveyed by the COX4 blot. However, to ensure clarity and address your concern, we have now included the anti-VDAC immunoblot directly in the figure. We hope this addition resolves any ambiguity and provides further confidence in the data presented.

(11) The proposed interaction between MIRO1 and NDUFA9 is very difficult to reconcile, as the two proteins reside in distinct mitochondrial compartments. MIRO1 is anchored to the outer mitochondrial membrane (OMM), with its functional domains facing the cytosol, whereas NDUFA9 is a matrix-facing accessory subunit of mitochondrial Complex I, positioned at the interface between the N- and Q-modules.

We appreciate the reviewer’s comment and agree that MIRO1 and NDUFA9 occupy distinct mitochondrial compartments. MIRO1 is anchored to the outer mitochondrial membrane with cytosol-facing domains, whereas NDUFA9 is a matrix-facing accessory subunit of Complex I at the N/Q-module interface.

Our data do not suggest a stable, constitutive interaction within intact mitochondria. Rather, the observed association likely reflects an indirect, transient, or context-dependent interaction, potentially occurring during mitochondrial stress, remodeling, or turnover. Such associations may be mediated by multi-protein complexes spanning mitochondrial membranes, dynamic contact sites, or post-lysis interactions detected under experimental conditions. Increasing evidence supports functional coupling between outer mitochondrial membrane proteins and inner membrane or matrix pathways without direct physical binding.

Additional comments:

(12) All the raw data should be provided to the readers (uncropped and annotated WB, IHC images, numerical data with statistics applied).

We agree with the reviewer and appreciate the emphasis on transparency. In accordance with eLife submission requirements, we have provided all raw data. The Source Data files associated with each figure now include uncropped and annotated immunoblots, as well as the numerical source data for all quantified analyses.

During the compilation of these materials, we were unable to locate the original source files for Figure 2A. The control experiment depicted in the previous version, which demonstrates in vitro recombination, was performed in 2018. However, this experiment was repeated several times throughout the project. Therefore, to ensure the manuscript remains complete, we have replaced this panel with a representative immunoblot from a similar experiment. Additionally, during our review, we discovered a labeling error in Figure 3D and G. We have corrected these figures to ensure accuracy.

All source files have been provided and carefully labeled to facilitate independent evaluation.

Reviewer #1 (Public review):

Summary:

In this work, the authors investigate the mechanisms of low-frequency synaptic depression at cerebellar parallel fiber to interneuron synapses using unitary recordings that allow direct quantification of synaptic vesicle release. They show that sparse stimulation can induce robust synaptic depression even in the absence of substantial vesicle consumption, and that this depressed state is rapidly reversed when stimulation frequency is increased. To account for these observations, the authors propose a model in which low-frequency depression reflects a redistribution of vesicles within the readily releasable pool, in particular, a reduction in docking site occupancy due to vesicle undocking.

Strengths:

I found the experimental work to be of high quality throughout. The use of simple synapse recordings to count individual vesicle release events is particularly powerful in this context and allows questions to be addressed that are difficult to approach with more conventional approaches. The demonstration that low-frequency depression can occur independently of prior vesicle release, together with the rapid recovery observed during high-frequency stimulation, places strong constraints on possible underlying mechanisms and represents a clear strength of the study.

The modeling framework is clearly laid out and helps organize a broad set of observations across stimulation frequencies. Several of the experimental tests appear well-motivated by the model, including the recovery train experiments, the analysis of failures, and the use of doublet stimulation. Taken together, the data provide a coherent phenomenological description of low-frequency depression and its relationship to vesicle availability within the readily releasable pool.

Weaknesses:

While the experimental results are strong, the manuscript would benefit from rebalancing the strength of the mechanistic conclusions drawn from the modeling in light of its limitations. The framework is clearly useful and provides a coherent interpretation of the data, but it is not uniquely constrained by the experimental observations, and alternative models or interpretations could plausibly account for the findings. The use of different model regimes concatenated across time, with substantially different parameter values, highlights the abstract nature of the approach. For these reasons, the model seems best presented as one plausible explanatory framework rather than a definitive biological mechanism. Clarifying the distinction between data-driven observations and model-based inferences would help readers assess which conclusions are strongly supported and which remain more speculative.

The interpretation of the Ca2+-related experiments would benefit from more cautious wording. The absence of detectable changes in presynaptic Ca2+ signals does not exclude more localized or subtle Ca2+-dependent mechanisms, and conclusions regarding Ca2+ independence should therefore be framed accordingly. In addition, while low-frequency depression is still observed at reduced extracellular Ca2+, these experiments appear less diagnostic of the specific model-derived mechanism emphasized elsewhere in the manuscript - namely, a selective reduction in docking-site occupancy - and should be discussed with appropriate qualification in the text.

Major points:

(1) Clarify and qualify mechanistic claims derived from the model.

Throughout the manuscript, changes in model parameters are at times described as if they directly reflected underlying physiological mechanisms. As a result, the conceptual distinction between experimentally observed phenomena, model-derived variables, and biological interpretation is not always clear. Several conclusions in the Results and Discussion are phrased as mechanistic statements, although they rest on assumptions intrinsic to the modeling framework. The authors should systematically review the text and explicitly distinguish between (i) experimentally observed changes in synaptic responses and (ii) inferences about vesicle docking states or transitions within the model.

In particular, statements implying that vesicle undocking is the mechanism underlying low-frequency depression should be rephrased to reflect that this is an interpretation within the proposed framework rather than a uniquely demonstrated biological process. For example, statements such as "Low-frequency depression is caused by synaptic vesicle undocking" should be replaced with formulations such as "Within the framework of our model, low-frequency depression is accounted for by a redistribution of synaptic vesicles away from docking sites" or "Our results are consistent with a model in which changes in vesicle docking-state occupancy contribute to low-frequency depression."

A particularly problematic example is the statement that "these experiments further confirm that LFD only involves a decrease in δ, without accompanying changes in ρ or IP size." Here, an experimentally defined phenomenon (LFD) is directly equated with changes in model-derived variables. Such statements should be revised to make clear that δ, ρ, and IP size are inferred quantities within the model, and that the experimental data are interpreted through this framework rather than directly confirming changes in these parameters. Similarly, over-generalizing statements such as "Undocking therefore represents the key mechanism controlling short-term depression across stimulation frequencies" should be softened to reflect that this conclusion emerges from the model rather than from direct experimental evidence.

(2) Address the biological interpretation of time-dependent model regimes.

The model relies on distinct parameter regimes applied at different time points, with some transitions effectively suppressed in certain regimes. While this approach captures the data well, its biological interpretation remains unclear. The authors should either (i) expand the discussion to outline plausible biological processes that could give rise to such regime changes (for example, calcium-dependent modulation of transition rates or activity-dependent changes in vesicle state stability), or (ii) more explicitly frame this aspect of the model as a descriptive abstraction rather than a mechanistic proposal. This further underscores the need to clearly separate the descriptive role of the model from claims about underlying biological mechanisms.

(3) Reframe conclusions drawn from calcium-related experiments.

The calcium imaging data demonstrate no detectable changes in the measured presynaptic calcium signals under the tested conditions, but they do not rule out that calcium signals contribute in ways undetectable by the assay. Conclusions should therefore be revised to reflect this limitation, avoiding statements that exclude a role for calcium-dependent mechanisms. Wording such as "we did not detect evidence for..." would be more appropriate than conclusions implying the absence of an effect.

Similarly, while low-frequency depression is still observed at reduced extracellular calcium (1.5 mM Ca²⁺), the specific mechanistic signature emphasized elsewhere in the manuscript - namely a selectively reduced first response during a high-frequency recovery train - is no longer apparent. These experiments should therefore be discussed as consistent with the proposed framework, but not as providing independent support for a selective reduction in docking-site occupancy. Explicitly acknowledging this limitation would improve clarity and avoid over-interpreting these data.

(4) Soften interpretations based on non-significant comparisons.

In several places, comparisons that do not reach statistical significance are used to argue for equivalence between conditions (for example, comparisons involving failure versus non-failure trials or different LFD conditions). These conclusions should be revised to emphasize the limits of statistical power and framed as a lack of evidence for a difference rather than evidence of independence.

Reviewer #3 (Public review):

Summary:

The manuscript builds on the observation that, at some synapses, low-frequency stimulation causes synaptic depression, which can be reversed by subsequent high-frequency stimulation. Such low-frequency depression (LFD) cannot be easily explained by the depletion of a single vesicle pool. Here, Silva and colleagues propose a model of activity-dependent vesicle trafficking to explain LFD at synapses between cerebellar granule cells and molecular layer interneurons.

Strengths:

Overall, LFD is interesting and worthy of examination, and the authors provide new experimental results that are of the high quality expected from this group.

Weaknesses:

The study proposes a novel model of vesicle trafficking that is not explained by known biological mechanisms, and the manuscript does not adequately compare or discuss alternative models.

I have several concerns about how the authors interpret the data. First, the manuscript's primary conceptual advance is the idea that LFD involves vesicle undocking, rather than depletion. However, most experiments were performed under conditions that promote vesicle depletion (3 mM extracellular Ca2+). When experiments were repeated in physiological Ca2+, there appeared to be little or no LFD (stats are not provided). Second, the RS/DS/DU/undocking model, though not outside the realm of possibility, is not readily explained by known mechanisms and is only loosely supported by experimental findings. Third, when simulating LFD, the authors do not compare alternative models and use inappropriate language to imply that a model fit represents the truth (e.g., "the finding of identical experimental and simulated values confirms that the undocking mechanism accounts for LFD"). Finally, the model is presented in an overly complicated manner. The sheer amount of terms and nomenclature makes the manuscript confusing and difficult to read. Overall, the manuscript would benefit from added experiments and more statistics, a better justification and evaluation of the model, and more nuanced language.

Major concerns:

(1) Most experiments were performed under conditions that exacerbate depletion

In order to attribute LFD to vesicle undocking rather than depletion, it is important to show LFD under conditions where depletion is minimal. As mentioned above, the authors only report significant LFD in elevated extracellular Ca2+. In a small number of experiments performed in more physiological Ca2+ (1.5 mM), there is no depression after a single stimulus, and it is not clear that there was statistically significant depression during a low-frequency train. Several studies cited in support of LFD share this problem:

• Abrahamsson et al., (2007) recorded from Schaffer collaterals in 4 mM Ca, 3-4X physiological Ca2+.

• Doussau et al., (2010) recorded from aplysia synapses in 3X Ca compared to seawater.

• Rudolph et al., (2011) is cited as an example of LFD. However, this study performed experiments at high release probability cerebellar climbing fibers, and reported depression that increased monotonically with

stimulation frequency, so it does not resemble the phenomenon studied in this paper. Lin et al., (2022) also largely describe monotonic depression at the calyx.

The authors note that their results differ from those of Atluri and Regehr, but do not mention that a possible reason for the difference is the increased release probability in their experiments.

The authors should provide statistics for the data obtained in 1.5 mM Ca, and discuss why LFD is increased in conditions that also elevate vesicle release probability.

(2) Lack of biological mechanisms supporting the model

The model is presented without compelling biological support. The evidence in support of vesicle undocking comes from experiments by the Watanabe lab, which showed fewer-than-expected docked vesicles under EM when cultured synapses were stimulated immediately prior to high-pressure freezing. Kusick et al were careful to note that these vesicles may have been lost to fusion.

The putative undocking Kusick describes is immediate (< 5 ms after stimulation), and was not shown to be Ca2+ sensitive. This manuscript describes "calcium-dependent undocking" that proceeds from 10 ms - 200 ms. Multiple studies from the Watanabe lab show that a single stimulus lowers the number of docked vesicles, and subsequently, there is a transient redocking of vesicles that can be blocked by EGTA or Syt7 knockout.

I also question the rationale for the authors' model that 2 vesicles are coupled in series to a single release site. Previous papers from this lab cited EM studies from frog and neuromuscular that showed filamentous connections between vesicles (do these synapses show LFD?). Here, the authors primarily cite their previous models to support their arguments. I encourage them to continue searching for ultrastructural evidence for 2-vesicle-docking-units and to cite such studies.

(3) Comparison to other vesicle models

The authors use overly assertive language to suggest that the model proves a mechanism. "Altogether, these results indicate that the slow phase of LFD ... reflects a δ decrease without significant changes in pr, in ρ or in IP size". Simulating data does not conclusively "indicate" the underlying mechanism, but the authors could state their data can be "explained by a model where..".

However, LFD does not require activity-dependent undocking. Instead, the phenomenon has been explained by high-release probability, paired with an activity-dependent increase in either docking or release probability (Chiu and Carter, 2024; Doussau et al., 2017). Does the new model do a better job of replicating some facet of the data? If multiple models can explain the same data, how can we determine which model is correct? The "Alternative Presynaptic Depression Mechanisms" should be expanded to discuss these issues.

Author response:

Public Reviews:

Reviewer #1 (Public review):

Summary:

In this work, the authors investigate the mechanisms of low-frequency synaptic depression at cerebellar parallel fiber to interneuron synapses using unitary recordings that allow direct quantification of synaptic vesicle release. They show that sparse stimulation can induce robust synaptic depression even in the absence of substantial vesicle consumption, and that this depressed state is rapidly reversed when stimulation frequency is increased. To account for these observations, the authors propose a model in which low-frequency depression reflects a redistribution of vesicles within the readily releasable pool, in particular, a reduction in docking site occupancy due to vesicle undocking.

Strengths:

I found the experimental work to be of high quality throughout. The use of simple synapse recordings to count individual vesicle release events is particularly powerful in this context and allows questions to be addressed that are difficult to approach with more conventional approaches. The demonstration that low-frequency depression can occur independently of prior vesicle release, together with the rapid recovery observed during high-frequency stimulation, places strong constraints on possible underlying mechanisms and represents a clear strength of the study.

The modelling framework is clearly laid out and helps organize a broad set of observations across stimulation frequencies. Several of the experimental tests appear well-motivated by the model, including the recovery train experiments, the analysis of failures, and the use of doublet stimulation. Taken together, the data provide a coherent phenomenological description of low-frequency depression and its relationship to vesicle availability within the readily releasable pool.

We thank the Reviewer for his positive assessment of our work.

Weaknesses:

While the experimental results are strong, the manuscript would benefit from rebalancing the strength of the mechanistic conclusions drawn from the modelling in light of its limitations. The framework is clearly useful and provides a coherent interpretation of the data, but it is not uniquely constrained by the experimental observations, and alternative models or interpretations could plausibly account for the findings. The use of different model regimes concatenated across time, with substantially different parameter values, highlights the abstract nature of the approach. For these reasons, the model seems best presented as one plausible explanatory framework rather than a definitive biological mechanism. Clarifying the distinction between data-driven observations and model-based inferences would help readers assess which conclusions are strongly supported and which remain more speculative.

The interpretation of the Ca²⁺-related experiments would benefit from more cautious wording. The absence of detectable changes in presynaptic Ca²⁺ signals does not exclude more localized or subtle Ca²⁺-dependent mechanisms, and conclusions regarding Ca²⁺ independence should therefore be framed accordingly. In addition, while low-frequency depression is still observed at reduced extracellular Ca²⁺, these experiments appear less diagnostic of the specific model-derived mechanism emphasized elsewhere in the manuscript - namely, a selective reduction in docking-site occupancy - and should be discussed with appropriate qualification in the text.

Concerning Ca²⁺ signals, the Reviewer is right. While we found no change in Ca²⁺ signalling apart from a slow Ca²⁺ accumulation during long trains at 1 Hz, the possibility of an undetected change cannot be excluded. We have added a word of caution in this direction on p. 11. Concerning the 1.5 mM Ca²⁺ experiments, the Reviewer presumably alludes to the first recovery train (yellow) point in Supplementary Fig. 2C. This is also the last point (s11) of the slow train at 0.5 Hz because no delay at all was interposed between the slow train and the recovery train. We have now included one more experiment (with a present total number n = 6), and we have corrected Fig. S2C accordingly. In the new version the depression measured for s4-s10 vs s1 during the 0.5 Hz trains is 0.69 +/- 0.05 (p = 0.00058, paired one-tail t-test). The ratio of the s1 value of the recovery train compared to control s1 is 0.83 +/- 0.08 (p = 0.028, paired one-tail t-test).

Major points:

(1) Clarify and qualify mechanistic claims derived from the model.

Throughout the manuscript, changes in model parameters are at times described as if they directly reflected underlying physiological mechanisms. As a result, the conceptual distinction between experimentally observed phenomena, model-derived variables, and biological interpretation is not always clear. Several conclusions in the Results and Discussion are phrased as mechanistic statements, although they rest on assumptions intrinsic to the modelling framework. The authors should systematically review the text and explicitly distinguish between (i) experimentally observed changes in synaptic responses and (ii) inferences about vesicle docking states or transitions within the model.

In particular, statements implying that vesicle undocking is the mechanism underlying low-frequency depression should be rephrased to reflect that this is an interpretation within the proposed framework rather than a uniquely demonstrated biological process. For example, statements such as "Low-frequency depression is caused by synaptic vesicle undocking" should be replaced with formulations such as "Within the framework of our model, low-frequency depression is accounted for by a redistribution of synaptic vesicles away from docking sites" or "Our results are consistent with a model in which changes in vesicle docking-state occupancy contribute to low-frequency depression."

A particularly problematic example is the statement that "these experiments further confirm that LFD only involves a decrease in δ, without accompanying changes in ρ or IP size." Here, an experimentally defined phenomenon (LFD) is directly equated with changes in model-derived variables. Such statements should be revised to make clear that δ, ρ, and IP size are inferred quantities within the model, and that the experimental data are interpreted through this framework rather than directly confirming changes in these parameters. Similarly, overgeneralizing statements such as "Undocking therefore represents the key mechanism controlling short-term depression across stimulation frequencies" should be softened to reflect that this conclusion emerges from the model rather than from direct experimental evidence.

As suggested, we clarify the distinction in the revised version between experimental data and modelling, and we refrain from making definitive statements on underlying cellular mechanisms.

(2) Address the biological interpretation of time-dependent model regimes.

The model relies on distinct parameter regimes applied at different time points, with some transitions effectively suppressed in certain regimes. While this approach captures the data well, its biological interpretation remains unclear. The authors should either (i) expand the discussion to outline plausible biological processes that could give rise to such regime changes (for example, calcium-dependent modulation of transition rates or activity-dependent changes in vesicle state stability), or (ii) more explicitly frame this aspect of the model as a descriptive abstraction rather than a mechanistic proposal. This further underscores the need to clearly separate the descriptive role of the model from claims about underlying biological mechanisms.

We thank the Reviewer for drawing our attention to this important point. Below 10 ms, rate constants are largely determined by the large amplitude, fast decaying Ca²⁺ signal occurring near voltage-dependent Ca²⁺ channels (‘Ca²⁺ nanodomain’). After 10 ms, the rate constants depend on the low amplitude, slowly decaying Ca²⁺ signals averaged over the entire varicosity (‘volume-averaged Ca²⁺’). We explain this better in the revised version (Materials and Methods, p. 21).

(3) Reframe conclusions drawn from calcium-related experiments.

The calcium imaging data demonstrate no detectable changes in the measured presynaptic calcium signals under the tested conditions, but they do not rule out that calcium signals contribute in ways undetectable by the assay. Conclusions should therefore be revised to reflect this limitation, avoiding statements that exclude a role for calcium-dependent mechanisms. Wording such as "we did not detect evidence for..." would be more appropriate than conclusions implying the absence of an effect.

Similarly, while low-frequency depression is still observed at reduced extracellular calcium (1.5 mM Ca²⁺), the specific mechanistic signature emphasized elsewhere in the manuscript - namely a selectively reduced first response during a high-frequency recovery train - is no longer apparent. These experiments should therefore be discussed as consistent with the proposed framework, but not as providing independent support for a selective reduction in docking-site occupancy. Explicitly acknowledging this limitation would improve clarity and avoid overinterpreting these data.

This has been discussed above (‘weaknesses’).

(4) Soften interpretations based on non-significant comparisons.

In several places, comparisons that do not reach statistical significance are used to argue for equivalence between conditions (for example, comparisons involving failure versus non-failure trials or different LFD conditions). These conclusions should be revised to emphasize the limits of statistical power and framed as a lack of evidence for a difference rather than evidence of independence.

We have attended this point in the revised version.

Reviewer #2 (Public review):

Summary:

Silva and co-workers exploit their previously established methods of analyzing release events at single parallel fiber to molecular layer interneuron synapses. They observed synaptic depression at low transmission frequencies (< 5 Hz), which rapidly recovers during high-frequency transmission. Analysis of the time course of low-frequency depression revealed an initial rapid and a slow linearly increasing time course. Strikingly, the initial depression occurred even in the absence of preceding release, arguing against vesicle depletion as the underlying mechanism.

Strengths:

The main strength of the study is the careful demonstration of an interesting synaptic phenomenon challenging the classical vesicle-centered interpretation of synaptic depression.

We thank the Reviewer for his positive assessment of our work.

Weaknesses:

No major weaknesses were identified by this reviewer.

The finding of release-independent synaptic depression is important and would have widespread implications. Therefore, some more analyses to increase the confidence in these findings could be performed.

My concern is whether rundown could explain the findings. If the rate of failures in s1 increases and at the same time the amplitude decreases during the experiments, an apparent depression in s2 could arise. The Supplementary Figure 5A addresses run-down, but the figure is not easy to understand, and, as far as I understood, it does not address the question of whether the release-independent depression could be caused by a rundown. To address this, the analysis of Figure 5 could be repeated by investigating the failure rate and amplitude separately or by analyzing the 1st and 2nd half of the recordings separately.

The Reviewer makes a very important point that had escaped our attention. If the responses were declining over the course of an experiment, near the end of the recordings, a high proportion of failures would be associated with a weak response to the second AP. This could distort the relation between initial failures and amount of LFD, perhaps to the point of indicating LFD after failures when there were none. As suggested by the Reviewer, we tested this possibility by examining the stability of the synaptic responses during experiments. We found a mean s₁ value of 0.87 ± 0.13 for the first half of the experiments used in Fig. 5, and of 1.10 ± 0.17 for the second half (p > 0.05, n = 10). This analysis shows that there was no rundown during these experiments. We show in Author response image 1 a plot of s1 as a function of the number of experiments. These plots do not suggest any artefactual correlation between failures, mean s1, and rundown.

Author response image 1.

Plot of s1 as a function of train number for the experiments of Fig. 5. In response to a request of Reviewer 2, this figure illustrates the evolution of s1 values as a function of train number for the experiments used to produce Figure 5. In each experiment, about 20 s1 values were obtained at two ISIs (either 10 ms and 500 ms, or 800 ms and 1600 ms). The figure shows two examples of s1 values as a function of train number (these values fluctuate widely between 0 and 3), and the average across cells and ISI values. There is no indication of a rundown of S1 values as a function of train number

Reviewer #3 (Public review):

Summary:

The manuscript builds on the observation that, at some synapses, low-frequency stimulation causes synaptic depression, which can be reversed by subsequent high-frequency stimulation. Such low-frequency depression (LFD) cannot be easily explained by the depletion of a single vesicle pool. Here, Silva and colleagues propose a model of activity-dependent vesicle trafficking to explain LFD at synapses between cerebellar granule cells and molecular layer interneurons.

Strengths:

Overall, LFD is interesting and worthy of examination, and the authors provide new experimental results that are of the high quality expected from this group.

Weaknesses:

The study proposes a novel model of vesicle trafficking that is not explained by known biological mechanisms, and the manuscript does not adequately compare or discuss alternative models.

I have several concerns about how the authors interpret the data. First, the manuscript's primary conceptual advance is the idea that LFD involves vesicle undocking, rather than depletion. However, most experiments were performed under conditions that promote vesicle depletion (3 mM extracellular Ca²⁺). When experiments were repeated in physiological Ca²⁺, there appeared to be little or no LFD (stats are not provided). Second, the RS/DS/DU/undocking model, though not outside the realm of possibility, is not readily explained by known mechanisms and is only loosely supported by experimental findings. Third, when simulating LFD, the authors do not compare alternative models and use inappropriate language to imply that a model fit represents the truth (e.g., "the finding of identical experimental and simulated values confirms that the undocking mechanism accounts for LFD"). Finally, the model is presented in an overly complicated manner. The sheer amount of terms and nomenclature makes the manuscript confusing and difficult to read. Overall, the manuscript would benefit from added experiments and more statistics, a better justification and evaluation of the model, and more nuanced language.

We respectfully disagree with these sweeping criticisms, as described in more detail below.

Major concerns:

(1) Most experiments were performed under conditions that exacerbate depletion

In order to attribute LFD to vesicle undocking rather than depletion, it is important to show LFD under conditions where depletion is minimal. As mentioned above, the authors only report significant LFD in elevated extracellular Ca²⁺. In a small number of experiments performed in more physiological Ca²⁺ (1.5 mM), there is no depression after a single stimulus, and it is not clear that there was statistically significant depression during a low-frequency train. Several studies cited in support of LFD share this problem:

- Abrahamsson et al., (2007) recorded from Schaffer collaterals in 4 mM Ca, 3-4X physiological Ca²⁺.

- Doussau et al., (2010) recorded from Aplysia synapses in 3X Ca compared to seawater.

- Rudolph et al., (2011) is cited as an example of LFD. However, this study performed experiments at high release probability cerebellar climbing fibers, and reported depression that increased monotonically with stimulation frequency, so it does not resemble the phenomenon studied in this paper. Lin et al., (2022) also largely describe monotonic depression at the calyx.

The Reviewer suggests that LFD may only occur under non-physiological conditions, if the release probability has been increased by artificially elevating the extracellular Ca²⁺. The implication is that LFD is at best a curiosity with little or no significance for brain signalling. We disagree with this point of view for several reasons.

Concerning the statement ‘In order to attribute LFD to vesicle undocking rather than depletion, it is important to show LFD under conditions where depletion is minimal’: This is the purpose of the analysis shown in Fig. 5.

The statement ‘the authors only report significant LFD in elevated extracellular Ca²⁺’ is inaccurate. Fig. S2C shows a clear LFD in 1.5 mM Ca²⁺, as acknowledged by Reviewer 1 (‘low-frequency depression is still observed at reduced extracellular Ca²⁺’). However, we failed to provide a p-value for the depression in the initial version of the paper (p = 0.004, n = 5, with this data set; paired t-test, one-tailed). In the revised version, we document the 1.5 mM results more extensively, including the incorporation of the results of an additional experiment, and an explicit statistical analysis of the data (p = 0.00058, n = 6; paired t-test, one-tailed).

Concerning the statement ‘there is no depression after a single stimulus’: We find that the onset kinetics of LFD is slower in 1.5 Ca²⁺ than in 3 Ca²⁺ (respectively 1.8 ISI and 0.51 ISI, Fig. 2C and Fig. S2C). This explains that the PPR is not significantly <1 in 1.5 Ca²⁺ without implying any weakening of extent of LFD at steady state.

As explained in the manuscript (p. 5), in a previous work, we developed a method to ascribe changes in SV pools, within the RS/DS model, with specific modifications of s1, s2 and s5-s8 during test 100 Hz trains (Tran et al., 2022). This method was developed in 3 mM Ca²⁺ conditions, and for this reason, we performed most experiments for the present work in 3 mM Ca²⁺.

Chiu and Carter (2024) demonstrated LFD in neocortical synapses; they performed their study in 1.2 mM Ca²⁺, not in elevated Ca²⁺.

Rudolph et al. (2011) showed low frequency depression not only in elevated external Ca²⁺, but also in 0.5 mM Ca²⁺. While Rudolph et al. (2011) did not make an explicit link between their observations and LFD, there is no reason to doubt that these observations are an example of LFD. They showed a biphasic depression when switching the stimulation frequency from 0.05 Hz to 2 Hz. In one of the founding papers of LFD, Doussau et al. (2010) describe a biphasic depression when switching the stimulation frequency from 0.025 Hz to 1 Hz; the Fig. 1 of the two papers (Rudolph 2011 and Doussau 2010) are strikingly similar.

Lin et al. (2022) would probably not agree with the statement that the depression at the calyx is ‘largely monotonic’, as they stress the finding of quasi-constant depression between 5 and 50 Hz.

The authors note that their results differ from those of Atluri and Regehr, but do not mention that a possible reason for the difference is the increased release probability in their experiments.

In fact, we clearly listed the difference in external Ca²⁺ as a likely source of the discrepancy by saying ‘This discrepancy presumably stems from differences in experimental conditions (room temperature, stimulation of multiple presynaptic PFs and 2 mM external Ca²⁺ concentration in the previous work, vs. near-physiological temperature, single presynaptic stimulation and 3 mM external Ca²⁺ here)’.

The authors should provide statistics for the data obtained in 1.5 mM Ca, and discuss why LFD is increased in conditions that also elevate vesicle release probability.

See our comments above: the revised version includes the requested statistics. On p. 6 of the manuscript, we do provide an explanation for the apparent lack of LFD at 1.5 Ca²⁺ and 2 Hz, namely a superimposition of LFD with facilitation. At 1.5 Ca²⁺ and 0.5 Hz, our LFD numbers are not weaker than at 3 mM Ca²⁺ and 0.5 Hz of 1 Hz.

Altogether, it is correct that many LFD experiments have been carried out in high release probability synapses, and/or under conditions of elevated Ca²⁺. However, the reasons underlying these choices are diverse (in our case, to build on the previous SV pool analysis developed in Tran et al. 2022 in 3 Ca²⁺ conditions) and do not imply a limitation to the phenomenon. LFD is present in physiological conditions for low-to-moderate release probability synapses (as shown in our work), and altogether, there is no reason to dismiss LFD as nonphysiological.

(2) Lack of biological mechanisms supporting the model

The model is presented without compelling biological support. The evidence in support of vesicle undocking comes from experiments by the Watanabe lab, which showed fewerthanexpected docked vesicles under EM when cultured synapses were stimulated immediately prior to high-pressure freezing. Kusick et al were careful to note that these vesicles may have been lost to fusion.

The Watanabe lab showed an SV deficit at docking sites at times ranging from about 100 ms to several seconds (Kusick et al., 2020, their Fig. 5E). This corresponds to the ISI values where we see paired-pulse depression. In their Summary, Kusick et al. raise the possibility of SV fusion as an alternative to undocking at the 100 ms time point. But, the same issue had previously been considered in Miki et al., 2018 with other techniques (their Fig. 2d), where it was shown that the SV deficit seen in paired-pulse experiments could not be explained by fusion. This leaves undocking as the most likely explanation, at least in our preparation. We have added a new paragraph on p. 14 to clarify this point.

The putative undocking Kusick describes is immediate (< 5 ms after stimulation), and it was not shown to be Ca²⁺ sensitive. This manuscript describes "calcium-dependent undocking" that proceeds from 10 ms - 200 ms. Multiple studies from the Watanabe lab show that a single stimulus lowers the number of docked vesicles, and subsequently, there is a transient redocking of vesicles that can be blocked by EGTA or Syt7 knockout.

This is not an accurate description of the Kusick results or of our results. In the Kusick paper, the SV deficit seen at <5 ms after stimulation is attributed to exocytosis, not to undocking. Clearly, it is Ca²⁺ dependent. Our manuscript describes potential calcium-dependent undocking not during the time 10 ms- 150 ms, during which our undocking rate is assumed to be calcium-independent, but starting at 150 ms, and lasting a few hundred ms thereafter.

I also question the rationale for the authors' model that 2 vesicles are coupled in series to a single release site. Previous papers from this lab cited EM studies from frog and neuromuscular that showed filamentous connections between vesicles (do these synapses show LFD?). Here, the authors primarily cite their previous models to support their arguments. I encourage them to continue searching for ultrastructural evidence for 2-vesicle-docking-units and to cite such studies.

It is important to remember that our sequential two-step model was not based on EM data, but on a series of functional data including variance-mean analysis of summed SV release numbers; covariance analysis among subsequent SV release numbers; analysis of release latencies as a function of stimulus number during an AP train; analysis of SV release numbers under conditions of very high release probability. We note that the phenomenon of Ca²⁺-dependent docking that we proposed based on these observations has been consistent with flash-and-freeze or zap-and-freeze results from several laboratories. Concerning potential filamentous connections between SVs and the AZ plasma membrane at a distance of several 10s of nm, this has been seen not only in frog or mice neuromuscular junctions, but also at brain synapses (ex: Siksou et al., Journal of Neuroscience 2007; Cole et al., Journal of Neuroscience 2016; Fernandez-Busnadiego, Journal of Cell Biology 2010; 2013).

(3) Comparison to other vesicle models

The authors use overly assertive language to suggest that the model proves a mechanism. "Altogether, these results indicate that the slow phase of LFD ... reflects a δ decrease without significant changes in pr, in ρ or in IP size". Simulating data does not conclusively "indicate" the underlying mechanism, but the authors could state their data can be "explained by a model where..".

Please see our response above to a similar point by Reviewer 1.

However, LFD does not require activity-dependent undocking. Instead, the phenomenon has been explained by high-release probability, paired with an activity-dependent increase in either docking or release probability (Chiu and Carter, 2024; Doussau et al., 2017). Does the new model do a better job of replicating some facet of the data? If multiple models can explain the same data, how can we determine which model is correct? The "Alternative Presynaptic Depression Mechanisms" should be expanded to discuss these issues.

We could not find statements in the Chiu and Carter paper or in the Doussau et al. paper explaining LFD ‘by high-release probability, paired with an activity-dependent increase in either docking or release probability’. As far as we can see, Chiu and Carter do not propose any specific mechanism for LFD, beyond saying that depression and facilitation must be separate. Doussau et al. (their Fig. 6) clearly frame their interpretation in a sequential two-step model. As in the preceding Miki et al. paper (which they cite extensively), they assume a rapid (a few ms), Ca-dependent transition between their ‘reluctant pool’ and their ‘fully-releasable pool’, respectively homologous to RS and DS. Thus, the Doussau et al. interpretation is close to that presented in our present work, even though significant differences exist. An important difference is that Doussau et al. did not use simple synapses, so that they did not have access to key synaptic parameters such as the number of docking sites or the release probability per docking site. Consequently, the model in Doussau et al. does not have the same level of detail as ours. The revised version explains better the differences and similarity between the models of Doussau et al. and that exposed in our work (new paragraph on p. 14).

Reviewer #1 (Public review):

Sensory hair cells of the inner ear convert mechanical sound vibrations into electrical signals through mechano-electrical transduction (MET), a process critically dependent on the specialized organization and lipid composition of their plasma membrane. Although the protein components of the MET complex are relatively well characterized, the role of the lipid environment remains poorly understood and often overlooked. Recent discoveries that core MET proteins TMC1 and TMC2 function as lipid scramblases, disrupting membrane lipid asymmetry, expose a significant gap in our understanding of how lipid homeostasis is regulated in hair cells and how membrane dynamics influence MET function.

In this study, the authors address this gap by identifying the P4-ATPase ATP8B1 and its chaperone TMEM30B as essential regulators of membrane lipid asymmetry in outer hair cells. They also generated HA-tagged knock-in mice to precisely localize the P4-ATPase ATP8B1 and its chaperone TMEM30B within outer hair cells, demonstrating their enrichment in stereocilia, and convincingly demonstrate that loss of these proteins causes phosphatidylserine externalization, hair cell degeneration, and hearing loss in mouse models, phenocopying defects observed in TMC1 mutant mice with constitutive scrambling activity. While these findings establish lipid flippase pathways as critical for hair cell survival and auditory function, they also raise important questions about the precise mechanisms linking lipid asymmetry disruption to MET dysfunction and hair cell pathology.

Overall, the data convincingly support the conclusion that ATP8B1-TMEM30B flippase activity is required to maintain stereocilia lipid asymmetry and auditory function. The study substantially advances understanding of how lipid homeostasis intersects with MET. However, several points require clarification to ensure that localization claims and mechanistic interpretations are fully supported by the presented data.

Revisions considered essential by this reviewer are:

(1) Figure 1D.<br /> The authors should clarify how the qPCR data were normalized and specify the reference (housekeeping) genes used. This information is necessary to evaluate the robustness and comparability of the gene expression data.

(2) Figure 1F.<br /> The lack of F-actin staining at the hair cell base raises the possibility that the permeabilization conditions may have limited antibody access to certain membrane regions. This is especially important given that the authors used a gentle permeabilization agent such as saponin to preserve membrane integrity. Because the authors conclude that ATP8B1 and TMEM30B are localized "almost exclusively to OHC bundles and the apical membrane, with minimal staining in the remaining plasma membrane," (line 128). Including co-labeling with a plasma membrane marker or more comprehensive F-actin visualization of lateral and basal regions would help ensure that the restricted localization is biological rather than technical. In the absence of such controls, the localization claim may be somewhat overstated and should be tempered accordingly.

(3) Figure 7B.<br /> Although quantification of ATP8B1-HA intensity at the bundle appears similar between WT and Cib2 KO samples, the representative image suggests that some bundles lack detectable labeling. To better capture phenotype variability, it would be helpful to include an additional quantification showing the fraction or number of bundles with detectable ATP8B1-HA signal in Cib2 KO mice.

(4) Lines 346-349.<br /> The manuscript suggests that IHCs lack stereocilia-enriched P4-ATPases. However, this conclusion is not directly supported by the presented data. The authors should either provide supporting localization or expression data for other P4-ATPases or soften the statement to indicate that no stereocilia-enriched P4-ATPases were detected under the conditions examined.

Recommendations:

(5) The authors convincingly demonstrate that TMEM30B loss results in ATP8B1 mislocalization. While not essential to the central conclusions, examining TMEM30B localization in ATP8B1 KO hair cells would clarify whether this interdependence is reciprocal, as described for other P4-ATPase-CDC50 complexes.

(6) Lines 359-374.<br /> The discussion of Annexin V labeling is careful and balanced. This paragraph would benefit from referencing other studies that showed minimal Annexin V labeling in healthy P6 organ of Corti, reinforcing that robust PS externalization in the present study is pathological rather than developmental.

(7) Lines 392-399.<br /> The proposed feedback model linking MET activity and ATP8B1-TMEM30B localization is compelling. The discussion could be strengthened by noting that in TMC1/2 double knockout hair cells, PS externalization is not observed, consistent with the idea that flippase activity becomes critical specifically when scrambling occurs. The mislocalization observed in Cib2 KO hair cells further supports the coupling between TMC-mediated scrambling and flippase-mediated membrane restoration.

Reviewer #2 (Public review):

Summary:

Prior work identified TMEM30B (knockout mice) as well as ATP8B1 (human genetics and mouse model), ATP8A2 (knockout mice), and ATP811A (human genetics) as relevant for hearing. The authors also reasoned that, given the recent discovery of TMC1 and TMC2's dual function as mechanotransduction channels of the inner ear and as lipid scramblases, a counterpart flippase should be in the sensory hair-cell stereocilia bundle where mechanotransduction happens. They use CRISPR/CAS to modify the endogenous mouse genes and add an HA tag at the N-terminus of the ATP8B1, ATP8A1, ATP8A2, and ATP11A proteins. Their experiments with these mice unambiguously localized ATP8B1 at the base of outer hair cell stereocilia bundles. Knockout of ATP8B1 results in loss of outer hair cells, deficient auditory function (ABR), and degeneration of outer hair cell stereocilia bundles. Similarly, hair cells from genetically modified mice with endogenous HA-tagged TMEM30B proteins show localization of this protein to outer hair cell stereocilia bundles. TMEM30B knock-out mice phenocopy the ATP8B1 knock-out model. Interestingly, the authors show that annexing V staining precedes hair cell loss in ATP8B1 and TMEM30B knockout mice and that proper localization of these proteins is lost in mice that lack CIB2, a protein essential for hair cell mechanotransduction.

Strengths:

(1) Use of knock-in HA-tagged proteins, rather than antibody staining, to unambiguously localize ATP8B1 and TMEM30B.

(2) Systematic characterization of auditory function (ABR), hair cell loss, and hair-cell stereocilia bundle morphology.

(3) Advances our understanding of the role played by lipid homeostasis in auditory function.

(4) Reports on mouse models that will be helpful to further understand the mechanistic role played by ATP8B1 and TMEM30B in normal hearing and hereditary deafness.

Weaknesses:

(1) Are the HA tags causing any functional issues? Function and localization of tagged proteins can sometimes be compromised. It would be good to know, for each knock-in model (TMEM30B, ATP8B1, ATP8A1, ATP8A2, and ATP11A ), whether the HA-tagged protein is causing any issues with the mice and particularly with hearing (ABRs). Are these mice normal? Can they hear? These data are missing.

(2) Following on the point above, is it possible that ATP8B1-HA is well localized, but localization for the other three flippases (ATP8A1-HA, ATP8A2-HA, and ATP11A-HA) is compromised by the tag? Is this potential mislocalization causing any functional phenotypes? (ABRs of point 1). I find it surprising that there are flippases only in outer hair cells, and only formed by ATP8B1. A possible explanation is that the tag is interfering with trafficking. If so, there should be a phenotype (ABRs), although this might be masked by redundancy among these flippases or caused by systemic issues (admittedly difficult to sort out). Given that this manuscript will likely become foundational, and that there is evidence that at least two of the other flippases are involved in hearing loss, it would be good to provide more information about the mice and HA-tagged proteins in the other knock-ins (ATP8A1-HA, ATP8A2-HA, and ATP11A-HA). Depending on the data available for the knock-ins, the authors may want to discuss these scenarios and soften the statement indicating that inner-hair cells may lack flippase activity altogether.

(3) Expression of ATP8B1 at P0 (Figure 1D), when there should not be protein in outer hair cells yet, seems high. Does this mean that other cells in the cochlea also express ATP8B1? Is this a concern?

(4) Fluorescence scales in Figure 6 B and D and Figure 7 B and D are very different. So are the values for WT. One would expect that the WT would be similar in all cases (at least within the same compartments), given that the methods section indicates that "All images were collected using identical acquisition parameters, including zoom and laser power, across genotypes". If WT shows such variability, how can we compare?

Author Response:

Summary of Planned Revisions:

We will clarify the qPCR methodology and interpretation to address potential misunderstandings.

We will assess hearing in the generated HA-tagged mouse lines and, where appropriate, include a properly powered ABR analysis in the revised manuscript.

We will address concerns regarding the z-stack in Figure 1f.

We will include additional quantification for Figure 7B to strengthen the analysis.

We will revise the relevant statement to read: “No IHC stereocilia-enriched P4-ATPases were detected under the conditions examined.”

While we appreciate the suggestion to examine TMEM30B localization on the ATP8B1 KO background, this is not feasible within a reasonable timeframe; we will clarify this limitation in the manuscript.

We will incorporate relevant prior work (e.g., George and Ricci, 2026) demonstrating minimal Annexin V labeling prior to P6 and lack of PS externalization in TMC1/2 double knockout models.

We will clarify that hearing thresholds for TMEM30B-HA and ATP8B1-HA lines will be addressed in this study, while additional HA-tagged flippase lines (ATP8A1, ATP8A2, ATP11A) are part of ongoing work to be reported separately.

We will soften statements regarding HA-tag insertion and clarify that, to our knowledge, localization and function are not disrupted, while acknowledging this as a potential limitation.

We will revise the Methods section to clarify differences in fluorescence measurements across experiments.

In addition to the experiments in response to reviewer’s suggestions, we will add the following data that we have generated while the paper was in review:

Distortion product otoacoustic emission (DPOAEs) of the Atp8b1 KO and Tmem30b KO mice. Consistent with OHC function, their DPOAEs thresholds were elevated.

Public Reviews:

Reviewer #1 (Public review):

(1) Figure1D.

The authors should clarify how the qPCR data were normalized and specify the reference (housekeeping) genes used. This information is necessary to evaluate the robustness and comparability of the gene expression data.

We thank the reviewer for this comment. qPCR data were normalized to GAPDH as the reference (housekeeping) gene. We will clarify this in the Methods section to ensure transparency and reproducibility.

(2) Figure 1F.

The lack of F-actin staining at the hair cell base raises the possibility that the permeabilization conditions may have limited antibody access to certain membrane regions. This is especially important given that the authors used a gentle permeabilization agent such as saponin to preserve membrane integrity. Because the authors conclude that ATP8B1 and TMEM30B are localized "almost exclusively to OHC bundles and the apical membrane, with minimal staining in the remaining plasma membrane," (line 128). Including co-labeling with a plasma membrane marker or more comprehensive F-actin visualization of lateral and basal regions would help ensure that the restricted localization is biological rather than technical. In the absence of such controls, the localization claim may be somewhat overstated and should be tempered accordingly.

We appreciate this important point. The image shown represents a single z-slice from a larger stack, and the hair cell body lies outside the plane of this section. To clarify this, we will revise the figure presentation. Specifically, we can provide the full z-stack (already available via OSF) and/or replace the image with a resliced whole-mount view to better visualize the full cellular context.

In terms of the possibility that the lack of staining in the hair cell’s plasma membrane might be due to insufficient antibody penetrance, we routinely perform Prestin (located in OHC plasma membrane) staining after saponin-mediated permeabilization and have never experienced antibody accessibility issues. Nevertheless, we will perform co-labeling for Prestin and include in the new submission.

(3) Figure 7B.

Although quantification of ATP8B1-HA intensity at the bundle appears similar between WT and Cib2 KO samples, the representative image suggests that some bundles lack detectable labeling. To better capture phenotype variability, it would be helpful to include an additional quantification showing the fraction or number of bundles with detectable ATP8B1-HA signal in Cib2 KO mice.

We thank the reviewer for this suggestion. To better capture variability, we will include an additional quantification measuring the fraction of hair cell bundles with detectable ATP8B1-HA and TMEM30B-HA signal per field of view. This analysis will complement the existing intensity-based quantification.

(4) Lines 346-349

The manuscript suggests that IHCs lack stereocilia-enriched P4-ATPases. However, this conclusion is not directly supported by the presented data. The authors should either provide supporting localization or expression data for other P4-ATPases or soften the statement to indicate that no stereocilia-enriched P4-ATPases were detected under the conditions examined.

We agree with the reviewer and will revise this statement to read: “No IHC stereocilia-enriched P4-ATPases were detected under the conditions examined.”

Recommendations:

(5) The authors convincingly demonstrate that TMEM30B loss results in ATP8B1 mislocalization. While not essential to the central conclusions, examining TMEM30B localization in ATP8B1 KO hair cells would clarify whether this interdependence is reciprocal, as described for other P4-ATPase-CDC50 complexes.

We appreciate this insightful suggestion. However, performing this experiment would require generating a compound mouse line (crossing TMEM30B-HA into the ATP8B1 knockout background), which is not feasible within the revision timeframe. Additionally, the lack of a robust commercial antibody for TMEM30B further complicates this approach. We will note this as a future direction in the revised manuscript.

(6) Lines 359-374.

The discussion of Annexin V labeling is careful and balanced. This paragraph would benefit from referencing other studies that showed minimal Annexin V labeling in healthy P6 organ of Corti, reinforcing that robust PS externalization in the present study is pathological rather than developmental.

We thank the reviewer for this suggestion and will incorporate relevant prior work, including George and Ricci (2026), which demonstrates minimal Annexin V labeling prior to P6, and further supports our interpretation.

(7) Lines 392-399.

The proposed feedback model linking MET activity and ATP8B1-TMEM30B localization is compelling. The discussion could be strengthened by noting that in TMC1/2 double knockout hair cells, PS externalization is not observed, consistent with the idea that flippase activity becomes critical specifically when scrambling occurs. The mislocalization observed in Cib2 KO hair cells further supports the coupling between TMC-mediated scrambling and flippase-mediated membrane restoration.

We agree and will expand the discussion to include that TMC1/2 double knockout hair cells do not exhibit phosphatidylserine externalization, supporting the idea that flippase activity becomes critical in the context of scrambling.

Reviewer #2 (Public review):

Weaknesses:

(1) Are the HA tags causing any functional issues? Function and localization of tagged proteins can sometimes be compromised. It would be good to know, for each knock-in model (TMEM30B, ATP8B1, ATP8A1, ATP8A2, and ATP11A), whether the HA-tagged protein is causing any issues with the mice and particularly with hearing (ABRs). Are these mice normal? Can they hear? These data are missing.

We thank the reviewer for raising this important point. In this study, we will focus on TMEM30B-HA and ATP8B1-HA mouse lines, while additional HA-tagged flippase lines (ATP8A1, ATP8A2, ATP11A) are part of ongoing work to be reported separately.

Both TMEM30B-HA and ATP8B1-HA mice are viable and exhibit normal breeding and aging. Preliminary (pilot) ABR measurements indicate wild-type–like hearing thresholds. We agree that this is important and will attempt to raise sufficient mouse numbers (in the time given) for a properly powered ABR analysis in the revised manuscript.

(2) Following on the point above, is it possible that ATP8B1-HA is well localized, but localization for the other three flippases (ATP8A1-HA, ATP8A2-HA, and ATP11A-HA) is compromised by the tag? Is this potential mislocalization causing any functional phenotypes? (ABRs of point 1). I find it surprising that there are flippases only in outer hair cells and only formed by ATP8B1. A possible explanation is that the tag is interfering with trafficking. If so, there should be a phenotype (ABRs), although this might be masked by redundancy among these flippases or caused by systemic issues (admittedly difficult to sort out). Given that this manuscript will likely become foundational, and that there is evidence that at least two of the other flippases are involved in hearing loss, it would be good to provide more information about the mice and HA-tagged proteins in the other knock-ins (ATP8A1-HA, ATP8A2-HA, and ATP11A-HA). Depending on the data available for the knock-ins, the authors may want to discuss these scenarios and soften the statement indicating that inner-hair cells may lack flippase activity altogether.

We appreciate this concern. To our knowledge, the HA tag does not appear to disrupt localization or function of the tagged proteins. However, we agree that this cannot be fully excluded. We will therefore soften our conclusions about IHC flippases and clarify that additional flippases (ATP8A1, ATP8A2, ATP11A) are under investigation and will be described in a separate study.

(3) Expression of ATP8B1 at P0 (Figure 1D), when there should not be protein in outer hair cells yet seems high. Does this mean that other cells in the cochlea also express ATP8B1? Is this a concern?

We thank the reviewer for this observation. We interpret the elevated signal at P0 as reflecting transcription preceding detectable protein expression. While expression in other cochlear cell types is possible, we have not observed detectable ATP8B1 localization outside hair cells using the HA-tagged model. We will clarify this point in the manuscript.

(4) Fluorescence scales in Figure 6 B and D and Figure 7 B and D are very different. So are the values for WT. One would expect that the WT would be similar in all cases (at least within the same compartments), given that the methods section indicates that "All images were collected using identical acquisition parameters, including zoom and laser power, across genotypes". If WT shows such variability, how can we compare?

We appreciate the need for clarification. Identical acquisition parameters were maintained within each experiment used for direct comparison (e.g., within a given panel). However, different panels (e.g., Figures 6B vs. 6D) were acquired on different days using different imaging settings.

We will revise the Methods section to explicitly state this and clarify that comparisons are intended only within panels, not across experiments.

1. The WHO MDA program administered in 2023 should have been described in the background, including its extent (e.g., how many persons received MDA; what was coverage).
2. Looking at table 1, it seems that the surge occurred only from 2022-2023, and thus the costing for those two years can be averaged and compared to the pre-surge (2021) and post-surge/post-WHO MDA (2024)
3. For Table 2-Pls give how many grams of the permethrin 5% ointment per tube and what dosage frequency they were administered (single dose or 2 weekly doses?). also how many ml was flucloxacillin syrup, how many mg was cetirizine tab and syrup; Pls indicate currency of unit cost per drug; Pls provide costs for IPC supplies
4. What software was used to compute for costing?

Sentences in lines 138 and 139 are duplicates Table 2 is not cited Table 1 - pls provide total consultations for each year, which served as denominator to get the proportional morbidity Vancouver style is not followed in some references Ref 2 - only 1st letter of 1st word should be capitalized) Ref#6 has unnecessary symbols (stars) after title Ref #14-16 have no date of citation Ref 4 and 8 should not have editor's names

R0:

Reviewer #1:

Thank you for the opportunity to review this manuscript examining determinants of measles vaccine (MR1–MR2) dropout in an urban slum setting. The topic is highly relevant to measles elimination efforts, particularly in vulnerable urban populations where service continuity remains challenging. The study addresses an important operational question and employs an appropriate case–control design. However, several aspects of the manuscript require clarification and strengthening before it can be considered for publication.

Introduction 1. The Introduction does not crisply say what is unknown about measles dropout in the Dhaka slum context. You need a single paragraph that: (a) identifies the knowledge gap, (b) explains why Korail/slum populations require focused study, and (c) states the study’s unique contribution. 2. Terminology and consistency. Use consistent vaccine labels (Penta1, MCV1, MR1, MR2). Early in the Introduction define what you mean by “drop-out” (the operational definition appears later in Methods — bring a short definition into the Introduction). 3. Some background facts belong in Methods/Results. E.g., the specific urban slum population size and annual vaccination target are Methods details and should not be in the Introduction. 4. At present the Introduction jumps between global stats, EPI history, WHO recommendations, and local data without clear transitions. Reorder so each paragraph follows logically (global → regional → national → evidence on determinants → gap in urban slums → study aim). 5. Missing justification of novelty. Say explicitly why this study adds new evidence (e.g., limited studies in Dhaka slums, few case–control analyses of MR1–MR2 drop-out in highly mobile urban slum populations, service-delivery factors not well quantified in Dhaka). This is essential for reviewers. 6. The intro cites Ethiopia, Somalia, Pakistan; add (or at least state you reviewed) South-Asia or Bangladesh-specific evidence on urban slums and drop-out. If those studies are sparse, say that explicitly — that is the gap.

Methods Section 1. Please provide a precise definition of dropout, including the age/time cutoff for MR2 completion and whether delayed vaccination was considered acceptable. 2. It should be explicitly stated that both groups were drawn from the same source population using identical eligibility criteria to minimize selection bias. 3. Provide more detail on the sampling frame and recruitment process. Specify whether participants were identified through EPI registers, household listings, or community census data, and clarify whether random or convenience sampling was used. 4. Expand the description of the sample size calculation. Include the assumed effect size (odds ratio), exposure prevalence among controls, alpha level, statistical power, and the formula or software used. 5. Clearly define how key variables (e.g., maternal education, household income, waiting time, ANC/PNC visits) were categorized and justify the chosen cutoffs. 6. Clarify the source and validation of vaccination data. Indicate whether vaccination status was verified through vaccination cards, caregiver recall, or both, and explain how discrepancies were handled. 7. Provide more detail on bias control measures. Describe steps taken to minimize selection bias, recall bias, and information bias, including interviewer training and standardization procedures. 8. Strengthen the description of data management and quality control. Indicate whether data were double-entered, validated, and which statistical software (including version) was used. 9. Clarify ethical procedures. Provide the name of the approving ethics committee, approval number, and details on how informed consent was obtained and documented.

Results Section 1. Strengthen the presentation of multivariable findings. Adjusted odds ratios (AORs), 95% confidence intervals, and p-values should be consistently reported in both tables and narrative text. Emphasize adjusted results over crude associations to avoid overinterpretation of unadjusted findings. 2. Clarify reference categories in tables. Tables presenting logistic regression results should clearly indicate the reference group for each categorical variable. This is essential for accurate interpretation of odds ratios. 3. Improve consistency between tables and text. Ensure that all key numerical results mentioned in the text match those in the tables (including decimal places). Avoid repeating entire tables in narrative form; instead, summarize the most important findings.

Discussion and Conclusion 1. Strengthen the synthesis between findings and existing literature. While prior studies are cited, the discussion would benefit from more critical comparison. Clearly indicate whether your findings confirm, contradict, or extend previous evidence, particularly in South Asian or urban slum contexts. 2. Deepen interpretation beyond statistical significance. Move beyond reporting that associations were significant and elaborate on potential mechanisms (e.g., health system barriers, caregiver perceptions, structural inequities) that may explain the observed relationships. 3. Expand the discussion of public health and programmatic implications. The manuscript would benefit from clearer operational recommendations. For example, explain how EPI managers or urban health planners could translate these findings into targeted interventions. 4. Explicitly discuss potential biases (selection bias, recall bias, residual confounding), the inherent limitations of the case–control design, and issues of generalizability beyond Korail slum. 5. The discussion should more explicitly state what new knowledge this study adds compared to prior research—particularly regarding urban informal settlements and MR1–MR2 dropout.

Reviewer #2:

Beyond the reduced confirmed incidence of measles from 2019 (31.4) to 2022 (1.34 per million), at national level needs to include the measles case- based surveillance sensitivity indicators if they are met (Non measles febrile rash illness rate and % specimen collected from suspected cases ) Measles case-based surveillance indicators if achieved or not need to be described for the period of the study 15/10/2023 to 30/04/2024 for Dahka

Reviewer #3:

In this manuscript, Alam et al. report a study investigating factors associated with measles vaccination drop-out in children aged 12-23 months in urban areas in Bangladesh. It is quite interesting that the author found that maternal occupation, birth order, and waiting time for vaccination were among factors that were significantly associated with vaccination drop-out. Overall, the manuscript is modestly presented. My comments are summarized below. 1. What are MCV1, MCV2? 2. What is included in a pentavalent dose? 3. The statement in lines 53-54 needs to be supported by a reference. Particularly, to better protect children against measles, a herd immunity level of 95% is needed. And if the statement remains correct, what is the problem when the drop-out rate in Bangladesh is 3.4-5.5%? 4. The differences in vaccine coverage between urban and rural areas (lines 61-62) are significant? And is it due to vaccination drop-out? 5. Paragraphs in lines 53-60 and 63-70 are duplicated. 6. I think the introduction needs to be revised. It remains unclear why this study is conducted. 7. If possible, please make the questionnaire available for review and describe how the questionnaire is evaluated. 8. Some language errors in Table 4. 9. The conclusion of the manuscript introduces new information (measles elimination in Bangladesh), but it seems likely irrelevant.

R0:

Reviewer #1: Manuscript Number: PGPH-D-25-02685 Review Report Male Allyship Overall summary of the review Strength This manuscript addresses the important topic of male allyship in advancing women’s leadership in global health academia, using a well-structured qualitative approach and presenting findings across individual, institutional, and societal levels. Strengths include clear objectives, rigorous methods, and practical insights for policy and leadership. Areas that need improvement include: • Clarify the study type in the title and make it action-oriented. • Expand geographic representation beyond the U.S. and Canada. • Provide context for participant quotes. • Report data saturation and response rates. • Improve readability by breaking up long sentences and structuring results around clear subthemes. • acknowledge limitation for geographic representation beyond the U.S. and Canada Point by point feedback Title: - Male Allyship to Advance Women's Global Health Leadership in the Academy Strength • It addresses a timely and high-Impact Topic: The study area is forgotten by global community especially in academia on the importance of gender equity and leadership. • The title accurately reflects the manuscript’s core theme male allyship in academic global health leadership. • Timely and High-Impact Topic: The study addresses a significant gap in global health leadership literature—moving beyond simply identifying barriers to focusing on actionable solutions (allyship and sponsorship). This shift in focus is highly valuable for policymakers and institutional leaders Weakness • The short and long title of the manuscript is the same; no difference • The title talks about two things one “Global Health Leadership” and second “the academic institution in North America”. the focus of study population is not clear • The kind of the study type is no clearly indicated in the title. • The phrase “in the Academy” could be slightly ambiguous to international audiences—consider specifying “in academic global health institutions.” Suggested Revision • It is better if the title is an action oriented Like “Exploring Male Allyship to Advance Women’s Leadership in Global Health Academia: A Qualitative Study” or Male Allyship to Advance Women’s Leadership in Global Health Academia: A Qualitative Study Abstract Strengths: Introduction • Well-structured abstract with clear objectives, methods, and findings. • Strong justification for the study, citing global gender disproportionate disparities and responsibilities gaps in global health leadership. • Appropriate Methodology: It used a qualitative, semi structured interview approach to explore the perception, experiences and perceptions of high level leaders. Clear thematic analysis • It use clear research question on the experience of global leaders • Findings: Clearly structured around three levels—individual male ally, institutional, and societal level which offers a useful conceptual framework to shift cultural norms on gender roles for practical implications Area of improvement: • Introduction looks like an advocacy; no clearer separation between background and rationale. • • Participants were drawn only from the U.S. and Canada, which limits the geographic coverage of the study. In addition, selecting participants exclusively from the WomenLift Health network may reduce the diversity of perspectives and potentially affect the credibility of the findings. • Conceptual clarity: The term male allyship could be briefly defined in one sentence for clarity. • The conclusion partially repeats ideas from the introduction it looks like the summary of the introduction and better if based on the findings and highlighting the practical or policy relevance to enhance the impact Main Manuscript • The study team approached participants via email and invited them to participate and conduct the interview via zoom; so why the study participants restricted to two high-income countries? Result • Line 178-183: The results section reports the number of participants but does not indicate whether data saturation was achieved. In qualitative research, explaining when and how saturation was reached strengthens the credibility and adequacy of the sample size. • Reporting the response rate as a percentage would help readers interpret the level of participation more easily. • Line 185-191: The paragraph communicates the general findings, better if key themes are mentioned to give readers a concrete examples • Line 202: The quote is powerful, but providing brief context about the respondent role, experience, or institution better if included. • Line Motivation and incentives it is more plausible to read if concrete example of participant quotes are included • Line 252 to 278: the section contains valuable insights, but some sentences are long and dense. Breaking them into shorter sentences will improve readability. Consider structuring the section around clear subthemes: like awareness, role modeling etc., • Line 332-341 quote -P7, F, 40-44 is clear and conventional; however it’s a bit long and better if lightly edit for readability while retaining authenticity Discussion Strength • It is strong in structure, logic, and scholarly tone. It clearly links findings to prior research and offers practical and theoretical insights • Line 633 Toking et al reference number (54). Line 638 Sinha et al (59) need consistency Limitation Strength: Clearly states the population studied & acknowledges selection of diverse perspectives Area of Improvement: Findings may not generalize to early-career leaders, non-academic settings, or global contexts.

Reviewer #2: This paper examines an important topic: male allyship in global health. A key strength of the paper is its focus on solutions as reported by participants. This helps move the focus away from challenges women in global health face, to exploring actual solutions to the problem. The paper presents many examples of what male allyship looks like, many of these being very actionable. I commend the authors for this. That said, there are several areas that need attention.

1. The findings could be synthesized and made more concise. The authors present A LOT of information, which is overwhelming. There are many ways to address this. First, the authors can use much shorter direct excerpts from participants. Second, the authors could move participant excerpts into a table. Third, the authors could synthesize their findings much more which would reduce the number of themes/issues and tell the story a bit differently. The paper would read better if they structured the results based on the subheadings used in Fig 1. It would help tell a more succinct story.

2. It is not clear what Fig 2 is showing.

3. I wonder if to would help to present the findings by gender, that is, by showing similarities and differences between female and male participants.

4. Could the authors present more details on the study participants. Sone of the content in the excerpts suggests that they were from academic institutions. A demographics table would help, in terms of academic vs non-academic institutions etc. The authors should also provide more details on the sampling and recruitment method: how exactly did they find these 21 participants?

5. The Discussion could be strengthened by a more critical analysis of the concept of male allyship. The authors should consider what their findings/study implications are for the potential and pitfalls of the concept.

Reviewer #1 (Public review):

Summary:

This paper examines plasticity in early cortical (V1-V3) areas in an impressively large number of rod monochromats (individuals with achromatopia). The paper examines three things:

(1) Cortical thickness. It is now well established that early complete blindness leads to increases in cortical thickness. This paper shows increased thickness confined to the foveal projection zone within achromats. This paper replicates work by Molz (2022) and Lowndes (2021), but the detailed mapping of cortical thickness as a function of eccentricity and the inclusion of higher retinotopic areas is particularly elegant.

(2) Failure to show largescale reorganization of early visual areas using retinotopic mapping. This is a replication of a very recent study of Molz et al. but I believe, given anatomical variability, the larger n in this study, and how susceptible pRF findings are to small changes in procedure, this replication is also of interest.

(3) Connective field modelling, examining the connections between V3-V1. The paper finds changes in the pattern of connections, and smaller connective fields in individuals with achromatopsia than normally sighted controls, and suggests that these reflect compensatory plasticity, with V3 compensating for the lower resolution V1 signal in individuals with achromatopsia.

This is a carefully done study (both in terms of data collection and analysis) that is an impressive amount of work.

*Effects of eye-movements

The authors have carried out the eye-movement analyses I asked of them. Unfortunately, in 4 individuals they couldn't calibrate the eyetracker (it's impressive they managed in 10). I think this means that 4 of 13 (since a different participant was excluded from head motion) individuals weren't included in correlation analyses. Limiting the correlation analysis to individuals with better fixation has obvious issues. I'd recommend redoing (or additionally including) stats using non-parametric measures while classifying these 4 as having fixation instability of 3 (i.e. greater instability than the participant with the worst fixation who was successfully calibrated).

*Interpreting pRFs

The paper would be strengthened by a little more explicit clarity about what pRFs represent and how that affects their interpretation of their findings as plasticity vs. non-plasticity (I know the authors are aware of this, but I think it would be helpful for readers who are less experienced in pRFs). In the introduction it would be helpful to point out that pRFs represent the collective response of a large population of neurons, and as a result pRF estimates can vary depending on which population of neurons that stimulus drives.

For example, imagine for the sake of argument that rods only project to V1 neurons with larger receptive fields. If one measured pRFs in a control observer under phototopic vs. scotopic conditions one would see smaller pRFs in the photopic conditions. This wouldn't represent 'plasticity' - it would represent the fact that the firing neurons contributing to the pRF signal are a slightly different population because of a change in the stimulus content. This is of course exactly what you see in 2C. And indeed, the authors make this identical point ". In the non-selective condition, the smaller pRFs in controls are in line with the higher spatial resolution of the<br /> cone system, which is not active in the achromat group." But this point would be clearer if more of the conceptual underpinnings were made explicit in the introduction (or at this point in the paper).

Shifts in which population of neurons drive your pRFs can explain main of the more puzzling results in the paper without detracting from your main conclusions. For example, in 2D, I don't think it's differences in S/N driving your results (pRFs are at least theoretically meant to be robust to S/N). If smaller RFs 'drop out' under low luminance and these smaller RFs also tend to be more central, then one would expect the control results of 1D. And I think a similar argument might even be made for the smaller difference in the rod monochromats.

It would be possible to make the point of Figure 4B more simply if Figure 4B was replaced by additional Panels in Figure 2 simply showing V3 pRF sizes/eccentricity distributions. That would make the point that you don't see the same expansion in pRF sizes in V3 in a way that is just as clear, and is closer to the data.

*Interpreting cRFs

Similarly, I think the paper would be improved with more clarity about the underlying signal in CF modeling. Once again, I appreciate that the authors are familiar with this, but it will help the reader in interpretation. (And I do believe thinking carefully about this may alter your interpretations). CF receptive fields 'find' the region in V1 that best predict the V3 signal in a given voxel. In resting state this likely represents a combination of:

(1) visually driven signal - correlations that may or may not reflect connectivity but represent the fact that regions that represent the same region of visual space will be active at the same time.

(2) global bilaterally symmetrical signal consisting of enhanced correlations between iso-eccentric regions (Raemaekers et al., 2014), which may arise from vasculature that symmetrically stems from the posterior cerebral artery (Tong et al., 2013; Tong and Frederick, 2014).

(3) intrinsic neural fluctuations that are more strongly correlated between connected neurons. These are likely quite weak compared to the other contributions.

I think if you ignore 2, (which is not likely to differ between rod mono and controls) and model 1 and 3, you might well see shifts in CFs towards the boundary of the scotoma - essentially the CF's location will be biased towards the region of V1 that has stronger correlations - which = the region which has a visual signal.

I do find convincing the argument that you don't see the same shift in controls in the rod-selective condition. So I think the results of 4A are fine. But a little more clarity about 'what's under the hood' in CF modeling would be nice.

*Interpreting the relationship between pRFs and cRFs

So there's something here that confuses me. We are all agreed that V3 pRF sizes are similar across RM and control. V1 pRFs are larger in RM. It feels intuitive that smaller CFs would compensate but I can't make it make sense to myself when I think it through. Each pRF represents a combination of receptive field location scatter and bandwidth. You want to argue that eccentricity mapping looks pretty normal, so there's no reason to think increased rf scatter, and I can believe that (though I do think this assumption should be discussed explictly).

So far I think we agree.

But let's think about what drives a CF during visual stimulation ... Specifically lets think about 'the pRF of the CF' (the region of visual space represented by the cluster of voxels in the CF). If pRFs for individual voxels in V1 are big, then the pRF for the CF is also going to be large. But we know that pRFs for V3 are normal size. So, the V3 CF will 'find' a smaller number of voxels in V1, in order to try to find the 'correct sized' CF pRF. Note that this explanation is very similar to yours. But doesn't require ANY 'intrinsic' connectivity. It's really just assuming the whole thing is driven by the visual signal and the CF size is determined by the ratio of the pRF sizes in V3 vs. V1.

One possible solution would be to regress out the visual stimulus and redo this analysis based on the residuals.

Author response:

The following is the authors’ response to the original reviews.

Public Reviews:

Reviewer #1 (Public review):

Summary:

This paper examines plasticity in early cortical (V1-V3) areas in an impressively large number of rod monochromats (individuals with achromatopia). The paper examines three things:

(1) Cortical thickness. It is now well established that early complete blindness leads to increases in cortical thickness. This paper shows increased thickness confined to the foveal projection zone within achromats. This paper replicates the work by Molz (2022) and Lowndes (2021), but the detailed mapping of cortical thickness as a function of eccentricity and the inclusion of higher visual areas is particularly elegant.

(2) Failure to show largescale reorganization of early visual areas using retinotopic mapping. This is a replication of a very recent study by Molz et al. but I believe, given anatomical variability (and the very large n in this study) and how susceptible pRF findings are to small changes in procedure, this replication is also of interest.

(3) Connective field modelling, examining the connections between V3-V1. The paper finds changes in the pattern of connections, and smaller connective fields in individuals with achromatopsia than normally sighted controls, and suggests that these reflect compensatory plasticity, with V3 compensating for the lower resolution V1 signal in individuals with achromatopsia.

Strengths:

This is a carefully done study (both in terms of data collection and analysis) that is an impressive amount of work. I have a number of methodological comments but I hope they will be considered as constructive engagement - this work is highly technical with a large number of factors to consider.

Weaknesses:

(1) Effects of eye-movements

I have some concerns with how the effects of eye-movements are being examined. There are two main reasons the authors give for excluding eye-movements as a factor in their results. Both explanations have limitations.

(a) The first is that R2 values are similar across groups in the foveal confluence. This is fine as far as it goes, but R2 values are going to be low in that region. So this shows that eyemovements don't affect coverage (the number of voxels that generate a reliable pRF), but doesn't show that eye-movements aren't impacting their other measures.

We agree with the reviewer that eye movements could affect pRF measures. We have now also included data for all participants where we were able to obtain eye tracking measures and directly tested this relationship. Relevant results are copied below.

Recap of results: 1) as expected gaze was less stable in achromats than controls, 2) achromats with more stable gaze did not show more activation in the scotoma projections zone, which we might have observed if fixation instability masks signals in this region 3) Gaze instability was not correlated with pRF size and eccentricity across V1 in achromats. We note that the relationship between nystagmus and visual sampling is complex - patients experience a stable image and may sample only during a specific phase of the eye movement. It is therefore not inherently clear if and how nystagmus affects pRF size.

Relevant Manuscript text incorporating these analyses is copied below.

To quantify eye movement, we used the following methods added to the manuscript:

“Fixation stability

Participants’ gaze was tracked throughout all pRF mapping runs. Collecting reliable gaze data from individuals with nystagmus is a challenge because out of the box calibration procedures mostly fail without stable fixation. To account for this, we implemented a post-hoc custom calibration procedure (Tailor et al., 2021). The eye-tracker was first precalibrated on a typically sighted individual. Then, before every other run, we collected gaze data from a 5-point fixation task (at fixation and above, below, left, and right of fixation at 5 eccentricity). This data allowed us to subsequently map the patient's recorded gaze coordinates to their precise locations on the screen. In 10 out of the 14 achromats we acquired reliable enough data to assess fixation stability.

Calibration data processing: We first removed the first 0.5 seconds for each fixation location to allow for fixation to arrive on the target. We then performed (a) blink removal, (b) filtered out time points with eye movement velocity outliers (±2SD), and (c) filtered out any positions >3SDs to the left or right of the mean fixation location, and >1SD above or below. We took the median of the remaining gaze measurements as an approximate fixation estimate. The resulting 5 median fixation locations were used to fit an affine transformation that remapped the recorded gaze positions into screen space. 

Quantifying fixation stability: after applying the transformation of the post-hoc calibration, data was filtered for blinks and extreme velocities (<2SD). For each functional run, fixation instability was measured as the standard deviation of gaze x-positions across 1second windows. Measures were then averaged across the two run repeats.”

We report the resulting new fixation data results as follows:

Results (coverage section):

“Another potential confound in our findings is fixation instability. In pRF mapping, which is usually conducted under photopic (cone-dominant) conditions, unstable fixation can cause a signal drop in the foveal projection zone. As expected due to nystagmus, the achromatopsia group showed higher fixation instability compared to controls (rodselective: t_(9.08)=-3.19, p=0.01; non-selective: t<sub<(9.41)</sub>=-4.88, p<0.001 degrees-offreedom corrected for unequal-variance; see Supplement Figure S2a). However, several lines of evidence suggest this instability cannot fully account for the lack of "filling in" in achromats. First, within the achromat group, we found no correlation between fixation stability and coverage (rod-selective: spearman-r₍₈₎ = -0.36, p=0.31; non-selective spearman-r₍₈₎=0.07,p=0.85); Individuals with more stable, control-like fixation did not show more signal inside the scotoma (see Supplement 2). Second, in adults with achromatopsia, typically with less severe nystagmus (Kohl et al., 1993), two recent studies also found absence of filling in (Anderson et al., 2024; Molz et al., 2023).

So, while we cannot fully exclude nystagmus masking foveal signals in the cortex of some patients, this converging evidence from structural and functional MRI measures across different studies and groups, strongly suggests that the deprived cortex does not substantially ‘fill in’ with peripheral rod inputs in achromatopsia.”

Results (pRF size + eccentricity):

“Larger pRFs indicate that neuronal populations in achromats’ V1 cortex, combine information across larger areas in visual space than in typically sighted controls. This could reflect true neural tuning differences as well as be driven by larger eye movement. However, fixation instability in achromats do not significantly correlate with pRF size in our sample (rod-selective: spearman-r₍₈₎ = -0.41, p=0.24; non-selective spearman-r₍₈₎=0.37,p=0.29)

It has been shown that fitting artefacts around scotoma edges, can give rise to similar outward eccentricity shifts (Binda et al., 2013). However, when accounting for fitting artefacts around the foveal scotoma edge by modelling the rod-free zone during pRF fitting, pRF size and eccentricity differences remain unchanged (see Supplement 3). Finally, we found no significant correlations between gaze stability and the eccentricity shift (rod-selective: spearman-r₍₈₎ = 0.58, p=0.08; non-selective spearman-r₍₈₎=0.09,p=0.8, Supplement 4D)

Together, these analyses reveal subtle differences in how V1 of achromats responds to rod signals outside the foveal zone, which are consistent with results from other studies (Molz et al. 2023, Anderson et al. 2024). While we found no direct evidence that these are being driven by confounding factors such as eye-movements or fitting artefacts, more work is needed to understand the underlying processes that give rise to these shifts.”

The following text has been added to Supplement 2

“As expected, achromats showed significant higher fixation instability compared to controls (as reported in the main text). We found no significant correlation between fixation instability and either coverage, pRF size, eccentricity in achromats. Results of Spearman R correlations in both rod- and non-selective conditions are reported in the figure. We note that the relationship between nystagmus and visual sampling is complex- patients experience a stable image and may sample only during specific eyemovement phases. It is therefore not fully clear if and how nystagmus should give rise to altered pRFs.”

(b) The authors don't see a clear relationship between coverage and fixation stability. This seems to rest on a few ad hoc examples. (What happens if one plots mean fixation deviation vs. coverage (and sets the individuals who could not be calibrated as the highest value of calibrated fixation deviation. Does a relationship then emerge?).

In any case, I wouldn't expect coverage to be particularly susceptible to eye-movements. If a voxel in the cortex entirely projects to the scotoma then it should be robustly silent. The effects of eye-movements will be to distort the size and eccentricity estimates of voxels that are not entirely silent.

There are many places in the paper where eye-movements might be playing an important role. 

Examples include the larger pRF sizes observed in achromats. Are those related to fixation instability?

We thank the reviewer for their comment. As detailed in our previous response, we have now extracted fixation instability data from additional patients and have expanded our discussion of its potential effects throughout the manuscript.

Given that fixation instability is expected to increase pRF size by a fixed amount, that would explain why ratios are close to 1 in V3 (Figure 4).

We agree with the reviewer’s point, that the ratio change on its own is not strong evidence of compensation, this analysis was meant to complement the CF result. The plot in Figure 4 is intended to reconcile the connective field (CF) and pRF results. Its purpose is to illustrate that even though larger pRFs in achromats might seem counterintuitive alongside their smaller V3 CF sizes, the pRF data do not contradict the CF findings but they are in fact consistent with one another. We also agree that there are alternative explanations for the differences in pRF size, such as fixation stability, and we have now added this point to the text.

Results (CF size):

“To understand how this finer cortical sampling in V3 (smaller connective fields) impacts visual processing, we consider its effect on population receptive fields (pRFs). In V1, pRF sizes in achromats were significantly larger than in controls for both stimulus conditions, indicating coarser spatial tuning at the cortical input stage (Figure 4C, left). By selectively sampling from a smaller area of the V1 surface (smaller CFs), V3 can effectively compensate for this coarser input. If so, this process should result in a relative normalisation of pRF size in V3 compared to V1 (Figure 4C, right).

To test this prediction, we plotted the ratio of pRF sizes between achromats and controls, where a value of 1 indicates parity between the groups (Figure 4B). As our compensatory connective field hypothesis predicts, the ratio was closer to 1 in V3 than in V1 across both stimulus conditions, confirming the pRF size difference was significantly reduced at the higher cortical stage. Together this shows converging evidence across the two models (pRF and CF) of hierarchical refinement as a possible compensatory mechanism, where V3's altered connectivity helps to normalize the processing of degraded sensory input from V1.”

Discussion:

“The hierarchical reorganisation observed in V3 is unlikely to be driven by fixation instability. Connective field (CF) estimates are robust to eye movements (Tangtartharakul et al., 2023), because they are anchored to V1 inputs rather than absolute screen position. Considered alone, the pRF results could alternatively be explained by eye movements introducing a fixed size offset that affects smaller V1 pRFs more strongly than those in V3. While we found no evidence for this relationship between pRF size and gaze measures in our patients, we cannot fully rule out the possibility. Nevertheless, the internal consistency between the CF and pRF measures provides a more parsimonious account; that sampling across the hierarchy accounts for coarser tuning at the input stage.”

(2) Topography

The claim of no change in topography is a little confusing given that you do see a change in eccentricity mapping in achromats. 

Either this result is real, in which case there *is* a change in topography, albeit subtle, or it's an artifact. 

Perhaps these results need a little bit of additional scrutiny. 

One reason for concern is that you see different functions relating eccentricity to V1 segments depending on the stimulus. That almost certainly reflects biases in the modelling, not reorganization - the curves of Figure 2D are exactly what Binda et al. predict. 

Another reason for concern is that I'm very surprised that you see so little effect of including/not including the scotoma - the differences seem more like what I'd expect from simply repeating the same code twice. (The quickest sanity check is just to increase the size of the estimated scotoma to be even bigger?).

We thank the reviewer for their comment. We have double-checked our scotoma modelling, confirming its correct implementation. The results of the scotoma modelling are not identical to the full one, just similar (see below).

Previous studies on “artificial scotomas” (such as the one reported by Binda et al.) have shown mixed results. While Binda and colleagues found that modelling artificial scotomas normalised pRF shifts, others found no effect (Haak et al. 2012, Prabhakaran et al. 2020). Notably, the rodfree zone in achromatopsia is considerably smaller (~0.5° radius) than most tested artificial scotomas. Moreover, it is unclear whether scotoma modelling is beneficial in clinical populations as artificial scotomas (screen-based masking) are not equivalent to retinal scotomas from inactive photoreceptors. A recent achromatopsia study (Anderson et al. 2024) also found no change in pRF estimates with scotoma modelling.

In our scotoma analyses, we found meaningful differences only in the non-selective condition in controls where cones in the rod-free zone are stimulated - which would be the main expected effect of this modelling exercise (see below). In all other conditions (rod-selective in controls, both conditions in achromats), only rods are stimulated, we found no difference in coverage, eccentricity or pRF size when modelling the scotoma likely because the foveal signal is weak/absent, and did not contribute much to pRF estimates in the unmasked analyses.

This means we cannot account for the eccentricity shift as an edge effect with this scotoma model – but we remain cautious about interpreting it as real. This is because first, as we mention in the paper, in the non-selective condition, which has a higher signal-to-noise ratio, the eccentricity estimates in achromats match those of the control group's rod system. Second, it is still possible that the observed shift is an artefact of modelling that was not accounted for by the approach of scotoma modelling.

Our claim of "no change in topography" specifically referred to the absence of "filling-in" as measured by cortical coverage - the percentage of activated tissue regardless of fitted parameters. However, to avoid confusing given the eccentricity and pRF size results we now rephrased our claim.

Abstract:

“Cortical input stages (V1) exhibited high stability, with input-deprived cortex showing no retinotopic remapping and exhibiting structural hallmarks of deprivation.”

Results (pRF eccentricity):

“It has been shown that fitting artefacts around scotoma edges, can give rise to similar outward eccentricity shifts (Binda et al., 2013). However, when accounting for fitting artefacts around the foveal scotoma edge by modelling the rod-free zone during pRF fitting, pRF size and eccentricity differences remain unchanged (see Supplement 3). Finally, we found no significant correlations between gaze stability and the eccentricity shift (rod-selective: spearman-r₍₈₎ = 0.58, p=0.08; non-selective spearman-r₍₈₎=0.09,p=0.8, Supplement 4D)

Together, these analyses reveal subtle differences in how V1 of achromats responds to rod signals outside the foveal zone, which are consistent with results from other studies (Molz et al. 2023, Anderson et al. 2024). While we found no direct evidence that these are being driven by confounding factors such as eye movements or fitting artefacts, more work is needed to understand the underlying processes that give rise to these shifts.”

To better illustrate the effect of scotoma modelling text has been added to Supplement 3:

“Studies on artificial scotomas, where part of the visual field is masked, suggest that pRF estimates of eccentricity and size can be biased by fitting scotoma-edge artefacts, and that these can be mitigated by modelling the scotoma in the pRF fitting procedure (e.g., Binda et al. 2013).

We therefore repeated the pRF modelling procedure with the rod-scotoma being modelled as a black oval mask (1.25°x0.9°) over the stimulus aperture model. As expected, a visible difference between the two models is only apparent in the nonselective condition in controls where the cones in the rod-free zone are being stimulated. In all the other conditions (rod-selective in controls, and both stimulation conditions in achromats) only the rods are stimulated, therefore the masked stimulus still matches the retinal activation, and no major differences can be observed. Performing the same statistical tests applied to the full model in the main text yields equivalent results of equivalent coverage in the rod-selective condition, with equivalent coverage across groups(t(47) = 0.78, p=0.43, BF10=0.31) and controls show a higher coverage in the non-selective stimulation condition compared to achromats (Mann U(52)=141, p<0.01; unequal variance, reverted to non-parametric).

This consistency in pRF properties when modelling the rod scotoma, is in line with previous results from scotoma modelling; While Binda and colleagues found that this normalised pRF shifts, others found no effect (Haak et al. 2012, Prabhakaran et al. 2020). Notably, the rod-free zone in achromatopsia is considerably smaller (~0.5° radius) than most tested artificial scotomas, and as artificial scotomas (screen-based masking) are not equivalent to retinal scotomas from inactive photoreceptors, it is unclear how artificial scotoma findings generalise to clinical populations. Our results are in line with a recent achromatopsia study (Anderson et al. 2024) which also found no change in pRF estimates with scotoma modelling.”

I'd also look at voxels that pass an R2>0.2 threshold for both the non-selective and selective stimulus. Are the pRF sizes the same for both stimuli? Are the eccentricity estimates? If not, that's another clear warning sign.

Comparable results were obtained when using higher R2 thresholds. These results are now included in Supplement 6.

(3) Connective field modelling

Let's imagine a voxel on the edge of the scotoma. It will tend to have a connective field that borders the scotoma, and will be reduced in size (since it will likely exclude the cortical region of V1 that is solely driven by resting state activity). This predicts your rod monochromat data. The interesting question is why this doesn't happen for controls. One possibility is that there is topdown 'predictive' activity that smooths out the border of the scotoma (there's some hint of that in the data), e.g., Masuda and Wandell.

One thing that concerns me is that the smaller connective fields don't make sense intuitively. When there is a visual stimulus, connective fields are predominantly driven by the visual signal. In achromats, there is a large swath of cortex (between 1-2.5 degrees) which shows relatively flat tuning as regards eccentricity. The curves for controls are much steeper, See Figure 2b. This predicts that visually driven connective fields should be larger for achromats. So, what's going on?

The reviewer raises interesting points about the interpretation of our connective field results. The possibility of differential top-down modulation between controls and achromats is intriguing, however it is not supported by the data, if top-down modulation is activating foveal V1 in controls then we shouldn’t see a drop in the amount of significant vertices sampling from the fovea in the rod-selective condition compared to the non-selective, but in fact we do see quite a large drop in the amount of significant vertices in that area in the rod-selective condition. Therefore, at the moment we do not think there is strong basis to assume our data could be explained by achromats lacking top-down predictive activity in the scotoma area that is present in controls.

Regarding the concern about smaller CFs seeming counterintuitive given the flat eccentricity tuning in achromats' V1: we believe there is not a straightforward prediction from pRF properties to CF sizes. The relationship between V1 pRF characteristics and V3 CF sampling is complex and not well-established in the literature, and the two can be decoupled to some degree. For instance, in our data, controls show flat V1 pRF sizes in the rod-selective condition (similar to achromats), yet their V3 CF sizes maintain the typical eccentricity-dependent increase seen in the non-selective condition. This suggests that CF size patterns don't simply mirror V1 pRF properties or visual stimuli responses.

Importantly, CF modelling fundamentally differs from pRF analysis in how it might be affected by scotomas. Unlike pRF analysis where a scotoma creates a "silent" region in visual space, in CF modelling the deprived cortex remains physically present and continues generating neural signals (albeit not visually-driven ones). If V3-V1 connectivity were anatomically fixed, V3 would continue sampling from deprived V1 regions even if they do not produce visual-driven signals. A change in this sampling pattern, as we see in our data, is therefore evidence for plasticity.

Our data support this interpretation. First, in achromats, the CF size pattern observed cannot be easily explained by scotoma-edge artefacts. V3 vertices sampling from the immediate vicinity of the scotoma (1°-3°) show CF sizes comparable to controls. The effect is only significant further away from the scotoma (4°-6°).

Second, to assess how the presence of a scotoma affects CF measure we can compare the two conditions in the controls, since the rod-selective condition has a scotoma present and the nonselective condition does not. For this purpose, we performed an additional analysis, quantifying on a vertex-by-vertex level the differences in CF fitted parameters between the two stimulation conditions across V1. See results below. In achromats there are no systematic shifts between the stimulation conditions, as expected as both are rod-driven. In controls, this analysis reveals only subtle shifts (~0.45° in the rod-selective condition). CF size has also changed slightly although not significantly different from that observed in achromats. These shifts are much smaller than the CF size and eccentricity differences between controls and achromats, so we consider it unlikely that our findings are driven by scotoma artefacts.

Author response image 1.

Results (CF size):

“The significant CF size differences are unlikely to be a model-fitting bias around a scotoma edge, as V3 vertices sampling from the immediate vicinity of the scotoma (1°3°) show CF sizes comparable to controls. The significant reduction in CF size occurs only further in the periphery (4°-6°), in regions that are primarily stimulus-driven.

To understand how this finer cortical sampling in V3 (smaller connective fields) impacts visual processing, we consider its effect on population receptive fields (pRFs). In V1, pRF sizes in achromats were significantly larger than in controls for both stimulus conditions, indicating coarser spatial tuning at the cortical input stage (Figure 4C, left). By selectively sampling from a smaller area of the V1 surface (smaller CFs), V3 can effectively compensate for this coarser input. If so, this process should result in a relative normalisation of pRF size in V3 compared to V1 (Figure 4C, right).

To test this prediction, we plotted the ratio of pRF sizes between achromats and controls, where a value of 1 indicates parity between the groups (Figure 4B). As our compensatory connective field hypothesis predicts, the ratio was closer to 1 in V3 than in V1 across both stimulus conditions, confirming the pRF size difference was significantly reduced at the higher cortical stage. Together this shows converging evidence across the two models (pRF and CF) of hierarchical refinement as a possible compensatory mechanism, where V3's altered connectivity helps to normalize the processing of degraded sensory input from V1.”

Discussion (added paragraph):

“The hierarchical reorganisation observed in V3 is unlikely to be driven by fixation instability. Connective field (CF) estimates are robust to eye movements (Tangtartharakul et al., 2023), because they are anchored to V1 inputs rather than absolute screen position. Considered alone, the pRF results could alternatively be explained by eye movements introducing a fixed size offset that affects smaller V1 pRFs more strongly than those in V3. While we found no evidence for this relationship between pRF size and gaze measures in our patients, we cannot fully rule out the possibility. Nevertheless, the internal consistency between the CF and pRF measures provides a more parsimonious account; that sampling across the hierarchy accounts for coarser tuning at the input stage.”

The beta parameter is not described (and I believe it can alter connective field sizes).

In Author response image 2, we plot the beta parameter of the pRF modelling in V1 with no R² filtering, error bars are 95% CIs:

Author response image 2.

The reviewer did not specify how beta might alter connective field sizes. We assume he meant that as in pRF mapping, the slope of activity from deprived to non-deprived cortex will artefactually create a CF model fit with smaller CF sizes. To test this, we calculated the slope of beta values between 0° and 3° in each participant in the rod-selective condition, as this range includes the scotoma and the area at the edge of the scotoma. We then used the slope as a covariate in an ANCOVA when comparing the CF sizes across groups in each sampled V1 segment. Accounting for the beta slope of V1 did not change the reported results. This analysis still shows smaller CF sizes in V3 in the rod-selective conditions between 4°-6° eccentricity – these differences remain significant (p<0.001 for 4°-5° and p<0.05 for 5°-6° when comparing achromats vs controls).

Similarly, it's possible to get very small connective fields, but there wasn't a minimum size described in the thresholding.

CF sizes were fit with a grid fit. Possible values were [0.5,1,2,3,4,5,7,10]. Therefore, the minimum size is 0.5. Filtering out the smallest connective field sizes does not change the results:

Author response image 3.

I might be missing something obvious, but I'm just deeply confused as to how the visual maps and the connectome maps can provide contradictory results given that the connectome maps are predominantly determined by the visual signal. Some intuition would be helpful.

We agree that this appears counterintuitive, and now added further clarification. The two models (pRF and CF) fundamentally differ in what they measure and how they relate to visual processing. V1 pRF sizes reflect the relationship between neural activity and visual stimuli - essentially how much of a visual stimulus drives a voxel's response - while V3 CF sizes reflect how V3 samples from the V1 cortical surface, indicating how many V1 voxels contribute to a V3 voxel's activity.

The measures constrain each other, as a V3 voxel's pRF size is expected to match the pooling of its connected V1 inputs. But they can be decoupled: A V3 voxel could sample from a small area of V1 cortex (a small CF in mm) that happens to represent a large area of visual space if those V1 voxels have large pRFs. The aim of Figure 4B is to clarify that the measures are consistent with one another even though they diverge in direction. In achromats, where V1 voxels have larger pRFs (coarser spatial resolution), V3 appears to compensate by sampling more selectively from V1 via smaller CF sizes. Theoretically, this should reduce the pRF size difference between controls and patients in V3, a prediction that our data supports.

Results (CF size):

“To understand how this finer cortical sampling in V3 (smaller connective fields) impacts visual processing, we consider its effect on population receptive fields (pRFs). In V1, pRF sizes in achromats were significantly larger than in controls for both stimulus conditions, indicating coarser spatial tuning at the cortical input stage (Figure 4C, left). By selectively sampling from a smaller area of the V1 surface (smaller CFs), V3 can effectively compensate for this coarser input. If so, this process should result in a relative normalisation of pRF size in V3 compared to V1 (Figure 4C, right).

To test this prediction, we plotted the ratio of pRF sizes between achromats and controls, where a value of 1 indicates parity between the groups (Figure 4B). As our compensatory connective field hypothesis predicts, the ratio was closer to 1 in V3 than in V1 across both stimulus conditions, confirming the pRF size difference was significantly reduced at the higher cortical stage. Together this shows converging evidence across the two models (pRF and CF) of hierarchical refinement as a possible compensatory mechanism, where V3's altered connectivity helps to normalize the processing of degraded sensory input from V1.”

Discussion (added paragraph):

“The hierarchical reorganisation observed in V3 is unlikely to be driven by fixation instability. Connective field (CF) estimates are robust to eye movements (Tangtartharakul et al., 2023), because they are anchored to V1 inputs rather than absolute screen position. Considered alone, the pRF results could alternatively be explained by eye movements introducing a fixed size offset that affects smaller V1 pRFs more strongly than those in V3. While we found no evidence for this relationship between pRF size and gaze measures in our patients, we cannot fully rule out the possibility. Nevertheless, the internal consistency between the CF and pRF measures provides a more parsimonious account; that sampling across the hierarchy accounts for coarser tuning at the input stage.”

Some analyses might also help provide the reader with insight. For example, doing analyses separately on V3 voxels that project entirely to scotoma regions, project entirely to stimulusdriven regions, and V3 voxels that project to 'mixed' regions.

We agree that it is important to plot the connective field dynamics across the scotoma region.

In Figure 4A we split the V3 vertices based on the V1 area they sample from. Therefore the 0°-1° would be considered as mainly sampling from the “scotoma” region and the higher the eccentricity is, the less “scotoma” it includes. The V3 vertices that have a significantly smaller CF size compared to controls are those sampling from mostly if not entirely stimulusdriven regions 4°-5° and 5°-6°. We are not sure how further binning the data by within, across and outside scotoma would be more informative.

However, in Author response image 4, we plot in more details the distribution of CF sizes sampling from a V1 segment clearly inside and clearly outside the scotoma. The top figure shows the CF size distribution of V3 vertices that sample from a V1 0°-1° segment, where V1 is deprived of input due to the rod scotoma. In achromats, there is a clear drop in vertices with a very small (0.5) CF size. The bottom figure shows the distribution of V3 vertices that sample from the V1 4°-5° segment which falls outside the scotoma and shows a significant difference in CF size across the groups. Here in achromats you can see a drop in larger V3 CF sizes sampling from the V1 region, and an increase in smaller ones (note that this further addresses a previous concern that connective field differences across groups are solely driven by very small CFs).

Author response image 4.

Following the reviewer’s comment we have added the following statement in the results section discussing CF size:

“The significant CF size differences are unlikely to be a model-fitting bias around a scotoma edge, as V3 vertices sampling from the immediate vicinity of the scotoma (1°3°) show CF sizes comparable to controls. The significant reduction in CF size occurs only further in the periphery (4°-6°), in regions that are primarily stimulus-driven.”

The finding that pRF sizes are larger in achromats by a constant factor as a function of eccentricity is what differences in eye-movements would predict. It would be worth examining the relationship between pRF sizes and fixation stability.

We found no relationship between fixation stability and pRF size in V1, although as we explain in response to an earlier point, this does not fully exclude the reviewers alterative explanation, which we now add to the discussion.

Discussion:

“The hierarchical reorganisation observed in V3 is unlikely to be driven by fixation instability. Connective field (CF) estimates are robust to eye movements (Tangtartharakul et al., 2023), because they are anchored to V1 inputs rather than absolute screen position. Considered alone, the pRF results could alternatively be explained by eye movements introducing a fixed size offset that affects smaller V1 pRFs more strongly than those in V3. While we found no evidence for this relationship between pRF size and gaze measures in our patients, we cannot fully rule out the possibility. Nevertheless, the internal consistency between the CF and pRF measures provides a more parsimonious account; that sampling across the hierarchy accounts for coarser tuning at the input stage.”

Reviewer #2 (Public review):

Summary:

The authors inspect the stability and compensatory plasticity in the retinotopic mapping in patients with congenital achromatopsia. They report an increased cortical thickness in central (eccentricities 0-2 deg) in V1 and the expansion of this effect to V2 (trend) and V3 in a cohort with an average age of adolescents.

In analyzing the receptive fields, they show that V1 had increased receptive field sizes in achromats, but there were no clear signs of reorganization filling in the rod-free area. In contrast, V3 showed an altered readout of V1 receptive fields. V3 of achromats oversampled the receptive fields bordering the rod-free zone, presumably to compensate and arrive at similar receptive fields as in the controls.

These findings support a retention of peripheral-V1 connectivity, but a reorganization of later hierarchical stages of the visual system to compensate for the loss, highlighting a balance between stability and compensation in different stages of the visual hierarchy.

Strengths:

The experiment is carefully analyzed, and the data convey a clear and interesting message about the capacities of plasticity. 

Weaknesses:

The existence of unstable fixation and nystagmus in the patient group is alluded to, but not quantified or modeled out in the analyses. The authors may want to address this possible confound with a quantitative approach.

We have responded to this in the “Recommendations for the authors” section of this reviewer, as they included a more detailed description of these points there.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

(1) I think the term rod monochromats should be included early in the paper since it's a more intuitive term to describe this population.

We agree with the reviewer that the term “rod monochromats” is more intuitive as it clarifies the retinal source of the disease but have chosen the term achromats for consistency with a wide literature of published work in this group, including our own and our close collaborators’. To clarify, in the first mention of the group as achromats in the introduction we have now added this term:

“Achromatopsia (also known as rod monochromacy) causes cone photoreceptors in the retina to be inactive from birth (Aboshiha et al., 2014).”

(2) The paper essentially contains two definitions of 'eccentricity'. One (atlas/segments) comes from the Benson atlas and the other (functional) comes from pRF mapping. It would be good to make this distinction terminology clearer earlier in the paper. It would also be good to use more consistent terminology. I assume 'sampled atlas V1 eccentricity' in 3A is the same as 'V1 segment' in 1A?

For consistency we have now referred to these as V1 segment and sampled V1 segment in the figures when describing the atlas-based definition, and eccentricity for the measured pRF-based eccentricity.

(3) The 'stability vs. plasticity' framing in the introduction could be tightened slightly.

We have made the following changes following the reviewer’s comment:

“In the visual domain, the focal point of the debate on plasticity and stability has hinged on the extent to which retinal input deprivation can drive local reorganisation in early visual cortex, for example, for deprived tissue to take on inputs from spared retinal locations (Adams et al., 2007; Baker et al., 2005, 2008; Baseler et al., 2002, 2011; Calford et al., 2005; Dilks et al., 2009; Dumoulin & Knapen, 2018; Ferreira et al., 2016; Goesaert et al., 2014; Haak et al., 2015; Molz et al., 2023; Ritter et al., 2019; Schumacher et al., 2008). In reality visual impairment is a more global phenomenon, affecting all levels of visual processing, with complex dynamics beyond constricted local retinocortical projection zones(Carvalho et al., 2019).”

(4) Figure 1A, define the x axis as degrees.

We have now added the ° sign to all the tick labels indicating Benson map eccentricity.

(5) Figure 2B, is there room for pictures of the silent substitution/standard stimulus

We have now added images in a Supplement 5 to avoid cluttering the main Figure 2B

(6) Figure 2

Panel A has a slightly weird organization. The reader is supposed to compare the square symbols to each other, and the circles to each other, why not organize the figure so they are adjacent in the graph (i.e. non selective control, non-selective achromat, selective control, selective achromat)? That also helps the reader orient that in the non-selective conditions you have almost complete pRF coverage. 

We have taken on the reviewer’s suggestion and changed the order.

In the inset, maybe use empty symbols? That's the traditional way to say that the square/circle applies to both red and black.

We prefer the current format.

Figure 2C - the symbols change to circles? Why not keep the symbols of A?

We have now changed the symbols of 2C&D.

I'd put the non-selective maps above the selective maps?

We appreciate the feedback but prefer to keep it as it is, as we feel the critical point is conveyed by the rod maps.

(7) 'We propose a new hierarchical model of neural adaptation'. These ideas are hardly new. There are also other models, that would explain your data (cumulative plasticity) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5953572/

We thank the reviewer for the reference. We have now cited it in our discussion and removed the word “new” form the mentioned sentence.

“Therefore, there is theoretically broader scope for experience-dependent reweighting of inputs (Beyeler et al., 2017; Makin & Krakauer, 2023) and to optimise use of inputs that are still available, more reliable, or more relevant in the impaired system. Conversely, higher-order visual areas may appear more plastic simply because they integrate the cumulative effects of learning from multiple lower stages (Beyeler et al., 2017).”

We propose a hierarchical model of neural adaptation…” [deleted the word new]

(8) Line 508. No image of the stimulus is contained in the paper

Corrected

(9) Line 620. I believe the Figure is 1B, not 1C.

Corrected

(10) Figure 4A. CF Size - add mm2 to the axes.

Corrected

Reviewer #2 (Recommendations for the authors):

I am not an expert on pRF mapping, and as such, I am unsure how to relate to pRF mapping performed in patients with unstable fixation (not quantified, but referred to) and nystagmus, such as the achromatic population here. Since the majority of the results hinge on this analysis, I would appreciate more data about the differences between the groups. Supplement 2, which is meant to speak to this, shows only the data from 3 typical participants, and in itself is not evidence for "no correlation between stable fixation and enhanced foveal". Additionally, I'd appreciate a clear methods explanation of how the authors address these confounds; this is too important a concern to be left for the discussion section.

We agree with the reviewer that eye movements could affect pRF measures. We have now also included data for all participants where we were able to obtain eye tracking measures and directly tested this relationship. Relevant results are copied below.

Recap of results: 1) as expected gaze was less stable in achromats than controls, 2) achromats with more stable gaze did not show more activation in the scotoma projections zone, which we might have observed if fixation instability masks signals in this region 3) Gaze instability was not correlated with pRF size and eccentricity across V1 in achromats. We note that the relationship between nystagmus and visual sampling is complex - patients experience a stable image and may sample only during a specific phase of the eye movement. It is therefore not inherently clear if and how nystagmus affects pRF size.

Relevant Manuscript text incorporating these analyses is copied below.

To quantify eye movement, we used the following methods added to the manuscript:

“Fixation stability

Participants’ gaze was tracked throughout all pRF mapping runs. Collecting reliable gaze data from individuals with nystagmus is a challenge because out of the box calibration procedures mostly fail without stable fixation. To account for this, we implemented a post-hoc custom calibration procedure (Tailor et al., 2021). The eye-tracker was first precalibrated on a typically sighted individual. Then, before every other run, we collected gaze data from a 5-point fixation task (at fixation and above, below, left, and right of fixation at 5 eccentricity). This data allowed us to subsequently map the patient's recorded gaze coordinates to their precise locations on the screen. In 10 out of the 14 achromats we acquired reliable enough data to assess fixation stability.

Calibration data processing: We first removed the first 0.5 seconds for each fixation location to allow for fixation to arrive on the target. We then performed (a) blink removal, (b) filtered out time points with eye movement velocity outliers (±2SD), and (c) filtered out any positions >3SDs to the left or right of the mean fixation location, and >1SD above or below. We took the median of the remaining gaze measurements as an approximate fixation estimate. The resulting 5 median fixation locations were used to fit an affine transformation that remapped the recorded gaze positions into screen space.

Quantifying fixation stability: after applying the transformation of the post-hoc calibration, data was filtered for blinks and extreme velocities (<2SD). For each functional run, fixation instability was measured as the standard deviation of gaze x-positions across 1second windows. Measures when then averaged across the two run repeats.”

Results (coverage section):

“Another potential confound in our findings is fixation instability. In pRF mapping, which is usually conducted under photopic (cone-dominant) conditions, unstable fixation can cause a signal drop in the foveal projection zone. As expected due to nystagmus, the achromatopsia group showed higher fixation instability compared to controls (rodselective: t_(9.08)=-3.19, p=0.01; non-selective: t<sub<(9.41)</sub>=-4.88, p<0.001 degrees-offreedom corrected for unequal-variance; see Supplement Figure S2a). However, several lines of evidence suggest this instability cannot fully account for the lack of "filling in" in achromats. First, within the achromat group, we found no correlation between fixation stability and coverage (rod-selective: spearman-r₍₈₎ = -0.36, p=0.31; non-selective spearman-r₍₈₎=0.07,p=0.85); Individuals with more stable, control-like fixation did not show more signal inside the scotoma (see Supplement 2). Second, in adults with achromatopsia, typically with less severe nystagmus (Kohl et al., 1993), two recent studies also found absence of filling in (Anderson et al., 2024; Molz et al., 2023).

So, while we cannot fully exclude nystagmus masking foveal signals in the cortex of some patients, this converging evidence from structural and functional MRI measures across different studies and groups, strongly suggests that the deprived cortex does not substantially ‘fill in’ with peripheral rod inputs in achromatopsia.”

Results (pRF size + eccentricity):

“Larger pRFs indicate that neuronal populations in achromats’ V1 cortex, combine information across larger areas in visual space than in typically sighted controls. This could reflect true neural tuning differences as well as be driven by larger eye movement. However, fixation instability in achromats do not significantly correlate with pRF size in our sample (rod-selective: spearman-r₍₈₎ = -0.41, p=0.24; non-selective spearman-r₍₈₎=0.37,p=0.29)

It has been shown that fitting artefacts around scotoma edges, can give rise to similar outward eccentricity shifts (Binda et al., 2013). However, when accounting for fitting artefacts around the foveal scotoma edge by modelling the rod-free zone during pRF fitting, pRF size and eccentricity differences remain unchanged (see Supplement 3). Finally, we found no significant correlations between gaze stability and the eccentricity shift (rod-selective: spearman-r₍₈₎ = 0.58, p=0.08; non-selective spearman-r₍₈₎=0.09,p=0.8, Supplement 4D)

Together, these analyses reveal subtle differences in how V1 of achromats responds to rod signals outside the foveal zone, which are consistent with results from other studies (Molz et al. 2023, Anderson et al. 2024). While we found no direct evidence that these are being driven by confounding factors such as eye-movements or fitting artefacts, more work is needed to understand the underlying processes that give rise to these shifts.”

The following text has been added to Supplement 2

“As expected, achromats showed significant higher fixation instability compared to controls (as reported in the main text). We found no significant correlation between fixation instability and either coverage, pRF size, eccentricity in achromats. Results of Spearman R correlations in both rod- and non-selective conditions are reported in the figure. We note that the relationship between nystagmus and visual sampling is complex- patients experience a stable image and may sample only during specific eyemovement phases. It is therefore not fully clear if and how nystagmus should give rise to altered pRFs.”

The field connectivity analysis similarly seems to be used only on task data from the same design; if it was replicated from resting-state data, that would be a good way to show consistency which is independent of measures requiring fixation. 

We agree that resting-state data would be valuable; however, we did not collect such data in these individuals due to time limitations. Instead, we demonstrate the consistency and reliability of our results by replicating our findings across two different stimulation conditions (rod-selective and non-selective), which differ in luminance, contrast and signal amplitude in both groups and for controls also in the photoreceptors involved. The convergence of results across these distinct visual conditions strengthens our confidence in the reliability of the observed effects. Also, notably, CF estimates have been shown to be robust to large eye movements, and therefore also to differences in fixation stability across groups (Tangtartharakul et al., 2023).

The authors may want to contextualize their findings in relation to what reorganization exists in cases of late-onset loss of part of the visual field on one hand (stroke recovery), and in the case of complete blindness from early life on the other, as both speak to different levels of plasticity the visual system is capable of.

We thank the reviewer for their comment and have added a new paragraph discussing this topic.

Discussion:

“Our findings on hierarchical adaptation have broader implications for other visual disorders, depending on their timing and nature. For instance, a central scotoma acquired in adulthood, as in macular degeneration, may not trigger the same V3 sampling shifts (Haak et al., 2016), suggesting a sensitive window for this form of plasticity, after which connective fields remain more stable. This also raises questions about congenital blindness, where the absence of any driving input could lead to weakening or repurposing of hierarchical connections (Saccone et al., 2024). Moreover, principles may differ between a deprived but structurally intact cortex, as in retinal dystrophies, and a physically damaged cortex, as in stroke. In the latter, more extensive reorganisation may be required to sample effectively from surviving, and potentially disparate, regions of V1. Perceptual training effects in stroke rehabilitation may reflect such dynamics (Cavanaugh et al., 2025; Elshout et al., 2021).”

A more minor point: Can the authors clarify what the dark adaptation is used for, and provide the supplementary analysis showing that the duration difference for some of the participants didn't impact the results (stated but not shown).

The dark adaptation period before the rod-selective condition allowed rod photoreceptors to recover from bleaching caused by prior mesopic light exposure, ensuring optimal rod sensitivity under scotopic conditions. To verify that our 15-minute adaptation period was sufficient, we tested 10 control participants with an extended 45-minute adaptation period. As we found no differences in the resulting rod maps between standard and extended adaptation protocols, these participants were combined with the main control group for all analyses. Author response image 5 are the plots for the two dark adaptation periods.

Author response image 5.

On 2021-06-13 21:16:52, user thomas wrote:

I am not in the health field (that may be obvious from the questions I have) but I am very interested in this study because my parents (in their 70's) both had and recoverd from covid. They have not received a vax yet.

1. Why wouldn't having the infection give immunity? Is there something about this specific virus, or this type of virus in general, that it wouldn't be expected to give immunity?

2. If infection doesn't give immunity, how will the vaccines work? I realize some vaccines are mRNA or viral vector, but at least the two Chinese ones, the Indian one, and a new one the French are working on are all based on using a dead/weakened virus. Shouldn't recovering from an actual infection work just as good as the simulated infection of a vaccine?

3. Is 1,359 subjects really considered small? How big where the sample sizes for the initial vaccine studies? What would be an acceptable size? My background is more in the social sciences, and we often see samples in the hundreds.

4. Is it really correct to assume that people who had COVID would be more careful afterwards? I know with my parents, they were almost consumed with fear about catching the disease, but once they did and recovered, much of that went away. I wasn't around to see their behavior, but just based on conversations, I find it hard to believe they were more careful.

When my parents saw the doctor after recovering, he told them they could not get the vaccine for at least 3 months and that they didn't need to get it until after 6 months. So this study seems in line with what the medical establishment was already saying (they had COVID back in March).

On 2021-06-11 13:41:25, user Christy Blanchford wrote:

We don't develop long lasting immunity to the other 4 common covid viruses so why would we have long term immunity to covid 19? This was only 42 days out, we get reinfected with the covid common cold after 1-2 years. Manus, Brazil showed us that despite 80% covid infection rate that should have conferred herd immunity , 6 months later they were digging mass graves again. This paper is doing a disservice....

On 2020-04-30 19:12:43, user Sinai Immunol Review Project wrote:

Main findings<br /> This report describes the use of systemic tissue plasminogen activator (tPA) to treat venous thromboembolism (VTE) seen in four critically ill COVID-19 patients with respiratory failure. These patients all exhibited gas exchange abnormalities, including shunt and dead-space ventilation, despite well-preserved lung mechanics. A pulmonary vascular etiology was suspected.

All four patients had elevated D-dimers and significant dead-space ventilation. All patients were also obese, and 3/4 patients were diabetic.

Not all patients exhibited an improvement in gas exchange or hemodynamics during the infusion, but some did demonstrate improvements in oxygenation after treatment. Two patients no longer required vasopressors or could be weaned off them, while one patient became hypoxemic and hypotensive and subsequently expired due to a cardiac arrest. Echocardiogram showed large biventricular thrombi.

Limitations<br /> In addition to the small sample size, all patients presented with chronic conditions that are conducive to an inflammatory state. It is unclear how this would have impacted the tPA therapy, but it is likely not representative of all patients who present with COVID-19-induced pneumonia. Moreover, each patient had received a different course of therapy prior to receiving the tPA infusion. One patient received hydroxychloroquine and ceftriaxone prior to tPA infusion, two patients required external ventilator support, and another patient received concurrent convalescent plasma therapy as part of a clinical trial. Each patient received an infusion of tPA at 2 mg/hour but for variable durations of time. One patient received an initial 50 mg infusion of tPA over two hours. 3/4 patients were also given norepinephrine to manage persistent, hypotensive shock. Of note, each patient was at a different stage of the disease; One patient showed cardiac abnormalities and no clots in transit on an echocardiogram, prior to tPA infusion.

Significance<br /> The study describes emphasizes the importance of coagulopathies in COVID-19 and describes clinical outcomes for four severe, COVID-19 patients, who received tPA infusions to manage poor gas exchange. While the sample size is very limited and mixed benefits were observed, thrombolysis seems to warrant further investigation as a therapeutic for COVID-19-associated pneumonia that is characterized by D-dimer elevation and dead-space ventilation. All four patients had normal platelet levels, which may suggest that extrinsic triggers of the coagulation cascade are involved.

The authors suspect that endothelial dysfunction and injury contribute to the formation of pulmonary microthrombi, and these impair gas exchange. Pulmonary thrombus formation has also been reported by other groups; post-mortem analyses of 38 COVID-19 patients' lungs showed diffuse alveolar disease and platelet-fibrin thrombi (Carsana et al., 2020). Inflammatory infiltrates were macrophages in the alveolar lumen and lymphocytes in the interstitial space (Carsana et al., 2020). Endothelial damage in COVID-19 patients has also been directly described, noting the presence of viral elements in the endothelium and inflammatory infiltrates within the intima (Varga et al., 2020). One hypothesis may be that the combination of circulating inflammatory monocytes (previously described to be enriched among PBMCs derived from COVID-19 patients) that express tissue factor, damaged endothelium, and complement elements that are also chemotactic for inflammatory cells may contribute to the overall pro-coagulative state described in COVID-19 patients.

References<br /> Carsana, L., Sonzogni, A., Nasr, A., Rossi, R.S., Pellegrinelli, A., Zerbi, P., Rech, R., Colombo, R., Antinori, S., Corbellino, M., et al. (2020) Pulmonary post-mortem findings in a large series of COVID-19 cases from Northern Itality. medRxiv. 2020.04.19.20054262.

Varga, Z., Flammer, A.J., Steiger, P., Haberecker, M., Andermatt, R., Zinkernagal, A.S., Mehra, M.R., Schuepbach, R.A., Ruschitzka, F., Moch, H. (2020) Endothelial cell infection and endotheliitis in COVID-19. Lancet. 10.1016/S0140-6736(20)30937-5.

The study described in this review was conducted by physicians of the Divisions of Pulmonary, Critical Care, and Sleep Medicine, Cardiology, Nephrology, Surgery, and Neurosurgery and Neurology at the Icahn School of Medicine at Mount Sinai.

Reviewed by Matthew D. Park as part of a project by students, postdocs, and faculty at the Immunology Institute of the Icahn School of Medicine, Mount Sinai.

On 2021-06-23 21:55:50, user David Wiseman PhD wrote:

Summary:<br /> Regarding the continued and unnecessary confusion related to the Argoaic and Artuli comments.<br /> 1. These are in reality distractions from the central issue that the original NEJM paper remains uncorrected in NEJM as to shipping times. Although a secondary issue, also uncorrected is the "days" nomenclature that is the reason for confusion in the Argoaic and Artuli comments on this forum. Also uncorrected in the original paper is the exposure risk definition which were informed were also incorrect. Together, these issues controvert the conclusions of the original study.<br /> 2. The incorrect nomenclature for "days" in the NEJM paper as well as in a follow up work (Clin Infect Dis, Nicol et al.) inflates the number of "elapsed time" days. This has not been corrected by the original authors. We on the other hand have corrected this by providing the correct information in our preprint.<br /> 3. Dr. Argoaic seems to have been given a wrong and earlier version (10/26) of the data which, although contains a variable that is supposed to correct the above problem, does not. In fact one cannot come to any conclusion that there is a discrepancy based on this incorrect 10/26 version, unless you have some preconceived notion.<br /> 4. Other post hoc analyses reported in follow up works (including social media) by the original authors looking at time from last exposure, or using a pooled placebo group, although flawed for a several reasons, when examined closely, nonetheless support our conclusions that early PEP prophylaxis with HCQ is associated with a reduction of C19.

Detail:<br /> Any confusion about "days" would disappear once the original authors correct the NEJM June 2020 paper as well as a follow up letter in Dec 2020 Clin Infect Dis (see upper red graph in Nicol et al. pubmed.ncbi.nlm.nih.gov/332... "pubmed.ncbi.nlm.nih.gov/33274360/)"). These errors inflate the "DAYS" by 1 day because the nomenclature for describing "days" was incorrect. As far as we know those corrections have not been made in the journals where these errors appear and in a way that can be retrieved in pubmed etc..

As far as we can tell, anyone who has cited the NEJM paper (NIH guidelines, NEJM editorial, many meta-anlayses etc., our protocol in preprint version) also misunderstood the "days" to mean the inflated figure. So the authors need to correct this. As far as we know we are the only ones to do this. After we were informed of this error by the PI (who was unaware of the problem himself) we described this problem very clearly in our preprint, distinguishing between elapsed time and the day on which a study event occurred. For the benefit of those who remain confused, we will endeavor to make it even clearer in a future version. You can read our correspondence log referenced in the preprint to verify that the incorrect "days" nomenclature was unknown to the PI, at least until 10/27 when he informed us about it.

You are confusing "DAY ON which an event occurred" with "DAYS FROM when an event occurred." For example the original NEJM Table 1 says "1 day, 2 days etc." for "Time from exposure to enrollment". This falsely inflates the number of elapsed time days by 1, and as the authors informed us (documented in our preprint), this really means DAY ON which enrollment occurred, with Day 1 = day of exposure, so you need to subtract 1 from the days to get elapsed time FROM exposure. The same error is repeated in Nicol et al. (note: we discuss other unrelated issues relating to time estimates in our preprint).

To confuse matters further, the problem is not even corrected in the dataset linked (datestamp 10/26/20) in the Argoaic comment. In column FS there is a variable "exposure_days_to_drugstart." This appears to indicate elapsed time (ie DAYS FROM) when it actually means the "DAY ON" nomenclature. We were only informed of the nomenclature error on 10/27/20 and later provided with a new version of the dataset on 10/30 where an additional variable "Exposure_to_DrugStart" (column GR) was provided that corrects this error by subtracting 1 from all the values.

Why the Argoaic comment does not link to the correct 10/30 version is unclear, but in this incorrect 10/26 version, the values for the new variable "Exposure_to_DrugStart" (column GR) are IDENTICAL to those in the "exposure_days_to_drugstart" (column FS) variable (they should be smaller by 1). Accordingly, unless Drs. Argoaic and Artuli had a preconceived notion (without checking the data) that some alteration had occurred, it is impossible to draw such a conclusion (albeit one that is incorrect for other reasons) from this incorrect 10/26 dataset. A number of colleagues have downloaded the 10/26 dataset from the link provided in the Agoraic comment, and have verified this problem.

So in addition to the original data set released in August 2020, as well as the three revisions (9/9, 10/6 and 10/30) we describe in our preprint there is this incorrect 10/26 version. I don't know how many people this affects but it would be appropriate for them to be notified that the version they have may be an incorrect one. An announcement on the dataset signup page covidpep.umn.edu/data would also be in order (nothing there today).

Regarding the possibly higher placebo rate of C19 on numbered day 4 (18.9%). This is matched by a commensurate change in its respective treatment arm, yielding RR=0.624 similar to that for numbered days 2 (0.578) and 3 (0.624), justifying pooling. We don't know if the 18.9% represents normal variation or has biological meaning.

Although they used enrollment time data (completely irrelevant to considering whether or not early prophylaxis is beneficial), the original authors (Nicol et al.) in a post hoc analysis, used a pooled placebo cohort to compare daily event rates (red bar graph). This would mitigate possible effects of an outlying value in the placebo cohort. We applied this same pooled placebo method to the data that correctly takes into account shipping times. This method is still limited because it may obscure a poorly understood relationship between time and development of Covid-19. Although at best this would be considered a sensitivity analysis, we did it to answer the Artuli question. This approach yields the same trends as our primary analysis. Using 1-3 days elapsed time of intervention lag (numbered days 2-4) for Early prophylaxis, there is a 33% reduction trend in Covid-19 associated with HCQ (RR 0.67 p=0.12). Taking only 1-2 days elapsed time intervention lag, we obtain a 43% reduction trend (RR 0.57 p=0.09). This analysis appears to reveal a strong regression line (p=0.033) of Covid-19 reduction and intervention lag.

We also looked at the post hoc analysis provided by the original authors (Nicol et al.) that used “Days from Last Exposure to Study Drug Start,” a variable not previously described in the publication, protocol or dataset, so we have no way of verifying it from the raw data. As in a similar PEP study (Barnabas et al. Ann Int Med) this variable has limited (or no) value, as we are trying to treat as quickly as possible from highest risk exposure, not an event (ie Last Exposure) that occurs at an undefined time later. (even the use of highest risk exposure has some limitation, which the authors pointed out to us and which we discuss in our preprint). Further the Nicol analysis used a modified ITT cohort, rather than the originally reported ITT cohort. with these limitations, pooling data for days 1-3 and comparing with the pooled placebo cohort (yields a trend reduction in C19 associated with HCQ (it is unclear which "days" nomenclature is used) after last exposure from 15.2% to 11.2% (RR 0.74, p=0.179).

Taken together with these "sensitivity" analyses inspired by the original authors' methodology, suggests that this is not an artifact of subgroup analysis. It could be said that any conclusions made by the sort of analyses conducted by Nicol are equally prone to the "subgroup artifact" problem. (also note that in our paper, the demographics for placebo and treatment arms in the early cohort match well).

Mention has been made elsewhere of two other PEP studies (Mitja, Barnabas) which concluded no effect of HCQ. It is important to note that the doses used in these studies were much lower than those used in the Boulware et al. NEJM study. Further, according to the PK modelling of the Boulware group (Al-Kofahi et al.) these doses would not have been expected to be efficacious (the Barnabas study used no substantial loading dose). So citing the Mitja and Barnabas studies to support claims of HCQ inefficacy in the Boulware et al paper is unjustified. On the contrary, taken together three studies suggest a dose-response effect. We discuss this in detail in our preprint.

Lastly it is important to note the since the original NEJM study was terminated early, the entire original analysis can be thought of as a subgroup analysis, with all of the attendant problems referenced by the original authors (and us). There is certainly a great deal of under powering and propensity to Type 2 errors, among the issues inherent in a pragmatic study design. The study was not powered as an equivalence study and so no definitive statement can be made that the HCQ is not efficacious. Along with the still uncorrected (in the original journal) issues of shipping times, "days" nomenclature and exposure risk definitions, there are are certainly many efficacy signals that oppugn the original study conclusions,and controvert the statement made in a UMN press release (covidpep.umn.edu/updates) "covidpep.umn.edu/updates)") that the study provided a "conclusive" answer as to the efficacy of HCQ.

_________________<br /> Please note that despite our offer to Dr. Argoaic to contact us directly to walk though the data to try to identify any issues, we have not been contacted.That offer is still extended to anyone who remains confused. We have also attempted to locate both Drs. Argoaic and Artuli to try to clear up their confusion, but these names do not exist in the mainstream literature (i.e pubmed, medrxiv), nor do they appear to have any kind of internet footprint.

With regard to Table 1 of our preprint, the reason why there are no patients for “Day 1” is that there were no patients who received drug the same day as their high-risk exposure. This is consistent with the PIs comment on 8/25/20 (p10 of email log) (at a time when he thought that there was a “Day zero”) “Exposure time was a calculated variable based date of screening survey vs. data of high risk exposure. Same day would be zero. (Based on test turnaround time, I don’t think anyone was zero days).”

We notice an obvious typo in the heading for the second column of our Table 1, which says “To”. But it should say “nPos”, to match the 5th column (and other tables). It is patently absurd that there should be a category of “1 to 0” days or “7 to 5” days etc. “From” makes no sense either and these typos have absolutely no effect on the analysis, interpretation or conclusions. This will be corrected in a later version.

On 2021-07-04 05:23:23, user PriyankaPulla wrote:

Major protocol violations occurred at the largest site of the Covaxin phase 3 trial, a private hospital called People's Hospital, which recruited 1700 participants. These violations are documented extensively by multiple media outlets. And these violations raise questions about the integrity of the Phase 3 trial data. They also raise questions about the sponsors' attitude to due process, and the independence/training of the DSMB: both sponsors (the Indian Council of Medical Research and Bharat Biotech) responded to the allegations with cursory dismissals, while the DSMB remained mum.

Further details here: https://www.thequint.com/co...

I am listing a few of the documented irregularities:

1. Participants told media outlets that they didn't give their informed consent, an Indian legal requirement. Many participants belonged to disadvantaged tribal communities/were illiterate, which necessitates special consent protocols under Indian law, which investigators didn't follow.

Investigators admitted in a video-recorded press conference that they didn't give participants a copy of their informed-consent form during their first visit, unless participants explicitly asked for it. This strongly suggests that the investigators weren't trained in Indian legal requirements or Good Clinical Practices.

1. Investigators allegedly advertised the trial as a vaccination drive in communities of poor and illiterate people.

2. Dozens of participants say the trial team did not contact them to record solicited adverse events. These participants often didn't have their own mobile phones (mobile phones are the mode through which solicited adverse events were to be collected, as per trial protocol). Even though these participants came from poor communities, investigators didn't foresee the fact that they may not have their own mobile phones, and may be hard to contact. Nor did they attempt to contact them in their homes in the days following the doses.

3. People's Hospital recruited a record 1700 participants in 1.5 months (no other Covaxin trial site in India managed such numbers). In contrast, another government-run Covaxin site in Bhopal struggled to even recruit a few hundred participants, and was, therefore, excluded from the trial. This supports the allegation that People's Hospital misadvertised the trial as a vaccination drive.

4. Many participants told media outlets that they suffered Covid-like symptoms post jab, but the investigators never called them to collect this information. Nor did the participants know where to report their symptoms. This raises questions about how well Covid cases were recorded.

5. Participants say they were denied medical treatment at People's Hospital when they fell sick. This, again, raises questions about how well the investigators captured adverse-events.

6. When one participant at the Bhopal site died, investigators ignored his family's version of the participant's symptoms in their causality analysis. In the family's version, the participant suffered from very severe symptoms (vomiting, dizziness, weakness) for 7-8 days before death, while the investigators claimed he was fine during solicited-adverse event monitoring, and died suddenly.

The dismissal of the family's version of events, when the family was present during the participant's death (but the investigators weren't), raises serious questions about how Serious Adverse Events are investigated. No post-mortem report or causality analysis was shared with the family despite multiple requests. Further, the family alleges that the deceased participant received no phone calls from the investigators to record solicited adverse events in the days leading up to his death.

The investigators could easily have shared proof of their claims by sharing a record of the phone calls with the family. They haven't.

Despite the above serious concerns (which are supported by video testimony from participants broadcast on multiple media outlets, specifically NDTV), the trial's government sponsor, ICMR, and Bharat Biotech, denied all allegations in a cursory manner. Further, the preprint makes no mention of them, or explain how these irregularities were handled.

This raises questions about overall data integrity in Bharat Biotech's phase 3 trial. Bharat Biotech has been under substantial pressure from the government to roll out Covaxin fast, which may explain why the company is overlooking such data integrity issues. More details here: https://www.livemint.com/sc...

Reviewers of this paper, and licensing authorities, including the World Health Organisation, must investigate these allegations thoroughly.

On 2021-08-28 18:17:03, user Squid Pro Crow wrote:

Despite the fact that I have no formal medical training, I think that I now have the real life experience to knowledgeably comment on this. My wife and I both had our second doses of the Phizer just under 5 months ago. Also my daughter and son-in-law had the Pfizer shots about 3-1/2 or 4 months ago. At the end of a 3 day stay of 2 grandkids i began to get a cough and slight fever, and lost my sense of smell and taste. So I got tested and it was positive, My wife has a cough and body aches and will be tested today. My daughter and son-in-law (in their low 40's) are also experiencing mild symptoms and will be tested today. The kids, of course had very minor symptoms for about a day, and are completely fine. So, assuming that the adults test positive, it seems evident that the delta strain does indeed spread rapidly and easily, and the vaccine(s) may not be as effective against it. HOWEVER, I feel that at my age, with asthma and possibly COPD history, I would be much worse off had I decided against the vaccine, as my symptoms are very mild now, except for the chest congestion that I have (which is already better) that I also get from just about every cold.

My main concern is that there is not enough focus on theraputics, and major health providers like Kaiser just expect even their at-risk patients like me to just sit at home and wait to see if their lips turn blue and they can't breathe, and make it to an E.R. for a company that is usually proactive about health care, this is just stupid. An apparently, this is the norm. There are some treatments that are effective if taken early, but our government and the health system that follows their dictates are afraid to prescribe safe drugs off-label that are semi-proven to be very helpful, like ivermectin, which I managed to get from a nearby Dr. It seems to be helping clear it up even faster--my sense of smell is even starting to come back.

On 2020-09-08 12:00:16, user Wendy Olsen wrote:

I noted that the assumptions going into this model are a consistent proportion of Overseas and Home students, and a similar size student body, as last year. In addition the cases arriving at UK campuses would be over half from UK Home Students. So even if the assumption of consistent proportion from Overseas turns out untrue, there is still the problem that having more UK Home students will bring more cases into the campuses. I also noted the summary, written by the authors:

Their core estimate is that "81% of the 163 UK Higher Educational Institutes (HEIs) have more than a 50% chance of having at least one COVID-19 case arriving on campus when considering all staff and students. Across all HEIs it is estimated that there will be a total of approximately 700 COVID-19 cases (95% CI: 640 - 750) arriving on campus of which 380 are associated from UK students, 230 from international and 90 from staff. This assumes all students will return to campus and that student numbers and where they come from are similar to previous years. According to the current UK government guidance approximately 237,370 students arriving on campus will be required to quarantine because they come from countries outwith designated travel corridors. Assuming quarantining is 100% efficient this will potentially reduce the overall number of cases by approximately 20% to 540 (95% CI: 500 - 590). Universities must plan for COVID-19 cases ... and ... reduce the spread of disease. It is likely that the first two weeks will be crucial to stop spread of introduced cases. Following that, the risk of introduction of new cases onto campus will be from interactions between students, staff and the local community as well as students travelling off campus for personal, educational or recreational reasons.

"COVID-19 has resulted in the on-campus closure of HEIs across the UK in March 2020 (1). Since that point universities have been working predominantly as virtual establishments with most staff working from home. Autumn sees the start of the new academic term with the potential return of more than 1.5 million UK and almost half a million international students (2).

"The COVID-19 pandemic continues ... approximately 1000 new cases reported each day in the UK, 25,000 across Europe and 250,000 worldwide ((3) accessed 28/03/20). There have been a number of outbreaks of COVID-19 reported in universities in the USA (The University of North Carolina, Notre Dame in Indiana, Colorado College, Oklahoma State and University of Alabama (4)) where the national infection rate is approximately 10 times higher than the UK (3). advice ...(5, 6). However, it is currently unknown to what extent COVID-19 will be brought to campus by staff and students whether from the UK or abroad."

On 2020-10-25 19:08:24, user Daniel Haake wrote:

Dear study team,

Thank you for your study, which shows that the risk of COVID-19 death increases significantly with age. To improve the quality of the study I have some comments regarding the statistical analysis of the study. In the following I would like to go into it.

The time of the determination of the death figures

You write that antibodies are formed in 95% of people after 17-19 days. In contrast, 95% of deaths are reported after 41 days. That is a difference of 22-24 days. Nevertheless, you take the number of deaths 28 days after the midpoint of the study. Why do you take a later point in time than you yourselve have determined? Even with this approach, you are 4 - 6 days too late and overestimate the number of deaths. Why even this would be too late, I will explain in more detail below.

The 41 days were given for the USA. But what is the situation in other countries? In Germany, for example, there is a legal requirement that the death must be reported after 3 working days at the latest. Of course there can also be unrecognized deaths in Germany, where it takes longer to report. But this should be the minority. If we transfer however this fact of the USA to other countries, in which the risk of the long reporting time does not exist in such a way, you take up too many deaths into the counter of the quotient with. This leads to a too high IFR.

Counting the deaths 28 days after the study midpoint is also problematic because in the meantime, further deaths may appear in the statistics that were not infected until after the infected persons identified in the study became infected. This is because not all deaths take as long to report. These are then deaths that are not related to the study. You yourself write that the average value of the report of a dead person lasts 7 days with an IQR of 2 - 19 days. These figures speak in the statistical sense for a right-skewed distribution in the reporting of death figures. This in turn means that the majority of the deceased have a rather shorter reporting time. The procedure leads to a too high number of deaths. This is a problem especially with still existing infection waves, even with already declining infection waves.

You write: “The mean time interval from symptom onset to death is 15 days for ages 18–64 and 12 days for ages 65+, with interquartile ranges of 9–24 days and 7–19 days.”<br /> If we assume the 3 days reporting time for Germany, we receive 18 days for the age 18-64 and 15 days for 65+. In contrast, 95% of the antibodies are formed after 17-19 days, which is about the same or later than the time when the dead appear in the statistics. For other countries this may be different and would therefore need to be investigated. In any case, a blanket assumption from the USA is not possible for studies outside the USA.

Since the mean time interval from onset of symptoms to death is 15 days for the age 18-64 with the interquartile range of 9-24 days, but the midpoint of the range would be 16.5 days, this suggests a right-skewed distribution in the values. The same applies to the mean time interval from the onset of symptoms of 12 days with interquartile range of 7-19 days for the age 65+, where the midpoint of this range is 13 days. This also speaks for a right-skewed distribution of the values. This would mean that the majority of the values would be below the mean value in each case, making shorter times more likely. This also shifts the time too far back. Therefore it would be better to assume the median value, because it is less prone to outliers.

Your example infection wave from figure 1 also shows the problem with this procedure. As you say, antibodies are formed in 95% of people after 17 - 19 days. Now you have an example study with the median 14 days after the start of infection. At that time, only a few of the infected persons have formed antibodies at all, since just 14 days before the infection wave starts with low numbers and then increases. Only 4 days before is the peak of the infection wave. This means that the time period, which is very strongly represented, cannot have developed any antibodies at all. This leads to the fact that only very few infected persons are recognized as infected. In your example, 95% of the deceased are now infected, but only very few of the infected. This leads to a clear overinterpretation of the IFR.

Due to the problems mentioned, the number of deaths should therefore be taken at the median time of the study. Of course, it would be best if the studies took place immediately after the end of a wave of infection, where the death rates are stable and the expression of antibodies is complete.

Antibody Studies

You write: "A potential concern about measuring IFR based on seroprevalence is that antibody titers may diminish over time, leading to underestimation of true prevalence and corresponding overestimation of IFR, especially for locations where the seroprevalence study was conducted several months after the outbreak had been contained.“

You have made many assumptions about the death figures and adjusted the death figures (upwards) accordingly. Here you find that the antibodies disappear over time and that this can lead to an underestimation of the number of infected persons. However, you do not adjust the number of infected persons upwards, unlike your approach to adjusting the death figures. For example, a study by the RKI found that 39.9% of those who tested positive for PCR before did not develop antibodies (https://www.rki.de/DE/Conte... "https://www.rki.de/DE/Content/Gesundheitsmonitoring/Studien/cml-studie/Factsheet_Bad_Feilnbach.html)"). From this, we could conclude that the antibody study only detected around 60% of those previously infected and that the number of infected persons would have to be adjusted accordingly. But you have not done that. I can understand that you did not do that. I wouldn't have done it either, because we don't know how this is transferable to other studies. But in adapting the dead, you have transferred such assumptions to other studies. This should therefore also be avoided. There, too, we do not know how transferable it is. If you only make an adjustment in the dead, but not justifiably in the infected, this leads to an overestimated IFR.

PCR tests from countries with tracing programs

You write in your appendix D: "By contrast, a seroprevalence study of Iceland indicates that its tracing program was effective in identifying a high proportion of SARS-CoV-2 infections“.

In my opinion this is a wrong conclusion. In my opinion, it is not the success of the tracing program, but the number of tests and thus fewer unreported cases. To date, Iceland has performed almost as many tests as there are inhabitants in Iceland. Therefore they could keep the number of unreported cases lower. Other countries did not test as much. Therefore the results are not easily transferable to other countries. The PCR tests only show the present, but not the past and not the untested.<br /> You write it yourself: „(…) hence we make corresponding adjustments for other countries with comprehensive tracing programs, and we identify these estimates as subject to an elevated risk of bias.“<br /> Nevertheless, you leave these studies in meta-analysis, although for the reasons mentioned above this leads to severe problems. The figures for countries with tracing programs should therefore not have been included. The estimated number of unreported cases is not known and cannot be taken over by Iceland.

Study selection

You sort out some seroprevelence studies. These include Australia [63], Blaine County, Idaho, USA [67], Caldari Ortona, Italy [72], Chelsea, Massachusetts, USA [73], Czech Republic [75], Gangelt, Germany [79], Ischgl, Austria [81], Riverside County, California, USA [98] , Slovenia [101] and Santa Clara, California, USA [116]. For the most part, these studies are sorted out because there is no age specification for seroprevelence. Since this is the study's investigation, this is of course understandable. However, these studies in particular have shown calculated IFR values between 0.1% and 0.5%. At the same time, you leave the numbers of PCR tests from countries with tracing programs in the meta-analysis. As already mentioned, this is not correct due to the unknown dark figure and the transfer from Iceland is also not possible, as described before. This leads to the fact that studies with low values are sorted out, but at the same time uncertain numbers with high values are left in the study. This shifts the calculated IFR value upwards in purely mathematical terms.

It is precisely the outliers upwards that cause problems in the calculation. Since the numbers are rather small (in a mathematical sense), there can be no deviation as strong downwards as upwards. This means that there may be studies that deviate perhaps 0.2 percentage points downwards, but other studies that deviate upwards by 1.2 percentage points. This is a problem for the regression, because the regression then leads to too high values. Therefore, outlier detection should be performed upstream and the outliers should be excluded. You can also make it easier by taking the median value, since it is less susceptible to outliers. But then you would have only one value.

You write: “The validity of that assumption is evident in Figure 3: Nearly all of the observations fall within the 95% prediction interval of the metaregression, and the remainder are moderate outliers.”<br /> You can see it in figure 3, but due to the logarithmic scale it is difficult to estimate the ratios. Better suited is Figure 4, which would be desirable for the different age groups to be able to make a better estimation there. Figure 4 shows that many studies are outside the confidence interval, often to a considerable extent and to a greater extent also towards the high IFR values. Looking at the values and the confidence interval, these studies must have significant z-scores, which would show that these are clearly outliers that should not be considered. This leads to the fact that the regression will be brought further in the direction of high values, which results in too high IFR values.

Adjustment of death rates for Europe due to excess mortality

In Appendix Q you write: "In the absence of accurate COVID-19 death counts, excess mortality can be computed by comparing the number of deaths for a given time period in 2020 to the average number of deaths over the comparable time period in prior calendar years, e.g., 2015 to 2019. This approach has been used to conduct systematic analysis of excess mortality in European countries.[159] For example, the Belgian study used in our metaregression computed age-specific IFRs using seroprevalence findings in conjunction with data on excess mortality in Belgium“

I understand why you want to do this. But there are some dangers involved. The above statement may be true for Belgium, but it cannot be transferred to other countries in a general way. Especially since you cannot say in general terms that every dead person above average is a COVID 19 dead person. Mathematically, this would mean that there have been COVID-19 deaths in some of the last few years, because there have been periods with more deaths than the average. This makes the average straight. Especially since, as I said, you can't simply say that every death above the average is a COVID-19 death. The majority will be it, but not necessarily everyone. Thus, even cancer operations that did not take place or untreated heart attacks due to the circumstances and unnoticed visits to the doctor may have contributed a share. Whether this is the case, we do not know without a study. A blanket assumption that every death above the mean value is a COVID-19 death is not correct. From the statement "For example, the Belgian study used in our metaregression computed age-specific IFRs using seroprevalence findings in conjunction with data on excess mortality in Belgium", we could also conclude that the number of reported COVID-19 deaths is correct and can therefore be used as the numerator of the quotient for calculating the IFR. <br /> If you take this as a blanket assumption, how do you deal with those countries that do not have excess mortality but have several thousand COVID-19 deaths in the official statistics? Would you then correct the number of COVID-19 deaths downwards, perhaps even to 0? Certainly not.

Variation in the IFR

You write: "We specifically consider the hypothesis that the observed variation in IFR across locations may primarily reflect the age specificity of COVID-19 infections and fatalities.“

It is also possible that the variation in the calculated IFRs occurs due to still different dark figures. If, for example, the PCR tests are taken in countries with a tracing app, but an IFR based on Iceland is calculated there, this can lead to incorrect and too high IFR values. Also the adjustments of the death rates themselves or the late time of the death rate determination 4 weeks after the study center can lead to this high variance.

Conspicuous features regarding the correct determination of the death figures

In Table 1 you write that on July 15 there were 8 million inhabitants with a projected 1.6 million infections. According to my research there are 8.4 million inhabitants. You calculate the 1.6 million infected on the basis of the 22.7% infected in the study. However, the blood samples were taken between April 19 and 28, so the infections occurred before or until the beginning/middle of April. So you now take the number of infected persons from the beginning/mid-April or from April 24 (study midpoint) and insert them for July 15, i.e. just under 3 months later! In the meantime, however, not only people have died, but have also become infected and formed antibodies. They thus increase the numerator of the quotient, but leave the denominator unchanged, although the denominator would also be higher. So you shift the IFR upwards here as well.

The study on Gangelt, which was not taken into account, shows a similar picture. You write that at the end of June there were 12 deaths and therefore the IFR rises to 0.6%. That is 8 weeks (!) after the study center. This does not take into account that in Germany the deaths must be reported after 3 days. If you have proceeded in this way when calculating the other IFRs from other studies, this suggests that the IFR values are too high.

Calculation of the IFR of Influenza

You calculate the IFR of influenza based on the CDC figures for the 2018/2019 influenza season and indicate the IFR as 0.05%. Firstly, it should be said that statistically it is never good to look at just one value. The average of a time series should be considered. You calculate the value by looking at the estimated deaths and looking at how many were estimated to be symptomatically infected with influenza. You use a study according to which about 43.4% of cases are asymptomatic or subclinical (95% CI 25.4%-61.8%). You then take the mean value from the confidence interval with the value 43.6% and use this figure to calculate how many people were probably infected with influenza. Statistically it is not correct to take the average value of 43.6%. The value of 43.4% must be taken. Due to the small difference, this does not make much difference, but it shows the statistically imprecise consideration that runs through the study and generally leads to an IFR that is too high or, in the case of influenza, too low.

Now a statement on the selection of the 2018/2019 flu season, the CDC writes: "These estimates are subject to several limitations. (...) Second, national rates of influenza-associated hospitalizations and in-hospital death were adjusted for the frequency of influenza testing and the sensitivity of influenza diagnostic assays, using a multiplier approach3. However, data on testing practices during the 2018-2019 season were not available at the time of estimation. We adjusted rates using the most conservative multiplier from any season between 2010-2011 and 2016-2017, Burden estimates from the 2018-2019 season will be updated at a later date when data on contemporary testing practices become available. (...) Fourth, our estimate of influenza-associated deaths relies on information about location of death from death certificates. However, death certificate data during the 2018-2019 season were not available at the time of estimation. We have used death certification data from all influenza seasons between 2010-2011 and 2016-2017 where these data were available from the National Center for Health Statistics. (…)

The CDC writes the same for the 2017/2018 season, so the values, which were always only estimated anyway, were estimated even more due to missing data. Therefore we should have considered the figures for the seasons 2010/2011 to 2017/2017. If we calculate the IFR of influenza in this way and also use the confidence interval to calculate the number of people potentially infected per season, we get an IFR of influenza of 0.077%, ranging from 0.036% to 0.164%. Every single year prior to the 2018/2019 season was above the 0.05% and the average of 0.077% is also 54% above your reported value. This means that influenza is still not as lethal as COVID-19 has been so far, but the factor is not as high as suggested by your study.

It should also be noted that it is not possible to compare an IFR calculation that is equally distributed over age with an IFR of influenza that is not equally distributed over age. You do not do it directly, but by naming these numerical values, this has been taken up by the media. The IFR just indicates the mortality per actually infected person. Therefore the IFR of the actually infected persons of COVID-19 must be compared with the IFR of influenza. You can of course calculate a hypothetical IFR assuming that every age is equally likely to be infected. In this case, however, the calculation must be performed not only for COVID-19, but also for influenza.

I hope I can help you to improve the study in terms of statistical issues. I remain with kind regards.

On 2019-11-12 00:51:39, user Guyguy wrote:

EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AT NOVEMBER 10, 2019

Monday, November 11, 2019<br /> Since the beginning of the epidemic, the cumulative number of cases is 3,287, of which 3,169 confirmed and 118 probable. In total, there were 2,193 deaths (2075 confirmed and 118 probable) and 1067 people cured.<br /> 411 suspected cases under investigation;<br /> No new cases confirmed;<br /> No new deaths of confirmed cases have been recorded;<br /> 3 people healed from the CTE in North Kivu in Mabalako;<br /> No health workers are among the newly confirmed cases. The cumulative number of confirmed / probable cases among health workers is 161 (5% of all confirmed / probable cases), including 41 deaths;

NEWS

Awareness and vaccination day for Beni mototaxi drivers with the support of Unicef S / Coordination MVE Beni, Wednesday 06-11 - 2019 HIVUM room

• There were many, about three hundred, the drivers of Mototaxi Beni invited to a day of awareness and vaccination against Ebola Virus Disease this Wednesday, November 06, 2019 in the HIVUM room.

• This day is welcome for the city of Beni during this period of EVD epidemic which, unfortunately, displays a lethality of 86.3% among motorcyclists, as pointed out by Dr. Pierre ADIKEY, Coordinator of the response of Sub Coordination of Beni.

• Thus, in his presentation, he focused his message on the risk of transmission of EVD among motorotaxi drivers and the conduct to be held in the exercise of their craft to protect themselves and the community.

• He asked bikers more often to respect the measures of prevention, namely: washing hands regularly, stopping at checkpoints, not being bribed to divert checkpoints, not carrying suspicious parcels and reporting and / or direct any suspicions of illness to colleagues or the community.

• In order to circumscribe the day, Dr. P. ADIKEY traced the path of the last Motard who died of EVD before his death confirmed at the CTE. To close his presentation, he made a reminder of the various events that prevented the teams of the response from working: among other things the days of the dead city, the fire of the vehicles of the riposte, the destruction of the structures of the care, the cases of resistance and others whose bikers were part of it.

• Dr. Bibiche MATADY, as Epidemiologist and Chair of the Monitoring Commission, introduced to the participants the importance of accepting to be listened to if you are in contact with a case, to let yourself be followed for the entire period indicated and to orient in a management structure as soon as the first sign appears. She also emphasized the collaboration between the bikers and the teams of the response.

• To justify this day again, one of the 3 Hikers shared his testimony and urged his colleagues to collaborate and follow the recommendations of the response teams starting with vaccination.

• Vaccination is one of the preventive measures against EVD, said Dr Adonis TERANYA, the Chair of the Immunization Subcommission. In his presentation, he explained the evolution of the vaccination protocol, the current targets, the side effects and the action to take in the event of an adverse event. Before calling for the voluntary vaccination of participants, he spoke about vaccines currently used in the DRC.

• In his words, the President of Bikers reiterated to the Coordinator the commitment of his organization and all its members to support the interventions of the response, while affirming its availability to any solicitation for the fight against the disease to Ebola virus in the city of Beni and its surroundings.

• The day ended with the vaccination of 100 Bikers and some of their dependents.

VACCINATION

• Since vaccination began on 8 August 2018, 250,234 people have been vaccinated;
• The only vaccine to be used in this outbreak is the rVSV-ZEBOV vaccine, manufactured by the pharmaceutical group Merck, following approval by the Ethics Committee in its decision of 20 May 2018.

MONITORING AT ENTRY POINTS

• Since the beginning of the epidemic, the total number of travelers checked (temperature rise) at the sanitary control points is 115,778,240 ;
• To date, a total of 111 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.

As a reminder, the recommendations of the MULTISECTORAL COMMITTEE OF THE RESPONSE TO EBOLA VIRUS DISEASE are as follows:

1. Follow basic hygiene practices, including regular hand washing with soap and water or ashes;
2. If an acquaintance from an epidemic area comes to visit you and is ill, do not touch her and call the North Kivu Civil Protection toll-free number;
3. If you are identified as a contact of an Ebola patient, agree to be vaccinated and followed for 21 days;
4. If a person dies because of Ebola, follow the instructions for safe and dignified burials. It is simply a funeral method that respects funerary customs and traditions while protecting the family and community from Ebola contamination.
5. For all health professionals, observe the hygiene measures in the health centers and declare any person with symptoms of Ebola (fever, diarrhea, vomiting, fatigue, anorexia, bleeding).<br /> If all citizens respect these health measures recommended by the Secretariat, it is possible to quickly end this 10th epidemic.

On 2019-11-15 16:53:09, user GuyguyKabundi Tshima wrote:

EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AS AT NOVEMBER 13, 2019

Thursday, November 14, 2019

• Since the beginning of the epidemic, the cumulative number of cases is 3,292, of which 3,174 are confirmed and 118 are probable. In total, there were 2,193 deaths (2075 confirmed and 118 probable) and 1067 people cured.<br /> • 527 suspected cases under investigation;<br /> • 1 new case confirmed in North Kivu in Mabalako;<br /> • No new deaths of confirmed cases have been recorded;<br /> • No cured person has emerged from ETCs;<br /> • No health worker is among the new confirmed cases. The cumulative number of confirmed / probable cases among health workers is 163 (5% of all confirmed / probable cases), including 41 deaths;

NEWS

Ebola Virus Disease Response Co-ordination Announces Three Road Traffic Accident in Bunia, Ituri

• The overall coordination of the response to the Ebola Virus Disease epidemic in North, South Kivu and Ituri was informed on Thursday 13 November 2019 of the tragic traffic accident between two motorcycles, one of which carried three agents of the riposte;<br /> • These three officers, who work for the Epidemiological Surveillance Commission at the Point of Entry and Control, were returning from Bunia to Mambasa, where they are respectively delivering;<br /> • This accident occurred around Marabo in Bunia on the evening of Wednesday 13 November 2019;<br /> • The balance sheet reports an officer who died at the scene and two others who were seriously injured, including one in a coma. The two wounded were taken to the Nyakunde Reference General Hospital in Ituri for appropriate care;<br /> • The overall coordination of the response sends its deepest condolences to the grieving family and expresses all its compassion and solidarity to the injured officers, while wishing them a quick recovery.

Effective start of Johnson & Johnson vaccination in two Goma health areas

• Ebola vaccination with the Ad26.ZEBOV / MVA-BN-Filo vaccine, produced by Janssen Pharmaceuticals for Johnson & Johnson, began on Thursday, November 14, 2019 in two Karisimbi health areas in Goma City , North Kivu Province;<br /> • The Epidemic Response Coordinator for Ebola Virus Disease in North, South Kivu and Ituri. For this purpose, Prof. Steve Ahuka Mundeke visited the vaccination sites to inquire about the evolution of activities in the field. He was satisfied with the work of the teams;<br /> • He took the opportunity to invite the population of the targeted areas to be vaccinated in order to protect themselves from the resurgence of the Ebola virus;<br /> • Several people were present in Majengo and Kahembe health areas to get vaccinated. The first person to be vaccinated is a Kahembe community leader who has been protected against the Ebola virus today and also in case of a possible new Ebola outbreak. This community leader has appealed to all residents of his community and sites targeted to come take this second vaccine. "This is an opportunity not to be missed, because it is said that prevention is better than cure, " he said;<br /> • The logistics of this vaccination are provided by the international non-governmental organization Médecins Sans Frontières of France (MSF / France).<br /> • Approved October 22, 2019 by the Ethics Committee of the School of Public Health of the University of Kinshasa and October 23, 2019 by the National Ethics Committee, this second vaccine, called Ad26.ZEBOV / MVA-BN -Filo , is produced by Janssen Pharmaceuticals for Johnson & Johnson;<br /> • This new vaccine complements the first, the rVSV-ZEBOV, the vaccine used until then in this epidemic. Manufactured by the pharmaceutical group Merck, after approval of the Ethics Committee on May 20, 2018, it was recently approved.

Closing of the training workshop for media professionals in Beni on the role and responsibility of journalists during public health crises

• The Deputy Mayor of the city of Beni, Muhindo Bakwanamaha Modeste, closed this Thursday, November 14, 2019 in Beni in the province of North Kivu the training of media professionals on the role and responsibility during public health crises;<br /> • The coordinator of the Beni Ebola Ebola response sub-coordination, Dr. Pierre Adikey, on behalf of the Coordinator-General of the Response, Prof. Steve Ahuka, wished to see these kinds of trainings be organized, not only in other sub-Coordination of the response, but also throughout the Democratic Republic of the Congo so that journalists from all over the country are ready to face any possible epidemic crisis;<br /> • This training, he said, is part of the zero-case Ebola strategy and strengthening the health system of tomorrow;<br /> • The focal point of Beni's journalists, Moustapha MULONDA, reaffirmed the commitment of journalists to combat Ebola Virus Disease through various programs and publications disseminated and published by their respective media thanks to the new tools acquired during this period. training;<br /> • This training was organized by the Ministry of Health in collaboration with the World Health Organization and benefited from the facilitation of the overall coordination of the response, UNICEF, CDC Africa and MSF.

VACCINATION

• Since the start of vaccination on August 8, 2018 with the rVSV-ZEBOV vaccine, 251,637 people have been vaccinated;

• Vaccination with the second Ad26.ZEBOV / MVA-BN-Filo vaccine, produced by Janssen Pharmaceuticals for Johnson & Johnson, began on Thursday November 14, 2019 in Goma. This vaccine was approved on 22 October 2019 by the decisions of the Ethics Committee of the School of Public Health of the University of Kinshasa and 23 October 2019 of the National Ethics Committee;

• Until then, only one vaccine was used in this outbreak. This is the rVSV-ZEBOV vaccine, manufactured by the pharmaceutical group Merck, after approval of the Ethics Committee in its decision of 20 May 2018 and which has recently been approved.

MONITORING AT ENTRY POINTS

• A 27-year-old woman from Butembo for Goma, an escaped suspect from Makasi Hospital in Butembo, North Kivu, was intercepted at the Kanyabayonga checkpoint in Kayna. When she was intercepted, she experienced signs such as fever at 38.4 ° C, severe asthenia, abdominal pain and vaginal bleeding. It was sent to the KAYNA Transit Center.

• Since the beginning of the epidemic, the total number of travelers checked (temperature rise) at the sanitary control points is 116,622,388 ;

• To date, a total of 112 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.

As a reminder, the recommendations of the MULTISECTORAL COMMITTEE OF THE RESPONSE TO EBOLA VIRUS DISEASE are as follows:

1. Follow basic hygiene practices, including regular hand washing with soap and water or ashes;
2. If an acquaintance from an epidemic area comes to visit you and is ill, do not touch her and call the North Kivu Civil Protection toll-free number;
3. If you are identified as a contact of an Ebola patient, agree to be vaccinated and followed for 21 days;
4. If a person dies because of Ebola, follow the instructions for safe and dignified burials. It is simply a funeral method that respects funerary customs and traditions while protecting the family and community from Ebola contamination.
5. For all health professionals, observe the hygiene measures in the health centers and declare any person with symptoms of # Ebola (fever, diarrhea, vomiting, fatigue, anorexia, bleeding).<br /> If all citizens respect these health measures recommended by the Secretariat, it is possible to quickly end this 10th epidemic.

On 2019-11-30 17:00:40, user Guyguy wrote:

EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AT NOVEMBER 27, 2019

Thursday, November 28, 2019<br /> • Since the beginning of the epidemic, the cumulative number of cases is 3,309, of which 3,191 are confirmed and 118 are probable. In total, there were 2,201 deaths (2,083 confirmed and 118 probable) and 1077 people healed.<br /> • 443 suspected cases under investigation;<br /> • 5 new confirmed cases, including:<br /> o 4 in Ituri in Mandima;<br /> o 1 in North Kivu in Mabalako;<br /> • 2 new deaths of confirmed cases, including:<br /> o 2 new community deaths in Ituri in Mandima;<br /> o No deaths among confirmed cases in CTEs;<br /> • No cured person has emerged from CTEs;<br /> • No health worker is among the new confirmed cases. The cumulative number of confirmed / probable cases among health workers is 163 (5% of all confirmed / probable cases), including 41 deaths.

NEWS

Three members of the Ebola Virus Epidemic response killed during an attack in Biakato, Ituri

• Following the attack on the sub-coordination of the Biakato response in Ituri on the night of Wednesday 27th to Thursday 28 November 2019, three members of the Ebola response teams in this sector lost their lives ;<br /> • It is a provider and a driver of the vaccination committee and another driver;<br /> • In addition to these three deaths, there are 7 wounded and 6 others with psychological disorders and extensive material damage.<br /> • A good number of these teams from Biakato were evacuated in three waves to Goma. As soon as they arrived, they were greeted by a coordination team led by Prof. Steve Ahuka, general coordinator, who also visited the wounded before going to inquire about the security conditions and accommodation of evacuees. He did not fail to comfort them.

VACCINATION

• The vaccination commission is in mourning. A service provider and a driver of his team were killed on the night of Wednesday 27 November 2019 following attacks at the Biakato base in Ituri;<br /> • 2nd day without vaccination activity with the 2nd J & J vaccine following the disorders initiated by young people related to the security situation in Beni;<br /> • 724 people were vaccinated, until Tuesday, November 26, 2019, with the 2nd Ad26.ZEBOV / MVA-BN-Filo vaccine (Johnson & Johnson) in the two health zones of Karisimbi in Goma;<br /> • Since the start of vaccination on August 8, 2018 with the rVSV-ZEBOV vaccine, 255,373 people have been vaccinated;<br /> • Approved October 22, 2019 by the Ethics Committee of the School of Public Health of the University of Kinshasa and October 23, 2019 by the National Ethics Committee, the second vaccine, called Ad26.ZEBOV / MVA-BN -Filo, is produced by Janssen Pharmaceuticals for Johnson & Johnson;<br /> • This new vaccine is in addition to the first, the rVSV-ZEBOV, vaccine used until then (since August 08, 2018) in this epidemic manufactured by the pharmaceutical group Merck, after approval of the Ethics Committee on May 20, 2018. has recently been pre-qualified for registration.

MONITORING AT ENTRY POINTS

• Sanitary control activities are disrupted in the towns of Beni and Butembo in North Kivu province following demonstrations by the population which decries killings of civilians;<br /> • Since the beginning of the epidemic, the total number of travelers checked (temperature measurement ) at the sanitary control points is 121,159,810 ;<br /> • To date, a total of 109 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.

As a reminder, the recommendations of the MULTISECTORAL COMMITTEE OF THE RESPONSE TO EBOLA VIRUS DISEASE are as follows:

1. Follow basic hygiene practices, including regular hand washing with soap and water or ashes;
2. If an acquaintance from an epidemic area comes to visit you and is ill, do not touch her and call the North Kivu Civil Protection toll-free number;
3. If you are identified as a contact of an Ebola patient, agree to be vaccinated and followed for 21 days;
4. If a person dies because of Ebola, follow the instructions for safe and dignified burials. It is simply a funeral method that respects funerary customs and traditions while protecting the family and community from Ebola contamination.
5. For all health professionals, observe the hygiene measures in the health centers and declare any person with symptoms of # Ebola (fever, diarrhea, vomiting, fatigue, anorexia, bleeding).<br /> If all citizens respect these health measures recommended by the Secretariat, it is possible to quickly end this 10th epidemic.

On 2019-09-30 05:15:29, user Guyguy wrote:

EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AS AT SEPTEMBER 22, 2019

The epidemiological situation of the Ebola Virus Disease dated September 22, 2019

Monday, September 23, 2019

Since the beginning of the epidemic, the cumulative number of cases is 3,168, of which 3,057 are confirmed and 111 are probable. In total, there were 2.118 deaths (2007 confirmed and 111 probable) and 975 people healed. <br /> • 343 suspected cases under investigation; <br /> • 4 new confirmed cases, including: <br /> • 1 in North Kivu in Butembo; <br /> • 3 in Ituri, including 2 in Mandima and 1 in Mambasa. <br /> • 3 new confirmed deaths, including: <br /> • 2 community deaths, including 1 in North Kivu in Butembo and 1 in Ituri in Mambasa; <br /> • 1 confirmed death in Ituri in Mandima. <br /> • No health worker is among the new confirmed cases. The cumulative number of confirmed / probable cases among health workers is 160 (5% of all confirmed / probable cases), including 41 deaths.

NEWS

Beginning of trainers training in Goma on good clinical practices related to the second Ebola vaccine <br /> • The Ebola Virus Disease Response Information Management Coordinator, representing the Technical Secretariat, Mathias Mossoko, launched on Monday in Goma the training of trainers which runs from 23 to 28 September 2019 on the good clinical practices (PCBs) related to the second Ebola vaccine. <br /> • This training benefits from the expertise of CVD's Malians on the transmission of notions about good clinical practice. It aims to provide participants with the standards applicable to the design, conduct, monitoring and stopping of studies, to teach them the activities of audit, analysis, reporting and documentation with the guarantee that these studies 'rely on sound scientific and ethical principles. It is also intended to introduce participants to the correct documentation of the clinical properties of the vaccine tested or evaluated. <br /> • The Response Information Management Coordinator called the attendance participants to demonstrate better actors for the implementation of good practice in this second vaccine. <br /> • For its part, the chairman of the Immunization Committee, Stéphane Hans, said that this five-day training announces the forthcoming launch of the second vaccine that will come at any time in the targeted health zones. "We welcome this supplementary vaccine very positively compared to the first vaccine. This second vaccine has the advantage of preventing all strains of the Ebola virus. It is therefore positive for the population that will receive it, "he said while inviting all communities targeted by this vaccination to take ownership of this activity, once launched. <br /> • The training on good clinical practice will revolve around several presentations on different topics, among others, the Ebola virus disease, the responsibilities of the INRB for the QA system, study vaccines (storage, management, chain cold and accounting), inclusion and follow-up of pregnant women, community involvement and informed consent, etc. <br /> • This training was organized for the different actors involved in this project, including doctors, epidemiologists, clinicians and pharmacists. A total of 25 people from Kinshasa, including the INRB, UNIKIN, CUK and specialized programs and North Kivu, including the Provincial Health Inspectorate (IPS), the Provincial Division of Health Centers (DPS) and Health Zone Coordinating Offices (BCZS) are participating in this meeting. <br /> As a reminder, the recommendations of the MULTISECTORAL COMMITTEE ON THE RESPONSE TO THE EBOLA VIRUS DISEASE are as follows: * <br /> 1. Follow basic hygiene practices, including regular hand washing with soap and water or ashes; <br /> 2. If an acquaintance from an epidemic area comes to visit you and is ill, do not touch her and call the North Kivu Civil Protection toll-free number; <br /> 3. If you are identified as a contact of an Ebola patient, agree to be vaccinated and followed for 21 days; <br /> 4. If a person dies because of Ebola, follow the instructions for safe and dignified burials. It is simply a funeral method that respects funerary customs and traditions while protecting the family and community from Ebola contamination. <br /> 5. For all health professionals, observe the hygiene measures in the health centers and declare any person with symptoms of Ebola (fever, diarrhea, vomiting, fatigue, anorexia, bleeding). <br /> If all citizens respect these health measures recommended by the Secretariat, it is possible to quickly end this 10th epidemic.

VACCINATION <br /> Opening of an expanded vaccination ring around two confirmed cases from 19-21 Sept 2019 in the Madidi health area in Mambasa, Ituri. Another satellite ring was opened at the Kitatumba General Referral Hospital in the Butembo Health Zone in North Kivu around the case notified on 22 09 2019. This case started the disease in the health area of Kasindi in Mutwanga, North Kivu. <br /> • The Expanded Program of Vaccines has received 4320 doses of vaccine at the national level; <br /> • Since vaccination began on August 8, 2018, 226,722 people have been vaccinated; <br /> • The only vaccine to be used in this outbreak is the rVSV-ZEBOV vaccine, manufactured by the pharmaceutical group Merck, following approval by the Ethics Committee in its decision of 20 May 2018.

MONITORING AT ENTRY POINTS <br /> • High-risk contact was intercepted at Kangote PoC in Butembo, North Kivu. This is a 28-year-old unvaccinated woman on the 14th day (D14) follow-up who was listed around a confirmed case in the Katwa Health Zone. During her interception, this woman presented some signs related to the #Ebola Virus Disease. She was sent to the Butembo CTE for treatment. <br /> • Kituku PoC providers in Goma, North Kivu, were assaulted by about 20 onlookers called "Maibobo" who were avenging one of their drowned during the night of 20 to 21 September 2019. These providers feel insecure and ask to be supported by officers of the National Police (PNC) or FARDC. <br /> • Since the beginning of the epidemic, the total number of travelers checked (temperature measurement) at the sanitary control points up to 22 September 2019 is 96,998,860; <br /> • To date, a total of 111 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.

LEXICON <br /> • A community death is any death that occurs outside a Ebola Treatment Center. <br /> • A probable case is a death for which it was not possible to obtain biological samples for confirmation in the laboratory but where the investigations revealed an epidemiological link with a confirmed or probable case.

On 2019-10-04 22:38:03, user GuyguyKabundi Tshima wrote:

EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AS AT 03 OCTOBER 2019

Friday, October 04, 2019

Since the beginning of the epidemic, the cumulative number of cases is 3,201, of which 3,087 are confirmed and 114 are probable. In total, there were 2.139 deaths (2025 confirmed and 114 probable) and 999 people cured.<br /> 451 suspected cases under investigation;<br /> 3 new confirmed cases, including:<br /> 1 in North Kivu in Beni;<br /> 2 in Ituri, including 1 in Mambasa and 1 in Mandima;<br /> 2 new confirmed deaths in North Kivu, including 1 in Beni and 1 in Mabalako;<br /> 4 people healed from the CTE in North Kivu in Beni;<br /> No health workers are among the newly confirmed cases. The cumulative number of confirmed / probable cases among health workers is 161 (5% of all confirmed / probable cases), including 41 deaths.<br /> Day 18 without response activities in the Lwemba Health Area in Mandima, Ituri.

LEXICON<br /> • A community death is any death that occurs outside a Ebola Treatment Center.<br /> • A probable case is a death for which it was not possible to obtain biological samples for confirmation in the laboratory but where the investigations revealed an epidemiological link with a confirmed or probable case.

NEWS<br /> The 10th Ebola Virus Disease epidemic in the DRC reaches its 1000th cure<br /> - The thousandth cured of the Ebola Virus Disease came out Friday of the Mangina CTE in Mabalako in North Kivu Province;<br /> - Indeed, this 1000th cured is part of four healed Friday of this CTE. It is about a woman, quarantine gone, case contact of her nephew with the Air of Health of Lwemba with Mandima in Ituri. As soon as she felt the fever, she went to the Health Center, where she was detected as a suspected case and transferred directly to the CTE. She was confirmed and followed her treatment until recovery. She advises the population to go quickly to the Health Center and not fear the CTE to cure Ebola Virus Disease;<br /> - Among these four cures, there is also a health provider. This is an ambulance hygienist, the 1001 st healed, who was contaminated during the unloading of his personal protective equipment (PPE). He recommended a lot of protection and precautions to all hygienists when removing PPE. And in case of possible contamination, do not panic, but rather go quickly to the Health Center for appropriate treatment;<br /> - For the Ebola Epidemic Epidemic Response Coordinator, Dr. Faustin Bile Saka, these healers will be the ambassadors for the response in their respective communities and testify that when we arrive early we have the chance to come out healed like them. He handed out the certificates of release to the cured, with the various partners of the response, WHO and IMC to the 1000, 1001, 1002 and 1003 th cures of the Ebola Virus Disease in the DRC;<br /> - As a miracle, the 10th epidemic of the Ebola Virus Disease began around the end of July 2018 and declared in early August 2019 in Mangina and it is still in Mangina, where came the 1000th cured.

VACCINATION

• Since vaccination began on August 8, 2018, 232,725 people have been vaccinated;
• The only vaccine to be used in this outbreak is the rVSV-ZEBOV vaccine, manufactured by the pharmaceutical group Merck, following approval by the Ethics Committee in its decision of 20 May 2018.

MONITORING AT ENTRY POINTS

• Since the beginning of the epidemic, the total number of travelers checked (temperature measurement ) at the sanitary control points is 102,092,950 ;
• To date, a total of 111 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.

As a reminder, the recommendations of the MULTISECTORAL COMMITTEE OF THE RESPONSE TO EBOLA VIRUS DISEASE are as follows:

1. Follow basic hygiene practices, including regular hand washing with soap and water or ashes;
2. If an acquaintance from an epidemic area comes to visit you and is ill, do not touch her and call the North Kivu Civil Protection toll-free number;
3. If you are identified as a contact of an Ebola patient, agree to be vaccinated and followed for 21 days;
4. If a person dies because of Ebola, follow the instructions for safe and dignified burials. It is simply a funeral method that respects funerary customs and traditions while protecting the family and community from Ebola contamination.
5. For all health professionals, observe the hygiene measures in the health centers and declare any person with symptoms of # Ebola (fever, diarrhea, vomiting, fatigue, anorexia, bleeding).<br /> If all citizens respect these health measures recommended by the Secretariat, it is possible to quickly end this 10th epidemic.

On 2019-10-07 13:54:02, user GuyguyKabundi Tshima wrote:

EPIDEMIOLOGICAL SITUATION

EVOLUTION OF THE EBOLA EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI OCTOBER 05, 2019<br /> Sunday, October 06, 2019<br /> Since the beginning of the epidemic, the cumulative number of cases is 3,204, of which 3,090 are confirmed and 114 are probable. In total, there were 2,142 deaths (2028 confirmed and 114 probable) and 1004 people healed.<br /> 414 suspected cases under investigation;<br /> No new cases confirmed;<br /> 1 new confirmed death at CTE in Ituri in Komanda;<br /> No one healed out of ETCs;<br /> No health workers are among the newly confirmed cases. The cumulative number of confirmed / probable cases among health workers is 161 (5% of all confirmed / probable cases), including 41 deaths.<br /> Day 19 without response activities in the Lwemba Health Area in Mandima, Ituri, where the dialogue continues in the community.

NEWS

Reconciliation between displaced people from Lwemba to Biakato and communities left in Lwemba in Mandima in Ituri

The Lwemba communities that moved to Biakato in Mandima in Ituri reconciled on Sunday 06 October 2019 with the communities that had remained in Lwemba in the presence of the response team led by the Deputy General Coordinator, Dr. Justus Nsio Mbeta, head of the Cheffery and Mandima MCZ, coordinator of Mangina's sub-coordination of the response, as well as some partners from the Ministry of Health, including WHO, MSF, UNICEF and United Nations ;<br /> - From this meeting, follows the following recommendations: setting up a community committee to support the response, the local recruitment of sensitizers in the monitoring of community-based surveillance, decontamination and the workforce in the community. burning houses. The Ministry of Health has promised the next supply of drugs to Lwemba;<br /> - The Deputy General Coordinator for the Ebola Virus Epidemic Response, representing the Ministry of Health and the Technical Secretariat of the CMRE, Dr. Justus Nsio Mbeta, took this opportunity to recall the regulatory role of the Ministry of Health and the role of each partner involved in the response;<br /> - For the community victim of the fire, they ask for the guarantee of their security, the emergency humanitarian aid, the compensation of their destroyed property and the reconstruction of their burned houses, the commitment or the hiring of all victims in the various services at all levels, the immediate arrest of all the alleged perpetrators of these uncivil acts and the care of the children affected;<br /> - These fires occurred following the death of a nurse from Lwemba, confirmed with Ebola Virus Disease. His death sparked the uprising of the population to burn down the houses and other property of all the unknowns of Lwemba. This remains the cause, even, the cessation of the activities of the response in this Health Area for more than 15 days;<br /> - The leaders of the Lwemba community also asked for the construction of the houses for the displaced, the organization of an intercommunal dialogue session by the Administrator of the territory or his delegate and the rehabilitation of the road leading to Lwemba ;<br /> - In the response, WHO is responsible for epidemiological surveillance, communication and prevention against infection (IPC) and immunization, UNICEF is in charge of communication, psychosocial care and PCI, MSF and ALIMA take care of the treatment of patients in Ebola treatment center and PCI and psychosocial support within CTE, WFP brings food products to contacts, IOM deals with Entry and Control Points (water supply, soap and chlorine);<br /> - As for the National Institute for Biomedical Research (INRB), Dr. Nsio stated that he is in charge of the diagnosis and gives MSF and ALIMA the medicines to treat patients with CTE.<br /> - The World Health Organization has pledged to rebuild burned houses, to provide community surveillance (community watch) and investigations of all suspected cases, as well as to build a transit center in LWEMBA, while UNICEF has pledged to improve communication and awareness through the use of space, to support ICH, decontamination and psychosocial, to provide water sources and to build latrines in 5 priority schools;<br /> - On the other hand, Médecins Sans Frontières intends to help the community of Lwemba to resume primary health care, to organize triage in the Health Zones present in the village and to break the PCI, as well as to train sensitizers;<br /> - At the end of this Lwemba meeting, all partners, including WHO, UNICEF and MSF, met around the Deputy General Coordinator at the Biakato Reference Health Center to review the joint and shared planning of activities in Lwemba.

VACCINATION

• Since vaccination began on August 8, 2018, 234,108 people have been vaccinated;
• The only vaccine to be used in this outbreak is the rVSV-ZEBOV vaccine, manufactured by the pharmaceutical group Merck, following approval by the Ethics Committee in its decision of 20 May 2018.

MONITORING AT ENTRY POINTS

• Three high-risk contacts were intercepted on Saturday 05 October 2019 at Maboya Checkpoint (PoC) in Butembo. They are all from the same family and came from the Kabasha Health Area to Kalunguta for Bunyuka in Vuhovi;
• They are all contacts of a confirmed case, died of the Ebola Virus Disease (EVD) of September 30, 2019 in Kabasha;
• The first contact is an unvaccinated 8-year-old girl who presented fever at 38 ° C. She was taken to the CTE of Butembo for the care after validation of the alert was validated;
• The 2nd contact is a 24 year old man vaccinated and asymptomatic. He is the biological father of the first contact;
• 3rd contact, first contact grandmother, 54 years old, unvaccinated and asymptomatic;
• Since the beginning of the epidemic, the cumulative number of travelers checked (temperature measurement ) at the sanitary control points is 102,840,774 ;
• To date, a total of 111 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.

As a reminder, the recommendations of the MULTISECTORAL COMMITTEE OF THE RESPONSE TO EBOLA VIRUS DISEASE are as follows:

1. Follow basic hygiene practices, including regular hand washing with soap and water or ashes;
2. If an acquaintance from an epidemic area comes to visit you and is ill, do not touch her and call the North Kivu Civil Protection toll-free number;
3. If you are identified as a contact of an Ebola patient, agree to be vaccinated and followed for 21 days;
4. If a person dies because of Ebola, follow the instructions for safe and dignified burials. It is simply a funeral method that respects funerary customs and traditions while protecting the family and community from Ebola contamination.
5. For all health professionals, observe the hygiene measures in the health centers and declare any person with symptoms of # Ebola (fever, diarrhea, vomiting, fatigue, anorexia, bleeding).<br /> If all citizens respect these sanitary measures recommended by the Secretariat, it is possible to quickly end this 10th epidemic.

On 2019-10-16 13:01:03, user GuyguyKabundi Tshima wrote:

EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AS AT OCTOBER 13, 2019<br /> Monday, October 14, 2019<br /> Since the beginning of the epidemic, the cumulative number of cases is 3,220, of which 3,106 confirmed and 114 probable. In total, there were 2,150 deaths (2036 confirmed and 114 probable) and 1033 people healed.<br /> 383 suspected cases under investigation;<br /> 2 new confirmed cases at CTE in Ituri in Mandima;<br /> No new confirmed deaths have been recorded;<br /> 1 person healed out of CTE in Ituri in Mambasa;<br /> No health workers are among the newly confirmed cases. The cumulative number of confirmed / probable cases among health workers is 161 (5% of all confirmed / probable cases), including 41 deaths.

NEWS

Governors of North Kivu and Ituri Raise Awareness on Ebola Virus Disease in Biakato, Ituri<br /> - The Technical Secretariat of the Multisectoral Ebola Epidemic Response Committee (CMRE) in collaboration with the Governor of North Kivu, Carly Nzanzu and Ituri, Jean Bamanisa, organized this Monday October 14, 2019 an awareness raising day on Ebola Virus Disease in Biakato, Ituri;<br /> - This tripartite awareness-raising aimed to share the experience of North Kivu on Ebola Virus Disease and to show that the movement of people between the two provinces can encourage further spread of this epidemic in the region, as much as the last four cases recorded in North Kivu (in Beni and Kalunguta) came from Biakato;<br /> - The governor of North Kivu has indeed responded favorably to the invitation of the Technical Secretariat of the CMRE because he wants to reinforce the surveillance in his province and refuses to see his province plunge into the epidemic;<br /> - To achieve their objectives the two governors were accompanied each by a strong delegation, where one finds the presidents of their provincial assemblies and some influential deputies of their respective countries;<br /> - In addition, the Ebola Virus Epidemic Response Coordination Team, which has been in the Mambasa Health Zone in Ituri for the past week, has been monitoring Bavalakaniki Control Points and Mabakese in this health zone.

VACCINATION

• Since vaccination began on 8 August 2018, 237,956 people have been vaccinated;
• The only vaccine to be used in this outbreak is the rVSV-ZEBOV vaccine, manufactured by the pharmaceutical group Merck, following approval by the Ethics Committee in its decision of 20 May 2018.

MONITORING AT ENTRY POINTS

• Since the beginning of the epidemic, the total number of checked travelers (temperature rise) at the sanitary control points is 105,840,505 ;
• To date, a total of 111 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the major cities of the country. countries and prevent the spread of the epidemic in neighboring countries.

As a reminder, the recommendations of the MULTISECTORAL COMMITTEE OF THE RESPONSE TO EBOLA VIRUS DISEASE are as follows:

1. Follow basic hygiene practices, including regular hand washing with soap and water or ashes;
2. If an acquaintance from an epidemic area comes to visit you and is ill, do not touch her and call the North Kivu Civil Protection toll-free number;
3. If you are identified as a contact of an Ebola patient, agree to be vaccinated and followed for 21 days;
4. If a person dies because of Ebola, follow the instructions for safe and dignified burials. It is simply a funeral method that respects funerary customs and traditions while protecting the family and community from Ebola contamination.
5. For all health professionals, observe the hygiene measures in the health centers and declare any person with symptoms of # Ebola (fever, diarrhea, vomiting, fatigue, anorexia, bleeding).<br /> If all citizens respect these health measures recommended by the Secretariat, it is possible to quickly end this 10th epidemic.

On 2019-11-19 17:15:54, user Guyguy wrote:

EPIDEMIOLOGICAL SITUATION OF THE EVOLUTION OF THE EBOLA VIRUS DISEASE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI IN THE DEMOCRATIC REPUBLIC OF THE CONGO AT NOVEMBER 17, 2019

Monday, November 18, 2019

• Since the beginning of the epidemic, the cumulative number of cases is 3,296, of which 3,178 are confirmed and 118 are probable. In total, there were 2,196 deaths (2,078 confirmed and 118 probable) and 1,070 people healed.<br /> • 407 suspected cases under investigation;<br /> • 4 new confirmed cases in North Kivu, including 2 in Mabalako, 1 in Beni and 1 in Oicha;<br /> • 1 new death of confirmed cases, including:<br /> o 1 new community death in North Kivu in Oicha;<br /> o No new deaths among confirmed cases in CTEs;<br /> • No cured person has emerged from CTEs;<br /> • No health worker is among the new confirmed cases. The cumulative number of confirmed / probable cases among health workers is 163 (5% of all confirmed / probable cases), including 41 deaths;

NEWS

NOTHING TO REPORT

VACCINATION

• 147 people were vaccinated, until Saturday, November 16, 2019, with the 2nd Ad26.ZEBOV / MVA-BN-Filo vaccine (Johnson & Johnson) in the two health zones of Karisimbi in Goma;

• Since the start of vaccination on August 8, 2018 with the rVSV-ZEBOV vaccine, 253,545 people have been vaccinated;

• Approved October 22, 2019 by the Ethics Committee of the School of Public Health of the University of Kinshasa and October 23, 2019 by the National Ethics Committee, the second vaccine, called Ad26.ZEBOV / MVA-BN -Filo, is produced by Janssen Pharmaceuticals for Johnson & Johnson;

• This new vaccine is in addition to the first, the rVSV-ZEBOV, vaccine used until then (since August 08, 2018) in this epidemic manufactured by the pharmaceutical group Merck, after approval of the Ethics Committee on May 20, 2018. has recently been approved.

MONITORING AT ENTRY POINTS

• New positive case among Mukulya Checkpoint alerts in Beni, North Kivu. It is a lifeless body of a 35-year-old man from Oicha for burial at Kabasha in Butembo;<br /> • Since the beginning of the epidemic, the total number of travelers checked (temperature rise) at the sanitary control points is 117,987,763 ;

• To date, a total of 112 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.

As a reminder, the recommendations of the MULTISECTORAL COMMITTEE OF THE RESPONSE TO EBOLA VIRUS DISEASE are as follows:

1. Follow basic hygiene practices, including regular hand washing with soap and water or ashes;
2. If an acquaintance from an epidemic area comes to visit you and is ill, do not touch her and call the North Kivu Civil Protection toll-free number;
3. If you are identified as a contact of an Ebola patient, agree to be vaccinated and followed for 21 days;
4. If a person dies because of Ebola, follow the instructions for safe and dignified burials. It is simply a funeral method that respects funerary customs and traditions while protecting the family and community from Ebola contamination.
5. For all health professionals, observe the hygiene measures in the health centers and declare any person with symptoms of Ebola (fever, diarrhea, vomiting, fatigue, anorexia, bleeding).<br /> If all citizens respect these health measures recommended by the Secretariat, it is possible to quickly end this 10th epidemic.

On 2020-01-07 12:53:20, user Guyguy wrote:

EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI ON 05 JANUARY 2020

Monday, January 06, 2020

• Since the start of the epidemic, the cumulative number of cases has been 3,390, including 3,272 confirmed and 118 probable. In total, there were 2,233 deaths (2,115 confirmed and 118 probable) and 1,114 people healed;<br /> • 373 suspected cases under investigation;<br /> • 2 new confirmed cases in Ituri in Mambasa;<br /> • No new deaths among the confirmed cases, including:<br /> o No community deaths have been recorded;<br /> o No death among the confirmed cases;<br /> • No healed person has left the CTE;<br /> • No health worker is among the new confirmed cases. The cumulative number of confirmed / probable cases among health workers is 164 (approximately 5% of all confirmed / probable cases), including 41 deaths;<br /> • Mambasa again reported a confirmed case after 66 days of silence.

NEWS<br /> Organization of an evaluation session of awareness-raising activities in the Malepe health area in Beni<br /> • The sub-coordination of the response to the Ebola virus disease epidemic organized this Monday 06 December 2020 an evaluation session of awareness-raising activities in the Malepe health area in Beni;<br /> • According to the Coordinator of this Sub-coordination, Dr. Pierre-Céleste Adikey, this evaluation aims to intensify surveillance around visitors and raise alerts. These strategies, he said, will strengthen measures to protect the City against any possible reinfection of the City;<br /> • On this occasion, it was announced the resumption of free healthcare within the Malepe health center with the support of the NGO ALIMA which, from now on, provides drugs for the free care of the sick;<br /> • In addition, the Ebola Treatment Center (CTE) in Mangina unloaded the first eight Ebola winners in 2020 on Monday. These survivors, who were reintegrated into their respective communities, notably in Aloya / Canteen, testified to good care within this CTE.

VACCINATION<br /> • 4,802 people were vaccinated, until January 2, 2020, with the 2nd vaccine Ad26.ZEBOV / MVA-BN-Filo (Johnson & Johnson) in the two health areas from Karisimbi to Goma;<br /> • Since the start of vaccination on August 8, 2018 with the rVSV-ZEBOV vaccine, 261,596 people have been vaccinated;<br /> • Approved on October 22, 2019 by the Ethics Committee of the School of Public Health at the University of Kinshasa and on October 23, 2019 by the National Ethics Committee, the second vaccine, called Ad26.ZEBOV / MVA-BN -Filo, is produced by Janssen Pharmaceuticals for Johnson & Johnson;<br /> • This new vaccine complements the first, rVSV-ZEBOV, a vaccine used until then (since August 08, 2018) in this epidemic manufactured by the pharmaceutical group Merck, after approval by the Ethics Committee on May 20, 2018. It was recently pre-qualified for certification.

ENTRY POINT SURVEILLANCE<br /> • Since the start of the epidemic, the total number of travelers checked (temperature measurement ) at health checkpoints has been 135,503,900 ;<br /> • To date, a total of 109 entry points (PoE) and health control points (PoC) have been established in the provinces of North Kivu and Ituri in order to protect the country's major cities and avoid the spread of the epidemic in neighboring countries.

As a reminder, the recommendations of the MULTISECTORAL COMMITTEE OF THE EBOLA VIRUS DISEASE RESPONSE are as follows:

1. Respect basic hygiene measures, in particular regular hand washing with water and soap or ash;
2. If an acquaintance from an epidemic area comes to visit you and that he is sick, do not touch him and call the toll-free number for civil protection in North Kivu;
3. If you are identified as a contact with an Ebola patient, agree to be vaccinated and followed for 21 days;
4. If someone dies due to Ebola, follow the guidelines for dignified and secure burials. It is simply a mode of burial that respects funeral customs and traditions while protecting the family and the community from Ebola contamination.
5. For all health professionals, observe hygiene measures in health centers and report any sick person showing symptoms of Ebola (fever, diarrhea, vomiting, fatigue, anorexia, bleeding).<br /> If all citizens respect these health measures recommended by the Secretariat, it is possible to quickly end this 10th epidemic.

On 2019-10-10 12:11:25, user GuyguyKabundi Tshima wrote:

EPIDEMIOLOGICAL SITUATION

EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AT OCTOBER 06, 2019<br /> Monday, October 07, 2019<br /> Since the beginning of the epidemic, the cumulative number of cases is 3,205, of which 3,091 are confirmed and 114 are probable. In total, there were 2,142 deaths (2028 confirmed and 114 probable) and 1006 people healed.<br /> 363 suspected cases under investigation;<br /> 1 new confirmed case at CTE in North Kivu at Oicha;<br /> No new confirmed deaths<br /> 2 people healed from Butembo CTE;<br /> No health workers are among the newly confirmed cases. The cumulative number of confirmed / probable cases among health workers is 161 (5% of all confirmed / probable cases), including 41 deaths.

NEWS

7 people healed from Ebola Virus Disease released Monday at Komanda CTE<br /> - A total of 7 people cured of Ebola Virus Disease were released on Monday October 7th at the Ebola Treatment Center (ETC) in Komanda. ;<br /> - This is 4 people from Mambasa and 3 cases from Komanda Health Zone to whom discharge certificates were given by the director of this Ebola Treatment Center<br /> - This certificate of discharge bears as inscription: "On the date of issue of this document the bearer of this certificate does not present any risk of contaminating other people, because his test was negative for the Ebola virus disease. He / she is thus DECLARE GUERI (E) . His current state of health is not a danger to the community. That is why he / she can return to his household and his professional environment to continue the daily activities. The family, the community and the authorities are asked to welcome him to promote his social integration ".

VACCINATION

• Continuation of vaccination around the confirmed case of 04 October 2019 in the Tenambo Health Area in Oicha, North Kivu;
• Continuation of the vaccination of newly recruited front-line staff at the General Reference Hospitals of Katwa and Kyondo in North Kivu;
• Since vaccination began on 8 August 2018, 234,693 people have been vaccinated;
• The only vaccine to be used in this outbreak is the rVSV-ZEBOV vaccine, manufactured by the pharmaceutical group Merck, following approval by the Ethics Committee in its decision of 20 May 2018.

MONITORING AT ENTRY POINTS

• Since the beginning of the epidemic, the total number of travelers checked (temperature increase) at the sanitary control points is 103,167,809 ;
• To date, a total of 111 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.

As a reminder, the recommendations of the MULTISECTORAL COMMITTEE OF THE RESPONSE TO EBOLA VIRUS DISEASE are as follows:

1. Follow basic hygiene practices, including regular hand washing with soap and water or ashes;
2. If an acquaintance from an epidemic area comes to visit you and is ill, do not touch her and call the North Kivu Civil Protection toll-free number;
3. If you are identified as a contact of an Ebola patient, agree to be vaccinated and followed for 21 days;
4. If a person dies because of Ebola, follow the instructions for safe and dignified burials. It is simply a funeral method that respects funerary customs and traditions while protecting the family and community from Ebola contamination.
5. For all health professionals, observe the hygiene measures in the health centers and declare any person with symptoms of # Ebola (fever, diarrhea, vomiting, fatigue, anorexia, bleeding).<br /> If all citizens respect these health measures recommended by the Secretariat, it is possible to quickly end this 10th epidemic.

On 2019-10-17 18:36:39, user GuyguyKabundi Tshima wrote:

EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AS OF OCTOBER 15, 2019

Wednesday, October 16, 2019<br /> Since the beginning of the epidemic, the cumulative number of cases is 3,227, of which 3,113 are confirmed and 114 are probable. In total, there were 2,154 deaths (2040 confirmed and 114 probable) and 1038 people healed.<br /> 530 suspected cases under investigation;<br /> 3 new confirmed cases, including:<br /> No cases in North Kivu;<br /> 3 in Ituri in Mandima;<br /> 1 new confirmed death, of which:<br /> 1 community death in Ituri in Mandima;<br /> No confirmed deaths;<br /> 2 people healed from the CTE in Ituri in Mambasa;<br /> No health workers are among the newly confirmed cases. The cumulative number of confirmed / probable cases among health workers is 161 (5% of all confirmed / probable cases), including 41 deaths.

NEWS

The state of play of the response at the center of an interview in Goma between the Technical Secretary of the CMRE and the United Nations Emergency Coordinator for Ebola<br /> - The Technical Secretary of the Multisectoral Committee on Epidemic Response to Ebola Virus Disease (ST / CMRE), Prof. Jean Jacques Muyembe Tamfum, granted a hearing on Wednesday, October 16, 2019 in Goma to the United Nations Emergency Coordinator for Ebola;<br /> - During their meeting, the two personalities discussed the state of play of the response to the 10th Ebola Virus Disease outbreak and the security situation in the areas affected by this epidemic;<br /> - It should be noted that the 10th Ebola epidemic has been taking place in the Democratic Republic of the Congo in areas of armed conflict, particularly in the provinces of North Kivu and Ituri, for more than a year;<br /> - Some time before this meeting, the technical secretary of the Multisectoral Committee for the Response to the Ebola Virus Disease Epidemic (ST / CMRE), Prof. Muyembe Tamfum, who is currently staying in Goma, North Kivu to inquire about the evolution of the response, chaired the morning meeting of the general coordination of the Ebola response to the epidemic.

Pygmies at Mahombo camp in Mambasa territory in Ituri pledge to fight Ebola Virus Disease

• The pygmies residing in Mahombo camp located more than 30 minutes walk from the main road from the village Nyangwe in the territory of Mambasa in ITURI, pledged Tuesday, October 15, 2019 to fight against Ebola by raising alerts with teams of the response;<br /> This commitment is the result of awareness raising by the Community Risk and Commitment (CREC) teams for 79 pygmies about the generalities of the Ebola virus disease, its methods of prevention and contamination;<br /> Pygmies have, for this purpose, asked for hand washing kits to break the chain of transmission of the Ebola virus in their respective communities.

VACCINATION

• Since vaccination began on 8 August 2018, 238,700 people have been vaccinated;
• The only vaccine to be used in this outbreak is the rVSV-ZEBOV vaccine, manufactured by the pharmaceutical group Merck, following approval by the Ethics Committee in its decision of 20 May 2018.

MONITORING AT ENTRY POINTS

• The Governor of North Kivu, Carly Nzanzu Kasivita accompanied by a strong delegation, visited Maboya Control Points (PoCs) in Kalunguta and Kangote in Butembo in North Kivu Province;
• The providers of the Mususa Point of Control (PoC) in Butembo, North Kivu, in collaboration with the Ndondo Primary School and the Kyambogho School Complex, participated in a mass sensitization session (travelers and riverside population) under the theme " All Eliminate Ebola Virus Disease "on International Handwashing Day;
• Since the beginning of the epidemic, the total number of travelers checked (temperature rise) at the sanitary control points is 106.625.956 ;
• To date, a total of 111 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.

As a reminder, the recommendations of the MULTISECTORAL COMMITTEE OF THE RESPONSE TO EBOLA VIRUS DISEASE are as follows:

1. Follow basic hygiene practices, including regular hand washing with soap and water or ashes;
2. If an acquaintance from an epidemic area comes to visit you and is ill, do not touch her and call the North Kivu Civil Protection toll-free number;
3. If you are identified as a contact of an Ebola patient, agree to be vaccinated and followed for 21 days;
4. If a person dies because of Ebola, follow the instructions for safe and dignified burials. It is simply a funeral method that respects funerary customs and traditions while protecting the family and community from Ebola contamination.
5. For all health professionals, observe the hygiene measures in the health centers and declare any person with symptoms of # Ebola (fever, diarrhea, vomiting, fatigue, anorexia, bleeding).<br /> If all citizens respect these health measures recommended by the Secretariat, it is possible to quickly end this 10th epidemic.

On 2019-11-17 04:20:48, user GuyguyKabundi Tshima wrote:

EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AS AT NOVEMBER 15, 2019<br /> Saturday, November 16, 2019<br /> • Since the beginning of the epidemic, the cumulative number of cases is 3,292, of which 3,174 are confirmed and 118 are probable. In total, there were 2,195 deaths (2077 confirmed and 118 probable) and 1070 people healed.<br /> • 517 suspected cases under investigation;<br /> • No new confirmed cases;<br /> • No new deaths of confirmed cases have been recorded;<br /> • No cured person has emerged from CTEs;<br /> • No health worker is among the new confirmed cases. The cumulative number of confirmed / probable cases among health workers is 163 (5% of all confirmed / probable cases), including 41 deaths.

NEWS

Goma opens leadership capacity building workshop for Ebola epidemic response to Ebola Virus Disease.

• The coordinator of the epidemic response to Ebola Virus Disease in North and South Kivu Province and Ituri, Prof. Steve Ahuka Mundeke, opened this Saturday, November 16, 2019 in Goma North Kivu a workshop on building the capacity of actors involved in the response against Ebola;<br /> • For four days, participants, coordinating and sub-coordinating officers from the response, the Ministry of Health, the World Health Organization (WHO), national security, CDC and DFID will be equipped with management skills epidemics before, during and after the tenth epidemic of Ebola Virus Disease, especially in the event of any outbreak;<br /> • According to Prof. Ahuka, this workshop will not only benefit this epidemic, but will help, through acquired skills, to cope with other epidemics or other crises in a collective and individual way. " Each participant will be able to use these skills in his daily life ," he concluded;<br /> • This training for the response officers, from 16 to 20 November 2019, is organized by the Ministry of Health in collaboration with WHO with funding from UKaid from the British people.

VACCINATION

• 93 people were vaccinated with the 2nd Ad26.ZEBOV / MVA-BN-Filo vaccine (Johnson & Johnson) in the two Health Zones of Karisimbi in Goma;<br /> • Since the start of vaccination on August 8, 2018 with the rVSV-ZEBOV vaccine, 252,835 people have been vaccinated;<br /> • Approved October 22, 2019 by the Ethics Committee of the School of Public Health of the University of Kinshasa and October 23, 2019 by the National Ethics Committee, the second vaccine, called Ad26.ZEBOV / MVA-BN -Filo, is produced by Janssen Pharmaceuticals for Johnson & Johnson;<br /> • This new vaccine complements the first, the rVSV-ZEBOV, vaccine used until then (since August 08, 2018) in this outbreak, manufactured by the pharmaceutical group Merck, after approval of the Ethics Committee on May 20, 2018. It has recently been approved.

MONITORING AT ENTRY POINTS

• Since the beginning of the epidemic, the total number of travelers checked (temperature rise) at the sanitary control points is 117,333,420 ;<br /> • To date, a total of 112 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.

As a reminder, the recommendations of the MULTISECTORAL COMMITTEE OF THE RESPONSE TO EBOLA VIRUS DISEASE are as follows:

1. Follow basic hygiene practices, including regular hand washing with soap and water or ashes;
2. If an acquaintance from an epidemic area comes to visit you and is ill, do not touch her and call the North Kivu Civil Protection toll-free number;
3. If you are identified as a contact of an Ebola patient, agree to be vaccinated and followed for 21 days;
4. If a person dies because of Ebola, follow the instructions for safe and dignified burials. It is simply a funeral method that respects funerary customs and traditions while protecting the family and community from Ebola contamination.
5. For all health professionals, observe the hygiene measures in the health centers and declare any person with symptoms of # Ebola (fever, diarrhea, vomiting, fatigue, anorexia, bleeding).<br /> If all citizens respect these health measures recommended by the Secretariat, it is possible to quickly end this 10th epidemic.

On 2019-11-30 16:39:58, user Guyguy wrote:

EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AT NOVEMBER 26, 2019<br /> Wednesday, November 27, 2019<br /> • Since the beginning of the epidemic, the cumulative number of cases is 3,304, of which 3,186 are confirmed and 118 are probable. In total, there were 2,199 deaths (2081 confirmed and 118 probable) and 1077 people cured.<br /> • 366 suspected cases under investigation;<br /> • No new confirmed cases;<br /> • No new deaths among confirmed cases;<br /> • No cured person has emerged from CTEs;<br /> • No health worker is among the new confirmed cases. The cumulative number of confirmed / probable cases among health workers is 163 (5% of all confirmed / probable cases), including 41 deaths.

NEWS

Closure of training of Ebola Rapid Response Teams in Goma

• The Ebola response coordinator for the Ebola response to operations, Dr. Luigino Mikulu, closed on Wednesday 27 November 2019 the training of Rapid Response Teams (RRTs), composed of units of the Armed Forces. (FARDC) and the Congolese National Police (PNC), on the Ebola virus disease that took place in Goma, capital of North Kivu Province from 22 to 26 November 2019;<br /> • For Dr. Luigino, this team is the first in the Rapid Response Teams to be composed of elements from other sectors, such as those of the Ministries of Defense and Security and the Ministry of the Interior;<br /> • This training aligns with the vision of the Technical Secretariat of the Multisectoral Ebola Virus Disease Response Committee (ST / CMRE), through the overall coordination of the response, to expand its mixed and multidisciplinary teams available and able to intervene 24 hours a day, 7 days a week and everywhere, where they will be deployed, not only for the response to this epidemic to Ebola Virus Disease, but also for other epidemics;<br /> • This training was a pride for WHO to accompany the Ministry of Health in order to capitalize the capacity building of FARDC and PNC units in public health;<br /> • The participants, in turn, reassured the overall coordination of the response, the Ministry of Health and all those who contributed to the delivery of this training, particularly to WHO and all facilitators, to be faithful disciples in the field by putting into practice all the notions learned during these sessions;<br /> • At the end of this training, the thirty participants, including the facilitators, received a participation certificate.

VACCINATION

• Despite the tense situation of the city of Beni, a vaccination ring was opened around the confirmed case of 24 October 2019 in the Kanzulinzuli Health Area of the General Reference Hospital;<br /> • 724 people were vaccinated, until Tuesday, November 26, 2019, with the 2nd Ad26.ZEBOV / MVA-BN-Filo vaccine (Johnson & Johnson) in the two health zones of Karisimbi in Goma;<br /> • Since the start of vaccination on August 8, 2018 with the rVSV-ZEBOV vaccine, 255,247 people have been vaccinated;<br /> • Approved October 22, 2019 by the Ethics Committee of the School of Public Health of the University of Kinshasa and October 23, 2019 by the National Ethics Committee, the second vaccine, called Ad26.ZEBOV / MVA-BN -Filo, is produced by Janssen Pharmaceuticals for Johnson & Johnson;<br /> • This new vaccine is in addition to the first, the rVSV-ZEBOV, vaccine used until then (since August 08, 2018) in this epidemic manufactured by the pharmaceutical group Merck, after approval of the Ethics Committee on May 20, 2018. has recently been pre-qualified for registration.

MONITORING AT ENTRY POINTS

• Sanitary control activities are disrupted in the towns of Beni and Butembo in North Kivu province following demonstrations by the population which decries killings of civilians;<br /> • Since the beginning of the epidemic, the total number of travelers checked (temperature measurement ) at the sanitary control points is 121,159,810 ;<br /> • To date, a total of 109 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.

As a reminder, the recommendations of the MULTISECTORAL COMMITTEE OF THE RESPONSE TO EBOLA VIRUS DISEASE are as follows:

1. Follow basic hygiene practices, including regular hand washing with soap and water or ashes;
2. If an acquaintance from an epidemic area comes to visit you and is ill, do not touch her and call the North Kivu Civil Protection toll-free number;
3. If you are identified as a contact of an Ebola patient, agree to be vaccinated and followed for 21 days;
4. If a person dies because of Ebola, follow the instructions for safe and dignified burials. It is simply a funeral method that respects funerary customs and traditions while protecting the family and community from Ebola contamination.
5. For all health professionals, observe the hygiene measures in the health centers and declare any person with symptoms of # Ebola (fever, diarrhea, vomiting, fatigue, anorexia, bleeding).<br /> If all citizens respect these health measures recommended by the Secretariat, it is possible to quickly end this 10th epidemic.

On 2019-11-09 20:30:28, user GuyguyKabundi Tshima wrote:

EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AT 07 NOVEMBER 2019<br /> Friday, November 08, 2019<br /> • Since the beginning of the epidemic, the cumulative number of cases is 3,286, of which 3,168 are confirmed and 118 are probable. In total, there were 2,192 deaths (2074 confirmed and 118 probable) and 1064 people healed.<br /> • 560 suspected cases under investigation;<br /> • No new confirmed cases;<br /> • No new confirmed deaths have been recorded;<br /> • 1 person cured out of the CTE of Butembo;<br /> • No health worker is among the new confirmed cases. The cumulative number of confirmed / probable cases among health workers is 161 (5% of all confirmed / probable cases), including 41 deaths;

NEWS

End of tour of the general coordinator of the Ebola response in North Kivu and Ituri

• The Epidemic Response Coordinator for Ebola Virus Disease, Prof. Steve Ahuka Mundeke, was on mission from 05 to 07 November 2019 in a few areas affected by Ebola Virus Disease in North Kivu and Ituri, to inquire about the epidemiological and security evolution of the response. During this mission, he visited some sites of the response to Beni in North Kivu, including the Mangango camp where the vaccination of pygmies took place;

• In Ituri, Prof Ahuka traveled to Biakato Mines in Mandima, Mambasa Territory, where he first reinserted three of the four cured patients he had discharged well into the Mangina Ebola Treatment Center in the area. Mabalako health center in North Kivu. He also comforted the family of the retaliating agent and journalist, murdered on the night of Saturday, November 2, 2019 in Lwemba in Mambasa territory in Ituri;

• He also chaired the daily meeting on the activities of the response in the sub-coordination of Biakato Mines;

• On his way back, the general coordinator of the riposte went to the Mangina Subcommittee, where he chaired under the trees the morning meeting in Mangina. He also visited the Health Center "Case of Salvation" which collaborates with the response and to whom he handed over a large batch of mattresses in the presence of the WHO coordinator of Mangina's sub-coordination. He again visited the Mangango camp, where the pygmies who have joined the activities of the riposte live to help the response reach all the other pygmies;

• He closed his tour of North Kivu and Ituri with a visit to the Ebola Treatment Center in Beni.

VACCINATION

• Pygmy vaccination continues in Mabalako at Mangango camp, 19/19 vaccinated pygmies;<br /> • Continuation of vaccination in expanded ring, around 3 confirmed cases on 04/11/2019 and 2 cases confirmed on 05/11/2019 and the vaccination of the biker as contacts, in Beni in five (5) areas health care, including in Butsili, Ngongolio, Tamende, mandrandele and Kasabinyole;<br /> • Since vaccination began on August 8, 2018, 248,460 people have been vaccinated;<br /> • The only vaccine to be used in this outbreak is the rVSV-ZEBOV vaccine, manufactured by the pharmaceutical group Merck, following approval by the Ethics Committee in its decision of 20 May 2018.

MONITORING AT ENTRY POINTS

• Since the beginning of the epidemic, the total number of travelers checked (temperature rise) at the sanitary control points is 114,626,335 ;<br /> • To date, a total of 111 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.

As a reminder, the recommendations of the MULTISECTORAL COMMITTEE OF THE RESPONSE TO EBOLA VIRUS DISEASE are as follows:

1. Follow basic hygiene practices, including regular hand washing with soap and water or ashes;
2. If an acquaintance from an epidemic area comes to visit you and is ill, do not touch her and call the North Kivu Civil Protection toll-free number;
3. If you are identified as a contact of an Ebola patient, agree to be vaccinated and followed for 21 days;
4. If a person dies because of Ebola, follow the instructions for safe and dignified burials. It is simply a funeral method that respects funerary customs and traditions while protecting the family and community from Ebola contamination.
5. For all health professionals, observe the hygiene measures in the health centers and declare any person with symptoms of # Ebola (fever, diarrhea, vomiting, fatigue, anorexia, bleeding).<br /> If all citizens respect these health measures recommended by the Secretariat, it is possible to quickly end this 10th epidemic.

On 2019-11-10 21:15:52, user GuyguyKabundi Tshima wrote:

EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AT 08 NOVEMBER 2019<br /> Saturday, November 09, 2019<br /> • Since the beginning of the epidemic, the cumulative number of cases is 3,286, of which 3,168 are confirmed and 118 are probable. In total, there were 2,192 deaths (2074 confirmed and 118 probable) and 1064 people healed.<br /> • 501 suspected cases under investigation;

THE LIST OF NO:

• No new cases have been confirmed;<br /> • No new confirmed deaths have been recorded;<br /> • No cured person has emerged from CTEs;<br /> • No health worker is among the new confirmed cases. The cumulative number of confirmed / probable cases among health workers is 161 (5% of all confirmed / probable cases), including 41 deaths;

NEWS

NOTHING TO REPORT

VACCINATION<br /> • Since vaccination began on August 8, 2018, 249,290 people have been vaccinated;<br /> • The only vaccine to be used in this outbreak is the rVSV-ZEBOV vaccine, manufactured by the pharmaceutical group Merck, following approval by the Ethics Committee in its decision of 20 May 2018.

MONITORING AT ENTRY POINTS<br /> • Since the beginning of the epidemic, the total number of travelers checked (temperature measurement ) at the sanitary control points is 115.036.328 ;<br /> • To date, a total of 111 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.

As a reminder, the recommendations of the MULTISECTORAL COMMITTEE OF THE RESPONSE TO EBOLA VIRUS DISEASE are as follows:

1. Follow basic hygiene practices, including regular hand washing with soap and water or ashes;
2. If an acquaintance from an epidemic area comes to visit you and is ill, do not touch her and call the North Kivu Civil Protection toll-free number;
3. If you are identified as a contact of an Ebola patient, agree to be vaccinated and followed for 21 days;
4. If a person dies because of Ebola, follow the instructions for safe and dignified burials. It is simply a funeral method that respects funerary customs and traditions while protecting the family and community from Ebola contamination.
5. For all health professionals, observe the hygiene measures in the health centers and declare any person with symptoms of # Ebola (fever, diarrhea, vomiting, fatigue, anorexia, bleeding).<br /> If all citizens respect these health measures recommended by the Secretariat, it is possible to quickly end this 10th epidemic.

On 2019-11-27 15:46:04, user Guyguy wrote:

EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AS AT 25 NOVEMBER 2019<br /> Tuesday, November 26, 2019<br /> • Since the beginning of the epidemic, the cumulative number of cases is 3,304, of which 3,186 are confirmed and 118 are probable. In total, there were 2,199 deaths (2081 confirmed and 118 probable) and 1077 people cured.<br /> • 392 suspected cases under investigation;<br /> • 1 new case confirmed in North Kivu in Mabalako;<br /> • No new deaths among confirmed cases;<br /> • No cured person has emerged from CTEs;<br /> • No health worker is among the new confirmed cases. The cumulative number of confirmed / probable cases among health workers is 163 (5% of all confirmed / probable cases), including 41 deaths;

NEWS

NOTHING TO REPORT

VACCINATION

• Despite the tense situation of the city of Beni, a vaccination ring was opened around the confirmed case of 24 October 2019 in the Kanzulinzuli Health Area of the General Reference Hospital;<br /> • 724 people were vaccinated with the 2nd Ad26.ZEBOV / MVA-BN-Filo vaccine (Johnson & Johnson) in the two Health Zones of Karisimbi in Goma;<br /> • Since the start of vaccination on August 8, 2018 with the rVSV-ZEBOV vaccine, 255,215 people have been vaccinated;<br /> • Approved October 22, 2019 by the Ethics Committee of the School of Public Health of the University of Kinshasa and October 23, 2019 by the National Ethics Committee, the second vaccine, called Ad26.ZEBOV / MVA-BN -Filo, is produced by Janssen Pharmaceuticals for Johnson & Johnson;<br /> • This new vaccine is in addition to the first, the rVSV-ZEBOV, vaccine used until then (since August 08, 2018) in this epidemic manufactured by the pharmaceutical group Merck, after approval of the Ethics Committee on May 20, 2018. has recently been pre-qualified for registration.

MONITORING AT ENTRY POINTS

• Sanitary control activities are disrupted in the towns of Beni and Butembo in North Kivu province following demonstrations by the population which decries killings of civilians;<br /> • Since the beginning of the epidemic, the total number of travelers checked (temperature measurement ) at the sanitary control points is 120,825,670 ;<br /> • To date, a total of 109 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.

As a reminder, the recommendations of the MULTISECTORAL COMMITTEE OF THE RESPONSE TO EBOLA VIRUS DISEASE are as follows:

1. Follow basic hygiene practices, including regular hand washing with soap and water or ashes;
2. If an acquaintance from an epidemic area comes to visit you and is ill, do not touch him/her and call the North Kivu Civil Protection toll-free number;
3. If you are identified as a contact of an Ebola patient, agree to be vaccinated and followed for 21 days;
4. If a person dies because of Ebola, follow the instructions for safe and dignified burials. It is simply a funeral method that respects funerary customs and traditions while protecting the family and community from Ebola contamination.
5. For all health professionals, observe the hygiene measures in the health centers and declare any person with symptoms of Ebola (fever, diarrhea, vomiting, fatigue, anorexia, bleeding).<br /> If all citizens respect these health measures recommended by the Secretariat, it is possible to quickly end this 10th epidemic.

On 2020-04-22 02:20:27, user Mike wrote:

This was certainly an interesting paper. It's done a lot of work and the findings are notable. IMHO it warrants as much attention as the pro-HCQ study via Dr. Raoult. While it is entertaining, I will add that it is not conclusive, nor without fault. A double-blind study is still required, but it is worth the read.

Observations/Questions:

1. "hydroxychloroquine, with or without azithromycin, was more likely to be prescribed to patients with more severe disease”<br /> 2. "we cannot rule out the possibility of selection bias or residual confounding”<br /> 3. demographic: 100% male, 66% black, median age ~70 (59 youngest)<br /> 4. uses PSM, which despite a common practice, could be considered controversial (https://gking.harvard.edu/f... "https://gking.harvard.edu/files/gking/files/psnot.pdf)")<br /> 5. Unless I missed it, I didn't see any specifics about how the treatments were administered.<br /> - How long before death were patients treated? <br /> - What was the quantity/frequency of the treatments? <br /> - Were the treatments consistent between hospitals?<br /> 6. The rate of ventilation was less in HC+AZ (half of the HC and no-HC rates). Why was that and what does that suggest?<br /> 7. Although they were statistically insignificant, what was the result of the 17 women not included in the study?<br /> 8. Why does the paper seem to address political points? It seems like the Abstract is editorialized, which I'm not accustomed to. The Conclusions portion (and page after) seeming to address topical issues of the times. Perhaps this introduces my own subjective bias, but I infer potential for analysis/deciphering bias when the study shows awareness of other controversial studies being conducted, rather than being a standalone independent study of its own; essentially, it leaves me to question motivations of the author, rather than that motivation being scientific discovery. I don't mind such commentary in the Discussion section, I'm just not as accustomed to seeing it in the Abstract.

On 2020-04-22 01:10:17, user Gunnar V Gunnarsson wrote:

After reading the paper I unfortunately find the usage of data to be misleading and I think you might have drawn the wrong conclusions.

The problem lies in the fact that once people went on ventilators they where given HC or HC+AZ. This re-categorised the patients by increasing the number of high risk patients in the HC and HC+AZ groups making the No HC an invalid control group.

Before ventilation the statistics was like this: (Table 4 in paper)

HC: 90 - 9 (10.0%) deaths - 69 (76.6%) recover - 12 (13.3%) onto ventilation HC+AZ: 101 - 11 (10.9%) deaths - 83 (82.2%) recover - 7 (06.9%) onto ventilation No HC: 177 - 15 ( 8.4%) deaths - 137 (77.4%) recover - 25 (14.1%) onto ventilation

We see that death-rate is about the same for all groups but HC+AZ seams to have the highest recovery rate but it might not be statistically significant.

Now once people hit ventilation the re-categorisation occurs. More patients where given HC and HC+AZ which moved them from the No HC group to the HC or HC+AZ group. These groups therefore have a much higher % of ventilation patients because they where given the drugs after they hit ventilation.

The following data can be derived from the paper but is not presented:<br /> Once people hit ventilation we have the following results.

HC: 19 - 18 (95%) deaths - 1 (11%) recover HC+AZ: 19 - 14 (73%) deaths - 5 (27%) recover No HC: 6 - 3 (50%) deaths - 3 (50%) recover

If you compare these 2 tables, you see that 25 patient with No HC reach ventilation. Once they reach ventilation, 19 of these where give HC or HC+AZ, thereby moved from the No HC group to the other two. 79.5% of all patients reaching ventilation died so arguably 14 patients that died where moved from the No HC group to the other 2 groups only once they reach the much higher risk state.

Here are the number of people per group that got ventilation:

HC: 97 - 19 (19.6%) got ventilation HC+AZ: 113 - 19 (16.8%) got ventilation No HC: 158 - 6 ( 3.4%) got ventilation

So in the end result the No HC group had a very low % of patients who got ventilation and therefore should have a significant lower death rate which is then totally unrelated to the treatment.

On 2020-04-23 02:46:06, user Raspee wrote:

(1) There appears to be a statistically significant imbalance in the arms with regard to disease severity.

“However, hydroxychloroquine, with or without azithromycin, was more likely to be prescribed to patients with more severe disease, as assessed by baseline ventilatory status and metabolic and hematologic parameters.”

The base line pulse oximetry data and baseline line absolute lymphocyte count (Table 2) - indicates a statistical difference at p = 0.024 - the subjects that received hydroxychloroquine had a worse baseline respiratory status - and a worse absolute lymphocyte count p = 0.021.

This is an inherent bias in the design that has not been adequately addressed. The analysis should compare treatment in subjects with the same disease severity.

(2) If we look at table 4 - (HC + AZ) - 82% were discharged without ventilation vs. 77% discharged without ventilation both in the HC and non- HC group - Apparently the HC + AZ group did better than the other two groups.

This is supported by the observation that the adjusted HR for ventilation is 0.43 (0.16 - 1.12) - It was better than the control arm with regard to disease progression and no different than the control for death.

So in patients that were sicker at baseline, HC + AZ appears to have had a better outcome - than the other two groups - with regard to being discharged without requiring an ICU admission.

(3) Please provide a better justification to exclude the 17 women Please go back and perform the analysis including the 17 women.

(4) What were the doses of azithromycin and hydroxychloroquine administered? How are the different doses and dose regimens adjusted in the analysis? Not everyone in the HQ and HQ + AZ groups were dosed in the same fashion. Is there a minimum number of doses that you used to include them in the treatment groups?

(5) If the control group had less severe illness at presentation, it stands to reason that the mortality rate would be lowest in the control group.

(6) Was there a sub analysis looking at impact of secondary bacterial pneumonia - which occurs in 5-15% of moderate to severe COVID-19 patients? Were the antibiotics utilized the same over the 3 cohorts or were they different?

(7) How many patients were on ace inhibitors and/or angiotensin receptor blockers? Were these medications balanced in the 3 arms? What about corticosteroid use in the 3 cohorts? Was corticosteroid use balanced?

(8) Please go back and re-run the analysis with an additional 14 days of COVID-19 data (using April 25th cut -off) as your sample size will undoubtedly be greater and we would expect that the HQ + AZ group will now have a p value < 0.05. for discharge without ventilation.

(9) Please include length of stay in your analysis as well

(10) Please include readmission rates to the hospital in your analysis

On 2020-04-22 00:53:03, user Mike Cee wrote:

This paper is flawed and should be withdrawn immediately.<br /> 1) This paper is flawed due to the limitation discussed on page 12 about the likelihood that the HCQ group, "However, hydroxychloroquine, with or without azithromycin, was more likely to be prescribed to patients with more severe disease, as assessed by baseline ventilatory status and metabolic and hematologic parameters."<br /> Doctors working the front lines have already noted that patients at SYMPTOMS ONSET + 14 days should not be prescribed HCQ<br /> 2) The important grouping by number of days since SYMPTOM ONSET was left out of this study. Previous studies, while anecdotal, suggest that patients should be prescribed HCQ early because it is believed to prevent the virus from infecting the type 2 lung cell through the ACE2 receptor and thus stops the progression of the disease.<br /> 3) This study did not document the dosage given to the patients. That would have been a helpful inclusion so we could understand if the patients who died were actually poisoned by excessive the treatment.<br /> 4) HCQ prescribed in patients in the first week after SYMPTOMS ONSET to include a zinc supplement which anecdotal evidence suggests a dual function of the combination: The HCQ provides an avenue for the zinc to enter the Type 2 lung cell where it interferes with the virus replication process.

On 2020-05-01 10:56:16, user Ivan Berlin wrote:

Rentsch CT et al. Covid-19 Testing, Hospital Admission, and Intensive Care Among 2,026,227 United States Veterans Aged 54-75 Years. <br /> medRxiv preprint doi: https://doi.org/10.1101/202... version posted April 14, 2020<br /> Comment of the results concerning smoking related issues. Corrected Version. Please ignore the previous one.<br /> Ivan Berlin, Paris, France<br /> The title is somewhat misleading. Only 3789 persons were tested for SARS-CoV-2, no data on the 2,022,438 are reported.<br /> Data are extracted from the Veteran Administration (USA) Birth Cohort born between 1945 and 1965 electronic database. Between February 8 and March 30, 2020, 3789 persons were tested for SARS-CoV-2. Among them 585 were tested SARS-CoV-2 positive (15.4%) and 3204 SARS-CoV-2 negative. (Remark: the authors frequently confound testing for SARS-CoV-2 and having the disease: COVID-19 +.)<br /> Testing used nasopharyngeal swabs, 1% of the testing samples was from other unspecified sources. Testing was performed “in VA state public health and commercial reference laboratoires”, page 7. No further specification about the testing method is provided. Data are analyzed as if no between test-sources variability existed. However, it is unlikely that between test-source variability would influence the findings.<br /> It seems that only individuals with symptoms were tested, however this is not clearly stated.<br /> Data extraction included diagnostics by diagnostic codes of comorbidities, non-steroid inflammatory drug (NSAID), angiotensin converting enzyme inhibitor (ACE) and angiotensin II receptor blocker (ARB) use, vital signs, laboratory results, hepatic fibrosis score, presence or absence of alcohol use disorder and smoking status.<br /> Smoking status data, never, former, current smokers were extracted using the algorithm described in McGinnis et al. Validating Smoking Data From the Veteran’s Affairs Health Factors Dataset, an Electronic Data Source. Nicotine & Tobacco Research, Volume 13, Issue 12, December 2011, Pages 1233–1239, https://doi.org/10.1093/ntr... used for HIV patients. According to this paper, the algorithm correctly classified 84% of never-smokers 95% of current smokers but only 43% of former smokers. The reported overall kappa statistic was 0.66. When categories were collapsed into ever/never, the kappa statistic was somewhat better: 0.72 (sensitivity = 91%; specificity = 84%), and for current/not current, 0.75 (sensitivity = 95%; specificity = 79%). Thus, classification error cannot be excluded in particular in classifying former smokers. <br /> In unadjusted analyses (Table 1) factors associated significantly with SARS-CoV-2 positivity were: male sex, black race, urban residence, chronic kidney disease, diabetes, hypertension, higher body mass index, vital signs but not NSAID or ACE/ARB exposure. It is to note, that among the laboratory findings, severity of hepatic fibrosis was associated with positive SARS-CoV-2 tests. <br /> Among those with positive SARS-CoV2 alcohol use disorder was reported by 48/585 (8.2%), versus 480/3204 (15%) among those with negative SARS-CoV-2 test. Among those with alcohol use disorder, 9.1 tested positive. <br /> Among SARS-CoV-2 positives there were 216/585 (36.9%) never smokers vs 826/3204 (25.8%) among SARS-CoV-2 negatives. 20.7% tested positive among never smokers. Among SARS-CoV-2 positive persons 179 (30.6%) were former smokers vs 704 (22%) among SARS-CoV-2 negatives. 20.3 % tested positive among former smokers. Among SARS-CoV-2 positive individuals 159 (27.7%) were current smokers vs 1444 (45.1%) among SARS-CoV-2 negative individuals. 9.9% tested positive among current smokers. Expressed otherwise, among SARS-CoV-2 negative individuals, there were less never smokers, less former smokers and more current smokers. Among individuals with SARS-CoV-2 positivity there were 338/585 (61%) persons with smoking history (former + current smokers=ever smokers) and among those with SARS-CoV-2 negativity 2149/3204 (72%) were ever smokers. <br /> COPD, known to be strongly related to former or current smoking, was more frequent among SARS-CoV-2 negative (28.2%) than among SARS-CoV-2 positive (15.4%) individuals.<br /> In multivariable analyses (Table 2), male sex, black ethnicity, urban residence, lower systolic blood pressure, prior use of NSAID but not ACE/ARB use and obesity were associated with SARS-CoV-2 positive test; current smoking (OR: 0.45, 91% CI: 0.35-057), alcohol use disorder (OR 0.58, 95% CI: 0.41-0.83) and COPD (OR: 0.67, 95%CI: 0.50-0.88) were associated with decreased likelihood of SARS-CoV-2 positive test. No association with age and SARS-CoV-2 positive test was observed. The association with hepatic fibrosis with SARS-CoV-2 positive tests remained significant in the multivariable analysis and the authors point out (page 15) that the “pronounced independent association with FIB-4 (fibrosis) and albumin suggest that virally induced haptic inflammation may be a harbinger of the cytokine storm.”, page 15. <br /> The main risk factors for hospitalization or ICU among SARS-CoV-2 positive persons are those that associated with worse clinical signs (status). This is expected: clinical decision about severity is based on current clinical signs and not on previous history. <br /> Neither co-morbidities, nor smoking status or alcohol use disorder were associated with hospitalization/ICU. Surprisingly, age was inversely associated with hospitalization (Table 4) among SARS-CoV-2 positive individuals.<br /> Conclusion

To the best of our knowledge, this is the first report showing that there are less current smokers among SARS-CoV-2 positive persons. However, looking at smoking history (former + current smoking=ever smokers), less subject of classification bias, the difference seems to be less. It is not known what is the percent of former smokers who were recent quitters; duration of previous abstinence from smoking is a crucial variable in assessing associations with smoking status. There is no report of biochemical verification of smoking status. <br /> It is not known when smoking status is reported with respect of the SARS-CoV-2 testing. It is likely that individuals with clinical symptoms stopped smoking some days before testing and considered themselves as former smokers.

The fact that alcohol use disorder, which is frequently associated with tobacco use disorder, is also less frequent among SARS-CoV-2 positive individuals raises the question of the specificity of the smoking finding and raises the contribution of substance use disorders overall i.e. the finding about current smoking is part of a cluster of various previous or current substance use disorders e.g. cannabis use, potentially associated with SARS-CoV-2 negative test directly or through associated health disorders e.g. hepatic disorders as a consequence of alcohol use. <br /> COPD as well as current smoking are being reported to be more frequent among SARS-CoV-2 negative individuals raising the possibility that reduced respiratory function (entry of SARS-CoV-2 is by the respiratory tract) is associated with lower likelihood of SARS-CoV-2 positive tests. <br /> It seems that all individuals included were tested because they had symptoms suggestive of COVID-19. It is surprising that only 585/3789 (15.4%) tested positive. This should be discussed.<br /> The paper does not report on analyses of smoking by clinical signs/co-morbidities interactions. It is likely that former smokers or those with alcohol use disorders are more frequent among individuals with comorbidities. Based on previous knowledge about smoking associated health disorders, one can assume that more severe clinical signs were associated with current smoking or among recent quitters; the smoking x clinical signs interaction is not tested. <br /> The authors conclude on page 14 “To wit, we found that current smoking, COPD, and alcohol use disorder, factors that generally increase risk of pneumonia, were associated with decreased probability of testing positive. While they were not associated with hospitalization or intensive care, it is too early to tell if these factors are associated with subsequent outcomes such as respiratory failure or mortality.”<br /> The reduced current smoking rate among SARS-CoV-2 positive individuals is an interesting but preliminary finding. It is likely that it is part of a more complex symptomatology and not specific to current smoking. Smoking status should have been assessed on a more detailed manner. The current findings, from a retrospective, cross sectional analysis, are insufficient to support the hypothesis that current smoking protects against SARS-CoV-2 positivity.

On 2020-04-30 14:34:37, user Ivan Berlin wrote:

Rentsch CT et al. Covid-19 Testing, Hospital Admission, and Intensive Care Among 2,026,227 United States Veterans Aged 54-75 Years. <br /> medRxiv preprint doi: https://doi.org/10.1101/202... version posted April 14, 2020<br /> Review of the results concerning smoking related issues.<br /> Ivan Berlin<br /> The title is somewhat confusing. Only 3789 persons were tested for SARS-CoV-2.<br /> Data are extracted from the Veteran Administration (USA) Birth Cohort born between 1945 and 1965 electronic database. Between February 8 and March 30, 2020, 3789 persons were tested for SARS-CoV-2. Among them 585 were tested SARS-CoV-2 positive (15.4%) and 3204 SARS-CoV-2 negative. (Remark: the authors frequently confound testing for SARS-CoV-2 and having the disease: COVID-19.)<br /> Testing used nasopharyngeal swabs, 1% of the testing samples was from other unspecified sources. Testing was performed “in VA state public health and commercial reference laboratoires”, page 7. No further specification about the testing method is provided. Data are analyzed as if no between test-sources variability existed. However, it is unlikely that between test-source variability would influence the findings.<br /> Data extraction included diagnostics by diagnostic codes of comorbidities, non-steroid inflammatory drug (NSAID), angiotensin converting enzyme inhibitor (ACE) and angiotensin II receptor blocker (ARB) use, vital signs, laboratory results, hepatic fibrosis score, presence or absence of alcohol use disorder and smoking status.<br /> Smoking status data, never, former, current smokers were extracted using the algorithm described in McGinnis et al. Validating Smoking Data From the Veteran’s Affairs Health Factors Dataset, an Electronic Data Source. Nicotine & Tobacco Research, Volume 13, Issue 12, December 2011, Pages 1233–1239, https://doi.org/10.1093/ntr... used for HIV patients. According to this paper, the algorithm correctly classified 84% of never-smokers 95% of current smokers but only 43% of former smokers. The reported overall kappa statistic was 0.66. When categories were collapsed into ever/never, the kappa statistic was somewhat better: 0.72 (sensitivity = 91%; specificity = 84%), and for current/not current, 0.75 (sensitivity = 95%; specificity = 79%). Thus, classification error cannot be excluded in particular in classifying former smokers. <br /> In unadjusted analyses (Table 1) factors associated significantly with SARS-CoV-2 positivity were: male sex, black race, urban residence, chronic kidney disease, diabetes, hypertension, higher body mass index, vital signs but not NSAID or ACE/ARB exposure. It is to note, that among the laboratory findings, severity of hepatic fibrosis was associated with positive SARS-CoV-2 tests. <br /> Among those with alcohol use disorder, 48 (8.2%) tested positive versus 480 (15%) who tested negative (p<0.001).<br /> Among never smokers 216 (36.9%) tested positive vs 826 (25.8%) who tested negative. Among former smokers 179 (30.6%) tested positive vs 704 (22%) who tested negative. Among current smokers 159 (27.7%) tested positive vs 1444 (45.1%) who tested negative. Expressed otherwise, among SARS-CoV-2 negative individuals, there were less never smokers, less former smokers and more current smokers. To note: the reported OR for current smoking should be the inverse to that presented i.e. <1 and not >1. However, among individuals with SARS-CoV-2 positivity there were more persons with positive smoking history (former + current smokers): 57.8 % than with negative smoking history (never smokers): 36.9%. <br /> COPD, known to be strongly related to former or current smoking, was more frequent among SARS-CoV-2 negative (28.2%) than among SARS-CoV-2 positive (15.4%) individuals p<001).<br /> In multivariable analyses (Table 2), male sex, black ethnicity, urban residence, lower systolic blood pressure, prior use of NSAID but not ACE/ARB use and obesity were associated with SARS-CoV-2 positive test; current smoking (OR: 0.45, 91% CI: 0.35-057), alcohol use disorder (OR 0.58, 95%CI: 0.41-0.83) and COPD (OR: 0.67, 95%CI: 0.50-0.88) were associated with decreased likelihood of SARS-CoV-2 positive test. No association with age and SARS-CoV-2 positive test was observed. The association with hepatic fibrosis with SARS-CoV-2 positive tests remained significant in the multivariable analysis and the authors point out (page 15) that the “pronounced independent association with FIB-4 (fibrosis) and albumin suggest that virally induced haptic inflammation may be a harbinger of the cytokine storm.”, page 15. <br /> The main risk factors for hospitalization or ICU among SARS-CoV-2 positive persons are those that associated with a worse clinical signs (status). This is expected: clinical decision about severity is based on current clinical signs and not on previous history. <br /> Neither co-morbidities, nor smoking status or alcohol use disorder were associated with hospitalization/ICU. Surprisingly, age was inversely associated with hospitalization (Table 4) among SARS-CoV-2 positive individuals.<br /> Conclusion of the reviewer.<br /> This is the first report showing that there are less current smokers among SARS-CoV-2 positive persons. However, smoking history (former + current smoking) seems to be more frequent among SARS-CoV-2 positive individuals than never smoking. It is not known what is the percent of former smokers who were recent quitters; duration of previous abstinence from smoking is a crucial variable in assessing associations with smoking status. This raises the question of the validity of smoking status category classification. <br /> It is not known when smoking status is reported with respect of the SARS-CoV-2 testing. It is likely that individuals with clinical symptoms stopped smoking some days before testing and considered themselves as former smokers.

The fact that alcohol use disorder, which is frequently associated with tobacco use disorder, is also less frequent among SARS-COV-2 positive individuals raises the question of the specificity of the smoking finding and the raises the contribution of substance use disorders overall i.e. the finding about current smoking is part of a cluster of various previous or current substance use disorders e.g. cannabis use, potentially associated with SARS-CoV-2 negative test. <br /> COPD as well as current smoking are being reported to be more frequent among SARS-CoV-2 negative individuals raising the possibility that reduced respiratory function (entry of SARS-CoV-2 is by the respiratory tract) is associated with lower likelihood of SARS-CoV-2 positive tests. This hypothesis may suggest that reduced respiratory function and not smoking itself is associated with higher likelihood of SARS-CoV-2 negative tests. <br /> The paper does not report on analyses of smoking by clinical signs/co-morbidities interactions. It is likely that former smokers or those with alcohol use disoders are more frequent among individuals with comorbidities. Based on previous knowledge about smoking associated health disorders, one can assume that more severe clinical signs were associated with current smoking or among recent quitters; the smoking x clinical signs interaction is not tested. <br /> The authors conclude on page 14 “To wit, we found that current smoking, COPD, and alcohol use disorder, factors that generally increase risk of pneumonia, were associated with decreased probability of testing positive. While they were not associated with hospitalization or intensive care, it is too early to tell if these factors are associated with subsequent outcomes such as respiratory failure or mortality.”<br /> The reduced current smoking rate among SARS-CoV-2 positive individuals is an interesting but preliminary finding. It is likely that it is part of a more complex symptomatology and not specific to current smoking. Smoking status should have been assessed on a more detailed manner. The current findings, from a retrospective cross sectional analysis, certainly not support the hypothesis that current smoking protects against SARS-CoV-2 positivity.

On 2020-04-16 21:17:49, user Sinai Immunol Review Project wrote:

Key findings:

The authors wanted to better understand the dynamics of production SARS-CoV-2-specific IgM and IgG in COVID-19 pneumonia and the correlation of virus-specific antibody levels to disease outcome in a case-control study paired by age. The retrospective study included 116 hospitalized patients with COVID-19 pneumonia and with SAR-CoV-2 specific serum IgM and IgG detected. From the study cohort, 15 cases died. SARS-CoV-2 specific IgG levels increased over 8 weeks after onset of COVID-19 pneumonia, while SARS-CoV-2 specific IgM levels peaked at 4 weeks. SARS-CoV-2 specific IgM levels were higher in the deceased group, and correlated positively with the IgG levels and increased leucocyte count in this group, a indication of severe inflammation. IgM levels correlated negatively with clinical outcome and with albumin levels. The authors suggest that IgM levels could be assessed to predict clinical outcome.

Potential limitations:

There are limitations that should be taken into account. First, the sample: small size, patients from a single-center and already critically ill when they were admitted. Second, the authors compared serum IgM levels in deceased patients and mild-moderate patients and found that the levels were higher in deceased group, however even if the difference is statistically significant the number of patients in the two groups was very different. Moreover, receiving operating characteritics (ROC) curves were used to evaluate IgM and IgG as potential predictors for clinical outcome. Given the low number of cases, specially in the deceased group, it remains to be confirmed if IgM levels could be predictive of worst outcome in patients with COVID-19 pneumonia. The study did not explore the role of SARS-CoV-2-specific IgM and IgG in COVID-19 pneumonia.

Overall relevance for the field:

Some results of this study have been supported by subsequent studies that show that older age and patients who have comorbidities are more likely to develop a more severe clinical course with COVID-19, and severe SARS-CoV-2 may trigger an exaggerated immune response. The study seems to demonstrate that the increase of SARS-CoV-2-specific IgM could indicate poor outcome in patients with COVID-19 pneumonia, however given the very small sample size, the results are not yet conclusive.

Review by Meriem Belabed as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn school of medicine, Mount Sinai.

On 2022-02-08 21:10:34, user Sara wrote:

Thank you for your comment, unfortunately, I did not receive your comment once you replied. 1- we are in the era in the big data, more projects are aimed at generation of large cohort that we can depend upon to derive our clinical decision. <br /> The analysis used the data from US, the model will be deployed and can be used after that to predict the survival time of small cohorts. <br /> 2- We investigated the hazards assumption, we agree with you, we should add the results in the manuscript<br /> 3- SEER database identify the surgery as the surgical removal of the tumour.<br /> 4- I agree with you on the grade, it was on the old grading system for glioblastoma which is mentioned on SEER guidelines. Updated version will be posted and will update the analysis removing this one<br /> 5- we agree with you, we will change it in the updated comments<br /> 6- It is not insane! Developing models that consider these cases is a challenge. These models will be deployed for survival prediction of different cases of glioblastoma with different survival times.

7- we are developing a model that can be used for the routine data "we use", in this case US cancer data. We have a model that performed well so it can be deployed in the future for the clinical use for our routine data. the model is trained on large sample size that we believe it will achieve accurate prediction results for any routine data. The deployment of the model and its use in clinical practice is the goal. I hope you see the full picture.

Thank you for your comments.

On 2022-06-24 22:03:50, user Charles Warden wrote:

Hi,

Thank you very much for posting this preprint. This certainly represents a large amount of work and careful consideration!

I have some questions / comments:

1) Is there a way for me to calculate enhanced scores for myself?

For example, I would like to learn more, but I was not very satisfied with the PRS that I listed for my own genomic sequence in this blog post:

https://cdwscience.blogspot...

2) In the blog post link above, there seemed to be a noticeable disadvantage to the PRS without taking the BMI into consideration for Type 2 Diabetes.

In this paper, age is an important factor in Figure 1 for the PRS.

If other non-genetic factors are known, do you have a comparison for non-PRS models? <br /> For example, I wonder how performance of age + BMI (+ other established factors) compares to the plot for Type 2 diabetes in Figure 1.

3a) I see that the percent variance explained is sometimes provided (such as Supplemental Figure 5), but sometimes it is not.

For example, in Figure 3, the effect per 1 SD of PRS is higher for LDL cholesterol than height. However, how does the ability to predict an individual's height from genetics alone compare to the ability to predict an individual's LDL from genetics alone?

After a certain age (as an adult), the exact value for my own LDL has varied more than my height. However, I was not sure how that variation by year compared to others and/or the variation over decades.

In general, I would like to have a better sense of how absolute predictability compares for height versus disease scores. I also understand that there are complications with binary versus continuous assignments, but it is something that I thought might be helpful.

3b) I see AUC statistics in Supplemental Figure 2, described as for AUROC. However, am I correct that some of the cases are not well balanced with controls?

If so, should something like AUPRC be provided (possibly as a complementary supplemental figure)? I believe the idea is described in Saito and Rehmsmeier 2015; the application is very different, but you can see the inflated AUROC values in Figure 1A of Xi and Yi 2021. I expect that there are other good ways to illustrate the differences with PRS in cases and controls of varying proportions, but that was one thought.

In the context of genomic risk, I might expect that high predictability in a small number of individuals may be preferable over a small difference in low predictability in a large number of individuals. There is emphasis on thresholds like top/bottom 3% (in many but not all figures), which I thought might be consistent with that opinion.

So, I think something like Figure 1 was helpful. In order to try and capture how false positives change when sensitivity increases, I am not sure if something similar for positive predictive value might help? I would consider that very important if the PRS might be used for screening purposes.

4) In the Supplemental Methods, I believe that you have a minor typo:

Current: 100,000 Genomes Project (100KGP). The 100,00 Genomes Project, run by Genomics England,<br /> Corrected: 100,000 Genomes Project (100KGP). The 100,000 Genomes Project, run by Genomics England,

Thank you very much!

Sincerely,<br /> Charles

On 2025-07-24 23:50:17, user Rong Liu wrote:

Update on the association between influenza vaccination and cardiovascular outcomes

Dear readers,<br /> As the authors of a living systematic review on the association between influenza vaccination, cardiovascular mortality and hospitalization, (1) we want to update readers on the findings from our most recent search. The review protocol specifies updates every six months for a minimum of three years, commencing April 2022. The baseline search was conducted on 31 May 2022, with subsequent updates on 25 January 2023 and 1 September 2023. Results from these initial searches were published in Vaccine in January 2024. (1)

The latest search, completed on 31 March 2025, identified two studies that meet the eligibility criteria for review inclusion. Both are multi-center trials conducted within a single country, with a follow-up duration of at least 12 months. A third study was excluded due to its shorter follow-up period of only six months. (2,3) The eligible studies include a China-based trial (PANDA II) enrolling patients hospitalized for heart failure, (4) and an India-based trial (FLUENTI-MI) enrolling patients with recent myocardial infarction. (5,6) In both studies, the intervention is influenza vaccination. The comparator in FLUENTI-MI is saline placebo, and standard care in PANDA II. The primary outcome in both trials is a composite of all-cause mortality and all-cause hospitalization during the locally defined influenza season.

As of 6 June 2025, neither study has publicly available results, and therefore we are unable to update the meta-analysis at this time. Table 1 summarizes the study characteristics and expected timelines. PANDA II completed recruitment in February 2024 and is expected to report results within the next year. (4) FLUENTI-MI is projected to complete recruitment in October 2028. Given the current pace of research in this area, we believe that biannual updates are no longer necessary, and we will transition to annual updates for the next five years, starting from the date of this latest search.

Reference <br /> 1. Liu R, Fan Y, Patel A, et al. The association between influenza vaccination, cardiovascular mortality and hospitalization: A living systematic review and prospective meta-analysis. Vaccine. 2024/02/15/ 2024;42(5):1034-1041. doi: https://doi.org/10.1016/j.vaccine.2024.01.040 <br /> 2. Liu R, Patel A, Du X, et al. Association between influenza vaccination, all-cause mortality and cardiovascular mortality: a protocol for a living systematic review and prospective meta-analysis. BMJ Open. 2022;12(3):e054171. doi:10.1136/bmjopen-2021-054171<br /> 3. Tkaczyszyn M. Vaccination Against Influenza Pre-discharge in Heart Failure. https://clinicaltrials.gov/study/NCT06725927 <br /> 4. Zhang Y, Liu R, Zhao Y, et al. Influenza vaccination in patients with acute heart failure (PANDA II): study protocol for a hospital-based, parallel-group, cluster randomized controlled trial in China. Trials. 2024/11/25 2024;25(1):792. doi:10.1186/s13063-024-08452-8<br /> 5. Roy A. Influenza Vaccine to reduce cardiovascular events in patients with recent myocardial infarction: a multicentric randomized, double-blind palcebo-controlled trial. https://trialsearch.who.int/Trial2.aspx?TrialID=CTRI/2024/05/067056 <br /> 6. Roy A, Yadav S. Influenza vaccine in cardiovascular disease: Current evidence and practice in India. Indian Heart Journal. 2024/11/01/ 2024;76(6):365-369. doi: https://doi.org/10.1016/j.ihj.2024.11.247 <br /> https://uploads.disquscdn.c...

On 2020-05-14 14:35:10, user Hans Tinger wrote:

3% after 1 Werk, 6%after 2 Weeks, 9% after 3 Weeks... I am curious for week 4-8. Will you publish preliminary results soon again?

On 2020-03-25 21:03:54, user Sinai Immunol Review Project wrote:

Summary of Findings: <br /> - Clinical data from 116 hospitalized CoVID-19 patients analyzed over 4 weeks for correlation with renal injury. Comorbidities included chronic renal failure (CRF) in 5 patients (4.3%). <br /> - Approx 10.8% of patients with no prior kidney disease showed elevations in blood urea or creatinine, and 7.2% of patients with no prior kidney disease showed albuminuria. <br /> - Patients with pre-existing CRF underwent continuous renal replacement therapy (CRRT) alongside CoVID-19 treatment. Renal functions remained stable in these patients. <br /> - All 5 patients with CRF survived CoVID-19 therapy without progression to ARDS or worsening of CRF.

Limitations: <br /> - Renal injury biomarkers in patients with incipient kidney abnormalities not tabulated separately, making overall data hard to interpret. It will be critical to separately examine kidney function (BUN, urine creatinine and eGFR) in patients that developed any kidney abnormalities (7.2~10.8% of cohort). <br /> - No information on type of CoVID-19 therapy used across cohort; will be useful to correlate how treatment modality influences kidney function (and other parameters). <br /> - Invokes previous clinical-correlation studies that indicate low instances of kidney damage [1,2], but those studies did not track longitudinal urine samples for acute renal injury markers and viral shedding. <br /> - CRRT in patients with CRF is standard therapy irrespective of CoVID-19 status; it will be important to compare clinical parameters of these patients (n=5) with virus-naïve CRF patients (none in this study) to make any meaningful conclusions.

Importance/Relevance: <br /> - This study argues that renal impairment is uncommon in CoVID-19 and not associated with high mortaility, in stark contrast to a concurrent study (https://doi.org/10.1101/202... ). If supported by further studies, it suggests kidney impairment is secondary to cytokine storm/inflammation-induced organ failure, and not due to direct viral replication. <br /> - Will be important to comprehensively characterize larger datasets of CoVID-19 patients across hospitals (meta-analyses) to conclude if kidney function is actively disrupted due to viral infection, and if renal disease is a major risk factor for worse CoVID-19 outcomes.

References: <br /> 1. Wang D, Hu B, Hu C, et al. JAMA 2020; published online Feb 7. <br /> doi: 10.1001/jama.2020.1585

1. Guan WJ, Ni ZY, Hu Y, et al. MedRvix 2020; <br /> doi: https://doi.org/10.1101/202....

Review by Samarth Hegde as part of a project by students, postdocs and faculty at the <br /> Immunology Institute of the Icahn school of medicine, Mount Sinai.

On 2024-05-01 23:32:45, user ppgardne wrote:

This is an excellent paper, showing a clear association between variation in RNU4-2 and NDD phenotypes. The enrichment of variation in the gene between undiagnosed NDD and population cohorts was remarkable.

I thought there were a few areas where the manuscript could be improved slightly.

* Figure 1: Clearly define the measures “genotype quality”, “allele balance” and “total coverage”. We can infer what these mean, but definitions of each in the method section would be helpful.

* Table 1: I spent some time gathering the population sizes for each of the count columns. Please add an extra row or two, giving the number of individuals in GEL NDD, Non-GEL NDD and the population cohort.

* The statement “Humans have multiple genes that encode the U4 snRNA, although only two of these, RNU4-2 and RNU4-1, are highly expressed in the human brain” is slightly inaccurate. The HGNC database and reference (https://doi.org/10.15252/em... "https://doi.org/10.15252/embj.2019103777)") list just those two functional copies of U4 in the human genome. There are ~100 annotated pseudogenes however.

* You state that there is “97.2% homology” between RNU4-1 & RNU4-2 – this is a wrong (but common) use of the term homology. You should have stated “similarity” instead.

* Figure 3: I understand that the BrainVar RNAseq data are from samples of human dorsolateral prefrontal cortex. This should be stated in the caption.

* Figure 3: you state that “expression of RNU4-1 & 2 is tightly correlated”. Looking at the figure it appears the tissues with higher expression are also the ones were more samples were taken. Was the potential confounding of sample depth and/leverage accounted for in the analysis?

* Figure 4: it is unclear what this heatmap is showing. Is it really normalised on a per-gene basis, or is the null for SNV densities derived from the 1,000 random intergenic sequences mentioned in the methods? That would seem to be a more useful measure of variant enrichment or paucity. The ordering of the sequences is odd too, why are the paralogous genes U4/U4ATAC, U1/U11, U2/U12, U5 etc not next to each other? Surely the paralogs are more comparable. What is the justification for an 18bp window? –Other than that is the size of the variable region in RNU4-2.

* The recurrence of n.64_65insT is fascinating. And speculation on the mechanism is very worthwhile. You mention early in the manuscript the possibility of slippage in homopolymer regions, but this is not mentioned again in the appropriate section. You mention local secondary structure as a possible driver, but there seems to be very little evidence to support this based on free energy modelling.

On 2024-11-30 22:32:43, user xPeer wrote:

Summary<br /> The preprint investigates the remodeling effects of icosapent ethyl (IPE) supplementation on plasma lipoproteins and its subsequent impact on cardiovascular disease (CVD) risk markers in normolipidemic individuals. The study finds that IPE supplementation significantly enhances eicosapentaenoic acid (EPA) levels in the plasma, reducing major CVD risk markers such as triglycerides, remnant cholesterol, and apoB levels. There are consistent alterations across all lipoprotein classes, influencing their lipidomes, reducing proteoglycan binding properties, and potentially decreasing the atherosclerotic risk. However, the study's small sample size and short duration limit the generalizability of findings.

Major Revisions

1. Extended Sample Size and Duration:<br /> The study's findings are constrained by a limited sample size and short duration (28 days), impeding the generalizability to broader populations or those with pre-existing cardiovascular conditions.

2. Example: Expand the cohort size and extend the duration to assess long-term impacts and variability of EPA incorporation among different CVD risk groups (Discussion, Page 14).

3. Detailed Mechanistic Insights:<br /> The precise mechanisms by which IPE alters lipoprotein characteristics and its direct influence on cardiovascular outcomes remain unclear.

4. Example: Detailed mechanistic studies on how IPE-induced lipid species changes relate to atherosclerosis progression are needed (Results, Page 11).

5. Individual Variability Analysis:<br /> The study underscores substantial interindividual variability in response to IPE supplementation, calling for personalized treatment approaches.

6. Example: Investigate genomic or lifestyle factors contributing to variability in response to IPE (Results, Page 13).

7. Proteoglycan Binding and Aggregation:<br /> The study notes reduction in proteoglycan binding and different responses in LDL aggregation among participants but lacks detailed analysis.

8. Example: Provide more comprehensive data and rationale behind the differential LDL aggregation responses post IPE-supplementation (Results, Page 8).

Recommendations

1. Larger and Diverse Cohort Studies:<br /> Conduct studies with larger and more diverse cohorts to bolster the reliability and applicability of the findings across various population subsets.
2. Longitudinal Studies:<br /> Extend the study duration to capture long-term effects of IPE on lipoprotein profiles and cardiovascular health outcomes.
3. Mechanistic Pathway Research:<br /> Incorporate omics approaches (genomics, proteomics) to unravel the underlying mechanisms modified by IPE that contribute to reduced CVD risks.
4. Personalized Medicine Approaches:<br /> Develop stratified medicine approaches to optimize IPE dosage and treatment protocols tailored to individual lipidomic profiles and genetic backgrounds.
5. Detailed Biophysical Characterization:<br /> Enhance the biochemical and biophysical characterization of proteoglycan binding and lipoprotein aggregation properties altered by IPE supplementation.

Minor Revisions

1. Textual and Formatting Errors:
2. Ensure consistency in figure label fonts and styles across the manuscript.
3. Correct minor typographical errors and ensure uniformity in section formatting (e.g., use of italics, bold).

4. Specific errors include inconsistent capitalization in headings and figure labels requiring standardization (Introduction, Page 2; Results, Page 8).

5. AI Content Analysis:

6. Estimated AI Content: Approximately 10%.
7. Highlighted AI-Detected Sections: Notable in the background and introduction sections with possible AI involvement in text generation.
8. Assessed Epistemic Impact: The AI-generated content does not undermine the scientific rigor but would benefit from expert revision to enhance field-specific terminology and depth.

Overall, the preprint presents insightful preliminary findings on the cardioprotective impacts of IPE supplementation, recommending essential improvements and comprehensive validations for future extensive studies.

On 2025-02-24 23:42:40, user Stephen Goldstein wrote:

Manuscript summary

The authors report a small study comparing patients with “post-vaccination syndrome” or “PVS” with vaccinated, healthy controls. They used a variety of immunological techniques and report they have identified potential immune signatures in PVS patients, which may reflect an underlying mechanism of this condition.

Personal disclaimer

This manuscript has received considerable attention and attracted much commentary, including critical commentary from myself on twitter (@stgoldst). I was immediately skeptical of these findings given the attention to it, small study size, and amplification by anti-vaccine activists. However, the potential for vaccine injury is a serious matter, so a rigorous review of this manuscript is a critical need. I attempt here to account for my biases, and to check for these I used a Google AI model to conduct an orthogonal review. That is posted separately.

Review

Overview

This study described by this manuscript is methodologically flawed to a degree that undermines the authors’ stated goal to identify biomarkers for post-vaccination syndrome (PVS). These flaws are systematic, ingrained into the study design, and compounded by analytic flaws throughout the manuscript. As is, this study provides weakly informative data at best towards understanding chronic illness following vaccination. The methodological flaws are listed below and subsequently expanded upon.

1. PVS and control cohorts are very small, and even smaller when stratified by infection status.
2. Prior infection status is poorly controlled – though this may be difficult to overcome
3. The study does not include a control group of unvaccinated individuals reporting similar chronic symptoms as the PVS cohort.
4. PVS is defined by self-reported symptoms with no clinical assessment or classification system.
5. Small effect sizes and weak correlations are repeatedly described via their statistical significance, with no biological context provided by the authors.

6. The study provides no evidence for a causal link

7. PVS and control cohorts are very small, and even smaller when stratified by infection status.

The PVS cohort comprised only 44 patients originally, and was reduced to 39 due to pharmacological inhibition in 2 patients. The authors acknowledge that due to the small size of the study and its exploratory nature they did not conduct a power analysis. They acknowledge the difficulty in producing robust results due to the sample size. Despite acknowledging these problems, the authors repeatedly invoke the statistical significance of various analyses and in some cases rely on extremely involved statistical testing to identify weak signals. This presents an impression that the authors understand the inability, baked in from the start, of the study to be informative yet press ahead anyway.

1. Prior infection status is poorly controlled – though this may be difficult to overcome. T

he authors stratify the cohorts by infection status, with the primary determination based on serological status of anti-nucleocapsid (N) antibodies. The study participants were recruited in December 2022 at the earliest, nearly 3 years after the first SARS-CoV-2 infections were identified in the United States. Given the expected decline in serum antibody titers over time, it’s likely that people infected in the first year of the pandemic (and possibly even later into the pandemic) would test seronegative. Therefore, the -I cohorts likely include individuals who were in fact infected with SARS-CoV-2 at some point. This is a critical issue. The number of individuals without infection history is likely even smaller than presented, reducing the utility of stratification. In addition, this may actually confound the ability to disentangle the effects of vaccination vs infection in the development of chronic illness. It would be difficult to methodologically correct for this without a prospective longitudinal study. However, larger sample sizes might allow researchers to mitigate its impact. Given these sample sizes and the inability to reliable sort by prior infection status, the issue precludes making robust inferences from the data.

1. The study does not include a control group of unvaccinated individuals reporting similar chronic symptoms as the PVS cohort.

The authors describe the health of study participants based on GH VAS scores and note that PVS participants were in worse health than the control participants. In the Discussion, the authors expand on this, noting that PVS participants also had worse health than the U.S. general population. Given the real potential for other disease processes to impact every one of the biomarkers tested, the lack of unvaccinated, chronically ill participants (reporting the same syndromic profile as PVS patients) confounds any correlates between these biomarkers and vaccination. The study analyses are uninterpretable with respect to the impact of vaccination on health, as a result.

1. PVS is defined by self-reported symptoms with no clinical assessment or classification system.

PVS was previously described by some of the same authors based on self-reported chronic sequelae following vaccination. This definition is then relied upon in this study. However, many of these symptoms are non-specific and certainly there is no evidence, given the lack of complete overlap, that they represent a single syndrome. There does not appear to be any clinical assessment to verify any of them. This is a repeated issue with descriptive studies of long covid (PACS) and now PVS, and I acknowledge the inherent challenges in establishing other criteria. Nevertheless, it represents a major problem in trying to describe a unified syndrome downstream of vaccination.

1. Small effect sizes and weak correlations are repeatedly described via their statistical significance, with no biological context provided by the authors.

Throughout the manuscript the authors describe differences between PVS and patient cohorts solely through the p-value returned by statistical testing. Looking at the figures themselves the effect sizes turn out to be extremely small in virtually every case. Small effect sizes don’t mean there is no biological significance, but the authors in this study expend no effort to offer context or even a coherent hypothesis for why these effect sizes are significant. Expecting the reader to favorably interpret the data, or indeed interpret it all, based purely on p-values is…disconcerting. It’s not clear in the writing that the authors even consider effect sizes to be relevant, or if getting a sufficiently small p-value is good enough to report and believe a major finding. I’m not confident that the authors really interpreted the data to any depth themselves.

1. The study provides no evidence for a causal link.

There is simply no causality evident in the data or really presented by the authors. Given the generally poor health of the PVS participants, all of the elevated inflammatory biomarkers and the elevated EBV reactivity could all be due to varied other disease processes, infectious or not. One clear example of this is Figure 4K where the authors correlate EBVgp42 reactivity with the percentage of CD8+ T cells producing TNF?. The Correlation R value is 0.47, indicating a weak to moderate link. Because EBV reactivation is tightly linked to general stress, the weakness of this correlation is highly suggestive of other disease processes making a significant contribution, or the PVS link being artifactual. The authors make no effort to account for this.

Specific Points

References 16 and 18 need to be corrected

“interaction with full-length S, its subunits (S1, S2), and/or <br /> peptide fragments with host molecules may result in <br /> prolonged symptoms in certain individuals16.”<br /> -Ref16 is a study describing circulating spike and S1 <br /> following vaccination, but does not mention anything about<br /> prolonged symptoms.

“Recently, a subset of non-classical monocytes has been shown to harbor S protein in patients with PVS18.” <br /> -Ref18 is a study on PACS (post-acute covid-19 sequelae) <br /> and does not mention vaccination or post-vaccination <br /> syndrome<br /> -Ctrl+F for “vaccine” “vaccination” “PVS” returns no results in <br /> this manuscript

Figure 3 on the kinetics of serological findings is generally confusing<br /> -For Control and PVS+I groups the authors report no decline <br /> in anti-spike antibodies over the course of months to year. <br /> -This runs counter to basic immunological principles and <br /> robust, repeatable findings with respect to anti-SARS-CoV-2<br /> spike antibodies in particular<br /> -One explanation for this is subsequent mild infections that <br /> boost antibody levels, but there are no spikes evident, but <br /> rather a steady maintenance.<br /> -The exception to this is PVS-I antibodies which decline at <br /> what is to the naked eye a normal rate. <br /> -This suggests an issue with the control or PVS+I cohorts, or <br /> a disturbing indication that they are not representative of the <br /> immunological state in their respective populations. Due to <br /> the small sample size, this seems likely<br /> -The authors should explain that because the PVS-I <br /> participants weren’t infected, their “days since post-<br /> exposure/vaccination” data are identical. Absent that, it’s <br /> confusing to notice that the PVS-I data in rows B and C are <br /> identical and raises concern about duplication in figures

The authors don’t describe the rationale for the EBV coinfection analysis displayed in Figure 4, and so there’s no way for the reader to interpret what (if any) significance to ascribe to it.<br /> -Figure 4D shows a small but statistically significant <br /> increase in IgG against EBVgp42 for PVS cohort relative to <br /> controls – however...<br /> -When the PVS cohort is stratified by prior infection status <br /> there is no statistically significant difference<br /> -This make it really difficult to interpret the difference when<br /> the PVS group remains together<br /> -It raises the question for me of whether the statistical <br /> significance is just sensitive to the number of data points,<br /> which for me makes it not robust<br /> -Again – as throughout the paper no biological context is<br /> given

Even the correlation between EBVgp42 in serum and EBVgp42 antibody reactivity is low<br /> -Again very difficult data to interpret and unclear what the <br /> biological significance would be<br /> -Problems with the correlation analysis in Figure 4K were <br /> discussed above<br /> Figure S4C is discussed in the text, but briefly and important data is ignored<br /> -It appears true that PVS participants have elevated<br /> autoantibodies of IgM and IgA isotypes, but their IgG <br /> autoantibodies are actually similar to controls<br /> -Not clear if there might be a class switching defect that <br /> could be related to a pathogenic process, or other<br /> explanation – the authors don’t address<br /> -The authors just say PVS patients just have autoantibodies,<br /> which obfuscates their own data that it’s isotype specific<br /> The interpretation of Figure 5C is also strange – most PVS patients have no circulating anti-S1 antibodies and the statistically significant difference is driven by a minority who do<br /> -The authors state there’s a difference without any effort to<br /> interpret it<br /> -This suggests that PVS, which the authors are trying to<br /> characterize as one syndrome, is either not one thing, or the<br /> presence or absence of anti-spike antibodies is ancillary<br /> -Unfortunately the authors gloss over any nuance in the data<br /> The data on specific biomarkers in Figure 5H is based on such small sample sizes I question whether it was even appropriate to do this analysis at all<br /> -To be clear, the issue isn’t whether the question is worth<br /> asking, it is. The issue is that one should not do an analysis<br /> that is so underpowered it will be definitionally <br /> uninterpretable<br /> -The fact that the authors had to jump through statistical<br /> hoops to find a statistically significant effect is concerning <br /> -the fact this includes a sub-group of only three patients is <br /> just methodologically inappropriate.<br /> Given the authors’ use of machine learning failed to reveal any coherent set of biomarkers further argues against the contention that PVS is a definable syndrome<br /> -Or, that this study is so small it lacks value in defining the <br /> syndrome

Final summary

Ultimately this study adds little value, at best, towards understanding post-vaccination sequelae experience and reported by some individuals. At worst, it injects claims and interpretations into the field and discourse that are unfounded, and will ultimately slow efforts to help patients. These results have already been used to advance anti-vaccine narratives in online discourse. If the data were robust, no one could complain. Because the data are not, it is tragic. Ultimately, there is no compelling evidence in this paper for an immunological signature associated with chronic illness following vaccination. Perhaps reflecting this, the authors provide almost no biological context for any of their findings, often reporting data merely as a p-value with no comment on the effect size (whether large or small). This leaves it unclear to a reader whether the authors are even aware of flaws in their work. Given the methodological flaws of this study, it is a questionable investment for researchers to follow up on it in a targeted way. Rather, well-powered, controlled, and methodologically sound studies should be conducted at scale to enable actionable findings to be made.

On 2025-04-10 16:27:18, user Epidemiologist wrote:

This is a phenomenally bad study, which contains stark evidence of its bias in the Figure purportedly supporting its conclusions. To summarize:<br /> 1. They compare two groups of employees who received a trivalent, inactivated influenza vaccine. Those who received the vaccine (82%) and those who sought an exemption (18%).<br /> 2. As hospital employees, they are aware of the extent to which their work puts them at risk of exposure but the investigators make no effort to determine differences between these groups beyond very crude categorizations.<br /> 3. They find that, after 100 days, they see higher influenza rates in the vaccinated.<br /> 3. They provide no plausible explanation as to how the inactivated vaccine puts one at increased risk of influenza 100 days after vaccination.<br /> 4. That means the ONLY plausible explanation for a significantly higher risk in the vaccinated is a significantly higher exposure risk in the vaccinated. Ergo, the sample is biased.<br /> 5. It is notable that the infection rate among the vaccinated was only 2.5% in a high risk setting for infection. <br /> 6. In sum, the best explanation for their results is that the vaccine was very effective and their sample was biased.

On 2025-04-10 20:11:03, user Jeffrey_S_Morris wrote:

This study's conclusion of -27% negative effectiveness does not seem to be supported by the study, given they did not account for testing bias, which happens to also be 27%, with vaccinated testing on average a 27% higher rate than unvaccinated.

To their credit, the authors acknowledged this in the following plot:<br /> https://uploads.disquscdn.c... <br /> Here it can be seen in my replotting of their Figure 1a scatterplot on the log y axis (after extracting the data by applying AI tool to their scatterplot image), with the 27% increase being the (geometric) mean testing rate (vaccinated/unvaccinated) over the days they plotted.

https://uploads.disquscdn.c...

Incidentally, taking simple means (or fitting linear regressions) for a sample of ratios is not good statistical practice since the <1 and >1 parts are asymmetric, so instead the geometric mean (averaging on the log scale) should be used. For example, if one day is 4x higher for vaccine and one day 4x lower, they should average to be equivalent. The average on the raw scale (4 + 0.25)/2 = 2.125 would imply a mean 2.125x increase, which is incorrect, while a geometric mean (averaging on the log scale and then exponentiating) would get the correct result. 2^{log_2(4)+log_2(0.25)} = 2^(2 + -2) = 2^0 = 1. That is why I used geometric mean in the plot above and plot in the log scale, and think the authors should do the same in their paper.

While they acknolwedge the increased testing rate, the text of the paper dismisses it as a potential source of bias by claiming the test positivity rate is equivalent in vaccinated and unvaccinated. I agree with their logic that if test positivity were identical in vaccinated and unvaccinated, then the 27% higher testing rate could simply be a result of a 27% higher infection rate, and not from testing bias.

However, the analysis they present to support this assumption is not justified and seems flawed. They perform a linear regression of the ratio of testing positivity (vaccinated/unvaccinated) by day over time, and because the confidence bands intersect zero they conclude the test positivity is no different between vaccinated and unvaccinated, and thus the difference in testing rate is not a bias, but from the negative effectiveness that they conclude is true.<br /> https://uploads.disquscdn.c... <br /> However, this analysis is problematic for numerous reasons:<br /> 1. It is not clear why a regression over time should be done to answer this question, and not clear why one would assume any time trend is strictly linear. It would make much better sense to compute a (geometric) mean over time, or if wanting to model time trends to use a smooth nonparametric function.<br /> 2. Computing means or modeling time trends on ratios should not be done on the raw scale, but the log scale, for the reasons discussed above.

Plotting these numbers on the log scale (again, after using AI tool to extract it from their scatterplot image in the paper), I computed the geometric mean test positivity, and find it to be 0.80, meaning the "average" test positivity over time is 20% lower in vaccinated than unvaccinated, certainly not the same.

https://uploads.disquscdn.c... <br /> This lower test positivity is obscured in their original plot on the raw scale, since the ratios <1 got compressed and ratios>1 expanded.

If you have a situation with vaccinated having 1.27x the testing rate and 0.80x the test positivity, this would correspond to an infection rate that is 1.27 x 0.80 = 1.016x higher infection rate. This would correspond no difference in infection rate, certainly not a 27% increased infection rate in vaccinated.

While not a formal analysis, this demonstrates that vaccinated having a 27% higher testing rate along with a 20% lower test positivity rate could result in a 27% higher rate of confirmed flu infections even if the infection rate was equivalent between vaccinated and unvaccinated.

In that case. the 1.27x increased testing rate would be a testing bias that produces a spurious 1.27x confirmed infection rate even if the infection rate were not higher in the vaccinated.

Based on this, one cannot tell from the study whether the 1.27x increased rate of confirmed flu infections is from negative effectiveness (as claimed), or from the testing bias (which is not adjusted for in the analysis).

The authors cannot rule out the possibility that their results are caused by the testing bias, which is not accounted for in their analysis.

Thus, I don't think the conclusion of -27% VE is valid.

At most, they could say there is no evidence of any vaccine effectiveness vs. infection, but cannot conclude a significant negative effectiveness because of failure to account for the testing bias.

Of course, there are designs to adjust for this testing bias -- test negative designs -- but the authors eschew this design, seemingly because it gives odds ratios rather than relative rates which they express concern that they are not as intuitive to grasp.

To me, that seems like a relatively minor issue relative to testing bias of sufficient magnitude to drive spurious results.

If I were reviewing this paper, I'd require them to adjust for the testing bias, and ideally perform a test negative design, even if considered a secondary analysis.

Of course test negative designs have their own limitations and potential biases, but at least considering it as a secondary analysis would be useful to see if they obtain equivalent results using that design and, if not, should raise questions on whether they should boldly conclude negative effectiveness in this study, or instead more carefully conclude a lack of evidence of vaccine effectiveness in their cohort.

These concerns are also summarized in an http://x.com thread

On 2025-10-20 15:20:57, user xPeer wrote:

Courtesy Double-Blind Peer Review Simulation from xPeerd :

Reviewer #1 Report

Summary<br /> The study aims to assess and compare the effectiveness of three advanced large language models (LLMs)—ChatGPT-5, DeepSeek V3, and Grok 4—in generating educational content about ADHD for non-specialist educators and outsourced physical education coaches. Employing a controlled prompt-based methodology and multiple readability/complexity indices, the manuscript investigates response accuracy, clarity, stability, and potential public health communication barriers in AI-generated outputs.

Major Comments

1. Methodological Rigor & Generalizability<br /> The authors delineate a robust comparative framework, utilizing three guiding questions on ADHD for model interrogation. However, the scope is limited, as the testing population pivots exclusively on English-language outputs and Melbourne-based prompts. The authors themselves acknowledge:

2. "The study was conducted exclusively in English within a Melbourne-based testing environment, limiting generalizability to non-English-speaking populations" (page 21, Strengths and limitations).<br /> Reviewer suggestion: Future analyses should encompass a broader linguistic and cultural spectrum to truly capture the global applicability of AI for health education.

3. Depth of Statistical/Computational Analysis<br /> The study makes extensive use of readability indices (FKGL, SMOG, etc.), but does not sufficiently discuss their limitations when assessing AI-authored medical content. There is potential for bias when equating increased complexity with reduced accessibility; often, necessary clinical nuance may inherently raise reading levels. The manuscript states:

4. "Readability analyses further showed that DeepSeek V3 had the greatest variability, GPT-5 displayed steadily increasing complexity, and Grok-4 remained the most stable and comparatively less complex" (Discussion, page 17).<br /> Reviewer suggestion: A more critical lens is warranted—consider a combined readability/accuracy approach to better contextualize the trade-offs between precision and simplicity.

5. Real-World Impact and Usability<br /> Despite extensive quantitative comparison, the practical implications for coaches, teachers, and parents are relegated to future work. The manuscript admits, "The study focused primarily on textual readability and stability, rather than evaluating real-world comprehension or decision-making by specific user groups" (page 21).<br /> Reviewer suggestion: The next phase should prioritize empirical user testing to validate whether model outputs actually enhance pedagogical or clinical understanding and decision-making.

6. Novelty and Ethical Perspective<br /> The comparative model analysis is novel, considering recent LLM advances and lack of similar head-to-head studies tailored for disability inclusion in school settings. However, no ethical concerns are addressed regarding AI output veracity, data privacy, or the risk of erroneous instruction imparted to underqualified staff.

Minor Comments

• The referencing format is occasionally inconsistent and page numbers for tables/figures are absent in some cases.
• The abstract is concise and provides a clear structure; nonetheless, the results section could briefly mention statistical significance values or variability ranges.
• Some sentences are overly long or complex, detracting from readability—ironically contrary to the study's focus.
• In "Ethics approval and consent" (page 22), it is useful to state "Not applicable," but the authors might clarify that all AI-generated responses involved no human data or interventions.

Recommendation <br /> Major Revision. The manuscript exhibits methodological strength and addresses a pressing question. However, broader evidence on practical efficacy, nuanced readability analysis, and an explicit discussion of ethical boundaries are required prior to acceptance.

Reviewer #2 Report

Summary<br /> This manuscript sets out to systematically evaluate the readiness and reliability of LLMs to deliver inclusive, high-quality ADHD education materials, especially for outsourced PE instructors and non-specialist users—a group often neglected in the literature. The three chosen models represent current state-of-the-art options. The topic is pertinent and innovative.

Major Comments

1. Overstatement of Claims and Realistic Outcomes<br /> The conclusion suggests that "model selection should be tailored to specific use cases," advocating for Grok-4, DeepSeek V3, and GPT-5 each in particular contexts (page 20, Discussion). However, the comparative exercise data provided fall short of substantiating such a granular recommendation; the outcome differences, though statistically noted, remain within a similar range of excessive complexity:

2. "All models exhibited high reading levels (FKGL > 12), exceeding recommended public-health standards" (page 2).<br /> Caution should be exercised when suggesting differential real-world deployment based on such preliminary and textual-only evidence.

3. Potential for Algorithmic and Sampling Bias<br /> The study design is at risk of sample/data selection bias by exclusively testing models with English-language queries and drawing all responses from the same geographical/IP base (Melbourne). This potentially disadvantages queries that might behave differently in other contextual deployments; more granular breakdowns by topic or scenario might add value.

4. Empirical/Practical Verification—A Missing Piece<br /> While the authors readily admit the absence of real-world user testing (page 21), at a minimum, the study could have incorporated expert review(s) by practicing educators or clinicians to validate the appropriateness, accuracy, and utility of the outputs. Relying strictly on “readability” as a performance surrogate is insufficient.

5. Accessibility and Communication Gaps<br /> The core finding—that "readability emerged as a persistent barrier across all models" (page 20)—is highly significant. However, the manuscript stops short of offering actionable guidance to AI developers or educators on how to bridge this gap (e.g., adaptive output tuning, multilayered content, or collaborative design with stakeholders).

6. Risk of Exacerbating Health Inequities<br /> The text insightfully warns, "the broad dissemination of LLM-generated health information risks exacerbating health inequities" (page 20). Surprisingly, no strategies or intervention suggestions are offered. It would strengthen the manuscript to suggest how LLM output might be scaffolded or tailored for vulnerable groups.

Minor Comments

• In the methods section, the protocol could be described more clearly, including how the ten independent attempts for each prompt were randomised or sequenced.
• The discussion occasionally rehashes results rather than linking them to broader theory or policy implications.
• The limitations section should be expanded to acknowledge not just the lack of user participation but also incomplete handling of model drift and update cycles.

Tone and Style<br /> The review has detected sporadic verbosity or ambiguous phrasing (e.g., “the findings demonstrate that stability of response generation is varied between models”—page 20). Succinct, active language would benefit the overall clarity.

Recommendation <br /> Major Revision. Useful, important groundwork is laid here, but the manuscript requires deeper, more practice-oriented exploration, and a more measured, cautious reporting of implications. The lack of empirical field validation is a critical limitation.

Editorial Decision<br /> Decision: Major Revision Required

Both reviewers acknowledge the relevance and methodological rigor of the comparative approach, but insist on more empirical user validation, a critical reappraisal of the readability/accuracy trade-off, and practical translation of findings for end-users and policy-makers. Ethical considerations and limitations should be explicitly elaborated.

On 2023-05-28 06:54:51, user Stuart Gilmour wrote:

Dear authors, I really want to believe this study (I am vulnerable to Ramsay Hunt Syndrome and have got this vaccine, and I would love to believe it also reduces my risk of dementia!) but I think you have massively under-estimated the effectiveness of the vaccine, which is a real missed opportunity. I want to explain why and I hope you'll take my comments into account. I think there are three sources of error in your study which I list in order of severity: 1) failure to take into account period at risk, 2) the change in slope term and 3) confounding due to education/wealth in sub-analyses.

[Obviously, the comments that follow assume I have correctly understood your methods, so please forgive me if I have missed something your explanation]

1) is the reason I think the study under-estimates the effect. I wondered why it is that you found a vaccine efficacy (after adjusting for take-up of the vaccine) against shingles of 41%, while the 2005 NEJM study you reference finds it to be 55%, and I think this is because you have not properly accounted for follow-up time. Judging by how you report probabilities, you seem to have calculated the proportion of people over seven years who got shingles (Fig 2) or dementia (FIg 3). This is also clear from your equation (1), which is a linear probability model. But since shingles incidence, dementia incidence and death risk increase by age and your primary study cohort is 80 years old, follow-up time is a very important variable. Judging from your figure 2, the youngest people were 78 and the oldest 82 in this study. It's very likely therefore that the youngest people had to be followed for considerably longer before a diagnosis of shingles/dementia, and were also less likely to die of other causes. A person who dies of other causes before getting shingles/dementia should not be considered in the calculation, since we didn't find out whether they got it - they should be censored. Then, if we calculate incidence densities, we will find the youngest people (with the lowest proportion of cases) have a considerably longer follow-up time to diagnosis, and were less likely to drop out of follow-up early due to death. If you properly account for this in the model, I think you'll find that the rate in younger people is much lower than in older people and the discontinuity is greater.

I don't have UK data to hand, but I do have a life table by single year of age for the USA, which implies that there would probably be about 40% more follow-up time in the 78 year olds than the 82 year olds over the entire 7 years of the study, simply because of drop out due to death from all causes - a 78 year old american has a 4% chance of dying in one year, while an 82 year old has a 5.7% chance. Those differences add up over 7 years of follow-up!

This study is a classic survival study, and your decision not to use the follow-up time means that you have over-estimated the incidence density in young people and under-estimated it in older people. This also explains why your sex-stratified analysis finds no effect in men. How could the vaccine not work in men but work in women? Because at this age (~80 years old) men are dying much faster than women, with death rates increasing more rapidly over the study period, which attenuates the effectiveness more in men than in women.

If you use an incidence density (Poisson regression) or survival approach, it's easy to reproduce the approach described in equation (1) but you'll be properly accounting for follow-up time, avoiding the known problems associated with a linear probability model, and properly able to compare your results with those of the previous shingles vaccine studies.

[I'm sorry all my comments here hinge on my interpretation from your methods that you have assumed a 7 year follow-up for everyone, and simply calculated the proportion of events as the number who got shingles/dementia divided by the number at risk at the start of the 7 years. If I'm wrong about this, please ignore everything I wrote!]

For problem 2), the change of slope term, it seems obvious to me that the slope after week 0 in figure 3A is poorly fitted. If there was no change of slope term in this model, the change in level would be smaller and your study would show no effect. Was the beta3 term in your model for figure 3 statistically significant? I think it wasn't - there is no visible change of slope in the data shown there. Given how borderline your estimate of the change in level (Beta1) is, I think the conclusion of this analysis depends heavily on whether you choose to include the non-significant change of slope. Of course, this isn't very important because a) we should always report studies of this kind separately by sex and b) once you properly adjust for follow-up time the effect of the vaccine will be so huge that we'll immediately have a statistically significant effect with or without the change of slope term.

For problem 3), you estimate the CACE based on the assumption that there is "no other difference in characteristics that affects the probability of our outcomes occurring", and date of birth eligibility threshold "is a valid instrumental variable to identify the causal effect of receipt of the zoster vaccine on our outcomes". I'm not sure why you would believe this. People who receive any voluntary preventive health care in the UK are much more likely to be wealthy, to be better educated, and to be from certain occupations and backgrounds, and I would suggest it's highly likely that these factors are strongly associated with reduced risk of dementia. The method here is nice, but the assumption is completely unreasonable in the NHS context, and it's likely that these confounding factors would lead to a reduction in the CACE estimate. Again, if you properly account for follow-up time I doubt this will matter because the raw impact of the vaccine eligibility itself will be so much larger than your estimate that you will find a much bigger impact without needing to do any calculation of CACE (but anyway a simple caveat about this, or a calculation separately in each wealth stratum, might solve the issue).

I can't see any way that the lack of proper calculation of follow-up time would reduce the effectiveness of the intervention you have tested, so I'm going to continue to believe that this vaccine prevents dementia, but I worry that you have massively under-estimated the size of the effect and I guess there is a tiny chance the impact of this mis-calculation could go the other way.

I guess you could argue it doesn't matter if you've under-estimated the effect but I would say it does. I'm sure you're aware that in the UK the chickenpox vaccine is not part of the routine childhood immunization schedule. If your study finds a huge effect of shingles on dementia risk, this is a strong argument for preventing it at childhood, through inclusion of the vaccine in the routine schedule. But currently your study finds no benefit for men, a 20% overall reduction in relative risk, and about a 40% reduction in relative risk for women. I think if you properly account for follow-up time the effects will be much larger and consistent across men and women. Even a cursory consideration of such large numbers would surely be sufficient to tip even the UK's relatively anti-vaccination institutions into recommending both a) routine chickenpox vaccination of children b) routine shingles vaccination of adults and c) earlier implementation of adult vax. Currently for example in Japan the vaccination for shingles is recommended at age 50 but not covered under insurance, costs about 40,000 yen (350 pounds) and is not widely taken. If it has a huge impact on dementia risk the policy implications are enormous. So please don't undersell your work by using this linear probability model!!!

Thank you!<br /> Stuart Gilmour<br /> Professor, Biostatistics and Bioinformatics<br /> St. Luke's International University<br /> Tokyo<br /> Japan

On 2024-01-17 12:03:28, user Leonardo Martins wrote:

This ancestral-reconstruction based phylogeographic approach has been used before by us in SARS-CoV-2 analyses: <br /> 1. for finding the number of transmission events into or outside Lebanon https://www.ncbi.nlm.nih.go... <br /> 2. For estimating migration patterns between regions of England https://www.nature.com/arti...<br /> 3. To count the number of exports and importations into Pakistan https://www.ncbi.nlm.nih.go...

In our case we used the mugration model as implemented in TreeTime or ASR models implemented in Castor for R (https://cran.r-project.org/... "https://cran.r-project.org/web/packages/castor/index.html)")

On 2020-04-28 14:00:55, user Sinai Immunol Review Project wrote:

Main Findings<br /> This preprint sought to compare the daily deaths in countries using CQ/HCQ as a treatment from the beginning of the COVID-19 pandemic to those that did not. From a list of 60 countries in descending order by number of confirmed cases, 16 countries were selected for inclusion into either the high CQ/HCQ production or use group, versus not. Countries were included if they met the criteria for having data from the day of the 3rd death in the entire country and the daily deaths for the 10 days immediately following, until both groups were populated with a list of 16 (Figure 1: Table with the CQ/HCQ group list; Figure 2: Table with the “control” group list). For each group of countries, the average daily deaths were determined, and the curves projected to illustrate trajectories. In Figure 3, the author suggests that the deaths in the countries belonging to the control group follow an exponential curve, while the progression of average daily deaths in the countries with greater use of CQ/HCQ follow a polynomial curve.

The author then applies Auto Regressive Integrated Moving Average (ARIMA), a modeling tool used for time-series forecasting (i.e., predicting the future trajectory of data over time using the data from previous time points as predictors in a linear regression). The Auto Regressive component refers to each difference between two previous time points that make the model “stationary” (current – previous); the Moving Average is the number of forecast errors from calculating these differences that should go in the model. The author uses ARIMA to predict the next 10 days of mean deaths for the CQ/HCQ list (Figure 6) and the control countries (Figure 8). In figures 9 and 10, autocorrelations of residuals are performed to determine internal validity of the model, here defined as no significant autocorrelations.<br /> In conjunction, the author argues that these findings support major differences in death rates between countries that use/mass produce CQ/HCQ versus those that do not.

Limitations<br /> The title of this study refers to itself as an ecological study, an observational study in which the data are defined at the population level, rather than individual. Although this study design allows for rapid hypothesis testing in large datasets, a robust ecological study should account for as many known risk-modifying factors or confounders as possible. Subsequently, any results should be reviewed under strict criteria for causality, since there is high probability of the outcomes falling under the definition of ecological fallacy, which occurs when inferences about individuals are determined from inferences about a group to which they belong.

This study conflated the use and mass production of CQ/HCQ at the start of the COVID-19 pandemic in each respective country, with that country’s direct pandemic response. It is never explained whether use or production is the key output for any given country, which are vastly different metrics. The author fails to consider other reasons for having existing infrastructure for the mass production of drugs like hydroxychloroquine, whether the country was a global supplier of the medication (India), or is a region where malaria is endemic (India, Pakistan, Indonesia, Malaysia, South Korea), which may correlate to both chloroquine production and use. Notably, the countries from which studies of HCQ in the treatment of COVID-19 have been predominantly performed (China, France, USA), are all in the control list of countries. Additionally, the data for cases and deaths were collected from reports accessed from https://www.worldometers.in... data were not selected from the top countries using a methodological approach, but rather skipping certain countries to use only the most complete death data for the timeframe of interest, allowing for bias introduced by the reporting of each individual country.

With regards to the statistical methods applied, namely ARIMA, they are non-standard practices for interpreting the results of an ecological study. The first problem with this, in my opinion, is that the message will be difficult to interpret and criticize for many scientists, as ARIMA will be unfamiliar to most in the biological sciences. Further, the models applied (Table 4) do not take into account any confounders, which is a requirement for robust analysis of an ecological study. There are only 3 variables in this type of model: p, the autoregressive coefficient, q, the moving average coefficient, and d, the difference between points in the time-series. Any flaws or bias inherent to the input data are then upheld and propagated by the model, which does not allow for any other variable that would contribute to the risk of death.

Significance<br /> The faults of the stratification of countries into the groups proposed in this study, together with the unorthodox application of ARIMA modeling, make it challenging to accept the conclusion that the author draws in this study. The apparent decrease in death rate in countries with a high production/use/either/or of CQ/HCQ could be due to any number of other factors for which this study did not account. The top 5 countries in both confirmed cases and reported deaths are all in the control list, which has no relationship to the amount of CQ/HCQ production within those countries yet skews the data to make the dynamics of death rate appear more dramatic.

Reviewed by Rachel Levantovsky as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn School of Medicine at Mount Sinai.

On 2025-11-30 07:05:45, user Ali Rahimi wrote:

Dear authors,

I have read your interesting article. I think the following revisions would strengthen the article:

Abstract<br /> Clarify that the 72.4% and 38.2% figures come from patients reporting barriers, not from the full sample, so the denominator is clear.<br /> Keep wording aligned with the design: change “barriers limit uptake of cataract surgery in Bangladesh” to “barriers were commonly reported among patients undergoing cataract surgery in Bangladesh.”<br /> Make the main statistical result consistent with the Results: state that education, income and prior surgery were associated with the number of barriers (Adj R² = 0.138).

Introduction<br /> A few sentences are long and repetitive around “accessibility” and “health inequities”. Tighten these into one concise paragraph without changing meaning.<br /> Where you describe evidence as “scarce”, add 1 sentence that positions your study among Bangladeshi work (rural children, Rohingya, etc) and makes clear that prior studies were population specific.

Methods<br /> In “Participants and data collection” clarify in one sentence that 595 patients consented, but analyses of barriers use 583 due to item non-response.<br /> Briefly describe how the “fear score (0–5)” and “barrier count” were constructed (number of items, response scale, direction).<br /> You model a count outcome with linear regression. Add one line acknowledging that barrier counts were approximately normal and that this approach was chosen for simplicity; alternatively mention that Poisson or negative binomial regression would give similar interpretation.

Results<br /> Ensure mean age is reported consistently (Abstract uses 62 years, Table 1 has 61.3). Choose one rounding rule and use it everywhere.<br /> Replace approximate p notation “p ? 0.003” and “p ? 0.221” with standard “p = 0.003” and “p = 0.221”.<br /> Table 3: the p value shown as “1” for “Afraid of surgery” under gender should be reported as “1.000” or the exact test result.<br /> Table 4: the p values for “Number of reported barriers” currently read “> 0.001”; this should be “< 0.001”.<br /> In the text for section 3.3, “The geographical barrier of transportation is predominant in our study” is misleading because cost is clearly highest. Rephrase to “an important barrier” rather than “predominant”.

Discussion<br /> Soften causal phrasing. Examples:<br /> “Patients who delay seeing an eye doctor are more likely to postpone surgery and show up with advanced cataracts” could be “Patients reporting delays in seeing an eye doctor often present with more advanced cataracts.”<br /> Any sentences that link barriers directly to “prolonging the waiting period” or “contributing to disability” should be framed as association, not cause.<br /> When you describe gender norms and decision making, keep language neutral and clearly signpost what comes from your data versus from cited literature.<br /> Consider one short sentence acknowledging that your barrier profile reflects people who ultimately accessed surgery and may under-represent those who never reach services.

Limitations<br /> Add explicit mention that the cross-sectional design and the hospital-based sample (only patients scheduled for surgery) limit causal inference and generalisability to all people with cataract in Bangladesh.<br /> You already mention possible social desirability bias; make that sentence more direct and link it to self-reported barriers.

Conclusion<br /> Tone down strength of generalisation: instead of “The study's strength lies in its inclusion of a diverse population, thereby increasing its generalizability” use “The inclusion of patients from hospital clinics and outreach camps provides some diversity, although findings still reflect one service network.”<br /> Rephrase recommendations as suggestions: “could help improve access” or “may help bridge the knowledge gap” rather than “can facilitate” or “will improve”.<br /> Keep the ending sentence tightly tied to your data: emphasis on cost, transport, time, fear, and gendered escort constraints.

Tables and Figures<br /> Check that the labels in Figure 1 and Figure 2 match exactly the barrier wording used in the questionnaire and in the text (for example “hospital too far / no transportation”).<br /> Consider adding “multiple responses allowed” to the figure legends for barriers.

On 2025-11-30 17:00:32, user Cyril Burke wrote:

RESPONSE TO REVIEWER #2<br /> June 27, 2022<br /> Reviewer #2: Thank-you for the opportunity to review this work which highlights the importance of monitoring serum creatinine over time and how this can be a useful tool in detecting possible CKD. This is an important topic as the use of sCr on its own is certainly under-utilized and changes are often missed because they don’t fall into a predefined category.<br /> Thank you for considering our manuscript and for your detailed comments.

MAJOR CONCERNS

A. “Choi- rates of ESRD in Black and White Veterans” doesn’t fit with the rest of the paper including the title; the introduction and conclusion also don’t adequately address this portion of the paper. It feels disjointed from the main point of discussion which is the use of sCr in screening “pre-CKD”. This section and discussion should be removed and possibly considered for another type of publication.<br /> We have attempted to clarify this inclusion. This manuscript could be divided into three or four short papers, increasing the likelihood that any one of them would be read. However, different groups tend to read papers about screening for kidney impairment, racial disparities, cofactors in modeling physiologic parameters, or policy proposals to encourage best practices. Despite the appeal of perhaps three or four publications, we decided to tell a complete story in a single paper, but we are open to suggestions.

Black Americans suffer three times the kidney failure of White Americans. Other minority groups also have excessive rates of kidney disease. However, analysis of Veterans Administration interventions can bring that ratio close to one, similar interventions might also reduce to parity the risk for Hispanic, Asian, Native Americans, and others. Within-individual referencing should allow better monitoring of all patients and help to reveal the circumstances and novel kidney toxins that lead to progressive kidney decline. The ability to identify a healthy elderly cohort with essentially normal kidneys would help to calibrate expectations for all. Better modeling of GFR should help everyone, too.

Over eight decades, anthropologists have had little scholarly success in diminishing the inappropriate use of ‘race’. Keeping these parts together may be no more successful, but we feel compelled to try.

B. Cases 1 - 3, (lines 93 – 122): where are these cases from? There is no mention of ethics to publish these patient results, which appears to be a clear ethics violation. If so, these cases should be removed and patient consent and ethical approval obtained to publish them.<br /> The authors describe the reasons for not obtaining an ethics waiver for this secondary data analysis. Despite this, the relative ease of obtaining an ethics waiver for secondary data analysis usually means that this is done regardless.<br /> We take patient privacy seriously and have completely de-identified the Case data, as required by Privacy Act regulations. We understand that no authorization or waiver was necessary. We discussed the issues with an IRB representative, reviewed the relevant regulations, and confirmed no need for formal review of a secondary analysis of already publicly available IRB-approved data or of completely de-identified clinical data collected in the course of a treating relationship.

IRBs have a critical role to play, but many (including ours) are overworked. We understand the impulse authors feel to gain IRB approval even when the regulations clearly do not required it. As we discuss in the revision, there is a more significant matter that IRBs could help to resolve if they have the resources to do so. For all of these reasons, and even though we, too, felt the urge to obtain IRB approval, we resisted adding “just a little more” to their work.

C. The message of the article and data representation is unclear: do the authors wish to show that sCr is superior to eGFR in this “pre-CKD” stage, should both be used together? Do the authors wish to convey that a “creatinine blind range” does not exist? Or is the aim to demonstrate that continuous variables should not be interpreted in a categorical manner?<br /> Our interest is detection and prevention of progression of early kidney injury at GFRs above 60 mL/min – a range in which eGFR is especially unreliable. We have advanced the best argument we can to detect changes in sCr while kidney injury is still limited and perhaps reversible. If experience reveals that some avoidable exposure(s) begins the decline, then clinicians might alert patients and thereby reduce kidney disease. How best to use longitudinal sCr remains to be determined from experience. However, our message is that early changes in sCr can provide early warning of a decline in glomerular filtration. We are confident that clinicians can learn to separate other factors that may alter sCr, as we do for many other tests.

MINOR CONCERNS<br /> ABSTRACT<br /> A. Vague. Doesn’t give a clear picture of the study<br /> We have tried to clarify the title and abstract and are open to further suggestions.

INTRODUCTION<br /> B. 51 – 57: needs to state that these stats are from e.g. the US. The authors should consider adding international statistics to complement those from the US.<br /> We have updated the statistics on death rates from kidney disease to include US and global data.

C. 68: reference KDIGO guidelines, state year<br /> We now reference the KDIGO 2012 guidelines.

D. 75 – 77: is this reference of the New York Times the most appropriate?<br /> We have expanded this section with peer-reviewed, scholarly references. However, we found Hodge’s summary of the issue succinct and hence potentially more persuasive for some than decades of scholarly references that have had limited or no effect in the clinic.

E. 82: within-individual variation not changes (this is repetition of the point made in lines 425 – 427, but should match the language)<br /> We have matched the language.

F. 82 – 84: reference? If this is a question it should be presented as such<br /> We have attempted to clarify this statement.

G. 84: “normal GFR above 60” = guidelines (including KDIGO) do not refer to 60 as normal GFR, 60 – 89 is mildly decreased. (see line 126)<br /> We agree and have corrected the language.

H. 93: avoid the use of emotive words such as apparently (also in line 428)<br /> We wanted to emphasize appearance without proof and have made these changes.

I. 94: “Not meeting KDIGO guidelines”: KDIGO 2.1.3 includes a drop in category (including those with GFR >90). This would appear to include some of the cases listed. Additionally, albuminuria should have been measured for case 2 and 3.<br /> We have clarified that cases may or may not fit KDIGO categories, though that question will frequently arise in evaluating sCr changes. Where available, we have added urine protein and/or albumin results to the Cases.

J. 97: “progressive loss of nephrons equivalent to one kidney”: this is based on a single creatinine measurement.<br /> Since the original submission, we discovered for this Case (now Patient 3) early serum creatinine results and notes indicating a six-month period off thiazide diuretic. This data clarified the baseline and showed a remarkable effect of thiazide diuretic on sCr. We have added follow-up sCr results and details of thiazide use to the ASC chart.

K. 93 – 122: Could any of these shifts be explained by changes in creatinine methodology or standardization of assays, especially over 15 – 20 years (major differences between assays existed before standardization and arguably still exist with certain methods).<br /> It would be useful to see a comparison between serial sCr and eGFR measurements on the same figure. There appears to be significant (possibly more pronounced) changes when eGFR is used. As line 87 mentions changes in eGFR may be as useful (and in some situations more useful) than changes in sCr alone.

It would be helpful to have a chronology from each local laboratory with the date of every change in creatinine assay or standardization. However, any single shift draws attention but does not necessarily indicate significant change in glomerular filtration. After one or several incremental increases, over at least three months, the sCr pattern may meet the reference change value (RCV) that signals significant change. In the future, from age 20 or so, a patient’s medical record should retain the full range of the longitudinal sCr for true baseline comparison.

As noted in the revised manuscript, Rule et al showed that there is measurable nephrosclerosis even in the youngest kidney donors, suggesting that some injuries (perhaps exposure to dietary toxins) may begin in childhood and that early preventive counseling may be worthwhile. Experience will show whether this can slow progression to CKD. As we note, quoting Delanaye, sCr accounts for virtually 100% of the variability in eGFR equations based on sCr (eGFRcr), and these equations add their own uncertainties, so no, we do not believe that eGFR is more useful than sCr when GFR is above 60 mL/min and possibly much lower as well.

We have added eGFR results to the ASC charts (in blue), though availability was somewhat limited.

L. 127 – 142: should there be separate charts for males and females, the differences in creatinine between males and females needs to be discussed somewhere in the paper.

We do not think there should be separate charts for men and women based on size. The role of sex in eGFR equations is mainly based on the presumption that the average woman has less muscle mass than the average man. Clinicians care for individuals, not averages, and this sweeping generalization that increases agreement of the average of a population introduces unacceptable inaccuracy to individual care. Within-individual comparison eliminates the need for assumptions on relative size or muscle mass. Major changes in an individual’s muscle mass will usually be evident to the clinician who can adjust for them.

However, reports suggest significant influence of sex hormones on renal function, including effects of estrogen and estrogen receptors, such as reducing kidney fibrosis, increasing lupus nephritis, and increasing CKD after bilateral oophorectomy. The mechanism of these effects and how they might be incorporated into eGFR estimating equations is unclear, but the effort may benefit from a more individualized approach with focus on a measurand rather than matching population-based averages of a quantity value (calculated from measurands).

M. Similarly, is this suitable for all ages?<br /> We think so. Another sweeping generalization based on age merely introduces another inaccuracy which complicates the task of clinicians caring for individuals. Older persons have varying health, athleticism, muscle mass, dietary preferences, etc. Rule et al reported that biopsies of about 10% of older kidney donors had no nephrosclerosis. Within-individual comparison eliminates the need for assumptions on relative muscle mass or inevitable senescent decline in nephron number. We substitute the assumption that any change in an individual’s muscle mass will be evident and can be accounted for. A seemingly ubiquitous risk factor, or factors, starts injuring kidneys at a young age, which we may yet identify.

N. 162 – 163: rephrase<br /> Done.

METHODS<br /> O. 185 – 193: aim belongs in the introduction, can be adjusted to complement paragraph 178 – 182.<br /> Reorganized and rewritten.

P. 196 – 205: reference sources

References provided.

Q. 224 – 247: not in keeping with the rest of the article or title and conclusion

We have revised and restructured this section.

RESULTS<br /> R. If eGFR is treated as a continuous variable does inverted sCr still have higher accuracy?<br /> We believe so. Serum creatinine is a measurand and reflects the total sum of physiologic processes, known and unknown. In contrast, eGFR equations yield a quantity value, calculated from a measurand and dependent on the assumptions and approximations incorporated by their authors. The eGFR equations are thus necessarily less accurate than the measurands they are derived from, in this case, sCr. In a hyperbolic relationship, as the independent variable drops below one and approaches zero, the effect is to amplify the inaccuracy of the independent variable in the dependent variable. By avoiding the mathematical inverting, the data suggest that direct use of sCr is far more practical for pre-CKD.

S. As mentioned, the section on ESRD in black and white veterans doesn’t fit in with the rest of the article.<br /> We have revised, reorganized, and rewritten. We also outlined our rationale above.

DISCUSSION<br /> T. As mentioned, section 4.1 doesn’t fit in with the rest of the article. As the authors note the correlation between illiteracy and CKD is likely not causal.<br /> See above.

U. 387: erroneous creatinine blind range. The data presented does not show this is erroneous there is still a relative blind range. A distinction must be made between a population level “blind range” and an individual patient’s serial results. The data and figure 4 in particular demonstrate the lack of predictive ability of sCr above 40ml/min compared to below 40ml/min at a population level. For an individual patient this “blind range” is more relative, and a change in sCr even within the normal range may be predictive. (Note: the terminology “blind range” is problematic).<br /> We agree. On reading closer, Shemesh et al call attention to “subtle changes” in serum creatinine even though they had access only to the uncompensated Jaffe assay, so their recommendation to monitor sCr is even more forceful, today, due to more accurate and standardized creatinine assays. We have attempted to clarify this in the manuscript.

V. 399 – 400: “rose slowly at first and then more rapidly as mGFR decreased below 60” this refers to a relative blind range. Whether these slow initial changes can be distinguished from analytical and intra-individual variation is the question that needs to be answered before we can say a “blind-range” doesn’t exist for an individual patient.

We appreciate this observation. We believe longitudinal sCr is worth adopting to gain insights into individual sCr patterns, which may reveal early changes in GFR, among other influences on sCr. This is a low-cost, potentially high-impact population health measure, and there seems little risk in trying it because many clinicians already use components of the process.

W. 425 - 432: sCr is indeed very useful when baseline measurements are available. eGFR remains useful when baseline sCr is not available or when large intervals between measurements are found.<br /> As Delanaye et al noted, virtually 100% of the variability in longitudinal eGFR is due to sCr, so we understand that the errors in eGFR can be (and usually are) greater than but cannot be less than those in sCr.

X. 425: low analytical variation- if enzymatic methods are used<br /> Lee et al suggest that even the compensated Jaffe method provides some accuracy and reproducibility, which may allow longitudinal tracking of sCr even where more modern assays are as yet unavailable.

Y. 428: avoid the use of “apparently”<br /> Done.

Z. 430: reference 56 compares sCr and sCysC with creatinine clearance NOT with mGFR, this does not prove that mGFR has greater physiologic variability. Creatinine clearance is known to be highly variable (partially due to two sources of variability in the measurements of creatinine: serum and urine).<br /> The creatinine clearance is another form of mGFR, and our understanding of it begins with the units: if the clearance or removal of creatinine were being measured, the units should be umoles/minute, but they are mL/min. “Clearance” is an old concept coined by physiologists to describe many substances, such as urea, glucose, amino acids, and other metabolites. Since creatinine is mostly not reabsorbed and is only slightly secreted in the tubules, the “creatinine clearance” became a measure of GFR. The ratio of urine Creatinine to serum Creatinine is simply a factor for how much the original glomerular filtrate then gets concentrated (typically about 100-fold) by the kidney. Since the assumption is that the timed urine was once the rate of glomerular filtrate production, the creatinine clearance is a measure of the GFR.

Creatinine clearance has some inaccuracies based on tubular secretion, but also has some advantages: blood concentrations are essentially constant during urine collection, no need for exogenous administration, and reliable measurements in serum and urine. The methods that we often call mGFR also have problems, including unverifiable assumptions about distributions, dilutional effects, and others we cite in the text. None of these are direct measures of GFR. Due to changes in remaining nephrons, even true GFR itself is not strictly proportional to the lost number of functional nephrons, which seems the ultimate measure of CKD that Rule et al estimated from biopsy material.

AA. The limitations of sCr for screening should also be discussed: differences in performance and acceptability between enzymatic and Jaffe methods (still widely used in certain parts of the world), the effect of standardizing creatinine assays (an important initiative but one that could also produce shifts in results around the time of standardization- see cases), low InIx means that once-off values are exceedingly difficult to interpret, is a single raised creatinine value predictive (or should there be evidence of chronicity): similarly are there effects from protein rich meals, etc (The influence of a cooked-meat meal on estimated glomerular filtration rate. Annals of Clinical Biochemistry. 2007;44(1):35-42. doi:10.1258/000456307779595995)<br /> We have added discussion of additional references on reproducibility of sCr assays and discuss dietary meat and, in Part Three, possible dietary kidney toxins.

CONCLUSION<br /> BB. The discussion recommends using SCr above eGFR while the conclusion recommends the NKF-ASN eGFR for use in pre-CKD and ASC charts. While the use of both together in a complementary fashion is understandable- this needs to be congruent with the discussion, aims and results.<br /> We have rewritten this section. We would welcome any further recommendations.

Cyril O. Burke III, MD, FACP

On 2025-11-30 16:49:17, user Cyril Burke wrote:

[Note: This is the first of several reviews of an earlier version of our combined manuscript that aims to reduce ‘racial’ disparity in kidney disease. The comments were kindly offered by nephrologists, through a medical journal, and we remain grateful to them for the time and care they gave to improve our manuscript.

We removed identifying features and will include our responses in a subsequent comment. The changing title and line numbers refer to versions prior to our medRxiv preprints.]

April 1, 2022<br /> Screening for early kidney disease and population health using longitudinal serum creatinine

Dear Dr. Burke III,

REDACTED.

Reviewer #1: Burke et al submit a somewhat unusual paper, devoted to a topic of potential major clinical relevance, and as yet understudied.

General comments

1. The thesis of the authors, that using the baseline serum creatinine of a given patient would potentially improve the earlier diagnosis of kidney disease, even in the normal range, is in line with the experience of this reviewer, who always retrieves , whatever the difficulty of reaching that goal, past results of blood tests, and uses them as a way to date the onset of kidney disease, sometimes with important prognostic implications.

2. Yet, the authors do not provide data strongly supporting their thesis. For instance, when looking at case 2, should the last point (the most recent one) be omitted, there would be very little evidence supporting progressive early kidney disease.

3. The claim that the statistics fit the data better when all points are used (page 9,11) should not come as a surprise. Using thresholds instead of the full range of values has long been known to be more powerful for statistical analysis. But fitting the data does not equal to a high positive predictive value!

4. A key question is whether in a real world context, the earlier diagnosis of kidney disease would be possible, without too much background noise from intercurrent illness (functional), drugs (NSAIDS, etc..). In other words, would the specificity (or PPV) of the suspicion of early kidney disease be reasonable enough to catch the attention of clinicians

5. Even though there has been improvement in the standardization of measurement of serum creatinine (IDMS), the comparability of results measured by different labs remains suboptimal, at least in the experience of this reviewer, and medical shopping is not uncommon, making the availability of all previous results in the same graph a logistical challenge.

Specific comments

1. The authors should mention that the USPTFS decided a month ago to revisit the question of screening for kidney disease in high risk groups (page …)

2. Even though ESRD has a legal meaning in the USA, not very relevant to the topic of this paper about early kidney disease, the authors should stick to the nomenclature proposed by a recent KDIGO consensus conference (see Levey et al. Nature Reviews in Nephrology ). In particular, use kidney failure instead of ESRD/ESKD. When the topic is glomerular filtration, use that wording instead of kidney function (page…)

3. The authors allude to the concepts of prediabetes and prehypertension. But this reviewer points to the fact that the levels used to define those entities are currently “generic” , rather than based on previous values in an individual subject. Please discuss.

4. The authors repeatedly mention in the discussion section evidence that even small increases in serum creatinine have prognostic significance. This has indeed been known for decades but is a different topic: AKI . Admittedly, there is growing evidence that AKI and CKD are linked. But that the stability of a biological parameter is prognostically best is all except surprising: the same is true for body weight, mood, blood pressure etc…

Reviewer #2: Thank-you for the opportunity to review this work which highlights the importance of monitoring serum creatinine over time and how this can be a useful tool in detecting possible CKD. This is an important topic as the use of sCr on its own is certainly under-utilised and changes are often missed because they don’t fall into a predefined category.

MAJOR CONCERNS

“Choi- rates of ESRD in Black and White Veterans” doesn’t fit with the rest of the paper including the title; the introduction and conclusion also don’t adequately address this portion of the paper. It feels disjointed from the main point of discussion which is the use of sCr in screening “pre-CKD”. This section and discussion should be removed and possibly considered for another type of publication.

Cases 1 - 3, (lines 93 – 122): where are these cases from? There is no mention of ethics to publish these patient results, which appears to be a clear ethics violation. If so, these cases should be removed and patient consent and ethical approval obtained to publish them.<br /> The authors describe the reasons for not obtaining an ethics waiver for this secondary data analysis. Despite this, the relative ease of obtaining an ethics waiver for secondary data analysis usually means that this is done regardless.

The message of the article and data representation is unclear: do the authors wish to show that sCr is superior to eGFR in this “pre-CKD” stage, should both be used together? Do the authors wish to convey that a “creatinine blind range” does not exist? Or is the aim to demonstrate that continuous variables should not be interpreted in a categorical manner?

MINOR CONCERNS

ABSTRACT<br /> Vague<br /> Doesn’t give a clear picture of the study

INTRODUCTION<br /> 51 – 57: needs to state that these stats are from e.g. the US. The authors should consider adding international statistics to complement those from the US.

68: reference KDIGO guidelines, state year

75 – 77: is this reference of the New York Times the most appropriate?

82: within-individual variation not changes (this is repetition of the point made in lines 425 – 427, but should match the language)

82 – 84: reference? If this is a question it should be presented as such

84: “normal GFR above 60” = guidelines (including KDIGO) do not refer to 60 as normal GFR, 60 – 89 is mildly decreased. (see line 126)

93: avoid the use of emotive words such as apparently (also in line 428)

94: “Not meeting KDIGO guidelines”: KDIGO 2.1.3 includes a drop in category (including those with GFR >90). This would appear to include some of the cases listed. Additionally, albuminuria should have been measured for case 2 and 3.

97: “progressive loss of nephrons equivalent to one kidney”: this is based on a single creatinine measurement.

93 – 122: Could any of these shifts be explained by changes in creatinine methodology or standardisation of assays, especially over 15 – 20 years (major differences between assays existed before standardisation and arguably still exist with certain methods).<br /> It would be useful to see a comparison between serial sCr and eGFR measurements on the same figure. There appears to be significant (possibly more pronounced) changes when eGFR is used. As line 87 mentions changes in eGFR may be as useful (and in some situations more useful) than changes in sCr alone.

127 – 142: should there be separate charts for males and females, the differences in creatinine between males and females needs to be discussed somewhere in the paper. Similarly, is this suitable for all ages?

162 – 163: rephrase

METHODS<br /> 185 – 193: aim belongs in the introduction, can be adjusted to complement paragraph 178 – 182.

196 – 205: reference sources

224 – 247: not in keeping with the rest of the article or title and conclusion

RESULTS<br /> If eGFR is treated as a continuous variable does inverted sCr still have higher accuracy?

As mentioned, the section on ESRD in black and white veterans doesn’t fit in with the rest of the article.

DISCUSSION<br /> As mentioned, section 4.1 doesn’t fit in with the rest of the article. As the authors note the correlation between illiteracy and CKD is likely not causal.

387: erroneous creatinine blind range. The data presented does not show this is erroneous there is still a relative blind range. A distinction must be made between a population level “blind range” and an individual patient’s serial results. The data and figure 4 in particular demonstrate the lack of predictive ability of sCr above 40ml/min compared to below 40ml/min at a population level. For an individual patient this “blind range” is more relative, and a change in sCr even within the normal range may be predictive. (Note: the terminology “blind range” is problematic).

399 – 400: “rose slowly at first and then more rapidly as mGFR decreased below 60” this refers to a relative blind range. Whether these slow initial changes can be distinguished from analytical and intra-individual variation is the question that needs to be answered before we can say a “blind-range” doesn’t exist for an individual patient.

425 - 432: sCr is indeed very useful when baseline measurements are available. eGFR remains useful when baseline sCr is not available or when large intervals between measurements are found.

425: low analytical variation- if enzymatic methods are used

428: avoid the use of “apparently”

430: reference 56 compares sCr and sCysC with creatinine clearance NOT with mGFR, this does not prove that mGFR has greater physiologic variability. Creatinine clearance is known to be highly variable (partially due to two sources of variability in the measurements of creatinine: serum and urine).

The limitations of sCr for screening should also be discussed: differences in performance and acceptability between enzymatic and Jaffe methods (still widely used in certain parts of the world), the effect of standardizing creatinine assays (an important initiative but one that could also produce shifts in results around the time of standardization- see cases), low InIx means that once-off values are exceedingly difficult to interpret, is a single raised creatinine value predictive (or should there be evidence of chronicity): similarly are there effects from protein rich meals, etc (The influence of a cooked-meat meal on estimated glomerular filtration rate. Annals of Clinical Biochemistry. 2007;44(1):35-42. doi:10.1258/000456307779595995)

CONCLUSION<br /> The discussion recommends using SCr above eGFR while the conclusion recommends the NKF-ASN eGFR for use in pre-CKD and ASC charts. While the use of both together in a complementary fashion is understandable- this needs to be congruent with the discussion, aims and results.

On 2020-04-30 16:31:03, user Dr SK Gupta wrote:

Authors have reported the high prevalence of Mycobacterium Tuberculosis infection in Covid19. Authors have tried to portray not only the Higher prevalence of MTBI but also more severe and rapid progression of disease. However, since their findings are not in tune with observational data on the subject all across the world. Rather corona infection has been found to be low in South East Asia, Africa and other places where the tuberculosis is rampant. Also burden of Covid-19 has been highest in United States and Europe where the prevalence of Tuberculosis is low.

These Observations have prompted the scientist to look for the role of BCG vaccination/ past TB infection in prophylaxis and treatment of Covid 19.

Authors have erroneously relied upon use of Interferon gamma release assay (IGRA) to diagnose MTB Infection using a kit X.DOT-TB kits (TB Healthcare, Foshan, China). Not much has been described in article about the methodology used in these kits, but as the name suggests probably it is T-spot test which measures the number of IFN-?-secreting T cells via an enzyme-linked immunospot (ELISPOT) assay.<br /> Two types of IGRAs available, the QuantiFERON-TB Gold In-Tube test and the T-SPOT.TB blood test. Though both these tests are approved by the Food and Drug Administration as indirect tests for TB infection (including active disease) when used in combination with other medical and diagnostic evaluations. Since aging leads to a decline in the strength of immune responses, it is also argued that these tests loose their sensitivity with advancing age.

Overall Interferon gamma release assay (IGRA) has a poor sensitivity and specificity for the diagnosis of Tuberculosis.<br /> In patients with Non Tuberculous Mycobacterial Disease specificity of only 74% for infection and a relatively high indeterminate rate was found for QuantiFERON®-TB Gold(QTF) test assay with a sensitivity of 81.7 %. Hence the test is not able to discriminate between tuberculosis(TB) and non-tuberculous mycobacterial (NTM) disease with high degree of specificity.

The problem gets compounded even more in countries like China and India where the prevalence of TB is high and use of Tuberculin Testing and BCG vaccination is a routine and such cases have all the likelihood of being labelled as positive despite no active disease.<br /> Contrary to current practice Authors have also not used the available gold standards to define active TB based on either a positive Mycobacterium culture or a positive TB polymerase chain reaction/Gene expert/CBNAAT.

Not only that present investigators have also not describe any base line x-ray lung findings like cavitation, fibro-infiltration, lymph node enlargement, Spirometry based poor Lung function suggestive of tuberculosis in patients with positive MTBI or active tubercular disease which may have contributed to the rapid progression of superimposed pneumonia of Covid 19 in these patients.

In Covid-19 disease pathogenesis initially it is the role of Innate immunity mediated by Neutrophils Macrophages which mount a protective response. In tuberculosis Cell mediated immunity or the adaptive immunity involving T cells and B cells is at work. This has prompted world scientists to look for the role of BCG in treatment and prophylaxis of Covid-19. BCG Vaccine for Health Care Workers as Defense Against COVID 19 (BADAS) (NCT04348370) in USA and Brace trial by an Australian University are such attempts.

The current study needs the support of larger data which doesnot seem to be coming from other countries like India where TB is rampant. Till now the observations don’t support the hypothesis of increased susceptibility of TB patients for Covid-19 nor are there any indicators of more severe/ rapid progression of disease in patients with TB infection.

Dr S K Gupta <br /> Senior Consultant Physician <br /> Secretary Community Health Care Foundation<br /> Dr Prabhat Prakash Gupta <br /> Dr Mrs Praveen Gupta

References:<br /> 1.Comparison of the Sensitivity of QuantiFERON-TB Gold In-Tube and T-SPOT.TB According to Patient Age Won Bae,Kyoung Un Park,Eun Young Song,Se Joong Kim,Yeon Joo Lee,Jong Sun Park,Young-ae Cho,Ho Il Yoon,Jae-Joon Yim,Choon-Taek Lee,Jae Ho Lee <br /> Published: June 3,216 https://doi.org/10.1371/jou...<br /> 2. Sensitivity of the QuantiFERON-TB Gold test in culture-verified NTM disease and TB in a Danish setting Thomas Stig Hermansen, Vibeke Østergaard Thomsen, Pernille Ravn <br /> European Respiratory Journal 2012 40: P426; DOI:<br /> 3. https://clinicaltrials.gov/...<br /> 4. COVID-19: a recommendation to examine the effect of hydroxychloroquine in preventing infection and progression Dan Zhou , Sheng-Ming Dai and Qiang Tong J Antimicrob Chemother<br /> doi:10.1093/jac/dkaa114<br /> 5. Covid-19 coronavirus pandemic. https://www.worldometers.in...<br /> 6. 1. Mehta P. Mc Auley DF, brown M et al. Covid-19, consider cytokine storm syndromes and immunosuppression. Lancet. 2020. doi.org/10.1016/S0140-6736(...

1. Roitt I, Brostoff J, Male D. Immunology (Fifth Edition). Philadelphia: Mosby; 1998. ?

2. Wang L, Cai Y, Cheng Q, Hu Y, Xiao H. Imbalance of Th1/ Th2 cytokines in patients with pulmonary ?tuberculosis. Zhonghua Jie He He Hu Xi Za Zhi. 2002; 25 (9) : 535-537. ?

3. Collins FM. Cellular antimicrobial immunity. Crit Rev Microbiol. 1979;7:27–91. ?

4. Bretscher PA. An hypothesis to explain why cell-mediated immunity alone can contain infections by ?certain intracellular parasites and how immune class regulation of the response can be subverted. ?Immunol Cell Biol. 1992;70:343–351.

On 2020-05-01 10:16:00, user mendel wrote:

The specificity trials on page 19 are not normal.<br /> 7 trials show 100%, with N=30,70,1102,300,311,500,99, sum 2412.<br /> The 6 remaining trials:

368/371 = 99.2% (97.7-99.8)<br /> 198/200 = 99.0% (96.4-99.9)<br /> 29/31 = 93.6% (78.6-99.2)<br /> 146/150 = 97.3% (93.3-99.3)<br /> 105/108 = 97.2% (92.1-99.4)<br /> 50/52 = 96.2% (86.8-99.5)

Pooling these, I get 896/912=98.3% (97.2-99.0).

"We use the pooled test performance based on the available information:<br /> Sensitivity: 82.8% (exact binomial 95CI 76.0-88.4%)<br /> Specificity: 99.5% (exact binomial 95CI 99.2-99.7%)"

There is no trial that has exactly 1 false positive. There are 3 <br /> trials that don’t have 99.5% in the 95% CI (4 trials if you include <br /> 1102/1102). There is no trial that falls inside the 99.2-99.7 range (one<br /> straddles it). The specifity range they’re using is an empty space <br /> between the values that the trials are actually at. This is not a normal distribution.

187 samples had loss of smell and taste in <br /> the past 2 months. This is a very specific indicator for Covid-19, ~70% <br /> of patients (well, 33,9–85,6%, depending on the study, e.g. <br /> Mons/Belgium, Heinsberg/Germany) have that, and I don’t think this kind <br /> of nerve affliction has been reported for any other common illness. Yet <br /> only 11% of these samples test positive. For the 59 more recent samples,<br /> it’s 22%.

This looks like the prevalence this study should have measured is <br /> 267/3330 = 8%, and the test failed to pick up on that. It would fail to <br /> pick up on recent infections, because they wouldn’t have seroconverted <br /> (created enough antibodies) yet, and it would fail to pick up on <br /> infections that happened too long ago (because the antibody levels would<br /> have fallen off below the sensitivity of this test). This study really <br /> needed a more sensitive test, like an ELISA, which is actually available<br /> at Standford, and is able to detect much lower levels of antibodies.

This kit has not been validated against people who had the infection a month ago.

The presence of false positives is an indication that cross-reativity <br /> with outher cold viruses exists. If you test a sample with few people <br /> who haven’t had a severe cold recently, which probably includes most <br /> samples taken of people who check into the hospital for elective <br /> surgery, or samples taken in the summer months, you get an optmistic <br /> sensitivity that does not apply to the general population in early <br /> spring.

The WHO Early investigation protocol (Unity protocol) for the <br /> investigation of population prevalence mandates the use of an ELISA <br /> test, or the freezing of samples until a time when such a test becomes <br /> available. The WHO does not endorse the use of lateral flow assays for <br /> this kind of testing.<br /> —-<br /> P.S.: No study that does not measure prevalence in the older <br /> population where the majority of deaths occurs should speak on fatality <br /> rates. This study had 2/167 positives in the age 65+ population, that’s <br /> 0.1-4.3% (95% CI), a 30-fold spread, and hardly a representative sample,<br /> since I don’t expect residents from care homes were able to attend the <br /> drive-through testing.

On 2020-04-21 09:14:54, user Michael Rosenberg wrote:

Some additional information about performance of the Premier Biotech test is available at the distributors's web site. See links at the bottom of this page.

Package Insert shows false positive rate of 2/371 for IgG and 3/371 for IgM. It is not clear if same samples that tested positive for IgG also tested positive for IgM or these were different samples. Assuming best case scenario, cumulative FP rate for IgG and IgM is 3/371 (0.8%).

One could add to FP calculation 0/30 FPs reported in the preprint and 0/88 FPs mentioned by Dr. Sood in LA briefing yesterday. Adding these samples brings naive FP rate to 3/489 or 0.6%.

Distributor also provides what appears a submission for approval of the test by China FDA (link). This document shows 3/150 false positives for IgG and 1 - for both IgG and IgM. Therefore cumulative FP rate for IgG and IgM in this study is 4/150 or 2.7%. Note however that this number likely overestimates FP rate - all negative subjects in this study were COVID contacts excluded by PCR.

On 2020-04-18 05:16:02, user rodger bodoia wrote:

Deeply flawed methodology. Others have noted (as did the authors) the obvious inherent bias towards those seeking antibody testing (maybe they had symptoms, maybe they knew someone who had symptoms). Also note the bias that is inherent in the method of using Facebook as the messenger with a brief period between posting on FB and the actual testing. We would need significant information on the other behaviors of people who use FB this frequently and whether they are more or less likely to have engaged in practices that would have put them at risk of acquiring the virus.<br /> Back of the envelope "smell test": 48,000 infections and only 69 deaths (as of April 17) is an infection fatality rate of 0.14%. This is inconsistent with Diamond Princess data, even if we adjust for age differences. Also compare with https://www.nejm.org/doi/fu... in which they did UNIVERSAL screening of obstetric patients from March 22 to April 4 in NYC and found 15% positivity of SARS-CoV-2. Without lots of population-weighted adjustments we can interpret this as pretty good evidence of roughly 15% prevalence in NYC (say roughly 1.2 million infections) and roughly 9,000 deaths for infection fatality rate of 0.75%

On 2020-04-22 00:40:03, user Unko J wrote:

It's nice to read below what essentially IS the 'peer-review' for this pre-print online paper! I wish I had read these comments last night before having a heated debate with my fellow quarantinees. My point was how could these possibly be 2%-4% of the population that is positive and yet Santa Clara has only 83 deaths? These divergent sets of data can't really exist in one universe, unless either we're wildly wrong about either a) the mortality rate or b) how many people can be asymptomatic and test positive with an Ab test. So yeah, between cross-reactivity against non-Covid antibodies and other false positives, I think we've decided to reject this paper. And aren't some of the authors the same on both papers?

On 2020-04-22 20:36:24, user Konstantin Momot wrote:

The crucial issue here is sample selection. The participants essentially self-selected, but that is a potential source of huge bias. As a hypothetical scenario, if the people who chose to participate were predominantly people who’d had a cold and were curious to find out if it was COVID, then the cohort would a priori be hugely overweight with people who had a higher-than-average likelihood of COVID exposure. That would not be a good sample of the general population in that it would not represent the true percentage of CoV-exposed and CoV-naive people in the population as a whole. That would mean that the 2-4% figure is completely meaningless. Given how crucial this number is to any epidemiological modelling, I think it's important to remember that this is just one study with no guarantee of flawless methodology, and avoid making far-fetched conclusions based on limited evidence.

On 2020-05-13 14:21:49, user Sinai Immunol Review Project wrote:

Main Findings: <br /> Given the urgent need for diagnostic testing for COVID-19, this study uses enzyme-linked immunoabsorbent assay (ELISA) to measure serum antibody levels against recombinant spike protein ectodomain as well as its receptor binding domain (RBD) to angiotensin-converting enzyme (ACE2). Twenty RT-PCR confirmed COVID-19 patients as well as 99 healthy donors were tested for IgG titers in their serum. Antibodies to spike protein ectodomain were detected in 17 out of 20 patients, of which 5 showed borderline levels. 15 out of 20 patients tested positive for antibodies against spike RBD, of which 7 indicated borderline levels. These findings suggest that while majority of COVID-19 patients develop antibodies against the RBD, some patient responses may target other epitopes of the spike protein. Furthermore, they show that circulating antibody levels (ie: positive vs borderline) do not correlate with clinical severity or recovery from COVID-19. Strikingly, 1 patient who recovered did not have detectable IgG antibodies against RBD, suggesting a potential role of cellular immunity in the clinical resolution of COVID-19. In addition, they report that 4 out of 10 healthy donor serum collected since January 2020 tested positive. This indicates that apparently healthy individuals may be asymptomatic carriers, which underscores the importance of developing effective methods for community wide testing.

Limitations: <br /> The authors cite a study in their introduction that demonstrates minimal cross reactivity of antibodies between SARS-CoV and SARS-CoV-2 patients suggesting a specific antibody response for each disease. However, their study showed that five out of 89 serum samples collected from healthy donors between 2017 to 2019 tested positive for antibodies against spike protein ectodomain, and acknowledge a possible cross reactivity from prior exposure to other strains of coronavirus. This result also stands in contrast with other recent studies*. Understanding whether or not there is indeed such cross reactivity would be important for interpreting their results and designing vaccines against this specific virus. Furthermore, their thresholds for determining positivity versus borderline antibody levels are arbitrary and can significantly influence the outcome of their assay. It will be critical to obtain a larger cohort to further validate the robustness of their thresholds for determining circulating antibody levels.

Significance: <br /> This study establishes a straightforward assay in testing for circulating antibodies against spike protein in the serum of COVID-19 patients. This is important not only for surveying the population for people with immunity, but also improves sensitivity for diagnosis when combined with RT-PCR. In addition, their finding of a patient who recovered without detectable antibodies against spike protein RBD provides important insights to designing therapies for COVID-19.

Reviewed by Joel Kim as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn School of Medicine, Mount Sinai.

References:<br /> *Amanat, F., et al. A serological assay to detect SARS-CoV_2 seroconversion in humans. medRxiv preprint (2020)

On 2021-01-24 19:40:01, user Han-Kwang Nienhuys wrote:

I have further analyzed the data in fig. 2; the odds ratios (frequency ratio B.1.1.7 / other) grow exponentially with daily growth factors between 1.06 and 1.09 between 6 weeks and 1 week before the of the data (only considering the UK regions where the error bars in Fig. 4 were reasonably small: EE, EMid, London, NEE, SEE, SWE, WMid). For this I need to assume that a fraction of the SGTF cases are 'false positive', since most regions show a constant SGTF rate in October, before taking off with exponential growth.

Also notable, genomic analysis in UK SEE, Denmark, Netherlands, and Portugal show consistently growth rates between 7 %/d and 9.4 %/d with only Denmark showing a slowdown (from 12 %/d to 7 %/d).

Also, one would expect the odds ratio to grow exponentially over time if there are just two competing variants, each with their own transmissibility or reproduction number. However, the other strains that make up everything else than B.1.1.7 are likely to have slightly different transmissibilities. Over time, one would expect the transmissibility to drift to higher values, also among those other strains. The fact that the odds ratio growth rate is decreasing does not necessarily mean that the B.1.1.7 is getting less infectious; rather, the mixture of other strains could be getting more infectious over time, just because the contributions of the less infectious ones in the mix gradually decreases.

Summarizing: I believe that 6 %/d is an estimate that is significantly too low.

For graphs of my analysis, please see https://twitter.com/hk_nien... .

On 2021-02-17 17:12:29, user Tim Pollington wrote:

Dear Epke and colleagues,

I would like to share some comments following reading your (v. relevant) paper on impact of COVID on VL in India at the country level. This is the second time I've commented on a preprint like this on medrxiv, and shared an 'open review' so I hope you receive it in the spirit it was intended. As I'm interested in doing similar studies your manuscript was relevant to me. And since I am funded by BMGF I thought it would be a waste of my funded time if I do not share these thoughts with you too, especially since you're at the preprint/pre-accepted stage.

I thought the paper could benefit from an additional author who has field experience of the IRS/ACD activities occurring there to back-up your assumption that "no IRS and ACD take place and that only passive case detection" during an interruption.

Given that the role of Asx in infecting others is still debated (some say recent xeno shows near zero contribution while ours last year did fit estimates consistently when relative Asx infectiousness of 0,1 or 2% were used), your use of the models E1 & E0 is a smart move to err on the cautious side.

Model structure and quantification section<br /> Thanks for much for following best practice and using PRIME-NTD. It is the first time I have seen it and I definitely plan to use it in my next modelling publication and also when initially planning a model re engagement with policymakers.

Given that the model runs for 30 years has population growth been taken into account?

Impact assessment section<br /> Although adding incidence rates in the same period is acceptable, as events share the same 'person time at risk' denominator (and if the events are mutually exclusive), I'm not sure if epidemiologically it's a correct calculation to sum up rates over the 30 years since the population will be changing in this time and thus the denominators are changing. Perhaps one can convert it into absolute cases in each year and then sum those up?

Discussion section - First paragraph<br /> It may help the reader if more emphasis was made on how a 1-year impacted delay by describing how it is amplified. ie How just one year interruption causes growth which needs to be curtailed before it turns over and falls, and the excess cases this generates. This concept of amplification could be strengthened.

Second paragraph<br /> "80% of [VL-endemic???] sub-districts..." Did this cover just Bihar or all 4/5? endemic states.

Third paragraph<br /> I think mortality rates are really relevant but can understand your caution re scant data. I think it's so important now considering the 1%CFR 2021-2030 target. Could this independent review help provide some rough estimates from pages 12-15 & 40? <br /> Even rough estimates from your model on excess VL cases and when they would likely be seen in the coming years, could be a useful starting place for resource planning of drugs.

I think a caveat needs to be noted that this analysis is country-level whereas the threshold targets are at the block-level, to avoid the reader making an ecological fallacy.

I hope that helps and also encourage you to comment on my work if I get to that stage!

All the best, Tim.

On 2021-01-06 12:33:57, user C'est la même wrote:

The authors state that there were 25 cases of GBS in London during the sampling period, which would lead to an estimated occurrence rate of 0.82 GBS cases per 1000 COVID-19<br /> infections.<br /> Yet they discount this by citing a claim that 17.5% of individuals London had been infected by that time. We now know that estimate was wildly inaccurate.<br /> Serological survey data collected by the ONS found that prevalence in London was just under 0.4% around that date (https://www.medrxiv.org/con... "https://www.medrxiv.org/content/10.1101/2020.07.06.20147348v1)")

Which works out to around 36,000 people in comparison to the 26,784 PCR confirmed cases. <br /> This would lead to an estimated occurrence rate of ~0.6 GBS cases per 1000 COVID-19 infections which certainly seems suggestive of an association.

The authors also performed genomic analyses to rule out molecular mimicry due to epitope similarities.

I'd like to draw attention to the fact that many of the known viral triggers of GBS also do not have evidence of molecular mimic epitopes, instead suggesting other mechanisms of generating autoimmunity including the co-capture hypothesis, (http://www.pnas.org/content... "http://www.pnas.org/content/114/4/734)"), given that spike protein interactions with gangliosides have already been characterised in a substantial number of publications to date.

As such, while the lower population incidence during the observed period is compelling, that data alone is not enough to rule out the association of GBS with SARS-CoV-2, given the impact of lockdown measures on other infectious causes that happen to have lower infectivity (basic reproduction number) than SARS-CoV-2.