Reviewer #2 (Public review):

Summary:

This study investigates the cytotoxic activity of human NK-cell subsets against autologous HIV-1-infected CD4 T cells and identifies CD56dimCD16dim NK cells as the dominant effector population. The authors propose that this subset possesses superior cytotoxic activity compared with CD56dimCD16bright NK cells and could therefore represent an attractive target for HIV cure strategies. While the study addresses an important and clinically relevant question, several of its major conclusions rely on assumptions that are not adequately supported by the experimental design. In particular, CD16 is treated as a stable phenotypic marker throughout most of the study despite its well-established and rapid downregulation following NK cell activation.

Strengths:

(1) The study addresses an important and clinically relevant question regarding which NK cell subset is responsible for the elimination of autologous HIV-1-infected cells. To the best of my knowledge, this is the first study directly comparing the anti-HIV functional activities of CD56dimCD16dim vs CD56dimCD16bright NK cells.

(2) The experiments performed with purified NK cell subset (Figure 2) provide some evidence that CD56dimCD16dim NK cells possess enhanced cytotoxic activity relative to CD56dimCD16bright NK cells. This experimental approach is considerably more convincing than the analyses performed on mixed NK cell populations and should be expanded throughout the study.

Weaknesses:

(1) The central conclusion is weakened by the use of CD16 as a stable phenotypic marker. CD16 is well established to be rapidly downregulated following NK-cell activation and target cell (K562 or infected cells) engagement through ADAM17-mediated shedding. NK cell shedding regulates NK cell effector functions by promoting target cell detachment, boosting serial killing capacity, and preventing overstimulation. Therefore, NK cells displaying a CD56dimCD16dim phenotype after co-culture cannot be assumed to represent a pre-existing subset with intrinsically superior cytotoxic activity, but may instead correspond to activated CD56dimCD16bright NK cells that have downregulated CD16 during the assay. Because the vast majority of the functional experiments classified NK cell subsets based on post-assay CD16 expression, it is difficult to distinguish intrinsic functional differences between NK cell subsets from activation-induced phenotypic conversion. This limitation affects the interpretation of most of the study's principal findings.

(2) The "killing frequency" analysis presented in Figure 3 is based on a mathematical estimate rather than a direct experimental measurement. Since total target cell killing is measured in mixed NK cell populations, it cannot be attributed to individual NK cell subsets. This experiment must be repeated using purified NK cell subsets.

(3) The serial degranulation assay presented in Figure 4 does not directly measure serial target cell killing and therefore does not support the conclusion that CD56dimCD16dim NK cells possess superior serial killing capacity. Furthermore, the increased serial degranulation observed in the CD16dim population could simply reflect activation-induced CD16 downregulation rather than an intrinsic property of this subset. This experiment should therefore be repeated using purified NK cell subsets.

(4) The finding that CD56dimCD16dim NK cells exhibit greater ADCC activity is somewhat counterintuitive given the central role of CD16 in mediating ADCC. Moreover, these experiments are likely confounded by activation-induced CD16 downregulation, which is expected to be even more pronounced during ADCC. Thus, the apparent superiority of the CD56dimCD16dim subset may simply reflect the conversion of activated CD56dimCD16bright NK cells into the CD16dim gate rather than intrinsically greater ADCC activity. To directly compare the intrinsic ADCC capacity of each subset, these experiments should be repeated using purified NK cell populations prior to target-cell stimulation.

Reviewer #2 (Public review):

Summary:

The manuscript submitted by Arico and co-workers describes the impact of two lectin-domain-containing proteins (LecRK-I.9* and LecTM) on the formation and persistence of Hechtian strands. Based on a survey of selected candidates, overexpression of these two proteins resulted in an increase in Hechtian strand formation. Removal of the lectin domains and expression of this variant did not alter HS formation compared to the WT. In addition, the existence of the lectin domain reduced protein mobility, probably due to interactions with the wall. Last but not least, overexpression of LecRK-I.9 increased the resistance of plants towards water loss conditions.

Strengths:

The study seems well conducted, but may require some small additions. While the results themselves seem not surprising, I think that this is a valuable demonstration of the cell wall binding ability of lectin proteins and its physiological and microscopical consequences.

Weaknesses:

At this stage, some of the study would benefit from some additional quantification.

Reviewer #2 (Public review):

Summary:

The study analyzes stool metagenomes from 98 SCD patients and 46 controls, with SCD and control groups matched on age, race, sex, and ethnicity. The authors report lower Shannon diversity, lower Firmicutes/Bacteroidetes ratio, loss of health-associated taxa, increased disease-associated indicators, altered butyrate/fatty-acid metabolism pathways, and enrichment of provirus/prophage fractions in SCD. They further correlate aged-like neutrophils and prophage fractions with inflammatory cytokines. The main strength is that this is not just another 16S comparison. The use of whole-community metagenomics, immune profiling, neutrophil assays, and clinical metadata makes the study more biologically interesting than prior small SCD microbiome papers. The main weakness is that the causal and mechanistic interpretation is too strong. The data support an association between SCD status and microbiome/virome features, but they do not yet establish a clear "axis of pathophysiology." The provirus findings are intriguing, but require stronger statistical control, better validation, and more cautious interpretation.

Strengths:

The major strengths of the study include the clinically relevant disease setting, the use of whole-community sequencing, the integration of microbial, immune-cell, cytokine, and clinical measurements, and the novel attention to bacterial virus-related features. A particularly interesting aspect of the work is the analysis of virus-like elements integrated into bacterial genomes. The authors report that these elements are enriched in the gut microbial communities of patients with sickle cell disease and are associated with several inflammatory signals in blood. This observation is potentially important because it suggests that the microbial contribution to inflammation in sickle cell disease may involve not only bacteria but also bacterial virus-related genetic elements.

Reviewer #2 (Public review):

The authors have utilised two main models to assess the function of S1PR1 in neutrophils in mice. The knockout of this receptor shows no conclusive effect on neutrophil numbers or functions; it was only the overexpression that resulted in significant alterations. Therefore, often the conclusions do not describe normal or disease physiology but could be useful in a bioengineering context.

Strengths:

From a bioengineering standpoint, this seems like an important study - showing enforced expression of S1PR1 in neutrophils has improved outcomes for influenza infection (Figures 6 and 7).

Weaknesses:

Although the strength is the influenza model, genetic modification of human neutrophils cannot be a strategy, and therefore, is there any way to increase this receptor for mouse, or more importantly, human neutrophils? This study only looks at mice with a non-physiological model of overexpression. It does not offer a real therapeutic option, which drastically hinders the importance of the study. I have other concerns with the data analysis and interpretation, which I detail on a figure-by-figure basis (and how it relates to conclusions) below:

Main specific issues:

(1) Figure 2A+B: This is unconvincing; in the surface staining there seem to be real cells positive for the receptor (high staining in the histogram), but none of the transgenic protein is getting there? This undermines the idea that the effects of the transgene are related to S1P signalling. In the 'Total S1PR1' this is both underwhelming and misleading, as an isotype control (or better S1PR1 knockout) is missing, which would give a better representation of actual expression (flow cytometry autofluorescence famously increases in the red laser channels with fix/perm). The Imagestream chosen images are showing best-case scenarios - and aren't representative. What does the isotype/ KO look like here? All in all, the conclusion on receptor internalization is not well supported, especially when theoretically the TG overexpression should overload S1P availability. This also highlights the lack of another control - does overexpression of another random/non-functional protein have the same effect? To play devil's advocate, perhaps overloading of the ubiquitin-proteasome system is responsible?

(2) Figures 2E-H: In the text, the authors should fix the statement 'Additionally, surface CXCR2 was downregulated and CXCR4 upregulated in LysM-S1pr1 TG neutrophils across bone marrow, spleen, and blood (Fig. 2, E and F)' to better reflect that there is no significant difference in the bone marrow regarding CXCR4. Of note, the total MFI from this data would also be informative, another noticeable absence being the gating strategies for much of the data. Also, alter the statement: 'CD62L expression was largely preserved across compartments, with only a modest reduction in bone marrow neutrophils (Fig. 2G)'. A 50% reduction in CD62L is not modest.

(3) Supplemental Figure 3. A common theme: the wrong statistics have been used here, which has led to a false conclusion. Megakaryocyte/erythrocyte progenitors (MEPs) were only elevated in 2/3 TG mice, and the numbers are so small that this is not significant by any measure of the word. This is certainly not statistically significant if the correct test of (log-normalized) two-way ANOVA is performed (with Sidak's post hoc test). Another acceptable test would be Kruskal-Wallis with Dunn's post-test just for MEPs.

(4) Starting at Figure 3, the authors refer to 'S1PR1hi neutrophil accumulation'. Crucially, the authors must here and throughout be explicitly clear in which cells they are referring to, as this can be misleading - particularly as there are real S1PR1-high cells identified in Figure 2A surface staining. It is my understanding that the authors here mean the transgenic artificially high mice - a very large distinction.

(5) Figure 3A: It is difficult to interpret the figure with the necessary details about the experiment. For instance, there is no mention that this is sterile inflammation or what caused it.

(6) Figure 3B and C: It should be made clear whether these splenic neutrophils are related to the time course of peritoneal inflammation in 3A. Why are there so many apoptotic neutrophils in the spleen? The low numbers here suggest a processing issue rather than real death in vivo (which usually is absent).

(7) Figure 3D: This can also be misleading - the wrong statistics are again used. This should be a log-transformed two-way ANOVA. Regardless of this, the data is not strong enough to be conclusive, a minor effect at best that could also just be related to the type of cell tracker used.

(8) Figure 5E: It is stated that 'LysM-S1pr1 TG mice exhibited a higher bacterial burden in the lungs than controls (Fig. 5E).' Again, misleading results, first the wrong statistical test was used (correct = log norm one-way ANOVA with Tukey's or Kruskal Wallis with Dunn's), secondly the only significance is between S1PR1(fsf) and the Mrp8-S1PR1, not with the LysM TG. 5F is also not strong, with only 2/7 values appearing outside the range of the control - P values can be misleading when poor statistics are used.

(9) Figure 6G: Some discussion should be given for why Neutrophils are lower in BALF in the IAV model - even though higher in the lung in the non-IAC mice in Figure 1. In general, rather than focusing on the non-physiological differences, the discussion could better reflect the inconsistencies and more fully address the difference between the TG and KO and what this means going forward.

Reviewer #2 (Public review):

Summary:

Based on observations of localisation of MreBEc at the poles within an aggregate-like structure, upon heterologous expression of MreBMx, the authors set out to investigate how this non-canonical localisation of MreBs leads to a reprogramming of peptidoglycan synthesis to the poles. This is analogous to the polar growth observed in phyla which are not dependent on dispersed growth of PG, but only at the poles, and are MreB independent.

The authors proceed to establish that PG synthesis is MreB-dependent, Rod enzyme-dependent, and requires the prior establishment of a pole.

Strengths:

(1) It is a very interesting idea to design experiments to demonstrate reprogramming of non-polar to polar growth based on the observation of localisation of a heterologously expressed MreB.

(2) The experiments to demonstrate the factors that determine polar growth and the observation of the PG in each of these experimental situations are convincing.

(3) I find the observation of an extra layer of PG in the heterologously expressed system very intriguing. It will be interesting to see if this layer merges with the other PG layer at some stage or branches from the non-polar growth near the poles.

Weaknesses:

(1) It is not clear what exactly the identity of the polar aggregates is and how much of this activity is an artefact of partially functional MreBs.

(2) I find it intriguing that the localisation and growth are predominantly at one pole only. It is unclear to me how this can be reconciled with growth and shape maintenance, and an increase in length and width. Is the increase in length and width a consequence of misshapen cells that are bulged in the absence of a normal PG layer?

(3) The authors do not follow up on the observations in the first figure on the length and width changes and the extra peptidoglycan layer (which I feel are the most interesting aspects), and how this can be connected to the polar growth observed in the later sections of the manuscript.

(4) The claim that this could be a precursor of an MreB-independent polar growth mechanism appears to be a bit far-fetched, because the system is still dependent on having an established pole for PG synthesis to occur in the new place.

Reviewer #2 (Public review):

Summary:

The authors describe a computational model for the acquisition of sensorimotor skills and explore these dynamics using vocal learning in the zebra finch, a system rich in experimental data, to describe the developmental trajectory of vocal imitation by trial and error. They set up their model as a dual-pathway system, with a cortical pathway that drives the vocal effector and a basal ganglia (BG) pathway that uses dopamine-mediated reinforcement learning (RL) by gradient descent to optimize the vocal imitation process.

Strengths:

A key strength of the model, due in part to the fact that his model was generated by a computational laboratory that has also contributed significantly to the collection of experiment-driven empirical data, is that the model is biologically constrained and incorporates a considerable amount of experimental data, including some of the latest findings in the field. In addition to providing a compelling model for the acquisition of vocal learning, this biologically based RL model outperforms many current models. A key feature of this model, which makes it unique, is the implementation of a synaptic volatility variable within the BG pathway that aims to mimic published work showing that juvenile birds exhibit post-sleep deterioration. The model uses a motor output to drive a biophysical model of the avian vocal organ (syrinx) and explores not only the ability to copy song acoustic units (syllables) but also the underlying neural dynamics in both the cortical and BG pathways, showing that each converges onto the types of neural activity patterns that are observed experimentally. Because of the richness of experimental data in this system, the authors can perform "computational experiments" where they can block sleep-driven synaptic volatility or lesion various pathways to replicate experimental observations.

In addition to providing important computational insights to our understanding of vocal learning in the songbird, this study provides key insights into the general architectures that are optimal for RL by gradient descent. These include the conclusion that effective RL requires adaptive regulation of exploration and exploitation, that cortical consolidation must occur at a slower timescale than BG-driven exploration, and intriguingly that the introduction of synaptic volatility prevents RL models of incomplete learning by getting "stuck" in local minima.

Weaknesses:

In the methods section, the authors state "... HVC and RA layers are fully connected, as are the HVC and BG layers. Synaptic weights in these pathways are plastic, reflecting activity-dependent plasticity at RA and BG synapses." Unless I missed it, it is unclear how much the authors consider the synaptic differences between HVC and BG inputs to RA. This seems like an important feature to highlight, especially given that HVC-RA connections are primarily AMPA-mediated whereas those from LMAN are predominantly NMDA. The authors should be clearer about how they model these synapses and better highlight (and describe) the importance of these synaptic differences in their modeling efforts. Ideally, they should evaluate whether the differences in synapse type influence the outcome of their model. It would be interesting, for example, to test the effect on learning of synaptic conductance substitution (i.e., replacing NMADA with AMPA) on the LMAN-RA synapse.

The model focuses exclusively on the interaction of two converging pathways, and learning is based purely on acoustic feature properties of what seem like four independent syllables of similar or identical duration. For this model, this is fine. But it would be helpful for the authors to state more clearly that they are not modeling respiratory influences on syllable production, which include amplitude modulation of the syllables and expiratory pulse duration. It should be noted that the authors do not (unless I missed it) mention the existence or role of recurrent loops in song initiation (and possibly syllable sequencing). They should at least mention this in the discussion, perhaps as a limitation and item for future versions of the model.

Reviewer #2 (Public review):

Summary

The authors examine how dominance hierarchy modulates defensive strategies in mice exposed to two naturalistic threats: a transient visual looming stimulus and a sustained live rat. By comparing single versus paired testing conditions, they demonstrate that social presence attenuates fear responses, and that dominant and subordinate mice display distinct behavioral and social patterns depending on threat type. The study offers a rich behavioral dataset and a potentially valuable framework for investigating hierarchical influences on innate fear.

Strengths

(1) The use of two ecologically relevant threat paradigms allows for meaningful comparisons across transient and sustained contexts.

(2) Behavioral quantification is thorough, incorporating manual annotation of multiple behavior types and transition‑matrix analyses.

(3) The comparison between dominant and subordinate pairs is novel within the innate‑fear literature.

(5) The manuscript is well structured and clearly written, with figures that are visually informative and effectively support the main conclusions.

Weaknesses

The investigation of neural mechanisms underlying the observed behavioral effects remains limited.

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 proceeding 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.

Weaknesses:

There are no weaknesses.

Reviewer #2 (Public review):

Summary:

This article reports measurements of iEEG signals on the rat auditory cortex during cochlear implant or sound stimulation in separate groups of rats. The observations indicate some spatial organization of cochlear implant stimuli, but that is very different from cochlear implants.

Strengths:

The study includes some interesting analyses of the sound and cochlear implant representation structure based on decoders.

Weaknesses:

The observation that responses to cochlear implant stimulation (stimulation) is spatially organized but not exactly as sound-driven responses is not new.

The analyses in Fig. 8 supporting the claim that there is a mismatch between cochlear implant and normal sound representations remain hard to evaluate. The shuffle control now provided by the authors indicates that the information transfers between normal hearing representations is at chance level and between cochlear implant and normal hearing is below chance (Fig 8H). This clearly indicates, unlike the authors suggest in their response, that the analysis used to make this claim is not sensitive enough. Therefore, the claim does not seem to be supported.

Reviewer #2 (Public review):

Summary

Schubert et al. recorded MEG and eye tracking activity while participants were listening to stories in single-speaker or multi-speaker speech. In a separate task, MEG was recorded while the same participants were listening to four types of pure tones in either structured (75% predictable) or random (25%) sequences. The MEG data from this task was used to quantify individual 'prediction tendency': the amount by which the neural signal is modulated by whether or not a repeated tone was (un)predictable, given the context. In a replication of earlier work, this prediction tendency was found to correlate with 'neural speech tracking' during the main task. Neural speech tracking is quantified as the multivariate relationship between MEG activity and speech amplitude envelope. Prediction tendency did not correlate with 'ocular speech tracking' during the main task. Neural speech tracking was further modulated by local semantic violations in the speech material and by whether or not a distracting speaker was present. The authors suggest that part of the neural speech tracking is mediated by ocular speech tracking. Story comprehension was negatively related with ocular speech tracking.

Strengths

This is an ambitious study, and the authors' attempt to integrate the many reported findings related to prediction and attention in one framework is laudable. The data acquisition and analyses appear to be done with great attention to methodological detail. Furthermore, the experimental paradigm used is more naturalistic than was previously done in similar setups (i.e.: stories instead of sentences).

Weaknesses

While the analysis pipeline is outlined in much detail, some analysis choices appear ad-hoc and could have been more uniform and/or better motivated (other than this is what was done before).

Reviewer #2 (Public review):

Summary:

Delacruz et al. describe a new method, called "MARBL" (Methionine Analogues for Ratiometric Bioenergetics in Live cells) to measure metabolic activity in single cells. The concept is similar to the SCENITH (anti-puromycin flow cytometry) assay to measure energy metabolism by measuring protein translation activity, yet offers, in theory, two advantages: 1) it keeps cells alive for downstream biological assays and 2) it is a ratiometric measurement, measuring both baseline translation and translation in the presence of metabolic inhibitors to correct for inherent cell-to-cell translation differences.

Specifically, this method takes advantage of two click-chemistry-active methionine analogs, and then clicks fluorophores onto newly-synthesized surface proteins that have incorporated these analogs to measure translational activity. One methionine analog is given to cells for 2-4 hours to measure baseline translational activity, then metabolism is blocked using 2-deoxyglucose and oligomycin and the second methionine analog given to measure "metabolically-linked" translation activity. The authors establish this technique and show that mouse T cells polarized as pathogenic Th17 cells are more translationally active ("resilient") compared to non-pathogenic Th17 cells, and when sorted, the resilient cells produce more interferon-gamma. This latter finding requires live cells after the metabolic measurement assay, showcasing findings that are inaccessible to the SCENITH assay.

Strengths:

The approach used is conceptually clever. It is appealing to measure metabolic/translational activity and to then be able to carry out further assays on sorted cell populations with different degrees of metabolic activity. This would indeed represent a useful advance.

Weaknesses:

In principle, one key benefit of this technique is that cells can be used for biological assays after the metabolic measurement. Indeed, this would represent a valuable tool in the field.

However, in this technique, cells are subjected to methionine deprivation, addition of non-natural methionine analogs, click chemistry, and high doses of toxic metabolic inhibitors 2-deoxyglucose and oligomycin. Indeed, the authors show in Figure S5F that 1/3 more of the post-MARBL cells die relative to cells not subject to this technique (60% viability in unclicked control, 40% in MARBL-measured cells). This data suggests that cells after this technique may be stressed and not reflective of the biological function of unmanipulated cells. More controls on viability and cell function (e.g. cytokine production) at more time points after the MARBL assay would have been valuable to address this issue.

Another weakness of the paper is limited benchmarking against established metabolic assays in the field. The main assays used currently in the field are SCENITH and Seahorse. The authors do not compare their findings to SCENITH. They do compare their results to Seahorse, but the data shown don't address the key question: how does energy production measured by Seahorse, say in unmanipulated vs 2dg+oligomycin-treated cells, compare to the MARBL measurement? (Instead, they show a calculated "glucose dependence" metric in cells subjected to low vs high inhibitor dose, not showing the underlying data or cells that didn't receive an inhibitor).

Reviewer #2 (Public review):

This work provides empirical data on how GABA and NMDA agonists globally affect timescales as measured through MEG. The authors reproduce the previously observed gradient of intrinsic timescales in the placebo condition, as well as its relationship to cortical hierarchy in T1/T2w maps. Timescales were not fixed, but dynamic, as revealed by large-scale network analysis separating into discrete network states. Pharmacologically, GABA agonist Lorazepam produced a brain-wide increase in timescales while NMDA agonist D-cycloserine did not. Furthermore, the GABA-mediated increase in timescale was area- and state-dependent, and more detailed analyses show changes in state occupancy mainly for DMN and DAN.

Overall, the paper contributes valuable data on a relevant topic of research in understanding the timescales of network dynamics at the local and global level. The question is well-motivated, and the analyses are technically sound and described in a straightforward manner. The network-level analysis in TDE-HMM is interesting and provides a complementary and more fine-grained perspective to the global timescale gradient, both in terms of space and time. The hypotheses were straightforward since both GABA and NMDA have relatively long timescales (of the dominant synaptic currents), though the lack of effect from NMDA-agonist is quite surprising but reasonably explained by the voltage-dependence of NMDA receptors in such a task-free setting. The paper overall is clearly written, and the figures are of high-quality, though some things could be presented in slightly more informative ways (see below). I have some questions and minor suggestions, but don't have too much to criticize as a whole.

My biggest question is the following: the mixed effects model shows that lorazepam additionally mediates timescale over and above the hierarchy (myelination map). This leaves a very clear gap. What the authors also probably want to show is that greater GABA_A receptor expression (of any or all the subunits) results in greater change under lorazepam, not against the myelination map only, or that the residue can be explained by the GABA_A maps. This, of course, would not explain the non-stationary nature of the dynamics (and state-dependent timescale maps), but would give a more direct explanation of the spatial effect. Since you already compared to the prior MEG map in Shafiei et al., 2023, I guess it's not a huge technical effort to grab the gene maps from neuromaps (https://github.com/netneurolab/neuromaps). I think this could strengthen the current manuscript.

Reviewer #2 (Public review):

Summary:

The authors investigate whether inhibition of the WNK-SPAK/OSR1 pathway using the allosteric inhibitor WNK463 improves neuronal chloride homeostasis and suppresses epileptiform activity in organotypic hippocampal slice cultures. Using Super Clomeleon imaging combined with extracellular field recordings, they demonstrate that WNK463 accelerates recovery of intracellular chloride following chloride loading, reduces interictal chloride accumulation, and progressively suppresses recurrent ictal-like discharges. Pharmacological inhibition and siRNA-mediated knockdown of NKCC1 and KCC2 are then used to investigate the contribution of these transporters to the anti-ictal effects of WNK463.

Strengths:

The study addresses an important question in the field of chloride homeostasis and epilepsy and combines complementary experimental approaches. In particular, the distinction between baseline chloride measured in the presence of TTX and activity-dependent interictal chloride accumulation provides a useful conceptual framework for interpreting previous studies of WNK-SPAK inhibition. The imaging, electrophysiological, and pharmacological data are internally consistent and support the conclusion that WNK463 alters chloride dynamics and substantially suppresses ictal-like activity in this model.

Weaknesses:

The principal limitation of the manuscript is that several mechanistic conclusions extend beyond the experimental observations. Throughout the results and discussion, the authors interpret the observed changes in intracellular chloride dynamics as evidence of enhanced CCC-mediated chloride extrusion, while the pharmacological and siRNA-mediated experiments are interpreted as supporting coordinated NKCC1 inhibition and KCC2 activation, ultimately leading to restoration of GABAergic inhibition and negative shifts in EGABA. While these interpretations are plausible and consistent with the data, they remain inferential because transporter phosphorylation or activity, EGABA, and inhibitory synaptic function were not directly assessed in the current study. Moreover, although the pharmacological and knockdown experiments support a contribution of NKCC1 and KCC2 to the actions of WNK463, they do not definitively establish coordinated modulation of both transporters as the primary mechanism underlying seizure suppression. These mechanistic conclusions should therefore be presented more cautiously.

The manuscript would also benefit from broader contextualization within the current literature. The introduction largely focuses on previous work from the authors' group and provides a relatively narrow overview of chloride homeostasis in epilepsy. In particular, the discussion would benefit from broader consideration of studies examining KCC2 dysfunction in human epilepsy and experimental models, alternative mechanisms regulating KCC2 activity following seizures, and recent therapeutic strategies targeting KCC2.

Finally, although the authors appropriately acknowledge that the experiments were performed exclusively in vitro, the discussion could more explicitly address the limitations of the organotypic hippocampal slice model, including how culture-induced network reorganization and spontaneous epileptiform activity may influence chloride homeostasis and the extent to which these findings generalize to traumatic brain injury and chronic epilepsy in vivo. In addition, the statistical analysis would benefit from clarification regarding the experimental unit and the treatment of repeated measurements.

Reviewer #2 (Public review):

Summary:

This manuscript investigates the kinematics, aerodynamics, and neural control of free-flight roll perturbation in fruit flies.

Strengths:

The paper employs a variety of appropriate methods, including magnetically sourced in-flight perturbations, free-flight wing kinematic measurement, and optogenetic silencing of specific motor units (and thus steering muscles). The results are generally consistent with prior work, showing that 5 different bilateral pairs of steering muscles contribute to the roll response, affecting the wing stroke amplitude and wing pitch. Furthermore, the roll response - both the overall animal performance and the details of the wing motion - is not detectably altered by knocking out any one of the five muscle pairs.

The reverse approach, optogenetic activation of specific phasic muscle pairs or silencing of tonic pairs, confirms that the selected muscles produce changes to wing kinematics appropriate for a roll response (confirmed by quasi-steady aerodynamic modeling). This set of results corroborates the main conclusions.

Weaknesses:

The authors refer to this as robust control of roll, though exactly what is meant by this is not clearly defined, and the word "detectably" may be important to understanding the limitations of the findings, since the large amount of variability in many of the experimental measurements would make it challenging to detect differences among treatments. As with the silencing experiments, the wing kinematics after optogenetic activation were highly varied, making it challenging to identify differences between the effects of individual muscles.

Reviewer #2 (Public review):

Summary:

This study explores risk factors for neural atrophy following alpha-synuclein injection from two complementary perspectives. First, it evaluates the effect of biological and experimental factors (genotype, alpha-synuclein species, biological sex, seeded brain region and time since injection) on the extent of neural atrophy. Second, it assesses whether regional biological features (gene expression and structural connectivity) can predict the spatial distribution of that atrophy. Using longitudinal in vivo MRI, the authors map brain volume changes over time. They relate the brain changes from striatum seeding to behavioral outcome, identifying factors associated with more severe pathology. Finally, the authors validate a previously developed in silico model for predicting brain atrophy from alpha-synuclein seeding. The model is based on the alpha-synuclein prion-like spreading hypothesis and uses local gene expression and structural connectivity to predict atrophy following the injection. They conclude that the model accurately predicts atrophy following striatal seeding but performs poorly for hippocampal seeding. They further show that structural connectivity alone is insufficient to explain the observed atrophy after striatal seeding, and that incorporating regional gene expression substantially improves model performance.

Strengths:

The authors have expanded on their previous work by systematically evaluating how multiple biological and experimental variables influence the development of brain atrophy. The use of MRI to map structural changes and the subsequent analysis is well validated by this group and enables comprehensive whole-brain quantification across a large number of experimental conditions. The evaluation of the in silico model linking regional gene expression and structural connectivity to patterns of atrophy under different experimental conditions is important for expanding our understanding of how atrophy develops in synucleinopathies.

Weaknesses:

My principal concern is that the manuscript is framed as an investigation of alpha-synuclein propagation, whereas the primary outcome measured throughout the study is a change in regional brain volume. Although atrophy is likely related to the underlying spread of pathological alpha-synuclein, the spatial distribution of alpha-synuclein pathology is not directly quantified. Conclusions regarding propagation of alpha-synuclein and the relationship with tissue loss are inferred from the performance of the in silico model in predicting atrophy. I think the manuscript could be revised to make this distinction clearer.

A second concern relates to the comparison between striatal and hippocampal seeding. A key conclusion of the manuscript is that the in silico model accurately predicts atrophy following striatal seeding but not hippocampal seeding. However, the two analyses use different experimental group comparisons (striatum: M83 Ms-PFF versus WT PBS; hippocampus: M83 Hu-PFF versus M83 PBS). It would be helpful to demonstrate that the observed difference in model performance is not attributable to these differing experimental/ control groups.

Reviewer #2 (Public review):

Summary:

The authors use FANS of rapidly obtained postmortem brain tissue from DPWH, seven aviremic, four viremic and three HIV-negative controls to characterize the CNS HIV reservoir and cell-type-specific transcriptional changes.

Strengths:

The study addresses a genuinely important and understudied question: the effect of viral suppression specifically on the CNS reservoir and transcriptome using a rare and well-characterized specimen set.

Weaknesses:

I have some reservations about the conclusions, because of the confounders, mechanistic narrative, and the data itself.

(1) With n = 3 negative, n = 4 viremic, and n = 6 aviremic (post-H5 exclusion), every DEG and enrichment result rests on very few individuals. Rather than HCA reporting effect-size distributions and per-gene sample support, the authors should consider sensitivity/leave-one-out analyses to show that results are not driven by single donors. To me, it is as in Figure 3: major changes in the DGE are between the viremic vs aviremic, interestingly not with the negative control.

(2) HIV-negative controls were significantly older (74,76 & 83, inflammaging) and entirely male (sex-based immune differences). Both bias the immune comparisons that anchor the paper. PCA reassurance with n = 3 is weak. The authors should address this quantitatively, e.g., age/sex as model covariates, or explicit discussion of directionality of bias for each key pathway.

(3) HIV DNA was detectable in only 5/11 DPWH, and the microglial reservoir signal comes from ~3 individuals. The 10³-10⁴ copies/million figure and "dominant reservoir" claim should be framed against this limited detection and the focal distribution of infection.

(4) Only two participants had documented cognitive symptoms, and histopathology showed no neuropathology in anyone. The transcriptome-to-HAND link is currently asserted rather than demonstrated. The authors should state this limitation prominently and avoid implying an established relationship.

(5) A large fraction of DPWH had TB (one TBM), and controls had SARS-CoV-2. TBM alone causes microglial activation. Excluding H5 does not remove the broader TB signal. The authors should analyze/discuss TB status as a potential driver of the microglial immune signature in the retained cohort.

(6) Sorting on IRF5 cannot distinguish microglia from perivascular macrophages, as correctly stated by the authors in the discussion, so the "microglial" reservoir may include other myeloid populations. The authors should change the cell-type attribution accordingly.

Reviewer #2 (Public review):

Summary:

This study investigates the population structure and ancestry of Helicobacter pylori in Cabo Verde, where the human population has mixed West African and European ancestry. The authors combine a population survey, serum markers, bacterial genome analysis, and paired human-bacterial ancestry data. They report high H. pylori seropositivity, several distinct bacterial groups, and limited correlation between human ancestry and bacterial ancestry. They also identify one European-derived bacterial group that appears to have undergone a recent expansion and carries fewer well-known virulence-related genes.

The study is interesting, and the dataset is valuable, especially because population-based H. pylori genomic data from Cabo Verde and West Africa are limited. The results provide useful information on bacterial diversity, historical migration, and host-bacterial ancestry. However, some of the main conclusions are stronger than the evidence currently supports, particularly the claims of host adaptation, increased transmission, and reduced virulence.

Strengths:

(1) A major strength is the study population. Participants were recruited from the general population and not only from patients with gastrointestinal disease. This gives a broader view of H. pylori diversity in Cabo Verde than studies based only on hospital patients.

(2) The number of participants tested for H. pylori antibodies is substantial, and the authors also obtained a relatively large number of bacterial genomes. The combination of human and bacterial genomic information is another important strength. This allows the authors to directly examine whether human ancestry is related to the ancestry of the colonising bacteria.

(3) The population genetic analyses are extensive. The authors use several different approaches, and these generally support the existence of African-derived and European-derived bacterial groups in Cabo Verde. The identification of two low-diversity European-derived groups is also interesting and suggests a relatively recent expansion.

(4) The addition of new strains from Ghana and Portugal improves the reference dataset. The results may help future studies of H. pylori population structure in Africa, Europe, Cabo Verde, and populations affected by historical Atlantic migration.

(5) The finding that human ancestry and bacterial ancestry are only weakly related in this population is potentially important. It suggests that the long-term relationship between human and bacterial ancestry may be less stable in recently admixed populations.

Weaknesses:

The main weakness is that several biological conclusions are based on indirect evidence. The genomic results support recent expansion of one bacterial group, but they do not directly show that this expansion was caused by adaptation to local hosts or by increased transmission. Founder effects, population history, geographic clustering, household transmission, or random expansion may also explain the pattern. The wording should therefore be more cautious.

The conclusion of reduced virulence is also not fully supported. The expanded lineage often lacks the cag pathogenicity island and carries less virulent forms of vacA, which suggests lower virulence potential. However, this does not prove that the strains cause less gastric damage or lower disease risk. There are no endoscopic or histological data, and serum pepsinogen values are only indirect markers.

The description of the study population as having limited gastric inflammation is too strong. Serum pepsinogen measurements are useful for estimating gastric atrophy, but they do not directly measure the degree of histological gastritis. In addition, participants were recruited independently of symptoms, but this does not mean that they were all asymptomatic.

The epidemiological estimate is based on antibody testing. This measures seropositivity and cannot clearly distinguish current from previous infection. Therefore, terms such as active infection or colonisation should be used carefully.

The proposed new West-Central African bacterial group is based on a small number of reference strains from Ghana and Nigeria. The result is interesting, but broader sampling from African countries is needed before this group can be considered firmly established.

The interpretation related to the trans-Atlantic slave trade is plausible, but the data mainly show patterns consistent with known historical migration. They do not directly demonstrate when or how the bacterial lineages moved.

The gastric cancer comparison may also be affected by bacterial population structure. Differences between the Cabo Verdean lineage and gastric cancer strains may reflect ancestry or lineage differences rather than disease association alone.

Overall, the study achieves its main aim of describing H. pylori diversity and ancestry in Cabo Verde. The evidence is strong for the population structure and ancestry findings, but less strong for the proposed mechanisms of adaptation, transmission, and reduced disease-causing potential. The work will be useful to the field, but the main conclusions should be stated more carefully.

Reviewer #2 (Public review):

Continuing their work distinguishing sensory latencies of "cognitive" processes, the authors turn their attention to "response inhibition". The "square quotes" are being used to highlight how this manuscript aims to challenge previous descriptions of performance data and inferred computational processes. The authors assert that previous descriptions of the measure known as "stop signal reaction time" (SSRT) are flawed because they did not account for sensory latencies empirically or theoretically.

Enthusiasm for the manuscript cannot be high in light of many weaknesses countering the possible strengths. Strengths include offering an opportunity to more carefully characterize the quantity SSRT and a specific empirical approach offered to the research community. However, these strengths are countered by the following structural, theoretical, and empirical weaknesses:

As announced by the elephant in the title, the writing could be described as excessively polemical. However, the characterization and interpretation of previous empirical and theoretical work is disputable.

The major theoretical claim regarding sensory delays inherent in SSRT is not novel. The authors assert, "...this corpus of work may have been misinterpreted because the SSRT is systematically influenced by low level sensory and motor transmission times, arguably more so than by inhibition or cognitive processes." This was certainly recognized by Logan and Cowan in their original work. They wrote, "An act of control, like any other act, must take time. The theory provides methods for measuring the latency of control even when the act of control is not directly observable." (page 298) Also, "... the estimate of stop-signal reaction time includes the latency of the internal response to the stop signal and the duration of the ballistic process." (page 316-317). Moreover, subsequent computational and empirical work, some noted by the authors, has distinguished the sensory encoding interval from the interval during which the STOP process interrupts the GO process.

The theoretical suggestion that an accounting for sensory delays undermines the functional interpretation of SSRT mischaracterizes the original literature. For example, in the Abstract the authors write "Sensory and motor contributions must be ruled out before linking SSRT results to inhibition or cognition". The original Logan and Cowan theory was about what happens at the end of SSRT, and that was described only as an "act of control", in perfectly positivist fashion. For example, Logan and Cowan wrote, "Estimates of stop-signal reaction time provide a measure of the latency of control." (page 315). Thus, the authors are misstating what was meant originally by SSRT. In addition, the authors offer no specific or formal definition to specify what they mean by "inhibition or cognitive processes".

Confidence in the new empirical conclusions of the manuscript must be low because the new performance data are of questionable quality. The first issue is that the stopping accuracy (or inhibition functions in original terminology) shown in Figure S3 is very problematic for the interpretation of the authors' empirical work in this manuscript. There are two problems. First, these plots should span from nearly 0% to nearly 100%. It is not possible to resolve the span of each individual in the figure, but it is clear that many, if not most, in both the Manual and Saccadic data span just 20-30%. Second, the plots should span the 50% success value. It is clear that the maximum or minimum values for many participants do not reach the 50% value. These two problems indicate that many (most?) participants were not really sensitive to the stop signal.

The second issue concerns the pattern of response times (RTs) on "ignore" trials. The authors portray performance as exemplifying a "pause-then-go" strategy. This is not uncommon, but it is not the only way participants perform. Many participants across multiple studies of selective stimulus stopping produce RTs on "Ignore" trials essentially indistinguishable from RTs on no-stop trials. The authors must acknowledge and account for such individual variability. In fact, the "T_s" value is measured by the difference in distributions of RT on no-signal and ignore trials. If these distributions are not different, then the measurement and interpretation of this quantity is questionable.

Related, the distributions of RT on stop trials, particularly for saccade responses, are portrayed with a second mode in the schematic illustrations and clearly peaking at SSRT in Figure S1. This second mode is not observed in other saccade stop signal studies. This indicates that the participants in this study were in a peculiar mode of performance.

Finally, given the pivotal role of measures of differences of RT distributions and the pronounced variation of stopping accuracy (Figure S3), the authors must show the distributions for all of their new participants. The authors' claim to higher resolution obliges them to reveal every step of analysis.

In its current form, this manuscript is unlikely to change the thinking of modelers or practitioners of the stop signal task.

Reviewer #3 (Public review):

Summary:

In humans, short photoperiods are associated with hypersomnolence. The mechanisms underlying these effects is, however, unknown. Chen et al. use the fly Drosophila to determine the mechanisms regulating sleep under short photoperiods. They find that mutations in the circadian photoreceptor cryptochrome (cry) increase sleep specifically under short photoperiods (e.g. 4h light : 20 h dark). They go on to show that cry is required in GABAergic neurons and that the effects of the cry mutation on sleep are mediated by alterations in GABA signalling. Further, they suggest that the relevant subset of GABAergic neurons are the well-studied small ventral lateral neurons that they suggest inhibit the arousal promoting large ventral neurons via GABA signalling.

Strengths:

Genetic analysis to show that cryptochrome (but not other core clock genes) mediates the increase in sleep in short photoperiods, and circuit analysis to localise cry function to GABAergic neurons.

Weaknesses:

The authors' have substantially revised their manuscript, and the manuscript is much better for the revisions. However, the idea that the sLNvs are GABAergic is unfortunately still not well supported by the data. The authors have acknowledged the limitations of their methods though which is very welcome, and a substantial improvement.

Reviewer #3 (Public review):

Summary:

The study "Resetting of H3K4me2 during mammalian parental-to-zygote transition" provides valuable insights into the dynamic changes in H3K4me2 during early embryonic development.

Strengths:

The findings provide valuable insights into the temporal and spatial dynamics of H3K4me2 and its potential role in zygotic genome activation (ZGA).

Weaknesses:

Key areas for improvement include enhancing the innovation and novelty of the study, providing robust functional validation, establishing a clear model for H3K4me2's role, and addressing technical and presentation issues. While the findings are significant, the current manuscript falls short in several critical areas. Addressing these major and minor issues will significantly strengthen the study's contribution to the field of epigenetic reprogramming and embryonic development.

Comment on revised version:

It would be better for the author to directly provide some experimental or analytical data rather than discussing and defending.

Reviewer #2 (Public review):

Summary:

Rajagopalan et al. shows how extracellular domain features regulate KIR2DL4 internalization. The trafficking phenotypes of cysteine mutants are logically organized and well summarized in Table. The disulfide mapping and differential alkylation strategy is appropriate and provides strong support for alternative disulfide configurations in D0. The higher accessibility or more selective reduction of Cys10-Cys28 as compared to Cys28-Cys74 by PDI is a key mechanistic anchor.

Strengths:

The identification of a conformational switch in KIR2DL4 is conceptually novel. Experimental elegance, detailed and well written.

Reviewer #2 (Public review):

Summary:

The authors measured whether a phylogenetically wide sample of marine species was experiencing declining genetic diversity, as one might expect from widespread habitat threat, over a recent 2-decade time span. They next identified key environmental variables that are impacting genetic diversity within and between reefs. A key insight was to apply k-mer-based genetic distances to massively speed up the reanalysis of genetic data into a common pipeline, which is otherwise onerous. The manuscript ends by highlighting key seascape variables that were associated with increases or decreases with genetic diversity through time. The authors achieved their overall aims, though I remain unsure of how well the identified seascape variable-genetic diversity predictions can be generalized, as implied in the abstract.

Strengths:

A key strength of the study was its rigor in vetting the k-mer based distance metrics, checking whether they give population structure patterns (Figure S2) and correlated with nucleotide diversity. This surpasses previous studies that used a similar method. The modeling procedure of genetic diversity predictions from environmental variables is also rigorous and presented with some appropriate nuance.

Weaknesses:

I noted five weaknesses, listed below in order of potentially more severe at the top to more minor at the bottom.

First, only one k-mer distance metric was tested. There are many k-mer distance metrics that will potentially give different weight to different frequencies of polymorphism, like how Watterson's theta and nucleotide diversity weight polymorphisms, depending on their frequency. It would be interesting to see if the seascape variable predictions hold with a Jaccard or cosine distance metric, or if the observed results are purely restricted to the choice of Bray-Curtis distance. Another option would be to use mash, skmer, or (very recent development) re-skmer distances, which attempt to more directly approximate the average nucleotide identity between two sequence sets based on the k-mer sets of their reads while also being faster than traditional alignment. This would potentially give cleaner trends, seeing as the goal is to have a proxy for nucleotide diversity, with the downside of not including the impacts of non-SNP variation.

Second, it is unclear to me whether the number of species analyzed, 18, can accurately identify important environmental variables in early warning systems, as claimed in the abstract. While this likely represents the best available balance of evidence, it is worth highlighting the manuscript's note that the environment-diversity predictions did not scale across marine realms. This is likely a limitation of data availability, rather than a study design flaw, but is nonetheless important for readers to keep in mind. Would recommend that the abstract acknowledge this limitation.

Third, it is unclear to me how the included datasets compare in terms of genome-wide coverage. Figure S1 gives sequencing depths in terms of read number, but what is the range normalized for genome size - are the datasets 1x, 5x, 10x, on average, etc? This is probably most key to how the k-mer distance metrics will perform, because low coverage will make two samples appear artificially distant due to rarity of sampling the same k-mer multiple times. However, the correlation between k-mer distance and regular alignment-based SNP distance (Figure 2C) gives some confidence that this effect could be small.

Fourth, though k-mer distances may in some sense better capture the breadth of DNA sequence diversity, they lack a concrete interpretation of what loci may/may not be under selection as marine environments are increasingly threatened over time. This is a different question than what the manuscript tries to address, but is of interest to the field and is something that would be seemingly difficult to do with k-mers.

Finally, I had a more minor concern: the k-mer-based distances use only k-mers that are mapped to a reference genome. This is done to thoroughly remove contaminant sequences, which is important, but is a double-edged sword because there is potentially additional pangenomic variation that is real but does not map to a single reference. The authors state in the first paragraph of the discussion that this choice did not affect the results, but I did not find an associated analysis in the supplement or main text. It would be interesting to compare distance metrics based on screening against all known microbial+human genomes vs screening against the reference genomes.

Reviewer #2 (Public review):

This study used publicly available Tara Oceans and Tara Oceans Polar Circle metagenomic and metatranscriptomic datasets, including viromes, to construct sample-specific, gene-scale metabolic models. This reviewer understood that, for each sample, genes or transcripts associated with metabolic pathways were integrated into a single virtual "superorganism" or "community cell." These sample-level models were then compared across global ocean regions to investigate spatial patterns in heterotrophic prokaryotic metabolism, metabolic synergy, and the potential effects of virus-encoded auxiliary metabolic genes. However, it was not clear whether archaeal genes were also included in the heterotrophic prokaryotic fraction.

The study represents an ambitious and potentially valuable attempt to connect large-scale environmental omics data with constraint-based metabolic modeling. The authors handled a very large dataset and introduced quantitative approaches based on flux sampling, Reaction Cumulative Correlation, and synergy scores to describe community-level metabolic phenotypes using several mathematical formulations. The recovery of previously defined oceanic ecological zones from reaction-based models may provide preliminary support for the ecological relevance of the framework, although only approximately 26% of prokaryotic genes and 7% of viral genes were mapped to known metabolic reactions.

However, the framework should be understood as gene- or reaction-resolved, sample-level metabolic modeling rather than genome-resolved community modeling. By combining all detected genes within a sample into a single superorganism, the approach likely loses taxon-specific metabolic information and cannot directly distinguish intracellular metabolism from interspecies metabolic exchange. Consequently, several ecological interpretations, including cooperation, stability, reaction essentiality, and viral impacts, remain strongly dependent on the underlying model assumptions.

Overall, the manuscript presents a novel and scalable framework with considerable potential. However, greater methodological clarification and more cautious interpretation are needed before the ecological and biogeochemical conclusions can be fully supported.

Reviewer #2 (Public review):

Summary:

The authors extend their previous population-based Ct-value framework for inferring community epidemic trajectories from human infections to vector infections, using mosquitoes as vectors for West Nile virus. They use agent-based modelling to distinguish virus-positive detections arising from non-active infection states from those reflecting active infections, and then apply this framework to mosquito surveillance data from Colorado and Texas.

Overall, this is a well-designed and carefully evaluated study. The manuscript proposes a feasible and potentially valuable framework for vector infection surveillance. The findings are supported by both mechanistic agent-based simulations and applications to real-world mosquito surveillance data, which strengthens the biological plausibility and practical relevance of the proposed approach.

Strengths:

A major strength of the study is its clear methodological extension from human infection surveillance to vector infection surveillance. The agent-based modelling framework provides a useful basis for distinguishing active infections from virus-positive detections that may reflect non-active infection states. The application to surveillance data from two different geographic settings further supports the feasibility of the framework. Overall, the study is carefully designed, and the model schematic and main analyses are generally clear.

Weaknesses:

(1) It would be helpful if the authors could provide plots showing variation across locations and over time. This would further support the claim made in the paragraph at lines 101-107.

(2) Figure 2: The model schematic is clear in terms of workflow, but it would benefit from more information on model parameterization. In particular, it would be helpful to clarify which parameters or migration rates were estimated from the data and which were assumed based on prior literature.

(3) Figure 4: I wonder whether the authors examined how changes in the proportion of mosquitoes with static viral-kinetics trajectories would affect the observed bimodal distribution. Relatedly, it would be useful to know whether there is a threshold proportion at which the method becomes less able to distinguish active from static viral-kinetics patterns.

Conclusion:

Overall, the evidence is reasonably strong for demonstrating the feasibility and biological plausibility of the proposed framework. Some conclusions would be further strengthened by additional sensitivity analyses on key assumptions, especially the proportion of static viral-kinetics trajectories and spatial-temporal heterogeneity across surveillance sites.

Reviewer #2 (Public review):

Using electrophysiological recordings in a well-characterized animal model of acute pain, and analytical and modeling methods, the authors show that descending pain-modulatory neurons in the rostral ventromedial medulla (RVM) operate across various timescales. They have both rapid multi-phase responses to noxious stimuli that unfold over tens of seconds, with distinct fast and slow recovery dynamics. Additionally, they generate slow quasi-periodic oscillations with approximately 5-minute periods during ongoing activity. These oscillations are statistically predictable and cell-type specific, demonstrating that descending pain control is organized through structured temporal dynamics that encompass immediate stimulus-evoked responses and slower fluctuations associated with physiological state.

A novel discovery is a ~5-minute quasi-periodic oscillation in ongoing ON- and OFF-cell activity. This oscillation, along with its coherence with heart rate, forms the basis for the claim that descending pain circuits exhibit intrinsic multi-timescale organization. However, it's crucial to demonstrate that this periodicity is independent of external experimental cycles such as methohexital infusion pharmacokinetics, servo-controlled temperature regulation, or slow autonomic feedback loops, all of which operate on similar timescales. For instance, the 300-second period closely matches typical drug infusion cycling and thermoregulatory feedback intervals. Therefore, heart-rate coherence peaks at multiples of this period could equally reflect a shared external driver rather than intrinsic RVM organization. Although the absence of this cyclic structure in Neutral cells argues against this possibility, the authors might want to explicitly discuss this potential confound.

The findings are important and novel in that they characterize an intriguing structure in the activity of ON and OFF neurons in the RVM. However, in the absence of a causal manipulation causality can only be inferred. That there is no phase-dependence of withdrawal latency argues against a causal role. The author are encouraged to qualify their conclusions (and their title) accordingly.

Because anesthesia can affect global dynamics, this might affect the oscillations reported. Without awake validation, it remains uncertain whether these rhythms reflect an intrinsic property or an anesthesia-induced regime. Again, the absence of oscillations in Neutral cells argues against this possibility, but it is still possible that ON/OFF cells are embedded in different circuits that are affected differently by anesthesia.

Analyses of many of the ON-cells had longer training windows (>1 sec) compared to those for the NEUTRAL cells. Could this have reduced the ability to fit and validate periodicity for the latter cell type?

Reviewer #2 (Public review):

This is an innovative and technically strong study that integrates dual-gas respirometry with LC-MS metabolomics to examine how sleep and circadian disruption shape metabolism in Drosophila. The combination of continuous O₂/CO₂ measurements with high-temporal-resolution metabolite profiling is novel and provides fresh insight into how wild-type flies maintain anticipatory fuel alignment, while mutants shift to reactive or misaligned metabolism. The use of lag-shift correlation analysis is particularly clever, as it highlights temporal coordination rather than static associations. Together, the findings advance our understanding of how circadian clocks and sleep contribute to metabolic efficiency and redox balance.

However, there are several areas where the manuscript could be strengthened. The authors should acknowledge that their findings may be gene-specific. Because sleep deprivation was not performed, it remains uncertain whether the observed metabolic shifts generalize to sleep loss broadly or are restricted to the fmn and sss mutants. This concern also connects to the finding of metabolic misalignment under constant darkness despite an intact clock. The conclusion that external entrainment is essential for maintaining energy homeostasis in flies may not translate to mammals. It would help to reference supporting data for the finding and discuss differences across species. Ideally, complementary circadian (light-dark cycle disruption) or sleep deprivation (for several hours) experiments, or citation of comparable studies, would strengthen the generality of the findings. Figures 1-4 are straightforward and clear, but when the manuscript transitions to the metabolite-respiration correlations, there is little description of the metabolomics methods or datasets, which should be clarified. The Discussion is at times repetitive and could be tightened, with the main message (i.e., wild-type flies align metabolism in advance, while mutants do not) kept front and center. Terms such as "anticipatory" and "reactive" should be defined early and used consistently throughout.

Overall, this is a strong and novel contribution. With clarification of scope, refinement of presentation, and a more focused Discussion, the paper will make a significant impact.

Comments on revised version.

The authors have satisfactorily addressed my concerns in the revised manuscript

Reviewer #2 (Public review):

Summary:

The study presents novel results on the presence of the Entner Doudoroff pathway in Synechocystis sp. PCC 6803. In contrast to an earlier study, compelling evidence is given that this strain lacks both an ED pathway and a glucose dehydrogenase/glucokinase bypass but contains a promiscuous aldolase, which also decarboxylates oxaloacetate and cleaves 2-keto-4-hydroxyglutarate (as it occurs in proline degradation). The study concludes with successfully reconciling data of different studies and with lessons learned from the previous misconception.

Strengths:

Solid biochemical data is presented to reconcile contradicting data of earlier studies and to serve as basis for disclosing possible functions of a promiscuous aldolase. Earlier misconceptions and lessons to be learned are well discussed.

Weaknesses:

The materials and methods section is rather lengthy, suffering from a lack of conciseness and repetitions, and nevertheless misses some specifications.

Comments on revised version.

The materials and methods section has been significantly improved. The revised manuscript is now recommended for publication as it is.

Reviewer #2 (Public review):

Summary:

The article describes an interesting methodology to test hypotheses about the impact of anthropogenic noise on a small arboreal primate, the pygmy marmoset. The authors used a motion-triggered combination of camera traps and speakers to play back control sounds, avian predator calls, and anthropogenic noise to test the risk-disturbance hypothesis and the distracted prey hypothesis. In addition, the authors implemented a technique that is usually used for larger mammals and has not been used before for smaller arboreal animals. The authors are careful in their interpretation of the results and do not favor one hypothesis over the other. The authors also elaborate extensively in their discussion on how to improve this kind of data collection in the future.

Strengths:

This study provides a method for rapid data collection while minimizing observer impact. The sample size is comparatively large for a wild animal in a reserve, given the overall observation time. The article also benefits from a solid analysis of the data.

Weaknesses:

Though the authors tested two contrasting hypotheses, the discussion would benefit from more detail on the ecological relevance of the observed behaviors.

Reviewer #2 (Public review):

Summary:

Previous work established that FZF1 is both necessary and sufficient for activation of FZF1 target genes through the CS2 sequence motif, which is present upstream of FZF1-responsive targets. This study extends that model by demonstrating that, in addition to direct binding of FZF1 to CS2 elements, FZF1 can also promote reduced nucleosome-mediated repression, thereby contributing an additional layer of transcriptional regulation.

The authors investigate why FZF1-dependent transcriptional responses exhibit different magnitudes despite FZF1 binding to CS2 elements with similar affinity. Using promoter constructs derived from the DDI2-3 gene, the authors identify a region upstream of the CS2 element that functions as a repressive regulatory element. Based on this observation and publicly available datasets, the authors propose that this repression may be mediated through nucleosome occupancy.

Strengths:

The authors demonstrate that the DDI2-3 promoter contains positioned nucleosomes and show that chemical stress results in decreased histone protein levels and reduced histone-associated transcripts. They further examine whether histone depletion alone is sufficient to activate the DDI2-3 response and find that reduced histone levels increase expression, although chemical treatment produces an additional increase that remains dependent on FZF1. These findings suggest that FZF1 contributes to reductions in nucleosome occupancy at DDI2-3 and SSU1, revealing a second, potentially independent mechanism by which FZF1 regulates transcriptional responses to chemical stress.

Overall, the authors provide strong evidence that nucleosome occupancy influences the magnitude of FZF1-mediated DDI2-3 responses to chemical stress. This work has important implications for understanding how transcriptional networks evolve to generate highly tuned responses by combining multiple regulatory mechanisms acting on shared molecular components.

Weaknesses:

However, several additional considerations should be addressed. While histone depletion may contribute to differential FZF1-mediated responses, alternative mechanisms may also influence the observed transcriptional differences. For example, YHB1 exhibits basal expression that is independent of FZF1, and SSU1 contains the CS1 regulatory element, which can promote increased expression independently of FZF1 responsiveness. Therefore, differences in promoter architecture and the presence of alternative regulatory sequences may also contribute to differential FZF1 responses and should be discussed.

Additionally, the authors should clarify whether nucleosome depletion is directly mediated by the FZF1 ZF5 domain or occurs indirectly as a consequence of RNA polymerase II (Pol II) recruitment. Although the data presented in Figure 9 are consistent with a direct interaction model, the current evidence does not fully exclude the possibility that Pol II recruitment contributes to subsequent nucleosome/histone depletion. Unless there is direct experimental evidence demonstrating that FZF1 ZF5 independently promotes nucleosome remodeling, this alternative mechanism should be acknowledged and considered in the discussion.

Reviewer #2 (Public review):

Summary:

This manuscript systematically evaluates the impact of experimental workflows on plasma cell-free transcriptome sequencing (cfRNA-seq) data. The authors integrate a large number of cfRNA sequencing datasets from multiple publicly available studies and establish a unified bioinformatics framework to systematically assess the effects of experimental workflows, genomic DNA contamination, library diversity, and preanalytical factors on cfRNA transcriptomic profiles.

Strengths:

This study addresses the technical heterogeneity that may hinder cfRNA biomarker discovery and clinical translation and is of substantial value.

Weaknesses:

The effects of disease phenotype, technical confounding, criteria for library quality, and conclusions regarding DNase treatment require further clarification and validation.

Major Points:

(1) The conclusion that donor phenotype explains only a small fraction of transcriptomic variation requires further support from within-study analyses.

The authors conclude from variance partitioning across all studies that phenotype explains only a small fraction of cfRNA transcriptomic variation. However, the included studies encompass different diseases, while phenotype is simplified into healthy, cancer, and non-cancer disease categories, and the overall transcriptomic variation is strongly influenced by study-specific and experimental workflow batch effects. Therefore, the cross-study pooled analysis may underestimate genuine disease-associated cfRNA differences within individual studies conducted under the same experimental workflow.

Recommendation: The authors are encouraged to perform within-study phenotype analyses in datasets that include both healthy controls and disease samples and have sufficient sample size, and to quantitatively estimate the proportion of transcriptomic variance explained by phenotype. For example, the Zhu dataset includes healthy controls and liver cancer samples, and the authors have already observed relatively clear phenotype-associated clustering between the two groups. The contribution of healthy-versus-liver-cancer phenotype to transcriptomic variation could therefore be quantified within this dataset. If similar results are obtained across multiple independent cohorts, the findings could then be summarized across studies. The authors should also note that a low contribution of phenotype to global transcriptomic variance does not necessarily imply that disease-associated cfRNA signals lack biological or clinical relevance.

(2) Comparison of the relative contributions of technical factors and disease phenotype may be affected by confounding.

Figure 1C shows that phenotype is strongly or even completely confounded with technical variables such as collection center and centrifugation protocol in some cohorts. Nevertheless, the variance partitioning analysis across all samples is used to conclude that technical factors are the primary sources of variation, whereas phenotype contributes little. In the presence of such confounding, technical effects and disease-associated biological effects may not be reliably estimated independently, and this conclusion therefore requires more direct validation.

Recommendation: The authors are encouraged to perform an independent within-study variance analysis in cohorts in which technical variables and phenotype are relatively balanced. For example, in the Moufarrej cohort, phenotype is essentially unconfounded with collection center/centrifugation protocol (Cramer's V = 0). Phenotype and relevant technical variables could be included simultaneously in a within-cohort model to quantify their respective contributions to cfRNA transcriptomic variation. If technical factors still explain a larger fraction of variance in such relatively unconfounded cohorts, this would provide stronger support for the central conclusion of the manuscript.

(3) The use of NG80 as a criterion for defining "high-quality libraries" requires further validation.

The authors use NG80 as a metric of library diversity and further apply NG80 > 1,000 as one criterion for defining high-quality libraries in Figure 6. However, because NG80 is based on gene counts, it may be affected by sequencing depth. In addition, gDNA contamination can artificially increase NG80, whereas genuinely abundant non-coding RNAs in WRR libraries can lower NG80. Therefore, a higher NG80 does not necessarily indicate better overall library quality, and the metric may reflect both technical quality and genuine RNA composition.

Recommendation: The authors are encouraged to re-evaluate NG80 after downsampling samples to a common number of mapped fragments and to examine the relationship between NG80 and sequencing depth. The rationale for the NG80 > 1,000 threshold should also be further justified, and the impact of alternative NG80 thresholds on high-quality library classification and the main conclusions should be assessed. Unless there is evidence that this threshold reliably predicts library reproducibility or biomarker-related information content, library diversity and overall library quality should be clearly distinguished, and NG80 should not be presented as a universal criterion for high-quality libraries.

(4) Conclusions regarding DNase treatment should be interpreted more cautiously.

The Toden study did not explicitly report DNase treatment. The manuscript infers that DNase digestion was performed based on the fact that this study originated from the same laboratory as other studies and used a similar workflow; this inference should not be treated as an established experimental fact. In addition, the authors state that double DNase treatment is the most effective approach among non-EB workflows, but this conclusion is mainly based on cross-study comparisons, in which DNase strategy varies together with laboratory, sample handling, and cohort-specific factors. The current evidence is therefore insufficient to establish that double DNase treatment itself is superior.

Recommendation: The authors are encouraged to label the DNase status of the Toden study as "not reported" or "inferred", unless confirmation can be obtained from the original authors. The conclusion that double DNase treatment is the most effective approach should also be tempered, with explicit acknowledgment that it requires direct parallel validation using the same samples under different DNase treatment strategies.

Reviewer #2 (Public review):

Summary:

The authors conducted a functional high-throughput drug screening using hiPSC-CMs derived from patients with LMNA-DCM. Cyproheptadine emerged as a therapeutic candidate.

Strengths:

The screen appears well designed.

Weaknesses:

The single candidate that emerged from the screen, cyproheptadine, raises issues with potency. In addition, validation studies that are both expected and necessary for a drug proposed as a novel therapeutic for human cardiomyopathy have not yet been performed. Rigor could be improved once the basic mechanistic and validation studies discussed below have been performed.

Reviewer #2 (Public review):

Summary:

In this study, the impact of prenatal alcohol (PAE) on amyloid precursor protein (APP) C-terminal fragments and notch intracellular domain (NICD) levels in adulthood is measured in 3xTg-AD mice.

Prenatal alcohol alters gamma secretase activity with development and aging. This could have implications for Alzheimer's disease risk in populations without inherited Alzheimer's risk genetics.

Strengths:

Strengths include the model, the use of orthogonal approaches, and the rigorous, high-quality data.

Weaknesses:

Some figures lack prenatal alcohol treatment in the 3xTg-AD mice.

Some overstatements should be tempered. For instance, one cannot conclude that the changes in CTFs are driving the changes in learning and memory (as suggested in the last line of the abstract) without a direct intervention testing this. For instance, though PAE caused a more robust learning deficit at 6 mo in WT, the impact on CTFs was less than it was at 3 mo. PAE did not significantly change CTFs or learning/memory in 3xTg-AD mice at 4 months, suggesting the genotype effect takes over at this point. The text should be adjusted to reflect this.

Conclusion:

In summary, this is a rigorous assessment of the long-term impacts of PAE on CTFs and learning/memory in adult WT and 3xTg-AD mice.

Reviewer #2 (Public review):

This manuscript reveals functional connectivity of two different classed of cortical neurons that respond in opposite ways to mismatches between sensory and top-down inputs. These data are very valuable because different theories of information processing in the cortex make different predictions on the patterns of connectivity of these neurons. Therefore, these data strongly constrain possible theories of cortical processing.

Comments on revised version.

I thank the Authors for answering my questions and updating the manuscript.

Congratulations on this important work!

Reviewer #2 (Public review):

Summary:

Toxoplasma gondii is an obligate intracellular parasite and the causative agent of toxoplasmosis. Parasite invasion of host cells, intracellular replication, and subsequent egress, which results in destruction of the infected cell, are central to pathogenicity. This manuscript focuses on understanding how maternal resources, specifically cellular organelles, are shared between daughter parasites during cell division. Many organelles are present as a single copy, making their division and inheritance essential for successful replication. In T. gondii, our understanding of how organelles are divided during cell division remains limited, and this study helps address this important knowledge gap.

Strengths:

The major strength of this study is the use of a Halo-based pulse-chase assay to characterize patterns of organelle inheritance and to monitor protein synthesis, turnover, and movement. This approach will be of considerable interest to the field. Using this method, the authors identify three major modes of organelle inheritance:

(1) Organelles present in multiple copies (such as micronemes and rhoptries) are partitioned between daughter parasites, with additional contributions from newly formed vesicles. Newly synthesized and pre-existing material remain as distinct populations within the cell.

(2) Single-copy organelles, such as the Golgi and apicoplast, are expanded through the incorporation of newly synthesized material before division.

(3) Cytoskeletal structures are synthesized de novo during each round of cell division.

These findings provide a more refined understanding of organelle inheritance and demonstrate that secretory organelles are not generated entirely de novo during each round of division, as was previously thought.

The paper places particular emphasis on the fate of maternal micronemes and rhoptries during division. The data show that (1) during division in wild-type cells, maternal micronemes and rhoptries are detectable in the residual body (RB); however, the majority of these organelles are localized within the parasite body, either at the apical or basal ends of the daughter parasites (Fig. 6). (2) In the absence of the myosin motor MyoF, micronemes and rhoptries accumulate in the residual body and are not properly trafficked to the daughter cells. Upon restoration of MyoF protein levels, these organelles redistribute to the daughter cells, although in an uneven manner.

Weaknesses:

The second half of the paper focuses on a more detailed characterization of microneme and rhoptry recycling. The authors strongly argue that the RB is a central hub for recycling micronemes and rhoptries; however, this conclusion is not fully supported by the data. For example, the authors state:

Line 227:<br /> "Notably, after endodyogeny was completed, M-MIC2 was redistributed from the RB to the apical tip of the daughter cells (Figure 6A, 11:30, 16:00 h), confirming that the RB serves as a temporary reservoir during microneme recycling (Periz et al., 2019)."

Line 231:<br /> "In approximately 90% of parasites undergoing replication, M-RON2 was integrated into daughter rhoptries prior to mother cell collapse and formation of the RB (Figure 6B, 4:15-4:30 h and 10:30-10:45 h). Like M-MIC2, M-RON2 was occasionally detected in the RB, though less prominently, suggesting more rapid, tightly regulated, or more efficient recycling due to their lower number."

Line 326:<br /> "However, we show that the RB temporarily stores maternal secretory organelles, such as micronemes and rhoptries, which are later redistributed to daughter cells in a MyoF-dependent manner (Figure 9B)."

Thus, the model that all microneme and rhoptry trafficking is RB-dependent is based primarily on the MyoF depletion phenotype (which results in RB accumulation) together with the observation that a relatively small amount of maternal microneme and rhoptry material is detectable in the RB of wild-type parasites. Although the authors' interpretation-that recycling is RB-dependent-is one possible explanation, alternative models are not discussed.<br /> For example, an alternative possibility is that the majority of micronemes and rhoptries are trafficked directly from the apical end of the mother parasite to the daughter cells without passing through the RB. In this scenario, only a subset of the organelles would enter the residual body, perhaps reflecting imperfect trafficking efficiency rather than an obligatory recycling step. Loss of MyoF would impair this trafficking pathway, resulting in the accumulation of secretory organelles within the RB. In other words, RB accumulation could be a consequence of MyoF depletion rather than evidence that all trafficking in wild-type parasites normally proceeds through the RB.

This alternative interpretation seems particularly relevant for the rhoptries, given that the authors themselves state that "M-RON2 was integrated into daughter rhoptries prior to mother cell collapse and formation of the RB."

Other comments:

Figure S10C<br /> To determine whether microneme degradation occurs in the RB, the authors quantified the fluorescence intensity of individual micronemes in control parasites and following auxin washout, showing that after redistribution the fluorescence intensity of individual vesicles is unchanged. However, this is not the appropriate analysis to address the question being asked. To conclude that micronemes are not degraded, the authors would need to quantify the total fluorescence intensity within the entire vacuole. For example, if half of the micronemes were degraded, the remaining micronemes would be expected to retain the same fluorescence intensity as those in the control parasites. Thus, unchanged fluorescence intensity of individual vesicles does not exclude the possibility that degradation has occurred.

Reviewer #3 (Public review):

Summary:

This excellent manuscript by Pinto, Sharp, and colleagues examines bovine tissue tropism for influenza viruses. They find that bovine flu, as well as other strains, have strong replication in mammary tissue. They also map the genetic changes to influenza that improve replication in bovine cells. Overall, the study is well designed and executed and the results are very timely.

Strengths:

(1) The experiments are well-controlled.

(2) The figures are well-constructed and easy to follow.

(3) The Methods and legends are detailed, with sufficient information.

Comment on revised version.

The authors have strengthened the manuscript by addressing comments from the three reviewers and I have no additional concerns/suggestions.

Reviewer #2 (Public review):

Summary:

This paper studies the interplay of evolutionary and in-lifetime learning. The authors develop a neural network model in which initial weight configurations evolve under selective pressure, while fitness is determined by the network's performance after a learning period. They show that such a network displays very distinct learning dynamics from those trained by either gradient descent or genetic algorithms alone: in particular, they do not learn the task, but they show evidence of learning-to-learn and unusual representational structure.

Strengths:

(1) The writing, figures, and presentation of ideas were clear.

(2) The question of how evolution on initial weights combines with learning from within-lifetime experience to structure a learning trajectory seems interesting.

(3) The analysis of existing experiments was well-done, highlighting that though these networks did not really learn, they show latent learning structure that makes the network perform better from less data.

(4) The interplay between Baldwin & learning dynamics seemed novel and interesting, presenting many attractive puzzles.

Weaknesses:

First, the authors point to an important distinction between performing evolutionary selection on the weights pre- or post- lifetime training, the latter of which is Lamarckian. They argue, correctly, that their model is interesting because it selects on the weight initialisation, unlike, for example, Shuvaev et al. However, my understanding is that a long line of papers beginning perhaps with Hinton & Nowlan also do non-Lamarckian evolution: Hinton & Nowlan have unspecified weights (denoted '?' in the paper) that can be inherited and then learnt. Is this not exactly inheritance of initial conditions (in this case, whether learnable or not)? This novelty is a primary motivation of the paper, whereas to me it seems it was already apparent in Hinton & Nowlan, and developed further in what seems to be a long line of uncited literature (see next paragraph). As such, this paper's conclusions seem poorly positioned within the existing state of knowledge/literature.

Second, the algorithm is framed as novel, but I think it is a rediscovery. This framework is very close to MAML, in which an initial weight configuration is optimised by gradient descent to be good after a few steps of fine-tuning (Finn et al., 2017). The authors' approach differs in using a genetic algorithm to perform the training of the initial weights, avoiding some of the computational complexities of MAML, especially after long fine-tuning. In this, the authors have, I think, rediscovered ES-MAML, MAML where the inner optimisation loop is gradient descent, while the outer is genetic (Song et al., 2020). Other similar work is "Meta-Learning by the Baldwin Effect" (Fernando et al., 2018).

Further, within Fernando et al. there is a rich literature review, almost none of which are cited by the authors. I point especially to Keesing & Stork, 1990, which appears to show a strong dependence of Baldwin-like improvements on the amount of data, something this paper also shows but explores less thoroughly.

To summarise my critique thus far: I think the literature already answers the main concern of the motivation (i.e. non-Lamarckian neural network evolution and learning), I think it has already discovered this particular algorithm, and I think past work has more thoroughly analysed behaviours similar to those presented in this paper. Without positioning correctly within this literature, the more general contribution of the paper is hard to establish. The true novelty of the authors' analysis seems to be the emphasis on Saxe et al.-like learning dynamics and its interplay with the Baldwin effect, but I am not certain of this without knowing the literature better.

Regarding experiments, there was an interesting effect where the EC networks didn't learn but did show latent learning (Figure 2, Figure 3), which sped up later learning (Figure 4). There were a few details I was surprised by on which I would appreciate clarity:

(1) The main result has basically no headline learning under EC. This will clearly be very dependent on parameters (e.g. if you add or remove enough training steps, the algorithm becomes SGD/GA, which both show learning). It seems like a natural analysis would examine this (e.g. a plot of final performance of EC after 4000 generations with different per-generation learning budgets).

(2) It is then shown that after 4000 generations EC can learn very quickly to perform the semantic task perfectly, at least within 200 generations (Figure 4C, and perhaps much sooner, Figure 4D, Figure 4F last panel; it was hard to say. This and the previous point seem somewhat inconsistent; was it just that Figure 3 used only 100 fine-tuning steps while the perfect-task-performing networks in Figure 4 required somewhere between 100 and 200? This seems to point to extreme parameter dependence. More broadly, how should I square this inconsistency/near-inconsistency?

(3) Figure 3k, and especially Figure 4f bottom right panel, seem to show networks that correctly separate all stimuli but cannot classify them. Should I understand this as networks learning to just push apart all pairs of datapoints without structure?

(4) If I understood the genetic algorithm correctly, only three individuals from each population seeded the next generation. This seems another important parameter to tune, since I think it is far lower than standard evolutionary work, but I am not sure.

Finally, the paper most interested me as a neural network learning puzzle: how can the network perform so badly, yet lead to such different post-fine-tuning results? The paper pointed to these as 'distinct' learning phenomena without explaining what was causing those differences. The only way I could square these results in my head was as above: that the 4000 generations pushed the initial representation to represent all datapoints differntly, effectively changing the learning problem gradient descent faces from one with a lot of structure (the semantic task) that leads to stepwise learning, to one in which it was basically linear regression on a set of well separated stimuli without the structure necessary for stepwise learning. Since the paper focuses so much on learning dynamics, and studies a task where such things can be precisely probed, it would have been nice to pin down exactly what was happening slightly more.

Reviewer #2 (Public review):

Summary:

The authors use simulations and empirical data fitting in order to demonstrate that informing a decision model using noisy single-trial estimates of an underlying fixed non-decision time can guide the model to more reliable parameter estimates, especially when the model has collapsing bounds.

Strengths:

The paper is well written and motivated, with clear depth of knowledge in the areas of neurophysiology of decision-making, sequential sampling models, and in particular, the phenomenon of collapsing decision bounds.

Two large-scale simulations are run to test parameter recovery, and two empirical datasets are fit and assessed; the fitting procedures themselves are state-of-the-art, and the study makes use of a very new and well-designed ERP decomposition algorithm that provides single-trial estimates of the duration of diffusion; the results provide inferences about the operation of decision bound collapse - all of this is impressive.

Weaknesses:

This is an interesting and promising idea, but a very important issue is not clear: it is an intuitive principle that information from an external empirical source can enhance the reliability of parameter estimates for a given model, but how can the overall BIC improve, unless it is in fact a different model?

Comment on revised version.

Thanks to the authors for their responses and inclusion of additional analyses and simulations. Thanks, in particular for clarifying a crucial detail, that the ndt-informed model actually assumes, like the uninformed model, that there is no variability in the non-decision time, and the idea is that the variable single-trial measurements of non-decision time are noisy estimates of an underlying, constant ndt. The revised paper itself has not made this clear - for example, throughout the Intro, there is no statement that the behavioural model assumes a trial-invariant ndt, and line 231 still calls tau the 'mean' non decision time, implying there is a distribution rather than an invariant single value in the behavioural model.

One implication of the above is that if the lognormal sigma is purely measurement noise that does not relate to actual variation in the underlying decision process generating behaviour, then the HMP latencies should not relate to behaviour, e.g. shorter latencies predicting shorter RT. I assume that even if the authors did find such a relationship, the principle still stands that a model with fixed ndt is more accurately fit when there are single-trial ndt estimates whose mean provides a constraint on that ndt value, than without such measurements. Still, given ndt variability is a core feature of many decision models, the authors could comment on whether the strategy would work in theory for a model with ndt variability (in the behavioural part), where the single trial estimates would then presumably reflect a mix of measurement noise and genuine ndt variability.

Another more important implication is that since it is in fact the same model being compared with and without the HMP data guiding the fixed ndt estimate, the reason the fit quality improves with HMP-information is not because it is a better model per se (it is the same model) but because without the HMP guidance, the search algorithm somehow gets lost and fails to find the 'optimal' parameter vector. That is, the parameter vector (just the parameters that relate to the behavioural model itself, not the HMP lognormally-distributed noise associated with VEP measurements) identified as optimal in the HMP-informed version of the model exists in the parameter space of the model without HMP information, but it is just not found? I raised this implication before, and it is still not clear whether it applies. I'm sorry to press on it, but it is critical for readers to understand why it is that neural information can improve overall model fit. Again, the enhancement of parameter recovery (like in Nunez 2025) makes sense, but the enhancement of the "model's fit to behavioural data" does not, without pointing to a deficiency in the search algorithm / fitting procedure.

The authors state in their replies that the onset of bound collapse is set at accumulation onset and imply that setting it instead at stimulus onset could "mathematically resolve the issue" but they don't do it because it is implausible. It is in fact not only plausible but clearly evidenced in empirical data - collapsing bounds are implemented neurally through urgency signals, and these can begin to dynamically build toward threshold well before, let alone at, stimulus onset. There is nothing bizarre about this - we can prepare movements without sensory input, and indeed even if choosing actions based on a sensory discrimination, motor preparation can launch well before the sensory evidence (e.g. Stanford, Salinas et al 2010) and this in effect collapses the bound on cumulative evidence for triggering action before any evidence actually arrives. So, Urgency/bound-collapse does not need to be triggered by a stimulus; it can start in anticipation of the stimulus. It seems critical, therefore, for the authors to clarify this point - does re-defining the onset of the collapse at stimulus onset remove the trade-off and render unnecessary the neurally-informed ndt estimation?

Related to this, it is still not clear how bias in the estimation of nondecision time would not be a problem. What if, for example, it is the end of the N2 rather than the peak of the N2 that marks accumulation onset, and/or there is an additional fixed motor time that adds to the N2-based marker to make the full nondecision time that applies in the underlying decision process. By definition (and I think this is essentially what the authors' new simulations verify), because of the trade-offs, this bias would simply be absorbed in shifted estimates of theta and lambda describing the bound collapse function. But wasn't the whole point of the exercise to more accurately estimate those parameters? The obvious implication is that the parameter-estimation accuracy of the ERP-informed model is determined by the accuracy with which the proposed ERP marker directly pinpoints the full nondecision time without bias, but this is not at all obvious in the paper as written. Importantly, in the example scenario I describe above where accumulation onsets when N2 ends, there may still be a perfect correlation of N2 peak latency with underlying ndt across trials - they could still be very strongly "linked" statistically, but we can't know what size offset might be involved.

Reviewer #2 (Public review):

Summary:

The study presents an in-depth analysis of the peptide repertoire bound by a promiscuous chicken MHC molecule using mass spectrometry, x-ray crystallography and modelling. While the MHC can bind a very diverse set of peptides, the authors have found some new rules that govern peptide binding to this MHC that could help to build a predictive model to study the repertoire of pathogen-derived peptides.

Strengths:

The study uses a range of well performed experiment across multiple techniques and provides an in-depth analysis of the peptide repertoire, including peptide sequences, length, preferred residues, stability and MHC presentation.

Reviewer #3 (Public review):

Summary:

The primary objective of this study was to establish a practical and functional framework for propagation of stable transgenic cell lines of Blastocystis, a common animal gut microeukaryote. Although the work focused on Blastocystis ST7-B, a subtype with relatively low prevalence in humans, this choice is justified by its association with more frequent negative health effects. Beyond their relevance to the medical field, the methodological advances described here have the potential to also expand cell biology studies of this anaerobic organism, including its unusual mitochondria and redox metabolism.

Strengths:

Prior to this work, genetic tools for Blastocystis were very limited, relying on a single strong promoter-terminator combination. The authors successfully expanded the available promoter set across a range of expression strengths by testing two dozen variants in luciferase-based assays. Critically, they developed an integrated workflow from a modular transgenic construct design to an expanded inventory of molecular components (promoters, reporters), optimized DNA delivery, stepwise antibiotic resistance-mediated clonal selection and propagation, and to reporter validation. The evaluation of several anaerobiosis-compatible labeling strategies for live (and fixed) cell optical imaging will be particularly useful, with the SNAP-tag system appearing especially promising for Blastocystis.

Reviewer #2 (Public review):

Summary:

Cerebrospinal fluid contacting neurons (CSF-cNs) are GABAergic cells surrounding the spinal cord central canal (CC). In mammals, their soma lies sub-ependymally, with a dendritic-like apical extension (AP) terminating as a bulb inside the CC.

How this anatomy-soma and AP in distinct extracellular environments-relates to their multimodal CSF-sensing function remains unclear.

The authors confirm in the GATA3:GFP mice where these cells are labeled that CSFcNs exhibit prominent spontaneous electrical activity mediated by PKD2L1 (TRPP2) channels, non-selective cation channels with ~200 pS conductance modulated by protons and mechanical forces.

They investigated PKD2L1 pH sensitivity and its effects on CSFcN excitability. They uncovered that PKD2L1 generates both phasic and tonic currents, bidirectionally modulated by pH with high sensitivity near physiological values.

Combining electrophysiology (intact and isolated AP recordings) with elegant laser-photolysis, they show functional PKD2L1 channels localize specifically to the apical extension (AP).

This spatial segregation, coupled with PKD2L1's biophysical properties (high conductance, pH sensitivity) and the AP's unique features (very high input resistance), renders CSFcN excitability highly sensitive to PKD2L1 modulation. Their findings reveal how the AP's properties are optimised for its sensory role.

Strengths:

This is a very convincing demonstration using elegant and challenging approaches (uncaging, outside out patch of the AP) together to form a complete understanding on how these sensory cells can detect so finely the changes of pH in the CSF.

Weaknesses:

Not weaknesses, there are only minor requests to complete the beautiful study.

(1) The apical extension's response to removal of acidification is nicely illustrated in Figure 4C,G. There's something puzzling there: while the response to Glutamate is immediate, the channel responses to H+ is extremely delayed by 100ms - 2s, and even sometimes came in bursts separated by few hundreds of ms. H+ diffuse even faster than glutamate. Why is that?

I don't quite understand how the response is so delayed & how to explain the recurring bursts of channel opening in the figure panel ?

- The authors should show in Fig 4C,G the traces for 1-2 s before uncaging occurs so we can appreciate whether such events occur as well in baseline and discuss this further in revisions.

- Could the authors use a fluorescent pH sensor to monitor pH in the extracellular space and in the cell ?

- Could the authors investigate whether in the apical extension, PKD2L1 channels are mainly at the outer membrane in the apical extension OR whether many channels are located in inner membranes ?

(2) Suppl Fig 4 is very cool and should be moved to main figure. The coupling of Soma and AP is very tight, yet there is a clear difference in targeting of channels that respond to cues in the CSF. In the context of an intact spinal cord, we can wonder how and when the contribution from ASIC in the some would be relevant to physiology. Can the authors think of experiments with an intact central canal to test the sensitivity and condition of recruitment of pH sensing in the soma (ASIC) versus the apical extension (PKD2L1)?

(3) The Reissner fiber is missing after slicing the spinal cord. From our observations in fish, the fiber being under tension triggers lots of activity in CSF-cNs (Bellegarda et al Elife 2023) that also relies on PKD2L1 (Bohm et al NC 2016; Sternberg et al NC 2019). Could the authors discuss the contribution of the Reissner fiber to the PKD2L1 mediated modulation of CSFcN excitability ? Could the authors conceive a way to slice along the anteroposterior axis (sagitally) the spinal cord to keep the Reissner fiber in the central canal when recording CSF-cN apical extension ?

Reviewer #2 (Public review):

Summary:

This manuscript introduces HSSM, a Python-based toolbox for fitting cognitive models, with a specific focus on sequential sampling models. The toolbox brings together several components: a model construction interface, surrogate likelihoods, sampling tools, an inference backend, formula-based regressions, and tools for validation and visualization.

One of the key advantages is that HSSM relies on well-established open-source packages. This ensures both a robust foundation and also opens a potential for future (community-driven) development. While HSSM is not the first publicly available toolbox for fitting sequential sampling models, it introduces several novel features that will be very valuable to researchers in the field.

Strengths:

The biggest strength of HSSM is its flexibility and ease of use for hierarchical modeling. Many existing toolboxes work as closed systems that are hard to modify. In contrast, HSSM's modular design allows it to be used either as a stand-alone tool or to pick out specific components to integrate into existing pipelines. In addition, the toolbox combines simulation-based inference, surrogate likelihoods, and formula-based regression. This opens up a lot of new modeling possibilities and makes it easy to incorporate trial-by-trial neural or physiological covariates alongside standard RT and choice data.

Weaknesses:

The paper provides a high-level overview of the toolbox, rather than a didactic walk-through that shows how to use it in practice. Additionally, despite being framed as a broad toolbox for "neurocognitive modeling", HSSM currently focuses on sequential sampling models. While these models are widely used, they represent only a small slice of neurocognitive modeling as a whole. Additionally, the toolbox is currently in beta phase, and lots of planned extensions are not implemented yet. Finally, there is currently no information on general performance benchmarks.

Reviewer #2 (Public review):

Summary:

The generation of alternate stages in the life cycle of a single species requires vast remodeling of the cellular complement of the individual during metamorphosis from one stage to another. In this paper, the authors provide a detailed description of single-cell RNA-seq data derived from the planula stage of the hydrozoan model Clytia hemispherica and compare this to an expanded dataset from the medusa stage to assess changes in transcriptomic identity of cell types between these two phases of the life cycle. The paper further includes valuable TEM data illustrating fine anatomy of cell types present at both stages investigated, and documentation of the retention of epithelial polarity from the planula through to the polyp stage, using a reporter line.

Strengths:

The study provides a solid and convincing transcriptomic characterization of planula cell types (including in situ validations and a planula-to-polyp mapping of epithelial polarity), and introduces a potentially valuable method for evaluating cluster similarity.

Weaknesses:

The work suffers from insufficient documentation of methodological approaches and missing code, lack of clarity regarding clustering resolution and nomenclature (thereby hindering cross-referencing with prior papers), and unclear plans for public, fully annotated data release.

Full Review:

The single-cell transcriptomic data analyzed include both previously published and newly generated data: two additional medusa libraries and two additional planula libraries were generated and integrated with the data from https://doi.org/10.1126/sciadv.abh1683, and https://doi.org/10.1126/sciadv.adv1159. The original release of the planula dataset in their 2025 Science Advances paper did not include analyses of all cell types. Here the authors provide this analysis for the planula stage. However, as both the number of clusters and the nomenclature of the clusters changed, this leads to some confusion and inability to cross-reference the two papers. There is no explanation given for the re-processing of the planula dataset in the current paper, and the fact that only some of the data is new is buried in the supplement, which is not referenced in the main document, while the text within the main article suggests that the entire dataset is new. The fact that the dataset in the current analyses contains fewer cells than presented in their Science Advances paper further adds to this confusion. The current paper would benefit from greater transparency in the origin of the data analyzed.

The authors do try to apply the same nomenclature for the updated medusa dataset that is present in their 2021 Science paper. For example, the previously identified 'bioluminescent cells' are identified as 'gas-m8'. A look-up table that has all of the cluster id's cross-referenced would be useful (i.e. new: 8 = gas-m8 = previous: 28 = BC = "Tentacle GFP cells"). The inability to easily cross-compare with the published data is a major weakness of the current work and would benefit greatly from consistency between the three papers. Indeed, the clustering resolution is quite different across all three papers, and the current work does not adequately address how the clustering resolution was selected here. As an updated atlas, one would expect the entire transcriptomic diversity to be included here, so that the previous work can be transferred to the updated genomic mapping resource used in the current work. Nonetheless, presenting a unified nomenclature for moving forward would benefit the community as a whole and would increase the impact of the current work substantially.

The paper also includes new TEM data of the planula cell types. The authors attempt to correlate transcriptomic profiles with these anatomical data through in situ hybridizations that provide spatial distribution of the profiles. While the TEM data are valuable to catalog the presence of cells with different morphologies within the planula, the association with the transcriptomic profiles is somewhat speculative. These valuable anatomical data should be provided at a high enough resolution to zoom in and see the details, and further description could be provided. For example, the paper states that vacuolated cells are characteristic of the basal gastrodermal cells adjacent to the mesoglea; please identify the vacuoles in Figure 4f/h for the reader.

A novel method for reconstructing cluster similarity relationships is applied to grouping clusters into cell categories within the same life cycle stage, and also for matching cell types between stages. This is a valuable contribution to the field that is worthy of further evaluation. This is, however, difficult, as the methods for which DESeq2 was applied ("see code for details") are not present in the provided code, nor is it adequately described how the "binary matrix of marker gene presence/absence" was constructed. Similarly, there are additional details of other parts of the data analysis that are missing from the provided code, and the provided supplementary material is not referenced in the main document. More rigorous documentation of the methods is warranted.

The description of the transcriptomic profiles present in the planula is solid, and the attempt to associate these profiles with anatomic locations and putative morphology provides a foundation onto which further studies can be developed. Mapping of the planula ectoderm through to the polyp stage is also an important step forward in characterizing the life cycle, and the evidence for the retention of the oral/aboral ectodermal axis is convincing. The paper falls short in describing the updated medusa dataset and could benefit from a minor restructuring of the paper. Introducing the new medusa data only after the planula dataset is fully described would mediate the shallower treatment of the updated medusa dataset, where only 22 of the original 36 transcriptomic states are recovered. In this way, the focus will shift onto the cross-life cycle stage comparisons, and it could be argued that the lower resolution of the medusa dataset is justified in order to simplify the comparisons.

It will be essential that the datasets that are presented in this work be made available for public exploration in a fully annotated format. It is currently unclear how the authors intend to do this; however, there are many repositories available for this. The UCSC Cell Browser hosted at cells.ucsc.edu is one very good option if the authors do not wish to develop an interactive tool themselves. It is imperative that the gene annotations which correspond to the dataset, and the cluster annotations that are presented in this paper, are available and easily connected to the released dataset.

Reviewer #2 (Public review):

Summary:

This paper presents a large structural survey of extracellular vesicles (EVs) and non-vesicular extracellular particles (NVEPs) in the olfactory sensilla of Drosophila melanogaster. Using high-pressure freezing and serial block-face SEM, the authors avoid many of the artifacts associated with conventional fixation and analyze more than 7,800 particles across 352 sensilla. The manuscript maps the distribution of these particles, describes their morphological heterogeneity, and examines their likely origins across different sensillum classes in both normal and degenerating tissue.

Strengths:

The strongest aspect of the paper is the imaging. Preservation is painstakingly controlled. The cryofixation appears to preserve the sensillum lymph in a more convincing native state than standard preparation methods, giving this work gravitas. Further, the authors characterized thousands of particles, further making this data strong.

The figures are strong. They are clear, easy to read, and generally well designed; I think people will use this paper as a model for how to present complex data in a concise and straightforward manner. The manuscript is careful in how it presents the dataset and does not overinterpret the descriptive observations. As an ultrastructural resource, this paper will be useful to the field. The identification of auxiliary support cells as major secretory sites, together with the striking accumulation of EVs in degenerating tissue, will provide a useful starting point for future work.

Weaknesses:

The main point that could use more clarification is the vesicle categorization. In particular, the distinction between "dense," "cargo-filled," and "double EVs" is not always easy to follow from a biological perspective. Some additional discussion of how the authors think these categories relate to one another, and whether they are intended as purely morphological groupings or as distinct biological classes, would strengthen the manuscript.

Reviewer #2 (Public review):

The authors investigate the mechanism by which a gasdermin pore-forming effector of the cartilaginous fish Callorhinchus milii, GSDMA/B (CmiGSDMA/B), is activated. This potentially provides information on the ancestral function of gasdermins, a class of proteins broadly important in human health and disease. By reconstituting components of this system in vitro using transfection models, they show that GSDMA/B is activated by cleavage by the caspase-1 homolog CmiCASP1, which directly senses lipopolysaccharide. This mechanism is broadly similar to the non-canonical pathway in mammals, wherein caspase-4/5/11 cleaves GSDMD upon cytosolic LPS sensing. The conclusions of these interactions are mostly well supported by data, but some aspects need clarification, and based on the experimental approaches, some of the broader interpretations have limitations that should be considered and further discussed.

A more detailed analysis and discussion on the differences between caspases with regard to their LPS-binding capacity would be valuable for comparison. The analysis of Figure 4A and 4B effectively shows that there are similarities between CmiCASP1 and some of the studied mammalian caspases. However, part of this analysis is to make the point that some caspases do not bind LPS, and it would benefit from the inclusion of additional relevant LPS-insensitive caspases to show the connection between the chondrichthyan caspase residues highlighted and LPS-binding dependence. Modeling the LPS binding site (such as in Figure 1F) would further help clarify whether these are appropriately positioned for coordination, or for non-conserved residues, if there are alternate binding modes thought to have biological relevance.

The authors note that two different cleavage products are formed, with variable function, which is of interest. The results of Figure 2b suggest that the 241A mutation (blocking the 30 kDa product) increases processing to the larger 35 kDa product, while the 288A mutation decreases processing of the 30 kDa product (also blocking the 35 kDa form). Paired with the lysis data (Figures 2C-2E), its not clear that the 35 kDa product is anything but inactive, but this is quite different from the observations in the experiments with each form (Figure 3N-3Q). A more detailed kinetic and stoichiometric analysis between full-length, N241, and N288 would be important for clarifying the potentially interesting observation of N288 inhibition of N241.

The mechanism of bacteriocidal activity proposed in the final model and by the experiments of Figure 5 would benefit from further development to support the claim. The experiments do not adequately address whether, during pyroptosis, there is release of N241-like fragments that can kill bacteria. Figure 3G would indicate that it stays in the cell, either in the membrane or mitochondria, and it's not clear there would be circumstances where it could be extracted from it to then target bacteria. Figure 5B might require additional explanation and analysis, but the appearance of similar colonies between conditions would appear to support that there is not measurable antibacterial activity. More rigorous support would come from differences in bacterial killing by knockout Callorhinchus cells, but a minimal step to demonstrating the relevance would be MIC assays, and connecting the effective concentration with one that could naturally occur in Callorhinchus.

Broadly, the methods of reconstitution of components of this system demonstrate the sufficiency of LPS for activating Casp1, and Casp1 for activating GSMDA/B. However, in more established models, it is clear that there are inhibitors, feedback mechanisms, alternative pathways, and regulation that could render these interactions irrelevant in Callorhinchus. For example, it's not clear where Casp1 and GSMDA/B are ever expressed in the same cell, at quantities sufficient for this mechanism, or that Casp1 doesn't induce more rapid death by acting on something other than GSDMA/B, or that Casp1 is irrelevant because GSDMA/B can be activated more readily by another mechanism. Therefore, while the insights into the evolution of the individual factors of GSDMA/B and Casp1 are interesting and of potential value to the field, reconstituting choice components by transfection of human HeLa and HEK293 cells introduces limitations to how far these experiments can be interpreted as a system. The abstract, for example, states this is a "pyroptosis pathway in cartilaginous fish". However, for all the interest of these data in the evolution of these proteins, the evidence falls short of this. It establishes a biological potential, but it's not clear this is an active pathway in fish.

Reviewer #2 (Public review):

Summary:

This paper presents theoretical and empirical insights into the use of multi-task batteries for precision functional brain mapping and offers practical guidelines for optimal task design. Specifically, the authors evaluate differences between single-contrast and multi-task localizers, explore data-driven strategies for battery selection, such as minimizing collinearity, and compare grouped and interspersed stimulus-presentation designs. Through a combination of simulations and analyses of empirical fMRI data, the study provides a systematic set of recommendations for improving the reliability and specificity of individualized functional mapping.

Strengths:

Traditional functional mapping has long relied on single-contrast localizers or resting-state fMRI. However, there is growing recognition that diverse batteries of general tasks can yield more detailed functional maps with higher signal-to-noise ratios (SNRs). This manuscript systematically evaluates these advantages using both simulations and empirical data. The contribution is timely and provides the community with not only a theoretical justification for multi-task designs but also practical tools, in the form of the MultiTaskBattery toolbox, for implementing them.

Weaknesses:

Although the results are robust, they are largely consistent with existing expectations in the field, and the conceptual novelty or "surprise" factor is therefore somewhat limited. Nevertheless, synthesizing these findings into a coherent set of design recommendations provides significant value to researchers.

Additionally, there appears to be a slight mismatch between the content of the manuscript and its designated article type. Although the manuscript was submitted as a "Tools and Resources" article, its extensive empirical analyses and theoretical evaluation make it read more like a "Research Article." I defer this categorization to the Editor's judgment.

Finally, the authors use inter-subject overlap as a primary metric for validating the accuracy of functional mapping (Figure 3). However, given that genuine inter-individual variability in brain organization is a central premise of precision mapping, greater overlap across subjects may not necessarily indicate more accurate individual-level localization. A more detailed analysis or discussion of how to distinguish measurement noise from genuine individual differences would make the paper more comprehensive and strengthen its overall contribution.

Reviewer #2 (Public review):

Summary:

Two types of Schwann cells (SCs) ensheath motor axons - myelinating SCs along the axonal length and terminal SCs (tSCs) that cover nerve terminals at the neuromuscular junction (NMJ). Therefore, the NMJ is, like other synapses, tripartite, with specialized presynaptic, postsynaptic, and glial cells. Many studies have shown that tSCs play roles in the development and function of the NMJ, but for some of these, interpretation is difficult because it is hard to manipulate tSCs without also manipulating myelinating SCs. To circumvent this problem, Kong et al. make use of a gene selectively expressed in tSCs, Col20a1 (Figure 1), to generate a knock-in mouse line, Col20a1-CreER, that gives them genetic access to tSCs. They cross this to Cre-dependent lines that mark tSCs with a red fluorescent protein (Figures 2 and 3) or ablate them by expression of diphtheria toxin along with the fluorescent protein (Figure 4). They show that ablation at postnatal day (P) 10 does not affect the overall structure or function of the NMJ (Figures 4 and 5). It does, however, affect some aspects of neuromuscular transmission over the following few weeks (Figures 6 and 7). Long-term effects cannot be studied by this method, however, because terminal SCs are replaced, presumably from the preterminal population (Figure 8).

Strengths:

The work is done to a high technical standard, including detailed characterization of the knock-in model. Results are presented clearly and illustrated beautifully. The finding that some early reports of synaptic alterations may result from concurrent loss of axonal SCs is important in rethinking the role of tSCs.

Weaknesses:

(1) The authors claim that tSCs are dispensable for some aspects of NMJ maturation, including synapse elimination (called pruning here), formation of "pretzel-like" postsynaptic topology, and generation of junctional folds in the postsynaptic membrane (lines 223 and 363). However, this conclusion is based on injection of tamoxifen to initiate tSC ablation at P10, which is necessary because Col20a1 is expressed in some preterminal SCs at earlier times. It presumably takes a few days for CreER to translocate to the nucleus and activate the toxin transgene, and some more time for the toxin to be generated and act. This is problematic because synapse elimination and other aspects of maturation mentioned occur during the first two postnatal weeks and are largely complete by P14. Therefore, one cannot conclude that these aspects "proceeded normally despite the loss of tSCs....".

(2) Effects on synaptic transmission are modest at best, being significant at a level of p<0.05 but not p<0.01 (Figure 6E, G, H and most of L). Effects on vesicle density are more robust (Figure 7).

(3) The authors use red fluorescent protein from the Col20a1 to label tSCs, and antibodies to S100b to label all SCs. This is appropriate in normal muscle and soon after tSC ablation. At later times, however, the NMJ is repopulated by S100+ Col20a1- SCs (Figure 8B). It is therefore important to show when this repopulation begins, because a modest recovery of SC coverage could have a big effect. For example, Figure 4C quantifies loss of NMJs with residual RFP+ cells but not S110+ cells; both should be quantified at this and slightly later stages.

Reviewer #2 (Public review):

Summary:

Genes associated with risk for a specific disease commonly have widespread expression and functions across the body. Surveying patterns in these effects may reveal novel mechanisms, organs, and systems implicated in a disease, amongst other associations that are truly independent. In this work, Husen and coauthors use the Human Protein Atlas to explore such associations in Alzheimer's disease (AD), Lewy body dementia (DLB), and Frontotemporal dementia (FTD). Focusing on human non-disease tissue expression may avoid the effects of disease progression obscuring initial vulnerabilities. However, associations in non-diseased tissues do not necessarily reflect mechanisms causally related to the diseases themselves.

The work describes patterns of enrichment of genes across tissue types, brain regions, and cell types. A relatively small set of classes of each show enrichment for disease. While neural signatures are unsurprisingly prevalent, these classes are largely distinct across the three diseases. Alzheimer's disease is linked to liver and central and peripheral immune cells, while DLB shows interesting enrichments associated with cilia, which are linked to an existing literature. Results from the drug repurposing approach are then presented, with 1777 drugs linked to protein products of any of the modules enriched by the risk genes using DrugBank, categorised according to key signatures.

The authors developed R code (the HPA GeneSet Explorer) to automate the production of multi-system summaries of the organs, brain regions, cells and gene modules associated with traits and diseases and associated gene sets, within the HPA. Risk gene sets for the three dementia types were derived from the GWAS Catalog.

Strengths:

While many studies of how risk genes contribute to disease take a narrow approach focusing on organs, cell types, and processes already associated with a disease, it is a sensible approach to start with a system-agnostic approach that assesses tissues that are not ostensibly affected by disease. Here, this approach reveals a range of associations for 3 neurodegenerative diseases, identifying disease-associated modules and drug candidates that might be prioritized for subsequent confirmatory inference across biological scales. Results highlight key organs and cell types, most of which have established associations with the disease. Perhaps the most intriguing results are the links of DLB to cilia-related processes, which can be linked to some prior reports of DLB/PD but are not a core element of current theories of pathogenesis.

Weaknesses:

A difficulty with broad, multi-dataset surveys of disease associations is the need to distinguish novel and robust patterns - even if they lack causal evidence - from those that are unsurprising or do not stand out statistically. The work is exploratory in nature, but it is often hard to know how strong the evidence is for particular observations reported.

The work combines nominal, FDR<0.1, and Monte Carlo-based inference (with no apparent multiple assessment control across all tested modules) p-values throughout the paper, with patterns of effects of nominal significance. In some places, modules appear to be retained if they meet any of these criteria, muddying inference. This makes it difficult to weigh the different reported associations. Results report numbers of risk genes showing nominal p<0.05 enrichment across gene modules and biological scales - it is difficult for the reader to determine null expectations for false positives here. Similarly, it is unsurprising that thousands of drugs can be linked to the risk genes and their signatures using nominal significance.

The results have limited mechanistic specificity. The modules identified often reflect biological processes implicated in the diseases. This provides some validation of the approach, but the modules are often broadly defined, providing little mechanistic insight. For example, many aspects of ciliary biology may overlap with DLB, but can the HPA provide more specific insight? More generally, it is difficult to determine how much relevance that enrichment in non-disease tissue has for disease processes. Similarly, it is hard to determine whether overlap of drug targets from DrugBank with these modules realistically increases their prioritization.

Methodologically, there could be more detail. The paper - in particular the methods - is partially presented as a tool/pipeline paper, but thorough descriptions of the HPA models that are employed and modules reported for the analyses should still be presented in detail. The drug repurposing approach is described in a couple of sentences without a precise reference to the tool or statistical methods.

Reviewer #3 (Public review):

Thapliyal, Gopinath, and Glauser show that starvation alters how C. elegans respond to noxious thermal stimuli. Using targeted neural ablation, mutant analysis, and live-cell functional imaging the authors demonstrate that hunger changes the properties of AWC sensory neurons, which sense noxious heat. The authors further show that effects of hunger on nociception require ASI neurons, which are known to respond to hunger and mediate effects of food deprivation on behavior. Finally, the study uses mutant analysis to implicate glutamate and specific neuropeptides in thermal nociception and in modulation of nociceptors by hunger-responsive neurons.

The study clearly shows a strong effect of hunger on nociception and documents a striking effect of hunger on the intrinsic properties of AWC sensory neurons, which respond to noxious heat. The study also clearly and compellingly demonstrates that ablation of hunger-responsive ASI neurons blocks effects of hunger on nociceptive AWCs. These data, which constitute the kernel of the manuscript, are striking and exciting. This revised manuscript analyzes effects of starvation on AWC physiology and clearly shows that starvation alters the way AWCs respond to thermal stimuli by decreases the probability that AWCs will be activated and increases the probability that they will be inhibited. New data also identify ASI-derived neuropeptides that are required for modulation of AWCs by starvation. This study reveals a mechanistic link between an animal's metabolic state and sensory processing and establishes modulation of AWC function as a powerful model to study the molecular basis of this link.

Reviewer #2 (Public review):

Summary:

The authors used whole-network imaging to identify sensory neurons that responded to the repellant 1-octanol. While several olfactory neurons responded to the initial onset of odor pulses, two neurons consistently responded to all the pulses, ASH and AWC. ASH typically activates in response to repellants, and AWC typically activates in response to the removal of attractants. However, in this case, AWC activated in response to the removal of 1-octanol, which was unexpected because 1-octanol is a harmful repellant to the worm. The authors further investigated this phenomenon by testing different concentrations of 1-octanol in a chemotaxis assay and found that at lower (less harmful) concentrations the odor is actually an attractant, but becomes repulsive at higher concentrations. The amplitude of the ASH response appeared to be modulated by concentration, but this was not true for AWC. The authors propose a model where the behavioral response of the worm is the result of integrating these two opposing drives, where repulsion is a result of the increased ASH activity over-riding the positive drive from AWC. The authors further tested this theory by testing mutants that ablated the AWC response (tax-4 or AWC::HisCl) or ASH response (osm-9 or ASH::HisCl). The chemo-silencing (HisCl) and tax-4 experiments were consistent with their hypothesis, while the osm-9 mutation had a limited impact on chemotaxis behavior, highlighting the potential role of osm-9-independent signaling in ASH in response to 1-octanol. While the interneuron(s) that integrate these signals to influence behavior were not identified, the authors did find that increasing concentrations of 1-octanol did increase the likelihood of AVA activity, a neuron which drives reversals (and hence, behavioral repulsion).

Strengths:

This was simple and elegant work that identified specific neurons of interest which generated a hypothesis, which was further tested with mutants that altered neuronal activity. The authors performed both neuronal imaging and behavioral experiments to verify their claims.

Weaknesses:

The authors note that other sensory neurons likely contribute to 1-octanol chemotaxis. Given the NeuroPAL data, it would have been nice to identify these other neurons as well. However, the reviewer is aware that this is tangential to the primary focus of this study.

Reviewer #3 (Public review):

Summary:

In the manuscript by Greter, et al., entitled "Targeted induction of gut-microbial metabolism acutely affects feeding patterns and clock gene expression in the host" the authors investigate whether acute exposure to a non-nutritive disaccharide (lactulose) promotes microbial metabolism that feeds back onto the host to impact circadian networks. The premise of the study is interesting, and the experiments are thoughtfully designed to dissect these relationships. The evidence presented generally supports the authors' conclusions regarding the impact of lactulose administration during the fasting period, which is intended to mimic a feeding-associated perturbation of the gut microbiota, and its comparison with lactulose administration during the fed state. The studies employ complementary model systems, including germ-free mice, mice colonized with a simplified three-member microbial community, and conventionally colonized animals. These approaches support the authors' conclusions regarding the relationship between diurnal rhythms of microbial fermentation and host circadian clock gene networks. Overall, the work provides a useful experimental framework for developing a deeper mechanistic understanding of how microbial fermentation products contribute to diurnal host-microbe interactions.

Strengths:

Attempting to disentangle nutrient acquisition from microbial fermentation and its impact on diurnal dynamics of gut microbes on host circadian rhythms is an important step for providing insights into these host-microbe interactions.

The authors utilize a novel approach in leveraging lactulose coupled with germ-free animals and metabolic cages fitted with detectors that can measure microbial byproducts of fermentation, particularly hydrogen, in real time.

The authors consider several interesting aspects of lactulose delivery, including how it shifts osmotic balance as well as providing calculations that attempt to explain the caloric contribution of fermentation to the animal in the context of reduced food intake. This provides interesting fundamental insights into the role of microbial outputs on host metabolism.

The authors employ complementary systems, including a simplified three-member microbial community, providing insight into the minimal set of functionally distinct community members necessary to promote the rhythmic production of fermentation products that can affect host physiology.

Residual limitations:<br /> Hypothesis and study framing: The manuscript still does not clearly articulate a specific, testable hypothesis. While the Introduction provides motivation and objectives (e.g., line 53 onward), it remains unclear what precise hypothesis was being evaluated. A more explicit statement would strengthen the conceptual framework of the study.

Interpretation of circadian gene expression changes: The authors have not fully reconciled the differing effects of lactulose treatment on circadian gene expression in the 3MM and SPF settings. In particular, it remains unclear how the increased expression of certain circadian genes observed in lactulose-treated 3MM mice, particularly Cry1, relates to the decreased expression seen in SPF mice, and how the reduction in Arntl expression observed in lactulose-treated SPF mice fits within the proposed model. The authors acknowledge that resolving these mechanistic differences is beyond the scope of the current study, but the limitation should be discussed more explicitly.

Reviewer #2 (Public review):

Summary:

In this manuscript, Koh and colleagues describe ADePT (Axially Decoupled Photo-stimulation and Two-photon Readout), a modular approach for combining patterned one-photon optogenetic stimulation with two-photon calcium imaging in independently controlled axial planes. The method relies on a digital micromirror device together with a motorized holographic diffuser to generate spatially confined stimulation patterns while imaging deeper neuronal populations. As proof-of-principle applications, the authors use the system to map excitatory and inhibitory functional connectivity in the mouse olfactory bulb by stimulating superficial glomerular circuits and recording responses from mitral and tufted cells in deeper layers.

This is a well-executed Tools and Resources manuscript. The technical implementation is described in considerable detail, the optical performance is systematically characterized, and the biological experiments provide convincing demonstrations of the types of circuit questions that can be addressed using the method.

Strengths:

The greatest strength of the manuscript is the comprehensive technical characterization of the optical system. The authors carefully benchmark the spatial resolution, axial confinement, registration accuracy, calibration procedure, and practical operating limits of the setup. I found the extensive optical benchmarking particularly helpful, as it gives readers a realistic sense of the operating regime and practical limitations of the approach.

Another strength is the high level of methodological transparency. The optical design, calibration procedures, stimulation strategies, and analysis pipeline are described in sufficient detail that an experienced laboratory could realistically evaluate whether the system is suitable for its own applications. This level of documentation is particularly appropriate for a Tools and Resources article.

A further strength is the clear positioning of ADePT relative to existing approaches. The authors are transparent about the trade-off between spatial resolution and implementation complexity: ADePT does not provide single-cell photostimulation, but offers flexible axial separation, a large stimulation field, and cellular-resolution two-photon readout in deeper planes without requiring a full holographic stimulation system. This defines a credible and potentially useful experimental niche.

The biological applications convincingly demonstrate the utility of ADePT. The experiments identifying sister mitral/tufted cells through selective glomerular stimulation and the mapping of heterogeneous inhibitory influences from DAT-positive interneurons illustrate the types of functional connectivity questions that become experimentally accessible with this approach. Importantly, the authors generally avoid overstating these biological findings and appropriately present them as proof-of-principle demonstrations of the technology.

Weaknesses:

The primary limitation is inherent to the method itself rather than the execution of the study. Because ADePT relies on one-photon patterned illumination, photo-stimulation remains restricted to relatively superficial structures and does not achieve single-cell spatial resolution. The authors appropriately acknowledge these constraints and clearly position the method within this operating regime. Consequently, ADePT occupies a useful niche for interrogating spatially organized functional units such as olfactory glomeruli or cortical barrels, rather than applications requiring single-cell precision or deeper tissue penetration.

Although the manuscript describes the approach as relatively simple and cost-effective, implementation still requires careful optical alignment, registration, calibration, and optimization. This does not diminish the value of the approach, but terms such as modular or accessible may better reflect the practical implementation than simple. Likewise, a brief bill of materials, approximate add-on cost, and indication of which components are essential versus substitutable would help prospective users assess the accessibility of the system.

Finally, the manuscript provides an impressive level of technical characterization, but much of the practical guidance for adopting the system is distributed across the Results and Discussion. Bringing together the principal limitations, recommended operating regime, expected calibration workflow, evidence for long-term alignment stability, and the circumstances in which ADePT is preferable to alternative approaches would further strengthen the manuscript as a community resource.

Reviewer #2 (Public review):

Summary:

The main contribution of this study is that brain activations related to linguistic context varied as a result of presentation speed, with the main finding that increased activity for coherent stories relative to other conditions was reduced in fast presentation relative to slow. The results thus challenge certain assumptions about the nature of the brain dynamics of language processing, with certain effects even disappearing under faster presentations, which may be related to the processing mode of the participant. The results continue to establish the viability of a parallel presentation design, which generally produces results congruent with those of the literature.

Strengths:

The study contains a somewhat novel presentation method, illustrating its viability. The results are bolstered by a strong sample size (N=33) and robust analytic techniques. The conclusions are measured and appropriate to the results, and the manuscript is exceedingly clearly written and accessible to readers.

Weaknesses:

The spatial specificity of the effects is hampered by the use of MEG, particularly with minimal structural MRIs for participants. Thus, the conclusions of the study in the spatial domain are tentative and more general than might result from other studies.

In addition, the general finding that faster presentation speed reduced activity overall (and eliminated it in the frontal cortex) appears to be somewhat contradictory to existing literature, which finds that sentences which are complex or difficult to process generally produce greater activation, particularly in the frontal cortex. These studies might be reviewed, and this (seeming) contradiction could be addressed.

Reviewer #2 (Public review):

Summary:

Chen et al. consider the activity of retrosplenial cortex (RS) neurons during performance of an open-field navigation task in mice. Using a Ca-++ transient imaging approach to examine activity, the authors claim to find tuning to distance of the animal to a hidden reward location. The question of tuning to distance in RS is of much interest of late, with other works making claims. In this respect, the present work is interesting in that it utilizes an actual navigational task that does not explicitly demand encoding of distance and does consider an open-field environment. I do have reservations concerning the robustness of distance tuning.

Strengths:

Testing of distance coding in open fields during performance of an actual navigational task.

Weaknesses:

Lack of robust evidence for distance coding and head direction coding.

Reviewer #2 (Public review):

Summary:

The vertebrate spinal cord receives inputs from many supraspinal regions. The authors used optical backfilling to trace neurons in the zebrafish larval brain sending axons to the spinal cord. With two-photon microscopy, they managed to render a comprehensive 3D map of these neurons and drew homologs with mammalian brain structures.

Strengths:

The main strength lies in the precise 3D mapping. The fact that most of the previously reported neuron groups have been confirmed by their approach is a solid endorsement of their methodology.

This study provides a comprehensive alternative anatomical reference framework for studying individual groups of supraspinal neurons with projections to the zebrafish spinal cord.

Weaknesses:

The whole approach could be enhanced by counter-staining their preparation to profile brain structures, including many nuclei more precisely.

Also, the backfilling approach does not reveal the full trajectories of axons, which is already available to some degree by ZExplorer Atlas.

Reviewer #2 (Public review):

In this work, Alamdari et al. present EvoDiff, which provides the capability to generate protein sequences directly in sequence space, using a discrete diffusion model. There are several versions. EvoDiff-seq is trained on UniRef50 sequences (~42 million), and EvoDiff-MSDA operates instead by using sequence alignment methods to generate new members of protein families. The authors demonstrate many modes of sequence generation, including unconditional and conditional, inpainting of disordered regions, and also generating scaffolding of functional motifs. Their evaluation is also multifaceted, covering foldability, folding self-consistency, language embeddings, secondary structure distributions, and experiments for a set of different scenarios.

The paper has many notable strengths. It is comprehensive in breadth, and the experimental component is distinctive, although I am not personally suited to review the rigor of that element.

I would suggest that the paper's results certainly support the conclusion that order-agnostic sequence generation can yield useful candidates for multiple conditional design tasks. I am not totally convinced that it necessarily establishes diffusion as a generally superior approach to other competitors, like the conventional protein language models- EvoDiff is certainly competitive, and I think that the demonstration of diffusion is nice. I also am not sure that it is fair to say that sequence alone is sufficient for the broad design capabilities claimed (other than the "in principle" statement).

I am overall quite supportive of the work and its demonstration, but I have a few comments for consideration in any revision.

(1) I did not work through all dates of everything, but it appears to me that there are several recent conceptual and methodological competitors. These include DPLM and ProtBFN - both of these seem to be after the first preprint of EvoDiff, but given the time gap, there probably deserves to be some additional discussion or comparison. I would say, ideally, they should offer direct benchmarking. If the authors are disinclined, then I would think they should just temper their claims of contemporary SOTA performance or general superiority. Instead, the paper would still remain valuable as an early and experimentally demonstrated sequence diffusion framework. I don't think it needs to be more than that.

(2) Related to the above, the manuscript should more carefully distinguish the demonstrated advantage of order-agnostic generation from the quality of unconditional generation. Regarding Figure 3, the authors argue that Evodiff's diffusion objective is necessary, but this does not seem to account for or address the LRAR baselines in Tables S1 and S3. Unless I am misunderstanding, the 640M LRAR model exhibits several better scores. The authors later suggest that EvoDiff's principal advantage is conditioning on arbitrary positions, which is valid, but that's a little different that what is being claimed. I suggest that the LRAR results should be shown or discussed alongside Figure 3, and then the authors revise to say that they have flexible conditional generation as the principal empirical benefit.

(3) I really like the IDR experiment, but I'm not sure it demonstrates that Evodiff can design functional IDRS generally. Cox15 is a favorable target because its mature sequence strongly identifies a conserved mitochondrial protein, and EvoDiff-MSA is supplied directly with its orthologous family. The eight tested sequences were also selected from hundreds of candidates using both DR-BERT and MitoFates, making the experiment a test of the full generation-and-prediction pipeline rather than of EvoDiff alone. Moreover, mitochondrial targeting is tested, but the disordered character of the generated sequences is not experimentally established. In any case, I think it would certainly be more convincing if there were other examples, with unrelated proteins or IDR functions. I would appreciate that this is again a step beyond what the authors might be compelled to do, but their claim could be simply more calibrated.

(4) The authors might benefit from explaining the advantages or complementarity of EvoDiff to other property-directed approaches for exploring sequence space. This has been done, for example, by using Bayesian optimization and genetic algorithms to tune properties of IDP condensates (DOI: 10.1021/acs.jpcb.8b03822). In my understanding, these are addressing a different problem from EvoDiff by optimizing sequences explicitly towards physical targets, while EvoDiff is a generative framework that can be used for sampling/inpainting/ etc. Is it clear how these strategies might be plausibly integrated? If so, that would be a relevant point of discussion and a potential advantage for EvoDiff.

Reviewer #2 (Public review):

Summary:

Studies in rodents have demonstrated that early life adversity (ELA) impacts many aspects of the exposed offspring's brain and behavior. Work in this field has traditionally focused on how<br /> stress in very early life can impact cognitive and emotion-related behaviors in the ELA-exposed offspring. By contrast, this manuscript focuses on how stress in a slightly later adolescent period can produce latent and intergenerational effects by impacting maternal caregiving from female offspring, as well as social outcomes of the next generation of animals born to ELA-exposed females. Specifically, the manuscript describes that female mice exposed to ELA in the form of social isolation in late adolescence show reduced pup-directed maternal behaviors, while self-directed behaviors remain intact. Offspring reared by these dams in turn show deficits in social behavior, which are linked to reduced activity in an excitatory connection between the medial cingulate cortex (mCg) and prelimbic cortex (PrL). Further, the authors find that social behavior can be rescued by chemogenetic activation of the mCg-PrL pathway in the offspring of ELA-exposed/stressed mice or recapitulated in control mice by chemogenetic inhibition of this connection. Importantly, co-housing ELA-exposed/stressed dams with experienced parous females during the early postpartum period restores pup-directed maternal behaviors in these mice and normalizes offspring social outcomes as well as mCg-PrL activity.

Strengths:

Strengths of the manuscript include the focus on an important and novel question about intergenerational effects of adolescent ELA transmitted via subsequent maternal care, and the use of multiple techniques to link circuit function to behavior, including slice electrophysiology and chemogenetics. While the findings that maternal care can influence offspring behavior and that experienced females can instruct and improve maternal care of less experienced mice are not novel, they add support to this important area of literature.

Weaknesses:

Weaknesses of the paper include the lack of validation that the viral chemogenetic paradigm was appropriately targeted in the brain and impacted the excitability of mCg to PrL projections as anticipated, the use of inappropriate statistical tests that do not account for non-independence of pups from the same litter or cells measured from the same pup or categorical versus continuous data, and the lack of important descriptions of methods or experimental paradigms in several places that altogether make it difficult to judge the rigor of the findings in its current state.

If these weaknesses are addressed, these findings will provide important information about circuit mechanisms underlying intergenerational effects of adolescent stress on social behavior in next-generation offspring.

Reviewer #2 (Public review):

Summary:

In this study, Nollet and colleagues sought to determine whether selective amyloid pathology confined to medial septal (MS) cholinergic neurons is sufficient to recapitulate the prodromal Alzheimer's disease-like phenotypes observed in global AppNL-G-F knock-in mice. To this end, the authors employed a cell-type-specific AAV-mediated approach to selectively express the familial AppNL-G-F allele in MS-ChAT neurons, and subsequently characterized sleep-wake architecture, EEG spectral features, cognitive function, emotional behavior, and histological changes over 13-14 months. By comparing these mice with global AppNL-G-F knock-in mice and with mice in which MS-ChAT neurons were selectively ablated via caspase expression, the authors found that cholinergic cell lesioning recapitulated most disease phenotypes, suggesting that cholinergic loss, rather than amyloid deposition, is a likely driver of these phenotypes.

Strengths:

The study has several notable strengths. First, the experimental design is rigorous and well-controlled, employing three complementary mouse models that enable elegant causal inference. The use of cell-type-specific APP expression is a powerful approach for distinguishing the contributions of MS-ChAT neurons and amyloid deposition. Second, the combination of multiple behavioral assessments, EEG spectral analysis using FOOOF parameterization, and detailed histological quantification strengthens the validity of the conclusions. Third, the finding that caspase-induced cholinergic lesions largely recapitulate the cognitive and REM sleep phenotypes, while amyloid pathology contributes additional features such as epileptiform spikes and astrogliosis, represents an important mechanistic dissection.

Weaknesses:

Despite the overall strength of the study, several limitations warrant consideration. First, the mechanism by which amyloid is "broadcast" from MS-ChAT terminals to distant brain regions remains unclear. The authors do not definitively determine whether the amyloid detected in hippocampal and cortical regions represents released soluble Aβ, transported APP fragments, or amyloid derived from degenerating axons. Second, while the authors demonstrate that MS-ChAT cell loss correlates with cognitive, emotional, and REMS deficits, the causal relationship among these phenomena and the specific circuits involved remains unresolved.

Reviewer #2 (Public review):

Summary:

To address how the CHIKV macrodomain contributes to replication dynamics in mammalian and insect hosts, the authors initially created two separate mutations in the highly conserved N24 residue, which is known to be critical for the CHIKV macrodomain's ability to erase ADP-ribose from target proteins. Interestingly, they could not produce a virus with a mutation in this residue without second-site mutations in an aspartic acid residue nearby (D31). However, when tested biochemically, these second-site mutations did not enhance the enzymatic activity of the protein, indicating that other enzyme dynamics, such as substrate binding, may be impacting these mutations. Mutations at this residue allowed the CHIKV to replicate in Vero cells and in mosquito cells, but they replicated poorly in IFN-competent human cells, indicating clear IFN-specific impacts on these viruses. Interestingly, they found unique impacts on virus dissemination and replication in live mosquitoes. While the N24A/D31N virus did poorly in vivo in all accounts, the N24D/D31H/N virus tended to infect both the bodies and heads of the mosquitoes better than the WT virus, though titers were reduced. The authors claimed, based on a DSF assay, that there were no real differences in ADP-ribose binding and thus suggested that these differences could be due to changes in substrate specificity, as the D31 residue resides in the substrate exit path, potentially tuning the virus to unique substrates in different species. The authors also produced crystal structures of the mutants to demonstrate the changes in the binding pocket caused by these mutations.

Strengths:

The authors have done a rigorous job of evaluating CHIKV macrodomain mutant viruses and the proteins' biochemical activities. The use of live mosquitoes is highly unique and provides important insights into the importance of the macrodomain in different species.

Weaknesses:

It is not clear if the interpretation of the ADP-ribose binding data is correct. It appears there are notable differences that could explain the results, though the authors chose to minimize the impact that these differences had on the results. The N24D-D31H/N proteins had at least a 1C degree difference in the thermal shift assay when compared to the N24A/D31N, single D31 mutants, and WT proteins, which is likely significant and could explain the dichotomous results between the two viruses in mosquito cells. Even the single N24D mutant had enhanced binding compared to the WT protein. Furthermore, as this virus has no enzymatic activity, one could hypothesize that enhanced binding to a substrate that is normally cleaved by the protein could certainly lead to alterations in phenotypic effects, whether good or bad. The authors should test the binding activity in a separate assay, such as an ITC assay, to determine if there are, in fact, binding differences or not. Having said this, it is likely that the impacts of these mutations on replication and transmission in human and mosquito cells are multi-factorial and could include both enhanced binding with altered substrate specificity amongst other activities.

Additionally, as both mutants had no detectable enzymatic activity but had quite different phenotypes in mosquitoes, I don't agree with the title stating that catalytic activity modulates dissemination and transmission potential in mosquitoes. It seems more likely that alterations in binding activity or substrate recognition (even suggested by the authors) impact these phenotypes in mosquitoes.

Reviewer #2 (Public review):

Summary:

This manuscript presents an interesting and conceptually valuable analysis of compensatory evolution using a large combinatorial deep-mutational-scanning dataset for yeast His3p.

Strengths:

I particularly like the identification of "super compensatory" substitutions that improve fitness across diverse genetic backgrounds and apparently reduce the sensitivity of the local fitness landscape to subsequent mutations. The work connects epistasis, protein stability, mutational robustness, and evolvability in a clear and potentially broadly relevant manner.<br /> The authors provide several complementary lines of evidence in support of this central conclusion. In particular, the new experimental validation of S189A is an important strength because it directly demonstrates that a predicted super compensator can buffer the effects of diverse deleterious substitutions, while analyses of additional DMS datasets from other proteins and assay systems suggest that the phenomenon is not restricted to the original His3p landscape.

Weaknesses:

The structural analysis currently relies primarily on correlations with RSA, weighted contact number, conservation, and Rosetta-predicted changes in folding or binding energy. For super compensators, the mechanistic evidence is largely limited to predicted stabilization and individual examples, such as the proposed salt bridge between 110D and R112. I believe that the newly developed structure-aware deep-learning approaches could provide useful information on the mechanism of super compensators. For example, an inverse-folding model such as ESM-IF1 could score complete multi-mutant sequences conditioned on the His3p backbone and test whether adding a super compensator restores sequence-structure compatibility across backgrounds. More recent multimodal mutation-effect or stability models could similarly be used to cross-check the Rosetta results, including models that explicitly support combinatorial mutations. I would not recommend simply comparing AlphaFold confidence scores between mutants, because current structure predictors are not necessarily sensitive to subtle mutation-induced energetic or conformational changes.

The manuscript states that the pipeline was applied to 217 ProteinGym datasets and concludes that super compensators are broadly distributed across proteins and assays. However, this central generalization is described in only a few sentences and is largely relegated to Figure S7. The Methods do not explain which datasets contained sufficient combinatorial mutants to calculate compensatory ability or buffering, how many genotype pairs or quadruplets were available per substitution, or how differences in assay scale and library design were handled. This point requires clarification because supercompensation is inherently a background-dependent property and cannot be established from single-mutant measurements alone. ProteinGym is widely used as a substitution-effect benchmark, and many of its constituent assays primarily contain single substitutions; for example, an analysis of an earlier ProteinGym collection reported that 76 of 87 assays contained only single substitutions. It is therefore unclear how the same compensatory-interaction pipeline could be applied uniformly to all 217 datasets.

The analysis of 335 His3p orthologs in Discussion is potentially very interesting, but co-occurrence between super compensators and putatively deleterious amino-acid states does not by itself demonstrate evolutionary compensation. Closely related species share substitutions through common ancestry, and both states could be associated with a particular lineage or ecological context. A tree-aware analysis would considerably strengthen this result. The authors could reconstruct ancestral states and ask whether acquisition of a super compensator tends to precede or accompany otherwise deleterious substitutions. Alternatively, they could use phylogenetically informed permutations that preserve substitution frequencies and shared ancestry.

Reviewer #2 (Public review):

This study addresses an important question in motor learning: whether algorithmic versus retrieval-based explicit strategies differentially shape implicit recalibration. The progressive experimental logic across three experiments is commendable, and the plan-based generalization account is a plausible and interesting interpretation. However, several methodological concerns limit the strength of the conclusions. I recommend the authors temper their claims accordingly, in the results/discussion section.

Concerns

(1) The retrieval group received 5 pre-exposure trials before main training began, which the algorithmic group did not. Faster RTs in the retrieval group could therefore reflect task familiarity from extra practice rather than efficient memory retrieval per se. I might have missed this, but I did not see performance data from these pre-exposure trials. The early training advantage in the retrieval group might be confounded with the 5 pre-exposure trials they received. Unless there is a direct comparison between the pre-exposure trials for the caching group and the first 5 trials of the algorithmic group, the claim that "storing and retrieving a memory from a short-term memory cache confers more rapid performance improvements than executing an algorithmic strategy" seems somewhat unwarranted.

The algorithmic group also visited the critical target approximately 40% of trials across 356 trials (about 140 trials?). McDougle & Taylor (2019) showed that 300 trials of practice with 2 targets is enough transition from algorithmic to caching strategies. It seems likely that the number of visits to the critical target here was sufficient for caching to develop in the algorithmic condition. This concern about caching in the algorithmic group has implications for the implicit recalibration measurements. As I understand it, the 7 exclusion blocks were distributed throughout training, and so, implicit recalibration was measured across both early and late practice. If caching emerged in the algorithmic group during late practice, then the generalization functions - averaged across all 7 exclusion blocks - conflate early algorithmic strategy and later caching. The broader generalization function observed in the algorithmic group may therefore be driven primarily by early exclusion blocks, while later exclusion blocks may increasingly resemble the retrieval group as caching develops. This is testable in the data: if generalization breadth in the algorithmic group narrows across the 7 exclusion blocks while remaining stable in the retrieval group, that would be consistent with a strategy transition occurring during training. The authors should either report exclusion block-by-block generalization functions separately for each group, or acknowledge that the averaged generalization functions may obscure a strategy transition in the algorithmic group.

(2) The error-clamp paradigm in Experiment 3 introduces two problems. First, it breaks the relationship between planned movement direction and feedback of movement direction, likely reducing the sense of agency over movement feedback (indeed, typical error clamp study instructions tell participants to ignore the movement feedback).

Reduced agency may itself suppress differences between algorithmic and caching conditions. First, if strategy type exerts its influence on implicit recalibration via the explicit plan - as the plan-based generalization account predicts - then severing the link between intended movement and feedback might close off the channel through which strategy could shape the implicit system, regardless of which strategy is used. Second, reduced agency could modify the explicit strategies themselves. For caching, the stimulus-response association might be reinforced by a consistent relationship between intended movement and observed outcome; the clamped feedback may make it more difficult to reinforce the cached response, weakening the stimulus-response association. For the algorithmic strategy, effortful mental rotation may depend on the perception that the computation meaningfully determines the outcome; as participants understand that clamped feedback does not depend on their behavior (although yes, the text-based "Excellent/Good Move feedback) does depend on their behavior, they may engage in somewhat less complete mental rotation. Both possibilities could contribute to convergence between groups in generalization. It is noted that the preserved RT difference between groups in Experiment 3 partially argues against a loss of effort under the algorithmic condition, but it does not rule out weakened formation of stimulation-response associations during caching.

Reviewer #2 (Public review):

In this study, the authors investigate the mechanisms underlying phosphatidylserine (PS) exposure during efferocytosis in Drosophila. They first show that Xkr promotes PS exposure and apoptotic cell clearance in both S2 cells and Drosophila embryos. As Drosophila Xkr lacks the canonical caspase cleavage site found in mammalian XKR proteins, the authors further explore the underlying mechanism by which Xkr regulates PS externalization. Through protein interaction studies, they identify TM9SF4 as an interacting partner of Xkr that regulates PS distribution and show that non-vesicular PS transport contributes to apoptotic PS exposure and efferocytosis. Using protein interaction studies, they further demonstrate that Xkr interacts with the lipid transfer protein dORP9 at ER-PM contact sites to facilitate non-vesicular PS transport to the plasma membrane. Loss of these proteins affects PS externalization and efferocytosis in Drosophila. Finally, using human cells, they demonstrate that human OSBPL8 interacts with XKR8 to regulate apoptotic PS exposure. Overall, the study supports a model in which Xkr promotes efferocytosis by facilitating lipid transport in addition to its role as a phospholipid scramblase.

Reviewer #2 (Public review):

Summary:

In this study, the authors investigate high-frequency oscillations (HFOs) in the prefrontal cortex during REM sleep. They identify a specific pattern where these HFOs occur in "chains" that are phase-locked to theta oscillations, primarily during the "phasic" periods of REM. The study contrasts these events with isolated HFOs and NREM ripples, suggesting a unique role for these chains in coordinating activity between the prefrontal cortex and the hippocampus. Most notably, the authors report that a specific subset of hippocampal cells-those that co-fire with the prefrontal cortex during these HFOs-increase their firing rates over the course of sleep, suggesting a potential mechanism for selective memory consolidation.

Strengths:

The study addresses an under-explored area of sleep physiology: the fine-grained temporal coordination between the cortex and hippocampus during REM sleep. The identification of HFO "chains" and their association with higher theta power provides an interesting framework for understanding how the brain might organize information transfer outside of NREM sleep. The observation that specific hippocampal populations show differential firing rate changes based on their participation in these HFO events is a striking finding that warrants further investigation.

Comments on revised version.

I do have one remaining concern, which is about their continued use of the term "reactivation" during REM sleep, whereas it still seems "activation" is more appropriate. The only place they show more Post vs. Pre activation is in Figure 6F/6G which includes NREM sleep where indeed reactivation is robust (but not the main focus of this paper). There is no evidence offered that the REM ensembles are not already "pre-configured" and active at similar levels (with similar activation patterns) during Pre sleep. Notably Louie and Wilson 2001 found greater "replay" during Pre than Post during REM. Also, the first half vs. second half comparisons (e.g. Fig 6C) could be more effectively performed in Figure 6A, showing that the same ordering persists across the periods. If this point were addressed, the significance of the findings could potentially increase.

Reviewer #2 (Public review):

Summary:

The manuscript by Qin and colleagues entitled "Pupil and Neural Dynamics Reveal Belief-Dependent Decision Making Under Ambiguity" examines decision-making under risk and ambiguity using pupillometry and EEG. The study employs a lottery choice task with three levels of ambiguity (zero, low, high). Participants were classified into three groups based on their choice behavior in a condition with risk and no ambiguity: ideal (choosing in line with objective expected values), aggressive (preference for investments), and conservative (preference against investments). The authors then compared behavior, pupil, and EEG results across these groups. The study concludes that individual beliefs about ambiguity are reflected in different behavioral strategies and neural correlates.

Strengths:

The combination of behavior, computational modeling, pupillometry, and EEG.

Weaknesses:

(1) It is unclear whether group definition is theoretically justified.

One general concern is that the strategy to form three distinct groups is not clearly motivated. The authors created the three groups, "aggressive", "ideal", and "conservative", based on the zero-ambiguity trials. However, as the authors state: "Ambiguity differs fundamentally from risk at both the physiological level (34; 6) and the behavioral level" (page 4). Under this assumption, it is questionable whether forming groups based on risk preferences is a useful strategy for studying ambiguity. What do we learn about ambiguity processing when group differences are primarily based on risk preferences? Might the present results partly be driven by risk preferences rather than ambiguity preferences? I recommend the following two points: (a) Clearly justify the reasoning behind the group approach; (b) Add an additional continuous analysis approach indicating whether the key results hold independent of the group definition based on risky decision-making.

(2) k-parameter.

The authors use the k-parameter that infers the expected high-payoff probability (e.g., page 11). On page 22, this is explained as: "the subjective value term K was assigned according to each participant's internal belief of the high-payoff rate under ambiguity, yielding a participant-specific estimate of expected value under uncertainty." I hope I have not missed anything, but I neither understood the role of this parameter nor how it was computed.

(3) How were individual beliefs and models computed?

A related but more general point is that it remained unclear how the authors computed internal beliefs and internal models in the study. The study contains many statements suggesting that the authors measured internal beliefs. For example:

a) Abstract: "We show that individuals adopt distinct decision strategies that reflect different internal beliefs about unknown outcomes."<br /> b) Page 3: "We then inferred subjective belief parameters that captured how individuals internally interpreted the ambiguous probability mass and examined how these beliefs related to choice behavior, arousal dynamics, and neural activity."<br /> c) Page 16: "Together, these findings show that ambiguity does not evoke a uniform behavioral or physiological response across participants with different decision-making styles; instead, individuals rely on distinct internal models and computational strategies when forming decisions under ambiguity."<br /> d) Page 16: "Taken together, these results show that ambiguity aversion is not a uniform psychological bias, but a set of heterogeneous belief-driven strategies that shape how ambiguity is represented and acted upon."<br /> e) Page 18: "Ambiguity processing, therefore, reflects distinct belief-driven pathways rather than a single canonical mechanism."

Based on the present data, analyses, and results, I don't think that the authors can draw these conclusions. Which analyses in the manuscript identify these internal beliefs, models, or strategies? How can we dissociate a unified strategy from a heterogeneous set of strategies based on the present results? My feeling is that the k-parameter might be related to this, but as explained above, I did not understand how it was computed and what it is supposed to reflect. The DDM analyses might also be targeted at this. However, it remains elusive how the DDM captures internal beliefs about ambiguity itself. My recommendation is that the authors more clearly explain (a) why the DDM is a useful model to study ambiguity, (b) what the different parameters exactly reflect about ambiguity processing, and (c) how the DDM captures internal beliefs and distinct belief-driven strategies in this context.

(4) Statistical tests.

4.1. Figure 2B: The authors summarize the number of participants with significant effects of ambiguity on choice behavior for each group. I recommend a statistical test at the second level that properly assesses the effects of ambiguity and group within a common statistical model. In my opinion, it is not enough to simply count the number of significant tests (from the first level) for each group.

4.2. Figure 2C: For the analysis of response times, the authors might want to consider reporting the main effects of group and ambiguity.

4.3. Figure 2D: The text on page 8 states that Figure 2D indicates that "aggressive investors showed no significant pupil modulation by ambiguity...". However, the figure and its caption indicate significant differences between ambiguous and non-ambiguous trials across all groups. Moreover, if the authors want to compare the groups, it is necessary to compare the groups to each other; a test against zero within each group would not be enough to demonstrate any group differences. In my mind, this would also be important for analyses in Figure 3C and D.

4.4. Strictly speaking, for the statistical tests, it would be necessary to take into account that participants completed multiple sessions (within-subject variance is different from between-subject variance). Currently, each session is treated independently (page 19: "Each individual completed one to three experimental sessions. For data analysis, each session was treated as an independent participant, yielding a total of 108 sessions.")

(5) Necessary quality control for pupillometry and EEG data.

The task was performed in a virtual reality environment with a head-mounted display. The task was not isoluminant, and, to the best of my knowledge, participants were not instructed to avoid eye movements. The authors applied a GLM to control for luminance effects in the pupil data. For EEG, they used ICA to remove ocular and muscular artifacts. While these methods are established, they are usually applied to more controlled paradigms optimized for EEG and pupillometry. To demonstrate high data quality despite these issues, it is necessary to present quality-control analyses. Can the authors please indicate how many blinks had to be removed from the data? Could the authors please indicate how many blinks were removed from the data? Can the authors please show trial-level data (after preprocessing) for a few subjects?

(6) Quality control for the DDM.

The manuscript lacks systematic posterior predictive checks and parameter recovery for the DDM results. It is important to validate that the model accurately captures the data. Currently, we only see the model parameters, but it remains unclear whether the model performs well on the current data set. Moreover, if the authors aimed to test different strategies using the DDM, it might be useful to perform systematic model comparison.

(7) Implications of the second experiment with collaborative task remain unclear.

To me, the link between the main study and the second experiment on leadership and team performance is not obvious. In my opinion, this topic is beyond the scope of the present paper. Linking the two studies more comprehensively based on deeper theoretical grounds would likely be better suited for an independent manuscript.

Reviewer #2 (Public review):

Summary:

Price et al. present new work providing insight into the function and mechanisms of mitochondrial-derived compartments (MDCs) in yeast. The Hughes lab previously established that these large ~micron-sized structures are formed under a variety of conditions including amino acid stress (rapamycin, conA, cycloheximide), alterations in mitochondrial metabolites and lipids, or acute expression of specific outer membrane proteins. These stressors lead to the sequestration of outer membrane proteins (that can include mistargeted inner membrane proteins) that extend or tubulate into large multilamellar structures that ultimately target the vacuole in an ATG5/Dnm1 dependent autophagy related pathway for degradation. Initially reported in aging yeast a decade ago, it has now been accepted as a mechanism to remove excess mitochondrial proteins as a pathway distinct from mitophagy or the extraction of stalled precursors from the import translocon.

In this study, the authors examined additional metabolic transitions they suspected would drive increased mitochondrial protein expression and promote MDC formation. Indeed, they show that glucose-restricted conditions (or a switch to galactose or incubation with 2DG) induced MDCs within 2 hours. This correlated with increased transcription/translation of mitochondrial precursors porin and OM45. Similar results were seen with osmotic shock, a process previously shown to induce mitochondrial gene expression. The metabolic or osmotic shift was shown to activate a yeast AMPK-type kinase called Snf1, which phosphorylates a key substrate Mig1 - an established repressor of mitochondrial gene expression. Loss of these pathways abolished the generation of MDCs under these conditions. As the key novel finding in the study, the authors explored the relationship/requirement for Snf1 and Mig1 using multiple approaches in different backgrounds and employing auxin-inducible degron tools for acute depletion. These data further support the hypothesis that excess mitochondrial outer membrane proteins result in MDC formation to facilitate their removal, at least transiently until the import machinery can adapt to the increased import demand. To test this more directly, they generated an inducible yeast strain to express a canonical transcription factor Hap4 that induces mitochondrial gene expression. In this system, induction of Hap4 expression also resulted in MDC formation. While not all previously reported MDC inducers act through Snf1/Mig1, the common feature is the transcriptional induction of mitochondrial protein expression.

Strengths:

The important aspect of this work is that the authors dissected the transcriptional signaling pathway that induces MDCs in a much more physiological metabolic transition, which complements the more common use of chemical compounds. They had previously shown that overexpression of individual outer membrane proteins could lead to MDCs, but here the Hap4 expression offers a new condition to show that the canonical induction of mitochondrial biogenesis leads to MDC shedding. Overall, the data are of high quality, the findings are clear, and the work provides important new insights into the regulation of MDC formation.

Weaknesses:

There are a few points that should be addressed.

(1) MDCs are almost exclusively monitored through GFP-tagged TOM70, and the authors do not show the inclusion of any endogenous cargo. The evidence for their fate in the vacuole is through the appearance of cleaved, free GFP after 6 hours that is dependent on ATG5, Dnm1, Pep4, etc. Can the authors demonstrate the appearance of MDCs without expressing any GFP tags and instead monitor known outer membrane cargoes? In the case of Hap4 expression, the proteomics identifies some very highly induced mitochondrial proteins, and there surely must be some with antibodies that can detect the protein by IF and Western blot.

(2) There is a very unexpected ~10X increased in a sporulation factor SPO21 upon induction of Hap4. I see no evidence of sporulation, and it's not long enough for stationary phase. Is the increased mitochondrial biogenesis driving a specific metabolic state of these cells that is signaling to other biology?

(3) It is important to understand the kinetics and stoichiometry of outer membrane loading that drives MDCs, and their transit to the vacuole. This is why it would be highly informative to monitor some endogenous cargoes (previous point). In the review the authors cite (NRMBC, Pfanner lab 2019), it was stated that the import machinery is not generally increased upon metabolic induction of mitochondrial gene expression. Therefore, (pre-MDCs) the field concluded that the import machinery has a very high capacity for the rapid biogenesis of newly synthesized proteins, along with regulation through the phosphorylation of import receptors (ie; the work of Meisenger). Consistent with this, the Hap1 proteomics did not show any increases in the core import machinery, while ETC subunits and a large swath of mitochondrial proteins were elevated over 2-fold (I looked carefully through the Excel sheet). Since MDCs are induced transiently about 2 hours after glucose deprivation, and fully dependent on de-repression of Mig1, the authors are right to imply that this is coupled to the import of newly synthesized proteins.

However, it seems to me that MDCs are being formed at very early stages of mitochondrial protein expression, not after they have necessarily "overloaded" the outer membrane. The Hap4 proteomics after 3.5hr of induction would suggest that the bulk of the mitochondrial proteins have been successfully inserted (no import failure) and are likely already functional (metabolizing). I'm trying to understand the percentage of the proteins that would be incorporated within MDCs, as the mitochondria appear to handle the bulk of their newly inserted proteins without issue. How can the authors adapt their "free GFP" assay to understand the stoichiometry of the transport of endogenous, newly imported outer membrane proteins to the vacuole?

(4) As a last theoretical point for discussion: Can the authors exclude that MDCs are not functional or play a signaling role? Given the emerging work on SPOTs (Lena Pernas), and from the new evidence from Craig Thompson's lab that there can be very specific functional mitochondria (oxidizing vs reducing), it is possible that MDCs are not simply there to be degraded. They last at least 3 hours, which is a long time for yeast (budding cycle 90 min, 3 hours in glucose deprivation). Taking the data presented here very objectively, there is no direct evidence that the cargoes within MDVs reflect any failure to import, or that they are damaged in any way. The deletions of Tom70/71 have way too many pleotropic effects and essentially demonstrate only that the MDC cargoes came from the mitochondria. It could be helpful if the discussion also positioned these MDC mechanisms within the context of other aspects of selective mitochondrial-related compartments that have been emerging in the literature.

Reviewer #2 (Public review):

The manuscript describes a numerical analysis of the domains of the T. cruzi cell surface containing different proteins. It has the potential to be of great interest.

I do not have the expertise necessary to comment on the image collection or analysis.

I have one concern: the amount of manipulation of the cells prior to fixation; these were clearly stated in the methods, which is good.

My concern is whether these manipulations prior to fixation alter the observations. The 'Labelling sialic acid acceptors' involves >6 centrifugations and >90 minutes incubation in PBS prior to fixation, and the 'immunostaining' protocol involves cells 'extensively washed with PBS' prior to fixation. I would like to suggest that the authors do controls in which they compare the pattern of anti-SAPA staining under four conditions.

(1) Cells fixed in culture by the addition of paraformaldehyde to 4%, followed by blocking and PBS washes.

(2) Cells fixed in culture by the addition of paraformaldehyde to 4% and glutaraldehyde to 0.2% followed by blocking and PBS washes.

(3) Cells fixed by the 'labelling sialic acid acceptors' protocol.

(4) Cells fixed by the 'immunostaining protocol'.

Reviewer #2 (Public review):

Summary:

In the submitted manuscript, Akter et al use a series of ferroptosis inhibitors in mesenchymal-like ovarian cancer cells and discover that the ferroptosis inducers induce cell death that is inhibited by pyroptosis inhibitors, namely YVAD-fmk and disulfiram, which inhibit pore formation by gasdermin D (GSDMD). Remarkably, the authors also saw the release of IL-1β in response to ferroptosis inducers. Unexpectedly, they did not observe the involvement of caspase-1 but rather observed that caspase-5 was activated in response to the ferroptosis inducers. Moreover, they found that caspase-5 directly cleaves GSDME in response to the ferroptosis inducers, establishing CASP5/GSDME as downstream executors of ferroptosis.

Strengths:

These findings are interesting because only CASP1 is known to induce IL-1β maturation, and their data suggest that CASP5 rather than CASP1, is responsible for IL-1β activation in the context of ferroptosis inducers. Notably, CASP3 is the only caspase reported to be able to cleave GSDME, so the identification of CASP5 as a driver of ferroptosis in this context is a significant finding. They genetically show that loss of CASP5 and GSDME knockdown inhibits cell death in response to the ferroptosis inducers ML162 and Erastin, which is evidence that they play a role in this context.

Weaknesses:

The major findings in this paper are interesting, but the data presented do not robustly support the claims made in this paper. For example, they claim that CASP5 is responsible for the activation of GSDME by cleaving it directly to induce cell death. They try to rule out the involvement of CASP1, ASC, and CASP4 using siRNA targeting these genes, but the knockdowns are incomplete, and the loading controls are inconsistent. They also claim they do not see GSDMD or CASP3 cleavage and activation but use negative data to make that claim. It is unclear if the antibodies used can detect cleaved GSDMD or CASP3 as they do not include a positive control to show that they can indeed detect these activation events if they were occurring. This needs to happen in the same experiment - they need to show in the same experiment with the same lysates that they can detect CASP5, GSDME and IL-1β activation but not CASP1, GSDMD, CASP4, or CASP3 activation. Of course, they should include agonists for positive controls of CASP1, CASP4 and GSDMD activation, which are lacking in the current manuscript.

Notably, the major evidence supporting a direct role for CASP5 cleavage of GSDME is one Coomassie gel using recombinant CASP5 and GSDME, but there were too many non-specific bands, and the full-length uncleaved protein could not be detected even in the untreated lanes. The authors need to show a gel where the protein can easily be identified and should also include a positive control protein like GSDMD to show the relative cleavage efficiency of GSDME compared to a known substrate. It would also be great to compare this to CASP3-mediated cleavage of GSDME. With recombinant proteins, calculating the catalytic efficiencies would be the best way to ascertain if this is biologically similar to other known substrates.

The way that ferroptosis is defined, it is caspase-independent, and pyroptosis is defined as gasdermin-mediated cell death. Given that these agents lead to activation of CASP5/GSDME, it would be more accurate to say that these ferroptosis inducers also induce CASP5/GSDME-dependent pyroptosis, as opposed to them being the executors of ferroptosis. This can be a distinct mechanism/pathway from the ferroptosis pathway, as multiple cell death pathways can be initiated in cells. Consistent with this, ferrostatin-1 also inhibited cell death, likely due to inhibition of the ferroptosis signaling cascade. It is unclear if this pathway is upstream of the caspases. How these ferroptosis triggers selectively activate CASP5 and not CASP4 to induce GSDME cleavage is a major unresolved question. Notably, it is also unclear if this biology is specific to the mesenchymal-like cells used in this study or if it expands to other cells.

Reviewer #2 (Public review):

This study examines the evolutionary context of the emergence of human speech. The authors address the widely held hypothesis that the expansion of the human vocal space, resulting from modifications of the vocal tract, was a key prerequisite for the evolution of spoken language.

To test this hypothesis, the authors quantified the acoustic space of human speech, non-linguistic vocalizations, and musical vocalizations and compared it with that of nonhuman primates, chimpanzees, bonobos, and chacma baboons.

The authors found that speech and song occupied significantly less volume in the acoustic space than human non-linguistic vocalizations. In addition, the acoustic-feature volume of speech and song was not statistically distinct from that of non-human primates. Accordingly, the authors conclude that the evolution of human speech did not depend on an expansion of the human vocal acoustic space.

I find the analysis presented in this manuscript highly convincing. It is conducted at a contemporary scientific standard, and the results provide strong support for the authors' conclusions. I particularly appreciate that the authors explicitly discuss the limitations of their approach. For example, they acknowledge that MFCCs cannot capture all aspects of acoustic structure.

I have only three minor comments:

First, the authors may wish to briefly summarize the main findings of the study by Anikin et al., as it represents the central reference for the present work. A concise summary in two or three sentences would help readers who are not familiar with that study.

Second, I would appreciate a brief explanation of why the authors chose this particular statistical approach.

Third, the authors could briefly mention that the Chacma baboon dataset provides a very comprehensive representation of the vocal repertoire of this species, although a small number of rare vocalizations are not included. I am not sure whether a similar limitation also applies to the chimpanzee and bonobo datasets, but if so, it would be useful to mention this as well.

Reviewer #2 (Public review):

Summary:

The aim of the authors was to measure starvation-induced and basal autophagy in vivo across several tissues and developmental stages. For this, they developed a novel mouse model expressing the GFP-LC3-RFP reporter. They also aimed to provide a more high-throughput method for autophagy flux measurements than assessment by imaging and developed an assay based on a microplate reader.

Strengths:

(1) Good validation of the mouse model. The knock-in strategy is well explained and illustrated.

(2) The model has potential to be applied to a wide range of research questions. The Cre-dependent expression allows for customization of KO timing, which will be beneficial in developmental studies.

(3) The authors presented consistent findings using two different methods to quantify autophagy, strengthening the robustness of their results.

(4) The authors demonstrated the validity of the high-throughput method (microplate reader).

Weaknesses:

(1) The comparison of neuronal populations in different areas of the brain is not ideal. In the cerebellum, Purkinje cells were chosen, which are rare and not representative of this tissue, as well as functionally very different from the neurons in the hippocampus and cortex that they were compared to.

(2) The explanation of the GFP-LC3-RFP construct and specifically if/how autophagosome formation can be measured and distinguished from flux could be clearer.

Conclusion:

The work presented is thorough, and the authors achieved their goals for this study. The effort used to further investigate unexpectedly high basal levels of autophagy in the brain is well appreciated and adds value to this paper. The conclusions of the authors are mostly very well supported by the data provided. The well-structured description of the results, along with clear figures, allows the reader to comprehend the authors' reasoning in reaching their conclusions.

The presented mouse model has great potential for a lasting positive impact on the research field of in vivo study of autophagy. The method of utilizing a microplate reader will also benefit future research where semi-high throughput is an advantage. Together, the information provided in this study not only presents new methodology that will allow the investigation of new research questions, but also provides novel information about in vivo autophagy flux at the selected developmental stages that opens up new follow-up research questions.

EP.99 故事线A: 预计 2026 年底达到 1000-1200 亿年化收入，对应的 IPO 估值预期超过 2 万亿美元——这将是历史上规模最大的 IPO。AI 公司的财务规模正在超越大多数传统行业巨头，速度令人咋舌。

Reviewer #2 (Public review):

In this study, Serrano et al. employed a combination of cell biological and molecular approaches to investigate the localization and regulation of Casein Kinase CK1 during the cell cycle using U20S cells. They show that CK1 dynamically localizes between the centrosomes and the nucleus but can be sequestered away from the centrosomes upon overexpression of its binding partner PER2. They provide evidence that CK1 WT but not a phospho-null mutant strongly accumulates in a hyperphosphorylated form upon inhibition of phosphatases (using Calyculin and Okadaic Acid) and thus conclude that CK1 tail phosphorylation protects the kinase from degradation. Using synchronized cells, they show that CK1 accumulates unphosphorylated in S-phase (APC/Cdh1 inactive) but phosphorylated at the G2-M transition. Immunostaining shows that CK1 localizes to the centrosomes during mitosis.

The manuscript has improved overall, but some sections are still inconclusive and require clarification.

Major comments:

Figure 1 is inconclusive. CK1 nuclear staining is highly similar in untreated cells and in cells treated with CHX + PF670462. The reduction in centrosomal staining in these cells is barely significant. However, the authors draw very strong conclusions from these data sets. In panel B, the cells appear to have been fixed incorrectly, and the anti-PCNT shows a strong background signal. Not convinced that immunofluorescence is the best approach to look at protein dynamics in vivo.

In Figure 2, panel B, the authors should co-stain the centrosomes of cells that co-express CRY1 and CK1, as some of these dots may represent the centrosomes.

Figures 3B, please provide information on the non-phosphorylable CK1a mutant (it is mentioned as a variant in which all serine and threonine residues in the C-terminal tail were replaced by alanine). Specify the number of sites mutated and their exact position. Is this non-phosphorylable CK1a version catalytically active? Treatment of samples with inactivated PPase should be used as a control.

Strengths:

The authors reveal that the activity and abundance of dephosphorylated and phosphorylated CK1δ are regulated in a cell cycle-dependent manner. This suggests that these different pools are associated with distinct physiological functions.

Weaknesses:

Unfortunately, some of the data are inconclusive, and there is no data/information linking the cell cycle regulation of CK1δ to its function during the cell cycle.

Reviewer #2 (Public review):

This study focuses on revealing the essential divergent function of the Acyl Carrier protein (ACP) in the deadliest human malaria parasite, Plasmodium falciparum. More precisely, using inducible KO, cellular and biochemical approaches, the authors determined that instead of a canonical role for ACP allowing the de novo synthesis of fatty acids in the apicoplast (essential relict plastid) of the parasite, the enzyme couples with pyruvate kinase II to generate nucleoside triphosphate to maintain parasite survival during blood stages. The study is novel, well-designed, providing interesting new data on Plasmodium and apicomplexa biology. The results convincingly support the major claim of the study. However, it is currently incomplete to support some claims on the essentiality of some apicoplast pathways.

In this study, Geher et al. focused on deciphering the role of the Acyl Carrier Protein (ACP) present in the relict non-photosynthetic plastid, i.e. the apicoplast of the most lethal human malaria parasite, Plasmodium falciparum. More particularly, they determined an essential function of ACP independent of its usual/typical function as the central protein for the normal function of the apicoplast Type II fatty acid synthesis (FASII) pathway. Rather, the protein seems to associate with the apicoplast Pyruvate Kinase II, together generating an essential nucleoside triphosphate (NTPs) source to fuel the apicoplast and parasite survival instead.

By generating a TetR-DOZY-based inducible KD line for ACP, they confirmed that the protein is indeed essential to maintain apicoplast integrity and parasite survival during asexual blood stages, as previously predicted and experimentally shown. They showed that ACP requires a biochemical modification, typically activating the protein for its function in the FASII pathway, i.e. binding of the 4-PP group by holoACP synthase. Then, they showed that the other enzymes of the FASII pathway are likely dispensable during the blood stage, as they were able to generate a KO line of the first enzyme of the pathway, FabD (which was predicted to be essential in P. falciparum). Based on a cell culture approach in a controlled culture medium, they further claimed that, unlike current evidence-based hypotheses, the FASII pathway (and thus a potentially FASII-linked ACP) has no role/activity during blood stages. Using a proximity biotinylation approach, they determined that ACP associates with the apicoplast pyruvate Kinase II (PKII), previously shown to generate NTPs in the apicoplast for energy and DNA/RNA maintenance (Xia et al. 2019), and not to fuel the FASII pathway as its main function in blood stages. Finally, they showed that the disruption of ACP induces the reduction of the presence/content in PKII in the parasite, as well as the drastic reduction of the apicoplast DNA and RNA content. Together, they concluded that the main function of ACP is indeed the NTP formation via its association with PKII, rather than its canonical role for the generation of fatty acids in the apicoplast.

This study is novel and focuses on a topic of particular interest in malaria biology, but also for most of the apicomplexa-related diseases, and beyond for plastid bearing orgnaisms and this unusual role for ACP. The study is well thought out with proper biochemical approaches that convincingly point to this association of ACP with PKII for NTP synthesis as a major function during P. falciparum blood stages.

Reviewer #2 (Public review):

Summary:

In the manuscript "Primordial Cardiomyocytes orchestrate myocardial morphogenesis and vascularization but are dispensable for regeneration", Sun et al. identify a novel marker of primordial cardiomyocytes and use it to visualize and ablate the population during development and regeneration. The role of the primordial layer has not been investigated because the tools to manipulate this population have not existed. The manuscript is straightforward, easy to understand, and addresses an important question that has not been explored.

While the manuscript provides important insights into the role of primordial CMs, backed by a convincing methodology, the authors should clarify their requirements for heart development and maturation. Specifically, is the primordial layer required for the fish to survive? Do primordial CMs regenerate when ablated during development, and do the defects observed (in trabecular and compact CMs and coronary vessels) resolve after 10 days post-treatment when they were detected?

Strengths:

The major strengths are the identification of a marker that enables manipulation of primordial cardiomyocytes and the tools generated by the team.

Weaknesses:

The major weakness is not considering the longer-term consequences of primordial layer ablation during development, as it is unclear whether the animals succumb to the acute cardiac defects observed or fully recover.

Reviewer #2 (Public review):

Summary:

As a member of DspB subfamily, PRRT2 is predominantly expressed in CNS and has been associated with various paroxysmal neurological disorders. Previous studies have shown that PRRT2 interacts with Nav and Cav channels, modulating channel properties and neuronal excitability.

In this manuscript, Lu et al. demonstrate that PRRT2 is a potent regulator of Nav channel slow inactivation, promoting the development of Nav slow inactivation and impeding the recovery from slow inactivation. This effect is highly conserved in PRRT2s across species as well as among DspB family members (TRARG1 and TMEM233). The authors further confirmed the interaction between Nav channels and PRRT2 in heterologous expression systems as well as in Prrt2-V5 knock-in mice. Prrt2-mutant mice, which lack PRRT2 expression, require lower stimulation thresholds for evoking after-discharges when compared with WT mice.

Overall, this is a well-executed and methodologically comprehensive study. This work offers valuable insight into the physiological functions of PRRT2 and reveals a potential pathogenic mechanism underlying PRRT2-associated neurological disorders.

The revised manuscript has addressed most of the concerns raised by the reviewers and has been substantially strengthened, although I still have several concerns regarding the discussion section.

Strengths:

(1) Overall, this is a well-executed and methodologically comprehensive study. The electrophysiological data strongly support the conclusion that PRRT2 is a potent regulator of Nav channel slow inactivation. The observation that this regulation is conserved in PRRT2 across species and among DspB family members raises the possibility that altered regulation of Nav channels may also contribute to the pathogenesis of TRARG1- or TMEM233-associated disorders.

(2) Co-immunoprecipitation assay performed using brain tissue from genetically modified Prrt2-V5 knock-in mice provides convincing in vivo evidence for the interaction between PRRT2 and Nav1.2 channels.

(3) Prrt2-V5 KI mice show markedly reduced PRRT2 protein expression and display phenotypes similar to those observed in Prrt2-mutant mice, supporting an important role of PRRT2 in regulating neuronal and network excitability.

Weaknesses:

(1) Nav1.6 is also highly expressed in cortical neurons and is widely regarded as a major contributor to action potential initiation and sustained high-frequency firing. Given that PRRT2 similarly regulates the fast and slow inactivation of Nav1.6 and Nav1.2 channels, the potential contribution of Nav1.6 regulation to neuronal and network excitability should be discussed.

(2) Slow inactivation is generally considered to develop over timescales ranging from hundreds of milliseconds to seconds or longer. Therefore, the statement in Discussion (Page 13, line 381-382) that "slow inactivation develops on a timescale of tens of milliseconds to seconds" may not accurately reflect the conventional kinetic definition of slow inactivation and should be clarified.

(3) Page 14, line 417-430: "question about how Nav channel slow inactivation is regulated in cells that do not express PRRT2".<br /> PRRT2 is unlikely to be the sole regulator of Nav channel slow inactivation. Other molecules and signaling pathways may regulate Nav channel and contribute to neuronal excitability. In addition, neuronal excitability can also be regulated through modulating other Nav properties, such as long-term inactivation or slow recovery from inactivation, as well as through modulating the activity of other ion channels, for example, Kv7.2 and Kv7.3 channels. Therefore, PRRT2-negative cells may utilize alternative mechanisms to fine-tune neuronal excitability. In its current form, this paragraph somewhat overstates the role of PRRT2 and would benefit from a more balanced discussion.

(4) Page 50, Figure 7-figure supplement 2: It would be helpful to include representative traces of the 1st and the last (20th) compound APs in panels B and C.

Reviewer #2 (Public review):

Summary:

In this paper, the authors describe the results of a longitudinal study of pertussis infection in mother/infant dyads in Lusaka, Zambia. Unlike many past studies, the authors assessed the infection status of individuals independently of whether they were symptomatic for a respiratory infection. As a result, this work represents one of the first studies specifically designed to assess asymptomatic transmission of pertussis. Using qPCR, the authors find strong evidence for the role of asymptomatic transmission from mothers to infants and also evidence for long-term bacterial carriage. This work represents an important contribution to our understanding of the global burden of pertussis. Also, it highlights the still under-appreciated role of asymptomatic transmission across many infectious diseases (including vaccine-preventable ones).

Strengths:

Unlike many past studies, the authors assessed the infection status of individuals independently of whether they were symptomatic for a respiratory infection. As a result, this work represents one of the first studies specifically designed to assess asymptomatic transmission of pertussis. Using qPCR, the authors find strong evidence for the role of asymptomatic transmission from mothers to infants and also evidence for long-term bacterial carriage.

Comments on revised version:

I appreciate the authors' attention to my comments during the revision process and still believe that their work represents an important contribution to our understanding of pertussis epidemiology. In most cases, the authors have done a thorough job of either addressing or responding to my comments. However, I do not believe the authors engaged sufficiently with two of the queries raised in my previous round of comments. The two queries were about the vaccination status of the mothers and engagement with literature on asymptomatic transmission. I still think they matter and ask the authors to consider them again.

I do not think the authors can rule out two alternative explanations: (1) recent introduction of pertussis and low vaccination coverage amongst study mothers, or (2) recent introduction of a breakthrough strain (either w.r.t. the vaccine or prior infection) and higher vaccination coverage/infection-derived immunity amongst study mothers. Depending on which mechanism was mostly driving the observed patterns in Zambia, i.e.,

a. long-running, widespread, unreported transmission;<br /> b. transmission started recently, and vaccination was low amongst study mothers;<br /> c. a breakthrough strain is causing the current rise (here we'd still want to know about vaccination status); and<br /> d. something else that I have not considered

would have implications for how the results are interpreted, and potentially far-reaching implications for the broader pertussis community. All of that is to say, I think the authors were too quick to dismiss these concerns (even if they disagree with my assertions).

In their reply, the authors largely dismissed concerns about not knowing the mother's vaccination status, stating in their reply that, "our findings strongly suggest ongoing pertussis transmission in this population. Based on this, we expect that mothers in our study who were not vaccinated would likely have some degree of infection-derived immunity."

However, they also stated that, "Zambia offers an evocative example of pertussis surveillance, where no cases have appeared in official WHO reports since 2009" and "As we noted above (and now address in our Discussion), widespread genomic surveillance and microbiological characterization of pertussis are sorely lacking across Africa."

I don't disagree with the authors' conclusion that pertussis is clearly spreading in Zambia. I also don't disagree that there's clearly evidence for minimally symptomatic, infectious mothers spreading infections to children. Both of these findings matter for Zambia and for our broader understanding of pertussis. However, I don't see how the authors can so confidently conclude that low vaccination rates, coupled with a recent introduction, high vaccination rates, coupled with a breakthrough strain, or high infection-derived immunity, coupled with a breakthrough strain, couldn't be what's driving the increase. The authors do hedge in places and also state in the discussion that their findings don't line up with expectations related to WP/infection-derived immunity, "This corresponds to a mean return frequency of one infection per 14.8 years, which is much shorter than the presumed duration of immunity from natural infection or the whole-cell pertussis vaccination used in Zambia (70, 71)." But, my read of the paper is that the authors are pushing way to ward for a preferred hypothesis that is not more favored than other alternatives.

Secondly, I asked about placing this work in the context of other studies on asymptomatic transmission, but realize that I did not list any specific papers. Two worth considering are Warfel et al. 2014 and Althouse and Scarpino 2015. Restating for the editor, the Warfel study found that WP facilitated rapid clearance in a non-human primate experimental infection study (admittedly with small sample sizes and many other caveats). Many took that as evidence that WP would also block transmission (admittedly experiments Warfel did not run). If the mechanism underlying the results in Zambia is that either WP or natural infection does not block transmission (in the absence of a breakthrough strain), that would upend many of the assumptions in pertussis research. While not incompatible with the Warfel et al. results, it would negate most of the importance of their finding that WP blocked transmission. From what I can see, the authors do not even cite Warfel et al. 2014, which is a serious gap regardless of whether the authors agree or disagree with the findings. A quick sidebar, the authors seem to duplicate Craig et al. 2020 10.1093/cid/ciz531, listing it as both citation 9 and 38.

In Althouse and Scarpino, they found evidence of a rise in asymptomatic/underreported/subclinical transmission following the switch from WP to AP. While not as directly relevant to the current study as the Warfel paper (so I leave it to the authors to decide whether citing this paper is important), Althouse and Scarpino discuss asymptomatic transmission at length and also assume that WP conferred strong protection against transmission, so their results (along with dozens and dozens of other studies assuming similar WP/infection-induced immunity protection and durability) would also need to be reinterpreted in the context of this study. The authors should engage with the implication of their results in the context of past modeling studies and what we think we know about vaccine-/infection-derived immunity.

Going back to my earlier points, unvaccinated mothers and the recent introduction of pertussis, or vaccinated/infection-induced immune mothers with a breakthrough strain, would both explain the current results and be compatible with Warfel et al., Althouse and Scarpino, and a sizable number of other studies. Instead, if transmission from WP- or naturally infected mothers is common (in the absence of a breakthrough strain), that would really change the landscape of pertussis epidemiology. The authors have not convinced me that they can make this conclusion. Hence, why I think it's important that the authors engage more actively with those hypotheses and with relevant debates in the pertussis literature on asymptomatic transmission. I think it's appropriate for the authors to present their preferred hypothesis, but, absent other data, they should also present plausible alternatives that are consistent with past publications.

References:

Althouse, B. M., & Scarpino, S. V. (2015). Asymptomatic transmission and the resurgence of Bordetella pertussis. BMC medicine, 13, 1-12.

Warfel, J. M., Zimmerman, L. I., & Merkel, T. J. (2014). Acellular pertussis vaccines protect against disease but fail to prevent infection and transmission in a nonhuman primate model. Proceedings of the National Academy of Sciences, 111(2), 787-792.

Reviewer #2 (Public review):

Summary:

The authors use an Evolve-and-Resequence approach in Drosophila to study the genomic basis of adaptation to long-term starvation. Replicated selection lines and control populations are sequenced and analyzed to identify signals of selection, which are then related to starvation-related phenotypes. The general experimental design is appropriate, and the combination of genomic and phenotypic data is a clear strength of the study.

Strengths:

The strongest aspect of the work is the experimental evolution framework combined with population genomic inference across replicate populations. The observed parallelism across replicates supports the robustness of at least a subset of the detected selection signals. However, several key methodological details are either unclear or insufficiently justified. In particular, both the maintenance of control populations and demographic assumptions are not fully described, and the treatment of structural variation (e.g., segregating inversions) is not sufficiently addressed. The phenotypic analyses are broadly appropriate and replicated but would benefit from access to raw data.

Weaknesses:

The human ortholog enrichment analysis is an interesting component of the study, but it should be interpreted more cautiously. As currently presented, it is based on correlational signals of differentiation and is therefore sensitive to potential confounding factors. While the analysis may point to intriguing patterns consistent with conserved genetic architecture, the evidence is not sufficient to support strong claims of conserved starvation/malnutrition-related polygenic adaptation in humans. Framing this component more explicitly as exploratory would strengthen the manuscript. In its current form, this analysis is somewhat less conclusive than the experimental evolution results in flies.

Overall, the study provides a useful dataset and a reasonably solid analysis of starvation adaptation in experimental Drosophila populations, but several methodological clarifications and a more balanced framing of the cross-species comparisons would strengthen the manuscript.

Reviewer #2 (Public review):

Summary:

Lee et al. is a comprehensive conservation genomics study that combines a chromosome-level genome assembly (sex-specific, too), population resequencing, coalescent species delimitation, and simulations to reassess the evolutionary status and conservation outlook of the Formosan landlocked salmon, Oncorhynchus formosanus. The authors showed a distinctive genome structure, replete with chromosome fusions and an unusual placement of the sex-determining gene sdY. Across sampling sites, they observed variable levels of genetic diversity, but in a way that was surprising given previous census numbers and conservation history. In particular, the authors report a previously unrecognised native population in Hehuan Creek, and conclude that Hehuan is more resilient to typhoon disturbance than the long-protected Qijiawan population - motivating stream-specific rather than range-wide conservation.

Overall, this is a well-written paper that combines a number of elements that are timely and relevant. It uses state-of-the-art techniques to reach its conclusions and is generally performed to a high standard. It describes a critically endangered species that poses its unique conservation challenges. There are a number of things to like, as well as some substantial shortcomings in this paper.

Strengths:

The genomic resource is excellent. The assembly is well validated (97.3% anchored to 25 scaffolds, 95.7% BUSCO), and the authors generated a separate male assembly specifically to resolve the sex-determining region, allowing XY-shared and Y-specific contigs to be distinguished on coverage rather than inference. This is truly well done, and at a high standard. The synteny evidence for telomere-to-telomere fusions involving at least 14 ancestral chromosomes, against two in O. m. masou, is convincing.

The Hehuan Creek result is the paper's most valuable contribution. Elevated heterozygosity, short and infrequent runs of homozygosity, and private alleles absent from the Qijiawan broodstock are difficult to reconcile with a purely reintroduced origin. The contrast with Luoyewei is a clean and useful cautionary case for hatchery supplementation.

Weaknesses:

(1) The species-rank claim is featured in the abstract, but it is made with any level of rigour in the paper. "New species" appears once, in the abstract (l. 32). The Results conclude only that O. formosanus is a distinct evolutionarily significant unit (ll. 188-191), which itself can be well-justified, but it's far from a taxonomic rank (see author's own ref 10). No species concept is explicitly named anywhere, and the taxon is referred to across the manuscript as a subspecies (l. 68), a "new species" (l. 32), and an ESU (l. 189) in turn.

(2) Gene flow is asserted, not tested, and two divergence estimates disagree twentyfold. The abstract reports "no detectable gene flow for ~50,000 years." That figure is a divergence time from BPP under the A00 model, which contains no migration parameter; a model that cannot fit gene flow cannot report its absence. Separately, Figure 1b shows a split at 1.15-5.09 Mya (Figure 1b), while the ddRAD coalescent places the same split at ~50 kya (Figure 1d). The explanation offered (ll. 417-421, "differing temporal sensitivity of genomic markers") is not a mechanism.

(3) The placement of sdY is unresolved, and the paper's own figures conflict with its text. Figure S10 and Table S6 both make O. formosanus chr13 homologous to O. m. masou chr32, whereas reference 28 - on which the authors rely - places the sdY contig on O. m. masou chr7, whose O. formosanus homologue is chr5 (Table S6). These cannot both be correct, and Figure S10's caption compounds the confusion by attributing chr13 to masou and omitting the chr32 track entirely.

(4) The population-viability model's stated mechanisms are contradicted by the authors' own supplementary tables. The Discussion attributes Qijiawan's vulnerability to "lower juvenile survival, decreased fecundity, and narrower terminal age class representation" (ll. 522-525). Table S10 gives Qijiawan higher age-0 survival (0.202/0.616 vs 0.184/0.615); Table S11 gives it higher fecundity at every reproductive age (7.68/19.27/7.86 vs 6.10/8.95/4.14); Table S9 gives it a broader terminal age class (5.0% vs 0.8% age-3 in November). The only parameter favouring Hehuan is age-1 survival - 0.087 (95% CI 0.000-0.180) versus 0.131 (0.093-0.187) under typhoon, and 0.054 (0.000-0.167) versus 0.087 (0.047-0.149) at baseline. Both Qijiawan intervals include zero and overlap Hehuan's, yet a reported extinction odds ratio of 4.48 rests on this difference.

(5) The two streams were not measured equivalently, and every asymmetry favours the conclusion.

Reviewer #2 (Public review):

In this manuscript, the authors dissect how Gβγ potentiates PLCβ3 signaling in cells. Using engineered crosslinking to stabilize a Gβγ-PLCβ3 complex, single particle cryo-EM, and cell-based functional assays, they identify map multiple putative Gβγ interaction surfaces on PLCβ3, including a previously unrecognized binding mode. Structure-guided mutagenesis supports the functional relevance of these interactions and suggests that Gβγ potentiation is not primarily mediated by PLCβ3 membrane recruitment, but instead enhances PLCβ3 activity after the lipase is already at the membrane.

Previous reconstitution work on membrane surface (Falzone & MacKinnon, 2023) proposed a recruitment/partitioning-centric model in which Gβγ increases PLCβ3 output largely by elevating its membrane surface concentration, whereas Gαq primarily increases catalytic turnover; under those reconstitution conditions, the two inputs can combine approximately multiplicatively. In receptor-driven cellular signaling, however, PLCβ3 is robustly recruited to the plasma membrane upon Gαq activation, which raises the question of whether Gβγ contributes mainly through additional recruitment or through a post-recruitment mechanism once PLCβ3 is already at the membrane.

This manuscript helps address that gap by using membrane-anchored PLCβ3 and complementary cellular readouts to separate "getting PLCβ3 to the membrane" from "boosting activity once PLCβ3 is already there." Their results argue that, in cells, membrane recruitment is largely dominated by Gαq·GTP, while Gβγ can further potentiate PIP2 hydrolysis after membrane association, consistent with a modulatory role at the membrane rather than primary recruitment.

Overall, the work provides a structural and mechanistic framework for Gβγ-PLCβ3 cooperation and helps clarify the basis of Gq pathway amplification.

Comments on revised version.

The authors have reasonably addressed my comments.

Reviewer #2 (Public review):

This manuscript, "Nerve Injury-Induced Protein 2 preserves lysosomal membrane integrity to suppress ferroptosis", identifies a previously unrecognized function of NINJ2 as a regulator of lysosomal membrane integrity and iron homeostasis, thereby suppressing ferroptosis. The authors demonstrate that NINJ2 localizes to lysosomes, interacts with LAMP1, limits lysosomal membrane permeabilization (LMP), stabilizes ferritin, and protects cells from ferroptotic cell death. They further extend these mechanistic findings to human cancer datasets, showing co overexpression and positive correlation of NINJ2 with ferritin genes in iron addicted cancers.

Overall, the study is conceptually interesting, technically solid, and integrates cell biology, iron metabolism, and ferroptosis in a coherent framework. The work expands the functional repertoire of the Ninjurin family beyond plasma membrane rupture and inflammation, which will be of interest to researchers in cell death, lysosome biology, and cancer metabolism.

Strengths:

(1) The identification of NINJ2 as a lysosome-associated protein that suppresses ferroptosis represents a meaningful advance beyond its previously described roles in inflammation, pyroptosis, and tumorigenesis.

(2) The work distinguishes NINJ2 functionally from NINJ1, reinforcing the idea that structurally related Ninjurins have divergent membrane-related roles.

(3) The study presents a logically connected pathway:<br /> NINJ2 loss → LMP → labile iron increase → ferritin degradation → ferroptosis sensitization, which is well supported by the data.

(4) The link between LAMP1, ferritin turnover, and ferroptosis is particularly compelling and timely given recent interest in lysosomal contributions to ferroptotic signaling.

(5) The authors use confocal microscopy, proximity ligation assays, biochemical IPs, iron measurements, protein half-life analyses, ferroptosis assays, and TCGA-based analyses, providing convergent evidence for their model.

(6) Use of two distinct cell lines (MCF7 and Molt4) strengthens generalizability.

(7) The integration of cancer expression datasets linking NINJ2 with ferritin expression in hepatocellular and breast carcinomas enhances translational relevance.

(8) Assigning NINJ2 a lysosomal protective function, distinct from NINJ1-mediated plasma membrane rupture is novel.

(9) Linking NINJ2 to ferroptosis regulation via lysosomal iron handling, rather than canonical GPX4 or system Xc⁻ pathways is also novel, along with proposing a NINJ2-LAMP1-ferritin axis as a buffering mechanism against iron-driven lipid peroxidation.

(10) These insights are not incremental; they reframe how NINJ2 may function at the intersection of membrane biology, iron metabolism, and regulated cell death.

Reviewer #2 (Public review):

Summary:

This study identifies IR20a-expressing gustatory neurons in Drosophila as a multimodal sensory population integrating amino acid (arginine) and low-salt signals through combinatorial IR20a/IR25a/IR76b receptor assemblies. The proposed model of peripheral-level signal integration and synergistic enhancement of feeding preference is potentially significant, as it expands current understanding of gustatory coding beyond single-modality labeled lines.

Strengths:

Overall, the findings are conceptually interesting and suggest a novel framework for multimodal taste integration, but some mechanistic interpretations remain incompletely supported by direct evidence.

Weaknesses:

(1) Although the authors demonstrate co-expression of IR20a, IR25a, and IR76b in the same GRN population, this evidence is insufficient to support the proposed model of distinct receptors coexisting within individual neurons. Additional molecular or structural data would be required to distinguish whether these subunits assemble into complexes.

(2) Given that IR76b has already been established as a sodium/salt sensing channel, the novelty of this study relies on the proposed role of IR20a in conferring multimodal integration and synergy. However, it remains unclear whether this represents a fundamentally new sensory mechanism or a re-interpretation of known IR76b-dependent salt responses in a different neuronal context.

(3) Line 127:<br /> -The statement that there is no overlap between IR20a-GAL4 and GR64f-LexA or GR66a-LexA is not sufficiently supported by the presented imaging data. In particular, the resolution and clarity of the confocal images in Figure 1 appear suboptimal, making it difficult to confidently assess co-localization. The authors are encouraged to provide higher-resolution images or additional quantitative co-localization analysis to substantiate this conclusion.<br /> -In addition, the images shown in Figure 1 F1-F2 suggest possible partial overlap between IR20a and GR66a signals, which appears inconsistent with the authors' statement of no co-expression. This discrepancy should be clarified.

(4) Lines 138-141:<br /> There appears to be a discrepancy between imaging and behavioral data: IR20a is reported as dispensable for arginine-evoked neural responses, yet IR20a mutants show significantly reduced attraction to arginine in behavioral assays. The authors should clarify how behavioral deficits arise in the absence of detectable changes in calcium imaging,

(5) The manuscript proposes that IR20a functions in combination with IR25a to mediate multimodal detection of arginine and low NaCl. However, the specific role of IR25a in this context remains unclear.

(6) The authors report that co-expression of IR20a and IR25a confers synergistic responses to combined arginine and NaCl stimulation, whereas the inclusion of IR76b abolishes this response (Figures 5E-K). This is an intriguing and potentially important finding; however, the mechanistic basis for this suppression is not clearly explained.

(7) The authors propose that IR56b mediates state-dependent modulation of low-salt preference. However, the current data do not clearly distinguish whether IR56b acts as a real nutrient state sensor or just functions as a downstream modulatory component within a broader feeding circuit. Additional evidence linking IR56b activity changes to upstream metabolic state signals would be necessary to support the interpretation that IR56b functions as a primary state sensor.

(8) The manuscript suggests that IR20a and IR56b define two parallel and functionally independent pathways mediating nutrient detection and state-dependent preference, respectively. However, this conclusion is not fully supported by the current dataset. While the two receptors are shown to be expressed in distinct neuronal populations, the possibility of indirect interactions or convergence at downstream circuit nodes has not been excluded. Given that both pathways ultimately influence feeding behavior, it remains possible that they converge at higher-order interneurons or shared neuromodulatory circuits.

(9) In the state-dependent feeding assays (Figure 6), using H2O as a control introduces a severe masking effect. Salt-deprived flies actively suppress pure water intake to avoid osmotic shock, which artificially inflates the Preference Index (P.I.) for salt due to the denominator effect. To cleanly isolate salt preference from the thirst/osmotic drive, the authors will need to utilize an "isosmotic sucrose vs. isosmotic sucrose + salt" paradigm (Jaeger et al., 2018, eLife; Puri et al., 2026, PNAS).

Reviewer #2 (Public review):

Summary:

This review constructs a novel theoretical framework to elucidate incomplete postmenopausal age-related lobular involution (ARLI) in the breast. Differing from the conventional view of persistent lobules as passive residual structures, the work innovatively defines them as an actively maintained senescence-immune reserve niche. It comprehensively integrates multidisciplinary evidence from breast epidemiology, stromal biology, cellular senescence and immune surveillance, as well as cross-tissue research findings, and identifies menopause as a core biological turning point regulating ARLI and relevant breast cancer risk, providing a new theoretical perspective for subsequent breast cancer risk assessment and preventive intervention research.

Strengths:

This study presents an original, logically rigorous, and well-organized research hypothesis. It innovatively breaks through the traditional cognitive perspective of ARLI and adopts a multidisciplinary and cross-tissue analytical approach to sort out relevant biological mechanisms systematically. The proposed theoretical framework is insightful, with good theoretical innovation and potential translational value for guiding breast cancer risk evaluation and targeted prevention strategies.

Weaknesses:

The manuscript currently serves primarily as a conceptual framework rather than a rigorously evidenced synthesis. Its central argument relies heavily on cross-sectional correlations and theoretical analogies to other organ systems, lacking operational definitions for the reserve state in human breast tissue.

Reviewer #2 (Public review):

Summary:

The authors identify KIN-G as an in vitro substrate for phosphorylation by TbPLK and show that several of the in vitro P-ated sites, including T310, overlap with P-ation sites seen in live cells. The authors further show that PLK-mediated P-ation inhibits KIN-G binding to microtubules in vitro, as does a KIN-G-T301D mutant, and that expression of a KIN-G-T301D Phospho-mimic in T. brucei phenocopies KIN-G RNAi knockdowns, producing defects in cell division, morphogenesis of the centrin arm, FAZ and other cellular structures, as well as misplaced cytokinesis furrow.

Understanding cytoskeletal rearrangements that drive cell division in T. brucei is an important and unresolved problem, so the work addresses important questions that are of great interest. PLK and KIN-G have previously been shown to be important for cell division and morphogenesis of cytoskeletal structures that drive cell division in T. brucei. The current work advances our understanding by suggesting a potential mechanism by which PLK and KIN-G might participate, namely through PLK-dependent P-ation to control KIN-G MT binding activity.

Strengths:

The authors use a rigorous combination of biochemistry, phosphoproteomics, cell biology, and mutant analysis to support their conclusion that PLK-mediated P-ation of KIN-G negatively regulates KIN-G microtubule binding and this may explain the observation that a KIN-G T301 phosphomimic mutant blocks cell division and perturbs biogenesis of cytoskeletal structures that drive cell division and morphogenesis. Combining rigorous and informative in vitro studies with mutant analysis in live cells is a great strength. The work is solid and important, though a few pieces are needed to fully connect the in vitro findings with the in vivo observations.

Reviewer #2 (Public review):

Summary:

This is an interesting study that explores how human RPE could be used as a source for new retinal neurons. This is a welcome addition to the field of retinal regeneration, which is currently focused almost exclusively on the regenerative capacity of Müller glia cells. The line of inquiry is firmly rooted in findings from amphibian and embryonic chick model systems and advances a fetal human retina RPE-based screening system as a rich resource for insights into human RPE biology, including as a potential stem cell source.

The authors investigate the potential of fetal human RPE cells to be reprogrammed into retinal neurons using overexpression of pro-neural factors. While this is a critical knowledge gap in the field of retinal regeneration with significant promise for developing regenerative therapies, several methodological concerns impact the interpretation of results. Firstly, while the authors sought to evaluate factors that enhance RPE reprogramming when co-expressed with ASCL1, nearly all co-expression constructs tested failed to achieve appreciable expression of ASCL1, leaving a central hypothesis of this study largely untested (Major concern 1). Second, although the authors were able to detect a cluster of photoreceptor-like cells in their screen, they were unable to identify which reprogramming construct generated this cluster (Major concern 2). Finally, an essential control that definitively demonstrates the value of combinatorial transcription factor reprogramming is missing (Major concern 3).

In summary, the authors establish a valuable new paradigm for culturing and reprogramming fetal human RPE, and even more importantly, demonstrate successful reprogramming to neural fates. However, the discussion and interpretation of results needs to be modified significantly to make it clear that (i) the outcome of many co-expression paradigms remains effectively unknown/untested due to failed over-expression of ASCL1, and that (ii) the reprogramming construct giving rise to photoreceptor-like cells could not be conclusively identified from their initial screen.

Strengths:

(1) Powerful new screening system advanced for exploring the regenerative potential of human fetal RPE cells.

(2) Co-expression vector system for testing additive effects of proneural transcription factors.

Weaknesses:

Major concerns:

(1) The authors executed a screen for combinations of factors that can enhance ASCL1-mediated reprogramming of RPE into retinal neurons. However, the expression level of ASCL1 was remarkably low in virtually all co-expression paradigms (see Figure 3C). Notably, the reprogramming combination with the highest potency (ASCL1 + NEUROD1) was also the one exhibiting the highest level of ASCL1 expression. The "failed" reprogramming of most of the co-expression constructs (ASCL1+LMO1, ASCL1+EZH2, and ASCL1+RAX2) is potentially a false negative resulting from low transgenic expression of ASCL1.

(2) The authors' interpretation is that the overexpression of NeuroD1 and Ascl1 generated a new cluster that expressed markers of photoreceptors such as RXRG and RCVRN (see Figure 3D). However, there does not actually appear to be any overlap between the ASCL1+NEUROD1 cluster (orange dots, left panel) and the cells expressing markers of photoreceptors (yellow/green/purple?/black? dots, right panel; yellow being ASCL1-EZH2, green being ASCL1, purple being ASCL1-and black being control - though color coding here is admittedly somewhat confusing). Thus, the photoreceptor-like cluster of interest actually seems to correspond to gray cells that were unmapped/exposed to an unknown programming cocktail. So, it remains completely unknown which reprogramming construct generated this cluster.

(3) To conclusively establish the additive role of NEUROD1 in reprogramming, it would be prudent to compare ASCL1 + FA directly to ASCL1+NeuroD1+FA. This control was not included but is needed for a more complete interpretation of results.

Biểu đồ phân tán (Scatter Plot) Khái niệm: Biểu diễn tập hợp các điểm dữ liệu "phân tán" trên mặt phẳng tọa độ.

Cách sử dụng: Đánh dấu các điểm bất thường (outliers), có thể thêm đường xu hướng (trendline) hoặc dùng màu sắc/kích thước điểm khác nhau để biểu diễn các nhóm đè lên nhau.

Sử dụng khi nào: Khi muốn khám phá mối quan hệ, mô hình giữa 2 biến liên tục (continuous variables).

Biểu diễn điều gì: Biểu diễn mối tương quan (Correlation), quan hệ và sự tập trung/phân cụm (Clusters/Outliers) giữa 2 biến.

Reviewer #2 (Public review):

Summary:

The authors investigated whether neurofeedback (NFB) training targeting spontaneous gamma oscillations (30-60 Hz) at the parieto-occipital region (Pz electrode) could reduce experimental pain perception. They randomized 88 healthy participants to active or sham NFB groups across two cohorts (44 each). Active NFB consisted of real-time feedback based on participants' own gamma power; sham NFB consisted of the preceding participant's gamma power. Participants completed three ~16-min sessions, and approximately 52% of active NFB participants showed increased gamma power in session 3 and were considered responders. Analyses restricted to these 23 responders (matched with 23 sham controls) showed reduced pain intensity, unpleasantness, and laser-evoked potential (LEP) amplitudes, with a significant negative correlation between gamma power and pain intensity after session 3.

Strengths:

(1) The distinction between spontaneous and stimulus-evoked gamma oscillations in pain processing is theoretically important.

(2) The rationale for targeting spontaneous gamma via NFB is clearly articulated.

(3) The study was sham-controlled, and the blinding was adequate.

(4) The authors commendably ran a second cohort (n=44) with simultaneous posterior neck EMG recording to address the critical concern of muscle artifact contamination of gamma, in response to a previous review

Weaknesses:

(1) The most critical issue is about the exclusion of non-responders from the analysis. I find this problematic, as the reasoning becomes circular (selecting the participants who managed to increased gamma and then asking whether gamma NFB influenced pain), effect sizes are inflated, and the selection itself may introduce biases. For example, the responders may differ from the non-responders with respect to other characteristics (better attention skills, better self-regulation, etc). It would be more principled to present the results for the entire sample and only present the responder analysis as a secondary analysis. In the preregistration, the responder-only analysis was not mentioned.

(2) Another critical point is about the causal claims made in the abstract, introduction, and discussion. Given that the current results provide only correlational evidence in a subsample, the language should be revised to avoid overinterpretation. If the authors can demonstrate a significant mediation effect (NFB group -> gamma change -> pain change), they may be able to argue that increases in gamma activity mediate the observed reduction in pain.

Minor points:

(1) For the sham procedure, the authors used the preceding participant's gamma data for feedback. This raises two questions: How was this handled for the first participant? Did the authors check the discrepancy between actual gamma and presented gamma in the sham NFB group?

(2) Was baseline gamma power comparable between groups?

Reviewer #2 (Public review):

Many insects possess extremely sensitive olfactory systems that can detect chemical signals from distances of several kilometers. For decades, the arms race between bats and insects has served as a prime example of acoustic co-evolution. The auditory adaptations of insects to echolocation have been well documented. Cricket has a multi-sensory predator recognition system with keen olfactory, tactile, and auditory senses. However, whether crickets can use the scent of bats to avoid them remains unknown at present. The authors hypothesized that cricket prey (Loxoblemmus equestris) might eavesdrop on predator bat (Scotophilus kuhlii) VOCs as an early warning. L. equestris is one of the prey species of S. kuhlii, and the authors demonstrated that the body odor of the insectivorous bat S. kuhlii triggers robust avoidance and electrophysiological responses in the cricket L. equestris, and that a single compound, (-)-limonene, is sufficient to elicit this avoidance in the laboratory and suppress calling in the field. Overall, this paper has a complete chain of evidence and should be a highly praised study.

Reviewer #2 (Public review):

Summary:

The authors introduce a K-mer-based method for profiling repeat content within a species, applied here to 1,142 A. thaliana genomes sequenced with short reads. This approach allowed them to bypass the challenges of genome assembly, particularly for repetitive regions, while still quantifying copy number variation. Their analysis identified >50 trans-acting loci regulating repeat abundance, enriched for genes involved in DNA repair, replication, and methylation. They also speculate on the role of selection in shaping genome repeat content, arguing that purifying selection tends to suppress alleles that promote repeat expansion.

The work presents a scalable way to extract meaningful insights from the large quantities of short-read datasets available. However, I have several concerns regarding the methodology, scope of claims, and interpretation of results.

Strengths:

The authors leverage a large dataset, >1100 samples, of A. thaliana. The scale of the study is impressive and clearly bolsters their findings. Additionally, this provides a framework for future, large-scale studies and offers a solid foundation for hypothesis generation. The k-mer-based method is generally practical for large-scale analysis and should be transferable to other datasets. Finally, the authors are commendably upfront about many of the project's limitations.

Weaknesses:

The decision to use k=12 is loosely justified. While the authors performed a sweep of k-mer lengths (from 5-20) and noted computational constraints, the choice is highly dataset-specific. Benchmarking across different k values with additional datasets (especially including other species) would strengthen confidence in the robustness of the method.

All analyses rely exclusively on the TAIR10 reference genome, which is incomplete and known to collapse certain repetitive regions. This dependence raises concerns that some repeats (especially recently expanded or highly variable ones) are systematically undercounted. With improved A. thaliana assemblies now available, testing the method against a more complete reference would alleviate these concerns.

The manuscript's conclusions are framed in very broad terms (e.g., "shaping genome evolution in plants"). However, the study is restricted to a single species, A. thaliana, which may not represent other plants. While the findings may suggest general principles, the claims in the abstract and conclusion should be moderated to reflect the study system more accurately.

The identification of >50 trans-acting loci enriched for DNA repair and replication genes is compelling, but the conclusions remain correlational.

Reviewer #2 (Public review):

Summary:

The authors aimed to determine the molecular mechanisms by which nuclear pore component NPP-3/NUP205 regulates chromosome localization in C. elegans embryos. Previous studies had shown that depletion of NPP-3 caused premature chromosome condensation and movement of chromosomes to the nuclear periphery. Peripheral location of chromosomes is also observed under respiratory stress conditions, suggesting that peripheral chromosome positioning could act as a protective response to stress conditions. How NPP-3 affects chromosome positioning was unknown. Here, the authors conduct a screen to identify factors that promote chromosome relocation to the periphery in npp-3-depleted embryos, identifying an important role for spindle assembly checkpoint components in this process.

Strengths:

Using cytological tools to visualise chromosomes and nuclear envelope markers, the authors show that, in addition to the peripheral location of chromosomes, NPP-3 depletion causes partial rupture of the nuclear envelope and premature chromosome condensation. By systematically co-depleting NPP-3 and factors required for heterochromatin association with nuclear lamina (CEC-4), telomere binding to nuclear envelope (SUN-1 and POT-1), proteins required for the nuclear rupture repair machinery (BAF-1 and LEM-2), kinetochore proteins and components of the spindle assembly checkpoint (SAC) (MDF-1 and MDF-2), the authors convincingly show that SAC components are required for peripheral relocation of chromosomes in absence of NPP-3. The study also provides convincing evidence that peripheral relocation of chromosomes in the absence of NPP-3 has functional implications as it causes transcriptional deregulation and premature relocation of SAC components from the nuclear envelope to chromosomes. Co-depletion of NPP-3 and SAC components accelerates progression through miotic prophase and increases the incidence of defects in chromosome segregation during mitosis. These findings demonstrate that SAC proteins play an important role in regulating chromosome positioning during prophase (at least in the absence of NPP-3) and that they can regulate cell cycle progression at earlier stages than previously thought.

Weaknesses:

The authors also propose that NPP-3 depletion causes DNA damage; however, the evidence presented to support this claim is not as strong as that presented for the effects mentioned above. Also, the premature condensation of chromosomes appears as a clear consequence of NPP-3 depletion, but this intriguing phenotype remains unexplored.

Reviewer #2 (Public review):

Summary:

STX is a non-steroidal, CNS-selective estrogenic compound with neuroprotective effects in stroke and Alzheimer's disease models, but its molecular target has remained unknown for nearly 20 years. In this study, the authors identify VDAC proteins as the direct mitochondrial targets of STX using chemoproteomics, single-cell qPCR, electrophysiology, and metabolic flux analyses. They further show that VDAC2 is the primary functional target in female POMC neurons, linking STX-mediated VDAC modulation to enhanced mitochondrial bioenergetics and neuroprotection.

Strengths:

This study is strengthened by its innovative chemoproteomic approach, in which the authors developed a novel bifunctional STX probe (BF-STX) containing a photo-crosslinkable diazirine group and an alkyne handle to capture transient STX-protein interactions in living cells. The experimental design is further reinforced by rigorous controls, including no-UV negative controls and competition assays with excess unlabeled STX, which provide convincing evidence that VDAC1, VDAC2, and VDAC3 are genuine STX-binding targets rather than nonspecific artifacts. Finally, the authors validate the STX-VDAC interaction using multiple complementary approaches, including chemoproteomics, single-cell qPCR, planar lipid membrane electrophysiology, and Seahorse metabolic flux analyses, providing strong mechanistic support for their conclusions.

Weaknesses:

While the study provides convincing evidence that STX directly modulates VDAC function, several limitations remain. Most experiments were performed in immortalized cell lines rather than primary neurons or in vivo models, limiting their physiological relevance. In addition, the exact structural binding site of STX on VDAC remains unresolved, and no loss-of-function experiments (e.g., VDAC2 knockdown) were performed to establish a direct causal link between VDAC2 and STX's bioenergetic and neuroprotective effects. The non-linear dose-response at higher STX concentrations also requires further investigation.

Reviewer #2 (Public review):

This manuscript addresses an important and timely question in TDP-43 biology by systematically identifying regulators of TDP-43 anisosome formation, with a particular focus on nuclear export via XPO1. Using a combination of unbiased chemical screening, genetic perturbation, and advanced imaging approaches, the authors propose that inhibition of nuclear export modulates the abundance and biophysical properties of TDP-43 anisosomes. They further strengthen their findings by introducing an additional model system, a semi-permeabilized in vitro assay, which provides mechanistic evidence that XPO1 activity prevents anisosome dissolution by retaining nuclear RNAs. The study is conceptually innovative and has potential relevance for neurodegenerative diseases characterized by TDP-43 pathology. Some minor concerns remain, mostly about experimental design of the newly added data.

Strengths:

(1) The study employs an unbiased, hypothesis-free compound screen to identify regulators of TDP-43 anisosome formation, which is a major strength and reduces confirmation bias.

(2) The authors combine chemical and genetic screening approaches, providing orthogonal validation of key pathways and increasing confidence in the biological relevance of top hits.

(3) The focus on biophysical properties of TDP-43 assemblies, assessed through imaging and FRAP, moves beyond simple presence/absence of aggregates and provides mechanistic insight into the biophysical states of TDP-43.

(4) The use of multiple experimental modalities, including live-cell imaging, FRAP, pharmacological perturbation, and transcriptomic analysis, reflects a technically sophisticated and ambitious study design.

(5) The authors attempt to extend findings beyond immortalized cancer cell lines by incorporating organoid models, demonstrating awareness of disease relevance and translational importance.

(6) The authors extend their study by incorporating a semi-permeabilized in vitro system, which provides compelling evidence that inhibition of nuclear export promotes the retention of nuclear anisosomes, an effect driven by the accumulation of nuclear RNAs.

Overall, the manuscript is clearly written and logically structured, making complex experimental workflows accessible and the central hypotheses easy to follow.

Weaknesses:

(1) The manuscript has significantly improved with the revisions. Some experimental procedures and method details, as well has statements remain incompletely described:<br /> a) What is the smear in Figure S1 after VLX treatment?<br /> b) The authors state that "The reduction in TDP-43 signal was not due to protein elimination.", however no data is provided to support that statement.<br /> c) The authors state that "TDP-43 shifts from phase-separated state to a soluble state ...", however no data is provided to support that statement.<br /> d) Why did the authors choose cow lover cytosol for this study?<br /> e) The experimental setup for supplementing with cytosol/ATP/GTP is unclear. A more detailed schematic would be helpful to understand at what stage in the experiment these factors were added. Which step of the protocol was performed at 37 {degree sign}C, which is indicated in the figure schematic but not described in the methods.<br /> f) In the organoid model, the authors mention that they observe similar levels of total TDP-43, however they do not provide quantification. Instead, they provide a graph that shows highly significant changes in nuclear TDP-43, which was not addressed in the text.

Additionally, some questions remain unclear:

(1) The anisosomes induced by ATP/GTP or cytosol are insufficiently characterized. It remains unclear whether these structures correspond to canonical ring-shaped anisosomes, and whether they exhibit dynamic (liquid-like) or more static (gel-like) properties.

(2) The contribution of the cytosol and ATP/GTP supplementation experiments to the overall narrative is unclear. While the findings are intriguing, their interpretation within the context of the study is not well articulated. In particular, the rationale for including cytosol is not sufficiently justified, given that ATP/GTP alone induces a pronounced effect, whereas cytosol alone does not.

(3) The authors should address why endogenous XPO1 does not co-localize with anisosomes, whereas overexpressed XPO1 does. This raises the possibility that the observed co-localization may be an artifact of non-physiological protein levels, which should be discussed.

(4) The iPSC-based model remains insufficiently characterized. While the authors propose that this system recapitulates the accumulation of liquid and solid aggregates resembling anisosomes, it is unclear whether this phenotype is robustly observed and whether KPT treatment effectively modulates it.

(5) The rationale for the selected treatment durations is unclear, and the timing appears inconsistent across experiments (ranging from 3 to 16 hours), including within experiments involving the same compound. This variability should be justified or standardized.

(6) Several figure legends require clarification:<br /> a) In the section stating "Collectively, our results suggest that the stability and dynamics of anisosomes are modulated by XPO1-mediated nuclear export ...", the cited figure appears to be incorrect. This should refer to Figure 5L rather than Figure 5J.<br /> b) Figure 1B: Please specify the number of replicates per concentration, the number of cells analyzed, and the model used for regression analysis. Additionally, the legend indicates a treatment duration of 15 hours, whereas Figure 1A states 24 hours.<br /> c) Figure 2G: The authors state "7 anisosomes per condition," but the graph displays only 4-6 data points. Please clarify what each data point represents.<br /> d) Figures 3B and 3G: Please clarify whether a defined threshold was used to determine a "reduction in anisosome number."<br /> e) Figure 4B: These do not represent biological replicates, as all samples derive from a single cell line; rather, they constitute independent experimental replicates.<br /> f) Figures 5B and 5H: The legend states "n = 3 biological repeats," but the number of data points shown appears higher. Please clarify.<br /> g) Figures 5K, 6C, and 6E: "Mean Fluorescence Intensity (MPI)" should be corrected to "MFI."<br /> h) Figure 6C: Please include the number of cells analyzed and provide relevant statistical measures (e.g., R², p-value).<br /> i) Figure 6D: The experimental timeline is unclear. Please specify the duration of incubation and the timing of each step.<br /> j) Figure 7B: Improved labeling is needed (e.g., clarification of "mean spot volume") to better align with the figure legend.

Reviewer #2 (Public review):

Summary:

The authors have made a convincing argument that the current system of in vitro translation using E. coli extracts can be significantly optimized to work with much lesser components, while maintaining activity. They have showcased their improved activity using not only physical but also functional readouts.

Strengths:

The experiments are designed in a very logical and easy to understand manner, which makes it easier not only to follow the paper, but also reproduce the results. Functional assays with the synthesized proteins are a good way to demonstrate functionality and applicability of the system. They also benchmark their system against a commercial kit to show superior performance of their system.

Weaknesses:

The production of the lysate requires special instrumentation, limiting accessibility.

Comments on previous version:

Thank you to the authors for addressing the concerns both textually and experimentally. This work has significant value.

Reviewer #2 (Public review):

Summary:

Chapman, Determan et al. investigate how pathogenic mutations in DNMT3A which cause of Tatton-Brown-Rahman Syndrome (TBRS) disrupt human cortical developmental processes using a comprehensive panel of human pluripotent stem cell models spanning DNMT3A loss-of-function severity. The authors aim to identify the cellular and molecular mechanisms underlying TBRS-associated brain overgrowth and intellectual disability, and to test whether mechanistic convergence exists between TBRS and other overgrowth-intellectual disability disorders (OGIDs) caused by mutations in EZH2 (Weaver syndrome) or PIK3CA pathway components. Their central conclusion is that GABAergic interneuron development is selectively vulnerable to DNMT3A mutation where reduced DNA methylation causes premature de-repression of neuronal and synaptic genes, driving precocious neuronal maturation and hyperactivity sufficient to disrupt neuronal network synchrony. This report adds to a growing literature supporting the vulnerability of GABAergic interneurons in NDDs and further provides a mechanistic view of this vulnerability potentially convergent across OGIDs. The mechanistic claims around H3K27me3 compensation and mTOR-based therapeutic convergence, while promising, rest on more preliminary evidence and would benefit from the distinction between correlation and mechanism being made more explicit in the text. Overall, this is a compelling study with rigorous experimental design and novel findings with potential impact across better understanding OGID pathophysiology.

Strengths:

(1) A major strength of this work is the breadth and rigor of the disease modeling approach. Four independent TBRS model systems are used in tandem: a patient-derived iPSC line with isogenic CRISPR-corrected control (R882H), a knock-in hESC model (P904L) with its wild-type isogenic, patient deletion iPSC lines (Del1/2), and CRISPRi knockdown models (G1/G2), collectively spanning a range of DNMT3A loss-of-function that correlates with phenotypic severity. This allelic series design substantially strengthens causal inference beyond what any single isogenic pair could provide.

(2) The multi-omic integration across matched developmental stages provides a strong mechanistic foundation for the cellular phenotyping and provides significantly enhanced novelty. RNA-seq, whole-genome bisulfite sequencing, and H3K27me3 CUT&Tag are combined in the same cell types and timepoints show that DNMT3A loss reduces CG methylation at neuronal and synaptic gene loci, leading to premature transcriptional activation.

(3) The selective vulnerability of ventral (GABAergic) versus dorsal (glutamatergic) progenitors is one of the study's most important findings. This lineage specificity is consistently observed across all model systems and in both 2D and organoid formats, where ventral NPCs show increased proliferation, premature neuronal gene expression, and increased neurogenesis, while dorsal NPCs are largely unaffected at the transcriptomic and cellular level despite exhibiting comparable DNA methylation changes. This adds to a body of emerging work showing GABAergic interneuron vulnerability in NDDs where ubiquitously expressed genes such as chromatin modifiers are perturbed and provides additional molecular insights into potential mechanisms of "resilience" of dorsal populations.

(4) The functional characterization follows a logical progression from single-neuron electrophysiology (demonstrating GABAergic hyperactivity with increased action potential amplitude and firing rate) to network-level analysis using high-density multi-electrode arrays. The HD-MEA experimental design - pairing TBRS or control GABAergic neurons with a constant background of control iGlut neurons - cleanly isolates GABAergic dysfunction as the driver of network hypersynchrony.

Weaknesses:

(1) The concomitant induction of proliferation and differentiation in TBRS V-NPCs is conceptually striking, since these are generally considered antagonistic developmental programs. The authors clarify that neuronal and synaptic gene de-repression is the more prominent direct consequence of mCG loss, while PIK3/AKT/mTOR pathway upregulation is not itself directly linked to differentially methylated regions, suggesting an indirect relationship between DNMT3A LOF and increased proliferative signaling. This framing is reasonable, but the mechanism linking DNMT3A mutation to mTOR activation remains unresolved, and the manuscript would benefit from being explicit about this gap. Relatedly, the rapamycin rescue, while demonstrated across multiple models including 904 and Del1 (Supplementary Fig. S3e-f), remains limited to proliferation readouts. Whether mTOR inhibition also rescues the downstream neurogenesis, maturation, or network phenotypes is an important open question that the authors appropriately frame as motivation for future work.

(2) The claim that H3K27me3 compensates for mCG loss is supported by prior work (Lii et al. 2022), which demonstrated increased PRC2 component expression and H3K27me3 gain at sites of DNA methylation loss in Dnmt3a knockout mouse neurons, and by data showing that PRC2 subunits (SUZ12, EED, EZH2) are significantly more highly expressed in D-NPCs than V-NPCs. Together, these findings provide a plausible molecular basis for why dorsal progenitors may be better equipped to maintain repression when DNA methylation is lost, and they make the EZH2 overexpression rescue in V-NPCs more interpretable. Yet, a formal distinction related to two competing, potentially underlying mechanisms, between active compensation, in which EZH2 is recruited to specific loci in response to methylation loss, and functional redundancy, in which higher baseline Polycomb occupancy in dorsal cells simply becomes the dominant repressive mark once mCG is reduced, has not been resolved.

Reviewer #2 (Public review):

Summary:

This work presents a spiking network model of traveling waves at the whole-brain scale in mouse neocortex. The authors use data from the Allen Institute to re-construct connectivity between different neocortical sites. They then quantify macroscopic traveling waves following stimulation of all layer 4 neurons in neocortex.

Strengths:

Overall, the results are interesting and shed new light on the dynamic organization of activity across neocortex of the mouse. The paper uses realistic neuron models specifically fit to intracellular recordings, demonstrating that traveling waves occur in the mouse neocortex with both realistic connectivity and realistic single-neuron dynamics. The paper is also well-written in general. For these reasons, the authors have generally achieved their aims in this work.

Weaknesses:

(1) Description of Algorithm 1: While the Methods section clearly explains the density parameter \rho, the statement on line 358 concerning the "ideal" average number of connections is a little unclear. The authors should explicitly clarify that \rho is a free parameter that can be adjusted to balance computational feasibility (for a given set of computational resources) and biological fidelity.

(2) Lines 102-103: The \rho parameter used here results in approximately 300 connections per neuron on average. The authors should state clearly that the number of connections per cell is the key determinant of computational feasibility (cf. Morrison et al., Neural Computation, 2005). The authors should also review neuronal density and synaptic connectivity in mouse neocortex and clearly reference density and connectivity in their model to the biological scales found in the mouse.

(3) Line 131: From the plots in Figure 2, it is not clear that the stimulus response is necessarily a rhythmic oscillation, in the sense of a single narrowband frequency.

(4) Line 217: Can the authors clarify how these findings relate to the results from Mohajerani et al. (Nature Neuroscience, 2013), or differ from them?

(5) Line 230: Because higher temporal frequency activity also tends to be more spatially localized, a correlation between PGD and temporal frequency could be an inherent consequence of this relationship, rather than a meaningful result.

(6) Line 247-248: It is not clear that the algorithm for generating connections between neurons presented here really relates to those for community detections. For example, in the case of the Allen Institute data, the communities are essentially in the data already.

(7) Line 284-285: The relationship between conduction delay is more direct than this sentence suggests. Conduction delay is fundamentally determined by the time required for action potentials to propagate along axons, making it intrinsically linked to anatomical distance.

(8) Line 287-288: The authors suggest at this point that they do not have enough information to estimate time delays due to axonal conduction along white matter fibers. However, experimental data from white matter connections typically includes information about fiber length, which does enable estimating conduction delays. These estimations have been previously implemented for Allen Institute connectome data in the mouse (Choi and Mihalas, PLoS Comput Biology, 2019) and human connectome data (Budzinski et al., Physical Review Research, 2023).

(9) Lines 294-295: Several methods do exist for detecting and characterizing wave dynamics in three-dimensional data (Budzinski et al., Physical Review Research, 2023).

Comments on revised version.

In this response and revised manuscript, the authors have addressed all points raised in the first round of review. In response to Point 2.7, however, is it not the case that the Allen dataset has the axonal lengths?

Reviewer #2 (Public review):

Summary and Strengths:

This in-depth genetic analysis of Zasp52 function in Drosophila indirect flight muscle (IFM) provides an interesting perspective regarding the role of a partially disordered region (IDR) in exon 15e. This exon seems to be exclusively present in IFM and contributes to the prevention of myofibril disintegration during aging, likely due to interactions of this region with Z-disc insertion and/or stability. The addition of an isoform (PR) that lacks exon 15e serves as a nice control to illustrate the necessity of exon 15e in muscle structure and function. Overall, the manuscript is exceptionally well-written, logical, with nicely controlled experiments and detailed statistical analysis that largely support the conclusions drawn by the authors. While exon 15e is clearly involved in preventing muscle degeneration, a solid role for thin filament stability is not clearly shown (as mentioned in the abstract). In addition, which regions/how the proteins of the IDR may contribute are unclear.

Reviewer #2 (Public review):

Summary:

This manuscript examines how the statistical properties of others' charitable donations shape subsequent giving using four preregistered experiments and computational modelling. The authors find that both the average level and variability of observed donations influence donation behaviour, and that individual differences in social information use are associated with psychopathic traits.

Strengths:

This is a well-executed paper on the important question of how social information shapes charitable giving. In my view, the combination of preregistered experiments, large sample sizes, computational modelling, and a multi-paradigm approach makes for convincing evidence. The progression across experiments, the use of real donation data rather than deception, the incentivized experiment 4, and the generalization to a second paradigm are all notable strengths. The introduction is clearly written and well-motivated - an enjoyable read. The experimental paradigm is thoughtfully designed, and the methods and supplementary materials are described in considerable detail. The computational modelling provides useful additional insights beyond the behavioural analyses.

As far as I could tell, the manuscript also adheres closely to the preregistrations. The primary hypotheses, experimental designs, exclusion criteria, and key analyses are all consistent with the preregistered plans. Deviations seem to consist of methodological improvements (e.g., mixed-effects models replacing ANOVAs), additional computational and robustness analyses, and therefore strengthen rather than weaken the manuscript. (NB: for transparency, I would appreciate a clearer distinction between preregistered and post hoc analyses, as well as a brief explanation for why some preregistered secondary analyses are no longer reported; see minor comments below).

Overall, I enjoyed reading this paper. I believe it will make a valuable contribution. My comments below are intended to further strengthen an already solid manuscript.

Weaknesses:

(1) The rationale for the social-information phase could be clarified further. Given the research question, I wondered why participants observed the five donations sequentially (and only briefly) rather than simultaneously. In particular, variance is arguably more difficult than the mean to encode and remember, and a sequential presentation may both obscure distributional differences and introduce primacy or recency effects. It would be helpful if the authors could better motivate this design choice, and indicate whether they examined possible order effects.

Relatedly, I felt somewhat uncertain about the purpose of asking participants to predict each donation before observing it. The prediction phase appears to play an important role in the computational model, but its theoretical role is not clearly introduced. Is it intended as a measure of participants' evolving beliefs about the descriptive norm, or primarily as a modelling device? Finally, were these predictions incentivized (e.g., for accuracy), and if not, how should readers interpret them?

(2) I would appreciate having the full experimental materials reproduced in the Supplementary Information. This would make it easier to understand what participants experienced during the task, including what they were told about the "other participants" whose donations they observed.

Minor points:

(1) The interpretations around domain-generality would be strengthened by reporting the association between social information use in the charitable giving task and in the BEAST. Currently, both measures are shown to correlate with psychopathy, but it remains unclear whether individuals who rely strongly on social information in one task also do so in the other. Reporting this correlation (or explaining why it cannot be meaningfully computed) would provide a nice and direct test of a domain-general tendency to use social information.

(2) It would help to explain more explicitly why the standard deviation of donations is theoretically interesting in its own right. The motivation for studying the mean seems immediately intuitive, whereas the motivation for focusing on variability could be elaborated on further in the Introduction.

(3) As I said above, I think the manuscript follows the preregistrations closely. Maybe I missed it, but it seems that prediction accuracy and reaction-time analyses were omitted. It would improve transparency further if the authors would briefly mention the preregistered secondary analyses that are no longer reported (and explain why they were omitted).

Reviewer #2 (Public review):

Summary:

The manuscript by Lau et al. investigates the mechanisms underlying IRF4 and BLIMP1 transcriptional activities during antibody-secreting cell fate decision. Both master regulators of plasma cell differentiation, these two transcription factors have distinct targets and non-overlapping roles. The authors used an in vitro culture system to generate antibody-secreting cells from human naïve B cells, and scRNA-seq, Crispr Cas9 editing, and Cut&Run to dissect the molecular mechanisms defining their specificity.

Strengths:

The experiments are overall well executed, and the manuscript is well written. The in vitro culture model appears to generate genuine human antibody-secreting cells. The identification of non-conserved nucleotides within the binding motifs that induce the specific binding of IRF4 or BLIMP1 is convincing, novel, and exciting.

Weaknesses:

The authors need to correct some overstatements and flaws to improve the manuscript.

In Figure 1f, the authors aimed to determine whether in their culture system the plasma cells emerged from the plasmablasts or directly from the activated B cells. First, it is noticeable that the distinction between plasmablasts and plasma cells relies here only on the expression of CD138. It does not include a higher capacity to secrete antibody or their proliferative state. In Figure 1e, the authors could have strengthened their distinction by showing the Ki67 staining at day 21 for both subpopulations. Second, this question does not seem to be related to IRF4 or Blimp1 activity, and thus one could wonder if it is relevant to this study. Finally, and most importantly, the design of the experiment appears flawed to me. The authors sorted cells at day 7 of culture based on their expression of CD20 and put the two subpopulations back for 14 more days. This culture system is a stepwise system, and it is not specified if the CD20+ cells were put back in the day 7 condition or the day 0 condition with the CD40L stimulation. Have both conditions been tested? This experiment also assumes that all B cells have equal potential to differentiate into antibody-secreting cells. What if it is not the case and some are anergic or have committed to the memory B cell fate during the first 7 days? Then the day 7 CD20+ fraction would be enriched in these cells. Moreover, this experiment didn't show that the plasma cell derived from the plasmablasts in the strict sense of the term, as the CD138+CD20- cells could be a mix of proliferative plasmablasts and immature plasma cells.

In Figure 3a and thereafter, the authors claimed that IRF4 acted earlier than BLIMP1, but both deletions strongly affected differentiation at day 7. IRF4 might have a stronger effect, but it does not mean that it had an earlier effect. To substantiate their claim, the authors would need to demonstrate that, at an earlier time point, deletion of IRF4, but not BLIMP1, results in defective differentiation.

In Figure 3b, the authors stated that in each individual KO the expression of the other transcription factor was lower. Given that there were no cells in the gate, it is puzzling to figure out how these expressions were compared.

In Figure 3c, on the UMAP the bottom right part of the activated B cell cluster does not appear to be attributed to any condition. How can it be? Besides, it is highly surprising that at D9 we cannot see any plasmablast on these UMAP, even in the control. Based on the G1/S and G2/M scores, none of the ASC represented were proliferating. Could the authors explain this strong discrepancy with Figure 1?

Another discrepancy exists between Figure 3b and c: Figure 3b depicted no IRF4- or BLIMP1-expressing cells in either KO, so what were the stunted PC and the BLIMP-KO PC reported in Figure 3c? What are the signature genes defining pre-PC and the score depicted in Supplementary Figure 3d, as the materials and methods only state that they are intermediate between PC and B cells? Could the authors show IRF4, BLIMP1 and some of their known target expression in these populations?

The authors claim that BLIMP1 is not needed to initiate the transition from pre-PC to PC, but in Figure 1, the intracellular staining showed that at day 7 the antibody secreting cells already expressed BLIMP1. This would rather suggest that BLIMP1, unlike IRF4, does not need to be maintained once the cell reaches a certain point.

Reviewer #2 (Public review):

Summary:

The authors tested whether the olfactory cues that drive attraction or avoidance behavior have diverged between surface‑dwelling and cave‑adapted strains of the Mexican cavefish Astyanax mexicanus. They use high‑throughput odor‑discrimination assays between known attractants and repellents by calculating an "odor index" per fish (=the difference in time spent in an odor zone versus a control zone). Further, hybrid crosses to probe heritability, starvation experiments to assess plasticity of odor perception, and whole‑brain pERK detection/mapping to link behavioral changes with known localized neural activity. The results support the hypothesis that the extreme cave environment has selected for an approach response to stimuli that are ancestrally aversive (like alarm or death odors) but in harsh environments can be used as guidance to the rare food sources in this ecosystem.

Strengths:

The odor index analysis is convincing, and the experiments for odor attraction/avoidance are robustly performed. The light-to-darkness shift reflected by avoidance to attraction in cavefish towards skin odors is compelling and carefully analyzed. The analysis of odor indices of three cave-dwelling populations in comparison to surface fish highlights a similar regime, yet with differences among the different populations, suggesting population-specific genetic variation.

Another strength of the paper is exactly this genetic inheritance study by generating F2 hybrids of cave-dwelling and surface-living individuals. The hybrids displayed a continuous range of odor indices for social, alarm, and death odors, indicating that these traits are heritable and likely based on additive genetic markers. Further, the authors uncovered a sexual dimorphism: only female cavefish exhibited approach behavior to social odors, whereas males remained neutral. This result aligns with known differences in olfactory organ morphology between sexes of other species from harsh environments.

Although limited in number, the neurophysiological correlation using whole‑brain pERK mapping after 10 min of odor exposure is convincing. The data revealed overlapping activation in the thalamus and pre‑optic region for food and decay odors, suggesting that these brain areas mediate the evolved attraction response to previously repellent stimuli.

Overall, the manuscript presents a concise story: cavefish have evolved attraction to alarm and death odors as a result of shifting from ancestral avoidance-driven to attraction by genetic changes and physiologically similar activation of specific neural circuits. The evidence is robust, with multiple independent experiments (behavioral assays, hybrid genetics, starvation experiments, and brain mapping) that collectively support the conclusions.

Furthermore, exposure to unpleasant odors can not only be tolerated but can even serve as a trigger for foraging. This plasticity demonstrates that genetic predispositions can be put into practice through active changes in physiology in species or organisms confronted with (drastically) changing environmental conditions.

Weaknesses:

I value that the authors are critical of their own data, indicating low numbers in the pERK/brain experiments. Yet this is a weak point as the statistical power is thus limited. However, their reasoning is careful, based on the results and not over-interpreting.

The layout/design of the ethograms (bout category plots) for both individual and population-wise are not easy to follow. Reworking these display items to convey the information is necessary.

Taken together, the manuscript uses odor perception and attraction/avoidance behavior studies to show that environmental changes (light-to-darkness) have an immediate impact on smell perception and behavior. Attraction to otherwise repellent odors is used by cavefish to likely adapt to harsh environments with low food sources. The manuscript convincingly demonstrates this plasticity, which is an interesting idea to follow up for other traits spreading among a population. This also underlines that a genome may be fixed and the blueprint for behavioral traits, but extrinsic cues can readily be adapted to change wired behavior even to the extreme as reported here: changing avoidance to attraction.

Reviewer #2 (Public review):

Summary:

In this short paper, a clever single-cell Strand-seq method was used to study the number and location of sister chromatid exchange events (SCEs) in cells after CRISPR/Cas9-induced DNA double-strand breaks (DSBs). Unique as well as multiple genomic loci were targeted. Cas9-induced cuts at unique genomic locations led to statistical enrichment of SCEs at the target site, whereas Cas9 targeted at repetitive targets revealed only mild enrichment of on-target SCEs unless analysis was restricted to a subset of cells with >8 SCEs per cell. Interestingly, reciprocal daughter-cell pair analysis revealed large-scale structural alterations on some chromosomes. Whereas disruption of DNA repair genes, including LIG3, LIG4, XRCC1, and XRCC4, did not measurably alter SCE frequency per cell within 24 hrs, consistent with delayed functional loss following editing and selection against essential genes. Together, these findings demonstrate that Cas9-induced DSBs are potent local triggers of SCE at unique loci and can be associated with structural alterations, highlighting the influence of lesion type and genomic context on recombination outcomes during genome editing.

Strengths:

The data in this paper represent a very rich resource of how parental DNA template strands are distributed in paired daughter cells after various treatments. Abnormalities observed in only one of such paired daughter cells provide a novel and exciting approach to study mechanisms of DNA instability and DNA repair at a genome-wide level in general and following Cas9-induced DSB in particular.

Weaknesses:

The effect of Cas9-induced DSBs in the cells that are used will depend on the cell cycle stage of the cells that are targeted, as well as the number of times cuts are made. The latter could happen before, during, and after DNA repair reactions on one or both alleles in a diploid cell. As a result, it is very difficult to extrapolate the mechanisms of DNA instability and DNA repair from the observed genomic rearrangements. Novel approaches are needed to limit the number and timing of Cas9-induced breaks to overcome some of these limitations. The language and logic in the paper can be improved, and some of the claims seem incorrect. For example, the abstract reads "A single Cas9 cut at a unique genomic locus led to strong local enrichment of SCE at the break site, reaching up to 41% in the same cell cycle and 17% in the subsequent division, indicating that DSB repair frequently engages non-local inter-sister repair." The evidence that only a single Cas9 cut was made is lacking (see my earlier comment); it is not clear how local enrichment or non-local inter-sister repair are defined.

Reviewer #2 (Public review):

Summary:

The authors use DRL to train a C. elegans connectome-based ANN to control stepping in a D. melanogaster body model. The resulting system can walk. This shows that one needs further constraints to derive biologically meaningful results from this approach.

Strengths:

The authors perform a very simple experiment with a clear outcome. The interpretation (or lack of interpretation) is a striking cautionary tale.

Weaknesses:

There is little analysis of precisely how robust this result is to parameter variation and network wiring. The worm also undulates in an oscillatory fashion. Thus, it is possible that the network is tapping into biologically meaningful motifs to generate oscillations for walking. As well, it would be useful to examine which heuristics one can use to determine whether modeling efforts are sufficiently constrained (i.e., how much biological data will be necessary to start obtaining fruitful, interpretable outcomes from DRL task optimization). For example, their "solution" using the worm connectome is not sparse (i.e., it uses many neurons). Perhaps a signature of a biologically-meaningful, interpretable result is one that is sparse?

Reviewer #2 (Public review):

Summary:

The authors showed the expression of TGR5 in hematopoietic compartments and that loss of TGR5 doesn't impair steady-state hematopoiesis. Notably, TGR5 knockout significantly decreases BMAT, increase the APC population and accelerate the recovery upon bone marrow transplantation.

Strengths:

The role of TGR5 is interesting.

Weaknesses:

Additional mechanistic studies would further strengthen the work and provide deeper insight into how TGR5 regulates the bone marrow microenvironment.

Reviewer #2 (Public review):

Summary:

Ma and colleagues presented a study on the characterization of brain-wide spatio-temporal impact of olfactory cortical outputs. They take advantage of multi-modal techniques on rats: fMRI, optogenetics and electrophysiology. In addition, they used cutting-edge analytical techniques and modeling to support and interpret their data. The main findings of the study are:

(1) Neurons in Olfactory Bulb (OB) predominantly activate primary olfactory network regions, while stimulation of OB afferents in Anterior Olfactory Nucleus (AON) and Piriform Cortex (Pir) primarily orthodromically activates hippocampal/striatal and limbic networks, respectively.<br /> (2) Non-specified adaptation or habituation mechanisms may play a significant role in modulating olfactory outputs over subsequent fMRI sessions.

(3) Artificially induced aging in rats induces profound modification in the functional interaction between olfactory cortices and multiple brain regions.

The results on AON are of particular interest because of the lack of functional information on this region, despite its recognized importance in shaping OB output and behavior (odor localization tasks).

Strengths:

The manuscript is very accurate. The figures are well-crafted, clear and provide much information with the most appropriate plots and graphics. The study's amount and data quality are remarkable, and the experimental size adequately addresses the scientific questions. I particularly appreciated the details in the description of the methods regarding the missing data and the size of the different animal groups. The supplementary data complete the leading figures and provide information at a single animal level.

Weaknesses:

(1) One of the main reasons the Piriform Cx is understudied in rodents is because of the proximity to air, which creates artifacts in fMRI images. This issue becomes more critical at ultra-high magnetic fields, but I would expect it also at 7T. One main achievement of this study is, indeed, the acquisition of fMRI data from Piriform, and this point should be highlighted by showing raw functional data from a rat. The best would be if an fMRI data sample for a rat, no matter which stimulation, is shared on a public repository, like Zenodo or similar. I am curious to check the quality of the BOLD data from such an 'enormous' field of view, particularly in the OB, with a single-shot sequence. Also, the visual inspection of raw data is essential to appreciate how many 0.5 x 0.5 x 1 mm voxels fit into AON, and others analyzed small brain structures, like the amygdala, etc. Was the amygdala entirely visible in BOLD, or did the air in the ear channel make an artifact partially shadowing it?

(2) Surprisingly, the only information missing in the methods is the post-surgery period and the time between two consecutive fMRI sessions. How much time was accorded to rats to recover from the surgeries, and what time interval between two scans? This information is crucial for interpreting the decrease in most BOLD responses in subsequent recordings. The supposed adaptation should fit into the known time frames for odor adaptation. Usually, fast adaptation does not last for days (and it should be measured within a single experiment: is it the case?), while for long-lasting adaptation the stimulus (odor or opto) should be maintained constantly ON. This does not seem to be the case in this study. The hypothesis, alternative to adaptation, of a less efficient light activation, for example, due to gliosis around the fiber tips, should be discarded with more evidence than the preservation of OB > Pir responses or acknowledged in the manuscript.

(3) The D-galactose experiments were conducted only after administering the aging molecule, with no baseline/reference data on the same animals. Then, comparisons were made with healthy rats, but the two groups not only can be discriminated with respect to D-galactose administration but also with age (10 VS 18 weeks). A control group for 18-weeks-old rats with no D-galactose treatment would better compare the D-galactose effect and avoid any potential bias from group comparisons of rats at different ages. Do you confirm that D-galactose was injected into each rat 56 times/days in a raw, or am I mistaken?

The updated version of the manuscript partially addresses the flaws of the original submission. Here are my general concerns:

(1) Overall, the revised version comes with a few modifications/additions and no new data. Apart from a new correlation analysis, the improvements are mainly discursive, often non-convincing, justifications of the authors' choices. This may reflect a lack of interest in a publication that, in the meantime, lost its original peer-review value. However, it should be acknowledged that the Authors made an effort to partially address the concerns raised by the reviewers.

(2) My main concern was the quality of fMRI recordings. In the revised version, the Authors provided a new figure with an example single-mouse fMRI data. However, the depicted regions of interest (ROIs) mostly cover the brain spots that I expected to be the most impacted by the BOLD artifacts caused by the proximity of the air and the big field-of-view. In addition, these ROIs do not appear to match the mouse anatomy shown above the functional data. As an example, the EPI images in the OB are almost entirely covered by the colored mask. The feeling is that the fMRI data was indeed poor, as I worried, and the lack of any public repository of raw data reinforces that feeling. To make this point clear: I do not think the findings are not true, but poor fMRI data quality might have hidden more insightful results and does not foster the use of fMRI to monitor the olfactory pathway, which lowers the impact of this article.

Reviewer #2 (Public review):

Summary:

Overall, the authors aimed to provide evidence that clarifies two debates within metacognition research concerning subjective confidence reports:

(1) Does the post-decision confidence report arise from the same process that drives the initial decision, or does a separate, independent process support confidence computation?

(2) How do we stop accumulating evidence for the post-decision confidence report? Is it based on a self-imposed time limit, or on accumulated evidence crossing a boundary?

For the investigation, the authors constructed four models (2 × 2 factorial) to compare each combination of processes to account for random-dot motion tasks data with speed/accuracy manipulations. The models are generally embedded in the drift diffusion model framework, retaining basic parameters such as drift rate, boundary separation, starting point, and non-decision time, while adding linearly collapsing boundaries to model the initial choice. For the single vs. distinct process dimension, the difference lies in whether post-decision evidence accumulation is referenced to the endpoint of the initial decision process or restarts from a new, freely estimated starting point. For the time- vs. boundary-based stopping rule dimension, the key difference is that post-decision evidence accumulation stops either at a deadline sampled from a normal distribution or when the accumulated evidence hits a collapsing boundary.

Based on model comparison, the boundary-based stopping rule clearly outperformed the time-based stopping rule. However, models with the boundary-based stopping rule performed similarly regardless of whether a single or distinct process was used. Here, the authors drew additional insights from EEG recordings during the task, focusing on the centro-parietal positivity (CPP), which has been proposed as a neural correlate of the evidence accumulation process. By simulating evidence accumulation trajectories (with additional assumptions) and comparing the patterns of those trajectories with observed ERP waveforms, the authors argued that the single-process model provided a better match to the CPP findings and was therefore preferred. This was specifically demonstrated by the model's superior ability to match the pre-response CPP amplitude differences conditioned on the post-decision confidence-related variables.

Strengths:

(1) The authors translated existing theories into computational models of decision-making and systematically compared different cognitive processes by assessing model fits to the data. This provides strong evidence supporting the idea that post-decision confidence reports could be better explained by boundary crossing rather than a self-imposed deadline to respond.

(2) Beyond model evidence, an important result is that CPP amplitude predicted confidence before the initial choice was reported, which is a unique prediction of the single-process model. The use of EEG as an independent validation measure provided additional evidence in favour of this model.

(3) Combining points 1 and 2, this study successfully addressed the two key debates with solid evidence to favour one theory over another.

(4) Another strength of this study is the data quality. The high number of trials provided a strong foundation for model inference as well as ERP analysis. The experiment also contained a speed-accuracy manipulation to evaluate model performance across diverse situations.

Weaknesses:

I have two main concerns around the modelling work and neural analyses, which in my opinion could have limited the interpretation of the findings. My responses here will be lengthier, but this reflects the nature of the modelling work rather than implying stronger criticisms than those suggested by the strengths discussed above.

(1) There are a few assumptions in the models that lack psychologically meaningful interpretations, and this study placed more effort into model comparison while lacking discussion of the cognitive processes inferred from parameter estimates.

To start, I think some of the parameterisations were not properly justified. For the boundary models, it is not very clear why the upper and lower boundaries were different and collapsed at different rates for confidence decisions, given that a single boundary parameter and collapse rate were used for the initial decision. This allows more flexible shifts in the model's predictions of confidence ratings without strong justification. Specifically, it is unclear why the boundary-single model has such an implementation while the boundary-distinct model was only equipped with one boundary parameter (a2, compared to a2up and a2down).

Similarly, the inclusion of metacognitive noise creates another layer of flexibility in the predictions of confidence ratings. In most existing evidence accumulation models with a diffusion process, noise comes from two sources: within-trial noisy evidence accumulation and across-trial variability (e.g., drift rate variability). Beyond these, such models almost always assume that the decision is made deterministically once the evidence reaches a specific boundary. The inclusion of metacognitive noise here sounds more like a noisy decision-to-action mapping.

I also have similar doubts about allowing the non-decision time parameter for confidence accumulation in the distinct model to be negative. The authors argued that confidence accumulation may begin during initial evidence accumulation. However, this is a flawed implementation, as the non-decision time was simply added to the evidence accumulation time rather than being incorporated within it. Allowing negative non-decision times may achieve similar predictions, but it is ad hoc.

The inclusion of a collapsing boundary mechanism in the post-decision confidence accumulator helped the model reach more diverse levels of accumulated evidence and ultimately improved predictions of confidence ratings. However, no strong argument is presented for this implementation beyond the observation that the model performs worse without it. The collapsing boundary mechanism has traditionally been interpreted as reflecting a sense of urgency. For the boundary models, I noticed that the collapse rate of the upper boundary differed significantly between speed and accuracy conditions, which is consistent with the urgency interpretation. Overall, I would like to see more discussion of the specific model mechanisms included by the authors, interpreted in light of parameter estimates.

(2) While the ERP findings provided external evidence and validation of the modelling results, I find the simulation practices not particularly useful and potentially misleading for naive readers. Specifically, the authors attempted to draw a parallel between patterns of simulated evidence accumulation traces and observed CPP waveforms. While the CPP has received support as a correlate of the evidence accumulation process, the DDM is by no means a neural model capable of generating predictions of neural observations. To my understanding, the superior fit of the boundary-single model was primarily due to the fact that pre-response CPP amplitude predicts post-decision confidence ratings. Therefore, as the boundary-distinct model did not connect the two phases of evidence accumulation, it would fail to account for this observation. I think this point could be clearly demonstrated without the need to introduce additional assumptions into the model simulations in order to directly compare averaged trajectories with averaged ERP waveforms. While the authors did not explicitly claim otherwise, this approach creates an illusion that the model can mechanistically account for ERP data. I would like the authors to provide explicit clarification on this point.

Appraisal:

Overall, the authors have provided solid evidence in support of their research aims. The findings contribute to longstanding debates with insights from model mechanisms and neural findings that should not be overlooked by future studies on this topic. This study also offers a good starting point for future model development and refinement in broader contexts of confidence reporting, such as paradigms involving simultaneous initial decisions and confidence judgements. The high quality of the behavioural and EEG data will make a valuable contribution to future research.

Reviewer #2 (Public review):

Summary:

The authors studied cognitive control and attention in response to mnemonic prediction errors (MPEs): situations in which the external reality violates internal memory-based predictions. The behavioral task first established strong versus weak predictions, and then either confirmed or violated these predictions. The authors examined markers of cognitive control (frontal theta) and attention (posterior alpha suppression, pupil response) while strong and weak predictions were confirmed or violated. They found increased cognitive control (frontal theta) for strong MPEs, which correlated with subsequent memory. Markers of attention (alpha suppression, pupil response) also accompanied strong MPEs but did not correlate with subsequent memory. Pupil response was investigated using an interesting approach that decomposes the response into different components, finding that different components respond earlier or later and show different correlations with MPEs and their strength. The authors also investigated how EEG, reaction time, and pupil responses correlated with one another, providing further insight into the mechanism underlying the response to MPEs. Together, the study points toward multiple control and attention mechanisms involved in MPE response and memory.

Strengths:

The study has a clear behavioral paradigm with multiple measures - behavioral, EEG, and pupillometry that offer an investigation into different aspects of MPE response and memory.

The study is also very comprehensive in looking at multiple phases in processing MPEs: the prediction phase (prior to the violation), the response to MPEs, and subsequent memory of MPEs, all within one study. Specifically, the link between neural mechanisms and subsequent memory is a major advancement, as most prior studies did not include this component. Mechanisms underlying subsequent memory of MPEs are theoretically important, as a primary function of MPEs is to promote learning and memory. As the authors mention, the different neural and pupillary signals are not robustly correlated, suggesting multiple mechanisms underlying MPE detections, which is interesting, offers avenues for future research, and can facilitate a better theory of how MPEs are processed in the brain. Finally, the decomposition of pupil response into different components and their correlation with behavior (RT during match/MPE detection) is interesting.

Weaknesses:

The methods are rigorous, and the data support the claims. The weaknesses are minor and are offered here as avenues for future research.

(1) The relationships the authors find between brain measures and pupil components were largely not specific to mismatches/matches. Thus, the specificity of this relationship is untested.

(2) The results with subsequent memory are important and address a major gap in the field that largely did not relate neural effects of MPE to subsequent memory. However, one major limitation of the study is that the authors did not test memory for matches. I understand the logic of avoiding testing matches. Because matches were repeated more times in the study, it's not a fair comparison and could change participants' overall criterion for old/new decisions. Future research could address this, e.g., by testing weak matches or potentially using a between-subject design.

Comments on revised version.

The authors addressed all my concerns. I appreciate the authors' thoughtful and detailed response.

Reviewer #2 (Public review):

The authors investigate the contribution of dorsal CA1 hippocampal dysfunction to cognitive impairments in the Cntnap2 knockout mouse model of autism spectrum disorder. Building on previous evidence implicating the hippocampus in episodic and relational memory processes, they combine trace fear conditioning, fiber photometry, optogenetic manipulation, a relational/declarative memory radial maze task, and cFos mapping to test whether altered CA1 function contributes to deficits in temporal binding and memory flexibility.

The study has several important strengths. First, the work addresses a relatively understudied aspect of autism-related cognition, namely hippocampal-dependent memory processes, whereas much of the literature has focused on social behavior, cortical circuits, or striatal dysfunction. Second, the authors employ multiple complementary approaches that converge on a coherent mechanistic hypothesis. The behavioral data demonstrate a reduced ability of Cntnap2 knockout mice to retain associations across long temporal gaps. Fiber photometry recordings reveal reduced dorsal CA1 activity during conditions that challenge temporal binding, and optogenetic activation of dorsal CA1 neurons during the trace interval is sufficient to rescue memory performance. Together, these findings provide strong support for a causal contribution of dorsal CA1 activity to temporal binding deficits in this model.

The second major strength of the manuscript is the extension of these findings to a more complex hippocampus-dependent memory task. The radial maze experiments indicate that Cntnap2 knockout mice show impaired memory flexibility and a greater reliance on egocentric learning strategies. The accompanying cFos analyses suggest altered recruitment of hippocampal and striatal networks during learning, providing a systems-level framework that may explain the observed behavioral phenotype.

Overall, the main conclusions regarding impaired temporal binding and reduced dorsal CA1 engagement are well supported by the data. The optogenetic rescue experiments are particularly compelling because they move beyond correlation and directly test causality. The manuscript therefore makes a meaningful contribution to our understanding of how hippocampal dysfunction may contribute to cognitive abnormalities associated with autism.

Weaknesses:

Some conclusions are necessarily more inferential than others. In particular, the interpretation that the observed behavioral phenotype reflects a broader shift from hippocampal-dependent declarative memory toward striatum-dependent procedural learning is supported primarily by cFos activity patterns and behavioral strategy measures. While the data are consistent with this interpretation, they do not directly demonstrate a causal reorganization of memory systems. Similarly, although the findings identify a mechanism in the Cntnap2 model, caution is warranted when extrapolating these conclusions to autism spectrum disorder more broadly; but I believe this caution is addressed in the discussion.

Despite these limitations, the study presents a coherent and well-executed body of work that provides novel mechanistic insight into hippocampal contributions to cognitive dysfunction in a widely used autism model. The findings should be of considerable interest to researchers studying hippocampal function, memory systems, and neurodevelopmental disorders.

Reviewer #2 (Public review):

Summary

This manuscript by Schilling et al. presents an important advancement in our understanding of how mTOR signaling regulates organismal aging. While the longevity-promoting effects of reduced mTOR activity have been extensively documented across species, the mechanisms by which mTOR communicates systemic metabolic information to regulate lifespan remain unclear. In this study, the authors provide strong evidence that longevity induced by reduced TORC1 signaling requires the bile acid-like steroid hormone dafachronic acid (DA) and its cognate nuclear receptor DAF-12. Furthermore, through a combination of transcriptomics and functional genomics, they identify the conserved short-chain dehydrogenase DHS-26/DHRS1 as a previously unrecognized downstream effector of this pathway. The work integrates genetics, lifespan analyses, sterol measurements, transcriptomics, proteomics, endogenous genome engineering, and comparative mammalian datasets. The resulting model, in which mTOR influences lifespan through regulation of endocrine steroid signaling, represents a conceptual advance that links nutrient sensing, metabolism, and organismal aging. Although several mechanistic questions remain unresolved, the study is comprehensive, technically rigorous, and likely to be of broad interest to investigators studying aging, metabolism, endocrine signaling, and cellular stress responses.

Strengths:

One of the major strengths of this manuscript is its conceptual novelty. Rather than reinforcing the well-established role of mTOR as a longevity regulator, the study proposes a specific endocrine mechanism that links reduced mTOR activity to increased lifespan through steroid hormone signaling. This advances the field beyond descriptive observations of mTOR-dependent longevity and introduces a model in which bile acid-like hormones function as systemic mediators of nutrient-sensing pathways. The idea that endocrine steroid signaling may serve as a downstream effector of mTOR provides a new perspective on how longevity signals are coordinated at the organismal level.

The genetic evidence supporting this model is particularly strong. In Figure 1, the authors use a series of epistasis experiments to demonstrate that mutations in daf-36, daf-9, and daf-12 suppress lifespan extension in raga-1 mutants. The DA supplementation experiments further strengthen the pathway ordering by rescuing longevity in hormone-deficient backgrounds while failing to restore lifespan in receptor-deficient animals. Importantly, the direct quantification of endogenous DA levels elevates the study by providing biochemical support for the proposed model.

The transcriptomic analyses presented in Figure 2 provide a valuable systems-level perspective on the interaction between mTOR and steroid signaling pathways. The observation that DAF-12 profoundly reshapes the RAGA-1 transcriptional program highlights the importance of steroid signaling in mediating the physiological consequences of reduced mTOR activity. The enrichment of metabolic, lysosomal, and peroxisomal pathways is consistent with established longevity-associated programs and generates a valuable resource for future mechanistic studies.

Figure 3 effectively integrates discovery-driven and hypothesis-driven biology. The authors use transcriptomic information to prioritize candidate genes and then perform a functional genomic screen to identify factors required for RAGA-1-mediated lifespan extension. This approach converges on DHS-26, which subsequently emerges as a central mechanistic component of the study. The progression from transcriptomics to functional validation is well executed.

In Figure 4, the generation of CRISPR-engineered dhs-26 deletion mutants and endogenous tagged reporter strains provides strong validation for DHS-26 function. The demonstration that dhs-26 deletion selectively abolishes RAGA-1-dependent longevity without substantially affecting wild-type lifespan strongly supports its role as a context-dependent mediator of mTOR signaling. Furthermore, the conservation analyses linking DHS-26 to mammalian DHRS1 provide biological context and enhance the broader significance of the findings.

In Figure 5, multiple independent experimental approaches converge on the conclusion that DHS-26 participates in DA-dependent lifespan regulation. The rescue of lifespan by DA supplementation, reductions in DA levels in raga-1;dhs-26 mutants, reporter-based analyses of DAF-12 activity, and proteomic profiling collectively support a mechanistic model. The proposed positive feedback relationship between DA/DAF-12 signaling and DHS-26 is intriguing and offers a plausible explanation for how endocrine signaling may amplify longevity-promoting responses. Finally, the incorporation of mammalian datasets showing regulation of DHRS1 by rapamycin and FXR signaling provides a promising avenue for future studies investigating conservation of this pathway.

Weaknesses:

Despite the many strengths of the study, important mechanistic questions remain unresolved. The most significant limitation is that the precise molecular connection between reduced mTOR activity and increased DA production remains unclear. While the genetic and biochemical data convincingly place DA/DAF-12 signaling downstream of mTOR, the study does not establish whether mTOR regulates DA biosynthesis, degradation, intracellular trafficking, sterol uptake, or hormone availability. The observed increase in endogenous DA levels is statistically significant but relatively modest, and the mechanistic basis for this increase remains speculative. Additional experiments examining sterol flux, enzyme activity, or intracellular sterol trafficking would substantially strengthen the proposed model.

The transcriptomic analyses in Figure 2 are informative but correlative. Because the RNA-sequencing was performed at a single adult time point, it remains difficult to distinguish primary transcriptional responses from secondary adaptive changes. Similarly, while pathway enrichment analyses identify plausible processes, they do not establish direct regulatory relationships. Additional temporal analyses or direct assessment of DAF-12 occupancy at candidate loci would strengthen mechanistic interpretations and help distinguish direct from indirect targets.

A major unresolved question concerns the biochemical function of DHS-26 itself. While the genetic evidence clearly establishes DHS-26 as an important regulator of RAGA-1-mediated longevity, its endogenous substrate and enzymatic activity remain unknown. The manuscript presents evidence linking DHS-26 to sterol metabolism, but direct biochemical characterization is lacking. Thus, the mechanistic model remains somewhat incomplete. Defining the substrates and products of DHS-26 activity would greatly strengthen the study and provide important insight into how this enzyme influences DA availability.

Another area requiring additional clarification is the proposed neuroendocrine role of DHS-26. The expression of DHS-26 in canal-associated neurons is interesting and raises the possibility that these cells participate in systemic longevity regulation. However, the current data do not establish whether DHS-26 functions autonomously within these neurons or whether expression in other cell types contributes to the observed phenotypes. Tissue-specific rescue or depletion experiments would strengthen the neuroendocrine model and help establish physiological sites of action.

Finally, the mammalian data presented in Figure 5 are supportive and suggestive of evolutionary conservation, but they remain correlative. While regulation of DHRS1 expression by rapamycin and FXR signaling is interesting, these observations do not yet demonstrate functional conservation of the longevity mechanism itself. Additional studies directly testing DHRS1 function in mammalian systems will be required before stronger conclusions regarding conservation can be drawn.

In summary, this manuscript provides a significant contribution to the aging field and introduces a model linking mTOR signaling, endocrine steroid hormones, and longevity. The study is comprehensive, technically sophisticated, and supported by multiple complementary approaches. Although some mechanistic questions remain open regarding the precise regulation of DA production, the biochemical function of DHS-26, and the extent of conservation, these limitations represent opportunities for future investigation. Overall, the work substantially advances our understanding of how nutrient-sensing pathways regulate aging and is likely to stimulate considerable interest within the fields of aging biology, metabolism, and endocrine signaling.