Reviewer #2 (Public review):

The Revision title and abstract are not updated enough to distinguish the special niche piRNA clusters from the more prominent major dual strand piRNA clusters that are widely known in the field for Drosophila, like 42AB and 38C. This revision mainly adds the term "piRNA source loci (piSL)" that is too vague and not a well-accepted name that would distinguish just these particularly niche piRNA clusters from major dual strand piRNA clusters like 42AB and 38C. This piSL term is problematic because it seems to imply these piSL's are connected to or would eventually become major dual strand piRNA clusters, but there is zero evidence in this study for any genetic or evolutionary connection between these two distinct types of piRNA sources. This revision still lacks the necessary changes needed to point out like in the abstract that major dual strand piRNA clusters like 42AB, 38C, 80F, and 102F in Drosophila that make up the bulk of piRNAs cannot be shown to be impacted by changes aimed at depleting ADMA-histones from these loci, and the authors' current evidence is still only limited to showing in these few 'niche' piRNA clusters that ADMA-histones may exhibit a direct interaction with Rhino as supported only by the knockdown of Drosophila Art4.

The author's rebuttal letter argues that 42AB and 38C are just conserved piRNA clusters that may no longer be regulated by ADMA. This is still a weak claim for dismissing the potential genetic redundancy problem when this study can only report strong knockdown of Art4. First, the dual strand 42AB piRNA cluster's conservation as a Drosophilid piRNA cluster is actually still a relatively recent evolutionary innovation in just D.simulans and D.melanogaster that are less than 3MYA diverged. This 42AB cluster is no longer conserved in D.sechelia and is also younger than the uni-strand Flamenco piRNA cluster that is conserve to 7MYA. The evolutionary arguments by the authors are not well-grounded. Second, the 42AB and 38C are the largest major dual strand piRNA clusters with very significant localization of Rhino and impact from Rhino loss of function, and if this paper's central thesis is that ADMA-histones directed by Art1 or Art4 is critical for the expression of dual-strand piRNA cluster loci by impacting Rhino, the current data still remain weak with no new experiments to help bolster their claims.

The author's rebuttal letter argues that the challenges they faced in trying to knock down Art1 in the fly was thwarted by reagent issues, and the explanations are unsatisfactory. They claim they only tested two RNAi cross lines to try to knock down Art1: the strain BDSC #36891, y[1] sc[*] v[1] sev[21]; P{y[+t7.7], v[+t1.8]=TRiP.GL01072}attP2/TM3, Sb[1] that they said they could not obtain this strain to be alive from the stock center? And then testing an alternative line VDRC #v110391P{KK101196}VIE-260B that displayed mediocre knockdown, the authors seemed to suggest they have given up trying to make this very important experiment work? They should have tried to figure out with the BDSC, a venerable stock center for Drosophila genetic tools, why they could not receive that fly strain alive (shipping flies at the economy rate internationally may be cheaper but often is too strenuous for flies to survive), and the authors have not acknowledged testing two other available knockdown lines for Art1: BDSC #31348, y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.JF01306}attP2 dsRNA and VDRC #w1118 P{GD11959}v40388. Trying to get good knockdown of Art1 would be a critical must-have experiment to address whether this arginine methyltransferase has an in vivo impact on ADMA-histones in the Drosophila ovary and showing an impact on 42AB and 38C. The revision does not address this major deficiency in impact on these two major dual strand piRNA clusters, only the very few niche piRNA clusters that are responsive to Art4 knockdown.

The rebuttal letter argues that "Therefore, conserved clusters such as 42AB and 38C may no longer be regulated by ADMA." but then the revision discussion is still speculating much too wildly that the piRNA source loci are then precursors for the eventual large piRNA clusters of 42AB and 38C. This renaming of the term piRNA source loci and the model in Fig. 7C is still misleading because 42AB and 38C are the main largest dual-strand piRNA clusters, and the pictures depict the ADMA-histones as recruiting Rhino and then Kipferl at a piRNA cluster. The term "piRNA source loci" does not sound distinct enough to separate it from the main piRNA clusters of 42AB and 38C, and I had suggested calling them 'niche piRNA clusters' to denote they are very special and distinct to only be responsive to Drosophila Art4 knockdown.

In regards to the revision's changing of gene names, the convention for gene names is to use the previous name designation. Rather than calling the gene DART1, the conventional name of this gene in Flybase is Art1 (CG6554). There is the same problem with using the new name DART4 when in Flybase the gene is called Art4 (CG5358). Alternatively, the authors should clarify the re-naming up front and make it consistent with Drosophila genetics nomenclature, perhaps dArt1 or dArt4 would be more appropriate.

Reviewer #1 (Public review):

Summary:

Even though mutations in LRRK2 and GBA1 (which encodes the protein GCase) increase the risk of developing Parkinson's disease (PD), the specific mechanisms driving neurodegeneration remain unclear. Given their known roles in lysosomal function, the authors investigate how LRRK2 and GCase activity influence the exocytosis of the lysosomal lipid BMP via extracellular vesicles (EVs). They use fibroblasts carrying the PD-associated LRRK2-R1441G mutation and pharmacologically modulate LRRK2 and GCase activity.

Strengths:

The authors examine both proteins at endogenous levels, using MEFs instead of cancer cells. The study's scope is potentially interesting and could yield relevant insights into PD disease mechanisms.

Weaknesses:

Many of the authors' conclusions are overstated and not sufficiently supported by the data. Several statistical errors undermine their claims. Pharmacological treatment is very long, leading to potential off target effects. Additionally, the authors should be more rigorous when using EV markers.

Comments on revisions:

The authors have not addressed most of my concerns. For example, instead of trying with a 1-2 hour MLi2 treatment, they cited all the papers that use extremely long time points for LRRK2 inhibition; the fact that other groups do it does not mean it is biologically correct. They also refused to quantify their western blots in a proper manner, without the "hyper-normalization" claiming that it is an accepted way to quantify western blots. Again, it is statistically incorrect and biologically impossible. They also do not have a satisfactory explanation as to why the R1441G cells (which increase LRRK2 kinase activity) have no effect on EV release, but they still claim it is LRRK2 kinase activity dependent.

Overall, I am very confused by the model proposed by the authors. They only see increased EV release in the G2019S expressing cells, but not the R1441G cells, yet they claim that the increase of EV release is LRRK2 kinase activity dependent. Then, they claim that the presence of BMP (unchanged in R1441G vs CTL) in EVs is also LRRK2 kinase activity dependent. Finally, they perform TIRF with pHluorin-CD63 construct and observed an increase in G2019S cells vs CTL "further confirming that BMP release is associated with EV secretion". First, I could not see the increase in BMP release in G2019S cells (if I missed it, I apologize). And second, why didn't they do this experiment in R1441G cells? As, the R1441G cells have not displayed an increase in EV release compared to CTL cells, it could also be possible that the BMP release might be more abundant through lysosomal exocytosis (which could explain the pHluorin results) than EVs. Overall, the authors nicely demonstrate that the R1441G cells have more BMP species, likely due to increase CLN5 expression, but the release of the BMP is still not clear to this reviewer.

Reviewer #1 (Public review):

Summary:

Marchand et al. seek to understand how basement membrane (BM) is initially assembled around developing vasculature (and by extension basement membrane assembly generally progresses). To do this, they use an established cell culture system that is amenable to advanced microscopy techniques, including high-resolution fluorescence imaging and atomic force microscopy. This allows them to produce very high-quality imaging data that includes both protein localization and matrix topography in 3D. They show that fibronectin (FN) is remodeled as collagen IV (Col IV) assembles. Lysyl oxidase-like-2 (LOXL2) is needed for this process, and without it, BM does not form correctly, cells cannot adhere to BM, and cells also don't correctly form junctions with other cells.

Detailed Review:

The authors provide quantitative measures of BM fibril assembly at the earliest timepoints. They show two phases of growth - initial deposition, elongation, and interconnection of short fibers; the second is a significant thickening. As the BM forms, FN is immediately associated with filaments, but laminin and Col IV are not associated with fibers as detected by AFM. LOXL2 is associated with fibers, similar to FN. At a later time point, Col IV becomes associated with fibers, but laminin never does. Likely FN templates LOXL2, which crosslink Col IV into fibrils over time. Could the authors comment on how this data fits with in vivo data from model organisms? Also, I would like to know if they can uncouple LOXL2 from the FN matrix? Could you express a mutated form of LOXL2 that cannot interact with FN but still is able to crosslink Col IV?)

Depletion of LOXL2 supports this mechanism. Without it, Col IV and FN are uncoupled and accumulate as large aggregates rather than a complex fibrous network. Further, long-term thickening/growth of the fibronectin network is inhibited, indicating LOXL2 and/or the Col IV network positively reinforces fibronectin assembly. (Does LOXL2 directly act on FN, or is this effect dependent on Col IV? The nature of the molecular interactions between COL IV, LOXL2, and FN will be an important future research area.)

Next, Marchand et al. ask if failure to produce mature BM (induced by LOXL2 depletion) has consequences for underlying cells. They demonstrate a clear shift in the orientation of actin towards a linear alignment, and similarly, cells change shape from round to very elongated. Cell junctions also shifted to a linear arrangement in LOXL2 depletion. This fits with the known balance between cell-ECM and cell-cell adhesion. The changes in actin network and cell shape/adhesion correlate with a change in B1 integrin localization upon LOXL2 depletion. B1 integrin colocalized with sparse early FN fibers, but was absent from large FN aggregates that occur if LOXL2 is depleted. Similar reorganization of integrin adhesion components (FAK, Vinc, Pax). Clearly, there is feedback between BM assembly and cell junction organization. But I think the authors might emphasize to the reader that this normally reinforces the epithelial fate of these cells. It's less a balance and more like a tipping point. (Related to this section, I could not read Figure 4C graphs unless I enlarged them to 300%.)

Finally, they culture cells on micro groove plates, with or without LOXL2. The grooved substrate can orient the cells, and they show this is superseded by BM once it assembles. Without LOXL2 cells on micro-grooved substrates become disorganized, similar to their observation on flat surfaces (elongated cells, linear actin, etc.). This demonstrates a switch from external topographical cues to self-generated BM. This is consistent with the idea of reorganizing junctions to produce a stable epithelial tube. I was very interested in their 3D culture. The effect of BM assembly on tube diameter makes sense. But how does BM assembly support complex capillary functions like branching? (Can they force branching with targeted mutations that decouple integrin from the BM?) Is this a question of change to cell fate? (Are other remodeling enzymes activated after initial BM assembly that could support growth and/or branching?)

Reviewer #1 (Public review):

Summary:

The authors utilize genetic code expansion to tag TDP-43 and G3BP1, and evaluate this protein tagging system (ANAP) compared to antibodies, and evaluate protein trafficking and stress granule formation in response to stress with sodium arsenite treatment. They find similar staining to antibodies in HeLa cells, mouse embryonic stem cells, and primary mouse cortical neurons. This is a useful study that demonstrates the utility of ANAP tagging to evaluate ALS proteins.

Strengths:

Rescue of cell survival by ANAP-tagged TDP-43 is compelling

Weaknesses:

While the ANAP-tagged proteins had similar distributions to antibody staining, there were some discrepancies that may be more explained by the technique than by novel findings, as the authors suggested. The inclusion of additional controls to evaluate this would be helpful.

Reviewer #2 (Public review):

Summary:

Egawa et al describe the developmental timeline of the assembly of nodes of Ranvier in the chick brainstem auditory circuit. In this unique system, the spacing between nodes varies significantly in different regions of the same axon from early stages, which the authors suggest is critical for accurate sound localization. Egawa et al set out to determine which factors regulate this differential node spacing. They do this by using immunohistological analyses to test the correlation of node spacing with morphological properties of the axons, and properties of oligodendrocytes, glial cells that wrap axons with the myelin sheaths that flank the nodes of Ranvier. They find that axonal structure does not vary significantly, but that oligodendrocyte density and morphology varies in the different regions traversed by these axons, which suggests this is a key determinant of the region-specific differences in node density and myelin sheath length. They also find that differential oligodendrocyte density is partly determined by secreted neuronal signals, as (presumed) blockage of vesicle fusion with tetanus toxin reduced oligodendrocyte density in the region where it is normally higher. Based on these findings, the authors propose that oligodendrocyte morphology, myelin sheath length, and consequently nodal distribution are primarily determined by intrinsic oligodendrocyte properties rather than neuronal factors such as activity.

Significance:

In our view the study tackles a fundamental question likely to be of interest to a specialized audience of cellular neuroscientists. This descriptive study is suggestive that in the studied system, oligodendrocyte density determines the spacing between nodes of Ranvier, but further manipulations of oligodendrocyte density per se are needed to test this convincingly.

Reviewer #1 (Public review):

Summary:

The authors attempted to clarify the impact of N protein mutations on ribonucleoprotein (RNP) assembly and stability using analytical ultracentrifugation (AUC) and mass photometry (MP). These complementary approaches provide a more comprehensive understanding of the underlying processes. Both SV-AUC and MP results consistently showed enhanced RNP assembly and stability due to N protein mutations.<br /> The overall research design appears well planned, and the experiments were carefully executed.

Strengths:

SV-AUC, performed at higher concentrations (3 µM), captured the hydrodynamic properties of bulk assembled complexes, while MP provided crucial information on dissociation rates and complex lifetimes at nanomolar concentrations. Together, the methods offered detailed insights into association states and dissociation kinetics across a broad concentration range. This represents a thorough application of solution physicochemistry.

Weaknesses:

Unlike AUC, MP observes only a part of solution. In MP, bound molecules are accumulated on the glass surface (not dissociated) thus concentration in solution should change as time develops. How does such concentration change impact the result shown here?

Comments on revisions:

The response from the authors is appropriate and reasonable.

Reviewer #1 (Public review):

Summary:

Cai et al have investigated the role of msiCAT-tailed mitochondrial proteins that frequently exist in glioblastoma stem cells. Overexpression of msiCAT-tailed mitochondrial ATP synthase F1 subunit alpha (ATP5) protein increases the mitochondrial membrane potential and blocks mitochondrial permeability transition pore formation/opening. These changes in mitochondrial properties provide resistance to staurosporine (STS)-induced apoptosis in GBM cells. Therefore, msiCAT-tailing can promote cell survival and migration, while genetic and pharmacological inhibition of msiCAT-tailing can prevent the overgrowth of GBM cells.

Strengths:

The CATailing concept has not been explored in cancer settings. Therefore, the present provides new insights for widening the therapeutic avenue.

Reviewer #1 (Public review):

This study uses a new 'hidden multivariate pattern method' to parse in time and space the neural events intervening between stimulus and response in an immediately-reported perceptual decision, and use the resultant neural event timing information to show quite convincingly that Pieron's and Fechner's laws can apply in concert at distinct processing levels.

They designed a clever contrast comparison paradigm in which the contrast difference is kept constant while widely manipulating mean contrast, so that sensory encoding of the overall stimulus would be boosted with increasing mean contrast, whereas decision difficulty and hence duration would increase. With this, they found that the time intervening between early sensory-evoked components, up to an 'N200'-type component associated with launching the decision process, varies inversely with contrast according to Pieron's law. Meanwhile, the time intervals running up to neural events peaking near the time of response, consistent with decision termination, increases with contrast, fitting Fechner's law. Further, a diffusion model whose drift rates are scaled by Fechner's law, fit to RT, predicts the observed proportion of correct responses very well.

In the process of review and revision it was highlighted that presumably the full sequence of neural events intervening between stimulus and response is massively task dependent, but;

(1) The method is intended to capture all key components that specifically covary with RT, as opposed to each and every component in general, and

(2) The main conclusions of the study mentioned above do not change whether the method is set up to track three neural events, or five, as was done in the final analysis.

The propensity for topographic parsing algorithms to potentially lump-together distinct processes that partially co-evolve was acknowledged, but a key clarification in review was that even though the method entails a specification of neural event duration - which was changed from 50 to 25 ms - the success of the method is not strongly contingent on the actual underlying neural events in question having that very duration - indeed, the components extracted using that short template duration can be observed to evolve over a longer time frame associated with the Fechner diffusion process.

Notably, standard average event-related potential analysis was able to show expected amplitude effects - where sensory signals increased with contrast but decision signals decreased - but assessment of the by-trial distribution of their timings was grealy aided by the HMP method.

One of the stages of processing implicated in the parsing analysis was linked to attention orientation, and the authors speculate on whether this might reflect a spatially-selective deployment of attention or a resource allocation, but sensibly refrain from speculating too far since the focus here was on the sensory and decision process durations and their respective adherence to Pieron and Fechner's laws.

Reviewer #1 (Public review):

Summary:

The authors report the results of a tDCS brain stimulation study (verum vs sham stimulation of left DLPFC; between-subjects) in 46 participants, using an intense stimulation protocol over 2 weeks, combined with an experience-sampling approach, plus follow-up measures after 6 months.

Strengths:

The authors are studying a relevant and interesting research question using an intriguing design, following participants quite intensely over time and even at a follow-up time point. The use of an experience-sampling approach is another strength of the work.

Weaknesses:

There are quite a few weaknesses, some related to the actual study and some more strongly related to the reporting about the study in the manuscript. The concerns are listed roughly in the order in which they appear in the manuscript.

(1) In the introduction, the authors present procrastination nearly as if it were the most relevant and problematic issue there is in psychology. Surely, procrastination is a relevant and study-worthy topic, but that is also true if it is presented in more modest (and appropriate) terms. The manuscript mentions that procrastination is a main cause of psychopathology and bodily disease. These claims could possibly be described as 'sensationalized'. Also, the studies to support these claims seem to report associations, not causal mechanisms, as is implied in the manuscript.

(2) It is laudable that the study was pre-registered; however, the cited OSF repository cannot be accessed and therefore, the OSF materials cannot be used to (a) check the preregistration or to (b) fill in the gaps and uncertainties about the exact analyses the authors conducted (this is important because the description of the analyses is insufficiently detailed and it is often unclear how they analyzed the data).

(3) Related to the previous point: I find it impossible to check the analyses with respect to their appropriateness because too little detail and/or explanation is given. Therefore, I find it impossible to evaluate whether the conclusions are valid and warranted.

(4) Why is a medium effect size chosen for the a priori power analysis? Is it reasonable to assume a medium effect size? This should be discussed/motivated. Related: 18 participants for a medium effect size in a between-subjects design strikes me as implausibly low; even for a within-subjects design, it would appear low (but perhaps I am just not fully understanding the details of the power analysis).

(5) It remains somewhat ambiguous whether the sham group had the same number of stimulation sessions as the verum stimulation group; please clarify: Did both groups come in the same number of times into the lab? I.e., were all procedures identical except whether the stimulation was verum or sham?

(6) The TDM analysis and hyperbolic discounting approach were unclear to me; this needs to be described in more detail, otherwise it cannot be evaluated.

(7) Coming back to the point about the statistical analyses not being described in enough detail: One important example of this is the inclusion of random slopes in their mixed-effects model which is unclear. This is highly relevant as omission of random slopes has been repeatedly shown that it can lead to extremely inflated Type 1 errors (e.g., inflating Type 1 errors by a factor of then, e.g., a significant p value of .05 might be obtained when the true p value is .5). Thus, if indeed random slopes have been omitted, then it is possible that significant effects are significant only due to inflated Type 1 error. Without more information about the models, this cannot be ruled out.

(8) Related to the previous point: The authors report, for example, on the first results page, line 420, an F-test as F(1, 269). This means the test has 269 residual degrees of freedom despite a sample size of about 50 participants. This likely suggests that relevant random slopes for this test were omitted, meaning that this statistical test likely suffers from inflated Type 1 error, and the reported p-value < .001 might be severely inflated. If that is the case, each observation was treated as independent instead of accounting for the nestedness of data within participants. The authors should check this carefully for this and all other statistical tests using mixed-effects models.

(9) Many of the statistical procedures seem quite complex and hard to follow. If the results are indeed so robust as they are presented to be, would it make sense to use simpler analysis approaches (perhaps in addition to the complex ones) that are easier for the average reader to understand and comprehend?

(10) As was noted by an earlier reviewer, the paper reports nearly exclusively about the role of the left DLPFC, while there is also work that demonstrates the role of the right DLPFC in self-control. A more balanced presentation of the relevant scientific literature would be desirable.

(11) Active stimulation reduced procrastination, reduced task aversiveness, and increased the outcome value. If I am not mistaken, the authors claim based on these results that the brain stimulation effect operates via self-control, but - unless I missed it - the authors do not have any direct evidence (such as measures or specific task measures) that actually capture self-control. Thus, that self-control is involved seems speculation, but there is no empirical evidence for this; or am I mistaken about this? If that is indeed correct, I think it needs to be made explicit that it is an untested assumption (which might be very plausible, but it is still in the current study not empirically tested) that self-control plays any role in the reported results.

(12) Figures 3F and 3H show that procrastination rates in the active modulation group go to 0 in all participants by sessions 6 and 7. This seems surprising and, to be honest, rather unlikely that there is absolutely no individual variation in this group anymore. In any case, this is quite extraordinary and should be explicitly discussed, if this is indeed correct: What might be the reasons that this is such an extreme pattern? Just a random fluctuation? Are the results robust if these extreme cells are ignored? The authors remove other cells in their design due to unusual patterns, so perhaps the same should be done here, at least as a robustness check.

(13) The supplemental materials, unfortunately, do not give more information, which would be needed to understand the analyses the authors actually conducted. I had hoped I would find the missing information there, but it's not there.

In sum, the reported/cited/discussed literature gives the impression of being incomplete/selectively reported; the analyses are not reported sufficiently transparently/fully to evaluate whether they are appropriate and thus whether the results are trustworthy or not. At least some of the patterns in the results seem highly unlikely (0 procrastination in the verum group in the last 2 observation periods), and the sample size seems very small for a between-subjects design.

Reviewer #1 (Public review):

Summary:

This paper is a comprehensive review of perturbation studies and the state-dependence of the brain's response to perturbation at the circuit, mesoscale, and macroscale levels.

Strengths:

The strengths of the paper are the thorough description of many perturbation studies at different levels of organization, and the integration of both experimental and modeling studies. The review clearly communicates the need to consider (1) brain or local-population state, and (2) multiple levels of organization, in order to understand perturbation responses. Another major strength is the ability for the reader to reproduce figures using the EBRAINS platform.

Weaknesses:

Two major points of improvement should be resolved with the review, in order to make it useful for a broad audience.

The first is that the review does not include a significant integration across scales, and as a result, reads like three separate (though comprehensive) reviews. Currently, the only integration across the scales is in the brief conclusion paragraph. I would recommend adding an additional section, in which the overarching picture is discussed. (i.e. a unifying view of state dependence, and what is learned by considering across scales). This need not be too long, but it should be longer than a single conclusion paragraph.

The second major weakness is that there is a lack of clarity on many points throughout, which is needed for the reader to fully understand the results described.

Reviewer #1 (Public review):

Summary:

In the paper, the authors review literature on synchronous activity, its relationship to brain state, and the multi-scale mechanisms underlying it.

Strengths:

The overall strength of the paper is the wide range of information reviewed, and the diversity of perspectives/approaches it brings together.

Weaknesses:

However, this strength is also the source of its major weaknesses - namely, that the overall structure lacks clarity, and there are inconsistencies throughout. Overall, in the opinion of this reviewer, the manuscript reads as disorganized and incomplete. Major and minor points are delineated below.

Major points:

(1) Most of the text in many figures was too small to read.

(2) Terminology is inconsistent throughout the manuscript. What is the difference between slow oscillations and delta waves? Sometimes the term slow waves is used instead. For sleep state, sometimes the term SWS is used, sometimes non-REM. Similarly, "spindle activity" is not defined, but simply stated as if the reader knows. This brings up two issues: (a) the manuscript should be clearer and more consistent about its terminology, and (b) it's unclear who is the intended readership of the review - is it a pedagogical review for people outside the field of sleep and slow oscillations, or is it meant to be a consensus statement for readers who are already in the field in which a pressing concern has been addressed? It seems part way between these two, and as a result, is ineffective at either goal.

(3) I suggest the authors look again at the overall structure and flow of the review... many sections feel redundant, and it's unclear how they fit together into a single review.

(4) There are many speculative statements in the review that are not justified or explained sufficiently for the reader. For example: "While highly regular slow waves in vivo suggest a single mechanism of generation, namely local cortical circuits, irregular cycles are compatible with a larger role of subcortical nuclei, ..."; "The involvement of different cortical areas and subcortical nuclei can form the basis of these different roles in memory.". For these statements, I assume the relationship between slow wave statistics, subcortical nuclei, and memory either has been written about before, and then should be cited and summarized, or is a novel claim of the authors, which then should be explained and defended rather than stated. There are other similar examples, and I suggest the authors go through the manuscript and make sure that it's clear what is a novel claim of the authors vs a cited claim, and make sure that both are sufficiently justified for the reader.

(5) An especially notable example can be found in the section on the role of the thalamus, where the authors state that they "hold that slow oscillations are fundamentally cortical". However, this section is far too short, and very little evidence is provided to back up this claim. Please review the ways in which the thalamus modulates, and, e.g., ways in which up-down is similar/different without the thalamus.

Reviewer #1 (Public review):

Summary:

This report demonstrates that the gene expression output of the Wnt pathway, when controlled precisely by a synthetic light-based input, depends substantially on the frequency of stimulation. The particular frequency-dependent trend that is observed - anti-resonance, a suppression of target gene expression at intermediate frequencies given a constant duty cycle - is a novel aspect that has not been clearly shown before for this or other signaling pathways. The paper provides both clear experimental evidence of the phenomenon with engineered cellular systems and a model-based analysis of how the pairing of rate constants in pathway activation/deactivation could result in such a trend.

Strengths:

This report couples in vitro experimental data with an abstracted mathematical model. Both of these approaches appear to be technically sound and to provide consistent and strong support for the main conclusion. The experimental data are particularly clear, and the demonstration that Brachyury expression is subject to anti-resonance in ESCs is particularly compelling. The modeling approach is reasonably scaled for the system at the level of detail that is needed in this case, and the hidden variable analysis provides some insight into how the anti-resonance works.

In this revised manuscript, the authors have addressed issues in presentation and in discussing the broader relevance of their study to other pathways. Other limitations of the paper, including the fact that the anti-resonance phenomenon has not yet been demonstrated using physiological Wnt ligands and that the model has not been validated using experimental manipulations to establish that the mechanisms of the cell system and the model are the same, were deemed out of the scope of this initial demonstration by both the reviewers and authors. These questions will provide an interesting basis for further studies.

Reviewer #1 (Public review):

Summary:

This study presents a valuable contribution of NO signaling in zebrafish retinal regeneration in larval animals. The data on NO signaling are solid. There are multiple limitations to the study, but these are largely acknowledged by the authors in the revised text.

Strengths:

New data on NO signaling is valuable to the field but may be limited to larval "regeneration".

Weaknesses:

A weakness of the approach is testing cone ablation and regeneration in early larval animals. A near identical study was already done by Hoang et al 2020 in the adult zebrafish, a more relevant biological timepoint.

Reviewer #1 (Public review):

Summary:

Lai and Doe address the integration of spatial information with temporal patterning and genes that specify cell fate. They identify the Forkhead transcription factor Fd4 as a lineage-restricted cell fate regulator that bridges transient spatial transcription factors to terminal selector genes in the developing Drosophila ventral nerve cord. The experimental evidence convincingly demonstrates that Fd4 is both necessary for late-born NB7-1 neurons, but also sufficient to transform other neural stem cell lineages toward the NB7-1 identity. This work addresses an important question that will be of interest to developmental neurobiologists: How can cell identities defined by initial transient developmental cues be maintained in the progeny cells, even if the molecular mechanism remains to be investigated? In addition, the study proposes a broader concept of lineage identity genes that could be utilized in other lineages and regions in the Drosophila nervous system and in other species.

Strengths:

While the spatial factors patterning the neuroepithelium to define the neuroblast lineages in the Drosophila ventral nerve cord are known, these factors are sometimes absent or not required during neurogenesis. In the current work, Lai and Doe identified Fd4 in the NB7-1 lineage that bridges this gap and explains how NB7-1 neurons are specified after Engrailed (En) and Vnd cease their expression. They show that Fd4 is transiently co-expressed with En and Vnd and is present in all nascent NB7-1 progenies. They further demonstrate that Fd4 is required for later-born NB7-1 progenies and sufficient for the induction of NB7-1 markers (Eve and Dbx) while repressing markers of other lineages when force-expressed in neural progenitors, e.g., in the NB5-6 lineage and in the NB7-3 lineage. They also demonstrate that, when Fd4 is ectopically expressed in NB7-3 and NB5-6 lineages, this leads to the ectopic generation of dorsal muscle-innervating neurons. The inclusion of functional validation using axon projections demonstrates that the transformed neurons acquire appropriate NB7-1 characteristics beyond just molecular markers. Quantitative analyses are thorough and well-presented for all experiments.

Weaknesses:

(1) While Fd4 is required and sufficient for several later-born NB7-1 progeny features, a comparison between early-born (Hb/Eve) and later-born (Run/Eve) appears missing for pan-progenitor gain of Fd4 (with sca-Gal4; Figure 4) and for the NB7-3 lineage (Figure 6). Having a quantification for both could make it clearer whether Fd4 preferentially induces later-born neurons or is sufficient for NB7-1 features without temporal restriction.

(2) Fd4 and Fd5 are shown to be partially redundant, as Fd4 loss of function alone does not alter the number of Eve+ and Dbx+ neurons. This information is critical and should be included in Figure 3.

(3) Several observations suggest that lineage identity maintenance involves both Fd4-dependent and Fd4-independent mechanisms. In particular, the fact that fd4-Gal4 reporter remains active in fd4/fd5 mutants even after Vnd and En disappear indicates that Fd4's own expression, a key feature of NB7-1 identity, is maintained independently of Fd4 protein. This raises questions about what proportion of lineage identity features require Fd4 versus other maintenance mechanisms, which deserves discussion.

(4) Similarly, while gain of Fd4 induces NB7-1 lineage markers and dorsal muscle innervation in NB5-6 and NB7-3 lineages, drivers for the two lineages remain active despite the loss of molecular markers, indicating some regulatory elements retain activity consistent with their original lineage identity. It is therefore important to understand the degree of functional conversion in the gain-of-function experiments. Sparse labeling of Fd4 overexpressing NB5-6 and NB7-3 progenies, as was done in Seroka and Doe (2019), would be an option.

(5) The less-penetrant induction of Dbx+ neurons in NB5-6 with Fd4-overexpression is interesting. It might be worth the authors discussing whether it is an Fd4 feature or an NB5-6 feature by examining Dbx+ neuron number in NB7-3 with Fd4-overexpression.

(6) It is logical to hypothesize that spatial factors specify early-born neurons directly, so only late-born neurons require Fd4, but it was not tested. The model would be strengthened by examining whether Fd4-Gal4-driven Vnd rescues the generation of later-born neurons in fd4/fd5 mutants.

(7) It is mentioned that Fd5 is not sufficient for the NB7-1 lineage identity. The observation is intriguing in how similar regulators serve distinct roles, but the data are not shown. The analysis in Figure 4 should be performed for Fd5 as supplemental information.

Reviewer #1 (Public review):

The study introduces an open-source, cost-effective method for automating the quantification of male social behaviors in Drosophila melanogaster. It combines machine-learning based behavioral classifiers developed using JAABA (Janelia Automatic Animal Behavior Annotator) with inexpensive hardware constructed from off-the-shelf components. This approach addresses the limitations of existing methods, which often require expensive hardware and specialized setups. The authors demonstrate that their new "DANCE" classifiers accurately identify aggression (lunges) and courtship behaviors (wing extension, following, circling, attempted copulation, and copulation), closely matching manually annotated ground-truth data. Furthermore, DANCE classifiers outperform existing rule-based methods in accuracy. Finally, the study shows that DANCE classifiers perform as well when used with low-cost experimental hardware as with standard experimental setups across multiple paradigms, including RNAi knockdown of the neuropeptide Dsk and optogenetic silencing of dopaminergic neurons.

The authors make creative use of existing resources and technology to develop an inexpensive, flexible, and robust experimental tool for the quantitative analysis of Drosophila behavior. A key strength of this work is the thorough benchmarking of both the behavioral classifiers and the experimental hardware against existing methods. In particular, the direct comparison of their low-cost experimental system with established systems across different experimental paradigms is compelling. A weakness of the study is that the use of JAABA-based classifiers to analyze aggression and courtship is not novel (Tao et al., J. Neurosci., 2024; Sten et al., Cell, 2023; Chiu et al., Cell, 2021; Isshi et al., eLife, 2020; Duistermars et al., Neuron, 2018). However, the demonstration the JAABA classifiers they developed work as well without expensive experimental hardware opens the door to more low-cost systems for quantitative behavior analysis.

In summary, this work provides a practical and accessible approach to quantifying Drosophila behavior, reducing the economic barriers to the study of the neural and molecular mechanisms underlying social behavior.

Reviewer #1 (Public review):

Summary:

Biomolecular condensates are essential part of cellular homeostatic regulation. In this manuscript, authors develop a theoretical framework for phase separation of membrane bound proteins. They show the effect of non-dilute surface binding and phase separation on tight junction protein organization.

Strengths:

It is an important study considering the phase separation of membrane bound molecules are taking the center stage of signaling, spanning from immune signaling to cell-cell adhesion. A theoretical framework will help biologists to quantitatively interpret their findings.

Weaknesses:

Understandably, authors used one system to test their theory (ZO-1). However, to establish a theoretical framework, this is sufficient.

Comments on revisions:

I do not recommend new experiments. The manuscript is clear and establishes a new step in understanding the physical chemistry of biomolecular condensates.

Reviewer #1 (Public review):

Disclaimer: While I am familiar with the CFS method and the CFS literature, I am not familiar with primate research or two-photon calcium imaging. Additionally, I may be biased regarding unconscious processing under CFS, as I have extensively investigated this area but have found no compelling evidence in favor of unconscious processing under CFS.

This manuscript reports the results of a nonhuman-primate study (N=2 behaving macaque monkeys) investigating V1 responses under continuous flash suppression (CFS). The results show that CFS substantially suppressed V1 orientation responses, albeit slightly differently in the two monkeys. The authors conclude that CFS-suppressed orientation information "may not suffice for high-level visual and cognitive processing" (abstract).

The manuscript is clearly written and well-organized. The conclusions are supported by the data and analyses presented (but see disclaimer). However, I believe that the manuscript would benefit from a more detailed discussion of the different results observed for monkeys A and B (i.e., inter-individual differences), and how exactly the observed results are related to findings of higher-order cognitive processing under CFS, on the one hand, and the "dorsal-ventral CFS hypothesis", on the other hand.

Major Comments:

(1) Some references are imprecise. For example, l.53: "Nevertheless, two fMRI studies reported that V1 activity is either unaffected or only weakly affected (Watanabe et al., 2011; Yuval-Greenberg & Heeger, 2013)". "To the best of my understanding, the second study reaches a conclusion that is entirely opposite to that of the first, specifically that for low-contrast, invisible stimuli, stimulus-evoked fMRI BOLD activity in the early visual cortex (V1-V3) is statistically indistinguishable from activity observed during stimulus-absent (mask-only) trials. Therefore, high-level unconscious processing under CFS should not be possible if Yuval-Greenberg & Heeger are correct. The two studies contradict each other; they do not imply the same thing.

(2) Line 354: "The flashing masker was a circular white noise pattern with a diameter of 1.89{degree sign}{degree sign}, a contrast of 0.5, and a flickering rate of 10 Hz. The white noise consisted of randomly generated black and white blocks (0.07 × 0.07 each)." Why did the authors choose a white noise stimulus as the CFS mask? It has previously been shown that the depth of suppression engendered by CFS depends jointly on the spatiotemporal composition of the CFS and the stimulus it is competing with (Yang & Blake, 2012). For example, Hesselmann et al. (2016) compared Mondrian versus random dot masks using the probe detection technique (see Supplementary Figure S4 in the reference below) and found only a poor masking performance of the random dot masks.

Yang, E., & Blake, R. (2012). Deconstructing continuous flash suppression. Journal of Vision, 12(3), 8. https://doi.org/10.1167/12.3.8

Hesselmann, G., Darcy, N., Ludwig, K., & Sterzer, P. (2016). Priming in a shape task but not in a category task under continuous flash suppression. Journal of Vision, 16, 1-17.

(3) Related to my previous point: I guess we do not know whether the monkeys saw the CF-suppressed grating stimuli or not? Therefore, could it be that the differences between monkey A and B are due to a different individual visibility of the suppressed stimuli? Interocular suppression has been shown to be extremely variable between participants (see reference below). This inter-individual variability may, in fact, be one of the reasons why the CFS literature is so heterogeneous in terms of unconscious cognitive processing: due to the variability in interocular suppression, a significant amount of data is often excluded prior to analysis, leading to statistical inconsistencies. Moreover, the authors' main conclusion (lines 305-307) builds on the assumption that the stimuli were rendered invisible, but isn't this speculation without a measure of awareness?

Yamashiro, H., Yamamoto, H., Mano, H., Umeda, M., Higuchi, T., & Saiki, J. (2014). Activity in early visual areas predicts interindividual differences in binocular rivalry dynamics. Journal of Neurophysiology, 111(6), 1190-1202. https://doi.org/10.1152/jn.00509.2013

(4) The authors refer to the "tool priming" CFS studies by Almeida et al. (l.33, l.280, and elsewhere) and Sakuraba et al. (l.284). A thorough critique of this line of research can be found here:

Hesselmann, G., Darcy, N., Rothkirch, M., & Sterzer, P. (2018). Investigating Masked Priming Along the "Vision-for-Perception" and "Vision-for-Action" Dimensions of Unconscious Processing. Journal of Experimental Psychology. General. https://doi.org/10.1037/xge0000420

This line of research ("dorsal-ventral CFS hypothesis") has inspired a significant body of behavioral and fMRI/EEG studies (see reference for a review below). The manuscript would benefit from a brief paragraph in the discussion section that addresses how the observed results contribute to this area of research.

Ludwig, K., & Hesselmann, G. (2015). Weighing the evidence for a dorsal processing bias under continuous flash suppression. Consciousness and Cognition, 35, 251-259. https://doi.org/10.1016/j.concog.2014.12.010

Reviewer #1 (Public review):

Summary:

In this study, participants completed two different tasks. A perceptual choice task in which they compared the sizes of pairs of items and a value-different task in which they identified the higher value option among pairs of items with the two tasks involving the same stimuli. Based on previous fMRI research, the authors sought to determine whether the superior frontal sulcus (SFS) is involved in both perceptual and value-based decisions or just one or the other. Initial fMRI analyses were devised to isolate brain regions that were activated for both types of choices and also regions that were unique to each. Transcranial magnetic stimulation was applied to the SFS in between fMRI sessions and it was found to lead to a significant decrease in accuracy and RT on the perceptual choice task but only a decrease in RT on the value-different task. Hierarchical drift diffusion modelling of the data indicated that the TMS had led to a lowering of decision boundaries in the perceptual task and a lowering of non-decision times on the value-based task. Additional analyses show that SFS covaries with model derived estimates of cumulative evidence, that this relationship is weakened by TMS.

The paper has many strengths including the rigorous multi-pronged approach of causal manipulation, fMRI and computational modelling which offers a fresh perspective on the neural drivers of decision making. Some additional strengths include the careful paradigm design which ensured that the two types of tasks were matched for their perceptual content while orthogonalizing trial-to-trial variations in choice difficulty. The paper also lays out a number of specific hypotheses at the outset regarding the behavioural outcomes that are tied to decision model parameters and well justified.

Reviewer #1 (Public review):

Summary:

Age-related synaptic dysfunction can have detrimental effects on cognitive and locomotor function. Additionally, aging makes the nervous system vulnerable to late-onset neurodegenerative diseases. This manuscript by Marques et al. seeks to profile the cell surface proteomes of glia to uncover signaling pathways that are implicated in age-related neurodegeneration. They compared the glial cell-surface proteomes in the central brain of young (day 5) and old (day 50) flies, and identified the most up- and down-regulated proteins during the aging process. 48 genes were selected for analysis in a lifespan screen, and interestingly, most sex-specific phenotypes. Among these, adult-specific pan-glial DIP-β overexpression (OE) significantly increased the lifespan of both males and females and improved their motor control ability. To investigate the effect of DIP-β in the aging brain, Marques et al. performed snRNA-seq on 50-day-old Drosophila brains with or without DIP-β OE in glia. Cortex and ensheathing glia showed the most differentially expressed genes. Computational analysis revealed that glial DIP-β OE increased cell-cell communication, particularly with neurons and fat cells.

Strengths:

(1) State-of-the-art methodology to reveal the cell surface proteomes of glia in young and old flies.

(2) Rigorous analyses to identify differentially expressed proteins.

(3) Examination of up- and down-regulated candidates and identification of glial-expressed mediators that impact fly lifespan.

(4) Intriguing sex-specific glial genes that regulate life span.

(5) Follow-up RNA-seq analysis to examine cellular transcriptomes upon overexpression of an identified candidate (DIP-β).

(6) A compelling dataset for the community that should generate extensive interest and spawn many projects.

Weaknesses:

(1) DIP-β OE using flySAM:

a) These flies showed a larger increase in lifespan compared to using UAS-DIP-β (Figure 2 C, D). Do the authors think that flySAM is a more efficient way of OE than UAS? Also, the UAS construct would be specific to one DIP-β isoform, while flySAM would likely express all isoforms. Could this also contribute to the phenotypes observed?

b) The Glial-GS>DIP-β flySAM flies without RU-486 have significantly shorter lifespans (Figure 2C) than their UAS-DIP-β counterparts. flySAM is lethal when expressed under the control of tubulin-GAL4 (Jia et al. 2018), likely due tothe toxicity of such high levels of overexpression. Is it possible that a larger increase in lifespan is due to the already reduced viability of these flies?

c) Statistics: It is stated in the Methods that "statistical methods used are described in the figure legend of each relevant panel." However, there is no description of the statistics or sample sizes used in Figure 2.

(2) Figure 3: The authors use a glial GeneSwitch (GS) to knock down and overexpress candidate genes. In Figure 3A, they look at glial-GS>UAS-GFP with and without RU. Without RU, there is no GFP expression, as expected. With RU, there is GFP expression. It is expected that all cell body GFP signal should colocalize with a glial nuclear marker (Repo). However, there is some signal that does not appear to be glia. Also, many glia do not express GFP, suggesting the glial GS driver does not label all glia. This could impact which glia are being targeted in several experiments.

(3) It is interesting that sex-specific lifespan effects were observed in the candidate screen.

a) The authors should provide a discussion about these sex-specific differences and their thoughts about why these were observed.

b) The authors should also provide information regarding the sex of the flies used in the glial cell surface proteome study.

c) Also, beyond the scope of this study, examining sex-specific glial proteomes could reveal additional insights into age-related pathways affecting males and females differentially.

(4) The behavioral assay used in this study (climbing) tests locomotion driven by motor neurons. The proteomic analysis was performed with the central adult brain, which does not include the nerve cord, where motor neurons reside. While likely beyond the scope of this study, it would be informative to test other behaviors, including learning, circadian rhythms, etc.

(5) It is surprising that overexpressing a CAM in glia has such a broad impact on the transcriptomes of so many different cell types. Could this be due to DIP-β OE maintaining the brain in a "younger" state and indirectly influencing the transcriptomes? Instead of DIP-β OE in glia directly influencing cell-cell interactions? Can the authors comment on this?

Reviewer #2 (Public review):

Summary:

The current article adapts standard rhythmic measures to describe the temporal organisation of whale song units.

Strengths:

The detailed description of the internal temporal structure of whale songs is something that has thus far been lacking.

Weaknesses:

Conceptual and terminological bases of the paper are problematical and hamper comparison with other taxa, including humans. According to signal theory, codas are indexical rather than symbolic. They signal an individual's group identity. Borrowing from humans and linguistics, coda inter-group variation represents a case of accents -- phonologically different varieties of the same call -- not dialects, confirming they are an index. Moreover, symbolism is not a feature detectable or confirmed through rhythmic analyses or temporal characterisation. This raises serious doubt whether alleged "dialects," "symbolism" and similarity between whales and humans is factual. The comparative scope and relevance of this paper for the broader field is limited and evolutionary claims are potentially misleading and perilous.

Reviewer #1 (Public review):

Summary:

In this descriptive study, Tateishi et al. report a Tn-seq based analysis of genetic requirements for growth and fitness in 8 clinical strains of Mycobacterium intracellulare Mi), and compare the findings with a type strain ATCC13950. The study finds a core set of 131 genes that are essential in all nine strains, and therefore are reasonably argued as potential drug targets. Multiple other genes required for fitness in clinical isolates have been found to be important for hypoxic growth in the type strain.

Strengths:

The study has generated a large volume of Tn-seq datasets of multiple clinical strains of Mi from multiple growth conditions, including from mouse lungs. The dataset can serve as an important resource for future studies on Mi, which despite being clinically significant, remains a relatively understudied species of mycobacteria.

Weaknesses:

The primary claim of the study that the clinical strains are better adapted for hypoxic growth is yet to be comprehensively investigated. However, this reviewer thinks such an investigation would require a complex experimental design and perhaps form an independent study.

Comments on revisions:

The revised paper has satisfactorily addressed my previous concerns, and I have no further issues with this paper.

Reviewer #1 (Public review):

Summary:

This manuscript addresses the important problem of the uncoupling of oxidative phosphorylation due to hypoxia-ischemia injury in the neonatal brain and provides insight into the neuroprotective mechanisms of hypothermia treatment.

Strengths:

The authors used a combination of in vivo imaging of awake P10 mice and experiments on isolated mitochondria to assess various key parameters of brain metabolism during hypoxia-ischemia with and without hypothermia treatment. This unique approach resulted in a comprehensive data set that provides solid evidence to support the derived conclusions.

Weaknesses:

Several potential weaknesses were identified in the original submission, which the authors subsequently addressed in the revised manuscript. Here is the brief list of the questions:

(1) Is it possible that the observed relatively low baseline OEF and trends of increased OEF and CBF over several hours after the imaging start were partially due to slow recovery from anesthesia?

(2) What was the pain management, and is there a possibility that some of the observations were influenced by the pain-reducing drugs or their absence?

(3) Were P10 mice significantly stressed during imaging in the awake state because they didn't have head-restraint habituation training?

(4) Considering high metabolism and blood flow in the cortex, it could be potentially challenging to predict cortical temperature based on the skull temperature, particularly in the deeper part of the cortex.

(5) The map of estimated CMRO2 looks quite heterogeneous across the brain surface. Could this be partially resulting from the measurement artefact?

(6) It would be beneficial to provide more detailed justification for using P10 mice in the experiments.

Reviewer #2 (Public Review):

There is increasing evidence that viruses manipulate vectors and hosts to facilitate transmission. For arthropods, saliva plays an essential role for successful feeding on a host and consequently for arthropod-borne viruses that are transmitted during arthropod feeding on new hosts. This is so because saliva constitutes the interaction interface between arthropod and host and contains many enzymes and effectors that allow feeding on a compatible host by neutralizing host defenses. Therefore, it is not surprising that viruses change saliva composition or use saliva proteins to provoke altered vector-host interactions that are favorable for virus transmission. However, detailed mechanistic analyses are scarce. Here, Zhao and coworkers study transmission of rice stripe virus (RSV) by the planthopper Laodelphax striatellus. RSV infects plants as well as the vector, accumulates in salivary glands and is injected together with saliva into a new host during vector feeding.

The authors present evidence that a saliva-contained enzyme - carbonic anhydrase (CA) - might facilitate virus infection of rice by interfering with callose deposition, a plant defense response. In vitro pull-down experiments, yeast two hybrid assay and binding affinity assays show convincingly interaction between CA and a plant thaumatin-like protein (TLP) that degrades callose. Similar experiments show that CA and TLP interact with the RSV nuclear capsid protein NT to form a complex. Formation of the CA-TLP complex increases TLP activity by roughly 30% and integration of NT increases TLP activity further. This correlates with lower callose content in RSV-infected plants and higher virus titer. Further, silencing CA in vectors decreases virus titers in infected plants. Interestingly, aphid CA was found to play a role in plant infection with two non-persistent non-circulative viruses, turnip mosaic virus and cucumber mosaic virus (Guo et al. 2023 doi.org/10.1073/pnas.2222040120), but the proposed mode of action is entirely different.

Editors' note: this version was assessed by the editors, without further input from the reviewers.

Reviewer #1 (Public review):

The medicinal leech preparation is an amenable system in which to understand how the underlying cellular networks for locomotion function. A previously identified non-spiking neuron (NS) was studied and found to alter the mean firing frequency of a crawl-related motoneuron (DE-3), which fires during the contraction phase of crawling. The data are solid. Identifying upstream neurons responsible for crawl motor patterning is essential for understanding how rhythmic behavior is controlled.

Reviewer #1 (Public review):

Summary:

This study advances the lab's growing body of evidence exploring higher-order learning and its neural mechanisms. They recently found that NMDA receptor activity in the perirhinal cortex was necessary for integrating stimulus-stimulus associations with stimulus-shock associations (mediated learning) to produce preconditioned fear, but it was not necessary for forming stimulus-shock associations. On the other hand, basolateral amygdala NMDA receptor activity is required for forming stimulus-shock memories. Based on these facts, the authors assessed: 1. why the perirhinal cortex is necessary for mediated learning but not direct fear learning and 2. the determinants of perirhinal cortex versus basolateral amygdala necessity for forming direct versus indirect fear memories. The authors used standard sensory preconditioning and variants designed to manipulate the novelty and temporal relationship between stimuli and shock and, therefore, the attentional state under which associative information might be processed. Under experimental conditions where information would presumably be processed primarily in the periphery of attention (temporal distance between stimulus/shock or stimulus pre-exposure), perirhinal cortex NMDA receptor activation was required for learning indirect associations. On the other hand, when information would likely be processed in focal attention (novel stimulus contiguous with shock), basolateral amygdala NMDA activity was required for learning direct associations. Together, the findings indicate that the perirhinal cortex and basolateral amygdala subserve peripheral and focal attention, respectively. The authors provide support for their conclusions using careful, hypothesis-driven experimental design, rigorous methods, and integrating their findings with the relevant literature on learning theory, information processing, and neurobiology. Therefore, this work will be highly interesting to several fields.

Strengths:

(1) The experiments were carefully constructed and designed to test hypotheses that were rooted in the lab's previous work, in addition to established learning theory and information processing background literature.

(2) There are clear predictions and alternative outcomes. The provided table does an excellent job of condensing and enhancing the readability of a large amount of data.

(3) In a broad sense, attention states are a component of nearly every behavioral experiment. Therefore, identifying their engagement by dissociable brain areas and under different learning conditions is an important area of research.

(4) The authors clearly note where they replicated their own findings, report full statistical measures, effect sizes, and confidence intervals, indicating the level of scientific rigor.

(5) The findings raise questions for future experiments that will further test the authors' hypotheses; this is well discussed.

Reviewer #1 (Public review):

I have to preface my evaluation with a disclosure that I lack the mathematical expertise to fully assess what seems to be the authors' main theoretical contribution. I am providing this assessment to the best of my ability, but I cannot substitute for a reviewer with more advanced mathematical/physical training.

Summary:

This paper describes a new theoretical framework for measuring parsimony preferences in human judgments. The authors derive four metrics that they associate with parsimony (dimensionality, boundary, volume, and robustness) and measure whether human adults are sensitive to these metrics. In two tasks, adults had to choose one of two flower beds which a statistical sample was generated from, with or without explicit instruction to choose the flower bed perceptually closest to the sample. The authors conduct extensive statistical analyses showing that humans are sensitive to most of the derived quantities, even when the instructions encouraged participants to choose only based on perceptual distance. The authors complement their study with a computational neural network model that learns to make judgments about the same stimuli with feedback. They show that the computational model is sensitive to the tasks communicated by feedback and only uses the parsimony-associated metrics when feedback trains it to do so.

Strengths:

(1) The paper derives and applies new mathematical quantities associated with parsimony. The mathematical rigor is very impressive and is much more extensive than in most other work in the field, where studies often adopt only one metric (such as the number of causes or parameters). These formal metrics can be very useful for the field.

(2) The studies are preregistered, and the statistical analyses are strong.

(3) The computational model complements the behavioral findings, showing that the derived quantities are not simply equivalent to maximum-likelihood inference in the task.

(4) The speculations in the discussion section (e.g., the idea that human sensitivity is driven by the computational demands each metric requires) are intriguing and could usefully guide future work.

Weaknesses:

(1) The paper is very hard to understand. Many of the key details of the derived metrics are in the appendix, with very little accessible explanation in the main text. The figures helped me understand the metrics somewhat, although I am still not sure how some of them (such as boundary or robustness as measured here) are linked to parsimony. I understand that this is addressed by the derivations in the appendix, but as a computational cognitive scientist, I would have benefited from more accessible explanations. Important aspects of the human studies are also missing from the main text, such as the sample size for Experiment 2.

(2) It is not fully clear whether the sensitivity of human participants to some of the quantities convincingly reported here actually means that participants preferred shapes according to the corresponding aspect of parsimony. The title and framing suggest that parsimony "guides" human decision-making, which may lead readers to conclude that humans prefer more parsimonious shapes. I am not sure the sensitivity findings alone support this framing, but it might just be my misunderstanding of the analyses.

(3) The stimulus set included only four combinations of shapes, each designed to diagnostically target one of the theoretical quantities. It is unclear whether the results are robust or specific to these particular 4 stimuli.

(4) The study is framed as measuring "decision-making," but the task resembles statistical inference (e.g., which shape generated the data) or perceptual judgment. This is a minor point since "decision-making" is not well defined in the literature, yet the current framing in the title gave me the initial impression that humans would be making preference choices and learning about them over time with feedback.

Reviewer #1 (Public review):

Summary:

The study by Klotzsche et al. examines whether emotional facial expressions can be decoded from EEG while participants view 3D faces in immersive VR and whether stereoscopic depth cues affect these neural representations. Participants viewed computer-generated faces (three identities, four emotions) rendered either stereoscopically or monoscopically, while performing an emotion recognition task. Time-resolved multivariate decoding revealed above-chance decodability of facial expressions from EEG. Importantly, decoding accuracy did not differ between monoscopic and stereoscopic viewing. This indicates that the neural representation of expressions is robust against stereoscopic disparity for the relevant features. However, a separate classifier could distinguish the depth condition (mono vs. stereo) from EEG, i.e., the pattern of neuronal activity differs between conditions, but not in ways relevant for the decoding of emotions. It had an early peak and a temporal profile similar to identity decoding, suggesting that early, task-irrelevant visual differences are captured neurally. Cross-decoding further demonstrated that expression decoders trained in one depth condition could generalize to the other, supporting the idea of representational invariance. Eye-tracking analyses showed that expressions and identities could be decoded from gaze patterns, but not the depth condition, and EEG- and gaze-based decoding performances were not correlated across participants. Overall, this work shows that EEG decoding in VR is feasible and sensitive, and suggests that stereoscopic cues are represented in the brain but do not influence the neural processing of facial expressions. This study addresses a relevant question with state-of-the-art experimental and data analysis techniques.

Strengths:

(1) It combines EEG, virtual reality stereoscoptic and monoscopic presentation of visual stimuli, and advanced data analysis methods to address a timely question.

(2) The figures are of very high quality.

(3) The reference list is appropriate and up to date.

Weaknesses:

(1) The introduction-results-discussion-methods order makes it hard to follow the Results without repeatedly consulting the Methods. Please introduce minimal, critical methodological context at the start of each Results subsection; reserve technical details for Methods/Supplement.

(2) Many Results subsections begin with a crisp question and present rich analyses, but end without a short synthesis. Please add 1-2 sentences that explicitly answer the opening question and state what the analyses demonstrate.

(3) The Results compellingly show that (a) expressions are decodable from EEG and (b) mono vs stereo trials are decodable from EEG; yet expression decoding is comparable across mono and stereo. It would help if you articulate why depth is neurally distinguishable while leaving expression representations unchanged. Maybe improve the discussion of the results of source localization and give a more detailed connection to what we already know about the processing of disparity.

Reviewer #1 (Public review):

Summary:

In the present manuscript, de Bos and Kutay investigate the functional implications of persistent microtubule-ER contacts as cells go through mitosis. To do so, they resorted to investigating phosphorylation mutants of the ER-Microtubule crosslinker Climp63. They found that phosphodeficient Climp63 mutants induce a severe SAC-dependent mitotic delay after normal chromosome alignment, with an impressive mitotic index of approximately 75%. Strikingly, this was often associated with massive nuclear fragmentation into up to 30 micronuclei that are able to recruit both core and non-core nuclear envelope components. One particular residue (S17) that is phosphorylated by Cdk1 seems to account for most, if not all, these phenotypes. Furthermore, the authors use the impact on mitosis as an indirect way to map the microtubule binding domain of Climp63, which has remained controversial, and found that it is mostly restricted to the N-terminal 28 residues of Climp63. Of note, despite the strong impact on mitosis, persistent microtubule-ER contacts did not affect the distribution of other organelles during mitosis, such as mitochondria or lysosomes.

Strengths:

Overall, this work provides important mechanistic insight into the functional implications of ER-microtubule network remodelling during mitosis and should be of great interest to a vast readership of cell biologists.

Weaknesses:

Some of the key findings appear somewhat preliminary and would be worth exploring further to substantiate some of the claims and clarify the respective impact on mitosis and nuclear envelope reassembly on the resulting micronuclei.

The following suggestions would significantly clarify some key points:

(1) The striking increase in mitotic index in cells expressing the Climp63 phosphodefective mutant, together with their live cell imaging data indicating extensive mitotic delays that can be relieved by SAC inhibition, suggests that SAC silencing is significantly delayed or even impossible to achieve. The fact that most chromosomes align in 12 min, irrespective of the expression of the Climp63 phosphodefective mutant, suggests that initial microtubule-kinetochore interactions are not compromised, but maybe cannot be stably maintained. Alternatively, the stripping of SAC proteins from kinetochores by dynein along attached microtubules might be compromised, despite normal microtubule-kinetochore attachments. The authors allude to both these possibilities, but unfortunately, they never really test them. This could easily be done by immunofluorescence with a Mad1 or c-Mad2 antibody to inspect which fraction of kinetochores (co-stained with a constitutive kinetochore marker, such as CENP-A or CENP-C) are positive for these SAC proteins. If just a small fraction, then the stability of some attachments is likely the cause. If most/all kinetochores retain Mad1/c-Mad2, then it is probably an issue of silencing the SAC.

(2) The authors use the increase in mitotic index (H3 S10 phosphorylation levels) as a readout for the MT binding efficiency of Climp63 and respective mutants. Although suggestive, this is fairly indirect and requires additional confirmation. For example, the authors could perform basic immunofluorescence in fixed cells to inspect co-localization of Climp63 (and its mutants) with microtubules.

(3) The authors refer in the discussion that the striking nuclear fragmentation seen upon mitotic exit of cells expressing Climp63 phosphodefective mutant has not been reported before, and yet it is strikingly similar to what has been previously observed in cells treated with taxol (they cite Samwer et al. 2017, but they might elect to cite also Mitchison et al., Open Biol, 2017 and most relevantly Jordan et al., Cancer Res, 1996). This striking similarity and given the extensive mitotic delay observed in the Climp63 phosphodefective mutant, it is tempting to speculate that these cells are undergoing mitotic slippage (i.e., cells exit mitosis without ever satisfying the SAC) because they are unable to silence/satisfy the SAC. Indeed, the scattered micronuclei morphology has also been observed in cells undergoing mitotic slippage (e.g., Brito and Rieder, Curr Biol., 2006). The experiment suggested in point #1 should also shed light on this problem. The authors might want to consider discussing this possible explanation to interpret the observed phenotypes.

(4) One of the most significant implications of the findings reported in this paper is that microtubule proximity does not seem to impact the assembly of either core or non-core nuclear envelope proteins on micronuclei (that possibly form due to mitotic slippage, rather than normal anaphase). These results challenge some models explaining nuclear envelope defects in micronuclei derived from lagging chromosomes due to the proximity of microtubules, and, as the authors point out at the very end, other reasons might underlie these defects. Along this line, the authors might elect to cite Afonso et al. Science, 2014, and Orr et al., Cell Reports, 2022, who provide evidence that a spindle midzone-based Aurora B gradient, rather than microtubules per se, underlie the nuclear envelope defects commonly seen in micronuclei derived from lagging chromosomes during anaphase.

Reviewer #1 (Public review):

Summary:

The goal of this paper was to determine whether the T cell receptor (TCR) repertoire differs between a male and a female human. To address this, this group sequenced TCRs from double-positive and single-positive thymocytes in male and female humans of various ages. Such an analysis on sorted thymocyte subsets has not been performed in the past. The only comparable dataset is a pediatric thymocyte dataset where total thymocytes were sorted.

They report on participant ages and sexes, but not on ethnicity, race, nor provide information about HLA typing of individuals. Though the experiments themselves are heroic, they do represent a relatively small sampling of diverse humans. They observed no differences in TCRbeta or TCRalpha usage, combinational diversity, or differences in the length of the CDR3 region, or amino acid usage in the CD3aa region between males or females. Though they observed some TCRbeta CD3aa sequence motifs that differed between males and females, these findings could not be replicated using an external dataset and therefore were not generalizable to the human population.

They also compared TCRbeta sequences against those identified in the past using computational approaches to recognize cancer-, bacterial-, viral-, or autoimmune-antigens. They found very little overlap of their sequences with these annotated sequences (depending on the individual, ranging from 0.82-3.58% of sequences). Within the sequences that were in overlap, they found that certain sequences against autoimmune or bacterial antigens were significantly over-represented in female versus male CD8 SP cells. Since no other comparable dataset is available, they could not conclude whether this is a finding that is generalizable to the human population.

Strengths:

This is a novel dataset. Overall, the methodologies appear to be sound. There was an attempt to replicate their findings in cases where an appropriate dataset was available. I agree that there are no gross differences in TCR diversity between males and females.

Weaknesses:

Overall, the sample size is small given that it is an outbred population. The cleaner experiment would have been to study the impact of sex in a number of inbred MHC I/II identical mouse strains or in humans with HLA-identical backgrounds.

It is unclear whether there was consensus between the three databases they used regarding the antigens recognized by the TCR sequences. Given the very low overlap between the TCR sequences identified in these databases and their dataset, and the lack of replication, they should tone down their excitement about the CD8 T cell sequences recognizing autoimmune and bacterial antigens being over-represented in females.

The dataset could be valuable to the community.

Reviewer #1 (Public review):

Summary:

This is a careful, well-powered treatment of age effects in resting-state MEG. Rather than extracting (say) complex connectivity measures, the authors look at the 'simplest possible thing': changes in the overall power spectrum across age.

Strengths:

They find significant age-related changes at different frequency bands: broadly, attenuation at low-frequency (alpha) and increased beta. These patterns are identified in a large dataset (CamCAN) and then verified in other public data.

Weaknesses:

Some secondary interpretations (what is "unique" to age vs global anatomy) may go beyond what the statistics strictly warrant in the current form, but these can be tightened with (I think, fairly quick) additions already foreshadowed by the authors' own analyses.

Aims:

The authors set out to replace piecemeal, band-by-band ageing claims with t-maps, and Cohen's f2 over sensors×frequency ("GLM-Spectrum").

On CamCAN, six spatio-spectral peaks survive relatively strict statistical controls. The larger effects are in low-frequency and upper-alpha/beta ranges (f2 approx 0.2-0.3), while lower-alpha and gamma reach significance but with small practical impact (f2 < 0.075). A nice finding is that the same qualitative profile appears in three additional independent datasets.

Two analyses are especially interesting. First, the authors show a difference between absolute and relative spectral magnitude (basically, within-subject normalization). Relative scaling sharpens the spectral specificity of the spatial maps, while absolute magnitude is dominated by a broad spatial mode that correlates positively across frequencies, likely reflecting head-position/field-spread factors. The replication of the main age profile is robust to preprocessing decisions (e.g., SSS movement compensation choices) - the bigger determinant of the effect is whether they apply sensor normalization (relative vs absolute).

Second, lots of brain-related things might be related to age, and the authors spend some time trying to back out confounds/covariates. This section is handled transparently (in general, I found the writing style very clear throughout) - they examine single covariates (sex, BP, GGMV, etc.) and compare simple vs partial age effects. For example, aging is correlated with reductions in global grey-matter volume (GGMV), but it would be nice to find a measure that is independent of this: controlling for GGMV (via a linear model) reduces age-related effect sizes heterogeneously across space/frequency but does not eliminate them, a nuance the authors treat carefully.

This is a nice paper, and I have only a few concrete suggestions:

(1) High-gamma:

There can be a lot of EMG / eye movement contamination (I know these were RS eyes closed data, but still..) above 30-40 Hz, and these effects are the weakest anyway. Could you add an analysis (e.g., ICA/label-based muscle component removal) and show the gamma band's sensitivity to that step? Or just note this point more clearly?

(2) GGMV confound control:

Controlling for GGMV reduces, but does not eliminate, age effects. I have a few questions about this: a) Could we see the residuals as a function of age? I wonder if there are non-linear effects or something else that the regression is not accounting for. Also, b) GGMV and age are highly colinear - is this an issue? Can regression really split them apart robustly? I think by some cunning orthogonalisation, you can compute the effect of age independent of GGVM. I don't think this is the same as the effect 'adjusted' for GGMV (which is what is shown here if I'm reading it correctly). Finally, of course, GGMV might actually be the thing you want to look at (because it might more accurately reflect clinical issues) - so strong correlations are not really a problem: I think really the focus might even be on using MEG to predict GGMV and controlling for age.

Reviewer #1 (Public review):

Summary:

The manuscript investigates how exogenous attention modulates spatial frequency sensitivity within the foveola. Using high-precision eye-tracking and gaze-contingent stimulus control, the authors show that exogenous attention selectively improves contrast sensitivity for low- to mid-range spatial frequencies (4-8 cycles/degree), but not for higher frequencies (12-20 CPD). In contrast, improvements in asymptotic performance at the highest contrast levels occur across all spatial frequencies. These results suggest that, even within the foveola, exogenous attention operates through a mechanism similar to that observed in peripheral vision, preferentially enhancing lower spatial frequencies.

Strengths:

The study shows strong methodological rigor. Eye position was carefully controlled, and the stimulus generation and calibration were highly precise. The authors also situate their work well within the existing literature, providing a clear rationale for examining the fine-grained effects of exogenous attention within the foveola. The combination of high spatial precision, gaze-contingent presentation, and detailed modeling makes this a valuable technical contribution.

Weaknesses:

The manipulation of attention raises some interpretive concerns. Clarifying this issue, together with additional detail about statistics, participant profiles, other methodological elements, and further discussion in relation to oculomotor control in general, could broaden the impact of the findings.

Reviewer #1 (Public review):

Summary:

The study from Wu and Turrigiano investigates how disruption of taste coding in a mouse model of autism spectrum disorders (ASDs) affects aversive learning in the context of a conditioned taste aversion (CTA) paradigm. The experiments combine 2-photon calcium imaging of neurons in the gustatory portion of the anterior insular cortex (i.e., gustatory cortex) with behavioral training and testing. The authors rely on Shank3 knockout mice as a model for ASDs. The authors found that Shank3 mice learn CTA more slowly and extinguish the memory more rapidly than control subjects. Calcium imaging identified impairments in taste-evoked activity associated with memory encoding and extinction. During memory encoding, the authors found less suppressed neuronal activity and increased correlated variability in Shank3 mice compared to controls. During extinction, they observed a faster loss of taste selectivity and degradation of taste discriminability in mutants compared to controls.

Strengths:

This is a well-written manuscript that presents interesting findings. The results on the learning and extinction deficits in Shank3 mice are of particular interest. Analyses of neural activity are well conducted and provide important information on the type of impaired cortical activity that may correlate with behavioral deficits.

Weaknesses:

(1) The experiments rely on three groups: CS-only WT, CTA WT, and CTA KO. Can the authors provide a rationale for not having a CS-only KO group?

(2) The authors design an effective behavioral paradigm comparing consumption of water and saccharin and tracking extinction (Figure 3). This paradigm shows differences in licking across distinct behavioral conditions. For instance, during T1, licking to water strongly differs from licking to saccharin for both WT and KO. During T2, licking to water strongly differs from licking to saccharin only for WT (much less for KO), and licking to saccharin in WT differs from that in KO. These differences in taste sampling across conditions could contribute to some of the effects on neural activity and discriminability reported in Figures 5 and 6. That is sucrose and water trials may be highly discriminable because in one case the mouse licks and in the other it does not (or licks much less). The author may want to address this issue.

(3) Are there any omission trials following CTA? If so, they should be quantified and reported. How are the omission trials treated with regard to the analyses?

(4) The authors describe the extinction paradigm as "alternative choice". In decision-making, alternative choice paradigms typically require 2 lateral spouts to report decisions following the sampling from a central spout. To avoid confusion, the authors may want to define their paradigm as alternative sampling.

(5) Figure 4 reports that CTA increases the proportion of neurons that consistently respond to saccharin and water across days. While the saccharin result could be an effect of aversive learning, it is less clear why the phenomenon would generalize to water as well. Can the authors provide an explanation?

(6) The recordings are performed in the part of the anterior insular cortex that is typically defined as "gustatory cortex" (GC). Given the functional heterogeneity of the anterior insular cortex (AIC) and given that the authors do not sample all of the anteroposterior extent of AIC, I would suggest being more explicit about their positioning in GC. Also, some citations (e.g., Gogolla et al, 2014) refer to the posterior insular cortex, which is considered more inherently multimodal than GC. GC multimodality is typically associative in nature, as only a few neurons respond to sound and light in naïve animals.

(7) It would be useful to add summary figures showing the extent of viral spread as well as GRIN lens placement.

(8) I encourage the authors to add Ns every time percentages are reported. How many neurons have been recorded in each condition? Can the authors provide the average number of neurons recorded per session and per animal?

(9) It looks like some animals learned more than others (Figure 1E or Figure 3C). Is it possible to compare neural activity across animals that showed different degrees of learning?

Reviewer #1 (Public review):

Summary:

In the ecological interactions between wild plants and specialized herbivorous insects, structural innovation-based diversification of secondary metabolites often occurs. In this study, Agrawal et al. utilized two milkweed species (Asclepias curassavica and Asclepias incarnata) and the specialist Monarch butterfly (Danaus plexippus) as a model system to investigate the effects of two N,S-cardenolides - formed through structural diversification and innovation in A. curassavica-on the growth, feeding, and chemical sequestration of D. plexippus, compared to other conventional cardenolides. Additionally, the study examined how cardenolide diversification resulting from the formation of N,S-cardenolides influences the growth and sequestration of D. plexippus. On this basis, the research elucidates the ecophysiological impact of toxin diversity in wild plants on the detoxification and transport mechanisms of highly adapted herbivores.

Strengths:

The study is characterized by the use of milkweed plants and the specialist Monarch butterfly, which represent a well-established model in chemical ecology research. On one hand, these two organisms have undergone extensive co-evolutionary interactions; on the other hand, the butterfly has developed a remarkable capacity for toxin sequestration. The authors, building upon their substantial prior research in this field and earlier observations of structural evolutionary innovation in cardenolides in A. curassavica, proposed two novel ecological hypotheses. While experimentally validating these hypotheses, they introduced the intriguing concept of a "non-additive diversity effect" of trace plant secondary metabolites when mixed, contrasting with traditional synergistic perspectives, in their impact on herbivores.

Weaknesses:

The manuscript has two main weaknesses. First, as a study reliant on the control of compound concentrations, the authors did not provide sufficient or persuasive justification for their selection of the natural proportions (and concentrations) of cardenolides. The ratios of these compounds likely vary significantly across different environmental conditions, developmental stages, pre- and post-herbivory, and different plant tissues. The ecological relevance of the "natural proportions" emphasized by the authors remains questionable. Furthermore, the same compound may even exert different effects on herbivorous insects at different concentrations. The authors should address this issue in detail within the Introduction, Methods, or Discussion sections.

Second, the study was conducted using leaf discs in an in vitro setting, which may not accurately reflect the responses of Monarch butterflies on living plants. This limitation undermines the foundation for the novel ecological theory proposed by the authors. If the observed phenomena could be validated using specifically engineered plant lines-such as those created through gene editing, knockdown, or overexpression of key enzymes involved in the synthesis of specific N,S-cardenolides - the findings would be substantially more compelling.

Reviewer #1 (Public review):

Bajohr and colleagues propose a transcription factor-driven approach to generating bonafide oligodendrocyte lineage cells (OLCs) from primary mouse astrocytes. Ectopic expression of Olig2, Sox10, or Nkx6.2 in isolated astrocytes produced a range of OLC-like cell states, with Sox10 emerging from lineage tracing and single cell RNA sequencing experiments as the most successful transcription factor in driving direct lineage reprogramming. The authors strengthened their claims with an unbiased, deep learning perturbation model to predict genetic drivers of the astrocyte cluster to OLC cluster transition observed in their scRNA seq dataset. Here, Sox10 surfaced in the top ten correlated genes, and the top transcription factor, mediating this fate shift. Altogether, this paper presents an interesting approach to generate OLCs, a cell type historically difficult to procure, from primary mouse astrocytes to study this lineage in development and disease and perhaps repopulate it in dysmyelinating conditions. While this certainly addresses a technical gap in the field, authors defined iOLCs as ones with lineage-specific gene expression and morphological characteristics, lacking any functional analysis to assess the reprogrammed cells' capacity to myelinate. This comment and other critiques are discussed below.

While Sox10 and Mbp expression in iOLCs, as confirmed by IHC, is a promising result suggesting that ectopic Sox10 instructs transduced cells to develop into cells of myelinating potential, functional confirmation is essential. As mentioned in the discussion, the absence of a substrate for myelination may have also contributed to the low DLR efficiency. Co-culturing Sox10 iOLCs with primary neurons and examining the cells' potential to engage and enwrap axons would greatly strengthen the authors' claim that this could be an effective therapeutic approach to myelin regeneration in vivo, or even a technical approach to studying myelin dynamics in vitro.

In Figure 1B, it appears that Mbp expression in tdTomato+ cells decreases in Sox10 transduced iOLs during the observed time period. Can the authors elaborate on this result, given that MBP expression is crucial for myelination and should, if anything, increase with time?

The authors acknowledge that there is a conversion of tdTomato- zsGreen+ cells with an astrocyte-like morphology to OLC cells expressing Mbp following Sox10 induction (Supplementary figure 5C,D). While they note the diversity of the astrocyte lineage in the discussion, further analysis should be applied to this subset of cells to confirm the subset of astrocyte or progenitor-like cell type that gives rise to their cell endpoint of interest (Sox10-driven Mbp+ iOLs).

Finally, ectopic expression of Olig2 and Sox10 in primary astrocytes resulted in very different OLC subtypes, as evidenced by OLC marker expression seen in IHC and the subclustering of these cell types in scRNA seq. Although this diversity in OLC type and generation efficiency follows with previous reports showing that these two transcription factors vary in effect, might the authors further discuss this discrepancy given that the two transcription factors regulate one another (as mentioned in the introduction) and should theoretically give rise to more similar cells? Perhaps due to the lower specificity of Olig2 in marking a pure OLC population relative to Sox10?

Reviewer #1 (Public review):

This study explores the connectivity patterns that could lead to fast and slow undulating swim patterns in larval zebrafish using a simplified theoretical framework. The authors show that a pattern of connectivity based only on inhibition is sufficient to produce realistic patterns with a single frequency. Two such networks couple with inhibition but with distinct time constants can produce a range of frequencies. Adding excitatory connections further increases the range of obtainable frequencies, albeit at the expense of sudden transitions in mid-frequency range.

Strengths:

(1) This is an eloquent approach to answering the question of how spinal locomotor circuits generate coordinated activity using a theoretical approach based on moving bump models of brain activity.

(2) The models make specific predictions on patterns of connectivity while discounting the role of connectivity strength or neuronal intrinsic properties in shaping the pattern.

(3) The models also propose that there is an important association between cell-type-specific intersegmental patterns and the recruitment of speed-selective subpopulations of interneurons.

(4) Having a hierarchy of models creates a compelling argument for explaining rhythmicity at the network level. Each model builds on the last and reveals a new perspective on how network dynamics can control rhythmicity. I liked that each model can be used to probe questions in the next/previous model.

Comments on revisions:

I am very happy to see the simplified biophysical model supporting the original findings. The authors have done an excellent job addressing my comments.

Just a small note, please change C. Elegans to C. elegans.

Reviewer #1 (Public review):

The authors aim to predict ecological suitability for transmission of highly pathogenic avian influenza (HPAI) using ecological niche models. This class of models identify correlations between the locations of species or disease detections and the environment. These correlations are then used to predict habitat suitability (in this work, ecological suitability for disease transmission) in locations where surveillance of the species or disease has not been conducted. The authors fit separate models for HPAI detections in wild birds and farmed birds, for two strains of HPAI (H5N1 and H5Nx) and for two time periods, pre- and post-2020. The authors also validate models fitted to disease occurrence data from pre-2020 using post-2020 occurrence data.

Reviewer #1 (Public review):

Summary:

Davis and co-authors used many mouse models to investigate mechanisms that regulate the contractility of mouse popliteal collecting vessels, primarily chronotropy. Many of the mechanisms studied were previously shown to regulate pressure-induced constriction in small arteries. The authors use prior literature from the vasculature as a framework to test similar concepts in lymphatic vessels. The mouse models used provide evidence for and against the involvement of multiple proteins in regulating chronotropy and other contractile properties in lymphatic vessels. They propose that mechano-activation of GNAQ/GNA11-coupled GPCRs generates IP3, which induces Ca2+ release through IP3R1 and drives depolarization through the activation of ANO1 Cl- channels. Major concerns include the author's major conclusion that GNAQ/GNA11-coupled GPCRs contribute to chronotropy. This conclusion is not supported by the data presented.

Strengths:

One major strength of the study lies in the vast number of mouse knockout models that were used to test the importance of ion channels and G protein signaling pathways in the regulation of lymphatic vessel contractility. In this regard, the study is a valiant effort. The authors achieved several objectives to find that ANO1 and IP3R1 regulate chronotropy, and many other potential proteins do not regulate chronotropy. This study will have a major impact on the field if additional support for G proteins is provided.

Weaknesses:

Major conclusions concerning the involvement of G proteins are drawn from the global Gna11 knockout mouse models. This conclusion is weak. Global Gna11 knockout mice are highly likely to have a multifactorial phenotype that could create significant differences in the data. Control experiments need to be performed on vessels from the global knockout mice if these major conclusions are to be made. Similarly, pharmacological tools or alternative approaches to manipulate G proteins should be used to support the data from these mouse models to draw these major conclusions.

The Gnaq smKO mice are the most specific G protein model studied here. However, there is no phenotype. Do not discuss trends in the data. If the data are not significant, conclude so. If more experiments are required to reach significance, provide more data in the manuscript.

The conclusions repeatedly refer to a signaling pathway wherein the upstream component is GPCRs, which activate G proteins. While this may be the case, no GPCRs were identified here, and the involvement of G proteins is questionable, as the authors outline in lines 693-695 and noted above. The conclusions should be tempered, including in the abstract, unless additional experiments are performed to support the involvement of G proteins. Perhaps then the authors may be able to infer that GPCRs are involved.

Line 318. The point regarding the choice to use popliteal vessels versus IALVs will be unclear to the uninitiated, particularly as the authors previously used IALVs. Including additional justification in the text and/or data from IALVs in Figure 1, which compares IALVs to popliteal vessels, would better explain the logic.

The conclusions drawn for TRPC6 and TRPC3 are less convincing. Germline global knockout mice, which are known to undergo compensation, were used, and high data variability is apparent. Using TRPC3 and TRPC6 blockers in the mouse models studied in Figure 4 would strengthen the arguments made regarding these proteins.

Did you perform power analysis to ensure that experimental numbers were sufficient to conclude that no statistical difference exists between datasets? If not, this needs to be done. For example, data shown in Figure 5C for tone and 6C for frequency and tone appear to be significantly different, but are concluded not to be so.

At the end of each result section, a concluding statement is made regarding the effects on pressure-induced chronotrophy. In many cases, there are additional effects of manipulating protein expression on other contractile properties. One example is for TRPC3 and TRPC6 (lines 414-416), but others are TRPV4, TRPV3, ENaC, Kir, Cav3.1/3.2, etc. Some interpretation is in the Discussion, but the concluding statements at the end of each result section should be expanded to summarize what the authors think the other significant differences in the data represent.

Kv7.4 channels. You state you have data (not shown) with linopiridine and XE991. Why not show those results here to support the experiments with the Kcnq4 smKO mice? Otherwise, I suggest you remove the statement from the unpublished data.

Figure 13A. Kcnj2 is modestly expressed in LECs, but very little is present in LMCs. This likely underlies the effect of barium. If you remove the endothelium, does the effect of barium disappear? While this is not the major focus of the study, the effects of barium are dramatic, and it should be made clear whether this is due to inhibition of Kir channels in smooth muscle or endothelial cells.

Figure 18C tone. Several values for losartan look different but are not labelled as such. Please clarify and discuss if different.

The manuscript should include raw data traces in figures that show the major pathways that you conclude regulate chronotropy.

Reviewer #1 (Public review):

Summary:

The work of Bechara Rahme and colleagues provides an explanation as to how bacterially infected flies eventually die. While widespread tissue and multiorgan damage are to be expected in the latest stages of a systemic infection, the mechanisms leading to the host's death remain unresolved. To this end, this work illustrates the role of PrtA, a metalloproteinase found within Outer Membrane Vesicles (OMVs) secreted by Serratia marcescens, in inducing neuronal apoptosis and paralysis before death. Another interesting aspect of the work is the compromise of blood blood-brain barrier (BBB) by OMVs. BBB is different between mammals and flies; however, it merits scientific attention.

Strengths:

The strength of evidence lies in a wealth of experiments involving disparate innate immune mechanisms that either contribute (Imd, PPO1/2, Nox, Duox, SOD2) or oppose (hemocytes and Hayan protease) host defense. Moreover, the role of neuronal JNK and apoptic signaling is shown to contribute to host death.

Genetics is supported by experiments using chemical treatments (Vitamin C and mito-TEMPO) as host-protecting antioxidants, and the biochemical purification and quantification of OMVs and the PrtA protease.

Weaknesses:

However, the reliance on non-isogenised flies to provide quantitative data is unsafe, and at this point, the strength of the evidenceis apparently incomplete. The mutant flies used for the genes Key, Myd88, Hayan, and Nos are doubtfully comparable to the control fly strains used in terms of the general genetic background. The latter is of utmost importance in assessing quantitative traits.

The general background difference between control and test flies is also an issue when using tissue-specific expression via GAL4/UAS, because the UAS lines used are only apparently but not truly isogenic to the w flies used as controls.

Reviewer #1 (Public review):

The investigators elegantly utilized a single-cell co-assay of RNA and ATAC seq to unveil the heterogeneous gene regulatory networks in Ewing sarcoma. The authors should be commended on their ability to identify multiple unique modules of gene regulation of Ewing sarcoma utilizing complex computational methods between numerous Ewing sarcoma cell lines. Additionally, they complemented their single-cell findings with xenografts as well as primary Ewing sarcoma patient tumors - validating the intratumoral heterogeneous gene regulatory networks of Ewing sarcoma. More importantly, they have revealed that exogenous TGF-β may modify these distinct epigenetic and transcriptional signatures within Ewing sarcoma tumors. Overall, the manuscript highlights an important discovery of the heterogenous gene regulatory programming of Ewing sarcoma and further highlights the role that TGFB plays within the tumor microenvironment of Ewing sarcoma. There are some areas of ambiguity that require clarification to increase the impact of the manuscript.

Reviewer #1 (Public review):

Summary:

The authors investigate the effects of aging on auditory system performance in understanding temporal fine structure (TFS), using both behavioral assessments and physiological recordings from the auditory periphery, specifically at the level of the auditory nerve. This dual approach aims to enhance understanding of the mechanisms underlying observed behavioral outcomes. The results indicate that aged animals exhibit deficits in behavioral tasks for distinguishing between harmonic and inharmonic sounds, which is a standard test for TFS coding. However, neural responses at the auditory nerve level do not show significant differences when compared to those in young, normal-hearing animals. The authors suggest that these behavioral deficits in aged animals are likely attributable to dysfunctions in the central auditory system, potentially as a consequence of aging.To further investigate this hypothesis, the study includes an animal group with selective synaptic loss between inner hair cells and auditory nerve fibers, a condition known as cochlear synaptopathy (CS). CS is a pathology associated with aging and is thought to be an early indicator of hearing impairment. Interestingly, animals with selective CS showed physiological and behavioral TFS coding similar to that of the young normal-hearing group, contrasting with the aged group's deficits. Despite histological evidence of significant synaptic loss in the CS group, the study concludes that CS does not appear to affect TFS coding, either behaviorally or physiologically.

Strengths:

This study addresses a critical health concern, enhancing our understanding of mechanisms underlying age-related difficulties in speech intelligibility, even when audiometric thresholds are within normal limits. A major strength of this work is the comprehensive approach, integrating behavioral assessments, auditory nerve (AN) physiology, and histology within the same animal subjects. This approach enhances understanding of the mechanisms underlying the behavioral outcomes and provides confidence in the actual occurrence of synapse loss and its effects.The study carefully manages controlled conditions by including five distinct groups: young normal-hearing animals, aged animals, animals with CS induced through low and high doses, and a sham surgery group. This careful setup strengthens the study's reliability and allows for meaningful comparisons across conditions. Overall, the manuscript is well-structured, with clear and accessible writing that facilitates comprehension of complex concepts.

Weakness:

The stimulus and task employed in this study are very helpful for behavioral research, and using the same stimulus setup for physiology is advantageous for mechanistic comparisons. However, I have some concerns about the limitations in auditory nerve (AN) physiology. Due to practical constraints, it is not feasible to record from a large enough population of fibers that covers a full range of best frequencies (BFs) and spontaneous rates (SRs) within each animal. This raises questions about how representative the physiological data are for understanding the mechanism in behavioral data. I am curious about the authors' interpretation of how this stimulus setup might influence results compared to methods used by Kale and Heinz (2010), who adjusted harmonic frequencies based on the characteristic frequency (CF) of recorded units. While, the harmonic frequencies in this study are fixed across all CFs, meaning that many AN fibers may not be tuned closely to the stimulus frequencies. If units are not responsive to the stimulus further clarification on detecting mistuning and phase locking to TFS effects within this setup would be valuable. Given the limited number of units per condition-sometimes as few as three for certain conditions-I wonder if CF-dependent variability might impact the results of the AN data in this study and discussing this factor can help with better understanding the results. While the use of the same stimuli for both behavioral and physiological recordings is understandable, a discussion on how this choice affects interpretation would be beneficial. In addition a 60 dB stimulus could saturate high spontaneous rate (HSR) AN fibers, influencing neural coding and phase-locking to TFS. Potentially separating SR groups, could help address these issues and improve interpretive clarity.

A deeper discussion on the role of fiber spontaneous rate could also enhance the study. How might considering SR groups affect AN results related to TFS coding? While some statistical measures are included in the supplement, a more detailed discussion in the main text could help in interpretation.

Although Figure S2 indicates no change in median SR, the high-dose treatment group lacks LSR fibers, suggesting a different distribution based on SR for different animal groups, as seen in similar studies on other species. A histogram of these results would be informative, as LSR fiber loss with CS-whether induced by ouabain in gerbils or noise in other animals-is well documented (e.g., Furman et al., 2013).

Although ouabain effects on gerbils have been explored in previous studies, since these data is already seems to be recorded for the animal in this study, a brief description of changes in auditory brainstem response (ABR) thresholds, wave 1 amplitudes, and tuning curves for animals with cochlear synaptopathy (CS) in this study would be beneficial. This would confirm that ouabain selectively affects synapses without impacting outer hair cells (OHCs). For aged animals, since ABR measurements were taken, comparing hearing differences between normal and aged groups could provide insights into the pathologies besides CS in aged animals. Additionally, examining subject variability in treatment effects on hearing and how this correlates with behavior and physiology would yield valuable insights. If limited space maybe a brief clarification or inclusion in supplementary could be good enough.

Another suggestion is to discuss the potential role of MOC efferent system and effect of anesthesia in reducing efferent effects in AN recordings. This is particularly relevant for aged animals, as CS might affect LSR fibers, potentially disrupting the medial olivocochlear (MOC) efferent pathway. Anesthesia could lessen MOC activity in both young and aged animals, potentially masking efferent effects that might be present in behavioral tasks. Young gerbils with functional efferent systems might perform better behaviorally, while aged gerbils with impaired MOC function due to CS might lack this advantage. A brief discussion on this aspect could potentially enhance mechanistic insights.

Lastly, although synapse counts did not differ between the low-dose treatment and NH I sham groups, separating these groups rather than combining them with the sham might reveal differences in behavior or AN results, particularly regarding the significance of differences between aged/treatment groups and the young normal-hearing group.

Reviewer #1 (Public review):

Summary:

Grasper et al. present a combined analysis of the role of temporal mutagenesis in cancer, which includes both theoretical investigation and empirical analysis of point mutations in TCGA cancer patient cohorts. They find that temporal elevated mutation rates contribute to cancer fitness by allowing fast adaptation when the fitness drops (due to previous deleterious mutations). This may be relevant in the case of tumor suppressor genes (TSG), which follow the 2-hit hypothesis (i.e., biallelic 2 mutations are necessary to deactivate TS), and in cases where temporal mutagenesis occurs (e.g. high APOBEC, ROS). They provide evidence that this scenario is likely to occur in patients, in some cancer types. This is an interesting and potentially important result that merits the attention of the target audience. Nonetheless, I have some questions (detailed below) regarding the design of the study, the tools and parametrization of the theoretical analysis and the empirical analysis - that I think if addressed would make the paper more solid and the conclusion more substantiated.

Strengths:

Combined theoretical investigation with empirical analysis of cancer patients

Weaknesses:

Parametrization and systematic investigation of theoretical tools and their relevant to tumor evolution

Comments on revisions:

The authors have adequately addressed my suggestions. I think some of the details provided in some of the replies to my comments (specifically with regard to my points 1, 4, 6ii; minor point 6) could be integrated into relevant text in the introduction , discussion and methods, to help the readers follow better the model and its interpretation - but this is up to the authors to decide what to emphasize.

Reviewer #1 (Public review):

Summary:

In this study, Jeong and Choi examine neural correlates of behavior during a naturalistic foraging task in which rats must dynamically balance resource acquisition (foraging) with the risk of threat. Rats first learn to forage for sucrose reward from a spout, and when a threat is introduced (an attack-like movement from a "LobsterBot"), they adjust their behavior to continue foraging while balancing exposure to the threat, adopting anticipatory withdraw behaviors to avoid encounter with the LobsterBot. Using electrode recordings targeting the medial prefrontal cortex (mPFC), they identify heterogenous encoding of task variables across prelimbic and infralimbic cortex neurons, including correlates of distance to the reward/threat zone and correlates of both anticipatory and reactionary avoidance behavior. Based on analysis of population responses, they show that prefrontal cortex switches between different regimes of population activity to process spatial information or behavioral responses to threat in a context-dependent manner. Characterization of the heterogenous coding scheme by which frontal cortex represents information in different goal states is an important contribution to our understanding of brain mechanisms underlying flexible behavior in ecological settings.

Strengths:

As many behavioral neuroscience studies employ highly controlled task designs, relatively less is generally known about how the brain organizes navigation and behavioral selection in naturalistic settings, where environment states and goals are more fluid. Here, the authors take advantage of a natural challenge faced by many animals - how to forage for resources in an unpredictable environment - to investigate neural correlates of behavior when goal states are dynamic. They investigate how prefrontal cortex (mPFC) activity is structured to support different functional "modes" (here, between a navigational mode and a threat-sensitive foraging mode) for flexible behavior. Overall, an important strength and real value of this study is the design of the behavioral experiment, which is trial-structured, permitting strong statistical methods for neural data analysis, yet still rich enough for unconstrained, natural behavior structured by the animal's volitional goals. The experiment is also phased to measure behavioral changes as animals first encounter a threat, and then learn to adapt their foraging strategy to its presence. Characterization of this adaptation process is itself quite interesting and sets a foundation for further study of threat learning and risk management in the foraging context. Finally, the characterization of single-neuron and population dynamics in mPFC in this naturalistic setting with fluid goal states is an important contribution to the field. Previous studies have identified neural correlates of spatial and behavioral variables in frontal cortex, but how these representations are structured, or how they are dynamically adjusted when animals shift their goals, has been less clear. The authors synthesize their main conclusions into a conceptual model for how mPFC could encode task variables in a context-dependent manner, and provide a useful framework for thinking about circuit-level mechanisms that may support mode switching.

Weaknesses:

The task design in this study is intentionally stimulus-rich and places minimal constraint on the animal to preserve naturalistic behavior, and this introduces some confounds that place some limits on the interpretability of neural responses. For example, some variables which are the target of neural correlation analysis, such as spatial/proximity coding and coding of threat and threat-related behaviors, are naturally entwined. In their revisions, the authors have included extensive analyses and control conditions to disambiguate these confounds. Within the limits of their task design, this provides compelling evidence that mPFC neurons encode threat, decision, and spatial information in a context-dependent manner. Future experiment designs, which intentionally separate task contexts (e.g. navigation vs. foraging), could serve to further clarify the structure of coding across contexts and/or goal states.

While the study provides an important advance in our understanding of mPFC coding structure under naturalistic conditions, the study still lacks functional manipulations to establish any form of causality. This limitation is acknowledged in the text, and the report is careful not to over interpret suggestions of causal contribution, instead setting a foundation for future investigations.

Reviewer #1 (Public review):

In this manuscript, Chen et al. investigate the role of the membrane estrogen receptor GPR30 in spinal mechanisms of neuropathic pain. Using a wide variety of techniques, they first provide convincing evidence that GPR30 expression is restricted to neurons within the spinal cord, and that GPR30 neurons are well-positioned to receive descending input from the primary sensory cortex (S1). In addition, the authors put their findings in the context the previous knowledge in the field, presenting evidence demonstrating that GRP30 is expressed in the majority of CCK-expressing spinal neurons. Overall, this manuscript furthers our understanding of neural circuity that underlies neuropathic pain and will be of broad interest to neuroscientists, especially those interested in somatosensation. Nevertheless, the manuscript would be strengthened by additional analyses and clarification of data that is currently presented.

Strengths:

The authors present convincing evidence for expression of GPR30 in the spinal cord that is specific to spinal neurons. Similarly, complementary approaches including pharmacological inhibition and knockdown of GPR30 are used to demonstrate a role for the receptor in driving nerve injury-induced pain in rodent models.

Weaknesses:

Although steps were taken to put their data into the broader context of what is already known about the spinal circuitry of pain, more considerations and analyses would help the authors better achieve their goal. For instance, to determine whether GPR30 is expressed in excitatory or inhibitory neurons, more selective markers for these subtypes should be used over CamK2. Moreover, quantitative analysis of the extent of overlap between GPR30+ and CCK+ spinal neurons is needed to understand the potential heterogeneity of the GPR30 spinal neuron population, and to interpret experiments characterizing descending SI inputs onto GPR30 and CCK spinal neurons. Filling these gaps in knowledge would make their findings more solid.

Revised Manuscript Update:

In their revised manuscript, Chen et al. have added additional data that establishes GPR30 spinal neurons as a population of excitatory neurons, half of which express CCK. These data help to position GPR30 neurons in the existing framework of spinal neuron populations that contribute to neuropathic pain, strengthening the author's findings.

I have no new recommendations to the author's following this round of revisions.

Reviewer #1 (Public review):

In the Late Triassic (around 230 Ma ago), southern Wales and adjacent parts of England were a karst landscape. The caves and crevices accumulated remains of small vertebrates. These fossil-rich fissure fills are being exposed in limestone quarrying. In 2022 (reference 13 of the article), a partial articulated skeleton and numerous isolated bones from one fissure fill were named Cryptovaranoides microlanius and described as the oldest known squamate - the oldest known animal, by some 50 Ma, that is more closely related to snakes and some extant lizards than to other extant lizards. This would have considerable consequences for our understanding of the evolution of squamates and their closest relatives, especially for its speed and absolute timing, and was supported in the same paper by phylogenetic analyses based on different datasets.

In 2023, the present authors published a rebuttal (ref. 18) to the 2022 paper, challenging anatomical interpretations and the irreproducible referral of some of the isolated bones to Cryptovaranoides. Modifying the datasets accordingly, they found Cryptovaranoides outside Squamata and presented evidence that it is far outside. In 2024 (ref. 19), the original authors defended most of their original interpretation and presented some new data, some of it from newly referred isolated bones. The present article discusses anatomical features and the referral of isolated bones in more detail, documents some clear misinterpretations, argues against the widespread but not justifiable practice of referring isolated bones to the same species as long as there is merely no known evidence to the contrary, further argues against comparing newly recognized fossils to lists of diagnostic characters from the literature as opposed to performing phylogenetic analyses and interpreting the results, and finds Cryptovaranoides outside Squamata again.

Although a few of the character discussions can probably still be improved, I see no sign that the discussion is going in circles or otherwise becoming unproductive. I can even imagine that the present contribution will end it.

Reviewer #1 (Public review):

Summary and Strengths:

The very well-written manuscript by Lövestam et al. from the Scheres/Goedert groups entitled "Twelve phosphomimetic mutations induce the assembly of recombinant full-length human tau into paired helical filaments" demonstrates the in vitro production of the so-called paired helical filament Alzheimer's disease (AD) polymorph fold of tau amyloids through the introduction of 12 point mutations that attempt to mimic the disease-associated hyper-phosphorylation of tau. The presented work is very important because it enables disease-related scientific work, including seeded amyloid replication in cells, to be performed in vitro using recombinant-expressed tau protein.

Comments on revised version:

The manuscript is significantly improved, as also indicated by Reviewer 2, with the 100% formation of the PHF and the additional experiments to elucidate on the potential mechanism by the PTMs. This is a great work.

Reviewer #1 (Public review):

Summary:

Activation of thermogenesis by cold exposure and dietary protein restriction are two lifestyle changes that impact health in humans and lead to weight loss in model organisms, here the mouse. How these affect liver and adipose tissues has not been thoroughly investigated side by side. In mice, the authors show that the responses to methionine restriction and cold exposure are tissue-specific while the effects on beige adipose are somewhat similar.

Strengths:

The strength of the work is the comparative approach, using transcriptomics and bioinformatic analyses to investigate the tissue-specific impact. The work was performed in mouse models and is state-of-the-art. This represents an important resource for researchers in the field of protein restriction and thermogenesis.

Weaknesses:

The findings are descriptive and the conclusions remain associative. The work is limited to mouse physiology and the human implications have not been investigated yet.

Reviewer #1 (Public review):

Summary:

This manuscript describes a study examining the relationship between microsaccades and covert attention. This question has been widely investigated, with numerous studies showing that during sustained fixation, when subjects covertly attend to a peripheral stimulus, microsaccades tend to be biased toward the attended location. Here, the authors ask whether this microsaccade bias reflects a shift of covert attention or the maintenance of covert attention. They conclude that the bias is primarily driven by attention shifts, a finding that also helps reconcile the seemingly conflicting results of prior research, where the bias was questioned in paradigms that largely involved attention maintenance rather than shifting.

Strengths:

The paradigm and conclusions appear sound and supported by the results. A large sample size was used.

Weaknesses:

Weaknesses are mostly related to how the authors enforced fixation in the task, and clarifications are needed regarding some methodological details. A more direct comparison of the effect in the two experimental conditions is missing.

Reviewer #1 (Public review):

Summary:

The authors report intracranial EEG findings from 12 epilepsy patients performing an associative recognition memory task under the influence of scopolamine. They show that scopolamine administered before encoding disrupts hippocampal theta phenomena and reduces memory performance, and that scopolamine administered after encoding but before retrieval impairs hippocampal theta phenomena (theta power, theta phase reset) and neural reinstatement but does not impair memory performance. This is an important study with exciting, novel results and translational implications. The manuscript is well-written, the analyses are thorough and comprehensive, and the results seem robust.

Strengths:

(1) Very rare experimental design (intracranial neural recordings in humans coupled with pharmacological intervention).

(2) Extensive analysis of different theta phenomena.

(3) Well-established task with different conditions for familiarity versus recollection.

(4) Clear presentation of findings and excellent figures.

(5) Translational implications for diseases with cholinergic dysfunction (e.g., AD).

(6) Findings challenge existing memory models, and the discussion presents interesting novel ideas.

Weaknesses:

(1) One of the most important results is the lack of memory impairment when scopolamine is administered after encoding but before retrieval (scopolamine block 2). The effect goes in the same direction as for scopolamine during encoding (p = 0.15). Could it be that this null effect is simply due to reduced statistical power (12 subjects with only one block per subject, while there are two blocks per subject for the condition with scopolamine during encoding), which may become significant with more patients? Is there actually an interaction effect indicating that memory impairment is significantly stronger when scopolamine is applied before encoding (Figure 1d)? Similar questions apply to familiarity versus recollection (lines 78-80). This is a very critical point that could alter major conclusions from this study, so more discussion/analysis of these aspects is needed. If there are no interaction effects, then the statements in lines 84-86 (and elsewhere) should be toned down.

(2) Further, could it simply be that scopolamine hadn't reached its major impact during retrieval after administration in block 2? Figure 2e speaks in favor of this possibility. I believe this is a critical limitation of the experimental design that should be discussed.

(3) It is not totally clear to me why slow theta was excluded from the reinstatement analysis. For example, despite an overall reduction in theta power, relative patterns may have been retained between encoding and recall. What are the results when using 1-128 Hz as input frequencies?

(4) In what way are the results affected by epileptic artifacts occurring during the task (in particular, IEDs)?

Joint Public Review:

Summary

Non-alcoholic fatty liver disease (NAFLD) is a widespread metabolic disease associated with obesity. Endoplasmic reticulum and calcium dysregulation are hallmarks of NAFLD. Here, the authors explore whether the secreted liver protein transthyretin (TTR), which has been previously shown to modulate calcium signaling in the context of insulin resistance, could also impact NAFLD. The study is motivated by a small cohort of NASH patients who show elevated TTR levels. The authors then overexpress TTR in two mouse obesogenic models, which leads to elevated liver lipid deposition. In contrast, liver-specific TTR knockdown improves some liver lipid levels, reduces inflammation markers, and improves glucose tolerance, overall improving the NAFLD markers. These phenotypic findings are overall convincing and largely consistent in two different diet models.

Because of TTR's connection to calcium regulation, the authors then assess whether the knockdown affects ER stress and impacts SERCA2 expression. However, the direct mechanistic evidence supporting the central claim that TTR physically interacts with and inhibits the SERCA2 calcium pump is preliminary and requires further validation. Whether the broader effects on lipid accumulation, inflammation markers, and glucose tolerance are mechanistically connected remains to be determined.

Strengths

The premise of the study is built on prior work from the authors identifying a link between increased transthyretin secretion and the development of insulin resistance, a related obesity condition. The in vivo studies are comprehensive, using human NASH samples, two distinct diet-induced mouse models (HFD and GAN), and in vitro hepatocyte models. The phenotypic data showing that TTR knockdown alleviates steatosis, inflammation, and insulin resistance are robust and convincing across these systems.

Weaknesses

The mechanistic studies in Figures 6-9 are incomplete. There are several issues encompassing experimental design, rigor, and interpretation that, if properly addressed, would make the study much stronger.

(1) Exogenous TTR that is endocytosed by cells is unlikely to ever find itself inside the lumen of the ER. Conversely, endogenous TTR that is produced in cells and that has not yet been secreted is almost certain to have an ER lumenal localization (as in Figures 7B and 9A, and where an apparent colocalization with SERCA is likely to be incidental). In a model where TTR, acting as a hepatokine, has inhibitory effects on SERCA, these would almost certainly be realized from the cytosolic side of the ER membrane-a region inaccessible to lumenal endogenous TTR. It is possible that the overexpression and knockdown of endogenous TTR have the effects seen due to its secretion and uptake (that is, cell-non-autonomous effects), but this possibility was not directly tested through Transwell or similar assays. Given the identity of TTR as a secretory pathway client protein, the only localization data for TTR that are unexpected are those suggesting an ER localization of exogenously added TTR (Figure 7A), but this localization seems to involve only a minor population of TTR, is hindered by a technical issue with cell permeabilization (see below), and lacks orthogonal approaches to convincingly demonstrate meaningful localization of exogenous TTR at the ER membrane.

(2) The experimental logic in Figure 8 is problematic. The authors use Thapsigargin (Tg), a potent and specific SERCA inhibitor, to probe SERCA function. However, since both Tg and TTR are proposed to inhibit SERCA2, the design lacks a critical control to demonstrate that TTR's effects are indeed mediated through SERCA2. SERCA2 activity should, in principle, be fully and irreversibly inhibited by Tg treatment, especially using such a high concentration (5 µM). If TTR's effect on calcium flux is exclusively through SERCA2, then SERCA2 impairment by TTR should have no additional effect in the presence of Tg, as Tg would already be maximally inhibiting the pump. The current data (Figures 8G-H) showing an effect of TTR-KD even with Tg present is difficult to interpret and may suggest off-target or compensatory mechanisms.

(3) The coIP data in Figure 9 need to be better controlled, including by overexpression of FLAG- and MYC-tagged irrelevant proteins, ideally also localized to the ER. The coIP of overexpressed TTR with endogenous SERCA in Figure 9D, in addition to requiring a more rigorous control, is itself of relatively low quality, with the appearance of a possible gel/blotting artifact.

(4) The ER stress markers in Figure 6 are not convincing. Molecular weight markers and positive controls (for example, livers from animals injected with tunicamycin) are missing. In addition, the species of ATF6 that is purportedly being detected (cleaved or full-length) is not indicated, and this protein is also notoriously difficult to detect with convincing specificity in mouse tissues. As well, CHOP protein is usually not detectable in control normal diet mouse livers, raising questions of whether the band identified as CHOP is, in fact, CHOP. These issues, along with the observation that ER stress-regulated RNAs are not altered (Figure S5), raise the question of whether ER stress is involved at all. Likewise, the quantification of SERCA2 levels from Figure 6 requires more rigor. For all blots, it isn't clear that analyzing only 3 or 4 of the animals provides adequate and unbiased power to detect differences; in addition, in Figure 6C, at least the SERCA2 exposure (assuming SERCA2 is being specifically detected; see above) is well beyond the linear range of quantification.

In addition, the following important issues were raised:

(5) n=4 for overexpression might not provide adequate statistical power.

(6) The error for human NASH samples and controls in Figure 1A is surprisingly small. Larger gene expression data sets from NASH cohorts exist and should be used to test the finding in a larger population.

(7) For experiments involving two independent variables (e.g., diet and TTR manipulation, as in Figures 2, 3, 4, 5), a Two-way ANOVA must be used instead of One-way ANOVA or t-tests. Also, the ND-TTR-KD group is missing - these data are an essential control to show the specificity of the knockdown and its effects in a non-diseased state.

(8) Figure 7A: The co-localization signal between TTR-Alexa488 and the ER marker is not strong or convincing, which could be due to the inappropriate immunofluorescence protocol used, of permeabilization prior to fixation. The standard and recommended order is fixation first (to preserve cellular architecture), followed by permeabilization.

Reviewer #1 (Public review):

Summary:

The novel advance by Wang et al is in the demonstration that, relative to a standard extinction procedure, the retrieval-extinction procedure more effectively suppresses responses to a conditioned threat stimulus when testing occurs just minutes after extinction. The authors provide solid evidence to show that this "short-term" suppression of responding involves engagement of the dorsolateral prefrontal cortex.

Strengths:

Overall, the study is well-designed and the results are valuable. There are, however, a few issues in the way that it is introduced and discussed. It would have been useful if the authors could have more explicitly related the results to a theory - it would help the reader understand why the results should have come out the way that they did. More specific comments are presented below.

Please note: The authors appear to have responded to my original review twice. It is not clear that they observed the public review that I edited after the first round of revisions. As part of these edits, I removed the entire section titled Clarifications, Elaborations and Edits

Theory and Interpretation of Results

(1) It is difficult to appreciate why the first trial of extinction in a standard protocol does NOT produce the retrieval-extinction effect. This applies to the present study as well as others that have purported to show a retrieval-extinction effect. The importance of this point comes through at several places in the paper. E.g., the two groups in study 1 experienced a different interval between the first and second CS extinction trials; and the results varied with this interval: a longer interval (10 min) ultimately resulted in less reinstatement of fear than a shorter interval. Even if the different pattern of results in these two groups was shown/known to imply two different processes, there is nothing in the present study that addresses what those processes might be. That is, while the authors talk about mechanisms of memory updating, there is little in the present study that permits any clear statement about mechanisms of memory. The references to a "short-term memory update" process do not help the reader to understand what is happening in the protocol.

In reply to this point, the authors cite evidence to suggest that "an isolated presentation of the CS+ seems to be important in preventing the return of fear expression." They then note the following: "It has also been suggested that only when the old memory and new experience (through extinction) can be inferred to have been generated from the same underlying latent cause, the old memory can be successfully modified (Gershman et al., 2017). On the other hand, if the new experiences are believed to be generated by a different latent cause, then the old memory is less likely to be subject to modification. Therefore, the way the 1st and 2nd CS are temporally organized (retrieval-extinction or standard extinction) might affect how the latent cause is inferred and lead to different levels of fear expression from a theoretical perspective." This merely begs the question: why might an isolated presentation of the CS+ result in the subsequent extinction experiences being allocated to the same memory state as the initial conditioning experiences?<br /> This is not addressed in the paper. The study was not designed to address this question; and that the question did not need to be addressed for the set of results to be interesting. However, understanding how and why the retrieval-extinction protocol produces the effects that it does in the long-term test of fear expression would greatly inform our understanding of how and why the retrieval-extinction protocol has the effects that it does in the short-term tests of fear expression. To be clear; the results of the present study are very interesting - there is no denying that. I am not asking the authors to change anything in response to this point. It simply stands as a comment on the work that has been done in this paper and the area of research more generally.

(2) The discussion of memory suppression is potentially interesting but raises many questions. That is, memory suppression is invoked to explain a particular pattern of results but I, as the reader, have no sense of why a fear memory would be better suppressed shortly after the retrieval-extinction protocol compared to the standard extinction protocol; and why this suppression is NOT specific to the cue that had been subjected to the retrieval-extinction protocol. I accept that the present study was not intended to examine aspects of memory suppression, and that it is a hypothesis proposed to explain the results collected in this study. I am not asking the authors to change anything in response to this point. Again, it simply stands as a comment on the work that has been done in this paper.

(3) The authors have inserted the following text in the revised manuscript: "It should be noted that while our long-term amnesia results were consistent with the fear memory reconsolidation literatures, there were also studies that failed to observe fear prevention (Chalkia, Schroyens, et al., 2020; Chalkia, Van Oudenhove, et al., 2020; Schroyens et al., 2023). Although the memory reconsolidation framework provides a viable explanation for the long-term amnesia, more evidence is required to validate the presence of reconsolidation, especially at the neurobiological level (Elsey et al., 2018). While it is beyond the scope of the current study to discuss the discrepancies between these studies, one possibility to reconcile these results concerns the procedure for the retrieval-extinction training. It has been shown that the eligibility for old memory to be updated is contingent on whether the old memory and new observations can be inferred to have been generated by the same latent cause (Gershman et al., 2017; Gershman and Niv, 2012). For example, prevention of the return of fear memory can be achieved through gradual extinction paradigm, which is thought to reduce the size of prediction errors to inhibit the formation of new latent causes (Gershman, Jones, et al., 2013). Therefore, the effectiveness of the retrieval-extinction paradigm might depend on the reliability of such paradigm in inferring the same underlying latent cause." ***It is perfectly fine to state that "the effectiveness of the retrieval-extinction paradigm might depend on the reliability of such paradigm in inferring the same underlying latent cause..." This is not uninteresting; but it also isn't saying much. Ideally, the authors would have included some statement about factors that are likely to determine whether one is or isn't likely to see a retrieval-extinction effect, grounded in terms of the latent state theories that have been invoked here. Presumably, the retrieval-extinction protocol has variable effects because of procedural differences that affect whether subjects infer the same underlying latent cause when shifted into extinction. Surely, the clinical implications of any findings are seriously curtailed unless one understands when a protocol is likely to produce an effect; and why the effect occurs at all? This question is rhetorical. I am not asking the authors to change anything in response to this point. Again, it stands as a comment on the work that has been done in this paper; and remains a comment after insertion of the new text, which is acknowledged and appreciated.

(4) The authors find different patterns of responses to CS1 and CS2 when they were tested 30 min after extinction versus 24 h after extinction. On this basis, they infer distinct memory update mechanisms. However, I still can't quite see why the different patterns of responses at these two time points after extinction need to be taken to infer different memory update mechanisms. That is, the different patterns of responses at the two time points could be indicative of the same "memory update mechanism" in the sense that the retrieval-extinction procedure induces a short-term memory suppression that serves as the basis for the longer-term memory suppression (i.e., the reconsolidation effect). My pushback on this point is based on the notion of what constitutes a memory update mechanism; and is motivated by what I take to be a rather loose use of language/terminology in the reconsolidation literature and this paper specifically (for examples, see the title of the paper and line 2 of the abstract).

To be clear: I accept the authors' reply that "The focus of the current manuscript is to demonstrate that the retrieval-extinction paradigm can also facilitate a short-term fear memory deficit measured by SCR". However, I disagree with the claim that any short-term fear memory deficit must be indicative of "update mechanisms other than reconsolidation", which appears on Line 27 in the abstract and very much indicates the spirit of the paper. To make the point: the present study has examined the effectiveness of a retrieval-extinction procedure in suppressing fear responses 30 min, 6 hours and 24 hours after extinction. There are differences across the time points in terms of the level of suppression, its cue specificity, and its sensitivity to manipulation of activity in the dlPFC. This is perfectly interesting when not loaded with additional baggage re separable mechanisms of memory updating at the short and long time points: there is simply no evidence in this study or anywhere else that the short-term deficit in suppression of fear responses has anything whatsoever to do with memory updating. It can be exactly what is implied by the description: a short-term deficit in the suppression of fear responses. Again, this stands as a comment on the work that has been done; and remains a comment for the revised paper.

(5) It is not clear why thought control ability ought to relate to any aspect of the suppression that was evident in the 30 min tests - that is, I accept the correlation between thought control ability and performance in the 30 min tests but would have liked to know why this was looked at in the first place and what, if anything, it means. The issue at hand is that, as best as I can tell, there is no theory to which the result from the short- and long-term tests can be related. The attempts to fill this gap with reference to phenomena like retrieval-induced forgetting are appreciated but raise more questions than answers. This is especially clear in the discussion, where it is acknowledged/stated: "Inspired by the similarities between our results and suppression-induced declarative memory amnesia (Gagnepain et al., 2017), we speculate that the retrieval-extinction procedure might facilitate a spontaneous memory suppression process and thus yield a short-term amnesia effect. Accordingly, the activated fear memory induced by the retrieval cue would be subjected to an automatic fear memory suppression through the extinction training (Anderson and Floresco, 2022)." There is nothing in the subsequent discussion to say why this should have been the case other than the similarity between results obtained in the present study and those in the literature on retrieval induced forgetting, where the nature of the testing is quite different. Again, this is simply a comment on the work that has been done - no change is required for the revised paper.

Reviewer #1 (Public review):

Summary:

The study examines human biases in a regime-change task, in which participants have to report the probability of a regime change in the face of noisy data. The behavioral results indicate that humans display systematic biases, in particular, overreaction in stable but noisy environments and underreaction in volatile settings with more certain signals. fMRI results suggest that a frontoparietal brain network is selectively involved in representing subjective sensitivity to noise, while the vmPFC selectively represents sensitivity to the rate of change.

Strengths:

- The study relies on a task that measures regime-change detection primarily based on descriptive information about the noisiness and rate of change. This distinguishes the study from prior work using reversal-learning or change-point tasks in which participants are required to learn these parameters from experiences. The authors discuss these differences comprehensively.

- The study uses a simple Bayes-optimal model combined with model fitting, which seems to describe the data well. The model is comprehensively validated.

- The authors apply model-based fMRI analyses that provide a close link to behavioral results, offering an elegant way to examine individual biases.

Weaknesses:

The authors have adequately addressed most of my prior concerns.

My only remaining comment concerns the z-test of the correlations. I agree with the non-parametric test based on bootstrapping at the subject level, providing evidence for significant differences in correlations within the left IFG and IPS.

However, the parametric test seems inadequate to me. The equation presented is described as the Fisher z-test, but the numerator uses the raw correlation coefficients (r) rather than the Fisher-transformed values (z). To my understanding, the subtraction should involve the Fisher z-scores, not the raw correlations.

More importantly, the Fisher z-test in its standard form assumes that the correlations come from independent samples, as reflected in the denominator (which uses the n of each independent sample). However, in my opinion, the two correlations are not independent but computed within-subject. In such cases, parametric tests should take into account the dependency. I believe one appropriate method for the current case (correlated correlation coefficients sharing a variable [behavioral slope]) is explained here:

Meng, X.-l., Rosenthal, R., & Rubin, D. B. (1992). Comparing correlated correlation coefficients. Psychological Bulletin, 111(1), 172-175. https://doi.org/10.1037/0033-2909.111.1.172

It should be implemented here:

Diedenhofen B, Musch J (2015) cocor: A Comprehensive Solution for the Statistical Comparison of Correlations. PLoS ONE 10(4): e0121945. https://doi.org/10.1371/journal.pone.0121945

My recommendation is to verify whether my assumptions hold, and if so, perform a test that takes correlated correlations into account. Or, to focus exclusively on the non-parametric test.

In any case, I recommend a short discussion of these findings and how the authors interpret that some of the differences in correlations are not significant.

Reviewer #1 (Public review):

Summary:

Silbaugh, Koster and Hansel investigated how the cerebellar climbing fiber (CF) signals influence neuronal activity and plasticity in mouse primary somatosensory (S1) cortex. They found that optogenetic activation of CFs in the cerebellum modulates responses of cortical neurons to whisker stimulation in a cell-type-specific manner and suppresses potentiation of layer 2/3 pyramidal neurons induced by repeated whisker stimulation. This suppression of plasticity by CF activation is mediated through modulation of VIP- and SST-positive interneurons. Using transsynaptic tracing and chemogenetic approaches, the authors identified a pathway from the cerebellum through the zona incerta and the thalamic posterior medial (POm) nucleus to the S1 cortex, which underlies this functional modulation.

The authors have addressed all the necessary points.

Reviewer #1 (Public review):

The study aims to determine the role of Slit-Robo signaling in the development and patterning of cardiac innervation, a key process in heart development. Despite the well-studied roles of Slit axon guidance molecules in the development of the central nervous system, their roles in the peripheral nervous system are less clear. Thus, the present study addresses an important question. The study uses genetic knockout models to investigate how Slit2, Slit3, Robo1, and Robo2 contribute to cardiac innervation

Using constitutive and cell type-specific knockout mouse models, they show that the loss of endothelial-derived Slit2 reduces cardiac innervation. Additionally, Robo1 knockout, but not Robo2 knockout, recapitulated the Slit2 knockout effect on cardiac innervation, leading to the conclusion that Slit2-Robo1 signaling drives sympathetic innervation in the heart. Finally, the authors also show a reduction in isoproterenol-stimulated heart rate but not basal heart rate in the absence of endothelial Slit2.

The conclusions of this paper are mostly well supported by the data, but there are several limitations:

(1) It is well established that Slit ligands undergo proteolytic cleavage, generating N- and C-terminal fragments with distinct biological functions. Full-length Slit proteins and their fragments differ in cell association, with the N-terminal fragment typically remaining membrane-bound, while the C-terminal fragment is more diffusible. This distinction is crucial when evaluating the role of Slit proteins secreted by different cell types in the heart. However, this study does not examine or discuss the specific contributions of different Slit2 fragments, limiting its mechanistic insight into how Slit2 regulates cardiac innervation. While these points are mentioned in the discussion, they are not incorporated into the interpretation of the data or the presented model.

(2) The endothelial-specific deletion of Slit2 leads to its loss in endothelial cells across various organs and tissues in the developing embryo. Therefore, the phenotypes observed in the heart may be influenced by defects in other parts of the embryo, such as the CNS or sympathetic ganglia, and this possibility cannot be ruled out. The data presented in the manuscript does not dissect the relative contributions of endothelial Slit2 loss in the heart versus secondary effects arising from other organ systems. Without tissue-specific rescue or complementary conditional models, it remains unclear whether the observed cardiac phenotypes are a direct consequence of local endothelial Slit2 deficiency or an indirect outcome of broader developmental perturbations.

Reviewer #2 (Public review):

Summary:

This work presents a modality-agnostic decoder trained on a large fMRI dataset (SemReps-8K), in which subjects viewed natural images and corresponding captions. The decoder predicts stimulus content from brain activity irrespective of the input modality and performs on par with-or even outperforms-modality-specific decoders. Its success depends more on the diversity of brain data (multimodal vs. unimodal) than on whether the feature-extraction models are visual, linguistic, or multimodal. Particularly, the decoder shows strong performance in decoding imagery content. These results suggest that the modality-agnostic decoder effectively leverages shared brain information across image and caption tasks.

Strengths:

(1) The modality-agnostic decoder compellingly leverages multimodal brain information, improving decoding accuracy-particularly for non-sensory input such as captions-showing high methodological and application value.

(2) The dataset is a substantial and well-controlled contribution, with >8,000 image-caption trials per subject and careful matching of stimuli across modalities-an essential resource for testing theories about different representational modalities.

Weakness:

In the searchlight analysis aimed at identifying modality-invariant representations, although the combined use of four decoding conditions represents a relatively strict approach, the underlying logic remains unclear. The modality-agnostic decoder has demonstrated strong sensitivity in decoding brain activity, as shown earlier in the paper, whereas the cross-decoding with modality-specific decoders is inherently more conservative. If, as the authors note, the modality-agnostic decoder might have learned to leverage different features to project stimuli from different modalities, then taking the union of conditions would seem more appropriate. Conversely, if the goal is to obtain a more conservative result, why not focus solely on the cross-decoding conditions? The relationships among the four decoding conditions are not clearly delineated, and the contrasts between them might themselves yield valuable insights. As it stands, however, the logic of the current approach is not straightforward.

Reviewer #1 (Public review):

This work compiles a comprehensive atlas of ncORFs across mammalian tissues and cell types, derived from reanalysis of ~400 public ribosome profiling datasets. The authors then evaluate cross-species conservation and functional signatures, proposing that evolutionarily ancient ncORFs tend to have higher translation potential, stronger expression, and closer relationships with canonical coding sequences.

Strengths:

In general, the study provides a large-scale and timely resource of annotated ncORFs, which could be broadly useful for the community. The authors collected ~400 public ribosome profiling datasets for annotations of ncORFs, which, to my best knowledge, is the largest collection of data for such a purpose. The catalog could facilitate future investigations into ncORF biology and broaden understanding of the coding potential of the "non-coding" genome.

Weaknesses:

Based on the ncORF catalog, some of the analyses were not properly done. Some of the results are descriptive.

(1) Bias and representations of the data source. Public ribo-seq datasets are unevenly distributed across tissues and cell lines, raising concerns about heterogeneity and underrepresentation of certain contexts. This may limit the generalizability of the catalog.

(2) The discussion on modular domains of ncORFs is unclear, and the claim that they may originate via TE-related mechanisms is not well supported. Stronger evidence or clearer reasoning is needed.

(3) The conservation comparisons are not fully convincing. Figure S7 shows only mild differences between ncORFs and CDS, and statistical significance is not clearly demonstrated.<br /> Comparisons with other non-coding RNAs should be added, and overlapping sequences between ncORFs and CDS should be excluded to avoid bias.

(4) Figure 3 indicates that some ncORFs are subject to evolutionary constraints. This is not surprising. The authors should provide further analyses on more detailed features of these "conserved" ncORFs vs. the "non-conserved" ones. Some pretty informative works have been done in Drosophila, worms, mice, and humans. Figure 3 suggests some ncORFs are under evolutionary constraint, but this is not unexpected. More granular analyses contrasting "conserved" versus "non-conserved" ncORFs would be informative. In fact, small ORFs, especially uORFs, have been extensively studied for their functions and cross-species conservation. The authors should explicitly show what is new here in their analyses.

(5) Translation levels are reported using RPF counts. However, translation efficiency (normalized by RNA expression) is a more appropriate measure to account for expression heterogeneity.

(6) The correlation analyses between ncORF translation levels and PhyloCSF are confusing and largely descriptive. These sections need sharper framing and clearer conclusions.

(7) Public ribo-seq datasets, generated by different research labs, are known for their strong batch effects. Representations of tissues and cells are also very unbalanced. Therefore, the co-translation analysis between ncORFs and canonical CDS is not well controlled. This should be done by referring to a recent large-scale ribo-seq meta-analysis (Nat Biotechnol. 2025. doi: 10.1038/s41587-025-02718-5).

Reviewer #1 (Public review):

Summary:

RNA modification has emerged as an important modulator of protein synthesis. Recent studies found that mRNA can be acetylated (ac4c), which can alter mRNA stability and translation efficiency. The role of ac4c mRNA in the brain has not been studied. In this paper, the authors convincingly show that ac4c occurs selectively on mRNAs localized at synapses, but not cell-wide. The ac4c "writer" NAT10 is highly expressed in hippocampal excitatory neurons. Using NAT10 conditional KO mice, decreasing levels of NAT10 resulted in decreases in ac4c of mRNAs and also showed deficits in LTP and spatial memory. These results reveal a potential role for ac4c mRNA in memory consolidation.

This is a new type of mRNA regulation that seems to act specifically at synapses, which may help elucidate the mechanisms of local protein synthesis in memory consolidation. Overall, the studies are well carried out and presented. There is some confusion over training/learning vs memory, and the precise mRNAs that require ac4c to carry out memory consolidation are not clear. The specificity of changes occurring only at the end of training, rather than after each day of training, is interesting and warrants some investigation. This timeframe is puzzling because the authors show that ac4c can dynamically increase within 1 hour after cLTP.

Strengths:

(1) The studies show that mRNA acetylation (ac4c) occurs selectively at mRNAs localized to synaptic compartments (using synaptoneurosome preps).

(2) The authors identify a few key mRNAs acetylated and involved in plasticity and memory - e.g., Arc.

(3) The authors show that Ac4c is induced by learning and neuronal activity (cLTP).

(4) The studies show that the ac4c "writer" NAT10 is expressed in hippocampal excitatory neurons and may be relocated to synapses after cLTP/learning induction.

(5) The authors used floxed NAT10 mice injected with AAV-Cre in the hippocampus (NAT10 cKO) to show that NAT10 may play a role in LTP maintenance and memory consolidation (using the Morris Water Maze).

Weaknesses:

(1) The authors use a confusing timeline for their behavioral experiments, i.e, day 1 is the first day of training in the MWM, and day 6 is the probe trial, but in reality, day 6 is the first day after the last training day. So this is really day 1 post-training, and day 20 is 14 days post-training.

(2) The authors inaccurately use memory as a term. During the training period in the MWM, the animals are learning, while memory is only probed on day 6 (after learning). Thus, day 6 reflects memory consolidation processes after learning has taken place.

(3) The NAT10 cKO mice are useful to test the causal role of NAT10 in ac4a and plasticity/memory, but all the experiments used AAV-CRE injections in the dorsal hippocampus that showed somewhat modest decreases in total NAT10 protein levels. For these experiments, it would be better to cross the NAT10 floxed animals to CRE lines where a better knockdown of NAT10 can be achieved, with less variability.

(4) Because knockdown is only modest (~50%), it is not clear if the remaining ac4c on mRNAs is due to remaining NAT10 protein or due to an alternative writer (as the authors pose).

Reviewer #1 (Public review):

Summary:

In their manuscript, Richter and colleagues comprehensively investigate the cell wall recycling pathway in the model alphaproteobacterium Caulobacter crescentus using biochemical, imaging, and genetic approaches. They clearly demonstrate that this organism encodes a functional peptidoglycan recycling pathway and demonstrate the activities of many enzymes and transporters within this pathway. They leverage imaging and growth assays to demonstrate that mutants in peptidoglycan recycling have varying degrees of beta-lactam sensitivity as well as morphological and cell division defects. They propose that, rather than impacting the levels or activity of the major beta-lactamase, BlaA, defects in PG recycling lead to beta-lactam sensitivity by limiting the availability of new cell wall precursors. The findings will be of interest to those in the field of bacterial cell wall biochemistry, antibiotics and antibiotic resistance, and bacterial morphogenesis.

Strengths:

Overall, the manuscript is laid out logically, and the data are comprehensive, quantitative, and rigorous. The mutants and their phenotypes will be a valuable resource for Caulobacter researchers.

Weaknesses:

The only major missing piece is the complementation of mutants to demonstrate that loss of the targeted gene is responsible for the observed phenotypes.

Reviewer #1 (Public review):

The paper by Chen et al describes the role of neuronal themo-TRPV3 channels in the firing of cortical neurons at fever temperature range. The authors began by demonstrating that exposure to infrared light increasing ambient temperature causes body temperature rise to fever level above 38{degree sign}C. Subsequently, they showed that at the fever temperature of 39{degree sign}C, the increased spike threshold (ST) increased in both populations (P12-14 and P7-8) of cortical excitatory pyramidal neurons (PNs). However, the spike number only decreased in P7-8 PNs, while it remained stable in P12-14 PNs at 39{degree sign}C. In addition, the fever temperature also reduced the late peak postsynaptic potential (PSP) in P12-14 PNs. The authors further characterized the firing properties of cortical P12-14 PNs, identifying two types: STAY PNs that retained spiking at 30{degree sign}C, 36{degree sign}C and 39{degree sign}C, and STOP PNs that stopped spiking upon temperature change. They further extended their and analysis and characterization to striatal medium spiny neurons (MSNs) and found that STAY MSNs and PNs shared same ST temperature sensitivity. Using small molecule tools, they further identified that themo-TRPV3 currents in cortical PNs increased in response to temperature elevation, but not TRPV4 currents. The authors concluded that during fever, neuronal firing stability is largely maintained by sensory STAY PNs and MSNs that express functional TRPV3 channels. Overall, this study is well designed and executed with substantial controls, some interesting findings and quality of data.

Comments on revisions:

My previous concerns have been addressed in this revised manuscript.

Reviewer #1 (Public review):

Summary:

In the study by Roeder and colleagues, the authors aim to identify the psychophysiological markers of trust during the evaluation of matching or mismatching AI decision-making. Specifically, they aim to characterize through brain activity how the decision made by an AI can be monitored throughout time in a two-step decision-making task. The objective of this study is to unfold, through continuous brain activity recording, the general information processing sequence while interacting with an artificial agent, and how internal as well as external information interact and modify this processing. Additionally, the authors provide a subset of factors affecting this information processing for both decisions.

Strengths:

The study addresses a wide and important topic of the value attributed to AI decisions and their impact on our own confidence in decision-making. It especially questions some of the factors modulating the dynamical adaptation of trust in AI decisions. Factors such as perceived reliability, type of image, mismatch, or participants' bias toward one response or the other are very relevant to the question in human-AI interactions.

Interestingly, the authors also question the processing of more ambiguous stimuli, with no real ground truth. This gets closer to everyday life situations where people have to make decisions in uncertain environments. Having a better understanding of how those decisions are made is very relevant in many domains.

Also, the method for processing behavioral and especially EEG data is overall very robust and is what is currently recommended for statistical analyses for group studies. Additionally, authors provide complete figures with all robustness evaluation information. The results and statistics are very detailed. This promotes confidence, but also replicability of results.

An additional interesting method aspect is that it is addressing a large window of analysis and the interaction between three timeframes (evidence accumulation pre-decision, decision-making, post-AI decision processing) within the same trials. This type of analysis is quite innovative in the sense that it is not yet a standard in complex experimental designs. It moves forward from classical short-time windows and baseline ERP analysis.

Weaknesses:

This manuscript raises several conceptual and theoretical considerations that are not necessarily answered by the methods (especially the task) used. Even though the authors propose to assess trust dynamics and violations in cooperative human-AI teaming decision-making, I don't believe their task resolves such a question. Indeed, there is no direct link between the human decision and the AI decision. They do not cooperate per se, and the AI decision doesn't seem, from what I understood to have an impact on the participants' decision making. The authors make several assumptions regarding trust, feedback, response expectation, and "classification" (i.e., match vs. mismatch) which seem far stretched when considering the scientific literature on these topics.

Unlike what is done for the data processing, the authors have not managed to take the big picture of the theoretical implications of their results. A big part of this study's interpretation aims to have their results fit into the theoretical box of the neural markers of performance monitoring.

Overall, the analysis method was very robust and well-managed, but the experimental task they have set up does not allow to support their claim. Here, they seem to be assessing the impact of a mismatch between two independent decisions.

Nevertheless, this type of work is very important to various communities. First, it addresses topical concerns associated with the introduction of AI in our daily life and decisions, but it also addresses methodological difficulties that the EEG community has been having to move slowly away from the static event-based short-timeframe analyses onto a more dynamic evaluation of the unfolding of cognitive processes and their interactions. The topic of trust toward AI in cooperative decision making has also been raised by many communities, and understanding the dynamics of trust, as well as the factors modulating it, is of concern to many high-risk environments, or even everyday life contexts. Policy makers are especially interested in this kind of research output.

Reviewer #1 (Public review):

Summary:

This manuscript provides a comprehensive systematic analysis of envelope-containing Ty3/gypsy retrotransposons (errantiviruses) across metazoan genomes, including both invertebrates and ancient animal lineages. Using iterative tBLASTn mining of over 1,900 genomes, the authors catalog 1,512 intact retrotransposons with uninterrupted gag, pol, and env open reading frames. They show that these elements are widespread-present in most metazoan phyla, including cnidarians, ctenophores, and tunicates-with active proliferation indicated by their multicopy status. Phylogenetic analyses distinguish "ancient" and "insect" errantivirus clades, while structural characterization (including AlphaFold2 modeling) reveals two major env types: paramyxovirus F-like and herpesvirus gB-like proteins. Although bot envelope types were identified in previous analyses two decades ago, the evolutionary provenance of these envelope genes was almost rudimentary and anecdotal (I can say this because I authored one of these studies). The results in the present study support an ancient origin for env acquisition in metazoan Ty3/gypsy elements, with subsequent vertical inheritance and limited recombination between env and pol domains. The paper also proposes an expanded definition of 'errantivirus' for env-carrying Ty3/gypsy elements outside Drosophila.

Strengths:

(1) Comprehensive Genomic Survey:<br /> The breadth of the genome search across non-model metazoan phyla yields an impressive dataset covering evolutionary breadth, with clear documentation of search iterations and validation criteria for intact elements.

(2) Robust Phylogenetic Inference:<br /> The use of maximum likelihood trees on both pol and env domains, with thorough congruence analysis, convincingly separates ancient from lineage-specific elements and demonstrates co-evolution of env and pol within clades.

(3) Structural Insights:<br /> AlphaFold2-based predictions provide high-confidence structural evidence that both env types have retained fusion-competent architectures, supporting the hypothesis of preserved functional potential.

(4) Novelty and Scope:<br /> The study challenges previous assumptions of insect-centric or recent env acquisition and makes a compelling case for a Pre-Cambrian origin, significantly advancing our understanding of animal retroelement diversity and evolution. THIS IS A MAJOR ADVANCE.

(5) Data Transparency:<br /> I appreciate that all data, code, and predicted structures are made openly available, facilitating reproducibility and future comparative analyses.

Major Weaknesses

(1) Functional Evidence Gaps:<br /> The work rests largely on sequence and structure prediction. No direct expression or experimental validation of envelope gene function or infectivity outside Drosophila is attempted, which would be valuable to corroborate the inferred roles of these glycoproteins in non-insect lineages. At least for some of these species, there are RNA-seq datasets that could be leveraged.

(2) Horizontal Transfer vs. Loss Hypotheses:<br /> The discussion argues primarily for vertical inheritance, but the somewhat sporadic phylogenetic distributions and long-branch effects suggest that loss and possibly rare horizontal events may contribute more than acknowledged. Explicit quantitative tests for horizontal transfer, or reconciliation analyses, would strengthen this conclusion. It's also worth pointing out that, unlike retrotransposons that can be found in genomes, any potential related viral envelopes must, by definition, have a spottier distribution due to sampling. I don't think this challenges any of the conclusions, but it must be acknowledged as something that could affect the strength of this conclusion

(3) Limited Taxon Sampling for Certain Phyla:<br /> Despite the impressive breadth, some ancient lineages (e.g., Porifera, Echinodermata) are negative, but the manuscript does not fully explore whether this reflects real biological absence, assembly quality, or insufficient sampling. A more systematic treatment of negative findings would clarify claims of ubiquity. However, I also believe this falls beyond the scope of this study.

(4) Mechanistic Ambiguity:<br /> The proposed model that env-containing elements exploit ovarian somatic niches is plausible but extrapolated from Drosophila data; for most taxa, actual tissue specificity, lifecycle, or host interaction mechanisms remain speculative and, to me, a bit unreasonable.

Minor Weaknesses:

(1) Terminology and Nomenclature:<br /> The paper introduces and then generalizes the term "errantivirus" to non-insect elements. While this is logical, it may confuse readers familiar with the established, Drosophila-centric definition if not more explicitly clarified throughout. I also worry about changes being made without any input from the ICTV nomenclature committee, which just went through a thorough reclassification. Nevertheless, change is expected, and calling them all errantiviruses is entirely reasonable.

(2) Figures and Supplementary Data Navigation:<br /> Some key phylogenies and domain alignments are found only in supplementary figures, occasionally hindering readability for non-expert audiences. Selected main-text inclusion of representative trees would benefit accessibility.

(3) ORF Integrity Thresholds:<br /> The cutoff choices for defining "intact" elements (e.g., numbers/placement of stop codons, length ranges) are reasonable but only lightly justified. More rationale or sensitivity analysis would improve confidence in the inclusion criteria. For example, how did changing these criteria change the number of intact elements?

(4) Minor Typos/Formatting:<br /> The paper contains sporadic typographical errors and formatting glitches (e.g., misaligned figure labels, unrendered symbols) that should be addressed.

Reviewer #1 (Public review):

Summary:

From a forward genetic mosaic mutant screen using EMS, the authors identify mutations in glucosylceramide synthase (GlcT), a rate-limiting enzyme for glycosphingolipid (GSL) production, that result in ee tumors. Multiple genetic experiments strongly support the model that the mutant phenotype caused by GlcT loss is due to by failure of conversion of ceramide into glucosylceramide. Further genetic evidence suggests that Notch signaling is comprised in the ISC lineage and may affect endocytosis of Delta. Loss of GlcT does not affect wing development or oogenesis, suggesting tissue-specific roles for GlcT. Finally, an increase in goblet cells in UGCG knockout mice, not previously reported, suggests a conserved role for GlcT in Notch signaling in intestinal cell lineage specification.

Strengths:

Overall, this is a well-written paper with multiple well-designed and executed genetic experiments that support a role for GlcT in Notch signaling in the fly and mammalian intestine. The authors have addressed my concerns from the prior review.

Reviewer #1 (Public review):

The study analyzes the gastric fluid DNA content identified as a potential biomarker for human gastric cancer. However, the study lacks overall logicality, and several key issues require improvement and clarification. In the opinion of this reviewer, some major revisions are needed:

(1) This manuscript lacks a comparison of gastric cancer patients' stages with PN and N+PD patients, especially T0-T2 patients.

(2) The comparison between gastric cancer stages seems only to reveal the difference between T3 patients and early-stage gastric cancer patients, which raises doubts about the authenticity of the previous differences between gastric cancer patients and normal patients, whether it is only due to the higher number of T3 patients.

(3) The prognosis evaluation is too simplistic, only considering staging factors, without taking into account other factors such as tumor pathology and the time from onset to tumor detection.

(4) The comparison between gfDNA and conventional pathological examination methods should be mentioned, reflecting advantages such as accuracy and patient comfort.

(5) There are many questions in the figures and tables. Please match the Title, Figure legends, Footnote, Alphabetic order, etc.

(6) The overall logicality of the manuscript is not rigorous enough, with few discussion factors, and cannot represent the conclusions drawn

Reviewer #1 (Public review):

Summary:

Most studies in sensory neuroscience investigate how individual sensory stimuli are represented in the brain (e.g., the motion or color of a single object). This study starts tackling the more difficult question of how the brain represents multiple stimuli simultaneously and how these representations help to segregate objects from cluttered scenes with overlapping objects.

Strengths:

The authors first document the ability of humans to segregate two motion patterns based on differences in speed. Then they show that a monkey's performance is largely similar; thus establishing the monkey as a good model to study the underlying neural representations.

Careful quantification of the neural responses in the middle temporal area during the simultaneous presentation of fast and slow speeds leads to the surprising finding that, at low average speeds, many neurons respond as if the slowest speed is not present, while they show averaged responses at high speeds. This unexpected complexity of the integration of multiple stimuli is key to the model developed in this paper.

One experiment in which attention is drawn away from the receptive field supports the claim that this is not due to the involuntary capture of attention by fast speeds.

A classifier using the neuronal response and trained to distinguish single speed from bi-speed stimuli shows a similar overall performance and dependence on the mean speed as the monkey. This supports the claim that these neurons may indeed underlie the animal's decision process.

The authors expand the well-established divisive normalization model to capture the responses to bi-speed stimuli. The incremental modeling (eq 9 and 10) clarifies which aspects of the tuning curves are captured by the parameters.

Reviewer #1 (Public review):

The authors focus on the molecular mechanisms by which EMT cells confer resistance to cancer cells. The authors use a wide range of methods to reveal that overexpression of Snail in EMT cells induces cholesterol/sphingomyelin imbalance via transcriptional repression of biosynthetic enzymes involved in sphingomyelin synthesis. The study also revealed that ABCA1 is important for cholesterol efflux and thus for counterbalancing the excess of intracellular free cholesterol in these snail-EMT cells. Inhibition of ACAT, an enzyme catalyzing cholesterol esterification, also seems essential to inhibit the growth of snail-expressing cancer cells.

Overall, the provided data are convincing and enhance our knowledge on cancer biology.

Reviewer #1 (Public review):

Summary:

This study builds off prior work that focused on the molecule AA147 and its role as an activator of the ATF6 arm of the unfolded protein response. In prior manuscripts, AA147 was shown to enter the ER, covalently modify a subset of protein disulfide isomerases (PDIs), and improve ER quality control for the disease-associated mutants of AAT and GABAA. Unsuccessful attempts to improve the potency of AA147 have led the authors to characterize a second hit from the screen in this study: the phenylhydrazone compound AA263. The focus of this study on enhancing biological activity of the AA147 molecule is compelling, and overcomes a hurdle of the prior AA147 drug that proved difficult to modify. The study successfully identifies PDIs as a shared cellular target of AA263 and its analogs. The authors infer, based on the similar target hits previously characterized for AA147, that PDI modification likely accounts for a mechanism of action for AA263.

Strengths:

The work establishes the ability to modify the AA263 molecule to create analogs with more potency and efficacy for ATF6 activation. The "next generation" analogs are able to enhance the levels of functional AAT and GABAA receptors in cellular models expressing the Z-variant of AAT or an epilepsy-associated variant of the GABAA receptor, outlining the therapeutic potential for this molecule and laying the foundation for future organism-based studies.

The authors are able to establish that like AA147, AA263 covalently targets ER PDIs. While it is a likely mechanism that AA263 works through the PDIs, the authors are careful to discuss that this is a potential mechanism that remains to be explicitly proven. The study provides the foundation for future work to further define a role for the PDIs in the actions of AA263.

Reviewer #2 (Public review):

Summary:

This paper formulates an individual-based model to understand the evolution of division of labor in vertebrates. The model considers a population subdivided in groups, each group has a single asexually-reproducing breeder, other group members (subordinates) can perform two types of tasks called "work" or "defense", individuals have different ages, individuals can disperse between groups, each individual has a dominance rank that increases with age, and upon death of the breeder a new breeder is chosen among group members depending on their dominance. "Workers" pay a reproduction cost by having their dominance decreased, and "defenders" pay a survival cost. Every group member receives a survival benefit with increasing group size. There are 6 genetic traits, each controlled by a single locus, that control propensities to help and disperse, and how task choice and dispersal relate to dominance. To study the effect of group augmentation without kin selection, the authors cross-foster individuals to eliminate relatedness. The paper allows for the evolution of the 6 genetic traits under some different parameter values to study the conditions under which division of labour evolves, defined as the occurrence of different subordinates performing "work" and "defense" tasks. The authors envision the model as one of vertebrate division of labor.

The main conclusion of the paper is that group augmentation is the primary factor causing the evolution of vertebrate division of labor, rather than kin selection. This conclusion is drawn because, for the parameter values considered, when the benefit of group augmentation is set to zero, no division of labor evolves and all subordinates perform "work" tasks but no "defense" tasks.

Strengths:

The model incorporates various biologically realistic details, including the possibility to evolve age polytheism where individuals switch from "work" to "defence" tasks as they age or vice versa, as well as the possibility of comparing the action of group augmentation alone with that of kin selection alone.

Weaknesses:

The model and its analysis are limited, which in my view makes the results insufficient to reach the main conclusion that group augmentation and not kin selection is the primary cause of the evolution of vertebrate division of labour. There are several reasons.

First, although the main claim that group augmentation drives the evolution of division of labour in vertebrates, the model is rather conceptual in that it doesn't use quantitative empirical data that applies to all/most vertebrates and vertebrates only. So, I think the approach has a conceptual reach rather than being able to achieve such a conclusion about a real taxon.

Second, I think that the model strongly restricts the possibility that kin selection is relevant. The two tasks considered essentially differ only by whether they are costly for reproduction or survival. "Work" tasks are those costly for reproduction and "defense" tasks are those costly for survival. The two tasks provide the same benefits for reproduction (eqs. 4, 5) and survival (through group augmentation, eq. 3.1). So, whether one, the other, or both helper types evolve presumably only depends on which task is less costly, not really on which benefits it provides. As the two tasks give the same benefits, there is no possibility that the two tasks act synergistically, where performing one task increases a benefit (e.g., increasing someone's survival) that is going to be compounded by someone else performing the other task (e.g., increasing that someone's reproduction). So, there is very little scope for kin selection to cause the evolution of labour in this model. Note synergy between tasks is not something unusual in division of labour models, but is in fact a basic element in them, so excluding it from the start in the model and then making general claims about division of labour is unwarranted. In their reply, the authors point out that they only consider fertility benefits as this, according to them, is what happens in cooperative breeders with alloparental care; however, alloparental care entails that workers can increase other's survival *without group augmentation*, such as via workers feeding young or defenders reducing predator-caused mortality, as a mentioned in my previous review but these potentially kin-selected benefits are not allowed here.

Third, the parameter space is understandably little explored. This is necessarily an issue when trying to make general claims from an individual-based model where only a very narrow parameter region of a necessarily particular model can be feasibly explored. As in this model the two tasks ultimately only differ by their costs, the parameter values specifying their costs should be varied to determine their effects. In the main results, the model sets a very low survival cost for work (yh=0.1) and a very high survival cost for defense (xh=3), the latter of which can be compensated by the benefit of group augmentation (xn=3). Some limited variation of xh and xn is explored, always for very high values, effectively making defense unevolvable except if there is group augmentation. In this revision, additional runs have been included varying yh and keeping xh and xn constant (Fig. S6), so without addressing my comment as xn remains very high. Consequently, the main conclusion that "division of labor" needs group augmentation seems essentially enforced by the limited parameter exploration, in addition to the second reason above.

Fourth, my view is that what is called "division of labor" here is an overinterpretation. When the two helper types evolve, what exists in the model is some individuals that do reproduction-costly tasks (so-called "work") and survival-costly tasks (so-called "defense"). However, there are really no two tasks that are being completed, in the sense that completing both tasks (e.g., work and defense) is not necessary to achieve a goal (e.g., reproduction). In this model there is only one task (reproduction, equation 4,5) to which both helper types contribute equally and so one task doesn't need to be completed if completing the other task compensates for it; instead, it seems more fitting to say that there are two types of helpers, one that pays a fertility cost and another one a survival cost, for doing the same task. So, this model does not actually consider division of labor but the evolution of different helper types where both helper types are just as good at doing the single task but perhaps do it differently and so pay different types of costs. In this revision, the authors introduced a modified model where "work" and "defense" must be performed to a similar extent. Although I appreciate their effort, this model modification is rather unnatural and forces the evolution of different helper types if any help is to evolve.

I should end by saying that these comments don't aim to discourage the authors, who have worked hard to put together a worthwhile model and have patiently attended to my reviews. My hope is that these comments can be helpful to build upon what has been done to address the question posed.

Reviewer #1 (Public review):

Summary:

The authors investigate how the Drosophila TNF receptor-associated factor Traf4 - a multifunctional adaptor protein with potential E3 ubiquitin ligase activity - regulates JNK signaling and adherens junctions (AJs) in wing disc epithelium. When they overexpress Traf4 in the posterior compartment of the wing disc, many posterior cells express the JNK target gene puckered (puc), apoptose, and are basally extruded from the epithelium. The authors term this process "delamination", but I think that this is an inaccurate description, especially since they can suppress the "delamination" by blocking programmed cell death (by concomitantly overexpressing p35). Through Y2H assays using Traf4 as a bait, they identified the Bearded family proteins E(spl)m4 (and to a lesser extent E(spl)m2), as Traf4 interactors. They use Alphafold to model computationally the interaction between Traf4 and E(spl)m4. They show that co-overexpression of Traf4 with E(spl)m4 in the posterior domain of the wing disc reduces death of posterior cells. They generate a new, weaker hypomorphic allele of Traf4 that is viable (as opposed to the homozygous lethality of null Traf4 alleles). There is some effect of these mutations on wing margin bristles; fewer wing margin bristle defects are seen when E(spl)m4 is overexpressed, suggesting opposite effects of Traf4 and E(spl)m4. Finally, they use the Minute model of cell competition to show that Rp/+ loser clones have greater clone area (indicating increased survival) when they are depleted for Traf4 or when they overexpress E(spl)m4. Only the cell competition results are quantified. Because most of the data in the preprint are not quantified, it is impossible to know how penetrant the phenotypes are. The authors conclude that E(spl)m4 binds the Traf4 MATH/TRAF domain, disrupts Traf4 trimerization, and selectively suppresses Traf4-mediated JNK and caspase activation without affecting its role in AJ destabilization. However, I believe that this is an overstatement. First, there is no biochemical evidence showing that Traf4 binds E(spl)m4 and that E(spl)m4 disrupts Traf4 trimerization. Second, the data on AJs is weak and not quantified; additionally, cells that are being basally extruded lose contact with neighboring cells, hence changes in adhesion proteins. Related to this, the authors, in my opinion, inaccurately describe basal extrusion of dying cells from the wing disc epithelium as delamination.

Strengths:

(1) The authors use multiple approaches to test the model that overexpressed E(spl)m4 inhibits Traf4, including genetics, cell biological imaging, yeast two-hybrid assays, and molecular modeling.

(2) The authors generate a new Traf4 hypomorphic mutant and use this mutant in cell competition studies, which supports the concept that E(spl)m4 (when overexpressed) can antagonize Traf4.

Weaknesses:

(1) Conflation of "delamination" with "basal extrusion of apoptotic cells": Over-expression of Traf4 causes apoptosis in wing disc cells, and this is a distinct process from delamination of viable cells from an epithelium. However, the two processes are conflated by the authors, and this weakens the premise of the paper.

(2) Dependence on overexpression: The conclusions rely heavily on ectopic expression of Traf4 and E(spl)m4. Thus, the physiological relevance of the interaction remains inferred rather than demonstrated.

(3) Lack of quantitative rigor: Except for the cell competition studies, phenotypic descriptions (e.g., number of apoptotic cells, puc-LacZ intensity) are qualitative; additional quantification, inclusion of sample size, and statistical testing would strengthen the conclusions.

(4) Limited biochemical validation: The Traf4-E(spl)m4 binding is inferred from Y2H and in silico models, but no co-immunoprecipitation or in vitro binding assays confirm direct interaction or the predicted disruption of trimerization.

(5) Specificity within the Bearded family: While E(spl)m2 shows partial binding and Tom shows none, the mechanistic basis for this selectivity is not deeply explored experimentally, leaving questions about motif-context contributions unresolved.

Reviewer #1 (Public review):

Nielsen et al have identified a new disease mechanism underlying hypoplastic left heart syndrome due to variants in ribosomal protein genes that lead to impaired cardiomyocyte proliferation. This detailed study starts with an elegant screen in stem cell derived cardiomyocytes and whole genome sequencing of human patients and extends to careful functional analysis of RP gene variants in fly and fish models. Striking phenotypic rescue is seen by modulating known regulators of proliferation including the p53 and Hippo pathways. Additional experiments suggest that cell type specificity of the variants in these ubiquitously expressed genes may result from genetic interactions with cardiac transcription factors. This work positions RPs as important regulators of cardiomyocyte proliferation and differentiation involved in the etiology of HLHS, and point to potential downstream mechanisms.

The revised manuscript has been extended, facilitating interpretation and reinforcing the authors' conclusions.

Reviewer #1 (Public review):

The study analyzes the gastric fluid DNA content identified as a potential biomarker for human gastric cancer. However, the study lacks overall logicality, and several key issues require improvement and clarification. In the opinion of this reviewer, some major revisions are needed:

(1) This manuscript lacks a comparison of gastric cancer patients' stages with PN and N+PD patients, especially T0-T2 patients.

(2) The comparison between gastric cancer stages seems only to reveal the difference between T3 patients and early-stage gastric cancer patients, which raises doubts about the authenticity of the previous differences between gastric cancer patients and normal patients, whether it is only due to the higher number of T3 patients.

(3) The prognosis evaluation is too simplistic, only considering staging factors, without taking into account other factors such as tumor pathology and the time from onset to tumor detection.

(4) The comparison between gfDNA and conventional pathological examination methods should be mentioned, reflecting advantages such as accuracy and patient comfort.

(5) There are many questions in the figures and tables. Please match the Title, Figure legends, Footnote, Alphabetic order, etc.

(6) The overall logicality of the manuscript is not rigorous enough, with few discussion factors, and cannot represent the conclusions drawn.

Comments on revisions:

The authors have addressed all concerns in the revision.

Reviewer #1 (Public review):

The authors of this study set out to address a central question in the psycholinguistics literature: does the human brain's ability to predict upcoming language come at a cognitive cost, or is it an automatic, "free" process? To investigate this, they employed a dual-task paradigm where participants read texts word-by-word while simultaneously performing a secondary task (an n-back task on font color) designed to manipulate cognitive load. The study examines how this external cognitive load, along with the effects of aging, modulates the impact of word predictability (measured by surprisal and entropy) on reading times. The central finding is that increased cognitive load diminishes the effects of word predictability, supporting the conclusion that language prediction is a resource-dependent process.

A major strength of the revised manuscript is its comprehensive and parallel analysis of both word surprisal and entropy. The initial submission focused almost exclusively on surprisal, which primarily reflects the cost of integrating a word into its context after it has been perceived. The new analysis now thoroughly investigates entropy as well, which reflects the uncertainty and cognitive effort involved in predicting the next word before it appears. This addition provides a much more complete and theoretically nuanced picture, allowing the authors to address how cognitive load affects both predictive and integrative stages of language processing. This is a significant improvement and substantially increases the paper's contribution to the field.

Furthermore, the authors have commendably addressed the initial concerns regarding the robustness of their replication findings. The first version of the manuscript presented replication results that were inconsistent, particularly for key interaction effects. In the revision, the authors have adopted a more focused and appropriately powered modeling approach for the replication analysis. This revised analysis now demonstrates a consistent effect of cognitive load on the processing of predictable words across both the original and replication datasets. This strengthens the evidence for the paper's primary claim.

The initial review also raised concerns that the results could be explained by general cognitive factors, such as task-switching costs, rather than the specific demands on the language prediction system. While the complexity of cognitive load in a dual-task paradigm remains a challenge, the authors have provided sufficient justification in their revisions and rebuttal to support their interpretation that the observed effects are genuinely tied to the process of language prediction.

Reviewer #1 (Public review):

Summary:

Wojnowska et al. report structural and functional studies of the interaction of Streptococcus pyogenes M3 protein with collagen. They show through X-ray crystallographic studies that the N-terminal hypervariable region of M3 protein forms a T-like structure, and that the T-like structure binds a three-stranded collagen-mimetic peptide. They indicate that the T-like structure is predicted by AlphaFold3 with moderate confidence level in other M proteins that have sequence similarity to M3 protein and M-like proteins from group C and G streptococci. For some, but not all, of these related M and M-like proteins, AlphaFold3 predicts, with moderate confidence level, complexes similar to the one observed for M3-collagen. Functionally, the authors show that emm3 strains form biofilms with more mass when surfaces are coated with collagen, and this effect can be blocked by an M3 protein fragment that contains the T-structure. They also show the co-occurrence of emm3 strains and collagen in patient biopsies and a skin tissue organoid. Puzzlingly, M1 protein has been reported to bind collagen, but collagen inhibits biofilm in a particular emm1 strain but that same emm1 strain colocalizes with collagen in a patient biopsy sample. The implications of the variable actions of collagen on biofilm formation are not clear.

Strengths:

The paper is well written and the results are presented in a logical fashion.

Weaknesses:

A major limitation of the paper is that it is almost entirely observational and lacks detailed molecular investigation. Insufficient details or controls are provided to establish the robustness of the data.

Comments on revisions:

The authors' response to this reviewer's Major issue #1 is inadequate. Their argument is essentially that if they denature the protein, then there is no activity. This does not address the specificity of the structure or its interactions.

They went only part way to addressing this reviewer's Major issue #2. While Figure 8 - supplement 3 shows 1D NMR spectra for M3 protein (what temperature?), it does not establish that stability is unaltered (to a significant degree).

This reviewer's Major issue #3 is one of the major reasons for considering this study to be observational. This reviewer agrees that structural biology is by its nature observational, but modern standards require validation of structural observations. The authors' response is that a mechanistic investigation involving mutant bacterial strains and validation involving mutated proteins is beyond their scope. Therefore, the study remains observational.

Major issue 4 was addressed suitably, but brings up the problematic point that the emm1 2006 strain colocalizes quite well with collagen in a patient biopsy sample but not in other assays. This calls into question the overall interpretability of the patient biopsy data.

The authors have not provided a point-by-point response. Issues that were indicated to be minor previously were deemed to be minor because this reviewer thought that they could easily be addressed in a revision. It appears that the authors have ignored many of these comments, and these issues are therefore now considered to be major issues. For example, no errors are given for Kd measurements, Table 2 is sloppy and lacks the requested information, negative controls are missing (Figure 10 - figure supplement 1), and there is no indication of how many independent times each experiment was done.

And "C4-binding protein" should be corrected to "C4b-binding protein."

Reviewer #3 (Public review):

Summary:

In this well-written manuscript, Unitt and colleagues propose a new, hierarchical nomenclature system for the pathogen Neisseria gonorrhoeae. The proposed nomenclature addresses a longstanding problem in N. gonorrhoeae genomics, namely that the highly recombinant population complicates typing schemes based on only a few loci and that previous typing systems, even those based on the core genome, group strains at only one level of genomic divergence without a system for clustering sequence types together. In this work, the authors have revised the core genome MLST scheme for N. gonorrhoeae and devised life identification numbers (LIN) codes to describe the N. gonorrhoeae population structure.

Strengths:

The LIN codes proposed in this manuscript are congruent with previous typing methods for Neisseria gonorrhoeae like cgMLST groups, Ng-STAR, and NG-MAST. Importantly, they improve upon many of these methods as the LIN codes are also congruent with the phylogeny and represent monophyletic lineages/sublineages. Additionally, LIN code cluster assignment is fixed, and clusters are not fused as is common in other typing schemes.

The LIN code assignment has been implemented in PubMLST allowing other researchers to assign LIN codes to new assemblies and put genomes of interest in context with global datasets, including in private datasets.

Weaknesses:

The authors have defined higher resolution thresholds for the LIN code scheme. However, they do not investigate how these levels correspond to previously identified transmission clusters from genomic epidemiology studies. This will be an important focus of future work, but it may be beyond the scope of the current manuscript.

Comments on revisions:

The authors have addressed my previous comments. I have no additional recommendations.

Reviewer #1 (Public review):

Summary:

The authors set out to evaluate the regulation of interferon (IFN) gene expression in fish, using mainly zebrafish as a model system. Similar to more widely characterized mammalian systems, fish IFN is induced during viral infection through the action of the transcription factor IRF3 which is activated by phosphorylation by the kinase TBK1. It has been previously shown in many systems that TBK1 is subjected to both positive and negative regulation to control IFN production. In this work, the authors find that the cell cycle kinase CDK2 functions as a TBK1 inhibitor by decreasing its abundance through recruitment of the ubiquitinylation ligase, Dtx4, which has been similarly implicated in the regulation of mammalian TBK1. Experimental data are presented showing that CDK2 interacts with both TBK1 and Dtx4, leading to TBK1 K48 ubiqutinylation on K567 and its subsequent degradation by the proteasome.

Strengths:

The strengths of this manuscript are its novel demonstration of the involvement of CDK2 in a process in fish that is controlled by different factors in other vertebrates and its clear and supportive experimental data.

Weaknesses:

The weaknesses of the study include the following. 1) It remains unclear how CDK is regulated during viral infection and how it specifically recruits E3 ligase to TBK1. The authors find that its abundance increases during viral infection, an unusual finding given that CDK2 levels are often found to be stable. How this change in abundance might affect cell cycle control was not explored. 2) The implications and mechanisms for a relationship between the cell cycle and IFN production will be a fascinating topic for future studies. In particular, it will be critical to determine if CDK2 catalytic activity is required. An experiment with an inhibitor suggests that this novel action of CDK2 is kinase independent, but the lack of controls showing the efficacy of the inhibitor prevents a firm conclusion. It will also be critical to determine if there is a role for cyclins in this process or if there is competition for binding between TBK1 and cyclin and, if so, if this has an impact on the cell cycle. Likewise, an impact of CDK2 induction by virus infection on normal cell cycling will be important to investigate.

Reviewer #1 (Public review):

The authors investigated the potential role of IgG N-glycosylation in Haemorrhagic Fever with Renal Syndrome (HFRS), which may offer significant insights for understanding molecular mechanisms and for the development of therapeutic strategies for this infectious disease.

Reviewer #1 (Public review):

Summary:

The microbiota of Dactylorhiza traunsteineri, an endangered marsh orchid, forms complex root associations that support plant health. Using 16S rRNA sequencing, we identified dominant bacterial phyla in its rhizosphere, including Proteobacteria, Actinobacteria, and Bacteroidota. Deep shotgun metagenomics revealed high-quality MAGs with rich metabolic and biosynthetic potential. This study provides key insights into root-associated bacteria and highlights the rhizosphere as a promising source of bioactive compounds, supporting both microbial ecology research and orchid conservation.

Strengths:

The manuscript presents an investigation of the bacterial communities in the rhizosphere of D. traunsteineri using advanced metagenomic approaches. The topic is relevant, and the techniques are up-to-date; however, the study has several critical weaknesses.

Weaknesses:

(1) Title: The current title is misleading. Given that fungi are the primary symbionts in orchids and were not analyzed in this study (nor were they included among other microbial groups), the use of the term "microbiome" is not appropriate. I recommend replacing it with "bacteriome" to better reflect the scope of the work.

(2) Line 124: The phrase "D. traunsteineri individuals were isolated" seems misleading. A more accurate description would be "individuals were collected", as also mentioned in line 128.

(3) Experimental design: The major limitation of this study lies in its experimental design. The number of plant individuals and soil samples analyzed is unclear, making it difficult to assess the statistical robustness of the findings. It is also not well explained why the orchids were collected two years before the rhizosphere soil samples. Was the rhizosphere soil collected from the same site and from remnants of the previously sampled individuals in 2018? This temporal gap raises serious concerns about the validity of the biological associations being inferred.

(4) Low sample size: In lines 249-251 (Results section), the authors mention that only one plant individual was used for identifying rhizosphere bacteria. This is insufficient to produce scientifically robust or generalizable conclusions.

(5) Contextual limitations: Numerous studies have shown that plant-microbe interactions are influenced by external biotic and abiotic factors, as well as by plant age and population structure. These elements are not discussed or controlled for in the manuscript. Furthermore, the ecological and environmental conditions of the site where the plants and soil were collected are poorly described. The number of biological and technical replicates is also not clearly stated.

(6) Terminology: Throughout the manuscript, the authors refer to the "microbiome," though only bacterial communities were analyzed. This terminology is inaccurate and should be corrected consistently.

Considering the issues addressed, particularly regarding experimental design and data interpretation, significant improvements to the study are needed.

Reviewer #1 (Public review):

Summary:

This manuscript addresses an important methodological issue - the fragility of meta-analytic findings - by extending fragility concepts beyond trial-level analysis. The proposed EOIMETA framework provides a generalizable and analytically tractable approach that complements existing methods such as the traditional Fragility Index and Atal et al.'s algorithm. The findings are significant in showing that even large meta-analyses can be highly fragile, with results overturned by very small numbers of event recodings or additions. The evidence is clearly presented, supported by applications to vitamin D supplementation trials, and contributes meaningfully to ongoing debates about the robustness of meta-analytic evidence. Overall, the strength of evidence is moderate to strong, though some clarifications would further enhance interpretability.

Strengths:

(1) The manuscript tackles a highly relevant methodological question on the robustness of meta-analytic evidence.

(2) EOIMETA represents an innovative extension of fragility concepts from single trials to meta-analyses.

(3) The applications are clearly presented and highlight the potential importance of fragility considerations for evidence synthesis.

Weaknesses:

(1) The rationale and mathematical details behind the proposed EOI and ROAR methods are insufficiently explained. Readers are asked to rely on external sources (Grimes, 2022; 2024b) without adequate exposition here. At a minimum, the definitions, intuition, and key formulas should be summarized in the manuscript to ensure comprehensibility.

(2) EOIMETA is described as being applicable when heterogeneity is low, but guidance is missing on how to interpret results when heterogeneity is high (e.g., large I²). Clarification in the Results/Discussion is needed, and ideally, a simulation or illustrative example could be added.

(3) The manuscript would benefit from side-by-side comparisons between the traditional FI at the trial level and EOIMETA at the meta-analytic level. This would contextualize the proposed approach and underscore the added value of EOIMETA.

(4) Scope of FI: The statement that FI applies only to binary outcomes is inaccurate. While originally developed for dichotomous endpoints, extensions exist (e.g., Continuous Fragility Index, CFI). The manuscript should clarify that EOIMETA focuses on binary outcomes, but FI, as a concept, has been generalized.

Reviewer #1 (Public review):

The authors used fluorescence microscopy, image analysis, and mathematical modeling to study the effects of membrane affinity and diffusion rates of MinD monomer and dimer states on MinD gradient formation in B. subtilis. To test these effects, the authors experimentally examined MinD mutants that lock the protein in specific states, including Apo monomer (K16A), ATP-bound monomer (G12V) and ATP-bound dimer (D40A, hydrolysis defective), and compared to wild-type MinD. Overall, the experimental results support the conclusions that reversible membrane binding of MinD is critical for the formation of the MinD gradient, but the binding affinities between monomers and dimers are similar.

The modeling part is a new attempt to use the Monte Carlo method to test the conditions for the formation of the MinD gradient in B. subtilis. The modeling results provide good support for the observations and find that the MinD gradient is sensitive to different diffusion rates between monomers and dimers. This simulation is based on several assumptions and predictions, which raises new questions that need to be addressed experimentally in the future.

Reviewer #1 (Public review):

Summary:

Outstanding fundamental phenomenon (migrasomes) en route to become transitionally highly significant.

Strengths:

Innovative approach at several levels: Migrasomes, discovered by DR. Yu's group, are an outstanding biological phenomenon of fundamental interest and now of potentially practical value.

Weaknesses:

I feel that the overemphasis on practical aspects (vaccine), however important, eclipses some of the fundamental aspects that may be just as important and actually more interesting. If this can be expanded, the study would be outstanding.

Comments on revisions: This reviewer feels that the authors have addressed all issues.

Reviewer #1 (Public review):

Summary

This work performed Raman spectral microscopy for E. coli cells with 15 different culture conditions. The author developed a theoretical framework to construct a regression matrix which predicts proteome composition by Raman data. Specifically, this regression matrix is obtained by statistical inference from various experimental conditions. With this model, the authors categorized co-expressed genes and illustrate how proteome stoichiometry is regulated among different culture conditions. Co-expressed gene clusters were investigated and identified as homeostasis core, carbon-source dependent, and stationary phase dependent genes. Overall, the author demonstrates a strong and comprehensive data analysis scheme for the joint analysis of Raman and proteome datasets.

Strengths and major contributions

Major contributions: (1) Experimentally, the authors contributed Raman datasets of E. coli with various growth conditions. (2) In data analysis, the authors developed a scheme to compare proteome and Raman datasets. Protein co-expression clusters were identified, and their biological meaning were investigated.

Discussion and impact for the field

Raman signature contains both proteomic and metabolomic information and is an orthogonal method to infer the composition biomolecules. This work is a strong initiative for introducing the powerful technique to systems biology and provide a rigorous pipeline for future data analysis. The regression matrix can be used for cross-comparison among future experimental results on proteome-Raman datasets.

Comments on revisions:

The authors addressed all my questions nicely. In particular, the subsampling test demonstrated that with enough "distinct" physiological condition (even for m=5) one could already explore the major mode of proteome regulation and Raman signature. The main text has been streamlined and the clarity is improved. I have a minor suggestion:

(i) For equation (1), it is important to emphasize that the formula works for every j=1,...,15, and the regression matrix B is obtained by statistical inference by summarizing data from all 15 conditions.

Reviewer #1 (Public review):

Summary:

The authors recorded neural activity using laminar probes while mice engaged in a global/local visual oddball paradigm. The focus of the article is on oscillatory activity, and found activity differences in theta, alpha/beta, and gamma bands related to predictability and prediction error.

I think this is an important paper, providing more direct evidence for the role of signals in different frequency bands related to predictability and surprise in the sensory cortex.

Comments:

Below are some comments that may hopefully help further improve the quality of this already very interesting manuscript.

(1) Introduction:

The authors write in their introduction: "H1 further suggests a role for θ oscillations in prediction error processing as well." Without being fleshed out further, it is unclear what role this would be, or why. Could the authors expand this statement?

(2) Limited propagation of gamma band signals:

Some recent work (e.g. https://www.cell.com/cell-reports/fulltext/S2211-1247(23)00503-X) suggests that gamma-band signals reflect mainly entrainment of the fast-spiking interneurons, and don't propagate from V1 to downstream areas. Could the authors connect their findings to these emerging findings, suggesting no role in gamma-band activity in communication outside of the cortical column?

(3) Paradigm:

While I agree that the paradigm tests whether a specific type of temporal prediction can be formed, it is not a type of prediction that one would easily observe in mice, or even humans. The regularity that must be learned, in order to be able to see a reflection of predictability, integrates over 4 stimuli, each shown for 500 ms with a 500 ms blank in between (and a 1000 ms interval separating the 4th stimulus from the 1st stimulus of the next sequence). In other words, the mouse must keep in working memory three stimuli, which partly occurred more than a second ago, in order to correctly predict the fourth stimulus (and signal a 1000 ms interval as evidence for starting a new sequence).

A problem with this paradigm is that positive findings are easier to interpret than negative findings. If mice do not show a modulation to the global oddball, is it because "predictive coding" is the wrong hypothesis, or simply because the authors generated a design that operates outside of the boundary conditions of the theory? I think the latter is more plausible. Even in more complex animals, (eg monkeys or humans), I suspect that participants would have trouble picking up this regularity and sequence, unless it is directly task-relevant (which it is not, in the current setting). Previous experiments often used simple pairs (where transitional probability was varied, eg, Meyer and Olson, PNAS 2012) of stimuli that were presented within an intervening blank period. Clearly, these regularities would be a lot simpler to learn than the highly complex and temporally spread-out regularity used here, facilitating the interpretation of negative findings (especially in early cortical areas, which are known to have relatively small temporal receptive fields).

I am, of course, not asking the authors to redesign their study. I would like to ask them to discuss this caveat more clearly, in the Introduction and Discussion, and situate their design in the broader literature. For example, Jeff Gavornik has used much more rapid stimulus designs and observed clear modulations of spiking activity in early visual regions. I realize that this caveat may be more relevant for the spiking paper (which does not show any spiking activity modulation in V1 by global predictability) than for the current paper, but I still think it is an important general caveat to point out.

(4) Reporting of results:

I did not see any quantification of the strength of evidence of any of the results, beyond a general statement that all reported results pass significance at an alpha=0.01 threshold. It would be informative to know, for all reported results, what exactly the p-value of the significant cluster is; as well as for which performed tests there was no significant difference.

(5) Cluster test:

The authors use a three-dimensional cluster test, clustering across time, frequency, and location/channel. I am wondering how meaningful this analytical approach is. For example, there could be clusters that show an early difference at some location in low frequencies, and then a later difference in a different frequency band at another (adjacent) location. It seems a priori illogical to me to want to cluster across all these dimensions together, given that this kind of clustering does not appear neurophysiologically implausible/not meaningful. Can the authors motivate their choice of three-dimensional clustering, or better, facilitating interpretability, cluster eg at space and time within specific frequency bands (2d clustering)?

Reviewer #1 (Public review):

Summary:

This study develops and validates a neural subspace similarity analysis for testing whether neural representations of graph structures generalize across graph size and stimulus sets. The authors show the method works in rat grid and place cell data, finding that grid but not place cells generalize across different environments, as expected. The authors then perform additional analyses and simulations to show that this method should also work on fMRI data. Finally, the authors test their method on fMRI responses from entorhinal cortex (EC) in a task that involves graphs that vary in size (and stimulus set) and statistical structure (hexagonal and community). They find neural representations of stimulus sets in lateral occipital complex (LOC) generalize across statistical structure and that EC activity generalizes across stimulus sets/graph size, but only for the hexagonal structures.

Strengths:

(1) The overall topic is very interesting and timely and the manuscript is well written.

(2) The method is clever and powerful. It could be important for future research testing whether neural representations are aligned across problems with different state manifestations.

(3) The findings provide new insights into generalizable neural representations of abstract task states in entorhinal cortex.

Weaknesses:

(1) There are two design confounds that are not sufficiently discussed.

(1.1) First, hexagonal and community structures are confounded by training order. All subjects learned the hexagonal graph always before the community graph. As such, any differences between the two graphs could be explained (in theory) by order effects (although this is unlikely). However, because community and hexagonal structures shared the same stimuli, it is possible that subjects had to find ways to represent the community structures separately from the hexagonal structures. This could potentially explain why there was no generalization across graph size for community structures.

(1.2) Second, subjects had more experience with the hexagonal and community structures before and during fMRI scanning. This is another possible reason why there was no generalization for the community structure.

(2) The authors include the results from a searchlight analysis to show specificity of the effects for EC. A more convincing way (in my opinion) to show specificity would be to test for (and report the results) of a double dissociation between the visual and structural contrast in two independently defined regions (e.g., anatomical ROIs of LOC and EC). This would substantiate the point that EC activity generalizes across structural similarity while sensory regions like LOC generalize across visual similarity.

Reviewer #1 (Public review):

The authors present exciting new experimental data on the antigenic recognition of 78 H3N2 strains (from the beginning of the 2023 Northern Hemisphere season) against a set of 150 serum samples. The authors compare protection profiles of individual sera and find that the antigenic effect of amino acid substitutions at specific sites depends on the immune class of the sera, differentiating between children and adults. Person-to-person heterogeneity in the measured titers is strong, specifically in the group of children's sera. The authors find that the fraction of sera with low titers correlates with the inferred growth rate using maximum likelihood regression (MLR), a correlation that does not hold for pooled sera. The authors then measure the protection profile of the sera against historical vaccine strains and find that it can be explained by birth cohort for children. Finally, the authors present data comparing pre- and post- vaccination protection profiles for 39 (USA) and 8 (Australia) adults. The data shows a cohort-specific vaccination effect as measured by the average titer increase, and also a virus-specific vaccination effect for the historical vaccine strains. The generated data is shared by the authors and they also note that these methods can be applied to inform the bi-annual vaccine composition meetings, which could be highly valuable.

Thanks to the authors for the revised version of the manuscript. A few concerns remain after the revision:

(1) We appreciate the additional computational analysis the authors have performed on normalizing the titers with the geometric mean titer for each individual, as shown in the new Supplemental Figure 6. We agree with the authors statement that, after averaging again within specific age groups, "there are no obvious age group-specific patterns." A discussion of this should be added to the revised manuscript, for example in the section "Pooled sera fail to capture the heterogeneity of individual sera," referring to the new Supplemental Figure 6.

However, we also suggested that after this normalization, patterns might emerge that are not necessarily defined by birth cohort. This possibility remains unexplored and could provide an interesting addition to support potential effects of substitutions at sites 145 and 275/276 in individuals with specific titer profiles, which as stated above do not necessarily follow birth cohort patterns.

(2) Thank you for elaborating further on the method used to estimate growth rates in your reply to the reviewers. To clarify: the reason that we infer from Fig. 5a that A/Massachusetts has a higher fitness than A/Sydney is not because it reaches a higher maximum frequency, but because it seems to have a higher slope. The discrepancy between this plot and the MLR inferred fitness could be clarified by plotting the frequency trajectories on a log-scale.

For the MLR, we understand that the initial frequency matters in assessing a variant's growth. However, when starting points of two clades differ in time (i.e., in different contexts of competing clades), this affects comparability, particularly between A/Massachusetts and A/Ontario, as well as for other strains. We still think that mentioning these time-dependent effects, which are not captured by the MLR analysis, would be appropriate. To support this, it could be helpful to include the MLR fits as an appendix figure, showing the different starting and/or time points used.

(3) Regarding my previous suggestion to test an older vaccine strain than A/Texas/50/2012 to assess whether the observed peak in titer measurements is virus-specific: We understand that the authors want to focus the scope of this paper on the relative fitness of contemporary strains, and that this additional experimental effort would go beyond the main objectives outlined in this manuscript. However, the authors explicitly note that "Adults across age groups also have their highest titers to the oldest vaccine strain tested, consistent with the fact that these adults were first imprinted by exposure to an older strain." This statement gives the impression that imprinting effects increase titers for older strains, whereas this does not seem to be true from their results, but only true for A/Texas. It should be modified accordingly.

Reviewer #1 (Public review):

Summary:

This study provides evidence that neuropeptide signaling, particularly via the CRH-CRHBP pathway, plays a key role in regulating the precision of vocal motor output in songbirds. By integrating gene expression profiling with targeted manipulations in the song vocal motor nucleus RA, the authors demonstrate that altering CRH and CRHBP levels bidirectionally modulate song variability. These findings reveal a previously unrecognized neuropeptidergic mechanism underlying motor performance control, supported by molecular and functional evidence.

Strengths:

Neural circuit mechanisms underlying motor variability have been intensively studied, yet the molecular bases of such variability remain poorly understood. The authors address this important gap using the songbird (Bengalese finch) as a model system for motor learning, providing experimental evidence that neuropeptide signaling contributes to vocal motor variability. They comprehensively characterize the expression patterns of neuropeptide-related genes in brain regions involved in song vocal learning and production, revealing distinct regulatory profiles compared to non-vocal related regions, as well as developmental, revealing distinct regulatory profiles compared to non-vocal regions, as well as developmental and behavioral dependencies, including altered expression following deafening and correlations with singing activity over the two days preceding sampling. Through these multi-level analyses spanning anatomy, development, and behavior, the authors identify the CRH-CRHBP pathway in the vocal motor nucleus RA as a candidate regulator of song variability. Functional manipulations further demonstrate that modulation of this pathway bidirectionally alters song variability.

Overall, this work represents an effective use of songbirds, though a well-established neuroethological framework uncovers how previously uncharacterized molecular pathways shape behavioral output at the individual level.

Weaknesses:

(1) This study uses Bengalese finches (BFs) for all experiments-bulk RNA-seq, in situ hybridization across developmental stages, deafening, gene manipulation, and CRH microinfusion-except for the sc/snRNA-seq analysis. BFs differ from zebra finches (ZFs) in several important ways, including faster song degradation after deafening and greater syllable sequence complexity. This study makes effective use of these unique BF characteristics and should be commended for doing so.

However, the major concern lies in the use of the single-cell/single-nucleus RNA-seq dataset from Colquitt et al. (2021), which combines data from both ZFs and BFs for cell-type classification. Based on our reanalysis of the publicly available dataset used in both Colquitt et al. (2021) and the present study, my lab identified two major issues:

(a) The first concern is that the quality of the single-cell RNA-seq data from BFs is extremely poor, and the number of BF-derived cells is very limited. In other words, most of the gene expression information at the single-cell (or "subcellular type") level in this study likely reflects ZF rather than BF profiles. In our verification of the authors' publicly annotated data, we found that in the song nucleus RA, only about 18 glutamatergic cells (2.3%) of a total of 787 RA_Glut (RA_Glut1+2+3) cells were derived from BFs. Similarly, in HVC, only 53 cells (4.1%) out of 1,278 Glut1+Glut4 cells were BF-derived. This clearly indicates that the cell-subtype-level expression data discussed in this study are predominantly based on ZF, not BF, expression profiles.

Recent studies have begun to report interspecies differences in the expression of many genes in the song control nuclei. It is therefore highly plausible that the expression patterns of CRHBP and other neuropeptide-signaling-related genes differ between ZFs and BFs. Yet, the current study does not appear to take this potential species difference into account. As a result, analyses such as the CellChat results (Fig. 2F and G) and the model proposed in Fig. 6G are based on ZF-derived transcriptomic information, even though the rest of the experimental data are derived from BF, which raises a critical methodological inconsistency.

(b) The second major concern involves the definition of "subcellular types" in the sc/snRNA-seq dataset. Specifically, the RA_Glut1, 2, and 3 and HVC_Glu1 and 4 clusters-classified as glutamatergic projection neuron subtypes-may in fact represent inter-individual variation within the same cell type rather than true subtypes. Following Colquitt et al. (2021), Toji et al. (PNAS, 2024) demonstrated clear individual differences in the gene expression profiles of glutamatergic projection neurons in RA.

In our reanalysis of the same dataset, we also observed multiple clusters representing the same glutamatergic projection neurons in UMAP space. This likely occurs because Seurat integration (anchor-based mutual nearest neighbor integration) was not applied, and because cells were not classified based on individual SNP information using tools such as Souporcell. When classified by individual SNPs, we confirmed that the RA_Glut1-3 and HVC_Glu1 and 4 clusters correspond simply to cells from different individuals rather than distinct subcellular types. (Although images cannot be attached in this review system, we can provide our analysis results if necessary.)

This distinction is crucial, as subsequent analyses and interpretations throughout the manuscript depend on this classification. In particular, Figure 6G presents a model based on this questionable subcellular classification. Similarly, the ligand-receptor relationships shown in Figure 2G - such as the absence of SST-SSTR1 signaling in RA_Glut3 but its presence in RA_Glut1 and 2-are more plausibly explained by inter-individual variation rather than subcellular-type specificity.

Whether these differences are interpreted as individual variation within a single cell type or as differences in projection targets among glutamatergic neurons has major implications for understanding the biological meaning of neuropeptide-related gene expression in this system.

(2) Based on the important finding that "CRHBP expression in the song motor pathway is correlated with singing," it is necessary to provide data showing that the observed changes in CRHBP and other neuropeptide-related gene expression during the song learning period or after deafening are not merely due to differences in singing amount over the two days preceding brain sampling.

Without such data, the following statement cannot be justified: "Regarding CRHBP expression in the song motor pathway increases during song acquisition and decreases following deafening."

(3) In Figure 5B, the authors should clearly distinguish between intact and deafened birds and show the singing amount for each group. In practice, deafening often leads to a reduction in both the number of song bouts and the total singing time. If, in this experiment, deafened birds also exhibited reduced singing compared to intact birds, then the decreased CRHBP expression observed in HVC and RA (Figures 3 and 4) may not reflect song deterioration, but rather a simple reduction in singing activity.

As a similar viewpoint, the authors report that CRHBP expression levels in RA and HVC increase with age during the song learning period. However, this change may not be directly related to age or the decline in vocal plasticity. Instead, it could correlate with the singing amount during the one to two days preceding brain sampling. The authors should provide data on the singing activity of the birds used for in situ hybridization during the two days prior to sampling.

Reviewer #1 (Public review):

Summary:

The authors aim to investigate the mechanisms underlying Kupffer cell death in metabolic-associated steatotic liver disease (MASLD). The authors propose that KCs undergo massive cell death in MASLD and that glycolysis drives this process. However, there appears to be a discrepancy between the reported high rates of KC death and the apparent maintenance of KC homeostasis and replacement capacity.

Strengths:

This is an in vivo study.

Weaknesses:

There are discrepancies between the authors' observations and previous reports, as well as inconsistencies among their own findings.

Before presenting the percentage of CLEC4F⁺TUNEL⁺ cells, the authors should have first shown the number of CLEC4F⁺ cells per unit area in Figure 1. At 16 weeks of age, the proportion of TUNEL⁺ KCs is extremely high (~60%), yet the flow cytometry data indicate that nearly all F4/80⁺ KCs are TIMD4⁺, suggesting an embryonic origin. If such extensive KC death occurred, the proportion of embryonically derived TIMD4⁺ KCs would be expected to decrease substantially. Surprisingly, the proportion of TIMD4⁺ KCs is comparable between chow-fed and 16-week HFHC-fed animals. Thus, the immunostaining and flow cytometry data are inconsistent, making it difficult to explain how massive KC death does not lead to their replacement by monocyte-derived cells.

These data suggest that despite the reported high rate of cell death among CLEC4F⁺TIMD4⁺ KCs, the population appears to self-maintain, with no evidence of monocyte-derived KC generation in this model, which contradicts several recent studies in the field.

Moreover, there is no evidence that TIMD4⁺CLEC4F⁺ KCs increase their proliferation rate to compensate for such extensive cell death. If approximately 60% of KCs are dying and no monocyte-derived KCs are recruited, one would expect a much greater decrease in total KC numbers than what is reported.

It is also unexpected that the maximal rate of KC death occurs at early time points (8 weeks), when the mice have not yet gained substantial weight (Figure 1B). Previous studies have shown that longer feeding periods are typically required to observe the loss of embryo-derived KCs.

Furthermore, it is surprising that the HFD induces as much KC death as the HFHC and MCD diets. Earlier studies suggested that HFD alone is far less effective than MASH-inducing diets at promoting the replacement of embryonic KCs by monocyte-derived macrophages.

In Figure 2D, TIMD4 staining appears extremely faint, making the results difficult to interpret. In contrast, the TUNEL signal is strikingly intense and encompasses a large proportion of liver cells (approximately 60% of KCs, 15% of hepatocytes, 20% of hepatic stellate cells, 30% of non-KC macrophages, and a proportion of endothelial cells is also likely affected). This pattern closely resembles that typically observed in mouse models of acute liver failure. Given this apparent extent of cell death, it is unexpected that ALT and AST levels remain low in MASH mice, which is highly unusual.

No statistical analysis is provided for Figure 5D, and it is unclear which metabolites show statistically significant changes in Figure 5C.

In addition, there is no evaluation of liver pathology in Clec4f-Cre × Chil1flox/flox mice. It remains possible that the observed effects on KC death result from aggravated liver injury in these animals. There is also no evidence that Chil1 deficiency affects glucose metabolism in KCs in vivo.

Finally, the authors should include a more direct experimental approach to modulate glycolysis in KCs and assess its causal role in KC death in MASH.

Reviewer #1 (Public review):

Summary:

This study addresses the emerging role of fungal pathogens in colorectal cancer and provides mechanistic insights into how Candida albicans may influence tumor-promoting pathways. While the work is potentially impactful and the experiments are carefully executed, the strength of evidence is limited by reliance on in vitro models, small patient sample size, and the absence of in vivo validation, which reduces the translational significance of the findings.

Strengths:

(1) Comprehensive mechanistic dissection of intracellular signaling pathways.

(2) Broad use of pharmacological inhibitors and cell line models.

(3) Inclusion of patient-derived organoids, which increases relevance to human disease.

(4) Focus on an emerging and underexplored aspect of the tumor microenvironment, namely fungal pathogens.

Weaknesses:

(1) Clinical association data are inconsistent and based on very small sample numbers.

(2) No in vivo validation, which limits the translational significance.

(3) Species- and cell type-specificity claims are not well supported by the presented controls.

(4) Reliance on colorectal cancer cell lines alone makes it difficult to judge whether findings are specific or general epithelial responses.

Reviewer #1 (Public review):

This study presents an exploration of PPGL tumour bulk transcriptomics and identifies three clusters of samples (labeled as subtypes C1-C3). Each subtype is then investigated for the presence of somatic mutations, metabolism-associated pathway and inflammation correlates, and disease progression.

The proposed subtype descriptions are presented as an exploratory study. The proposed potential biomarkers from this subtype are suitably caveated and will require further validation in PPGL cohorts together with mechanistic study.

The first section uses WGCNA (a method to identify clusters of samples based on gene expression correlations) to discover three transcriptome-based clusters of PPGL tumours using a new cohort of n=87 PPGL samples from various locations in the body.

The second section inspects a previously published snRNAseq dataset, assigning the published samples to subtypes C1-C3 using a pseudo-bulk approach.

The tumour samples are obtained from multiple locations in the body, summarised in Fig1A. It will be important to see further investigation of how the sample origin is distributed among the C1-C3 clusters, and whether there is a sample-origin association with mutational drivers and disease progression.

Comments on revisions:

In SupplFile3 (pdf) - please correct the table format. The contents are obscured due to the narrowness of the table columns.

Deposit the new RNAseq data (N=87 cases, N=5 controls) in an appropriate repository; see "Data on human genotypes and phenotypes" at https://elife-rp.msubmit.net/html/elife-rp_author_instructions.html#dataavailability

Reviewer #1 (Public review):

This paper examines how geometric regularities in abstract shapes (e.g., parallelograms, kites) are perceived and processed in the human brain. The manuscript contains multimodal data (behavior, fMRI, MEG) from adults and additional fMRI data from 6-year-old children. The key findings show that (1) processing geometric shapes lead to reduced activity in ventral areas in comparison to complex stimuli and increased activity in intraparietal and inferior temporal regions, (2) the degree of geometric regularity modulates activity in intraparietal and inferior temporal regions, (3) similarity in neural representation of geometric shapes can be captured early by using CNN models and later by models of geometric regularity. In addition to these novel findings, the paper also includes a replication of behavioral data, showing that the perceptual similarity structure amongst the geometric stimuli used can be explained by a combination of visual similarities (as indexed by feedforward CNN model of ventral visual pathway) and geometric features. The paper comes with openly accessible code in a well-documented GitHub repository and the data will be published with the paper on OpenNeuro.

In the revised version of this manuscript, the authors clarified certain aspects of the task design, added critical detail to the description of the methods, and updated the figures to show unsmoothed data and variability across participants. Importantly, the authors thoroughly discussed potential task effects (for the fMRI data only) and added additional analyses that indicate that the effects are unlikely to be driven by linguistic labels/name availability of the stimuli.

Comments on the revision:

Thank you for carefully addressing all my concerns and especially for clarifying the task design.

Reviewer #1 (Public review):

Summary:

This paper presents three experiments. Experiments 1 and 3 use a target detection paradigm to investigate the speed of statistical learning. The first experiment is a replication of Batterink, 2017, in which participants are presented with streams of uniform-length, trisyllabic nonsense words and asked to detect a target syllable. The results replicate previous findings, showing that learning (in the form of response time facilitation to later-occurring syllables within a nonsense word) occurs after a single exposure to a word. In the second experiment, participants are presented with streams of variable length nonsense words (two trisyllabic words and two disyllabic words), and perform the same task. A similar facilitation effect was observed as in Experiment 1. In Experiment 3 (newly added in the Revised manuscript), an adult version of the study by Johnson and Tyler is included. Participants were exposed to streams of words of either uniform length (all disyllabic) or mixed length (two disyllabic, two trisyllabic) and then asked to perform a familiarity judgment on a 1-5 scale on two words from the stream and two part-words. Performance was better in the uniform length condition.

The authors interpret these findings as evidence that target detection requires mechanisms different from segmentation. They present results of a computational model to simulate results from the target detection task, and find that a bigram model can produce facilitation effects similar to the ones observed by human participants in Experiments 1 and 2 (though this model was not directly applied to test whether human-like effects were also produced to account for the data in Experiment 3). PARSER was also tested and produced differing results from those observed by humans across all three experiments. The authors conclude that the mechanisms involved in the target detection task are different from those involved in the word segmentation task.

Strengths:

The paper presents multiple experiments that provide internal replication of a key experimental finding, in which response times are facilitated after a single exposure to an embedded pseudoword. Both experimental data and results from a computational model are presented, providing converging approaches for understanding and interpreting the main results. The data are analyzed very thoroughly using mixed effects models with multiple explanatory factors. The addition of Experiment 3 provides direct evidence that the profile of performance for familiarity ratings and target detection differ as a function of word length variability.

Weaknesses:

(1) The concept of segmentation is still not quite clear. The authors seem to treat the testing procedure of Experiment 3 as synonymous with segmentation. But the ability to more strongly endorse words from the stream versus part-words as familiar does not necessarily mean that they have been successfully "segmented", as I elaborated on in my earlier review. In my view, it would be clearer to refer to segmentation as the mechanism or conceptual construct of segmenting continuous speech into discrete words. This ability to accurately segment component words could support familiarity judgments but is not necessary for above-chance familiarity or recognition judgments, which could be supported by more general memory signals. In other words, segmentation as an underlying ability is sufficient but not necessary for above-chance performance on familiarity-driven measures such as the one used in experiment 3.

(2) The addition of experiment 3 is an added strength of the revised paper and provides more direct evidence of dissociations as a function of word length on the two tasks (target detection and familiarity ratings), compared to the prior strategy of just relying on previous work for this claim. However, it is not clear why the authors chose not to use the same stimuli as used in experiment 1 and 2, which would have allowed for more direct comparisons to be made. It should also be specified whether test items in the UWL and MWL were matched for overall frequency during exposure. Currently, the text does not specify whether test words in the UWL condition were taken from the high frequency or low frequency group; if they were taken from the high frequency group this would of course be a confound when comparing to the MWL condition. Finally, the definition of part-words should also be clarified,

(3) The framing and argument for a prediction/anticipation mechanism was dropped in the Revised manuscript, but there are still a few instances where this framing and interpretation remain. E.g. Abstract - "we found that a prediction mechanism, rather than clustering, could explain the data from target detection." Discussion page 43 "Together, these results suggest that a simple prediction-based mechanism can explain the results from the target detection task, and clustering-based approaches such as PARSER cannot, contrary to previous claims."

Minor (4) It was a bit unclear as to why a conceptual replication of Batterink 2017 was conducted, given that the target syllables at the beginning and end of the streams were immediately dropped from further analysis. Why include syllable targets within these positions in the design if they are not analyzed?

(5) Figures 3 and 4 are plotted on different scales, which makes it difficult to visually compare the effects between word length conditions.

Reviewer #1 (Public review):

This study investigates how ant group demographics influence nest structures and group behaviors of Camponotus fellah ants, a ground-dwelling carpenter ant species (found locally in Israel) that build subterranean nest structures. Using a quasi-2D cell filled with artificial sand, the authors perform two complementary sets of experiments to try to link group behavior and nest structure: first, the authors place a mated queen and several pupae into their cell and observe the structures that emerge both before and after the pupae eclose (i.e., "colony maturation" experiments); second, the authors create small groups (of 5, 10, or 15 ants, each including a queen) within a narrow age range (i.e., "fixed demographic" experiments) to explore the dependence of age on construction. Some of the fixed demographic instantiations included a manually induced catastrophic collapse event; the authors then compared emergency repair behavior to natural nest creation. Finally, the authors introduce a modified logistic growth model to describe the time-dependent nest area. The modification introduced parameters that allow for age-dependent behavior, and the authors use their fixed demographic experiments to set these parameters, and then apply the model to interpret the behavior of the colony maturation experiments. The main results of this paper are that for natural nest construction, nest areas, and morphologies depend on the age demographics of ants in the experiments: younger ants create larger nests and angled tunnels, while older ants tend to dig less and build predominantly vertical tunnels; in contrast, emergency response seems to elicit digging in ants of all ages to repair the nest.

The experimental results are convincing, providing new information and important insights into nest and colony growth in a social insect species. A model, inspired by previous work but modified to capture experimental results, is in reasonable agreement with experiments and is more biologically relevant than previous models.

Reviewer #1 (Public review):

In this manuscript, the authors aimed to identify the molecular target and mechanism by which α-Mangostin, a xanthone from Garcinia mangostana, produces vasorelaxation that could explain the antihypertensive effects. Building on prior reports of vascular relaxation and ion channel modulation, the authors convincingly show that large-conductance potassium BK channels are the primary site of action. Using electrophysiological, pharmacological, and computational evidence, the authors achieved their aims and showed that BK channels are the critical molecular determinant of mangostin's vasodilatory effects, even though the vascular studies are quite preliminary in nature.

Strengths:

(1) The broad pharmacological profiling of mangostin across potassium channel families, revealing BK channels - and the vascular BK-alpha/beta1 complex - as the potently activated target in a concentration-dependent manner.

(2) Detailed gating analyses showing large negative shifts in voltage-dependence of activation and altered activation and deactivation kinetics.

(3) High-quality single-channel recordings for open probability and dwell times.

(4) Convincing activation in reconstituted BKα/β1-Caᵥ nanodomains mimicking physiological conditions and functional proof-of-concept validation in mouse aortic rings.

Weaknesses are minor:

(1) Some mutagenesis data (e.g., partial loss at L312A) could benefit from complementary structural validation.

(2) While Cav-BK nanodomains were reconstituted, direct measurement of calcium signals after mangostin application onto native smooth muscle could be valuable.

(3) The work has an impact on ion channel physiology and pharmacology, providing a mechanistic link between a natural product and vasodilation. Datasets include electrophysiology traces, mutagenesis scans, docking analyses, and aortic tension recordings. The latter, however, are preliminary in nature.

Reviewer #1 (Public review):

Summary:

This study identifies three redundant pathways-glycine cleavage system (GCS), serine hydroxymethyltransferase (GlyA), and formate-tetrahydrofolate ligase/FolD-that feed the one-carbon tetrahydrofolate (1C-THF) pool essential for Listeria monocytogenes growth and virulence. Reactivation of the normally inactive fhs gene rescues 1C-THF deficiency, revealing metabolic plasticity and vulnerability for potential antimicrobial targeting

Strengths:

(1) Novel evolutionary insight - reversible reactivation of a pseudogene (fhs) shows adaptive metabolic plasticity, relevant for pathogen evolution.

(2) They systematically combine targeted gene deletions with suppressor screening to dissect the folate/one-carbon network (GCS, GlyA, Fhs/FolD).

Weaknesses:

(1) The study infers 1C-THF depletion mostly genetically and indirectly (growth rescue with adenine) without direct quantification of folate intermediates or fluxes. Biochemical confirmation, LC-MS-based metabolomics of folates/1C donors, or isotopic tracing would strengthen mechanistic claims.

(2) In multiple result sections, the authors report data from technical triplicates but do not mention independent biological replicates (e.g., Figure 2C, Figure 4A-B, Figure 6D). In addition, some results mention statistical significance but without a detailed description of the specific statistical tests used or replicates, such as Figure 2A-C, Figure 2E, and Figure 2G-I.

Reviewer #1 (Public review):

Summary:

This important study functionally profiled ligands targeting the LXR nuclear receptors using biochemical assays in order to classify ligands according to pharmacological functions. Overall, the evidence is solid, but nuances in the reconstituted biochemical assays and cellular studies and terminology of ligand pharmacology limit the potential impact of the study. This work will be of interest to scientists interested in nuclear receptor pharmacology.

Strengths:

(1) The authors rigorously tested their ligand set in CRTs for several nuclear receptors that could display ligand-dependent cross-talk with LXR cellular signaling and found that all compounds display LXR selectivity when used at ~1 µM.

(2) The authors tested the ligand set for selectivity against two LXR isoforms (alpha and beta). Most compounds were found to be LXRbeta-specific.

(3) The authors performed extensive LXR CRTs, performed correlation analysis to cellular transcription and gene expression, and classification profiling using heatmap analysis-seeking to use relatively easy-to-collect biochemical assays with purified ligand-binding domain (LBD) protein to explain the complex activity of full-length LXR-mediated transcription.

Weaknesses:

(1) The descriptions of some observations lack detail, which limits understanding of some key concepts.

(2) The presence of endogenous NR ligands within cells may confound the correlation of ligand activity of cellular assays to biochemical assay data.

(3) The normalization of biochemical assay data could confound the classification of graded activity ligands.

(4) The presence of >1 coregulator peptide in the biplex (n=2 peptides) CRT (pCRT) format will bias the LBD conformation towards the peptide-bound form with the highest binding affinity, which will impact potency and interpretation of TR-FRET data.

(5) Correlation graphical plots lack sufficient statistical testing.

(6) Some of the proposed ligand pharmacology nomenclature is not clear and deviates from classifications used currently in the field (e.g., hard and soft antagonist; weak vs. partial agonist, definition of an inverse agonist that is not the opposite function to an agonist).

Reviewer #1 (Public review):

Summary:

This study presents a high-throughput screening platform to identify nanobodies capable of recruiting chromatin regulators and modulating gene expression. The authors utilize a yeast display system paired with mammalian reporter assays to validate candidate nanobodies, aiming to create a modular resource for synthetic epigenetic control.

Strengths:

(1) The overall screening design combining yeast display with mammalian functional assays is innovative and scalable.

(2) The authors demonstrate proof-of-concept that nanobody-based recruitment can repress or activate reporter expression.

(3) The manuscript contributes to the growing toolkit for epigenome engineering.

Weaknesses:

(1) The manuscript does not investigate which endogenous factors are recruited by the nanobodies. While repression activity is demonstrated at the reporter level, there is no mechanistic insight into what proteins are being brought to the target site by each nanobody. This limits the interpretability and generalizability of the findings. Related to this, Figure S1B reports sequence similarity among complementarity-determining regions (CDRs) of nanobodies that scored highly in the DNMT3A screen. However, it remains unclear whether this similarity reflects convergence on a common molecular target or is coincidental. Without functional or proteomic validation, the relationship between sequence motifs and effector recruitment remains speculative.

(2) The epigenetic consequences of nanobody recruitment are also left unexplored. Despite targeting epigenetic regulators, the study does not assess changes such as DNA methylation or histone modifications. This makes it difficult to interpret whether the observed reporter repression is due to true chromatin remodeling or secondary effects.

Reviewer #1 (Public review):

In this work, Zhang et al, through a series of well-designed experiments, present a comprehensive study exploring the roles of the neuropeptide Corazonin (CRZ) and its receptor in controlling the female post-mating response (PMR) in the brown planthopper (BPH) Nilaparvata lugen and Drosophila melanogaster. Through a series of behavioural assays, micro-injections, gene knockdowns, Crispr/Cas gene editing, and immunostaining, the authors show that both CRZ and CrzR play a vital role in the female post-mating response, with impaired expression of either leading to quicker female remating and reduced ovulation in BPH. Notably, the authors find that this signaling is entirely endogenous in BPH females, with immunostaining of male accessory glands (MAGs) showing no evidence of CRZ expression. Further, the authors demonstrate that while CRZ is not expressed in the MAGs, BPH males with Crz knocked out show transcriptional dysregulation of several seminal fluid proteins and functionally link this dysregulation to an impaired PMR in BPH. In relation, the authors also find that in CrzR mutants, the injection of neither MAG extracts nor maccessin peptide triggered the PMR in BPH females. Finally, the authors extend this study to D. melanogaster, albeit on a more limited scale, and show that CRZ plays a vital role in maintaining PMR in D. melanogaster females with impaired CRZ signaling, once again leading to quicker female remating and reduced ovulation. The authors must be commended for their expansive set of complementary experiments. The manuscript is also generally well written. Given the seemingly conserved nature of CRZ, this work is a significant addition to the literature, opening several avenues for testing the molecular and neurobiological mechanisms in which CRZ triggers the PMR.

However, there are some broad concerns/comments I had with this manuscript. The authors provide clear evidence that CRZ signaling plays a major role in the PMR of D. melanogaster, however, they provide no evidence that CRZ signaling is endogenous, as they did not check for expression in the MAGs of D. melanogaster males. Additionally, while the authors show that manipulating Crz in males leads to dysregulated seminal fluid expression and impaired PMR in BPH, the authors also find that CRZ injection in males in and of itself impairs PMR in BPH. The authors do not really address what this seemingly contradictory result could mean. While a lot of the figures have replicate numbers, the authors do not factor in replicate as an effect into their models, which they ideally should do.

Finally, while the discussion is generally well-written, it lacks a broader conclusion about the wider implications of this study and what future work building on this could look like.

Reviewer #1 (Public review):

In this study, the authors investigated a specific subtype of SST-INs (layer 5 Chrna2-expressing Martinotti cells) and examined its functional role in motor learning. Using endoscopic calcium imaging combined with chemogenetics, they showed that activation of Chrna2 cells reduces the plasticity of pyramidal neuron (PyrN) assemblies but does not affect the animals' performance. However, activating Chrna2 cells during re-training improved performance. The authors claim that activating Chrna2 cells likely reduces PyrN assembly plasticity during learning and possibly facilitates the expression of already acquired motor skills.

There are many major issues with the study. The findings across experiments are inconsistent, and it is unclear how the authors performed their analyses or why specific time points and comparisons were chosen. The study requires major re-analysis and additional experiments to substantiate its conclusions.

Major Points:

(1a) Behavior task - the pellet-reaching task is a well-established paradigm in the motor learning field. Why did the authors choose to quantify performance using "success pellets per minute" instead of the more conventional "success rate" (see PMID 19946267, 31901303, 34437845, 24805237)? It is also confusing that the authors describe sessions 1-5 as being performed on a spoon, while from session 6 onward, the pellets are presented on a plate. However, in lines 710-713, the authors define session 1 as "naïve," session 2 as "learning," session 5 as "training," and "retraining" as a condition in which a more challenging pellet presentation was introduced. Does "naïve session 1" refer to the first spoon session or to session 6 (when the food is presented on a plate)? The same ambiguity applies to "learning session 2," "training session 5," and so on. Furthermore, what criteria did the authors use to designate specific sessions as "learning" versus "training"? Are these definitions based on behavioral performance thresholds or some biological mechanisms? Clarifying these distinctions is essential for interpreting the behavioral results.

(1b) Judging from Figures 1F and 4B, even in WT mice, it is not convincing that the animals have actually learned the task. In all figures, the mice generally achieve ~10-20 pellets per minute across sessions. The only sessions showing slightly higher performance are session 5 in Figure 1F ("train") and sessions 12 and 13 in Figure 4B ("CLZ"). In the classical pellet-reaching task, animals are typically trained for 10-12 sessions (approximately 60 trials per session, one session per day), and a clear performance improvement is observed over time. The authors should therefore present performance data for each individual session to determine whether there is any consistent improvement across days. As currently shown, performance appears largely unchanged across sessions, raising doubts about whether motor learning actually occurred.

(1c) The authors also appear to neglect existing literature on the role of SST-INs in motor learning and local circuit plasticity (e.g., PMID 26098758, 36099920). Although the current study focuses on a specific subpopulation of SST-INs, the results reported here are entirely opposite to those of previous studies. The authors should, at a minimum, acknowledge these discrepancies and discuss potential reasons for the differing outcomes in the Discussion section.

(2a) Calcium imaging - The methodology for quantifying fluorescence changes is confusing and insufficiently described. The use of absolute ΔF values ("detrended by baseline subtraction," lines 565-567) for analyses that compare activity across cells and animals (e.g., Figure 1H) is highly unconventional and problematic. Calcium imaging is typically reported as ΔF/F₀ or z-scores to account for large variations in baseline fluorescence (F₀) due to differences in GCaMP expression, cell size, and imaging quality. Absolute ΔF values are uninterpretable without reference to baseline intensity - for example, a ΔF of 5 corresponds to a 100% change in a dim cell (F₀ = 5) but only a 1% change in a bright cell (F₀ = 500). This issue could confound all subsequent population-level analyses (e.g., mean or median activity) and across-group comparisons. Moreover, while some figures indicate that normalization was performed, the Methods section lacks any detailed description of how this normalization was implemented. The critical parameters used to define the baseline are also omitted. The authors should reprocess the imaging data using a standardized ΔF/F₀ or z-score approach, explicitly define the baseline calculation procedure, and revise all related figures and statistical analyses accordingly.

(2b) Figure 1G - It is unclear why neural activity during successful trials is already lower one second before movement onset. Full traces with longer duration before and after movement onset should also be shown. Additionally, only data from "session 2 (learning)" and a single neuron are presented. The authors should present data across all sessions and multiple neurons to determine whether this observation is consistent and whether it depends on the stage of learning.

(2c) Figure 1H - The authors report that chemogenetic activation of Chrna2 cells induces differential changes in PyrN activity between successful and failed trials. However, one would expect that activating all Chrna2 cells would strongly suppress PyrN activity rather than amplifying the activity differences between trials. The authors should clarify the mechanism by which Chrna2 cell activation could exaggerate the divergence in PyrN responses between successful and failed trials. Perhaps, performing calcium imaging of Chrna2 cells themselves during successful versus failed trials would provide insight into their endogenous activity patterns and help interpret how their activation influences PyrN activity during successful and failed trials.

(2d) Figure 1H - Also, in general, the Cre⁺ (red) data points appear consistently higher in activity than the Cre⁻ (black) points. This is counterintuitive, as activating Chrna2 cells should enhance inhibition and thereby reduce PyrN activity. The authors should clarify how Cre⁺ animals exhibit higher overall PyrN activity under a manipulation expected to suppress it. This discrepancy raises concerns about the interpretation of the chemogenetic activation effects and the underlying circuit logic.

(3) The statistical comparisons throughout the manuscript are confusing. In many cases, the authors appear to perform multiple comparisons only among the N, L, T, and R conditions within the WT group. However, the central goal of this study should be to assess differences between the WT and hM3D groups. In fact, it is unclear why the authors only provide p-values for some comparisons but not for the majority of the groups.

(4a) Figure 4 - It is hard to understand why the authors introduce LFP experiments here, and the results are difficult to interpret in isolation. The authors should consider combining LFP recordings with calcium imaging (as in Figure 1) or, alternatively, repeating calcium imaging throughout the entire re-training period. This would provide a clearer link between circuit activity and behavior and strengthen the conclusions regarding Chrna2 cell function during re-training.

(4b) It is unclear why CLZ has no apparent effect in session 11, yet induces a large performance increase in sessions 12 and 13. Even then, the performance in sessions 12 and 13 (~30 successful pellets) is roughly comparable to Session 5 in Figure 1F. Given this, it is questionable whether the authors can conclude that Chrna2 cell activation truly facilitates previously acquired motor skills?

(5) Figure 5 - The authors report decreased performance in the pasta-handling task (presumably representing a newly learned skill) but observe no difference in the pellet-reaching task (presumably an already acquired skill). This appears to contradict the authors' main claim that Chrna2 cell activation facilitates previously acquired motor skills.

(6) Supplementary Figure 1 - The c-fos staining appears unusually clean. Previous studies have shown that even in home-cage mice, there are substantial numbers of c-fos⁺ cells in M1 under basal conditions (PMID 31901303, 31901303). Additionally, the authors should present Chrna2 cell labeling and c-fos staining in separate channels. As currently shown, it is difficult to determine whether the c-fos⁺ cells are truly Chrna2 cells⁺.

Overall, the authors selectively report statistical comparisons only for findings that support their claims, while most other potentially informative comparisons are omitted. Complete and transparent reporting is necessary for proper interpretation of the data.

Reviewer #1 (Public review):

Summary:

This study investigates how human temporal voice areas (TVA) respond to vocalizations from nonhuman primates. Using functional MRI during a species-categorization task, the authors compare neural responses to calls from humans, chimpanzees, bonobos, and macaques while modeling both acoustic and phylogenetic factors. They find that bilateral anterior TVA regions respond more strongly to chimpanzee than to other nonhuman primate vocalizations, suggesting that these regions are sensitive not only to human voices but also to acoustically and evolutionarily related sounds.

The work provides important comparative evidence for continuity in primate vocal communication and offers a strong empirical foundation for modeling how specific acoustic features drive TVA activity.

Strengths:

­(1) Comparative scope: The inclusion of four primate species, including both great apes and monkeys, provides a rare and valuable cross-species perspective on voice processing.

­(2) Methodological rigor: Acoustic and phylogenetic distances are carefully quantified and incorporated into the analyses.

­(4) Neuroscientific significance: The finding of TVA sensitivity to chimpanzee calls supports the view that human voice-selective regions are evolutionarily tuned to certain acoustic features shared across primates.

­(4) Clear presentation: The study is well organized, the stimuli well controlled, and the imaging analyses transparent and replicable.

­(5) Theoretical contribution: The results advance understanding of the neural bases of voice perception and the evolutionary roots of voice sensitivity in the human brain.

Weaknesses:

­(1) Acoustic-phylogenetic confound: The design does not fully disentangle acoustic similarity from phylogenetic proximity, as species co-vary along both dimensions. A promising way to address this would be to include an additional model focusing on the acoustic features that specifically differentiate bonobo from chimpanzee calls, which share equal phylogenetic distance to humans.

­(2) Selectivity vs. sensitivity: Without non-vocal control sounds, the study cannot determine whether TVA responses reflect true selectivity for primate vocalizations or general auditory sensitivity.<br /> ­<br /> (3) Task demands: The use of an active categorization task may engage additional cognitive processes beyond auditory perception; a passive listening condition would help clarify the contribution of attention and task performance.

­(4) Figures and presentation: Some results are partially redundant; keeping only the most representative model figure in the main text and moving others to the Supplementary Material would improve clarity.

Reviewer #1 (Public review):

In this manuscript, the authors used a coarse-grained DNA model (cgNA+) to explore how DNA sequences and CpG methylation/hydroxymethylation influence nucleosome wrapping energy and the probability density of optimal nucleosomal configuration. Their findings indicate that both methylated and hydroxymethylated cytosines lead to increased nucleosome wrapping energy. Additionally, the study demonstrates that methylation of CpG islands increases the probability of nucleosome formation.

The major strength of this method is that the model explicitly includes the phosphate group as DNA-histone binding site constraints, enhancing CG model accuracy and computational efficiency and allowing comprehensive calculations of DNA mechanical properties and deformation energies.

The revised version has addressed the concerns raised previously, significantly strengthening the study.

Reviewer #1 (Public review):

Summary:

This study examines letter-shape knowledge in a large cohort of children with minimal formal reading instruction. The authors report that these children can reliably distinguish upright from inverted letters despite limited letter naming abilities. They also show a visual-search advantage for upright over inverted letters, and this advantage correlates with letter-shape familiarity. These findings suggest that specialized letter-shape representations can emerge with very limited letter-sound mapping practice.

Strengths:

This study investigates whether children can develop letter-shape knowledge independently of letter-sound mapping abilities. This question is theoretically important, especially in light of functional subdivisions within the visual word form area (VWFA), with posterior regions associated with letter/orthographic shape and anterior regions with linguistic features of orthography (Caffarra et al., 2021; Lerma-Usabiaga et al., 2018). The study also includes a large sample of children at the very beginning of formal reading instruction, thereby minimizing the influence of explicit instruction on the formation of letter-shape knowledge.

Weakness:

A central concern is that a production task (naming) is used to index letter-name knowledge, whereas letter-shape knowledge is assessed with recognition. Production tasks impose additional demands (motor planning, articulation) and typically yield lower performance than recognition tasks (e.g., letter-sound verification). Thus, comparisons between letter-shape and letter-name knowledge are confounded by task type. The authors' partial-correlation and multiple-regression analyses linking familiarity (but not production) to the upright-search advantage are informative; however, they do not resolve the recognition-versus-production mismatch. Consequently, the current data cannot unambiguously support the claim that letter-shape representations are independent of letter-name knowledge.

Reviewer #1 (Public review):

In this manuscript, Domingo et al. present a novel perturbation-based approach to experimentally modulate the dosage of genes in cell lines. Their approach is capable of gradually increasing and decreasing gene expression. The authors then use their approach to perturb three key transcription factors and measure the downstream effects on gene expression. Their analysis of the dosage response curve of downstream genes reveals marked non-linearity.

One of the strengths of this study is that many of the perturbations fall within the physiological range for each cis gene. This range is presumably between a single-copy state of heterozygous loss-of-function (log fold change of -1) and a three-copy state (log fold change of ~0.6). This is in contrast with CRISPRi or CRISPRa studies that attempt to maximize the effect of the perturbation, which may result in downstream effects that are not representative of physiological responses.

Another strength of the study is that various points along the dosage-response curve were assayed for each perturbed gene. This allowed the authors to effectively characterize the degree of linearity and monotonicity of each dosage-response relationship. Ultimately, the study revealed that many of these relationships are non-linear, and that the response to activation can be dramatically different than the response to inhibition.

To test their ability to gradually modulate dosage, the authors chose to measure three transcription factors and around 80 known downstream targets. As the authors themselves point out in their discussion about MYB, this biased sample of genes makes it unclear how this approach would generalize genome-wide. In addition, the data generated from this small sample of genes may not represent genome-wide patterns of dosage response. Nevertheless, this unique data set and approach represents a first step in understanding dosage-response relationships between genes.

Another point of general concern in such screens is the use of the immortalized K562 cell line. It is unclear how the biology of these cell lines translates to the in vivo biology of primary cells. However, the authors do follow up with cell-type-specific analyses (Figures 4B, 4C, and 5A) to draw correspondence between their perturbation results and the relevant biology in primary cells and complex diseases.

The conclusions of the study are generally well supported with statistical analysis throughout the manuscript. As an example, the authors utilize well-known model selection methods to identify when there was evidence for non-linear dosage response relationships.

Gradual modulation of gene dosage is a useful approach to model physiological variation in dosage. Experimental perturbation screens that use CRISPR inhibition or activation often use guide RNAs targeting the transcription start site to maximize their effect on gene expression. Generating a physiological range of variation will allow others to better model physiological conditions.

There is broad interest in the field to identify gene regulatory networks using experimental perturbation approaches. The data from this study provides a good resource for such analytical approaches, especially since both inhibition and activation were tested. In addition, these data provide a nuanced, continuous representation of the relationship between effectors and downstream targets, which may play a role in the development of more rigorous regulatory networks.

Human geneticists often focus on loss-of-function variants, which represent natural knock-down experiments, to determine the role of a gene in the biology of a trait. This study demonstrates that dosage response relationships are often non-linear, meaning that the effect of a loss-of-function variant may not necessarily carry information about increases in gene dosage. For the field, this implies that others should continue to focus on both inhibition and activation to fully characterize the relationship between gene and trait.

Comments on revisions:

Thank you for responding to our comments. We have no further comments for the authors.

Reviewer #1 (Public review):

Summary:

In the paper, the authors propose a new RNA velocity method, TSvelo, which predicts the transcription rate linearly based on the expression of RNA levels of transcription factors. This framework is an extension of its recent work TFvelo by including unspliced reads and designing a coherent neuralODE framework. Improved performance was demonstrated in six diverse datasets.

Strengths:

Overall, this method introduces innovative solutions to link cell differentiation and gene regulation, with a balance between model complexity (neuralODE) and interpretability (raw gene space).

Weaknesses:

While it seems to provide convincing results, there are multiple technical concerns for the authors to clarify and double-check.

(1) The authors should clarify and discuss the TF-target map: here, the TF-target genes map is predefined by the TF binding's ChIP-seq data. This annotation is largely incomplete and mostly compiled from a set of bulk tissues. Therefore, for a certain population, the TF-target relation may change. This requires clarification and discussion, possibly exploring how to address this in the model. In addition, a regulon database could be added, e.g., DoRothEA?

(2) The authors should clarify how example genes are selected. This is particularly unclear in Figure 2d.

(3) The authors should clarify confidence in the statement in lines 179-180, that ANXA4 should initially decrease. This is particularly concerning, as TSvelo didn't capture the cell cycle transitions well during the initial part.

(4) A support reference should be added for the statement in line 260 that "neuron migrations are inside-out manner". There is no reference supporting this, and this statement is critical for the model assessment.

(5) The comparison to scMultiomics data is particularly interesting, as MultiVelo uses ATAC data to predict the transcription rate. It would be very insightful to add a direct comparison of the estimated transcription rate between using ATAC and directly using TFs' RNA expressions.

(6) In Figure 6g, it should be clarified how the lineage was determined. Did the authors use the LARRY barcodes, predicted cell fate, or any other methods? Here, the best way is probably using the LARRY barcodes for individual clones.

Reviewer #1 (Public review):

Summary:

Stemming from the previous research on the adaptation of methylotrophic microbes in the phyllosphere environment, this paper tested a novel hypothesis on the molecular and cellular mechanisms by which yeast uses biomolecular condensates as unique niches for the regulation of methanol-induced mRNAs. While a few in vivo experiments were conducted in the phyllosphere, more assays were carried out on plates to mimic various stress conditions, diminishing the reliability of the conclusions in supporting the main hypothesis.

Strengths:

This study addressed an interesting and important biological question. Some of the experiments were conducted methodically and carefully. The visualization of both the biomolecular condensates and the mRNAs was helpful in addressing the questions. The results are expected to be useful in paving the way for the future study to directly test its main hypothesis. The results of this study could also have a general implication for the adaptation of a huge population of microbes in the enormous space of the phyllosphere on Earth.

Weaknesses:

The results were often over- and misinterpreted. Given mthat any hypotheses were tested indirectly on plates, the correlative results could only be used to carefully suggest the likelihood of the hypotheses. For example, a single edc3 mutant was used to represent a P-body-defective strain, although it is well known that EDC3 is a critical component in mRNA decapping; hence, the mutant should display a pleiotropic phenotype, rather than a mere reduced P-body phenotype. Using a similar reductionist approach, the study went on to employ a series of plate assays to argue that the conditions were mimicking the phyllosphere, which could be misleading under these circumstances. Furthermore, the low percentage of the colocalization between P-bodies and mimRNA granules and the similar results from negative control mRNAs do not convincingly support the idea that mimRNAs are sequestered between two biomolecular condensates, and P-bodies could serve as regulatory hubs. Given that the abundance of mimRNA granules was positively correlated with the transcript abundance of mimRNAs, and P-body abundance did not change too much under methanol induction, the results could not support an active mimRNA sequestration mechanism from mimRNA granules to P-bodies with a proportional increase of the overlap between the two condensates. More direct experiments conducted in the phyllosphere using multiple P-body defective yeast strains should strengthen the manuscript, assuming all the results turned out to be supportive.

Reviewer #1 (Public review):

Summary

The manuscript by Ma et al. provides robust and novel evidence that the noctuid moth Spodoptera frugiperda (Fall Armyworm) possesses a complex compass mechanism for seasonal migration that integrates visual horizon cues with Earth's magnetic field (likely its horizontal component). This is an important and timely study: apart from the Bogong moth, no other nocturnal Lepidoptera has yet been shown to rely on such a dual-compass system. The research therefore expands our understanding of magnetic orientation in insects with both theoretical (evolution and sensory biology) and applied (agricultural pest management, a new model of magnetoreception) significance.

The study uses state-of-the-art methods and presents convincing behavioural evidence for a multimodal compass. It also establishes the Fall Armyworm as a tractable new insect model for exploring the sensory mechanisms of magnetoreception, given the experimental challenges of working with migratory birds. Overall, the experiments are well-designed, the analyses are appropriate, and the conclusions are generally well supported by the data.

Strengths

(1) Novelty and significance: First strong demonstration of a magnetic-visual compass in a globally relevant migratory moth species, extending previous findings from the Bogong moth and opening new research avenues in comparative magnetoreception.

(2) Methodological robustness: Use of validated and sophisticated behavioural paradigms and magnetic manipulations consistent with best practices in the field. The use of 5-minute bins to study the dynamic nature of the magnetic compass which is anchored to a visual cue but updated with a latency of several minutes, is an important finding and a new methodological aspect in insect orientation studies.

(3) Clarity of experimental logic: The cue-conflict and visual cue manipulations are conceptually sound and capable of addressing clear mechanistic questions.

(4) Ecological and applied relevance: Results have implications for understanding migration in an invasive agricultural pest with an expanding global range.

(5) Potential model system: Provides a new, experimentally accessible species for dissecting the sensory and neural bases of magnetic orientation.

Weaknesses

While the study is strong overall, several recommendations should be addressed to improve clarity, contextualisation, and reproducibility:

(1) Structure and presentation of results

Requires reordering the visual-cue experiments to move from simpler (no cues) to more complex (cue-conflict) conditions, improving narrative logic and accessibility for non-specialists.

(2) Ecological interpretation

(a) The authors should discuss how their highly simplified, static cue setup translates to natural migratory conditions where landmarks are dynamic, transient or absent.

(b) Further consideration is required regarding how the compass might function when landmarks shift position, are obscured, or are replaced by celestial cues. Also, more consolidated (one section) and concrete suggestions for future experiments are needed, with transient, multiple, or more naturalistic visual cues to address this.

(3) Methodological details and reproducibility

(a) It would be better to move critical information (e.g., electromagnetic noise measurements) from the supplementary material into the main Methods.

(b) Specifying luminance levels and spectral composition at the moth's eye is required for all visual treatments.

(c) Details are needed on the sex ratio/reproductive status of tested moths, and a map of the experimental site and migratory routes (spring vs. fall) should be included.

(d) Expanding on activity-level analyses is required, replacing "fatigue" with "reduced flight activity," and clarifying if such analyses were performed.

(4) Figures and data presentation

(a) The font sizes on circular plots should be increased; compass labels (magnetic North), sample sizes, and p-values should be included.

(b) More clarity is required on what "no visual cue" conditions entail, and schematics or photos should be provided.

(c) The figure legends should be adjusted for readability and consistency (e.g., replace "magnetic South" with magnetic North, and for box plots better to use asterisks for significance, report confidence intervals).

(5) Conceptual framing and discussion

(a) Generalisations across species should be toned down, given the small number of systems tested by overlapping author groups.

(b) It requires highlighting that, unlike some vertebrates, moths require both magnetic and visual cues for orientation.

(c) It should be emphasised that this study addresses direction finding rather than full navigation.

(d) Future Directions should be integrated and consolidated into one coherent subsection proposing realistic next steps (e.g., more complex visual environments, temporal adaptation to cue-field relationships).

(e) The limitations should be better discussed, due to the artificiality of the visual cue earlier in the Discussion.

(6) Technical and open-science points

• Appropriate circular statistics should be used instead of t-tests for angular data shown in the supplementary material.

• Details should be provided on light intensities, power supplies, and improvements to the apparatus.

• The derivation of individual r-values should be clarified.

• Share R code openly (e.g., GitHub).

• Some highly relevant - yet missing - recent and relevant citations should be added, and some less relevant ones removed.

Reviewer #1 (Public review):

Summary:

Zhou and colleagues introduce a series of generalized Gaussian process models for genotype-phenotype mapping. The goal was to develop models that were more powerful than standard linear models, while retaining explanatory power as opposed to neural network approaches. The novelty stems from choices of prior distributions (and I suppose fitted posteriors) that model epistasis based on some form of site/allele-specific modifier effect and genotype distance. The authors then apply their models to three empirical datasets, the GB1 antibody-binding dataset, the human 5' splice set dataset, and a yeast meiotic cross dataset, and find substantially improved variance explained while retaining strong explanatory power when compared to linear models.

Strengths:

The main strength of the manuscript lies in the development of the modeling approaches, as well as the evidence from the empirical dataset that the variance explained is improved.

Weaknesses:

The main weakness of the paper is that none of the models were tested on an in silico dataset where the ground truth is known. Therefore, it is unclear if their model actually retains any explanatory power.

Impact:

Genotype-phenotype mapping is a central point of genetics. However, the function is complex and unknown. Simple linear models can uncover some functional link between genes and their effects, but do so through severe oversimplification of the system. On the other hand, neural networks can, in principle, model the function perfectly, but it does so without easy interpretation. Gaussian regression is another approach that improves on linear regression, allowing better fitting of the data while allowing interpretation of the underlying alleles and their effects. This approach, now computable with state-of-the-art algorithms, will advance the field of genotype-to-phenotype associations.

Reviewer #1 (Public review):

Summary:

This paper presents an ambitious and technically impressive attempt to map how well humans can discriminate between colours across the entire isoluminant plane. The authors introduce a novel Wishart Process Psychophysical Model (WPPM) - a Bayesian method that estimates how visual noise varies across colour space. Using an adaptive sampling procedure, they then obtain a dense set of discrimination thresholds from relatively few trials, producing a smooth, continuous map of perceptual sensitivity. They validate their procedure by comparing actual and predicted thresholds at an independent set of sample points. The work is a valuable contribution to computational psychophysics and offers a promising framework for modelling other perceptual stimulus fields more generally.

Strengths:

The approach is elegant and well-described (I learned a lot!), and the data are of high quality. The writing throughout is clear, and the figures are clean (elegant in fact) and do a good job of explaining how the analysis was performed. The whole paper is tremendously thorough, and the technical appendices and attention to detail are impressive (for example, a huge amount of data about calibration, variability of the stim system over time, etc). This should be a touchstone for other papers that use calibrated colour stimuli.

Weaknesses:

Overall, the paper works as a general validation of the WPPM approach. Importantly, the authors validate the model for the particular stimuli that they use by testing model predictions against novel sample locations that were not part of the fitting procedure (Figure 2). The agreement is pretty good, and there is no overall bias (perhaps local bias?), but they do note a statistically-significant deviation in the shape of the threshold ellipses. The data also deviate significantly from historical measurements, and I think the paper would be considerably stronger with additional analyses to test the generality of its conclusions and to make clearer how they connect with classical colour vision research. In particular, three points could use some extra work:

(1) Smoothness prior.<br /> The WPPM assumes that perceptual noise changes smoothly across colour space, but the degree of smoothness (the eta parameter) must affect the results. I did not see an analysis of its effects - it seems to be fixed at 0.5 (line 650). The authors claim that because the confidence intervals of the MOCS and the model thresholds overlap (line 223), the smoothing is not a problem, but this might just be because the thresholds are noisy. A systematic analysis varying this parameter (or at least testing a few other values), and reporting both predictive accuracy and anisotropy magnitude, would clarify whether the model's smoothness assumption is permitting or suppressing genuine structure in the data. Is the gamma parameter also similarly important? In particular, does changing the underlying smoothness constraint alter the systematic deviation between the model and the MOCS thresholds? The authors have thought about this (of course! - line 224), but also note a discrepancy (line 238). I also wonder if it would be possible to do some analysis on the posterior, which might also show if there are some regions of color space where this matters more than others? The reason for doing this is, in part, motivated by the third point below - it's not clear how well the fits here agree with historical data.

(2) Comparison with simpler models. It would help to see whether the full WPPM is genuinely required. Clearly, the data (both here and from historical papers) require some sort of anisotropy in the fitting - the sensitivities decrease as the stimuli move away from the adaptation point. But it's >not< clear how much the fits benefit from the full parameterisation used here. Perhaps fits for a small hierarchy of simpler models - starting with isotropic Gaussian noise (as a sort of 'null baseline') and progressing to a few low-dimensional variants - would reveal how much predictive power is gained by adding spatially varying anisotropy. This would demonstrate that the model's complexity is justified by the data.

(3) Quantitative comparison to historical data. The paper currently compares its results to MacAdam, Krauskopf & Karl, and Danilova & Mollon only by visual inspection. It is hard to extract and scale actual data from historical papers, but from the quality of the plotting here, it looks like the authors have achieved this, and so quantitative comparisons are possible. The MacAdam data comparisons are pretty interesting - in particular, the orientations of the long axes of the threshold ellipses do not really seem to line up between the two datasets - and I thought that the orientation of those ellipses was a critical feature of the MacAdam data. Quantitative comparisons (perhaps overall correlations, which should be immune to scaling issues, axis-ratio, orientation, or RMS differences) would give concrete measures of the quality of the model. I know the authors spend a lot of time comparing to the CIE data, and this is great.... But re-expressing the fitted thresholds in CIE or DKL coordinates, and comparing them directly with classical datasets, would make the paper's claims of "agreement" much more convincing.

Overall, this is a creative and technically sophisticated paper that will be of broad interest to vision scientists. It is probably already a definitive methods paper showing how we can sample sensitivity accurately across colour space (and other visual stimulus spaces). But I think that until the comparison with historical datasets is made clear (and, for example, how the optimal smoothness parameters are estimated), it has slightly less to tell us about human colour vision. This might actually be fine - perhaps we just need the methods?

Related to this, I'd also note that the authors chose a very non-standard stimulus to perform these measurements with (a rendered 3D 'Greebley' blob). This does have the advantage of some sort of ecological validity. But it has the significant >disadvantage< that it is unlike all the other (much simpler) stimuli that have been used in the past - and this is likely to be one of the reasons why the current (fitted) data do not seem to sit in very good agreement with historical measurements.