Reviewer #1 (Public review):

The authors conducted a comprehensive benchmarking and evaluation of co-folding platforms, including AlphaFold3, Boltz-2, Chai-1, and the docking algorithm Dock3.7, which employs a physics-based scoring function that incorporates van der Waals interactions, electrostatics, and ligand desolvation energies. The system of interest was the SARS-CoV-2 NSP3 macrodomain (Mac1), an increasingly popular antiviral target, and the ligand sets comprised 557 unseen ligand poses (keeping the training for these co-folding platforms in mind). Additionally, the authors investigated whether the co-folding models could distinguish true ligands from non-binding small molecules. The study is thorough, with extensive statistical support and consensus across multiple metrics (chemoinformatics for quantifying ligand similarity and efficacy). The questions that the authors aim to address are whether the co-folding models struggle with memorization, whether they can distinguish between a true and a false binder, whether they replicate experimental binding affinities and efficacy, and how they compare to the physics-based docking algorithm (Dock3.7).

Strengths:

Overall, this is a scientifically solid paper.

The work is highly detailed and well executed, featuring thorough data analysis and statistical assessment.

Comments on revised version:

The authors have adequately addressed my concerns.

Reviewer #1 (Public review):

Summary:

This study revisits an important and controversial question in brain repair: whether NeuroD1 can convert brain immune cells into nerve cells in vivo. Using a virus-free genetic system, in vivo imaging, injury experiments, and single-cell profiling, the authors provide convincing evidence that NeuroD1-expressing cells do not become nerve cells under the tested conditions. Instead, these cells largely retain their original immune-cell identity, and some appear to undergo cellular stress or loss.

Strengths:

The main strength of the work is that it tests this question with a cleaner genetic strategy, avoiding some of the concerns associated with viral delivery and unintended cell labeling. Although the overall conclusion is consistent with the authors' previous work, the current study adds useful independent evidence, particularly through the virus-free fate-mapping system and live imaging in the brain.

Weaknesses:

The tested time window cannot fully exclude the possibility of very delayed or incomplete neuronal differentiation.

Overall, this is a useful and careful study that supports the conclusion that NeuroD1 does not drive brain immune cells to become nerve cells in the tested settings. It should be valuable for researchers studying brain repair, cell fate conversion, and genetic fate mapping, and it provides a clear caution against overinterpreting reprogramming results based only on viral labeling.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have addressed the comments raised in the previous round of review.]

Summary:

The current manuscript characterizes in detail the macrophages in the thymus. The authors identify two distinct populations of thymic macrophages and describe their surface marker expression and transcriptional signatures. They also explore their ontology and kinetics of settling and persistence in the thymus and find that the TIMD4+ macrophages are derived from embryonic progenitors and self-maintain in the thymus, while the TIMD4- macrophages are derived from monocytes. Most importantly, the authors test the functional importance of thymic macrophages for T cell development using an in vitro depletion system, from which they conclude that macrophages are important for one of the earliest selection steps in T cell development - the beta selection.

Strengths:

The authors use state-of-the-art techniques, such as multiple genetically modified mice, multi-color flow cytometry, single-cell RNA sequencing, genetic fate mapping, and fetal thymic organ culture (FTOC) combined with depletion. Their work is in good agreement with prior published studies on the subject, such as Tacke et al. (PMID: 26091486) and Zhou et al. (PMID: 36449334). In addition to reproducing prior knowledge, the authors uncover novel and unexpected facets of thymic macrophage biology, such as their SpiC independence and the fact that TIMD4- thymic macrophages depend on CCR2 (Tacke et al. have shown that the overall thymic macrophage compartment is normal in CCR2-/- mice). Most surprisingly, the authors claim that thymic macrophages control an early checkpoint in T cell development, the beta selection. This has not been reported before, as beta selection is usually considered a cell-autonomous process in thymocytes that does not require input from other cells.

Reviewer #1 (Public review):

Summary:

The authors provide in vivo and in vitro evidence for an interaction between AIRE and AID. This has implications for the dynamics of the germinal center response and autoimmunity related to the APSI disease.

Strengths:

Several both biochemical and in vivo experiments to show interaction and the function of AIREs regulation of AID activity in the GC response.

Comments on revised version.

I believe the manuscript is improved.

Reviewer #2 (Public review):

The manuscript reports protection of midlobular hepatocytes from APAP toxicity by activation of Atf4-CHOP (Ddit3)-mediated cell cycle arrest and stress response. The authors acknowledge that their finding is unexpected because CHOP typically induces cell death. Therefore, they functionally validate several aspects of the proposed Atf4-CHOP mechanism. Along these lines, the mitigation of APAP toxicity by AAV expression of Atf4 or Btg2, the latter identified as CHOP effector, is impressive. Whether Atf4 indeed acts through CHOP and whether midlobular hepatocytes are protected because of cell cycle arrest is less clear. These and other criticisms are described in the following.

Major points:

(1) Starting with the basics, one wonders why midlobular hepatocytes manage to mount a defensive response to APAP but PC hepatocytes don't. Is this because midlobular hepatocytes express the relevant Cyps (2e1 but also 1a2 and 3a11) at lower levels, which mitigates toxicity and buys them time? This would be supported by F2A but not by F3B, at least not for the most important Cyp2e1. A moderate difference is shown for Cyp1a2 expression in F3D but is that enough to explain the different fates? Or are additional post-transcriptional effects on these Cyps at work? In the re-revised manuscript, it was clarified in the legends of F2A and F3B that they visualize the same data in different ways.

(2) The evidence presented in support of cell cycle arrest of midlobular hepatocytes is not fully convincing: there is no overt difference in S and G2/M gene scores in F2F; the marker genes used for S phase and G1 to S progression in F2G are unusual. Along these lines, one wonders if spatial transcriptomics confirmed the Ki67 immunostaining results in F1 also for specific zones, not only overall, as shown in F2E? The discussion and abstract of the re-revised manuscript acknowledge that spatial transcriptomics did not independently confirm cell cycle arrest in midlobular hepatocytes.

(3) The authors conclude in line 364 that halting of proliferation by Btg2 favors survival, which raises the question of whether Btg2 knockout causes death in midlobular hepatocytes in F6K. Data addressing this question, that is, localization and extent of tissue necrosis and ALT levels after APAP, are missing. The efficiency of knockout of Btg2 is also not given. Additional Btg2 knockout data support its proposed role in the revised manuscript.

(4) Related to the previous question, the BTG2 immunostaining in F6F is not convincing when compared to F6D. One also wonders if it is necessary to apply APAP to find induction of BTG2 by AAV-Ddit3? The text of the re-revised manuscript reflects that issues with immunostaining did not allow for concluding that APAP promotes nuclear localization of BTG2.

(5) Related to the previous question, the proposed Atf4-Ddit3 axis is challenged by the lack of midlobular induction of Atf4 in the APAP scRNA-seq data published by another group presented in S4F and G. Further analysis of AAV-Atf4 samples generated for F5 could address if it is really Atf4 that acts on Ddit3 in APAP toxicity. The extended list of transcription factors (from 30 to 50) includes Atf4 but direct evidence for an interaction with Ddit3 is missing from the revised manuscript. The re-revised manuscript acknowledges this limitation by referring to a Atf4-Chop (Ddit3) axis and defining that as a functional pathway, not direct interaction of the proteins.

(6) Related to the previous question, the ATF4 immunostaining in F5A doesn't look convincing, with many brown pigments appearing to be outside of the nucleus, which was addressed by adding high-magnification images to F5A of the re-revised manuscript.

(7) It is not ruled out that AAV expression of Atf4 or Btg2 reduces hepatocyte sensitivity to APAP by affecting expression of the Cyps needed for activation. In other words, does AAV-Atf4 or AAV-Btg2 change the expression of any of the Cyps relevant to APAP in the 3 weeks before APAP application (F5B)? S5A of the revised manuscript rules out loss of Cyp2e1 expression as a confounding factor.

(8) It is laudable that the authors tried to extend their findings to human by using snRNA-seq data from a published study (line 391) but it is unclear why they didn't analyze all 10 patients in that study but instead focused on 2 and stated that this small sample number prevented drawing definitive conclusions and could therefore only be mentioned in the discussion. The re-revised manuscript includes analysis of the more substantial snRNA-seq dataset (in addition to the limited spatial transcriptomics) of patients with APAP toxicity in S4-3E, which confirms the midlobular expression of stress-response genes observed in mice but differs from mice in activation of proliferation genes, which may be due to sampling at later stages of the injury response as explained in the text.

Minor points:

(1) What is the functional classification of DEG in F2A based on? GO terms? Clarified in revised manuscript.

(2) The rationale for focusing on CHOP is not clear because Ddit3 is not shown in the spatial transcriptomics in F2A and not significant in F2B, contradicting what is stated in line 206. F2A includes Ddit3 in the revised manuscript and although it is not significant in S1G (former F2B), it is among the most highly expressed transcription factors in F4B and S3B.

(3) The term "redistribution" used in line 197 to describe expression of Cyp2e1 and other Cyps in the midlobular zone seems inappropriate considering that they just continue to be expressed there whereas PC hepatocytes are dying in F3B; the same applies to "Gene Expression Shift" in F3H. Clarified in revised manuscript.

Comments on revised version.

The revised manuscript addressed many of the original points and the re-revised manuscript clearly describes remaining uncertainties, which may be technical in nature such as lack of cell cycle arrest of midlobular hepatocytes in spatial transcriptomics or could be addressed in follow-up studies such as the nature of the interaction between Atf4 and CHOP.

Case#: Patient 11, male, age 53

DiseaseAssertion: STGD

FamilyInfo: diagnosis of autosomal recessive STGD based on the pedigree and clinical phenotype of fleck deposits with or without genetic testing

CasePresentingHPOs: HP:0000608, HP:0000007, HP:0030610, HP:0030500

CaseHPOFreeText: Macular degeneration. autosomal recessive, Photoreceptor outer segment loss on macular OCT, Yellow/white lesions of the macula

CaseNotHPOs: n/a

CaseNotHPOFreeText: n/a

Genotyping Method: n/a

PreviouslyPublished: n/a

Variant: NM_000350.3:c.5461-10T>C

ClinVar: NM_000350.3(ABCA4):c.5461-10T>C

CAID: CA220687

SupplementalData: composite mask analysis shown in figure 3 for patient 11, show large areas of matched degeneration and isolated IS/OS loss

Case#: Patient 14, female, age 42

DiseaseAssertion: STGD

FamilyInfo: diagnosis of autosomal recessive STGD based on the pedigree and clinical phenotype of fleck deposits with or without genetic testing

CasePresentingHPOs: HP:0000608, HP:0000007, HP:0030610, HP:0030500

CaseHPOFreeText: Macular degeneration. autosomal recessive, Photoreceptor outer segment loss on macular OCT, Yellow/white lesions of the macula

CaseNotHPOs: n/a

CaseNotHPOFreeText: n/a

Genotyping Method: n/a

PreviouslyPublished: n/a

Variant: Allele 1: NM_000350.3:c.4222T>C Allele 2: NM_000350.3:c.4918C>T

ClinVar:Allele 1: NM_000350.3(ABCA4):c.4222T>C (p.Trp1408Arg) Allele 2: NM_000350.3(ABCA4):c.4918C>T (p.Arg1640Trp)

CAID:Allele 1: CA227166 Allele 2: CA227253

SupplementalData: composite mask analysis shown in figure 3 for patient 14, show diffusely intact IS/OS and RPE with central area of mixed types of degeneration. Both patient 2 and 14 show foveal preservation of IS/OS and RPE

Reviewer #1 (Public review):

Summary:

This manuscript presents an innovative approach combining spatial miRNA profiling with computational analysis to characterize treatment-associated tumor states in a BRCA1-deficient breast cancer model.

Strengths:

(1) The integration of latent Dirichlet allocation-based topic modeling and Structural Similarity Index Measure maps analysis provides a potentially valuable framework for studying tumor heterogeneity.

(2) The innovation is high, both conceptually and on technical aspects. The work is a potentially important technical development as spatial transcriptomics for miRNAs is needed, and an interesting manuscript for a large spectrum of readers.

Weaknesses:

The method analysed a limited set of microRNAs, although all are functionally important and well published.

Case#: Female, age 44 years old

DiseaseAssertion: Discordant STGD phenotype

FamilyInfo: Information revolving the sister of this patient is given as well as they both have a discordant STGD phenotype. Additionally, it mentions that the parents each harboured a mutation but were asymptomatic/had normal examination results.

CasePresentingHPOs: HP:0001141, HP:0007401, HP:0030602

CaseHPOFreeText: At 23 central vision was deteriorating and patient had a VA of 6/36 in the right eye and 6/60 in the left. Through fundus photography, bilateral yellow/white flecks were found at the posterior pole. 12 years later, her VA was retested and it was 6/60 in both eyes. After autofluorescnece (AF) imaging was done, there was localized low signal at the macula found with abnromal foci. In 2008 her macular atrophy had enlarged and the flecks were less apparent.

CaseNotHPOs: N/a

CaseNotHPOFreeText: In this article there was not a phenotype presented that was normal.

CasePreviousTesting: It mentioned that there were two previously reported variants on the same allele detected in the siblings and one unique novel variant on the second allele for this patient. However, the testing they used was not listed, it just stated that the variants were found through sequencing. For this patient the variants were p.L541P/p.A1038V and p.R881C.

GenotypingMethod: Just mentioned sequencing and ABCA4 screening to look for two variants p.L541V and p.A1038V and a third novel variant p.R881C.

PreviouslyPublished: N/a

Variant: 1) NM_000350.3(ABCA4):c.1622T>C (p.Leu541Pro) 2) NM_000350.3(ABCA4):c.3113C>T (p.Ala1038Val) 3) N/a

ClinVar ID: 1) 99067 2) 7894 3) N/a

**CAID: ** 3) Because there was not a reference or alternate allele provided in this article I was unable to find a CAID for p.R881C.

gnomAD: 1) Highest minor allele frequency was 0.00017 (https://www.ncbi.nlm.nih.gov/clinvar/variation/99067/) 2) Highest minor allele frequency was 0.00188 (https://www.ncbi.nlm.nih.gov/clinvar/variation/7894/) 3) N/a

SupplementalData: Figure 1 had information regarding imaging and other testing done on the patient that is vital for phenotypic characterization. Also, it mentions a variant known as p.R881C, but was unable to find anything on ClinVar or gnomAD.

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 level.

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:

The major weakness 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 a 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), and more prefacing in the introduction of the overarching message and framework to the review.

Reviewer #1 (Public review):

Summary:

The authors identify and investigate a specific population of PVNOT neurons (oxytocin neurons of the paraventricular hypothalamus) that seem to be involved in both behavioral and autonomic thermoregulation. These cells are activated by social thermoregulatory behaviors, but can influence thermoregulation in both social and social contexts, specifically during transitions and when mice are at low core body temperature (Tb).

Comments on revised version.

The authors have addressed my concerns with clear and reasonable explanations and altered the text accordingly. This has improved the paper, but it still feels in some parts like a patchwork of nice work and discoveries stitched together. Further changes to format, analysis, and some experimental work could hugely improve the manuscript. I see that will surely come from future work, and this is the authors' choice.

Regarding the lack of behavioral analysis, I think it's fair for them to keep it for future studies.

I am happy to see they take and expand the opto inhibition suggestion. Again, that experiment would be nice for this paper, but not crucial.

Regarding discussing Raam et al 2026. It is good that they detail the practical decision of using females. What I meant was that, given that both papers study calcium dynamics around the time when mice engage in social thermoregulatory behaviour, they could have speculated on potential dmPFC-PVN functional connectivity, for example. Or the fact that Raam found that females showed fewer huddling behaviour than males at 5{degree sign}C (however, Vandendoren tested 15{degree sign}C, not 5{degree sign}C). Discussion of these features would be welcome, but maybe all of the current scope.

Overall, this is a very strong paper.

Reviewer #1 (Public review):

The manuscript from Zhu et al. identifies microbial riboflavin-derived MR1 ligands as potent pharmacological activators of human MAIT cells and provides evidence that MR1 ligand stimulation can enhance MAIT-mediated tumor killing across multiple solid tumor models. The study is conceptually interesting and supported by a broad combination of human primary samples, tumor cell lines, 3D models, SC transcriptomics, and xenograft experiments. Overall, the data largely support the central conclusion that MR1 ligand stimulation can strongly activate human MAIT cells and enhance anti-tumor cytotoxicity. However, the broader conclusions concerning endogenous MAIT mobilization, tumor specificity, and translational potential are not yet fully supported by the current data and should either be moderated or addressed with additional experiments.

Comments:

(1) The authors use one-way ANOVA throughout the manuscript, but this may not be appropriate for some analyses, particularly when multiple experimental factors are present and their interaction effects need to be considered. For example, Figure 3f appears to involve multiple factors, for which a two-way ANOVA may be more appropriate. Similar issues may apply to other panels.

(2) In Figure 3f, the authors show data from patients #1 and #2 and state that the experiment is representative of three experiments. What does the reported "n=4" represent in this figure?

(3) There appears to be a discrepancy between Figure 3f and Supplementary Figure 3b. The two panels appear to use the same treatment conditions and the same label, and both appear to use patient #1 samples, yet the reported values are different. Please clarify the experimental design and explain the reason for this discrepancy.

In addition, the gating strategy used to define live tumor cells should be clearly described in the figure legend and/or Methods. The authors define "live tumor cells" as MR1/5-OP-RU tetramer-CD45- cells. However, in primary liver tumor samples, the CD45-/tetramer- population may contain other non-hematopoietic cells, such as fibroblasts, and therefore may not exclusively represent tumor cells. The authors should clarify whether additional tumor-specific markers or other criteria were used. The gating strategies for the relevant flow cytometry experiments should be provided in the Supplementary figures.

(4) I have some concerns regarding the claims of "selective activation of anti-tumor inflammatory pathways rather than generalized cytokine release" and "avoiding induction of tumor-supportive mediators." The authors show that MAIT cells stimulated with 5-OP-RU can substantially reduce tumor cell viability. Therefore, the cellular composition of the co-culture is likely to change considerably during the assay, which may affect the absolute levels of cytokines and other soluble mediators detected. For example, reduced tumor cell numbers could lead to lower production of tumor-derived factors such as VEGF, potentially confounding the interpretation that these mediators are not induced by MAIT activation. The authors should consider whether cytokine measurements have been normalized to viable cell numbers or otherwise account for differences in tumor cell abundance.

(5) The in vivo tumor models may show substantial variability between independent experiments. Rather than presenting a single representative experiment, the authors should consider showing pooled data from all independent experiments, with the total number of mice clearly indicated.

(6) Why did the authors use an MR1-overexpressing tumor cell line for the in vivo studies rather than the parental cells with endogenous MR1 expression, together with MR1-KO cells as a negative control? The authors demonstrate that MR1 is detectable across multiple tumor cell lines and that endogenous MR1 expression is sufficient to support MAIT-mediated killing in vitro. Moreover, MR1 overexpression substantially enhances tumor cell susceptibility to MAIT-mediated killing. Therefore, it is unclear whether the strong therapeutic efficacy observed in vivo reflects physiologically relevant MR1 expression or is driven by artificially elevated MR1 expression. An in vivo comparison using parental and MR1-KO tumor cells would substantially strengthen the translational relevance and establish whether the therapeutic effect can be achieved at endogenous levels of MR1.

(7) How is tumor specificity of MAIT achieved ? The authors propose that MAIT-cell activation by MR1 ligands provides an antigen-independent approach for tumor targeting. However, MR1 is broadly expressed and is not tumor specific. While the relative sparing of T and B cells in Figure 7B provides some evidence of cell-type selectivity, this does not establish tumor versus normal tissue specificity. It remains unclear whether activated MAIT cells can discriminate tumor cells from other normal MR1-expressing cells and tissues. This raises an important question regarding the potential systemic toxicity of MAIT cells activated by systemic administration of 5-OP-RU. In particular, could other MR1-expressing cells be targeted when a large number of MAIT cells are simultaneously activated? The authors should consider assessing systemic toxicity in vivo, for example by examining serum ALT/AST levels and tissue pathology, and/or by evaluating the effects of MAIT + 5-OP-RU in tumor-free animals. At least, the potential specificity and safety limitations of systemic MR1 agonism should be discussed.

Reviewer #1 (Public review):

Summary:

Lee et al. investigate how parallel retinal pathways respond to a common loss of photoreceptor input. The authors induce partial cone loss in adult mice and compare the functional responses of sustained OFF alpha (sOFFa) and transient OFF alpha (tOFFa) ganglion cells, together with changes in their presynaptic circuits. Using targeted patch-clamp recordings, linear-nonlinear analyses, pharmacological dissection of inhibitory inputs, and quantitative synaptic imaging, they show that the two pathways do not respond uniformly to cone loss. tOFFa ganglion cells exhibit more extensive changes in spatiotemporal receptive fields than sOFFa ganglion cells, with contributions from excitatory transmission, presynaptic glycinergic inhibition, direct GABAergic and glycinergic inhibition, and intrinsic properties. At the same time, transformations between synaptic input and spike output partially preserve ganglion cell signaling despite the loss of cones.

Strengths:

This is a technically careful and high-quality study. The comparison of two well-defined ganglion cell types and their dominant bipolar-cell pathways provides an unusually detailed view of where circuit modifications arise following a shared perturbation. The combination of recordings at successive stages of signal processing, pharmacological manipulations, and synaptic imaging is a particular strength. The use of partial stimulation in control retina also helps distinguish the immediate consequence of reduced input from subsequent circuit changes. The resulting conclusion that common photoreceptor loss produces pathway-specific forms of remodeling rather than a uniform retinal response is interesting and well supported. The work adds to our understanding of the diversity and circuit specificity of responses to retinal degeneration.

Weaknesses:

The principal limitations concern the precision of some mechanistic interpretations rather than the central observation of pathway-specific remodeling. First, the framework used to classify effects as compensation or circuit change sometimes treats the absence of a statistically significant difference as evidence that two conditions are equivalent. Second, the numbers of animals and retinas contributing to the main physiological and anatomical comparisons are not consistently reported, making it difficult to evaluate the independence of measurements obtained from multiple cells, images, or synaptic puncta. Finally, the consequences of the observed remodeling for the visual signals carried by these pathways remain unclear. This is particularly relevant for tOFFa ganglion cells, which have been implicated in responses to looming or approaching dark objects. The altered temporal filtering, center-surround organization, and input-output transformation could preserve, degrade, or otherwise transform such signals. These issues qualify the mechanistic and functional interpretation but do not substantially weaken the main conclusion that the two pathways respond differently to partial cone loss.

Reviewer #1 (Public review):

In this manuscript, the authors explore whether GPCR signaling in astrocytes affects the production of TNF by astrocytes and, to a lesser extent, microglia. Unfortunately, the method used by the authors to acquire astrocyte-enriched cultures is known to result in meaningful rates of contamination by myeloid cells (microglia and others), oligodendrocyte-lineage cells, and neurons. Alternative methods of generating highly enriched astrocyte cultures, as well as purifying astrocytes with little to no neuronal or myeloid contamination across age and brain regions, have shown no evidence of TNF expression by astrocytes (Zhang et al., J Neurosci, 2014; Zhang et al., Neuron, 2016; Clarke et al., PNAS, 2018). In fact, the paper cited by the authors as demonstrating differences between human and rodent astrocytes found no evidence of TNF expression in immature or mature human astrocytes (Zhang et al., Neuron, 2016). The idea that the majority of the observed TNF transcriptomic signal, at least in culture, comes from myeloid or neuronal contamination also aligns with the authors' observation that myeloid-enriched cultures act identically to astrocyte-enriched cultures.

The authors also use a GFAP virus to drive GPCR signaling in astrocytes and neuronal progenitor cells in their cultures, but, given that these cultures are known to have meaningful contamination by other cell types, such signaling could be due to astrocyte → microglia/neuron signaling or other multicellular pathways that cannot be excluded. Similar concerns mean that we cannot assume the effect of DREADD activation of astrocytes in vivo (Figure 6) reflects a bulk change in TNF expression driven by astrocyte-specific changes rather than by multicellular signaling.

The most compelling evidence for their claim of astrocyte TNF expression comes from the human-induced astrocytes. However, their antibody staining is not sufficient to claim these cells are truly astrocyte-like. Antibody staining is highly prone to non-specificity, as highlighted by the fact that their ALDH1L1 antibody staining appears perfectly nuclear despite ALDH1L1 being a cytoplasmic protein.

To address both the purity concerns of the astrocyte-enriched cultures and the concerns about the astrocyte identity of the induced astrocytes, the authors should perform RNA sequencing. By profiling gene expression in these cultures at the genome-wide level, readers can truly assess the degree of contamination and thus the likelihood of the proposed mechanism (i.e., astrocyte-specific TNF production). Importantly, previous studies have suggested that very little neuronal and myeloid contamination is required to dramatically change cellular responses (Foo et al., Neuron, 2011; Liddelow et al., Nature, 2017).

Reviewer #1 (Public review):

Summary:

This manuscript describes a study examining MEG responses to participants free-viewing natural visual images. The vast majority of our knowledge of visual processing in the brain comes from studies where visual input is presented during fixation and the neural response is measured relative to stimulus onset. Even studies that include eye movements tend to either analyze the data relative to the start of each new fixation, or ignore saccades as noise. The current study simultaneously measures MEG and eye-tracking during active vision, and conducts a variety of analyses testing which of the saccade-related events produce the best alignment to the neural data. Five human participants viewed thousands of complex natural scene images while freely moving their eyes. MEG data were then binned as a function of saccade duration and aligned to different fixation and saccade events. M100 responses were better aligned with the preceding saccade onset than the current fixation onset. An additional analysis showed that when MEG signals were decomposed into independent components, the majority of the components showed more alignment and variance explained from saccade-related events (saccade onset, peak velocity, peak visual motion energy, and peak saccade curvature) compared to fixation-onset-defined events; the strongest performing of these factors was the time of peak saccade curvature. A final analysis compared the similarity of MEG topographies measured from stimulus onset (as would be standard in a static design) to those linked to peak saccade curvature and fixation onset, showing that stimulus onset responses were quite dissimilar to the active vision aligned events.

Strengths:

Overall, I think this is a fundamentally important research question, taking a novel and interesting approach. I very much like the idea behind this study. My enthusiasm is somewhat tempered by the weaknesses described below. However, at the very least I think this study would be valuable as a key launching point for future explorations, and for pushing the field into a much-needed new direction.

Weaknesses:

In its current state, the manuscript seems preliminary/incomplete in terms of both data analysis and engagement with the prior literature.

(1) In terms of the theoretical contribution, there are several potential contributions, some supported more by the data than others, and some more novel than others. In my rough assessment, from most general to most specific:<br /> a. Static vision is not the same as active vision. Supported somewhat by the analyses. Not novel (there are several studies both recent and older making this point, aside from the vaguely referenced sink-source sentence in the discussion), but this is still an understudied/underappreciated area.<br /> b. Neural responses are better aligned to saccade-related events than fixation-related events. Supported pretty compellingly by the analyses, and pretty novel. An important theoretical contribution.<br /> c. Peak saccade curvature is the saccade-related event explaining most variance. An extremely novel finding, but not well supported by the current data. At best, this seems a preliminary, exploratory hint of something to investigate further. It's intriguing but lacking in both empirical support (e.g. is this even consistent across subjects?) and theoretical discussion (what would it mean / what would be the mechanisms of such a link?).

(2) There is a small number of subjects, and for several main analyses, the data are pooled across them. Small N's can be reasonable in cases where there is large data for each subject. But it is standard to show the subjects individually to confirm reliability. Figure 1 does this nicely, but then for the main analyses examining the ICs and variance explained by the different saccade-related events (Figures 2C-F), the data were pooled across subjects. Strong conclusions are being drawn from the pooled data (e.g. highest proportion of explained variance from the peak curvature event), but it's unclear if this is consistent across subjects or potentially dominated by 1 or 2 subjects. Indeed, when the "best" score is presented for each participant (Fig 2E), only 2 of the 5 subjects showed peak saccade curvature as the best. And these results look strikingly different across subjects (P5 doesn't even look anything like an M100 response).

(3) Several parts of the results and methods are hard to follow. I had to read the paper several times to understand it. In many cases, the methods text doesn't even link with the results (e.g. the term "M100" is not anywhere in the methods).

(4) Several parts of the results felt under-explored:<br /> a) The analysis in Figure 1E is very interesting, but it's not reported in enough detail. There are no quantitative results here, just a visual of a distribution and a description of it being broad. I would be particularly interested in seeing the mean alpha reported for the best sensor for each participant (i.e. linking with the rest of that figure).<br /> b) How consistent is the timepoint of peak saccade curvature? It appears to increase with saccade duration, but is it a fixed / consistent percentage of saccade duration? If not, what factors cause it to vary? How similar is this timepoint to the optimal alpha from the analysis in Figure 1E? Would binning the data based on peak saccade curvature instead of saccade duration produce even better alignments for Figure 1D?<br /> c) For the Figure 3 analysis comparing static scene-onset responses to the saccade- and fixation-related responses: I am wondering how much of the difference is actual saccade-related activity vs a true difference in visual processing. It seems the interpretation is that "visual processing", when measured in static contexts, is very different from when measured in active contexts. But what's being compared is not visual processing specifically, but the entire whole-brain MEG response. I think in order to make this conclusion more compelling, there needs to be some way of filtering out these influences. E.g., a study that presents a simulated saccade condition, where a participant keeps their eyes fixated but views snapshots of the visual scene mimicking the exact saccade sequence of another subject.

(5) The discussion felt too thin. See some specific points below. In general, combined with the fact that the results were often hard to follow and sparse, I was left with the impression that this report was being forced into a shorter format than necessary.

(6) How do microsaccades and other types of eye movements fit into this story?

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors were responsive to the previous comments and, where needed, edited the manuscript to improve clarity around assumptions and to highlight specific sensitivity analyses.]

Summary:

This manuscript seeks to make use of information about Ct values from PCR testing of mosquito pools for West Nile virus infection to make inferences about mosquito prevalence and West Nile risk. It does so through analysis of empirical data and simulated data with a realistic agent-based model.

Strengths:

This work is conceptually innovative for mosquito-borne viruses, building on ideas developed primarily during work on SARS-CoV-2. Exploring this topic is worthwhile regardless of the outcome. The use of data, testing in multiple labs, and complementarity of modeling and empirical data analysis are all strengths of the approach.

Weaknesses:

Some of the primary weaknesses include a dependence of the results on relatively narrow model assumptions, and lack of compelling improvement over existing methods. None of these are fatal flaws but are instead modest weaknesses that limit the potential of or excitement about the method.

Reviewer #1 (Public review):

The authors attempted to compare calcium binding properties of wildtype calreticulin with calreticulin deletion mutant (CRTDel52) associated with myeloproliferative neoplasms.

The researchers conducted their study using advanced techniques They found almost no difference in calcium binding between the two proteins and observed no impact on calcium signaling, specifically store-operated calcium entry (SOCE). The study also noted an increase in ER luminal calcium-binding chaperone proteins. Surprisingly, the authors selected flow cytometry as a technique for measurements of ER luminal calcium. Considering limitations of this approach it would be better to use alternative approaches. This is particularly important as previous reports, using cells from MPN patients, indicate reduced ER luminal calcium and effects on SOCE (Blood, 2020). This issue matters because earlier research with MPN patient cells reported reduced ER luminal calcium levels and altered SOCE (Blood, 2020). How do the authors explain the difference between their results and previous findings about lower ER luminal calcium and changed SOCE in MPN patient cells expressing CRTDel52? Other studies have found that unfolded protein responses are activated in MPN cells with CRTDel52 calreticulin (see Blood, 2021), and increased UPR could account for higher levels of some ER resident calcium-binding proteins observed here. Overall, it remains unclear how this work improves our understanding of MPN or clarifies calreticulin's role in MPN pathophysiology.

Comments on revised version.

The authors have addressed the points raised in the original review. However, given the absence of significant differences between the wild-type and mutant proteins, the relevance of this work to MPN pathology remains unclear. The novelty of the study is limited, as calcium has generally not been considered a significant factor in MPN pathology associated with mutant calreticulin.

Reviewer #1 (Public review):

This manuscript describes a multi-modal study of associative learning and memory in humans that combines scalp EEG, pupillometry and behavioral analysis to explore the construct of mnemonic prediction errors (MPEs), in terms of their relationship to attention and cognitive control. Across two pooled studies, participants performed associative memory tasks in which they learned the relationship between a cue word (action verb) and subsequent picture (animate or inanimate) with a strong vs. weak (4 or 1 repetitions) encoding manipulation. At test, participants were encouraged to generate a prediction following the cue word to determine whether the subsequently presented picture was a match or mismatch. The timecourse of pupillary responses during match decisions were decomposed using temporal principal components analysis, which identified 6 distinct and overlapping processes. Some of the components (PC3/PC4) exhibited sensitivity to both the strength and mismatch conditions, as well as behavior (both RT and accuracy) and retrieval success on the subsequent trial. Furthermore, relationships were also observed between pupillary responses (specifically for PC4) and both frontal theta and posterior alpha power measures obtained from scalp EEG in Experiment 2, as well as for frontal theta and subsequent learning from mismatch stimuli (assessed using subsequent memory findings from a surprise recognition test). The authors suggest the findings indicate that MPEs elicit changes in attention, arousal and cognitive control which impact subsequent learning.

Strengths:

This manuscript has many strengths, including a clever study design, thoughtful integration of multiple neurocognitive measures, and a set of rigorous and technically sophisticated analyses, which reveal a large set of relationships among the measures and behavior. The findings demonstrating brain/physiology-behavior relationships are particularly important, in that they point to potential functional consequences of MPEs.\

Reviewer #1 (Public review):

This manuscript is very interesting and timely. By introducing the critical effects of desolvation barriers and solvent (water)-separated minima into the implicit-solvent potentials (of mean force, PMFs) for coarse-grained molecular dynamics simulations of biomolecular liquid-liquid phase separation (LLPS), this work fills a gap that should be apparent to researchers of protein folding in the past couple of decades but has so far escaped deserved attention such that these basic features of aqueous solvation have seldom, though not never, been invoked in recent studies of biomolecular condensates. Although the present paper deals almost exclusively with homopolymers, this work can be a foundation for the future development of a new, more physical coarse-grained interaction schemes for simulating amino acid sequence-dependent effects, which I presume is the authors' ongoing or next endeavor. The results presented in this manuscript are highly valuable.

However, there is room for improvement in the authors' description of (i) the broader impact of effects of desolvation barrier and solvent-separated minimum in the thermodynamics of biomolecular condensates, especially with regard to the ramifications on hydrostatic pressure-dependent effects; (ii) the physical implication of using a 20-parameter hydropathy scale rather than a 210-parameter pairwise amino acid interaction scheme; and (iii) temperature-dependent effects, including the authors' discussion of "enthalpic" and "entropic" contributions. In all these aspects, the authors' discussion should be put in a more comprehensive context of the existing literature. At a few other places, description of the methods and results should be clarified as well.

Comments on revised version

The authors have thoroughly and adequately addressed all my previous concerns and suggestions. The manuscript is now significantly improved in terms of clarity and proper placement in the context of prior works on desolvation effects in protein conformations.

Reviewer #1 (Public review):

This paper reports a previously unrecognized mechanism by which platelets compact fibrin fibers during clot retraction. Rather than simply pulling on fibers, the authors propose that platelets generate swirling motions that wind and loop fibrin into dense structures.

While the results are intriguing, the underlying physical mechanism remains unexplained. In particular, it is unclear how platelets generate swirling motion capable of inducing fibrin coiling, especially when suspended in 3d fibrin mesh. This raises concerns about the conclusions. Also, does fibrin have inherent chirality or structural asymmetry that could promote coiling independently of platelet activity? Furthermore, platelet retraction typically involves platelet aggregation rather than isolated cells, and it is unclear how fibrin coiling would proceed in clustered platelets.

Comments on revised version.

The authors have significantly improved the manuscript and enhanced the presentation of the results. In my opinion, the physical mechanism responsible for the compaction of fibers into the coiled structures caging platelets remains somewhat elusive. Nevertheless, I find the results convincing, and I believe the study will make a valuable contribution to the field.

Reviewer #1 (Public review):

Summary:

The authors combine discriminative auditory fear conditioning with longitudinal in vivo calcium imaging to ask how prelimbic (PL) representations of learned and generalized threat evolve across recent and remote memory time points. Using two different CS+ frequencies and a no-shock control group, they report that PL population activity tracks graded behavioral generalization, that population similarity is highest for tones eliciting strong threat responding, and that distinct subnetworks can be identified that appear to encode tone-specific sensory features versus learned threat-related response structure.

To my knowledge, this may be the first study to comprehensively examine neural encoding of fear generalization in prelimbic cortex (PL). The manuscript is ambitious and technically interesting, and several aspects are potentially important. In particular, the suggestion that neurons showing graded, learning-related response patterns become selectively stabilized over time is intriguing. The inclusion of two CS+ training conditions and a no-shock control also strengthens the case that at least some of the reported effects are related to associative learning rather than simple sensory differences. However, in its current form, the manuscript does not yet fully support the strength of the conceptual claims. Several issues limit confidence in the interpretation, including the possibility that repeated testing itself contributes to changes across days, uncertainty about the relationship between neural activity and freezing behavior, limited quantitative documentation of longitudinal cell registration, and a number of problems in figure clarity and statistical framing. Overall, the study contains promising observations, but the claims should be narrowed, and several analyses or controls would be needed to fully support the proposed framework.

Comments on revised version.

The authors have addressed my previous concerns well, and the revised manuscript is substantially improved. In particular, the additional analyses strengthen the conclusion that prelimbic cortical activity reflects learned threat value rather than simply freezing behavior, while the revised framing and additional controls clarify the interpretation of the longitudinal neural dynamics. This paper represents an important contribution to our understanding of the neural mechanisms supporting aversive learning, memory, and generalization.

Reviewer #1 (Public review):

Summary:

This paper characterises the physiological and computational underpinnings of the accumulation of intermittent glimpses of sensory evidence, with a focus on the centroparietal positivity and motor beta lateralization. The main finding is that the centroparietal positivity builds up during evidence accumulation but falls back to baseline during gaps, while motor beta lateralization maintains a continuous a sustained representation throughout the gap and until response.

Strengths:

- Elegant combination of electroencephalography and computational modelling.<br /> - Innovative task design, including parametric manipulation of gap duration.<br /> - The authors describe results of two separate experiments, with very similar results, in effect providing an internal replication.

Weaknesses:

- In their response to the reviewers, the authors now include a figure illustrating the relationship between the centroparietal positivity and motor beta lateralisation. However, in the absence of statistical analyses, it remains difficult to draw firm conclusions about this relationship.

- The paper does not provide an exhaustive characterisation across sensors and frequency bands. However, as the data are publicly available, these questions could be addressed in future work.

Reviewer #1 (Public review):

This work by Antonnen et al. was triggered by claims of auditory-mediated effects on altricial avian embryos which were published without any direct evidence that the relevant parental vocalizations were actually heard. I agree with Anttonen et al. that, based on the available evidence about avian auditory development, those claims are highly speculative and therefore necessitate more direct experimental verification.

Attonen et al. have embarked on a comprehensive series of experiments to

(1) Better characterize acoustically the relevant parental vocalizations (heat whistles; in a separate preprint, not reviewed here)

(2) Characterize the auditory sensitivity of zebra finches at various stages of their posthatching development. Despite the long-standing importance of the zebra finch as a songbird model in neuroethology of learned vocalizations, the auditory development of the species had not been studied so far.

(3) Explore an alternative hypothesis of how the parental vocalizations might be perceived.

The principal method used here is the non-invasive recording of ABR (auditory brainstem response), a standard neurophysiological method in auditory research. The click-evoked ABR provides a quick and objective assessment of basic hearing sensitivity that does not require animal training. Weaknesses of the technique include its limited frequency specificity and low signal-to-noise ratio. The authors are experienced with ABR measurements and well aware of those issues. ABR responses in zebra finches are shown to gradually appear during the first week posthatching and to mature in subsequent weeks, consistent with the auditory development in other altricial bird species studied previously. When matching the acoustic properties of parental heat whistles and auditory sensitivities, hearing of the parental heat whistles by zebra finch hatchlings was convincingly excluded. Although not directly measured, this also convincingly extrapolates to zebra finch embryos. Finally, the authors tested the hypothesis that parental heat whistles could induce perceptible vibrations of the egg and thus stimulate the embryo via a different modality. The method used here was laser doppler vibrometry, an appropriate, state-of-the-art technique that the authors also have proven experience with. The induced vibrations were shown to be several orders of magnitude below known vibrotactile sensitivities in mammals and birds. Thus, although zebra finch vibrotactile thresholds were not obtained directly, the hypothesis of vibrotactile perception of parental heat whistles by zebra finch embryos could also be rejected convincingly.

In summary, even when considering some weaknesses of the techniques (which the authors are aware of), the conclusions of the paper are well supported: Auditory and/or vibration perception of parental heat whistles can be excluded as an explanation for previous reports of developmental programming for high ambient temperatures. As a constructive suggestion towards resolving the apparent paradox, the authors recommend to repeat some of the crucial, previous playback experiments at lower sound levels that better match the natural parental vocalizations.

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors investigate the mechanisms underlying macrostructure formation in a freshwater filamentous cyanobacterium strain, F. draycotensis, focusing on how its ability to aggregate and form these structures depends on the physical properties of the filaments. Using experimental observations, they demonstrate that the cyanobacterium actively captures and surrounds particles, a process driven primarily by gliding motility.

To explain these physical dynamics, the authors present a 3D model indicating that particle collection relies on filament length, as well as a specific mechanical response, namely, filament buckling and the subsequent formation of loops of bundles of filaments. While the authors have previously documented the buckling and looping characteristics of this strain, this study provides new insight by demonstrating that these physical phenomena are essential for particle capture and collection.

Strengths:

This manuscript benefits from a rigorous and detailed quantitative analysis of video recordings, which clearly documents the motility, buckling behaviour, and particle collection dynamics of the filaments.

The authors effectively validate their hypothesis by using a naturally shorter filamentous strain, which fails to collect particles, suggesting that filament length is indeed a critical parameter.

To further confirm the length dependency within the same species, the authors experimentally generated shorter filaments of F. draycotensis. The fact that these shortened filaments also lose the capacity to collect particles provides strong evidence supporting their proposed mechanism.

Weaknesses:

There is a conceptual concern. The authors linked the specific physical properties of this strain to evolutionary data, highlighting that the studied lineages diverged approximately two billion years ago. This creates a misleading impression that particle collection via flexible looping filaments is a recent evolutionary adaptation. However, particle collection has been observed in other cyanobacteria, such as Trichodesmium, which features short, rigid filaments. Therefore, the term "emerging" does not seem appropriate for the title and text. The capacity to collect particles in the studied strain F. draycotensis appears to be primarily a function of physical characteristics (filament length and flexibility) rather than evolutionary age. Any cyanobacterial strain possessing similar physical properties is likely to exhibit comparable behaviour, rendering the evolutionary timeframe largely irrelevant to the core mechanism. In addition, the phylogenetic tree presented in Figure S5 does not reflect the current consensus on cyanobacterial evolution and systematics and does not align with modern phylogenomic frameworks (see, for example, Strunecky et al., 2023 https://doi.org/10.1111/jpy.13304). There is also no such order Cyanobacteriales, which has been mentioned in a few older publications but is clearly outdated.

Another concern is that the authors nearly completely ignore the role of type IV pili in the gliding motility of cyanobacteria, including filamentous strains. For a long time, there was a misconception that the gliding motility of cyanobacteria was due to slime protrusion. Slime plays a role in this process. However, several studies have shown that filamentous strains also use type IV pili to glide on surfaces. The authors should discuss this and include it in their model. In addition, the authors concluded that gliding motility is responsible for particle collection by Fluctiforma draycotensis. Although I believe that their conclusion is correct, there might be several limitations to the experiments which allow for other reasons to be considered. Their conclusions were based on the use of a non-motile strain and an unspecified community without the motile Fluctiforma draycotensis strain. The problem I see here is that it is not clear why this strain is not motile; it could be because of the lack of type IV pili, mutations which alter their functionality, defects in slime secretion, any other mutation (e.g. in chemoreceptors), cellular structure, metabolism, or combinations of these. Furthermore, it is possible that the community changes its composition and behaviour when it lives without the cyanobacterium with a rich carbon source (glucose) or with a non-motile cyanobacterium which may not secrete slime or, for example, a signalling component which controls behaviour of the bacteria in the community. For that reason, the authors should be more cautious with their conclusion that solely motility behaviour of Fluctiforma draycotensis is responsible for particle collection. Additional factors might be responsible for these effects.

Reviewer #1 (Public review):

In this study, Telias et al. identify the P2X7 receptor as a key component of retinoic acid signaling-mediated remodeling in the degenerating rd1 retina. The authors report increased P2X7R expression in the inner retina following photoreceptor loss and link P2X7R signaling to retinal ganglion cell hyperactivity, membrane hyperpermeability, and altered calcium homeostasis. Genetic deletion of p2rx7 abolishes ganglion cell hyperpermeability and reduces several features of pathological remodeling in the rd1 retina. The study provides valuable mechanistic insight into retinal remodeling following photoreceptor degeneration. However, several issues currently limit the strength of the conclusions. In particular, key comparisons are confounded by differences in genetic background, the cellular source of P2X7R expression is not sufficiently resolved, and several experiments require additional controls and more cautious interpretation.

Major comments:

(1) The Methods state that C57BL/6J mice were used as wild-type controls, whereas rd1 mice were maintained on a C3H/HeJ background, and the rd1-p2rx7 knockout line is on a mixed background. Direct comparisons among these groups are therefore potentially confounded by strain-specific differences. Authors should use littermate rd1 het mice as healthy controls in all their experiments.

(2) The authors do not demonstrate P2X7R expression in RGCs. The P2X7R signal in the rd1 retina shown in Figure 1B appears saturated and is therefore difficult to compare directly with the WT image in Figure 1A. Furthermore, Figure 1E indicates that overall P2X7R fluorescence in the GCL is not significantly different between WT and rd1 retinas, whereas the representative images appear to suggest a marked increase. The authors should provide images acquired and displayed under identical settings and consider including retinal whole-mount staining with an RGC-specific marker. P2X7R abundance should then be quantified specifically within identified RGCs in both healthy and rd1 retinas. As mentioned above, het rd1 mice should be included. As an additional control, the authors also should include the staining of rd1 p2x7r KO retinas.

(3) Does the increase in P2X7R abundance correlate with photoreceptor loss? Please include staining of younger rd1 mice along with het rd1 littermates.

(4) In Figure 1G-H, the description of the reporter is internally inconsistent: the Results refer to an artificial mini-Pax6 promoter, whereas the Figure 1 legend describes the Ple344 neuronal mini-promoter derived from Tubb3. Please clarify which promoter is used and what cell population the ECFP signal labels. Figure 1G should explain the function of each reporter element and how RAR activity is inferred. Figure 1H should include an RGC marker such as RBPMS and provide quantitative analysis of RBPMS-positive, reporter-positive, and Yo-Pro-positive cells. Additional controls are needed to exclude effects of viral transduction or retinal inflammation on Yo-Pro uptake. They should include rd1 retinas without AAV, rd1 het retinas with and without the reporter AAV.

(5) In addition, lines 143-144 state that two experiments were performed, but only one is described in that paragraph; the text should be reorganized or clarified.

(6) Yo-Pro-1-positive cell density in rd1 mice between Figure 1H and Figure 2D is different. Why?

(7) Constitutive deletion of p2rx7 may cause developmental or compensatory changes that could contribute to the observed phenotype in Figures 2 and 3. Additional controls are therefore needed to distinguish acute effects of p2rx7 loss from developmental consequences. The authors should assess whether p2rx7 deletion alters retinal cell-type composition, including RGC density, or affects the timing or extent of photoreceptor degeneration. Perform a rescue experiment to determine whether overexpression of p2rx7 in the knockout background restores the phenotype. For all experiments, het rd1 control mice should be included.

(8) Figure 3D and E experiments should include control AAV expression such as GFP.

(9) Figure 5 experiments should include control rd1 het mice.

Reviewer #1 (Public review):

Summary:

This paper suggests an alternative model for the function of the multiple demand network. Specifically, its role is not necessarily to sustain cognitive control and maintain task sets, but rather to "stabilize task-appropriate modes of thought". Evidence for this would be that the MD network is responsible for maintaining a particular thought state during a task. To investigate this, they use a combination of fMRI brain data during a set of 14 tasks and experience sampling in a different set of participants performing the same tasks. Using dimensionality reduction, they reduced the space of task features (and brain systems) to a smaller, more tractable set of dimensions and examined whether stability in specific thought components was related to recruitment of specific brain systems during the task.

Strengths:

Overall, this is an interesting and creative study with strong analytic methods that do a good job accounting for confounds or alternative explanations (save one I mention below).

Weaknesses:

I have mostly minor comments and one major one.

Major:

The principal finding is that tasks that evoke brain activity patterns that resemble the MDN also had more stable "deliberate task focus" features. While all the analysis and controls are impressive, I'm still left with the sense that this is reifying something we already know or that alternative explanations are more parsimonious than the MDN induces stability in "thought".

I thought an example might be easiest to understand my point: If I gave participants a series of working-memory-related tasks. Some of these are the crème de la crème, and others are sloppy and poorly designed. Then suppose I assess them on measures related to deliberate thought; I'd likely find the "good" tasks elicit more consistent/reliable deliberate task focus. I also would bet money that these same tasks would evoke canonical WM and MDN activity patterns more than the sloppy tasks. This isn't evidence of MDN stabilizing patterns, but rather that both stable thought patterns and activity in the MDN share a common cause. Thus, I would predict that with my thought experiment, your analysis would find the same result. So it strikes me as a strong alternative possibility for these results is that tasks that reliably evoke deliberate task focus are also those that more strongly and consistently evoke working-memory demand (i.e., Figure 2 shows that they are primarily driven by the executive/WM tasks).

Minor:

(1) The PCA was reviewed previously, and I don't want to relitigate a prior method, but I had one minor concern. It would be useful to know how the principal results are based merely on the "deliberate" or "focus" items specifically. Is the thought space necessary, or do the individual items that likely drive the "deliberate task focus" PC essentially replicate the main result?

(2) I struggled with the motivation for projecting the task data onto a resting state FC analysis that focuses on "gradients". I understand that with 14 tasks activation maps, data reduction is a good thing. But as someone who isn't as enmeshed in this work, I didn't follow why this specific "atlas" was chosen over any other (parcellations, meta-analytic maps of canonical networks, etc.). Maybe a brief sentence saying why this and not that would help readers who find themselves in my shoes.

Reviewer #1 (Public review):

Summary:

This manuscript reports on simultaneous neural recordings in the olfactory tubercle (OTu) and ventral tegmental area in head-fixed mice performing a simple go-nogo odor-guided reversal task. In the task, there were 3 odors that predicted lick-spout water at 0%, 50%, and 100% probability, with 0% and 100% odors reversing at some point each session. The authors fitted this neural data to a value function approximator in which reward prediction errors fed back onto state representations, allowing the optimal set of representations to be learned. They found that model predictions of adjustments to state representations were correlated with trial-by-trial changes in OTu neural activity, from which the authors conclude that such a system, with dopaminergic errors feeding back onto OTu representations of states, which then generate reward predictions, is biologically plausible.

Strengths:

This is a novel and creative modeling approach that has important implications. It seems to be showing the biological plausibility of a model that can learn state representations rather than relying on a fixed set of states that are programmed into the model. This makes tremendous sense, because the real world is much less well-defined than the kinds of tasks conventionally used by neuroscientists to probe reinforcement learning. As such, it is an important demonstration.

Weaknesses:

The task used in this study is quite simple in its state space, and in particular in how it maps sensory stimuli (odors) onto states, such that the task would seem not to require a system that can learn state representations, or at least that it would not be ideal for testing such a model. This mismatch raises some questions about why this model would perform as well as it appears to be doing here.

The model has two updating functions, both using dopaminergic RPE's. One of these maps raw stimuli to state representations using a parameter termed theta; the second maps state representations to a value prediction, using a parameter termed w. The interaction of these two updating functions seems to be giving the model its interesting characteristics. But it is critical to test what the first of these updates is doing in this model, given that odor stimuli appear to map straightforwardly onto states. For example, one might test the effect of ablating this part of the model, leaving only updates of what the authors term w. Relatedly, one might test the extent to which OTu neurons show simple odor selectivity before and after reversals, asking whether these neurons reflect state representations in this model merely by being selective for a particular odor, or if they develop a more complex kind of responsiveness.<br /> The authors compare the full model, which uses a gradient descent update, to a series of alternatives. The fact that the full model performs significantly better than any of the alternatives leads to the conclusion that the brain is using something like this model in this task. But these alternative models are all reduced or simplified versions of the primary model. This suggests that the full model is the best version within the basic framework posed by the authors. But to draw the conclusion that this model is capturing what is occurring in the brain, one would want to test how this model would perform compared to a different class of model, in particular one that assumes a fixed set of states.<br /> A second weakness of the paper is that the authors do not show the behavioral or raw neural data, which would be important to summarize for the sake of transparency and to help readers get an intuitive sense of what is going on in the task and why the model performs as well as it does. One essential issue is: how much training do mice receive before neural data used in the analysis are collected? Do mice get pre-exposure to contingency reversals before analyzed neural data is collected? Relatedly, how quickly (i.e., in how many trials) do mice show behavioral evidence of having learned initial contingencies and then reversed contingencies? What is the behavioral criterion? With regard to the number of trials mice take to learn the reversals, this can change enormously over training, and such changes could have a big effect on how the model performs. Regarding the neural data, one would want to show some measure of odor selectivity of SPN's and DAN's and how each population responds to delivery and omission of reward in different conditions.

Reviewer #2 (Public review):

[Editors' note: The Reviewing Editor has assessed the revised article without further input from the original reviewers. The Reviewing Editor noted the authors further addressed a methodological concern, and eLife's Assessment remains unchanged from the previous review.]

Summary:

The study aimed to assess the associations between meteorological drivers and influenza is important although not new. The authors used 6 years of surveillance data and deep learning models, combining distributed lag non-linear models (DLNM) with Bayesian-optimized LSTM neural networks for predictive modeling. The key interest in this area is to explore the subtropical locations, where influenza is less common and circulates year-round. The authors further claimed that such an association could be able to provide an early warning in the community.

Strengths:

Study design based on a prospective cohort to analyse the data for retrospective outcomes.

Reviewer #2 (Public review):

Summary:

This manuscript presents a sophisticated investigation into the mechanisms by which different inhibitor classes affect the SARS-CoV-2 main protease (Mpro), a pivotal antiviral drug target. This study reveals that effective inhibition can be achieved by modulating the stabilization of the essential dimeric state. It also indicates the dimer interface could be a druggable allosteric site, which may offer a strategy for developing broad-spectrum anticoronaviral agents.

Strengths:

The identification of dimer interface stabilization/destabilization as distinct inhibitory mechanisms and the discovery of C300 as a potential allosteric site for ebselen are important contributions to the field. The experimental approach is modern, multi-faceted, and generally well-executed.

Comments on latest version:

All of my concerns have been adequately addressed.

Reviewer #1 (Public review):

Summary:

In this report, the authors investigate the mechanisms underlying large-scale genomic amplification (DIGA) induced by genome-wide DNA double-strand breaks (DSBs), such as those generated by ionizing radiation (IR).

Strengths:

The authors demonstrate that DSB-induced DIGA does not require origin re-licensing but is dependent on proteins involved in break-induced replication (BIR). This finding represents a major strength of the study, as it reveals a previously unrecognized mechanism of DSB-induced genomic amplification. Additional strengths include the demonstration that DIGA is promoted by DNA end resection and suppressed by the 53BP1-RIF1-shieldin pathway. The authors also show that SET8 and SUV4-20H1 have opposing effects on CDT1 overexpression-induced and IR-induced re-replication. Furthermore, the finding that the extent of DIGA in cancer cells correlates with sensitivity to IR has potential implications for cancer treatment.

Weaknesses:

However, more comprehensive studies are needed to strengthen the conclusions. Although IR- or DSB-induced DIGA was observed in multiple cancer cell lines, the overall mechanisms underlying why DIGA is more pronounced in certain cell lines but not others remain unclear. Beyond p53 status, additional factors that determine DIGA susceptibility should be investigated. In addition, the evidence that DIGA-associated DNA synthesis occurs within the same cell cycle is not yet sufficient. For instance, a time-course experiment (EdU versus DAPI) should be performed after IR to determine when DIGA initiates relative to normal S-phase DNA replication. A parallel analysis of re-replication at different time points following MLN4924 treatment would provide a useful comparison. Cyclin B and phospho-histone H3 (Ser10) levels should be monitored to define cell cycle stage. Additional evidence supporting a BIR-dependent mechanism, such as demonstrating conservative DNA synthesis and mapping DIGA sites following AsiSI-induced DSBs, would be needed.

Overall, this study provides new insights into the mechanisms driving genome-wide amplification following DSB formation. Additional mechanistic studies will further strengthen the conclusions and broaden the impact of this work.

Reviewer #1 (Public review):

Summary:

Dong et al. present an in-depth analysis of mutant phenotypes of the Rab GTPases Rab5, Rab7, and Rab11 in Drosophila second-order olfactory neuron development. These three Rab GTPases are amongst the best-characterized Rab GTPases in eukaryotes and have been associated with major roles in early endosomes, late endosomes, and recycling endosomes, respectively. All three have been investigated in Drosophila neurons before; however, this study provides the most detailed characterization and comparison of mutant phenotypes for axonal and dendritic development of fly projection neurons to date. In addition, the authors provide excellent high-resolution data on the distribution of each of the three Rabs in developmental analyses.

Strengths:

The strength of the work lies in the detailed characterization and comparison of the different Rab mutants on projection neuron development, with clear differences for the three Rabs and by inference for the early, late, and recycling endosomal functions executed by each.

Comments on revised version.

The authors conducted extensive revision experiments, especially to characterize developmental defects. Efforts to identify cargoes were not successful. The evidence is now convincing.

Reviewer #1 (Public review):

Summary:

The authors sequenced 888 individuals from the 1000 Genomes Project using the Oxford Nanopore long-read sequencing method to achieve highly sensitive, genome-wide detection of structural variants (SVs) at the population level. They conducted solid benchmarking of SV calling and systematically characterized the identified SVs. While short-read sequencing methods, including those used in the 1000 Genomes Project, have been widely applied, they exhibit high accuracy in detecting single nucleotide variants (SNVs) and small insertions and deletions but have limited sensitivity for SV detection. This study significantly enhances SV detection capabilities, establishing it as a valuable resource for human genetic research. Furthermore, the authors constructed an SV imputation panel using the generated data and imputed SVs in 488,130 individuals from the UK Biobank. They then conducted a proof-of-principle genome-wide association study (GWAS) analysis based on the imputed SVs and selected traits within the UK Biobank. Their findings demonstrate that incorporating SV-GWAS analysis provides additional insights beyond conventional GWAS frameworks focusing on SNVs, particularly in improving fine-mapping.

Strengths:

The authors constructed a high-sensitivity reference panel of genome-wide SVs at the population level, addressing a critical gap in the field of human genetics. This resource is expected to significantly advance research in human genetics. They demonstrated the imputation of SVs in individuals from the UK Biobank using this panel and conducted a proof-of-concept SV-based GWAS. Their findings highlight a novel and effective strategy for integrating SVs into GWAS, which will facilitate the analysis of human genetic data from the UK Biobank and other datasets. Their conclusions are supported by comprehensive analyses.

Weaknesses:

The authors have addressed many of my previous comments, and I appreciate their efforts. However, I still have two related concerns.

(1) Shortly after reviewing this manuscript last year, my laboratory obtained access to the UK Biobank (UKB) Tier 3 dataset for an unrelated project. In August 2025, I searched the UKB Research Analysis Platform (UKB-RAP) for the imputed structural variant (SV) dataset described in this manuscript but was unable to locate it. After contacting UKB, I was informed that they were developing the system for releasing the data. To the best of my knowledge, the dataset remains unavailable. A major contribution of this work is the generation of an imputed SV resource for approximately 500,000 UKB participants with extensive phenotypic information. If this resource is not accessible to the research community, even to authorized UKB users, the practical impact and utility of the study are substantially diminished.

(2) Given that the imputed SV dataset is currently unavailable, it becomes even more important for the authors to provide a detailed, ready-to-run SV imputation pipeline for UKB-RAP, even if the "data processing simply consisted of running standard bioinformatics tools with the parameters exactly as described in the manuscript". In particular, the pipeline should include practical information such as computational requirements (e.g., memory and storage), expected running time, and estimated cost. Anyone with experience using UKB-RAP will agree that reproducing large-scale analyses on the platform can be both technically complex and financially expensive. Such pipeline would greatly improve the reproducibility and accessibility of this work.

Because my initial assessment of the manuscript was generally positive, I do not wish to change my overall evaluation, summary, or assessment of its strengths. However, I would view the work even more favorably if either (i) the imputed SV dataset became publicly available to authorized UKB users, or (ii) the authors extended their SV-GWAS analyses to the full range of UKB phenotypes and released the resulting summary statistics, analogous to the Pan UKBB ("https://pan.ukbb.broadinstitute.org/") resource. Although this would require considerable additional effort and computational resources, it would substantially enhance the long-term value and impact of the study.

Finally, I would like to emphasize that these comments are not intended to create unnecessary difficulties for the authors or the editors. Rather, I believe this highlights a broader issue in the use of this kind of large public datasets: reviewers cannot independently verify key results, and readers cannot readily build upon the work if the underlying resources are inaccessible, even after obtaining authorized access to the original dataset. I hope the authors, together with the eLife editors and UK Biobank where appropriate, can help facilitate the timely release of this valuable resource.

Reviewer #1 (Public review):

Summary:

In this MS, Muenker and colleagues, explore the intracellular mechanics of a range of animal adherent cells. The study is based on the use of an optical tweezer set up, which allows to apply oscillatory forces on endocytosed/phagocytosed glass beads with a large frequency range (from ~1 to 1000 Hz) , allowing to probe cytoplasm material properties at multiple time scales. By switching off the laser trap, the authors also record the positional fluctuations of beads, to extract passive rheological signatures. The combination of both methods allow to fit 6 parameters (from power law fits) that allow to characterize the viscous and elastic nature of the cytoplasm material as well as an effective active energy driven by cellular metabolism. Using these methodologies, the authors first establish/confirm, using HeLa cells, that the cytoplasm is more solid like at short frequencies, and more fluid like at higher frequencies, and that these material states depend on both microtubules and actin cytoskeleton. The manuscript then goes on to explore how these parameters evolve in other 6 cell types including muscles, highly migratory and epithelial cells. These results show for instance that muscle cells are much stiffer, while migratory cells are more fluid like with an increased active energy. Finally using statistical methods and principal component analysis , the authors establish some mechanical fingerprints (activity, fluidity and resistance) that allow to distinguish cell's mechanical state and relate it to their particular functions.

Strengths:

Overall, this is a very well executed work, which provides a large body of rigorous numbers and data to understand the regulation of cytoplasm mechanics and its relation to cell state/function. This work opens up on the possibility to systematically link cellular phenotype and cytoskeleton organization to intracellular mechanical signatures among many cell types and contexts.

Reviewer #1 (Public Review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers.]

Summary:

The study claims to explore plant microbiome engineering using host-mediated selection as a strategy to enhance rice growth and drought tolerance.

Strengths:

The authors have derived and identified simplified microbiomes from wild microbial communities of rice fields, deserts, and serpentine seep soils by selecting microbiomes from plants with desired phenotypes across generations. Metagenome-assembled genomes revealed enriched functions, such as glycerol-3-phosphate and iron transport, known to mediate plant-microbe interactions during drought.

Reviewer #1 (Public review):

Dwulet et al. combined experimental and modeling approaches to investigate how correlated spontaneous activity in the mouse's primary visual (V1) and primary somatosensory (S1) areas drives the development of multisensory integration in area RL. Notably, they focused on early developmental stages, before sensory experience occurs. Consistent with previous experimental findings, the authors first demonstrated that spontaneous activity becomes more sparse across development in all three areas, as measured by event amplitude, event duration, and participation ratio. Using a linear mixed model analysis to compare the maturation of this spontaneous activity, they found evidence that S1 matured the fastest. The authors then presented experimental evidence suggesting that these spontaneous events were moderately correlated both spatially and temporally.

They hypothesized that activity-dependent mechanisms use these correlations to establish connectivity across these regions. To test this hypothesis, the authors modeled a feedforward network with connections from S1 to RL and from V1 to RL, where the strength of connections depended on a Hebbian term for potentiation and a heterosynaptic term for depression. By investigating different levels of V1-S1 correlations, they found that moderate levels of correlation led to the significant development of topographically organized connectivity while maintaining a mix of bimodal and unimodal cells in RL. Additionally, when simulating a network with a more mature S1, they observed that topographical maps improved not only between S1 and RL but also between V1 and RL. Finally, the authors use linear regression to suggest that the mixture of bimodal and unimodal cells in RL is optimal for encoding the maximum amount of information from both V1 and S1.

Comments on revised version:

The revision closes most of the data-model gaps raised in my original review. The authors have clarified the experimental measures and statistical comparisons, improved the spatial correlation-map analysis, added a temporal-lag analysis that argues against stereotyped traveling waves, expanded the model description, and performed additional simulations examining the effects of differences in spontaneous activity. Taken together, these changes provide solid support for the paper's principal conclusion: structured and moderately correlated activity can, within the proposed model, guide the refinement of an initially coarse connectivity scaffold into aligned multisensory representations.

The remaining limitations primarily concern the more specific claim that the somatosensory pathway matures first and guides refinement of the visual pathway. The experiments support the conclusion that spontaneous activity in the somatosensory cortex matures earlier. However, the proposed consequence of this difference is carried in the model by an assumed stronger initial somatosensory-to-higher-order connectivity bias, motivated by pilot anatomical observations that are not included quantitatively in the manuscript. The new supplementary simulations suggest that differences in activity amplitude and frequency alone are insufficient, but the parameters are varied over ranges considerably smaller than the differences measured experimentally, and event duration is not varied. These simulations therefore do not strongly establish that the measured activity differences are insufficient to produce the effect. In addition, the Figure 4 caption and portions of the Discussion continue to imply that more mature somatosensory activity itself instructs map alignment, whereas the revised Results present the more qualified conclusion that an additional connectivity difference is required.

A few internal inconsistencies also remain. The abstract still describes activity in the three areas as being recorded simultaneously, although the cellular-resolution recordings were acquired sequentially; only the wide-field data were collected simultaneously across areas. The revised model also assigns spontaneous events durations and intervals in milliseconds, while the measured calcium events last several seconds and occur only a few times per minute.

Reviewer #1 (Public review):

Summary:

This study builds on earlier work showing that early-life odor exposure can trigger glial-mediated pruning of specific olfactory neuron terminals in Drosophila. Moving from indirect to direct functional imaging, the authors show that pruning during a narrow developmental window leads to long-lasting suppression of odor responses in one neuron type (Or42a) but not another (Or43b). The combination of calcium and voltage imaging with connectomic analysis is a strength, though the voltage imaging results are less straightforward to interpret and may not reflect synaptic output changes alone.

Strengths:

Biologically, one of the main strengths of this work is the direct comparison between two odor-responsive OSN types that differ in their long-term adaptation to early-life odor exposure. While Or42a OSNs undergo pruning and remain persistently suppressed into late adulthood, Or43b OSNs, which also respond to the same odor, show little lasting change. This contrast not only underscores the cell-type specificity of critical-period plasticity but also points to a potential role of inhibitory network architecture in determining susceptibility. The persistence of the Or42a suppression well beyond the developmental window provides compelling evidence that early glia-mediated pruning can imprint a stable, life-long functional state on selected sensory channels. By situating these functional outcomes within the context of detailed connectomic data, the study offers a framework for linking structural connectivity to long-term sensory coding stability or vulnerability.

Comments on revised version:

I thank the authors for their careful revision and thoughtful responses to the reviewers' comments. The revised manuscript addresses my previous concerns in a satisfactory manner, and the interpretation of the findings has been appropriately clarified and balanced. I have no further major comments.

Reviewer #1 (Public review):

Summary:

Recent findings have established that macrophage function is tailored to individual tissues through upregulation of tissue-specific transcription factors in response to local microenvironmental signals. However, how these transcriptional pathways affect macrophage lipid metabolism and the importance of this for homeostasis of neighbouring immune cells remains relatively uncharted. One exemplary pathway is the specific expression of GATA-6 by macrophages within the serous cavities that is triggered by local retinoic acid production. Here, Czubala et al have used mice with macrophage-specific deletion of GATA6 (GATA-6KO-mye) to study the importance of tissue-specific macrophage programming in regulating the macrophage and tissue lipidome and the functional importance of this for the regulation of eosinophil numbers in the tissue.

Strengths and Weaknesses:

The authors show accumulation of lipid-rich vesicles in the absence of GATA6, which lipidomic analysis suggests are largely comprised of sphingolipids and glycophospholipids. Using published transcriptional data identifies candidate genes in GATA6-deficient cells that may underlie these changes. Manipulating two of these candidate genes, Gba2 and Smpd1, in a macrophage cell line leads to similar changes in sphingolipid composition to those in GATA6-deficient macrophages in vivo, supporting the hypothesis that tissue specialisation of peritoneal macrophages induces transcriptional changes via GATA6 that directly control sphingolipid metabolism. GATA6 deficiency is then shown to affect the oxylipin content of peritoneal macrophages and peritoneal fluid, including higher levels of LTE4 in fluid. Elevated expression of the Ltc4s in GATA6-deficient cells is predicted as the likely mechanism leading to elevated LTE4.

To determine the functional effects of altered lipid metabolism, and specifically LTE4, the authors focus on the elevated accumulation of peritoneal eosinophils previously reported to occur in GATA-6KO-mye mice. They show that eosinophils undergo less apoptosis in these mice and the absence of a measurable increase in known eosinophil chemokines leads them to conclude that eosinophil numbers arise through increased longevity. However, this point remains to be formally demonstrated, and directly measuring the longevity of eosinophils in the cavity would greatly strengthen their conclusions. The authors then examine known regulators of eosinophil survival, IL-5 and GM-CSF. They convincingly demonstrate a role for IL-5 in the regulation of peritoneal eosinophil numbers but conclude that survival factors other than IL-5 and GM-CSF likely control the differential numbers in control and GATA-6KO-mye mice, given IL-5 was observed to be a general survival signal in both genotypes and that no difference in the levels of these growth factors was observed in lavage fluid between genotypes. The authors then blocked production of prostaglandins using the inhibitor indomethacin. This treatment also led to a general reduction in survival and number of eosinophils in both control and GATA-6KO-mye mice, leading to the conclusion that altered prostaglandin production is not the underlying mechanism regulating elevated eosinophil numbers in the absence of GATA6.

One weakness in these conclusions is that if the GATA-6-KO-mye phenotype does lead to increased production of a homeostatic growth factor for eosinophils, then inhibition/blockade of such a factor would be expected to lead to loss of eosinophils in both WT and GATA-6KO-mye mice. Furthermore, cytokines, chemokines, and lipid mediators can be rapidly bound and removed or metabolised in vivo by their receptors, meaning detecting an increase in production in body fluids can be difficult.

Finally, they block production of LTE4 using an inhibitor of the upstream enzyme 5-LO. This treatment reduces eosinophil survival and number in GATA-6KO-mye mice, from which the key conclusion is drawn that elevated LT4E is responsible for the increased survival and accumulation of eosinophils in GATA-6KO-mye mice. The major weakness here is that the equivalent experiment in control mice to determine if inhibition of 5-LO leads to a general reduction in survival/number of eosinophils or if this effect is restricted to the GATA-6KO-mye appears not to have been performed.

Impact and context:

Overall, this study demonstrates key alterations in lipid metabolism and lipid mediator release resulting from loss of GATA6 expression in peritoneal macrophages, and links this to the elevated survival/accumulation of eosinophils that occurs concurrently in GATA6-KO-mye mice. The role of endogenous LTE4 in regulation of eosinophil survival and/or migration into tissues is exciting and opens up a new avenue of research for understanding the importance of this pathway in regulation of eosinophils across tissues and during disease. Furthermore, unlike in the mouse, GATA6-expressing macrophages represent only a minor proportion of macrophages in the human peritoneal cavity, while the dominant GATA6-negative population is more equivalent to the GATA6-KO-mye cells studied here (PMID: 38102487). Hence, the data presented in the current manuscript could have important implications for how eosinophil numbers and lipid metabolism may be regulated by these cells in people.

Reviewer #1 (Public review):

Summary:

This paper describes an interesting phenotype of C. elegans lite-1 mutants. Previous work showed that lite-1 mutants lose a violet / blue light avoidance response. The authors show here that lite-1 mutants also show a defect in negative diacetyl chemotaxis. While wild-type worms avoid diacetyl at high concentrations, lite-1 mutants are instead *attracted* to it. The authors go on to perform Ca2+ imaging in sensory neurons and find that ADL and ASK neurons show altered Ca2+ responses to diacetyl in lite-1 mutants, suggesting LITE-1 is required for these responses. As unc-13 mutants with defective synaptic transmission show similar diacetyl Ca2+ responses as wild-type, this suggests these neurons respond cell autonomously to diacetyl. Indeed, expression of LITE-1 in ADL from a specific promoter shows phenotypic rescue. The authors then use a strain that expresses LITE-1 in the body wall muscles and show this expression is sufficient to engender them with sensitivity to diacetyl, as measured through altered swimming, hypercontractility, and egg laying. The authors interpret this result as LITE-1 may act as a diacetyl receptor. The authors test whether a structurally similar molecule, 2,3 pentanedione shows similar effects, and they find it does. Alpha-fold modeling and molecular docking analysis show where diacetyl might bind to the LITE-1 protein. They then test whether lite-1 mutants show chemotaxis defects to other molecules as seen with diacetyl.

Strengths:

Overall, the study follows up on an interesting and useful result. The experiments as presented are generally well-conceived and performed. The authors use a variety of behavior and imaging approaches to test how LITE-1 mediates diacetyl avoidance. The author revisions addressed the concerns I raised previously.

Weaknesses:

In response to the first submission, Reviewer 3 raised the possibility that light facilitates the production of diacetyl which then activates LITE-1. The authors helpfully revised the manuscript to incorporate this mechanisms. However, is it possible that diacetyl and 2,3-pentanedione are instead (or also) acting as photosensitizers, generating an(other) activator of LITE-1? Diacetyl has been previously shown to have chemical reactivity which is enhanced by light (citations below). I realize that the experiments have ruled out a role for acute light exposure in causing phenotypes in some of the experiments, but it is formally possible that prior light exposure may have caused diacetyl to generate peroxides or other photo-products that have the observed biological effect which is then lost in the lite-1 mutant. That is, what if the relevant molecule is already present in the diacetyl bottle / stock solution? At that point, further light exposure may not matter. This possibility was not really addressed in the manuscript.

-Huang CY, Li J, Liu W, Li CJ. Diacetyl as a "traceless" visible light photosensitizer in metal-free cross-dehydrogenative coupling reactions. Chem Sci. 2019 Apr 8;10(19):5018-5024. doi: 10.1039/c8sc05631e. PMID: 31183051; PMCID: PMC6530541.<br /> -Pengcheng Lian, Ruyi Li, Xiao Wan, Zixin Xiang, Hang Liu, Zhiyu Cao, Xiaobing Wan Acetylation of alcohols and amines under visible light irradiation: diacetyl as an acylation reagent and photosensitizer. Organic Chemistry Frontiers 2022, 9 (2), 311-319.<br /> -Rowell, Keiran N & Kable, Scott & Jordan, Meredith J. T. (2022). An assessment of the tropospherically accessible photo-initiated ground state chemistry of organic carbonyls. Atmospheric Chemistry and Physics. 22. 929-949. 10.5194/acp-22-929-2022.

Reviewer #1 (Public review):

Summary:

This paper examines whether humans use protracted temporal integration in a noise-free, deferred-response contrast discrimination task, using a covert evidence-duration manipulation combined with EEG (SSVEP, CPP, Mu/Beta). The key finding is that evidence for protracted sampling is behaviorally and neurally supported, but even joint CPP + behaviour fitting cannot fully discriminate a standard integration (DDM) model from a novel "extremum-flagging" non-integration model. The paper is transparent about this outcome.

Strengths:

This is a well-conducted and well-written study that makes a genuine contribution to the perceptual decision-making literature by introducing a clean experimental design for probing temporal integration without participants adapting their strategy and demonstrating for the first time that a non-integration model (extremum-flagging) can replicate CPP waveform dynamics that have long been considered hallmarks of evidence accumulation. The transparent treatment of equivocal modelling outcomes is commendable.

Weaknesses:

My main concerns relate to statistical power, the under-specification of the and the extremum-flagging mechanism. Addressing these would greatly strengthen the paper.

(1) The sample of 16 participants (15, after the exclusion of one participant) is described as "close to similar EEG studies" with no formal power analysis. Given that the paper's core claim rests on subtle quantitative differences between two model classes - differences that are, by the authors' own admission, not sufficient to declare a winner - even a modest increase in sample size might yield a more decisive outcome. At minimum, the authors should report a sensitivity analysis or post-hoc power calculation to indicate what effect sizes the current N could reliably detect, particularly for the rmANOVA comparisons and the neural constraint fitting.

(2) The Extremum-flagging model is the paper's most novel contribution, yet its physiological basis is underspecified. The model posits that each decision-terminating bound-crossing triggers a stereotyped, half-sine-shaped centroparietal signal, but no neural circuit or computational mechanism is proposed for how the brain could detect the first bound-crossing event in a non-accumulating evidence stream or generate a temporally precise, fixed-amplitude signal in response. Possible connections to P3b theories of context updating and response facilitation are acknowledged, but these are vague functional descriptions rather than mechanistic accounts. I think the discussion should engage more directly with potential neural substrates that could generate this flagging signal, and whether these are consistent with the known generators of the CPP/P3b. Without this, the extremum-flagging model risks being viewed as a mathematical convenience rather than a biologically plausible alternative.

(3) The Integration model at the preferred neural weighting estimates a high-to-low contrast drift rate ratio of 8.7, whereas the empirical Mu/Beta lateralization slopes suggest a ratio of approximately 3.5. The authors attribute this discrepancy to the nonlinear contrast response function of early visual cortex and the salience of the high-contrast evidence onset, but these explanations are speculative. These outcomes are arguably the most quantitatively damaging result for the integration model, so they deserves more than a brief discussion. I would recommend that the authors (a) estimate what range of contrast response nonlinearities would be required to close this gap, (b) test whether an alternative drift rate parameterization (e.g., scaling drift rates directly by SSVEP amplitude rather than contrast) reduces the discrepancy, or (c) be more explicit about treating this as a point against the Integration account.

(4) The sensitivity analysis over neural constraint weightings (w = 0.1 to 1000) is thoughtful, but the paper ultimately acknowledges that the preferred weighting is w=10, chosen because it achieves "a good fit to CPP dynamics without substantively sacrificing behavioral fit" - a qualitative criterion. No principled statistical framework is used to select the optimal weighting or to compare models at a given weighting. A Bayesian model comparison could provide a more formal framework for combining behavioral and neural fit components, and would allow a clearer statement about the relative posterior probability of each model.

Comments on revisions:

In reply to my comments, the authors have added a post-hoc power analysis that provides adequate justification for the sample size, a more nuanced discussion of neural mechanisms that could support an extremum flagging model, and several supplementary analyses that show the generality of findings across parameter levels. These are welcome additions that strengthen confidence in key findings while acknowledging nuances involved in quantitative analyses and model fitting.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have addressed the comments raised in the previous round of review.]

Summary:

In this study by Kitto et al., the authors set out to identify specific signaling components regulating the hypoxic response from the neurons to the periphery and which components are required for lifespan extension. Their previous work had shown that expression of a stabilized HIF-1 mutant in the nervous system extends lifespan through the serotonin receptor SER-7 and leads to the induction of fmo-2 in the intestine. In the current study, they mapped the precise neural circuits required for this response, as well as the signaling mediators. Their work reveals that neurotransmitters GABA and tyramine, and the neuropeptide NLP-17, act downstream of neuronal HIF-1 to convey a "hypoxic signal" to peripheral tissues. Through cell-type-specific expression studies, targeted knockouts, and comprehensive lifespan analysis, the authors provide robust evidence to support their conclusions. The insights gained from the study are both moving the field forward as they advance our understanding of neuro-peripheral hypoxic signaling, but they also lay the groundwork for potential therapeutic strategies aimed at the modulation of such signaling pathways.

Strengths:

(1) This study provides new evidence further delineating signaling components required for hypoxic signaling-mediated longevity, from the nervous system to the periphery. Using a rigorous approach where they express stabilized HIF-1 mutant selectively in ADF, NSM, and HSN serotonergic neurons, followed by cell-type-specific tph-1 knockouts to pinpoint ADF-dependent serotonin signaling as essential for both lifespan extension and intestinal fmo-2 induction.

This was followed by generating 11 transgenic lines that drive SER-7 expression under distinct neuron-specific promoters, to systematically tease out in which of 27 candidate neurons SER-7 functions to mediate hypoxia-induced longevity. This ultimately highlighted the RIS interneuron as the required signaling hub.

(2) As the intestine lacks direct neuronal innervation, the authors employ neuron-specific RNAi (TU3311 strain) and dense core vesicle analyses to identify that the neuropeptide NLP-17 is required to transmit the hypoxic signal from RIS to induce fmo-2 in the intestine.

(3) Overall, the paper is very well written. The experiments were carried out carefully and thoroughly, and the conclusions drawn are also well supported by the results they are showing.

Reviewer #2 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have addressed the comments raised in the previous round of review.]

Summary:

The manuscript by Wang and colleagues aims to determine whether hepatic glucose metabolism is differentially regulated by the left and right sides of the LPGi and to reveal decussation of hepatic sympathetic nerves.

The authors used tissue clearing to identify sympathetic fibers in the liver lobes, then injected PRV into the hepatic lobes. Five days post-injection, PRV-labeled neurons in the LPGi were identified. The results indicated contralateral dominance of premotor neurons and partial innervation of more than one lobe. The authors then activated each side of the LPGi, resulting in a greater increase in blood glucose levels after right-sided activation than after left-sided activation, and in changes in protein expression in the liver lobes. These data suggested lobe-specific modulation of HGP. Chemical denervation of a particular lobe did not affect glucose levels due to compensation by the other lobes. In addition, nerve bundles decussate in the hepatic portal region.

Strengths:

The manuscript is timely and relevant. It is important to understand the sympathetic regulation of the liver and the contribution of each lobe to hepatic glucose production. The authors use state-of-the-art methodology.

Weaknesses:

(1) Image clarity was improved in some cases, but not in others. For example, Figure 3I, showing c-Fos expression, is not convincing due to the image quality and lack of orientation.

(2) The methods section states that 8-week-old male mice were used in the experiments without specifying the experiments (e.g., brain injection with AAVs or PRV organ inoculation). The authors should include these details.

(3) The authors should use the exact location of pre- and postganglionic neurons, as they often refer to neurons in the sympathetic chain. Their findings should be compared with the existing literature on the location of preganglionic cells.

(4) Figure legends should be revised and matched with the text.

Reviewer #1 (Public review):

Summary:

The presented investigation aims to expand the sleep definition and its relationship with blood meal and/or circadian clock in the mosquito, Aedes aegypti. The authors exhausted the established sleep analytical paradigm and three behaviour toolkits: LAM10, EthoVision, and DART. They also investigated the potential underlying molecular mechanism by using dsRNA injection (LkR) and KO mosquito (Cyc-/-).

Strengths:

The authors presented a very solid dataset showing posture changes and increase in the arousal threshold of mosquito after 10 minutes of immobility. This is major clarification and extension to our understanding in insect sleep beyond Drosophila. Inclusion of analytical parameters such as bout length, waking activity and pDoze/Wake provide critical reminder for other investigators of the steps needed for defining sleep in a new species. The investigation, with its technical span in behaviour assays, therefore, establish a good standard for mosquito sleep analysis to the same quality seen in the landmark studies (Shaw et al 2000 and Hendricks et al 2000) for Drosophila sleep. The pioneering data showing clear effect of blood meal and LkR reduction on locomotion and sleep provides an entry point for further investigations. The author has addressed previous concern on coincidence of sleep increase and locomotion reduction by using their two high-res. video tracking velocity or pDoze/Wake, showing that the "sleepy" mosquitos remain capable to reach high speed locomotion albeit less frequently. The authors also discuss the possibility of ATP and alternative explanation regarding sugar content in diet.

Reviewer #1 (Public review):

Summary:

Maigler et al. set out to test the hypothesis that individual differences in taste preferences are (in part) due to individual differences in central taste processing. They first tested rats' preferences for a variety of taste stimuli on multiple days. They then recorded responses of neurons in taste cortex to the same tastes on two consecutive days.

Strengths:

The authors collected high-resolution behavioral data from the same animals across multiple days, allowing for a detailed characterization of individual variation in taste preferences. They then performed recordings from the same set of animals in response to the same stimuli, allowing them to draw parallels between behavioral and neural responses.

Weaknesses:

(1) The authors collect extensive behavioral data and show that preference vary between animals and days, but little insight is provided into what underlies these changes and to what extent they reflect "preference". Two animals drank equal amounts of sucrose and quinine on day one of preference testing, suggesting that behavior does not reflect preference but (lack of) habituation to/proficiency with the testing environment.

(2) Recordings were performed only after multiple days of preference testing, and preferences were not tested in between/following recording sessions. This design precludes a direct comparison between neural and behavioral responses.

(3) Similarly, correlations between neural responses and behavioral measures are not analyzed/reported on an animal-by-animal basis.

Reviewer #1 (Public review):

Summary:

The authors describe a clever genetic system based on rapamycin-inducible expression of a beta-galactose reporter. The authors compare this spectrophotometer-based readout to the parasite reduction rate version 2 (PRRv2) recently described by some of the same authors and based on incorporation of [3H]-hypoxanthine. The results are generally comparable, with some differences for slower-acting compounds. The authors report that this format is better suited for higher-throughput studies and requires less time to quantify time-dependent onset of parasiticidal action compared with the PRRv2.

This is a very well-executed and well-described body of work with a comprehensive set of analyses. The revised manuscript provided more context in comparing this method to other methods in the field, with a clearer explanation that the current MULT-i2 assay focuses on assessing viability, whereas other methods are more focused on assessing growth inhibition. The new assay is also faster than the prior PRR methodology. The current design will be useful to stay multi-drug combinations. The authors state that this parasite line will be available from BEI with an accompanying MTA. Other earlier comments and concerns were very well addressed by the authors.

Reviewer #1 (Public review):

Summary:

Patients with STX11 mutations develop familial hemophagocytic lymphohistiocytosis Type 4, a fatal immune disorder marked by defective T and NK cell cytotoxicity and cytokine storm. The conventional explanation attributes this to impaired cytotoxic granule release, but this has never fully accounted for the broader disease picture. This study proposes an alternative mechanism. The authors show that STX11 is required for store-operated calcium entry through ORAI1 channels, which are essential for both cytotoxic killing and NFAT-driven gene expression in T cells. In STX11-deficient cells, ORAI1 currents drop, NFAT nuclear translocation fails, IL-2 expression is suppressed, and degranulation is impaired. These defects are largely rescued by ionomycin or a constitutively active ORAI1 mutant, placing the primary lesion at calcium signaling rather than the fusion machinery. Mechanistically, STX11 binds the C-terminal tail of ORAI1 via its Habc domain and maintains ORAI1 in a state competent for productive assembly prior to STIM1-dependent gating, a step the authors call "priming."

Strengths:

The paper identifies a novel and disease-relevant role for STX11 in calcium channel regulation and raises the possibility of using channel agonists as a therapeutic strategy in the disease. The biochemical and functional data are of high quality and generally consistent with the interpretation. The proposal that a non-conventional syntaxin directly interacts with ion channels to prime its activation is novel and interesting. Additional experiments now exclude the possibility that STX11 acts as a SNARE to sustain calcium fluxes by promoting the delivery of additional functional channels.

Weaknesses:

Previous studies reporting regulation of ORAI1 by vesicular trafficking are ignored and alternative mechanisms are not considered.

Reviewer #1 (Public review):

Summary:

In this article, Vialat and his colleagues examine the early stages - which remain largely unknown - of the tumor escape process, particularly the basal extrusion of tumor cells following endocrine therapy for prostate cancer.

They first used the "Prostate Cancer Atlas" database, which provides access to a vast amount of transcriptomic data, to perform high-throughput analyses. Interestingly, analyzing a series of Androgen Receptor (AR) target genes in castration-resistant prostate cancers, they concluded that the loss of the canonical AR signaling pathway may contribute to tumor resistance.

Using a well-established model in Drosophila, they then replicated in vivo an endocrine therapy targeting the accessory gland by genetically inhibiting the expression of ecdysone, the only sex steroid present in Drosophila. These experiments induced basal extrusion similar to the mechanism observed in tumor escape in humans.<br /> These results suggest that the deprivation of sex steroids may play an important role in tumor progression.

However, although the data from the "Prostate Cancer Atlas" constitutes a powerful tool that serves as the basis for this new concept, clinical validation using carefully selected human tumor samples would help strengthen the authors' conclusions.

Strengths:

(1) The Prostate Cancer Atlas is a comprehensive collection of clinical data derived from RNA sequencing and serves as a powerful tool for conducting high-throughput analyses in this paper.

(2) The Drosophila model used in this article is well established and has already been the subject of publications by the team. In addition to being an in vivo model, Drosophila offers a threefold advantage for this study: i) the presence of an accessory gland, similar to the prostate, which allows for the simulation of tumor formation and, in particular, extrusion mechanisms; ii) its regulation by a single sex steroid, ecdysone; iii) the genetic ability to modulate or inactivate ecdysone expression, which allows for a parallel to be drawn with hormonal deprivation in humans.

(3) This study presents interesting and original findings. The data are, for the most part, of high quality.

Weaknesses:

(1) The Prostate Cancer Atlas, which is an essential tool in this study, was described only briefly - if at all - in both the introduction and the "Materials and Methods" section. The selection criteria used to distinguish CRPC or NEPC from adenocarcinoma in the Atlas or as determined by the authors, as well as the analytical methods, were not specified. It is therefore difficult to be convinced by the results, particularly those presented in Figures 1 and 2.

(2) Although the hypothesis put forward by the authors - that the deprivation of sex hormones contributes to tumor progression - is strongly supported by the Drosophila model and by the in silico analysis of transcriptomic data from the Atlas, this concept still needs to be clinically validated by analyzing a series of prostate cancer samples, either through transcriptomic analysis or by tracking gene expression in histological sections.

(3) With regard to the cells responsible for tumor escape, stem cells have been described as "candidates for the initiating resistant tumor growth" (lanes 50-55), but it is also essential to address the recent concept of "persistent cells". Indeed, these cells have been primarily associated with their tolerance to treatment (chemotherapy) and are referred to as "drug-tolerant cells". However, persistent cells could also correspond to cells that evade hormone therapy in the case of prostate cancer. This possibility should be discussed in the article.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. We thank the authors for revising the manuscript according to the reviewers' comments. We have no further comments.]

In this manuscript the applicants study two residues in the GHKL ATPase active site of Aq MutL and GyrB, and argue that the catalytic base function is shared between two conserved acidic residues that are 3 residues apart.

In the manuscript, the authors generated mutant versions in MutL and GyrB (both ala and the appropriate Asn/Gln version) and performed ATPase analysis. They also generated high resolution crystal structures of the GyrB NTD with AMPPnP for WT and mutants of the two acidic residues. The data show that mutation in either of these residues does not fully kill activity (with the exception of the Alanine mutation of the first of the two, that interferes with ATP (or AMPPnP) binding). When the acidic residues are mutated to Asn/Gln, the catalytic water can still be positioned, and hence these mutants are more active than the Ala mutants. In both cases the double mutation is catalytic dead.

The authors then perform phylogenetic analysis and ancestral gene reconstruction and based on this they argue that HSP90 forms a different class of GHKL ATPases, and lost rather than gained this separate status.

Reviewer #1 (Public review):

Summary:

The authors elegantly demonstrate a biochemically reconstituted approach to showcase the VDAC2-BAX interaction using lipid nanodiscs. The reconstitution method is specific to VDAC2 (and not VDAC1) and can capture several structural conformations. The authors show that the VDAC2-BAX heterodimer is sufficient for the direct capture and stabilization of BAX on the outer mitochondrial membrane by VDAC2. Their structural model demonstrates that a GXXXA motif within α-helix 9 of BAX drives its interaction with the β-barrel interface of VDAC2 in the membrane. AlphaFold 3 models suggest BAX adopts several distinct conformations, notably including both a strongly pore-occluding state and a loosely pore-occluding state. Functionally, electrophysiology experiments suggest that the addition of BAX modulates the voltage-gating function of VDAC2 by reducing conductance. Finally, conformation-specific antibodies and cross-linking mass spectrometry capture these structural rearrangements of BAX, reinforcing the proposed structural model.

Strengths:

Overall, the manuscript provides a solid structural and molecular rationale for BAX recruitment to VDAC2 and its subsequent oligomerization.

Weaknesses:

The authors have not sufficiently discussed key protein modifications during apoptosis in detail, especially regarding residues implicated in phosphorylation and their impact on VDAC2 association.

Overall, the manuscript is well written and presents an elegant biochemical and biophysical approach to identifying key functional states of the VDAC2-BAX complex. However, certain key functions of the complex are not extensively discussed or accounted for in the final model. For instance, components of this complex are phosphorylated in response to apoptotic or anti-apoptotic cues. Specifically, phosphorylation of S184 (located within the critical α-helix 9), T167, and S163 has key functions in promoting or preventing outer mitochondrial membrane translocation. How do the authors reconcile their structural models with the functional states of the complex generated in response to these signaling cues? This is particularly relevant given that the expression systems used here presumably yield proteins lacking these post-translational modifications (PTMs). The authors should consider running AlphaFold 3 predictions that incorporate key PTMs and discuss their potential functional impact. In its current state, the manuscript implies that unmodified BAX is sufficient for membrane translocation. Clarifying how PTMs influence pore occlusion and 6A7 epitope accessibility would significantly enrich this body of work.

Reviewer #1 (Public review):

This paper looks at the effect of vincristine-induced peripheral neuropathy (VIND), a common effect of cancer therapy. The authors performed in vivo experiments in mice by injecting them with vincristine sulphate i.p. (+/- various inhibitors or antibodies) or E-selectin intraplantar (i.pl.), and in vitro experiments using dorsal root ganglia (DRG) neurons and bone marrow derived macrophages (BMDMs).

Inhibition of E-selectin with antibodies or genetic depletion reduced the accumulation of F4/80+ macrophages in the DRG and sciatic nerves (located beside the spine) after vincristine administration, and attenuated the mechanical hypersensitivity (paw withdrawal).

The authors went on to perform spatial transcriptomics on isolated DRG neurons and found some pathways changed. E-selectin injected directly intraplantar (i.pl.) mimicked the effect of vincristine administration on the mechanical hypersensitivity. Whereas chlodronate depletion of myeloid cells reduced these changes in the E-selectin model. Using LPS priming before vincristine in BMDMs in vitro, the authors demonstrate an increase in many cytokines, including IL-1beta (typically associated with the formation of an inflammasome) and elevated p-NFkB. Finally, treatment of mice with anakinra (which neutralizes IL-1beta) also attenuated the E-selection-induced reduction in mechanical hypersensitivity when injected i.pl.

The authors address an important aspect that after cancer therapy, there can be peripheral nerve damage that has lasting consequences for patients, although the precise mechanism is unknown. The authors delineate that E-selectin has an important role in the mouse model, where depletion or inhibition attenuated the negative effect of vincristine (i.p.) on mechanical hypersensitivity (paw withdrawal). Administration of E-selectin into the foot (i.pl.) also mimicked the changes observed in the vincristine-treated mice. There seems to be a role for macrophages, as they were associated with DRGs in vivo, and depletion attenuated motor deficits in the E-selectin injection model.

However, I am not convinced by the data supporting some of the conclusions drawn by the authors, particularly on the role of the NLRP3 inflammasome in their in vivo model.

Main points:

(1) The initial experimental paradigm looks at the DRG neurons, which are located by the spine, and from there the foot pad is examined in subsequent experiments. It would be relevant to show whether the foot pad is altered in the vincristine-treated mice and whether the infiltration of myeloid cells that was demonstrated at DRGs is also observed in the foot in the vincristine model. Otherwise, the mechanism being investigated in the vincristine model, which might have similar functional results (paw withdrawal), but the mechanism behind both could be completely different.

(2) The rationale of performing spatial sequencing on DRG neurons isolated from vincristine mice is unclear. It is likely that more information could have been obtained from looking at sections from these animals, and there would be a better link to the experiments on BMDMs which follow afterwards. Indeed, the spatial data does not seem to play a key role in the study. There is not a clear link between it (which was carried out on DRGs) and the later focus on macrophages and indeed the NLRP3 inflammasome.

(3) The authors suggest that the E-selectin is enhancing NFkB-induced priming of the NLRP3 inflammasome. LPS+vincristine increased IL-1b release from BMDMs in vitro, which was elevated in the presence of E-selectin. E-selectin also increased ASC speck formation by approx. 20% in vitro. The ASC speck formation in vitro was blocked by MCC950, a specific NLRP3 inhibitor, but the authors went on to use anakinra in vivo using the E-selectin i.pl. model. It is really unclear why the switch to anakinra occurred for the in vivo work, as blocking IL-1b is central to many inflammatory pathways, not just NLRP3. Use of MCC950 would have been more appropriate to demonstrate that negative effects on mechanical function are mediated by the NLRP3 inflammasome. As there were no readouts of NLRP3 inflammasome activity measured in any of the mice in vivo (e.g. local ASC specks, IL-1b release, western blot of typical inflammasome components such as IL-1b, caspase-1, ASC or gasdermin D) either at the DRG site or the foot, we cannot say that the cell culture data mimics or models the in vivo conditions at this time.

(4) Additionally, the reliance on the E-selectin administration models for the second half of the paper is curious. It would have been relevant to test whether the immune-modulating inhibitors could also attenuate the vincristine-induced effects on mechanism hypersensitivity, to better link the E-selectin model with the vincristine one.

(5) Details are missing from the figure legends and the methods. The concentrations of compounds used in cell culture and exposure times are not clear.

Case#: Patient 9, female, Mexican, symptoms onset 6 yrs. ago, Mexico City

DiseaseAssertion: IRD

FamilyInfo: parents are non-sanguineous and asymptomatic, they also denied any history related to ocular diseases. Information disclosed that the mother had one stillbirth and three miscarriages, but denied any related diseases/health issues to this child.

CasePresentingHPOs: HP:00305, HP:00080, HP:0000493, HP:0025586, HP:0030329, HP:0012713

CaseHPOFreeText: Proband presented with light sensitivity as well as adaptation difficulties when going from dark-to-light. Right eye was 20/200 and left eye was 20/160 from the visual acuity test. Macular bull's eye appearance. Subnormal rod and cone responses. Peripapillary sparing retina.

CaseNotHPOs: HP:0007737, HP:0000750, HP:0000510

CaseNotHPOFreeText: No afferent pupillary defect. No anomalies in anterior segment.

Genotyping Method: QIAamp DNA Blood Kit was used to extract gDNA and quantification/purity of the sample was found using a NanoDrop 2000 spectrophotometer. 293 genes were sequenced. gDNA was sequenced via Illumina technology. Following, certain sequences were additionally analyzed against a reference genome in order to identify changes and interpret.

PreviouslyPublished: n/a

Variant: NM_000350.3(ABCA4):c.4926C>G (p.Ser1642Arg), NM_000350.3(ABCA4):c.5044_5058del (p.Val1682_Val1686del)

ClinVar: 99332, 99340

CAID: n/a

SupplementalData: Phenotype data in results section as well as figures 1, 2, and 3 showing phenotypic testing results.

Reviewer #1 (Public review):

Summary:

Late endosomes and lysosomes (LEL) are dynamic organelles with critical roles in cell physiology via transport of cargos to various destinations, degrading cargos, and as calcium stores. The latter is a less studied function of LELs, and virtually nothing is known about LEL function and transport in astrocytic processes. This manuscript investigates the dynamics of LELs in astrocyte processes co-cultured with neurons and finds that the lysosomal calcium channel Trpml1 regulates their positioning near astrocytic specializations (PAPs) downstream of synaptic activity.

Strengths:

Rigorous and well-controlled study of an understudied area of cellular neuroscience, namely regulation of organelle transport in astrocytes to shape synaptic environment and functionality.

Weaknesses:

Some of the same mechanistic links have been probed in neurons and other cell types, but astrocyte cell biology is still less extensively studied, making this an important contribution. Currently, only cultured astrocytes are being investigated.

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):

Summary:

The authors describe a new database that rigorously explores protein conformations.

Strengths:

It is extremely well done, using state-of-the-art tools by a group at the top of the field of structural modeling. The evaluation of qualities and the benchmarking of the structures are outstanding, and it is expected that the new database will have a significant impact on the field.

Weaknesses:

The authors are using MD simulation to generate some of the structure, and therefore should have access to standard MD energies. I am surprised that no evaluation is provided based on these energies that can be extended to free energies.

Reviewer #2 (Public review):

This work is composed of two largely independent parts. The first part (Figures 1-4) attempts to study correlations between the anterior cingulate cortex (ACC) and hippocampal area CA1 in the context of learning and memory; a number of issues including missing controls make this part inconclusive and hard to interpret. The second part (Figures 5 and 6) presents evidence for a pathway in which inputs from the ACC indirectly inhibit pyramidal cells in the superficial sublayer of CA1. The optogenetic evidence demonstrating the functional connection, including the interneurons likely to be involved, is convincing, making the second part of the manuscript a valuable contribution to neuroscience. However, I do not see evidence for this connection in the correlational analyses in the first part of the study, making the involvement of this pathway in learning and memory uncertain.

Strengths:

The biggest strength of the work is the optogenetic manipulation experiments in the second part of the study (Figures 5 and 6), which convincingly demonstrate that stimulation of ACC pyramidal neurons activates an interneuron population with symmetric spike waveforms, and inhibits parvalbumin interneurons and pyramidal cells in CA1sup, while CA1deep cells remained largely unaffected by the stimulation.

Weaknesses:

The main weakness is the disconnected nature of the two parts of the study. The second part convincingly shows that ACC provides a net inhibitory drive to the hippocampus (at least to CA1sup pyramidal and PV cells, while CA1deep cells were mostly unaffected). However, the first part investigates positive cross-correlations between pre-ripple ACC activity and subsequent CA1 ripple activity. This can be observed in Figure 1-supplement 1, where CA1 cells' activity peaks around 70ms after ACC spikes. Moreover, the GLM analyses were also based on positive ACC cell-CA1 cell pair correlations as the authors reported no bias towards negative weights for the GLM analyses (see the rebuttal letter). Thus, the correlational and GLM analyses in the first part primarily characterize a positive ACC-CA1 relationship, rather than the inhibitory influence demonstrated in the second part; the two parts of the manuscript therefore investigate different phenomena (possibly confounding inputs and network effects in part 1 versus the direct ACC-CA1 connection in part 2).

The key problem is that the main results of the two parts - namely, a dampening of the positive cross-correlations following learning in part 1 and the inhibitory ACC-CA1 connection revealed in part 2 - would be contradictory if they were interpreted as describing the same phenomenon. If the inhibitory ACC-CA1 connection was key to the downregulation of CA1 activity after learning as the authors suggest in the discussion, then we would expect ACC activity driving this change to be particularly predictive of CA1 activity in this post-learning period. Indeed, because prediction gain measures how well ACC spiking can predict subsequent CA1 spiking, any additional predictive information from the direct ACC->CA1 pathway should increase prediction gain. Instead, prediction gain decreased following learning. Thus, the positive (dampened after learning) ACC-CA1 correlations observed in the first part cannot be explained by the inhibitory ACC-CA1 pathway demonstrated in the second part. The most likely explanation is therefore that the cross-correlations studied in part 1 are dominated by other factors (such as shared inputs from other areas or coordination of cortical rhythms) and reported changes in prediction gain therefore primarily reflect changes in these factors, while the contribution of the direct ACC-CA1 pathway is drowned out and undetectable using this approach. As they stand, the two halves of the paper cannot be reconciled into the same framework.

The second weakness is the lack of control for learning. The main result of part 1 of the study is that there is dampening of the (positive) CA1 response to ACC pre-ripple activity after learning. However, nothing indicates this is due to learning as there is no control data with no learning. Moreover, the pre- and post- task periods were not matched for duration and sleep depth, so it is entirely possible that the observed dampening could be due to reduced recruitment of some cells in ripples. An appropriate control would therefore be important for attributing this to learning

The final weakness is statistical and goes beyond the lack of hierarchical statistics (which is also an issue with this work). The failure of a test to reach significance cannot be interpreted as evidence for the opposite. Yet the authors interpret it as such: for example, the lack of significant correlation between prediction gain values in pre- and post-task sleep in Figure 3C (p=0.14) is incorrectly interpreted as proof that ACC-CA1sup communication has reorganized as a result of learning. The claims of reorganization (mentioned multiple times in the abstract) hinge solely on this failed statistical test. Yet a failure to reach significance does not successfully demonstrate reorganization as it could result from a number of other reasons, including lack of statistical power or noisy estimates. To demonstrate reorganization, one would need to show that the observed change is greater than expected under an appropriate control (e.g. control task with no learning; or sleep data split in two halves), but this is missing from this manuscript.

Note that in the entire manuscript, the only differences between CA1sup and CA1deep are reported as two independent tests, one of which is significant and the other does not reach statistical significance. However, this is not evidence for different effects in CA1sup and CA1deep and statements like "we uncovered a pathway-specific difference" to describe these findings are unwarranted and not supported by the data; only direct statistical comparison between the two effects could support such claims. The exception to this weakness is the optogenetic experiments in Figure 5 where CA1sup and CA1deep responses to optogenetic ACC stimulation were directly compared and found to be different.

Reviewer #2 (Public review):

This study investigates how altered neural oscillations may contribute to unilateral spatial neglect (USN) following right-hemisphere stroke. By combining steady-state visual evoked potentials (SSVEPs), phase-amplitude coupling (PAC), transfer entropy (TE), and computational modeling, the authors aim to show that USN arises from disrupted hemispheric synchronization dynamics rather than simply from lesion extent. The integration of empirical EEG data with a mechanistic model is a major strength and offers a valuable new perspective on how frequency-specific neural dynamics relate to clinical symptoms.

The work has several notable strengths. The combination of experimental and modeling approaches is innovative and powerful, and the findings provide a coherent mechanistic framework linking abnormal neural entrainment to attentional deficits. The study also provides concrete compelling evidence supporting the potential for frequency-specific neuromodulatory interventions, which could have translational relevance.

In the revised manuscript, the authors have carefully and comprehensively addressed the concerns raised during the first round of review. In particular, the additional characterization of lesion distribution and volume provides important anatomical context for the electrophysiological findings, while the rationale for the choice of electrodes and clinical correlation analyses is now much clearer. The methodological description has also been improved substantially, including clarification of the SSVEP measure, analysis procedures, and potential confounds related to transfer entropy and volume conduction. In addition, the discussion now provides a more nuanced account of the relationship between stimulus-locked responses and intrinsic oscillatory activity, as well as the potential contribution of alpha lateralization to attentional dysfunction.

Overall, I consider the revised manuscript to provide compelling evidence for an important contribution to our understanding of the neural dynamics underlying spatial neglect. The authors have addressed my previous concerns satisfactorily, and the manuscript now provides a clearer and more balanced account of both the strengths and limitations of the findings. It should serve as a valuable reference for future work on oscillatory mechanisms in stroke and attention.

Reviewer #1 (Public review):

Summary:

The authors tackle a long-standing question in developmental theory: given a gene-regulatory network that includes extracellular signaling, which topologies are even capable of transforming an initial spatial profile into a genuinely new pattern? Building on the classical reaction-diffusion framework in one dimension, but imposing biologically motivated constraints, they prove that every one-signal sub-network must be either Hierarchical (H), self-activating (L+), or self-inhibiting (L-). They further demonstrate that only three composite classes of full networks - pure H, a coupled L+ L- "Turing" pair, and an L- module fed by an intracellular positive loop ("noise-amplifying")-can create non-trivial spatial transformations. Analytical criteria and illustrative simulations are provided, together providing a closed taxonomy, which is supposed to be relevant for real systems.

Strengths:

- Useful classification framework. Reducing a vast number of possible gene circuits to three canonical pattern-forming motifs is a valuable organizing insight for both theorists and experimentalists.

- Practical interpretability. Given a reaction network diagram, one can now decide (assuming the model applies to real systems) whether spatial patterning is even possible, saving experimental effort on in silico screens that could never succeed.

Weaknesses:

- Theoretical limitations in the application of Linear Stability Analysis (LSA): I remain uncertain about the framework's reliance on LSA as a necessary condition for non-trivial pattern transformation, especially for large initial perturbations ("spikes"). The revised manuscript itself states that spike amplitudes must be sufficiently small for the linearization to hold. In the rebuttal, the authors argue that large spikes can nevertheless be treated because their influence is initially small outside the spike. However, linear stability of a homogeneous steady state only describes the response to infinitesimal perturbations around that state; it does not generally exclude finite-amplitude perturbations from entering a different nonlinear basin of attraction and producing a heterogeneous stationary state, e.g., as in subcritical Turing patterns. Thus, I do not think the rebuttal establishes the stronger claim that a linearly stable network cannot produce a non-trivial pattern regardless of nonlinear terms.

- Presentation: The manuscript remains difficult to follow. The argument is distributed across many named requirements and topology classes, long prose descriptions of network structures, and repeated cross-references to the Supplementary Information. Given that the main contribution is a conceptual classification, I think the logical hierarchy should be considerably easier to reconstruct.

Discussion:

The study offers a solid conceptual organization of pattern-forming networks. However, the theoretical bridge between infinitesimal linear stability and macroscopic, non-linear pattern emergence still presents some uncertainties. The way the current framework formally treats large initial perturbations leaves some questions open regarding its broad analytical applicability to real biological tissues.

Reviewer #2 (Public review):

Summary:

The authors propose that bidirectional redistribution of actomyosin drives tissue invagination in Ciona siphon tube formation. They suggest a two-stage model where actomyosin first accumulates apically to drive a slow initial invagination, followed by redistribution to lateral domains to accelerate the invagination process through cell shortening. They have shown that actomyosin activity is important for invagination - modulation of myosin activity through expression of myosin mutants altered the timing and speed of invagination; furthermore, optogenetic inhibition of myosin during the transition of the slow and fast stages disrupted invagination. The authors further developed a vertex model to validate the relationship between contractile force distribution and epithelial invagination.

Strengths:

(1) The authors employed various techniques to address the research question, including optogenetics, use of MRLC mutants, and vertex modelling.

(2) The authors provide quantitative analyses for a substantial portion of their imaging data, including cell and tissue geometry parameters as well as actin and myosin distributions. The sample sizes used in these analyses appear appropriate.

(3) The authors combined experimental measurements with computer modeling to test the proposed mechanical models, which represents a strength of the study. It provides a framework to explore the mechanical principles underlying the observed morphogenesis.

Comments on revised version.

The authors have adequately addressed my previous concerns regarding the optogenetic experiments, and the addition of the new modeling analysis further strengthens the study.

Reviewer #1 (Public review):

Summary:

The study presents a novel analysis of MRI resources for 16 avian species, spanning major (though not all) clades and ecological niches. This is a significant step towards large-scale datasets on internal parcellation and long-range connectivity, central to evolutionary studies for understanding the evolution of the bird brain.

Strengths:

The integration of high-resolution T2-weighted and diffusion-weighted MRI with histological validation (Nissl and Luxol Fast Blue staining) provides a strong, cross-validated framework for studying avian brain anatomy. Data on long-range connectivity are particularly useful for understanding how relationships between brain components evolved. The approach is also scalable, allowing for more detailed evolutionary analyses compared to what is currently possible.

Weaknesses:

The sampling supports evidence of modular evolution in the bird brain, but it is limited for broad evolutionary claims, as the effects of sizes and phylogenies can be hard to disentangle without enough species per clade.

Tractography-based claims should be treated cautiously without sensitivity analyses. This is particularly important when comparing brains with different sizes and tissue properties.

Existing literature is not acknowledged sufficiently. This makes some claims of novelty misleading, and prevents readers from understanding the current state of knowledge in this research area.

Reviewer #1 (Public review):

Summary:

Naina Gour and colleagues provide a detailed observational study in which they demonstrate that MRGPRX4, a human G-protein coupled receptor (GPCR), is expressed exclusively in human melanomas and, when expressed in mouse melanocytes, drives the development of melanomas in mice. These findings provide evidence that MRGPRX4 has the properties of an oncogene, at least in certain cellular environments.

Strengths:

A strength of this work is the nice historical note in which overexpression of MAS1, a GPCR, led to classic studies of transformed fibroblasts in culture and tumors in nude mice. Cloning of MAS1 led to the identification of the MRGPR family of receptors, now known to be key players in neuroimmune and neurosensory phenomena. Here, the story comes full circle with a member of the MRGPR family being linked to a tumor, specifically melanoma. Perhaps the story is not entirely surprising given that the neural crest serves as a precursor for both nerves and melanocytes. But it is nice to see.

Additional strengths include the vast array of tools and techniques employed, from public databases to engineered mice, to establish firmly that MRGPRX4 is expressed in melanomas, although not in every malignant cell.

Weaknesses:

Given the power of the strengths of the data and story, the following comment is only sort of a weakness, as the topic is addressed while being saved for future studies. Specifically, what leads to the expression of MRGPRX4? The authors posit that it is an epigenetic phenomenon, look briefly at methylation, and rather than going down the proverbial rabbit hole of what comes first, have reasonably decided to punt.

Another concern is that given what comes across as the initial observation of MRGPRX4 being expressed in melanoma, what do all of the additional studies add?

For the non-cognoscenti, and to make the manuscript more accessible, the abbreviation NC/EMT, which is also inverted to EMT/NC, should be spelled out periodically as neural crest/epithelial-mesenchymal transition.

Please explain how this study came about. Was it a result of someone deciding to look at expression in the GTEx project and compare it to a tumor database?

A comment could be made to explain that while NSG and normal mice were used, the former are immunocompromised, and drawing conclusions without specifying these differences is a weakness.

In Figure 1A, the p-value of -145 begs for a little explanation. I don't recall seeing such a p-value.

Have you considered treating the murine melanomas with murine via PD-L1? I appreciate that this comment is somewhat superfluous given the inhibition of MRGPRX4 with compound 31-2, but given the human therapeutics combined with the fact that you have done 'everything else', I wonder what might happen.

Given the basal ligand-independent signaling, might engineering variants of MRGPRX4 that do not signal be of value?

Reviewer #1 (Public review):

Summary:

This work characterizes the regulation of lysine lactylation on influenza A virus PA protein, and describes how this post-translational modification at residues K605/K609 facilitates asymmetric polymerase dimerization at the ANP32 interface. The authors identify ATAT1 as the host enzyme mediating PA lactylation and SIRT1 as the enzyme responsible for removing this modification. They present evidence that PA lactylation enhances viral polymerase activity and viral replication, while suppression of lactylation impairs viral growth, polymerase function, and viral pathogenicity in vivo.

Strengths:

Overall, this manuscript explores a virus-host interaction axis illustrating how host metabolic signaling modulates influenza polymerase function. These findings are likely to attract broad interest, including influenza virologists studying polymerase regulation, as well as researchers investigating the functional roles of lactylation. This mechanistic insight may also offer clues for developing host-targeted antiviral strategies.

Weaknesses:

The manuscript lacks direct experimental evidence connecting lactylation to the proposed functional mechanism. While lactylation is detected in virions and overexpression systems, it remains unclear whether lactylation dynamically modulates polymerase function during infection. It is also unknown what proportion of PA undergoes lactylation at distinct infection stages, and whether lactylation specifically takes place within replication-competent asymmetric polymerase dimers. Importantly, the authors have not shown that mutation of K605/K609 abrogates the functional effects induced by lactate supplementation or ATAT1/SIRT1 overexpression in viral replication assays, which would help establish a direct connection between lactylation and viral replication. Therefore, although a correlation exists between these residues and viral replication, a direct mechanistic link between lactylation and the proposed replication model has not been firmly established. At minimum, the authors are encouraged to acknowledge these key limitations and moderate (tone down) their conclusions. For example, the observations are consistent with, but do not definitively prove, a functional role for PA lactylation in viral genome replication.

Major points:

(1) All experiments were performed using PR8, a laboratory-adapted H1N1 strain. Although this strain is commonly used for mechanistic investigations, evidence demonstrating conservation of this mechanism in currently circulating viral strains or other subtypes of influenza viruses would substantially support the conclusion that lactylation promotes viral pathogenicity. In the absence of such data, it remains unclear whether the observed findings apply broadly or are limited to the PR8 strain. In addition, the authors are encouraged to verify these phenotypes in additional cell lines.

(2) While the authors cite published work indicating that ATAT1 possesses lactyltransferase activity, it would be valuable to clarify whether ATAT1 directly catalyzes PA lactylation or functions indirectly as an intermediate. Similar considerations apply to SIRT1 regarding its potential role in removing lactylation from PA. Direct biochemical evidence, such as in vitro modification assays, would help strengthen the proposed mechanism.

(3) The available data cannot rule out the possibility that phenotypic changes induced by K605/K609 mutations stem from structural or charge alterations independent of lactylation. In fact, the results in Figure 4A and 4B support this alternative explanation: the K609R mutant shows reduced lactylation without obvious alterations in polymerase activity. This observation raises the question of whether the functional effects of these residues are driven by modified lactylation status or merely charge alterations.

(4) The proviral effect of ATAT1 appears largely independent of its enzymatic activity (Figure 2H), making it challenging to clarify whether ATAT1 functions by modifying PA to regulate polymerase activity and viral replication. Experiments examining SIRT1 on viral replication encounter similar interpretative limitations.

(5) Several siRNA knockdown results warrant careful interpretation. In Figure 3F and Figure 2E, the knockdown efficiency of SIRT1 and ATAT1 appears limited, especially at 12 and 24 h.p.i. Additional independent experiments with improved silencing efficiency or complementary approaches (such as CRISPR knockout) would help strengthen these observations.

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• Mitsubishi Hi-Uni HB
• Palomino Blackwing 602
• Palomino Blackwing Matte
• Viking Element 1
• Mitsubishi 9850 HB
• General's Cedar Pointe #2
• Tombow Mono 100 HB

Reviewer #1 (Public review):

Summary:

The authors ask whether self-supervised pretraining on related fungal genomes gives a useful prior for predicting gene expression in S. cerevisiae, where the compact ~12 Mb genome supplies too few independent windows to train a large supervised model from scratch. They pretrain a BERT-style masked DNA language model on a corpus of fungal genomes and fine-tune it to predict RNA-seq gene expression. They found a surprisingly (to me) large improvement in performance: 0.78 prediction Pearson R versus 0.67 for a randomly initialized model.

The manuscript also presents a new experimental resource: 3,053 RNA-seq data sets with perturbations using the YETI experimental platform to upregulate specific genes.

Strengths:

(1) Overall, the manuscript is well-written and is likely to be impactful.

(2) The protocol handles the train/test split of orthologous sequences well, which is nontrivial.

(3) The authors did a good job "steelman-ing" Shorkie_Random_Init: it received its own learning-rate sweep, and the authors tested two reduced-capacity from-scratch architectures to rule out some overparameterization issues.

(4) The public codebase is unusually well-organized.

Weaknesses:

I have a number of comments, none of which significantly impact the main findings.

Two analyses appear missing from the MPRA section: (1) Does self-supervised pre-training improve MPRA models such as DREAM-RNN? and (2) Is Shorkie better than Shorkie_Random_Init at the MPRA task? The language about "correlative, non-causal" associations makes me think the authors tried this and got poor results; it would be informative to include these as a supplementary negative result. (There is also (3): Does MPRA pre-training improve genomic models? But this is clearly out of scope for this paper.)

Reviewer #1 (Public review):

Summary:

In this study, the authors examine what happens when two facultative endosymbionts, Rickettsiella viridis and Regiella insecticola, are introduced into a novel aphid host, the Russian wheat aphid (Diuraphis noxia). They ask whether these introduced symbionts affect aphid performance, plant damage, alate production, dispersal, plant defense responses, and symbiont dynamics. The main result is that the two symbionts have contrasting effects: Rickettsiella tends to increase plant damage and reduce dispersal-related traits, whereas Regiella tends to reduce plant damage and aphid population growth, with less evidence for an effect on dispersal.

Strengths:

The manuscript presents successful establishment of stable transinfected populations of an agriculturally important aphid species, which is a substantial technical achievement in itself. I also appreciated that the authors examined the system across several experimental contexts, including different host plants, mixed cages at two temperatures, whole-plant assays, and a mesocosm dispersal experiment, rather than relying on a single laboratory setup. Taken together, these experiments provide a useful and reasonably convincing demonstration that novel symbiont associations can generate contrasting phenotypes in this system.

Weaknesses:

There are some major aspects of this paper that I thought could be strengthened. My main concern is that the manuscript feels broader than it is conceptually focused. A wide range of outcomes is measured, which gives the study breadth, but it also makes the central question harder to identify. As written, the paper reads more strongly as a proof-of-principle demonstration of ecologically relevant phenotypes than as a tightly framed test of a specific biological idea.

A second issue is that the biological basis of the reported phenotypes remains less developed than the phenotypic description itself. The authors make a genuine effort to address mechanism through JA, JA-Ile, SA, and metabolomic profiling, but these analyses only partially explain the main results. The negative result for the canonical defense markers is informative, yet it still leaves a substantial gap between the observed variation in plant damage and the processes responsible for it.

I also think some caution is needed in how the two symbionts are compared. The authors explain why some follow-up experiments were designed differently for Rickettsiella and Regiella, and that rationale is understandable. Still, because the downstream assays were not fully matched, the paper is strongest when each symbiont is interpreted on its own terms rather than as a strict comparison.

Overall, I would suggest softening the Significance Statement so that it more clearly reflects what is directly shown here, namely that introduced symbionts can alter plant damage and dispersal-related phenotypes under controlled conditions, rather than implying that the study directly tests management utility in agricultural settings.

Reviewer #1 (Public review):

Summary:

This study examines how type I IFN and IFN-γ exert opposing effects on macrophage responses relevant to TB. Using bone marrow-derived macrophages from genetically susceptible B6.Sst1S mice, the authors describe a persistent pathological activation state induced by TNF and characterized by sustained type I IFN signalling, oxidative stress and lipid peroxidation. They show that IFN-γ priming limits several features of this state and propose altered iron metabolism as one mechanism underlying this protective effect. They then use a computational cell-state approach to identify pharmacological interventions that may mimic aspects of IFN-γ activity. In particular, CDK4/6 inhibition with trilaciclib and activation of retinoic acid signalling with ATRA appear to act through complementary mechanisms and, when combined at low concentrations, improve control of intracellular M. tuberculosis.

Strengths:

A major strength of the study is the combination of several complementary approaches, including genetic susceptibility, cytokine signalling, oxidative stress, iron and lipid metabolism, transcriptomics, computational modelling and pharmacological perturbation. Together, these experiments build a coherent model of macrophage dysfunction.

The evidence that type I IFN signalling contributes to maintenance of the pathological state is particularly convincing within the TNF stimulation model. Blocking the type I IFN receptor after the phenotype has developed restores responsiveness to IFN-γ and prevents further accumulation of lipid-peroxidation products. The authors also provide evidence that persistence does not simply reflect continued TNF signalling, since blockade of the TNF receptor after 24 h does not abolish the elevated lipid-peroxidation phenotype. Another strength is that the computational analysis generates experimentally testable predictions, and two mechanistically distinct interventions identified by this approach are subsequently validated in macrophages.

Weaknesses:

There are, however, several limitations that affect the strength and scope of the conclusions.

(1) First, the use of the terms "persistent" and especially "self-sustaining" would be better supported by a more complete time-course analysis.

(2) Second, the proposed central role of ferritin-mediated iron sequestration in the protective effect of IFN-γ is not yet demonstrated directly. The data clearly link IFN-γ treatment to ferritin induction and reduced labile iron, but the causal contribution of ferritin itself remains to be established.

(3) Third, an important limitation is the connection between the mechanistic model developed with TNF stimulation and actual M. tuberculosis infection. Most of the mechanistic analysis, including type I IFN super-induction, lipid peroxidation, ferritin induction, labile iron and HIF1α regulation, is performed in TNF-stimulated macrophages. The infection experiments show that IFN-γ improves bacterial control and that low-dose trilaciclib plus ATRA reduces intracellular bacterial burden, but they do not establish that M. tuberculosis infection induces the same pathological circuit, or that these interventions improve bacterial control by acting through that circuit. The study therefore defines a convincing TNF-driven macrophage phenotype with relevance to bacterial control, but the broader conclusion that this mechanism underlies IFN-dependent susceptibility to TB remains only partially supported.

(4) Finally, the therapeutic implications go beyond the experimental evidence currently presented, since all of the pharmacological experiments are performed in cultured macrophages and there is no in vivo validation.

Conclusion:

Overall, this study proposes an interesting framework for understanding how inflammatory activation may become maladaptive in susceptible macrophages and how IFN-γ may combine antimicrobial activation with protection from oxidative damage. The convergence between IFN-γ, iron metabolism, lipid peroxidation and the pharmacological perturbations identified computationally is a clear strength. However, the causal role of ferritin, the operation of the proposed circuit during M. tuberculosis infection, and the in vivo relevance of the pharmacological strategy remain to be established. These limitations leave the mechanistic and translational evidence incomplete, while the study itself remains potentially important.

Reviewer #1 (Public review):

Summary:

The control of bovine tuberculosis in managed populations such as Ireland and Great Britain is unusual in that demonstrably sick animals are rarely, if ever, seen in herds. Control is therefore focused on the identification and removal of animals that test positive to the tuberculin skin test (the legal definition of infection). Despite over a century of study, the relationship between tuberculin test status, infection and most importantly infectiousness is still poorly quantified. Different formats of the tuberculin skin test are acknowledged to have both poor sensitivity and compromised specificity, although the characteristics of these tests are likely to vary considerably between contexts due to both biological variation and discretion in measurements by testers. There is an urgent need for new, more reliable and cheaper diagnostics to address the failures of existing control programs and to enable control in emerging markets that do not currently control the disease.

Strengths:

A key strength of this study is the use of samples from both naturally infected and experimentally infected animals. This data set is used to perform a careful and exhaustive evaluation of the extent to which patterns of transcriptomic expression can be used to classify between disease free animals and those infected with bovine tuberculosis.

The experimentally infected animal samples provide evidence that expression patterns of infected animals vary with respect to the time from infection. The authors highlight that this suggests transcriptomic markers may be able to detect infection earlier than tuberculin and IGRA tests that target cell-mediated immune responses. However, these methods could potentially provide a valuable new tool for quantifying the role of individual variation and progression for a disease where the individual life-history is still frustratingly mysterious.

Weaknesses:

However, the high levels of individual variation - and in particular differences in patterns of expression between naturally and experimentally infected animals do raise questions about how diagnostic tests developed from these tools would be used in practice. In particular, while many of the models considered achieved high sensitivity - estimated specificity is consistently lower than current diagnostic tests and considerably lower than that necessary for screening tests given the frequency of testing carried out as part of statutory control programs.

Expanding the number of samples may help to address these issues, but I would have liked to see some discussion of the extent to which the level of biological variation observed in this study may limit the precision of diagnostic tests developed using these tools. Given the likely characteristics of tests based on these methods, I would be interested to hear how the authors think they could fit within current statutory programs, either as supplementary or replacement tests?

Reviewer #2 (Public review):

Summary:

The authors wanted to achieve a detailed ultrastructural reconstruction of the gustatory sensory organs in the Drosophila pharynx. Using serial EM and the associated bioinformatics tools they have achieved their goal.

Strengths:

Given the dataset, finding presented are solid and will be an important work of reference for the future.

Comments on revised version.

The authors have well responded to my previous comments and added text and figure material.

Reviewer #1 (Public review):

Summary:

The manuscript "A predictive systems vaccinology framework enables rational optimization of MVA-based vaccines" by Deman and co-workers presents an approach to use Boolean models for the optimization of MVA for vaccinations. Different Boolean models are derived/inferred to perform in silico testing, e.g., of knock-outs.

Strengths:

The optimization of vaccine platforms is very important, and model-based approaches have proved a powerful framework for in silico testing. As far as I'm aware, this is the first time a comprehensive Boolean model is used for this. The authors make an effort to inform this model from available information and experimental data, using state-of-the-art calibration pipelines.

Weaknesses:

(1) Lines 154-158: "Because certain biological processes represented in KEGG (e.g., phosphorylation or ubiquitination) do not have direct logical equivalents, this conversion of signaling pathways into a Boolean network can lead to information loss and disconnection of nodes from the rest of the network. To mitigate this issue, we reconnected isolated nodes back to the main structure using oriented protein-protein interaction (PPI) data from 69, thereby restoring connectivity while preserving directionality of regulation." It is not clear to me how the reconnection addresses the described issue that not all processes can be represented in the selected modelling framework. In this context, I would also appreciate it if the authors could clarify the meaning of your states. Is it the presence of a protein (relating to low/high abundance), the activation status (relating to low/high phosphorylation), or a combination? Depending on this, different Boolean representations should be chosen, and different process information can be used.

(2) Lines159-160: "To enhance immediate readability and interpretability, we connected the resulting network with the corresponding cellular population abundances analyzed by cytometry in the samples." I would appreciate it if the authors could clarify how the cellular layer and the population layers were connected. Is this related to proliferative potential?

(3) Line 168++: It is unclear to me which parts of the Boolean network described in the section "Boolean naïve network construction" have been calibrated. Among other things, it would also be interesting to know how many logical expressions were changed by ZhegAlCal compared to the naive model and how these expressions were selected. Is there a regularization aiming to minimize the number of changes? In this context, I would also appreciate a clarification of the data processing. The current text mentions a 20% change compared to baseline, a threshold of 0.05, and a 2-means clustering strategy, yet it is unclear how they interact to obtain the binarized training and validation data.

(4) Line 267++: The model constructed by the authors describes cell-level processes in infected cells. Yet, the data used in the study - which have previously been published in reference 47 - seem to rather capture population averages over heterogeneous, partially non-infected cells. It is unclear to me why / how this can be compared. I would appreciate a clarification, potentially including a more detailed description of the employed datasets.

(5) Lines 758-759: "The networks generated and analysed during this study are publicly available in the CellCellective repository (MVA 3 pathways, MVA 6 pathways, YF17D)." I searched for the research but did not find it. In my opinion, it would be important to make the models as well as the implementations for calibration, etc. available. Without this, value and reproducibility are limited. I would encourage the authors to provide a detailed human-readable model description in the supplement.

(6) Lines 783-785: The GO analysis seems to be performed in comparison to the human genome. Yet, the model contains only 200 nodes, so a substantially reduced fraction. I was wondering if this was considered in the analysis process and if the authors checked how often the enrichments for multiple pathways were driven by the same genes.

(7) Figure 3: It appears as if the number of considered "network updates" was set to 10 (0 to 9) and that this somehow maps to the experimental time. Yet, the experimental observation times are far from uniform.

Reviewer #1 (Public review):

Summary:

The overall aims of this study are a bit unclear. The first experiments use organoids derived from cochlear GER cells in combination with single-cell RNA-seq to try to identify factors that might be important in the initiation of cellular proliferation, although the definition of proliferation is a bit loose and includes the number of organoids, the size of organoids, cell viability, and/or expression of Mki67.

Based on those results, the authors chose to focus on galectins 1 and 3 and Myc. The reasoning for these choices is a bit unclear, as their ranks in the DE gene list are 51 and 67, and the fold change for each is less than 2. Regardless, the subsequent experiments use inhibitors to examine the effects of galectins and Myc on proliferation of organoids. The results of these experiments do show an effect for inhibition of Lgals1 and Myc, although not Lgals3, but it was unclear whether the effects of these factors on growth could be separated from toxicity treatment, as both OTC008 and 10058-F4 seemed to lead to cell death.

Next, overexpression of Lgals1, 3 and Myc was actuated in organoids using AAV viruses. The results do show an effect on proliferation, but the results are confusing in that the mRNA expression profiles for two of the transgenes are markedly different in terms of timing, which would not be predicted based on similarities in the constructs. Also, while showing comparable results in some assays, the Myc vector is apparently toxic, killing ~25% of the cells by D9 even though mRNA levels are steady between D5 and D9 in those cells.

Finally, an in vivo model is used to kill several different types of cochlear cells followed by inhibition of Lgals1. The results of these experiments show a strong inhibition of expression of Ki67 following treatment with OTX008, which is intriguing. However, OTX008 was administered IP, and it does not appear that the ability of OTX008 to cross the blood-labyrinth or even blood-brain barrier has been examined. So it isn't clear whether the results of these experiments indicate a direct or indirect role for OTX008 and galectin-1 in cochlear proliferation. These issues need to be addressed.

Strengths:

The results present evidence for potential roles for galectins and myc in the modulation of proliferation of cochlear GER cells. In vitro and in vivo approaches are combined with single-cell profiling to provide a comprehensive analysis.

Weaknesses:

(1) Multiple transgenic mouse lines are used in this study, but there are no citations as to where these lines came from, how they were validated, and, for some inducible Cre lines, when the injections of tamoxifen were made.

(2) Sixty-four organoids were formed per well, but from an average of how many seeded single GER cells? This is not clear (page 5, third paragraph).

(3) Page 6: Why was cluster 7 grouped with clusters 1,2 and 3? Most cluster 7 cells are from D1.

(3) In Figure 3A, there does not appear to be a correlation between expression of either galectin-1 or galectin-3 and expression of Mki67, which I would expect would be predicted if these markers play a role in proliferation.

(4) Figure 3C: A more direct way to examine this would be immunofluorescence for galectin-1 and galectin-3 on cochlear tissue. This would also indicate whether galectin expression correlates with the Sox2+/Fgfr3- population of GER cells.

(5) For the data shown in Figure 4, what were the experimental conditions? In particular, how long in culture? One interpretation of the data in 4B and E is a decreased increase in the number of organoids, but an alternative is that the treatments are toxic and the organoids are dying. Based on a comparison with the results for myc inhibition, isn't cell toxicity in response to treatment with OTX008 or GB1107 the more likely explanation?

(6) I think the data in Figure 5 show that the inhibitor experiment demonstrates that the inhibitors, or their targets, are required for organoid survival, as the number of organoids drops to 0, which must be below the starting value.

(7) It is suggested (page 11, third paragraph) that galectins and myc could be linked or independent effectors of organoids. But couldn't this be tested by combining the inhibitors in the same experiment?

(8) On page 12, it seems AAV infection of the target cell population prevented organoid formation? This could be a major concern. If nothing else, doesn't this suggest that the effects observed in these experiments might be a result of induced organoid formation from other cochlear duct cells? Also, was expression of the transgenes (Lgals or Myc) confirmed in a cell type that is normally negative for those genes?

(9) The data in Figure 6C are confusing. The rate of mRNA expression from the AAV transgene should be comparable regardless of the construct given that the promoter is the same. But the results suggest a significant difference in the behavior of the two vectors, with Myc levels reaching a 15-fold increase in just three days while the Lgals vector is at only half that level after 7 days.

(10) An increase that is not significant is not an increase and should not be described as one (page 13 in the first paragraph).

(11) In the AAV-Myc experiments, the overall level of mRNA for Mki67 on D9 is comparable to that in the AAV-lgals1 AAV (Figure 6B), but 25% of the cells are dead (page 13, first paragraph)? Similarly, in Figures 6E and 6F, the number of organoids in the AAV-Myc samples is significantly larger than in either control or Lgals, but are most of those cells dead, then?

(12) Regarding the isolation process in Figure 7A, I am concerned this will also isolate cells from the stria vascularis? Do they retain a greater potential for growth that might lead to their predominance in the growth assay?

(13) Was the Ki67creERT2 used to label a subset of cells for FACS (page 14)? If not, why was this included? If so, when was the induction made? And doesn't this bias the selection to cells that were proliferating at the time of the induction?

(14) It is stated that "proliferation is most active at P4 with robust cycling of cells observed in the lateral GER". But then on the following page (page 15), it's stated that the single cell data indicates essentially no proliferating cells in the control, even though there are a lot of lateral GER cells. Can the authors give an explanation for this discrepancy?

(15) In the first figures in the study, the isolation approach collected lateral GER cells and identified Lgals and Myc as important for organoid expansion (page 15). In Figure 8, there appears to be no change in Lgals or Myc expression in lateral GER cells in response to the damage. Instead, it is medial GER cells that appear to have increased Lgals1 and Myc. And from Figure 8H, are those increases significant?

(16) A quick search of the literature suggests that there is no evidence that OTX008 can cross the blood-labyrinth or blood-brain barrier (page 15). Was this examined by the authors?

Reviewer #1 (Public review):

Summary of strengths:

Thank you very much for giving me the opportunity to review this very interesting paper. The research question is intriguing, allowing to address commonly observed co-morbidities between depression and anxiety and their dissociable and opposite relationship to mood fluctuations and sensitivity to reward prediction errors. The computational analyses are very in-depth, including many state of the art checks and validations. Finally, another strength is the inclusion of several large or very large samples, including a patient sample in addition to the general population sample.

Comments on revised version.

I want to thank the authors for taking the time to answer all my questions. Their answers were very thoughtful and well argued. I found the theoretical explanations very helpful for explaining their approach and ideas further. In particular, it was fascinating to see how including a single non-orthogonalized depression or anxiety scored show no effect, but including them in simultaneously revealed their previously observed patterns.

Reviewer #1 (Public review):

Summary:

This manuscript is an excellent follow-up to your 2022 study, in which Sox17 expression was localized to the rete testis and shown to be required for proper formation of the Sertoli cell valve (transition region). By using Nr5a1-Cre to drive conditional deletion of Sox17 specifically in rete testis cells, you demonstrate that testis weights remain normal at 2 weeks of age but become significantly reduced by 8 weeks in Sox17-cKO males. At the later time point, the seminiferous epithelium is severely disrupted, with apparent arrest of spermiogenesis: the epididymal lumen is essentially devoid of sperm, and most tubules lack elongated spermatids.

Strengths:

Clearly shows the role of Sox17 in Sertoli cells being important to the SV function. The SV (transition region) between the rete testis and seminiferous tubules remains an understudied domain of testicular biology. The present work, together with your prior study, highlights intriguing mechanisms operating in this specialized niche.

Weaknesses:

The available data do not fully explain either the developmental assembly of the Sertoli valve or the precise consequences of its functional disruption. These studies are nonetheless valuable precisely because they raise more questions than they answer; the conceptual implications are thought-provoking.

Case#: Patient 19, female, age 16

DiseaseAssertion: STGD

FamilyInfo: diagnosis of autosomal recessive STGD based on the pedigree and clinical phenotype of fleck deposits with or without genetic testing

CasePresentingHPOs: HP:0000608, HP:0000007, HP:0030610, HP:0030500

CaseHPOFreeText: Macular degeneration. autosomal recessive, Photoreceptor outer segment loss on macular OCT, Yellow/white lesions of the macula

CaseNotHPOs: n/a

CaseNotHPOFreeText: n/a

Genotyping Method: n/a

PreviouslyPublished: n/a

Variant: Allele 1: NM_000350.3:c.5714+5G>A Allele 2: NM_000350.3:c.4469G>A

ClinVar: Allele 1: NM_000350.3(ABCA4):c.5714+5G>A Allele 2: NM_000350.3(ABCA4):c.4469G>A (p.Cys1490Tyr)

CAID: Allele 1: CA227338 Allele 2: CA227198

SupplementalData: composite mask analysis shown in figure 3 for patient 19, show large areas of matched degeneration and isolated IS/OS loss

Reviewer #1 (Public review):

The authors sought to determine how Rif1 contributes to DNA replication timing (RT), transcriptional regulation, and embryonic development using zebrafish. They generated a maternal-zygotic rif1 knockout line and examined developmental phenotypes, genome-wide replication timing profiles, RNA-seq, and nascent transcription (SLAM-seq) during early embryogenesis.

Their major findings in this manuscript are

(1) Rif1 is not essential for zebrafish viability, unlike its partially essential role in mice.

(2) Rif1 deficiency causes defects in female sex determination, delayed epiboly, and reduced primitive erythropoiesis.

(3) Genome-wide RT is altered by Rif1, but developmental stage has a much larger influence than Rif1 itself.

(4) Rif1 is required for the proper maturation ("sharpening") of the RT program during development rather than for specific developmental RT switches.

(5) Rif1 has a much stronger effect on transcription during zygotic genome activation (ZGA) than on replication timing at these early stages.

(6) Loss of Rif1 leads to increased expression of early zygotic genes, indicating that Rif1 normally suppresses widespread transcription during ZGA.

Overall, the work proposes that Rif1 independently regulates replication timing and transcription, with these two functions becoming most prominent at different developmental stages.

The major strengths of the manuscript are as follows.

(1) the study combines multiple genome-wide approaches including whole-genome RT profiling, RNA-seq, SLAM-seq in combination with gene KO and developmental analyses.

(2) One of the strongest points is that the authors conducted the analyses at multiple developmental stages rather than a single point.

(3) The most important conclusion is that the Rif1 regulates transcription during development in a manner largely independent of its RT function, which was further strengthened by the additional data provided in the revised manuscript.

On the other hand, the weakness of the manuscript includes the followings.

(1) Limited mechanistic insight. The questions such as where Rif1 binds on the chromatin (in relation to the transcriptional promoters/ enhancers and replication origins).

(2) Which functional domains of RIf1 are involved in regulation of transcription and replication (Is PP1 recruitment required for transcription regulation?) are not addressed.

(3) Since Rif1 is known to be involved in chromatin organization/ nuclear architecture regulation, the studies addressing this (Hi-C, compartment analyses, ATAC seq etc) would provide important mechanistic information.

(4) Female sex determination phenotype is intriguing, but it remains largely descriptive, and its mechanisms are elusive at the moment.

Overall, the results support the authors' conclusions and they have successfully provided answers to the authors' original questions on developmental roles of Rif1 in RT and transcription in vertebrate.

Comments on revised version:

The authors responded to my comments in a largely satisfactory manner. They have conducted additional analyses and concluded that Rif1 regulates transcription during ZGA largely independently of its classical RT function, which is an important finding.

Although authors did not examine origin firing and replication fork rate in rif1 KO cells, which I suggested in my original review, this can be saved for their future studies.

I think the revised manuscript has been improved and provides important basic information on the functions of the conserved Rif1 protein in RT and transcriptional regulation.

I have no further recommendation for additional experiments or data analyses.

Reviewer #1 (Public review):

Summary:

In recent years, it becomes increasingly evident how beautifully intricate IAC are at the nanoscale. Studies like the one presented here that shed light on the precise inner organisation of IAC are thus quite important and relevant to obtain better in-depth understanding of IAC functioning and the contribution of different integrin subtypes to cell adhesive and mechanotransductive processes.

Interestingly, the authors found a distinct localisation of α5β1 and αVβ3 integrin nanoclusters within focal adhesion of human fibroblasts, with α5β1 integrin nanoclusters being at the periphery of IAC and αVβ3 integrin nanoclusters randomly distributed. Furthermore, a surprisingly high percentage of inactive integrins within IAC and relatively low spatial integrin colocalisation with adaptor proteins has been shown.

Strengths:

This is a very thoroughly performed STORM-based assessment of the nanodistribution of α5β1 and αVβ3 nanoclusters within IAC (and outside). The image quality is outstanding, and the authors have meticulously executed the experiments and the image analyses.

Weaknesses:

The only weakness is maybe that the manuscript remains descriptive. However, the high quality of the "description" of the nano-organisation of IAC by this scrupulous study is really important to better understand the inner workings of IAC. It provides a very solid foundation to look deeper into the (patho)physiological implications of this organisation, see recommendations (which are rather suggestions in this case).

Comments on revision:

The authors meticulously addressed all my questions and suggestions. I want to thank the authors for an exemplary revision.

Reviewer #1 (Public review):

Summary:

Since dimerization is essential for SARS-CoV-2 Mpro enzymatic activity, the authors investigated how different classes of inhibitors, including peptidomimetic inhibitors (PF-07321332, PF-00835231, GC376, boceprevir), non-peptidomimetic inhibitors (carmofur, ebselen, and its analog MR6-31-2), and allosteric inhibitors (AT7519 and pelitinib), influence the Mpro monomer-dimer equilibrium using native mass spectrometry. Further analyses with isotope labeling, HDX-MS, and MD simulations examined subunit exchange and conformational dynamics. Distinct inhibitory mechanisms were identified: peptidomimetic inhibitors stabilized dimerization and suppressed subunit exchange and structural flexibility, whereas ebselen covalently bound to a newly identified site at C300, disrupting dimerization and increasing conformational dynamics. This study provides detailed mechanistic evidence of how Mpro inhibitors modulate dimerization and structural dynamics. The newly identified covalently binding site C300 represents novelty as a druggable allosteric hotspot.

Strengths:

This manuscript investigates how different classes of inhibitors modulate SARS-CoV-2 main protease dimerization and structural dynamics, and identifies a newly observed covalent binding site for ebselen.

Weaknesses:

None. The requested mutagenesis data have been provided in the revised manuscript, and all of my previous concerns have been satisfactorily addressed.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have addressed the comments raised in the previous round of review.]

This study by Vitar et al. probes the molecular identity and functional specialization of pH-sensing channels in cerebrospinal fluid-contacting neurons (CSFcNs). Combining patch-clamp electrophysiology, laser-based local acidification, immunohistochemistry, and confocal imaging, the authors propose that PKD2L1 channels localized to the apical protrusion (ApPr) function as the predominant dual-mode pH sensor in these cells.

The work establishes a compelling spatial-physiological link between channel localization and chemosensory behavior. The integration of optical and electrical approaches is technically strong, and the separation of phasic and sustained response modes offers a useful conceptual advance for understanding how CSF composition is monitored.

Reviewer #2 (Public review):

This study asks whether auditory responses in the songbird auditory pallium/field L during singing are modulated by social context. Specifically, the authors examine neural responses to delayed auditory feedback during male zebra finch song produced either alone or in the presence of a female. This is an interesting and important question because the evaluation of self-generated vocal output may differ when the song has a dedicated social function.

The main strength of the work is that it addresses auditory feedback processing during natural vocal behavior and does so across two naturalistic contexts. The revised manuscript is strengthened by additional analyses of spike waveform similarity, response significance, response latency stability, and exclusion of motifs overlapping with female calls. These additions make the reported context-dependent response differences more credible and help address some concerns about recording stability and contamination by female vocalizations.

The results show that some auditory pallium neurons respond differently to feedback perturbations during directed and undirected song. This finding is potentially significant because it suggests that auditory processing during vocal production is not rigid but could subserve a social function that depends on the listener. If robust, this would add an important dimension to models of song monitoring and sensorimotor control.

However, the strength of evidence remains moderate rather than conclusive. Several alternative explanations are not fully ruled out. Directed and undirected songs may differ acoustically in ways that could influence neural responses, and it is not yet clear that relevant song features were directly compared or controlled across contexts. The experimental sequence also appears to be ordered, with undirected song recorded before directed song, which makes it difficult to fully separate social-context effects from time-dependent changes in recording quality or neural responsiveness. The added waveform analysis is useful, but does not completely establish continuous unit stability across long recording sessions. In addition, possible song changes around the delayed-feedback target point, including compensatory modifications before or after feedback, remain an important potential confound. Finally, clarification of the time-warping and spike-alignment procedures is important because condition-specific alignment could affect comparisons between directed and undirected song.

Overall, the data support context-dependent differences in neural responses in some neurons, but do not yet fully establish that these differences arise specifically from audience-dependent modulation of auditory feedback processing rather than from acoustic, temporal, or recording-related confounds. The work is likely to be useful to researchers interested in vocal communication, auditory feedback, and social modulation of sensorimotor processing, particularly as a foundation for future experiments using counterbalanced designs and more direct controls of song structure across contexts.

Reviewer #1 (Public review):

Summary:

This study investigates the molecular mechanisms allowing the KSM mite to infest tea plants, a host that is toxic to the closely related TSSM mite due to high concentrations of phenolic catechins. The authors utilize a comparative approach involving tea-adapted KSM, non-adapted KSM, and TSSM to assess behavioral avoidance and physiological tolerance to catechins. The main finding is that tea-adapted KSM possesses a specific detoxification mechanism mediated by an enzyme, TkDOG15, which was acquired via horizontal gene transfer. The study demonstrates that adaptation is a two-step process: (1) structural refinement of the TkDOG15 enzyme through amino acid substitutions that enhance enzymatic efficiency against catechins, and (2) significant transcriptional upregulation of this gene in response to tea feeding. This enzymatic adaptation allows the mites to cleave and detoxify tea catechins, enabling survival on a toxic host plant.

Strengths:

A multiomics approach (transcriptomics and proteomics) provided a compelling cross-validation of its findings. Functional bioassays, such as RNAi and recombinant enzyme assays, demonstrated that the adapted mite has higher activity against catechins via TkDOG15. Other methodologies, like feeding assay using a parafilm-covered leaf disc, were effective in avoiding contact chemosensation.

Comments on revised version.

The authors have satisfied all previous concerns through necessary text revisions and clarified discussions. The manuscript is now well-balanced and scientifically sound.

Reviewer #1 (Public review):

The manuscript by Yang, Wang, and Cléry presents a pipeline for real-time identification of common marmosets in a laboratory setting. Models were trained and evaluated on data derived from a family of three closely related adults and a set of juvenile twins. Freely moving animals entered an enclosed space fixed to the housing cage door, which permitted the entry of individual animals for data acquisition. Utilizing YOLOv8-nano, identification was improved through the introduction of uniquely colored collar beads. Analyses of facial similarity showed close morphological relatedness amongst individuals and highlighted the need for highly discriminative classification. The authors demonstrate that combining facial detection with visual markers enables adequate identity assignment under controlled laboratory conditions with minimal cross-individual misclassification.

The main strengths are that the proposed pipeline offers a solution for real-time identity tracking in common marmosets. Its lightweight design enables deployment across a wide range of hardware configurations. Furthermore, if similar strategies are employed, this methodology is likely adaptable for other species with minimal modification. Additionally, evaluation of closely related individuals provides a necessary stress test for the discrimination of facial identity tracking. However, the main weakness is the pipeline's reliance on controlled animal isolation and small visual markers, which raises questions about the approach's generalizability to unconstrained multi-animal environments. The authors justify the use of beads, but the dependency of facial recognition on the beads needs to be described more clearly, as it is unclear how independent facial recognition performance truly was. The overall utility of this approach therefore remains to be seen.

Reviewer #1 (Public review):

Summary:

Kaku and Flenniken investigate the mechanistic pathways through which specific viral infections alter the flight capabilities of honeybees. Building on their previous discovery that DWV impairs flight while SBV unexpectedly enhances it, the authors hypothesized that these behavioral shifts are driven by interactions with the insect's octopamine (OA) signaling pathway, which is responsible for the "fight-or-flight" neurohormonal stress response and energy mobilization. To test this, the authors experimentally infected adult honeybees with DWV or SBV and pharmacologically manipulated the OA pathway using either octopamine supplementation or epinastine (EP), an OA-receptor antagonist. They then evaluated the bees' flight performance (distance, duration, and speed) on custom flight mills and profiled their gene expression using qPCR and RNA sequencing.

Strengths:

A major strength of this study Is the high prevalence of preexisting background DWV and SBV infections in the honeybee cohorts, which meant there were no completely "virus-free" control groups. However, the authors successfully mitigated this limitation by rigorously quantifying viral RNA copies for every individual bee via qPCR and utilizing these viral abundances as continuous variables in powerful linear mixed-effect models.

Weaknesses:

The primary weakness lies in the methodology used for targeted pharmacological manipulations, as well as the lack of OA quantification across different treatments. Thus, their claims are not sufficiently supported by the current data.

Comments on revised version.

I appreciate the authors' efforts to address the reviewers' concerns and to revise the wording of the manuscript. The revised version is more cautious than the original, and some of the discussion has been appropriately toned down. However, I remain unconvinced that the key mechanistic conclusions are sufficiently supported by the current evidence.

(1) The specificity of epinastine remains insufficiently demonstrated.<br /> The authors argue that AmOARβ2 is the predominantly expressed octopamine receptor subtype in their RNA-seq dataset and therefore the physiological effects of epinastine are most likely mediated through this receptor. However, I do not find this argument fully convincing.

First, relatively low transcript abundance of other OA receptor subtypes does not exclude their physiological contribution. Even receptors expressed at lower levels may play important functional roles, particularly in specific neuronal populations or flight-related tissues. Therefore, the possibility that epinastine affects multiple OA receptor subtypes cannot be excluded.

Second, although epinastine is widely used as a pharmacological tool to inhibit octopamine signaling, its receptor pharmacology has not been comprehensively characterized. The study by Roeder et al. primarily employed radioligand binding assays, which provide information on receptor affinity but not on functional antagonism or subtype selectivity. Without systematic functional characterization across the insect octopamine receptor family, it remains difficult to exclude contributions from other OA receptor subtypes or potential off-target effects.

A more convincing pharmacological strategy would be to demonstrate similar results using an additional chemically distinct octopamine receptor antagonist. Concordant phenotypes obtained with two independent antagonists would substantially strengthen the conclusion and reduce concerns regarding off-target effects.

(2) The OA supplementation experiments should be interpreted more cautiously.<br /> The authors correctly acknowledge that exogenous octopamine produces only transient elevations in signaling. However, I do not find the comparison with synthetic agonists entirely appropriate.

Although synthetic agonists such as amitraz generally produce more prolonged receptor activation than endogenous octopamine, the more fundamental difference lies in their physicochemical properties. Octopamine is a highly polar endogenous amine that exhibits limited tissue penetration and is rapidly cleared through uptake and metabolic pathways. Consequently, exogenously administered OA is unlikely to efficiently reach relevant target tissues or receptor populations in a manner comparable to endogenous neurotransmitter release. In contrast, the greater lipophilicity of amitraz facilitates its distribution into target organs and enables more sustained receptor engagement following systemic administration.

More importantly, the observation that OA supplementation partially rescues flight behavior does NOT necessarily establish that altered endogenous OA signaling is the primary mechanism underlying the virus-induced phenotypes. Such rescue experiments demonstrate that pharmacological enhancement of octopaminergic signaling can modulate the phenotype, but they do NOT provide direct evidence that endogenous OA levels or OA signaling are altered by viral infection. Therefore, these experiments should be interpreted as supportive rather than mechanistic evidence.

(3) Direct quantification of octopamine remains the major missing evidence.<br /> The authors acknowledge that direct measurements of octopamine and tyramine would strengthen their conclusions but argue that technical limitations and cost prevented these analyses. While these practical considerations are understandable, they do not compensate for the absence of the critical mechanistic evidence.

Overall, I appreciate the authors' revisions and agree that the manuscript provides interesting evidence that octopaminergic signaling is associated with virus-dependent changes in honeybee flight performance. However, I do not believe that the current data are sufficient to support the stronger mechanistic claims regarding regulation of the OA pathway or the specific involvement of the AmOARβ2 receptor.

Unless direct measurements of endogenous OA (and ideally tyramine) can be provided, I recommend that the authors substantially moderate the mechanistic conclusions throughout the manuscript, including the Abstract, Results, and Discussion. The study should be presented primarily as evidence for a pharmacological association with octopaminergic signaling rather than as definitive proof of the proposed mechanistic model.

Reviewer #1 (Public review):

The authors have considered a panel of antibodies that target epitopes at the gp120/gp41 interface (8ANC195 and PGT151), the fusion peptide in the gp41 domain (VRC34), and the MPER region of gp41 (DH511.2_K3 and VRC42). They also investigate 10E8.4/iMab, which is an engineered bispecific antibody that targets the MPER and the CD4 receptor. On a technical note, they have applied a double amber codon-readthrough strategy to incorporate the non-natural TCO*A amino acid, which gets labeled through click chemistry. This approach should result in less disruption of the native Env structure as compared to the peptide insertion previously used for smFRET imaging of Env. Furthermore, previous implementations of smFRET imaging of HIV-1 Env, which focus on gp120 conformation, have yielded limited information on antibodies that target gp41. Altogether, through the cutting-edge application of smFRET imaging, the study provides novel insights into the mechanisms of action of interesting and clinically relevant antibodies.

Comments on revised version:

The authors have nicely responded to all of my concerns. I have no further issues.

Reviewer #1 (Public review):

Summary:

Fujita and colleagues investigated two selective peripheral nerve voltage-gated sodium channel inhibitors targeting either Nav1.7 or Nav1.8 on excitability of human dorsal root ganglion neurons. The authors discovered that Nav1.8 inhibition is more effective at suppressing repetitive firing of DRG neurons and this may explain the greater clinical efficacy observed for suzetrigine.

Strengths:

The study is interesting and the findings are conceptually satisfying in that they may explain one aspect of Nav1.7 vs Nav1.8 targeting success.

Weaknesses:

(1) The use of postmortem human DRG neurons provides translational relevance, but the use of these cells is also a liability given their high degree of variability. Of note are the 10 to 20-fold differences in baseline properties among cells, which dwarfs the effects of the test compounds. The experiments may suffer from under sampling.

Comments on revised version.

The revised manuscript addresses my prior concern with reasonable effort given the limitations of human postmortem DRGs.

Reviewer #2 (Public review):

The paper by Freas and Wystrach is an interesting computational study, exploring the detailed mechanisms of how simple neural circuits could explain complex behavioral patterns observed in navigating ants. The authors compare detailed, high speed video recordings of Australian desert ants (Melophorus bagoti) with predictions made by their new computational model and find convincing similarities between the model and the behavioral data, at a level of detail not previously studied. Particularly interesting are emerging properties of the model, yielding behavioral motifs it was not designed to reproduce, but which occur in natural ant behavior.

A strength of the study is that the model is based on previous models, without making major novel assumptions. It combines existing models of the insect central complex with a model of the lateral accessory lobe and adds a stochastic inhibition of forward velocity to the interaction of central complex and lateral accessory lobes. In essence, the central complex provides corrective steering signals when the goal direction and the current heading of the insect are not aligned, while the lateral accessory lobes provide an intrinsic oscillator underlying the behavioral oscillations shown by walking ants at all times. These background oscillations are modulated by the steering signals from the central complex. Depending on which phase of the intrinsic oscillations coincides with the corrective signals, and how fast the ant is moving forward during this time, a complex set of behaviors emerges.

Most prominently, scanning behaviors, which are regularly carried out by the ants, are recapitulated in great detail by the model. Additionally, other behaviors, such as full loops, emerge naturally from the model. While computational models are not to be seen as definite evidence for any biological reality, they can provide strong support for particular neural implementations. The current study is an excellent example in that it provides evidence for a serial arrangement of central complex circuits upstream of the lateral accessory lobe circuits, modulated by speed regulating input. While the latter is hypothetical, it yields a clear hypothesis that can be validated by connectomics studies and functional work in the future.

The computational model is explained in detail and information about all model parameters is provided in an accessible way. The approach is thus transparent and reproducible, leaving it to the readers to assess the assumptions made in the model and how the studied complex behaviors emerge. This also provides the possibility to combine this new model with existing models to expand the scope and to more comprehensively capture the behavioral repertoire of ants, and insects in general.

Importantly, the study shows that even complex behavioral motifs do not require dedicated neural modules, but can rather emerge from the interplay of already known circuits - highlighting the efficiency of insect brains and possibly providing the path towards embodied hardware solutions of such circuits in autonomous agents.

Reviewer #1 (Public review):

This interesting paper addresses the phenomenon of potentiation in single-cell habituation in Stentor coeruleus. This is an important "hallmark" of habituation that helps to establish single-cell learning as being similar to habituation in animals. Prior studies from Wood, as well as our own results, have shown that potentiation occurs in Stentor, but I have always remained a little bit skeptical that this effect was possibly just due to incomplete recovery after the first trial. When I first read this paper and saw the habituation curves for the first and second trials, such as in Figure 5, I thought, yes, that is definitely what is happening, and so is this really potentiation?

The authors were also clearly aware of this issue and, notably, they embraced it head-on by developing an analysis that allows potentiation effects to be detected even despite failure of the cell to fully recover after the first trial. The key is their "phase portrait" that allows the learning process to be depicted as a curve capturing how learning rates and response probability evolve over time, thus allowing the curves to be compared between trials. If my interpretation was correct that so-called potentiation was just incomplete recovery, the prediction would be that the curves for two successive trials would overlap, with the first trial curve extending beyond the second one towards higher response probabilities, which would be lost in the second trial due to failure to recover fully. But the data clearly are not consistent with that idea. I think that this result is very strong and important.

Especially nice is the approach of Figure 7C, which uses a vertical shift in the phase portrait as an indicator of potentiation. I did, however, find Figure 6 a little hard to digest at first, and I have a few suggestions about that. First, I think it would be a good idea to explicitly say which curve is the first trial and which is the second. Second, I think it would help readers if the authors could start with a cartoon that explains visually what the curves mean. For example, show a habituation curve, indicate how the slope is calculated at different parts of the curve, and then show how the slope versus response are plotted to make the phase portrait. It is all spelled out in the text, but it would help a lot of readers to see it visually, I think.

One question I have about Figure 6 is that it looks like the specific case of ITI 1 hour ISI 2 min has some kind of pathological behavior in the second trial, despite not seeing any indication of any 'weirdness' in Figure 5. I gather that this is meant to be due at least in part to the incomplete recovery seen after the first trial, but then I don't see why this would not also be an issue for ITI 1 hour ISI 3 min. I would not require the authors to explain every anomaly, but this one stands out, and I feel it could be telling us something interesting.

Reviewer #1 (Public Review):

The paper itself has a reasonable aim, to compare the inputs to the hippocampus from cortical regions across mammals. But for some reason, the conclusions that are reached are very limited. We know for example that the main laboratory rodents investigated, rats and mice, are nocturnal, live in underground tunnels, and have a very wide field of view with no fovea. In contrast, primates have a highly developed cortical system for vision and a fovea, and so have very different capabilities to rodents, as they have an ability to identify people or objects at a distance, and to remember where they have been seen. Despite this major difference in the visual cortical processing in these different mammals, somehow important points are missed in this paper about how the cortical processing is organised in these different mammals, and how this is reflected in the anatomy.

Reviewer #1 (Public review):

Summary:

These authors used a binocular rivalry task with flickering stimuli in which subjects had to report the color of the target grating at the end of each trial. Target or distractor cues provided information about the orientation of the respective stimulus prior to each trial. The stated goals of this project include testing the neural mechanisms underlying strategic target and distractor processing. Behavioral enhancement was observed for target cueing, while no cost was noted for distractor cueing. These authors present evidence for reactive suppression, characterized by pronounced frontal theta activity that reduced the sensory gain (SSVEP) of the distractor. Distractor cues also increased alpha activity over parietal areas, which these authors link to attentional gating while pointing out no relationship with sensory gain.

Strengths:

This manuscript clearly reflects thoughtful analysis of the available data. Alongside a simple and effective task design, sophisticated methods provide good support for most of the claims made by these authors.

Weaknesses:

Lack of temporal precision for SSVEP effects. I would like to see how sensory gain is/isn't dynamically modulated in the moments after the initial ERP to see if there could be differences compared to the broader window used presently (1.3 to 3.1 seconds).

These authors indicate that persistence of the neural representation of cued distractor orientations into the rivalry period is evidence against a "search-and-destroy" type mechanism where distractors are enhanced to then be suppressed reactively. This claim relies on an indirect link between the maintenance of information about distractor orientation (i.e., successful orientation decoding) and the processing of sensory representations. This claim would be backed up more substantially if the SSVEP (a measure of sensory processing) could reveal temporal dynamics on a finer scale.

Lorraine Hansberry and one BIG typewriter!<br /> by [[Robert Messenger]] oz.Typewriter <br /> accessed on 2026-09-09T19:45:55

Joint Public Review:

Summary:

Inferring so-called "functional connectivity" between neurons or groups of neurons is important both for validating models and for inferring brain state, including in human patients. This study aims to enhance this inference process by using closed-loop perturbation-based approaches. To this end, the authors develop a framework based on linear dynamical models that minimizes the estimation error. Based on this framework, the authors provide a practical guide for applying it in realistic experiments. Modalities include non-invasive ones, such as fMRI, iEEG, and invasive ones, such as optogenetic perturbations combined with neuropixel probes or calcium imaging.

Strengths:

A main strength of this paper is the application and adaptation of an explicit error expression to system dynamics estimation from evoked neural responses, bringing a useful theoretical tool into computational neuroscience for, as far as we know, the first time. Importantly, while the analytical derivation assumes the neural dynamics is linear and the control signal is known, these assumptions do not appear to be essential: their method outperforms passive observation even when the true dynamics is nonlinear or the control input is not known perfectly. Moreover, the relative simplicity of the method makes its practical applications straightforward, as the authors illustrate in the context of brain state classification and neural control.

Besides being of practical importance, simply pointing out that passive observation can lead to large mis-estimation of functional connectivity should serve as a wakeup call to anybody engaged in this endeavor.

Weaknesses:

None.

Reviewer #1 (Public review):

Lohse et al. describe an open-source system for laser scanning photostimulation (LSPS) in head-fixed animals. Although similar systems have been developed and used by different groups, Zapit provides an open-source solution requiring few custom parts and minimal coding. This tool can clearly facilitate and speed the adoption of LSPS, particularly for the increasingly used purpose of mapping the effects of focal cortical silencing during behavior. Other potential uses include mapping optogenetically evoked movements and selectively activating genetically labeled neuronal subtypes of interest in the cortex. The design is well thought through, and the presentation is mostly clear and well written.

In general, the more modular such a system is, the better, in terms of compatibility with existing hardware and software that potential users may already have purchased - laser, galvo, and camera in particular. The system has struck a reasonable balance between allowing modularity and providing an integrated complete package, but even more flexibility would be welcome for potential users looking to cut costs, as would clearer presentation of such flexibility as already exists.

Comments and suggestions are mostly minor, as follows.

(1) Command signals:

How is the relationship between analog voltage commands and laser power determined? Is this assumed (or required) to be linear (as Figure 7F implies)? Usability and modularity would be improved by an option to measure or provide a calibration curve for systems with a nonlinear mapping between command voltage and laser power.

For the grid calibration step, how is the initial mapping from galvo voltage commands to image position determined? Presumably, some sort of initial guess or calculation based on the hardware specifications is needed for the grid calibration to be feasible. Also, how are the number of grid lines and the distance between them determined?

Why is the mapping between analog outputs and hardware (galvos, laser, masking light) fixed? This would be trivial to make configurable and allow labs with existing setups to adopt Zapit without rewiring existing hardware.

(2) Laser and optics:

In Figure 1, the authors should consider explaining the scanning principle schematically, i.e., depicting how tilting of the scan mirrors translates via the scan lens into beam displacement in the specimen plane. Perhaps Zemax can be used for accurate rendering.

Since the unexpanded beam greatly under-fills the back aperture of the lens, the z resolution is presumably terrible - which is good! That is, for the purposes of LSPS, this advantageously avoids focus-dependent effects, which might otherwise arise due to (e.g.) skull curvature. The authors should consider pointing this out, as well as providing an estimate of the z resolution.

What is the working distance?

Reviewer #1 (Public review):

Sensory hair cells of the inner ear convert mechanical sound vibrations into electrical signals through mechano-electrical transduction (MET). While the protein components of the MET machinery have been studied extensively, much less is known about how the surrounding membrane lipid environment contributes to hair cell function. The recent discovery that TMC1 and TMC2 also function as lipid scramblases has brought renewed attention to the importance of membrane lipid asymmetry and the mechanisms that maintain it in sensory hair cells.

In this study, the authors identify the P4-ATPase ATP8B1 and its partner TMEM30B as key regulators of membrane lipid asymmetry in outer hair cells. Using complementary genetic models, HA-tagged knock-in mice, localization analyses, and functional experiments, they show that ATP8B1-TMEM30B is enriched in stereocilia and the apical membrane of outer hair cells and is required to maintain phosphatidylserine asymmetry, support hair cell survival, and preserve normal hearing. The parallels between the ATP8B1/TMEM30B loss-of-function phenotypes and TMC1 deafness-associated mutants with constitutive scrambling support a model in which ATP8B1-TMEM30B flippase activity maintains membrane lipid asymmetry and homeostasis, whereas constitutive TMC1-mediated phospholipid scrambling disrupts this balance and contributes to membrane instability.

The authors have addressed the points raised during the initial review thoroughly. The revised manuscript includes clearer methodological details, additional physiological characterization, improved presentation and quantification of several datasets, and a more balanced interpretation of the localization and mechanistic findings. These changes improve both the clarity and rigor of the study while leaving its main conclusions unchanged.

As with any study that opens a new area of investigation, important mechanistic questions remain. In particular, it will be interesting to determine how disruption of membrane lipid asymmetry ultimately impairs MET function and triggers hair cell degeneration, how flippase and scramblase activities are coordinated in vivo, and how these pathways are integrated with the broader molecular machinery underlying mechanotransduction. These questions highlight the exciting directions that this study opens for the field.

Overall, this work provides evidence that ATP8B1-TMEM30B is a critical regulator of stereocilia membrane lipid asymmetry and represents an important contribution to our understanding of membrane homeostasis in auditory hair cells. I have no further major concerns and support publication.

Reviewer #1 (Public review):

Summary:

This is a study utilizing several types of analyses (computational modeling, neuronal cultures, rodent epilepsy model, and human intracranial multi-scale recordings) to address a highly relevant conceptual question: Are fast ripples (FRs) distinct pathological entities or largely emergent products of stochastic spike clustering? The results can potentially reshape current approaches to incorporating fast ripples into the epilepsy surgery evaluation.

Strengths:

The conceptualization of fast ripples as potentially arising by chance is highly novel and builds effectively on questions raised in prior studies that have never been satisfactorily resolved. Integration across biological scales and models provides a rigorous approach, now improved by addressing theoretical concerns regarding validity of the shuffling approach and state dependence. The discussion has been updated to provide a more nuanced interpretation of the study's findings.

Weaknesses:

The authors have satisfactorily and thoughtfully addressed the critiques provided in the first review. However, there remain two points that I would like authors to address:

(1) Synchronized burst firing is a key feature of an epileptic site generating interictal discharges, and one that could generate either oscillatory or stochastic FRs as documented in multiple prior publications cited in the manuscript and/or in the prior review. Paroxysmal depolarization, for example, has been very well described, and consists of strong, disorganized burst firing (resulting in summated postsynaptic potentials strong enough to generate high gamma signal) in a neuronal population coinciding with a large low-frequency deflection. I would like to see the results described in this context, and to avoid blanket dismissal of stochastic FRs without a clear oscillatory component.

(2) It would be highly useful to add a conclusion paragraph that spells out implications of the study for use of FRs as epileptic biomarkers in clinical invasive EEG recordings.

Please address the above critiques in Discussion, or elsewhere as deemed necessary by the authors.

Reviewer #1 (Public review):

Summary:

This manuscript by Ghosh and colleagues investigates the transcriptional changes within the oligodendrocyte lineage that contribute to age-related declines in oligodendrocyte differentiation and myelination. Combining bulk RNA-Seq on acutely purified oligodendrocyte lineage cells with bioinformatic approaches, the authors identify groups of genes that show different patterns of dynamic regulation during differentiation (which they term "switch" genes, or "switches"). A subset of these switch genes are differentially regulated with age. The authors identify two transcription factors, Bcl11a and Foxm1 that are downregulated during differentiation, have predicted binding site enrichment at other switch genes and are downregulated in aged OPCs. Functionally testing Bcl11a, the authors show that Bcl11a knockdown inhibits the differentiation of young OPCs in culture, whereas overexpression promotes differentiation of aged OPCs. Viral expression of Bcl11a in Sox10 expressing cells accelerates the formation of Plp1+ oligodendrocytes in aged rodents following lysolecithin induced demyelination.

Strengths:

The work is clearly presented and addresses an important biological problem. The bioinformatic approaches used in the manuscript are powerful, and the identification of Bcl11a as a modulator of oligodendrocyte differentiation is a novel finding. The combined in vitro and in vivo approaches to assess the function of Bcl11a in oligodendrocyte differentiation are a substantial strength of the work.

Comment on revised version.

In the revised version the authors now provide analysis of expression of stage-specific markers for OPCs, preOls and OLs in their isolated cells. It is slightly concerning that the OPC markers show higher expression in the isolated preOLs than in the isolated OPCs, but the authors do provide some discussion on this point in the supplementary text.

Reviewer #1 (Public review):

Summary:

This work provides a comprehensive analysis of how adult zebrafish show fear responses to conspecific alarm substances (CAS) and retain their associative memory. It shows that freezing is a more reliable measure of fear response and memory compared to evasive swimming, and that the reactivity and the type of responses depend on the zebrafish strain. It further suggests neuronal substrates of different fear responses based on c-Fos mapping.

Strengths:

The behavioral part is the most comprehensive and detailed yet in the zebrafish field, providing strong support for the authors' claim. The flow from Figure 1 to Figure 4 is very smooth. They provide extremely detailed, yet complementary and necessary, analyses of how different categories of behavior emerge over time during the CAS exposure and memory retrieval. I'm convinced that neuro researchers who study fear/stress responses will always refer to this paper to plan and interpret their future experiments.

Comments on revised version:

The authors successfully addressed my comments, including the addition of Figure S6-2, which gives us some intuition into the relationships between c-Fos levels in individual areas and the behavioral outputs.

Reviewer #1 (Public review):

Summary:

The authors set out to evaluate whether AGES, a recently developed auxin/TIR1-based conditional GAL4 expression system, is a suitable tool for Drosophila ageing research. They characterise induction efficiency across sex, transgene insertion site, auxin dose and age, then test whether AGES can replicate a well-established pro-longevity manipulation (dominant-negative insulin receptor expression).

Strengths:

The study is thorough and methodical. The authors use appropriate genetic controls throughout, which is required to properly interpret AGES-based experiments. They identify an important issue, in that activation of the AGES machinery itself (independent of any UAS-transgene) shortens lifespan and alters protein levels, while high-dose auxin independently affects body mass, and even a moderate dose (5 mM) impairs stress resistance across all genotypes. These findings are important for researchers when interpreting their experiments. The tissue and age mapping of induction efficiency (brain, fat body, gut) is also useful, and the inclusion of driver-only positive controls at each age (Figure 2) establishes that da-GAL4 activity itself is stable across the ages tested, ruling out declining driver activity as an explanation for the reduced induction seen in older flies (though, as noted below, reduced auxin ingestion with age remains a very plausible contributing factor alongside declining AGES efficacy).

Weaknesses:

Longevity and stress assays were conducted only in females, which, combined with the finding that males show weaker and less consistent induction, means the study cannot speak to whether the metabolic and survival costs of auxin/AGES activation observed here also apply to, or differ in, males. The KCl vehicle control matches the potassium cation (K⁺) content of K-NAA across conditions; therefore, chloride (Cl⁻) concentration differs between control and auxin-fed media (both minor weaknesses).

Achievement of aims and impact:

The authors achieve their stated aim. Rather than validating AGES as unambiguously suitable for longevity work, they set out to characterise its behaviour and limitations in this context, which they do convincingly. The data support their overall conclusion that AGES can be used to conditionally induce transgene expression at advanced ages, but that its use in longevity/healthspan studies requires caution and rigorous control genotypes. This is a useful contribution with direct practical value: it will help other researchers make informed decisions about whether and how to deploy AGES in ageing-related work, and the cautionary findings regarding auxin/AGES toxicity are likely to be of broad relevance to the growing community of AGES users beyond the ageing field specifically.

Reviewer #1 (Public review):

This study investigates the role of a specific neuronal population in the lateral septum (LS) in balancing exploratory and defensive behaviors. The authors created a mouse model (cKO) lacking Nkx2.1-lineage neurons in the LS by deleting the Prdm16 gene. They discovered that this ablation specifically eliminated Crhr2-expressing neurons, which are normally targeted by urocortin-3 (UCN-3) inputs. Behaviorally, cKO mice did not show general changes in anxiety but displayed a significantly increased exploratory drive. In a predator odor test (using TMT), cKO mice spent more time investigating the aversive stimulus compared to controls, suggesting these LS neurons normally suppress exploration during threat. Furthermore, the study found that Nkx2.1-lineage neurons in the LS are specifically activated by acute stress (body restraint), as shown by an increased number of c-Fos-positive neurons. While the loss of these neurons caused some connectivity and electrophysiological changes, the remaining Nkx2.1-lineage neurons were more excitable. Therefore, the authors demonstrate that LS Nkx2.1-lineage/Crhr2+ neurons are a distinct population crucial for calibrating behavioral responses to stress, acting to inhibit exploration in favor of defensive strategies.

This work provides new insights into the neural circuitry underlying anxiety and threat avoidance. However, some of the methods and data analyses require revision for greater clarity, and additional experiments and analyses are needed to further substantiate the conclusions.

Some of my specific questions and concerns are as follows:

(1) The authors showed a reduction in the size of LS and a specific decrease in Crhr2+ neurons in cKO mice. I would suggest examining whether the density of other types of neurons (e.g., Crhr1+ cells or other known cell types in LS) was altered in the cKO mice.

(2) For the single-cell sequencing experiment (Figure 2), it is unclear whether tissues from the 3 male and 3 female mice within each genotype were pooled together or processed individually (i.e., as 6 separate samples). This information is not clearly stated in the manuscript. Given that male and female mice exhibited behavioral differences, it would be valuable to examine sex-dependent effects in the analysis shown in Figure 2.

(3) Previous studies have shown that LS neurons exhibit distinct firing patterns, including regular spiking, bursting, complex-bursting, and phasic spiking. Since the authors recorded from both tdTomato-positive and -negative LS cells, it would be interesting to determine whether the positive cells display a unique firing pattern, thereby representing a distinct electrophysiological cell type within the LS.

(4) More detailed descriptions of the electrophysiological data analysis should be provided in the Methods section. Some LS neurons display spontaneous firing without current injection; therefore, it should be clarified how the resting membrane potential was measured in these cells. The amplitude and onset latency of the first spike are presented in the figures; however, it is unclear how the first spike was selected-whether from spiking responses to rheobase current or to a specific current pulse. I would suggest defining the first spike based on responses at a certain firing frequency. The method used to determine the spike voltage threshold should also be specified.

(5) Could the authors analyze the single-cell sequencing data to examine whether changes in ion channel expression might explain the observed alterations in spike waveforms?

Reviewer #1 (Public review):

Summary:

Amadei et al investigate how excitation/inhibition balance in the prefrontal cortex plays a role in social behavior. To address this question, they developed a behavioral task where adult female mice can choose between a social reward (e.g., an adult male for sociosexual choice, or an adolescent female mouse) and a non-social reward (e.g., milk). They found that optogenetic inhibition of inhibitory neurons expressing oxytocin receptors (OXTR neurons) in the prefrontal cortex (PFC) reduces choice for sociosexual interaction compared to non-social reward and to a greater extent in sexually receptive females. They also found that this manipulation increases pyramidal neuron activity. Specifically, the authors identified a neuronal ensemble which represent the male option. Inhibition of OXTR disrupts the ability of the neuronal ensemble to represent the male option during decision-making in the behavioral task. Thus, using computational modeling, the authors proposed that OXTR neurons promote male choice by letting a male-representing pyramidal ensemble outcompete other pyramidal populations in the mPFC.

Strengths:

The study addresses an important topic in social behaviour and reward neuroscience with a focused hypothesis. The combination of behavioral testing and circuit manipulation combined with calcium imaging is a clear strength, and the work has the potential to make a solid contribution.

Weaknesses:

The main weaknesses are limited methodological clarity and details.

Reviewer #1 (Public review):

The paper presents novel evidence that spatial representations prioritize coarse topological features (T‑junctions, holes, crosses) over precise Euclidean metrics like angle and length, using drawing-based memory tasks with adults and children. The study is interesting and well‑motivated, and the importance of topological relations is clear, but stronger and more nuanced evidence is needed before concluding that topological relations are more important than metric details, as task difficulty and the potentially distinct roles of metric and topological information in spatial representation have not yet been fully disentangled.

Introduction<br /> (1) P.5: Please explain in more detail what you mean by "What is relevant is the relative prioritization of each of these features."

Results<br /> (2) P.8: Please clarify how the "proportion of drawings with angles biased towards 90{degree sign}" was computed. Specify the criterion for counting a drawing as biased (e.g., a certain absolute deviation toward 90{degree sign} from the original angle), and explicitly state in the Results that absolute degrees of deviation were used, as described in Methods.

(3) It would help to spell out whether the findings imply that obtuse angles are typically drawn smaller (closer to 90{degree sign}) and acute angles larger (closer to 90{degree sign}). Also, would angles be more biased toward 90{degree sign} or 180{degree sign} (or 0{degree sign}) depending on the angle? (e.g., 175{degree sign} is seen more as 180{degree sign} while 95 is seen more as 90{degree sign})

(4) Figure 4B: The statement that "positive values indicate bias in the direction of 90 degrees" needs a more precise explanation. Please explain exactly how the bias metric is computed (e.g., signed difference between drawn and original angle, with the sign indicating movement toward or away from 90{degree sign}) and what the y-axis values represent. Given that the Methods refer to absolute deviations, it would be useful to reconcile where the positive/negative signs come from in this plot.

(5) Figure 4C: The description in the Results seems to use a different metric than what is plotted. Please ensure that the measure in the text matches the measure shown in the figure, and adjust labels or wording so they align clearly.

(6) P.11: Consider briefly justifying why the authors predicted that participants would also add L‑junctions, rather than only remove them.

(7) P.12: The last sentence: Weren't the overall rates of feature preservation 'higher' in the adult sample?

Methods<br /> (8) Experiment 1: Please clarify whether the angles associated with T‑ and L‑junctions were equated or differed systematically. A short description of stimulus generation (e.g., angle ranges, line lengths, junction configurations) would be helpful.

(9) It would also be helpful to specify the statistical tests used (e.g., t‑tests, ANOVAs, mixed‑effects models), including the main factors and any random effects, so readers can clearly follow your analysis pipeline.

Discussion<br /> (10) It may be important to note that task difficulty likely differs across feature types: junctions involve presence/absence or counting, whereas angle and length reproduction require finer metric precision. The authors' claim of "prioritization" and possible difficulty effects should be disentangled.

(11) Furthermore, would it be possible that people retain relative order/comparison of different angles/lengths rather than computing precise values?

(12) I agree that topological relations are extremely important. However, for above reasons, it seems like stronger/stricter evidence is needed to claim that topological relations are 'more' important than metric details. They also might serve different roles in spatial representations

(13) The Discussion would benefit from a short paragraph on where different junction types (T, L, crosses) typically appear in everyday scenes and objects (e.g., as cues to occlusion, surface intersections, 3D structure) and what functions they serve. This would help connect your experimental findings to the ecological importance of these features for natural vision and spatial cognition.

Reviewer #1 (Public review):

Summary:

The authors developed a novel theoretical/computational procedure to count bacterial populations without introducing artificial randomness effects due to dilution. Surprisingly, this very important aspect of studies of bacterial systems has been overlooked. The proposed method provides a simple and transparent approach to eliminate the randomness of bacterial accounting procedures, allowing now to fully concentrate on the intrinsic effects of the studied systems.

Strengths:

A very simple and clear procedure is introduced and explained in full detail. This elegant approach finds an excellent compromise between mathematical rigor and computational efficiency, which is important for practical applications. The provided examples are convincing beyond a doubt, clearly indicating the potential strong impact of the proposed framework. Various complications and possible issues are also discussed and analyzed. This seems to be a very powerful novel method that should significantly advance the analysis of complex biological systems.

Weaknesses:

The only minor weakness that I found is the assumption of independence of bacterial species, which is expressed as the well-stirred approximation. One could imagine that bacterial species might cooperate, leading to non-uniform distributions that are real. How to distinguish such situations?

I believe that this method can be extended to determine if this is the case or not before the application. For example, if the bacteria species are independent of each other and one can use the binomial distributions - then the Fano factor would be proportional to the overall relative fraction of bacterial species. Maybe a simple test can be added to test it before the application of REPOP. However, I believe that this is a minor issue.

Comments on revised version.

I am satisfied with the correction proposed by the authors. The method is already quite impressive, and there is no need to complicate it at this stage.

Reviewer #1 (Public review):

Summary:

The authors combine discriminative auditory fear conditioning with longitudinal in vivo calcium imaging to ask how prelimbic (PL) representations of learned and generalized threat evolve across recent and remote memory time points. Using two different CS+ frequencies and a no-shock control group, they report that PL population activity tracks graded behavioral generalization, that population similarity is highest for tones eliciting strong threat responding, and that distinct subnetworks can be identified that appear to encode tone-specific sensory features versus learned threat-related response structure.

To my knowledge, this may be the first study to comprehensively examine neural encoding of fear generalization in prelimbic cortex (PL). The manuscript is ambitious and technically interesting, and several aspects are potentially important. In particular, the suggestion that neurons showing graded, learning-related response patterns become selectively stabilized over time is intriguing. The inclusion of two CS+ training conditions and a no-shock control also strengthens the case that at least some of the reported effects are related to associative learning rather than simple sensory differences. However, in its current form, the manuscript does not yet fully support the strength of the conceptual claims. Several issues limit confidence in the interpretation, including the possibility that repeated testing itself contributes to changes across days, uncertainty about the relationship between neural activity and freezing behavior, limited quantitative documentation of longitudinal cell registration, and a number of problems in figure clarity and statistical framing. Overall, the study contains promising observations, but the claims should be narrowed, and several analyses or controls would be needed to fully support the proposed framework.

Detailed Comments

(1) A general concern is that the repeated test procedure itself may contribute to extinction. Because the animals are exposed to multiple CS frequencies across multiple test days, and each tone is presented three times per session, some of the reported changes in behavior and neural activity across days could reflect extinction or repeated nonreinforced retrieval rather than the passage of time per se. This is especially relevant given that the manuscript makes claims about recent versus remote representations and representational drift over 30 days. At a minimum, the authors should discuss this limitation explicitly and temper claims about time-dependent changes. Ideally, they would include a control group in which animals are tested only once or twice (e.g., at an early and later time point with fewer CS frequencies), or a reduced-frequency testing design that minimizes extinction while still allowing evaluation of recent versus remote memory.

(2) More generally, some of the reported learning-related neural differences may be driven by behavioral differences, particularly freezing, rather than by learning or generalization per se. For example, animals that freeze more to certain frequencies may show corresponding neural response differences simply because freezing alters PL activity. The authors should examine this possibility more directly. Analyses testing whether recorded cells encode freezing behavior, or whether tone frequency-related neural differences remain robust when comparing high- and low-freezing epochs, would help determine whether the reported effects reflect learned stimulus value rather than behavioral state differences.

(3) A central feature of the manuscript is the analysis of neural response properties over an extended period of time, up to 30 days after learning. However, aside from a brief mention in the Methods that spatial registration was used, the manuscript provides very little quantitative information about this critical aspect of the study. The paper would be strengthened by including explicit metrics describing longitudinal cell tracking, such as the number and proportion of ROIs retained across all sessions, distributions of spatial-footprint correlations or centroid distances across days, and representative examples of matched imaging fields over time. Without this information, it is difficult to assess how strongly the longitudinal claims are supported.

(4) The text states that "Figs. 1c and 1d show GCaMP6f expression in PL, representative calcium footprints, and activity traces". However, the figure as presented does not clearly show all of these elements, at least not in a way that matches the description in the Results. The correspondence between text and figure should be corrected.

(5) The labeling of Figure 2a is insufficient for interpretation. The legend states that the panel shows raster plots of sound responsiveness, but the axes and scaling are not clearly defined. It is not clear from the figure what the x-axis represents, whether the y-axis corresponds to individual neurons, where the CS period occurs, or what the activity scale at the right denotes. Also, the term 'rasters' implies that spikes were analyzed. It seems that the spike inference approach (CASCADE) was only used for later analyses. Perhaps 'heat-plot' would be more accurate here? Generally, this figure should be annotated more clearly so that the reader can understand it without referring back to the Methods.

(6) In relation to Figure 3, the analysis of population-averaged responses across tone frequencies is useful, but the manuscript would be stronger with additional statistical analyses across time and across groups. For example, if the authors want to argue that learning induces graded changes in neural responses and that these evolve across time, they should directly compare within-group responses across days and also compare matched frequencies between the conditioned groups and the no-shock controls. These analyses would help establish whether the observed differences are genuinely learning dependent and whether they change significantly over time.

(7) The inclusion of two different CS+ frequencies and a no-shock control is a strength of the study and substantially improves the interpretation that graded neural responses are related to learning and generalization rather than to simple sensory processing or passage of time. That said, I am not entirely comfortable with the use of the term "inference" throughout the manuscript. What is being measured here appears closer to sensory generalization than inference in a stronger cognitive sense. The current task does not clearly require that animals infer hidden structure or stimulus value through abstract reasoning; rather, the generalized stimulus may simply be treated as similar to the conditioned cue. The terminology should therefore be reconsidered or softened.

(8) I also found the use of the term "valence" somewhat problematic. The manuscript appears to use valence to refer to graded responding across tones with different aversive significance, but valence typically refers more broadly to distinctions between appetitive and aversive value. Here, terms such as "threat value," "aversive value," may be more precise. The authors should consider revising this language throughout.

Reviewer #3 (Public review):

Summary:

Human and animal trypanosomiasis are fatal illnesses caused by African trypanosomes transmitted by tsetse flies during a bloodmeal. Thus, tsetse fly feeding is the key physical step in disease transmission to mammals. Tsetse fly feeding is not a new story, but it is revisited here through the application of sophisticated imaging techniques and novel biomechanical methods of analysis. The author's aim is to provide a high-resolution picture of the structures and forces involved in feeding to provide mechanistic insights into the process of feeding, from attachment, penetration, drinking and retraction of the feeding parts.

Largely the authors have achieved their aims. They (i) examine the structures and forces involved in attachment; (ii) they provide detailed multi image analysis of the proboscis providing insights into its probing ability and physical mechanism of penetration; (iii) they conduct a controlled analysis of the physical forces involved in penetration and report that they are in the low nM range, not especially strong but much higher that the mosquito bite and finally they provide a first analysis of blood uptake during feeding.

Strengths:

The study images the tsetse fly feeding structures in unprecedented detail, with resolution to the uM scale, in 3-D, and during feeding. The resulting images are dramatic and insightful (and beautiful and frightening!) that researchers interested in trypanosomes, tsetse flies or blood feeding by flies in general will want to see.

They conclude that flies attach strongly to smooth surfaces, because of interactions possible via the array of acanthae of the pulvillus pad at the ends of the tarsi. The estimated attachment forces are similar in male & female flies, in the low mM range (they look impressively strong in video 1). They provide a very striking analysis of the proboscis and labellum and associated tooth structures (Figs 4 & 5). I recall many years ago observing that tsetse flies are messy feeders, and these structures, especially the rasping teeth structures on the reverse folded labial tips explain why! This seems more like a chainsaw than a jigsaw in action, but the authors are probably correct that these structures and probing/retraction mechanism explain many features of tsetse fly feeding and their ability to feed on a wide range of hosts with very different skin types.

The impressive aspect of this paper is the range of imaging techniques, (CLSM, SEM, uCT, FIB SEM), the quality of the images which attests to the obvious care taken with sample preparation. The biomechanically analysis, especially the penetration analysis is impressive. Finally, the paper is clearly written and presented, it was a very easy read and overall, a very engaging study.

Weaknesses:

I suppose it could be said that the paper is a descriptive study; it doesn't really test a hypothesis but that is not a prerequisite for publication. Perhaps the least convincing prats are the imaging of the flexible v rigid parts of the structures, which is based on amount of resilin (flexible) and chitin-protein (stiff) based on their autofluorescence. In seems odd that the joints would be less blue (stiffer) in Fig 1i, or what the blue structures correspond to in Fig. 6B-D.

Comments on revised version.

In revised version these issues have been satisfactorily addressed

Reviewer #1 (Public Review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers.]

Summary:

This study aims to understand how cell fusion contributes to wound healing using a laser-induced injury in the notum epithelium of a developing fruit fly. The authors meticulously characterize the epithelial fusion events using a live imaging approach and report that syncytia arise by 'border breakdown' and 'cell shrinking'. The syncytial epithelial cells also appear to outcompete mononucleated cells and preferentially dissolve their tangential borders, which correlates with the accumulation of actin at the leading edge.

Strengths:

The strength of this study is the authors' live imaging approach to capture these dynamic fusion events that are a fundamental yet poorly understood biological process.

Reviewer #1 (Public review):

Summary:

This study asks how selection for male aggressiveness affects life-history and reproductive fitness traits in Drosophila melanogaster males.

Strengths:

Multiple comprehensive assays are used to address the question.

Weaknesses:

(1) The flies used for comparisons are inadequate. Behavioral assays compare Bully males mated top non-coevolved Cs females with Cs males mated to coevolved Cs females.

(2) Lifespan analysis is done on male progeny of Cs females mated to either genetically more distant Bully or co-evolved Cs males, the longer lifespan and performance on the former is interpreted as trade-off with aggressiveness, rather than a simple explanation of hybrid vigor.

(3) Differences in CHCs between Bully and Cs males and Cs females mated to those males are not shown to cause difference in measured behavioral outcomes.

Comments on revised version.

I appreciate authors responding to reviewer's comments. The inclusion of additional Bully lines in behavioral analysis, and Bully homozygous male progeny in lifespan analysis gives more strength to the authors' conclusions. It does not exclude other possible explanations for the observed results, but now authors note genetic drift as an alternative explanation for some of their results.

I do want to point to a potential misunderstanding of male-female co-evolution by authors. The authors state that "The Bully lines used in our work were derived from Canton-S flies and thus did co-evolve with Cs". This statement is incorrect if the process of selection and line maintenance in this study was the following:

In my understanding to create Bully lines the most aggressive males were first chosen from an ancestral Cs line and their most aggressive male progeny were mated to their sibling females, repeating the process for 37 generations. Therefore, Bully females were co-evolving with Bully males during selection process of over 37 generations, while Cs females were staying co-evolved with their own males, since they mated within the line. Moreover, after aggressive lines were created, they were kept separate from each other, and from Cs line since about the year 2010, until the experiments described in the paper were performed (which must over 10 years?). Over 10 years, a significant genetic drift can happen, that changes allele frequencies, and may results in differences in male-female co-evolved traits and in lifespan that are unrelated to selection for aggression.

Also, decapitating females does not completely prevent female influence over mating process, but just removes central brain control over it. In Drosophila, however, the main control over copulation process for males and female is not central. Therefore, you do not completely remove the effect of coevolved or non-coevolved female traits over copulatory and post-copulatory processes.

Reviewer #1 (Public review):

Summary:

Deng and colleagues pursue the possibility that red light exposure can provide some benefits and anti-senescence effects in aged mouse models. In addition, they show how red light influence metabolism in cultured keratinocytes. The authors provide a long dissection of the potential paths involved in the changes promoted by red light exposure, identifying CytC oxidase, SIRT4, PPARa and MCD as key players.

Strengths:

The authors did a thorough exploration of the multiple potential avenues by which red light exposure influence metabolism. The in vitro and in vivo evidence nicely complement each other.

Weaknesses:

This is a challenging hypothesis that would require some additional experimental controls. The pathway dissection, while extensive, sometimes is approach in unconvincing ways and the results are not always evident to judge or interpret. Technically, the western blots and transcriptomic analyses require notable improvements.

Comments on revised version.

The revised version of the manuscript provides some improvements. However, I feel that many aspects remain poorly addressed. In the authors' favour, many of these limitations are now acknowledged in their rebuttal, as well as in the discussion section.