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    1. 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:

      From a big picture viewpoint, this work aims to provide a method to fit parameters of reduced models for neural dynamics so that the resulting tuned model has a bifurcation diagram that matches that of a more complex, computationally expensive model. The matching of bifurcation diagrams ensures that the model dynamics agree on a region of parameter space, rather than just at specially tuned values, and that the models share properties such as qualitative features of their phase response curves, as the authors demonstrate. A notable point is the inclusion of extracellular potassium concentration dynamics into the reduced model - here, the quadratic integrate-and-fire model; this is straightforward but nonetheless useful for studying certain phenomena.

      Strengths:

      The paper demonstrates the method specifically on the fitting of the quadratic integrate-and-fire model, with potassium concentration dynamics included, to the Wang-Buzsaki model extended to include the potassium component. The method works very well overall in this instance. The resulting model is thoroughly compared with the original, in terms of bifurcation diagrams, production of various activity patterns, phase response curves, and associated phase-locking and synchronization properties.

      Weaknesses:

      It is important to note that the proposed method requires that a target bifurcation diagram be known. In practical terms, this means that the method may be well suited to fitting a reduced model to another, more complicated model, but is not likely to be useful for fitting the model to data.

    1. 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, 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.

    1. Reviewer #1 (Public review):

      Summary:

      In this study, the authors elegantly combined latent variable models (i.e., HMM, GPFA and dynamical system models) with a calcium imaging observation model (i.e., latent Poisson spiking and autoregressive calcium dynamics (AR)).

      Strengths:

      Integrating a calcium observation model into existing latent variable models improves significantly the inference of latent neural states compared to existing approaches such as spike deconvolution or Gaussian assumptions.

      The authors also provide an open-source access to their method for direct application to calcium imaging data analysis.

      Weaknesses:

      As acknowledged by the authors, their method is dependent on the quality of calcium traces extraction from fluorescence videos. It should be noted that this limitation applies to alternative strategies.

      While the contribution of this study should prove useful for researchers using calcium imaging, the novelty is limited, as it consists of an integration of the calcium imaging model from Ganmor et al. 2016 with existing LVM frameworks.

      Comments on revised version.

      The authors addressed my comments and I have no further concerns.

    1. Reviewer #1 (Public review):

      [Editors' note: This revised version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have satisfactorily addressed the substantive comments raised in the previous round of review. The qualifications and limitations are now more clearly acknowledged in the revised manuscript.]

      Summary:

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

      Strengths:

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

      Comments on previous version:

      The authors have made efforts to address most of the previous concerns, and several points have been clarified or improved in the revision. However, in a number of cases, the responses rely more on acknowledgment and reframing rather than substantive analytical strengthening. Overall, the manuscript is improved, particularly in terms of clarity, transparency, and positioning of claims. I support its publication and look forward to seeing how the field engages with and discusses these claims.

    1. Reviewer #1 (Public review):

      Summary:

      The manuscript entitled "Autonomic reflex plasticity associates with time-dependent SUDEP susceptibility in a murine model with hyperactive stress circuits" by Dr. Saunders and colleagues combined a traditional mouse model of SUDEP, ventral intrahippocampal kainite (vIHKA) injection, with a genetic model of chronic hyperactivity of central corticotropin-releasing hormone (CRH) neurons (Kcc2/Crh) that further increases the risk of SUDEP in the weeks following seizure.

      Strengths:

      Their results show during spontaneous seizures Kcc2/Crh mice had more pronounced reflex-like ictal bradycardias compared to WT controls that notably occurred prior (~10 sec) to seizure termination and had greater autonomic disturbances compared to WT controls, including a pronounced serotonin-mediated Bezold Jarisch reflex. These results show chronic hyperactivity of central corticotropin-releasing hormone (CRH) neurons (Kcc2/Crh) increased autonomic disturbances and risk of SUDEP in a kainic acid model of epilepsy.

      Weaknesses:

      This study could be improved with a more thorough assessment of heart rate, blood pressure and breathing during and following the seizures, and in particular the fatal event. It is unclear if the bradycardias were spontaneous, or a result of preceding central or obstructive apneas, oxygen desaturations, hypercapnia, arrhythmias, or other possible triggers.

      Considerable prior work in the literature suggests SUDEP could be mediated, in some patients, by a burst of parasympathetic activity to the heart. Were the heart rate changes in these animals during seizures inhibited or blocked by atropine, or atenolol? The injection of the 5HT agonist phenylbiguanide into the right jugular is not a selective approach for activating the Bezold Jarisch Reflex (BJR) which is caused by increased activity of intracardiac sensory neurons (generally activated with ischemia or a combination of low preload with high contractility). The results should be interpreted more cautiously, as a response to systemic administration of phenylbiguanide only.

    1. 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:

      This work asks the question of how different organelles and structures in the apicomplexan parasite Toxoplasma gondii are recycled and/or segregated to the daughter cells during cell replication. In particular, they consider an unusual cell structure called the residual body that links replicating cells during the intracellular infection stage of this parasite. The residual body has historically been considered a 'dumping ground' for unnecessary relics of the mother cell during division, but this notion is increasingly being revised. Indeed, cell replication in Toxoplasma is often misinterpreted as cell division (cytokinesis), but in fact, the cell replicates its organelles and structures to multiple 10s of copies in seemingly distinctly formed daughter cells, but cytokinesis is delayed for many such cycles and typically only occurs simultaneously with parasite egress from its host cell. The residual body is, in fact, the connection between these pre-cytokinetic replicated daughters, and effectively, this is still a single cell at this stage. The authors have previously shown that an actin network extends through the residual body between these daughter cells, and ER and mitochondria common to all cells are also linked through this structure. This study examining the fates of organelles during cell replication is timely for continuing our understanding of how this fascinating component of the cell participates in these processes. The authors use Halo-tags as their principal tool to track discrete populations of proteins, labelling their organelle locations, and this provides beautiful insight into these processes.

      Strengths:

      Using dyes conjugated to Halo tags this work elegantly tracks the fates of proteins synthesised by an original 'mother' cell over several replication cycles of pre-cytokinetic 'daughters'. Using this tool, they show that some organelles are made intact just once and that some of these can be subsequently sorted to the daughters (micronemes and rhoptries) while others are dismantled (IMC) and the daughters must make their own. A third set of organelles (largely synthesis, sorting and metabolic compartments) are divided and inherited, and new daughter-synthesised proteins are added to the preexisting maternal proteins in these structures. A role for actin and myosin is clearly demonstrated for micronemes and rhoptries, and this correlates with their relatively late inheritance into the developing daughters. Overall, this work gives clarity to the behaviours of several cell structures during replication and paves the way to better understanding the mechanisms that drive the differences between structures and the universality of these processes in other apicomplexan parasites. In particular, this study shows that the residue body is a region of the cell syncytium that organelles can be actively transported from. Therefore, it is a space that can actively contribute to the segregation of the late segregating micronemes and rhoptries.

    1. Reviewer #1 (Public review):

      Summary:

      This study demonstrates that nutrient resorption efficiency (NuRE) in Phragmites australis is genetically canalized rather than plastic to salt stress. Using 110 genotypes in a common garden, the authors show that intraspecific variation in NuRE is explained by phylogeographic lineage, ecotype, and latitude, not by effective salinity. Element specific regulatory strategies further reveal how N, P, and K resorption are differentially controlled. At the population level, this is an important study that fundamentally advances our understanding of plant functional trait evolution and its implications for ecosystem nutrient dynamics under global change.

      Strengths:

      This study is the first to demonstrate genetic determination of a key nutrient conservation trait under effective salt stress in a widespread macrophyte, directly testing the 'plastic acclimation versus inherent conservatism' paradigm in a non-nutrient stress context. The experimental design is rigorous: each genotype was paired across control and salt treatments, and multilevel stress effectiveness (metabolomics, biomass, Na accumulation) was confirmed before evaluating NuRE. The large sample size of a macrophyte and dual classification (phylogeography + ecotype) allow robust disentangling of genetic versus plastic sources of variation.

      The analysis comprehensively tests three resorption control hypotheses using appropriate SMA regression, revealing element specific and condition dependent patterns. The latitudinal gradient and variation partitioning provide strong evidence that genetic origin and geographic context outweigh short term plasticity, with important implications for predicting ecosystem nutrient cycling under global change. This study provides a clear empirical demonstration that a key nutrient conservation trait can remain homeostatic under non nutrient stress, and that intraspecific variation is primarily a product of population differentiation rather than short term plasticity.

      Weaknesses:

      First, the salinity treatment spanned only one growing season. The conclusion of genetic canalization therefore specifically refers to the absence of plasticity to an acute salt shock. Whether long term, multigenerational chronic salinity could act as a selective agent or induce transgenerational plasticity remains an open and interesting question for further research. Likewise, the physiological mechanisms underlying the observed lack of plastic increase in NuRE (for example, phloem loading or senescence gene expression) are not directly resolved, leaving some inference about trade-offs versus true unresponsiveness. These points do not weaken the study's main conclusion. Instead, they suggest productive future directions, such as longer-term field manipulations and targeted molecular investigations.

      Second, the test of nutrient limitation control relies on resorbed N:P and N:K ratios as proxies, an established but indirect approach. Direct nutrient addition experiments would provide stronger causal evidence. Also, the metabolomic analysis is used primarily to validate stress effectiveness; deeper integration of specific metabolites with NuRE variation across genotypes could have offered mechanistic insights but was not pursued. Additionally, the potential collinearity between ecotype and phylogeographic lineage among Chinese populations is not quantitatively addressed. None of these considerations undermine the main finding, which is supported by a robust experimental design and widely accepted analytical approaches.

      Comments on revised version.

      The author carefully revised the parts that might cause confusion.

    1. Reviewer #1 (Public review):

      Summary:

      In this study, the authors trained mice to perform a memory-guided navigation task, in which they must navigate to a previously cued arm after a delay period. They optogenetically inhibited the dorsal hippocampus or mPFC (targeting PL) in different task epochs. They found that for both regions, inactivating at the beginning of the navigation epoch impaired performance and induced mice to revert to habitual side biases. Inactivating during other epochs, including a delay period before the navigation phase, had little or no impact on behavior. The relationship between trial duration and behavioral performance was differentially impacted by hippocampal and mPFC inactivation, suggesting that the nature of the deficits was somewhat different.

      Strengths:

      The effects of perturbations are robust across animals and generally convincing. The lack of effect at some task epochs serves as a nice internal control. The finding that hippocampus and mPFC inactivation produced subtly different effects is interesting.

      Weaknesses:

      The simplicity of the behavior makes it difficult to resolve how exactly the hippocampus and mPFC contribute to working memory. Also, the language does not always reflect the trends in the data: the authors claim that optogenetic perturbations cause mice to repeat previous choices, but the data show that perturbations increase the likelihood of choosing a preferred side (which is left for most mice). A side bias is not the same as choice repetition. This has implications for interpreting the nature of the behavioral effects.

    1. 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:

      This manuscript uses sci-L3-Strand-seq to map sister chromatid exchange events following CRISPR/Cas9-induced DNA damage. Because exchanges between identical sister chromatids are largely invisible to conventional sequencing, the study addresses an important blind spot in the assessment of genome editing outcomes. The authors compare single-locus Cas9 cleavage, simultaneous targeting of 237 repetitive genomic sites, and Cas9 nickase variants. They further use reciprocal daughter-cell pair analysis to ask whether Cas9-associated SCEs are copy-neutral or linked to larger structural alterations. Overall, this is a valuable study that introduces an important additional layer to the analysis of CRISPR/Cas9 repair outcomes. The central finding that Cas9-induced DSBs can trigger frequent local SCE is well supported and likely to be of broad interest.

      Strengths:

      The major strength of the manuscript is the application of a strand-resolved, single-cell method to a question that is difficult to address with standard genome sequencing. The evidence that a single Cas9-induced DSB can trigger strong local SCE is compelling in concept and supported by multiple guide RNAs targeting distinct loci. The reported on-target SCE frequencies, reaching up to 41%, suggest that inter-sister exchange is a substantial and underappreciated outcome of Cas9 cleavage.

      Of particular interest is the comparison between single-site and multi-site targeting. The finding that 237 programmed Cas9 targets produce only mild bulk enrichment of on-target SCE but stronger enrichment in a subpopulation of cells with elevated SCE burden is interesting and may have wider biological implications, particularly if the findings extend beyond Cas9-induced SCE to spontaneous SCEs.

      The reciprocal daughter-cell pair analysis is another notable feature of the study. The observation that some Cas9-associated SCEs are accompanied by structural alterations could challenge the assumption that SCE after a programmed break reflects error-free homologous recombination.

    1. Reviewer #1 (Public review):

      In this manuscript, the authors present ClustIRR, a computational tool that analyzes multiple TCR repertoires together, instead of one at a time. It builds one shared similarity graph across all the repertoires, then finds communities (CJs) on that graph that can be compared across samples. Building one shared graph across repertoires, rather than clustering each repertoire on its own, is a real improvement over existing tools. However, there are a few concerns that need to be addressed.

      (1) The Introduction motivates ClustIRR by contrasting it with beta-binomial regression, Fisher's exact test, and scCODA/tascCODA (lines 62-77), but none of these are actually run on the same data in the Results. Could the authors include a direct comparison, e.g., applying a standard beta-binomial or Fisher's exact test to the Dataset 1 CJ occupancy matrix, to show the Bayesian model gives a lower false-positive rate or better-calibrated intervals than the alternatives it's positioned against?

      (2) Prior predictive and posterior predictive checks are both reported as "(data not shown)" (lines 644, 728). Since the manuscript's central claim is rigorous, uncertainty-aware inference, it would help to include these diagnostic plots, along with Rhat and ESS values, in the supplement rather than stating they were checked.

      (3) With 7,505 CJs tested simultaneously for differential occupancy in Dataset 1 alone (Figure 1 legend), what is the expected false discovery rate under the non-overlapping-HDI criterion used throughout? A short discussion of multiple-comparisons correction, or an argument for why it isn't needed under this framework, would strengthen the statistical claims.

      (4) Line 115 states the Dataset 1 joint graph produced 10,301 CJs, of which 3,038 were singletons, leaving 7,263 non-singleton CJs. The Figure 1 legend reports 7,505 CJs used for the β modeling. Could the authors clarify how these two numbers relate - whether some singletons were included in the model, or a filtering step was applied that isn't described in Methods?

      (5) The Methods section states that archival pretreatment tumor tissue was available for four patients (Pt4, Pt32, Pt36, Pt38; line 531), but the T+/T- DCJ analysis in Fig. 3B-C is only shown for Pt4. Was this analysis attempted in the other three patients? Extending it, even partially, would substantially strengthen the claim that contracting DCJs are enriched for tumor-infiltrating TCRs, which is currently based on a single patient.

      (6) Dataset 1 was generated by deliberately stimulating T cells with EBV or MART1 antigen, so recovering EBV/MART1-annotated CJs from VDJdb is closer to a positive control than a blinded validation. Do the authors have, or could they obtain, any independent confirmation (e.g., tetramer data or an orthogonal cohort) for the CJs with large β that lack VDJdb annotation (orange dots, Figures 1B-C)?

    1. Reviewer #1 (Public review):

      This meta-analysis addresses long-standing questions about the reliability and interpretation of choice probability in macaque visual areas, and provides some important findings (e.g., the cross-study consistency of the CP-sensitivity relationship, V1 distinctiveness). However, the evidence for several claims is incomplete: the analysis does not consider the statistical dependence of data points from the same studies and monkeys, and both the bistable-stimulus effect and the stimulus-duration effect rely on interpretive assumptions.

      Strengths:

      The paper's transparency about its own limitations is a genuine strength. Several sections of the paper and the supplement report null results (task exposure, lapse rate, eccentricity) rather than omitting them. This kind of self-scrutiny is uncommon in meta-analyses and substantially increases confidence in the parts of the analysis that do hold up.

      Weaknesses:

      (1) No mixed/hierarchical statistical models for nested data. The paper considers 150 data points from 59 studies and treats them as independent samples, though many share monkeys and brain areas. This reduces the confidence in the reported p-values. A standard way of dealing with this would be to use mixed-effect models with random intercepts rather than OLS.

      (2) Evidence for one of the main findings in the abstract ("First, CPs were higher in tasks involving bistable percepts, reinforcing the link between CP magnitude and subjective perception.") is weak. This effect relies entirely on studies using bistable rotating cylinder stimuli performed in a single lab (lines 702 - 711). I would suggest making this more explicit in the abstract / discussion and in Figure 8b,c.

      (3) The interpretation of main drivers of CP is unclear. The discussion summarizes the 4 main drivers of CP as "four systematic drivers of this variability: neuronal sensi758tivity, brain area, stimulus duration, and task type." The independent contribution of task type is however, questionable. In line 623, it is stated that the difference between coarse and fine discrimination can be entirely explained by the difference in sensitivity (explained possibly by differences in optimizing the stimuli). Again, detection tasks (line 658) show a trend for higher CP because most studies used tailored stimuli from single-recording experiments. Bistable task: see point 2. Thus, all "task effects" can be attributed to confounds, and the claim of the "four drivers of CP" should be revised.

      (4) The paper could be improved by a Discussion that synthesizes the results in a concise manner. Now it seems more like a re-iteration of the results. Overall, I appreciate that the paper is thorough and discusses many of the caveats. However, those are somewhat buried in the long subsections, and I fear that the quick reader may walk away with a stronger impression of "four robust independent drivers" than the text, read carefully, actually supports.

      (5) Datapoints are not weighted according to their standard error (common practice in meta-analysis is inverse-variance weighting). The concern is that underpowered studies with high variance (e.g., due to a low number of recorded neurons) have the same impact as well-powered studies, and this may change some of the estimates. For example, Supplementary Figure 4 shows that mean CP values decrease with statistical power of the study, consistent with the concern. If SEMs are not available, could the authors show the robustness of the results by weighting by sample size as a partial check?

      (6) Interpretation of feed-forward vs. feedback origin of CP [Disclosure: I am an author of Wimmer et al. 2015.]. This paper presents a mechanistic network model of area MT and a decision area that decomposes CP into two components with distinct time courses, and, directly relevant to Section 2.6, shows how a combination of an early feedforward and a late feedback component can produce a roughly time-invariant (flat) CP. This is a specific, quantitative instance of the "sustained plateau" pattern the authors themselves note is inconsistent across studies (lines 480-486) but don't develop further. Engaging with this model in Section 2.1/2.6 would let the authors contrast their duration-effect interpretation against an explicit dynamical model rather than the generic feedforward/feedback dichotomy in Figure 7a.

      (7) Reaction-time experiments. I am worried that differences in CP in RT vs. fixed duration tasks (Supplementary Figure 12) could have an influence on the main regression analysis (because RT experiments are mostly from detection tasks, and because RT experiments presumably include less of a post-decision period). Could this factor be included in the main analysis?

    1. Reviewer #1 (Public review):

      Summary:

      The manuscript presents several reinforcement learning (RL) approaches to control activity in small, ring-shaped neural networks. The paradigm is to find temporally and spatially patterned stimuli applied to axons that maximize the length of activity propagation along the network. Several RL versions were compared. Some RL-designed stimulation patterns worked better than others.

      Strengths:

      The work is technically and statistically very sound, and important controls were done that are missing in some earlier work along this line of research. The statistics and technical solutions seem solid, though I am no specialist in RL. The figures are well done and informative, with matching quality of the captions. The work presented is of value mainly for someone who wants to build a good closed-loop stimulation system to experiment with neuronal networks in-vitro.

      Weaknesses:

      The manuscript appears undecided about whether it wants to be about RL control, about a technical implementation of long-term stimulation in vitro, or about the properties of neuronal networks and interaction with them. The introduction is well written, comprehensive and insightful, focusing on biological aspects. Methods are then extensively about RL algorithms, without explaining why several were used or why these in particular, but with specialist language hard to understand for neuroscientists. The results then quantitatively compare the performance of the RL but do not really explain what this teaches us about neuroscience or what we learn about the networks beyond that they can be stimulated for longer propagation patterns. Extensive supplementary material almost advertises the hardware built by the team. Some figures suggest, though I'm not 100% certain about this, that different algorithms find different optimal stimulation patterns in the same network - which I find puzzling. What then does this tell us about the stimulation patterns and the variability of the responses? There is some speculative mechanistic reasoning, but no data to support this further. The conclusions hardly address the initial motivation of the manuscript. To me, it is not clear what can be learned that was not, in one way or another, presented previously, with as well as without RL.

    1. Reviewer #1 (Public review):

      Summary:

      The authors investigated somatosensory processing along the afferent somatosensory pathway (cuneate nucleus, thalamus, S1) in a group of spinal cord injury patients and a group of controls. They propose that reduced motor function in SCI patients would reduce bottom-up activity; thus, recorded activity in SCI patients would reflect top-down modulation of overt or attempted movements.

      Strengths:

      (1) Strong methods.

      (2) Experimental and control groups.

      (3) Strong writing.

      (4) Results well presented.

      (5) Appropriate statistics.

      Weaknesses:

      Some results (or lack of) cast doubt about the ability of the used technique (3T fMRI) to detect the desired effects (bottom-up vs top-down activity).

    1. Reviewer #1 (Public review):

      Summary:

      This manuscript uses a valuable dataset of simultaneous LC single-unit recordings and pupillometry in awake monkeys to examine one aspect of the relationship between LC activity and pupil diameter: whether baseline LC activity predicts evoked pupil and whether baseline pupil predicts evoked LC. These relationships are largely absent in the present dataset, and the authors conclude that this type of prediction is not reliable.

      Strengths:

      This is a valuable dataset of simultaneous LC single-unit recordings and pupillometry in awake monkeys, the within-modal and within-epoch analyses are sound. The new results further caution the use of pupil diameter to infer LC activity.

      Weaknesses:

      There is an obvious rationale for asking whether baseline LC relates to baseline pupil or evoked LC relates to evoked pupil. It is also obvious to ask about the relationship between baseline and evoked LC activity, and between baseline and pupil responses. However, the rationale for the cross-modal and cross-epoch analysis is not clear. Why should one expect baseline LC to predict evoked pupil, or baseline pupil to predict evoked LC? What is the biological importance of such predictions? These analyses simultaneously change the modality and the temporal domain.

      Furthermore, some recent studies, which are not referenced in this manuscript, showed variability in the relationship between pupil and LC within the same epoch, and that tonic and phasic pupil responses could be regulated by different inputs to LC. Given that the pupil-LC coupling is readily imperfect and potentially controlled by different cellular and circuit mechanisms, it is not surprising that their cross-epoch relationship is even more variable.

      One main analysis that correlated baseline pupil with evoked LC showed statistically different results between the two monkeys, raising the question of to what extent a general claim for the cross-modal cross-epoch analysis can be made.

    1. Reviewer #1 (Public review):

      Summary:

      The authors asked whether neurofeedback during competing continuous speech can help to modulate the attention-related N1-component in the temporal response function (TRF), which is an event-related-response-like estimate of the phase-locked EEG activity following the envelope. The research question is relevant because it asks to what degree the strength of attention can be controlled beyond the binary decision to attend or ignore something, and whether this control is beneficial for the behavioral outcome.

      Strengths:

      (1) Sample size of 56 participants.

      (2) Control group with sham feedback.

      (3) Novelty: Under-explored field of neurofeedback in selective speech tracking.

      (4) Pragmatic and reasonable methodological decisions.

      (5) Transparent results not hiding the fact that effect sizes are small.

      Weaknesses:

      Besides some need for clarification, I could only find one methodological weakness, which the authors discuss anyway:

      (1) Overall, speech tracking-based neurofeedback may lead to more robust results, because the N1-extraction does not have to be handcrafted and all components would be taken into account. As the authors state, the P2-component has been related to effort, and this may provide more "room to play" for voluntary modulation.

      The following "weaknesses" are related to the impact of the results:

      (2) Non-translating effects to post-training trials, neither neurally nor behaviorally.

      (3) Neurofeedback-related Modulation of N1

    1. Reviewer #1 (Public review):

      This work provides a valuable toolkit for endogenous isolation of projection neuron subtypes. With further validation, it could present a solid method for low-input ribosome affinity purification using a ribosomal RNA (rRNA) antibody. The experimental evidence for the distinct ribosomal complexes is limited to this method and indirect support from complementary analyses of pre-existing data. However, with additional experimental data to support the specificity of ribosomal complex pulldown and confirmation of the putative ribosomal complex proteins of interest, the study would provide compelling evidence for translation regulation of neuronal development through compositional ribosome heterogeneity. This work would be of interest to neuroscientists, developmental biologists, and those studying translational networks underlying gene regulation.

      Strengths

      (1) This in vivo labeling of specific projection neurons and ribosomal rRNA affinity purification method accommodates a low input of <100K somata per replicate, which is useful for the study of neuronal subtypes with limited input. In principle, this set of techniques could work across different cell types with limited input depending on the molecule used for cell type labeling.

      (2) The authors are also able to isolate endogenous neurons with minimal perturbation up to the point of collection, preserving the native state for the neuron in vivo as long as possible prior to processing.

      (3) This study identified over a dozen potential non-ribosomal proteins associated with SCPN ribosomal complexes, as well as a ribosomal protein enriched in CPN.

      Limitations

      (1) In this study, the authors address the advantages of their ribosomal complex isolation method in SCPN and CPN against RPL22-HA affinity purification. While this does show more pull down of the ribosomal RNA by the Y10B rRNA antibody, the authors claim this method identifies cell-type specific ribosomal complex proteins without demonstrating a positive control for the method's specificity. There are very limited experiments to truly delineate how "specific" this method is working and whether there could be contamination from other complexes bound by the antibody. I see this as the major limitation that should be addressed. To boost their claims of capturing cell-type specific ribosomal complexes, the authors could consider applying their rRNA affinity purification pipeline to compare cell-types with well-characterized ribosome-associated proteins, like mouse embryonic stem cells and HELA cells. The reviewer can completely appreciate the elegance in the neural characterization here, but it seems there needs to be a solid foothold on the specificity of the method, perhaps facilitated by cell types that can be more readily scaled up and tested.

      (2) The authors followed up on their differentially enriched ribosomal complex proteins by analyzing ribosome association of these proteins in external datasets. While this analysis supports the ribosome-association of these proteins, there is limited experimental validation of physical association with the ribosome, much less any functional characterization. The reciprocal pulldown of PRKCE is promising; however, I would recommend orthogonal validation of several putative ribosomal complex proteins to increase confidence. Specifically, the authors could use sucrose gradient fractionation of SCPN and CPN, followed by western blot to identify the putative interaction with the 80S monosome or polysomes. This would also provide evidence towards the pulldown capturing association with mature ribosome species, which is currently unclear. This experiment would provide substantial evidence for the direct association of these non-ribosomal proteins with subtype-specific ribosomal complexes.

      (3) The authors state interest in learning more about the differences underlying translational regulation of projection neuron development. This method only captures neuronal somata, which will only capture ribosomes in the main cell body. There are also ribosomes regulating local translation in the axons, which may also play a critical role in axonal circuit establishment and activity. These ribosomal complex interactions may also be rather transient and difficult to capture at only one developmental stage. Therefore, this method is currently limited to a single developmental snapshot of ribosomal complexes at P3 within the main cell body. It would be exciting to see extended utility of this method to sample neurites and additional developmental stages to gain further resolution on the developmental translation regulation of these projection neurons.

      Likely impact of the work on the field, and the utility of the methods and data to the community

      The authors introduce a unique pipeline of techniques to identify cell-type specific ribosomal complex compositions. With more validation, there is certainly potential for those studying neuronal translation to leverage this method in limited primary cells as an alternative to existing methods that do not rely on ribosomal protein tagging, such as ARC-MS (Bartsch et al., 2023), RAPIDASH (Susanto and Hung et al., 2024), and RAPPL (Nature Communications, 2025).

      Comments on revised version.

      We thank the authors for their thorough response to our comments. The revised manuscript satisfactorily addresses most reviewer comments through clarification and expanded discussion, although we believe some important limitations remain. In particular, we continue to view experimental validation of the identified ribosome-associated proteins as an important component of introducing this methodology to the field, rather than work that falls beyond the scope of the study. The authors have acknowledged that these experiments are future directions, and it is clear they plan to pursue additional validation outside of the current manuscript. Given their emphasis that the primary contribution is the development of a methodological framework, we believe the work may be appropriately framed as a Tool and Resource article. Such positioning would better align reader expectations with the manuscript's strengths as a technical advance while recognizing that further validation and functional characterization will be needed in future studies. Despite these limitations, I believe the manuscript makes a valuable methodological contribution.

    1. Reviewer #3 (Public review):

      Summary:

      This manuscript presents a well-designed study examining human adaptation to room acoustics, building on prior work. The psychophysical results are convincing and add meaningful knowledge to our understanding of reverberation learning. The transcranial magnetic stimulation (TMS) component shows a role of prefrontal cortex in this listening task, targeting dorsolateral prefrontal cortex (dlPFC). Cautious interpretation of the TMS results is warranted, especially given the modest statistical effects, the fact that the main TMS result of interest is a null result, and the limited ability of TMS to precisely target dlPFC in individual subjects. A surprising and interesting finding in the study is that listeners performed the speech recognition task more poorly in anechoic conditions than in those with naturalistic levels of reverberation. This is likely due to contributions of spatial release from masking provided by reverberation acoustics, which may counteract the detrimental effects of reverberation on speech perception itself. Overall, the experiments are well performed and clearly presented, improving our understanding of how the brain copes with reverberant environments.

      Strengths:

      (1) Well designed acoustical stimuli and psychophysical task.

      (2) Comparisons across room combinations is well conducted.

      (3) Virtual acoustic environment is impressive and applied well here.

      (4) Timely study with interesting behavioural results.

      (5) Causal evidence of a role for dlPFC in reverberation learning.

      Weaknesses:

      (1) Poorer performance in anechoic environments than some reverberant environments suggests and interplay of spatial release from masking and speech intelligibility that are not fully unpicked here. This could be controlled in future experiments, for example by comparing monaural and binaural listening conditions.

      (2) Lack of evidence for targeting TMS to dlPFC in individual participants. This is simply a limitation of the technique which the reader should keep in mind.

      (3) Most interesting effect of TMS is a null result compared to a weak statistical effect for "meta-adaptation"

    1. Reviewer #1 (Public review):

      The study by Luden et al. seeks to elucidate the molecular functions of AHL15, a member of the AT-HOOK MOTIF NUCLEAR LOCALIZED (AHL) protein family, whose overexpression has been shown to extend plant longevity in Arabidopsis. To address this question, the authors conducted genome-wide ChIP-sequencing analyses to identify AHL15 binding sites. They further integrated these data with RNA-sequencing and ATAC-sequencing analyses to compare directly bound AHL15 targets with genes exhibiting altered expression and chromatin accessibility upon ectopic AHL15 overexpression.

      The analyses indicate that AHL15 preferentially associates with regions near transcription start sites (TSS) and transcription end sites (TES). Notably, no clear consensus DNA-binding motif was identified, suggesting that AHL15 binding may be mediated through interactions with other regulatory factors rather than through direct sequence recognition. The authors further show that AHL15 predominantly represses its direct target genes; however, this repression appears to be largely independent of detectable changes in chromatin accessibility.

      In addition to the AHL protein family, the globular H1 domain-containing high-mobility group A (GH1-HMGA) protein family also harbors AT-hook DNA-binding domains. Recent studies have shown that GH1-HMGA proteins repress FLC, a key regulator of flowering time, by interfering with gene-loop formation. The observed enrichment of AHL15 at both TSS and TES regions, therefore, raises the intriguing possibility that AHL15 may also participate in regulating gene-loop architecture. Consistent with this idea, the authors report that several direct AHL15 target genes are known to form gene loops.

      Overall, the conclusions of this study are well supported by the presented data and provide new mechanistic insights into how AHL family proteins may regulate gene expression.

    1. Reviewer #2 (Public review):

      The authors initial goal was to demonstrate loss of PG during the slow sporulation process of Myxococcus xanthus, with examination of the PG degradation products in order to implicate possible enzymes involved. Upon finding a predominance of LTG products, they examined sporulation in strains lacking each of the 14 candidate LTGs encoded in the genome, leading to the identification of two sporulation-linked LTGs. An extensive characterization of the roles played by these LTGs. One LTG is responsible for the slow sporulation PG degradation, while another is required for the rapid sporulation process. Interestingly, the "slow" LTG seems to provide an important regulatory brake on the rapid enzyme. Single molecule fluorescent tracking of these enzymes was used to develop a model for their interaction with PG that mimics their observed activity. The rate of PG synthesis activity was also shown to impact the rate of PG degradation, suggesting potential interplay between the synthetic and degradative enzymes.

      Strengths:

      The genetic analysis to identify sporulation-linked LTGs and their effects on growth sporulation, and spore properties was well done and productive. The fluorescence microscopy to track LTG mobility, presumably tied to activity, produced a convincing argument about the mechanism of regulation of one LTG by another. The authors have responded well to all points of the previous reviews.

    1. Reviewer #1 (Public review):

      Summary:

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

      Strengths:

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

      Weaknesses:

      The authors did an excellent job addressing the weaknesses highlighted in my first assessment.

    1. Reviewer #1 (Public review):

      Summary:

      This is a study which used 7T diffusion MRI in subjects from a Human Connectome Project dataset to characterize the zona incerta, an area of gray matter whose involvement has been demonstrated in a broad range of behavioral and physiologic functions. The authors employ tractography to model white matter tracts that involve connections with the ZI and use clustering techniques to segment the ZI into distinct subregions based on similar patterns of connectivity. The authors report a rostral-caudal organization of the ZI's streamlines where rostrally-projecting tracts are rostrally-positioned in the ZI and caudally-projecting tracts are caudally-positioned in the ZI.

      Strengths:

      The paper presents robust findings that demonstrate subregions of the human ZI that appear to be structurally distinct using a combination of spectral clustering and diffusion map embedding methods. The results of this work can contribute to our understanding of the anatomy and structural connectivity of the ZI, allowing us to further explore its role as a neuromodulatory target for various neurological disorders.

      Weaknesses:

      There should be further discussion of the clustering methods employed and why they are appropriate for the pertinent data. Additionally, the limitations of analyzing solely the cortical connections of the zona incerta should be addressed, as anatomical studies of the ZI have shown significant involvement of the ZI in tracts projecting to deep brain regions.

      Comments on the latest version:

      I reviewed the file and am more than satisfied with the authors responses and edits.

    1. 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 responded critically to all issues raised in the initial round of reviews.]

      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.

    1. Reviewer #1 (Public review):

      Summary:

      Yuan and colleagues present a thorough study of gene activation before and during metamorphosis in sponge larvae, combining in depth analyses of staged transcriptomes and chromatin accessibility profiling (ATACseq). Amongst several very interesting findings, the study reveals that the acquisition of settlement competence, which arises in response to decreasing light at sunset, is characterized by changes in chromatin accessibility that anticipate strong transcriptional shifts occurring as metamorphosis starts. Another notable finding is a set transcription factors amongst the genes strongly up-regulated at the onset of metamorphosis. In addition, larvae exposed to constant light, a condition that stalls metamorphosis, were found to activate metabolic pathways that are not normally expressed in swimming larva, Together the findings provide a rare level of understanding into how environmental conditions can promote deployment of alternative developmental programs in planktonic larvae.

      Strengths:

      This is a comprehensive and rigorous study of a phenomenon of wide interest. It will inspire researchers working on other species to look for similar, environmentally-driven "anticipatory" epigenetic mechanisms. It also provides a wealth of detailed information on genes, notably transcription factors, that are candidates for involvement in regulating specific metamorphosis transitions - and beyond. The data presented here are thus undoubtedly a rich and valuable resource.

      Weaknesses:

      It is not always straightforward to connect the conclusion statements in the text to the figures, or to grasp the aims and logic of the workflows.

    1. Reviewer #1 (Public review):

      Summary:

      A well-presented computational work on how post-translational modifications take place from a thermodynamic and mechanistic point of view.

      Strengths:

      A model capable of recapitulating complex phenomena to simulate, such as phosphorylation.

      Weaknesses:

      The methodology relies on multiple user-defined parameters that alter the setup. Below are the specific concerns:

      (1) The abstract reads: 'First, reactions that weaken favorable interactions are thermodynamically suppressed within condensates. As a consequence, regulation of condensate solubility is most efficient when PTMs tune interactions to values close to the solubility threshold.' This phrasing is confusing. PTMs that weaken interactions will, in principle, shift the solubility to higher values, and therefore closer to the thermodynamic conditions that allow for condensate formation, but if those transitions are most efficient when they tune interactions to values close to the solubility threshold, they will not be suppressed? The authors have to make this statement clearer to readers, which is particularly important in the abstract of the manuscript

      (2) The computational framework used by the authors is reasonable given the coarse-grained nature of the model required to study this problem. However, there are multiple user-defined variables that require further validation in order to make their choices justifiable:

      a) NN and NK have the same interaction epsilon value, as well as K-K. This would effectively make kinase form condensates on their own if the right stoichiometry was imposed. This should be re-evaluated with a reduced K-K interaction to validate whether the conclusions remain invariant with this assumption.

      b) N, P and K beads also have the same molecular diameter. This should be justified, for instance, with solvent available surface area calculations to determine the excluded volume for the different species, or by citing other works that support this approach.

      c) The phosphorylation reaction takes place when 2 particles are found within a 1.5sigma distance; however, this value choice is not justified. The authors should prove how variations to this choice affect their conclusions.

      (3) Figure 2a is informative although not entirely intuitive to follow. It can be concluded, as the authors mention, that the capacity to form condensates decreases as phosphorylation is favored. Therefore, as the text also says, there is a higher fraction of P particles as lambdaP increases; however, the fraction NP/NT appears to decrease based on the color scale. According to the figure caption, this is meant to represent the fraction of P particles over the total, but this should not exceed 1. This should be clarified and better explained in a revised version. Moreover, the information related to this, shown in Figure S4a, is very informative, and I advise the authors to include it as part of the main set of figures, as it will potentially help many readers to follow the manuscript better. Moreover, in Figure S4a, some lines appear to be disconnected; this probably comes from trajectory merging; the authors must check this.

      (4) 'At the interface, N and K concentrations remain relatively high, but scaffold proteins experience fewer stabilizing interactions, lowering the energetic cost of phosphorylation. This leads to enhanced reaction activity specifically at the boundary between phases.' This statement perfectly explains why the density profiles of K and N do not match the phosphorylation probability curve. This probability is determined by the energetic impact of the reaction and the probability of encountering each other in space, but also on the short timescale diffusion: N and K proteins have greater access to more microstates at the interface and can access them faster, while having enough density to encounter each other. It would be interesting for the authors to prove or invalidate this argument. At the very least, it should be mentioned.

      (5) Characterizing the real impact of condensate interfaces in real size condensates is an interesting approach, nonetheless this paragraph lacks most of the necessary details to be robust and obtain any reliable conclusion out of it in its current form:

      a) There are several CALVADOS parametrizations, which one do the authors use? The force field must be cited.

      b) R is not well defined in the caption.

      c) In the rendered images, periodic boundary conditions appear not to be implemented; this should be clarified

      d) In the Intermolecular energy profiles, it seems that FUS-LC has no condensate bulk.

      e)How is the interface width calculated?

      f) Why do the authors choose the energy profile and not density? Or other observables such as the radius of gyration.

      g) The interface width will depend on the temperature, and how distant this temperature is from the critical temperature for phase separation. Currently, this information is lacking.

      h) Variations in the temperature, quantity used to define the interface, should be addressed in order to make the interfacial importance claim robust.

      (6) 'Since the size of typical cellular condensates rarely exceeds the 2 μm diameter'. This statement should be supported by multiple references.

      (7) Figure S2 should be improved: The use of 'weak' or 'strong' labels is subjective and it is unclear which parameters are being used. Moreover, 'exp reference' is not described or cited. Furthermore, this plot shows what appear to be sketched curves. The calculation of the coexistence densities to construct this phase diagram is trivial for the system studied here; the authors should provide direct estimates.

    1. Reviewer #1 (Public review):

      The work shows that the ECS-induced calcium waves recapitulate several hallmarks of CSD, including hemodynamic alterations, distinct propagation patterns, and elevated Fos expression.

      Update of the weakness section.

      (1) I still have concerns about the use of Fos staining as the exclusive marker of neuroplasticity. Of course, Fos drives many forms of plasticity. But in addition to the role, Fos upregulation also reflects a recent history of elevated neuronal activity. This has been reported in numerous papers, including those cited in the article (e.g. Mahringer et al., 2019; Tyssowski et al., 2018). If the authors claim that their main finding is that ECS-induced CSD is necessary to drive Fos, then the relevant background should be presented in the Introduction.

      (2) The authors did not sufficiently address the concern regarding the bilateral suppression of EEG following unilateral calcium waves. Unilateral CSD is known to depress EEG only in the affected (ipsilateral) cortex. I suspect that the bilateral EEG suppression can be driven by the bilateral seizure (phase III oscillations) that is always coupled with the ECS-induced calcium waves.

      (3) Using the term 'phase III oscillations' instead of 'seizures' is confusing because the word "oscillations" covers a wide range of brain oscillations - from normal to pathological ones. First, the authors base the terminology change on the absence of "the ictal spikes characteristic of epileptic seizures..." during the phase. However, anesthesia can suppress ictal spiking and the phase III activity can represent an aborted seizure induced under anesthesia. Second, the authors cite the study by Brumback and Staton (1982) to justify their use of the term "phase III oscillations". However, the cited work describes the phase III as a seizure with "spike/polispike-wave activity".

      (4) Cortical SD cannot invade the hippocampus in the in vivo brain, although SD can occur in the hippocampus in response to generalized seizures. Invasion of CSD suggests its non-synaptic propagation via the contiguous gray matter. The following studies showed that CSD cannot invade the hippocampus non-synaptically: Fifkova E. Spreading EEG depression in the neo-, paleo- and archicortical structures of the brain of the rat. 1964 (PMID: 14138725); Yoshida et al. Identification of the extent of cortical spreading depression propagation by Npas4 mRNA expression. 2015 (doi: 10.1016/j.neures.2015.04.003). Concerning the papers cited in the discussion ("In mice, the ECS driven CSD likely invades hippocampus" (Mitlasóczki et al., 2025)), and response (Bahari et al., 2020; Bonaccini Calia et al., 2022), hippocampal SD was triggered by focal seizures, independent of CSD, in the experiments.

    1. Reviewer #1 (Public review):

      Summary:

      The "multiple-demand" (MD) system is a well-known finding of human brain imaging and is thought to play a central role in cognitive control. To directly compare the MD system in humans and monkeys, Mione et al. used functional magnetic resonance imaging to measure whole brain activation in a multi-step saccadic maze task. In humans, the authors found a distributed pattern of brain activity close match to the canonical MD network and extending to adjacent regions of dorsal attention and other networks. While there was good correspondence between monkey and human data, differences were also notable in lateral frontal cortex, dorsal parietal cortex, and sensorimotor cortex.

      Strengths:

      Though previous data hint at a corresponding network in the macaque, there has been no direct comparison to human data. This study provides a direct cross-species comparison with whole-brain data of fMRI, and the findings suggest an extended and strongly interconnected brain network recruited by increased cognitive challenge.

      Weaknesses:

      In previous human imaging, the MD system is defined by overlapping activation for many kinds of cognitive demand. In the present work, however, the authors used just a single task. Although there is some overlap between putative monkey MD network and canonical MD network identified in human imaging, it should be cautious to link current findings to MD system based on limited task events.

    1. Reviewer #1 (Public review):

      [Editors' note: The reviewing editor has assessed the revisions. The authors have addressed the previous minor concerns of the reviewers, added more details on the generation of the brainbow constructs and have made the image stacks available on public repositories.]

      Summary:

      Pang et al. investigated the expression pattern of the transcription factor foxQ2II in an adult beetle brain. They find nine distinct clusters, with many neurons expressing Glut/ChaT and dopamine. Some of the dopamine neurons resemble cell types described in Drosophila. Several neurons seem to project to prominent higher brain regions such as the MB and CX, and might even connect to both.

      Strengths:

      The authors use state-of-the-art labeling techniques for the analysis of individual cell types, such as beetle brainbow, to investigate the until now unknown expression of the transcription factor in the adult beetle brain.

      Rigorous cell reconstruction and image analysis revealed a better understanding of the anatomy of the labeled cells.

    1. Joint 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.]

      The revised manuscript is much clearer, and the additional analyses address several of the original concerns. RAIN analyses (Rhythmicity Analysis Incorporating Nonparametric methods) now detects circadian rhythmicity in 7/11 recordings under light-dark conditions and 8/12 recordings in constant darkness, compared with 2/12 following treatment with the Orco antagonist. This supports circadian modulation of spontaneous firing and a role for Orco in its normal expression. The expanded qPCR analysis of Orco also supports the conclusion that Orco transcript abundance is not circadian, and the cAMP experiment shows that cAMP can modulate Orco-dependent activity.

      The remaining issue concerns the mechanistic interpretation. The lack of rhythmic Orco transcript abundance does not distinguish an autonomous post-translational feedback-loop (PTFL) clock from a model in which the canonical transcriptional-translational (TTFL) clock acts upstream through cAMP, calcium, kinases, phosphatases, channel trafficking, or related pathways to regulate Orco.

      Similarly, the new Figure 10 provides a useful representation of the authors' hypothesis, but the proposed delayed feedback and coupling mechanisms are not experimentally demonstrated.

      We do not think any further experiments are necessary for the present study. Instead, we recommend that the manuscript should clearly distinguish between what the data show and what remains proposed. The data support circadian modulation of ORN firing a role for Orco in its normal expression, non-circadian Orco transcript abundance, and cAMP-sensitive modulation of Orco-dependent activity. The proposal that an Orco-centred membrane feedback loop generates the rhythm is intriguing and may remain a hypothesis generated through this study that needs formal testing in the future. This should be explicitly stated. While this has been done in the discussion section, elsewhere, including in the abstract and elsewhere, the original claim remains.

    1. Reviewer #3 (Public review):

      Combining a five-year field experiment with a global meta-analysis, Wu et al. investigate how grazing intensity influences ecosystem carbon dioxide (CO₂) fluxes in grasslands and how these effects are regulated by environmental conditions such as grazing duration, wetness index, and soil temperature and moisture responses.

      The authors show that the response of net ecosystem productivity (NEP) to light grazing shifts from negative to positive along a wetness gradient, whereas heavy grazing consistently suppresses NEP across wetness conditions. Importantly, this pattern is supported by both the field experiment and the meta-analysis, suggesting that may help maintain moderate levels of grazing can potentially enhance both plant productivity and carbon sequestration under favorable moisture conditions.

      The integration of experimental data with a global synthesis is a particular strength of the study, allowing the authors to evaluate grazing impacts across both temporal variability (precipitation fluctuations in the field experiment) and spatial variability (wetness gradients across global grasslands). Overall, the conclusions are well supported by the data.

      Overall, the principal conclusions are generally supported by the reported results, and the study provides useful evidence that the effects of grazing on grassland carbon cycling depend on both grazing intensity and environmental context. The comparison between field and synthesis results is potentially valuable for understanding why grazing effects vary among grassland systems. However, some aspects of the meta-analysis remain insufficiently documented. In particular, the study-selection numbers presented in the new PRISMA diagram require clarification, and the manuscript does not clearly explain how individual response ratios were weighted when estimating the pooled effect sizes. Resolving these reporting and methodological issues would improve the reproducibility and interpretation of the synthesis.

    1. Reviewer #1 (Public review):

      Summary:

      Choucri and Treiber have reassessed their previous study on TE-gene chimeric transcripts in neural genes in response to Azad et al (2024). Azad and colleagues argued that contrary to Choucri and Treiber's findings, chimeric TE-mRNAs are relatively infrequent, and they cautioned that further optimization of bioinformatics pipelines is needed to accurately detect TE insertions from RNA-seq. In this short response, Choucri and Treiber clearly show that differences in the tools used between their study and that of Azad et al. likely explain the contrasting results, along with RT-PCR failure to design primers that match the chimeric transcript and the use of different Drosophila lines. The authors emphasize the need for uniform, standardized criteria in such analysis, which would ultimately strengthen and advance the field.

      Strengths:

      The addition of a ratio to compute the number of splice reads specific to the chimeric transcript and to compare to the exon-exon splice reads is really interesting because it opens the door to finally quantify the contribution of chimeric TEs to the overall gene expression, although this is not the scope of the present article. The clear dissection of chimeric transcripts, along with the results from Azad et al, allows us to understand the differences between the two studies confidently. The methods are clear and thorough. The discussion on Drosophila lines is indeed essential, given that the lines and even individuals have high TE polymorphism.

      The biological function, if any, of such chimeric transcripts remains to be determined by further analysis, including chimeric transcripts with low to high overall contribution to gene expression (Figure 1B).

    1. Reviewer #1 (Public review):

      Summary:

      This paper by Boni and colleagues presents the engineering of a multi-step differentiation program in Escherichia coli based on synthetic gene circuits. The motivation behind the study was to engineer a system capable of undergoing differentiation in a step-wise manner without the presence of external spatial cues and without inducers added during the differentiation process. To achieve this, the authors created several synthetic gene circuits, one being a toggle switch, and the others being quorum-sensing-mediated gene expression modules. The outputs of the differentiation process are fluorescent proteins, which allowed the authors to quantify the behavior of the system using fluorescence intensity measurements. The authors additionally built a multi-component mathematical model which is able to reproduce the experimental data and to make interesting predictions (which require future validation).<br /> The data presented are convincing and support the claims, the work is well executed.

      Strengths:

      (1) The differentiation process proceeds autonomously after the initial step in liquid culture in the presence of external inducers.

      (2) It is indeed a step-wise process.

      (3) The mathematical model predicts the outcome (% of green, blue and red FP-expressing cells in the population) when changing the initial ratio of green:blue FP-expressing cells.

      Comments on revised version:

      The authors' replies to my comments were very satisfactory. I think the paper has been strengthened.

    1. Reviewer #1 (Public review):

      Summary:

      This manuscript by Joshi and colleagues demonstrates that the precise theta-phase timing of spikes is causal for CA1 hippocampal theta sequences during locomotion on a linear track and is necessary for learning the cognitively demanding outbound component of a hippocampus-dependent alternation task (W-maze), independently of replay during immobility. To reach these conclusions, the authors developed a theta-phase-specific, closed-loop manipulation that used optogenetic activation of medial septal parvalbumin (PV) interneurons at the ascending phase of theta during locomotion. This protocol preserved immobility periods, allowing a clean and elegant dissociation from SWR-associated replay.

      The manuscript is well written and was a pleasure to read. The work described if of high quality and introduces several notable advances to the field:

      a) It extends prior studies that manipulated theta oscillations by examining precise temporal structure (specifically theta sequences) rather than only LFP features.

      b) The closed-loop manipulation enabled dissociation between deficits in theta sequences during a behavioural task and SWR-associated replay activity.

      c) As controls, the authors included rats with suboptimal viral transduction or optic-fibre placement, and, within subjects, both stimulation-on (stim-on) and stimulation-off (stim-off) trials. Notably, sequence disruption persisted into stim-off periods within the same session.

      Overall, this is a strong manuscript that will provide valuable insights to the field.

      After revision, the manuscript has been substantially strengthened. The authors did incorporate the vast majority of the reviewer's comments and have expanded the discussion of prior medial septal manipulations, clarified the rationale for their theta-sequence analyses, added analyses of SWR and replay in the rest/sleep box as well as provided additional methodological and histological validation.

      The new rest-box analysis is a great addition and directly addresses my request to distinguish aSWRs from events during longer off-track rest periods (rSWR). The data support the narrower conclusion that no large group difference was detected in rest-box ripple rate or duration.

      The new observation (in response to reviewer #2, point3.2) that on the W-track theta power does not fully recover during stimulation-off periods does change the interpretation of the results. It means that these epochs are then not a physiologically recovered control condition. Therefore, the persistent disruption of theta sequences during the middle block cannot, alone, demonstrate that disrupting sequences during the earliest experience produced a lasting plasticity-related effect. It could also reflect a lingering network effect of the stimulation that persists after laser delivery has stopped. In my opinion the discussion should present at least these two alternatives: the disruption of early experience-dependent plasticity, as well as the incomplete physiological recovery from the preceding stimulation. The linear-track recovery data is helpful, but it does not guarantee the same mechanisms/effects will be present on the novel Wmaze (versus the familiar linear track).

    1. Reviewer #1 (Public review):

      Summary:

      This manuscript investigates how the Saccharomyces cerevisiae telomere-binding protein Cdc13 assembles on a 12-nucleotide single-stranded telomeric DNA substrate. Using complementary smFRET and CoSMoS measurements, together with dimerization- and DNA-binding-defective mutants, mass photometry, photobleaching analysis, and kinetic modeling, the authors assign state II to a DNA-bound Cdc13 monomer and state III to a stable complex containing two Cdc13 molecules. They propose that the stable DNA-bound dimer forms predominantly through sequential recruitment of two monomers, while direct binding of a preformed dimer represents a less frequent pathway. This work addresses an important mechanistic question in telomere biology because the pathway of Cdc13 assembly may influence telomere recognition, end protection, and recruitment of telomere-maintenance factors.

      Strengths:

      Overall, the manuscript is well written, and the combination of two complementary single-molecule approaches is a strength. The central model is interesting and potentially important.

      Weaknesses:

      Several issues require clarification or additional analysis.

      Major comments:

      (1) The mass photometry results are central to the mechanistic model and should be presented more prominently.

      The conclusion that Cdc13 binds DNA predominantly through sequential monomer recruitment depends strongly on the oligomeric state of Cdc13 at the concentrations used in the single-molecule experiments. The mass photometry results currently provide the principal direct evidence that Cdc13 is predominantly monomeric at 5 nM but exists as a mixture of monomers and dimers at 20 nM. These results should therefore be included in a main figure rather than only in the Supplementary Information. The authors should also provide a complete description of the mass photometry in the Methods section.

      Related to lines 191-192, the authors should discuss the estimated cellular or nuclear concentration and abundance of Cdc13 and compare these values with the experimental concentrations at which states II and III are populated. Because the relevant quantity may be the effective local concentration at a telomere rather than the average nuclear concentration, this distinction should also be acknowledged. Such a discussion is needed to establish under what physiological conditions sequential monomer loading versus binding of a preassembled dimer would be expected.

      (2) 75% labeling efficiency must be clearly defined and incorporated into both the stoichiometric and kinetic analyses.

      In line 251, the authors state that the labeling efficiency of DY-649P1-Cdc13 is 75%, but it is not clear how this value was measured. The authors should state whether 75% refers to the efficiency of the sortase reaction, the fraction of labeled molecules in the final purified preparation, or a value inferred from the plateau in Figure 3B. If it was inferred from the binding plateau, the plateau below 100% could also arise from inactive or inaccessible DNA molecules, incomplete colocalization detection, inactive protein, or an effect of the fluorophore on binding. An independent measurement, such as absorbance-based determination of the dye-to-protein ratio, quantitative gel analysis, or intact-mass analysis, would be preferable.

      Incomplete labeling has direct consequences for the interpretation of Figure 3. With a labeling probability of 0.75, a true Cdc13 dimer would contain zero, one, or two fluorophores. Thus, even among detectable dimers, 40% would appear as one-step photobleaching events. A one-step event therefore cannot automatically be equated with a monomer without correcting for labeling efficiency. The authors should quantitatively account for incomplete labeling when inferring the relative monomer and dimer populations from the photobleaching data.

      The same issue is even more important for the CoSMoS kinetic model. The authors should incorporate labeling efficiency into the observation model, or at minimum perform simulations or a sensitivity analysis demonstrating that the inferred transition rates and state assignments are robust to 75% labeling.

      (3) Apparent state I→III transitions do not by themselves demonstrate direct binding of a preformed Cdc13 dimer.

      At lines 326-330, the authors interpret state I→III transitions as direct binding of a solution dimer and conclude that sequential binding is approximately eightfold faster than direct dimer binding. This interpretation is not yet sufficiently established. An observed I→III transition demonstrates only that no state II intermediate was resolved; it does not distinguish true binding of a preformed dimer from sequential binding in which the state II lifetime is shorter than the temporal resolution of the experiment.

      This concern is particularly important because the CoSMoS experiments were conducted at only 0.3-1.25 nM Cdc13, whereas mass photometry indicates that Cdc13 is predominantly monomeric even at 5 nM. In addition, the smFRET signals were averaged over a sliding window of ten 50-ms frames, which could obscure short-lived intermediate states.

      The authors should show representative raw traces containing apparent I→III transitions in a supplementary figure and quantify the shortest state II dwell time that could be detected under the acquisition, smoothing, and HMM procedures used.

      (4) The interpretation of the WT-Cdc13/Cdc13^R635C mixture requires further clarification.

      For Figures 2G-H and lines 209-218, the reduced state III population in the mixture of 2.5 nM WT Cdc13 and 2.5 nM Cdc1^R635C is interpreted as evidence for a solution monomer-dimer equilibrium and formation of a nonfunctional WT-mutant heterodimer. However, at least two nonexclusive explanations should be considered:

      a) Formation of WT-mutant heterodimers in solution could reduce the concentration of free WT monomers and WT homodimers available to form state III.<br /> b) A WT-mutant heterodimer, or recruitment of Cdc13^R635C to a DNA-bound WT molecule through protein-protein interactions, could produce a DNA-bound complex that cannot adopt the state III conformation because only one subunit has an intact DNA-binding interface.

      The authors should discuss these possibilities explicitly and clarify expected FRET states.

      For direct visual comparison, Figure 2G should include the FRET histograms for 2.5 nM WT Cdc13 alone and 5 nM WT Cdc13 alone, in addition to the WT-mutant mixture. The concentrations of both the initially loaded WT Cdc13 and the WT or mutant protein added during the chase experiment in Figure 2I should also be stated in the main text and figure legend.

      (5) The physical basis of the different FRET values for states II and III should be explained earlier and more carefully.

      The assignment of state II and state III to one and two bound Cdc13 molecules is supported by the combined smFRET and CoSMoS results. However, the manuscript should explain earlier why the addition of a second Cdc13 molecule is expected to produce a further decrease in FRET. Because the fluorophores are attached to the DNA, the different FRET values imply a change in the distance, orientation, or local photophysical environment of the DNA-linked dyes when the second Cdc13 binds. CoSMoS establishes a change in protein stoichiometry, but it does not by itself establish that the DNA has undergone a particular conformational change.

      The discussion at lines 404-423 suggests that the second Cdc13 induces a rearrangement of the first Cdc13-DNA complex. This is a reasonable hypothesis, but it should be presented as an inference rather than as a demonstrated DNA conformational transition. References 44-46 describe different RPA binding modes and rearrangements of protein-DNA contacts; they do not directly demonstrate the specific DNA conformational change proposed here. The authors should either provide more direct support or revise the discussion accordingly. The distance estimates should also be described cautiously because they assume that dye orientation and photophysical properties are unchanged between states.

      The rationale for the internally positioned Cy3 constructs in lines 147-149 should also be explained more clearly. Why does it demonstrate that Cdc13 cannot bind duplex DNA?

    1. Reviewer #1 (Public review):

      Excitation/inhibition (E/I) balance between excitatory (glutamate) and inhibitory (GABA) neurotransmission is being increasingly studied using magnetic resonance spectroscopy (MRS), for example in autism spectrum disorder, schizophrenia and attention deficit/hyperactivity disorder. These are typically measured using standard single-voxel MRS methods (eg PRESS, sLASER) to measure glutamate/glutamine or "Glx" and spectral editing methods (eg MEGAPRESS, MEGA-sLASER) techniques to measure GABA. Such methods only give a measure of the total MR-visible metabolite concentration in the voxel. That is, they don't distinguish between glutamate/GABA involved in neurotransmission or in other metabolic processes.

      Cherix et al present a method for measuring glucose metabolism, with the potential to be used on a standard clinical MRI scanner. This proof-of-concept study focused on measuring proton signals from glucose metabolites, including lactate, glutamate, GABA & Glx. The method works by administering 13C universally labelled glucose (where all six carbon atoms are substituted with 13C). When the glucose is metabolised, 13C label is incorporated into specific positions within its metabolites. Protons attached to 13C don't produce a signal in 1H-MRS in a subsequent MEGA-sLASER scan, leading to a drop in the signal as the labelled metabolite concentration builds up. At the same time, "satellite resonances" appear for protons coupled to 13C, which increase as the labelled metabolite concentration builds up. Metabolite concentrations were inferred using a simple dynamic model.

      The main strength of the method is that it enables dynamic metabolic information that would typically only be available with multi-nuclear MRS capability (13C or 2H) to be achievable using standard preclinical or high field (>= 7T) human MRI systems, with widely available spectral-editing acquisitions.

      The results in the mouse spectra seem very convincing for lactate and GABA/Glx. For the human scans, changes in lactate weren't detectable, which is not surprising given how little lactate appears in the normal brain. In the discussion, the authors argue the method can potentially be used in a standard, 3T clinical scanner. It may be too soon to conclude that, as it's not yet clear there would be sufficient SNR in spectra at that field strength. Additionally, the heteronuclear coupling constants are quite high. The authors recognise that this may complicate detection of satellite resonances due to signal dephasing. Another potential complication at 3T (or 2.9T) is the potential for the satellite resonances to come close to the GABA peak at 3 ppm. More accurate measurements of coupling constants will allow that to be determined. Another potential limitation of the method is macromolecule contamination of the 3 ppm GABA peak. That may be overcome by using macromolecule-nulled MEGA-editing, though frequency navigators may be necessary to overcome the increased sensitivity to frequency drift.

      The authors achieved their aims of showing that imaging glucose metabolites was possible using standard proton-only MRI systems, without the need for additional multinuclear coils, transmitters and receivers. The evidence if very compelling for the mouse scans but only incomplete for the human scans.

      The ability to quantify metabolites involved in E/I balance has the potential to revolutionise studies into disorders where changes in E/I balance are implicated. This is especially the case for preclinical models. Such studies may be less feasible in clinical studies due to the high cost of universally 13C-labelled glucose, but this proof-of-concept is a promising start.

    1. Reviewer #1 (Public review):

      Summary:

      Remapping is clearly degraded in amyloid models, but people and animals with a lot of pathology often hold onto more function than their spatial maps would predict. The authors' idea is that CA1 carries two things at once: an explicit code where rate maps onto position, and an implicit one in the temporal relationships between cells, and that AD hits the first much harder. They recorded CA1 with tetrodes in App(NL-G-F) and WT rats running an A-B-B-A sequence of open field sessions, repeated daily for six days, with rest in between. They then compared rate map measures against a cofiring measure (pairwise Kendall's tau) and looked at SWR reactivation during rest.

      Strengths:

      (1) The design is right for the question. Alternating back to the familiar arena separates "can the network register a new context" from "can it get back to the old one," and the finding that App rats look OK on the first A to B transition but fall apart on the return is the most striking thing here. The confused cell result, 24% vs 4.5%, is easy to read and hard to dismiss.

      (2) Six consecutive days is also worth something. Most work on this is cross-sectional, and looking at how the coding changes with accumulated experience is the right way to ask about plasticity.

      (3) The PIR analysis in Figure 5 is the bit I liked best. Subtracting each cell's position-predicted rate before computing tau is a reasonable check that the cofiring effects aren't place fields in disguise, and it's more than most papers making this argument do. The theta index control is a good instinct too, though see below on how it's analysed.

      Weaknesses:

      (1) No behaviour. This is the main problem and everything else is secondary. The title, abstract, intro and discussion all turn on preserved learning and memory, and the rats were never tested on anything. They foraged for popcorn in an open field. No discrimination measure, no novelty preference, no probe, nothing. So "learning" ends up being defined as "decoder accuracy went up across days," which makes the central claim circular. Either add a behavioural readout in these animals or take the learning language out of the title and abstract and say what was actually measured, which is experience-dependent change in neural coding.

      (2) Four animals per group is fine for this kind of work, but the statistics don't respect it. Degrees of freedom in the thousands and tens of thousands (t(8616), t(36293), F(1,2674)) treat cells and cell pairs as independent, which they aren't. The mixed models in Figure 1 are the right approach, and I couldn't see why they were dropped everywhere else. The theta result is the clearest casualty: a null across 36,293 cell pairs from four rats isn't evidence that theta coordination is preserved; it's an untested question with n=4.

      (3) Also, the reported df do not always match the stated n. The Methods say 4 per genotype, but several animal-level tests give t(4), which implies 3. Figure 4C gives t(32), and Figure 5C gives t(31) for what look like per-day measures. I couldn't work out what the sampling unit was in each case.

      (3) Some statistics can't be right. I noticed three, without looking hard. For example. Figure 1C, rate overlap: t(471) = 2.3 with p = 2.0e-7. Fig 1G: t(163) = 5.3 with p = 0.48. Fig 3F: F(1,483) = 36.5 with partial eta squared = 0.7, when the almost identical test in the previous sentence gives 0.07. These are likely all typos, but there are enough that the whole set needs going through.

      (4) The dissociation isn't tested with matched methods. Explicit coding gets rate map correlations, PVC, rate overlap, and field size. Implicit coding gets an SVM across six days. The claim is that one improves with experience and the other doesn't, but they're never put through the same analysis. The authors should run the identical decoder on rate vectors and on tau vectors, same cross-validation, day by day, and show the slopes diverging. That would be a real dissociation. Figure 1G does run a rate decoder but only pooled, not across days. As it stands, the difference in learning slopes could partly be the two analyses having different sensitivity.

      (5) The PIR residual may not be as clean as it looks. PIR is observed rate minus rate predicted by the cell's own spatial map. If the spatial map is a worse model of firing in App rats, which is the paper's own claim, then less gets subtracted and more is left in the residual. So a group difference in residual tau structure could be partly downstream of the group difference in place coding quality rather than something independent. This is worth some kind of check, e.g. matching cells on spatial information, or at least reporting how much variance the spatial model explains in each group.

      (6) Reactivation consistency. This carries a lot of the interpretation, and it's the thinnest evidence in the paper. r = 0.2, p = 0.04 in App against r = -0.2, p = 0.06 in WT. That's a difference in significance, not a tested difference between groups, and with both p-values sitting on either side of 0.05, I wouldn't build a mechanism on it. Needs a group x day interaction. Separately, mean pairwise correlation across SWR population vectors depends on how many cells are active, how many events there are (panels show 189 to 491) and how sparse the firing is. SWR rate, duration, participating cells and firing rates would let the reader judge whether "more consistent reactivation" means what's claimed.

      (7) The hyperexcitability to excessive replay to Hebbian consolidation story on pp 21 to 22 runs about a page on the back of one marginal correlation. This section should be cut down and flagged as speculation.

      (8) Missing controls. Things I expected and didn't find: histology confirming tetrode placement in CA1, any pathology verification in this cohort rather than a citation to Pang 2022, and A1-A2 spatial correlation shown next to B2-A2. That last one matters. If the App representation of A just drifts across the day, that's a different story from a specific failure to reinstate A, and the confused cell analysis as built can't tell them apart. Also, with the threshold set at the 95th percentile of the A1B1 baseline, the WT value of 4.5% is basically the chance floor by construction, so the number that carries information is the App one.

      (9) The issue of males only should be mentioned.

    1. It is precisely this black-white experience which may prove of indispensable value to us in the world we face today. This world is white no longer, and it will never be white again.

      This is a strong reflective conclusion to his self experience. It challenges Western racial exclusivity and explains how global history has forced modern societies to reckon with multicultural realities."

    2. They are brimming with good humor and the more daring swell with pride when I stop to speak with them.

      The children's innocent words create a sense of warmth instead of feeling offended. The same word would cause different feeling, Imagine shout at a black person 'Nigger' nowadays would cause what kind of result.

    3. But I remain as much a stranger today as I was the first day I arrived, and the children shout Neger! Neger! as I walk along the streets.

      People said that children speak without restraint. But I still suprised that he would wrote this experience on the article.

    1. Reviewer #1 (Public review):

      Summary:

      This manuscript investigates state-, trait-, and recovery-related computational phenotypes in Major Depressive Disorder (MDD) using an unmedicated, four-group cross-sectional design comprising currently depressed participants, remitted individuals, first-degree relatives at familial risk, and healthy controls. Utilizing a volatile four-armed bandit task and an explicit risk gambling task alongside hierarchical Bayesian modeling, the authors report that remitted participants uniquely display a lower punishment learning rate relative to all other groups. The authors conclude that recovery from MDD does not represent a simple normalization to healthy baseline levels, but rather involves a protective computational recalibration that dampens reactivity to negative outcomes to sustain remission.

      Strengths:

      (1) Highly Valuable Clinical Sample: Evaluates a rare, unmedicated sample across four distinct clinical stages (MDD, REM, REL, CTR), providing an exceptionally controlled framework to disentangle state, trait, and recovery markers.

      (2) Combines dynamic reinforcement learning under environmental volatility with prospect-theoretic decision-making under explicit risk to capture multiple dimensions of value-based choice.

      (3) Challenges the conventional assumption of clinical "normalization," offering a compelling hypothesis that psychiatric recovery may depend on active, compensatory recalibrations of cognitive parameters.

      (4) Utilizes hierarchical Bayesian parameter estimation and leverages Bayesian Model Averaging (BMA) to mitigate single-model selection bias.

      Weaknesses:

      (1) The Discussion characterizes MDD and familial-risk groups as exhibiting "noisier" choice behavior in the gambling task, which directly contradicts the reported higher inverse temperature values that mathematically denote more deterministic choices.

      (2) Framing a reduced punishment learning rate as a "recovery mechanism" overinterprets single-timepoint data, which cannot differentiate an acquired post-episode adaptation from a pre-existing resilience trait.

      (3) The theoretical claim that lower punishment learning is protective in remission directly conflicts with the authors' dimensional findings, where lower punishment learning correlates with worse subclinical apathy and anhedonia in non-depressed participants.

      (4) Model-agnostic choice repetition yielded no significant group effects, contrasting sharply with the robust group differences in model-derived parameters and necessitating posterior predictive checks.

      (5) Fails to provide parameter recovery analyses to demonstrate that punishment learning rates can be reliably disentangled from lapse rates and outcome sensitivities across a 200-trial task structure.

      (6) Selects a lower-ranked model under LOOIC without sufficient quantitative justification, and lacks sensitivity analyses to confirm that group-specific hierarchical priors did not skew estimates given unequal group sizes.

      (7) Relies on several marginal p-values bordering across multiple parameters and symptom correlations without establishing a clear family-wise error or FDR correction strategy.

    1. Reviewer #1 (Public review):

      The studies by Hwangbo et al. diligently attempt to account for many of the typically neglected dietary and non-dietary factors.

      Strengths:

      • Work addresses many potential artifacts of dietary (e.g., dehydration stress, macronutrient ratios, and protein source) and non-dietary (e.g., leaky expression of S106-GAL4) manipulations-important factors that are too often overlooked.

      • Balanced and complementary behavioral, molecular, and bioinformatic experiments

      • Show necessity of proteostatic subunits in the fat body for DR-mediated longevity. The findings in the current manuscript lay the ground for future studies that test sufficiency of fat body prosβ3 and rpn7, or necessity of other proteostatic genes in other tissues.

      Comments on revised version:

      The revised manuscript is substantially improved and addresses many of the prior concerns. I have only a few minor recommendations and remaining issues:

      Clarify the interpretation of the Con‑Ex feeding data. The authors describe the ~70% higher intake on 1SY in Clk^Jrk as modest, and note a ~40% higher mean intake on 5SY that is not statistically significant. However, lack of significance can reflect limited power, and these differences are potentially biologically meaningful, given that relatively small changes in nutrient ingestion can substantially affect lifespan. If the average effects are real, the Clk^Jrk flies would be ingesting an effective diet closer to ~1.7SY and ~7SY relative to controls. A shift of the diet-lifespan response curve in Clk^Jrk therefore cannot be fully excluded, particularly given the absence of intermediate diets between 1SY and 5SY and the observation that Clk^Jrk is sometimes shorter‑ and sometimes longer‑lived than controls across different trials and diets.

      Although the core finding is strengthened by using several diet formulations, most additional experiments continue to rely on whole‑food dilution, even as the field is moving toward more defined DR regimens (e.g., yeast‑only or yeast‑extract-based protocols). There remains considerable variability and, in some cases, a lack of clear DR‑mediated lifespan extension in control cohorts (for example, in some GeneSwitch experiments using whole‑food dilution). It would be helpful if the authors briefly commented on this variability and justified their continued use of whole‑food dilution in these experiments.

      Please add a clear Methods description of the feeding assay (Con‑Ex), including fly age, assay duration, dye or tracer conditions, sample processing, quantification, and statistical analysis.

      Please ensure that the survival data shown in Figure 5 and associated supplements are explicitly linked to Cox proportional hazards analyses in the text or figure legends, with clear indication of the models used (e.g., gene, diet, and gene×diet interaction terms). The Methods state that diet is used as a continuous variable; given the non‑linear (U‑shaped) lifespan-diet reaction norm (reduced survival at both 1SY and higher yeast), it would be important to clarify whether 1SY was excluded from these Cox models, or alternatively, to model diet categorically, restrict the continuous analysis to 5-20SY, or apply an appropriate non‑linear transformation (e.g., splines). As written, it is not clear how the Cox model accommodates the non‑linear diet response.

    1. Reviewer #1 (Public review):

      Summary:

      This manuscript provides fundamental insight into ciliary biology, specifically, how ciliary axoneme orientation is governed by microenvironmental bending or intrinsic cytoskeletal steering rather than strictly basal body docking coordinates.

      Strengths:

      There are three major strengths in this manuscript. First, combining high-resolution imaging with deep-tissue sectioning yields impressive lateral resolution, enabling robust separation of dual centrioles within the crowded chondrocyte extracellular matrix. Second, the authors established an automated pipeline that evaluates thousands of individual cells across multiple anatomical regions and differentiation zones, lending strong statistical weight to positional and volumetric measurements. Lastly, they demonstrate that ciliation peaks in the peripheral resting zone and ciliary length peaks in hypertrophic cells, providing a compelling cellular explanation for why Ift88 deletion impacts peripheral growth plate geometry and hypertrophic expansion.

      Weaknesses:

      There are three major weaknesses in this manuscript. First, the paper lacks explicit descriptions of data mentioned in the Abstract and Methods, including the RNA-seq differential expression, WGCNA modules, and immobilization/ciliary alignment data. Second, while the Methods section mentions correcting for "Z-blur" / point-spread function distortion in 3D spherical coordinate calculations, further detail is required on how orientations are disambiguated from optical sectioning depth artifacts. Lastly, the RNA-seq analysis demonstrates that ambulatory unloading alters hedgehog and primary cilia gene signatures, yet axoneme orientation itself remains static. The narrative requires a clearer mechanistic synthesis regarding how mechanical loading modulates ciliary signaling if physical alignment of the cilia is refractory to mechanical force in chondrocytes.

    1. Reviewer #1 (Public review):

      Summary:

      The review addresses an important and timely topic that concerns the role of cryo-EM in transforming RNA structural biology from a "static" discipline to one increasingly concerned with conformational ensembles and molecular dynamics. The scope is well within the eLife standards, and the style and general architecture do fit eLife.

      Strengths:

      The review is extremely well written, well-conceived and clear. The main strengths are in the breadth of coverage, the clear theme, and the inclusion of practical examples that explain in detail the construct design, sample preparation, vitrification, and data analysis. The manuscript will certainly be impactful and valuable, especially for readers who are not specialists in cryo-EM, as it provides an accessible overview of recent advances across a wide range of RNA systems.

      Weaknesses:

      My only reservation is that, currently, the review reads too much like a list of examples. The authors should make an effort, and I am sure they are well up to it, to try to synthesise the message, provide more critical insights and amalgamate the text better, to really reach a wider audience.

      If revised along the lines detailed below, I am sure that the review will become an authoritative and influential resource for the RNA structural biology community.

    1. Reviewer #1 (Public review):

      The study addresses the organisation of synaptic connections from medial to lateral entorhinal cortex. Classic anatomical work has suggested these connections exist but very little is known about their identity or functional impact. The manuscript argues that these projections are mediated by glutamatergic neurons, providing excitatory input from MEC to all layers of LEC, and by SST+ve interneurons sending inhibitory projections to L1 of LEC. This appears the most likely interpretation of the data. Potential concerns about confounds due to spread of virus/tracer from the injection site are addressed in the supplemental figures. My view is that the weight of evidence favours the authors' interpretation although the evidence isn't quite compelling.

      Knowing the configuration of projections from MEC to LEC is important for thinking about circuit mechanisms for spatial cognition and episodic memory. This study adds to an emerging view that MEC and LEC can interact directly, indicating that the cell-type level organisation of these interactions is asymmetric and identifying an intriguing long range inhibitory pathway.

    1. Reviewer #1 (Public review):

      Summary:

      The authors examine the impact of heat stress during an embryonic CP in Drosophila, focusing on the larval locomotor network. They show that elevated temperature increases neuronal activity and, when applied during the CP, results in long-term instability of the network which manifests in prolonged seizure recovery times. At the neuromuscular junction, substantial structural changes occur, including terminal overgrowth and altered receptor composition, yet synaptic transmission remains preserved due to homeostatic regulation. Motoneurons display reduced excitability but receive increased synaptic input from premotor interneurons. These findings suggest that maladaptive instability originates within the central circuitry rather than at the neuromuscular junction, where changes seem to be homeostatically compensated. The study concludes that different network components exhibit distinct and hierarchical responses to CP perturbations, with premotor interneurons setting the tone for downstream adjustments in motoneurons.

      Strengths:

      The work takes advantage of the unique accessibility of the Drosophila system. A major strength of the study is the integration of structural, physiological, and behavioral analyses, which allows the authors to draw a comprehensive picture of how CP perturbations shape the locomotor network. The choice of an ecologically relevant stimulus (heat stress) is particularly convincing, as it links experimental manipulations more closely to natural environmental conditions. The experiments are carefully designed, and the results are robust and consistent with previous findings in the field, while also extending them in new directions. Importantly the work clarifies how temperature perturbations within distinct developmental time windows affect different properties of motor circuit formation.

      Weaknesses:

      A small limitation of the study is that it remains difficult to integrate maladaptive (seizure recovery) and adaptive/homeostatic phenotypes within a single mechanistic framework, leaving some space for interpretation.

      Comments on revised version.

      I think the authors did a great job at revising the manuscript and they addressed all my comments.

    1. Reviewer #1 (Public review):

      Wang, Zhou et al. investigated coordination between prefrontal cortex (PFC), and hippocampus (Hp), during reward delivery via analyzing beta oscillation. Beta oscillations are associated with various cognitive functions but their role in coordinating brain networks during learning is still not thoroughly studied. Authors focused on the changes in power, peak frequencies and coherence of beta oscillations in two regions when rats learn a spatial task thru days. Contradicting with authors hypothesis, beta oscillations in those two regions during reward delivery were not coupled in spectral or temporal aspects. They were, however, able to show reverse changes in beta oscillations in PFC and Hp as the animal's performance got better. Authors were also able to show a small subset of cell population in PFC that are modulated by both beta oscillations in PFC and sharp wave ripples in Hp. A similarly modulated cell population was not observed in Hp. These results are valuable in pointing out distinct periods during a spatial task when two regions modulate their activity independent from each other.

      Authors made a detailed analysis of the data to support their conclusions. Few more points of discussion would clarify the results of the paper.

      (1) One of the big conclusions of the paper is how the beta burst power is changing after learning the task (Figure 3). Authors have also showed in Figure 6-1, how the SWR power and rate are changing thru the training days. Did they observe a change in coordination of Beta bursts and SWR between the days, which would also reflect how experience changes the coordination?

      (2) Authors have shown in detail the opposite relationship between Beta phase locking and SWR modulation in Hippocampus in Figure 7I. This might require a different analysis, but is it possible to make a discussion on predicting a cell firing in a SWR after it fires in a beta burst.

      Other than these two points, authors have addressed previous comments and made a convincing analysis of their data.

    1. 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 both by revising their original presentation where necessary and by providing responses to the reviewers in cases where they disagreed that revision of the original presentation would be necessary.]

      Summary:

      As a general phenomenon, adaptation of populations to their respective local conditions is well-documented, though not universally. In particular, local adaptation has been amply demonstrated in Arabidopsis thaliana, the focal species of this research, which is naturally highly selfing. Here, the authors report assays designed to evaluate the spatial scale of fitness variation among source populations and sites, as well as temporal variability in fitness expression. Further, they endeavor to identify traits and genomic regions that contribute to the demonstrated variation in fitness.

      Strengths:

      With many (200) inbred accessions drawn from throughout Sweden, the study offers an unusually fine sampling of genetic variation within this much-studied species, and through assays in multiple sites and years, it amply demonstrates the context-dependence of fitness expression. It supports the general phenomenon of local adaptation, with multiple nuances. Other examples exist, but it is of value to have further cases illustrating not only the context-dependence of fitness expression but also the sometimes idiosyncratic nature of fitness variation. I commend the authors on their cautionary language in relation to inferences about the roles of particular genomic regions (e.g.l.140-144; l.227)

    1. 2 F 62 c.1222 C>T ND

      Case Annotation Template

      Case#: Patient 2, female, age 62

      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: ENST00000370225.4:c.1222C>T

      ClinVar: NM_000350.3(ABCA4):c.1222C>T (p.Arg408Ter)

      CAID: CA179692

      SupplementalData: composite mask analysis shown in figure 3 for patient 2, "Both patient 2 and 14 show foveal preservation of IS/OS and RPE," "Patients 2, 19, and 11 show large areas of matched degeneration and isolated IS/OS loss, "

    1. Reviewer #1 (Public review):

      Summary:

      The study identifies two previously uncharacterized endogenous receptors for Aplysia PRXamide peptides and shows that N-terminal pyroglutamylation can produce opposite effects on receptor activation. The authors further propose that this modification acts indirectly by altering peptide conformation and that receptor pocket properties determine the direction of its effect. The findings are potentially significant for understanding how peptide modifications influence receptor selectivity, but the evidence supporting the proposed molecular mechanism is not yet sufficiently strong.

      Strengths:

      The identification and functional characterization of the two receptors are valuable. The contrasting effects of pyroglutamylation, together with peptide and receptor mutagenesis and computational analyses, provide an interesting framework for investigating peptide-receptor selectivity.

      Weaknesses:

      Most of the statements about novelty and generality are stronger than warranted by the current data. The central mechanistic model relies heavily on computational predictions and indirect functional measurements, without direct structural or receptor-proximal evidence. In addition, the human receptor data provide only partial support for the proposed mechanism, particularly because the pyroglutamylated and non-pyroglutamylated peptides are not significantly different at human receptor 2. Thus, the data support differential effects of pyroglutamylation but do not yet fully establish the proposed distal conformational mechanism.

    1. Reviewer #1 (Public review):

      Summary:

      In this manuscript, the authors used the ABCD study to understand how changes in body fat composition affect brain development during the teenage years. They found that the key determinants of changes in the brain were changes in fat accumulation rather than just baseline measures. Less importantly, but still interesting, they reaffirmed that more complex measures, such as body roundness index, better captured the impact of obesity than body mass index.

      Strengths:

      This study uses an excellent open access dataset, asks an important set of questions, and is executed with diligence for proper methodology. The finding that trajectories in adiposity matter more than baseline differences is important both for understanding how the brain adapts to body composition changes and has potential impact for public health interventions.

      Weaknesses:

      While I am overall impressed with the study, there are a few weaknesses I would like to see the authors address:

      (1) There is no reason to limit analyses to the cerebral cortex. Body composition changes are as likely to affect the subcortex or cerebellum as the neocortex. In some cases, like the hypothalamus, potentially even more likely.

      (2) Confounders should be examined in more detail. How are adiposity changes mediated by (for example) socio-economic status?

      (3) I'd like to see more rationale for excluding 483 kids with extreme adiposity indicators. Is it that they are untrustworthy entries? Otherwise, they could be particularly informative.

      (4) Are there any blood measures of glucose/insulin available?

      (5) Some of the figures could benefit from having raw data included rather than just showing the fitted trend lines.

      (6) Are there any alternate explanations for baseline differences? Particular examples that came to mind are the influence that maternal adiposity has on offspring brain development.

  2. Sep 2026
    1. Reviewer #1 (Public review):

      Summary:

      The authors previously generated two cell-layer-specific mutants of petunia for the petal identity gene PhDEF. In this study, they profiled differential gene expression in those mutants through single-cell RNA sequencing (scRNA-seq). They found that more genes are highly and specifically expressed in the epidermal cell layer than in mesophyll cells. In addition, they identified cell-layer-specific and -aspecific PhDEF target genes. Using the extensive single-cell transcriptome and layer-specific target identification, the authors concluded that different cell identities affect homeotic regulator PhDEF, thereby influencing transcriptional regulation.

      Major comments from first round of review:

      This presented work provides comprehensive evidence, that pre-existing cell layer identity (epidermis and mesophyll) modulate transcriptional output of homeotic transcription factor, PhDEF.

      However, a disconnection between PhDEF bindings to genome and transcriptional output undermines the robustness of their conclusion although some binding loci were shown to be correlated with DEG. This may indicate the chromatin state, the existence of interacting partners, and the non-productive binding of PhDEF, suggesting that PhDEF binding alone is not sufficient to predict transcriptional outcomes and additional regulatory mechanisms that shape gene expression in addition to the layer-specific regulatory mechanisms. This disconnection may also be due to the developmental timing. Indeed, it appears authors used different flower stages for ChIP-seq and scRNA-sequencing. In fully differentiated organs, PhDEF binding itself may be no longer transcriptionally productive, and differential gene expression results primarily from the pre-established cell identity rather than directly from the homeotic regulation of PhDEF. Therefore, the main question the authors asked-how homeotic identity works with cell-layer identity and how the homeotic gene, PhDEF, acts in mature organs-was not clearly explained by this study.

      In Figure 2, the use of the term "target" is potentially misleading. It sounds like direct target genes (direct binding and differential expression) for PhDEF, but it refers only to DEGs.

      Lines 496-497: When the authors state, "~ demonstrates for the first time that the regulatory function of homeotic factor is influenced by cell layer identity," it sounds overstated, as prior studies have shown that pre-existing tissue or cell identity can shape transcriptional activity and developmental output.

      Significance:

      This study is well-designed and technically sound. They utilize single-cell transcriptomics and ChIP-seq by using genetically well-defined genetic materials and layer-specific PhDEF deletion mutants. The analysis showed where PhDEF binds to genomic loci and which genes are differentially expressed in petal epidermis and mesophyll, providing evidence of cell-layer-specific function of homeotic gene in mature organs. Although certain mechanistic aspects were not elucidated, the data from the extensive genome-wide study contributed to drawing their conclusions.

      Advances: This research goes beyond classical models of floral organ identity by showing that homeotic gene function is not uniform in the same floral organ. It represents a conceptual advance in our understanding by integrating cell layer identity into the framework of homeotic gene regulation.

      Audience: This study will be of broad interest to scientists who study transcription networks, cell and organ identity in the context of plant development.

      My field of expertise: Transcriptional regulation by transcription factor, epigenetic regulation of gene expression, plant development.

      Comments on latest version:

      Thank you for sharing the assessment. I am happy with the proposed eLife assessment. I do not have any further amendments to my review.

    1. Reviewer #2 (Public review):

      The authors investigate the contribution of dorsal CA1 hippocampal dysfunction to cognitive impairments in the Cntnap2 knockout mouse model of autism spectrum disorder. Using two complementary behavioral paradigms, trace fear conditioning and a relational/declarative memory radial maze task, together with fiber photometry, optogenetic manipulation, and cFos mapping, they examine whether altered CA1 function contributes to deficits in temporal binding and memory flexibility.

      A major strength of the study is the combination of behavioral, recording, and causal manipulation approaches. The trace fear conditioning experiments show that Cntnap2 knockout mice retain associations across shorter temporal intervals but fail when the temporal gap is increased to 40 s. Fiber photometry reveals reduced dorsal CA1 activity under these conditions, and, importantly, optogenetic activation of dorsal CA1 pyramidal neurons during the trace interval rescues subsequent memory performance. This provides compelling evidence for a causal contribution of dorsal CA1 activity to the temporal binding deficit observed in this model.

      The radial maze experiments extend these findings to a more complex form of relational/declarative memory. Cntnap2 knockout mice are able to acquire the task but show impaired flexibility when previously learned spatial relations must be recombined. Their behavior is also characterized by greater lateralization, consistent with increased reliance on an egocentric rather than an allocentric spatial strategy. The revised manuscript now explains more clearly how this paradigm distinguishes relational/declarative from procedural learning strategies and how the 20-s inter-trial interval introduces a temporal binding requirement. This clarification substantially improves the conceptual link between the two behavioral paradigms.

      The accompanying cFos analyses further show reduced recruitment of hippocampal regions and increased engagement of striatal and prefrontal regions in Cntnap2 knockout mice. These findings are consistent with altered recruitment of memory systems accompanying the behavioral strategy shift. However, unlike the optogenetic experiments in the trace fear conditioning paradigm, the cFos measurements remain correlational. They therefore support, but do not by themselves establish, a causal reorganization from hippocampal-dependent declarative memory toward striatum-dependent procedural learning. The authors have appropriately moderated this interpretation in much of the revised manuscript, although some statements, particularly in the Abstract, could still be phrased more cautiously.

      The revised manuscript also addresses the potential influence of the well-described hyperactivity of Cntnap2 knockout mice. The distinction between hyperactivity and impulsive-like behavior is now more explicitly discussed. In the trace fear conditioning experiments, comparable resting and freezing behavior under control conditions argues against locomotor activity accounting for the memory phenotype. In the radial maze, shorter decision latencies combined with longer post-choice running times are more consistent with reduced deliberation than with a simple increase in locomotor activity. Importantly, the authors acknowledge that the task was not specifically designed to measure impulsivity.

      Overall, the revision has strengthened the manuscript and addressed my main concerns. The principal conclusion-that reduced dorsal CA1 activity contributes causally to impaired temporal binding in Cntnap2 knockout mice-is well supported by the converging behavioral, photometric, and optogenetic evidence. The broader proposal that hippocampal dysfunction is accompanied by greater reliance on egocentric/striatal learning strategies is also supported by the behavioral and cFos data, provided that it is interpreted as an association rather than a demonstrated causal reorganization of memory systems.

      The study makes a valuable contribution by linking hippocampal circuit dysfunction to specific components of declarative memory in a widely used model of autism. More broadly, the combination of temporal binding and memory flexibility paradigms provides a useful framework for investigating how hippocampal dysfunction may alter the organization and flexible expression of memory in neurodevelopmental disorders.

    1. Reviewer #1 (Public review):

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

      Summary:

      In this study, the authors investigate whether glycogen phosphorylase represents a molecular target of benzoylphenylurea insecticides and evaluate the physiological consequences of suppressing glycogen phosphorylase activity in the diamondback moth Plutella xylostella. The authors combine recombinant protein biochemistry, enzyme inhibition assays, RNA interference, structural modelling, metabolite profiling, gene expression analyses, and physiological measurements to determine whether diflubenzuron directly inhibits glycogen phosphorylase and whether suppression of this enzyme is sufficient to impair insect development. Based on these experiments, the authors conclude that diflubenzuron does not directly inhibit glycogen phosphorylase and that insects tolerate substantial suppression of this enzyme through compensatory metabolic responses.

      Strengths:

      This study addresses an important question in insect toxicology by systematically evaluating glycogen phosphorylase as a potential insecticidal target. The authors combine complementary biochemical, molecular, physiological, and structural approaches, including recombinant enzyme characterization, inhibitor assays, RNA interference, metabolite profiling, structural modelling, and measurements of fitness-related traits. This integrative approach provides a comprehensive evaluation of the biological consequences of glycogen phosphorylase suppression. In particular, the biochemical evidence that diflubenzuron does not inhibit glycogen phosphorylase, together with the observation that strong suppression of glycogen phosphorylase produces only transient physiological effects without measurable impacts on development or reproduction, provides strong support for the conclusion that glycogen phosphorylase is unlikely to represent an effective standalone insecticidal target.

      Weaknesses:

      The main limitation concerns the proposed mechanism underlying metabolic compensation. The observed increases in gluconeogenic gene expression, changes in metabolite abundance, and reductions in total protein are consistent with activation of compensatory metabolism, but are insufficient to directly demonstrate increased gluconeogenic flux or establish that amino acid-derived carbon is incorporated into newly synthesized glucose. Similarly, although the analyses of glycogen-associated enzymes strengthen the discussion of alternative metabolic pathways, changes in gene expression alone do not demonstrate that these pathways contribute to glycogen utilization in vivo.

      Some mechanistic interpretations therefore extend beyond the data presented. For example, decreases in total protein are interpreted as evidence of protein catabolism fuelling gluconeogenesis, yet they do not directly demonstrate amino acid mobilization or incorporation into glucose. Likewise, increased expression of gluconeogenic genes is interpreted as evidence of increased pathway activity, although transcriptional changes do not necessarily reflect metabolic flux. Finally, the absence of major developmental defects following glycogen phosphorylase suppression is attributed primarily to metabolic compensation, but an alternative explanation is not fully considered. Such explanation could be that glycogen phosphorylase is not rate-limiting for glucose homeostasis under the nutrient-rich experimental conditions, where dietary carbohydrates are continuously available. Consequently, the proposed compensatory mechanism remains plausible and well supported by indirect evidence, but several aspects would benefit from more cautious interpretation.

      Overall, the authors successfully achieve their primary objective of evaluating glycogen phosphorylase as a candidate insecticidal target. The study provides useful biochemical and physiological evidence that this enzyme is unlikely to represent an effective target for insecticide development in P. xylostella, while highlighting the importance of metabolic plasticity when assessing metabolic targets. The experimental approaches and datasets presented here should be valuable to researchers studying insect metabolism, insecticide mode of action, and target validation, although the precise mechanisms underlying the proposed metabolic compensation remain an important subject for future investigation.

    1. Reviewer #3 (Public review):

      Summary:

      Large Language Models have revolutionized Artificial Intelligence and can now match or surpass human language abilities on many tasks. This has fueled interest in cognitive neuroscience in exposing representational similarities between Language Models and brain recordings of language comprehension. The current study breaks from this mold by: (1) Systematically identifying sentence structures for which brain and Large Language Model representations diverge. (2) Using models structured by semantic roles to help account for divergences. As such the study may now fuel interest in characterizing how Large Language Models and brain representations differ, which may prompt new more brain like language models.

      Strengths:

      (1) This study challenges a literature trend that has touted similarities between Transformer models and human cognition based on representational correlations with brain activity. This challenge is substantiated by identifying sentences for which brain and model representations of sentences diverge.

      (2) This study conducts a rigorous pre-registered analysis of a comprehensive selection of the state-of-the-art Large Language Models, on a controlled sentence comprehension fMRI dataset. The analysis is conducted within a Representation Similarity framework to support similarity comparisons between graph structures and brain activity without needing to vectorize graphs. Transformer language models are predicted and shown to diverge from brain representations on subsets of sentences with similar word-level content but different sentence structures.

      (3) The study introduces a 7T fMRI sentence comprehension dataset and accompanying human sentence similarity ratings which may be a fruitful resource for developing more human-like language models. Unlike other model-based sentence datasets, the relation between grammatical structure and word-level content is controlled, and subsets of sentences for which models and brains diverge are identified.

      Weaknesses:

      (1) The interpretation of findings is nuanced. Although Transformers underperform as brain models on the critical subsets of controlled sentences, a Transformer outperforms all other models when evaluated on the union of all sentences when both word-level content and structure vary. Transformers also yield equivalent or better models of human behavioral data. Thus, although Transformers have demonstrable flaws as human models which are pinpointed here, when tested on all sentences (some) Transformers are more human-like than the other models considered.

      (2) There may be confounds between the critical sentence structure manipulations and visual processing. This is inconvenient because activation in brain regions that process semantics tends to partially correlate with low-level representations of sentence surface features encoded in visual cortex. Although the study commendably controls for confounds associated with sentence length, correlations with key sentence structure models are most salient in visual cortex and diminish in other brain networks when V1-V4 activation is controlled for.

      (3) Sentence similarity computations are emphasized as the basis for unifying comparative analyses of graph structures and vector data. A strength of this approach is that correlation is not always the ideal similarity metric. However, a weakness is that similarity computations are not unified across models. This has practical consequences because different similarity metrics applied to the same model produce positive or negative correlations with brain data.

      Comments on revised version.

      Thanks again for the responses. In particular, the new sentence-length control is helpful for interpreting the anomalous outcomes from the DIEM analysis, and the amendments to the discussion are appreciated.

    1. Joint Public Review:

      Summary:

      Brain sizes vary by orders of magnitude between different organisms, while neuronal circuits maintain essential computational functions. Castro and Cardona explore invariant features across animal species that lend themselves as fundamental constraints on scaling mechanisms. The authors leverage a number of existing connectomics datasets for their study, from which they extract morphologies and synaptic connections for numerous neurons, resulting in a set of neuronal features such as neuron lengths and synapse counts.

      Their core result is a rather stable synapse density of 1 synapse per 1 µm of dendritic path length across neurons from different datasets, in line with prior results in mouse (Turner et al., 2022) and human (Lomba et al., 2022). The authors show that this finding also holds for the selected neurons in Drosophila (adult and larva) and zebrafish larva, and further aim to explore mechanisms creating this density and its consequences on neuronal excitability. They show that their data is in agreement with previously reported scaling rules of dendritic arborization (Cuntz et al., 2012). Through exploration of synapse sizes and dendrite radii, the authors identify a compensatory effect of dendrite radius for fluctuations of synaptic densities that can provide voltage response stabilities.

      Overall, this study is an addition to the burgeoning field of comparative connectomics, and as such, the presented analyses are important methodological contributions. The conclusions presented here are, however, too general. The analyzed datasets are reduced to a few cell types due to technical challenges, and cell type identities are ignored even though they have large ramifications for the analyses presented (e.g., E vs I for stability analyses, and cell type correlations with synapse sizes).

      Strengths:

      (1) Novelty.

      The authors provide new ways to compare neuronal measurements between brains and species and how to interpret the results. In particular, their conclusions for normalization of connection strength (by total number of synapses onto a neuron) are an important contribution to the analysis of neuronal circuits, especially in Drosophila. The finding of the density is important, but similar numbers have been reported by prior studies of some of the same datasets (Loomba, Turner).

      (2) Wiring optimization.

      The presented study is an important validation of the scaling law across organisms and cell types.

      (3) Scale.

      The authors collected neurons from several connectomics datasets from different organisms that were created by different labs, requiring standardizing reconstructions and extracting features across a large number of neurons

      Weaknesses:

      (1) Data preparation and presentation. The authors describe how the data was processed and manually corrected in the methods, but at no point other than in Figure S4 (which shows a single neuron from afar) is an actual neuron skeleton shown to convince the reader that this was done well. The resolution of the skeleton has important ramifications for the measured path lengths. Further, it is not clear how spine heads, very short branches, and twigs were handled. Tracing out spine heads could double the path length, similar for twigs. How these were handled should be discussed and justified. Radius measurements were taken at the trunk of the neuron, but for synapses on spines, the spine size (especially neck (Harnett et al., 2012)) is critical for estimating input resistance. This should at least be discussed and justified. Further, it is not clear how synapses onto the soma were handled. What was chosen as the radius there?

      (2) Data filtering. The authors excluded substantial numbers of neurons from the analyzed datasets, leaving only cells from a few cell types. However, the manuscript gives the impression in many places that the analyses were run across the entirety of those datasets. Given the number of neurons used (e.g. only 60 from the Drosophila adult!), it would be much more prudent to talk about the specific cell types and not the datasets/animals. Further, the way the included neurons were chosen is likely to introduce a bias. E.g., in Drosophila datasets, neurons with more synapses on the backbone rather than twigs automatically have higher postsynaptic completion ratios. Overall, given the number of neurons, the results cannot be easily generalized even for the datasets used here.

      (3) Ignoring cell types. Especially for the mammalian datasets, presynaptic cell type identity is correlated with synapse size and location. Ignoring this information removes important context from the analysis. For instance, inhibitory synapses are more prevalent close to the soma, etc.. This clearly impacts the analyses presented, yet is ignored and not discussed. Further, the sign of the synapses and, in particular, the balance of E vs I synapses, is important for the analysis of voltage response stability.

      (4) Wiring optimization rule. The presented analysis convincingly confirms the scaling law from Cuntz, et al. (Figure 3b). However, taken together with the prior finding of the 1 synapse / 1 µm density along dendrites, the sensitivity analysis appears to be circular (Fig. 3c). Since the inputs are length and synapse count, the same that were put into the density analysis, the result rather reconfirms the scaling law.

      (5) Synapse size and PSD area. Two measurements for the synapses were used for the MICrONS datasets, but in some places, this is confusing. Why were the volumetric synapse sizes not fully replaced with the PSD measurements, as these are likely a superior measurement of the "size" of the synapse? Annotations of the PSD should also be shown somewhere to convince the reader of their quality.

      (6) Zebrafish dataset. The validity of the corrections used for the zebrafish dataset is difficult to judge for someone not familiar with that dataset. It appears that there are substantial problems in the reconstruction of the dendritic tips. Other datasets were ignored for seemingly similar reasons. Why was this one kept? The correction factor introduces an arbitrariness to the analysis, and it directly affects the core result of this study.

    1. Reviewer #1 (Public review):

      The mitochondrial intermembrane space (IMS) is a compartment under constant proteostasis stress. During the development of multicellularity, the IMS acquired the AAA+ ATPase CLPB, a disaggregase whose absence from cells results in aggregate formation in the IMS and whose mutation in humans leads to rare but severe human diseases.

      The precise molecular function of CLPB in the human IMS remains unresolved and is addressed in this study, in particular the crosstalk with the IMS protein HAX1, which is a prominent interaction partner of CLPB.

      The authors find HAX1 to serve as an activating cofactor of CLPB as a disaggregase and refoldase in a purified system. This is well in line with the similar phenotypes of HAX1 and CLPB loss, and is an exciting finding as it not only assigns a direct role for HAX1 in the IMS but also yields the potential for CLPB activity regulation by regulating amounts of HAX1. The experimental support for this finding is strong and acquired by a combination of different and carefully executed in vitro enzyme activity assays.

      One potential weakness of this study is that it does not consider recently identified players in the CLPB-HAX1 axis, FAM136A (now called TIMCC) and MIA40, that might additionally modulate/regulate CLPB activity. This might constitute an exciting route for future research.

    1. 10 F 19 c.2588G>C c.1222C>T

      Case#: Patient 10, female, age 19

      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.2588G>C Allele 2: NM_000350.3:c.1222C>T

      ClinVar: Allele 1: NM_000350.3(ABCA4):c.2588G>C (p.Gly863Ala) Allele 2: NM_000350.3(ABCA4):c.1222C>T (p.Arg408Ter)

      CAID: Allele 1: CA119128 Allele 2: CA179692

      SupplementalData: composite mask analysis shown in figure 3 for patient 10

    2. 11 M 53 c.5461–10T>C ND

      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

    3. 14 F 42 c.4222T >C c.4918C>T

      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

    4. 19 F 16 c.5714+5G>A c.4469G>A

      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

    1. Reviewer #1 (Public review):

      Objectives of the study and impact of the work

      The authors of this article primarily aim to reconstruct the evolutionary history of the insect odorant receptor (OR) family, which is responsible for the detection of odorant signals by olfactory neurons. Due to the lack of phylogenetic signal present in the sequences of this multigene family, which evolves very rapidly, phylogenetic analyses have so far never made it possible to precisely retrace how ORs diversified prior to the appearance of present-day insect orders, and what the drivers of this diversification were. For example, one may suspect that the adaptation of ORs to odors emitted by plants constituted a critical step in insect evolution during the "angiosperm terrestrial revolution," which occurred at the end of the Cretaceous, but nothing currently allows this to be asserted.

      There are very nice examples, notably in drosophilids, derived from comparisons between closely related species and documenting mechanisms of OR adaptation to certain signals. However, what the authors attempt to do in this work is to produce a macroevolutionary analysis at the scale of insects as a whole, based almost exclusively on bioinformatic analyses. To do this, they annotated OR genes in about one hundred insect species and developed pipelines for analyzing sequence similarity, structural similarity and functional similarity, the latter being estimated through a molecular docking approach. An important element in the evolution of insect ORs is the appearance of a unique co-receptor, called Orco, which appears to be an OR that has lost the ability to bind odorants. In addition to the large-scale bioinformatic analysis, the authors also aim to explore more specifically the factors that favored the emergence of Orco and the selective advantage conferred by the existence of OR-Orco complexes.

      Given the importance of odorant receptors in insect biology and in their adaptation to different environments and lifestyles, retracing their evolutionary history is indeed a major question in evolutionary biology. In principle, this type of work therefore has the potential to become a reference in the field and to provide a basis for significant scientific advances.

      Major strengths and weaknesses

      The sampling chosen for collecting OR sequences is very impressive, with more than 100 insect families represented, covering most of the major orders. This sampling appears appropriate for the question being addressed. The analysis pipeline used to collect the sequences makes sense, relying on homology-based annotation tools coupled with a structure-based filter. Nevertheless, one can note aberrant numbers of ORs for certain species (much lower than reality). A lower number of OR genes is somewhat expected, as the authors chose to apply a fairly stringent filter on sequence quality (based on predicted 3D structure), which reduces the number from 14,000 to 9,000. This choice seems logical given the subsequent use of these data, but it inevitably leads to data loss. However, the low number of genes also results from the fact that the pipeline did not function correctly for all genomes.

      In the revised version of the manuscript, the authors included a benchmarking step, which is a good point. They compared their OR gene annotations with previous reports in the same species. Unfortunately, this comparison is irrelevant because the chosen reference OR repertoires are actually a mix of transcriptome and genome annotations. Furthermore, comparisons with entire OR gene repertoires essentially demonstrate that their annotation was of good quality for species in which OR sequences were already present in the query OR database, but poor for species in which they were not. Therefore, these supplementary analyses made by the authors are not particularly in favor of an overall good quality of OR gene repertoires in the >110 species studied. The fact that some OR genes may be missing and that the total number may not be exact for each species is not prohibitive for studying the evolution of the family on a broad scale. However, it does call into question the correlation between the number of ORs and lifestyles and diets.

      From the dataset collected, the authors attempted to categorize ORs in several ways, starting with the reconstruction of sequence similarity networks. The approach is interesting, but fails to reveal homology relationships between ORs from species belonging to different insect orders. So it is unclear what the advantage of this approach is compared with the "classical" phylogenetic approach.

      The clustering based on structure also leads to the identification of a majority of "order-specific" clusters, which does not provide major insights into the evolution of ORs. However, the authors highlight a group of ORs in flies that appear to possess an unusual intracellular region, as well as a cluster of OR shared across many insect orders that exhibit a larger binding cavity. This is really interesting, although more relevant to OR structure than to their evolution.

      The analysis of structural diversity then leads the authors to focus on the Orco co-receptors, which are characterized by modifications of the binding pocket and the appearance of an extracellular loop that could explain the loss of the ability to bind odorant molecules. This part, which relies on in vitro experiments, is interesting and constitutes the most striking result of this study, which could in itself have been the subject of a separate manuscript.

      The rest of the manuscript is based on the prediction of OR response spectra using molecular docking. The work that has been carried out is extremely substantial, and the objective of linking clusters based on sequence similarity or 3D structural similarity with functional categories is entirely relevant. The docking score threshold used was chosen thoughtfully, which is very good, and according to the calculation performed should ensure a true positive rate of more than 20%, which is excellent in such a docking analysis. But in the absence of functional validation, this 20% true positive rate is not sufficient to extrapolate OR function, and docking-derived binding breadth measures used in the remaining of the manuscript have to be taken with caution, as acknowledged by the authors themselves. Consequently, the chance that results of this part of the work will enlighten the evolution of OR on a broad scale is low. For example, the fact that insect lineages that emerged after the Permian-Triassic extinction have more broadly-tuned OR is an interesting observation, yet remains highly speculative.

      In summary, despite the large number of analyses performed, the authors do not really succeed in achieving the stated objective of reconstructing the evolutionary history of insect ORs, and the results obtained do not strongly support all the conclusions regarding the links between OR repertoires and environment or lifestyle.

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

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

      Strengths:

      • Novelty and significance: First strong demonstration of a magnetic-visual compass in a globally relevant migratory moth species, extending previous findings from the Bogong moth and opening new research avenues in comparative magnetoreception.<br /> • Methodological robustness: Use of validated and sophisticated behavioural paradigms and magnetic manipulations consistent with best practices in the field. The use of 5 min bins to study a dynamic nature of magnetic compass which is anchored to a visual cue but updated with latency of several minutes is an important finding and a new methodological aspect in insect orientation studies.<br /> • Clarity of experimental logic: The cue-conflict and visual cue manipulations are conceptually sound and capable of addressing clear mechanistic questions.<br /> • Ecological and applied relevance: Results have implications for understanding migration in an invasive agricultural pest with expanding global range.<br /> • Potential model system: Provides a new, experimentally accessible species for dissecting the sensory and neural bases of magnetic orientation.

      Weaknesses:

      Overall, this is a strong study, and the authors have completed an excellent major revision.

    1. Reviewer #1 (Public review):

      Summary:

      Davis and co-authors used many mouse models to investigate the mechanisms which regulate the contractility of mouse popliteal collecting vessels, primarily chronotropy. The authors use prior literature from the vasculature as a framework to test concepts in lymphatic vessels. The mouse models they used provide evidence for and against the involvement of multiple proteins in regulating chronotropy and other contractile properties in lymphatic vessels. The large amount of data indicate that mechano-stimulation of GNAQ/GNA11-coupled GPCRs generates IP3, which induces intracellular Ca2+ release through IP3R1 to drive depolarization through the activation of ANO1 Cl- channels.

      Strengths:

      Major strengths of the study are the vast number of mouse knockout models which were used to test the importance of ion channels and G protein signaling pathways in the regulation of lymphatic vessel contractility. The study is a valiant effort and contains a large amount of data. The authors achieved several objectives to find that ANO1 and IP3R1 regulate chronotropy and many other potential proteins do not regulate chronotropy. This study will have a major impact on the field.

      Weaknesses:

      The authors did an excellent job with the revision. There are no weaknesses.

    1. Reviewer #1 (Public review):

      Summary:

      In this revised manuscript, Vineis et al. examined the functional capacity for organic matter decomposition among cooccurring microbes in Spartina patens dominated deep salt marsh sediment cores using genome reconstruction, cooccurrence networks, and genome scale metabolic modeling. They attempted to test a couple of hypotheses that include 1) microbial communities are structured according to sediment depth, 2) deeper communities are functionally streamlined, 3) the community found within deeper sediments is more likely to contain cooccurring members, 4) there is metabolic complimentary enabling sequential decomposition of complex carbon among microbial communities located in deeper sediments, and 5) the population structure is depth-dependent. They identified depth-dependent structure of microbial communities and populations, environmental filtering of microbes with depth, and metabolic complimentary among members of the Bathyarchaeia BA1 subnetwork that possibly enables sequential decomposition of organic carbon in the deep sediment. Overall, the authors have achieved their aims, with the results supporting their main conclusions. The findings of this work will contribute to our understanding of organic matter transformation in salt marsh sediments and, more broadly, microbial metabolism in energy-limited systems.

      Strengths:

      (1) Two long sediment cores (down to 240 cm deep) were collected in this study, allowing investigation of the less well characterised subsurface microbiome in salt marsh.

      (2) A genome-resolved metagenomic approach was employed here, which provides information on both the structure and functional potential of the salt marsh sediment microbiome, which is not possible in commonly performed 16S rRNA-based surveys.

      (3) Metabolic complementarity analysis and metatranscriptomics were used to address the likelihood of metabolic handoffs, providing evidence of potentially active microbial interactions.

      Weaknesses:

      (1) No geochemical data are available to provide context for the genomic analysis here. Without such information, readers cannot even tell whether the surface sediment samples were oxic or anoxic.

      (2) A single metagenomic binning tool, CONCOCT, was used in this study, which very likely has resulted in a limited number of MAGs recovered. More (high-quality) MAGs are expected with the use of additional binners and a bin consolidation procedure. A manual bin refining process was used to improve the quality of the bins obtained though.

    1. Reviewer #1 (Public review):

      [Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. After previous evaluation by three competent reviewers, the authors have provided an extensive response to their criticisms and recommendations. I believe that authors have done an adequate job in addressing the initial reviews and recommend that the paper be processed for the Version of Record without further work at this time.]

      Summary:

      Torpor can be induced by chemogenetic activation of the medial preoptic area. This activation leads to protection from myocardial infarction in an isolated heart preparation despite normalization of the ambient temperature, thus, in principle, uncoupling hypothermia from torpor-induced neuroprotection. Putative pathways of protection are suggested by proteomic studies.

      Strengths:

      (1) Elegant strategy for inducing torpor in rats.

      (2) Appropriate controls for verifying the neuron transducer.

      (3) Cardiac protection is significant and appears independent of hypothermia.

      (4) Interesting omic strategy to begin to find established and novel pathways mediating organ autonomous torpor-induced protection.

    1. Reviewer #1 (Public review):

      Pyne and Pandey et al. report the observation of early DNA degradation at the phagocytic cup during macrophage engulfment. Using an elegant experimental system that combines actin staining to visualise cup formation with direct monitoring of DNA degradation, the authors identify rapid recruitment of the membrane-bound nuclease DNase X (DNase1L1) to nascent phagocytic cups. This recruitment occurs within minutes of cup formation, is independent of DNA presence at the substrate, and appears to originate from intracellular membrane structures rather than from the extracellular environment. The results support the conclusion that DNase X activity is present at the phagocytic cup and that DNA digestion can begin prior to phagolysosomal maturation.

      The study is technically strong. The experimental system is clean, specific, and allows precise spatial and temporal detection of DNA degradation. The imaging-based approaches are carefully executed and enable convincing visualisation of DNase X recruitment and activity. The use of an alternative substrate beyond the primary SNS system strengthens the core observation, and the data broadly support the authors' central claim.

      However, several limitations temper the physiological interpretation. The system relies largely on short, free DNA substrates, leaving open how efficiently DNase X processes more complex or physiologically relevant DNA structures, such as nucleosome-bound DNA or neutrophil extracellular traps (NETs). It remains unclear whether DNase X deficiency would alter macrophage responses to larger nucleic acid structures, influence engulfment efficiency, or modify downstream inflammatory signalling pathways such as TLR9 or STING activation. Moreover, the experimental setup prevents full phagocytic cup closure, potentially prolonging DNase activity compared with physiological phagocytosis, which typically proceeds rapidly to cargo internalisation. For example, the peak signal observed in Figure 5 occurs approximately 90 minutes after phagocytic cup formation, a time point at which many phagocytic cups would be expected to have already closed under physiological conditions. Additional work using fully engulfed cargo in more physiological contexts would clarify whether early DNase X activity meaningfully contributes to overall DNA clearance kinetics.

      Mechanistically, the signal that triggers DNase X recruitment remains unresolved. Although actin rearrangement was excluded as the primary driver, the upstream cues that direct DNase X-containing membrane structures to the forming cup are not yet defined.

      In the broader context, early DNase X activity at the phagocytic cup could represent an additional safeguard against inflammatory signalling by limiting extracellular or surface-associated DNA before phagolysosomal degradation by DNase II. This mechanism may be particularly relevant in settings where DNA fragmentation before engulfment is incomplete, such as necroptosis or NET formation. Determining whether DNase X deficiency exacerbates inflammatory responses, alters DNA clearance efficiency in vivo, or contributes to immune pathology will be critical for establishing its physiological and disease relevance.

      Overall, this is a compelling study that introduces a novel concept of pre-phagolysosomal DNA digestion. The conclusions are well supported within the in vitro system used, but further investigation using diverse DNA substrates and physiologically relevant models will be required to fully define the impact of this mechanism on immune regulation and disease.

      Comments on revised version.

      The authors have responded constructively to the points raised in my original review. Fig. S5 extends the substrate range beyond the 18-bp SNS construct by showing degradation of plasmid DNA immobilised on microbeads, and fig. S8 addresses my concern that the surface-immobilised platform prevents phagocytic cup closure, by demonstrating DNase activity at cups forming over free, internalisable beads. Together with the live-imaging data in Fig. 1I, these additions support the central claim that DNase activity begins at the nascent phagocytic cup, before closure and well before phagolysosomal maturation. I consider my principal concerns addressed and see no reason to alter the eLife Assessment.

      One point remains for readers rather than as a request. The new data establish that DNA at the cup is degraded, but do not themselves demonstrate that DNaseX is responsible, since neither fig. S5 nor the biofilm experiments in Fig. 7 include the PI-PLC or siRNA controls used in Fig. 3; the authors appropriately acknowledge this limitation for the biofilm data. The physiological questions raised in my original review - the handling of chromatin-associated DNA and NETs, and whether DNaseX activity at the cup limits downstream sensing of extracellular DNA - remain open, and the manuscript is appropriately framed as establishing the phenomenon rather than resolving its physiological role.

    1. Reviewer #1 (Public review):

      This study applies a recently developed reverse-engineering framework for motor unit discharge to a large dataset from individuals with multiple sclerosis (MS) and neurologically intact controls. The authors aim to determine whether abnormalities in voluntary motor control in MS can be attributed to different patterns of excitatory, inhibitory, and neuromodulatory input to spinal motoneurons. A major conceptual emphasis of the study is on heterogeneity: rather than asking only whether people with MS differ from controls on average, the authors examine whether the distributions of motor unit discharge features and derived physiological variables are broader and more diverse across affected individuals.

      A major strength of the work is the size and richness of the dataset. The study includes 89 participants with MS and 34 controls, with high-density surface electromyography (HDsEMG) used to obtain large populations of motor unit discharge patterns from the tibialis anterior (TA) and soleus (SOL) muscles. The resulting dataset contains many thousands of motor unit recordings and allows the authors to examine both group means and the shapes and variances of participant-level distributions. The finding that several motor unit discharge characteristics are more broadly distributed in MS than in controls is convincing and potentially important. In particular, the observation that affected individuals can occupy both high and low extremes of these distributions provides a useful empirical description of the diversity of motor unit behavior in this disease.

      The principal limitation concerns the physiological interpretation assigned to these discharge patterns. The excitation, inhibition, and neuromodulation variables are not directly measured physiological inputs. They are composite variables derived from several features of motor unit discharge, with each feature weighted according to relationships identified in simulations reported previously by Chardon and colleagues (reference 1). Thus, the step from observed discharge behavior to specific underlying synaptic mechanisms is necessarily model-dependent. The distinction between these two levels of inference is important for interpreting the main conclusions of the study.

      This issue is especially relevant because several different physiological processes can plausibly influence the same discharge features. Motor unit firing patterns reflect not only excitatory and inhibitory synaptic inputs and neuromodulation, but also intrinsic motoneuron properties, persistent inward currents (PICs), after-hyperpolarization (AHP) properties, tonic inhibition, the time course of synaptic excitation, and afferent input. Some of these factors are acknowledged as limitations of the modeling framework in the manuscript. The current data therefore provide strong evidence for heterogeneous motor unit discharge phenotypes in MS, but more indirect evidence that this heterogeneity can be uniquely attributed to distinct patterns of excitatory, inhibitory, and neuromodulatory input.

      The interpretation of inhibition is a particularly clear example of this general inverse problem. In the underlying modeling framework, inhibition is represented along a continuum from proportional or balanced inhibition to reciprocal or push-pull inhibition. These different patterns influence PICs and consequently alter firing-rate nonlinearity and rate modulation. This provides a plausible forward-model relationship between inhibitory organization and motor unit discharge. However, observing a particular firing pattern in vivo does not necessarily identify the organization of inhibitory input uniquely, because similar changes in firing-rate modulation or hysteresis could arise from altered neuromodulation, intrinsic motoneuron properties, or other changes in synaptic drive. The inhibition composite is therefore best interpreted as a discharge phenotype that is consistent with a particular inhibitory organization under the assumptions of the model, rather than as a direct measure of inhibitory synaptic input.

      A related methodological issue concerns the construction of the composite variables. The authors use mutual-information (MI) values from the previous simulation study as weights in signed linear combinations of normalized discharge features. Mutual information quantifies how informative a feature is about a modeled input parameter, but it is not itself a regression coefficient or a measure of the magnitude of a physiological effect. In addition, different discharge features may contain overlapping information about the same underlying process. The resulting composites are therefore useful summary measures of patterns associated with the modeled physiological variables, but their quantitative interpretation as direct estimates of those variables is less certain. This distinction is particularly relevant because the manuscript sometimes moves from describing the composite variables to describing the corresponding physiological inputs themselves.

      The study's emphasis on variability also raises an important measurement issue. Because increased between-participant variance is itself one of the central biological findings, differences in measurement precision between the MS and control groups are more consequential here than in a conventional comparison of group means. Participants with MS sometimes had greater difficulty producing smooth triangular contractions, and motor unit yield and decomposition quality may plausibly vary more across affected participants. If measurement or decomposition uncertainty were more heterogeneous in the MS group, this could broaden participant-level distributions and thereby amplify the appearance of biological heterogeneity. The manuscript uses established decomposition and quality-control procedures, so this is not a general challenge to the validity of HDsEMG. Rather, it is a consideration that is particularly important when increased distributional spread is itself the primary result.

      The manuscript also makes a stronger interpretive step from broad group distributions to patient-specific pathophysiology. The data convincingly show that motor unit discharge-derived measures are more heterogeneous among people with MS. They do not yet establish whether this variation represents distinct mechanisms in individual patients, continuous variation in a common mechanism, identifiable pathophysiological subgroups, differences in disease severity or lesion distribution, or some combination of these factors. The manuscript itself recognizes this distinction when it identifies the separation of individual-level variation from potential subgroups as an important goal for future work.

      Overall, this is a valuable study with an unusually large motor unit dataset and a compelling demonstration that motor unit discharge behavior is markedly heterogeneous in MS. The work also provides an informative application of a model-based reverse-engineering framework to a clinically diverse human population. The evidence is strongest for the descriptive conclusion that motor unit discharge phenotypes are heterogeneous and altered in MS. The more specific attribution of these phenotypes to excitatory, inhibitory, and monoaminergic inputs is plausible and potentially useful, but remains contingent on the assumptions and identifiability of the underlying model. With this distinction in mind, the dataset and analytical approach should be useful to researchers interested in motor unit physiology, disease-related variability in motor control, and the possibilities and limitations of inferring latent physiological mechanisms from human motor unit discharge.

      Reference 1: Chardon, M. K. et al. Supercomputer framework for reverse engineering firing patterns of neuron populations to identify their synaptic inputs. eLife 12, RP90624 (2024).

    1. Reviewer #1 (Public review):

      Summary:

      Here, the authors attempt to show that CCL5 is increased after stroke, possibly due to decreased miR-324, and that this is a modifiable system to decrease stroke damage. By bidirectionally manipulating CCL5 levels through direct injection of CCL5; a CCL5 blocking antibody; miR324; miR324 antagomir; or CCR5-blocking Maraviroc, they broadly show improvement with lower CCL5 levels. This includes infarct size, behavioral analysis, and immunohistochemical analysis of astrocytes, microglia, and neurons. They further try to mechanistically tie miR324 and CCL5 in astrocytes specifically to stroke-induced changes using a neuronal/astrocytic coculture system. They argue that decreasing CCL5 leads to increased ERK and CREB phosphorylation as a potential neuroprotective mechanism. CCL5 is one potential ligand for CCR5, and recent work identified CCR5 as a targetable mechanism by clinically-approved drug Maraviroc to enhance stroke recovery. Particularly given the high level of interest in CCR5 in stroke recovery, the focus on CCL5 - one of CCR5's potential ligands - and its miR regulation is an exciting expansion of this area of stroke biology.

      Strengths:

      The authors' findings that decreasing CCL5 acutely after stroke shows behavioral improvement appear robust. This broadly replicates work from other groups, although the finding that miR324 manipulation can phenocopy direct CCL5 manipulation is novel and intriguing. However, many of their other claims are difficult to evaluate based on a combination of missing methodological information, inappropriate statistical testing, and a flawed culture system.

      Weaknesses:

      Broadly speaking, the manuscript takes a zoomed-out view of what is fundamentally highly localized biology.

      (1) miRNA-based regulation, by definition, has to include miR and mRNA in the same cell type; as the authors note, CCL5 is expressed in many cells. It is therefore impossible to propose any interaction on the basis of the tissue-level changes described; any evidence of in vivo cell-type specificity would dramatically improve the claims.

      (2) The authors treat an extensive area of ipsilesional cortex uniformly as "IP". Astrocytic and microglial responses to localized injuries such as stroke are highly location-dependent and undoubtedly change dramatically within this area. The presented data cannot be interpreted without confirmation that these were taken at identical distances from the injury, and what that distance was. These do not appear to be adjacent to the injury, where the responses would presumably be the most informative. Similarly, it is difficult to interpret the neuronal Sholl and spine data without more information on where within the large IP region these neurons were found.

      The authors attempt to narrow in on cell-type specificity via culture. However, astrocytes are notoriously prone to a dramatic change in culture and require careful methods (immunopanning; see eg doi: 10.1016/j.neuron.2011.07.022) to maintain much resemblance to their in vivo counterpart. It is difficult to conclude much about the role of astrocytes in the CCL5 pathway based on the use of this shaking-based culture system, particularly in the absence of cell-type specific validation in vivo.

      There is missing methodological information, including infarct size measurements, TUNEL staining, and statistical testing. The TTC figures look very odd, like a collection of overlapping stars have been placed on the images rather than the natural relatively smooth infarct edges one would expect. It is unclear if the infarct volume measurements accounted for edema, as is standard; there is no description of the protocol used for quantification. It is also unclear if the infarct volume measurement comparisons were also done with t-tests vs ANOVA, as the statistical test used is not listed in the figure legends. In numerous cases where statistical testing is listed, repeated t-tests between subgroups are used vs the more appropriate ANOVA (assuming normality; nonparametric testing as appropriate), making it difficult to have confidence in the results.

    1. Reviewer #1 (Public review):

      Summary:

      Hsiung et al. investigated whether the effects of autophagy gene knockdown on the lifespan of long-lived C. elegans mutants depend on experimental conditions. The authors first compiled published data on autophagy-dependent lifespan regulation in daf-2 and wild-type backgrounds, highlighting that prior results are notably inconsistent and likely context-dependent. They then systematically tested the lifespan effects of RNAi knockdown of six autophagy genes (atg-2, atg-4.1, atg-9, atg-13, atg-18, and bec-1) in wild-type (N2), daf-2 (reduced insulin/IGF-1 signalling), and glp-1 (germlineless) animals, while varying temperature, daf-2 allele, FUDR concentration, and bacterial infection status.

      The key findings are as follows. In wild-type animals, lifespan suppression by most autophagy gene knockdowns was more pronounced at 20{degree sign}C than at 25{degree sign}C, where little or no effect was observed. In daf-2 mutants, stronger lifespan suppression was seen in the weaker daf-2(e1368) allele at 20{degree sign}C, but not in the stronger daf-2(e1370) allele, and effects were largely absent at 25{degree sign}C. In glp-1 mutants, four of six gene knockdowns suppressed lifespan to a greater extent than in N2, though again in a temperature-dependent manner. FUDR at a high concentration (800 µM) abolished the life-shortening effects of most knockdowns and, in the case of atg-9 and atg-13, led to lifespan extension. Kanamycin treatment to eliminate bacterial proliferation did not fully account for the lifespan effects, suggesting that increased susceptibility to infection is not the primary mechanism. The authors also tested the programmed aging hypothesis that autophagy promotes lifespan reduction through biomass repurposing, but found no changes in vitellogenin levels upon knockdown of any of the six genes.

      Altogether, among all genes tested, atg-18 knockdown produced the strongest and most consistent lifespan suppression across nearly all conditions, including both daf-2 and glp-1 backgrounds. The authors probed whether atg-18 acts through the FOXO transcription factor DAF-16 by examining dauer formation and ftn-1 expression, but found no evidence for this, suggesting a DAF-16-independent mechanism.

      Strengths:

      The primary strength of this work lies in its systematic and comprehensive approach to dissecting how experimental variables influence the outcome of autophagy-lifespan epistasis tests. The compilation of prior data alongside the authors' own multi-condition dataset is a genuinely useful resource for the field. The study raises a timely and important point about condition selection bias in interpreting autophagy lifespan relationships, with broader relevance to C. elegans studies. The finding that atg-18 behaves distinctly from other autophagy genes across a range of experimental conditions is particularly noteworthy and provides an interesting direction for future mechanistic investigation.

      Comments on revised version.

      The authors have carefully addressed the concerns raised in the previous review and have incorporated most of the suggested revisions. In particular, the revised manuscript provides greater clarity regarding the effects of glp-1 and FUDR and improves the presentation and interpretation of the experimental findings. The authors have also provided useful clarification regarding the variability between lifespan experiments, the number of biological replicates, and the interpretation of RNAi efficacy.

      I have only two minor suggestions concerning the wording and organization of the manuscript, which I have communicated separately to the authors. These points are intended to further improve clarity and accuracy and do not affect my overall assessment of the study.

      Overall, I am satisfied with the revisions and consider the manuscript to be a valuable contribution to our understanding of the context dependence of autophagy-mediated lifespan regulation.

    1. Reviewer #1 (Public review):

      [Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The original reviews were generally positive. In their revision, the authors partially address reviewers concerns, but mention that a number of requested experiments are for future studies.]

      Summary:

      This is an interesting manuscript by Kirk and colleagues describing a highly valuable knock-down system that leverages CRISPRi in order to further elucidate the role of the Kruppel-Like Factor (KLF) transcription factor family in regulating the maturation of postnatal cortical projection neurons. The authors firstly use RNA-Seq and ATAC-Seq data in order to identify the KLF TF family as a potential regulator of cortical neuron maturation in the postnatal brain and subsequently knock down four KLF family members; KLF9, KL13, KLF6 and KLF7, in order to ascertain the functions of specific KLF genes in the developing cortex. The described CRISPRi knock down strategy is highly robust and penetrant as evidenced by a KD efficiency > 95% (assessed by both qPCR and single molecule FISH) and demonstrates that KLF6 and KLF7 play an activating role in driving the expression of target genes relating to axonal growth whereas KLF9 and 13 play a repressive role that inhibits the expression of overlapping gene targets. Together, the authors propose a model where the KLF TF family acts as a regulatory "switch" from activation to repression in the postnatal cortex as a mechanism to control a shift in projection neuron function from axonal growth to circuit refinement. The findings and conclusions of the manuscript offer a valuable contribution to the field of postnatal cortical development and further our understanding of the regulatory mechanisms that govern neuron maturation.

    1. 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.

    1. Reviewer #1 (Public review):

      Summary:

      This study addresses the gap between calls to incentivize Open Science practices through research assessment reform and its implementation by Research Performing Organizations (RPOs). To help RPOs get started and prioritize their assessment reforms, it makes a series of recommendations for action. It does so via an expert Delphi process, where consensus around six standards was reached. The purpose is to provide a resource for would-be reformers in Research Performing Organizations around the world, in the hope of advancing the Responsible Research Assessment and Open Science reform movements across global academia. The standards are not meant to be one-size-fits-all, but customizable to local needs and implemented selectively at the discretion of a given RPO.

      Strengths:

      Overall I was impressed with the contribution. Generally speaking, it clearly sets out its methods and arguments. I recognize there is indeed a growing need to support RPOs at varying levels of maturity, to get started and orient themselves around research assessment reform, so this seems to me like it will be a useful offering. The Delphi approach is well explained, and further information is provided in supplementary files.

      Weaknesses:

      Some further reflection on the disciplinary make-up of the Delphi participants would be helpful. Somewhat more hedging on the limitations of the manuscript would help improve the contribution, as would further details on how this contribution sits in relation to existing resources and studies on implementing open science-aware research assessment reforms.

    1. Reviewer #1 (Public review):

      Summary:

      In this manuscript, Matar et al. introduce Mespilia globulus, the tuxedo sea urchin, as a new genomically-enabled model for echinoderm developmental biology. The authors establish a closed life-cycle culture system in a land-locked aquarium facility, demonstrate that key experimental techniques (hybridization chain reaction labelling and CRISPR/Cas9 gene knockout) are tractable in this species, and report chromosome-scale genome assemblies for two colour morphs and both sexes. Using these resources, they compare genome architecture and gene family evolution across sea urchin species, and investigate the genomic basis of sex determination.

      Strengths:

      The central motivation for this work is well justified: the long larval and juvenile periods of established sea urchin models such as Strongylocentrotus purpuratus have long limited the study of post-metamorphosis and adult biology, and M. globulus reaches metamorphosis in around two weeks and sexual maturity within four to six months, a substantial acceleration. The husbandry and life-cycle data are thorough, and the demonstration that hybridization chain reaction staining and CRISPR/Cas9 knockout both work as expected in this species convincingly establishes its experimental tractability. The two chromosome-scale genome assemblies are of high quality (BUSCO completeness above 99%, 21 chromosome-scale scaffolds consistent with other sea urchins), and the comparative synteny and gene family analyses are carefully constructed, drawing on a solid phylogenomic framework (CAFE-based gene family turnover analysis across six echinoderm species). The authors' finding that M. globulus has fewer duplicated genes in the gene repertoire relative to other camarodont urchins is a genuinely useful observation for researchers choosing a model system for functional genetics, since fewer paralogues should simplify interpretation of knockout phenotypes.

      Weaknesses:

      Some claims in the manuscript would benefit from additional supporting detail.

      (1) The efficiency of the CRISPR/Cas9 knockout is illustrated qualitatively, but no sample size or penetrance value is reported, making it difficult for readers to judge how robust or reproducible this result is.

      (2) The gene annotation is reported to have complete PFAM domain coverage for only 75% of predicted genes, but no independent completeness metric (such as BUSCO scored against the annotated gene set rather than the assembly) is provided, leaving open whether the remaining genes are genuinely novel, partial models, or annotation artefacts.

      (3) Finally, at the time of review the NCBI BioProject accession cited for the genome and sequencing data (PRJNA1477966) could not be located, and it is not clear from the text whether this accession, once available, will include the gene annotation and RNA-seq datasets in addition to the raw genomic sequencing reads.

      In summary, the authors achieve their stated aim of establishing M. globulus as a tractable, fast-developing echinoderm model, and the genomic and experimental resources presented support this conclusion. The comparative genomic conclusions - conservation of ancestral chromosome linkage groups, absence of a heteromorphic sex chromosome, and a comparatively low rate of gene family expansion - are well supported by the data shown, though some of the finer-grained claims (knockout efficiency, annotation completeness) require some clarification. Given the scarcity of tractable models for post-metamorphosis and adult echinoderm biology, this resource is likely to be of real value to the field, provided the genomic and transcriptomic data are made fully and clearly accessible to the community.

    1. Reviewer #1 (Public review):

      [Editors' note: Overall, the reviewing editor and reviewers agreed that authors rigorously addressed reviewers' major scientific concerns.]

      Hanako and colleagues demonstrated that glycolipid MPIase is essential for the TAT system, and they successfully reconstituted the TAT system in vitro for the first time. This will facilitate the understanding of the mechanism of the TAT system.

      Comments on revised version from Reviewer 1 and the Reviewing Editor:

      In Reviewer 1's points 1 and 2 regarding statistical significance of immunoblotting data (in recommendation to authors), authors stated that they repeated the experiments three times in the rebuttal letter but not in the figure legends. We recommend authors to add a statement such as "errors denote +-SD (N = 3)" in the final version, which will make the data more solid and reliable.

    1. Reviewer #1 (Public review):

      Summary:

      Polymyxins are the last line of drugs to treat gram-negative bacteria induced multi-drug resistance, however, they cause nephrotoxicity in 60% of patients. In this work, authors have studied the structure-interaction relationship (SIR) of polymyxins with hPepT2 using computational and experimental methods. Moreover, it is observed that the electrostatic interactions coordinate the hPepT2-Polymyxin interactions, hence, an alanine scanning strategy is used to understand the interactions and derive the polymyxin variants.

      Computational methods such as molecular modeling, coarse grained and all atom MD simulations, and interaction studies are performed. While the results are validated in the mouse model which is a great strategy to prove the hypothesis.

      Strengths:

      A clear understanding on the hPepT2-Polymyxin interactions and role of electrostatic interactions is one of the very important strengths of the paper. In addition, this work proposes a great pipeline for using computational approaches and experimental validation methods to guide the development of newer antibiotics.

      Overall, the study proposes novel polymyxin analogues with reduced or no nephrotoxicity, thereby providing a promising foundation for the rational development of safer lipopeptide antibiotics.

      Comment on revised manuscript:

      I appreciate the effort by Authors to address my comments. The manuscript now contains details of ACE inhibitors in the introduction. In addition, method section is updated for better reproducibility of the MD simulation and structure modeling methods. I congratulate authors for reporting a wonderful scientific study. I don't have any further recommendations. Thank you!

    1. Reviewer #1 (Public review):

      Summary:

      How the regenerative capacity of the heart varies among different species has been a long-standing question. Within teleosts, zebrafish can regenerate their hearts, while medaka and cavefish cannot. The authors examined heart regeneration in two livebearers, platyfish and swordtails. Interestingly, they found that these two fish species lack the compact myocardium layer that contains coronary vessels. Furthermore, these fish form a "pseudoaneurysm" after cryoinjury without initial deposition of fibrotic tissues. However, delayed leukocyte infiltration and prolonged inflammation lead to permanent scar tissue in the injured heart. Although their cardiomyocytes can also proliferate, platyfish and swordtails can only regenerate partially. The authors argue that the restorative mechanism of platyfish and swordtails likely reflects "evolutionary innovations in the ventricle type and the immune system".

      Strengths:

      The authors took advantage of the annotated genome of platyfish to perform transcriptomic analyses. The histological analyses and immunostaining are beautifully done.

      Comments on revised version:

      The authors have addressed all my previous concerns. I don't have further questions.

    1. Reviewer #1 (Public review):

      The neuronal microtubule cytoskeleton is essential for long-range transport in axons and dendrites. Axon-specific plus-end-out microtubule organization versus dendrite-specific plus-end-in organization (in invertebrates) enables selective transport into each neurite, establishing neuronal polarity. Dendritic microtubule organization is also thought to be important for dendrite pruning in Drosophila during metamorphosis. However, the precise mechanisms that organize microtubules in neurons remain incompletely understood.

      In this manuscript, the authors show that the spectraplakin Shot is important for developmental dendrite pruning. Shot mutants display dendritic microtubule polarity defects, which-based on the authors' rescue experiments and prior work-likely underlie the pruning defects. Since Shot is a known actin-microtubule crosslinker, the authors also examine the role of actin and find that it, too, is required for dendrite pruning.

      Notably, Shot localizes transiently to dendrite tips during the 1st instar larval stage, a time when microtubule defects are already detectable. Given that Shot interacts with both plus- and minus-end microtubule-binding proteins, and that overexpression of Shot's microtubule-binding domain alone is sufficient to rescue the mutant phenotype, the authors propose that Shot's principal function is to stabilize microtubules at dendrite tips during the 1st instar stage (and possibly along the entire dendritic shaft at later stages).

      In parallel, the authors investigate microtubule nucleation and find that, specifically at the 1st instar stage, microtubules can nucleate from RAB11-positive vesicles carrying γ-tubulin. Interestingly, this nucleation occurs only toward the cell body, suggesting additional layers of control. The authors do not observe nucleation from the dendrite tip, as previously reported in C. elegans. While this discrepancy could be technical, it more likely reflects a genuine mechanistic difference between the two systems.

      Strengths:

      Overall, this work was technically well performed, using advanced genetics and imaging. The authors convincingly show that Shot plays an important role in microtubule stabilization, and that its interaction with actin is likely important for localizing the protein.

      The transient localization of Shot to dendrite tips and microtubule nucleation from RAB11 endosomes during the 1st instar stage is intriguing. This suggests that specific mechanisms may act during early neuronal development to establish microtubule organization, while different mechanisms maintain this organization later in development.

      Weaknesses:

      The link between nucleation (rab11/gamma-tubulin) and stabilization (Shot/Actin/EB/Patronin) at this stage is unclear. The authors are correct to discuss that we may be missing early events, e.g. maybe we miss early microtubule nucleation from the tip. Or alternatively could MTs frow with their minus-ends into the dendrite (see Feng et al)?

      Distal enrichment of shot at 1st instar is a critical piece of data (it appears in the title). However, this was seen upon overexpression of GFP::Shot. However, does this correctly reflect the endogenous situation? Also, because its binding partner, EB1, can only be seen enriched to dendrite tips upon shot overexpression but not in controls.

    1. 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.

    1. Reviewer #1 (Public review):

      Summary:

      This article taps into the very interesting phylogeographic situation of two sympatric species of clingfishes sharing the same distribution and environment around Crete and the island of Cythera. Basically, it shows that the population structures of these fishes are influenced in a parallel manner by seascape, low dispersal, and potentially drift or selection despite a different phylogeographic history. This parallelism is looked after in a detailed manner at the genome level. I am very enthusiastic about this extremely well-constructed and very cleverly designed study of this natural "common garden" evolutionary duplicate situation, something sufficiently rare to be underlined.

      The authors have produced complete genomes for the two species and their five population samples, from which they are able to conduct up-to-date data analyses. The text is clearly written, without too much jargon, and the options chosen for the various analyses and bioinformatic pipelines are sufficiently detailed so it is rather easy to follow what they've precisely done, something which is alas not that frequent in comparable studies.

      Strengths:

      The structural part of their study is really very convincing, with results showing that despite very small differences, the population structures of the two species conform quite well with what could be inferred from larval dispersal modeled according to passive particle drift. The parallelism is striking, despite minute differences, and despite quite different population sizes for the two species.

      Weaknesses:

      After that, the authors tried to identify a set of outlier loci whose distribution doesn't conform to the main population differentiation. This search for outliers is made according to classical methods based on Fst or its derivates, like the program PBS which compares the Fst values in trios on sliding windows along the genome. The study is well conducted, namely taking into account false positives and false discovery rates in a conservative manner.

      Assuming that some environmental variables differ between the five locations where they have samples, the authors hypothesized from this that similar environmental pressures give similar patterns, potentially affecting pro parte similar places in the genome of the two species. However, there is a blind spot in their analysis inasmuch as it seems that recombination and linkage are not taken into account. It is well known that recombination rates are very variable along the chromosomes, going from recombination hot spots to stretches of very low levels of crossovers. It is well known as well that a variety of phenomena like background, purifying, and sweep selection are quite sensitive to the recombination rates, this having important bearings on local variation of a series of variables like Fst, D, Pi... . Hence, their conclusions about a direct action of environmental pressures may largely be challenged, especially when it is to look for functionality of tightly linked genes, and should be taken as the last hypothesis to be retained when the others can be ruled out.

      There are probably sufficient levels of conservation and synteny in teleost fish and a sufficient number of species where recombination maps exist so that the authors can reconstruct a map for their species, at least partially, permitting to use methods explicitly taking recombination rate variation along the genome into consideration (like for instance DILS: Demographic inferences with linked selection 2021 Mol Ecol Res) to challenge their adaptationist conclusions, all the more given the fact that the question of the eventual nature of differential environmental pressures cannot be addressed with extant data.

      (3) Moreover, there is now a considerable amount of literature which deals with what is coined "islands of differentiation" or "islands of speciation" or "barriers loci". These genomic segments coincide very often with low recombination regions, and some of them are quite often shared in multiple pairs of closely related species. It seems that their experimental set up (several closely related species) is ideal to easily derive the landscape of genomic architecture of divergence in the genus, this permitting to see where the conserved islands of differentiation stand, how much they are conserved or not in the different species, and how this matches or not with their PBS peaks, and by the way, allowing a more direct comparison with similar landscapes published in other species. They have everything at hand, and this will be a very valuable addition to this article that could hence become a more fascinating paper.

    1. Reviewer #1 (Public review):

      Summary:

      In this paper, the authors combine a well-controlled decision-making task with a secondary probe task in order to understand how covert attention is shaped and how it influences the ongoing decision process. The authors report that the likelihood of overtly attending an alternative is shaped both by its decision relevance and its decision value. Further, covert attentional allocation comes at the expense of overt attentional allocation and attenuates the impact that covert gazes have on choice. Importantly, covert attentional allocation is dissociable from pre-saccadic activity. This paper sheds new light on the role of covert attention in decision-making. From an experimental aspect, the authors make excellent use of behavioural and process-tracing methods, presenting an exemplary paradigm that could be valuable to researchers working in related fields.

      Strengths:

      (1) The paper utilises a very rich and clever experimental design, which allows for probing covert attention at the level of a single trial. Extending the paradigm to ternary choices was an excellent addition. The decision task is also well-controlled. Overall, the results are very clearly presented, and the paper is very well written.

      (2) The paper addresses important yet overlooked questions in decision neuroscience: what influences covert attention during decision-making and what is the functional relevance of covert attentional shifts. It is impressive that the authors are able to tackle these questions using behavioural and eye-tracking data alone.

      (3) The authors thoroughly check that the secondary probe task can indeed be used as a proxy for covert attention. Checking that covert attentional allocation is dissociable from pre-saccadic activity was an excellent control.

      Weaknesses:

      (1) It is not clear why the decision task is described as "value-guided" instead of "perceptual". Participants receive momentary reward on the basis of their overall accuracy, but this is common practice in perceptual tasks. A value-based analogue of this task would provide trial-by-trial reward as a function of the perceptual magnitude (decision value) of the chosen stimulus. On a related note, the secondary task was not incentivised. The authors should further justify this choice.

      (2) The authors do a great job in describing the determinants of covert attention. However, the relevant analyses are rather "phenomenological". It would be useful to try and dig further into the data in order to understand at a deeper, causal level these determinants. I suggest doing so by utilising in full the rich behavioural and overt attention data this paradigm offers. Specifically, the authors show that the higher the value of an alternative, the higher the likelihood this alternative is covertly attended. Decision values, however, could impact aspects of saccadic behaviour that directly influence covert attentional allocation (saccadic speed, dwell times, locus of gaze). At a more global level, decision value and/ or value difference could affect sampling behaviour (frequency of switching) or decision times, which can manifest in probe accuracy. Overall: a) overt sampling behaviour is at present reduced to the presence of saccades; but saccadic behaviour could be decomposed into richer metrics, b) although the task is "free-response", decision times are not analysed. Metrics based on a) and b) could be tested as mediating factors, enabling the authors to better understand the causal determinants of covert attention.

      (3) The authors claim that covert attention attenuates: a) the impact of the last fixation on choice, b) the "time advantage" of the alternative that was overtly attended for longer. To further qualify these claims as functional/causal, further analyses are required. A few suggestions follow below. On trials where the "unattended" probe letter was successfully reported, the last fixation may exhibit different characteristics, which could explain away its reduced impact. For example, it may differ in duration, or it might correspond to a "switching" (rather than "staying" on the same alternative) saccade. These potential covariates need to be further examined. Additionally, correctly reporting unattended probes could come at the expense of decision accuracy due to dual task demands. If that is the case, then the reported attenuation of the impact of the last fixation could just be due to noisier responses. Similar points can be raised about the "time advantage", especially given that decision times do not feature in any of the analyses. More difficult decisions may lead to higher probe accuracy but also to prolonged decision times. The authors quantify the "time advantage" using cumulative fixation time, but perhaps relative metrics (e.g., relative fixation time or cumulative fixation time normalised by decision time) are better suited for this analysis.

    1. Reviewer #1 (Public review):

      Summary:

      The authors introduce ordinal EPR (Dsym) as a novel metric for characterizing tFUS-evoked calcium responses. The concept is interesting and could offer an innovative way of looking at neural responses to neuromodulation more broadly. Their main result, that EPR carries information beyond mean GCaMP amplitude, is compelling, but the manuscript would be strengthened by testing whether it holds against other conventional GCaMP metrics beyond mean amplitude (e.g. decay time). More importantly, the EPR metric requires further validation before its central claim, that it reflects genuine dynamical reorganization of the underlying circuit rather than artifacts of the measurement pipeline (e.g. GCaMP indicator kinetics), can be accepted. A rigorous surrogate/synthetic signal validation would be a very valuable, if not essential, addition to this paper.

      Strengths:

      This manuscript frames tFUS-evoked activity in a way that is uncommon in the field. Moving beyond amplitude-based readouts to ask how sonication reshapes the temporal organization of neural activity is a novel contribution to the ultrasound neuromodulation literature. The finding that EPR shows a distinct dose-response profile from calcium amplitude and retains dose-related structure after controlling for amplitude, is a promising demonstration that this framework can extract information not visible to conventional measures.

      Methods are very detailed and well explained for reproducibility purposes.

      Weaknesses:

      Major weaknesses:

      EPR may carry information beyond mean GCaMP amplitude- but is it carrying information beyond other elements of the GCaMP signal? For the on-target recovery window, the calcium signal has not yet returned to baseline (original data traces, Fig. 2C, Fig. 4A), so the trace still contains a residual decay transient at the time Dsym is computed. This decay rate reflects neuronal activity returning to baseline and will be dependent on things such as calcium indicator kinetics. Would a change in Dsym always accompany this kind of decay, regardless of whether this has anything to do with endogenous dynamics, irreversibility etc.? Would any gradual return to baseline/decay of this kind produce elevated Dsym on its own, independent of underlying stochastic fluctuations/endogenous dynamics? Is it not expected that a system that is not at steady state shows entropy production? Perhaps the decay rate is simply different by dose, which explains the findings? Could this be tested i.e. with synthetic data or by removing the decay? The fact that a change in EPR is measured when there is no significant GCaMP change indicates that the measure is not purely dominated by decay kinetics but it is not clear whether decay kinetics etc. could be confounding this result.

      GCaMP's rise and decay kinetics are asymmetric (fast rise, slow decay). Since Dsym is a measure of asymmetry between forward and time-reversed ordinal statistics, could this kinetic asymmetry alone have any impact on "irreversibility", independent of underlying neural dynamics? Could this be tested with synthetic data? The authors note that the GCaMP signal is filtered through an indicator with slow kinetics but don't mention the asymmetry.

      When different stimulation periods are used, what impact if any, does this have on computation of the EPR metric?

      What impact does having a noisier/lower SNR calcium signal have on the EPR metric, if any?

      Minor weaknesses:

      The major advantage of TUS as a non-invasive brain stimulation technique is its capacity for spatially focused deep brain stimulation. However, it carries a significant auditory confound, which leads to activation of widespread (not spatially restricted) neuronal networks (Kop et al., 2024; Sato et al., 2018). The data used in this paper does not adequately control for this confound (i.e. deafened animals (Guo et al., 2023; Sato et al., 2018). Whilst this is not the responsibility of the authors of this manuscript, it should be mentioned in the discussion that any of the tFUS-calcium evoked responses could be due to indirect auditory stimulation rather than a direct pressure-mediated effect. The authors may just be measuring EPR in response to the auditory confound, which does not undermine the overall impact of this paper (as it is more focused on an approach to looking at this kind of data), but should be mentioned. I do think that presence of the auditory confound could impact interpretability of the results in the manuscript. Could the authors comment on this? Could auditory mediated arousal or state shift (perhaps activating brain regions not captured by the fiber) explain any of the presented EPR results or affect interpretation?

      Guo, H., Salahshoor, H., Wu, D., Yoo, S., Sato, T., Tsao, D. Y., & Shapiro, M. G. (2023). Effects of focused ultrasound in a "clean" mouse model of ultrasonic neuromodulation. iScience, 26(12). https://doi.org/10.1016/j.isci.2023.108372<br /> Kop, B. R., Shamli Oghli, Y., Grippe, T. C., Nandi, T., Lefkes, J., Meijer, S. W., Farboud, S., Engels, M., Hamani, M., Null, M., Radetz, A., Hassan, U., Darmani, G., Chetverikov, A., den Ouden, H. E., Bergmann, T. O., Chen, R., & Verhagen, L. (2024). Auditory confounds can drive online effects of transcranial ultrasonic stimulation in humans. eLife, 12, RP88762. https://doi.org/10.7554/eLife.88762<br /> Sato, T., Shapiro, M. G., & Tsao, D. Y. (2018). Ultrasonic Neuromodulation Causes Widespread Cortical Activation via an Indirect Auditory Mechanism. Neuron, 98(5), 1031-1041.e5. https://doi.org/10.1016/j.neuron.2018.05.009

    1. Reviewer #1 (Public review):

      Summary:

      The manuscript describes a novel mechanism underlying the formation of secondary lesions following treatment-induced injury. Comprehensive analyses were conducted, including bioinformatics, cell culture, and xenograft models, to investigate the role of IL1b/IRAK4 in ovarian cancer. A novel IRAK4 antagonist was designed and tested in these models, demonstrating its effectiveness in reducing metastatic seeding and tumor growth at injury sites.

      Strengths:

      Mechanistic role of IRAK4 and its small molecule antagonist was demonstrated using several murine and human ovarian cancer cell lines.

      Properties of the novel investigational compound UR241-2 were comprehensively assessed.

      The data show the effectiveness of UR241-2 in reducing metastatic seeding after injury.

      Weaknesses:

      An expanded description of the histological types of ovarian cancer used to generate survival curves and demonstration of the expression of total IRAK4 would strengthen the manuscript.

      If the information is available, it could be useful to indicate the percentages of different ovarian cancer histotypes analyzed in Figure 1.

      Providing panels demonstrating the expression of total IRAK4 in Figure 4 would be informative.

    1. 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.

    1. Reviewer #1 (Public review):

      Summary:

      This study quantifies the ability of the four isoforms of the calcium-release calcium-activated (CRAC) channel Orai to mediate calcium entry and transcriptional responses. By genetically invalidating each isoform and by separately re-expressing them in Orai-deficient human embryonic kidney cells, the authors show that the rates of calcium entry across the four native Orai calcium channel isoforms (Orai1α/β, Orai2, Orai3) correlate with the degree of NFAT activation. They further show that the two alternatively translated isoforms Orai1α and Orai1β are interchangeable, as their expression in Orai1-deficient primary mouse T cells induces identical cytokine responses and transcriptional programmes, and that individuals bearing frameshift mutations causing a loss of the Orai1α isoform do not exhibit immune, muscular, or dermatologic features and have preserved T cells' Ca2+ and transcriptional responses.

      Strengths:

      The data are of high quality, relying on clean cell line and mouse knockout models to link calcium entry rates directly to NFAT activation, and human data from homozygous and heterozygous frameshift mutation carriers confirm that Orai1α and Orai1β are functionally redundant in vivo.

      Weaknesses:

      An acknowledged limitation is that some conclusions depend on transient overexpression experiments. The authors should explicitly address whether Orai1α could possess non-redundant functions under unique physiological environments not captured by these assays.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. Patient 1 is 44 years old and presented in 1991 aged 23 with deteriorating central vision and visual acuity (VA) of 6/36 in the right eye and 6/60 in the left. Fundus photography in 1994 identified bilateral numerous yellowish-white flecks at the posterior pole (Fig. 1). In 2003, her VA was 6/60 in each eye, with bilateral macular atrophy surrounded by flecks (Fig. 1). Autofluorescence (AF) imaging in 2005 detected a localized low signal at the macula with numerous foci of abnormal signal (Fig. 1). By 2008, the macular atrophy had enlarged and flecks were less apparent.

      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.

    1. 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.

    1. 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.

    1. 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.

    1. 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).

    1. 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?

    1. 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.

    1. 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.\

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. Case report: Disease phenotype associated with simultaneous biallelic mutations in ABCA4 and USH2A due to uniparental disomy of chromosome 1

      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.

    1. 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.

    1. 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?

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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?

    1. 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.

    1. 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.)

    1. 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.

    1. 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.

    1. 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?

    1. 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.

    1. 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.

    1. 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?

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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?

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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?

    1. 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.

    1. 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.

    1. 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.

    1. 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.

    1. 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

    1. 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.

    1. 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.

    1. 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.

    1. Reviewer #1 (Public review):

      Summary:

      The authors investigate the role of different specific dopaminergic neurons in the mushroom body of Drosophila larvae for learning and innate behavior. All the tested neurons are thought to be involved in punishment learning. The authors discover that artificial activation of single DANs in training leads to safety learning, but not punishment learning. Furthermore, activation of single DANs can lead to changes in locomotion behavior, which can affect light preference. The authors provide a deeper understanding of the functional diversity of single dopamine neurons; however, it is unclear how translatable these findings are to learning experiments with real punishment stimuli.

      The authors provide a detailed behavioral analysis of locomotion in response to activation of various dopamine neurons. This analysis allows them to exclude that the locomotion defects affect memory recall behavior.

      Strengths:

      The authors disentangle which kind of memories are formed with the activation of different dopamine neurons - safety learning and/or punishment learning. They further investigate whether the US is required in the test for recall. They do indeed find differences, and the results will be of interest to the learning and memory community.

      Interestingly, optogenetic activation of a single DAN during training leads to safety memory, but not punishment memory. Furthermore, DAN activation also affects innate locomotion, and the authors show that optogenetic activation of different DANs affects locomotion differently.

      Weaknesses:

      All experiments in the manuscript use optogenetic activation of DANs, thus it is not clear what kind of memories are formed. Several stimuli can be used as punishment, such as electric shock, salt, bitter, and light - it is not clear what kind of memory the authors investigate here. The findings could be discussed in the context of what DANs respond to. Furthermore, studies in adults and larvae showed that most DANs can code for both valences - etc., aversive DANs can be activated by punishment, and inhibited by reward. Thus, safety learning might be a result of a decrease in activity in DANs during odor presentation. The authors also do not discuss possible feedback loops from MBONs to DANs across compartments. Could such connections allow for safety learning in larvae?

      The authors show that artificial activation with different light intensities can form different memories and that increasing the light intensity sometimes leads to no memories. Also, using different optogenetic tools reveals different results. This again raises the question of how applicable the results will be for learning with real stimuli. Is there a natural stimulus that only induces safety learning, but no punishment learning? The authors discuss these limitations.

    1. Reviewer #1 (Public review):

      Summary:

      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, they 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.<br /> 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.

      Strengths:

      The biochemical analysis seems solid.

      Weaknesses:

      - A major question that remains, is why the mutations have so much more detrimental effect in MutL (100-fold lower kcat/KM) than they do in GyrB (3-fold lower). Can the authors explain this? Doesn't this argue against the proposed catalytic conservation?

      The authors need to discuss this issue explicitly to make it clear that conservation of the mechanism is not complete and that other interpretations are possible.

      - The structure figures all have omit maps for just the AMPPnP and the water, whereas the density for the the acidic residues and their mutants are not shown.

      This has been addressed.

      There are some issues with figure S2B and S5.

    1. Reviewer #1 (Public review):

      Summary:

      The authors conducted a carefully constructed experiment to test reorganization in the auditory cortex in deafness in response to task (spatial vs. temporal working memory) and modality (visual vs. somatosensory). They found a complex pattern of results, which included changes to univariate response strength in deafness that differed between the primary and association auditory cortex. HG showed a preference for the somatosensory working memory task, whereas STG/S responded more in both modalities for the temporal task. They further showed multivariate similarity of their results to models representing both task and modality in both groups, which were increased in deafness. Curiously, the task effect was for a sensorily-bound model, which shows mid-level representation, and not high-level task ("metamodal") code.

      Strengths:

      I appreciated the matched design, rigorous analysis, and careful interpretation of the nuanced results.

      Weaknesses:

      Only minor weaknesses: behavior and residual hearing can be better controlled.

    1. Reviewer #1 (Public review):

      Summary:

      The present report describes an investigation into the use of machine learning techniques to improve cross-racial/ethnic performance of brain models of cognitive function. The authors tested several approaches to boost prediction of NIH cognitive toolbox scores using brain imaging data (function, structure) for minoritized (Black) participants in the ABCD Study sample compared to white (majority) participants. Structural (e.g., volume) measures showed the greatest performance gap, and a balanced weighting method showed the greatest performance gain across features. The authors conclude that supervised domain adaptive methods can improve models for cognitive prediction and mitigate cross-racial/ethnic performance disparities.

      Strengths:

      This investigation makes some headway into issues by identifying computational methods that may help to improve some models for limited outcome variables (i.e., general cognitive performance). Addressing racial/ethnic disparities in brain imaging research has significant implications for generalizability of findings and for the practical utility of imaging findings in the wider population. A comparative approach to evaluate the improvements in a "prediction gap" across various methods could have benefits for neuroimaging beyond racial/ethnic disparities. The use of the ABCD Study, given its deep phenotyping of individuals, is also a benefit.

      Weaknesses:

      Despite its strengths, there are several large conceptual and related methodological issues that impact its conclusions and the overall utility of the approach. The sample selection approach limits insight into likely drivers of the performance gap (e.g., socioenvironmental disparities known to exist between groups and associated with neurodevelopment), and in so doing ignores a critical component of understanding racial brain differences, particularly in relation to cognitive functions. Further, while the relative gaps in performance of a single cognitive score across features are well described, the actual performance (and therefore relative benefit to these techniques) is unclear. Specific examples include the following.

      (1) The overarching conceptual issue with the manuscript is a lack of engagement with a substantial and growing evidence base on the drivers of racial disparities in brain imaging which impact model performance. Racial/ethnic groups in the US (and other regions of the world) are not equivalent in terms of developmental environments that shape brain function and structure (see Harnett et al., 2023, Neuropsychopharmacology; Ricard et al., 2023, Nature Neuroscience; Cardenas-Iniguez & Gonzalez, 2024, Nature Neuroscience for some overview here). The socioenvironmental disparities inherent to race in the US further shape cognitive development and brain associations with cognitive performance (e.g., Marek et al., 2025, Science). The framing of the manuscript focuses almost exclusively on broad sampling issues, and in doing so treats racial/ethnic variability as if it reflects statistical abnormality rather than a critical component of understanding human brain development. This lack of contextualizing racial disparities significantly impacts the overall utility of the proposed approach and the conclusions of the manuscript.

      (2) In relation to the above, another conceptual issue in this approach of using a majority to inform minority brain associations with cognitive variables is an assumption that minority brain patterns should match the majority, rather than developmental stressors inducing alternative brain-weighting to predict outcomes. This framework does not assess this possibility and may in fact obscure such an outcome, limiting our inferences into neurodevelopment.

      (3) Another conceptual/methodological issue here is the use of "matched groups" for analysis. The specifics of matching are fairly vague, but given the description one would assume the w/B groups are matched on a number of behavioral/socioenvironmental variables, which is a significant issue for interpretability and applicability. As noted, w/B groups in the US (and the ABCD Study) differ substantially across variables; matching has the likely consequence of creating a highly non-generalizable sample, particularly when the minority group is restricted to N = 10.

    1. Reviewer #1 (Public review):

      Summary:

      This paper leverages 7T fMRI data from the Natural Scenes Dataset to investigate whether retinotopic coding the position-selective organization of visual responses structures spontaneous resting-state interactions between the Default Network (DN) and the Dorsal Attention Network (dATN). Using individualized network parcellations and population receptive field (pRF) modeling, the authors show that DN voxels can be split into two subpopulations based on their response to visual stimulation: those with position-specific positive BOLD responses (+pRFs) and those with position-specific negative BOLD responses (-pRFs). Critically, these subpopulations relate differently to the dATN during rest: -pRFs are anticorrelated with the dATN, +pRFs are positively correlated, and non-retinotopic DN voxels show no coupling. The anticorrelation (and positive correlation) is enhanced when DN and dATN voxels share visual field preferences. An event-triggered analysis suggests that retinotopic coding shapes both "top-down" (DN-initiated) and "bottom-up" (dATN-initiated) spontaneous activity transients, supporting the claim that the retinotopic scaffold is intrinsic to the DN. These findings challenge the prevailing view of global DN-dATN antagonism and suggest retinotopic coding as an organizing principle for cross-network communication.

      Strengths:

      The central finding that what looks like network-level independence between DN and dATN decomposes into structured, bivalent interactions organized by voxel-level visual field preferences is a compelling demonstration that macro-scale network descriptions can hide meaningful substructure. The logic of the analysis is clean: pRF properties are estimated from retinotopic mapping data and then used to predict resting-state coupling in completely independent scanning sessions. This cross-session, cross-modality design rules out many circularity concerns.

      The use of individualized multi-session hierarchical Bayesian parcellation (Kong et al.) to define DN and dATN boundaries within each subject is the right methodological choice for this question. Network boundaries in posterior cortex, where DN and dATN interdigitate most closely, vary considerably across individuals, and group-average approaches would introduce exactly the kind of misassignment that would most confound the result.

      The matched-vs-random pRF analysis is well-controlled. The authors demonstrate that cortical distance between matched and randomly matched dATN pRFs does not differ, effectively ruling out spatial proximity on the cortical surface as a confound. tSNR controls further show that signal quality differences do not drive the effect.

      The event-triggered analysis (Figure 3) is creative and adds genuine value. Showing that retinotopically-specific coupling persists during DN-initiated activity transients not only dATN-initiated ones is the key piece of evidence for the claim that the code is intrinsic to the DN rather than passively inherited through bottom-up visual drive.

      The result is observed consistently across all individual participants, which provides strong evidence for the robustness of the qualitative pattern despite the small sample size inherent to densely sampled designs.

      Comments on revised version:

      I'm content with the additional analyses and alterations to the writing that the authors have performed. I'm convinced that this work will spawn a very productive thread in the literature.

    1. Reviewer #1 (Public review):

      Summary:

      Forbes et al. developed an integrated approach to identify cis-regulatory elements (CREs) in the large (3.6 Gbp) genome of the crustacean Parhyale hawaiensis, addressing the challenge of pinpointing these regions among large regions of non-coding sequences. They combined ATAC-seq chromatin accessibility profiling (both bulk and single-nucleus) across embryonic and adult tissues with low-coverage genome sequencing of three congeneric species (P. aquilina, P. darvishi, P. plumicornis). Without assembling congener genomes, they mapped reads with low stringency to the P. hawaiensis reference, identifying about 55k conserved islands that overlap ATAC peaks more than expected by chance. This dual filter was used to select CRE candidates for transgenic reporter validation, yielding 6 functional elements (out of 11 tested) driving ubiquitous, neuronal, or muscle-specific expression, a major advance for non-model systems with large genomes.

      Strengths:

      Forbes et al. generated high-quality ATAC data across multiple scales. Using bulk ATAC-seq (from whole embryos, developing and adult legs) they identified tens of thousands of open chromatin peaks across the assembled P. hawaiensis large genome. Moreover, using single-nucleus ATAC-seq from adult legs, they could resolve differentially accessible chromatin profiles across more than 15 cell types previously identified by scRNA-seq, enabling cell-type-specific candidate selection.

      Furthermore, their innovative low-coverage comparative genomics method mapped 0.46-6.4% of congener reads to P. hawaiensis without genome assembly, revealing hundreds of thousands of conserved non-coding islands, including about 55k showing conservation in all four species, far exceeding random expectation.

      Using the developed approach, the authors could validate 6 (out of 11 candidates) reporter constructs, driving robust ubiquitous and tissue-specific expression, succeeding where prior promoter-only screening failed and providing immediately useful genetic tools for the Parhyale community.

      Weaknesses:

      The primary limitation is that functional CRE testing was performed only in P. hawaiensis. While the conservation maps provide a valuable resource for comparative analyses, functional validation in congener species was not performed, so the extent to which the identified CREs or the prioritization strategy can be functionally generalized across related species remains to be established.

      The approach did not successfully identify developmental CREs among the candidates tested. None of the candidates selected using the combined ATAC-seq and conservation filtering drove reporter expression matching the expected endogenous patterns. The authors appropriately discuss possible technical and biological explanations.

      Overall Assessment:

      Forbes et al. fully succeed with their integrated approach to (1) generate an ATAC-seq atlas plus functional CRE discovery and (2) innovative low-coverage sequencing for conservation mapping in the large 3.6 Gbp genome of Parhyale hawaiensis. Their combination of ATAC-seq chromatin accessibility profiling (bulk and single-nucleus) across embryonic and adult tissues with low-coverage genome sequencing of three congeneric species (P. aquilina, P. darvishi, P. plumicornis), without congener genome assembly, drastically shrank the CRE search space. Using this approach, the authors could validate six out of 11 candidate transgenic reporters (ubiquitous, neuronal, and muscle-specific) where prior promoter-only screening failed.

      The low-coverage mapping innovation cuts cost and labour while snATAC-seq provides cell-type resolution, making these resources valuable for building new genetic and imaging tools in Parhyale.

      This compelling method also has the potential to enable labs with limited resources to identify and characterize regulatory elements in more non-model organisms, advancing our understanding of their evolution while establishing a scalable pipeline for large-genome systems.

      Comments on revised version.

      The authors have adequately addressed all my previous comments. I have no further specific suggestions or requests.

    1. Reviewer #1 (Public review):

      Summary:

      The article is testing the relative advantages of plant lineages with differing ploidy and admixture across environmental gradients. The results show that intraspecific variation in ploidy and admixture between lineages impacts plant traits that may enable persistence and range expansion.

      Strengths:

      Suitable marker panel size and strong results that include attempts to analyse mixed ploidy level data which is a challenge.

      Weaknesses:

      The sample sizes of the common garden experiments are very low making it difficult to draw robust conclusions.

    1. Reviewer #1 (Public review):

      Summary:

      The authors used single-nucleus RNA sequencing (snRNA-seq) to investigate accelerated tooth replacement following tooth plucking in cichlid fish. They analyzed four stages of regeneration using elegant and well-designed approaches to characterize cellular trajectories and interactions within the dental epithelium and mesenchyme during the accelerated replacement process. Their analyses identified cell type-specific gene expression profiles and intercellular signaling interactions associated with whole-tooth regeneration.

      Strengths:

      This is a highly interesting and thoughtfully executed study that provides compelling and convincing insights into the mechanisms underlying accelerated tooth regeneration.

      Comments on revised version.

      I noted in my initial review that "the manuscript currently lacks experimental validation of the single-nucleus RNA-seq data." In response, the authors have added a statement indicating that their cell-type annotations and pathway interpretations are supported by extensive prior experimental work in the cichlid tooth model, including histology, in situ hybridization, immunohistochemistry, and pharmacological perturbation of major developmental pathways. They have also acknowledged this limitation in the Study Limitations and Future Directions section, stating that direct experimental validation of the single-nucleus RNA-seq findings will be the focus of future studies.

      The authors have carefully addressed my comments, particularly the Major Points (2), (3), and (4), as well as all of the Minor Points. I appreciate their efforts to further characterize the mesenchymal landscape surrounding the putative successional lamina and to provide additional evidence supporting the presence of a specialized stromal microenvironment associated with tooth regeneration. Overall, the revisions have substantially strengthened the manuscript.

    1. Reviewer #3 (Public review):

      Summary:

      In this manuscript, Barré et al utilize the Gp1ba-Cre transgenic mouse model to build upon previous findings in a Pf4-Cre system to investigate the effects of individual and combined Shp1 and Shp2 deletion in megakaryocytes and platelets. They report decreased megakaryocyte maturation, macrothrombocytopenia, and increased blood loss primarily in association with the Shp1/Shp2 double-knockout condition. The authors further show that this phenotype appears to be driven primarily by Shp2 and implicate dysregulation of Tpo signaling and downstream Ras/MAPK pathways, including ERK1/2. They propose that Shp1 may be functioning through a distinct pathway that has yet to be identified, opening up areas for future study.

      Strengths:

      Overall, the experiments combine in vitro, in vivo, and ex vivo approaches and appear to have been carefully designed and carried out, with multiple technical and biological replicates where relevant. The authors make a compelling argument for using the Gp1ba-Cre as opposed to the Pf4-Cre system and demonstrate both the dose- and stage-dependent effects of Shp1 and Shp2 on megakaryopoiesis and thrombopoiesis. They find that Shp1 and Shp2 are required in late-stage megakaryocyte maturation and that even low levels of expression compared to baseline are likely sufficient to yield generally normal megakaryocytes. Their findings also lead to specific future directions, such as the mechanism by which Shp1 regulates megakaryopoiesis and thrombopoiesis that is distinct from Tpo-mediated signaling. Figure 8 is particularly effective in summarizing the different models and pathways presented.

      Weaknesses:

      The effects of Shp1 and Shp2 knockouts are described as "synergistic," but it is not always clear that the effects are synergistic vs. additive, especially as the specific mechanism by which Shp1 functions in megakaryocyte development has yet to be identified. On a more minor point, although a significant part of the introduction focuses on the role of Mpl signaling in human disease, there is ultimately limited reference to Mpl (although there is of course a strong focus on Tpo) and the potential clinical implications of the findings presented here.

    1. Reviewer #1 (Public review):

      Summary:

      This study provides valuable evidence that hilar mossy cells play important roles in maintaining the structural organization of the dentate gyrus and regulating the maturation of adult-born granule cells. The evidence for the structural reorganization and for the accelerated dendritic maturation of adult-born granule cells is convincing: it rests on converging anatomical, viral tract-tracing, retroviral birth-dating, and electrophysiological measurements, with appropriate controls for viral spread, off-target CA3 expression, and axonal degeneration. Support for the study's broader interpretive claim - that the dentate circuit functionally compensates for mossy cell loss - is incomplete. That claim rests on two null results obtained under baseline conditions (home-cage cFos and PTZ seizure metrics) in small cohorts, without behavioral assessment and without a stimulus-driven activity readout, and the manuscript does not engage with published work showing that mossy cells regulate neural stem cell activation and are required for stimulus-evoked neurogenic and behavioral responses.

      Strengths:

      (1) The study is technically rigorous and employs multiple complementary approaches, including selective genetic manipulations, viral tracing, immunohistochemistry, retroviral labeling of adult-born neurons, electrophysiology, and anatomical analyses. The comparison between complete mossy cell ablation and chronic synaptic silencing is particularly powerful, allowing the authors to examine the significant role of mossy cells in structural and functional organization in the dentate gyrus.

      (2) One of the most notable findings is the identification of a previously unrecognized collapse of the inner molecular layer following extensive mossy cell ablation. This observation substantially expands current understanding of dentate gyrus structural plasticity. The demonstration that adult-born granule cells undergo accelerated dendritic maturation after both mossy cell loss and silencing also provides important insight into how mossy cells regulate adult neurogenesis.

      Weaknesses:

      (1) The functional significance of the observed structural remodeling remains incompletely addressed. Mossy cells have been strongly implicated in pattern separation, spatial information, and emotional behavior, yet no behavioral analyses were conducted. Consequently, it remains unclear whether the dramatic anatomical changes observed following mossy cell ablation translate into meaningful behavioral alterations.

      (2) The conclusion that the dentate gyrus exhibits remarkable homeostatic compensation is reasonable but remains indirect. Although cFos expression and PTZ-induced seizure susceptibility are unchanged despite altered E:I balance, the mechanisms responsible for maintaining network stability are not investigated. Additional analyses of inhibitory circuit remodeling or compensatory synaptic adaptations would strengthen this conclusion.

    1. Reviewer #1 (Public review):

      Summary:

      This manuscript addresses how internally generated evaluative signals can arise during self-guided learning in the absence of external reward. Using zebra finch song learning as a model system, the authors propose that tutor-song memorization and vocal performance evaluation are not separate processes, but instead emerge from a shared local circuit that learns to predictively cancel tutor-song-related auditory input. The comparison across several candidate circuit architectures, the quantitative comparison to experimental calcium imaging data, and the decomposition of the learned recurrent connectivity into modes shaping the error landscape are all strong aspects of the work. The final demonstration that the learned error signal can guide a downstream reinforcement learning agent also provides a useful proof of principle.

      Strengths:

      The idea that tutor-song memorization and performance evaluation can emerge from a shared predictive-cancellation circuit is interesting, and the combination of circuit modeling, comparison to experimental data, and error-landscape analysis is compelling.

      Weaknesses:

      (1) A central conclusion of the manuscript is that the E→I→E model best matches experimental data. This establishes model fit, but it does not yet explain why E→I and I→E plasticity are important for tutor-song cancellation and error-signal formation. Does E→I plasticity primarily teach the inhibitory population to represent tutor-song-related excitatory activity? Does I→E plasticity then implement the negative image required to cancel expected excitatory responses? Does the closed E/I loop primarily control gain, shift the minimum of the error landscape, or both? A useful analysis would be to compare models in which only E→I synapses are plastic, only I→E synapses are plastic, both are plastic, or neither is plastic.

      (2) The analysis in Fig. 5 does not yet explain how the identified modes arise from the specific E→I/I→E plasticity mechanism. For example, are the landscape modes mainly produced by E/I gain-control dynamics? Are the memory modes related to an inhibitory negative image of the tutor song? Are these modes localized to particular blocks of the recurrent connectivity, such as E→I or I→E weights, or are they distributed across the full network?

      (3) The manuscript emphasizes the emergence of sparse population error codes. However, in Fig. 6, the downstream actor-critic model uses the population mean excitatory activity as a scalar negative reward. This compresses the high-dimensional sparse population response into a single scalar. If the downstream system only uses the mean response, why is a sparse high-dimensional error code functionally important, beyond matching the observed response distribution? Conversely, if the sparse population pattern contains richer information about the direction or structure of vocal errors, how might downstream reinforcement pathways read out this information?

      The manuscript should clarify whether sparsity is proposed to have a functional role in motor learning, or whether it is primarily a biological feature of the evaluative circuit. This point is particularly important because the broader framing of the paper concerns internal evaluative signals, whereas the final reinforcement learning demonstration uses a scalar reward.

      (4) The actor-critic model in Fig. 6 is useful because it demonstrates that the learned error signal contains enough information to guide motor learning. However, the reinforcement learning module is attached downstream of the auditory circuit and is highly simplified. Therefore, it remains somewhat ambiguous whether Fig. 6 should be interpreted as a circuit model of song learning or as a demonstration of sufficiency. The latter interpretation seems appropriate and valuable, but the manuscript should state this more explicitly. The central contribution appears to be the bootstrapping of an internal evaluative signal, rather than a complete model of sensorimotor song learning. Clarifying this distinction would prevent overinterpretation of the actor-critic results.

    1. Reviewer #1 (Public review):

      Summary:

      Marschall et al. develop a theoretical framework for analyzing multi-task dynamics in nonlinear recurrent neural networks (RNNs). In the RNN model, recurrent connectivity is a linear superposition of multiple non-overlapping low-rank components, each corresponding to a separate "task". Each task is an autonomous dynamical system that does not incorporate external inputs. The "multi-task computation" setting examines whether multiple tasks (dynamical systems) can operate concurrently or how a network can switch between tasks.

      Within this framework, the authors show that when connectivity consists of two low-rank components implementing two tasks (a limit cycle and a bistable attractor), the network exhibits winner-takes-all dynamics, resulting in only one task being active and the other one suppressed. A task consistently dominates this competition when the magnitude of its low-rank connectivity ("task strength") exceeds that of the other task. When one task is dominant and many other tasks with weaker low-rank connectivity are present, increasing the number of tasks destabilizes the dominant-task dynamics, leading to chaotic fluctuations in network activity. Supported by the dynamical mean-field theory analysis, the authors show that as the dominant-task strength increases, the network transitions through three dynamical regimes: chaotic spontaneous activity, chaotic task-selected dynamics, and non-chaotic task-selected dynamics. The theoretical analysis additionally predicts how latent task-related dynamics manifest in single-neuron activity and how the dimensionality of population activity changes across the three dynamical regimes.

      The results are interesting, the analyses and simulations are rigorous, and the text is clear and easy to follow. Overall, this study is a significant and timely contribution to the literature on low-rank RNNs, an influential model class for low-dimensional neural dynamics in computational neuroscience.

      Main comments:

      (1) In this modeling framework, only one dominant task can be selected while all other tasks are suppressed. In contrast, several previous studies constructed RNNs (either through gradient-descent optimization or reservoir computing) that simultaneously generate outputs for multiple tasks across the corresponding task-specific readouts. Of course, what counts as a task is arbitrary, and one could view the dynamics of a reservoir network as implementing a single high-dimensional "task" with multiple readouts. Nevertheless, it would be helpful to explicitly clarify the distinction and similarities between the current modeling framework and networks that simultaneously solve multiple tasks.

      (2) The role of external inputs in task selection appears to be underdeveloped. It is only briefly examined in Fig. S4, with the conclusion that external inputs aligned with the task subspace cannot enable selection of the desired task. However, previous multi-task RNN models (e.g., optimized through gradient descent) are clearly able to switch across many tasks using external inputs. In these models, external inputs modulate RNN activity along specific directions, shaped through gradient descent, to select the relevant task for each input. In contrast, this study only considers inputs aligned with the m-direction (left loading vector in the low-rank connectivity for a task). Such input cannot enhance the corresponding task's activity through recurrent amplification (Fig. S4). Yet, low-rank RNN theory predicts that inputs aligned with the n-direction (task's right loading vector) are selectively amplified by the recurrent dynamics. Why inputs aligned with the n-direction were not examined? More broadly, focusing only on inputs aligned with either m- or n-direction appears too narrow, as trained multi-task RNNs indicate that task selection through external inputs is possible, but may require input directions different from m and n.

      (3) It is unclear what the reason is for the task interference: overlaps between task loading vectors for different tasks or other nonlinear effects? This issue is especially prominent in the analysis of task capacity (Fig. 2D and Fig. 4A). The text states that the loading vectors are independent across tasks, i.e. there is zero expected overlap between loading vectors of different tasks (line 126). For a network of N neurons, a rank-R task requires 2R loading vectors. Under the assumption of independence, the maximum number of tasks is P = N/(2R). Then α=P/N can be at most 1/(2R). In the simulations, it is chosen R=2, such that alpha can be at most 1/4 for the loading vectors to remain independent. However, the range of alpha reaches up to 1 in Fig. 2D and Fig. 4A, suggesting that loading vectors are no longer independent across tasks for larger alpha. Is the linear dependence between loading vectors (i.e. overlap across tasks) the reason for the task-1 component norm to drop sharply around alpha=1/4 in Fig. 2D? More broadly, is it possible to isolate the contribution of overlap in task loading vectors versus other nonlinear effects?

      (4) In the current version of the paper, it is difficult to understand how the analysis based on the dynamical mean-field theory in Methods explains the key observations from the numerical simulations. For example, the mechanism underlying the transition from the spontaneous state to chaotic task-selected state, and to the non-chaotic task-selected state remain opaque. Further, it would be helpful to specify which section in Methods is being referred to at each mention throughout the main text. Finally, Fig. 7 and Eqs. (11-13) clearly state the input sources that drive single unit activity, non-dominant task latent states and dominant task latent state. The decomposition is potentially very informative, but its implications are not discussed in sufficient detail. It would be helpful to provide an intuitive explanation of how contributions of these input sources evolve as connectivity strength of one task increases, and which of them eventually leads to the loss of stability of the previous network state.

      (5) The text states that the results can be easily extended to include task-specific inputs and outputs (lines 117-119). However, such an extension does not seem to be straightforward and requires additional explanations. The dynamical mean-field theory analyses here are stationary and describe the steady-state of network dynamics. In contrast, common input-output tasks typically involve transient dynamics, in which time-dependent external inputs keep changing the RNN flow field, and steady-state is never reached. Under these transient conditions, it is unclear whether the same conclusions apply. For example, if a network is at a low-activity baseline when a task-input begins to drive activity in the corresponding task subspace, it is unclear whether the activity in other task-subspaces would grow sufficiently fast to cause interference, or whether such interference would not be observed. Thus, a more detail analyses are necessary to support the extension of the results to input-driven transient tasks beyond autonomous dynamical systems.

      (6) When task strength is the same for all tasks, what determines which task will win the competition? Is it frozen noise in connectivity such that one task always wins, or do initial conditions determine which task wins, based on which task's activity grows faster?

      (7) Does the theory require the activity of all neurons to operate in the saturating part of nonlinearity? For example, the text states "increased activity reduces the gain factor <Φ'(t)>" (line 169). This statement is only true when Φ'<0. For sigmoid nonlinearity used in the paper, Φ'>0 when firing rate is small. If a substantial fraction of neurons in the network is near the rest state, would the theory still apply? Similarly, this statement does not hold for ReLU nonlinearity, and it is unclear how the theory applies to ReLU networks in Fig. S3. The paper states that the results are not specific to the choice of nonlinearity (lines 176-178). However, the dynamics being studied (bistability and limit cycles) both operate on the saturating part of the nonlinearity. Could the authors clarify the assumptions on the nonlinearity for the theory to apply?

      (8) Is it possible to interpret the results in Fig. 4? What does this dependence on the overlap matrix mean? Is there an intuition for this particular dependence, or is it just an observation without general interpretation?

      (9) The results in Fig. 5E appear underdeveloped and somewhat arbitrary. It is unclear how the dependence of dimensionality on the recording time would change as a function of time spent in a task. If this time is long, then the curve grows slowly and total dimensionality is high. If this time is very short, then the network may not have sufficient time for all task variables to grow sufficiently large to contribute significantly to the total variance. Thus, the grows may be faster and the total variance may saturate at a lower value. Hence, it is unclear whether there will be always a qualitative difference from the spontaneous activity curve. Furthermore, since only one of two curves is measured, what quantitative criteria should be used to determine whether it is consistent with task switching or spontaneous state?

      (10) On line 368: "For sufficiently large number of tasks, the dimensionality associated with sequential task selection can greatly exceed that of the spontaneous state (Fig. 5E inset)" - it seems that Fig. 5E inset shows the opposite that the dimensionality of spontaneous state can saturate at a very high value for large N, exceeding the dimension of task-switching network in the main plot. Although it is hard to say, since the inset has many lines with only two labels and no ticks on axis, so it is unclear what exactly does it show.

      (11) Related to discussion on line 368-370: In a task-switching state, would the switching between tasks also be reflected in behavior? In addition, the time-correlation functions would not be stationary in task-switching state, i.e. they would change over time, whereas they will be stationary in the spontaneous state. Thus, could the two mechanisms be dissociated in experiments using behavior or metrics beyond dimensionality?

      (12) On line 385, could the authors provide more details on how they envision the two potential mechanisms-synaptic plasticity and targeted neuromodulation-to reinforce a task-specific low-rank connectivity pattern? If neuromodulation changes the gain of individual neurons, this modulation corresponds to scaling of connectivity by a diagonal matrix, not strengthening of a specific low-rank component. Short-term facilitation or depression also modulates synaptic strength depending on the activity of the presynaptic neuron, thus also scaling connectivity by a diagonal matrix. It is unclear how these two mechanisms could produce a specific low-rank modulation.

    1. Reviewer #1 (Public review):

      Summary:

      The authors present MiPS, a platform combining DMD-based patterned illumination, automated microscopy, retrained DeLTA segmentation, and mother-machine microfluidics to selectively inhibit or eliminate cells based on dynamic phenotypes. The system enables targeted UV or red-light illumination in real time using segmentation-informed projection masks, allowing selective enrichment directly within mother-machine devices. The manuscript demonstrates proof-of-concept enrichment of mCherry cells from mixed GFP/mCherry populations, characterizes off-target effects, and performs computational simulations of iterative enrichment rounds. Overall, the engineering and systems integration are impressive, and the platform has strong potential for applications in directed evolution, biosensor optimization, and dynamic phenotype-based selection workflows.

      Overall, I believe the work is suitable for publication after minor revisions and clarification of several aspects of the manuscript. In particular, the paper would benefit from additional context in the Introduction and Methods sections, clearer positioning relative to existing platforms, improved figure readability/captions, and a more careful revision of the English throughout the manuscript.

      Major comments:

      (1) The manuscript should better position MiPS relative to recent microscopy-based and DMD-enabled selection/control systems, particularly Lugagne et al., Nature Communications (2024), DOI: 10.1038/s41467-024-46361-1. That work also combines mother-machine microfluidics, DeLTA-based real-time image analysis, and DMD projection. The key distinction here appears to be physical selection/enrichment through targeted killing rather than optogenetic control, and this difference should be stated more explicitly.

      (2) The manuscript currently compares MiPS mostly to FACS/MACS. However, the more relevant comparison may be recent image-based and microfluidic photoselection systems. A dedicated comparison table discussing throughput, temporal phenotyping, iterative selection, dynamic phenotype tracking, and enrichment capabilities would strengthen the paper.

      (3) The enrichment experiment in Figure 4 represents a relatively simple classification problem (GFP vs mCherry). Since the proposed applications involve subtle continuous phenotypes, it would considerably strengthen the manuscript to include at least one experiment selecting for high vs. low expressors within a single fluorescent reporter population.

      (4) The strongest enrichment result (~170-fold enrichment in Figure 5) is entirely simulation-based. Since the manuscript already states that ~45 min is sufficient between rounds for growth evaluation, a real 2-3-round enrichment experiment seems feasible and would substantially strengthen the platform's practical relevance. This experiment appears realistic within a relatively short time investment.

      (5) The bimodal distributions in Figure 2 suggest that a fraction of cells may be stress-resistant rather than simply surviving randomly. It would be useful to discuss whether repeated rounds could progressively enrich UV-resistant subpopulations.

      (6) The manuscript repeatedly uses the term "killed," although the data shown in Figures 2 and 4 mostly demonstrate strong growth arrest/inhibition. Please clarify how the cutoff of division rate <0.4 h⁻¹ was selected and whether an independent viability assay was performed.

      (7) The off-target analysis in Figure 3 is one of the strongest parts of the paper and should probably be emphasized more. The conclusion that the dominant effects are global rather than local is interesting, but additional discussion about optical scattering, ROS diffusion, or device-wide coupling effects would strengthen the interpretation.

      (8) UV exposure is inherently mutagenic in E. coli, and untargeted cells still receive a substantial fraction of the UV dose at high targeting fractions. Please discuss whether the MB/red-light modality may be preferable in applications where preserving genotype integrity is important.

      (9) The manuscript discusses that methylene blue (MB) improves the on:off target ratio, but MB also appears to reduce baseline growth by ~40% even without red-light exposure. This is potentially important for iterative selection workflows. Please discuss whether this effect is reversible after washout and how rapidly cells recover.

      (10) The manuscript states that the retrained DeLTA model used ~3,000 annotated fluorescence images, but no train/validation/test split or segmentation performance metrics are reported. Since segmentation directly impacts phenotype classification and projection targeting, these details are important for reproducibility.

      (11) The manuscript would benefit from a stronger Methods description regarding DMD calibration, alignment procedures, projection accuracy validation, and computational timing requirements for the real-time analysis pipeline.

      Significance:

      General assessment: This is a creative and technically impressive study that combines mother-machine microfluidics, automated microscopy, real-time image analysis, and DMD-based photoselection into a unified platform for dynamic, phenotype-based enrichment. The strongest aspects of the work are the systems integration, the quantitative characterization of off-target effects, and the conceptual demonstration that dynamic microscopy-derived phenotypes can be linked to physical enrichment workflows.

      The main limitations are that the biological validation remains largely proof-of-concept and the most compelling enrichment results are currently simulation-based rather than experimentally demonstrated across multiple rounds. In addition, the manuscript would benefit from stronger positioning relative to recent image-based and DMD-enabled microfluidic control systems.

      Advance: The study extends the field of single-cell microfluidics and image-based selection by introducing a platform that links longitudinal microscopy measurements directly to physical enrichment decisions within mother-machine devices. To my knowledge, the combination of iterative feedback-driven selection, DMD-based targeted elimination, and dynamic phenotype tracking in this context is novel.

      The closest related systems appear to be recent DMD-enabled mother-machine platforms for real-time optogenetic control, particularly those reported by Lugagne et al. (Nature Communications 2024, DOI: 10.1038/s41467-024-46361-1). However, MiPS introduces a distinct conceptual advance by using patterned illumination for selective enrichment/elimination rather than gene-expression modulation alone.

      The advance is primarily technical and conceptual, with potential downstream applications in directed evolution, synthetic biology, biosensor engineering, and dynamic phenotype screening workflows that are difficult or impossible to implement using FACS alone.

      Audience: The work will likely be of strongest interest to researchers working in synthetic biology, microfluidics, single-cell analysis, systems biology, bioengineering, and automated microscopy. It may also be of broader interest to communities developing dynamic phenotype screening technologies, closed-loop biological control systems, and next-generation directed evolution platforms.

      The audience is likely specialized but multidisciplinary, spanning both engineering-oriented and biology-oriented researchers. The methods and conceptual framework may also influence future development of automated selection systems beyond the specific mother-machine context.

      Expertise - My expertise includes: Microfluidics, Synthetic biology, Single-cell systems, Automated microscopy, Real-time image analysis, Bioengineering platforms, Dynamic phenotype characterization.

    1. Reviewer #1 (Public review):

      Summary:

      The study by McKim et al (eLife-RP-RA-2024-102684) seeks to provide a comprehensive description of the connectivity of neurosecretory cells (NSCs) using a high-resolution electron microscopy dataset of the fly brain and several single cell RNA seq transcriptomic datasets from the brain and peripheral tissues of the fly. They use connectomic analyses to identify discrete functional subgroups of NSCs and describe both the broad architecture of the synaptic inputs to these subgroups as well as some of the specific inputs including from chemosensory pathways. They then demonstrate that NSCs have very few traditional presynapses consistent with their known function as providing paracrine release of neuropeptides. Acknowledging that EM datasets can't account for paracrine release, the authors use several scRNAseq datasets to explore signaling between NSCs and characterize widespread patterns of neuropeptide receptor expression across the brain and several body tissues. The thoroughness of this study allows it to largely achieve its goal and provides a useful resource for anyone studying neurohormonal signaling.

      Strengths:

      The strengths of this study are the thorough nature of the approach and the integration of several large-scale datasets to address shortcomings of individual datasets. The study also acknowledges the limitations that inherent to studying hormonal signaling and provide interpretations within the context of these limitations.

    1. Reviewer #1 (Public review):

      Summary:

      This study extends the authors' prior work on transgenic nhomie/homie boundary pairing (Fujioka et al. 2016 PLoS Genetics), which showed that these elements - corresponding to the eve TAD's left and right boundaries - can pair with endogenous copies over large genomic distances (142 kb here), bridging a linked reporter gene to endogenous eve enhancers for long-range gene activation (shown again here in Figure 1). Physical pairing was previously confirmed (Chen et al. 2018 Nat Genet) and further resolved by Micro-C (Bing et al. 2024 eLife), supporting the hypothesized "stem-loop" or "circle loop" topologies used to explain homie/nhomie directional pairing (shown here for nhomie in Figures 2-3). The authors recently showed that a Su(Hw) binding site is required for homie-mediated reporter gene activation by eve enhancers (Fujioka et al. 2025 Genetics); here, they extend this finding to nhomie (Figures 4-6), further showing that Su(Hw) motifs are required for Micro-C-detectable looping between transgenic and endogenous eve boundaries (Figures 7-9). Finally, they show that while cis-pairing over 142 kb is highly specific to homie/nhomie elements, transvection between homologous transgene insertions is more permissive (functioning with the Su(Hw)-bound gypsy insulator) but still shows some specificity (failing with the CTCF-bound Fab8 boundary, Figures 10-11).

      Strengths:

      The question of how pairs of loci can specifically physically pair over relatively long genomic distances is an interesting fundamental question. The study's strengths are the clarity and meticulous interpretation of the results, and the authors' conclusions are compelling.

      Weaknesses:

      A major weakness is that some figures reproduce previously published findings; in some cases it is unclear whether the same fly lines were used, and in others, the lines differ only slightly from those used previously (e.g., a shorter version of the Homie transgene than the one used previously). Most conclusions in this manuscript have already been published elsewhere. As a result, the paper does not report a genuine new discovery, and only incrementally advances our understanding of boundary pairing.

    1. Reviewer #1 (Public review):

      Summary:

      Mast cells have previously been reported to play an important role in bacterial immune defence and act protectively in sepsis. However, many of these findings were based on studies using Kit mutant mice. In this study, the authors conducted a detailed investigation using mast cell-deficient Cpa3 Cre-Master mice. As a result, the authors found that the Cpa3 Cre-Master mice exhibited responses similar to wild-type mice in terms of bacterial immune defense. This suggests that the observed phenotype is not due to mast cell-dependent bacterial immune defense, but rather is associated with dysbiosis of the gut microbiota.

      Strengths:

      Mast cells have long been reported to play an important role in the protective response against sepsis, and their function in infection defense has been demonstrated. However, Kit mutant mice have been reported to exhibit impaired peristalsis, and several mast cell-specific genetically modified mouse lines have since been developed and examined in detail. This study presents an important finding by logically demonstrating that the exacerbation of sepsis in Kit mice is due to alterations in the gut microbiota, and that the phenotype previously thought to be mast cell-dependent was, in fact, not.

      In addition, the experiments were carefully designed using mice with matched genetic backgrounds. These findings underscore the importance of microbiota composition in interpreting immune phenotypes and highlight the need for co-housing controls in mutant mouse studies.

      A major strength of this work is the robustness of the CLP data, generated over eight years by three independent researchers across two institutions with large sample sizes, lending strong support to the conclusions.

      Weaknesses:

      The study assesses only a limited subset of gut bacterial species, leaving the extent to which E. coli expansion contributes to the observed phenotype unclear. Moreover, in the cohousing experiments, there is no evidence provided to confirm successful microbiota normalization between groups. A more detailed analysis of the microbial composition would be necessary to strengthen the reliability of the findings.

      It is also important to note that Cpa3-deficient mice exhibit not only mast cell depletion but also defects in basophils and T cells. These additional immunological alterations may counterbalance one another, potentially masking phenotypic changes and complicating interpretation.

      Furthermore, it remains to be determined whether the altered gut microbiota observed in KitW/Wv mice is a consequence of impaired intestinal motility, whether a similar phenotype is observed in KitW-sh/W-sh mice, and whether comparable results occur in SCF-deficient models. Addressing these questions would provide greater clarity on the contribution of mast cells versus secondary factors in the observed phenotypes.

      Given that KitW/Wv mice exhibit impaired peristalsis, is the observed increase in E. coli a consequence of this dysfunction?

      Previous studies with BMMC reconstitution experiments have indicated that mast cells are a source of TNF-how does this align with the current findings?

      Comments on revised version.

      The authors have made substantial efforts to address the concerns raised in the previous review, and the revised manuscript has been substantially strengthened by the additional microbiome analyses. In particular, the new data provide a more comprehensive characterization of the intestinal microbiota in both Kit mutant and mast cell-deficient mice and strengthen the interpretation that the microbiota alterations observed in Kit mutant mice are associated with Kit deficiency rather than mast cell deficiency per se. Although Enterobacteriaceae were significantly increased based on the unadjusted Welch's t-test, this difference did not remain statistically significant after correction for multiple comparisons. The authors appropriately acknowledge this limitation in the revised manuscript. Overall, I consider the major concerns regarding the microbiome analysis to have been adequately addressed.

    1. Reviewer #3 (Public review):

      In this work, Bryant, et al. investigate genetic interactions between non-essential members of the outer membrane protein biogenesis pathway and other genes in the genome using a transposon-directed insertion sequencing (TraDIS) approach in E. coli K-12. The authors identify interactions with other components of the envelope including LPS, peptidoglycan, and enterobacterial common antigen biogenesis, and they tie these interactions to specific members of the outer membrane biogenesis pathway. Although many of these interactions are known and have been previously investigated in the field, the study provides several synthetic phenotypes that could be useful for further investigations.

      The strengths of the paper include the unbiased, TraDIS approach, and follow up on the interactions observed. The interactions with genes of unknown function also are of interest as they may suggest experiments to find the functions of these genes. Although the paper could better address the relation of its findings to existing literature, the work in the paper is well controlled and the findings will be of interest to the field.

    1. Reviewer #1 (Public review):

      Summary:

      This study aimed to determine whether bacterial translation inhibitors affect mitochondria through the same mechanisms. Using mitoribosome profiling, the authors found that most antibiotics, except telithromycin, act similarly in both systems. These insights could help in the development of antibiotics with reduced mitochondrial toxicity.

      They also identified potential novel mitochondrial translation events, proposing new initiation sites for MT-ND1 and MT-ND5. These insights not only challenge existing annotations but also open new avenues for research on mitochondrial function.

      Strengths:

      Ribosome profiling is a state-of-the-art method for monitoring the translatome at very high resolution. Using mitoribosome profiling, the authors convincingly demonstrate that most of the analyzed antibiotics act in the same way on both bacterial and mitochondrial ribosomes, except for telithromycin. Additionally, the authors report possible alternative translation events, raising new questions about the mechanisms behind mitochondrial initiation and start codon recognition in mammals.

      Weaknesses:

      All the weaknesses I previously highlighted were adequately addressed.

    1. 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:

      D. Fuller et al. set out to study the molecular partners that cooperate with ATG2A, a lipid transfer protein essential for phagophore elongation, during the process of autophagy. Through a series of experiments combining microscopy and biochemistry, the authors identify ARFGAP1 and Rab1A as components of early autophagic membranes, which accumulate at the periphery of aberrant pre-autophagosomal structures induced by loss of ATG2. While ARFGAP1 has no apparent function in autophagy, the authors show that RAB1A is implicated in autophagy, although the precise mechanisms are not explored in the manuscript.

      Strengths:

      The work presented by Fuller et al. provides new insights into the composition of early autophagic membranes. The authors provide a series of MS experiments identifying proteins in close proximity to ATG2A, which is a valuable dataset for the field. Furthermore, they show for the first time the interaction between ATG2A and RAB1A both in fed and starved conditions, which extends the characterisation of the pre-autophagosomal structures observed in ATG2 DKO cells.