Reviewer #1 (Public review):

Summary:

The authors performed seqFISH in 26 gastruloids and performed a variety of computational analyses on these novel spatial data sets. Whilst the data is valuable and the computational concepts useful (exposure index, L-metric, ... ), the article falls short on novelty and is written using a very clunky language, often with contradictory conclusions.

Major issues:

(1) The authors did well in explaining and detailing the provenance of data and the individual experiments performed. However, their 26 gastruloid data still constitute a very limited sampling from their total organoids: one experiment pooled 4 plates at an 80-94% success rate; 6 different aggregation experiments were done, making a total of 1843 gastruloids, sampled 26 (~1-2%). A simple IF stain of 2-3 markers in a bigger sample could have given a more accurate picture of specific domains of interest and their proximity. Regardless, more information should be given about the existing samples: variation across experimental batches, differences between 300-cell vs 100-cell gastruloids that were used.

(2) Language in the manuscript should be revised. Overall the manuscript is very long, descriptive and written "impressions and beliefs" are often not adequately justified and indeed can be contradictory, e.g. in Section 1: the title states "cell types' locations ...are consistent", a few sentences down we find "there was substantial variation" and "within range of what would be considered a 'morphologically normal' gastruloid". "quite consistent", "compelling patterning", "we don't believe"... these types of expressions are best avoided and replaced with data or used and bolstered with quantitative numbers such as percentages when a given cutoff is used. Another example: "location of each cell type relative to gastruloid morphology was quite consistent the posterior region ... mainly consisted in NMPs." Given T expression in the posterior, this result phrased as such appears quite inflated, in fact, looking at cell types in Figures S1, 2a/b/c, this reviewer would state they are all but consistent and indeed it takes sophisticated analyses to find a pattern (of sorts) beyond the coarse domains expected!

(3) Figure 6 is one of the most valuable parts of the work, as the authors use the battery of analyses developed to investigate the variable and not-so-robust endothelial clusters in gastruloids. However, this investigation is still very preliminary, and it should be further linked with known biology. It is still unclear what the unique organization of this cell type is (circularity isn't convincing) and whether any signalling cues of adjacent cells could explain it. Is there any evidence that more mature endodermal cell types are generated (like the suggested "liver") to give rise to endothelial cells? It would certainly be interesting to perform IF for this cell type together with mesodermal and endodermal markers to validate seqFISH predictions on a bigger sample.

(4) Figures 1c and 6b need statistical significance assessments.

(5) The article should include an analysis of Hox colinearity expression in these gastruloids as a validation of the system.

Reviewer #2 (Public review):

Summary:

Protein synthesis - translation - involves repeated recognition and incorporation of amino-acyl-tRNAs by the ribosome. This process is a trade-off between the rate and accuracy of selection (for review see (Johansson et al, 2008; Wohlgemuth et al, 2011)). The ribosome does not just maximise the rate or the accuracy, it balances the two. Therefore, it is possible to select mutants that translate faster than the wt (but are sloppy) or that are very accurate (more than the wt) but translate slower. Slow translation is detrimental as it limits the rate of protein synthesis (and, therefore, growth) and hyper-accurate mutants accumulate mis-translated proteins, which is detrimental for the cell.

Bi and colleagues employ genetics, MIC measurements, reporter assays and structural biology to characterise the role of GidB rRNA methylase in translational accuracy in Mycobacterium smegmatis.

Strengths:

The genetics and phenotypic assays are convincing and establish the biological role of the methylase. The authors use a powerful set of complementary assays that convincingly demonstrates that the loss of GidB results in mistranslation.

Weaknesses:

Cryo-EM analysis of vacant 70S ribosomes is not sufficient for understanding the mechanisms underlying the accuracy defects in the gidB KO. Ideally, one should assemble and solve structurally near-cognate and non-cognate complexes.

References:

Johansson M, Lovmar M, Ehrenberg M (2008) Rate and accuracy of bacterial protein synthesis revisited. Curr Opin Microbiol 11: 141-147

Wohlgemuth I, Pohl C, Mittelstaet J, Konevega AL, Rodnina MV (2011) Evolutionary optimization of speed and accuracy of decoding on the ribosome. Philos Trans R Soc Lond B Biol Sci 366: 2979-2986

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 satisfactorily and toned down the comments as advised.]

In this manuscript, the authors investigate the relationship between genetic codes and their robustness to single-point mutations. They construct ten alternative genetic codes by reassigning nine codons to Leu, Ser, or Ala, and assess mutational robustness using three reporter proteins subjected to error-prone PCR. This represents an interesting experimental approach to addressing the hypothesis that the standard genetic code is optimized for mutational robustness.

Reviewer #1 (Public review):

Summary:

In their article, Guo and coworkers investigate the Ca²⁺ signaling responses induced by Enteropathogenic Escherichia coli (EPEC) in epithelial cells and how these responses regulate NF-κB activation. The authors show that EPEC induces rapid, spatially coordinated Ca²⁺ transients mediated by extracellular ATP released through the type III secretion system (T3SS). Using high-speed Ca²⁺ imaging and stochastic modeling, they propose that low ATP levels trigger "Coordinated Ca²⁺ Responses from IP₃R Clusters" (CCRICs) via fast Ca²⁺ diffusion and Ca²⁺-induced Ca²⁺ release. These responses may dampen TNF-α-induced NF-κB activation through Ca²⁺-dependent modulation of O-GlcNAcylation of p65. The interdisciplinary work suggests a new perspective on calcium-mediated immune response by combining quantitative imaging, bacterial genetics, and computational modeling.

Strengths:

The study provides a new concept for host responses to bacterial infections and introduces the concept of Coordinated Ca²⁺ Responses from IP₃R Clusters (CCRICs) as synchronized, whole-cell-scale Ca²⁺ transients with the fast kinetics typical of local events. This is elegantly done by an interdisciplinary approach using quantitative measurements and mechanistic modelling.

Comments on revised version.

The revised version of the manuscript has addressed all my raised points. I'd like to thank the authors for the work they have put into the revision to make this a very compelling publication.

Reviewer #1 (Public review):

The authors present a compelling case for the necessity of age-specific templates in functional hyperalignment. Given that the brain undergoes substantial developmental, structural, and functional changes across the lifespan, a 'one-size-fits-all' canonical template is often insufficient. This study effectively demonstrates that incorporating age-congruent features significantly enhances the performance and sensitivity of hyperalignment models. By validating these findings across two independent datasets (Cam-CAN and DLBS), the paper provides robust evidence that accounting for age-related functional organization is a critical prerequisite for accurate functional alignment in lifespan research

Comments on revised version:

The authors have been exceptionally thorough in addressing the concerns raised by the reviewers. In particular, the inclusion of the supplemental analysis on the middle-aged cohort is a valuable addition that strengthens the manuscript. Furthermore, the rationale for employing a congruent template is well-articulated; this approach clearly provides a more robust and accurate foundation for reconstructing individualized connectomes. I appreciate the authors' detailed responses and have no further comments.

Reviewer #1 (Public review):

Summary:

This manuscript presents a tunable Bessel-beam two-photon fluorescence microscopy (tBessel-TPFM) platform that enables high-speed volumetric imaging with stable axial focus. The work is technically strong and broadly significant, as it substantially improves the flexibility and practicality of Bessel-beam-based two-photon microscopy. The demonstrations are generally strong and bridge a wide range of neuroimaging applications, namely vascular dynamics, neurovascular coupling, optogenetic perturbation, and microglial responses. These convincingly show that the approach enables biological measurements that are difficult or impractical with existing methods.

The evidence supporting the technical and biological claims is generally strong. The optical design is carefully motivated, clearly described, and validated through a combination of simulations and experimental characterization. The biological applications are diverse and well chosen to highlight the strengths of the proposed method, and the data are of high quality, with appropriate controls and comparative measurements where relevant.

Strengths:

(1) The optical innovation addresses a well-recognized limitation of existing Bessel-TPFM implementations, namely axial focus drift during tuning, and does so using a relatively simple, light-efficient, and cost-effective design.

(2) The manuscript provides convincing experimental evidence for this being a versatile platform to map flow dynamics across diverse vessel sizes and orientations in both healthy and pathological states.

(3) Biological demonstrations are comprehensive and span multiple domains such as hemodynamics, neurovascular coupling, and neuroimmune responses.

(4) Quantitative analyses of blood flow across vessel sizes and orientations, including kilohertz line scanning, are particularly compelling and clearly beyond the reach of standard Gaussian TPFM.

(5) Particular advantages are that higher blood slow speeds become measurable up to 23mm/sec (20x more than conventional frame scanning), and that simultaneous (Bessel-)imaging and (Gaussian-)perturbation are possible because of the stable axial focus.

Weaknesses:

(1) At present, the paper does not properly position the new Bessel-beam method against previous work, and fails to compare it to alternative fast volumetric imaging methods without Bessel beams.

(2) The cost-effectiveness of the proposed method is not well described or supported by evidence; it would be useful to include more detail or remove this claim.

(3) Some biological conclusions, e.g., regarding novel features of microglial dynamics (i.e., the observed two-wave responses and coordinated extension-retraction), are based on relatively limited sample size and would benefit from clearer discussion of variability across animals and fields of view.

(4) The use of neural network-based denoising for microglial imaging is reasonable but introduces potential concerns about trustworthiness; additional clarification of validation or failure modes would strengthen confidence in these results.

To conclude, most of the authors' claims are well supported by the data. The central conclusion, namely that tBessel-TPFM provides tunable volumetric imaging enabling experiments not feasible with existing two-photon approaches, is justified. Some biological interpretations would benefit from a more cautious framing, but they do not undermine the main technical and methodological contributions of the study. This is a strong and technically rigorous manuscript that makes a substantial methodological advance with clear relevance to neuroscience and intravital imaging. Minor clarifications and a slightly more measured discussion of certain biological findings are recommended.

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.]

The authors pair analysis of replication timing and allele-specific expression in clonal populations of primary human cells. They combine these data with previously published data on clones from transformed human cell lines. They identify a number of genomic regions that display asynchronous replication timing in at least one clone and correlate these regions with allele-specific expression of genes within them. They also observe that several interesting gene sets, including genes that are associated with human diseases, map to asynchronously replicating regions. This is a good experimental approach that builds on already published data demonstrating the connection between allelic imbalance and replication timing.

Joint Public Review:

This manuscript puts forward the provocative idea that a posttranslational feedback loop regulates daily and ultradian rhythms in neuronal excitability. The authors used in vivo long-term tip recordings of the long trichoid sensilla of male hawkmoths to analyze spontaneous spiking activity indicative of the ORNs' endogenous membrane potential oscillations. This firing pattern was disrupted by pharmacological blockade of the Orco receptor. They then use these recordings together with computational modeling to predict that Orco receptor neuron (ORN) activity is required for circadian, not ultradian, firing patterns. Orco did not show a circadian expression pattern in a qPCR experiment, and its conductance was proposed to be regulated by cyclic nucleotide levels. This evidence led the authors to conclude that a post-translational feedback loop (PTFL) clockwork, associated with the ORN plasma membrane, allows for temporal control of pheromone detection via the generation of multi-scale endogenous membrane potential oscillations. The findings will interest researchers in neurophysiology, circadian rhythms, and sensory biology. However, the manuscript has limited experimental evidence to support its central hypothesis and is undermined by several assumptions that underlie their data analysis and model builds, as well as insufficient biological data including critical controls to validate and/or fully justify the model the authors are proposing.

Strengths:

The authors raise several intriguing model-based hypotheses regarding the mechanisms that underlie the generation of olfactory rhythms. The electrophysiological approach and the long-term recording paradigm are elegant and technically impressive. In the revised version, the authors have added additional qPCR data supporting the lack of rhythmic Orco transcript expression and included a new figure suggesting that cAMP can modulate Orco conductance.

Major weaknesses:

(1) The cAMP experiment was only conducted at one time-point, which is insufficient to support the central claim that "AMP and cGMP may have ZT-dependent effects on Orco conductivity".

(2) The revised manuscript continues to rely heavily on prior publications or defers key mechanistic questions (or important manipulations) to future studies. In its current form, the evidence presented remains insufficient to support the central claim that a PTFL constitutes the primary underlying circadian clock mechanism. The proposed model is intriguing, but the data provided do not yet directly demonstrate the novel mechanism.

Reviewer #1 (Public review):

M. tuberculosis exhibits metabolic flexibility, enabling it to adapt to various environmental stresses, including antibiotic treatment. In this manuscript, Serafini et al. investigate the metabolic remodeling of M. tuberculosis used to survive iron-limited conditions by employing LC-MS metabolomics and 13C isotope tracing experiments. The results demonstrate that metabolic activity in the oxidative branch of the TCA cycle slows down, while the reductive branch is reverted to facilitate the biosynthesis of malate, which is subsequently secreted.

Overall, this study is experimentally well-designed, particularly the use of 13C isotope tracing to monitor TCA cycle remodeling under iron-limited conditions. The findings are valuable as they offer potential new targets for antibiotics aimed at non-replicating M. tuberculosis occurring in the hosts.

Comments on revised version:

All concerns are well addressed.

I have one minor concern: Page 3 line 16 - Fig. 1G & H: The kinetics of ATP levels between H37Rv and Erdman seem different; Erdman induces greater ATP at days 2 and 3 after DFO treatment, which was not clear in H37Rv. Fig. 1I shows NAD/NADH ratio not NADH/NAD ratio. Please change it to NADH/NAD+ to be consistent with Supplement Fig. 1 result. Include the 17-day result of NADH/NAD+ in the discussion section to explain the different viability between the two strains.

Reviewer #1 (Public review):

This paper aims to improve the accuracy of predictions of the impact of ITN strategies by developing a method to estimate duration of ITN access and use over time on a subnational scale from cross-sectional survey data and the numbers ITNs received annually. The subnational estimates are then input into a mathematical model to predict clinical cases under different ITN distribution strategies.

Strengths:

The approach is novel and addresses a useful and timely topic. It makes use of available routine data, and has considered all of the relevant components of ITN distributions.

The authors have made revisions, particularly to the methods, appendices and title - leaving the paper easier to follow, and with a clear, consistent aim. The assumptions are clearly stated.

Weaknesses:

The weaknesses are shared with other models of a similar complexity - it is not easy for a casual reader to fully understand the model or the implications of the assumptions which were required to be made. That routine data is used is good for availability, but data quality may be an issue in some places.

Reviewer #1 (Public review):

Summary:

Launay et al., conducted a screen of PDE in 25 new Rhabditidae species through cytological approaches and found PDE is detected in 17 out of 25 species, representing 12 out of 17 genera within the family. This work is significant because it expands PDE from a few known nematodes to a much broader set of Rhabditidae species.

Strengths:

By demonstrating PDE across many genera with the exception of C. elegans and some other Caenorhabditis species, the study provides an important resource for investigating PDE's evolutionary origins, mechanisms of genome reorganization and DNA repair, and its functional consequences.

Most of the observed PDEs were supported by solid evidence through a survey-style cytological screen (PDE detected in 17/25 species and in 12/17 genera), which supports the main claim of widespread occurrence.

Weaknesses:

Although most PDE claims are supported by solid evidence, some of the existing data do not describe the depth of characterization, e.g., how many replicates were conducted for each species? How reproducible are the claimed PDEs between embryos in terms of timing and cell identities destined for PDE? Is it possible to validate a subset of PDE with independent evidence, especially for those with marginal PDE? This is important because some dying embryos may fail to maintain their chromosome integrity and release some of the broken DNAs, some others may suffer from noise such as intracellular parasites, for example, microsporidia, or even highly condensed mitochondrial DNAs.

Reviewer #1 (Public review):

"Learning is a fundamental source of individuality," by Manna and colleagues, interrogates different sources of variation in individual behavior. The authors place individual flies in a Y-shaped arena, which is a common design in the field, and illuminate the arms of the Y with blue versus green light. They track the color preference of individual animals and also perform operant conditioning, meaning that they teach the fly to avoid a particular color/arm by generating a foot shock when the fly enters that arm. There are a number of things that are impressive about this setup: The authors are able to collect data on thousands of individual flies of many different strain backgrounds, and they demonstrate a strong change in color preference after conditioning. This is nice, because in past papers, visual learning ability has been modest and difficult to study. To put a number on it, in this paper, animals on average don't show a color preference at the start of the assay, spending around 30% of their time in the one arm illuminated green, and the remaining time in the two arms illuminated blue. After conditioning, the average animal spends only 23% of its time in the green arm.

The authors run 64 animals through the assay for each of 88 wild-type strains (maybe? see Major Point 1 below) and see considerable strain-specific (genetic) variation in the change in time spent in the shocked color after conditioning. Some strains show no learning, while others spend <10% of their time in the shocked color after conditioning. They also, I believe, see that some strains have more variability across individuals, which would suggest that some strains have stronger canalization at the development or circuit function level than others, i.e., some genotypes produce more consistent copies of the individual, others less consistent copies. (Or, some genotypes produce robust circuits, and others produce noisy circuits.)

Finally, the authors argue statistically that learning itself increases variability in individual performance. This makes a lot of sense to me intuitively. Learning changes the physical/chemical properties of circuits in the brain, and because it evolves over time and interacts with environmental variables, it seems like it should send different animals down different channels. Or, at a conceptual level, if I learn to play the piano and my sister doesn't (because of some genetic difference between us or something stochastic), this learning experience will cause all sorts of other differences in our behavior as time passes. I also think the authors do have enough data to be able to make this finding. However, the presentation of the argument in this portion of the paper is hard for me to understand, and I am not an expert in statistics, so the strength of the result is difficult for me to evaluate.

Major points

(1) It's difficult to track through the paper the number of animals tested for different assays. At the beginning, it says N=5632, which works out to 64 flies for each of the 88 DGRP strains. 64 happens to be the number of parallel Y arenas they have. Later in the methods, there's a description of more variation within the set of 64 for each strain, two different parent sets per strain, different sexes, conditioned and unconditioned. And, while the results text focuses on the color learning, the methods discuss additional assays (place learning, multi-day learning).

Given the numbers, does each run of the 64 mazes include all the tested flies of one strain, or are flies of many strains included in each batch? Do different flies do different assays (color, place, multi-day), or do they all do all the assays? Perhaps there is a table including this information already in the supplement, but I recommend making it much clearer in the main results text and methods. While the dataset is large, if it is split over many conditions and/or if batch and genotype confound each other, this will affect the robustness of the results and how strong the conclusions can be.

(2) The data presentation in Figure 1 is elegant and easy to follow, but getting into Figure 2 and subsequently, I get lost in the statistics and have trouble understanding what is being measured. My understanding of the big picture is that while genetics and individual randomness contribute a lot to behavior, the evidence for learning as an amplifier of individuality is that variance in behavior among animals of the same strain increases over time in the conditioned group (i.e., the group that is doing the most learning, or a specific kind of learning), but not in the control group. This idea is illustrated in the flattening distributions in the cartoons in Figure 1A. The authors should include graphs of the real data that use the same format as in that cartoon. Instead, the graphs present "residuals," and I don't know what those are. I suspect it's "variation left over after accounting for effects of strain and individual stochasticity." I see the residuals being tracked per strain over time in Figure 2H, but I don't see the change over time in other graphs. I'm looking for something simple like, "variation within the strain at the beginning of learning and at later time points in learning." (But I'm not sure exactly what instantaneous measurement would be the focus in longitudinal analyses of learning behavior.)

(3) Figure 3 is a cool stab at tracking down the precise mechanism by which a stochastic environment interacts with learning to send individuals along different behavioral routes. But again, like in Figure 2, I don't have the sophisticated understanding of statistics to understand exactly what the graphs are telling me, or how they relate to the underlying measurements. I'm relying on the results text alone to reach a conceptual understanding, and just taking the graphs on trust.

So, overall, the authors have a very nice body of work here, and with the potential to add a new facet to our understanding of the origins of diversity in animal behavior. In addition to the interpretations they focus on here, this dataset also represents an advance in studying visual associative learning in general, and quite an amazing ability to make longitudinal measurements of many behavioral decisions within the same animals. Improving the data presentation to make it easier to follow for a larger swathe of researchers, especially in figures 2 and 3, will increase its potential impact.

Reviewer #1 (Public review):

Summary:

This paper presents a toolkit for the transformation of Blastocystis. The authors have screened a number of selectable agents, promoters and reporter genes and present their findings. This resource will be of immense use to those in the Blastocystsis field, as well as those seeking to establish transformation tools in other species where such tools do not yet exist. Establishing new transformation tools is extremely challenging, and the authors have done an excellent job.

Strengths:

The authors have carried out a systematic screen of promoters, reporter genes and selectable agents. They have screened numerous for each, and all the data is presented. It is good to see when things did not work as well as when things did, so this data set is extremely useful indeed.

Weaknesses:

The findings are reported by reporter gene assay (microscopy). No evidence is given using genetics. The authors claim that the DNA is maintained episomally. However, could it be possible that there is integration? No PCRS/RT-PCRs are shown (although it can safely be assumed that the DNA/RNA is present where the transformation was successful), nor are any Western blots. These would have been useful to show that the P2A ribosomal skipping had occurred, and that proteins were expressed individually rather than as a polyprotein.

Joint Public Review:

In this manuscript, the authors proposed an approach to systematically characterise how heterogeneity in a protein signalling network affects its emergent dynamics, with particular emphasis on drug-response signalling dynamics in cancer treatments. They named this approach Meta Dynamic Network (MDN) modelling, as it aims to consider the potential dynamic responses globally, varying both initial conditions (i.e., expression levels) and biophysical parameters (i.e., protein interaction parameters). By characterising the "meta" response of the network, the authors propose that the method can provide insights not only into the possible dynamic behaviours of the system of interest but also into the likelihood and frequency of observing these dynamic behaviours in the natural system.

The authors study the Early Cell Cycle (ECC) network as a proof of concept, focusing on pathways involving PI3K, EGFR, and CDK4/6 with the aim of identifying mechanisms that may underlie resistance to CDK4/6 inhibition in cancer. The biochemical reaction model comprises 50 state variables and 94 kinetic parameters, implemented in SBML and simulated in Matlab. A central component of the study is the generation of large ensembles of model instances, including 100,000 randomly sampled parameter sets intended to represent intra-tumour heterogeneity. On the basis of these simulations, the authors conclude that heterogeneity in kinetic rate parameters plays a stronger role in driving adaptive resistance than variation in baseline protein expression levels, and that resistance emerges as a network-level property rather than from individual components alone. The revised manuscript provides additional clarification regarding aspects of the simulation and filtering procedures and frames the comparison with experimental data as qualitative. Nonetheless, the study is best interpreted as a theoretical and exploratory analysis of the model's behaviour under heterogeneous conditions. Consequently, questions remain regarding the biological grounding of the sampled parameter regimes and the extent to which the reported frequencies of resistance-associated behaviours can be directly interpreted in physiological terms.

While the authors propose a potentially useful computational framework to explore how heterogeneity shapes dynamic responses to drug perturbation, a number of important conceptual and methodological concerns remain to be addressed:

(1) The sampling of kinetic parameters constitutes the backbone of the manuscript, yet important concerns remain regarding its biological grounding and transparency. Although the revised version provides additional clarification on the exploration of "model instances", it is still not sufficiently clear how parameter values and initial conditions are generated, nor how the chosen ranges relate to biological measurements. The kinetic rates are sampled over broad intervals without explicit justification in terms of experimentally measured bounds or inferred distributions. As a consequence, it remains uncertain whether the ensemble of simulated behaviours reflects physiologically plausible cellular regimes or primarily the properties of the assumed parameter space. In this context, the large-scale sampling (100,000 parameter sets) resembles a Monte Carlo exploration of the model rather than a biologically calibrated representation of tumour heterogeneity.

Furthermore, the adequacy of the sampling strategy in such a high-dimensional space (94 free parameters) remains open to question. In the absence of biologically informed constraints, the combinatorial space of possible parameter configurations is vast, and it is unclear to what extent the sampled ensembles can be considered representative. This issue is particularly relevant because the manuscript interprets the frequency of resistance-associated behaviours as indicative of their likelihood.

The validation presented in Figure 7 does not fully resolve these concerns. The comparison with experimental data is qualitative, and the simulations are performed in arbitrary time units, which complicates direct interpretation alongside time-resolved experimental measurements. Moreover, certain qualitative discrepancies between simulated and experimental trends (e.g., persistent versus decreasing CDK4/6 activity) are not thoroughly discussed. As this figure represents the primary empirical reference point in the manuscript, the extent to which the model captures experimentally observed dynamics remains uncertain.

Finally, aspects of presentation continue to limit transparency. Parameter ranges are described at different points in the manuscript but are not consolidated clearly in the Methods, and the definition of initial conditions remains ambiguous - particularly whether these correspond to conserved quantities or to the dynamic variables used to initialise simulations. In addition, the exact number of model instances underlying specific analyses and figures is not always explicit. Greater clarity on these issues is essential for assessing reproducibility and for interpreting the quantitative claims of the study.

(2) A central conclusion of the manuscript is that heterogeneity in protein-protein interaction kinetics is a stronger driver of adaptive resistance than heterogeneity in protein expression levels. To assess the latter, the authors fix a nominal set of kinetic parameters and generate 100,000 random initial concentrations for the 50 model species. However, according to the simulation protocol described in the manuscript, each trajectory includes three phases: (i) simulation under starvation conditions to equilibrium, (ii) mitogenic stimulation to a second ("fed") equilibrium, and (iii) application of drug treatment. The equilibrium concentrations reached in phases (i) and (ii) are determined by the kinetic parameters of the model and are independent of the initial concentrations, provided the system converges to a stable steady state. In dynamical systems terms, stable equilibria are defined by the parameter set and attract all initial conditions within their basin of attraction. Since the kinetic parameters are fixed in this experiment, the pre-treatment equilibrium that serves as the starting point for drug application should likewise be fixed. Under these conditions, it is therefore not unexpected that sampling a large number of initial concentrations has limited influence on the treated dynamics.

This raises conceptual questions about the interpretation of the comparison between kinetic and expression heterogeneity. If the system converges to a unique stable steady state prior to treatment, then variability in initial concentrations does not propagate into variability in drug response, and the observed dominance of kinetic heterogeneity may partly reflect this structural property of the model rather than a biological principle. Clarification is needed regarding whether multiple steady states exist under the nominal parameter set, and if so, how basins of attraction are explored.

More broadly, it remains unclear why initial protein concentrations can be sampled independently of the kinetic parameters. In biological systems, steady-state expression levels are typically determined by the underlying kinetic rates. A more consistent approach might require constraining initial concentrations to correspond to equilibrium states of the chosen parameter set, thereby introducing relationships between at least some of the 50 initial conditions and the 94 kinetic parameters. Finally, the manuscript employs a non-standard terminology regarding "initial conditions," which may further obscure interpretation of these results and would benefit from clarification.

(3) The technical implementation of the modelling and simulation framework remains difficult to evaluate due to insufficient methodological detail. Although the authors state that kinetic parameters are randomly sampled, the manuscript does not specify the distributions from which parameters are drawn, nor whether potential correlations between parameters are considered or explicitly ignored. Without this information, it is not possible to assess how implicit modelling assumptions shape the ensemble of simulated behaviours. Given that the conclusions rely on frequency-based interpretations across sampled parameter sets, greater transparency regarding the sampling procedure is essential.

A further concern relates to the parameter filtering step. The authors report that the "vast majority" of sampled parameter sets produced systems that were "too stiff," and that these were excluded on the grounds that stiff dynamics are not biologically plausible. However, the manuscript does not clearly define how stiffness is assessed, nor why stiffness is interpreted as biologically unrealistic rather than as a numerical property of the formulation. In standard practice, stiff systems are typically handled using appropriate implicit solvers rather than being discarded. Similarly, parameter sets that produce negative state values are excluded, yet such behaviour may arise from numerical artefacts rather than from intrinsic model inconsistency. The rationale for excluding these parameter sets, rather than adapting the numerical scheme, is not sufficiently justified.

The reported rejection rate - approximately 90% of sampled parameter sets - is substantial and raises questions regarding the interplay between model structure, parameter ranges, and numerical methods. As currently described, the filtering step appears to select parameter sets based primarily on computational tractability rather than on experimentally motivated biological criteria. The manuscript would be strengthened by clarifying whether the retained parameter sets are representative of biologically meaningful regimes, and by distinguishing clearly between exclusions based on biological plausibility and those arising from numerical considerations.

Finally, important aspects of the simulation protocol require clarification. The model is simulated under "fasted" and "fed" conditions until equilibrium is reached, yet the criterion used to determine convergence is not specified. It would be important to describe how equilibrium is assessed (e.g., based on the norm of the time derivatives). Additionally, it remains unclear whether the mitogenic stimulus applied in the "fed" phase is assumed to be constant over time and, if so, how this assumption relates to biological experimental conditions. Greater detail on these implementation choices is necessary to ensure interpretability and reproducibility.

(4) The manuscript states that the modelling conclusions are strongly supported by existing literature; however, the validation presented does not fully substantiate this claim. As noted above, the comparison with CDK2 and CDK4/6 experimental data remains qualitative, and the use of arbitrary simulation time units complicates interpretation of temporal agreement. The extent to which the model quantitatively or mechanistically recapitulates experimentally observed dynamics therefore remains uncertain.

The claim that the model reproduces known resistance mechanisms is also difficult to assess in light of Figure S10, where a large fraction of network nodes (~80%) appear implicated in resistance under some conditions. If most components of the network can, in at least some parameter regimes, be associated with resistance phenotypes, the resulting lack of selectivity weakens the strength of model-based validation. It becomes challenging to distinguish specific mechanistic insights from generic consequences of network connectivity.<br /> In addition, the Supplementary Information notes that certain components of the mitogenic and cell-cycle pathways were abstracted or excluded in order to maintain computational tractability. While such abstraction is understandable in a large ODE framework, it raises interpretative questions. Proteins identified as potential resistance drivers within the model may, in some cases, represent aggregated or simplified pathway effects. Clarifying in the main text how such abstractions may influence the attribution of resistance mechanisms would strengthen the biological interpretation of the results.

Drug inhibition is central to the manuscript's conclusions. The revised version clarifies that inhibition is implemented as a fixed fractional modification of specific kinetic rate laws. This abstraction is appropriate for exploring network-level responses, but it represents a stylised perturbation rather than a pharmacologically calibrated model of drug action. For full interpretability and reproducibility, the mathematical form of the modified rate laws, as well as the timing of inhibition relative to network equilibration, should be specified unambiguously. The biological implications of the findings depend critically on understanding this modelling choice.

The one-at-a-time perturbation analysis presented in Figure 5 provides an interpretable ranking of first-order control points across the ensemble and offers mechanistic insight into primary sensitivities of the network. However, many targeted therapies act on multiple components, and resistance frequently arises through combinatorial mechanisms. The reported rankings should therefore be interpreted as identifying primary influences under isolated perturbations, rather than as a comprehensive account of multi-target drug behaviour.

Overall, the manuscript succeeds in presenting a conceptual and exploratory framework for analysing how signalling network topology can shape the qualitative landscape of adaptive responses under heterogeneous kinetic conditions. Its principal contribution lies in establishing a systematic platform for large-scale in silico exploration. At the same time, the current limitations in biological calibration, parameter grounding, and validation constrain the extent to which the conclusions can be interpreted as predictive or quantitatively representative of specific tumour contexts. Addressing these issues would further strengthen the connection between the theoretical landscape described here and experimentally observed resistance dynamics.

Reviewer #2 (Public review):

Summary:

This paper attempts to examine how rare, extreme events impact decision-making in rats. The paper used an extensive behavioural study with rats to evaluate how the probability and magnitude of outcomes impact preference. The paper, however, provides limited evidence for the conclusions because the design did not allow for the isolation of the rare, extreme events in choice. There are many confounding factors, including the outcome variance and presence of less-rare, and less-extreme outcome in the same conditions.

Strengths.

(1) The major strength of the paper is the significant volume of behavioural data with a reasonable sample size of 20 rats.

(2) The paper attempts to examine losses with rats (a notoriously tricky problem with non-human animals) by substituting time-outs as a proxy for losses. This allows for mixed gambles that have both gain and loss possible outcomes.

(3) The paper integrates both a behavioural and a modelling approach to get at the factors that drive decision-making.

(4) The paper takes seriously the question of what it means for an event to be rare, pushing to less frequent outcomes than usually used with non-human animals.

Weaknesses:

(1) The primary issue with this work is that the primary experimental manipulation fails to isolate the rare, extreme events in choice. As I understand the task, in all the conditions with a rare extreme event (e.g., 80 pellets with probability epsilon), there is also a less-rare, less-extreme event (e.g., 12 pellets with probability 5). In addition, the variance differs between the two conditions. So, any impact attributable to the rare, extreme event could be due to the less rare event or due difference in the variance (or other statistical moments, like skew or kurtosis). That the distributions can be shown to be different under specific assumption to value maximizing agents (e.g., with Jensen Gaps and Table 2) is not really relevant to what rats are sensitive and what drive their behaviour. The design here does not support the conclusions. Finally, by deliberately confounding rarity and extremity, the design does not allow for assessing the impact of either aspect on rat behaviour.

(2) The RL modelling work also fails to show a specific impact of the rare extreme event. As best as I can understand Eq 2, the model provides a free parameter that adds a bonus to the value of either the two options with high-variance gains (A and V in the paper) or to the two options with high-variance losses (F and V in the paper). Or equivalently to the ones with "Jackpots" vs the ones with "Black Swans" (see Point 1 above as to how these different aspects are all confounded in this design). This parameter seems to only depends on whether this option could have possibly yielded the rare, extreme outcome (i.e., based on the generative probability) and was not connected to its actual appearance. [This point is unclear as the text says this, but the rebuttal states otherwise; plus some options never received the REE, see Table S11]. That makes it a free parameter that just bumps up (or down) the probability of selecting a pair of options. That may be due to presence of the REE or the other rare event or just the variance difference. Moreover, in the case of the "black swan" or high-variance loss conditions, this seems very much like a loss aversion parameter, but an additive one instead of a multiplicative one. Is there a theoretical claim here that "extreme losses" need an additive loss-aversion parameter?

(3) The paper presented the methods and results with lots of neologisms and fairly obscure jargon (e.g., fragility, total REE sensitivity). That might it very hard to decipher exactly what was done and what was found. For example, on p. 4, the use of concave and convex was very hard to decipher; the text even has to repeat itself 3 times (i.e., "to repeat" and "in other words") and is still not clear. It would be much clearer (and probably accurate) to say that the options varied along the variance dimension, separately for gains and losses. Option A was low-variance gains and losses. Option B was low-variance losses and high-variance gains. Option C was high-variance losses and low-variance gains, and Option D was high-variance losses gains. That tells much more clearly what the animals experienced without the reader having to master a set of new terminologies around fragility and robustness, which brings a set of theoretical assumption unnecessarily into the description of the experimental design. Alternatively, if the authors are wary of using the term "variance" because other moments of the distribution also differ, they could use "high-value gains" or "high-value losses" or something else which does not obscure the experimental design with jargon. Again, this goes back to point 1 above, whereby the different options differ on so many dimensions (as is made even more apparent in the rebuttal) that the design cannot isolate the impact of the variables of interest.

(4) Were the probabilities shuffled or truly random (seem to be fixed sequences, so neither)? What were the experienced probabilities? Given the fixed sequences, these experienced ("ex-post") probabilities, could differ tremendously from the scheduled ("ex ante") probabilities. It's quite possible than an animal never experienced the rare, extreme event for a specific option. From Table S11, that is guaranteed to have happened in that 4 animals only ever experienced the "black swan" outcome once. It's even possible (if they only picked a specific option on the 10th/60th choices by chance), that they only ever experienced that rare extreme event. This point still cannot be known given the information provided, which does not break down outcomes by options. The Supplemental in Table S11 only gives overall numbers but does not indicate what the rats experienced for each choice/option-which is what matters here. A simple table that indicates for each of the 4 options, how often they were selected, and how often the animals experienced each of the 6-8 possible outcome would make it much clearer how closely the experience matched the planned outcomes. In addition, by restricting the rare outcome to either the 10th or 60th activations in a session, these are not random. Did the animals learn this association? The text states that they did not, but no evidence is provided.

(5) The choice data are generally presented in an overprocessed fashion with a sum and a difference (in both figures and tables). The basic datum (probability/frequency of selecting each of the 4 options) is not provided directly in the main text, even if it can theoretically be inferred from the sum and the difference. New right side of Table S4 is probably the most valuable piece in terms of explaining what rats did and should be highlighted a lot more. Inspection of that table reveals some interesting (and potentially worrying) results. Most notably, the vast majority of responding happens on the "anti-fragile" and "robust" option, often totalling around 90% of all selections, especially amongst the most common blue rats. Alas, those were all those the two options that were deliberately assigned to the two most preferred holes in the training phase (see p. 26). Does this reflect genuine preference for reward distributions or does this reflect a spatial hole bias? The assignment strategy makes this impossible to tell apart.

(6) There is insufficient detail provided on the inferential statistical tests (e.g., no degrees of freedom or effect sizes), and only limited information on exactly what tests were run and how (bootstrapping, but little detail). Without code or data (only summary information is provided in the supplement), this is difficult to evaluate. In addition, the studies seem not to pre-registered in any way, leaving many research degrees of freedom. Not all studies need to be pre-registered and sometimes discovery of new things requires exploratory work, but preregistration does provide additional safeguards against overemphasizing post-hoc detected patterns-a serious issue in behavioural science. Moreover, this promotes transparency in reporting results and analyses, allowing for a better assessment of the strength of evidence for a claim. For example, here, were any alternative analysis pipelines attempted? Also, there were many sub-groupings of the animals and subsequent comparisons between them which all seemed post-hoc. On what grounds were these divisions made-were other divisions examined as well?

(7) On p. 12 (Fig 4), there is an attempt to look at the impact of a rare, extreme event by plotting a measure of preference for the 10 trials before/after the rare, extreme event. In the human literature, the main impact of experiencing a rare, extreme event is what is known as the wavy recency effect (See Plonsky et al. 2015 in Psych Review for example, now cited). What this means is that there tends to there tends to be some immediate negative recency (e.g., avoiding a rare gain) followed by positive recency (e.g., chasing the rare gain). Typically, this refers to the specific option that yielded that outcome. First, as the other analyses do, the current analysis combines choice of the option that yielded the rare outcome with choice of other options, so that cannot directly assess the impact of the rare, extreme event on choice. Also, using a 10-trial window would thus obscure any impact of this rare, extreme event. There is mention of the very next trial, but an analysis that looks at the 10-trial time course trial-by-trial could reveal any impact that might be predicted from the human literature.

(8) As I understood the method (p. 31), the assignment of options to physical locations was not random or counterbalanced, but deliberately biased to have one of the options in the preferred location. This would seem to create a bias towards a particular option and a bias away from the other options, which confounds the preference data in subsequent analyses. Table S4 reinforces this concern where the vast majority of response are clustered in the two most preferred options from training.

(9) Are delays really losses? This is a big assumption. Magnitude and delay are different aspects of experience, which are not necessarily commensurable and can be manipulated independently. And, for the model, how were these delays transformed into outcomes for the model. Eq 1 skips over that. Is there an assumption of linearity? In addition, I was not wholly clear if the delays meant fewer trials in a session or if the delays merely extended the session and meant longer delays until the next choice period.

Other points:

(1) I think the authors still misunderstand the concept of "hot-stove effects". The idea is that the experience of a very bad outcome can lead to avoiding the situation again (i.e., not sampling that option) and can provide the appearance of oversensitivity to that bad outcome. Here, that might be more thought as "black-swan avoidance". Imagine if, to the rat, all options are equal in value, then some initial bad luck in encountering the black swan might make the animal avoid that option, even though with enough experience, then it would have been equal in value.

(2) I am still not convinced that the Jensen inequalities add to this paper in terms of understanding the rat behaviour. That may be more suited for a different paper about the statistical and mathematical properties of certain generative distributions, but not here given what rats actually choose and experience.

(3) Providing the data open access is very good. The code, however, should be equally available and not just upon request. Code needs to be available for assessment during peer review and for reproducibility checks. There are substantial enough problems with reproducibility in the field that code availability should be a minimum criterion for publication (see Miske et al., 2026 in Nature for the most recent large-scale evaluation of this problem).

(4) The paper still somewhat mischaracterizes the literature on rare events, posing it as a series of "exceptions", rather than recognizing that a huge chunk of the literature uses rare events rarer than 10%. Also, there is even existing terminology in that literature for exactly the situation that is being created here-rare treasures (aka jackpots here) and rare disasters (aka Black Swans here).

(5) Defining the observed behaviour in terms convexity, instead of stating choices more plainly obscures what is done/found. This is especially the case here because convex and concave mean different things when applied to gains/losses in terms of whether or not that option can lead to the REE. The use of the terms obscures rather than clarifies and probably is best left for the discussion (and maybe the intro) when mapping from theoretical distributions to the experiment at hand. In the paper, even the bottom of p.5 seems to incorrectly define "Total Sensitivity" as the combined proportion of selecting convex options in either domain, which does not map how convex is defined in Fig 1B or elsewhere in the text.

(6). Fig 1C is baffling. Why are probabilities drawn moving away from the origin? The standard scientific plotting convention is for numbers to grow when moving away from the origin. That would be vastly clearer. Also, the color coding is confusing. Green-red maps onto convex-concave, but that would naturally seem to indicate gains vs losses, not convex vs concave. And why are probabilities growing larger in both directions from the origin? Much more sensible to communicate the procedure would likely be a standard plot of magnitude vs probability.

(7) Discussion: I think the main difference between the human situations discussed and this experiment is that humans have not experienced those rare "black swan" outcomes. Rather, they hear about the disasters that are possible and do not incorporate that information, as discussed in the description-experience literature already cited in this paper (though not in that context).

Reviewer #1 (Public review):

I read this paper with great interest based on my experience in insect sciences. Previous concerns:

(1) The paper has an original biological question that is overly broad and mechanistically ambitious. The central biological question, namely how CLas infection enhances fecundity of Diaphorina citri via dopamine signaling, is clearly stated and well motivated by previous literature. However, my advice to the authors is that, while the general question is clear, the manuscript attempts to answer multiple mechanistic layers simultaneously. As a result, I feel that the biological narrative becomes diffuse, especially in later sections where DA, miRNA regulation, AKH signaling, and JH signaling are all proposed as parts of a single linear cascade. In summary, my key concern is that the paper often moves from correlation to causal hierarchy without fully disentangling whether these pathways act sequentially, in parallel, or redundantly. A more explicitly framed primary hypothesis (e.g., "DA-DcDop2 is necessary and sufficient for CLas-induced fecundity") may improve conceptual clarity.

(2) On the novelty of the data, I feel they are moderately novel, with substantial confirmatory components. If I am correct, the novel contributions include the identification of DcDop2 as the DA receptor responsive to CLas infection in D. citri, the discovery that miR-31a directly targets DcDop2, which is supported by luciferase assays and RIP, and thirdly, the integration of dopamine signaling into the already-described CLas-AKH-JH-fecundity framework. My advice to the authors is to focus more on the manuscript's novelty, which lies more in pathway integration than in discovering fundamentally new biological phenomena. This is appropriate for a mechanistic paper, but should be framed as an extension of existing models rather than a paradigm shift.

(3) On the conclusions, I recommend that the authors modify their statements a little. I feel that there are some overstated or insufficiently supported claims. For instance, the assertion that CLas "hijacks" the DA-DcDop2-miR-31a-AKH-JH cascade implies direct pathogen manipulation, but no CLas-derived effector or mechanism is identified. Also, that the model suggests a linear signaling hierarchy, but the data largely show correlation and partial dependency rather than strict epistasis. In third, the term "mutualistic interaction" may be too strong, as host fitness costs outside fecundity (e.g., longevity, immunity) are not evaluated. In conclusion, I confirm that the data support a functional association, but mechanistic causality and evolutionary interpretation are somewhat overstated.

Comments on revised version:

The authors provided a satisfactory revision.

Reviewer #1 (Public review):

(1) In this study, the authors aimed at characterizing Huntington's Disease (HD) - related microstructural abnormalities in the basal ganglia and thalami as revealed using Soma and Neurite Density Imaging (SANDI) indices (apparent soma density, apparent soma size, extracellular water signal fraction, extracellular diffusivity, apparent neurite density, fractional anisotropy and mean diffusivity).

(2) The study implements a novel biophysical diffusion model that extends up-to-date methodologies and presents a significant potential for quantifying neurodegenerative processes of the grey matter of the human brain in vivo. The authors comment on the usefulness of this technique in other pathologies, but they exemplify only with multiple sclerosis. Further development of this, building evidence should be provided.

(3) Study found that HD-related neurodegeneration in the striatum accounted significantly for striatal atrophy and correlated with motor impairments. HD was associated with reduced soma density, increased apparent soma size and extracellular signal fraction in the basal ganglia, but not in the thalami. Additionally, these affects were larger at manifest stage.

(4) The results of this work demonstrate the impact of HD on basal ganglia and thalami which can be further explored as a non-invasive biomarker of disease progression. Additionally, the study shows that SANDI can be used to explore grey matter microstructure in a variety of neurological conditions.

Comments on revised version.

I have no further comments. Thank you

Reviewer #1 (Public review):

Integrating large-field stimulation with a retinotopic atlas, this study introduces an fMRI-based method for measuring contrast sensitivity across the visual field. Retinotopy was assessed using pRF mapping and a calibrated Benson atlas. The authors validate their method by replicating known patterns of contrast sensitivity across eccentricities and visual field quadrants in healthy subjects, and demonstrate its potential clinical utility through case studies of both simulated and real visual field loss.

Comments on revisions:

I appreciate the addition of the quadrant-scotoma condition and the authors' clarification that the goal is to demonstrate individual-level detection sensitivity. The 95% CI argument is reasonable, and I am satisfied with framing the simulated-scotoma work as proof-of-concept.

Reviewer #1 (Public review):

Summary:

In this study, the authors aim to characterize how moment-to-moment fluctuations in arousal during wakefulness shape large-scale functional brain connectivity. Using pupil diameter as an index of arousal and high-field functional imaging, they seek to determine whether arousal-related modulation of connectivity is uniform across the brain or organized into structured patterns, and whether such patterns show hemispheric asymmetry. The work further aims to assess whether these organizational features generalize across resting-state and naturalistic viewing conditions.

Strengths:

The study addresses an important and timely question regarding how spontaneous variations in arousal influence whole-brain communication during wakefulness. The dataset is rich, combining high-field imaging with concurrent physiological measurements, and the analyses are ambitious in scope. A key strength is the attempt to move beyond region-based effects and to describe arousal-related modulation at the level of large-scale connectivity organization. The comparison across rest and movie viewing provides useful context and suggests a degree of consistency across behavioral states.

Weaknesses

All analyses are based on 7T ultra-high-field imaging. The manuscript does not address whether the reported arousal-related patterns, including the community structure and hemispheric asymmetries, are expected to be reproducible at standard 3T field strengths. It therefore remains unclear whether the findings depend critically on the use of high-field data or whether they would generalize to more widely available datasets, limiting the broader applicability of the results.

Reviewer #1 (Public review):

This is an excellent paper from Dr. Yokoyama and colleagues. The experiments are technically demanding, given the very low cell numbers and the challenges of working with implantation sites at gestational days 6.5, 10.5, and 14.5. Overall, the impact of TGF-β receptor II deficiency in the NK lineage on uterine trNK cell numbers and litter size is convincing, and the authors' conclusions are well supported by the data. Less convincing, however, is the claim that the decrease in trNK cells is compensated by an increase in cNK cells; rather, the absence of TGF-β receptor II appears to result in an overall reduction of NK/ILC1 cells.

Comments on revised version:

I thank the authors for addressing all my comments from my initial review.

Reviewer #1 (Public review):

Intron retention is observed in many long noncoding RNAs. The authors here used a powerful genome-wide screening strategy to identify proteins controlling intron retention in the long noncoding RNA PURPL. One of the top hits across multiple cell lines surprisingly, was U2AF2, which is well known to bind the polypyrimidine tract close to the 3' splice site to promote splicing. Nonetheless, U2AF2 is working in the opposite direction here. Convincing follow-up RT-PCR experiments confirmed that knocking down U2AF2 does indeed lead to reduced intron retention of PURPL. The authors then show that this intron retention event is functionally important for both the nuclear retention of PURPL as well as its ability to enhance cell proliferation.

The authors then used transcriptome-wide analyses to look for additional intron retention events affected by U2AF2. Among the ~250 genes with decreased intron retention (more splicing) upon U2AF2 knockdown was MALAT1, a well-established long noncoding RNA that normally localizes to nuclear speckles. Depletion of U2AF2 or removal of the MALAT1 2nd intron resulted in reduced speckle localization and cell migration, revealing a critical and fascinating role for this intron retention event. Overall, the authors have used a set of complementary approaches to clearly demonstrate a very intriguing role for U2AF2 in controlling intron retention and functionality of a set of long noncoding RNAs.

I feel the current work has revealed an important role of intron retention in controlling the localization and functionality of long noncoding RNAs, which is likely broad in scope and is likely regulated by cell state.

One experimental suggestion: The authors show that expressing intron-2 containing PURPL in PURPL-depleted cells is sufficient to induce faster proliferation, but a valuable comparison would be identifying the phenotype expressing spliced PURPL transcript.

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 authors generated mouse and zebrafish models for DeSanto-Shinawi Syndrome, caused by loss-of-function variants in the WAC gene. Using these vertebrate systems, they demonstrate conserved craniofacial and social-behavioral phenotypes that parallel human clinical features, along with deficits in GABAergic markers. They observe increased seizure susceptibility and male-biased brain volumetric changes in Wac mutant mice. Together, these findings begin to define the biological consequences of Wac haploinsufficiency and provide valuable resources for future mechanistic studies.

Strengths:

WAC is a high-confidence neurodevelopmental disorder gene and one of the genes identified by large-scale exome sequencing efforts, including the Satterstrom et al. (2020) autism spectrum disorder cohort. This study establishes the first vertebrate Wac models, addressing a major gap in the understanding of DeSanto-Shinawi Syndrome, and provides a framework for studying other syndromic forms of autism. The models generated will be impactful and useful to the community to study and understand DeSanto-Shinawi Syndrome.

The cross-species analysis is important and well executed, and reveals both conserved and divergent phenotypes. The behavioral and anatomical assays are rigorously executed and well-controlled, and the inclusion of RNA-sequencing analyses adds valuable insights into the mechanisms underlying brain function in Wac mutants. Notably, the RNA-seq data reveal upregulation of several clustered protocadherins, genes central to neuronal identity and cell-cell interactions, which are known to be regulated by dynamic developmental regulation of chromatin architecture. This observation provides an intriguing hint that could link Wac function to higher-order chromatin organization and neuronal connectivity.

Weaknesses:

The evidence is solid, though the study remains incomplete in its mechanistic depth and molecular interpretation. The authors compellingly describe behavioral, anatomical, and transcriptomic phenotypes associated with WAC loss, yet do not explore how WAC mechanistically regulates chromatin or transcription. Given prior evidence that WAC interacts with the RNF20/40 ubiquitin ligase complex and promotes histone H2B ubiquitination and transcriptional elongation, the paper would benefit from a discussion of these functions as a potential link between Wac haploinsufficiency and the observed changes in neuronal gene expression. Similarly, the authors mention WAC's WW and coiled-coil domains but do not consider how these domains could mediate nuclear interactions or recruitment of transcriptional cofactors that shape gene regulation and chromatin organization in neurons.

The transcriptomic analysis is rich but largely descriptive. Although the upregulation of clustered protocadherins is particularly intriguing, these findings are not validated or localized to specific neuronal populations. The study would be strengthened by independently validating the most significant RNA-seq changes, such as protocadherin gamma genes, using in situ hybridization methods to confirm the spatial and cellular specificity of expression changes.

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 behaviour of cells expressing constitutively active HRas is examined in mosaic monolayers, both in MCF10a breast epithelial and Beas2b bronchial epithelial cell lines, mimicking the potential initial phase of development of carcinoma. Single HRas-positive cells are excluded from MCF10a but not Beas2b monolayers. Most interestingly, however, when in groups, these cells are not excluded, but rather sharply segregated within a MCF10a monolayer. In contrast, they freely mix with wt Beas2b cells. Biophysical analysis identifies high tension at heterotypic interfaces between HRas and wild-type cells as the likely reason for segregation of MCF10a cells. The hypothesis is supported experimentally, as myosin inhibition abolishes segregation. The probable reason for lack of segregation in the bronchial epithelium is to be found in the different intrinsic properties of these cells, which form a looser tissue with lower basal actomyosin activity. The behaviour of single cells and groups is recapitulated in a vortex model based on the principle of differential interfacial tension, under the condition of high heterotypic interfacial tension.

Strengths:

Despite being long recognized as a crucial event during cancer development, segregation of oncogenic cells has been a largely understudied question. This nice work addresses the mechanics of this phenomenon through a straightforward experimental design, applying the biophysical analytical approaches established in the field of morphogenesis. Comparison between two cell types provides some preliminary clues on the diversity of effects in various cancers.

Reviewer #1 (Public review):

Summary:

The authors address the lack of validated tools for the detection and quantification of proteins associated with amyotrophic lateral sclerosis (ALS) through an extensive screening of 303 commercially available antibodies to 33 protein targets. Their ALS-Reproducible Antibody Platform (ALS-RAP) delivers a validated antibody toolbox for ALS research, which will provide an advantageous starting point for researchers in this field. Ayoubi R. et al. showcase the characterization workflow, presenting as an example the characterization of antibodies targeting Galectin-1, encoded by the LGALS1 gene. A selection of these antibodies was also used to profile protein levels across human induced pluripotent stem cell (iPSC)-derived and primary neurological cell types, and the findings support that the ALS disease mechanism involves both neuronal and glial cells.

Strengths:

The knockout (KO)-based approach is definitely the major strength of this study, providing a high level of confidence in the data collected in human induced pluripotent stem cell (iPSC)-derived and primary neurological cell types. The focus on renewable reagents (monoclonal and recombinant antibodies) is also important. The extensive characterization of this set of antibodies will benefit any scientist interested in any of the 33 target proteins, even in fields other than neuroscience.

The authors perform an interesting protein profiling study assessing 27 proteins, comparing RNA and protein expression data, and using two independent WB preparations of the same cell types.

The conclusions that can be drawn from this first assessment might not be final, but the data are compelling because they have been collected with reliable and validated antibodies.

Another strength of this work is the data dissemination strategy, which includes the Only Good Antibodies (OGA) platform, where YCharOS data are curated and presented in an easy and intuitive manner that facilitates antibody selection by the end user for WB, IP and IF applications.

Weaknesses:

The authors mentioned the development of single-chain variable fragment (scFv) recombinant antibodies raised by the SGC against the six proteins (ANXA11, OPTN, MATR3, PFN1, UBQLN2 and VCP) that had limited renewable antibodies that are commercially available. The development was optimized to generate antibodies particularly suitable for IP, and the clone selection process was carried out using IP coupled to mass spectrometry. Even though the generation of these novel reagents is not the focus of this work, the authors do not provide any data on this aspect.

The protein profiling study is limited to WB data, and the authors did not provide any explanation on why there was no integration with IP and IF data, not even for those targets that have validated antibodies. Also, not all the cell types have been screened by chemiluminescence-based detection and by fluorescence-based WB, and the authors do not elaborate on the reason for such a choice.

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors reveal that the availability of extracellular asparagine (Asn) represents a metabolic vulnerability for the activation and differentiation of naive CD4+ T cells. To deplete extracellular Asn, they employed two orthogonal approaches: activating naive CD4+ T cells in either PEGylated asparaginase (PEG-AsnASE)-treated medium or custom-formulated RPMI medium specifically lacking Asn. Importantly, they demonstrate that Asn depletion not only impaired metabolic reprogramming associated with CD4+ T cell activation but also reduced CD4+ helper T cell lineage-specific cytokine production, thereby ameliorating the severity of experimental autoimmune encephalomyelitis.

The experiments presented here are comprehensive and well-designed, providing compelling evidence for the conclusions. The conclusions will be important to the field.

Comments on revised version:

The authors have sufficiently addressed my previous comments. The manuscript represents an excellent contribution to the field.

Reviewer #1 (Public review):

Summary:

In this study, the authors set out to define how arginine availability regulates lipid metabolism and to explore the implications of this relationship in pancreatic ductal adenocarcinoma (PDAC), a tumor type known to exist in an arginine-poor microenvironment. Using a combination of rigorous genetic and metabolomic approaches, they uncover a previously underappreciated role for arginine in maintaining lipid homeostasis. Importantly, they demonstrate that arginine deprivation sensitizes PDAC cells to ferroptosis through lipidome perturbations, which can be exploited therapeutically via co-treatment with aESA and ferroptosis inducers (FINs). These findings have meaningful implications for the field. They not only shed light on the metabolic vulnerabilities created by nutrient restriction in PDAC, but also suggest a practical avenue for combination therapies that exploit ferroptosis sensitivity. This is particularly relevant in the context of pancreatic cancer, which is notoriously resistant to conventional treatments. The methods employed are broadly applicable to other nutrient-stress contexts and may inspire similar investigations in other solid tumor types.

Strengths:

One of the major strengths of the study is the use of complementary and well-controlled approaches-including metabolomic profiling, genetic perturbations, and in vivo models-to support the central hypothesis. The experiments are thoughtfully designed and clearly presented, and the conclusions are, for the most part, well supported by the data. The findings provide mechanistic insight into nutrient-lipid crosstalk and identify a potential therapeutic strategy for targeting arginine-deprived tumors.

Comments on revised version:

The authors have substantially strengthened the revised manuscript and have addressed my prior concerns, and the evidence supports the central conclusions. This work provides meaningful insight into how nutrient limitation in the tumor microenvironment creates metabolic liabilities that may be therapeutically exploited, and it should be of interest to investigators studying cancer metabolism, pancreatic cancer, lipid biology, and ferroptosis.

Reviewer #1 (Public review):

Summary:

This study investigates how two closely related fish species differ in their processing of visual motion, with a focus on spatial and temporal integration underlying behavior. Using a series of behavioral assays combined with computational modeling, the authors identify clear species-specific differences in how visual information is integrated to guide movement.

Strengths:

A major strength of the work is the systematic and quantitative behavioral analysis, which reveals robust differences between species, including broader spatial integration and longer temporal persistence in medaka compared to zebrafish. The decomposition of behavior into distinct components provides a useful framework for interpreting these differences.

Weaknesses:

The computational modeling captures several key aspects of the observed temporal dynamics, particularly differences in response persistence. However, the modeling framework is primarily focused on temporal processing and does not incorporate spatial integration, which is a central finding of the study. In addition, some experimental observations, such as responses to short-duration stimuli and certain frequency-dependent features, are only partially reproduced. These limitations indicate that the link between the model and the full range of behavioral results remains incomplete.

Reviewer #1 (Public review):

Summary:

This paper presents rare and unique recordings of single neurons, LFPs, and SEEG data from human patients performing reading and listening tasks. They identify single neurons in temporal and ventral occipito-temporal cortex that respond specifically to spoken and written language, and primarily encode either phonological or orthographic features of the stimuli. They also identify neurons in the middle temporal and inferior frontal cortex that respond to both modalities, which they interpret as amodal language responses. In general, neuronal population firing rates are correlated with both micro- and macro- scale broadband gamma responses, though they observe some dissociations, particularly with the macro-scale. The results are interpreted to support a model of modality-specific to amodal processing throughout many distributed brain areas for language.

Strengths:

(1) The data are truly unique, providing a large-scale characterization of single neuron responses from the human brain during written and spoken language processing.

(2) The task and stimulus conditions allow for examination of both low-level (e.g., orthographic/phonological) and higher-level (e.g., syntactic) encoding.

(3) Showing relationships between single neuron and multi-scale LFP recordings from the same sites helps bridge neuronal and meso/macroscale literatures.

Weaknesses:

(1) My main comment about the paper is that it feels like a collection of somewhat random descriptions of a very small number of hand-picked single neurons. I think that the task and stimulus design shown in Figure 1A sets up some clear hypotheses that could be tested rigorously across the full neuronal population, but instead, the authors pick a few neurons and fit encoding models that don't take advantage of the contrasts. I agree that encoding models are a powerful approach, but with only 508 total words and what appears to be a limited set of variability across the various features, it's not clear to me that the stimuli, which were apparently designed as minimal pairs, provide enough power to find robust results. Perhaps this is why the majority of the results only show a very small number of units (most of which are actually buried in the supplement), but it's odd to me that they don't show the results of the minimal contrasts other than for length.

(2) Related to point (1), other than Figure 2H and Figure 6A-B, the results are only shown for a tiny number of units. This is great for demonstrating qualitatively what the effects look like, but there is no quantification of the findings across the population, which undermines the point in the abstract that 1000 neurons were recorded. This is acknowledged in some places, but as a reader, it leaves me wondering how seriously to take the interpretations if they seemingly cannot be replicated. I understand this is a challenge with human single neuron recordings, but as presented, the paper as a whole comes across as largely anecdotal.

(3) Some of the key claims rest on the idea that neurons were recorded from the superior temporal gyrus and fusiform gyrus. For the STG claim, I don't understand how this was done, or what specifically they mean by STG, since the microwire locations do not appear to be anywhere near the lateral surface. This makes sense given the profile of the Behnke-Fried electrodes, but if they want to claim that there are neurons from the STG, they need to be more specific and show where precisely these wires are. If they are more medial as it appears, they need to explain how they dissociated STG from Heschl's gyrus. Similarly, for the fusiform neurons, I can only see a couple of probes that appear to have their tips near where I would think this area is. Perhaps this is more of a visualization issue with Figure 1F, but overall, I am not convinced that the neurons are exactly where they say they are.

(4) Related to point (3), some of the authors have made strong claims in prior work about the precise coordinates of the VWFA, so it would help to know how many units are within this exact region. The ROIs marked in Figure 2 are quite large, and given results like Vinckier et al. 2007, it's important to know where along the hierarchy the recordings were actually performed. Similarly, given the framing in the intro around the VWFA as a key area, the idea that some of the best example neurons are from the right fusiform is a bit confusing. I don't think they can make the claims about visual hemifields since it does not appear that they recorded eye tracking to verify constant central fixation, and it may be a bit surprising to see such strong orthographic selectivity in the right hemisphere (though, as a result, it may suggest a more nuanced view of lateralization of reading at the single neuron.

(5) In many sections of the paper, there are vague and unquantified claims like "many neurons" or "a large number of units". This needs to be made explicit. It would also help to show where statistical threshold cutoffs are on plots like Figure 2H, since the "brain-score" is used to select units for many analyses.

(6) More detail on the TRF models is needed in the methods. At the very least, a complete list of the features in each group is necessary to evaluate claims about very broad sets of features like "syntax". It would also help to know how the features were coded, especially where there is a mixture of continuous and discrete features within the model.

(7) Depending on how exactly the features were defined, I'm skeptical of some of the claims, like position-specific "w". There are some obvious confounds that need to be controlled here, like whether word-initial "w" is strongly associated with shorter, higher frequency words (like "wh-" words). There are other examples, like whether specific forked letters tend to appear in certain syllables in English words. While it may be the case that these kinds of patterns are uniformly distributed, it needs to be established in this particular stimulus set.

(8) The claim that there is monotonic encoding of word length does not seem strongly supported in the data. In both PC1 and the single neuron examples, it seems like there may be a non-linear relationship, which could suggest that another correlated feature (e.g., word frequency) is involved.

Minor Points:

(1) What are "boundaries"? They are not described anywhere I could find, but they are a feature group that was used in the TRFs. )

(2) The caption for Figure 6C says MTG and insula, but the text says MTG and IFG. Similar to the above comment about STG and fusiform, it's not clear to me how they achieved single-unit recordings with Behnke-Fried probes in these areas.

(3) The somewhat less robust correlations between firing rate and BGA in macro vs micro contacts are potentially interesting. However, did they verify that the closest macro contact was always in the gray matter of the same gyrus as the microwire?

Reviewer #1 (Public Review):

The medial reticular formation (MRF) in the brainstem has long been implicated in the regulation of locomotion. One common - albeit very simple - model often presents the MRF as a major relay station receiving inputs from MLR circuits, among other brain regions, that together convey locomotor signals through efferent projections targeting the caudal brainstem and the spinal cord. Yet, the MRF is a particularly large brain area whose cellular complexity is far from understood. How molecularly distinct MRF ensembles contribute to the regulation of locomotor behaviors is largely unknown. Here, the authors apply focal activation of either glutamatergic, GABAergic, or serotonergic neurons throughout the MRF using a chemogenetic gain-of-function approach to uncover the putative modulatory properties of these neuronal ensembles during walking. Using kinematic analysis of mice limbs during self-paced over-ground walkway locomotion, the authors find that activation of GABAergic MRF neurons can selectively slow down walking, whereas activation of glutamatergic neurons can induce a specific "shuffle" limb trajectory, altogether revealing that distinct MRF populations may retain the capability to engage divergent walking signatures, whose behavioral relevance are not yet clear. In contrast, the activation of serotonergic neurons did not affect walking signatures as described for the other two subgroups but led to an increase of locomotor speed. Interestingly, MRF neurons in each regional activation "hotspots" appear to target different domains in the lumbar spinal cord, suggesting that distinct circuit mechanisms are at play for the slowmo vs shuffle effects.

Major points:

1. While the experiments are carefully done and the results are well analyzed and clearly presented in a series of beautiful figures, several aspects of the methodology remain very confusing. In particular, the initial choice for the injection coordinates is not justified and the authors don't leverage the mapping of spinal projection neurons to drive their chemogenetic screen. Similarly, the authors group very different injection schemes (unilateral or bilateral targeting of MRF neurons), that should be analyzed separately. The choice of Z score cutoff that dictates the in-depth analysis of the chemogenetic phenotypes appears arbitrary and is not grounded in a set of objective criteria.

2. One issue that arise from the work presented here is that we don't know if these MRF neurons are active during locomotion in normal, unperturbed conditions. Knowing the recruitment profile of these MRF neurons would clarify whether the chemogenetic activation boosts the firing of neurons that are already active during walking, or activate neurons that are otherwise silent. Disentangling between these possibilities may have a profound impact on the overall interpretation of the results.

3. The results should be discussed in the broader context of historic stimulation experiments, notably in cats and other species, as well as more recent circuit mapping approaches in rodents. For instance, the notion that focal stimulation of distinct area within the MRF can elicit or modify the pattern of locomotion is not really new, so is the notion that some of these modulations are phase-specific and can influence the duration of single muscle activation during stance or swing phases. This last point has for instance already been assessed through individual muscle recordings paired with MRF stimulation in cats. Perhaps better introducing these key studies and a thorough discussion of what the results presented in this manuscript bring in terms of novelty will help readers ground this work into a more comprehensive and larger body of work.

Reviewer #1 (Public review):

Summary:

The authors considered the mechanism underlying previous observations that H2A.Z is preferentially excluded from methylated DNA regions. They considered two non-mutually exclusive mechanisms. First, they tested the hypothesis that nucleosomes containing both methylated DNA and H2A.Z might be intrinsically unstable due to their structural features. Second, they explored the possibility that DNA methylation might impede SRCAP-C from efficiently depositing H2A.Z onto these DNA methylated regions.<br /> Their structural analyses revealed subtle differences between H2A.Z-containing nucleosomes assembled on methylated versus unmethylated DNA. To test the second hypothesis, the authors allowed H2A.Z assembly on sperm chromatin in Xenopus egg extracts and mapped both H2A.Z localization and DNA methylation in this transcriptionally inactive system. They compared these data with corresponding maps from a transcriptionally active Xenopus fibroblast cell line. This comparison confirmed the preferential deposition or enrichment of H2A.Z on unmethylated DNA regions, an effect that was much more pronounced in the fibroblast genome than in sperm chromatin. Furthermore, nucleosome assembly on methylated versus unmethylated DNA, along with SRCAP-C depletion from Xenopus egg extracts, provided a means to test whether SRCAP-C contributes to the preferential loading of H2A.Z onto unmethylated DNA.

Strengths:

The strength and originality of this work lie in its focused attempt to dissect the unexplained observation that H2A.Z is excluded from methylated genomic regions.

Weaknesses:

The study has two weaknesses. First, although the authors identify specific structural effects of DNA methylation on H2A.Z-containing nucleosomes, they do not provide evidence demonstrating that these structural differences lead to altered histone dynamics or nucleosome instability. Second, building on the elegant work of Berta and colleagues (cited in the manuscript), the authors implicate SRCAP-C in the selective deposition of H2A.Z at unmethylated regions. Yet the role of SRCAP-C appears only partial, and the study does not address how the structural or molecular consequences of DNA methylation prevent efficient H2A.Z deposition. Finally, additional plausible mechanisms beyond the two scenarios the authors considered are not investigated or discussed in the manuscript.

Comments on revisions:

The authors have addressed all previously raised concerns and propose a revised version of the manuscript. Notably, the abstract and discussion sections have been improved, and new experimental data have been incorporated. Collectively, these revisions enhance the rigor and clarity of the data interpretation and discussion.

Given these improvements, this reviewer believes that the manuscript could be published, particularly if this publication is accompanied by the critical points discussed in the rebuttal letter.

Reviewer #2 (Public review):

Summary:

This is a laudable effort to help dissect the contributions of type I and type III IFNs to the antiviral response in chicken and therefore represents an important piece of work, not least in the light of birds being a key carrier and worldwide distributor of influenza virus. The first part of the study characterises the generation of IFNAR and IFNLR KO chicken strains and describes basic differences. Four different viruses are then tested in chicken embryos, while the subsequent analysis of the antiviral response in vivo is performed with one influenza H3N1 strain.

Strengths:

Having these two KO chicken strains as a tool is a great achievement. The initial analysis is solid. Clear effect of IFNAR deficiency in in vivo infection, less so for IFNLR deficiency.

Weaknesses:

(1) The antibody induction by KLH immunisation: We still don't know whether or not this vaccination induces IFN responses in wt mice, so it is still not possible to judge whether the effects observed are due to steady-state differences or to differential effects of IFN induced during the vaccination phase. Pre-immune results are now shown and are indeed zero. As suggested, the whole figure 4 is now condensed into one or two panels by proper calculation of Ab titers - would these titres be significantly different? This as all of the other in vivo experiments have not been repeated if I understand the methods section correctly. I understand that there are three R restrictions that are tighter in some countries, and I accept that with the numbers used here, some statistical significance is reached, but this is for instance not the case for survival.

(2) The basic conundrum here and in later figures is now addressed by the authors in the discussion: Situations where IFN type 1 and 3 signalling deficiency each have an independent effect (i.e. fig.4d) suggest that they act by separate, unrelated mechanisms. However, all the literature about these IFN families suggest that they show almost identical signalling and gene induction downstream of their respective receptors. How can the same signalling, clearly active here downstream of the receptors for IFN type 1 or type 3, be non-redundant, i.e. why does the unaffected IFN family not stand in? The mouse studies, which showed a rather subtle phenotype when only one of the two IFN systems was missing, but a massive reduction in virus control in double KO mice, are discussed, but a clear-cut explanation for the differences has not been reached. Reasons could be a direct effect of IFNab on B cells and an indirect effect of IFNL through non-B cells, timing issues, and many other scenarios can be envisaged. The authors do not address this question experimentally, which limits the depth of analysis, they have however now included a discussion of this dilemma.

(3) In the one in vivo experiment performed with chickens, only one virus tested, more influenza strains should be included as well as non-influenza viruses. I appreciate that this is logistically difficult.

(4) The basic conundrum of point 2 applies equally to Fig. 6a, both KOs have a phenotype. Again, in 6d, both IFNs appear to be separately required for Mx induction. An explanation has been attempted, but more experiments, for instance looking at different time points to understand if we are dealing simply with different kinetics of the response, have not been attempted, despite the fact that such experiments are likely not covered by strict three R rules.

(5) The in vivo infection is the most interesting experiment, and the key outcome here is that IFN type 1 is crucial for anti-H3N1 protection in chickens, while type 3 is less impactful. However, this experiment suffers from the different time points when chickens were culled, so many parameters are impossible to compare (e.g. weight loss, histopathology). Some explanation is given as to the comparisons chosen here, but a more thorough analysis at several time points would have strengthened this study.

Comments on revised version:

In the rebuttal, the authors have gone to some length to add to the discussion of the experiments, and some aspects are better explained now than before. Many of these explanations remain speculative however, so the study remains inconclusive in several aspects. As no new data was added, my overall judgement of this study remains unchanged.

Reviewer #1 (Public review):

Summary:

Ducrocq et al. present research exploring the genetic link between simple multicellular group formation (ace2Δ/ace2Δ) and its interaction with cell-cycle progression mutants (e.g., cln3Δ/cln3Δ), demonstrating that this combination can provide fitness benefits during fluctuating resource conditions, resulting in a rapid increase in the fraction of multicellular cell-cycle mutants over unicellular yeast without selection for multicellular size. Because both the multicellular phenotype and the regulatory link enabling faster escape from the stationary phase are controlled by the ACE2 transcription factor, this work demonstrates that multicellular cluster formation can arise as a side effect of a completely independent fitness advantage unrelated to the benefits of group formation itself. As a "passenger phenotype," multicellularity could thus emerge for other selective reasons, potentially facilitating a later transition to more entrenched multicellularity if novel conditions arise that make multicellular group formation directly beneficial.

Importantly, while the literature generally assumes that multicellular group formation incurs a cell-level fitness cost, this work demonstrates that certain genetic - environmental interactions can confer fitness benefits even at the level of individual cells forming multicellular groups. This finding should inspire both theoretical and empirical work exploring multicellular group formation selected for benefits at the level of individual cells, rather than the benefits of forming a larger organismal size that most work has relied on so far.

Strengths:

This work is novel and exciting for research exploring the very first steps of the transition from unicellularity to simple multicellularity. The formation of multicellular groups is almost always assumed to come at a cell-level fitness cost due to reduced reproductive fitness compared to remaining unicellular, which generally needs to be outweighed by the benefits of multicellular group formation (e.g., large size to escape predation) for the multicellular phenotype to be stable. However, this study presents an interesting case of a genetic and environmental condition under which individual cells forming simple multicellular clusters can actually have higher reproductive fitness than solitary living yeast cells. This contrasts with previous snowflake yeast studies where the multicellular phenotype was primarily beneficial due to strong selection for large groups (rather than cell-level fitness gains).

The claims and interpretation of the results align well with the data presented. This is due to the careful and straightforward experimental design testing predictions with a clear, stepwise methodology. The authors rule out alternative explanations and provide support for the proposed link between the mutations (ace2, cln3, and others), their impact on faster exit from quiescence and earlier entry into reproduction in fresh media, and the resulting higher fitness in the snowflake yeast phenotype compared to unicellular yeast.

This experimental framework (combining cell-cycle mutants under the same multicellular background) is very much likely to be adopted by others in the community to explore downstream implications of these results in laboratory and environmental yeast isolates.

Weaknesses:

The authors show that the same multicellular phenotype with higher cell-level fitness due to faster exit from the stationary phase can also be observed with alleles found at other loci in non-laboratory yeast strains, implying that the results are likely not specific to a peculiar case genetically engineered in laboratory strains, but that similar phenotypes may be present in nature. However, this remains to be explored by examining the natural ecology of commercially available or wild yeast isolates and their genomes. This is not a weakness of this study per se, but rather a direction for future work. It does mean, however, that the relevance of these findings for early multicellularity in yeast, and even more so for nascent multicellularity in distinct taxa, remains to be explored in the future. Until then, it is difficult to make strong claims about how applicable these results would be for non-laboratory yeast and other taxa. Regardless, this work represents a very exciting finding.

Comments on revised version:

The authors addressed all concerns thoroughly.

Reviewer #1 (Public review):

Summary:

Morgan et al. studied how paternal dietary alteration influenced testicular phenotype, placental and fetal growth using a mouse model of paternal low protein diet (LPD) or Western Diet (WD) feeding, with or without supplementation of methyl-donors and carriers (MD). They found diet- and sex-specific effects of paternal diet alteration. All experimental diets decreased paternal body weight and the number of spermatogonial stem cells, while fertility was unaffected. WD males (irrespective of MD) showed signs of adiposity and metabolic dysfunction, abnormal seminiferous tubules and dysregulation of testicular genes related to chromatin homeostasis. Conversely, LPD induced abnormalities in the early placental cone, fetal growth restriction and placental insufficiency, which was partly ameliorated by MD. The paternal diets changed placental transcriptome in a sex-specific manner and led to a loss of sexual dimorphism in the placental transcriptome. These data provide a novel insight on how paternal health can affect the outcome of pregnancies, which is often overlooked in prenatal care.

Strengths:

The authors have performed a well-designed study using commonly used mouse models of paternal underfeeding (low protein) and overfeeding (Western diet). They performed comprehensive phenotyping at multiple timepoints including of the fathers, the early placenta and late gestation feto-placental unit. The inclusion of both testicular and placental morphological and transcriptomic analysis is a powerful non-biased tool for such exploratory observational studies. The authors describe changes in testicular gene expression revolving around histone (methylation) pathways that are linked to altered offspring development (H3.3 and H3K4), which is in line with hypothesised paternal contributions to offspring health. The authors report sex differences in control placentas that mimic those in humans, providing potential for translatability of the findings. The exploration of sexual dimorphism (often overlooked) and its absence in response to dietary modification is novel and contributes to the evidence-base for the inclusion of both sexes in developmental studies.

Comments on revised version:

The authors have done a great job addressing my concerns. The description of the data analysis and the figures are now much clearer. The inclusion of the potential links between the microbiome and male reproductive fitness is informative and improves the flow of the discussion.

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 manuscript, the authors employ diaphragm denervation in rats and mice to study titin-based mechanosensing and longitudinal muscle hypertrophy. By integrating bulk RNA-seq, proteomics, and phosphoproteomics, they map the stretch-responsive signalling landscape, uncovering robust induction of the muscle-ankyrin-repeat proteinsௗ(MARP1-3) together with enhanced phosphorylation of titin's N2A element.

Genetic ablation of MARPs in mice amplifies longitudinal fibre growth and is accompanied by activation of the mTOR pathway, whereas systemic rapamycin treatment suppresses the hypertrophic response, highlighting mTORC1 as a key downstream effector of titin/MARP signalling.

Strengths:

The authors address a clear biological question: "how titin-associated factors translate mechanical stretch into longitudinal fibre growth" using a unique and clinically relevant animal model of diaphragm denervation. Using a comprehensive multiomics approach, the authors identify MARPs as potential mediators of these effects and use a genetic mouse model to provide compelling evidence supporting causality. Additionally, connecting these findings to rapamycin, a drug widely used clinically, further increases the relevance and potential impact of the study.

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 influences 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 influences 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, is sometimes approached in unconvincing ways, and the results are not always evident to judge or interpret. Technically, the western blots and transcriptomic analyses require notable improvements.

Reviewer #1 (Public review):

Summary:

The manuscript has several strengths, including a technically comprehensive approach that combines mouse genetics, electrophysiology, live imaging in assembloids, and human organoid models, providing a rich and multifaceted dataset. Cross-species validation through the parallel use of mouse and human systems strengthens the generality of the observed phenotypes and increases relevance to human neurodevelopment.

Consistent phenotypic observations across systems show that ARHGEF6 loss affects migration, neurite morphology, growth cone structure, and neuronal survival, supporting a coherent role in cytoskeletal regulation.

There is clear evidence for developmental defects, including reduced interneuron numbers, increased apoptosis in the ganglionic eminences, and migration deficits, all well supported by quantitative analyses. Also, there is a high-quality electrophysiological characterization that demonstrates reduced firing in interneurons, providing a well-controlled functional phenotype.

Strengths:

The manuscript has several strengths, including a technically comprehensive approach that combines mouse genetics, electrophysiology, live imaging in assembloids, and human organoid models, providing a rich and multifaceted dataset. Cross-species validation through the parallel use of mouse and human systems strengthens the generality of the observed phenotypes and increases relevance to human neurodevelopment.

Consistent phenotypic observations across systems show that ARHGEF6 loss affects migration, neurite morphology, growth cone structure, and neuronal survival, supporting a coherent role in cytoskeletal regulation.

There is clear evidence for developmental defects, including reduced interneuron numbers, increased apoptosis in the ganglionic eminences, and migration deficits, all well supported by quantitative analyses. Also, there is a high-quality electrophysiological characterization that demonstrates reduced firing in interneurons, providing a well-controlled functional phenotype.

Weaknesses:

Despite the strengths mentioned above, the study has some conceptual and experimental weaknesses that reduce its impact. The mechanistic insight is limited, as the research does not directly establish how ARHGEF6 regulates downstream signaling pathways.

Also, there is insufficient evidence for interneuron specificity; although the central claim is that ARHGEF6 plays a selective role in interneurons, the data do not adequately exclude the possibility that the observed effects reflect broader neuronal defects. The study lacks critical controls across cell types, as several phenotypes observed in organoids and progenitors, including apoptosis, reduced neuronal output, and altered morphology, could also affect multiple neuronal populations without being directly tested. Furthermore, the data are predominantly descriptive, with many results remaining correlative and failing to establish causal relationships.

Some more comments:

(1) Given that ARHGEF6 is a guanine nucleotide exchange factor for Rac1 and Cdc42, the absence of direct measurements of GTPase activity or downstream signaling represents a significant gap. The interpretation that the observed phenotypes are mediated through specific cytoskeletal pathways, therefore, remains inferential.

(2) The manuscript repeatedly interprets the findings as interneuron-specific. However, several key observations are not demonstrated to be restricted to IN. Without direct comparison to excitatory neurons or other cell types, it is difficult to conclude that ARHGEF6 plays a selective role in interneurons rather than a more general role in neuronal development. The well-done analysis of the transcriptomic dataset is not sufficient to claim IN specificity. This issue is particularly important for the interpretation of the human organoid experiments, where reductions in SOX2⁺ progenitors and NEUN⁺ neurons, as well as increased apoptosis, could reflect global developmental defects. Similarly, in the mouse experiments, the reduction in GAD67⁺ cells is compelling, but it is not shown whether other neuronal populations are also affected.

(3) The study provides a strong phenotypic description but limited causal resolution. For example, migration defects, altered growth cone morphology, and reduced branching are all consistent with impaired cytoskeletal regulation, but the links between these phenotypes are not directly established. Likewise, while the electrophysiological data convincingly show reduced firing in interneurons, the connection between altered cytoskeletal dynamics and intrinsic excitability is not explored.

(4) Several aspects of data presentation could be improved. In multiple figures (e.g., Figure 1A, D; Figure 4 and Video S1, 2), the images are difficult to interpret due to high cellular density, limited magnification, or lack of clear annotation. In some cases, it is not fully clear how quantifications were performed or which regions were analyzed. Improving the visual clarity with arrows, boxes, and high-magnification inserts of the data would strengthen confidence in the conclusions.

Reviewer #1 (Public review):

A triple-transgenic (3xTgAD) mouse model of Alzheimer's disease was exposed to a high-fat diet and assigned to one of three interventions: voluntary physical activity, a low-fat diet, and their combination. A high-fat diet significantly increased body weight and induced widespread neuroanatomical changes, with effects modulated by sex and genotype. The combined intervention led to significant weight loss in males of both genotypes. Neuroanatomical analyses revealed that a high-fat diet significantly reduced hippocampal and cerebellar volumes in wild-type mice but had a less pronounced effect on 3xTgAD mice; nevertheless, interventions, particularly the combined approach, increased localized brain volumes in these regions regardless of genotype. Spatial gene enrichment analysis of this pattern identified glucose homeostasis. Overall, these findings suggest that voluntary physical activity and a low-fat diet can modulate brain structure and behaviour, partially counteracting the effects of a high-fat diet, and potentially recruiting biological processes that may support brain health.

The authors describe studies of the 3xTg mouse model of Alzheimer's disease (AD). They set out to study the interactions of diet and exercise on three outcomes: weight gain, MRI, and either the novel object recognition or Morris water maze tasks of memory.

They conclude there are sex and genotype effects on hippocampal volume.

There are several strengths to the study. First, they start out with a great deal of mice. Once they are divided into groups, the sample sizes are not always strong, however. It would be good to know that they were sufficiently powered.

The data are also interesting. Mice were placed on several different diets during the study, which will be of interest to many who question the role of diet in outcomes. They also add exercise as an intervention, and study not only diet but also the combined effect of diet and exercise. This is relevant to those interested in controlling dementia by diet and exercise. Finally, they perform some very interesting analyses to study the data.

That said, the study also has several limitations. For example, it is quite complex. Mice had a standard diet until 2 months of age, then were switched to either a low-fat or a high-fat diet. Some mice had both a different diet and exercise. MRI was performed at 2, 4, and 6 months, when behavior was tested. A drawback of this design is that no assessment of outcomes relevant to this animal model, such as amyloid-beta or tau phosphorylation, was conducted. Also, they used the novel object recognition task, despite stating in the Discussion that this task does not show impairments until well after 6 months of age. They added exercise, but it is not clear whether the animals used the exercise apparatus equally. Also, the animals were housed "communally", so adding an exercise wheel may have made the cage crowded, adding stress to the study. The diets were not simply low- or high-fat because many constituents besides fat content also changed. Regarding fat, the type of fat also changed between diets. Therefore, the gut microbiome was probably affected differently by factors other than fat intake. There was no measurement of food consumption, so some mice may not have eaten as much of the new diet as they did of the old diet they were used to.

Regarding the data, only the outcomes of complex analyses are shown. One would first want to see the changes in body weight and perhaps later how it is analyzed in a more complex way. For behavior, one would first want to see outcomes as typically presented. For example, learning, recall, platform test results from the Morris water maze, and discrimination indices for object recognition. Note that, at one point, I believe the authors note that some groups did not explore thoroughly, which would make novel object recognition hard to interpret. If there was any difficulty with ambulation, both tasks would be hard to interpret.

Regarding MRI, from what can be seen, structures cannot be distinguished clearly. At least some raw data should be shown to demonstrate this and to determine what the data show. The raw data suggest that some of the larger structures can be distinguished, and we should see the data for these areas, even if all areas can't be assessed. Lifestyle interventions can mitigate the effects of diet-induced obesity on body weight, behaviour, and brain anatomy in mouse models. Using a longitudinal design, wild-type and triple-transgenic (3xTgAD) mouse models of Alzheimer's disease were exposed to a high-fat diet and assigned to one of three interventions: voluntary physical activity, a low-fat diet, and their combination. A high-fat diet significantly increased body weight and induced widespread neuroanatomical changes, with effects modulated by sex and genotype. The combined intervention led to significant weight loss in males of both genotypes. Neuroanatomical analyses revealed that a high-fat diet significantly reduced hippocampal and cerebellar volumes in wild-type mice but had a less pronounced effect on 3xTgAD mice; nevertheless, interventions, particularly the combined approach, increased localized brain volumes in these regions regardless of genotype. Multivariate integration of behavioural and neuroanatomical measures identified a brain pattern linking hippocampal and cerebellar volumes to intervention and behavioural performance. Spatial gene-enrichment analysis of this pattern identified biological processes, including glucose homeostasis, as potential biological mechanisms underlying intervention effects. Overall, these findings suggest that voluntary physical activity and a low-fat diet can modulate brain structure and behaviour, partially counteracting the effects of a high-fat diet, and potentially recruiting biological processes that may support brain health. In the end, the authors focus primarily on the hippocampus and discuss the cerebellum, but it seems that changes occur throughout the brain. The choice to focus on the hippocampus and cerebellum needs to be supported.

To gain further insight, the authors analyze genes across different brain regions using the Allen Brain Atlas. Although this seems reasonable in theory, once one realizes how many genes are shared across diverse brain regions, one wonders how such an analysis was conducted. More understanding of this approach, as well as how it was validated, is important. In the end, the authors conclude that the glucose homeostatic pathways were primarily altered, and one would like to understand whether that is indeed true and whether it is the only set of pathways that were changed.

This raises another point: what occurs in a normal wild-type mouse on the standard diet during the first 6 months of life? Do the glucose homeostatic pathways change simply due to age? Sex? It may be that, with age, the mice become more sedentary, which is why. Once that is resolved, what occurs on the standard diet for the 3xTg mice? Perhaps they are more active or more sedentary, regardless of diet or exercise? Thus, the studies end up raising more questions than answers.

Given so much work has already been done, it seems best to simply reorganize the presentation with raw data first, followed by the analysis. For the second section, the implicit assumptions of the analyses should be very clear so that the analyzed data are understood and believable. Limitations of the assumptions, pooling some groups, etc., need to be clear.

Figures. In Figure 1, the weekly measurements are not shown. The points are connected, so an unbroken line is shown. Around the line are lighter lines indicating errors, but with all the lines and colours, one does not know what standard errors surround the values for any given group. This makes the data hard to interpret. In later figures, significant differences are indicated with asterisks, but this seems to be done inconsistently.

In the text, more caution is needed for some assertions. For example, it is not clear that a 2- to 6-month-old is an adolescent. Opinions about the ages of mice that correspond to human life stages have always been debated. Another example is indicating that male mice might gain weight differently than females, as if it were an outcome of diet or exercise. This is because male rodents continue to gain weight in adulthood, but females stabilize because estrogen limits appetite. Additionally, females may not show group differences because they are more variable. This can relate to their estrous cycle. If stressed or housed without males nearby, they may not have a regular estrous cycle, which can then affect their outcomes. This may be particularly true for behavior when they may have been tested during different estrous cycle phases, if they had estrous cycles.

Reviewer #1 (Public review):

Summary:

This study presents an Important tool for the study of MR1 antigen binding, opening new possibilities, and cutting-edge techniques. The evidence supporting the claims of the authors is solid, although including some functional experiments using primary T-cells would also provide a more complete physiologic evaluation. The work will be of interest to T cell immunologists, in general, especially those studying unconventional T cells.

Strengths:

In this study, the authors developed a single-chain MR1-derived protein by exchanging the α3 domain and β2-microglobulin for a helical stabilizing domain that they had previously developed. The aim was to generate a more compact structure that would still fold properly, without the risk of losing β2-microglobulin. This overall more robust structure would facilitate ligand exploration using various cutting-edge biophysical techniques.

The authors successfully demonstrated that their construct folds similarly to native MR1 and retains the ability to bind MAIT TCR in solution, as shown by cryo-EM experiments. Its melting temperature was equivalent to that of the native protein. Importantly, the construct enables the use of differential scanning fluorometry and transverse relaxation-optimized spectroscopy, which represent the main strengths of this work. These approaches should greatly facilitate the screening of additional unknown ligands and enable interaction mapping.

Weaknesses:

One possible area for improvement would be to extend the validation to additional known ligands, particularly weaker binders. Furthermore, although the cryo-EM data are highly convincing, including either MAIT cell staining or MAIT activation assays with the generated construct would provide stronger functional validation of its equivalence to the wild-type protein with respect to ligand-binding properties.

Overall, this work is of great interest to the field, as several groups worldwide are seeking to identify endogenous/tumour-derived MR1 ligands. In addition, some pathogens lacking the capacity to produce 5-OP-RU have been shown to activate MAIT cells, raising the possibility that unknown pathogen-derived ligands may also exist.

Reviewer #1 (Public review):

Summary:

P. Izquierdo et al. investigated the genetic determinism of various traits of interest in switchgrass using large-scale genomic and transcriptomic data. More specifically, they worked on a diversity panel comprising 426 genotypes evaluated in common-garden experiments at two locations (Michigan and Texas). The phenotypic and genomic data were already published. In this work, they produced transcriptomic data for each of the 426 genotypes at each site, and they carried out phenotype predictions using genomic and transcriptomic data separately or together. While they were moderately correlated at each location, both omic information appeared to be complementary for the prediction of phenotype. To further exploit the fact that they have data across two locations, they computed differences for phenotypes and transcripts between locations as indicators of trait and transcript plasticity, respectively. They built predictive models of trait plasticity using genomic information and transcript plasticity, which proved to be quite accurate for traits affected by GxE. Finally, they made use of SHAP values from predictive models of flowering time and biomass at each location, as well as for their plasticity, to gain insight into their genetic determinism. These SHAP values provide the importance of the predictive features (SNP and/or transcripts) for trait prediction. This allowed them to confirm some candidate genes and to propose new candidates for both traits.

Strengths:

I found this study interesting and rich. I think the sample size (426 genotypes) is large enough to support the findings. The use of a modern machine-learning approach (XGBoost) together with SHAP indices to find interesting features and get insights into the biological mechanisms underlying flowering time and biomass production is quite original. The methodology employed is globally sound. I also like the fact that the authors accounted implicitly for the population structure by providing a baseline prediction using the first 5 PCs.

Weaknesses:

While the methodology is globally sound, I sometimes had difficulties following exactly what was done. This is partly due to the fact that the authors used 2 omics (SNPs and transcripts) to predict phenotypes, and sometimes, in the results, it is not clear which of the 2 is the focus. This was especially the case for the importance of the features and the interpretability of the models, where I found it sometimes hard to tell whether the analysis was done on SNPs or transcripts.

Also, regarding the methodology, I did not understand why the authors needed to perform a feature selection approach. Maybe it was required to perform the interaction analysis, which could not be deployed on all the features? But regarding the importance of the features, I do not get the added value of the selection over the direct use of SHAP indices when using all features. Maybe this is because I am not a specialist in this kind of approach, but maybe the authors could add more details to explain the rationale behind the feature selection.

Reviewer #1 (Public review):

Summary:

Wang Liao and colleagues aim to provide a comprehensive synthesis of zebrafish circadian research, with particular emphasis on the decentralized photoreceptive architecture that distinguishes teleosts from mammals, and to outline future research directions leveraging emerging technologies for translational applications. The authors frame zebrafish as occupying a "crucial evolutionary and experimental niche" and argue that the model system is uniquely suited to address open questions in chronobiology.

Strengths:

The review is broad in scope and up to date in its citation of recent primary literature. The coverage of physiological outputs - spanning cardiovascular rhythmicity, hepatic metabolism, immune function, reproduction, and gut homeostasis - is more comprehensive than many existing reviews in this area, and researchers seeking an entry point into any of these subfields will find a useful orientation. The figures are well-designed and effectively summarise complex regulatory relationships. The section on immune rhythmicity is a particular strength, providing mechanistic detail on how specific clock components (Clock1a, Per1b, Per2, Cry1a) differentially regulate neutrophil behaviour, bacterial killing, and cytokine expression; this level of molecular specificity distinguishes it from comparable sections in the review. The brief discussion of non-canonical clock gene functions (CLOCK in neuronal connectivity, BMAL1 in stem cell state, vascular calcification) raises genuinely interesting points that are underexplored in the field and might deserve more prominence.

The future perspectives section makes a conceptually interesting move in suggesting that the zebrafish decentralized architecture could reframe a central question in chronobiology - from how a master clock imposes order on passive peripheral oscillators, to how semi-autonomous oscillators achieve coherence. This is the most original conceptual contribution in the manuscript, and it would benefit from much further development.

Weaknesses:

The core limitation of this review is that it functions primarily as an annotated bibliography rather than a critical synthesis. Section after section follows the same pattern: a physiological system is introduced, several findings from recent papers are described in sequence, and the section ends. Missing throughout is an evaluative voice - where does the field agree, where does it disagree, which findings have been replicated versus remain preliminary, and which conceptual questions are genuinely unresolved versus merely unstudied? Readers with expertise in the field will find little that reframes their understanding; readers new to the field will receive information but not the interpretive scaffolding needed to assess its significance.

The framing of zebrafish as occupying a "crucial evolutionary and experimental niche" is asserted but not substantiated. The experimental advantages of zebrafish - optical transparency, external development, genetic tractability - are real, but they apply primarily to larval stages, typically the first two weeks of development. The review does not adequately address whether the key features it highlights, particularly peripheral photosensitivity and autonomous peripheral oscillators, have been demonstrated in adult animals, where optical transparency is lost. Many of the physiological findings described (sleep-wake cycles, cardiovascular function, reproduction, and immune function) are most relevant in adult or juvenile fish, yet the mechanistic underpinnings often come from larval studies. Whether the mechanisms generalise across developmental stages is not discussed, and this is an important gap that the review could acknowledge explicitly.

The claim that zebrafish bridge invertebrate and mammalian models is a conventional framing that appears in most zebrafish review articles; its repetition here adds little. More interesting - and underexplored - is the comparative question of how the decentralised clock architecture of teleosts compares with that of other non-mammalian vertebrates, or indeed with invertebrate systems such as Drosophila, where peripheral tissue clocks and non-visual photoreception have also been studied. The review does not engage with this comparative dimension, which would be the natural intellectual context for the claims being made.

The future perspectives section identifies several promising directions - optogenetic circuit mapping, whole-body longitudinal imaging, inter-organ communication, network modeling - but these are described at a high level of generality. Most are not specific to the questions raised by the zebrafish decentralized clock architecture; they would appear in any forward-looking review of circadian biology. The one conceptually distinctive idea - that zebrafish could be used to ask how distributed oscillators achieve coordinated coherence without hierarchical control - is identified but not developed into concrete experimental questions or testable predictions. The discussion of non-canonical clock gene functions in the Future Perspectives section would benefit from being more directly connected to what zebrafish specifically can offer: given that teleost genome duplication has produced additional paralogues of clock genes, there is a concrete opportunity to dissect canonical from non-canonical functions through comparative analysis of paralogues with diverged expression patterns. This point is hinted at but not made explicitly.

Appraisal of conclusions:

The conclusions are broadly consistent with the evidence cited, and the authors are appropriately cautious in noting that many signalling cascades and inter-tissue communication mechanisms remain incompletely characterised. The conclusion that zebrafish represents a valuable and underexploited model for circadian-disease translational research is well-supported. However, the review would be significantly strengthened if the authors distinguished more clearly between what is firmly established, what is supported by preliminary or single-study evidence, and what remains genuinely speculative.

Likely impact and utility:

This review will be useful as an orientation document for researchers new to zebrafish circadian biology, and the comprehensive treatment of physiological outputs across organ systems is a genuine service to the field. Its impact as an intellectual contribution is limited by the descriptive approach and the absence of original synthesis or conceptual reframing. The most interesting ideas in the manuscript - the reframing of the central/peripheral clock hierarchy question, and the potential of clock gene paralogues for probing non-canonical functions - could be further developed and, if pursued, could form the basis of a more distinctive and impactful contribution.

Reviewer #1 (Public review):

Sheidaei and colleagues report a novel and potentially important role for an early mitotic actomyosin-based mechanism, PANEM contraction, in promoting timely congression of chromosomes located at the nuclear periphery, particularly those in polar positions. The manuscript will interest researchers studying cell division, cytoskeletal dynamics, and motor proteins. Although some data overlap with the group's prior work, the authors extend those findings by optimizing key perturbations and performing more detailed analyses of chromosome movements, which together provide a clearer mechanistic explanation. The study also builds naturally on recent ideas from other groups about how chromosome positioning influences both early and later mitotic movements.

Comments on revised version:

In the revised manuscript, organizational issues have been largely resolved. In addition, the inclusion of new experiments in additional cell lines, along with an expanded discussion that places actomyosin contractility in the broader conceptual context of other mechanisms governing chromosome movement, has significantly strengthened the manuscript.

Reviewer #1 (Public review):

Summary:

This paper tries to address an important outstanding issue, which is the evolutionary origin of the SLC25 family of mitochondrial carrier proteins, which are common to all eukaryotic life, with few exceptions. The authors have carried out phylogenetic analyses and DALI searches of AlphaFold databases of bacterial and archaeal membrane proteins. They identify two bacterial proteins, CysZ and YhiY, and they propose that they are progenitors of SLC25 family members. Whilst the paper addresses an interesting topic, the conclusions are not supported by the data and are not presented in an unbiased manner, as they highlight only features that provide some tentative support for the hypothesis. They do not address the large number sequence and structural properties that refute the hypothesis, such as the asymmetric vs three-fold pseudo-symmetric features, hexamer vs monomer, and the complete lack of any conserved motifs with similar functions. Any resemblances between CysZ/YhiY and mitochondrial carriers thus seem to be superficial and could well be coincidental, as they represent generic properties of membrane proteins rather than specific ones, indicative of an evolutionary relationship.

Strengths:

This paper explores the evolutionary origins of the SLC25 family of mitochondrial carrier proteins, which are found across nearly all eukaryotic organisms. They were likely to be present in the last common ancestor of all eukaryotes, around two billion years ago. The question is whether they are of bacterial, archeal or eukaryotic origin. The authors propose that two bacterial proteins, CysZ and YihY, may represent ancestral forms of these carriers, based on structural comparisons of models, a sequence motif, and phylogenetic analyses. While the research addresses an important and longstanding question, the presented evidence does not convincingly support their hypothesis.

Weaknesses:

A central concern is the reliance on structural similarity searches using predicted protein models, since these models are often built using known protein structures as templates, and thus these searches may produce misleading matches. The reported similarities between CysZ, YihY, and mitochondrial carriers are weak and fall within ranges expected for unrelated membrane proteins, which commonly share general structural features, such as helical bundles. Quantitative measures of similarity are low and do not support a shared evolutionary origin. The case for YhiY is extremely poor as neither structure nor sequence features support the claim. Importantly, the opening of the YihY is towards the membrane rather than the water phase, as is the case for carriers, indicating that it has a very different structure and function. The case for CysZ is somewhat better, as it is a helical bundle with two short helices somewhat resembling the matrix helices of mitochondrial carriers, and a short sequence PXDXXK that is part of one of the known sequence motifs of mitochondrial carriers, but this is where the similarities end.

Mitochondrial carriers have a distinctive threefold pseudo-symmetrical structure and a highly complex transport mechanism involving six structural elements. This paper's hypothesis does not explain how such a high level of threefold pseudo-symmetry could have evolved from entirely asymmetric proteins. To complicate matters further, CysZ is not functional as a monomer but forms a functional hexamer, which also explains why it has two half helices rather than two transmembrane helices. Thus, the hypothesis is that CysZ, which is an asymmetric protomer of a functional hexamer, has evolved into a three-fold pseudo-symmetric protein, which is functional as a monomer. A more convincing explanation is that the threefold pseudo-symmetrical structure arose from gene triplication and fusions, with later mutations introducing asymmetry to support diverse substrate binding. In support of this notion, mitochondrial carriers transporting large molecules, such as ATP, show more asymmetry, whereas those for small molecules remain nearly symmetrical. In general, the vast majority of transport proteins arose from gene duplications and fusions of the domains.

Although mitochondrial carriers have a similar sequence motif as found in CysZ (PXDXXK), their roles are very different. In mitochondrial carriers, this motif is located roughly in the middle of transmembrane helices H1, H3, and H5, where proline creates a pronounced kink, bringing the charged residues inward to form a salt-bridge network in the central water-filled cavity. The formation and disruption of this network is essential for the transport mechanism when switching between inward- and outward-open states. In CysZ, the motif is found at the end of a helix and in the following loop at the end of the transporter, with residues pointing outward toward the water phase. These residues are typical of membrane-water interface regions, where proline acts as a helix breaker and charged residues interact with the water phase. Thus, this motif in CysZ does not match the position or function seen in mitochondrial carriers, and its presence is likely to be coincidental, because these residues often occur in the water-membrane region. Importantly, none of the other important conserved three-fold symmetrical motifs of mitochondrial carriers is found in these bacterial proteins, such as the cytoplasmic network [YF][DE]xx[RK], cardiolipin binding sites, ER-links, and sequences of small amino acids, which are critical for its dynamic mechanism.

The phylogenetic relationship is also overstated, as there is no sequence similarity between these proteins other than that occurring because of similar biophysical properties, such as transmembrane helices. The authors suggest that a specific mitochondrial carrier represents the ancestral member of the family, but this conclusion appears to be inferred rather than rigorously demonstrated. Key aspects, such as tree rooting and taxon sampling, are not sufficiently addressed, weakening confidence in the evolutionary claims. Further, the selection of only a few bacterial and archaeal proteomes for analysis limits the study's scope. Broader searches would be necessary to support claims about conservation and ancestry. Independent sequence searches indicate that CysZ and YihY are not widely conserved in the bacterial groups most closely related to mitochondria, undermining the argument that they are plausible ancestors.

Overall, the presented similarities are superficial and can be explained by general features of membrane proteins rather than by specific adaptations to function. The hypothesis that CysZ and YihY are evolutionary precursors of mitochondrial carriers is not supported by the presented data.

Reviewer #1 (Public review):

Renard, Ukrow et al. applied their recently published computational pipeline (CHROMAS) to the skin of Euprymna berryi and Sepia officinalis to track the dynamics of cephalopod chromatophore expansion. By segmenting each chromatophore into radial slices, and analyzing the co-expansion of slices across regions of the skin, they inferred the motor control underlying chromatophore groups.

Strengths:

- The authors demonstrate that most motor units of cephalopod skin include a subregion of multiple chromatophores, creating "virtual chromatophores" between fixed chromatophores. This is an interesting concept that challenges prevailing models of chromatophore organization, and raises interesting possibilities for how chromatophore arrays may be patterned during development.

- This study introduces new analytical approaches of cephalopod skin that will be valuable for the quantitative study of cephalopod behavior.

Weaknesses:

- The authors use patch-clamp experiments in E. berryi to test their approach for inferring motor units. The stimulations indeed evoke expansions of sub-regions of each chromatophore, creating "virtual chromatophores". However, they were not able to predict these motor units from behavioral analysis before confirming them with patch-clamp, limiting the strength of this validation.

- In S. officinalis, chromatophores are far more numerous than in E. berryi and exhibit frequent spontaneous activity, making it more challenging to distinguish shared motor drive. Patch-clamp experiments in this species would provide important validation and strengthen confidence in the method for inferring motor units.

- Although multiple experimental conditions were tested (e.g., age, size, behavioral context, sedation, head-fixation, lighting), data is only shown from a small subset of experiments. Analyzing pooled data across conditions would allow for more generalizable conclusions.

- Different clustering algorithms were used for the two species (HDBSCAN for E. berryi and Affinity Propagation for S. officinalis). Since Affinity Propagation appeared to better capture correlation structure in S. officinalis, it would be informative to reanalyze the E. berryi data using the same method to assess potential algorithm-dependent biases.

Conclusion:

The CHROMAS tool is likely to be valuable to the field, given the need for quantitative frameworks in cephalopod biology. The predictions outlined here provide a useful foundation for future experimental investigation.

Reviewer #1 (Public review):

Summary:

This paper investigates whether transformer-based models can represent sentence-level semantics in a human-like way. The authors designed a set of 108 sentences specifically to dissociate lexical semantics from sentence-level information and collected 7T fMRI data from 30 participants reading these sentences. They conducted representational similarity analysis (RSA) comparing brain data and model representations, as well as the human behavioral ratings. It is found that transformer-based models match brain representation better than static word embedding baseline which ignores word order but fall short of models that encode the structural relations between words. The main contributions of this paper are:

(1) The construction of a sentence set that disentangles sentence structure from word meaning.

(2) A comprehensive comparison of neural sentence representations (via fMRI), human behavior, and multiple computational models at the sentence level.

Strengths:

(1) The paper evaluates a wide variety of models, including layer-wise analysis for transformers and region-wise analysis in the human brain.

(2) The stimulus design allows precise dissociation between lexical and sentence-level semantics. The RSA-based approach is empirically sound and intuitive.

(3) The constructed sentences, along with the fMRI and behavioral data, represent a valuable resource for studying sentence representation.

Weaknesses:

(1) The rationale behind averaging sentence embeddings across multiple transformer models (with different architectures and training objectives) is unclear. These transformer-based models have different training paradigms and model architectures, which may result in misaligned semantic spaces. The averaging operation may dilute the distinct sentence representations learned by each model, potentially weakening the overall semantic encoding for sentences. Please clarify this choice or cite supporting methodology.

(2) All structure-sensitive models discussed incorporate semantics to some extent. Including a purely syntactic baseline, such as a model based on context-free grammar, would help confirm the importance of syntactic structures.

(3) In Figure 2, human behavioral judgments show weak correlations with neural data, and even fall below those of computational models, suggesting the behavioral judgments may not reflect the sentence structures in a brain-like way. This discrepancy between behavioral and neural data should be clarified, as it affects the interpretation of the results.

(4) To better contextualize model and neural performance, sentence similarity should be anchored to a notion of semantic "ground truth", such as the matrix shown in Figure 1a. Comparing this reference with human judgments, brain responses, and model similarities would help establish an upper bound.

(5) The structure of this paper is confusing. For instance, Figure 5 is cited early but appears much later. Reordering sections and figures would enhance readability.

(6) While the analysis is broad and comprehensive, it lacks depth in some respects. For instance, it remains unclear what specific insights are gained from comparing across brain regions (e.g., whole brain, language network, and other subregions). Similarly, the results of simple-average and group-average RSA appear quite similar and may not advance the interpretation.

(7) While explaining the grid-like pattern due to sentence length is important, this part feels somewhat disconnected from the central question of this paper (word order). It might be better placed in supplementary material.

Comments on revised version:

The new version of the paper has addressed my main concerns, including:

(1) clarification about the methodology of Transformer embeddings

(2) discussion about the purely syntactic models

(3) discussion about the low correlation between behavioural ratings and brain activations

(4) better structure of the paper

(5) clarification about pre-registration

I believe the paper has been substantially improved after revision.

Reviewer #1 (Public review):

This rigorous and creative study uses an elegant combination of metabolomics, transcriptomics, and budding yeast molecular genetics to discover that (i) activating AMPK to maintain mitochondrial respiration fueled by cytosolic Acetyl CoA and (ii) increasing fatty acid synthesis independent of respiration drive independent pathways that increase the fitness of replicatively-aged budding yeast cells, albeit without increasing their lifespan. This work will be of interest to scientists in the field of aging and metabolism. Some clarifications in the text would address the following concerns, which would increase the impact of the study:

(1) What does activation of AMPK (via PGDP-Sak1 expression) do to the replicative lifespan? How many bud scars, in general, do the subpopulations that are older - yet have less Tom70 (increased mitochondrial fitness) - have, after the 48 hrs time point that they are examining? How many divisions occurred in this 48hr time period - i.e. is it long enough to have all cells reach the end of their replicative lifespan? This information is important to rule out that a subset of the mutant cells just divided faster and hence had more divisions within 48 hrs (growing faster and living longer are different things). Having identical growth curves doesn't indicate per se that they all divide at the same rate, as there may be a subpopulation that divides faster and a subpopulation that doesn't grow so well.

(2) A2A cells do not have an extended replicative lifespan (RLS) but show an increase in the "low senescence" population (Figure 2). If the cells are not becoming senescent, why don't they have longer RLS? Not having a longer lifespan seems inconsistent with the statement that "bud scar counting confirmed that A2A cells reach a higher age than wild type", which comes back to how many times the cells can divide in the 48hr timepoint studied and their rate of cell division? Also, the lifespan curve shown is plotted against time, not cell division number, which does not take into account different division times of cells within the population (described above). It would be much more useful to show standard lifespan curves showing cell division numbers per lifespan per cell.

(3) Increased "fitness" of the old cells is implied from the increased size of the colonies that the old cells can make. However, this is a measure of the fitness of the daughters per se, not the old mother cells. Are the old mothers just passing on healthier mitochondria and more lipids to the daughters, such that they can divide more times? If the aged cells have an "increased fitness", why don't they divide more times themselves (i.e. live longer?).

(4) The statement is made that "these experiments define two classes of aging cells with distinct metabolic needs, coherent with the model of two aging trajectories previously proposed (referencing Nan Hao's work)". However, the big difference here is that in Nan Hao's work, their two aging trajectories influenced the length of lifespan, but that does not appear to be the case here. That distinction should be made clear. Perhaps the authors could also speculate as to why the A2A yeast stops dividing after presumably the same number of cell divisions, even though they have an activated AMPK and activated fatty acid synthesis pathway.

(5) I am a bit confused by the use of the word "senescence" by this lab here and in their previous growth on galactose studies. If yeast don't senesce, which is usually defined as an irreversible arrest of the cell cycle where cells stop dividing, shouldn't the yeast that do not senesce still be dividing and hence have a longer lifespan? Should a different term be used rather than senescence? Such as "fitness late in life". The authors giving their definition of senescence may help reduce this apparent contradiction.

Reviewer #1 (Public review):

[Editor's 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 work the authors investigate the molecular dynamics of MinD, a component of the Bacillus subtilis Min system, in vitro and in vivo. In Escherichia coli the Min system is highly dynamic and displays rapid pole to pole oscillation whereby a time average minimum of the Min proteins at mid cell is established. However, in B. subtilis, this is not the case, and there is no MinE present. MinD in B. subtilis dynamically relocalizes from the poles to division sites, and binds to MinC and MinJ, which mediates its interaction with DivIVA. This paper reports biochemical characterization of B. subtilis MinD in vitro and dynamics of MinD variants in vivo, providing mechanistic insight into the mechanism of dynamic localization.

Strengths:

In the current study, the authors perform a detailed biochemical characterization of the in vitro ATPase activity of MinD and demonstrate that rapid hydrolysis is elicited by adding phospholipids. They further show using a collection of substitution mutants of MinD that both monomers and dimers bind to the membrane, and ATP occupancy changes the on and off rates. Identification, quantification, and tracking of discrete Halo-MinD populations was nicely done and showed that mutations in MinD alter dynamic localization, correlating with PL binding on and off rates in vitro.

In the revised manuscript, the authors now demonstrate localization and tracking data for minC and minJ deletion strains, which suggest that MinJ impacts MinD membrane cycling, but MinC does not. Additional in vitro work showed that the PDZ domain of MinJ modifies MinD ATP hydrolysis rates, and the authors propose that MinJ may promote MinD dimer formation.

Weaknesses of the revised version: No major weaknesses.

Reviewer #1 (Public review):

Summary:

The study by the Obata group characterizes the dynamics of the canonical malate dehydrogenase-citrate synthase metabolon in yeast.

Strengths:

The study is well-written and appears to give clear demonstrations of this phenomenon.

Studies of the dynamics of metabolon formation are rare; if the authors can address the concern detailed below, then they have provided such for one of the canonical metabolons in nature.

Weaknesses:

There is a fundamental issue with the study, which is that the authors do not provide enough support or information concerning the split luciferase system that they use. Is the binding reversible or not? How the data is interpreted is massively influenced by this fact. What are the pros and cons of this method in comparison to, for example, FLIM-FRET? The authors state that the method is semi-quantitative - can they document this? All of the conclusions are based on the quality of this method. I know that it has been used by others, but at least some preliminary documentation to address these questions is required.

Comments on revised version:

I feel that the authors have adequately addressed my prior concerns. I have no further critiques of their work.

Reviewer #1 (Public review):

Summary:

This study investigated how visuospatial attention influences the way people build simplified mental representations to support planning and decision-making. Using computational modeling and virtual maze navigation, the authors examined whether spatial proximity and the spatial arrangement of obstacles determine which elements are included in participants' internal models of a task. The study developed and tested an extension of the value-guided construal (VGC) model that incorporates features of spatial attention for selecting simpler task mental representation.

Strengths:

(1) Original Perspective: The study introduces an explicit attentional component to established models of planning, offering an approach that bridges perception, attention, and decision-making.

(2) Methodological Approach: The combination of computational modeling, behavioral data, and eye-tracking provides converging measures to assess the relationship between attention and planning representations.

(3) Cross-validated data: The study relies on the analysis of three separate datasets, two already published and an additional novel one. This allows for cross-validation of the findings and enhances the robustness of the evidence.

(4) Focus on Individual Differences: Reports of how individual variability in attentional "spillover" correlates with the sparsity of task representations and spatial proximity add depth to the analysis.

Appraisal of Aims and Results:

The study sets out to determine how spatial attention shapes the construction of task representations in planning contexts. The authors provide evidence that spatial proximity and arrangement influence which environmental features are incorporated into internal models used for navigation, and that accounting for these effects improves model predictions. There is clear documentation of individual variation, with some participants showing greater attentional spillover and more sparse awareness profiles.

Comments on revised version:

The authors did a great job and I am very happy with the revised manuscript.

Reviewer #1 (Public review):

Summary: This study investigated how visuospatial attention influences the way people build simplified mental representations to support planning and decision-making. Using computational modeling and virtual maze navigation, the authors examined whether spatial proximity and the spatial arrangement of obstacles determine which elements are included in participants' internal models of a task. The study developed and tested an extension of the value-guided construal (VGC) model that incorporates features of spatial attention for selecting simpler task mental representation.

Strengths:

(1) Original Perspective: The study introduces an explicit attentional component to established models of planning, offering an approach that bridges perception, attention, and decision-making.

(2) Methodological Approach: The combination of computational modeling, behavioral data, and eye-tracking provides converging measures to assess the relationship between attention and planning representations.

(3) Cross-validated data: The study relies on the analysis of three separate datasets, two already published and an additional novel one. This allows for cross-validation of the findings and enhances the robustness of the evidence.

(4) Focus on Individual Differences: Reports of how individual variability in attentional "spillover" correlates with the sparsity of task representations and spatial proximity add depth to the analysis.

Weaknesses:

(1) Clarity of the VGC model and behavioral task: The exposition of the VGC model lacks sufficient detail for non-expert readers. It is not clear how this model infers which maze obstacles are relevant or irrelevant for planning, nor how the maze tasks specifically operationalize "planning" versus other cognitive processes.

The method for classifying obstacles as relevant or irrelevant to the task and connecting metacognitive awareness (i.e., participants' reports of noticing obstacles) to attentional capture is not well justified. The rationale for why awareness serves as a valid attention proxy, as opposed to behavioral or neurophysiological markers, should be clearer.

(2) Attention framework: The account of attention is largely limited to the "spotlight" model. When solving a maze, participants trace the correct trail, following it mentally with their overt or covert attention. In this perspective, relevant concepts are also rooted in attention literature pertaining to object-based attention using tasks like curve tracing (e.g., Pooresmaeili & Roelfsema, 2014) and to mental maze solving (e.g., Wong & Scholl, 2024), which may be highly relevant and add nuance to the current work. This view of attention may be more pertinent to the task than models of simultaneously tracking multiple objects cited here. Prior work (notably from the Roelfsema group) indicates that attentional engagement in curve-tracing tasks may be a continuous, bottom-up process that progressively spreads along a trajectory, in time and space, rather than a "spotlight" that simply travels along the path. The spread of attention depends on the spatial proximity to distractors - a point that could also be pertinent to the findings here.

Moreover, the tracing of a "solution" trail in a maze may be spontaneous and not only a top-down voluntary operation (Wong & Scholl, 2024), a finding that requires a more careful framing of the link to conscious perception discussed in the manuscript.

Conceptualizing attention as a spatial spotlight may therefore oversimplify its role in navigation and planning. Perhaps the observed attentional modulation reflects a perceptual stage of building the trail in the maze rather than a filter for a later representation for more efficient decision making and planning. A fuller discussion of whether the current model and data can distinguish between these frameworks would benefit readers.

(3) Lateralization of attention: The analysis considers whether relevant information is distributed bilaterally or unilaterally across the visual display, but does not sufficiently address evidence for attentional asymmetries across the left and right visual fields due to hemispheric specialization (e.g., Bartolomeo & Seidel Malkinson, 2019). Whether effects differ for left versus right hemifield arrangements is not made explicit in the presented findings.

(4) Individual differences: Individual differences in attentional modulation are a strength of the work, but similar analyses exploring individual variation in lateralization effects could provide further insight, and the lack of such analyses may mask important effects.

(5) Distinction between overt and covert attention: The current report at times equates eye movement patterns with the locus of attention. However, attention can be covertly shifted without corresponding gaze changes (see, for example, Pooresmaeili & Roelfsema, 2014).

The implications for interpreting the relationship between eye movement, memory, and attention in this setting are not fully addressed. The potential dynamics of attention along a maze trajectory and their impact on lateralization analysis would benefit from further clarification.

Appraisal of Aims and Results:

The study sets out to determine how spatial attention shapes the construction of task representations in planning contexts. The authors provide evidence that spatial proximity and arrangement influence which environmental features are incorporated into internal models used for navigation, and that accounting for these effects improves model predictions. There is clear documentation of individual variation, with some participants showing greater attentional spillover and more sparse awareness profiles.

However, some conceptual and methodological aspects would be clearer with greater engagement with the broader literature on attention dynamics, a more explicit justification of operational choices, and more targeted lateralization analyses.

Reviewer #1 (Public review):

Summary:

In this manuscript the authors derive a mean-field model for a network of Hodgkin-Huxley neurons retaining the equations for ion exchange between the intracellular and extracellular space.<br /> The mean-field model derived in this work relies on approximations and heuristic arguments that, on the one hand, allow a closed-form derivation of the mean-field equations, and on the other hand restrict its validity to a limited regime of activity corresponding to quasi-synchronous neuronal populations. Therefore, rather than an exact mean-field representation, the model provides a description of a mesoscopic population of connected neurons driven by ion exchange dynamics.

Strengths:

The idea of deriving a mean-field model which relates the slow-timescale biophysical mechanism of ion exchange and transportation in the brain to the fast-timescale electrical activities of large neuronal ensembles.

Weaknesses:

The idea underlying this work is not completely implemented in practice.

The derived mean field model do not show a one-to-one correspondence with the neural network simulations, except in strongly synchronous regimes. The agreement with the in vitro experiment is hardly evident, both for the mean-field model and for the network model. The assumptions made to derive the closed-form equations of the mean field model have not been justified by any biological reason, they just allow for the mathematical derivation. The final form of the mean-field equations do not clarify whether or not microscopic variables are used together with macroscopic variables in an inconsistent mixture.

Comments on revisions:

The main weaknesses I listed in the first report are still present, since the authors did not answer my questions on a solid basis. I report the list for completeness:

(1) It seems that the reduction methodology that is employed is not the most suitable one for the single-neuron model they are considering.<br /> (2) The formulation of the mean-field derivation is unnecessarily complicated. It could be heavily simplified by following previously published approaches to derive biologically realistic neural masses.<br /> (3) The model seems to work only for highly synchronized situations and not for the standard asynchronous evolution usually observed in neural circuits.

Therefore, my statement remains unchanged.

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.

Reviewer #1 (Public review):

Summary:

During erythroid differentiation, hematopoietic progenitors relinquish multipotency and activate lineage programs. The switch from GATA2 to GATA1 is particularly important in this process, yet GATA2 chromatin‑binding kinetics remain undefined. The authors investigated GATA2-chromatin interaction dynamics during erythroid differentiation in three different cell systems using single‑molecule live‑cell imaging, and they also used CUT&Tag to profile GATA2 chromatin occupancy.

By single‑molecule imaging, the authors report two interaction modes for GATA2: short‑lived (<1 s) and long‑lived (>5 s) binding. The proportion of long‑lived molecules, the number of binding events, and the duration of long‑lived binding change (or are maintained) during differentiation. Notably, long‑lived chromatin engagement by GATA2 increases during early erythroid differentiation and decreases at the late stage. CUT&Tag identifies regulatory elements selectively occupied by GATA2 during the early transition stage. Together, these results support a model in which transcription factor kinetics form a dynamic chromatin‑engagement profile that characterizes the GATA2‑to‑GATA1 transition.

Strengths:

(1) Characterizing transcription‑factor binding kinetics during the GATA2->GATA1 transition addresses a fundamental mechanism in erythroid differentiation.

(2) Combining single‑molecule live imaging with CUT&Tag provides both dynamic and locus‑specific perspectives.

(3) Single-molecule analysis across three different cell systems strengthens the potential generalizability of the findings and highlights biological variability.

Weaknesses:

I agree that single‑molecule imaging is a powerful approach for investigating GATA2 kinetics, but the single‑molecule data are the most important part of the paper and need improvement. The analyses focus on three measures: (i) duration of long binding, (ii) proportion of short‑ and long‑binding molecules, and (iii) total binding events. However, several methodological and control issues limit confidence in the kinetic interpretations. The authors should address the following major concerns.

(1) Two binding states: justification and controls

The authors propose two states of GATA2 binding. Are there only two states? Studies that separate short‑ and long‑lived binding (e.g., Chen et al., 2014, PMID: 25342811) address two states of transcriptional factors very carefully. Some long‑binding duration distributions here are very long‑tailed (e.g., Figure 2D middle), suggesting a possible third state. The authors must explain how they determined that two states provide the "best fit" to the data and how they classified "short" versus "long" binding.

Controls should be included for long‑lived and short‑lived binding (e.g., histone proteins, HaloTag‑NLS, or a binding‑deficient GATA2 mutant) as in other studies. These controls are essential to exclude alternative explanations (see points below).

(2) Exclude photophysical and focal‑plane artifacts

The authors should exclude contributions from (i) photobleaching, (ii) blinking, and (iii) Z‑axis motion (disappearance from the focal plane). Although photobleaching correction is mentioned in the Methods, no details are provided. Describe and quantify the photobleaching correction and demonstrate that it was applied across all cell types and conditions.

Some spots in the supplementary movies appear to blink or to move substantially between frames. Provide analyses or controls that distinguish true dissociation events from photophysical blinking/bleaching or axial motion.

(3) HILO illumination and nuclear region sampled

HILO is powerful but sensitive to illumination angle: slight changes sample different nuclear regions (e.g., nuclear interior versus periphery). The nuclear periphery is enriched in heterochromatin and may bias binding statistics. Explain how the authors controlled the HILO angle and confirmed that comparable nuclear regions were imaged across cells and conditions.

(4) Quantification of event counts and long‑binding durations

The number of binding events and measured long‑binding durations are strongly affected by imaging conditions (labeling/staining, bleaching, nucleus size, cell cycle state, focal plane, spot detectability, etc.). Imaging clarity appears to differ among cells/conditions in the supplementary movie. Provide more careful analysis describing how these variables were controlled or corrected for, and assess the sensitivity of results to choices in detection and tracking parameters.

(5) Evidence that spots are single molecules

The authors state that spots represent single molecules but do not provide supporting evidence. Spot brightness varies considerably in the movies. Brightness differences may reflect axial position. Provide evidence supporting single‑molecule assignment (e.g., single‑step photobleaching traces, brightness distributions compared to a known single‑molecule control, or photon count analysis).

(6) Description of spot‑analysis pipeline

The manuscript lacks a sufficient description of the spot‑analysis method. I reviewed the STRAP pipeline paper cited (Haque and Coleman 2025 bioRxiv) and the GitHub code, but the Methods in the current manuscript should include a detailed STRAP pipeline. This would enable readers to evaluate and reproduce the analyses.

(7) Differences among cell systems

The three cell systems yield notably different results (e.g., Figure 2C vs 4C and Figure 2D/3D vs 4D). Provide a more detailed explanation for these differences and discuss how biological variability, technical differences, or imaging biases might account for the discrepancies.

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 scheme 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, the description of the methods and results should be clarified as well. Accordingly, the authors should revise the manuscript to address the following items thoroughly within the revised manuscript (not merely in the response letter) with the additional references mentioned below included in the revised discussion:

(1) In several places, e.g., on line 77 (p.2), the authors appear to suggest that "implicit-solvent representation" is the origin of the deficiency in commonly utilized coarse-grained potentials that this study is aiming to rectify. But desolvation barriers and solvent-separated minima are also features of implicit-solvent representations; they are just features that should be incorporated in more accurate implicit-solvent potentials. This point is stated quite clearly and accurately in the Abstract (p.1) but not consistently in the rest of the text. The authors should check the entire text carefully to ensure that a coherent, accurate perspective is presented.

(2) In the discussion of the importance of desolvation barriers and solvent-separated minima in the Introduction (pp.1-3), connections should be drawn to recent works that utilize these PMF features to rationalize hydrostatic pressure (P)-modulated effects on biomolecular LLPS, including the P-dependent reentrant phase separation of alpha elastin; see Cinar et al. (2019) Chem Eur J 25:13049 (https://chemistry-europe.onlinelibrary.wiley.com/doi/full/10.1002/chem.201902210) and references therein, especially discussions around Figures 10, 11 & 13 in this reference.

(3) In the lower panels of Figures 2D, E (p.5), what do the differently colored small circles in the double-minimum free energy profiles represent? Does the color shading have the same meaning as that in the upper panels? If so, what do the positions of the circles on the free energy profile represent? The authors should clarify this.

(4) The discussion regarding entropy and enthalpy around Figure 2 is quite confusing as it stands. What do the authors mean exactly by the association of entropy or enthalpy with the desolvation barrier of the solvent-separated minimum? Are they referring to conformational entropy?

(5) Do the authors assume that the PMF (effective implicit-solvent potential) is a purely enthalpic term? It appears to be the authors' assumption. If so, the assumption has to be stated clearly in their discussion of "entropy" vs "enthalpy" around Figure 2.

(6) Closely related to points 3-5 above, it should be stated clearly that the "temperature" used in the authors' simulations does not represent experimental temperature if the authors are using purely enthalpic effective potentials because PMFs are in fact temperature-dependent. This clarification is necessary to avoid misunderstanding. In this regard, it should be noted that temperature-dependent effective interactions have been used for modeling biomolecular condensates in analytical theory (Lin, Song, Forman-Kay & Chan, J Mol Liq 2017, already in the citation list) as well as in coarse-grained molecular dynamics simulations [Dignon et al. (2019) ACS Cent Sci 5:821-830 (https://pubs.acs.org/doi/10.1021/acscentsci.9b00102); Chakravarti & Joseph (2025) Protein Sci 34:e70284 (https://onlinelibrary.wiley.com/doi/10.1002/pro.70284)]. The latter two studies, not cited currently, are particularly relevant and thus should be cited because the authors may wish to incorporate temperature-dependent features in their ongoing or future effort in constructing a more comprehensive coarse-grained interaction scheme for biomolecular LLPS simulation.

(7) In tackling "entropy" vs "enthalpy", it should be noted that the temperature dependence of the effective interactions entails an entropic contribution (which is itself temperature dependent) in addition to conformational entropy. As for the effective potential with desolvation barrier and solvent-separated minimum, it should be noted that the decomposition into entropic and enthalpic contributions at the direct contact, desolvation barrier, and solvent-separated minimum can be dramatically different, see, e.g., MaCallum et al. (2007) PNAS 104:6206-6210 (https://www.pnas.org/doi/full/10.1073/pnas.0605859104) and references therein.

(8) P.7, line 340: The proportionality relation follows directly from the standard Flory-Huggins result T_c = T chi(T)/chi_c, thus the proportionality constant is exactly 1/chi_c. Is this the standard relation that the authors are invoking here? The authors should clarify this.

(9) The study on dynamic consequences on pp.8-11 is interesting, but clarifications are necessary:

(i) The vertical schematic in Figure 4A should be explained in detail in its entirety. As it stands, no explanation is provided either in the figure caption or in the text. In particular, what does "elasticity driven" refer to?

(ii) The top snapshot in Figure 4A is labeled t_sim = 0 ns. Does it mean that the snapshot shown is the only chain configuration that the authors used to start the simulation, and that the snapshot does NOT represent the result of any time evolution, no matter how short the duration is? However, if that is the case, why is this snapshot identified with spinodal decomposition if it is not the product of a time evolution from a more homogeneous configuration?

(iii) Related to (ii) - do the rectangular boxes shown represent the entire simulation box or just part of the box containing the polymer chains? One would imagine that if the top snapshot represents spinodal decomposition, the simulation would have been started at a more uniform distribution a short time prior? Why is this not the case?

(iv) What precisely do the small yellow beads and black-colored springs in the zoom-in image of Figure 4E represent?

(10) In discussing dynamic effects, it is useful to draw connections to related works on the effect of chain flexibility on "aging" of condensate [Biswas & Potoyan (2024) PRX 45:9222-9245 (https://journals.aps.org/prxlife/abstract/10.1103/PRXLife.2.023011)] and characterization of viscoelasticity in simulations of biomolecular condensates [Tejedor et al. (2023) J Phys Chem B 127:4441-4459 (https://pubs.acs.org/doi/10.1021/acs.jpcb.3c01292)], as the effects of desolvation can be explored further based on these prior works.

(11) Much of the present study is based on the original HPS formulation of Dignon et al. (2018). In this regard and also in anticipation of future development of improved interaction schemes, several issues should be stated and discussed, even if briefly:

(i) The original HPS model has a basic shortcoming in accounting for the relative interaction strengths of, among others, arginine vs lysine residues [Das et al. (2020) PNAS 117:28795-28805 (https://www.pnas.org/doi/10.1073/pnas.2008122117)].

(ii) Compared to 210-parameter pairwise interaction schemes, such as KH in Dignon et al. (2018) and Joseph et al. (2021), the 20-parameter interaction scheme is likely too restrictive to account for pairwise amino acid residue interactions [Wessén et al. (2022) J Phys Chem B 45:9222-9245 (https://pubs.acs.org/doi/10.1021/acs.jpcb.2c06181)].

(iii) The height of the desolvation barrier may vary significantly for different amino acid residue pairs, see, e.g., Figure 11 of Cinar et al. (2019) mentioned above (and references therein). The authors should discuss these nuances in the revised version. They may also wish to take them into consideration in future investigations.

Reviewer #1 (Public review):

Summary:

This manuscript presents an original quantitative approach for tracking the online formation and updating of prior beliefs. In an Alternating Serial Reaction Time task, participants were exposed to probabilistic visual streams, and their pre-stimulus saccadic behavior (i.e., the first eye movement after the previous stimulus disappeared) was monitored via eye-tracking. Since the stimuli followed an alternating probabilistic sequence, upcoming events did not appear with full certainty: some stimuli had a higher, some a lower probability. By comparing anticipatory oculomotor behavior between high and low probability events, the authors dissociated between learning/belief updating and general oculomotor noise. Noise-driven errors were more frequent than learning-dependent errors, which nonetheless triggered more belief updating (i.e., a change in oculomotor behavior in a subsequent encounter of the same event). Interestingly, updating depended more strongly on whether a prior belief was consistent with the task's probabilistic structure than on prediction errors. These findings suggest that incidental, implicit statistical learning may rely on conservative updating with a relatively low learning rate, or on errorless algorithms, rather than prediction errors per se.

Strengths:

By applying a fine-grained analysis of anticipatory oculomotor behavior, this work establishes new continuous metrics to quantify the gradual learning and refinement of prior expectations during statistical learning. These metrics provide convincing evidence of the dynamics of anticipatory oculomotor behavior.

The method is paradigm-independent, offering generalizable metrics for tracking the dynamic formation and refinement of predictive models in any task involving probabilistic stimulus streams. In the future, computational modeling may leverage these continuous metrics to better dissect the mechanisms underlying statistical learning.

Weaknesses:

The authors subscribe to the idea that statistical learning is not a unified concept but rather is implemented via multiple underlying mechanisms. However, it remains unspecified what these different mechanisms could be, and how eye movements could contribute to distinguishing between them.

The authors claim that they developed a novel methodological approach to probe whether anticipatory eye movements directly reflect priors, thereby filling an outstanding gap. However, this claim ignores mounting relevant work on structure learning using eye-tracking in the developmental field.

The authors claim that their framework quantifies trial-by-trial oculomotor dynamics, while in fact the analyses use epochs (i.e. groups of multiple trials) as predictors. Why not use trial number as a predictor to truly investigate trial-by-trial dynamics that directly reflect anticipation, surprisal, and revision?

Reviewer #1 (Public review):

This paper reports an auditory-directed analysis of the HCP 7T short movie dataset. It has the goal of using the film audio to create tonotopic (pRF) maps and combine these with other HCP-provided data (e.g., T1/T2 ratio) to improve understanding of auditory cortex organization and relative functional segregation, particularly in reference to speech processing.

The paper is ambitious, uses well-founded existing tools for combining data across subjects, and in the Discussion in particular, makes a lot of careful points about interpretation. The paper shows that, at least for a very large dataset on 7T (and for at least a few individual participants) good quality cross-subject-average tonotopic maps can be extracted from fMRI movie datasets via basic spectral modelling of the movie soundtracks. It also suggests ways that these movie-based maps can be combined to come up with potential models of cortical organization. The PCA analysis is a creative way of combining maps (see below for comments)

These are valuable tools for the field in exploiting/exploring existing data, and I look forward to trying them out myself. I want to emphasize that this is not 'damning with faint praise' - a concrete demonstration of this approach with freely available tools/examples is not only the product of a lot of effort (thank you!), but will be an impetus to research going forward.

In terms of the contribution to our understanding of auditory cortex organization, using this large N cohort, they replicate a number of findings in the literature from the last couple of decades, including the overlap of low frequency preference with greater speech stimulus preference (e.g. Moerel, de Martino, & Formisano, 2012, J Neuro), patterns of BF width across cortex (Moerel et al., various; Thomas et al. 2015), use of shorter and longer natural sounds (Moerel et al., 2012, 2014; Dick et al., 2012), the importance/influence of sustained spectral attention for tonotopic mapping (da Costa et al., 2013; Dick et al., 2017; Riecke et al. 2017), the use of tonotopy and 'myelin' mapping to establish areal or regional boundaries (Dick et al., 2012; de Martino et al., 2015; Besle et al., 2018, etc) and the overall shape and consistency of tonotopic maps (e.g., Talavage et al., 2004, Humphries et al., 2010 and many others). To my knowledge/memory, this is the first tonotopy paper that has used the cross-subject cortical-surface-based averaging techniques that are driven by more than curvature/sulcal alignment.

The paper focuses in particular on creating new sets of ROIs based on the various maps derived from the data. Despite being quite familiar with this body of work, I found it difficult to follow how the ROIs were derived, and how and why they were different and/or an improvement over existing parcellation schemes (see for instance Sereno, Sood, & Huang, 2022 for a comprehensive parcellation framework across modalities including auditory, based on combined receptive surface mapping, myelin estimates, and other metrics).

Given the hour of fast(ish) fMRI data on a 7T with pretty big voxels (so high SNR), one aspect of the results that I found surprising - and potentially informative - was the lack of reliable tonotopic 'mappability' in the majority of participants. The authors' analytic approach to computing the pRFs seems completely reasonable (and shows good average maps), and yet individual maps seem unreliable except for the very best examples. I wondered if this might be due to problems in data collection with earbuds becoming slightly uncoupled and therefore delivering a lot less lower-frequency response and also not preventing scanner noise from getting to the ear; this is often a problem with any in-scanner earbud system (including the Sensimetrics). I wondered if the robustness of the 'speech maps' was associated with that of tonotopy; if they are highly associated, that would suggest that either there were huge individual differences in auditory attention, or perhaps that there was some variability in the acoustic signal delivered to each participant.

Reviewer #1 (Public review):

Summary:

This study by Tsuji et al. explores a mechanical threat model in Drosophila using air puffs as a stimulus. The authors first establish the paradigm and show that air puffs induce cardiac deceleration along with increased locomotion. They then identify dopamine as a key regulator of this response and go on to map the underlying circuit. In doing so, they pinpoint two pairs of DA-WED neurons as critical players. They carefully used intersectional strategies to achieve relatively clean labeling of these neurons, which helps ensure that the observed effects can be attributed specifically to DA-WED neurons. They further show that DA-WED neurons are both required and sufficient to drive cardiac deceleration, and that their activity increases in response to air puff stimulation. These neurons also contribute to the locomotor response. Directly inducing cardiac deceleration via optogenetic manipulation of cardiomyocytes also increases locomotion, suggesting a link between cardiac state and behavioral output.

Strengths:

Overall, the experiments are thoughtfully designed, well-controlled, and clearly presented. The figures are easy to follow, and the conclusions are generally well supported by the data. The manuscript is also clearly written, with a discussion that acknowledges potential caveats and outlines future directions. The genetic tools, behavioral paradigm, heart rate measurement approaches, and stimulation methods introduced here will be valuable resources for the community.

Weaknesses:

A few minor points to add to the clarity of the manuscript:

(1) The DA-WED driver (R48A08-AD ∩ VT008692-DBD ∩ TH-FLP) appears quite clean in the brain. However, since the study focuses on cardiac function and locomotion, it would be helpful to check expression in cardiomyocytes and the ventral nerve cord. This would help rule out any off-target expression that might contribute to the phenotypes and further support the idea of a descending pathway from brain dopaminergic neurons.

(2) Since DA-WED>Kir2.1 abolishes the puff-induced locomotor response (Figure 5b), suggesting that DA-WED neurons are directly involved in mediating locomotion. In the model (Figure 5L), it might make more sense for the pathway from mechanical threat to locomotion to pass through DA-WED neurons. The authors could consider adjusting the schematic if they agree.

(3) In line 408, Figure 5K should be 5L as it's a discussion of the model.

(4) In Figure 5j, the x-axis is missing time labels. Even if it matches Figure 5h, adding labels would make it easier to interpret at a glance.

(5) In line 312, it would be helpful to briefly explain why a 28 ms light pulse was used, compared to other pulse durations elsewhere in the paper.

(6) The cardiac deceleration seems to recover quickly after the air puff ends, whereas the locomotor response persists longer (around 10-15 seconds; see Figure 1 and Figure 5). This difference might suggest that DA-WED neurons influence locomotion through an additional or partially independent pathway, beyond their role in cardiac regulation. It could be worth briefly discussing this possibility.

Reviewer #1 (Public review):

Summary:

The current study is a follow-up to a previously published study by the same research group (Nold et al. 2025). In the previous study, the authors had included a set of exploratory analyses which assessed the effects of fitness level (denominated by a relative FTP), sex, and drug treatment (Naxolone versus placebo). In this previous study, the authors state that "exploratory analysis showed a significant main effect of fitness level on differences in pain ratings in the [saline] condition... suggesting increased hypoalgesia with increasing fitness levels, pooled across all stimulus intensities".

In the current study, the authors have recruited an additional 22 female participants (21 included in analysis) from local cycling clubs to assess if fitness level does indeed impact exercise-induced hypoalgesia responses to experimental thermal and pressure pain models.

Strengths:

The current study has the potential to present a convincing argument about the effect of fitness level and potentially other factors (e.g., sex) on exercise-induced hypoalgesia responses. Combining data across two of their primary studies would be highly fruitful to the research community interested in this area. Specifically, it has the potential to inform sports medicine practitioners and how they administer exercise protocols to help those experiencing pain with a further consideration for the fitness level (and maybe sex) of their patients.

Weaknesses:

However, the current study makes several bold claims about the role of fitness level and sex on exercise-induced hypoalgesia, which I do not believe that this study on its own - or in conjunction with the previously published study by the same authors - can make at present. Namely, the current study does not appear to conduct any specific analyses between the cohorts from either study (current and present). The results mention a difference in the group mean values in "fitness level" between cohorts, but the analysis itself on pain responses/exercise-induced hypoalgesia is limited only to the cohort from the current study. If the authors wanted to provide a convincing argument that fitness level has an effect on exercise-induced hypoalgesia, then the analysis of this study would have to include an analysis between the groups considered to be of "high" and "low" fitness level. I do not think the current study does this. Instead, it makes an assumption from the previous study (Nold et al. 2025) which only states that "exploratory analysis showed a significant main effect of fitness level on differences in pain ratings in the [saline] condition... suggesting increased hypoalgesia with increasing fitness levels, pooled across all stimulus intensities". The analysis of this study would have to include fitness level "high fitness" versus "low fitness" of participants across both studies in its statistical model to properly discern if fitness level has an impact on exercise-induced hypoalgesia.

A similar comment can be made with respect to sex differences, as these have not been assessed in the analysis of this study either.

Another area of weakness in this study is how "fitness level" has been demarcated across participants. One issue is how authors have assumed that the current cohort is 'fit', whereas the previous cohort was 'less fit', meaning that the authors could be coming to false conclusions about fitness level. In detail, figures within the current study show a large overlap between the 'fit' and 'less fit' cohorts, where some participants have a higher relative functional threshold power (FTP) in the 'less fit' cohort than the 'fit' cohort and vice versa. Therefore, I believe the authors should better demarcate between those that are in the 'more fit' and 'less fit' groups according to a validated and well-established criterion from the kinesiology and sport science literature. That being said, I think this may be problematic in some ways as FTP is considered a relatively poor measure to denote fitness levels, a limitation highlighted in the previous study's review.

Altogether, whilst I commend the researchers on their body of work across the two studies, the current methods and analysis provide an incomplete assessment of their primary research question, and therefore, I would urge the authors to reconsider some of their methods/analysis and the framing of their results to better reflect the main research question they have attempted to answer. Likewise, I would recommend that readers ensure they consider the current results with caution until the authors have addressed some areas of concern which currently limit their main conclusions.

Reviewer #1 (Public review):

Summary:

This manuscript investigates how cellular NAD/NADH ratios are controlled in cancer cell lines in vitro. The authors build on previous work, which shows that serine synthesis is sensitive to NAD/NADH ratios and PHGDH expression. Here, the authors demonstrate that serine synthesis is variable across a panel of cell lines, even when controlling for expression of serine synthesis enzymes such as PHGDH. The authors show that cellular NAD/NADH ratios correlate with the ability to synthesize serine and grow in serine-deprived environments when PHGDH levels remain constant. Investigating this variability in NAD/NADH ratios, the authors find that the cells that can positively respond to serine deprivation are able to increase oxygen consumption and cellular NAD/NADH ratios. Cells that do not increase oxygen consumption in response to serine deprivation do not increase NAD/NADH ratios and cannot grow well without serine. The authors go on to show that in cells with the ability to increase oxygen consumption upon serine deprivation, PHGDH expression alone is sufficient to fully restore growth-serine; in cells that cannot increase oxygen consumption, both PHGDH expression and interventions to increase NAD/NADH ratios are required to increase growth. Thus, cells need both PHGDH and NAD/NADH increases to maximize serine synthesis in response to serine deprivation. The authors previously showed that lipid synthesis likewise requires NAD regeneration. Interestingly, one cell line that does not increase oxygen consumption in response to serine limitation tends to increase oxygen consumption in response to lipid deprivation; accordingly, depriving this cell line of lipids increases the synthesis of serine. Together, these findings show that how cells respond to nutrient deprivation is highly variable and that the response to nutrient deprivation (for example, whether or not oxygen consumption is increased) will determine how well cells tolerate depletion of nutrients with related biosynthetic constraints. This work sheds light on the complexity of cancer cell metabolism and helps to explain why it is difficult to predict which nutrients will be limiting to any cancer cell type or environment.

Strengths:

(1) The authors use multiple interventions to manipulate NAD/NADH ratios in cells.

(2) Experiments are well controlled and appropriately interpreted.

Comments on revised version:

The authors thoughtfully and thoroughly responded to all reviewer comments. The revised manuscript addresses the critiques.

Reviewer #1 (Public review):

Summary:

Eroglu and Hobert demonstrate that injecting CRISPR guides and repair constructs to target three genes at a time, tagging each with a different fluorescent protein, and selecting which gene to tag with which fluorophore based on genes' expression levels, can improve efficiency of gene tagging.

Strengths:

This manuscript demonstrates that three genes can be targeted efficiently with three different fluorophores. It also presents some practical considerations, like using the fluorophore least complicated by agar/worm autofluorescence for genes with low expression levels, and cost calculations if the same methods were used on all genes.

Weaknesses:

Eroglu has demonstrated in a previous publication that single-stranded DNA injection can increase efficiency of CRISPR in C. elegans, while inserting two fluorescent proteins and a co-CRISPR marker into three loci, and Paix et al 2015 demonstrated simultaneous insertion of two fluorescent tags. The current work is valuable and incremental advance. In general, I applaud the authors' willingness to strategize about how whole proteome tagging might be accomplished. I predict that the advance here will be one of many small advances that will get the field to that goal. The title oversells the advance presented, in my view, since seems like one among many key advances, and the first sentence of the Discussion seems a more apt summary of the key advance here.

Some injections targeted genes on the same chromosome together, which will create unnecessary issues when doing crossing that will be useful for some future experiments. This made me wonder if injecting 3 together really is helpful vs targeting each gene separately, since only 5 worms need to be injected. It cuts time down by 2/3, but perhaps avoiding targeting the same chromosome with two tags would be useful.

The limited utility of current blue fluorescent proteins makes me wonder if it's worth using at this stage, before there are better blue fluorescent proteins, or better yet, far red, to avoid issues with live imaging under phototoxic UV or near-UV illumination.

Reviewer #1 (Public review):

[Editor's 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 authors aimed to uncover novel therapeutic vulnerabilities in APC-mutant colorectal cancer (CRC), which constitutes the majority of CRC cases. They hypothesized that modulating oxygen-sensing pathways (via PHD inhibition) could disrupt adaptive stress responses in these tumours.

Strengths:

The study employs a powerful, two-pronged approach to identify Molidustat's targets. By using both Thermal Proteome Profiling (TPP) and an orthogonal chemical proteomic competition assay, the authors provide compelling evidence that GSTP1 is a genuine, direct off-target, effectively addressing the common limitation of indirect effects in proteomic screens.

Reviewer #1 (Public review):

Summary:

Knowing that small pupil-size variations accompany brightness variations (even when these are illusory), the authors asked whether pupil constrictions would accompany the synesthetic perception of a brighter color (compared with a darker one), induced by the presentation of a black-white character. This grapheme-colour synesthesia is only experienced by few participants, sixteen of whom were enrolled in this study. The results reliably showed that a relative pupil constriction would "betray" the perception of a brighter color in these participants, while no such effect would be observed in control participants who were asked to report a color in association with each grapheme, even though they did not perceive any.

Strengths:

The main strength of the study lays in its combination of psychophysics (brightness ratings) and pupillometry, which allowed for showing clear-cut results.

Weaknesses:

I only see the following relatively minor weaknesses, namely:

- The pupil traces in Figure3 (main results) are heavily pre-processed (per-participant demeaned), loosing any feature besides the effect of interest. As I argued in my first review, I worry that this format gives unrealistic expectations about the effect (the perception of dark/bright colors do not generate a net dilation/constriction of the pupil; perception-related modulations of pupil size are always relative and generally small compared to the numerous other effects registered in pupil size; these include a pupil dilation that is more prominent in the controls and that gets analyzed later on in the manuscript; I do not think that eliminating one of the effects of interests from a main results figure helps the reader understand the results). In the revised manuscript, the authors addressed this concern by adding a Supplementary Figure 4, where a more complete representation of the results is shown (traces from individual trials are baseline corrected and averaged, resulting in more informative timecourses). I would strongly recommend that Supplementary Figure4 is brought to the main text (Figure3 could be presented in Supplementary).

- Responses to physical brightness modulations were only measured in the synesthethes group, not in controls. The authors point out that pupillary light responses have been thoroughly characterized in previous studies, and conclude that synesthethes' responses were in line with the expectations both in terms of amplitude and latency. However, as we are not dealing with standardized measurements, subtle differences in pupil reactivity across the two populations remain a possibility. I recommend that this possibility is mentioned in the discussion.

Impact:

This work is likely to improve our understanding of synesthesia, providing a new tool to quantify the subjective sensations; an interesting potential extension would be using pupillometry for tracking changes over time of the synesthetic experiences, opening up the possibility to evaluate the importance of learning for this peculiar experience.

Reviewer #1 (Public review):

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

Strengths:

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

Weaknesses:

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

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

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

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

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

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

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

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

Comments on revisions:

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.

Reviewer #1 (Public review):

Summary:

Meijer et al. sought to investigate the role of cortical layer 6b (L6b) neurons in modulating sleep-wake states and cortical oscillations under baseline and sleep deprived conditions and in response to orexin A and B. Using chronic EEG recordings in mice with silencing of Drd1a+ neurons (via constitutive Cre-dependent knockout of SNAP25), the authors report that while overall baseline sleep-wake architecture and response to sleep deprivation are minimal/unchanged, "L6b silencing leads" to a slowing of theta activity during wakefulness and REM sleep, and a reduction in EEG power during NREM sleep. The manuscript is well written with clarity and transparency. Although Drd1a+ neurons are not exclusive to L6b, the authors describe key future studies to identify a causal role for L6b neurons in brain state regulation. These studies contribute to a growing body of evidence that cortex-in addition to subcortical brain regions-plays a role in brain state regulation.

Strengths:

(1) The text is well written.

(2) The authors are transparent about methodological details and study limitations.

(3) The stated sleep, circadian, and orexin infusion experiments are well designed, executed, and analyzed.

Weaknesses:

(1) Outcomes are attributed to silencing cortical L6b neurons, but the genetic manipulation is not specific to L6b neurons or cortex. The authors acknowledge this as a limitation and offer targets for future studies to identify L6b neuron-specific contributions to stated outcomes that include spatially restricted manipulations.

(2) Experiments use only male mice, which limits generalizability to females.

Comments on revised version:

The authors took great care in addressing my previous comments, and I do not have any additional concerns.

Reviewer #1 (Public review):

Summary:

This manuscript explores the role of the Evening Complex (EC), specifically focusing on ELF3, a disordered protein component of the EC, and its temperature-dependent phase behavior. The study highlights the role of polyQ tracts in modulating temperature-sensitive condensate formation and provides a combination of computational approaches, including REST2 simulations and coarse-grained Martini simulations, to investigate how polyQ tract length and sequence context influence this behavior.

Strengths:

The study addresses a key question in plant biology - how temperature influences circadian clock-mediated growth regulation through protein phase behavior. The manuscript introduces the novel finding that polyQ tract length modulates the temperature-dependent formation of helices and condensates.

Weaknesses:

(1) Coarse-Grained Simulation Results Not Supported by Data:

The results presented in Figure 6A of the manuscript do not seem to show a clear trend in the number of clusters formed as a function of polyQ tract length. This is particularly evident in the comparison between 0Q and 7Q polyQ lengths, which display statistically similar values in terms of the number of clusters. The lack of distinction between these values raises questions about the sensitivity of the coarse-grained simulations to polyQ tract length, which the authors claim as a key modulator of condensate formation. This discrepancy weakens the argument that polyQ length directly impacts the clustering behavior in the simulations.

Suggested Analysis:

a) A more detailed statistical analysis should be performed to assess whether the observed differences between polyQ lengths are significant. This could involve hypothesis testing or the use of error bars in the graphs to better communicate the variability in the data.

b) Additionally, the authors should examine whether there are other features, such as cluster shape or internal structure, that might differentiate between different polyQ lengths, even if the total number of clusters is similar.

(2) Inconsistency in Cluster Size Across Temperatures (Figure 6B):

The results in Figure 6B show a striking difference in the size of the largest cluster between temperatures of 290K and 300K. This abrupt shift in behavior lacks a clear mechanistic explanation. Typically, phase transitions driven by temperature are more gradual, unless there is some underlying structural or chemical shift that the authors have not accounted for. Without a clear explanation, this sudden change in behavior reduces confidence in the simulation results.

Suggested Analysis:

a) The authors should explore possible explanations for the dramatic difference in cluster size between 290K and 300K. For example, they could investigate whether specific interactions (such as the breaking or formation of hydrogen bonds or hydrophobic contacts) might explain the behavior at higher temperatures.

b) It is important to check whether the coarse-grained simulation model has been adequately parameterized and scaled for accurate temperature dependence. Atomistic simulations of monomers and dimers with varying polyQ tract lengths could be used to fine-tune the coarse-grained model, ensuring it accurately reflects molecular behavior. The gross estimate of a 10% scaling factor might be insufficient and could lead to inaccurate representations of cluster formation.

(3) Scaling of Coarse-Grained Model with Atomistic Simulations:

As mentioned, the coarse-grained model used in the study may not have been properly scaled against atomistic data. A simple scaling factor of 10% may not be appropriate for accurately capturing the behavior of polyQ tracts across different lengths, especially considering their sensitivity to subtle changes in temperature. Without rigorous validation against atomistic simulations, the coarse-grained model's predictions could be skewed.

Suggested Analysis:

a) To address this, the authors should compare the coarse-grained model with atomistic simulations of monomeric and dimeric forms of ELF3 with different polyQ tract lengths. By comparing key structural parameters (e.g., radius of gyration, contact maps, and clustering propensity), the authors could adjust the coarse-grained model to more accurately reflect the atomistic behavior. The authors have wealth of atomistic simulation data that could afford such benchmarking and identification of scaling factor

b) Additionally, the authors should investigate whether the assumed scaling factor of 10% is appropriate for each polyQ length or whether it needs to be refined based on specific properties, such as the number of hydrophobic interactions or secondary structure stability.

(4) Lack of Analysis for Liquid-Like Behavior in Phase Separation:

The simulations presented in the manuscript do not analyze the liquid-like behavior of ELF3 condensates, which is a key characteristic of liquid-liquid phase separation (LLPS). In LLPS systems, condensates are often dynamic, with chains exchanging between clusters, indicating liquid-like rather than solid-like behavior. The authors fail to probe this crucial aspect, which is necessary to support the claim that ELF3 undergoes phase separation.

Suggested Analysis:

a) The authors should conduct additional analyses to probe the liquid-like nature of the clusters formed by ELF3. One approach would be to analyze the dynamics of chain exchange between clusters, measuring how frequently chains leave one cluster and join another over time. This analysis would reveal whether the condensates behave as liquid-like, dynamic structures or more static, solid-like aggregates.

b) Additionally, the temperature dependence of these exchange dynamics should be investigated. In true liquid-liquid phase separation, the rate of chain exchange is often sensitive to temperature. Observing how this rate changes between 290K and 300K, for instance, could help explain the abrupt shift in cluster size seen in Figure 6B.

c) The authors should also analyze whether the internal structures of the condensates are consistent with a liquid-like phase. For example, radial distribution functions and contact lifetimes could be calculated to reveal whether the clusters exhibit liquid-like organization.

(5) Lack of justification of polydispersity of polyQ:

The authors don't provide any rationale for choice of different copies of polyQ used in the manuscript for their chain-growth simulation studies. It will be more apt if it can be motivated via some precedent experimental observations.

(6) Lack of initiative to connect to Experiments:

While the computational models and simulations provide robust theoretical insights, the absence of direct experimental validation weakens the overall impact of the manuscript. For example, experimental data on how specific mutations in the polyQ tract influence ELF3 behavior in vivo would significantly bolster the authors' claims. The manuscript would benefit from either citing existing experimental studies that corroborate these findings or from suggesting future experimental directions.

Comments on revised version:

The authors have now adequately addressed to the key concerns of manuscript. The manuscript in the present form looks significantly improved.

Reviewer #1 (Public review):

Summary:

The authors present a novel approach to subcellular spatial proteomics by combining laser microdissection with expansion microscopy and LC-MS/MS analysis (SPEx). They implement two different workflows for LMD and LC-MS/MS quantification:

(1)The standard approach, where an area of interest is cut out by LMD, subjected to proteomics analysis, and compared to the rest of the cell without the dissected ROI.

(2) The subtraction approach, where ROIs are removed, and the remaining cellular material is compared to samples containing both the surrounding material and the ROI.

The authors assess the technique by applying it to subcellular targets of various sizes, volumes, and protein compositions such as the nucleus, nucleoli, and Golgi. They demonstrate that SPEx can identify proteins enriched or reduced in ROIs.

Strengths:

The broad, relatively easy, and inexpensive applicability of this approach to potentially many cell types and subcellular areas of interest provides an exciting alternative to subcellular fractionation, native immunoprecipitation, or genetically encoded proximity labeling constructs. Moreover, by visually selecting ROIs for subsequent analysis, subcellular context or organelle morphology can be taken into account, as discussed by the authors in the discussion section.

Weaknesses:

While strongly supporting the sharing of this approach, we have a number of comments and questions that will improve the impact of the manuscript:

(1) General:

a) The manuscript would benefit from restructuring and language revision. In its current form, the writing is sometimes dense and verbose (in particular, the Results section). This makes it difficult to follow the authors' arguments.

b) The authors mention the possibility of selecting organelles based on morphology. This is left for the discussion, but it seems like a missed opportunity - the authors could compare individual organelles in different morphological states, e.g., connected vs. fragmented mitochondria.

(2) Technical:

a) Why do the authors strive and optimize for a 10x expansion factor? Is SPEx compatible with a more standard 4x expansion, as e.g., used in the classic U-ExM approach (https://www.nature.com/articles/s41592-018-0238-1)? This could be added to the discussion.

b) The U-ExM approach shows improved ultrastructural preservation when using 3%FA with 0.1% glutaraldehyde fixation (GA). Is SPEx compatible with the use of low amounts of GA for fixation?

c) Related to the above, was the anchoring efficiency reduced only to achieve a 10x expansion factor or does this additionally affect the proteome coverage?

d) Have the authors considered using alternative anchoring approaches, such as GMA (https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0291506#pone.0291506.s001), which potentially increase the amount of sample retained in the hydrogel, thus allowing for better proteome coverage? This could be added to the discussion.

e) The limitation of the approach to near-2D samples should be mentioned, and alternative approaches for more 3D samples could be discussed.

f) How are peptides that are directly anchored to the hydrogel dealt with during LC-MS/MS analysis? Are they excluded, or can they be identified during the spectral search? The latter would allow us to get a deeper structural understanding of how proteins are actually anchored into hydrogels, which so far has not been assessed.

An alternative approach to address this question would be to investigate if the peptide coverage of proteins detected by SPEx is enriched for peptides representing the folded core of proteins as opposed to the surface-exposed regions, which likely get more anchored into the hydrogel.

g) Same question regarding peptides with NHS labeling. Can they be identified, or do they just compete for ionization and thus negatively affect coverage and dynamic range of the LC-MS/MS approach?

h) How are the primary and secondary antibodies affecting the proteomics analysis identified as contaminants?

i) Have the authors observed differences in proteomics coverage of only antibody vs NHS-labeling? Depending on the questions above, could pure antibody-based labeling increase proteomic coverage?

Reviewer #1 (Public review):

Summary:

This study investigates a fundamental question in cognitive science: is our ability to reason about the physical world an abstract mental process, or is it "embodied"-directly rooted in our real-time physical interactions with the environment? The authors compared participants' performance in computerized reasoning games with and without Galvanic Vestibular Stimulation (GVS). They suggest that participants failed more often and utilized suboptimal strategies under GVS compared to a sham stimulation condition. Furthermore, they found that this detrimental effect of GVS was reduced when the games were governed by altered gravity (hyper- and hypo-gravity). Consequently, the authors conclude that the physical experience of the body modifies high-level cognitive skills, such as reasoning.

Strengths:

The manuscript is well-written, organized, and easy to follow, making complex concepts accessible. Also, combining a specialized physical reasoning task with real-time vestibular disruption (GVS) is an intriguing approach to testing the boundaries of embodied cognition.

Weaknesses:

(1) Lack of Overall Effects and Inflated Type I Error for Game-Level Effects

The study utilizes a within-subject design. Taking Study 1 as an example, each subject participated in a familiarization session (4 games), a baseline session (12 games without stimulation), a GVS session (14 games), and a sham session (14 games). No game was repeated for any single subject. Performance was quantified using three primary measures (success rate, number of attempts, and time per attempt) and two strategy measures (tool switching and the distance between tool placements).

For Study 1, to identify condition differences at the game level (i.e., Figure 2), the authors effectively conducted 70 independent t-tests (5 measures × 14 games). While 7 significant results were reported, this large number of independent tests invites an inflated Type I error rate, as no multiple-comparison correction appears to have been applied.

A similar inflation is expected in Study 2, where 50 independent t-tests (5 measures × 10 games) yielded 5 significant comparisons (Figure 4). Although the authors might argue the direction of the differences is systematic, implying GVS generally impairs performance, at least one significant comparison shows the opposite effect: tool switching indicates that GVS led to better performance for the 'Table_A' game in Study 2 (Figure 4d), whereas the same variable indicated GVS led to worse performance in Study 1 (Figure 2d). I suspect that none of the significant game-level results would survive a proper statistical correction. If possible, the authors can redo statistical testing with corrections (FDR or Bonferroni) or with LMM using game as a random effect. Before proper statistical analyses, I strongly encourage the authors to refrain from drawing broad conclusions based on these isolated game-level results.

Furthermore, when analyzing data across all games, the study found no significant effect of GVS on overall performance or strategy measures in either Study 1 or Study 2. This lack of an aggregate effect contradicts the authors' conclusion that participants failed more often or utilized suboptimal strategies under GVS.

(2) Missing Rationale for Classification Analysis

It is puzzling why the authors pursued two exploratory analyses on tool placement after revealing that the two related primary measures (tool positioning and switching) did not generate significant condition differences in Study 1. These additional analyses-the Dirichlet Process Gaussian Mixture Model and leave-one-out classification-were not pre-registered. In the absence of overall condition differences, the authors appear to be "doubling down" by applying sophisticated classification tools to the raw data without a clear prior rationale.

(3) Insufficient Evidence for the Reduced Effect of GVS Under Altered Gravity

To compare Study 1 and Study 2, the authors devised a "gravity-weighted index," but its definition is not sufficiently justified. The index assigns weights of 1, 2, and 3 to low-, medium-, and high-gravity-dependent games, respectively. The choice of these specific weights appears arbitrary, making the quantitative results difficult to interpret. More importantly, there is no citation or explanation regarding how these three levels of "gravity impact" were defined in the first place (Line 468). This index was also not pre-registered.

The authors state that for the success rate index, a value close to -1 indicates a large negative difference for GVS, 0 indicates no difference, and 1 indicates a large positive difference. These are theoretical bounds; the actual distribution of each index should be examined to validate such claims. However, the paper lacks descriptive statistics for this composite index.

Notably, the "reduction" of the GVS effect in altered gravity was only demonstrated in one of the five available indices (success rate, p = 0.046). In fact, the success rate in Study 2 was 66.7(sham) vs 67.3 (GVS) in Table 2. It is highly debatable whether this marginal result justifies the conclusion that GVS effects "were reduced when the games included reasoning about altered gravity".

(4) Questionable Assumptions Regarding Strategy

The authors assume that "big changes in tool positioning and frequent tool switching indicate poor evaluation of the failed outcome". This assumption is questionable. In solving this cognitive task, participants must explore and exploit solutions based on feedback. Large shifts in positioning or frequent tool switching might reflect active, adaptive exploration based on failed outcomes rather than a failure to evaluate them.

(5) Confounding Factors in GVS Interpretation

The central theoretical question is whether physical reasoning is grounded in physical experience. GVS is used here to manipulate that experience. However, GVS does not selectively target the vestibular nerve; it also activates distributed fronto-parietal attention networks and hippocampal circuits essential for any reasoning task. Additionally, the vestibular system is linked to the limbic system and the cerebellum, which regulate emotional reactivity and arousal. Because attention and emotion are likely affected by GVS, the authors should be much more cautious in attributing their behavioral findings solely to changes in the "physical experience of the body."

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors 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.

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, which 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 catalytically 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.

Strengths:

The biochemical analysis seems solid.

Weaknesses:

(1) 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?

(2) The structure figures all have omit maps for just the AMPPnP and the water, whereas the density for the acidic residues and their mutants is not shown.

Reviewer #1 (Public review):

Summary:

By using an established NAFLD model, choline-deficient high-fat diet, Barros et al show that LPS challenge causes excessive IFN-γ production by hepatic NK cells which further induces recruitment and polarization of a PD-L1 positive neutrophil subset leading to massive TNFα production and increased host mortality. Genetic inhibition of IFN-γ or pharmacological blockade of PD-L1 decreases recruitment of these neutrophils and TNFα release, consequently preventing liver damage and decreasing host death.

Since NAFLD is often accompanied by chronic, low-grade inflammation, it can lead to an overactive but dysfunctional immune response and increase the body's overall susceptibility to infections, therefore this is very important research question.

Strengths:

The biggest strength of the manuscript is vast number of mouse strains used.

Weaknesses:

After the review, there are still some open questions from my side:

(1) I would like the authors to defend their choice of diet type since this has not been done in the review/response to authors. In case they cannot, we need additional proof (HFD or WD model).

(2) Since the authors used same control groups (chow and HFCD), as required by the animal ethics committee, they must have power analysis test to show that the number of controls (but also in other groups) they used is enough to see the effect. Please provide it.

Reviewer #1 (Public review):

Summary:

This study asks whether synapses formed by the same broad neuronal class (excitatory pyramidal neurons, PN) adapt their presynaptic organization in a cortex-specific manner, comparing the prefrontal cortex (PFC) with the primary somatosensory cortex (S1). The authors combine sophisticated electrophysiology (paired recordings and extracellular minimal stimulation), pharmacological perturbations of presynaptic Ca²⁺-secretion coupling, bouton Ca²⁺ imaging, and mechanistic modeling. Across two prominent excitatory connections (Layer 5 (L5) PN-L5PN and L2/3-L5PN), they provide convergent evidence that mature PFC synapses operate with looser Ca²⁺ channel-release sensor coupling than their S1 counterparts.

Overall, the study provides an appealing mechanistic link between synaptic nano/micro-architecture and cortical-area specialization. The idea that PFC synapses retain a more "plasticity-favoring" presynaptic state, while the primary sensory cortex emphasizes reliability and timing precision, is potentially impactful for how we think about circuit computation and plasticity across cortical hierarchies.

Strengths:

A major strength is the multi-pronged experimental strategy. The paper first establishes robust, area-dependent differences in synaptic efficacy, reliability, timing, and short-term plasticity (facilitation prevailing in PFC versus depression in S1), using both paired recordings and minimal extracellular stimulation paradigms. The coupling interpretation is then directly supported by differential sensitivity to EGTA (and appropriate positive-control effects of fast chelators). Finally, volume-averaged calcium signals are reported to be similar across areas, arguing against trivial explanations based on gross differences in calcium influx, and the modeling provides a quantitative framework for interpreting the observed chelator effects.

Weaknesses:

Limitations are minor and concern interpretation/clarity rather than core results. Some key inferences rely on indirect readouts (chelator sensitivity, fluctuation analysis-derived parameters, bouton-averaged calcium signals), each of which carries assumptions and potential confounds that should be discussed more explicitly. In particular, the repatching paradigm for the paired-recording EGTA experiment, though very impressive, and the limited number of extracellular calcium conditions used for fluctuation analysis (three concentrations), can influence quantitative estimates and the confidence intervals around them.

Reviewer #1 (Public review):

Very nice and coherent body of work with appropriate in vitro to in vivo transition in methods.

Lovely and easy to follow figures that can be understood even without the manuscript.

My recommendation is that a sentence or two be added clearly stating the authors think nafamostat is off the table and suggest other approaches/drugs that might be considered instead of just making a general statement. I think all this can be done in a few sentences.

Gabexate was administered to a snakebite victim in this case report from about 20 years ago and also a good example of the now better recognized threat to pregnancy.

Nasu K, Ueda T, Miyakawa I. Intrauterine fetal death caused by pit viper venom poisoning in early pregnancy. Gynecol Obstet Invest. 2004;57(2):114-6. doi: 10.1159/000075676. Epub 2003 Dec 19. PMID: 14691344

Reviewer #1 (Public review):

Summary:

This study presents a new Bayesian approach to estimate importation probabilities of malaria combining epidemiological data, travel history, and genetic data through pairwise IBD estimates. Importation is an important factor challenging malaria elimination, especially in low transmission settings. This paper focus on Magude and Matutuine, two districts in south Mozambique with very low malaria transmission. The results show isolation-by-distance in Mozambique, with genetic relatedness decreasing with distances larger than 100 km, and no spatial correlation for distances between 10 and 100 km. But again strong spatial correlation in distances smaller than 10 km. They report high genetic relatedness between Matutuine and Inhambane, higher than between Matutuine and Magude. Inhambane is the main source of importation in Matutuine, accounting for 63.5% of imported cases. Magude, on the other hand, shows smaller importation and travel rates than Matutuine, as it is a rural area with less mobility. Additionally, they report higher levels of importation and travel in the dry season, when transmission is lower. Also, no association with importation was found for occupation, sex and other factors. These data have practical implications for public health strategies aiming malaria elimination, for example, testing and treating travelers from Matutuine in the dry season.

Strengths:

The strength of this study relies in the combination of different sources of data - epidemiological, travel and genetic data - to estimate importation probabilities, the statistical analyses.

Weaknesses:

The authors recognize the limitations related to sample size and the biases of travel reports.

Reviewer #1 (Public review):

Summary:

Sidarta-Oliveira et al. present TopOMetry, a novel dimensionality reduction method based on the eigendecomposition of approximated Laplace-Beltrami Operator. Shortly, TopOMetry is an iterative version of the existing spectral methods (e.g., Laplacian Eigenmap or Diffusion map). It approximates the Laplacian operators twice, once in a "phenotypic space" and then once again in the eigenbases space. By doing this the approximated operator will contain more information of the manifold, which allows for more robust and accurate downstream analyses.

Strengths:

- Introduces operator-native fidelity scores and Riemannian diagnostics to single-cell analysis, enabling researchers to evaluate and trust embeddings - functionality absent in prior methods.<br /> - The approach was rigorously tested based on synthetic and real single-cell RNA-seq datasets.<br /> - The package is well-made and easily scalable to millions of cells.<br /> - The comprehensive documentation helps the end-users to run desired analyses.

Weaknesses:

- The method is an extension of the current state-of-art methods, not a fundamentally new one.

Comments on revised version:

The revised manuscript partially addresses the concerns raised in the prior review. The jargon weakness has been substantially mitigated by relocating mathematical derivations to the Methods section and simplifying language in the main text; this weakness has been updated accordingly.

The introduction of operator-native fidelity scores and Riemannian diagnostics represents a meaningful addition and has been added to the Strengths. The benchmarking scope has also been notably expanded.

The core weakness - that the method is an extension of existing spectral methods rather than a fundamentally new contribution - remains unchanged, as the authors' rebuttal did not provide a sufficiently precise mathematical argument to overturn it.

Reviewer #1 (Public review):

Summary:

In this manuscript, Ding et al. use genetic mouse models to demonstrate that atrial trabeculation is more dependent on Tie1/Tie2 signaling than ventricular trabeculation. With additional experimentation that would support the current claims, the results may hold significant value, as atrial trabeculation remains an understudied phenomenon in cardiac biology with potential implications for atrial cardiomyopathy and atrial fibrillation.

Strengths:

Detailed characterization of atrial versus ventricular trabeculation across different developmental timepoints, and the use of appropriate animal models to address the scientific question at hand.

Weaknesses:

The authors have consistently treated mice with tamoxifen after ventricular, but not atrial, trabeculation has already started. As such, the observed cardiac phenotypes - where predominantly atrial trabeculation is affected - might be a mere consequence of the precise time window in which Tie1/2 signaling was impaired, rather than a direct measurement of its relative importance for atrial versus ventricular trabeculation. The conclusions of the paper may thus be significantly strengthened by depleting Tie1/2 signaling prior to the onset of ventricular trabeculation, as is done for atrial trabeculation.

Reviewer #1 (Public review):

Summary:

In this review paper, the authors describe the concept of neural correlates of consciousness (NCC) and explain how noninvasive neuroimaging methods fall short of being able to properly characterise an unconfounded NCC. They argue that intracranial research is a means to address this gap and provide a review of many intracranial neuroimaging studies that have sought to answer questions regarding the neural basis of perceptual consciousness.

Strengths:

The authors have provided an in-depth, timely, and scholarly contribution to the study of NCCs. First and foremost, the review surveys a vast array of literature. The authors synthesise findings such that a coherent narrative of what invasive electrophysiology studies have revealed about the neural basis of consciousness can be easily grasped by the reader. The authors also succeed in describing how single-cell recordings can interface with task-design to help mitigate the impact of confounded neural activity when searching for NCCs.

The review is also, to the best of my knowledge, the first review to specifically target intracranial approaches to consciousness and to describe their results in a single article. This is a credit to the authors - as it becomes ever harder to apply strict tests to theories of consciousness using methods such as fMRI and M/EEG, it is important to have informative resources describing the results of human intracranial research so that theorists will have to constrain their theories further in accordance with such data. Additionally, the authors provide a compelling case for single-celled research in consciousness science, despite the dominance of theories situated at the system and circuit level of analysis. As far as the authors were aiming to provide a complete and coherent overview of intracranial approaches to the study of NCCs, I believe they have achieved their aim.

Weaknesses:

Overall, I feel positive about this paper. The authors have addressed my comments from my previous review and I see no significant weaknesses in the current version.

Comment on revised version:

No comments - congratulations to the authors!

Reviewer #1 (Public review):

Summary

In this review paper, the authors describe the concept of neural correlates of consciousness (NCC) and explain how noninvasive neuroimaging methods fall short of being able to properly characterise an unconfounded NCC. They argue that intracranial research is a means to address this gap and provide a review of many intracranial neuroimaging studies that have sought to answer questions regarding the neural basis of perceptual consciousness.

Strengths

The authors have provided an in-depth, timely, and scholarly contribution to the study of NCCs. First and foremost, the review surveys a vast array of literature. The authors synthesise findings such that a coherent narrative of what invasive electrophysiology studies have revealed about the neural basis of consciousness can be easily grasped by the reader. The review is also, to the best of my knowledge, the first review to specifically target intracranial approaches to consciousness and to describe their results in a single article. This is a credit to the authors, as it becomes ever harder to apply strict tests to theories of consciousness using methods such as fMRI and M/EEG it is important to have informative resources describing the results of human intracranial research so that theorists will have to constrain their theories further in accordance with such data. As far as the authors were aiming to provide a complete and coherent overview of intracranial approaches to the study of NCCs, I believe they have achieved their aim.

Weaknesses

Overall, I feel positive about this paper. However, there are a couple of aspects to the manuscript that I think could be improved.

(1) Distinguishing NCCs from their prerequisites or consequences

This section in the introduction was particularly confusing to me. Namely, in this section, the authors' aim is to explain how intracranial recordings can help distinguish 'pure' NCCs from their antecedents and consequences. However, the authors almost exclusively describe different tasks (e.g., no-report tasks) that have been used to help solve this problem, rather than elaborating on how intracranial recordings may resolve this issue. The authors claim that no-report designs rely on null findings, and invasive recordings can be more sensitive to smaller effects, which can help in such cases. However, this motivation pertains to the previous sub-section (limits of noninvasive methods), since it is primarily concerned with the lack of temporal and spatial resolution of fMRI and M/EEG. It is not, in and of itself, a means to distinguish NCCs from their confounds.

As such, in its current formulation, I do not find the argument that intracranial recordings are better suited to identifying pure NCCs (i.e. separating them from pre- or post-processing) convincing. To me, this is a problem solved through novel paradigms and better-developed theories. As it stands, the paper justifies my position by highlighting task developments that help to distinguish NCCs from prerequisites and consequences, rather than giving a novel argument as to why intracranial recordings outperform noninvasive methods beyond the reasons they explained in the previous section. Again, this position is justified when, from lines 505-506, the authors describe how none of the reported single-cell studies were able to dissociate NCCs from post-perceptual processing. As such, it seems as if, even with intracranial recording, NCCs and their confounds cannot be disentangled without appropriate tasks.

The section 'Towards Better Behavioural Paradigms' is a clear attempt to address these issues and, as such, I am sure the authors share the same concerns as I am raising. Still, I remain unconvinced that the distinguishing of NCCs from pre-/post- processing is a fair motivation for using intracranial over noninvasive measures.

(2) Drawing misleading conclusions from certain studies

There are passages of the manuscript where the authors draw conclusions from studies that are not necessarily warranted by the studies they cite. For instance:

Lines 265 - 271: "The results of these two studies revealed a complex pattern: on the one hand, HGA in the lateral occipitotemporal cortex and the ventral visual cortex correlated with stimulus strength. On the other hand, it also correlated with another factor that does not appear to play a role in visibility (repetition suppression), and did not correlate with a non-sensory factor that affects visibility reports (prior exposure). These results suggest that activity in occipitotemporal cortex regions reflecting higher-order visual processing may be a precursor to the NCC but not an NCC proper."

It's possible to imagine a theory that would predict HGA could correlate with stimulus strength and repetition suppression, or that it would not correlate with prior exposure (e.g. prior exposure could impact response bias without affecting subjective visibility itself). The authors describe this exact ambiguity in interpretation later in the article (line 664), but in its current form, at least in line 270 (when the study is most extensively discussed), the manuscript heavily implies that HGA is not an NCC proper. This generates a false impression that intracranial recordings have conclusively determined that occipitotemporal HGA is not a pure NCC, which is certainly a premature conclusion.

Line 243: "Altogether, these early human intracranial studies indicate that early-latency visual processing steps, reflected in broadband and low gamma activity, occur irrespective of whether a stimulus is consciously perceived or not. They also identified a candidate NCC: later (>200 ms) activity in the occipitotemporal region responsible for higher-order visual processing."

The authors claim in this section that later (>200ms) activity in occipitotemporal regions may be a candidate for an NCC. However, the Fisch et al. (2009) study they describe in support of this conclusion found that early (~150ms) activity could dissociate conscious and unconscious processing. This would suggest that it is early processing that lays claim to perceptual consciousness. The authors explicitly describe the Fisch et al results as showing evidence for early markers of consciousness (line 240: '...exhibited an early...response following recognized vs unrecognised stimuli.) Yet only a few lines later they use this to support the conclusion that a candidate NCC is 'later (>200ms) activity in the occipitotemporal region' (line 245). As such, I am not sure what conclusion the authors want me to make from these studies.

This problem is repeated in lines 386-387: "Altogether, studies that investigated the cortical correlates of visual consciousness point to a role of neural responses starting ~250 ms after stimulus onset in the non-primary visual cortex and prefrontal cortex."

This seems to be directly in conflict with the Fisch et al results, which show that correlates of consciousness can begin ~100ms earlier than the authors state in this passage.

(3) Justifying single-neuron cortical correlates of consciousness

The purpose of the present manuscript is to highlight why and how intracortical measures of neural activity can help reveal the neural correlates of perceptual consciousness. As such, in the section 'Single-neuron cortical correlates of perceptual consciousness', I think the paper is lacking an argument as to why single-neuron research is useful when searching for the NCC. Most theories of consciousness are based around circuit or system-level analyses (e.g., global ignition, recurrent feedback, prefrontal indexing, etc.) and usually do not make predictions about single cells. Without any elaboration or argument as to why single-cell research is necessary for a science of consciousness, the research described in this section, although excellent and valuable in its own right, seems out of place in the broader discussion of NCCs. A particularly strong interpretation here could be that intracranial recordings mislead researchers into studying single cells simply because it is the finest level of analysis, rather than because it offers helpful insight into the NCCs.

(4) No mention of combined fMRI-EEG research

A minor point, but I was surprised that the authors did not mention any combined fMRI-EEG research when they were discussing the limits of noninvasive recordings. Intracortical recordings are one way to surpass the spatial and temporal resolution limits of M/EEG and fMRI respectively, but studies that combine fMRI and EEG are also an alternative means to solve this problem: by combining the spatial resolution of fMRI with the temporal resolution of EEG, researchers can - in theory - compare when and where certain activity patterns (be they univariate ERPs or multivariate patterns) arise. The authors do cite one paper (Dellert et al., 2021 JNeuro) that used this kind of setup, but they discuss it only with respect to the task and ignore the recording method. The argument for using intracranial recordings is weaker for not mentioning a viable, noninvasive alternative that resolves the same issues.

Reviewer #1 (Public review):

Summary:

LRRK2 protein is familially linked to Parkinson's disease by the presence of several gene variants that confer a gain-of-function effect on LRRK2 kinase activity.

The authors examine the effects of BDNF stimulation in immortalized neuron-like cells, cultured mouse primary neurons, hIPSC-derived neurons, and brain tissue from genetically modified mice. They examine a LRRK2 regulatory phosphorylation residue, LRRK2 binding relationships, other kinase phosphorylation status, and measures of synaptic structure and function.

Strengths:

The study addresses an important research question: how does a PD-linked protein interact with other proteins, and contribute to responses to a well-characterized neuronal signalling pathway involved in the regulation of synaptic function and cell health.

They employ a range of models and techniques to convincingly demonstrate that BDNF stimulation alters LRRK2 phosphorylation at pS935 and binding to many proteins. Several independent data sets lead to some exciting conclusions.<br /> In this re-revised manuscript, some aspects are very convincing and well validated e.g., drebrin binding to LRRK2, increased by BDNF, and reduced LRRK2 protein levels in young (but not mature) drebrin KO mice. A phosphoproteomic analysis of PD mutant Knock-in mouse brain is included. Overall, the links between LRRK2, LRRK2 activity, and the changes to synaptic molecules, structures, and activity are intriguing.

Weaknesses:

Enthusiasm for the title claim that "LRRK2 regulates synaptic function through BDNF signalling" is tempered by disconnected results across different model systems and inconsistent alterations upon kinase phosphorylation in SHSY5Y cell line and primary neurons. Exciting conclusions are sometimes not consistently supported by the data and/or only conducted in one of the models.

BDNF increasing pS935 LRRK2 is quite well supported in cell lines, as is BDNF regulation of derbrin-LRRK2 binding. However, there is a lack of connection between this result and subsequent alterations to LRRK2 substrates e.g., phosphorylation of Rab GTPases, especially in neurons. Interesting omic data sets are provided, but with very little or no validation. For example, only drebrin protein was assessed in BDNF treatment omic, and the phosphoproteomic analysis of PD mutant Knock-in mouse is stand alone with no validation and G2019S is not explored elsewhere in the study.

The major disconnect this reviewer struggles with is the conclusion that the quite clear data in SHSY5Y cells is the same as that from neurons regarding BDNF / LRRK2 and ERK / Akt. It seems they are not.

ERK and Akt phosphorylation by BDNF is absent in CRISPR KO SHSY5Y cells.<br /> This conclusion is at odds with interpretation of neuronal data. To explain; in div14 neurons, BDNF's transient increase in pLRRK2 is seen and strongly prevented by MLi2. BDNF also increased pAkt & pERK1&2 in WT... but also in LRRK2 KO. Furthermore, this happened in the presence of MLi2 in WT despite no pLRRK2 increase. While the 5min BDNF induced increase to pAkt appears reduced in LKO, the same time BDNF in LKO with MLi2 is as high as WT (in these unquantified examples) and ERK is almost identical. This is described as "significantly reduced" but I see no replicates or quantification, and face value assessment of the blot argues against this.<br /> Thus, there is little or no evidence supporting that LRRK2 activity is involved in BDNF-stimulated increases in pAkt or pERK, upstream, in neurons as neither Mli2 nor KO prevented this.

Synapse markers increased in WT neuron with BDNF treatment which did not happen in LKO neurons. So this process requires pLRRK2, but is unrelated to pAkt or pERK (which do still go up with BDNF in KO)? Similarly, an increase in synaptic activity in WT hiPSC neurons in response to BDNF seems lost in LRRK2 KO hiPSC neurons, although their activity is already increased and depending on the age of the cells the effects were different. Both of these experiments lack supporting evidence by other measures e.g., LRRK2 inhibition effects on BDNF-induced increases in WT and parallel biochemistry of p'd LRRK2, Akt, ERK in WT & KO.

LRRK2 activating Akt1 has been published before (e.g., Ohta 2011 - not cited), but Ohta also conclude that LRRK2 gain of function mutations (more LRRK2 kinase activity) were associated with a reduced ability of LRRK2 to bind AND phosphorylate Akt at the same residue, in contradiction to the mechanism proposed here? This should be discussed. Here the authors also conclude Akt is Upstream of LRRK2. However, it appears from the data here in neurons that pLRRK2 increases in response to BDNF are separate from BDNF signalling to Akt.

Of note, in comparison to bTubulin control, LKO total Akt levels appear consistently higher in this single example blot; a large increase in Akt would skew the ratio down, while absolute levels of pAkt (probably the most important matter for an active enzyme - what is the ratio against total protein stain) are similar or increased. These are major problems for the conclusions as presented.

BDNF increased mEPSC frequency in hIPSC neurons; which didn't happen in LKO, which already had high frequency. Earlier in the manuscript BDNF is shown to alter synapse number in WT but not LKO mouse neurons, but no increase in synapse number was seen following BDNF treatment in any WT or LKO hiPSC neurons +/- BDFN.

If we are to assume that the WT neurons have LRRK2 (not demonstrated), and that LRRK2 KO neurons have similar drebrin (not demonstrated) it is unclear how to interpret this result in the model of BDNF-LRRK2 being upstream of pERK/Akt. There is no evidence that the BDNF increase in WT is blocked by LRRK2 inhibition, nor has it been associated with changes (or not) to pAkt or ERK1, which would be expected in both WT and KO based on Figure 4C.

There are many reports of acute and longer term BDNF application increasing event frequency in brain slices & primary neurons. Overexpression of BDNF in NPCs has also been shown to increase synapse function in hiPSC neurons derived from them. Here, BDNF has an effect on frequency in only one 6 comparisons (3 timepoints, two lines). Is it not concerning that expected BDNF effects occur at only one time point in WT, and that generally a lack of effect is more common both in WT and LKO... is this due to slow appearance of TrkB receptors and degeneration at 90 days?

There are no other data provided to show that BDNF was having a consistent expected effect in human neurons (pAkt, pLRRK2 etc etc), and there is little to link between this data and that in previous figures of the study.

The discussion of some of the weaknesses is mostly fair, asides the disparities noted above which are not.

Reviewer #2 (Public review):

Summary:

The authors investigated whether early-life malaria exposure has long-term effects on immune responses to unrelated antigens. They leveraged a natural experiment in coastal Kenya where two adjacent communities (Junju and Ngerenya) experienced divergent malaria transmission patterns after 2004. Using 15 years of longitudinal data from 123 children with weekly malaria surveillance and annual serological sampling, they measured antibody responses to multiple pathogens using a protein microarray technology and ELISA.

Strengths:

(1) Extensive longitudinal data collection with weekly malaria surveillance, enabling precise exposure classification.

(2) Use of a natural experiment design that allows for causal inference about malaria's immunological effects.

(3) Broad panel of antigens tested, demonstrating generalized rather than antigen-specific effects.

(4) Within-cohort analysis in Ngerenya controls for geographic and environmental factors.

(5) Validation of key findings using both serologic microarray and ELISA.

(6) Important public health implications for vaccine strategies in malaria-endemic regions.

Weaknesses:

(1) Due to its nature, the study lacks the ability to determine the direction of the associations found between malaria exposure and other IgG levels to unrelated pathogens.

(2) No evaluation of the clinical Implications of the reduced IgG levels observed in the area with high malaria exposure.

Assessment of Claims:

The data appear to support the authors' primary claims. The strength of the evidence is limited by the observational nature of the study and the results should be interpreted in that light. Together with the currently available evidence of P. falciparum's impact on the host's immune function, this natural experiment design provides further evidence for a relationship between early malaria exposure and reduced antibody responses to other pathogens and vaccine-derived antigens. The within-Ngerenya analysis controls for geographic factors and thus enhances the quality of the evidence; there is limited physical, nutritional, and socio-economic information on factors that may have driven the observed changes.

Impact and Utility:

This work has fundamental implications for understanding vaccine effectiveness in malaria-endemic regions and may contribute to inform vaccination strategies. The findings, if confirmed, would suggest that children in areas of high malaria transmission may require modified immunization approaches. The dataset provides a valuable resource for future studies of malaria's immunological legacy.

Context:

This study builds on prior work showing acute immunosuppressive effects of malaria but uniquely attempts to demonstrate the durability of these effects years after exposure. The natural experiment design addresses limitations of previous observational studies by providing a more controlled comparison.

Reviewer #1 (Public review):

Sebag et al. addressed the role of ADH5 in BAT in the development of aging and metabolic disarrangements associated with it. This is a follow-up study after the authors' demonstration of the role of BAT ADH5 in glucose homeostasis, obesity, and cold tolerance. By ablating ADH5 specifically in brown adipocytes or pharmacologically modulating ADH5 through activation of its transcription factor, the authors conclude that preservation of BAT function is crucial for healthy aging and ADH5 is causally involved in this process. The topic is appealing given the rise in the aging population and the unclear role of BAT function in this process. Overall, the study uses several techniques and addresses several physiological and molecular manifestations of aging. Therefore, the findings contribute to the growing body of literature pointing to the biological role of BAT activity in aging.

Comments on revised version:

I have no further comments other than to congratulate the authors on the nice piece of work.

Reviewer #1 (Public review):

Summary:

In their manuscript, Metz Reed and colleagues present an exceptionally thorough analysis of three-dimensional genome reorganization during breast cancer progression using the well-characterized MCF10 model system. The integration of high-resolution Micro-C contact maps with multi-omics profiling provides compelling insights into stage-specific dynamics of chromatin compartments, TAD boundaries, and looping events. The discovery that stable chromatin loops enable epigenetic reprogramming of cancer genes while structural changes selectively drive metastasis-associated pathways represents a significant conceptual advance. This work substantially deepens our understanding of genome topology in malignancy.

Strengths:

This work sets a benchmark for integrative 3D genomics in oncology. Its methodological sophistication and conceptual advances establish a new paradigm for studying nuclear architecture in disease.

Comments on revised version:

The authors made a significant effort to improve the manuscript. My comments were sufficiently addressed.

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.

Weaknesses:

For readers to appreciate the value of patient experiments derived from a single individual, the authors should quote prior studies showing that STX11 protein levels are abolished in all known human STX11 mutations. The priming model, while functionally well-supported, rests on indirect structural evidence, and the precise conformational transition involved remains to be defined. These are acknowledged limitations, but alternate mechanisms have not been explored and formally excluded. More direct evidence should be provided to exclude the possibility that STX11 could act as a conventional SNARE and sustain calcium fluxes by promoting the delivery of additional ORAI1 channels from vesicles.

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.

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.

Weaknesses:

(1) No spatial pattern emerges. There are some isolated colonies that turn on the downstream FPs, but I do not see a pattern, really. Nonetheless, some colonies do differentiate (i.e. they turn on additional FPs).

(2) The mathematical model appears somewhat superfluous. While it can clearly reproduce the data, it is not used to make interesting predictions, changing parameters (and not initial conditions) that guide further experimental implementations.

Future directions

The utility of this differentiation process (e.g. in metabolic engineering or for the study of biofilm formation and antibiotic resistance) will become clearer once the FPs are substituted with functional proteins that exert an effect on the cells.

Reviewer #1 (Public review):

Summary:

The metabolic profiles of immune cells under steady-state or immune-activated conditions remain poorly characterized. The authors find that embryonically derived hemocytes in Drosophila larvae predominantly utilize mitochondrial respiration to generate energy and exhibit minimal glycolysis rates under unchallenged conditions. Hemocytes developmentally elevate ATP production rates. Mitochondrial respiration drives metabolic activation in larval hemocytes. More specifically, lamellocytes exhibit unique metabolic activities, including enhanced trehalose catabolism and mitochondrial remodeling, required for their encapsulation response.

Strengths:

The study shows the metabolism that is most likely to operate in different immune cells in Drosophila during development and also during infection. This is related to mitochondrial organization and proliferation and/or differentiation state.

Weaknesses:

Even though there is a rigorous analysis of mitochondrial activity using the Sea Horse analyzer, the analysis of diverse mitochondrial activities in the different immune cell types across development and in infection could be carried out using microscopy. ROS, mitochondrial membrane potential, NADH/+ and FADH/+ levels in vivo are likely to give a more specific readout of change in cellular activities. The activities of mitochondrial fusion and fission need to be collectively tested to understand their role in development and also in infection. The relevance of the change in mitochondrial activity for development or immunity remains to be tested.

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

Strengths:

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

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

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

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 provided new data and text that addresses all of the reviewers' comments on the previous versions in a wholly satisfactory way.]

Summary:

This study presents evidence that addition of the two GTPases EngA and ObgE to reactions comprised of rRNAs and total ribosomal proteins purified from native bacterial ribosomes can bypass the requirements for non-physiological temperature shifts and Mg+2 ion concentrations for in vitro reconstitution of functional E. coli ribosomes.

Strengths:

This advance allows ribosome reconstitution in a fully reconstituted protein synthesis system containing individually purified recombinant translation factors, with the reconstituted ribosomes substituting for native purified ribosomes to support protein synthesis. This represents a significant development in the long-term effort to produce synthetic cells.

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.]

The paper from Hudait and Voth details a number of coarse-grained simulations as well as some experiments focused on the stability of HIV capsids in the presence of the drug lenacapavir. The authors find that LEN hyperstabilizes the capsid, making it fragile and prone to breaking inside the nuclear pore complex.

Comments on previous round of revisions:

I found that the authors addressed my concerns satisfactorily. The other reviewer raised a number of important points regarding the nuances of the model and the interpretation of the simulations, which the authors rebutted. I think the paper in its current form now is a worthwhile addition to the literature.

Reviewer #1 (Public review):

Summary:

Zinn and colleagues investigated the role of proteases 2A and 3C of enterovirus D68 (EVD68), an emerging pathogen associated with outbreaks of acute flaccid myelitis (AFM), a polio-like disease, on the nucleocytoplasmic trafficking in different systems, including human neurons derived from pluripotent cells. They found that 2A specifically cleaved Nup98 and POM121. Using reporter proteins and RNA synthesis and trafficking assays in cells expressing viral proteases, they showed that 2A induces broad loss of the nuclear pore barrier function, but, surprisingly, the RNA export appears to be minimally affected. Since nucleocytoplasmic trafficking defects are known to be associated with neuropatologies, they propose a hypothesis that 2A-dependent cleavage of nucleoporins in motoneurons underlies the development of EVD68-induced AFM. They further show that a 2A-specific inhibitor increases the survival of human neurons differentiated from stem cells upon EVD68 infection.

Strengths:

Use of multiple methods to investigate the effect of 2A and 3C expression on nucleoporin cleavage and nucleocytoplasmic trafficking.

Comments on revisions:

The following issues remain unresolved:

First, the authors still do not show representative images confirming specific nucleoporin degradation (Fig.1), which is the main focus of the work.

Second, the conclusion that 2A-mediated degradation of the nucleo-cytoplasmic barrier does not affect export of the RNA from the nucleus is not supported by the presented data. The representative images shown in Fig 3C do not have the signal for GFP (like in Fig. 2), and therefore it is impossible to see if those cells indeed express EVD68 proteases.

Moreover, to show RNA export, not only the decrease of nuclear EU signal should be quantified, but also the increase of the cytoplasmic signal. The diminishing of the nuclear staining may not necessarily reflect RNA export, but may well be explained by nuclease activity, all the more relevant in cells expressing 2A, where the nuclear-cytoplasmic barrier is disrupted and cytoplasmic nucleases may enter the nucleus.

The same applies to images in Fig. 3D. There are no markers of infection; moreover, the experiment description indicates that EU labeling began at 24 h post-infection with an MOI of 5, i.e., essentially all cells should have been infected. This is difficult to believe as the replication cycle of most EVD68 strains in HeLa cells is no longer than 12 h, yet the images do not show any signs of CPE, and demonstrate a strong EU signal, inconsistent with the expected inhibition of nuclear transcription, a known attribute of enterovirus infections.

The claim that nuclear transcription and RNA export remain unaffected in conditions of 2A-mediated disruption of the nucleo-cytoplasmic barrier is very strong and requires equally strong evidence.

Reviewer #1 (Public review):

Summary

Fogel & Ujfalussy report an extension of a visualization tool that was originally designed to enable an understanding of detailed biophysical neuron models. Named "extended currentscape", this new iteration enables visual assessment of individual currents across a neuron's spatially extended dendritic arbor with simultaneous readout of somatic currents and voltage. The overall aim was to permit a visually intuitive understanding for how a model neuron's inputs determine its output. This goal was worthwhile and the authors achieved it. Demonstrating the utility of extended currentscape, the authors leverage their models to generate interesting and detailed biophysical insights into widely studied neurophysiological phenomena with clear behavioral relevance. Overall, this study provides a valuable and well-characterized biophysical modeling resource to the neuroscience community.

Strengths

The authors significantly extended a previously published open-source biophysical modeling tool. Beyond providing important new capabilities, the potential impact of extended currentscape is boosted by its integration with preexisting resources in the field.

In keeping with the authors' goal to provide an approachable platform with intuitive visualizations of how current flows through neurons, the manuscript is approachable to non-computationalists. In particular, a dedicated glossary and elegant illustrations in Figure 2 boost accessibility for biologists.

Extended currentscape produces intriguing and detailed predictions spanning neurophysiological phenomena such as local dendritic spikes, complex spike generation, and feature selectivity (hippocampal place fields). By triggering analysis of modeled synaptic inputs on these events, the authors trace their origins from dendritic integration to synaptic input patterns.

The authors cleverly apply a graph theoretical approach to efficiently model bidirectional current flow throughout a neuron's dendritic arbor. As a result, extended currentscape can run on a standard personal computer.

The code is well-documented and freely available via GitHub.

Weaknesses

While extended currentscape meets its objective of modeling and illustrating the propagation of axial currents throughout a model neuron in great detail, it requires simulation and measurement of synaptic input currents. For this reason, there currently exists a very high technical barrier to conclusively test its intriguing predictions: simultaneous readout of synaptic inputs throughout a neuron's dendritic arbor. Mitigating this weakness, the authors propose a relatively more feasible alternative approach in Discussion: simultaneous voltage imaging of dendrites and their soma while estimating synaptic inputs from the distributions of voltage dynamics along individual dendritic branches.

Reviewer #1 (Public review):

Summary:

In this article by Xiao et al. the authors aimed to identify the precise targets by which magnesium isoglycyrrhizinate (MgIG) functions to improve liver injury in response to ethanol treatment. The authors found through a series of in-vivo and molecular approaches that MgIG treatment attenuates alcohol-induced liver injury through a potential SREBP2-IdI1 axis. The revised manuscript adds to a previous set of literature showing MgIG improves liver function across a variety of etiologies, and also provides mechanistic insight into its mechanism of action. All major weaknesses were addressed in the revised submission.

Strengths:

(1) The authors use a combination of approaches from both in-vivo mouse models to in-vitro approaches with AML12 hepatocytes to support the notion that MgIG does improve liver function in response to ethanol treatment.

(2) The authors use both knockdown and overexpression approaches, in-vivo and in-vitro, to support most of the claims provided.

(3) Identification of HSD11B1 as the protein target of MgIG, as well as confirmation of direct protein-protein interactions between HSD11B1/SREBP2/IDI1 is novel.

Weaknesses:

The authors addressed all my concerns.

Reviewer #2 (Public review):

In this paper, Biswas et al. describe the role of acetylcholine (ACh) signaling in protection against chronic oxidative stress in C. elegans. They showed that disruption of ACh signaling in either unc-17 mutant or gar-3 mutants led to sensitivity to toxicity caused by chronic paraquat (PQ) treatment. Using RNA seq, they found that approximately 70% of the genes induced by chronic PQ exposure in wild type failed to upregulate in these mutants. The overexpression of gar-3 selectively in cholinergic neurons was sufficient to promote protection against chronic PQ exposure in an ACh-dependent manner. The study points to a previously undescribed role for ACh signaling in providing organism-wide protection from chronic oxidative stress likely through the transcriptional regulation of numerous oxidative stress-response genes. The paper is well-written, and the data are robust. While the study identifies the muscarinic ACh receptor gar-3 as an important regulator of the response to PQ, the specific neurons in which gar-3 functions were not unambiguously identified, and the sources of ACh that regulate GAR-3 signaling and the identities of the tissues targeted by gar-3 remain unknown.

Comments on revisions:

No further comments.

Reviewer #1 (Public review):

Summary:

In the manuscript "Conformational Variability of HIV-1 Env Trimer and Viral Vulnerability", the authors study the fully glycosylated HIV-1 Env protein using an all-atom forcefield. It combines long all-atom simulations of Env in a realistic asymmetric bilayer with careful data analysis. This work clarifies how the CT domain modulates the overall conformation of the Env ectodomain and characterizes different MPER-TMD conformations. The authors also carefully analyze the accessibility of different antibodies to the Env protein.

Strengths:

This paper is state-of-the-art given the scale of the system and the sophistication of the methods. The biological question is important, the methodology is rigorous, and the results will interest a broad elife audience. The authors also establish strong connections to previous literature and acknowledge the limitations of the CT-truncated protein construct, which enhances the manuscript's relevance to the community.

Reviewer #1 (Public review):

Summary:

There is evidence that some genes encode mRNAs from which separate processed transcripts may arise, separating the coding sequence (CDS) from the 3'-UTR, and with both mRNA elements remaining stable in the cell. However, the functional consequences of these mRNA fragments have not been firmly established. In the manuscript by Yang et al., the authors probe the mRNA domain architecture of Nanog in the context of embryonic stem cell colonies and blastocysts. The authors detect spatial separation of Nanog CDS-containing mRNA from abundant Nanog 3'-UTR RNAs depending on the cell position in 2D embryonic stem cell colonies or in blastocysts.

Strengths:

The phenotypic analyses of the Nanog mRNA hold promise for revealing distinct roles for the Nanog encoded protein and a separate RNA encompassing the Nanog 3'-UTR.

Weaknesses:

There are a number of questions about the molecular nature of the mRNA species that the authors should address in order for the results to be firmly established, as noted below.

(1) It is not clear how the authors verified that their probes are specific for Nanog CDS or 3'-UTR regions. Especially for the 3'-UTR probe, it is confusing why colonies show green only regions, suggesting only the CDS is present. I would expect the CDS and 3'-UTR probes to colocalize in the interior cells. Is it possible that the 3'-UTR probe is targeting another RNA?

(2) It would help for the authors to include a graphic similar to Figure 3, Figure Supplement 1A, that diagrams the location of the CDS and 3'-UTR probes (this should also be done for Oct4 and Sox2). This graphic could also show all potential polyadenylation signals.

(3) I think, based on the fluorescence patterns, there is evidence that the signal for the Nanog 3'-UTR probe is nuclear (images with DAPI staining), but this is not commented on that I could find. This should be discussed, as nuclear retention has implications for the noncoding function of the 3'-UTR fragment.

(4) Figure 2, Figure Supplement 1A needs a better explanation. It's not clear how the reads map to the different regions of the Nanog mature mRNA. The authors should show examples at different ratios of CDS to 3'-UTR. Do the reads have a sharp boundary at the junction of where the isolated 3'-UTR is thought to occur?

(5) I looked in the Zenbu browser at human NANOG CAGE mapping in the FANTOM5 dataset. I could not see evidence for substantial capping of a 3'-UTR fragment when filtering for embryonic cell types. Given the strong signal for the 3'-UTR in border cells, I would expect to see evidence for capping if the RNA were indeed capped. This suggests that if it exists, it is likely uncapped and (as noted in point 3) is likely nuclear retained.

(6) Are there predicted polyadenylation signals near the end of the CDS that would generate a short 3'-UTR, and are these signals conserved across mammals?

(7) It would help to see a zoomed-in view of the region targeted by one of the guide RNAs in the 3'-UTR, and where that site is relative to the polyadenylation signal. Is the polyadenylation signal upstream, i.e., CDS proximal?

(8) A final note, the use of green and red together will be challenging for those who are colorblind. Providing a different false color palette would be helpful.

I am refraining from comments on the cell biology and morphological insights, as they are remote from my core expertise.

Reviewer #1 (Public review):

Summary:

Dalben et al. grafted the fusion loop mature (FLM) modification, based on a previously reported D2-FLM, to another serotype DENV4, and adapted them to replicate in Vero cells for live attenuated vaccine (LAV) manufacturing while retaining favorable antigenic profiles, generating two new strains: D2-vFLM and D4-vFLM. Deep sequencing revealed adapted mutations at the junction of envelope domains I and II (EDI and EDII), and both D2-vFLM and D4-vFLM showed no evidence of ADE in the presence of FL-targeting Abs. Sera from D2-vFLM immunized mice displayed strong homotypic and reduced heterotypic neutralization compared to wild-type viruses, with minimal to no ADE potential in vitro. Moreover, D2-vFLM immunization completely protected AG129 mice from lethal challenge with mouse-adapted D220. They demonstrate that the FLM modification platform is transferable across serotypes and yields strains with favorable immunogenicity and reduced ADE risk. The FLM approach provides a promising path toward the development of a safer tetravalent DENV LAV.

Strengths:

The authors carried out a series of experiments to generate and characterize two new strains (D2-vFLM and D4-vFLM) of FLM-modified viruses, and showed their antigenic and immunogenic profiles. The observation that the FLM modification platform is transferable across serotypes and yields strains with favorable immunogenicity and reduced ADE risk is interesting.

Weaknesses:

However, one concern is the total number of mutations (including originally introduced and compensatory mutations) in this FLM vaccine platform, and it is not clear regarding the future directions for the proof-of-concept vaccine in this study.

Reviewer #1 (Public review):

Summary:

The authors present a simplified neural bursting model with explicitly controllable parameterization of oscillator dynamics designed for neural circuit modeling involved in rhythm generation.

Strengths:

(1) The purpose of the model and applied abstractions are well articulated and justified (2D model, independent parameter control).

(2) Explicit control of burst duration, inter-burst interval, amplitude, resetting-behavior/entrainment. This allows modelers to focus on circuit interactions and is especially useful when details of intrinsic currents and bursting mechanisms are unknown. One could even imagine a scenario where this model would help identify predictions on key underlying burst generation mechanisms.

(3) The model is well described and validated with simulations and comparisons to the base model and one alternative model.

(4) Circuit-level validation is convincing, as it reproduces not only trivial examples.

(5) The underlying mechanism in phase space is well reasoned and justified, extends previous work, e.g., by McKean, by improving usability.

Weaknesses:

(1) The paper heavily relies on numerical demonstrations but does not provide a formal analysis of stability, bifurcations, or entrainment. While appropriate for the intended purposes, a more formal footing could strengthen the model.

(2) Lots of nice demonstrations are shown, but it is less clear how model parameterization was chosen, how behavior depends on parameterization, and in what parameter ranges certain behavior can be expected. A more detailed description of parameterization/exploration of parameter space would greatly benefit anyone using this model in the future.

(3) Some claims on reproduction of prior locomotor CPG model and production of "more biologically realistic activity" by the presented model are overstated. The key feature of the locomotor CPG models cited was that they not only reproduced speed-dependent gait expression of intact mice, but also changes of gait expression after silencing/removal of specific commissural and long propriospinal interneurons (e.g., selective loss of trot after deleting of V0V; changes in gait expression and step-to-step variability after silencing of descending long-propriospinal neurons or ascending V3 LPNs). While likely (at least partially) feasible with the model formulation, the correspondence of these silencing/ablation of neuron classes has not been shown by the model. Importantly, though, it appears that authors didn't show how the model in general behaves under the influence of noise, which is key to reproducing LPN silencing.

Reviewer #1 (Public review):

The idea is super interesting, and the subsequent work is potentially significant because it links peripheral inflammation to remodelling of perinodal adipose tissue and draining lymph nodes. This suggests an antigen-independent manner by which local tissue inflammation can communicate with and reshape immune organ structure and tissue metabolism. However, the evidence is suggestive. For instance, many conclusions rely on correlational weight/cellularity relationships, models with confounders (spontaneous wounding; potentially systemic IMQ), and macrophage dependence inferred from a single pharmacologic approach without definitive depletion/lineage or tracer-based causal link.

Major Comments:

(1) "Wounding/fighting" evidence is confounding.

Unless I am mistaken, a large part of the argument for inflammation-driven perinodal fat pad atrophy and LN expansion relies on spontaneous fighting injuries in co-housed CCR2-/- males, including animals "culled...due to excessive wounding." Because wound severity, duration, infection load, stress, and cage dynamics are uncontrolled, isn't it difficult to assign causality to "cutaneous inflammation"?

(2) The "CCR2-independent macrophage" conclusion.

The manuscript interprets persistence/accumulation of macrophages despite reduced inflammatory monocytes as CCR2-independent recruitment or local proliferation. However, CCR2 deficiency can alter immune baselines and long-term tissue remodelling. Perhaps consider bone marrow chimeras (WT to CCR2-/-, CCR2-/- to WT ????) or an inducible CCR2 deletion approach to separate developmental/systemic effects from acute inflammation-driven mechanisms. If "in situ proliferation" is proposed, include a direct readout (e.g., Ki67 in ATMs in the fat pad).

(3) IMQ and systemic effects.

The work relies on topical Aldara/imiquimod as an "inflammation without antigen" driver of distal LN/fat-pad remodelling. But IMQ is well known (and cited by the authors) to enter circulation and drive systemic responses, which could blur whether effects are truly draining-site specific vs systemic metabolic/inflammatory effects. It would be ideal to provide systemic context: plasma cytokines and/or metabolic readouts (e.g., circulating FFAs) to distinguish local vs systemic drivers.

(4) Macrophage dependence is inferred from CSF1R inhibitor treatment.

However, validation of macrophage depletion and specificity is incomplete. The manuscript uses AZD7507 (CSF1R inhibitor) and observes partial rescue of fat pad/LN phenotype while skin severity (PASI) is unaffected. But, to this reviewer, the data shown do not clearly quantify actual macrophage depletion efficiency in the target fat pad, and LN at endpoint, and CSF1R blockade can affect multiple myeloid populations. Therefore, show absolute macrophage counts (and likely other myeloid populations) in fat pad and LN with/without AZD7507 at the analysed timepoints, not only outcome weights. (The methods describe dosing but not endpoint depletion quantification??)

(5) Fat pad atrophy/LN expansion is a correlation.

The paper emphasises negative correlations between fat pad and LN weights/cellularity at baseline and with inflammation. But correlation does not establish whether fat pad lipolysis drives LN expansion, whether LN changes drive fat remodelling, or whether both reflect systemic mediators. Add tissue-level evidence distinguishing true adipocyte loss vs other contributors to "weight change" (e.g., oedema/fibrosis).

(6) Evidence for "fatty acid donation" from fat pad to LN.

The lipid data are described as "exemplary," and the inference that LN fatty acids originate from the fat pad is based on temporal ordering and relative abundance. This does not rule out plasma spillover, LN-intrinsic metabolism, or altered lymph flow.

Joint Public Review:

Summary:

Calle-Schuler et. al. reconstruct all the pre- and post-synaptic neurons to the bristle mechanosensory neurons on the adult fly head to understand if neural circuits support the parallel mechanosensory pathways, which could be instrumental in shaping the sequential motor patterns during fly grooming. They find that most presynaptic neurons, interneurons and excitatory post synaptic neurons are also somatotopically organized, such that each neuron is more connected to bristles mechanosensory neurons that are closer on the head and less connected to bristles mechanosensory neurons that are further away. These include the direct BMN-BMN circuits, excitatory interneurons, as well as the inhibitory networks. They also identify that the one entire hemi-lineage 23b form excitatory postsynaptic circuit with BMNs, highlighting how these circuits and hence their function could be developmentally determined.

Strengths:

This is a complete map of the all the neurons which make 5 or more pre- and post-synaptic connections of the fly head BMNs. Using this, the authors have identified various trends such as ascending neurons provide most of the GABAergic inhibitory input, which could provide the presynaptic inhibition essential for the parallel model for sequential grooming generation. Moreover, they identified that the entire cholinergic hemilineage 23b is postsynaptic to BMNs. Both their excitatory postsynaptic connectivity and inhibitory presynaptic connectivity demonstrate core motifs of the parallel circuits necessary for the hierarchical suppression model of grooming sequence.

Weaknesses:

Somatotropic organization with hierarchical suppression is an elegant mechanism to generate sequential motor sequence during grooming. Yet, anatomical connectivity alone, in absence of functional connectivity, cannot explain the grooming motor sequences. Future work should be aimed at mapping the functional connectivity with behavioral sequence.

Closing statement:

The authors have addressed the major concerns regarding clarity, scope, and interpretation. The manuscript is now significantly improved and is clearly framed as an anatomical resource that identifies circuit motifs consistent with existing models of grooming control.

Reviewer #1 (Public review):

Summary

The strength of this manuscript lies in the behavior: mice use a continuous auditory background (pink vs brown noise) to set a rule for interpreting an identical single-whisker deflection (lick in W+ and withhold in W− contexts) while always licking to a brief 10 kHz tone. Behaviorally, animals acquire the rule and switch rapidly at block transitions and take a few trials to fully integrate the context cue. What's nice about this behavior is the separate auditory cue, which shows the animals remain engaged in the task, so it's not just that the mice check out (i.e., become disengaged in the W- context). The authors then use optical tools, combining cortex-wide optogenetic inactivation (using localized inhibition in a grid-like fashion) with widefield calcium imaging to map what regions are necessary for the task and what the local and global dynamics are. Classic whisker sensorimotor nodes (wS1/wS2/wM/ALM) behave as expected with silencing reducing whisker-evoked licking. Retrosplenial cortex (RSC) emerges as a somewhat unexpected, context-specific node: silencing RSC (and tjS1) increases licking selectively in W−, arguing that these regions contribute to applying the "don't lick" policy in that context. I say somewhat because work from the Delamater group points to this possibility, albeit in a Pavlovian conditioning task and without neural data.

The widefield imaging shows that RSC is the earliest dorsal cortical area to show W+ vs W− divergence after the whisker stimulus, preceding whisker motor cortex, consistent with RSC injecting context into the sensorimotor flow. A "Context Off" control (continuous white noise; same block structure) impairs context discrimination, indicating the continuous background is actually used to set the rule (an important addition!) Pre-stimulus functional-connectivity analyses suggest that there is some activity correlation that maps to the context presumably due to the continuous background auditory context. Simultaneous opto+imaging projects perturbations into a low-dimensional subspace that separates lick vs no-lick trajectories in an interpretable way.

In my view, this is a clear, rigorous systems-level study that identifies an important role for RSC in context-dependent sensorimotor transformation, thereby expanding RSC's involvement beyond navigation/memory into active sensing and action selection. The behavioral paradigm is thoughtfully designed, the claims related to the imaging are well defended, and the causal mapping is strong.

Comments on revisions:

The authors have been responsive to the prior review and I think the manuscript is a valuable and important addition to the literature.

Reviewer #1 (Public review):

Summary:

The study examined the extent to which children's word recognition skill improves across early development, becoming faster, more accurate and less variable, and the extent to which word recognition skill is related to children's concurrent and later vocabulary knowledge.

The main strength of the study comes from the dataset which recycles previously collected data from 24 studies to examine the development of word recognition skill using data from 1963 children. This maximizes the impact of previously collected data while also allowing the study to reliably ask big picture questions on the development of word recognition skill and its relation to chronological age and vocabulary knowledge. Data analysis is rigorous, thought through and very clearly described. Data and code necessary to reproduce the manuscript are shared on the project's Github. The limitations of the study are acknowledged and the manuscript does well to tone down the causal implications of their results.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors investigate the role of the microtubule-binding protein EML3 during cortical development through the generation and characterization of an Eml3 mouse mutant. The authors focus mainly on the effects of EML3 loss on brain development, although Eml3 mouse mutants also present with developmental delay and growth restriction, and die perinatally due to respiratory distress caused by delayed maturation of the lungs. The main finding in the developing cortex is the presence of focal neuronal ectopias, which contain neurons from all cortical layers, as revealed by immunostaining. The authors use electron microscopy to show that ectopias seem to be caused by disruption to the pial basement membrane at early stages of development, which allows neurons to breach through it. To find a functional link between EML3 and the observed phenotype, studies are conducted that demonstrate expression of EML3 in radial glia cells and mesenchymal cells, both cell types involved in the formation and maintenance of the pial basement membrane. Furthermore, interaction partners for EML3 are identified through coIP-MS analysis, including tubulin beta-3, 14-3-3 proteins and cytoplasmic dynein light chain. However, mice carrying a mutant EML3 allele engineered to abolish the interaction between EML3 and cytoplasmic dynein light chain do not recapitulate any of the symptoms of complete EML3 loss.

Strengths:

The manuscript offers several important strengths that contribute significantly to the field. This study presents the first characterization of Eml3 knockout animals, providing novel insights into the role of Eml3 in vivo. Information on Eml3 function so far was restricted to cell culture data, so the results in this manuscript start to fill an important gap in our knowledge about this microtubule-binding protein. The experimental approach is carefully designed, with appropriate controls that ensure the reliability of the data. Moreover, the authors have addressed a key challenge in the analysis, namely the developmental delay of the knockout animals. By implementing a strategy to match developmental stages between wild-type and knockout groups, they allow for meaningful and valid comparisons between the two genotypes. Importantly, the authors have successfully generated three different Eml3 mutant mouse lines (knockout, floxed and with disrupted binding to cytoplasmic dynein light chain), which are very valuable tools for the broader scientific community to further study the roles of this gene in development and disease in the future.

Weaknesses:

While the manuscript presents valuable data, there are also several weaknesses that limit the overall impact of the study. Most notably, there is no clear mechanistic link established between the loss of Eml3 function and the observed phenotype, leaving the biological significance of the findings somewhat speculative, as it is not straightforward how a microtubule-associated protein can have an impact on the stability of the pial basement membrane. In this respect, but also in general for the whole manuscript, there seems to be a considerable amount of experimental work that has been conducted but is not presented, possibly due to the negative nature of the results. Additionally, the phenotype reported appears to be dependent on the genetic background, as it is absent in the CD1 strain. This observation raises concerns as to how robust the results are and how much they can be generalized to other mouse strains, but, more importantly, to humans.

Reviewer #1 (Public review):

[Editor's note: this version has been assessed by the Reviewing Editor with further input from the original reviewers. The authors have addressed the comments raised in the previous round of review.]

Summary:

Urination requires precise coordination between the bladder and external urethral sphincter (EUS), while the neural substrates controlling this coordination remain poorly understood. In this study, Li et al. identify estrogen receptor 1-expressing neurons (ESR1+) in Barrington's nucleus as key regulators that faithfully initiate or suspend urination. Results from peripheral nerve lesions suggest that BarEsr1 neurons play independent roles in controlling bladder contraction and relaxation of the EUS. Finally, the authors performed region-specific retrograde tracing, claiming that distinct populations of BarEsr1 neurons target specific spinal nuclei involved in regulating the bladder and EUS, respectively.

Strength:

Overall, the work is done with high quality. The authors integrate several cutting-edge technologies and sophisticated, thorough analyses, including opto-tagged single unit recordings, combined optogenetics and urodynamics, particularly those following distinct peripheral nerve lesions.

Comments on revised version:

During the revision, the authors have adequately addressed my concerns and made the suggested changes accordingly. I have no additional comments.

Reviewer #1 (Public review):

The authors point out that the fitness estimates obtained from different experimental assays (monoculture, pairwise competition or bulk competition) are not generally equivalent, not even with regard to the fitness ranking of different genotypes. Using a computational model based on experimentally measured growth phenotypes for knockout strains in yeast, as well as data from Lenski's Long Term Evolution Experiment (LTEE), they derive a set of best practice rules aimed at extracting the optimal amount of information from such experiments.

The study is very complete on a technical level, and the conceptual weaknesses raised in the first round of reviews have been fully addressed in the revision.

Reviewer #1 (Public review):

Summary:

This study presents evidence that addition of the two GTPases EngA and ObgE to reactions comprised of rRNAs and total ribosomal proteins purified from native bacterial ribosomes can bypass the requirements for non-physiological temperature shifts and Mg+2 ion concentrations for in vitro reconstitution of functional E. coli ribosomes.

Strengths:

This advance allows ribosome reconstitution in a fully reconstituted protein synthesis system containing individually purified recombinant translation factors, with the reconstituted ribosomes substituting for native purified ribosomes to support protein synthesis. This represents a significant development in the long-term effort to produce synthetic cells.

Weaknesses:

- The authors carried out additional experiments indicating that ~60% of the reconstituted ribosomes are functional and that a significant proportion are capable of synthesizing GFP from the correct initiation codon to the correct stop codon, and also of producing an enzymatically active protein at appreciable levels. Their SDS-PAGE and MS analyses of N-terminally tagged GFP are also quite useful but did not assess the frequency of initiation at the wrong start codon, termination at the incorrect stop codon, or the frequency of frameshifting during elongation. This would require examining additional reporters designed to examine dependence on a Shine-Dalgarno sequence or the impact of an in-frame stop codon to assess the fidelity of initiation and termination events, respectively, and one with a programmed frameshift site to assess the elongation fidelity of their reconstituted ribosomes.

- Reconstitution studies in the past have succeeded by using all recombinant, individually purified RPs that, if successful here, would have eliminated the possibility that one or more unknown ribosome assembly factors that co-purify with native ribosomes was added to their reconstitution reactions.

Reviewer #1 (Public review):

Summary:

This is an important study that describes the consequences of the DNMT3A mutation in human neuronal development for the first time. The selective impact of DNMT3A function on GABAergic interneurons is interesting and an important feature of future therapeutics. The claims made in that manuscript are supported by strong evidence for the most part. And the data are of high quality in general and presented well.

Strengths:

The strengths of the work include: Characterization of multiple DNMT3A loss-of-function alleles, including two misense variants, R882H, P904L, and a deletion allele. The missense mutation lines both include an ideal control with the same genetic background. The CRISPRi-mediated DNMT3A knockdown has also been included. The study identifies the mTOR-PI3K pathway as a factor of overgrowth issues found in the mutant organoid. In bulk mRNA sequencing and whole-genome bisulfite sequencing, identify hypomethylated genomic regions associated with gene expression repression. Again, this is more pronounced in the ventral organoid compared to the dorsal organoid. In addition, the extensive electrophysiological characterizations with a high-density microelectrode array support the more mature status of mutant interneurons.

Weaknesses:

Although a strong study overall, some weaknesses are noted. These include:

(1) The lack of validation data for the generated iPSCs and hESCs, such as the chromosomal contents, ploidy, and pluripotency states.

(2) Other weaknesses relate to data interpretation and insufficient discussion of related matters, as detailed in the recommendations to the authors.

(3) Also, some errors are noted and detailed in the recommendation section.

Reviewer #1 (Public review):

Kawamura et al. investigated the role of circumferential smooth muscle contractions in chick gut tube elongation, addressing the hypothesis that "peristaltic activity generated by the gut promotes its own elongation during embryogenesis". Although not acknowledged in the current manuscript, this interesting premise was, in fact, previously demonstrated.

Indeed, the experiments in the present manuscript closely parallel a previous study (Khalipina et al, 2019: "Smooth muscle contractility causes the gut to grow anisotropically") that also cultured chick gut tissue and performed time-lapse analyses to quantify peristalsis. Both studies showed that inhibiting peristalsis with Ca-channel blockers induces a switch from elongational to radial growth in the gut.

However, one of the main strengths of the current study is the innovative use of optogenetic manipulation to rescue gut lengthening in drug-inhibited gut tissue by re-stimulating peristaltic contractions. In addition, the authors use aphidicolin to show that peristalsis-mediated gut elongation is independent of cell division. They also track individual smooth muscle cells and show that they divide circumferentially, but become redistributed along the length of the gut tube with peristalsis.

While these data are solidly quantitative, they do not provide mechanistic insight into how peristaltic contractions cause smooth muscle cells to be redistributed.

The evidence presented in this manuscript supports the main conclusion that peristalsis plays a critical role in embryonic gut elongation, but this conclusion itself is not novel. In addition to corroborating previous work, this manuscript provides some useful additions to our existing knowledge of the role of mechanical forces in embryonic gut morphogenesis and illustrates the utility of a previously published optogenetic manipulation technique.

Reviewer #1 (Public review):

Summary:

Zhang et al. report on an ambitious study that investigates multiple aspects of the neural and behavioral underpinnings of auditory-motor surprisal in the context of an auditory-motor learning paradigm (piano keyboard). Using an intricate design comprising several sub-parts and control procedures, they report that early ERPs (50-100 ms latency) reflect violations of established key-pitch mappings.

Strengths:

This is a carefully devised and executed study. The paradigm is quite intricate and, at the same time, addresses multiple aspects of auditory-motor learning, and does so in a rigorous way.

Weaknesses:

Perhaps because of the exhaustive approach, it is sometimes difficult to follow which parts of the experimental design the results come from; there are some questions regarding appropriate statistical methods, the inclusion/treatment of musical background in participants, and the nature (latency & extent) of the identified neural components that detect auditory-motor violations.

Reviewer #1 (Public review):

Summary:

Osswald and colleagues aim to show how motor units of the first dorsal interosseous (FDI) are flexibly recruited across two functionally different movements: index finger abduction and index finger flexion. They motivate this by arguing that FDI is the prime mover in abduction but acts as a synergist in flexion, alongside flexor digitorum profundus (FDP) and flexor digitorum superficialis (FDS) as the prime movers. This is a worthwhile question because it speaks to how descending neural inputs to the spinal cord flexibly control movement.

The authors claim that recruitment order and recruitment threshold of FDI motor units differ between abduction and flexion, and that beta-band intramuscular coherence is reduced when FDI acts as a synergist. However, there are significant methodological concerns that undermine the results and conclusions.

Strengths:

The study certainly aims to address a central question in motor neuroscience - how flexible recruitment of motor units occurs across movements where the same muscle changes its functional role. They correctly identify the FDI as a multi-functional muscle and use intramuscular high-density EMG arrays to record several motor units simultaneously, which is a major technical strength. They also track individual motor units between conditions and, therefore, have generated a potentially valuable dataset for studying spinal motor control across different movements.