Reviewer #1 (Public review):

The authors describe a learning algorithm that is meant to deal with the problem of inference in large, complex environments. They argue that simpler but ensemble learning systems with heterogeneous learning rates often perform better than more complex approaches. They also relate the ideas of their model to a circuit implementation in the mushroom body, an associative learning area in insects.

I found the argument about the value of sublearners remaining simple to be thoughtful and intriguing. I also appreciated the connection to biology and, although there remain details to be worked out, it seems that the proposed approach has what I'd call a "biologically plausible" instantiation.

Comments on the major claims:

The paper claims that algorithms that learn stochasticity and volatility "necessarily result in worse short-term performance than Hetlearn." The results with Autocovariance Least Squares and the model of Piray and Daw are consistent with this statement, but the authors seem to be making a more generic claim. Is there a rigorous justification of this? In particular, I found the section "Competing sublearners should stay simple" to straddle a line between opinion and fact, and I wasn't sure where it intended to be regarding that line.

Relatedly, regarding the statement just before that section: "The exponential convergence of Hetlearn weightings stands in contrast to the slow convergence of stochasticity/volatility estimates (Figures 2A and C), which result in poor initial performance of the Kalman learner." Is the claim here that the Kalman learner doesn't converge exponentially, or that it converges more slowly?

The paper would benefit from a comparison to other models of multiple learning systems with different timescales. The classic one would be the complementary learning systems ideas about hippocampus and neocortex (McClelland, McNaughten, O'Reilly 1995), and the many subsequent follow-ups. Two other relevant ones to consider are Roxin & Fusi 2013 and Lindsey & Litwin-Kumar 2024, which also consider multiple memory systems with different plasticity rates.

Comments on clarity:

(1) Page 2: There could be some more unpacking of the relationship between x and z in equations 1a, 1b. If z_t are time-varying, shouldn't theta, if it represents what is learned about "large-world factors," also depend on time?

The description of second-order conditioning on page 6 is confusing. Second-order conditioning tests whether S2 acquires a positive predicted value after pairing with S1, which had previously been paired with reward. The text makes it seem like the goal of second-order conditioning is to learn S2->S1->no reward.

(2) Page 6: "Representations decay on a slower timescale than stimulus presentation. Hence, the representation x2 after experiencing S2 → S1 holds traces of the S2 representation." I couldn't understand this. Maybe an equation would help?

(3) Page 7: The phrase "unconditioned stimulus" is introduced without being described. Is this a reward or punishment? What does it have to do with valence lower-case v, or value upper-case V? The authors seem to mix notations from different subfields, leading to a rather confusing description of the model.

Comments on relationship to biology:

(1) Page 6: It is assumed that Kenyon cells interact recurrently through plastic weights. This is an unconventional assumption for mushroom body models, and it is made without much discussion. The authors cite papers that argue for changes in the calyx during learning (although these effects are generally much weaker than the well-documented plasticity onto MBONs). However, KC-to-KC interactions are largely in the lobes, not the calyx. The authors should provide more discussion of this assumption. What happens if the recurrence is weak or absent? A relevant reference to consider is Manoim et al. Current Biology 2022, which shows that KC-to-KC interactions are inhibitory.

The model seems to imply that each MBON compartment encodes only one memory, or did I misunderstand? Is this necessary? Typically, it is thought that because of the sparse, decorrelated representations in the KCs, an individual MBON could store multiple associations without too much interference.

Reviewer #2 (Public review):

Summary:

The study by Millard et al. investigates the effects of nicotine on peak alpha frequency and pain using a highly elaborate experimental design. According to the statistical analysis, the authors found a small covariate-corrected effect for prolonged heat pain and a small effect on global peak alpha frequency in response to nicotine treatment. However, the effect on heat pain was not found for pressure pain, was not mediated by peak alpha frequency, and appears mainly based on a worsening in the placebo condition rather than a clear reduction of pain after nicotine.

Strengths:

I very much like the study design and that the authors followed their research line by aiming to provide a complete picture of the pain-related cortical impact of peak alpha frequency. This is important work, even in the absence of clear statistical or mechanistic support for the main hypothesis. I also appreciate the preregistration of the study, the well-written and balanced introduction, and the additional analyses added during revision.

Weaknesses:

The weakness of the study revolves around two main aspects:

(1) Source separation would still have been more appropriate than electrode regions or global peak alpha frequency to extract the alpha signal. The added ICA analysis is appreciated, but in my view, it does not fully solve the problem. Different alpha sources, such as mu rhythm, occipital alpha, and lateralised alpha activity, are still not clearly disentangled. The main peak alpha frequency effect remains a small global, wide-band, sensor-space effect rather than a clearly source-specific sensorimotor effect.

(2) I still think the choice of nicotine is a major weakness of the study. The rationale for using nicotine as an intervention rests partly on previous reports of nicotine effects on experimental pain, but the most relevant cited meta-analysis already suggested that these effects are small and may be affected by publication bias. It is therefore not a clean way to test whether peak alpha frequency has a causal role in pain. The heat-pain result is also difficult to interpret as analgesia. Statistically, the placebo-controlled contrast may be significant, but in practice, the nicotine condition changed very little, and the effect seems mainly driven by worsening in the placebo group. In a real intervention, one gives the drug, not the difference between drug and placebo.

Impact:

The impact of the study could be to show what did not work to answer the authors' research question. The study is valuable because it provides a careful and largely negative mechanistic test: nicotine produced at most small effects, peak alpha frequency did not mediate pain, and pressure pain was not affected. The study would have more impact with a more direct intervention model and an analysis strategy that more clearly untangles the different alpha sources.

Reviewer #1 (Public review):

In the article, the authors set out to characterize in adipocytes an enhancer, ENH5, of the gene EPAS1, a gene that was found to show strong selection in Tibetan populations. They investigate whether this enhancer contributes to adipocyte response to environmental stress. The authors show that ENH5 is active in preadipocytes and that the Tibetan high-altitude allele confers reduced activity. They then use a mouse ENH5 knockout model to show a hypoxia/thermogenesis responsive phenotype of stronger transcriptional downregulation of aerobic respiration, electron transport chain, and adipogenesis pathways. The authors interpret these findings as evidence that ENH5 conditionally regulates adipocyte energetics and thermogenic response, potentially favoring energy conservation in Tibetans exposed to the demands of high-altitude hypoxia and cold. Overall, the paper presents an interesting potential connection between EPAS1-mediated high-altitude tolerance and energy metabolism; however, more work needs to be done to establish this connection.

Major comments:

(1) The authors use mouse ENH5 enhancer knockout (ENH5-KO) as the model of the Tibetan EPAS1 locus because the high-altitude allele of human ENH5 has lower transcriptional activity than the low-altitude allele (Figure 1A) and mouse ENH5 (musENH5) has enhancer activity (Figure 1D) in mouse preadipocytes. However, it is an overstatement to claim the functional role of Tibetan ENH5 haplotype only based on these data because musENH5 is neither identical to human ENH5 nor the murine high-altitude haplotype. The title should also be revised to better reflect the function of ENH5, like "An EPAS1 enhancer mediates hypoxic and cold response in mouse adipocytes". The authors should consider in some way to actually show that the Tibetan haplotype in ENH5-KO leads to expression changes. This could be done by inserting the haplotype into preadipocytes via CRISPR (realize this is a tough one) or if they have available cells from Tibetans or some eQTL or other similar datasets. The more closely they can connect this haplotype to EPAS1 expression, the more beneficial it would be for the article. As it stands, they currently have episomal luciferase assays showing reduction of enhancer activity in mouse preadipocytes of a human allele and a complete knockout of the mouse enhancer that doesn't recapitulate the Tibetan haplotype. A bit more work is needed to connect all of these to the Tibetan adaptation. As it stands now, this is all very circumstantial.

(2) In Figure 2A, the body weight of ENH5-KO normal diet is significantly lower until four weeks in male, and until 11 weeks and 18 and 19 weeks in female than that of WT. These are slight but significant differences between ENH5-KO and WT; therefore, the authors should describe and discuss this and how it could affect their results.

(3) For the mouse work, it is not clear why the authors did not do cold-exposure or some type of hypoxia experiment for the mice themselves. This will be helpful to support their claim, and if not done, or done without significant differences in the results, the authors should add and mention this. The RNA-seq work, while substantial, again provides circumstantial support.

(4) The authors used CL316243 as a β3-AR selective agonist to mimic thermogenesis in vitro. In humans, it is not β3-AR but β2-AR that mainly drives thermogenesis (Blondin et al., Cell Metabolism, 32, 287-300. e7). Therefore, the authors should describe the limitation due to the difference in mechanisms of action of thermogenesis between humans and mice, as they use the mouse cells as a human model.

(5) The authors note in the discussion that Figure 3's CL316243 stimulation intended to simulate a thermogenic reaction to cold temperatures also generated a change in OXPHOS pathways associated with hypoxia, thus making it difficult to separate the contribution of β3-adrenergic/thermogenic effect from an indirect local hypoxia response. The authors could further interrogate this effect by measuring canonical hypoxia-responsive genes, oxygen consumption, or performing an in vivo cold challenge.

(6) Figure 4: The authors mention that reduced aerobic respiration pathways are evidence for reduced thermogenesis, but it does not directly demonstrate altered thermogenesis correlates. They do not measure heat synthesis, oxygen consumption/respiration, uncoupled respiration, UCP1 protein levels or activity, mitochondrial changes, etc. Their evidence for changed thermogenesis stems from transcriptional changes in energy consumption pathways shared with hypoxia changes. They should tone down their findings.

(7) In the Discussion, the authors should interpret and discuss their data carefully. For example, in the GSEA analysis, the authors identified enriched gene sets in ENH5-KO. Therefore, the authors should discuss which genes might contribute to each pathway, since some genes show large logFC changes. In the current discussion, there is little mention of their results, and it mostly focuses on prospects.

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors investigated factors required for neural progenitors to exit cell cycle before the adult stage. They first show that Kr is expressed in pupal stage MBNBs, and depletion of Kr from pupal stage NBs leads to retention of MBNBs into the adult stage. Then they demonstrate that these retained NBs maintain the expression of Imp, and co-depletion of Imp abolishes the extended neurogenesis. Further, they show that co-depletion of kr-h1 significantly reduces the retained MBNBs caused by loss of kr, suggesting antagonistic genetic interactions between these two. In addition, they demonstrate that over-expressing Kr-h1 leads to the striking phenotype of tumor-like neuroblast overgrowth in adult brains. In the revised manuscript, they provide evidence suggesting that Kr does not regulate Kr-h1 expression, but rather Kr and Kr-h1 may regulate the late temporal gene E93 expression in parallel.

Strengths:

(1) The authors leveraged well-controlled powerful genetic tools (including temporal control of RNAi knock down using the Gal80ts system), and provided strong evidence that Kr is required for the Imp to Syp transition and to promote the end of neurogenesis through E93 in mushroom body neuroblasts. Similarly, the experimental result of co-depleting Kr-h1 and Kr, and the striking phenotype upon Kr-h1 mis-expression, support the antagonistic roles played by Kr-h1 and Kr in this process.

(2) The sample sizes, quantification methods and p-values are well documented for all experiments. In most parts, the data presented strongly support their conclusions.

(3) Identification of two transcription factors with opposite roles in controlling cell cycle exit, and their possible interactions with the Imp/Syp axis, is highly significant for the study on how the proliferation of neural progenitors is regulated and limited before the adult stage.

Weaknesses:

(1) In the revised manuscript, Kr immunostaining was done in KrIf-1 mutant brains using tyramide signal amplification (TSA) to enhance the weak endogenous Kr signal, and they conclude that Kr is ectopically detected in MBNBs and their progeny. However, a wildtype control with TSA amplified Kr immunostaining was not provided, so it is not known whether the elevated signal comes from TSA amplification or the mutant condition. If Kr is indeed mis-expressed in MBNBs in the KrIf-1 mutant, the authors should provide a hypothesis to explain why both loss of Kr and mis-expression of Kr in MBNBs lead to the same NB retention phenotype.

Reviewer #2 (Public review):

Summary:

This paper shows that imiquimod, a compound often used to induce a psoriasis-like skin inflammation in mice, has a TLR7-independent effects that induce the unfolded protein response and amplify cytokine expression in dendritic cells. Although these effects of imiquimod have been described in the literature before, this study provides more detailed evidence and different contexts to this observation. These findings add to existing literature that imiquimod has a pleotropic mechanism of action involving changes in mitochondrial functions and cellular stress responses. Specifically, the authors show that imiquimod can induce calcium signaling in immune cells and potentiate two branches of the unfolded protein response in a TLR7-independent and MyD88-independent manner. They also show that some of these effects might be partially mediated by direct binding of imiquimod to Gelsolin. These findings expand our understanding of imiquimod-mediated inflammation and are useful for the field of experimental skin immunology and mouse models of psoriasis. However, molecular and cellular mechanisms connecting Gelsolin to the unfolded protein response and skin inflammation presented in this paper requires further investigation in the context of TLR-mediated inflammation.

Strengths:

(1) TLR7-independent effects of imiquimod to the expression of genes and proteins involved into the unfolded protein response are well demonstrated.

(2) Gelsolin is identified as a new imiquimod-binding protein in mouse cells.

Weaknesses:

(1) Effects of imiquimod on mitochondrial Ca signaling are not clear form the presented data.

(2) The mechanism of action connecting imiquimod to Gelsolin on the unfolded protein response and cytokine production remains not fully explained.

(3) It remains unclear if Gelsolin contributes to regulating TLR7 (or other types of TLR-mediated) inflammation in vivo.

Reviewer #1 (Public review):

Summary:

Garcia-Alcala, Kratz and Cluzel investigate to what extent our understanding of bacterial physiology in bulk experiments can be applied to single-cell observations. They find that intrinsic noise may be powerful enough to even inverse the trends found in the bulk. The authors hypothesize that asymmetric distribution of ribosomes to daughter cells during the cell division plays the dominant role in the intrinsic noise and is able to generate the observed phenomenon. They do not show it directly, but the data and its agreement with the model suffice to support this claim.

Strengths:

The experimental part is convincing: the positive correlation between the elongation rate and promoter activity of unnecessary protein is clear, as well as the negative correlation between the mean values while changing the promoter strength. This was demonstrated in both rich and poor media. The causality between the growth rate and the promoter activity was shown using the negative lag time of the cross-correlation function. A simple, reasonable model accounts well for the data. This paper demonstrates an interesting phenomenon and provides a plausible theory for it, advancing our understanding of bacterial physiology on the single-cell level.

Weaknesses:

(1) Mean-reversion timescales were assumed to be longer than the simulation time and much longer than the cell cycle time. It is not clear whether the results robust in case mean-reversion timescales become of the order of cell cycle or smaller. If not, is there an argument for such practically infinite reversion timescales?

(2) It is not easy to understand the simulation part unless one reads Ref. [14]. Is k(t) assumed to follow Eq. (1) from ref. [14]? Is this crucial that the ribosome noise appears only at the division? The ribosome noise strength \sigma_R=0.06 - is it lower or higher than the naively expected binomial division?<br /> Also, more intuitive explanation of the Simpson paradox would help the reader.

(3) It would be useful for the reader to see the raw data and not only the filtered one to appreciate the measurement noise level.

(4) Negative lag time of the cross-correlation function is visible, but consider adding statistical test for it.

(5) Can you make similar cross-correlation plots using the model? Can you infer using it whether the data agrees better with the assumption that ribosomes noise appear only at division or continuous fluctuations during the cell cycle?

Comments on revised version:

The authors addressed the five comments listed above.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. We appreciate the care with which the authors have addressed the remaining concerns. The additional analyses and the revisions to the framing and interpretation have strengthened the manuscript and clarified several of the issues raised during the previous round of review. In particular, the added analyses in Figure 4 and the more precise treatment of repeated retrieval, learned threat value, and the relationship between neural activity and freezing have improved the paper substantially.]

Summary:

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

To my knowledge, this may be the first study to comprehensively examine neural encoding of fear generalization in prelimbic cortex (PL). The manuscript is ambitious and technically interesting, and several aspects are potentially important. In particular, the suggestion that neurons showing graded, learning-related response patterns become selectively stabilized over time is intriguing. The inclusion of two CS+ training conditions and a no-shock control also strengthens the case that at least some of the reported effects are related to associative learning rather than simple sensory differences.

Reviewer #2 (Public review):

Summary:

In this study, the authors developed a human forebrain organoid model that incorporates both iPSC-derived microglia and CD8⁺ T cells, allowing them to recreate and investigate multicellular aspects of AD pathology in a human-relevant system.

Their findings show that microglia help clear amyloid-β deposits, but they also promote inflammatory responses. Activated microglia recruit CD8⁺ T cells by releasing the chemokines CCL4, CCL5, and CXCL10, which signal through the receptors CCR1/CCR5 and CXCR3. Pharmacological inhibition of CCR5 or CXCR3 prevents T-cell recruitment and alters autophagy pathways in a microglia-dependent manner.

Strengths:

The manuscript has several strengths, including its innovative multicellular organoid model, the combination of complementary experimental approaches, and the identification of potentially relevant immune signaling pathways.

Comment on the revised version.

Overall, the revised manuscript is considerably improved, and the major conceptual concerns raised in the initial review have been adequately addressed.

Reviewer #1 (Public review):

Ma et al. use human-chimpanzee tetraploid cells, across different cell types, to identify the genetic causes and then transcriptomic consequences of divergence in DNA methylation. They conclude that the evolution of DNA methylation is driven primarily by cis-regulatory changes, and that the evolution of CpG sites contributes to cis-regulation while transcription factor expression underlies some trans changes. They then argue that divergence in DNA methylation is associated with changes in gene expression and may contribute to human phenotypes.

The tetraploid model is able to provide compelling evidence that most regulatory evolution occurs due to cis-regulatory changes, and that sites that have diverged in DNA methylation level cluster together into DMRs which share similar divergence patterns and genetic architecture. This stands in intriguing contrast to trans-mechanisms which explain most variation within modern human populations. The authors proceed to show that trans-effects can be explained, in part, by nearby TF binding motifs and many cis-regulatory changes are explained by CpG-disrupting variants. While these mechanisms clearly contribution to divergence in DNA methylation, the degree to which they explain cis- and trans-regulatory divergence would be valuable.

Next, the authors seek to show that differences in DNA methylation are functionally relevant. Consistent with previous results, they show that differences in DNA methylation are (weakly) associated with changes in gene expression. They hypothesize that genes with concordant regulatory should exhibit great methylation-expression coupling than other genes and show that cis-expression/cis-methylation pairs are more strongly correlated than trans/trans pairs. I think that looking at cis/trans or trans/cis changes would also be useful. Another limitation is that this analysis is limited to promoter regions. It is not clear how many divergent DMRs that includes and how many of those genes have differences in expression. The key question is whether differences in DNA methylation are functionally important, and the answer provided by these analyses is "sometimes".

Finally, the authors make a case for lineage-specific selection on DNA methylation that is connected to human traits. Using a sign-test, they identify sets of genes which have likely experienced selection in humans and may underlie human phenotypes.

In conclusion, I think this study provides a valuable resource for differences in DNA methylation between humans and chimpanzees across tissues and provides important insight into the relative abundance of cis and trans regulatory divergence. Additional research is necessary to investigate the underlying regulatory mechanisms and more care needs to be taken in exploring the functional consequences.

Reviewer #1 (Public review):

Summary

This computational modelling study investigates the functional role of metaplasticity in a calcium-dependent synaptic plasticity rule, using a biophysically detailed model of a striatal projection neuron. The learning rule is deliberately simple: local calcium signals derived from different sources regulate LTP and LTD through separate plasticity thresholds, while dopamine provides a reward-related signal that determines the direction of synaptic updates. The author uses linear and nonlinear feature-binding problems (FBP and NFBP) as learning tasks to illustrate the mechanics of competing LTP and LTD processes in this rule. The central aim is thus to use these classification tasks to understand what metaplasticity in the two calcium thresholds contributes to learning.

The study identifies complementary roles for metaplasticity in the LTP and LTD thresholds, enabling synapses exposed to competing plasticity processes to converge toward a stable outcome. In reversal-learning tasks, relaxing the conditions for metaplasticity allows previously stabilized synaptic states to become flexible again and permits relearning. Finally, the manuscript investigates whether two separate calcium thresholds are themselves necessary. While a modified rule with a single adaptive calcium threshold can solve the same tasks comparably well, two thresholds allow separate control over synaptic strengthening and weakening.

Strengths

A major strength of the study is the simplicity of the learning rule, which makes it possible to dissect the roles of individual components while retaining a connection to experimentally motivated mechanisms of cortico-striatal plasticity. The use of shared features in the FBP and NFBP is useful for exposing the interaction between competing LTP and LTD processes and for showing how adaptation of one plasticity threshold can indirectly permit expression of the opposite form of plasticity.

The manuscript also provides a much more systematic analysis of the rule than the original version. In particular, the expanded parameter analyses explore both successful and failing regimes for the learning and metaplasticity rates, while the scan over the maximum synaptic weight provides a clear mechanistic motivation for the additional upper LTP threshold.

Importantly, the single-threshold simulations directly address whether two calcium thresholds are computationally necessary. These additional simulations clarify that the principal advantage of two thresholds is not that they uniquely enable nonlinear learning, but that they permit independent regulation of strengthening and weakening. This considerably strengthens the conceptual conclusions of the study.

Weaknesses

The main limitations concern the scope and biological generalizability of the results. The simulations in this paper are based on a particular detailed SPN model and depend on several specific biological and modelling assumptions. Most notably, solving the nonlinear task requires appropriately clustered excitatory inputs, but the learning rule itself does not provide a mechanism for generating these clusters. The manuscript now discusses this limitation explicitly and appropriately identifies structural plasticity as an important direction for future work.

A second important assumption is the upper calcium threshold that prevents LTP once sufficiently strong supralinear responses are reached. This mechanism plays an important functional role in the model but has not been experimentally established for cortico-striatal synapses. The manuscript appropriately identifies this as a major assumption and discusses potential molecular mechanisms that could implement such an effect.

Overall assessment

The revised manuscript is substantially stronger. The conclusions are carefully matched to what is demonstrated by the simulations, and several important alternative explanations and model configurations are tested directly. In particular, the revised framing provides a more specific mechanistic account of what metaplasticity in two separate thresholds contributes within the proposed rule. The work therefore provides a valuable contribution to computational studies of synaptic plasticity and metaplasticity, with convincing evidence supporting its principal conclusions.

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

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

Weaknesses:

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

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

Comments on revised version.

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

Reviewer #1 (Public review):

In this work, Frey and colleagues have carried out a very large study of α-synuclein polymorphism as a function of aggregation conditions and sample preparation. They provide valuable insight into the many critical factors affecting α-synuclein polymorphism, thereby illuminating the need for detailed reporting in the literature as well as both rigorous and detail-oriented protocols when working with this protein. Indeed, their observations are in line with the difficulties of reproducing structural outcomes across different laboratories and experiments. The authors must be complemented on their openness about the difficulties experienced and the thoroughness of their work. Efforts like these are going to be crucial to achieve an understanding of the unparalleled structural plasticity of α-synuclein amyloid fibrils. It is particularly notable that the authors have managed to optimize protocols to form single-polymorph aggregation reactions with high reproducibility.

In this work, the authors focus on the influence of α-synuclein purity in aggregation reactions. They find that using reverse-phase HPLC to purify the protein significantly alters the aggregation behaviour. It is interesting, and rather uncommon in the field, to use reverse-phase HPLC as a final purification step, rather than SEC, which is commonly used in many laboratories. It would be useful to compare this new protocol even more directly and extensively with the commonly used SEC protocol. When mentioning their previously published work, it should be mentioned explicitly how the protein was purified in these previous studies.

On the point of protein purification, the authors lyophilize their protein prior to storage. In their work, they also find that pre-aggregation oligomer formation alters the aggregation pathway of α-synuclein. While they demonstrate that this can be solved by appropriate filtration, it should be discussed why the lyphilizaiton step was not reconsidered/omitted given that this process is known to facilitate oligomer formation. Do the authors have experience with aggregation studies using α-synuclein that has not undergone lyophilisation and are able to comment on the influence of this step in the protocol?

The authors make note of several degradation products affecting their aggregation reactions, which is why they employ a much more thorough purification protocol. However, they also point out that some of the degradation products found at the end of their reaction could form during the reaction itself. Unfortunately, they never investigate this further. In particular, it would be very useful to know if different aggregation conditions (pH, salt, agitation) lead to different and characteristic degradation patterns. HPLS/mass spec of the supernatant at the end of each aggregation reaction would have been a very insightful thing to do.

With respect to degradation products, in this work a NΔ4-variant is produced to mimic a disease-relevant degradation product and indeed it is found to alter the structural outcome even at low relative concentrations (5%). Have the authors investigated the minimal fraction of the NΔ4 variant necessary to still influence the structural outcome of the predominant WT protein? This type of analysis could have significant relevance to disease-related analysis, where several variants (truncations and PTM variants) are present in trace amounts.

While on this topic, the authors note that in several of their type 5 fibrils, they find unresolved peptide fragments in their cryo-EM structures. Can the authors speculate if these fragments are indeed peptide degradation products or residues wrapping around the fibril originating from the fibril-incorporated protein?

In this work, the authors have performed an extensive study of α-synuclein polymorphism. However, despite generating what is likely the largest single data set of fibril structures, they perform very little quantitative analysis of their data. It would be interesting to analyse the relative abundance of fibril polymorphs produced in each reaction. Perhaps from the particle-picking data it could be estimated the relative abundance of each polymorph as well as non-resolved fibrils to generate a more nuanced view of polymorphism beyond overall classifications of the resolved structures. Indeed, from such data it could also be studied if certain protofilaments are more prone to pair in asymmetric fibril structures over others or if fibril asymmetry can be attributed to random pairing of protofilaments in accord with their abundance. This latter point is particularly interesting for the type 1 fibrils. Perhaps, the propensity of α-synuclein to form specific symmetries could also be estimated.

The authors note that pH is a strong factor in determining polymorph selection. This does indeed appear to be the case, but other parameters do not appear to show any clear trend. Have the authors investigated the influence of aggregation parameters (agitation, duration) on structural outcomes systematically or quantitatively, such as with principal component analysis? Indeed, they also find that some fibril types that otherwise are not compatible at the same pH appear to co-exist when the shaking parameter is modified. Are the authors then confident in the claim that pH is a deterministic parameter?

It is evident from this and other work that amyloid aggregation is highly sensitive to kinetic effects. It is therefore curious that the effect of protein concentration and reaction time has not been systematically investigated. The authors have some data studying dilution series (Figure 6A) and different reaction times (reaction 56 & 57). Could the authors comment on the effects of these two parameters, and might there be more information touching upon this that could be highlighted in this work?

The authors state that this work likely underreports fibril polymorphisms in samples due to population size or data quality challenges. Could the authors, based on their extensive experience, try to quantify this statement?

Additionally, the authors point out that the current framework for classifying α-synuclein fibril polymorphism is not sufficient to describe the real complexity of this protein system. However, they do not seem to address some of the recent literature aiming to solve such issues (see Scheres 2026, Connor et al. 2025, Milchberg et al. 2025 & Price et al. 2025).

Was any biophysical/biochemical analysis performed of the many structures produced here, such as CD spectroscopy, Proteinase K digestion, dye binding or FTIR, which could act as low-resolution structure identifiers and might help to retrospectively explain some findings in the older literature? Such data would be very useful for the vast majority of researchers, who do not have access to cryo-EM.

Reviewer #1 (Public review):

Summary:

The authors have assembled the genome of four local chicken breeds from China and analysed their gene content. They come to the conclusion that thousands of genes present in the current reference genome of chicken have become pseudogenized during chicken evolution and domestication. They argue that their study provides strong support for the importance of the "less-is-more" hypothesis for adaptive evolution.

Strengths:

The paper provides medium-quality genome assemblies for four individuals representing four local populations of chickens and analyses their gene content.

Weaknesses:

They have not excluded the possibility that the high rate of putative pseudogenes reflects the presence of errors in gene models, in particular in GC-rich microchromosomes that are challenging to assemble correctly. The paper contains no genotype-phenotype analysis, which means that the adaptive significance of a high rate of pseudogenization, if it exists, is unknown.

Reviewer #1 (Public review):

Summary:

The CATCHR complexes are a family of five multisubunit complexes that act in vesicle tethering in several key transport steps. COG and GARP act at the Golgi, EARP acts on early endosomes, EXOCYST acts in transport to the cell surface, and DSL1 acts on the endoplasmic reticulum (ER). The authors have used in vivo proximity biotinylation and mass spectrometry to look for new neighbours of three of these complexes, COG, GARP, and EARP (despite the title, only two of the three are on the Golgi). The authors then follow up two of the hits, CCDC186 and WWOX, with more directed experiments.

Strengths:

The strength of the paper is that proximity biotinylation is of a high standard. To avoid overexpression, the authors express TurboID-tagged CATCHR subunits in cell lines from which the genes have been deleted. This allows them to confirm that the tagged proteins are functional and correctly located. Mass spectrometry is used to identify the proteins biotinylated in each cell line with four replicates, and the data are clearly presented in figures and supplementary tables. The authors make a good choice of proteins to follow up, as both CCDC186 and WWOX appear potentially interesting.

Weaknesses:

Overall, although the paper is based on a high-quality initial set of data, it seems somewhat incomplete and preliminary. There is undoubted value in presenting a through if descriptive set of in vivo proximity labelling data for a comprehensive overview of proteins or complexes. However, in this case the authors have only addressed three of the five CATCHR complexes, and so it is not a complete overview. It was also somewhat unclear why they examined VPS52 and VPS53, as these are present in both GARP and EARP, which adds some ambiguity, even if they did at least provide useful confirmation of some of the hits with EARP. Of course, a proximity biotinylation analysis does not need to cover all members of a family if it generates substantial biological insight.

However, the investigation of CCDC186 and WWOX does not provide significant insight into either function or mechanism. CCDC186 has already been identified in C. elegans as a protein involved in dense core vesicle biogenesis (CCCP-1, as the authors acknowledge), and work in C. elegans and mammalian cells has already linked it to EARP function. Less has been published on WWOX, but all that is found here are some small changes in Golgi appearance and glycosylation when it is reduced by RNAi. Thus, the paper falls between two stools: it is neither a comprehensive application of proximity biotinylation to the CATCHR family, nor is it the application of proximity biotinylation to reveal new insight into membrane traffic. I feel that for a broad-interest journal such, it should be one or the other of these.

Reviewer #1 (Public review):

Gary, Soret et al., present an interesting and ambitious study investigating the cellular and signaling mechanisms by which GDNF induces enteric neurogenesis in a disease model of HSCR. The manuscript combines scRNA-Seq, pharmacological inhibition, and several lineage-tracing strategies. The lineage tracing experiments in particular are technically impressive and clearly represent a substantial amount of work. The figures are generally beautiful and high quality, and the biological question is an important one.

However, while I found the study interesting, I also think that several of the major conclusions are substantially stronger than what the current data support. In particular, the scRNA-Seq dataset that the study is founded on is difficult to interpret because of the RFP-based enrichment strategy, the lack of WT reference controls, and the very non-stringent FACS gating. Several mechanistic claims are also based primarily on expression patterns or sequencing results.

Major concerns:

(1) The G4-RFP based enrichment strategy raises some concerns. The authors note that 88-90% of SOX10+ glial cells (where did this number come from, it doesn't seem to match the range in the bar graph?) and only 70% of GDNF-induced neurons. They then sort in "yield" mode using a non-stringent gating strategy, but do not provide the flow graphs in the supplements for interpretation. Consistent with this, the initial dataset contains multiple non-ENS populations, including lymphoid, myeloid cells etc, suggesting that their strategy, in addition to missing cell populations, additionally includes potential negative cells based on background fluorescence.

(2) It's not clear to me why the authors did not include a wild-type control for comparison. Due to the RFP-enrichment strategy, it is additionally difficult to compare to integrated with scRNA-seq datasets. The comparison seems important because the central question is not only whether GDNF induces neurons in the mutant colon, but whether the induced cells and associated populations resemble those found in a normal ENS.

(3) The proportional changes in Figure 2 are hard to interpret. The authors write that GDNF treatment leads to an enrichment in enteric neurons, "at the expense of" SCPs. This seems to be a strange conclusion or writing, unless the authors are suggesting that certain cell populations are additionally depleted by GDNF treatment. I think the authors should provide stronger support, or dial down on conclusions based on cluster proportions, given the sorting strategy.

(4) Some of the mechanistic conclusions are far too strong for the evidence. For instance, the claim that GDNF signals through GFRa1/2 based on only expression UMAPs is not justified. The authors should at least confirm some of the major findings via smFISH (HCR or RNA-Scope), and dial down the mechanistic claims. The pharmacological data is more supportive but still indirect. This section would be stronger if the authors validated NCAM1/FAK activation in the specific progenitor populations proposed to respond to GDNF.

(5) The inhibitors are administered during the same P4-8 window as GDNF. Given that the authors report cellular-level responses as early as 6 hours post GDNF treatment, it is important to know whether the inhibitors were already active at the time of GDNF administration. Why were the inhibitors not administered prior to the start time of GDNF treatment?

(6) The authors draw inferences and conclusions based on IHC images, but do not provide any details on the analysis procedures. For example, in Figure 3, the authors interpret changes in NCAM and FAK expression level. However, it does not appear that there are notable differences in intensity between the two timepoints. There are however, differences in signal coverage. Without knowing what was actually measured and quantified, it is not possible to interpret the results. Please provide the necessary information for all experiments in the methods section.

(7) The final results section introduces one of the more surprising claims in the paper, that a non-neural crest-derived progenitor contributes to regeneration, but the section ends quite quickly and abruptly after introducing the observation. The authors should provide additional validation or interpretations of the data.

Reviewer #1 (Public review):

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

Summary:

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

Strengths:

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

Weaknesses:

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

Reviewer #1 (Public review):

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

Summary:

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

Strengths:

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

Reviewer #1 (Public review):

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

Summary:

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

Strengths:

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

Comments on previous version:

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

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

Reviewer #1 (Public review):

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

Summary:

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

Strengths:

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

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

Weaknesses:

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

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

Comments on revised version.

The author carefully revised the parts that might cause confusion.

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

Reviewer #1 (Public review):

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

Summary:

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

Strengths:

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

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

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

Reviewer #1 (Public review):

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

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

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

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

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

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

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

Reviewer #1 (Public review):

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

Strengths:

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

Weaknesses:

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

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

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

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

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

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

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

(1) Strong methods.

(2) Experimental and control groups.

(3) Strong writing.

(4) Results well presented.

(5) Appropriate statistics.

Weaknesses:

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

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

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

(1) Sample size of 56 participants.

(2) Control group with sham feedback.

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

(4) Pragmatic and reasonable methodological decisions.

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

Weaknesses:

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

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

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

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

(3) Neurofeedback-related Modulation of N1

Reviewer #1 (Public review):

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

Strengths

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

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

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

Limitations

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

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

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

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

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

Comments on revised version.

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

Reviewer #3 (Public review):

Summary:

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

Strengths:

(1) Well designed acoustical stimuli and psychophysical task.

(2) Comparisons across room combinations is well conducted.

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

(4) Timely study with interesting behavioural results.

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

Weaknesses:

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

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

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

Reviewer #2 (Public review):

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

Strengths:

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

Comments on the latest version:

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

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have responded critically to all issues raised in the initial round of reviews.]

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

In general, the more modular such a system is, the better, in terms of compatibility with existing hardware and software that potential users may already have purchased - laser, galvo, and camera in particular.

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

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

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

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

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

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

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

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

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

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

b) R is not well defined in the caption.

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

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

e)How is the interface width calculated?

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

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

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

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

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

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Reviewer #1 (Public review):

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

Update of the weakness section.

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

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

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

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

Reviewer #1 (Public review):

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

Summary:

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

Strengths:

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

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

Joint Public Review:

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

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

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

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

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

Reviewer #3 (Public review):

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

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

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

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

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

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

Comments on revised version:

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

Reviewer #1 (Public review):

Summary:

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

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

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

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

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

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

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

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

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

Several issues require clarification or additional analysis.

Major comments:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Reviewer #1 (Public review):

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

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

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

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

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

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

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

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

Weaknesses:

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

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

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

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

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

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

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

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

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

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

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

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

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

Weaknesses:

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

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

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

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

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

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

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

Reviewer #1 (Public review):

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

Strengths:

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

• Balanced and complementary behavioral, molecular, and bioinformatic experiments

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

Comments on revised version:

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

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

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

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

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

Comments on revised version.

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

Reviewer #1 (Public review):

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

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

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

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

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

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have addressed the comments raised in the previous round of review both by revising their original presentation where necessary and by providing responses to the reviewers in cases where they disagreed that revision of the original presentation would be necessary.]

Summary:

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

Strengths:

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

Case Annotation Template

Case#: Patient 2, female, age 62

DiseaseAssertion: STGD

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

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

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

CaseNotHPOs: n/a

CaseNotHPOFreeText: n/a

Genotyping Method: n/a

PreviouslyPublished: n/a

Variant: ENST00000370225.4:c.1222C>T

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

CAID: CA179692

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

Case#: Patient 10, female, age 19

DiseaseAssertion: STGD

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

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

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

CaseNotHPOs: n/a

CaseNotHPOFreeText: n/a

Genotyping Method: n/a

PreviouslyPublished: n/a

Variant: Allele 1: NM_000350.3:c.2588G>C Allele 2: NM_000350.3:c.1222C>T

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

CAID: Allele 1: CA119128 Allele 2: CA179692

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

Case#: Patient 11, male, age 53

DiseaseAssertion: STGD

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

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

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

CaseNotHPOs: n/a

CaseNotHPOFreeText: n/a

Genotyping Method: n/a

PreviouslyPublished: n/a

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

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

CAID: CA220687

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

Case#: Patient 14, female, age 42

DiseaseAssertion: STGD

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

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

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

CaseNotHPOs: n/a

CaseNotHPOFreeText: n/a

Genotyping Method: n/a

PreviouslyPublished: n/a

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

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

CAID:Allele 1: CA227166 Allele 2: CA227253

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

Case#: Patient 19, female, age 16

DiseaseAssertion: STGD

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

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

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

CaseNotHPOs: n/a

CaseNotHPOFreeText: n/a

Genotyping Method: n/a

PreviouslyPublished: n/a

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

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

CAID: Allele 1: CA227338 Allele 2: CA227198

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

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

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

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

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

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

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

Reviewer #1 (Public review):

Summary:

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

Major comments from first round of review:

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

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

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

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

Significance:

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

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

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

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

Comments on latest version:

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

Reviewer #2 (Public review):

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

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

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

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

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

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

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

Reviewer #1 (Public review):

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

Summary:

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

Strengths:

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

Weaknesses:

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

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

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

Reviewer #3 (Public review):

Summary:

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

Strengths:

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

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

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

Weaknesses:

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

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

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

Comments on revised version.

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

Joint Public Review:

Summary:

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

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

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

Strengths:

(1) Novelty.

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

(2) Wiring optimization.

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

(3) Scale.

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

Weaknesses:

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

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

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

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

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

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

Reviewer #1 (Public review):

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

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

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

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

Reviewer #1 (Public review):

Objectives of the study and impact of the work

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

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

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

Major strengths and weaknesses

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

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

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

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

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

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

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

Reviewer #1 (Public review):

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

Summary:

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

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

Strengths:

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

Weaknesses:

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

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

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

Weaknesses:

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

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

Reviewer #1 (Public review):

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

Summary:

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

Strengths:

(1) Elegant strategy for inducing torpor in rats.

(2) Appropriate controls for verifying the neuron transducer.

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

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

Reviewer #1 (Public review):

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

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

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

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

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

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

Comments on revised version.

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

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

Reviewer #1 (Public review):

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

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

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

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

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

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

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

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

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

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

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

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

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

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

Reviewer #1 (Public review):

Summary:

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

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

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

Strengths:

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

Comments on revised version.

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

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

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

Reviewer #1 (Public review):

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

Summary:

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

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

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

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

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

Reviewer #1 (Public review):

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

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

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

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

Reviewer #1 (Public review):

Summary:

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

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

Strengths:

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

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

Comment on revised manuscript:

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

Comments on revised version:

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

Reviewer #1 (Public review):

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

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

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

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

Strengths:

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

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

Weaknesses:

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

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

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

Weaknesses:

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

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

Discussion:

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

Reviewer #1 (Public review):

Summary:

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

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

Strengths:

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

Weaknesses:

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

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

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

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

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

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

Weaknesses:

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

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

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

Methods are very detailed and well explained for reproducibility purposes.

Weaknesses:

Major weaknesses:

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

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

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

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

Minor weaknesses:

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

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

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

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

Weaknesses:

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

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

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

Reviewer #1 (Public review):

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

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

Comments on revised version.

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

Reviewer #1 (Public review):

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

Strengths:

Overall, this is a scientifically solid paper.

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

Comments on revised version:

The authors have adequately addressed my concerns.

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

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

Reviewer #1 (Public review):

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

Summary:

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

Strengths:

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

Comments on revised version.

I believe the manuscript is improved.

Reviewer #2 (Public review):

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

Major points:

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

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

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

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

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

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

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

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

Minor points:

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

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

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

Comments on revised version.

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

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

Weaknesses:

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

Case#: Female, age 44 years old

DiseaseAssertion: Discordant STGD phenotype

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

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

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

CaseNotHPOs: N/a

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

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

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

PreviouslyPublished: N/a

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

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

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

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

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

Reviewer #1 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

The major weakness is that the review does not include a significant integration across scales, and as a result reads like three separate (though comprehensive) reviews. Currently, the only integration across the scales is in a brief conclusion paragraph. I would recommend adding an additional section, in which the overarching picture is discussed. (i.e. a unifying view of state dependence, and what is learned by considering across scales), and more prefacing in the introduction of the overarching message and framework to the review.

Reviewer #1 (Public review):

Summary:

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

Comments on revised version.

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

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

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

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

Overall, this is a very strong paper.

Reviewer #1 (Public review):

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

Comments:

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

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

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

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

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

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

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

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

Reviewer #1 (Public review):

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

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

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

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