Reviewer #2 (Public review):

The authors used combined blockers/modulators to dissect the potassium currents mediated by inter-subunit heteromeric Kv channels. The method is robust given that the researchers know their limitations. Nevertheless, the authors elegantly tested their hypotheses, making this manuscript friendly to read despite the depth of all aspects they dealt with.

The quality of the data presented will positively impact the science involved in the study heteromeric channels, with clear developments in the field. Finally, the approach presented may unlock new studies related to these channels.

Comments on revisions:

The authors clarified all my points and beyond, specifically by adding some computational work that will also contribute to the subfield of heteromeric Kv channels.

Reviewer #2 (Public review):

Summary:

The authors have made microfluidic arrays of pores and obstacles with a complex shape and studied the swimming of multicellular magnetotactic bacteria through this system. They provide a comprehensive discussion of the relevant parameters of this system and identify one dimensionless parameter, which they call the scattering number and which depends on the swimming speed and magnetic moment of the bacteria as well as the magnetic field and the size of the pores, as the most relevant. They measure the effective speed through the array of pores and obstacles as a function of that parameter, both in their microfluidic experiments and in simulations, with good agreement between the two. They find an optimal scattering number, which they estimate to reflect the parameters of the studied multicellular bacteria in their natural environment. They finally use this knowledge to compare different species. Despite the variability of bacteria parameters, they estimate the scattering number to be rather narrowly distributed, suggesting that their results apply to a broad range of species.

Strengths:

This is a beautiful experimental approach and the observation of an optimal scattering number (likely reflecting an optimal magnetic moment) is very convincing. The results here improve on similar previous work in two respects: On the one hand, the tracking of bacteria does not have the limitations of previous work, and on the other hand, the effective motility is quantified. Both features are enabled by choices of the experimental system: the use the multicellular bacteria which are larger than the usual single-celled magnetotactic bacteria and the design of the obstacle array which allows the quantification of transition rates due to the regular organization as well as the controlled release of bacteria into this array through a clever mechanism.

Weaknesses:

Some of the key experimental choices on which the strength of the approach is based also come at a price and impose some limitations, namely the use of a non-culturable organism and the regular, somewhat unrealistic artificial obstacle array, but the advantages of these choices outweigh the drawbacks.

Comments on revisions:

The paper has been improved with respect to presentation and content. In particular, I appreciate the new plots comparing the simulation and experiments directly and the estimate of the scattering number for different species. In my opinion, all issues raised by the reviewers have been addressed in a productive way.

Reviewer #2 (Public review):

This is a great paper. Yoshida et al. convincingly show that DnaA does not exclusively do loading of the replicative helicase at the E. coli oriC, but that PriC can also perform this function. Importantly, PriC seems to contribute to helicase loading even in wt cells albeit to a much lesser degree than DnaA. On the other hand, PriC takes a larger role in helicase loading during aberrant initiation, i.e. when the origin sequence is truncated or when the properties of initiation proteins is suboptimal. Here highlighted by mutations in dnaA or dnaC.

This a major finding because it clearly demonstrates that the two roles of DnaA in the initiation process can be separated into initially forming an open complex at the DUE region by binding/nucleation onto DnaA-boxes and second in loading of the helicase. Whereas these two functions are normally assumed to be coupled, the present data clearly show that they can be separated and that PriC can perform at least part of the helicase loading provided that an area of duplex opening is formed by DnaA.<br /> This puts into questions the interpretation of a large body of previous work on mutagenesis of oriC and dnaA to find a minimal oriC/DnaA complex in many bacteria. In other words, mutants in which oriC is truncated/mutated may support initiation of replication and cell viability only in the presence of PriC. Such mutants are capable to generate single strand opening but may fail to load the helicase in absence of PriC. Similarly, dnaA mutants may generate aberrant complex on oriC that trigger strand opening but are incapable of loading DnaB unless PriC is present.

In the present work, the sequence of experiments presented is logical and the manuscript is clearly written and easy to follow. The very last part regarding PriC in cSDR replication does not add much to the story and may be omitted.

I have a few specific questions/comments

The partial complementation of the dnaC2 strain by PriC seems quite straightforward since this particular mutation leads to initiation arrest at the open complex stage and this sets the stage for PriC to load the helicase. The situation is somewhat different for dnaA46. Why is this mutation partly complemented by PriC at 37C? DnaA46 binds neither ATP nor ADP, yet it functions in initiation at permissive temperature. At nonpermssive temperature, it binds oriC as well but does not lead to initiation. Does the present data imply that the true initiation defect of DnaA46 lies in helicase loading? The authors need to comment on this in the text.

Relating to the above. In Fig. 3 it is shown that the pFH plasmid partly complement dnaA46 in a PriC dependent manner. Again, it would be nice to know the nature of the DnaA46 protein defect. It would be interesting to see how a pING1-dnaA46 plasmid performs in the experiment presented in Fig. 3.

Reviewer #2 (Public review):

Summary:

The authors use ligands (inverse agonists, partial agonists) for PPAR, and coactivators and corepressors, to investigate how ligands and cofactors interact in a complex manner to achieve functional outcomes (repressive vs. activating).

Strengths:<br /> The data (mostly biophysical data) are compelling from well-designed experiments. Figures are clearly illustrated. The conclusions are supported by these compelling data. These results contribute to our fundamental understanding of the complex ligand-cofactor-receptor interactions.

Weaknesses:

This is not the weakness of this particular paper, but the general limitation in using simplified models to study a complex system.

Reviewer #2 (Public review):

A long-standing debate in the field of Pavlovian learning relates to the phenomenon of timescale invariance in learning i.e. that the rate at which an animal learns about a Pavlovian CS is driven by the relative rate of reinforcement of the cue (CS) to the background rate of reinforcement. In practice, if a CS is reinforced on every trial, then the rate of acquisition is determined by the relative duration of the CS (T) and the ITI (C = inter-US-interval = duration of CS + ITI), specifically the ratio of C/T. Therefore, the point of acquisition should be the same with a 10s CS and a 90s ITI (T = 10; C = 90 + 10 = 100, C/T = 100/10 = 10) and with a 100s CS and a 900s ITI (T = 100; C = 900 + 100 = 1000, C/T = 1000/100 = 10). That is to say, the rate of acquisition is invariant to the absolute timescale as long as this ratio is the same. This idea has many other consequences, but is also notably different from more popular prediction-error based associative learning models such as the Rescrola-Wagner model. The initial demonstrations that the ratio C/T predicts the point of acquisition across a wide range of parameters (both within and across multiple studies) was conducted in Pigeons using a Pavlovian autoshaping procedure. What has remained under contention is whether or not this relationship holds across species, particularly in the standard appetitive Pavlovian conditioning paradigms used in rodents. The results from rodent studies aimed at testing this have been mixed, and often the debate around the source of these inconsistent results focuses on the different statistical methods used to identify the point of acquisition for the highly variable trial-by-trial responses at the level of individual animals.<br /> The authors successfully replicate same effect found in pigeon autoshaping paradigms decades ago (with almost identical model parameters) in a standard Pavlovian appetitive paradigm in rats. They achieve this through a clever change the experimental design, using a convincingly wide range of parameters across 14 groups of rats, and by a thorough and meticulous analysis of these data. It is also interesting to note that the two author's have published on opposing sides of this debate for many years, and as a result have developed and refined many of the ideas in this manuscript through this process.

Main findings

(1) The present findings demonstrate that the point of initial acquisition of responding is predicted by the C/T ratio.

(2) The terminal rates of responding to the CS appears to be related to the reinforcement rate of the CS (T; specifically, 1/T) but not its relation to the reinforcement rate of the context (i.e. C or C/T). In the present experiment, all CS trials were reinforced so it is also the case that the terminal rate of responding was related to the duration of the CS.

(3) An unexpected finding was that responding during the ITI was similarly related to the rate of contextual reinforcement (1/C). This novel finding suggests that the terminal rate of responding during the ITI and the CS are related to their corresponding rates of reinforcement. This finding is surprising as it suggests that responding during the ITI is not being driven by the probability of reinforcement during the ITI.

(4) Finally, the authors characterised the nature of increased responding from the point of initial acquisition until responding peaks at a maximum. Their analyses suggest that nature of this increase was best described as linear in the majority of rats, as opposed to the non-linear increase that might be predicted by prediction error learning models (e.g. Rescorla-Wagner). However, more detailed analyses revealed that these changes can be quite variable across rats, and more variable when the CS had lower informativeness (defined as C/T).

Strengths and Weaknesses:

There is an inherent paradox regarding the consistency of the acquisition data from Gibbon & Balsam's (1981) meta-analysis of autoshaping in pigeons, and the present results in magazine response frequency in rats. This consistency is remarkable and impressive, and is suggestive of a relatively conserved or similar underlying learning principle. However, the consistency is also surprising given some significant differences in how these experiments were run. Some of these differences might reasonably be expected to lead to differences in how these different species respond. For example:

- The autoshaping procedure commonly used in the pigeons from these data were pretrained to retrieve rewards from a grain hopper with an instrumental contingency between head entry into the hopper and grain availability. During Pavlovian training, pecking the key light also elicited an auditory click feedback stimulus, and when the grain hopper was made available the hopper was also illuminated.

- In the present experimental procedure, the rats were not given contextual exposure to the pellet reinforcers in the magazine (e.g. a magazine training session is typically found in similar rodent procedures). The Pavlovian CS was a cue light within the magazine itself.

These design features in the present rodent experiment are clearly intentional. Pretraining with the reinforcer in the testing chambers would reasonably alter the background rate of reinforcement (parameter), so it make sense not to include this but differs from the paradigm used in pigeons. Having the CS inside the magazine where pellets are delivered provides an effective way to reduce any potential response competition between CS and US directed responding and combines these all into the same physical response. This makes the magazine approach response more like the pecking of the light stimulus in the pigeon autoshaping paradigm. However, the location of the CS and US is separated in pigeon autoshaping, raising questions about why the findings across species are consistent despite these differences.

Intriguingly, when the insertion of a lever is used as a Pavlovian cue in rodent studies, CS directed responding (sign-tracking) often develops over training such that eventually all animals bias their responding towards the lever than towards the US (goal-tracking at the magazine). However, the nature of this shift highlights the important point that these CS and US directed responses can be quite distinct physically as well as psychologically. Therefore, by conflating the development of these different forms of responding, it is not clear whether the relationship between C/T and the acquisition of responding describes the sum of all Pavlovian responding or predominantly CS or US directed responding.

Another interesting aspect of these findings is that there is a large amount of variability that scales inversely with C/T. A potential account of the source of this variability is related to the absence of preexposure to the reward pellets. This is normally done within the animals' homecage as a form of preexposure to reduce neophobia. If some rats take longer to notice and then approach and finally consume the reward pellets in the magazine, the impact of this would systematically differ depending on the length of the ITI. For animals presented with relatively short CSs and ITIs, they may essentially miss the first couple of trials and/or attribute uneaten pellets accumulating in the magazine to the background/contextual rate of reinforcement. What is not currently clear is whether this was accounted for in some way by confirming when the rats first started retrieving and consuming the rewards from the magazine.

While the generality of these findings across species is impressive, the very specific set of parameters employed to generate these data raise questions about the generality of these findings across other standard Pavlovian conditioning parameters. While this is obviously beyond the scope of the present experiment, it is important to consider that the present study explored a situation with 100% reinforcement on every trial, with a variable duration CS (drawn form a uniform distribution), with a single relatively brief CS (maximum of 122s) CS and a single US. Again, the choice of these parameters in the present experiment is appropriate and very deliberately based on refinements from many previous studies from the authors. This includes a number of criteria used to define magazine response frequency that includes discarding specific responses (discussed and reasonably justified clearly in the methods section). Similarly, the finding that terminal rates of responding are reliably related to 1/T is surprising, and it is not clear whether this might be a property specific to this form of variable duration CS, the use of a uniform sampling distribution, or the use of only a single CS. However, it is important to keeps these limitations in mind when considering some of the claims made in the discussion section of this manuscript that go beyond what these data can support.

The main finding demonstrating the consistent findings across species is presented in Figure 3. In the analysis of these data, it is not clear why the correlations between C, T, and C/T and the measure of acquisition in Figure 3A were presented as r values, whereas the r2 values were presented in the discussion of Figure 3B, and no values were provided in discussing Figure 3C. The measure of acquisition in Figure 3A is based on a previously established metric, whereas the measure in Figure 3B employs the relatively novel nDKL measure that is argued to be a better and theoretically based metric. Surprisingly, when r and r2 values are converted to the same metric across analyses, it appears that this new metric (Figure 3B) does well but not as well as the approach in Figure 3A. This raises questions about why a theoretically derived measure might not be performing as well on this analysis, and whether the more effective measure is either more reliable or tapping into some aspect of the processes that underlie acquisition that is not accounted for by the nDKL metric. Unfortunately, the new metric is discussed and defined at great length but its utility is not considered.<br /> An important analysis issue that is unclear in the present manuscript is exactly how the statistics were run (how the model was defined, were individual subjects or group medians used, what software was used etc...). For example, it is not clear whether the analyses conducted in relation to Figure 3 used the data from individual rats or the group medians. Similarly, it appears that each rat contributes four separate data points, and a single regression line was fit to all these data despite the highly likely violation of the assumption independent observations (or more precisely, the assumption of uncorrelated errors) in this analysis. Furthermore, it is claimed that the same regression line fit the IT and CS period data in this figure, however this<br /> If the data in figure 3 were analyzed with log(ITI) or log(C/ITI) i.e. log(C/(T-C)), would this be a better fit for these data? Is it the case that the ratio of C/T the best predictor of the trial/point of acquisition, or is it the case that another metric related to reinforcement rates provides a better fit?

Based on the variables provided in Supplementary file 3, containing the acquisition data, I was unable to reproduce the values reported in the analysis of Figure 3.<br /> In relation to Figure 3: I am curious about whether the authors would be able to comment on whether the individual variability in trials to acquisition would be expected to scale differently based on C/T, or C, or (if a less restricted range was used) T?<br /> It is not clear why Figure 3C is presented but not analyzed, and why the data presented in Figure 4 to clarify the spread of the distribution of the data observed across the plots in Figure 3 uses the data from Figure 3C. This would seem like the least representative data to illustrate the point of Figure 4. It also appears to my eye that the data actually plotted in Figure 4 correspond to Figure 3A and 3B rather than the odds 10:1 data indicated in text.

What was the decision criteria used to decide on averaging the final 5 conditioning sessions as terminal responding for the analyses in Figure 5? This is an oddly specific number. Was this based on consistency with previous work, or based on the greatest number of sessions where stable data for all animals could be extracted?<br /> In the analysis corresponding to Figures 7-8: If I understand the description of this analysis correctly, for each rat the data are the cumulative response data during the CS, starting from the trial on which responding to the CS > ITI (t = 1), and ending at the trial on which CS responding peaked (maximum over 3 session moving average window; t = end). This analysis does not seem to account for changes (decline) in the ITI response rates over this period of acquisition, and it is likely that responding during the ITI is still declining after t=1. Are the 4 functions that were fit to these data to discriminate between different underlying generative processes still appropriate on total CS responding instead of conditional CS responding after accounting for changes in baseline response rates during ITI?

Page 27, Procedure, final sentence: The magazine responding during the ITI is defined as the 20s period immediately before CS onset. The range of ITI values (Table 1) always starts as low as 15s in all 14 groups. Even in the case of an ITI on a trial that was exactly 20s, this would also mean that the start of this period overlaps with the termination of the CS from the previous trial and delivery (and presumably consumption) of a pellet. Please indicate if the definition of the ITI period was modified on trials where the preceding ITI was <20s, and if any other criteria were used to define the ITI.

Were the rats exposed to the reinforcers/pellets in their home cage prior to acquisition? Please indicate whether rats where pre-exposed to the reward pellets in their home cages e.g. as is often done to reduce neophobia. Given the deliberate absence of a magazine-training phase, this information is important when assessing the experienced contingency between the CS and the US.

For all the analyses, please provide the exact models that were fit and the software used. For example, it is not necessarily clear to the reader (particularly in the absence of degrees of freedom) that the model fits discussed in Figure 3 are fit on the individual subject data points or the group medians. Similarly, in Figure 6 there is no indication of whether a single regression model was fit to all the plotted data or whether tests of different slopes for each of the conditions were compared. With regards to the statistics in Figure 6, depending on how this was run, it is also a potential problem that the analyses does not correct for the potentially highly correlated multiple measurements from the same subjects i.e. each rat provides 4 data points which are very likely not to be independent observations.

A number of sections of the discussion are speculative or not directly supported by the present experimental data (but may well be supported by previous findings that are not the direct focus of the present experiment). For example, Page 19, Paragraph 2: this entire paragraph is not really clearly explained and is presenting an opinion rather than a strong conclusion that follows directly from the present findings. Evidence for an aspect of RET in the present paper (i.e. the prediction of time scale invariance on the initial point of acquisition, but not necessarily the findings regarding the rate of terminal acquisition) - while supportive - does not necessarily provide unconditional evidence for this theory over all the alternatives.

Similarly, the Conclusion section (Page 23) makes the claim that "the equations have at most one free parameter", which may be an oversimplification that is conditionally true in the narrow context of the present experiment where many things were kept constant between groups and run in a particular way to ensure this is the case. While the equations do well in this narrow case, it is unlikely that additional parameters would not need to be added to account for more general learning situations. To clarify, I am not contending that this kind of statement is necessarily untrue, merely that it is being presented in a narrow context and may require a deeper discussion of much more of the literature to qualify/support properly - and the discussion section of the present experiment/manuscript may not be the appropriate place for this.

- Consider taking advantage of an "Ideas and Speculation" subsection within the Discussion that is supported by eLife [ https://elifesciences.org/inside-elife/e3e52a93/elife-latest-including-ideas-and-speculation-in-elife-papers ]. This might be more appropriate to qualify the tone of much of the discussion from page 19 onwards.

It seems like there are entire analyses and new figures being presented in the discussion e.g. Page 20: Information-Theoretic Contingency. These sections might be better placed in the methods section or a supplementary section/discussion.

Reviewer #2 (Public review):

This manuscript uses the ESM2 language model to map the evolutionary fitness landscape of intrinsically disordered regions (IDRs). The central idea is that mutational preferences predicted by these models could be useful in understanding eventual IDR-related behavior, such as disruption of otherwise stable phases. While ESM2-type models have been applied to analyze such mutational effects in folded proteins, they have not been used or verified for studying IDRs. Here, the authors use ESM2 to study membraneless organelle formation and the related fitness landscape of IDRs.

Through this, their key finding in this work is the identification of a subset of amino acids that exhibit mutation resistance. Their findings reveal a strong correlation between ESM2 scores and conservation scores, which if true, could be useful for understanding IDRs in general. Through their ESM2-based calculations, the authors conclude that IDRs crucial for phase separation frequently contain conserved sequence motifs composed of both so-called sticker and spacer residues. The authors note that many such motifs have been experimentally validated as essential for phase separation.

Unfortunately, I do not believe that the results can be trusted. ESM2 has not been validated for IDRs through experiments. The authors themselves point out its little use in that context. In this study, they do not provide any further rationale for why this situation might have changed. Furthermore, they mention that experimental perturbations of the predicted motifs in in vivo studies may further elucidate their functional importance, but none of that is done here. That some of the motifs have been previously validated does not give any credibility to the use of ESM2 here, given that such systems were probably seen during the training of the model.

I believe that the authors should revamp their whole study and come up with a rigorous, scientific protocol where they make predictions and test them using ESM2 (or any other scientific framework).

Reviewer #2 (Public review):

Summary:

This study by Leong and colleagues examines the role of the TCF7L2 transcription factor in the Wnt signaling pathway as a regulator of colon/small intestinal cancers and cachexia. Investigators utilize a Tet off repressor genetic system in mice under Dox regulation to silence TCF7L2. Results show DSS-treated APCMin/+ mice lose body weight that can be rapidly rescued by Dox treatment and suppression of TCF7L2 expression. Reduction of TCF7L2 rescues features of cachexia, including body weight, gastrocnemius muscle and adipose mass, as well as molecular markers of cachexia such as the E3 Ub ligases, MuRF1, and Atrogin-1. The most significant finding in the study is that loss of TCF7L2 reduces but does not eliminate tumor progression, as tumors go from adenomas to adenocarcinomas over time while mice are treated with Dox, yet cachexia persists. This implies that TCF7L2 has a direct effect on cachexia. Overall, the study provides insight into the role of TCFL2 in the development of intestinal cancers and muscle atrophy in cachexia.

Strengths:

The study uses an elegant genetic mouse model to provide significant new insight into the role of TCFL2 in colon and small intestinal cancers. In addition, the authors describe the role of TCF7L2 as a regulator of muscle wasting in cachexia. This, too, can be viewed as a new finding for the cachexia field.

Weaknesses:

However, in its current form, the study lacks sufficient data to support the authors' claim regarding the relevance of TCF7L2 as a regulator of cachexia.

Reviewer #2 (Public review):

Summary:

The authors wanted to investigate how cells defend against intracellular pathogens, such as Shigella and Burkholderia species, that co-opt the host actin machinery to spread from cell-to-cell. Previous work has identified IFNg-inducible GTPase of the Guanylate Binding Protein (GBP) family in cytosolic defence against Gram-negative bacteria. By forming a coat around Shigella, human GBP1 suppresses actin-based motility by displacing IcsA, which is the actin-polymerising virulence factor present at bacterial poles. In addition, GBP1 recruits the cytosolic LPS-sensor, caspase-4, to the bacterial surface, which results in the removal of bacterial replicative niches via pyroptotic cell death. Here, they followed up their finding that GBP1 can reduce actin-based motility of Shigella in HeLa cells and, surprisingly, fails to do so during Burkholderia infection. In contrast, in T24 bladder epithelial cells, GBP1 is competent in blocking Burkholderia actin-tails. They therefore wanted to identify the GBP1-independent factor that blocks actin-based motility in IFNg-treated cells that is absent in HeLa cells.

Major strengths and weaknesses of the methods and results:

The authors report a second IFNg-dependent pathway involving the protein product of the gene GVIN1, which was previously thought to be a pseudogene. GVIN1 (GTPase, very large interferon inducible 1) is thus the first human member of this family of ~250 kDa putative GTPases to be demonstrated to be functional and have potential antimicrobial roles. The discovery that GVIN1 is indeed functional, forms coats on Burkholderia in an LPS O-antigen-dependent manner, and limits actin-dependent motility are the main strengths of this paper. The authors use CRISPR/Cas9-based knockouts in HeLa and T24 cells, and complement them to demonstrate that GBP1 and GVIN1 are both required to inhibit actin-based motility.

An appraisal of whether the authors achieved their aims and whether the results support their conclusions:

The authors achieved their main goals through well-planned experiments and unbiased screens. They succeeded in finding the factor that blocks actin-based motility independently of GBP1. This is driven by GVIN1, which coats bacteria and limits actin-tail formation by reducing the expression of BimA through currently unknown mechanisms. Further, they found that an O-antigen mutant can escape coating by GVIN1, indicating the requirement for these polysaccharides in GVIN1-dependent bacterial sensing. However, the authors have not investigated whether GVIN1, which has two GTPase-domains, does indeed have GTPase activity and whether GVIN1 and GBP1 together completely block cell-to-cell spread by Burkholderia and thereby restrict bacterial numbers over the infection time course. They also do not show whether GBP1 and GVIN1 target the same bacterial cell or different populations of bacteria.

A discussion of the likely impact of the work on the field, and the utility of the methods and data to the community:

This work uncovers the antimicrobial actions of a member of yet another family of IFNg-induced GTPases, which potentially acts against other intracellular pathogens. GVIN1 appears to operate independently and in parallel to GBP1, pointing to the breadth and complexity of the IFNg-inducible GTPase families.

Reviewer #2 (Public review):

This observational study investigates the efficacy of intracameral injected human stems cells as a means to re-functionalize the trabecular meshwork for the restoration of intraocular pressure homeostasis. Using a murine model of glaucoma, human adipose-derived mesenchymal stem cells are shown to be biologically safer and functionally superior at eliciting a sustained reduction in intraocular pressure (IOP). The authors conclude that the use of magnetically-steered human adipose-derived mesenchymal stem cells has potential for long-term treatment of ocular hypertension in glaucoma.

Comments on revisions: Previously noted concerns have been thoughtfully and sincerely considered by the authors and are now clearly addressed in the revised manuscript. No further concerns/comments.

Örsted hat das derzeit weltweit größte Windenergieprojekt Harnz-ZV unterbrochen. Die Pause stellt die Realisierung des britischen Ziels, Bis 2030 50 Gigawatt Strom durch Auf Schrahr, Windenergie Windenergie zu produzieren in Frage. Der Windpark Hornzzi vor hätte alleine oder soll alleine 2400 Megawatt Strom produzieren. Für die Unterbrechung wurden vor allem kostengründelverantwortlich gemacht. In den USA wurden von der Trump-Administration mehrere Windenergieprojekte aus Tanz gestorpt.

https://www.connaissancedesenergies.org/afp/eolien-offshore-le-geant-orsted-met-en-pause-lexpansion-du-plus-grand-parc-du-monde-250507?utm_source=newsletter&utm_medium=fil-info-energies&utm_campaign=/newsletter/cde-aujourdhui-7-mai-2025&sstc=u36579nl166 571

Reviewer #2 (Public review):

Summary:

The present study sets out to examine the impact of counterconditioning (CC) and extinction on conditioned threat responses in humans, particularly looking at neural mechanisms involved in threat memory suppression. By combining behavioral, physiological, and neuroimaging (fMRI) data, the authors aim to provide a clear picture of how CC might engage unique neural circuits and coding dynamics, potentially offering a more robust reduction in threat responses compared to traditional extinction.

Strengths:

One major strength of this work lies in its thoughtful and unique design - integrating subjective, physiological, and neuroimaging measures to capture the variouse aspects of counterconditiong (CC) in humans. Additionally, the study is centered on a well-motivated hypothesis and the findings have potentials for improving the current understanding of pathways associated with emotional and cognitive control.

The data presentation is systematic, and the results on behavioral and physiological measures fit well with the hypothesized outcomes. The neuroimaging results also provide strong support for distinct neural mechanisms underlying CC versus extinction.

Weaknesses:

Overall, this study is a well-conducted and thought-provoking investigation into counterconditioning, with strong potential to advance our understanding of threat modulation mechanisms. Two minor weaknesses concern the scope and decisions regarding analysis choices. First, while the findings are solid, the topic of counterconditioning is relatively niche and may have limited appeal to a broader audience. Expanding the discussion to connect counterconditioning more explicitly to widely studied frameworks in emotional regulation or cognitive control would enhance the paper's accessibility and relevance to a wider range of readers. This broader framing could also underscore the generalizability and broader significance of the results. In addition, detailed steps in the statistical procedures and analysis parameters seem to be missing. This makes it challenging for readers to interpret the results in light of potential limitations given the data modality and/or analysis choices.

Comments on revisions: My previous concerns and questions have been sufficiently addressed.

Reviewer #2 (Public review):

Summary:

This manuscript presents a new approach for non-invasive, MRI-based, measurements of cerebral blood volume (CBV). Here, the authors use ferumoxytol, a high-contrast agent and apply specific sequences to infer CBV. The authors then move to statistically compare measured regional CBV with known distribution of different types of neurons, markers of metabolic load and others. While the presented methodology captures and estimated 30% of the vasculature, the authors corroborated previous findings regarding lack of vascular compartmentalization around functional neuronal units in the primary visual cortex.

Strengths:

Non-invasive methodology geared to map vascular properties in vivo.

Implementation of a highly sensitive approach for measuring blood volume.

Ability to map vascular structural and functional vascular metrics to other types of published data.

Weaknesses:

The key issue here is the underlying assumption about the appropriate spatial sampling frequency needed to captures the architecture of the brain vasculature. Namely, ~7 penetrating vessels / mm2 as derived from Weber et al 2008 (Cer Cor). The cited work, begins by characterizing the spacing of penetrating arteries and ascending veins using vascular cast of 7 monkeys (Macaca mulatta, same as in the current paper). The ~7 penetrating vessels / mm2 is computed by dividing the total number of identified vessels by the area imaged. The problem here is that all measurements were made in a "non-volumetric" manner and only in V1. Extrapolating from here to other brain areas is therefore not possible without further exploration with independent methodologies.

Please note that these are comments on the revised version.

Reviewer #2 (Public review):

Summary:

The authors generated three mouse lines harboring ASD, Schizophrenia, and Bi-polar-associated variants in the TRIO gene. Anatomical, behavioral, physiological, and biochemical assays were deployed to compare and contrast the impact of these mutations in these animals. In this undertaking the authors sought to identify and characterize the cellular and molecular mechanisms responsible for ASD, Schizophrenia, and Bi-polar disorder development.

Strengths:

The establishment of TRIO dysfunction in the development of ASD, Schizophrenia, and Bi-polar disorder is very recent and of great interest. Disorder-specific variants have been identified in the TRIO gene, and this study is the first to compare and contrast the impact of these variants in vivo in preclinical models. The impact of these mutations was carefully examined using an impressive host of methods. The authors achieved their goal of identifying behavioral, physiological, and molecular alterations that are disorder/variant specific. The impact of this work is extremely high given the growing appreciation of TRIO dysfunction in a large number of brain-related disorders. This work is very interesting in that it begins to identify the unique and subtle ways brain function is altered in ASD, Schizophrenia, and Bi-polar disorder.

Weaknesses:

(1) Most assays were performed in older animals and perhaps only capture alterations that result from homeostatic changes resulting from prodromal pathology that may look very different.

(2) Identification of upregulated (potentially compensating) genes in response to these disorder specific Trio variants is extremely interesting. However, a functional demonstration of compensation is not provided.

(3) There are instances where data is not shown in the manuscript. See "data not shown". All data collected should be provided even if significant differences are not observed.

I consider weaknesses 1 and 2 minor. While they would very interesting to explore, these experiments might be more appropriate for a follow up study. The missing data in 3 should be provided in the supplemental material.

Revised Manuscript:

All of my above concerns were well addressed by the authors in the revised submission.

Reviewer #2 (Public review):

Summary:

This study examines the role of TRPV1 signaling in the recruitment of monocyte-derived macrophages and the promotion of angiogenesis during tympanic membrane (TM) wound healing. The authors use a combination of genetic mouse models, macrophage depletion, and transcriptomic approaches to suggest that neuronal TRPV1 activity contributes to macrophage-driven vascular responses necessary for tissue repair.

Strengths:

(1) The topic of neuroimmune interactions in tissue regeneration is of interest and underexplored in the context of the TM, which presents a unique model due to its anatomical features.

(2) The use of reporter mice and bone marrow chimeras allows for some dissection of immune cell origin.

(3) The authors incorporate transcriptomic data to contextualize inflammatory and angiogenic processes during wound healing.

Weaknesses:

(1) The primary claims of the manuscript are not convincingly supported by the evidence presented. Most of the data are correlative in nature, and no direct mechanistic experiments are included to establish causality between TRPV1 signaling and macrophage recruitment or function.

(2) Functional validation of key molecular players (such as Tac1 or Spp1) is lacking, and their roles are inferred primarily from gene expression data rather than experimentally tested.

(3) The reuse of publicly available scRNA-seq data is not sufficiently integrated or extended to yield new biological insights, and it remains largely descriptive.

(4) The macrophage depletion model (CX3CR1CreER; iDTR) lacks specificity, and possible off-target or systemic effects are not addressed.

(5) Several interpretations of the data appear overstated, particularly regarding the necessity of TRPV1 for monocyte recruitment and wound healing.

(6) Overall, the study appears to apply known concepts - namely, TRPV1-mediated neurogenic inflammation and macrophage-driven angiogenesis - to a new anatomical site without providing new mechanistic insight or advancing the field substantially.

Overall:

While the study addresses an interesting topic, the current version does not provide sufficiently strong or novel evidence to support its major conclusions. Additional mechanistic experiments and more rigorous validation would be necessary to substantiate the proposed model and clarify the relevance of the findings beyond this specific tissue context.

Reviewer #2 (Public review):

Summary:

The current study aims to shed light on why previous work on perceptual rhythmicity has led to inconsistent results. They propose that the differences may stem from conceptual and methodological issues. In a series of experiments, the current study reports perceptual rhythmicity in different frequency bands that differ between different ear stimulations and behavioral measures. The study suggests challenges regarding the idea of universal perceptual rhythmicity in hearing.

Strengths:

The study aims to address differences observed in previous studies about perceptual rhythmicity. This is important and timely because the existing literature provides quite inconsistent findings. Several experiments were conducted to assess perceptual rhythmicity in hearing from different angles. The authors use sophisticated approaches to address the research questions.

Weaknesses:

(1) Conceptional concerns:

The authors place their research in the context of a rhythmic mode of perception. They also discuss continuous vs rhythmic mode processing. Their study further follows a design that seems to be based on paradigms that assume a recent phase in neural oscillations that subsequently influence perception (e.g., Fiebelkorn et al.; Landau & Fries). In my view, these are different facets in the neural oscillation research space that require a bit more nuanced separation. Continuous mode processing is associated with vigilance tasks (work by Schroeder and Lakatos; reduction of low frequency oscillations and sustained gamma activity), whereas the authors of this study seem to link it to hearing tasks specifically (e.g., line 694). Rhythmic mode processing is associated with rhythmic stimulation by which neural oscillations entrain and influence perception (also, Schroeder and Lakatos; greater low-frequency fluctuations and more rhythmic gamma activity). The current study mirrors the continuous rather than the rhythmic mode (i.e., there was no rhythmic stimulation), but even the former seems not fully fitting, because trials are 1.8 s short and do not really reflect a vigilance task. Finally, previous paradigms on phase-resetting reflect more closely the design of the current study (i.e., different times of a target stimulus relative to the reset of an oscillation). This is the work by Fiebelkorn et al., Landau & Fries, and others, which do not seem to be cited here, which I find surprising. Moreover, the authors would want to discuss the role of the background noise in resetting the phase of an oscillation, and the role of the fixation cross also possibly resetting the phase of an oscillation. Regardless, the conceptional mixture of all these facets makes interpretations really challenging. The phase-reset nature of the paradigm is not (or not well) explained, and the discussion mixes the different concepts and approaches. I recommend that the authors frame their work more clearly in the context of these different concepts (affecting large portions of the manuscript).

(2) Methodological concerns:

The authors use a relatively unorthodox approach to statistical testing. I understand that they try to capture and characterize the sensitivity of the different analysis approaches to rhythmic behavioral effects. However, it is a bit unclear what meaningful effects are in the study. For example, the bootstrapping approach that identifies the percentage of significant variations of sample selections is rather descriptive (Figures 5-7). The authors seem to suggest that 50% of the samples are meaningful (given the dashed line in the figure), even though this is rarely reached in any of the analyses. Perhaps >80% of samples should show a significant effect to be meaningful (at least to my subjective mind). To me, the low percentage rather suggests that there is not too much meaningful rhythmicity present. I suggest that the authors also present more traditional, perhaps multi-level, analyses: Calculation of spectra, binning, or single-trial analysis for each participant and condition, and the respective calculation of the surrogate data analysis, and then comparison of the surrogate data to the original data on the second (participant) level using t-tests. I also thought the statistical approach undertaken here could have been a bit more clearly/didactically described as well.

The authors used an adaptive procedure during the experimental blocks such that the stimulus intensity was adjusted throughout. In practice, this can be a disadvantage relative to keeping the intensity constant throughout, because, on average, correct trials will be associated with a higher intensity than incorrect trials, potentially making observations of perceptual rhythmicity more challenging. The authors would want to discuss this potential issue. Intensity adjustments could perhaps contribute to the observed rhythmicity effects. Perhaps the rhythmicity of the stimulus intensity could be analyzed as well. In any case, the adaptive procedure may add variance to the data.

Additional methodological concerns relate to Figure 8. Figures 8A and C seem to indicate that a baseline correction for a very short time window was calculated (I could not find anything about this in the methods section). The data seem very variable and artificially constrained in the baseline time window. It was unclear what the reader might take from Figure 8.

Motivation and discussion of eye-movement/pupillometry and motor activity: The dual task paradigm of Experiment 4 and the reasons for assessing eye metrics in the current study could have been better motivated. The experiment somehow does not fit in very well. There is recent evidence that eye movements decrease during effortful tasks (e.g., Contadini-Wright et al. 2023 J Neurosci; Herrmann & Ryan 2024 J Cog Neurosci), which appears to contradict the results presented in the current study. Moreover, by appealing to active sensing frameworks, the authors suggest that active movements can facilitate listening outcomes (line 677; they should provide a reference for this claim), but it is unclear how this would relate to eye movements. Certainly, a person may move their head closer to a sound source in the presence of competing sound to increase the signal-to-noise ratio, but this is not really the active movements that are measured here. A more detailed discussion may be important. The authors further frame the difference between Experiments 1 and 2 as being related to participants' motor activity. However, there are other factors that could explain differences between experiments. Self-paced trials give participants the opportunity to rest more (inter-trial durations were likely longer in Experiment 2), perhaps affecting attentional engagement. I think a more nuanced discussion may be warranted.

Discussion:

The main data in Figure 3 showed little rhythmicity. The authors seem to glance over this fact by simply stating that the same phase is not necessary for their statistical analysis. Previous work, however, showed rhythmicity in the across-participant average (e.g., Fiebelkorn's and similar work). Moreover, one would expect that some of the effects in the low-frequency band (e.g., 2-4 Hz) are somewhat similar across participants. Conduction delays in the auditory system are much smaller than the 0.25-0.5 s associated with 2-4 Hz. The authors would want to discuss why different participants would express so vastly different phases that the across-participant average does not show any rhythmicity, and what this would mean neurophysiologically.

An additional point that may require more nuanced discussion is related to the rhythmicity of response bias versus sensitivity. The authors could discuss what the rhythmicity of these different measures in different frequency bands means, with respect to underlying neural oscillations.

Figures:

Much of the text in the figures seems really small. Perhaps the authors would want to ensure it is readable even for those with low vision abilities. Moreover, Figure 1A is not as intuitive as it could be and may perhaps be made clearer. I also suggest the authors discuss a bit more the potential monoaural vs binaural issues, because the perceptual rhythmicity is much slower than any conduction delays in the auditory system that could lead to interference.

Reviewer #2 (Public review):

Summary:

This paper investigates the evolution of pesticide resistance in the two-spotted spider mite following the introduction of an SDHI acaricide, cyatpyrafen, in China. The authors make use of cyatpyrafen-naive populations collected before that pesticide was first used, as well as more recent populations (both sensitive and resistant) to conduct comparative population genomics. They report 15 different mutations in the insecticide target site from resistant populations, many reported here for the first time, and look at the mutation and selection processes underlying the evolution of resistance, through GWAS, haplotype mapping, and testing for loss of diversity indicating selective sweeps. None of the target site mutations found in resistant populations was found in pre-exposure populations, suggesting that the mutations may have arisen de novo rather than being present as standing variation, unless initially present at very low frequencies; a de novo origin is also supported by evidence of selective sweeps in some resistant populations. Furthermore, there is no significant evidence of migration of resistant genotypes between the sampled field populations, indicating multiple origins of common mutations. Overall, this indicates a very high mutation rate and a wide range of mutational pathways to resistance for this target site in this pest species. The series of population genomic analyses carried out here, in addition to the evolutionary processes that appear to underlie resistance development in this case, could have implications for the study of resistance evolution more widely.

Strengths:

This paper combines phenotypic characterisation with extensive comparative population genomics, made possible by the availability of multiple population samples (each with hundreds of individuals) collected before as well as after the introduction of the pesticide cyatpyrafen, as well as lab-evolved lines. This results in findings of mutation and selection processes that can be related back to the pesticide resistance trait of concern. Large numbers of mites were tested phenotypically to show the levels of resistance present, and the authors also made near-isogenic lines to confirm the phenotypic effects of key mutations. The population genomic analyses consider a range of alternative hypotheses, including mutations arising by de novo mutation or selection from standing genetic variation, and mutations in different populations arising independently or arriving by migration. The claim that mutations most likley arose by multiple repeated de novo mutations is therefore supported by multiple lines of evidence: the direct evidence of none of the mutations being found in over 2000 individuals from naive populations, and the indirect evidence from population genomics showing evidence of selective sweeps but not of significant migration between the sampled populations.

Weaknesses:

As acknowledged within the discussion, whilst evidence supports a de novo origin of the resistance-associated mutations, this cannot be proven definitively as mutations may have been present at a very low frequency and therefore not found within the tested pesticide-naive population samples.

Near-isofemale lines were made to confirm the resistance levels associated with five of the 15 mutations, but otherwise, the genotype-phenotype associations are correlative, as confirmation by functional genetics was beyond the scope of this study.

Reviewer #2 (Public review):

Summary:

This study focuses on Orf9b, a SARS-COV1/2 protein that regulates innate signaling through interaction with Tom70. San Felipe et al use a combination of biophysical methods to characterize the coupling between lipid-binding, dimerization, conformational change, and protein-protein-interaction equilibria for the Orf9b-Tom70 system. Their analysis provides a detailed explanation for previous observations of Orf9b function. In a cellular context, they find other factors may also be important for the biological functioning of Orf9b.

Strengths:

San Felipe et al elegantly combine structural biology, biophysics, kinetic modelling, and cellular assays, allowing detailed analysis of the Orf9b-Tom70 system. Such complex systems involving coupled equilibria are prevalent in various aspects of biology, and a quantitative description of them, while challenging, provides a detailed understanding and prediction of biological outcomes. Using SPR to guide initial estimates of the rate constants for solution measurements is an interesting approach.

Weaknesses:

This study would benefit from a more quantitative description of uncertainties in the numerous rate constants of the models, either through a detailed presentation of the sensitivity analysis or another approach such as MCMC. Quantitative uncertainty analysis, such as MCMC is not trivial for ODEs, particularly when they involve many parameters and are to be fitted to numerous data points, as is the case for this study. The authors use sensitivity analysis as an alternative, however, the results of the sensitivity analysis are not presented in detail, and I believe the authors should consider whether there is a way to present this analysis more quantitatively. For example, could the residuals for each +/-10% parameter change for the peptide model be presented as a supplementary figure, and similarly for the more complex models? Further details of the range of rate constants tested would be useful, particularly for the ka and kB parameters.

The authors build a model that incorporates an α-helix-β-sheet conformational change, but the rate constant for the conversion to the α-helix conformation is required to be second order. Although the authors provide some rationale, I do not find this satisfactorily convincing given the large number of adjustable parameters in the model and the use of manual model fitting. The authors should discuss whether there is any precedence for second-order rate constants for conformational changes in the literature. On page 14, the authors state this rate constant "had to be non-linear in the monomer β-sheet concentration" - how many other models did the authors explore? For example, would αT↔α↔αα↔ββ (i.e., conformational change before dimer dissociation) or α↔βαT↔ββ (i.e., Tom70 binding driving dimer dissociation) be other plausible models for the conformational change that do not require assumptions of second-order rate constants for the conformational change?

Overall, this study progresses the analysis of coupled equilibria and provides insights into Orf9b function.

Reviewer #2 (Public review):

Summary:

The authors were to investigate the functional role of IL10 on mucosal immunity in chickens. CRISPR technology was employed to generate IL10 knock-out chickens in both exon and putative enhancer regions. IL10 expressions were either abolished (knockout in exon) or reduced (enhancer knock-out). IL-10 plays an important role in the composition of the caecal microbiome. Through various enteric pathogen challenges, deficient IL10 expression was associated with enhanced pathogen clearance, but with more severe lesion scores and body weight loss.

Strengths:

Both in vitro and in vivo knock-out abolished and reduced IL10 expression, and broad enteric pathogens were challenged in vivo, and various parameters were examined to evaluate the functional role of IL10 on mucosal immunity.

Weaknesses:

Overexpression of IL-10 either in vitro or in vivo may further support the findings from this study.

Reviewer #2 (Public review):

Summary:

How corticostriatal synaptic connectivity gives rise to SPN encoding of sensory information is an important and currently unanswered question. The authors utilize a clever slice preparation in combination with electrophysiology and glutamate uncaging to dissect the synaptic connectivity between barrel cortex and individual striatal SPNs. In addition to mapping connectivity across major anatomical axes and cortical layers, the authors provide data showing that SPNs uniquely integrate sparse input from variable stretches across barrel cortex.

Strengths:

The methodology shows impressive rigor, and the data robustly support the authors' conclusions. Overall, the manuscript addresses its core question, provides valuable insights into corticostriatal architecture, and is a welcome addition to the field.

Weaknesses:

A few minor changes to the figures and text could be made to improve clarity.

Reviewer #2 (Public review):

Summary:

The authors attempt to estimate the heritability of brain activity evoked from a naturalistic fMRI paradigm. No new data were collected; the authors analyzed the publicly available and well-known data from the Human Connectome Project. The paper has 3 main pieces, as described in the Abstract:

(1) Heritability of movie-evoked brain activity and connectivity patterns across the cortex.

(2) Decomposition of this heritability into genetic similarity in "where" vs. "how" sensory information is processed.

(3) Heritability of brain activity patterns, as partially explained by the heritability of neural timescales.

Strengths:

The authors investigate a very relevant topic that concerns how heritable patterns of brain activity among individuals subjected to the same kind of naturalistic stimulation are. Notably, the authors complement their analysis of movie-watching data with resting-state data.

Weaknesses:

The paper has numerous problems, most of which stem from the statistical analyses. I also note the lack of mapping between the subsections within the Methods section and the subsections within the Results section. We can only assess results after understanding and confirming the methods are valid; here, however, Methods and Results, as written, are not aligned, so we can't always be sure which results are coming from which analysis.

(A) Intersubject correlation (ISC) (section that starts from line 143): "We used non-parametric permutation testing to quantify average differences in ISC for each parcel in the Schaefer 400 atlas for each day of data collection across three groups: MZ dyads, DZ dyads, and unrelated (UR) dyads, where all UR dyads were matched for gender and age in years." ... "some participants contributed to ISC values for multiple dyads (thus violating independence assumptions)"

This is an indirect attempt to demonstrate heritability. And it's also incorrect since, as the authors themselves point out, some subjects contribute to more than one dyad.

Permutation tests don't quantify "average differences", they provide a measure of evidence about whether differences observed are sufficient to reject a hypothesis of no difference.

Matching subjects is also incorrect as it artificially alters the sample; covarying for age and sex, as done in standard analyses of heritability, would have been appropriate.

It isn't clear why the authors went through the trouble of implementing their own non-parametric test if HCP recommends using PALM, which already contains the validated and documented methods for permutation tests developed precisely for HCP data.

The results from this analysis, in their current form, are likely incorrect.

(B) Functional connectivity (FC) (section that starts from line 159): Here the authors compute two 400x400 FC matrix for each subject, one for rest, one for movie-watching, then correlate the correlations within each dyad, then compared the average correlation of correlations for MZ, DZ, and UR. In addition to the same problems as the previous analysis, here it is not clear what is meant by "averaging correlations [...] within a network combination". What is a "network combination"? Further, to average correlations, they need to be r-to-z transformed first. As with the above, the results from this analysis in its current form are likely incorrect.

(C) ISC and FC profile heritability analyses (section that starts from line 175): Here, the authors use first a valid method remarkably similar to the old Haseman-Elston approach to compute heritability, complemented by a permutation test. That is fine. But then they proceed with two novel, ill-described, and likely invalid methods to (1) "compare the heritability of movie and rest FC profiles" and (2) to "determine the sample size necessary for stable multidimensional heritability results". For (1), they permute, seemingly under the alternative, rest and movie-watching timeseries, and (2), by dropping subjects and estimating changes in the distribution.

The (1) might be correct, but there are items that are not clearly described, so the reader cannot be sure of what was done. What are the "153 unique network combinations"? Why do the authors separate by day here, whereas the previous analyses concatenated both days? Were the correlations r-to-z transformed before averaging?

The (2) is also not well described, and in any case, power can be computed analytically; it isn't clear why the authors needed to resort to this ad hoc approach, the validity of which is unknown. If the issue is the possibility that the multidimensional phenotypic correlation matrix is rank-deficient, it suffices that there are more independent measurements per subject than the number of subjects.

(D) Frequency-dependent ISC heritability analysis (from line 216): Here, the authors decompose the timeseries into frequency bands, then repeat earlier analyses, thus bringing here the same earlier problems and questions of non-exchangability in the permutations given the dyads pattern, r-z transforms, and sex/age covariates.

(E) FC strength heritability analysis (from line 236): Here, the authors use the univariate FC to compute heritability using valid and well-established methods as implemented in SOLAR. There is no "linkage" being done here (thus, the statement in line 238 is incorrect in this application. SOLAR already produces SEs, so it's unclear why the authors went out of their way to obtain jackknife estimates. If the issue is non-normality, I note that the assumption of normality is present already at the stage in which parameters themselves are estimated, not just the standard errors; for non-normal data, a rank-based inverse-normal transformation could have been used. Moreover, typically, r-to-z transformed values tend to be fairly normally distributed. So, while the heritabilities might be correct, the standard errors may not be (the authors don't demonstrate that their jackknife SE estimator is valid). The comparison of h2 between dyads raises the same questions about permutations, age/sex covariates, and r-z transforms as above.

(F) Hyperalignment (from line 245): It isn't clear at this point in the manuscript in what way hyperalignment would help to decompose heritability in "where vs. how" (from the Abstract). That information and references are only described much later, from around line 459. The description itself provides no references, and one cannot even try to reproduce what is described here in the Methods section. Regardless, it isn't entirely clear why this analysis was done: by matching functional areas, all heritabilities are going to be reduced because there will be less variance between subjects. Perhaps studying the parameters that drive the alignment (akin to what is done in tensor-based and deformation-based morphometry) could have been more informative. Plus, the alignment process itself may introduce errors, which could also reduce heritability. This could be an alternative explanation for the reduced heritability after hyperalignment and should be discussed. An investigation of hyperaligment parameters, their heritability, and their co-heritability with the BOLD-phenotypes can inform on this.

(G) Relationships between parcel area and heritability (from line 270): As under F), how much the results are distorted likely depends on the accuracy of the alignment, and the error variance (vs heritable variance) introduced by this.

(H) Neural timescale analyses (from line 280): Here, a valid phenotype (NT) is assessed with statistical methods with the same limitations as those previously (exchangability of dyads, age/sex covariates, and r-z transforms). NT values are combined across space and used as covariates in "some multivariate analyses". As a reader, I really wanted to see the results related to NT, something as simple as its heritability, but these aren't clearly shown, only differences between types of dyads.

(I) Significance testing for autocorrelated brain maps and FC matrices (from line 310): Here, the authors suddenly bring up something entirely different: reliability of heritability maps, and then never return to the topic of reliability again. As a reader, I find this confusing. In any case, analyses with BrainSMASH with well-behaved, normally distributed data are ok. Whether their data is well behaved or whether they ensured that the data would be well behaved so that BrainSMASH is valid is not described. As to why Spearman correlations are needed here, Mantel tests, or whether the 1000 "surrogate" maps are valid realizations of the data under the null, remains undemonstrated.

(J) Global signal was removed, and the authors do not acknowledge that this could be a limitation in their analyses, nor offer a side analysis in which the global signal is preserved.

(K) FDR is used to control the error rate, but in many cases, as it's applied to multiple sets of p-values, the amount of false discoveries is only controlled across all tests, but not within each set. The number of errors within any set remains unknown.

(L) Generally, when studying the heritability of a trait, the trait must be defined first. Here, multiple traits are investigated, but are never rigorously defined. Worse, the trait being analyzed changes at every turn.

for - stats - natural language acquisition - 1 to 2 year old is age of fastest and best learning

comment - ALG philosophy - replicate the experiences that 1 to 2 year olds have

for - natural language acquisition - age - 2 year old is right age to aim to learn at

comment - 2 year old age is when an infant learns to hear and speak a spoken language first - reading and writing does not happen until about 5 years of age - When we are learning a new second language, it is therefore appropriate to aim for the same goal as a native 2 year old language user

Reviewer #2 (Public review):

Summary:

This study shows that when excitatory DREADD receptors are expressed in the ventral area of the cervical spinal cord containing phrenic motoneurons, systemic administration of the DREADD ligand J60 increases diaphragm EMG activity without altering respiratory rate. The authors took a non-selective expression approach in wild-type mice, as well as a more selective Cre-dependent approach in Chat-Cre mice and Chat-Cre rats to stimulate cervical motoneurons in the spinal cord. This is a proof of principle study that supports the use of DREADD technology to stimulate the motor output to the diaphragm.

Strengths:

The strengths of the study lie in the use of both mice and rats to test whether the chomogenetic activation of phrenic motoneurons with multiple experimental approaches increases diaphragm EMG activity (both tonic and phasic) and tidal volume.

Comments on revisions:

Thanks for addressing my comments. One last comment that could be discussed or addressed is :

Line 295- was the time post-infection, which varies considerably between groups and across samples, taken into consideration when comparison of response was made between ChatCre mice (4-9 weeks post-infection) and WT mice (four to five weeks post-infection)?

Reviewer #1 (Public review):

Summary:

This study provides an in-depth analysis of syncytiotrophoblast (STB) gene expression at the single-nucleus (SN) and single-cell (SC) levels, using both primary human placental tissues and two trophoblast organoid (TO) models. The authors compare the older TO model, where STB forms internally (STBin), with a newer model where STB forms externally (STBout). Through a series of comparative analyses, the study highlights the necessity of using both SN and SC techniques to fully understand placental biology. The findings demonstrate that the STBout model shows more differentiated STBs with higher expression of canonical markers and hormones compared to STBin. Additionally, the study identifies both conserved and distinct gene expression profiles between the TO models and human placenta, offering valuable insights for researchers using TOs to study STB and CTB differentiation.

Strengths:

The study offers a comprehensive SC- and SN-based characterization of trophoblast organoid models, providing a thorough validation of these models against human placental tissues. By comparing the older STBin and newer STBout models, the authors effectively demonstrate the improvements in the latter, particularly in the differentiation and gene expression profiles of STBs. This work serves as a critical resource for researchers, offering a clear delineation of the similarities and differences between TO-derived and primary STBs. The use of multiple advanced techniques, such as high-resolution sequencing and trajectory analysis, further enhances the study's contribution to the field.

Weaknesses were addressed during the revision.

The authors effectively addressed my critiques in the rebuttal letter and made corresponding changes in the manuscript. Specifically, they: 1) emphasized the importance of TO orientation in influencing STB nuclear subtype differentiation by adding text to the introduction; 2) clarified the differences in cluster numbers and names between primary tissue and TO data, explaining that each dataset was analyzed independently with separate clustering algorithms and adding clarifying text to the results section; 3) included additional rationale for using SN over SC sequencing, particularly for studying the multinucleated STB; 4) acknowledged that their original evidence was insufficient to definitively determine STBout nuclei differentiation status and removed language suggesting STB-3 as a terminally differentiated subtype, presenting alternative hypotheses in the discussion; and 5) incorporated new figures and clarifications, including RNA-FISH experiments, to validate subtype-specific marker gene expression. Overall, the authors' revisions strengthened the manuscript and aligned well with my critiques.

Reviewer #2 (Public review):

Summary:

This article presents a study on a mutant form of RNA polymerase I (RNAPI) in yeast, referred to as SuperPol, which demonstrates increased rRNA production compared to the wild-type enzyme. While rRNA production levels are elevated in the mutant, RNAPI occupancy as detected by CRAC is reduced at the 5' end of rDNA transcription units. The authors interpret these findings by proposing that the wild-type RNAPI pauses in the external transcribed spacer (ETS), leading to premature transcription termination (PTT) and degradation of truncated rRNAs by the RNA exosome (Rrp6). They further show that SuperPol's enhanced activity is linked to a lower frequency of PTT events, likely due to altered elongation dynamics and reduced RNA cleavage activity, as supported by both in vivo and in vitro data.

The study also examines the impact of BMH-21, a drug known to inhibit Pol I elongation, and shows that SuperPol is less sensitive to this drug, as demonstrated through genetic, biochemical, and in vivo approaches. The authors show that BMH-21 treatment induces premature termination in wild-type Pol I, but only to a lesser extent in SuperPol. They suggest that BMH-21 promotes termination by targeting paused Pol I complexes and propose that PTT is an important regulatory mechanism for rRNA production in yeast.

The data presented are of high quality and support the notion that 1) premature transcription termination occurs at the 5' end of rDNA transcription units; 2) SuperPol has an increased elongation rate with reduced premature termination; and 3) BMH-21 promotes both pausing and termination. The authors employ several complementary methods, including in vitro transcription assays. These results are significant and of interest for a broad audience.

Beyond the minor points listed below, my main criticism concerns the interpretation of data in relation to termination. While it is possible that the SuperPol mutation affects the wild-type Pol I's natural propensity for termination, it is also possible that premature termination is simply a consequence of natural or BMH-21-induced Pol I pausing. SuperPol may elongate more efficiently than the wild-type enzyme, pause less frequently, and thus terminate less often. In this light, the notion that termination "regulates" rRNA production might be an overstatement, with pausing as the primary event. Claiming a direct effect on termination by both the mutation and BMH-21 would require showing that with equivalent levels of pausing, termination occurs more or less efficiently, which would be challenging and should not be expected in this study. The authors address this point in the last two paragraphs of the discussion. My suggestion is to temper the claims regarding termination as a regulatory mechanism.

Significance:

These results are significant and of interest for a basic research audience.

Reviewer #3 (Public review):

In the present study, the author revealed that cardiomyocyte-specific deletion of mouse AARS2 exhibited evident cardiomyopathy with impaired cardiac function, notable cardiac fibrosis, and cardiomyocyte apoptosis. Cardiomyocyte-specific AARS2 overexpression in mice improved cardiac function and reduced cardiac fibrosis after myocardial infarction (MI), without affecting cardiomyocyte proliferation and coronary angiogenesis. Mechanistically, AARS2 overexpression suppressed cardiomyocyte apoptosis and mitochondrial reactive oxide species production, and changed cellular metabolism from oxidative phosphorylation toward glycolysis in cardiomyocytes, thus leading to cardiomyocyte survival from ischemia and hypoxia stress. Ribo-Seq revealed that AARS2 overexpression increased pyruvate kinase M2 (PKM2) protein translation and the ratio of PKM2 dimers to tetramers that promote glycolysis. Additionally, PKM2 activator TEPP-46 reversed cardiomyocyte apoptosis and cardiac fibrosis caused by AARS2 deficiency. Thus, this study demonstrates that AARS2 plays an essential role in protecting cardiomyocytes from ischemic pressure via fine-tuning PKM2-mediated energy metabolism, and presents a novel cardiac protective AARS2-PKM2 signaling during the pathogenesis of MI.

Comments on revised version:

The authors addressed all the issues, no more comments.

Reviewer #2 (Public review):

This work by Manley and Vaziri identify brain networks that are associated with trial-to-trial variability during prey-capture and predator avoidance behaviors. However, mixing of signals across space and time make it difficult to interpret the data generated and relate the data to findings from prior work.

Comments on revisions:'

In their response to prior reviewer comments, Manley and Vaziri have now provided helpful methodological clarity and additional analyses. The additional work makes clear that the claims of variability and mixing of sensory, motor, and internal variables at the single-cell level are not well supported.

RESOLUTION<br /> - The new information provided regarding resolution may not be very relevant as this was from an experiment in air. It would be much more informative to show how PSF degrades in the brain with depth.

DEPTH<br /> - It is helpful to see the registered light-field and confocal images. Both appear to provide poor or little information in regions >200 below the surface (like the hypothalamus), making the claim that whole brain data is being collected at cellular resolution difficult to justify.

MERGING<br /> - The typical soma at these ages has a radius of 2.5 microns, which corresponds to a volume of 65 microns^3. Given the close packing of most cells, this means that a typical ROI of 750 microns^3 contains more than 10 neurons. Therefore, the authors should not claim they are reporting activity at cellular resolution.<br /> - Furthermore, the fact that these ROIs contains tens of cells brings into question the degree of variability at the single-cell level. For example, if every cluster of 10 cells has one variable cell, then all clusters might be labeled as exhibiting variability even though only 10% of the cells show variability.

SLOW CALCIUM DYNAMICS<br /> - Convolution/Deconvolution with the inappropriate kernel both have problems, some of which the authors have noted. However, by not deconvolving, the authors are significantly obscuring the interpretation of their data by mixing together signals across time.<br /> - Also, the claim that "neurons highly tuned to a particular stimulus exhibited variability in their responses across multiple presentations of the same stimuli" should be clarified or qualified. It is not clear from what has been shown if the responses are indeed variable, or rather if there is additional activity (or apparent activity) occasionally present that shifts the pre-stimulus baseline around (for example, 3J suggests that in many cases the visual signal from the prior trial is still present when a new trial begins).<br /> - Figure 3A should show when the stimulus occurs, should show some of the prestimulus period, and ideally be off-set corrected so all traces in a given panel start at the same y-value at the beginning of the stimulus period.

ORTHOGONALITY<br /> - It is now clearer that the visual signal and noise vectors were determined for the entire time series with all trials. Therefore, the concern that sources of activation in advance of a given trial were being ignored is alleviated. The concern remains, however, that these sources are being properly accounted for given potential kernel variations and nonlinearity. Nonetheless, it is recognized that the GCaMP filtering most likely would lead to a decrease in the disparity between two populations.<br /> - The authors' clarification that the analyzed ROIs consist of cell clusters raises the trivial possibility that the observed orthogonality between the visual signal and leading noise vectors is explained by noise simply reflecting the activation of different motor or motor-planning related neurons in an ROI, neurons that are separate from visually-encoding neurons in the same cluster.

SOURCES of VARIABILITY<br /> - The data presented in Supplemental Figure 3Ei actually is suggestive that eye movements are a significant contributor to the reported variability. Notice how in (1 4) vs (1 5) and (4 7) vs (4 8) there is a notable difference in the distribution of responses. Adding eye kinematic variables to the analysis of Figure S4 could be clarifying.-

Reviewer #2 (Public review):

Summary:

This manuscript describes a workflow and software package, SMARTR, for mapping and analyzing neuronal ensembles tagged using activity-dependent methods. They showcase this pipeline by analyzing ensembles tagged during the learned helplessness paradigm. This is an impressive effort, and I commend the authors for developing open-source software to make whole-brain analyses more feasible for the community. After peer-review, the authors addressed reviewer suggestions and concerns regarding the usability and maintainability of the SMARTTR package, ensuring that the package will be published on CRAN, improving documentation, and including unit tests to ensure code stability. Overall, this software package will prove to have a broad impact on the field.

Reviewer #2 (Public review):

Summary:

This paper investigates the general concept that avian and mammalian pallium specifications share similar mechanisms. To explore that idea, the authors focus their attention on the role of miR-19b as a key controlling factor in the neuronal proliferation/differentiation balance. To do so, the authors checked the expression and protein level of several genes involved in neuronal differentiation, such as NeuroD1 or E2f8, genes also expressed in mammals after conducting their functional gene manipulation experiments. The work also shows a dysregulation in the number of neurons from lower and upper layers when miR-19b expression is altered.

To test it, the authors conducted a series of functional experiments of gain and loss of function (G&LoF) and enhancer-reporter assays. The enhancer-reporter assays demonstrate a direct relationship between miR-19b and NeuroD1 and E2f8 which is also validated by the G&LoF experiments. It´s also noteworthy to mention that the way miR-19b acts is maintaining the progenitor cells from the ventricular zone in an undifferentiated stage, thus promoting them into a stage of cellular division.

Overall, the paper argues that the expression of miR-19b in the ventricular zone promotes the cells in a proliferative phase and inhibits the expression of differentiation genes such as E2f8 and NeurD1. The authors claim that a decrease in the progenitor cell pool leads to an increase and decrease in neurons in the lower and upper layers, respectively.

Strengths:

(1) Novelty Contribution<br /> The paper offers strong arguments to prove that the neurodevelopmental basis between mammals and birds is quite the same. Moreover, this work contributes to a better understanding of brain evolution along the animal evolutionary tree and will give us a clearer idea about the roots of how our brain has been developed. This stands in contrast to the conventional framing of mammal brain development as an independent subject unlinked to the "less evolved species". The authors also nicely show a concept that was previously restricted to mammals - the role of microRNAs in development.

(2) Right experimental approach<br /> The authors perform a set of functional experiments correctly adjusted to answer the role of miR-19b in the control of neuronal stem cell proliferation and differentiation. Their histological, functional, and genetic approach gives us a clear idea about the relations between several genes involved in the differentiation of the neurons in the avian pallium. In this idea, they maintain the role of miR-19b as a hub controller, keeping the ventricular zone cells in an undifferentiated stage to perpetuate the cellular pool.

(3) Future directions<br /> The findings open a door to future experiments, particularly to a better comprehension of the role of microRNAs and pallidal genetic connections. Furthermore, this work also proves the use of avians as a model to study cortical development due to the similarities with mammals.

Weaknesses:

While there are questions answered, there are still several that remain unsolved. The experiments analyzed here lead us to speculate that the early differentiation of the progenitor cells from the ventricular zone entails a reduction in the cellular pool, affecting thereafter the number of latter-born neurons (upper layers). The authors should explore that option by testing progenitor cell markers in the ventricular zone, such as Pax6. Even so, it remains possible that miR-19b is also changing the expression pattern of neurons that are going to populate the different layers, instead of their numbers, so the authors cannot rule that out or verify it. Since the paper focuses on the role of miR-19b in patterning, I think the authors should check the relationship and expression between progenitors (Pax6) and intermediate (Tbr2) cells when miR-19b is affected. Since neuronal expression markers change so fast within a few days (HH24-HH35), I don't understand why the authors stop the functional experiments at different time points.

Reviewer #2 (Public review):

Summary:

In this study, the authors test whether intuitive biological causal knowledge is embedded in domain-specific semantic networks, primarily focusing on the precuneus as part of the animacy semantic network. They do so tanks to an fMRI task, by comparing brain activity elicited by participants' exposure to written situations suggesting a plausible cause of illness with brain activity in linguistically equivalent situations suggesting a plausible cause of mechanical failure or damage and non-causal situations. These contrasts confirm the PC as the main "culprit" in whole-brain and fROIs univariate analyses. In turn, inferring causes of mechanical failure engages mostly the PPA. The authors further test whether the content-specificity has to do with inferences about animates in general, or if there are some distinctions between reasoning about people's bodies versus mental states. To answer this question, the authors localize the mentalizing network and study the relation between brain activity elicited by Illness-Causal > Mech-Causal and Mentalizing > Physical stories. They conclude that inferring about the causes of illness partially differentiates from reasoning about people's states of mind. The authors finally test the alternative yet non-mutually exclusive hypothesis that both types of implicit causal inferences (illness and mechanical) depend on shared neural machinery. Good candidates are language and logic, which justifies the use of a language/logic localizer. No evidence of commonalities across causal inferences versus non-causal situations are found.

Strengths:

(1) This study introduces a useful paradigm and well-designed set of stimuli to test for implicit causal inferences.<br /> (2) Another important methodological advance is the addition of physical stories to the original mentalizing protocol.<br /> These tools pave the way for further investigation of domain-specific causal inference.<br /> (3) The authors have significantly improved the manuscript, addressing previous concerns and incorporating additional analyses that strengthen their conclusions.

Key improvements:<br /> (1) The revised introduction makes the study's contribution more explicit and resolves initial ambiguities regarding its scope.<br /> (2) The rationale for focusing primarily on the precuneus is now clearer and the additional analysis in the fusiform face area provides a valuable comparison.<br /> (3) The revised manuscript now includes a more detailed examination of the searchlight MVPA results, showing that illness and mechanical inferences elicit spatially distinct neural patterns in key regions, including the left PC, anterior PPA, and lateral occipitotemporal cortex.<br /> (4) The authors' justification for using an implicit inference task, arguing that explicit tasks introduce executive function confounds, is convincing.<br /> (5) The authors now acknowledge that while their results support a content-specific neural basis for implicit causal inference, domain-general mechanisms may still play a role in other contexts.

I have no major remaining concerns.

Reviewer #2 (Public review):

The data is largely electrophysiological recordings coupled with behavioral measurements (technically impressive) and some gain-of-function experiments in freely walking flies. Loss-of-function was tested but has minimal effect, which is not surprising in a system with partially redundant control mechanisms. The data is also consistent with/complementary to subsequent manuscripts (Yang 2023, Feng 2024, and Ros 2024) showing additional descending neurons with contributions to steering in walking and flying.

The experiments are well executed, the results interesting, and the description clear. Some hypotheses based on connectome anatomy are tested: the insights on the pre-synaptic side - how sensory and central complex heading circuits converge onto these DNs is stronger than the suggestions about biomechanical mechanisms for how turning happens on the motor side.

Of particular interest is the idea that different sensory cues can converge on a common motor program. The turn-toward or turn-away mechanism is initiated by valence rather than whether the stimulus was odor or temperature or memory of heading. The idea that animals chose a direction based on external sensory information and then maintain that direction as a heading through a more internal, goal-based memory mechanism, is interesting but it is hard to separate conclusively.

The "see-saw", where left-right symmetry is broken to allow a turn, presumably by excitation on one side and inhibition of the other leg motor modules, is interesting but not well explained here. How hyperpolarization affects motor outputs is not clear.

The statement near Figure 5B that "DNa02 activity was higher on the side ipsilateral to the attractive stimulus, but contralateral to the aversive stimulus" is really important - and only possible to see because of the dual recordings.

Comments on revisions:

I am happy that the revised manuscript addresses all reviewers' concerns.

Reviewer #2 (Public review):

Strengths:

The article addresses a topic of significant importance, focusing on early life growth faltering in low-income countries-a key marker of undernutrition-and its impact on brain functional connectivity (FC) and cognitive development. The study's strengths include the laborious data collection process, as well as the rigorous data preprocessing methods employed to ensure high data quality. The use of cutting-edge preprocessing techniques further enhances the reliability and validity of the findings, making this a valuable contribution to the field of developmental neuroscience and global health.

Weaknesses:

The study fails to fully leverage its longitudinal design to explore neurodevelopmental changes or trajectories, as highlighted by all three reviewers. The revised manuscript still primarily focuses on FC values at a single age stage (i.e., 24 months) rather than utilizing the longitudinal data to investigate how FC evolves over time or predicts cognitive development. Although the authors acknowledge that analyzing changes in FC (ΔFC) would reduce degrees of freedom (to ~30) and risk interpretability, they do not report or discuss these results, even as exploratory findings.

Furthermore, the study lacks specificity in identifying which specific brain networks are affected by growth faltering, as the current exploratory analyses mainly provide an overall conclusion that infant brain network development is impacted without pinpointing the precise neural mechanisms or networks involved.

Reviewer #2 (Public review):

Summary:

Communication between sensory and motor corticies is likely to be important for many aspects of behavior, and in this study the authors carefully analyse neuronal spiking activity in S1 and M1 evoked by peripheral paw stimulation finding clear evidence for sensory responses in both cortical regions

Strengths:

The experiments and data analyses appear to have been carefully carried out and clearly represented.

Weaknesses:

The revised manuscript addressed the minor weaknesses I noted relating to the first submission.

Reviewer #2 (Public review):

Summary:

The manuscript offers an important contribution to the field of virology, especially concerning NNV entry mechanisms. The major strength of the study lies in the identification of MmMYL3 as a functional receptor for RGNNV and its role in macropinocytosis, mediated by the IGF1R-Rac1/Cdc42 signaling axis. This represents a significant advance in understanding NNV entry mechanisms beyond previously known receptors such as HSP90ab1 and HSC70. The data, supported by comprehensive in vitro and in vivo experiments, strongly justify the authors' claims about MYL3's role in NNV infection in marine medaka.

Strengths:

(1) The identification of MmMYL3 as a functional receptor for RGNNV is a significant contribution to the field. The study fills a crucial gap in understanding the molecular mechanisms governing NNV entry into host cells.

(2) The work highlights the involvement of IGF1R in macropinocytosis-mediated NNV entry and downstream Rac1/Cdc42 activation, thus providing a thorough mechanistic understanding of NNV internalization process. This could pave the way for further exploration of antiviral targets.

Comments on revisions:

The authors have addressed the concerns from reviewers. This manuscript can be published in the current form.

Reviewer #2 (Public review):

Summary:

In this work, the investigators isolated one Lacticaseibacillus rhamnosus strain (P118), and determined this strain worked well against Salmonella Typhimurium infection. Then, further studies were performed to identify the mechanism of bacterial resistance, and a list of confirmatory assays were carried out to test the hypothesis.

Strengths:

The authors provided details regarding all assays performed in this work, and this reviewer trusted that the conclusion in this manuscript is solid. I appreciate the efforts of the authors to perform different types of in vivo and in vitro studies to confirm the hypothesis.

Weaknesses:

I have mainly two questions for this work.

Main point-1:<br /> The authors provided the below information about the sources from which Lacticaseibacillus rhamnosus was isolated. More details are needed. What are the criteria to choose these samples? Where were these samples originate from? How many strains of bacteria were obtained from which types of samples?

Lines 486-488: Lactic acid bacteria (LAB) and Enterococcus strains were isolated from the fermented yoghurts collected from families in multiple cities of China and the intestinal contents from healthy piglets without pathogen infection and diarrhoea by our lab.

Lines 129-133: A total of 290 bacterial strains were isolated and identified from 32 samples of the fermented yoghurt and piglet rectal contents collected across diverse regions within China using MRS and BHI medium , which consist s of 63 Streptococcus strains, 158 Lactobacillus/ Lacticaseibacillus Limosilactobacillus strains and 69 Enterococcus strains.

Main-point-2:<br /> As probiotics, Lacticaseibacillus rhamnosus has been widely studied. In fact, there are many commercially available products, and Lacticaseibacillus rhamnosus is the main bacteria in these products. There are also ATCC type strain such as 53103.

I am sure the authors are also interested to know if P118 is better as a probiotics candidate than other commercially available strains. Also, would the mechanism described for P118 apply to other Lacticaseibacillus rhamnosus strains?

It would be ideal if the authors could include one or two Lacticaseibacillus rhamnosus which are currently commercially used, or from the ATCC. Then, the authors can compare the efficacy and antibacterial mechanisms of their P118 with other strains. This would open the windows for future work.

Reviewer #2 (Public review):

Summary:

Shin et al aim to identify in a very extensive piece of work a mechanism that contributes to dynamic regulation of synaptic output in the rat cortex at the second time scale. This mechanism is related to a new powerful model and is well versed to test if the pool of SV ready for fusion is dynamically scaled to adjust supply demand aspects. The methods applied are state-of-the-art and both address quantitative aspects with high signal to noise. In addition, the authors examine both excitatory output onto glutamatergic and GABAergic neurons, which provides important information on how general the observed signals are in neural networks. The results are compellingly clear and show that pool regulation may be predominantly responsible. Their results suggests that a regulation of release probability, the alternative contender for regulation, is unlikely to be involved in the observed short term plasticity behavior (but see below). Besides providing a clear analysis pof the underlying physiology, they test two molecular contenders for the observed mechanism by showing that loss of Synaptotagmin7 function and the role of the Ca dependent phospholipase activity seems critical for the short term plasticity behavior. The authors go on to test the in vivo role of the mechanism by modulating Syt7 function and examining working memory tasks as well as overall changes in network activity using immediate early gene activity. Finally, they model their data, providing strong support for their interpretation of TS pool occupancy regulation.

Strengths:

This is a very thorough study, addressing the research question from many different angles and the experimental execution is superb. The impact of the work is high, as it applies recent models of short term plasticity behavior to in vivo circuits further providing insights how synapses provide dynamic control to enable working memory related behavior through non-permanent changes in synaptic output.

Weaknesses:

While this work is carefully examined and the results are presented and discussed in a detailed manner, the reviewer is still not fully convinced that regulation of release probability is not a putative contributor to the observed behavior. No additional work is needed, but in the moment, I am not convinced that changes in release probability are not in play. One solution may be to extend the discussion of changes in rules probability as an alternative.

Fig 3. I am confused about the interpretation of the Mean Variance analysis outcome. Since the data points follow the curve during induction of short term plasticity, doesn't these suggests that release probability and not the pool size increases? Related, to measure the absolute release probability and failure rate using the optogenetic stimulation technique is not trivial as the experimental paradigm bias the experiment to a given output strength, and therefore a change in release probability cannot be excluded.

Fig. 4B interprets the phorbol ester stimulation to be the result of pool overfilling, however, phorbol ester stimulation has also been shown to increase release probability without changing the size of the readily releasable pool. The high frequency of stimulation may occlude a increased paired pulse depression in presence of OAG, that others have interpreted in mammalian synapses as an increase in release probability.

The literature on Syt7 function is still quite controversial. An observation in the literature that loss of Syt7 function in the fly synapse leads to an increase of release probability. Thus the observed changes in short term plasticity characteristics in the Syt7 KD experiments may contain a release probability component. Can the authors really exclude this possibility? Figure 5 shows for the Syt7 KD group a very prominent depression of the EPSC/IPSC with the second stimulus, particularly for the short interpulse intervals, usually a strong sign of increased release probability, as lack of pool refilling can unlikely explain the strong drop in synaptic output.

Comments on revisions:

I am satisfied with the reply of the authors and I do not have any further points of concern.

Reviewer #2 (Public review):

Summary:

The authors developed a computational pipeline named CHROMAS to track and analyze chromatophore dynamics, which provides a wide range of biological analysis tools without requiring the user to write code.

Strengths:

(1) CHROMAS is an integrated toolbox that provides tools for different biological tasks such as: segment, classify, track and measure individual chromatophores, cluster small groups of chromatophores, analyze full-body patterns, etc.

(2) It could be used to investigate different species. The authors have already applied it to analyze the skin of the bobtail squid Euprymna berryi and the European cuttlefish Sepia officinalis.

(3) The tool is open-source and easy to install. The paper describes in detail the command format to complete each task and provides relevant sample figures.

Weaknesses:

(1) The generality and robustness of the proposed pipeline need to be verified through more experimental evaluations. For example, the implementation algorithm depends on relatively specific or obvious image features, clean backgrounds, and objects that do not move too fast.

(2) The pipeline lacks some kind of self-correction mechanism. If at one moment there is a conflicting match with the previous frames, how does the system automatically handle it to ensure that the tracking results are accurate over a long period of time?

Reviewer #2 (Public review):

Summary:

In this study, the researchers generated an impressive collection of sparse split GAL4 driver lines that target wing-relevant cell types. They then characterized the cell types according to function, development, and morphology. This resource is a necessary companion to the fly ventral nerve cord connectomes. The fly connectomes enable biologically-constrained hypothesis generation, but we need genetic reagents like the ones generated here in order to test those hypotheses and understand the biological limits of what we can learn from connectomes. This project identifies wing-relevant cell types and generates a library of driver lines to provide genetic access to small populations of these cell types. The study also characterizes these cell types according to developmental lineage and morphology, and performs functional analyses on some of the cell types, including single pairs of motor neurons.

Strengths:

The genetic toolkit that the authors produce is rigorous and well-documented, and will be broadly useful. Further, they bolster the utility of the resource by characterizing cell types according to developmental lineage, morphology, and connectome nomenclature. The authors successfully produce a foundation for future studies of the functional organization of neural circuits. In particular, the driver lines created in this study match the specificity of the connectome, providing a necessary resource to functionally test predictions from the connectomes.

Weaknesses:

The manuscript includes several broad statements about certain questions being "unexplored" (e.g., lines 71, 129). However, the authors cite papers (e.g., Harris 2015 and Lillvis 2024) that directly address these topics. To better support the narrative, it would be helpful to more accurately summarize the key findings from these prior studies. For example, the Harris paper found behavioral correlates of hemilineage activation. By using the sparse toolkit you have created, it may be possible to dissect behavior into finer-grained modules or specific movements, providing deeper insight into how complex behaviors are produced by the nervous system.

There are a few places where the current manuscript does not acknowledge the post-connectome universe it now exists in. For example, line 600: the morphology of DVMns in Drosophila had never been described, and line 762: revealed diversity within hemilineages which had not previously been reported. Although this manuscript was in progress before the VNC connectomes were released, they are now published, and the current manuscript should reflect this development.

The authors focus on some well-characterized "Named Neurons" e.g., ChINs and the PSI. This focused approach makes sense, but the authors miss the opportunity to point out a major strength of the toolkit they have produced: we are now less constrained by studying only these Named Neurons. With this new resource, we have genetic access to sparse sets of neurons that are likely just as important but were previously inaccessible.

Reviewer #2 (Public review):

This study investigates the role of RAP2A in regulating asymmetric cell division (ACD) in glioblastoma stem cells (GSCs), bridging insights from Drosophila ACD mechanisms to human tumor biology. They focus on RAP2A, a human homolog of Drosophila Rap2l, as a novel ACD regulator in GBM is innovative, given its underexplored role in cancer stem cells (CSCs). The hypothesis that ACD imbalance (favoring symmetric divisions) drives GSC expansion and tumor progression introduces a fresh perspective on differentiation therapy. However, the dual role of ACD in tumor heterogeneity (potentially aiding therapy resistance) requires deeper discussion to clarify the study's unique contributions against existing controversies. Some limitations and questions need to be addressed.

(1) Validation of RAP2A's prognostic relevance using TCGA and Gravendeel cohorts strengthens clinical relevance. However, differential expression analysis across GBM subtypes (e.g., MES, DNA-methylation subtypes ) should be included to confirm specificity.

(2) Rap2l knockdown-induced ACD defects (e.g., mislocalization of Cno/Numb) are well-designed. However, phenotypic penetrance and survival rates of Rap2l mutants should be quantified to confirm consistency.

(3) While GB5 cells were effectively used, justification for selecting this line (e.g., representativeness of GBM heterogeneity) is needed. Experiments in additional GBM lines (especially the addition of 3D primary patient-derived cell lines with known stem cell phenotype) would enhance generalizability.

(4) Indirect metrics (odd/even cell clusters, NUMB asymmetry) are suggestive but insufficient. Live imaging or lineage tracing would directly validate ACD frequency.

(5) The initial microarray (n=7 GBM patients) is underpowered. While TCGA data mitigate this, the limitations of small cohorts should be explicitly addressed and need to be discussed.

(6) Conclusions rely heavily on neurosphere models. Xenograft experiments or patient-derived orthotopic models are critical to support translational relevance, and such basic research work needs to be included in journals.

(7) How does RAP2A regulate NUMB asymmetry? Is the Drosophila Rap2l-Cno/aPKC pathway conserved? Rescue experiments (e.g., Cno/aPKC knockdown with RAP2A overexpression) or interaction assays (e.g., Co-IP) are needed to establish molecular mechanisms.

(8) Reduced stemness markers (CD133/SOX2/NESTIN) and proliferation (Ki-67) align with increased ACD. However, alternative explanations (e.g., differentiation or apoptosis) must be ruled out via GFAP/Tuj1 staining or Annexin V assays.

(9) The link between low RAP2A and poor prognosis should be validated in multivariate analyses to exclude confounding factors (e.g., age, treatment history).

(10) The broader ACD regulatory network in GBM (e.g., roles of other homologs like NUMB) and potential synergies/independence from known suppressors (e.g., TRIM3) warrant exploration.

(11) The figures should be improved. Statistical significance markers (e.g., p-values) should be added to Figure 1A; timepoints/culture conditions should be clarified for Figure 6A.

(12) Redundant Drosophila background in the Discussion should be condensed; terminology should be unified (e.g., "neurosphere" vs. "cell cluster").

Reviewer #2 (Public review):

Summary:

This is an important study characterizing striatal dysfunction and behavioral deficits in Cntnap2-/- mice. There is growing evidence suggesting that striatal dysfunction underlies core symptoms of ASD but the specific cellular and circuit level abnormalities disrupted by different risk genes remain unclear. This study addresses how deletion of Cntnap2 affects the intrinsic properties and synaptic connectivity of striatal spiny projection neurons (SPN) of the direct (dSPN) and indirect (iSPN) pathways. Using Thy1-ChR2 mice and optogenetics the authors found increased firing of both types of SPNs in response to cortical afferent stimulation. However, there was no significant difference in the amplitude of optically-evoked excitatory postsynaptic currents (EPSCs) or spine density between Cntnap2-/- and WT SPNs, suggesting that the increased corticostriatal coupling might be due to changes in intrinsic excitability. Indeed, the authors found Cntnap2-/- SPNs, particularly dSPNs, exhibited higher intrinsic excitability, reduced rheobase current and increased membrane resistance compared to WT SPNs. The enhanced spiking probability in Cntnap2-/- SPNs is not due to reduced inhibition. Despite previous reports of decreased parvalbumin-expressing (PV) interneurons in various brain regions of Cntnap2-/- mice, the number and function (IPSC amplitude and intrinsic excitability) of these interneurons in the striatum were comparable to WT controls.

This study also includes a comprehensive behavioral analysis of striatal related behaviors. Cntnap2-/- mice demonstrated increased repetitive behaviors (RRBs), including more grooming bouts, increased marble burying, and increased nose poking in the holeboard assay. MoSeq analysis of behavior further showed signs of altered grooming behaviors and sequencing of behavioral syllables. Cntnap2-/- mice also displayed cognitive inflexibility in a four-choice odor-based reversal learning assay. While they performed similarly to WT controls during acquisition and recall phases, they required significantly more trials to learn a new odor-reward association during reversal, consistent with potential deficits in corticostriatal function.

Strengths:

This study provides significant contributions to the field. The finding of altered SPN excitability, the detailed characterization of striatal inhibition, and the comprehensive behavioral analysis are novel and valuable to understand the pathophysiology of Cntnap2-/- mice.

Weaknesses:

All my concerns were addressed in the revised version of the manuscript

Reviewer #2 (Public review):

General comment:

This is a very valuable and unique comparative study. An excellent combination of scanning and histological data from three different species is presented. Obtaining the material for such a comparative study is never trivial. The study presents new data and thus provides the basis for an in-depth discussion about chondrichthyan mineralised skeletal tissues.

Comments on revised version:

The manuscript has been revised and improved and can be published. A very nice manuscript, indeed. My only recommendation (point of discussion, not a requirement) would still be to think about the claim of paedomorphosis in a holocephalan.

Within the chondrichthyes, how distant holocephali are in relation to elasmobranchii remains uncertain, holocephali are quite a specialised group. Holocephali are also older than Batoidea and Selachii. As paedomorphosis is a derived character, I imagine it is difficult to establish that development in an extant holocephalan is derived compared to development in elasmobranchii. If this type of development would have been typical for the "older" holocephali it would not be paedomorphic. Also, the uncertainty how distant holocephali are from elasmobranchii makes it difficult to identify paedomorphosis with reference to chondrichthyes.

Reviewer #2 (Public review):

Summary:

The study links Alzheimer's disease (AD) with metabolic disorders through elevated Kallistatin levels in AD patients. Kallistatin-overexpressing mice show cognitive decline, increased Aβ and tau pathology, and impaired hippocampal function. Mechanistically, Kallistatin enhances Aβ production via Notch1 and promotes tau phosphorylation through GSK-3β activation. Fenofibrate improves cognitive deficits by reducing Aβ and tau phosphorylation in these mice, suggesting therapeutic potential in AD linked to metabolic syndromes.

Strengths:

This study presents a novel insights into Alzheimer's disease (AD) pathogenesis and provides strong evidences about the mechanistic roles of Kallistatin and the therapeutic potential of fenofibrate in AD.

It was suggested that Kallistatin is primarily produced by the liver. The study demonstrates increased Kallistatin levels in the hippocampus tissue of AD mice. They also found that Kallistatin is also increased in the liver of AD mice.

They also showed that Kallistatin directly binds to Notch1 and contributes to the activation of the Noch1-HES1 signaling pathway

Reviewer #2 (Public review):

Summary:

The Flower protein is expressed in various cell types, including neurons. Previous studies in flies have proposed that Flower plays a role in neuronal endocytosis by functioning as a Ca2+ channel. However, its precise physiological roles and molecular mechanisms in neurons remain largely unclear. This study employs C. elegans as a model to explore the function and mechanism of FLWR-1, the C. elegans homolog of Flower. This study offers intriguing observations that could potentially challenge or expand our current understanding of the Flower protein. Nevertheless, further clarification or additional experiments are required to substantiate the study's conclusions.

Strengths:

A range of approaches was employed, including the use of a flwr-1 knockout strain, assessment of cholinergic synaptic activity via analyzing aldicarb (a cholinesterase inhibitor) sensitivity, imaging Ca2+ dynamics with GCaMP3, analyzing pHluorin fluorescence, examination of presynaptic ultrastructure by EM, and recording postsynaptic currents at the neuromuscular junction. The findings include notable observations on the effects of flwr-1 knockout, such as increased Ca2+ levels in motor neurons, changes in endosome numbers in motor neurons, altered aldicarb sensitivity, and potential involvement of a Ca2+-ATPase and PIP2 binding in FLWR-1's function.

The authors have adequately addressed most of my previous concerns, however, I recommend minor revisions to further strengthen the study's rigor and interpretation:

Major suggestions

(1) This study relies heavily on aldicarb assays to support its conclusions. While these assays are valuable, their results may not fully align with direct assessment of neurotransmitter release from motor neurons. For instance, prior work has shown that two presynaptic modulators identified through aldicarb sensitivity assays exhibited no corresponding electrophysiological defects at the neuromuscular junction (Liu et al., J Neurosci 27: 10404-10413, 2007). Similarly, at least one study from the Kaplan lab has noted discrepancies between aldicarb assays and electrophysiological analyses. The authors should consider adding a few sentences in the Discussion to acknowledge this limitation and the potential caveats of using aldicarb assays, especially since some of the aldicarb assay results in this study are not easily interpretable.

[Editor's note: The authors added a sentence in the first paragraph of the Discussion to acknowledge these complexities.]

(2) The manuscript states, "Elevated Ca2+ levels were not further enhanced in a flwr-1;mca-3 double mutant." (lines 549-550). However, Figure 7C does not include statistical comparisons between the single and double mutants of flwr-1 and mca-3. Please add the necessary statistical analysis to support this statement.

[Editor's note: In response, the authors noted that these comparisons were indeed carried out. As mentioned in the figure legend, the graph shows only those comparisons that indicated statistical significance.]

(3) The term "Ca2+ influx" should be avoided, as this study does not provide direct evidence (e.g. voltage-clamp recordings of Ca2+ inward currents in motor neurons) for an effect of the flwr-1 mutation of Ca2+ influx. The observed increase in neuronal GCaMP signals in response to optogenetic activation of ChR2 may result from, or be influenced by, Ca2+ mobilization from of intracellular stores. For example, optogenetic stimulation could trigger ryanodine receptor-mediated Ca2+ release from the ER via calcium-induced calcium release (CICR) or depolarization-induced calcium release (DICR). It would be more appropriate to describe the observed increase in Ca2+ signal as "Ca2+ elevation" rather than increased "Ca2+ influx".

[Editor's note: The authors revised their terminology to avoid ambiguities associated with the word "influx".]

Reviewer #2 (Public review):

Summary:

This manuscript reported that the pioneer factors ASCL1 and NeuroD1 in neuroendocrine transdifferentiation of Neuroendocrine prostate cancer (NEPC) and uncovered their abilities to silence AR expression by remodeling chromatin at the somatically acquired AR enhancer and global AR binding sites with enhancer activity. It also elucidated the dynamic temporal changes in the transcriptomic and epigenomic landscapes of cells undergoing acute lineage conversion from AR-active prostate cancer to NEPC which should inform future therapeutic development.

Strengths:

Data from cell lines is great and solid.

Weaknesses:

The paper would be better if some clinical data could be added.

Reviewer #2 (Public review):

Summary:

Kirk et al. use RNA-Seq and CRISPRi to provide evidence that KLF family transcription factors regulate postnatal neuronal maturation of pyramidal neurons. The genetic programs regulating postnatal neuronal maturation are not well understood. The authors first analyzed chromatin accessibility and gene expression data from layer 4 and 6 pyramidal neurons and found that KLF TFs are predicted regulators of postnatal neuronal maturation. They then use CRISPRi knockdown and find that KLF activators first activate genes and then this is followed by KLF repressors repressing genes. Interestingly, some genes, such as those with cytoskeletal functions, are shared targets of KLF activators and repressors.

Strengths:

The study is well-executed and the paper is well-written. A major strength of this study is the application of state-of-the-art transgenic approaches. The CRISPRi approach used to knock down multiple KLFs is compelling. The genomic data generated appears to be high quality and is carefully analyzed. The presented findings provide important insights into the genetic programs that regulate postnatal maturation in cortical pyramidal neurons. The discovery that KLF family activators/repressors regulate gene expression changes during this critical step of neuronal development fills an important gap in the field.

Weaknesses:

A limitation of the current study is that the functional importance of KLF for postnatal neuronal maturation is unclear. Although the authors find that KLFs regulate some of the gene expression changes during postnatal neuronal maturation, it is still unclear whether such gene expression changes mediate the postnatal changes in morphology and physiology. While beyond the scope of the current study, future studies should investigate the contributions of KLFs on postnatal morphological and physiological changes.

Reviewer #2 (Public review):

Summary:

The authors generated single and double knockout mutants for the eIF4E family members eIF4E, iso4E1, iso4E2, nCBP1, and nCBP2 in cassava. While a single knockout of these eIF4E genes did not abolish viral infection, the nCBP1/nCBP2 double knockout mutant displayed the weakest symptoms and viral infection. Through yeast two-hybrid screening, the nCBP-2 L51F mutant was identified, and the mutant was unable to interact with VPg, yet the nCBP-2 L51F mutant could complement the eIF4E yeast mutant. This L51F is a potentially important editing site for eIF4E.

Strengths:

This study systematically generated single and double knockout mutants for the eIF4E family members and investigated their antiviral activity. It also identified a L51F site as a potentially important antiviral editing site in eIF4E, however, its antiviral genetic evidence remains to be validated.

Weaknesses:

(1) The symptoms of the iso4E1 & iso4E2 double-knockout mutant are slightly alleviated, and those of the nCBP1 & nCBP2 double-knockout mutant are alleviated the most. If the iso4E1 & iso4E2 and nCBP1 & nCBP2 mutants are crossed to obtain quadruple-knockout mutant plants, whether the resistance of the quadruple mutant will be more excellent should be further investigated.

(2) Although the yeast two-hybrid identified the nCBP-2 L51F mutant, there is no direct biological evidence demonstrating its antiviral function. While the 6-amino acid deletion mutant (including L51F) showed attenuated symptoms, this deletion might be sufficient to cause loss-of-function of nCBP-2. These indirect observations cannot definitively establish that the L51F mutation specifically confers antiviral activity.

(3) Given that nCBP-2 can rescue yeast eIF4E mutants, introducing wild type and L51F nCBP2 into the Arabidopsis iso4e mutant viral infectious clones into yeast systems could clarify whether the L51F mutation (and the same mutations in eIF4E, iso4E1, iso4E2) abrogates their roles as viral susceptibility factors - critical genetic evidence currently missing.

Reviewer #2 (Public review):

Summary:

An abundant literature documents molecular changes in the rodent hypothalamus that occur during the transition from prepubertal to mature reproductive physiology. Equally well documented is the role of sex steroids and their receptors during this important period of reproductive development, as well as the importance of GABAergic and glutamatergic neurons. The medial preoptic area (MPOA) is known to play a central role in expression of sexually dimorphic reproductive function and previously reported sexually dimorphic patterns of gene expression are consistent with this role. The present manuscript extends this knowledge base and reports the results of a detailed evaluation of transcriptional dynamics in the MPOA during the adolescent transition to maturity with a particular focus on the role of the estrogen receptor gene (Esr1). Both single cell RNA sequencing (scRNseq) and multiplex in situ hybridization methods were employed and the results subjected to detailed computational analyses to demonstrate that the transcriptomic structure of MPOA neurons displays both sex and cell type specific expression profiles. In addition, both hormonal and genetic manipulations of Esr1 signaling during puberty altered the transcriptional profiles of MPOA neurons, and these changes aligned with maturation of hormone-dependent reproductive function. The authors provide this evidence to illustrate Esr1 dependent control of gene regulatory networks required for normal expression of reproductive behaviors expressed during the transition from adolescence to adulthood. The results presented in this manuscript are extensive and represent the most comprehensive evaluation of transcriptomic changes during reproductive maturation to date. The methods appear strong and the results provide a rich data set that will support a good deal of future analysis. Despite these strengths, the authors are encouraged to revise their manuscript to address significant gaps in their presentation, as well as clarify or improve their conclusions.

Strengths:

(1) The major strength of this manuscript is the extensive set of images and graphs that illustrate molecular changes that occur in MPOA neurons during adolescence, although additional spatial detail as to locations of the source neurons would be welcome in order to place the changes in the proper circuitry context.

(2) Targeting Esr1 deletion to MPOA GABA neurons is a good choice, given how these cells have been implicated in sexual differentiation of reproductive behavior previously, and the lack of comparable responses in glutamatergic neurons is convincing. The AAV-frtFlex-Cre virus created by the investigators is a most useful tool for such studies. Profiling distinct transcriptomic trajectories in GABA and glutamatergic neurons during reproductive maturation is impressive and leads to some of the best supported conclusions in this paper.

(3) Cellular and molecular resolution of the transcriptomics data appears excellent, however, because the source tissue for the scRNAseq analysis was obtained by bulk dissection of the MPOA anatomical resolution is limited. This problem is addressed to some extent by careful comparison of scRNAseq results with previously published spatial transcriptomics data. The HM-HCR-FISH analysis clearly documents spatially restricted changes in gene expression, but it is hard to discern where these changes occur based on the images presented or the descriptions included in the Results. The anatomical schematic included in Figure 4 suggests that investigators are not familiar with components of the MPOA (see Allen Mouse Brain Atlas).

Weaknesses:

(1) A major conceptual flaw is that the authors do not distinguish between genetically determined sex differences in patterns of gene expression and differences caused by the fact that MPOA neurons are exposed to different endocrine environments in adolescent males and females, which can cause different transcriptional trajectories independent of genetic sex. This issue does not render their results invalid, but their terminology should address the issue in the discussion and "limitations" section. At the very least the endocrine status of "intact females" should be included.

(2) A major technical flaw is that the MPOA is treated as a functionally distinct brain region (block dissections) with uniform distribution of cell types (FISH data are not illustrated or reported with sufficient spatial detail). Thus, an enormous amount of molecular data is provided that cannot be mapped to distinct neural circuits, thereby limiting the neurobiological impact. This is also a weakness of the FISH data, which is presented with only small regions illustrated without anatomical detail. In fact, some images are compared that appear to illustrate different MPOA structures, although it is impossible to be certain of this due to the lack of morphological landmarks. The analysis of how Esr1 orchestrates regulatory gene networks is impressive and interesting, but the fact that many of the observed transcriptional events occur in neural circuits that do not overlap confounds interpretation.

(3) The locations of the AAV injections should be characterized because deleting Esr1 in multiple distinct parts of the MPOA will likely confound interpretation. This is especially problematic given the limited number of mice used for parts of the RNAscope analysis.

(4) Although the focus of these experiments on adolescence is welcome, neither the Introduction nor the Discussion do a good job of placing these studies in the context of what is already known about brain maturation during puberty. It is true that this is very much a results-focused manuscript, but the scholarship can be improved. Simply stating that your results are consistent with previous reports places an undue burden on the reader to go figure out what is new.

(5) Throughout the manuscript the authors utilize obscure abbreviations, which often makes reading their text overly cumbersome. This is certainly justified in certain instances where complex names of analytical methods are used repeatedly, but the authors are encouraged to try and simplify their use of non-standard abbreviations.

Reviewer #2 (Public review):

Summary:

In this manuscript, Ye et al. examine the sequence of events that occur in the damaged zebrafish Muller glia (MG) in states between quiescence and the onset of proliferation. Using an inducible metronidazole (MTZ) and nitroreductase system to ablate red/green cones in larval zebrafish, they identify a novel transitional MG state that is characterized by the expression of cxcl18b. Using trajectory analysis from single-cell RNA-seq datasets, they find that cxcl18b is expressed before MG expression PCNA and becomes proliferative. They find that cxcl18b expression peaks in MG at approximately 24 hours post injury (hpi) and rapidly declines as MG proliferate following injury. In a most interesting finding, the authors find a link between nos2b-dependent nitric oxide signaling and cxcl18b-mediated proliferation. Mutagenesis of nos2b decreases MG proliferation. The mechanism linking NO signaling to proliferation was suggested to function via notch signaling as pharmacological inhibition of nitric oxidate signaling resulted in elevated Notch activity, thus preventing MG proliferation. The authors suggest a model whereby cxcl18b induces autocrine NO signaling in MG to reduce the activity of Notch3, thereby promoting MG proliferation. While this model is appealing, there are several limitations and inconsistencies within the data that raise concerns. Several conclusions regarding the role of nos2b rely on low-quality in situ hybridization data and RT-PCR results that are inconsistent with some single-cell RNA-seq data also provided. The temporal sequence of events lacks adequate rigor, as many conclusions are based on transgene expression in the Tg(cxcl18b:GFP) lines, where persistence of the GFP fluorescence may not reflect endogenous cxcl18b. Are cognate cxcl18b receptors found on MG to support an autocrine signaling pathway?

Strengths:

The authors utilize a number of sophisticated transgenic approaches and generate novel lines that will have value to the field. The identification of a novel cxcl18b transition state is exciting, and the putative link between NO signaling and Notch activity would provide new insight into the drivers of Muller glia proliferation.

Weaknesses:

While this model is appealing, there are several limitations and inconsistencies within the data that raise concerns. Several conclusions regarding the role of nos2b rely on low-quality in situ hybridization data and RT-PCR results that are inconsistent with some single-cell RNA-seq data also provided. The temporal sequence of events lacks adequate rigor, as many conclusions are based on transgene expression in the Tg(cxcl18b:GFP) lines, where persistence of the GFP fluorescence may not reflect endogenous cxcl18b. Are cognate cxcl18b receptors found on MG to support an autocrine signaling pathway? The images are generally well organized, although a number of typographical errors exist, and some sentences and phrases appear confusing. Additional proof-reading is strongly recommended.

Reviewer #2 (Public review):

Summary:

In this manuscript, Arnould et. al. develop an unbiased, affinity-guided reagent to label P2X7 receptor and use super-resolution imaging to monitor P2X7 redistribution in response to inflammatory signaling.

Strengths:

I think the X7-uP probe that they developed is very useful for visualizing localization of P2X7 receptor. They convincingly show that under inflammatory conditions, there is a reorganization of P2X7 localization into receptor clusters. Moreover, I think they have shown a very clever way to specifically label any receptor of interest. This has broad appeal

Weaknesses:

Overall, the manuscript is novel and interesting. However, I do have some suggestions for improvement.

(1) While the authors state that chemical modification of AZ10606120 to produce the X7-UP reagent has "minimal impact" on the inhibition of P2X7, we can see from Figure 2A and 2B that it does not antagonize P2X7 as effectively as the original antagonist. For the sake of completeness and quantitation, I think it would be great if the authors could determine the IC50 for X7-uP and compare it to the IC50 of AZ10606120.

(2) Do the authors know whether modification of the lysines with biotin affects the receptor's affinity for ATP (or ability to be activated by ATP)? What about P2X7 that has been modified with biotin and then labeled with Alexa 647? For the sake of completeness and quantitation, I think it would be great if the authors could determine the EC50 of biotinylated P2X7 for ATP as well as biotinylated and then Alexa 647 labeled P2X7 for ATP and compare these values to the affinity of unmodified WT P2X7 for ATP.

(3) It is a little misleading to color the fluorescence signal from mScarlet green (for example, in Figure 3 and Figure 4). The fluorescence is not at the same wavelength as GFP. In fact, the wavelength (570 nm - 610 nm) for emission is closer to orange/red than to green. I think this color should be changed to differentiate the signal of mScarlet from the GFP signal used for each of the other P2X receptor subtypes.

(4) It is my understanding that P2X6 does not form homotrimers. Thus, I was a little surprised to see that the density and distribution of P2X6-GFP in Figure 3 looks very similar to the density and distribution of the other P2X subtypes. Do the authors have an explanation for this? Are they looking at P2X6 protomers inserted into the plasma membrane? Does the cell line have endogenous P2X receptor subtypes? Is Figure 3 showing heterotrimers with P2X6 receptor? A little explanation might be helpful.

(5) It is easy to overlook the fact that the antagonist leaves the binding pocket once the biotin has been attached to the lysines. It might be helpful if the authors made this a little more apparent in Figure 1 or in the text describing the NASA chemistry reaction.

Reviewer #2 (Public review):

Summary:

The Flower protein is expressed in various cell types, including neurons. Previous studies in flies have proposed that Flower plays a role in neuronal endocytosis by functioning as a Ca2+ channel. However, its precise physiological roles and molecular mechanisms in neurons remain largely unclear. This study employs C. elegans as a model to explore the function and mechanism of FLWR-1, the C. elegans homolog of Flower. This study offers intriguing observations that could potentially challenge or expand our current understanding of the Flower protein. Nevertheless, further clarification or additional experiments are required to substantiate the study's conclusions.

Strengths:

A range of approaches was employed, including the use of a flwr-1 knockout strain, assessment of cholinergic synaptic activity via analyzing aldicarb (a cholinesterase inhibitor) sensitivity, imaging Ca2+ dynamics with GCaMP3, analyzing pHluorin fluorescence, examination of presynaptic ultrastructure by EM, and recording postsynaptic currents at the neuromuscular junction. The findings include notable observations on the effects of flwr-1 knockout, such as increased Ca2+ levels in motor neurons, changes in endosome numbers in motor neurons, altered aldicarb sensitivity, and potential involvement of a Ca2+-ATPase and PIP2 binding in FLWR-1's function.

The authors have adequately addressed most of my previous concerns, however, I recommend minor revisions to further strengthen the study's rigor and interpretation:

Major suggestions

(1) This study relies heavily on aldicarb assays to support its conclusions. While these assays are valuable, their results may not fully align with direct assessment of neurotransmitter release from motor neurons. For instance, prior work has shown that two presynaptic modulators identified through aldicarb sensitivity assays exhibited no corresponding electrophysiological defects at the neuromuscular junction (Liu et al., J Neurosci 27: 10404-10413, 2007). Similarly, at least one study from the Kaplan lab has noted discrepancies between aldicarb assays and electrophysiological analyses. The authors should consider adding a few sentences in the Discussion to acknowledge this limitation and the potential caveats of using aldicarb assays, especially since some of the aldicarb assay results in this study are not easily interpretable.

(2) The manuscript states, "Elevated Ca2+ levels were not further enhanced in a flwr-1;mca-3 double mutant." (lines 549-550). However, Figure 7C does not include statistical comparisons between the single and double mutants of flwr-1 and mca-3. Please add the necessary statistical analysis to support this statement.

(3) The term "Ca2+ influx" should be avoided, as this study does not provide direct evidence (e.g. voltage-clamp recordings of Ca2+ inward currents in motor neurons) for an effect of the flwr-1 mutation of Ca2+ influx. The observed increase in neuronal GCaMP signals in response to optogenetic activation of ChR2 may result from, or be influenced by, Ca2+ mobilization from of intracellular stores. For example, optogenetic stimulation could trigger ryanodine receptor-mediated Ca2+ release from the ER via calcium-induced calcium release (CICR) or depolarization-induced calcium release (DICR). It would be more appropriate to describe the observed increase in Ca2+ signal as "Ca2+ elevation" rather than increased "Ca2+ influx".

Reviewer #2 (Public review):

The manuscript from Belato et al., used advanced NMR approaches and a mutagenesis campaign probe the conformational dynamics of the recognition lobe (Rec) of the CRISPR Cas9 enzyme from G. stearothermophilus (GeoCas9). Using truncated and full-length constructs they assess the impacts of two different point mutations have on the redistribution and timescale of these motions and assess gRNA recognition and specificity. Single point mutations in the Rec domain in a Cas9 from a related species had profound impacts on- and off-target DNA editing, therefore the authors reasoned analogous mutations in GeoCas9 would have similar effects. However, despite a redistribution of local motions and changes in global stability, their chosen mutations had little impact on DNA editing in the context of the full-length enzyme.

In their revised manuscript, the authors were highly responsive to the reviewer's comments incorporating new experimental results including molecular dynamics simulations and RNA binding data using full-length GeoCas9, as well as reframing their discussion and conclusions in consideration of the new data. They were receptive to suggestions for clarification in both the text and methods section. With these changes, the manuscript has been significantly improved.

Their studies highlight the species-specific complexity of interdomain communication and allosteric mechanisms used by these multi-domain endonucleases. The noted strengths of the article remain, and despite the negative results, their approach will garner interest from investigators interested in understanding how the activity and specificity of these enzymes can be engineered to tune activity and limit off-target cleavage by these enzymes. Generally, the manuscript highlights the challenges of studying the effect of allosteric networks on protein function, particularly in multidomain proteins, and thus will be of broad interest to the community.

Reviewer #2 (Public review):

Patel et al perform the analysis of neurons in a somatosensory network involved in responses to noxious cold in Drosophila larva. Using a combination of behavioral experiments, Calcium imaging, optogenetics and synaptic connectivity analysis in the Drosophila larval they assess the function of circuit elements in the somatosensory network downstream of multimodal somatosensory neurons involved in innocuous and noxious stimuli sensing and probe their function in noxious cold processing, Consistent with their previous findings they find the multidendritic class III neurons , to be the key cold sensing neurons that are both required and sufficient for the CT behaviors response (shown to evoked by noxious cold). They further investigate the downstream neurons identified based on literature and connectivity from EM at different stages of sensory processing characterize the different phenotypes upon activating/silencing those neurons and monitor their responses to noxious cold. The work reveals diverse phenotypes for the different neurons studied and provides the groundwork for understanding how information is processed in the nervous system from sensory input to motor output and how information from different modalities is processed by neuronal networks. However, at times the writing could be clearer and some results interpretations more rigorous

Reviewer #2 (Public review):

The manuscript by Nakagawa R, et al describes a mechanism of how NSCLC cells become resistant to EGFR and KRAS G12C inhibition. Here, the authors focus on the initial cellular changes that occur to confer resistance and identify YAP activation as a non-genetic mechanism of acute resistance.

The authors performed an initial xenograft study to identify YAP nuclear localization as a potential mechanism of resistance to EGFRi. The increase in the stromal component of the tumors upon Afatinib treatment leads the authors to explore the response to these inhibitors in both 2D and 3D culture. The authors extend their findings to both KRAS G12C and BRAF inhibitors, suggesting that the mechanism of resistance may be shared along this pathway.

The paper would benefit from additional cell lines to determine the generalizability of the findings they presented. While the change in the localization of YAP upon Afatinib treatment was identified in a xenograft model, the authors do not return to animal models to test their potential mechanism, and the effects of the hyperactivated S127A YAP protein on Afatinib sensitivity in culture are modest. Also, combination studies of YAP inhibitors and EGFR/RAS/RAF inhibitors would have strengthened the studies.

Reviewer #2 (Public review):

Summary:

The authors harness single cell RNAseq data from zebrafish and mice to identify Oct4 as a candidate driver of neurogenesis. They then use adeno-associated virus vectors to show that while Oct4 overexpression alone converts rare adult Müller glia (MG) to bipolar cells, it synergizes with Notch pathway inhibition to cause this neurogenesis (achieved by Cre-mediated knockout of Rbpj floxed allele). Importantly, they genetically lineage-mark adult MG using a GLAST-CreER transgene and a Sun-GFP reporter, so that any non-MG cells that convert can be identified unambiguously. This is crucial because several high-profile papers made erroneous claims using short promoters in the viral delivery vector itself to mark MG, but those promoters are leaky and mark other non-MG cell types, making it impossible to definitively state whether manipulations studied were actually causing neurogenesis, or were merely the result of expression in pre-existing neurons. Once the authors establish Oct4 + RbpjKO synergy they use snRNAseq/ATACseq to identify known and novel transcription factors that could play a role in driving neurogenesis.

Strengths:

The system to mark MG is stringent, so the authors are studying transdifferentiation, not artifactual effects due to leaky viral promoters. The synergy between Oct4 and Notch pathway blockade is notable. The single cell results add the potential involvement of new players such as Rfx4 in adult-MG-neurogenesis.

Weaknesses:

The revised version is clear and there are no major weaknesses.

Overall, the authors achieved what they set out to do, and have made new insights into how neurogenesis can be stimulated in MG. Ultimately, a major long-term goal in the field is to replace lost photoreceptors as this is most relevant to many human visual disorders, and while this paper (like all others before it) does not generate rods or cones, it opens new strategies to coax MG to form a related neuronal cell type. Their approach underscores the benefits of using a gold standard approach for lineage tracing.

Reviewer #2 (Public review):

Summary:

The study investigates the brain's functional connectivity (FC) dynamics across different timescales using simultaneous recordings of intracranial EEG/source-localized EEG and fMRI. The primary research goal was to determine which of three convergence/divergence scenarios is the most likely to occur.

The results indicate that despite similar FC patterns found in different data modalities, the timepoints were not aligned, indicating spatial convergence but temporal divergence.

The researchers also found that FC patterns in different frequencies do not overlap significantly, emphasizing the multi-frequency nature of brain connectivity. Such asynchronous activity across frequency bands supports the idea of multiple connectivity states that operate independently and are organized into a multiplex system.

Strengths:

The data supporting the authors' claims are convincing and come from simultaneous recordings of fMRI and iEEG/EEG, which has been recently developed and adapted.

The analysis methods are solid and involved a novel approach to analyzing the co-occurrence of FC patterns across modalities (cross-modal recurrence plot, CRP) and robust statistics, including replication of the main results using multiple operationalizations of the functional connectome (e.g., amplitude, orthogonalized, and phase-based coupling).

In addition, the authors provided a detailed interpretation of the results, placing them in the context of recent advances and understanding of the relationships between functional connectivity and cognitive states.

The authors also did a control analysis and verified the effect of temporal window size or different functional connecvitity operationalizations. I also applaud their effort to make the analysis code open-sourced.

Comments on revisions:

The authors addressed all my concerns in the previous round of review.

Reviewer #2 (Public review):

Summary:

In this manuscript the authors have explored the beneficial effect of autophagy upregulation in the context of HD pathology in a disease stage-specific manner. The authors have observed functional autophagy lysosomal pathway (ALP) and its machineries at the early stage in HD mouse model, whereas impairment of ALP has been documented at the later stages of the disease progression. Eventually, the authors have taken advantage of operational ALP pathway at the early stage of HD pathology, in order to upregulate ALP and autophagy flux by inhibiting mTORC1 in vivo, which ultimately reverted back multiple ALP-related abnormalities and phenotypes. Therefore, this manuscript is a promising effort to shed light on the therapeutic interventions with which HD pathology can be treated at the patient level in future.

Strengths:

The study has shown alteration of ALP in HD mouse model in a very detailed manner. Such stage dependent in vivo study will be informative and has not been done before. Also, this research provides possible therapeutic intervention in patients in future.

Weaknesses:

In this revised version of the manuscript, the authors have satisfactorily addressed all the concerns raised by the reviewers. They have also provided futuristic viewpoints towards tackling neurodegenerative disorder, especially Huntington Disease (HD).

Reviewer #2 (Public review):

Summary:

This work used multiple approaches to show that CCK is critical for long-term potentiation (LTP) in the auditory thalamocortical pathway. They also showed that the CCK mediation of LTP is age-dependent and supports frequency discrimination. This work is important because is opens up a new avenue of investigation of the roles of neuropeptides in sensory plasticity.

Strengths:

The main strength is the multiple approaches used to comprehensively examine the role of CCK in auditory thalamocortical LTP. Thus, the authors do provide a compelling set of data that CCK mediates thalamocortical LTP in an age-dependent manner.

Weaknesses:

There are some details that should be addressed, primarily regarding potential baseline differences in comparison groups. The behavioral assessment is relatively limited, but may be fleshed out in future work.

Reviewer #2 (Public review):

This study presents a valuable finding on the neural encoding of speech in listeners with normal hearing and hearing impairment, uncovering marked differences in how attention to different levels of speech information is allocated, especially when having to selectively attend to one speaker while ignoring an irrelevant speaker. The results overall support the claims of the authors, although a more explicit behavioural task to demonstrate successful attention allocation would have strengthened the study. Importantly, the use of more "temporally continuous" analysis frameworks could have provided a better methodology to assess the entire time course of neural activity during speech listening. Despite these limitations, this interesting work will be useful to the hearing impairment and speech processing research community.

The study compares speech-in-quiet vs. multi-talker scenarios, allowing to assess within-participant the impact that the addition of a competing talker has on the neural tracking of speech. Moreover, the inclusion of a population with hearing loss is useful to disentangle the effects of attention orienting and hearing ability. The diagnosis of high-frequency hearing loss was done as part of the experimental procedure by professional audiologists, leading to a high control of the main contrast of interest for the experiment. Sample size was big, allowing to draw meaningful comparisons between the two populations.

An HM-LSTM model was employed to jointly extract speech features spanning from the stimulus acoustics to word-level and phrase-level information, represented by embeddings extracted at successive layers of the model. The model was specifically expanded to include lower level acoustic and phonetic information, reaching a good representation of all intermediate levels of speech.

Despite conveniently extracting all features jointly, the HM-LSTM model processes linguistic input sentence-by-sentence, and therefore only allows to assess the corresponding EEG data at sentence offset. If I understood correctly, while the sentence information extracted with the HM-LSTM reflects the entire sentence - in terms of its acoustic, phonetic and more abstract linguistic features - it only gives a condensed final representation of the sentence. As such, feature extraction with the HM-LSTM is not compatible with a continuous temporal mapping on the EEG signal, and this is the main reason behind the authors' decision to fit a regression at nine separate time points surrounding sentence offsets.

While valid and previously used in the literature, this methodology, in the particular context of this experiment, might be obscuring important attentional effects impacted by hearing-loss. By fitting a regression only around sentence-final speech representations, the method might be overlooking the more "online" speech processing dynamics, and only assessing the permanence of information at different speech levels at sentence offset. In other words, the acoustic attentional bias between Attended and Unattended speech might exist even in hearing-impaired participants but, due to a lower encoding or permanence of acoustic information in this population, it might only emerge when using methodologies with a higher temporal resolution, such as Temporal Response Functions (TRFs). If a univariate TRF fit simply on the continuous speech envelope did not show any attentional bias (different trial lengths should not be a problem for fitting TRFs), I would be entirely convinced of the result. For now, I am unsure on how to interpret this finding.

Despite my doubts on the appropriateness of condensed speech representations and single-point regression for acoustic features in particular, the current methodology allows the authors to explore their research questions, and the results support their conclusions.

This work presents an interesting finding on the limits of attentional bias in a cocktail-party scenario, suggesting that fundamentally different neural attentional filters are employed by listeners with high-frequency hearing loss, even in terms of the tracking of speech acoustics. Moreover, the rich dataset collected by the authors is a great contribution to open science and will offer opportunities for re-analysis.

Reviewer #2 (Public review):

Summary:

The manuscript claims to present a novel method for direct imaging of electric field networks from EEG data with higher spatiotemporal resolution than even fMRI. Validation of the EEG reconstructions with EEG/FMRI, EEG, and iEEG datasets are presented. Subsequently, reconstructions from a large EEG datasets of subjects performing a gambling task are presented.

Strengths:

If true and convincing, the proposed theoretical framework and reconstruction algorithm can revolutionise the use of EEG source reconstructions.

Weaknesses:

There is very little actual information in the paper about either the forward model or the novel method of reconstruction. Only citations to prior work by the authors are given with absolutely no benchmark comparisons, making the manuscript difficult to read and interpret in isolation to their prior body of work.

Comments on revisions:

This is a major rewrite of the paper. The authors have improved the discourse vastly. There is now a lot of didactics included but they are not always relevant to the paper. The section on Maxwell's equation does a disservice to the literature in prior work in bioelectromagnetism and does not even address the issues raised in classic text books by Plonsey et al. There is no logical "backwardness" in the literature. They are based on the relative values of constants in biological tissues. Several sections of the appendix discuss in terms of weather predictions and could just be written specifically for the problem here. There are reinventions of many standard ideas in terms of physics discourses, like Bayesian theory or PCA etc. I think that the paper remains quite opaque and many of the original criticisms remain, especially as they relate to multimodal datasets. The overall algorithm still remains poorly described. The comparisons to benchmark remain unaddressed and the authors state that they couldn't get Loreta to work and so aborted that. The figures are largely unaltered, although they have added a few more, and do not clearly depict the ideas. Again, no benchmark comparisons are provided to evaluate the results and the performance in comparison to other benchmarks.

DOI: 10.1038/s41467-025-58821-3

Resource: None

Curator: @dhovakimyan1

SciCrunch record: RRID:ZFIN_ZDB-ALT-110914-2

What is this?

DOI: 10.1038/s41467-025-58821-3

Resource: (ZFIN Cat# ZDB-ALT-061228-2,RRID:ZFIN_ZDB-ALT-061228-2)

Curator: @dhovakimyan1

SciCrunch record: RRID:ZFIN_ZDB-ALT-061228-2

What is this?

Reviewer #2 (Public review):

This paper shows and analyzes an interesting phenomenon. It shows that when people are exposed to sequences of moving dots (That is moving dots in one direction, followed by another direction etc.), that showing either the starting movement direction, or ending movement direction causes a coarse-grained brain response that is similar to that elicited by the complete sequence of 4 directions. However, they show by decoding the sensor responses that this brain activity actually does not carry information about the actual sequence and the motion directions, at least not on the time scale of the initial sequence. They also show a reverse reply on a highly-compressed time scale, which is elicited during the period of elevated activity, and activated by the first and last elements of the sequence, but not others. Additionally, these replays seem to occur during periods of cortical ripples, similar to what is found in animal studies.

These results are intriguing. They are based on MEG recordings in humans, and finding such replays in humans is novel. Also, this is based on what seems to be sophisticated statistical analysis. The statistical methodology seems valid, but due to its complexity it is not easy to understand. The methods especially those described in figures 3 and 4 should be explained better.

Comments on second revised version by editorial team:

In response to the reviewer, the authors have substantially expanded and clarified their description of the methodology in this version of the manuscript.

Reviewer #2 (Public review):

Summary:

The manuscript by Maurice and Katarzyna describes a self-supervised, annotation-free deep-learning approach capable of quantitatively representing complex poses and behaviors of C. elegans directly from video pixel values. Their method overcomes limitations inherent to traditional methods relying on skeletonization or keypoint tracking, which often fail with highly coiled or self-intersecting worms. By applying self-supervised contrastive learning and a Transformer-based network architecture, the authors successfully capture diverse behavioral patterns and depict the aging trajectory of behavioral repertoire. This provides a useful new tool for behavioral research in C. elegans and other flexible-bodied organisms.

Strengths:

Reliable tracking and segmentation of complex poses remain significant bottlenecks in C. elegans behavioral research, and the authors made valuable attempts to address these challenges. The presented method offers several advantages over existing tools, including freedom from manual labeling, independence from explicit skeletonization or keypoint tracking, and the capability to capture highly coiled or overlapping poses. Thus, the proposed method would be useful to the C. elegans research community.

The research question is clearly defined. Methods and results are engagingly presented, and the manuscript is concise and well-organized.

Weaknesses:

(1) In the abstract, the claim of an 'unbiased' approach is not well-supported. The method is still affected by dataset biases, as mentioned in the aging results (section 4.3).<br /> (2) In section 3.2, the rationale behind rotating worm images to a vertical orientation is unclear.<br /> (3) The methods section is clearly written but uses overly technical language, making it less accessible to the audience of eLife, the majority of whom are biologists. Clearer explanations of key methods and the rationale behind their selection are needed. For example, in section 3.3, the authors should briefly explain in simple language what contrastive learning is, why they chose it, and why this method potentially achieves their goal.<br /> (4) The reason why the gray data points could not be resolved by Tierpsy is not quantitatively described. Are they all due to heavily coiled or overlapping poses?<br /> (5) In section 4.1, generating pose representations grouped by genetic strains would provide insights into strain-specific differences resolved by the proposed method.<br /> (6) Fig. 3a requires clarification. Highly bent poses (red points) intuitively should be close to highly coiled poses (gray points). The authors should explain the observed greenish/blueish points interfacing with the gray points.<br /> (7) In Fig. 3a, some colored points overlap with the gray point cloud. Why can Tierpsy resolve these overlapping points representing highly coiled poses? A more systematic quantitative comparison between Tierpsy and the proposed method is required.<br /> (8) The claim in section 4.2 regarding strain separation in pose embedding spaces is unsupported by Fig. 3a, which lacks strain-based distinctions. As mentioned in point #5, showing pose representations grouped by different strains is required.<br /> (9) In section 4.2, how the authors could verify the statement, "This likely occurs since most strains share common behaviors such as simple forward locomotion"?<br /> (10) An important weakness of the proposed method is its low direct interpretability, as it is not based on handcrafted features. To better interpret the pose/behavior embedding space, it would be helpful to compare it against more basic Tierpsy features in Fig. 3 and 4. This comparison could reveal what understandable features were learned by the neural network, thereby increasing human interpretability.<br /> (11) The main conclusion of section 4.3 is not sufficiently tested. Is Fig. 5a generated only from data of N2 animals? To quantitatively verify the statement, "Young individuals appear to display a wide range of behaviors, while as they age their behavior repertoire reduces," the authors should perform a formal analysis of behavioral variability throughout aging.<br /> (12) In Fig. 5a, better visualization of aging trajectories could include plotting the center of mass along with variance of the point cloud over time.<br /> (13) To better reveal aging trajectories of behavioral changes for different genetic backgrounds, it would be meaningful to generate behavior representations for different strains as they age.<br /> (14) As a methods paper, the ease of use for other researchers should be explicitly addressed, and source code and datasets should be provided.

Reviewer #2 (Public review):

Summary:

In this study, Xiong et al. investigate whether rhythmic sampling - a process typically observed in the attended processing of visual stimuli - extends to task-irrelevant distractors. By using EEG with frequency tagging and multivariate pattern analysis (MVPA), they aimed to characterize the temporal dynamics of both target and distractor processing and examine whether these processes oscillate in time. The central hypothesis is that target and distractor processing occur rhythmically, and the phase relationship between these rhythms correlates with behavioral performance.

Major Strengths:

(1) The extension of rhythmic attentional sampling to include distractors is a novel and interesting question.

(2) The decoding of emotional distractor content using MVPA from SSVEP signals is an elegant solution to the problem of assessing distractor engagement in the absence of direct behavioral measures.

(3) The finding that relative phase (between 1 Hz target and distractor processes) predicts behavioral performance is compelling.

Major Weaknesses and Limitations:

(1) Incomplete Evidence for Rhythmicity at 1 Hz: The central claim of 1 Hz rhythmic sampling is insufficiently validated. The windowing procedure (0.5s windows with 0.25s step) inherently restricts frequency resolution, potentially biasing toward low-frequency components like 1 Hz. Testing different window durations or providing controls would significantly strengthen this claim.

(2) No-Distractor Control Condition: The study lacks a baseline or control condition without distractors. This makes it difficult to determine whether the distractor-related decoding signals or the 1 Hz effect reflect genuine distractor processing or more general task dynamics.

(3) Decoding Near Chance Levels: The pairwise decoding accuracies for distractor categories hover close to chance (~55%), raising concerns about robustness. While statistically above chance, the small effect sizes need careful interpretation, particularly when linked to behavior.

(4) No Clear Correlation Between SSVEP and Behavior: Neither target nor distractor signal strength (SSVEP amplitude) correlates with behavioral accuracy. The study instead relies heavily on relative phase, which - while interesting - may benefit from additional converging evidence.

(5) Phase-analysis: phase analysis is performed between different types of signals hindering their interpretability (time-resolved SSVEP amplitude and time-resolved decoding accuracy).

Appraisal of Aims and Conclusions:

The authors largely achieved their stated goal of assessing rhythmic sampling of distractors. However, the conclusions drawn - particularly regarding the presence of 1 Hz rhythmicity - rest on analytical choices that should be scrutinized further. While the observed phase-performance relationship is interesting and potentially impactful, the lack of stronger and convergent evidence on the frequency component itself reduces confidence in the broader conclusions.

Impact and Utility to the Field:

If validated, the findings will advance our understanding of attentional dynamics and competition in complex visual environments. Demonstrating that ignored distractors can be rhythmically sampled at similar frequencies to targets has implications for models of attention and cognitive control. However, the methodological limitations currently constrain the paper's impact.

Additional Context and Considerations:

(1) The use of EEG-fMRI is mentioned but not leveraged. If BOLD data were collected, even exploratory fMRI analyses (e.g., distractor modulation in visual cortex) could provide valuable converging evidence.

(2) In turn, removal of fMRI artifacts might introduce biases or alter the data. For instance, the authors might consider investigating potential fMRI artifact harmonics around 1 Hz to address concerns regarding induced spectral components.

Reviewer #2 (Public review):

Summary

Dozens of published studies have investigated rhythms in behavior. These studies have typically tested for oscillations by shuffling the timestamps of the individual observations and comparing the resulting shuffled spectra with the empirical spectrum. However, that shuffling-in-time method leads to strongly inflated rates of false positives. Brookshire (2022) suggested a method that controls the rate of false positives (the "AR-surrogate method"). In the current study, Harris and Beale propose a modification of the AR-surrogate analysis method with the goal of increasing the sensitivity while maintaining a low rate of false positives.

This study is carefully conducted and it addresses an interesting question. However, the simulations were performed in a way that ignores one important source of temporal structure: non-oscillatory patterns that are consistent across subjects. In order to know whether the updated AR-surrogate method would control the rate of false positives in real behavioral data, we need to know whether it controls the rate of false positives when the data includes aperiodic patterns that are consistent across subjects.

Strengths

This study was constructed carefully and written up very clearly. It's a clever idea to analyze the time series separately for each participant. After examining how the updated AR-surrogate method behaves when the simulated data includes consistency across subjects, this will be a useful contribution to the field.

Weaknesses

When describing their simulations of behavioral data, the authors write: "Each participant's data was produced by creating an independent idealised time-course of 1-second length, sampled at 60 Hz."

Because these simulations generated a totally independent time-course for every subject, they don't capture an important source of aperiodic structure in real behavior: consistent non-oscillatory patterns that occur across subjects. In other words, these simulations do not account for any pattern that remains after averaging across subjects. The literature is rich with patterns that persist across subjects, including all the studies of behavioral oscillations that analyze their data after averaging across subjects (e.g., Landau & Fries, 2012; Fiebelkorn, Saalmann, & Kastner, 2013, etc). As a consequence, I suspect that the reported increase in power comes at the expense of a corresponding increase in false positives, but that the false positives aren't captured here due to the lack of consistency across simulated subjects.

It's therefore possible that the authors' updated AR-surrogate method would mistakenly conclude that behavior oscillates when it only includes aperiodic consistency across subjects. Since that kind of aperiodic structure is ubiquitous, this analysis could lead to very high rates of false positives. Luckily, it's easy to find out whether this is the case - the authors could simulate data using an idealized time-course that is consistent across subjects.

Reviewer #2 (Public review):

In this paper, Griswold and Van Hooser investigate what happens if animals are exposed to patterned visual experience too early, before its natural onset. To this end, they make use of the benefits of the ferret as a well-established animal model for visual development. Ferrets naturally open their eyes around postnatal day 30; here, Griswold and Van Hooser opened either one or both eyes prematurely. Subsequent recordings in the mature primary visual cortex show that while some tuning properties like orientation and direction selectivity developed normally, the premature visual exposure triggered changes in temporal frequency tuning and overall firing rates. These changes were widespread, in that they occurred even for neurons responding to the eye that was not opened prematurely. These results demonstrate that the nature of the visual input well before eye opening can have profound consequences on the developing visual system.

The conclusions of this paper are well supported by the data, but some aspects of the data could be clarified, and the discussion could be extended.

(1) The assessment of the tuning properties is based on fits to the data. Presumably, neurons for which the fits were poor were excluded? It would be useful to know what the criteria were, how many neurons were excluded, and whether there was a significant difference between the groups in the numbers of neurons excluded (which could further point to differences between the groups).

(2) For the temporal frequency data, low- and high-frequency cut-offs are defined, but then only used for the computation of the bandwidth. Given that the responses to low temporal frequencies change profoundly with premature eye opening, it would be useful to directly compare the low- and high-frequency cut-offs between groups, in addition to the index that is currently used.

(3) In addition to the tuning functions and firing rates that have been analyzed so far, are there any differences in the temporal profiles of neural responses between the groups (sustained versus transient responses, rates of adaptation, latency)? If the temporal dynamics of the responses are altered significantly, that could be part of an explanation for the altered temporal tuning.

(4) It would be beneficial for the general interpretation of the results to extend the discussion. First, it would be useful to provide a more detailed discussion of what type of visual information might make it through the closed eyelids (the natural state), in contrast to the structured information available through open eyes. Second, it would be useful to highlight more clearly that these data were collected in peripheral V1 by discussing what might be expected in binocular, more central V1 regions. Third, it would be interesting to discuss the observed changes in firing rates in the context of the development of inhibitory neurons in V1 (which still undergo significant changes through the time period of premature visual experience chosen here).

Reviewer #2 (Public review):

Summary:

The study explores how single striatal projection neurons (SPNs) utilize dendritic nonlinearities to solve complex integration tasks. It introduces a calcium-based synaptic learning rule that incorporates local calcium dynamics and dopaminergic signals, along with metaplasticity to ensure stability for synaptic weights. Results show SPNs can solve the nonlinear feature binding problem and enhance computational efficiency through inhibitory plasticity in dendrites, emphasizing the significant computational potential of individual neurons. In summary, the study provides a more biologically plausible solution to single-neuron learning and gives further mechanical insights into complex computations at the single-neuron level.

Strengths:

The paper introduces a novel learning rule for training a single multicompartmental neuron model to perform nonlinear feature binding tasks (NFBP), highlighting two main strengths: the learning rule is local, calcium-based, and requires only sparse reward signals, making it highly biologically plausible, and it applies to detailed neuron models that effectively preserve dendritic nonlinearities, contrasting with many previous studies that use simplified models.

Reviewer #2 (Public review):

Summary:

Jeong & Choi (2023) use a semi-naturalistic paradigm to tackle the question of how the activity of neurons in the mPFC might continuously encode different functions. They offer two possibilities: either there are separate dedicated populations encoding each function, or cells alter their activity dependent on the current goal of the animal. In a threat-avoidance task rats procurred sucrose in an area of a chamber where, after remaining there for some amount of time, a 'Lobsterbot' robot attacked. In order to initiate the next trial rats had to move through the arena to another area before returning to the robot encounter zone. Therefore the task has two key components: threat avoidance and navigating through space. Recordings in the IL and PL of the mPFC revealed encoding that depended on what stage of the task the animal was currently engaged in. When animals were navigating, neuronal ensembles in these regions encoded distance from the threat. However, whilst animals were directly engaged with the threat and simultaneously consuming reward, it was possible to decode from a subset of the population whether animals would evade the threat. Therefore the authors claim that neurons in the mPFC switched between two functional modes: representing allocentric spatial information, and representing egocentric information pertaining to the reward and threat. Finally, the authors propose a conceptual model based on these data whereby this switching of population encoding is driven by either bottom-up sensory information or top-down arbitration.

Strengths:

Whilst these multiple functions of activity in the mPFC have generally been observed in tasks dedicated to the study of a singular function, less work has been done in contexts where animals continuously switch between different modes of behaviour in a more natural way. Being able to assess whether previous findings of mPFC function apply in natural contexts is very valuable to the field, even outside of those interested in the mPFC directly. This also speaks to the novelty of the work; although mixed selectivity encoding of threat assessment and action selection has been demonstrated in some contexts (e.g. Grunfeld & Likhtik, 2018) understanding the way in which encoding changes on-the-fly in a self-paced task is valuable both for verifying whether current understanding holds true and for extending our models of functional coding in the mPFC.

The authors are also generally thoughtful in their analyses and use a variety of approaches to probe the information encoded in the recorded activity. In particular, they use relatively close analysis of behaviour as well as manipulating the task itself by removing the threat to verify their own results. The use of such a rich task also allows them to draw comparisons, e.g. in different zones of the arena or different types of responses to threat, that a more reduced task would not otherwise allow. Additional in-depth analyses in the updated version of the manuscript, particularly the feature importance analysis, as well as complimentary null findings (a lack of cohesive place cell encoding, and no difference in location coding dependent on direction of trajectory) further support the authors' conclusion that populations of cells in the mPFC are switching their functional coding based on task context rather than behaviour per se. Finally, the authors' updated model schematic proposes an intriguing and testable implementation of how this encoding switch may be manifested by looking at differentiable inputs to these populations.

Weaknesses:

The main existing weakness of this study is that its findings are correlational (as the authors highlight in the discussion). Future work might aim to verify and expand the authors' findings - for example, whether the elevated response of Type 2 neurons directly contributes to the decision-making process or just represents fear/anxiety motivation/threat level - through direct physiological manipulation. However, I appreciate the challenges of interpreting data even in the presence of such manipulations and some of the additional analyses of behaviour, for example the stability of animals' inter-lick intervals in the E-zone, go some way towards ruling out alternative behavioural explanations. Yet the most ideal version of this analysis is to use a pose estimation method such as DeepLabCut to more fully measure behavioural changes. This, in combination with direct physiological manipulation, would allow the authors to fully validate that the switching of encoding by this population of neurons in the mPFC has the functional attributes as claimed here.

Reviewer #2 (Public review):

Summary:

Itoh et al. investigate the role of the zinc finger transcription factor Bcl11b/Citp2 on sub cerebral projection neurons (SCPN) development. They dissect Bcl11b cell-autonomous and non-cell-autonomous functions on subcerebral projection neurons. In addition, they identify Cdh13 as a downstream target of Bcl11b in the process of SCPN axon outgrowth.

Strengths:

Itoh et al. take advantage of a mouse CRE/Lox genetic system as a powerful tool to distinguish Bcl11b cell-autonomous function on cortical layer V subcerebral projection neurons and its non-cell-autonomous function mediated by the striatal medium spiny neurons (MSN).

Besides the description of the cellular and anatomical defects of the corticofugal projection neurons' outgrowth and fasciculation, they perform a transcriptomic analysis of SCPN somata to identify Bcl11b target genes. As a result, they find that Cdh13, a membrane-anchored cadherin , is downstream of Bcl11b and mediates its cell-autonomous role on axon outgrowth. To validate the role of Cdh13 as a mediator of Bcl11b on SCPN development, they set up a new technique to identify and quantify superficial antigens on growth cone membranes.

Weaknesses:

While the authors shed light on the role of Bcl11b on SCPN development, they lack to contextualize their findings on the previously described interplay between Bcl11a and b.<br /> In addition, this work is another example of the common practice of picking from a list of differentially expressed genes the most likely ones. This approach, while useful, does not allow the identification of new and unknown players.

Reviewer #2 (Public review):

Summary:

The authors examine medial entorhinal cortex (MEC) and postrhinal cortex (POR) responses using Ca imaging during a non-spatial, Go/No-Go visual association task. The authors specifically consider whether MEC encodes stimulus information, as previously seen and hypothesized in POR, as well as other task elements such as reward, and whether and how these responses evolve with learning in both regions. The authors find that, in general, POR encodes task-related information more strongly compared to MEC. In particular, POR encodes the stimulus even before the animal reaches expert performance, whereas MEC shows considerably weaker stimulus encoding that emerges with learning. Both regions also display licking-related coding, although notably this activity reflects choice or licking-preparation, which emerges with learning. Further, despite its overall reduced coding, MEC exhibits greater anatomical clustering of cells with similar functional properties compared to POR.

Strengths:

These data are generally well-presented, both in the description of the experimental paradigm - which is simple yet highly informative - and in the individual results for each section. A major strength is the dataset, which includes many cells, including a subset that are tracked across learning. I found the core findings - (1) that POR has robust stimulus encoding while MEC develops weaker stimulus information with learning, and (2) that both POR and MEC exhibit an increase in lick-modulated cells, although POR has more, and stronger, lick-modulated cells - to be generally well-supported by the data presented. The general question of whether and how MEC encodes non-spatial task-relevant features and how these responses (if they exist) emerge with learning is of general interest. In addition, how MEC activity contrasts with activity in an upstream region, thereby indicating what information MEC gets and what it does with it, is also of broad interest.

Weaknesses:

I perceived two primary weaknesses.

The first was that it was not entirely clear to me what was expected of MEC and POR responses, and whether the observations the authors made were surprising or entirely in line with what would've been predicted based on prior work. In some ways, the results seem expected - POR had visual signals, MEC had few visual signals but some reward signals.

The second is that it took me a long time to extract what I perceived to be the core results of the paper, and in some places, it was a little hard for me to understand all the analyses and results together as one cohesive step forward in our understanding of MEC and POR coding properties.

I think this was most evident in the results presented in Figure 4. Up until Figure 4, it seemed to me that the core results were:<br /> (1) visual (stimulus information) is present in POR responses from very early learning, whereas weak stimulus information develops in MEC with learning, and in both cases, there is a preference for the plus stimulus.<br /> (2), both POR and MEC show an increase in lick-modulated cells with learning, although more cells encode licking at all stages in POR.

This is nicely summarized in my view by Figure 3e. However, I became confused when Figure 4 entered the picture. Here, it seems that by far the most predominant coefficient in the model is the lick response, with stimulus features playing a smaller role - specifically, at the end of learning, 60% of POR cells were characterized as predominantly lick/non lick, compared to 25% defined by their coding to the stimulus. I can appreciate that there might be nuances to these and previous analyses such that all the results sit cohesively together, but I think that needs to be clarified.

A second example - Figure 2b - shows that many (75%) of MEC neurons seem to be selectively active for the plus stimulus, but when doing the GLM analysis with the plus stimulus (and reward/licking) as features, many fewer neurons (35%) are determined to be encoding task information. It was not clear to me what was contributing to the discrepancy between these two results - is it that MEC activity often increases with learning, but doesn't increase by that much?

I think in general this can be helped by specifically pointing out how the results of these different analyses relate to each other, including specifically mentioning where the results might seem unaligned (at least on the surface).

Reviewer #2 (Public review):

Summary:

Baniulyte and Wade describe how translation of an 8-codon uORF denoted toiL upstream of the topAI-yjhQP operon is responsive to different ribosome-targeting antibiotics, consequently controlling translation of the TopAI toxin as well as Rho-dependent termination with the gene.

Strengths:

The authors used multiple different approaches such as a genetic screen to identify factors such as 23S rRNA mutations that affect topA1 expression and ribosome profiling to examine the consequences of various antibiotics on toiL-mediated regulation.

Weaknesses: Future experiments will be needed to better understand the physiological role of the toiL-mediated regulation and elucidate the mechanism of specific antibiotic sensing.

The results are clearly described, and the revisions have helped to improve the presentation of the data.

Reviewer #2 (Public review):

This is a comprehensive analysis of Salmonella Dublin genomes that offers insights into the global spread of this pathogen and region-specific traits that are important to understand its evolution. The phenotyping of isolates of ST10 and ST74 also offer insights into the variability that can be seen in S. Dublin, which is also seen in other Salmonella serovars, and reminds the field that it is important to look beyond lab-adapted strains to truly understand these pathogens. This is a valuable contribution to the field. The only limitation, which the authors also acknowledge, is the bias towards S. Dublin genomes from high-income settings. However, there is no selection bias; this is simply a consequence of publicly available sequences.

Reviewer #2 (Public review):

This study provides an experimental and computational framework to examine and understand how C. elegans make decisions while foraging environments with patches of food. The authors show that C. elegans reject or accept food patches depending on a number of internal and external factors.

The key novelty of this paper is the explicit demonstration of behavior analysis and quantitative modeling to elucidate decision-making processes. In particular, the description of the exploring vs. exploiting phases, and sensing vs. non-sensing categories of foraging behavior based on the clustering of behavioral states defined in a multi-dimensional behavior-metrics space, and the implementation of a generalized linear model (GLM) whose parameters can provide quantitative biological interpretations.

The work builds on the literature of C. elegans foraging by adding the reject/accept framework.

Reviewer #2 (Public review):

Summary:

In "Assessment of the Epigenomic Landscape in Human Myometrium at Term Pregnancy" the authors generate a number of genome-wide data sets to investigate epigenomic and transcriptomic regulation of the myometrium at term pregnancy. These data provide a useful resource for further evaluation of gene regulatory mechanisms in the myometrium and include the first Hi-C data published for this tissue. There is a comparison to previously published histone modification data and integration with RNA-seq to highlight potential enhancer-gene regulatory relationships. The authors further investigate putative enhancers upstream of the PLCL2 gene and identify a candidate region that may be regulated by the PGR (progesterone receptor) signaling.

Strengths:

The strengths of this study are in the multi-omics nature of the design as several genome-wide data sets are generated from the same patient samples. Extending this type of approach in the future to a larger number of samples will allow for additional investigation into gene regulation as correlation between epigenomic features and gene expression across a larger number of samples can reveal regulatory relationships.

Weaknesses:

One of the most interesting aspects of this study is the generation of the first Hi-C data for the human pregnant myometrium, however, there is minimal description in the results section of the Hi-C data analysis and the only data shown are the number of loops identified and one such loop that includes the PLCL2 promoter shown in figure 3A. The manuscript would benefit from a more extensive analysis of the Hi-C data, for example, the analysis of TADs (topological associating domains) would be interesting to add and could be used to evaluate to what extent H3K27ac domains and putative regulated genes fall within the same TAD.

The authors present some convincing evidence on the transcriptional regulation of the PLCL2 gene using Perturb-Seq to identify putative upstream enhancer regions and PGR over-expression showing PGR can act as an activator. These two experiments on their own are interesting, however, they are not as mechanistically integrated as they could be to clarify the molecular mechanisms. Deletion of the putative enhancer upstream of PLCL2 followed by over-expression of PGR would clarify the mechanistic relationship between the proposed enhancer, PGR and PLCL2 expression. Does PGR act through the proposed enhancer? In addition, reporter assays using this proposed enhancer region with and without increased expression of PGR and mutation of any PRE sequences would also provide mechanistic insight. Although CRISPRa and Perturb-Seq can be used to identify potential regulatory regions, the best approach to verify the requirement for a particular enhancer in regulating a specific gene is a deletion approach.

Comments on revisions:

The authors have addressed my comments that were directly sent to them, however, my comments in the public review, specifically the superficial nature of the Hi-C analysis were not addressed.

In addition, many of the comments to reviewer 3 were unaddressed and declared out of the scope of this study, as these were points of accuracy in the data analysis they are very much in scope.

I hope the authors reconsider presenting a more thorough analysis.

Reviewer #3 (Public review):

Summary:

Cryptococcus neoformans is a global critical threat pathogen and the manuscript by Mota et al demonstrates that the pathogen's N-glycan-dependent protein quality control system regulates the capacity of the fungus to cause disease. The system ensures that glycoproteins are folded correctly. The system is involved in fitness and virulence of the fungus by regulating aspects of cellular robustness and the trafficking of virulence-associated compounds outside of the cell via transport in extracellular vesicles.

Strengths:

The investigators use multiple modalities to demonstrate that the system is involved in cryptococcal pathogenesis. The investigators generated mutant C. neoformans to explore the role of genes involved in the protein folding system. Basic microbiology, genetic analyses, proteomics, fluorescence and transmission microscopy, nanotracking analyses, and murine studies were performed. The validity of the findings are thus very high. Hypotheses are robustly demonstrated.

Reviewer #2 (Public review):

Summary:

In this work, the authors consider the required functional properties of neurons that trajectories in 2D space using cell sequences, ultimately linking the required properties to those found in grid cells. In their argument, the authors first introduce a set of definitions and axioms, which then lead to their conclusion that a hexagonal pattern is the most efficient or parsimonious pattern one could use to uniquely label different 2D trajectories using sequences of cells. The authors then go through a set of classic experimental results in the grid cell literature - e.g. that the grid modules exhibit a multiplicative scaling, that the grid pattern expands with novelty or is warped by reward, etc. - and describe how these results are either consistent with or predicted by their theory. Overall, this paper asks a very interesting question and provides an intriguing answer.

Major strengths:

The general idea behind the paper is very interesting - why *does* the grid pattern take the form of a hexagonal grid? This is a question that has been raised many times; finding a truly satisfying answer is difficult but of great interest. The authors' main assertion that the answer to this question has to do with the ability of a hexagonal arrangement of neurons to uniquely encode 2D trajectories is an intriguing suggestion. It is also impressive that the authors considered such a wide range of experimental results in relation to their theory.

Major weaknesses:

One weakness I perceive is that the paper overstates what it delivers. In the introduction, the authors claim to provide "mathematical proof that ... the nature of the problem being solved by grid cells is coding of trajectories in 2-D space using cell sequences. By doing so, we offer a specific answer to the question of why grid cell firing patterns are observed in the mammalian brain." By virtue of the fact that the authors make assumptions about biological function in their claims, this paper does not provide proof of what grid cells are doing to support behavior nor provide the true answer as to why grid patterns are found in the brain. Although I find this study both intriguing and important - and I respect the authors' perspective - as an experimentalist guided by the principle that biological theories are never proven but instead continually supported by data, suggestions of a proof of grid cell function are hard for me to get behind. Regardless, the paper presents a compelling line of reasoning that enhance our understanding of grid cells.

Reviewer #2 (Public review):

Summary:

This paper examines the CO2 sensitivity of Cx43 hemichannels and gap junctional channels in transiently transfected Hela cells using several different assays, including ethidium dye uptake, ATP release, whole cell patch clamp recordings, and an imaging assay of gap junctional dye transfer. The results show that raising pCO2 from 20 to 70 mmHg (at a constant pH of 7.3) causes an increase in opening of Cx43 hemichannels but does not block Cx43 gap junctions. This study also showed that raising pCO2 from 20 to 35 mm Hg resulted in an increase in synaptic strength in hippocampal rat brain slices, presumably due to downstream ATP release, suggesting that the CO2 sensitivity of Cx43 may be physiologically relevant. As a further test of the physiological relevance of the CO2 sensitivity of Cx43, it was shown that two pathological mutations of Cx43 that are associated with ODDD caused loss of Cx43 CO2-sensitivity. Cx43 has a potential carbamylation motif that is homologous to the motif in Cx26. To understand the structural changes involved in CO2 sensitivity, a number of mutations were made in Cx43 sites thought to be the equivalent of those known to be involved in the CO2 sensitivity of Cx26, and the CO2 sensitivity of these mutants was investigated.

Strengths:

This study shows that the apparent lack of functional Cx43 hemichannels observed in a number of previous in vitro function studies may be due to the use of HEPES to buffer the external pH. When Cx43 hemichannels were studied in external solutions in which CO2/bicarbonate was used to buffer pH instead of HEPES, Cx43 hemichannels showed significantly higher levels of dye uptake, ATP release, and ionic conductance. These findings may have major physiological implications since Cx43 hemichannels are found in many organs throughout the body, including the brain, heart, and immune system.

Weaknesses:

(1) Interpretation of the site-directed mutation studies is complicated. Although Cx43 has a potential carbamylation motif that is homologous to the motif in Cx26, the results of site-directed mutation studies were inconsistent with a simple model in which K144 and K105 interact following carbamylation to cause the opening of Cx43 hemichannels.

(2) Secondly, although it is shown that two Cx43 ODDD-associated mutations show a loss of CO2 sensitivity, there is no evidence that the absence of CO2 sensitivity is involved in the pathology of ODDD.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors investigated how the type-I interferon response (ISG) and antigen presentation (AP) pathways are repressed in luminal breast cancer cells and how this repression can be overcome. They found that a STING agonist can reactivate these pathways in breast cancer cells, but it also does so in normal cells, suggesting that this is not a good way to create a therapeutic window. Depletion of ADAR and inhibition of KDM5 also activate ISG and AP genes. The activation of ISG and AP genes is dependent on cGAS/STING and the JAK kinase. Interestingly, although both ADAR depletion and KDM5 inhibition activate ISG and AP genes, their effects on cell fitness are different. Furthermore, KDM5 inhibitor selectively activates ISG and AP genes in tumor cells but not normal cells, arguing that it may create a larger therapeutic window than the STING agonist. These results also suggest that KDM5 inhibition may activate ISG and AP genes in a way different from ADAR loss, and this process may affect tumor cell fitness independently of the activation of ISG and AP genes.

The authors further showed that KDM5 inhibition increases R-loops and DNA damage in tumor cells, and XPF, a nuclease that cuts R-loops, is required for the activation of ISG and AP genes. Using H3K4me3 CUT&RUN, they found that KMD5 inhibition results in increased H3K4me3 not only at genes, but also at repetitive elements including SINE, LINE, LTR, telomeres, and centromeres. Using S9.6 CUT&TAG, they confirmed that R-loops are increased at SINE, LINE, and LTR repeated with increased H3K4me3. Together, the results of this study suggest that KMD5 inhibition leads to H3K4me3 and R-loop accumulation in repetitive elements, which induces DNA damage and cGAS/STING activation and subsequently activates AP genes. This provides an exciting approach to stimulate the anti-tumor immunity against breast tumors.

KDM5 inhibition activates interferon and antigen presentation genes through R-loops.

Strengths:

Overall, this study was carefully designed and executed. This is a new approach to make breast tumors "hot" for anti-tumor immunity.

Weaknesses:

Future in vivo studies are needed to show the effects of KDM5 inhibitors on the immunotherapy responses of breast tumors.

Reviewer #2 (Public review):

This study by Jonker et al. examines how the metabolic adaptations to the microenvironment by pancreatic ductal adenocarcinomas (PDAC) present vulnerabilities that could be used for therapeutic purposes. The evidence supporting the claims of the authors is mostly solid, and the multiplicity of models used, as well as the combination of in vitro and in vivo work, are appreciated, but some conclusions would benefit from additional substantiation. This work would be of interest to biologists working on the impact of microenvironment and metabolism in cancer, and especially those investigating pancreatic cancer.

In this study, the authors use mostly "doublings per day" as an indicator of cell death, notably for Figures 4 to 6. However, proliferative arrest (or a decrease in the proliferative rate) is not necessarily synonymous with cell death. It might be nice to complement these experiments with a true measure of cell death (e.g., PI uptake).

The composition of Tumor Interstitial Fluid Medium (TIFM) was published previously, but nonetheless a reminder of the composition of this medium in a Supplemental file of this study might be helpful. In particular, at the start of the Results section, the nature of serum/lipids in the different media should be specifically noted, especially given that the subsequent focus of the work is on lipids/SREBP. It is known that differences in the extracellular availability of lipids can profoundly alter de novo lipid biosynthesis pathways.

Reviewer #2 (Public review):

Summary:

This paper by Misra and Pessoa uses switching linear dynamical systems (SLDS) to investigate the neural network dynamics underlying threat processing at varying levels of proximity. Using an existing dataset from a threat-of-shock paradigm in which threat proximity is manipulated in a continuous fashion, the authors first show that they can identify states that each have their own linear dynamical system and are consistently associated with distinct phases of the threat-of-shock task (e.g., "peri-shock", "not near", etc). They then show how activity maps associated with these states are in agreement with existing literature on neural mechanisms of threat processing, and how activity in underlying brain regions alters around state transitions. The central novelty of the paper lies in its analyses of how intrinsic and extrinsic factors contribute to within-state trajectories and between-state transitions. Additional analyses furthermore show how individual brain regions contribute to state dynamics. Finally, the authors show how their findings generalize to another (related) threat paradigm.

Strengths:

The analyses for this study are conducted at a very high level of mathematical and theoretical sophistication. The paper is very well written and effectively communicates complex concepts from dynamical systems. The paper provides valuable neuroscientific insights into threat processing, and the methodology has potential to deepen our understanding at a neurobiological level in future work.

Weaknesses:

I was somewhat disappointed initially by the level of inferences made by the authors based on their analyses at the level of systems neuroscience. After revision this has improved, for instance with inclusion of analyses on the importance of individual brain regions to state dynamics, but I still believe the findings can be made more biologically meaningful, for instance by focusing on what we learn from these sophisticated analyses beyond what is already known from more conventional methodologies. However, the paper as it stands is solid scientific work and such efforts may also be left to future work.

Reviewer #2 (Public review):

The authors have examined subpopulations of individual neurons recorded in the thalamus and subthalamic nucleus (STN) of awake humans performing a simple cognitive task. They have carefully designed their task structure to minimize motor components that could confound their analyses in these subcortical structures, particularly given that the data was collected from patients with Parkinson's disease (PD) and essential tremor (ET). The recorded data represents a valuable contribution to the field. Pereira et al. conclude that their single-neuron recordings indicate task-related activity that is purportedly distinct from previously identified sensory signals.

Despite the significance of the dataset, important limitations arise due to the small number of recorded neurons relative to the high number of participants. That raises concerns about the generalizability of the conclusions drawn from the study.

(1) While I support the work conducted by the authors and their efforts to improve the manuscript, the number of significant neurons is considerably lower than the number of participants studied-approximately 8 neurons, compared to 32 participants. This low number of neurons involved in encoding raises concerns about the strength of the conclusions drawn.

(2) Additionally, the authors state that participants do not need to perform a motor execution, yet they are required to communicate their response verbally. This presents a contradiction, as speech involves the activation of facial muscles, and previous studies have shown that neuronal activity in the ventral premotor cortex can encode such movements in humans (Willet et al., Nature 2023). Clarifying this point would strengthen the argument and ensure consistency in the interpretation of results.

(3) One way to improve the study is to analyze the local field potentials (LFPs) recorded alongside the spikes. By examining different LFP components, particularly the beta band (Haegens et al., PNAS 2011), it may be possible to identify consistent modulation across the 32 recorded participants. This approach could provide additional support for the study's conclusions and help clarify the role of neural activity in the observed phenomena.

Reviewer #2 (Public review):

Conceptually, this study is interesting and is the first attempt to account for the potentially interactive effects of seasonality and blood source on mosquito fitness, which the authors frame as a possible explanation for previously observed host-switching of Culex quinquefasciatus from birds to mammals in the fall. The authors hypothesize that if changes in fitness by blood source change between seasons, higher fitness on birds in the summer and on mammals in the autumn could drive observed host switching. To test this, the authors fed individuals from a colony of Cx. quinquefasciatus on chickens (bird model) and mice (mammal model) and subjected each of these two groups to two different environmental conditions reflecting the high and low temperatures and photoperiod experienced in summer and autumn in Córdoba, Argentina (aka seasonality). They measured fecundity, fertility, and hatchability over two gonotrophic cycles. The authors then used generalized linear mixed models to evaluate the impact of host species, seasonality, and gonotrophic cycle on fecundity, fertility, and hatchability. The authors were trying to test their hypothesis by determining whether there was an interactive effect of season and host species on mosquito fitness. This is an interesting hypothesis; if it had been supported, it would provide support for a new mechanism driving host switching. While the authors did report an interactive impact of seasonality and host species, the directionality of the effect was the opposite from that hypothesized. The authors have done a very good job of addressing many of the reviewer's concerns, especially by adding two additional replicates.

Reviewer #3 (Public review):

Summary:

The manuscript "SARS-CoV-2 nsp16 is regulated by host E3 ubiquitin ligases, UBR5 and MARCHF7" is an interesting work by Tian et al. describing the degradation/ stability of NSP16 of SARS CoV2 via K48 and K27-linked Ubiquitination and proteasomal degradation. The authors have demonstrated that UBR5 and MARCHF7, an E3 ubiquitin ligase bring about the ubiquitination of NSP16. The concept, and experimental approach to prove the hypothesis looks ok. The in vivo data looks ok with the controls. Overall, the manuscript is good.

Strengths:

The study identified important E3 ligases (MARCHF7 and UBR5) that can ubiquitinate NSP16, an important viral factor.

Comments on revisions:

I had gone through the revised form of the manuscript thoroughly. The authors have addressed all of my concerns. To me, the experimental approach looks convincing that the host E3 ubiquitin ligases (UBR5 and MARCHF7) ubiquitinate NSP16 and mark it for proteasomal degradation via K48- and K27- linkage. The authors have represented the final figure (Fig.8) in a convincing manner, opening a new window to explore the mechanism of capping the vRNA bu NSP16.

Reviewer #2 (Public review):

Rademacher et al. present a paper showing that chronic chemogenetic excitation of dopaminergic neurons in the mouse midbrain results in differential degeneration of axons and somas across distinct regions (SNc vs VTA). These findings are important for two reasons: 1. This approach can be used as a mouse model for Parkinson's Disease without the need for the infusion of toxins (e.g. 6-OHDA or MPTP). This mouse model also has the advantage of showing a axon-first degeneration over an experimentally-useful time course (2-4 weeks). 2. The findings that direct excitation of dopaminergic neurons causes differential degeneration sheds light on the mechanisms of dopaminergic neuron selective vulnerability. The evidence that activation of dopaminergic neurons causes degeneration, alters motor behavior, and alters mRNA expression is convincing. This is an exciting and important paper and will have an impact on the Parkinson's Disease field.

Strengths:

This is an exciting and important paper and will have an impact on the Parkinson's Disease field.

It presents a new highly useful mouse model of PD.

The paper compares mouse transcriptomics with human patient data.

It shows that selective degeneration can occur across the midbrain dopaminergic neurons even in the absence of a genetic, prion, or toxin neurodegeneration mechanism.

Weaknesses:

The authors have addressed all my concerns. This is an interesting, important, and carefully-controlled study.

Reviewer #2 (Public Review):<br /> <br /> Summary:

Rademacher et al. present a paper showing that chronic chemogenetic excitation of dopaminergic neurons in the mouse midbrain results in differential degeneration of axons and somas across distinct regions (SNc vs VTA). These findings are important. This mouse model also has the advantage of showing a axon-first degeneration over an experimentally-useful time course (2-4 weeks). 2. The findings that direct excitation of dopaminergic neurons causes differential degeneration sheds light on the mechanisms of dopaminergic neuron selective vulnerability. The evidence that activation of dopaminergic neurons causes degeneration and alters mRNA expression is convincing, as the authors use both vehicle and CNO control groups, but the evidence that chronic dopaminergic activation alters circadian rhythm and motor behavior is incomplete as the authors did not run a CNO-control condition in these experiments.

Strengths:<br /> This is an exciting and important paper.<br /> The paper compares mouse transcriptomics with human patient data.<br /> It shows that selective degeneration can occur across the midbrain dopaminergic neurons even in the absence of a genetic, prion, or toxin neurodegeneration mechanism.

Weaknesses:

Major concerns:

(1) The lack of a CNO-positive, DREADD-negative control group in the behavioral experiments is the main limitation in interpreting the behavioral data. Without knowing whether CNO on its own has an impact on circadian rhythm or motor activity, the certainty that dopaminergic hyperactivity is causing these effects is lacking.

(2) One of the most exciting things about this paper is that the SNc degenerates more strongly than the VTA when both regions are, in theory, excited to the same extent. However, it is not perfectly clear that both regions respond to CNO to the same extent. The electrophysiological data showing CNO responsiveness is only conducted in the SNc. If the VTA response is significantly reduced vs the SNc response, then the selectivity of the SNc degeneration could just be because the SNc was more hyperactive than the VTA. Electrophysiology experiments comparing the VTA and SNc response to CNO could support the idea that the SNc has substantial intrinsic vulnerability factors compared to the VTA.

(3) The mice have access to a running wheel for the circadian rhythm experiments. Running has been shown to alter the dopaminergic system (Bastioli et al., 2022) and so the authors should clarify whether the histology, electrophysiology, fiber photometry, and transcriptomics data are conducted on mice that have been running or sedentary.

Reviewer #2 (Public review):

In this manuscript, Hua et al. proposed SLC7A11, a protein facilitating cellular cystine uptake, as a potential target for the treatment of trastuzumab resistant HER2 positive breast cancer. If this claim holds true, the finding would be of significance and might be translated to clinical practice. Nevertheless, this reviewer finds that the conclusion was insufficiently supported by the data.

Notably, most of the data (Figures 2-6) were based on two cell lines - JIMT1 as a representative of trastuzumab resistant cell line, and SKBR3 as a representative of trastuzumab sensitive cell line. As such, these findings could be cell line specific while irrelevant to trastuzumab sensitivity at all. Furthermore, the authors' claim of ferroptosis induction is primarily based on lipid peroxidation assays (Figure 3). The rescuing effects of ferroptosis inhibitors on cell viability were missing. The xenograft experiments were also suspicious (Figure 4). Systemic cysteine starvation is known to cause adverse effects, including liver necrosis, and the compound (i.e., erastin) used by the authors is not suitable for in vivo experiments due to low solubility and low metabolic stability. Finally, the authors focus on epigenetic regulations (Figures 5 & 6) without first investigating well-established transcription factors, such as NRF2 and ATF4, which are known to regulate SLC7A11.

To sum up, this reviewer finds that the most valuable data in this manuscript is perhaps Figure 1, which provides unbiased information concerning the metabolic patterns in trastuzumab sensitive and primary resistant HER2 positive breast cancer patients.

Comments on revisions:

(1) Figure 3: The unit of concentration should be "μM". "μm" means micrometer.

(2) Figure S5: Ferroptosis inhibitors should be used in cell viability assays to exclude the off-target effect of RSL3 and erastin. Note that erastin also targets VDAC, while RSL3 may inhibit other selenoproteins at high concentrations. Cell viability assays are critical for demonstrating ferroptosis and should be included in the main figure rather than relegated to the supplemental materials.

(3) Figure 4B & 4C: the data of "H" group and "Erastin" group are inconsistent. In panel B, the tumor size in the "H" group appears smaller than in the "Erastin" group, while in panel C, the opposite trend is observed.

(4) The catalog numbers for the cystine/cysteine-deficient DMEM (from BIOTREE) and diet (from Xietong Bio) should be provided. This information is essential for readers to identify and verify the specific products used in the study.

Reviewer #2 (Public review):

Summary:

This manuscript addresses the structural basis of voltage-activation of BK channels using computational approaches. Although a number of experimental studies using gating current and patch-clamp recording have analyzed voltage-activation in terms of observed charge movements and the apparent energetic coupling between voltage-sensor movement and channel opening, the structural changes that underlie this phenomenon have been unclear. The present studies use a reduced molecular system comprising the transmembrane portion of the BK channel (i.e., the cytosolic domain was deleted), embedded in a POPC membrane, with either 0 or 750 mV applied across the membrane. This system enabled acquisition of long simulations of 10 microseconds, to permit tracking of conformational changes of the channel. The authors' principal findings were that the side chains of R210 and R213 rapidly moved toward the extracellular side of the membrane (by 8 - 10 Å), with greater displacements than any of the other charged transmembrane residues. These movements appeared tightly coupled to the movement of the pore-lining helix, pore hydration, and ion permeation. The authors estimate that R210 and R213 contribute 0.25 and 0.19 elementary charges per residue to the gating current, which is roughly consistent with estimates based on electrophysiological measurements that used the full-length channel.

Strengths:

The methodologies used in this work are sound, and these studies certainly contribute to our understanding of voltage-gating of BK channels. An intriguing observation is the strongly coupled movement of the S4, S5, and S6 helices that appear to underlie voltage-dependent opening. Based on Figures 2a-d, the substantial movements of the R210 and R213 side chains occur nearly simultaneously to the S6 movement (between 4 - 5 usec of simulation time). This seems to provide support for a "helix-packing" mechanism of voltage gating in the so-called "non-domain-swapped" voltage-gated K channels.

Weaknesses:

The main limitation is that these studies used a truncated version of the BK channel, and there are likely to be differences in VSD-pore coupling in the context of the full-length channels that will not be resolved in the present work. Nonetheless, the authors provide a strong rationale for their use of the truncated channel, and the results presented will provide a good starting point for future computational studies of this channel.

Reviewer #2 (Public review):

This second revision has partially addressed criticisms previously raised; however, substantial inadequacies, particularly concerning rigorous validation and model justification, remain unresolved. While recognizing evident strength, novelty, and technical complexity of this work, the authors have yet to fully resolve key major concerns explicitly pointed out during revision in a satisfactory manner. As currently written, the manuscript does not yet provide sufficiently robust validation, methodological rigour, or clarity required for complete acceptance in a top-tier scientific journal.

Summary of Authors' Aim:

In this revised version, the authors aimed to address prior reviewer critiques harshly pinpointing the need for greater clarity in the manuscript's logical flow, rigorous external validation, clearer explanation of methodological normalization choices, and deeper elaboration of diffusion MRI method relevance and potential translation. The authors present a diffusion-weighted MRS approach paired with complex biophysical modelling to elucidate differential developmental trajectories of cellular structures in cerebellum and thalamus in rat neonates, providing a novel, non-invasive avenue for monitoring cellular microstructure.

Major Comments:

Rigorous Validation (Reviewer #1 - point R1.1, Reviewer #2 - point R2.2):

The major concern previously raised and reiterated here is the insufficient external cross-validation of the dMRS-derived interpretations about cellular changes, including the particularly speculative interpretation that taurine undergoes compartment switching between neuronal and glial compartments in the thalamus. The authors acknowledge this important shortcoming (R1.1, R2.2) but attempt to mitigate these concerns merely through additional contextual comparisons from existing literature (page 23, lines 877-878, Figure S11, Table S2). While better contextualization is welcome, the modified manuscript still falls notably short of the level of rigour necessary to validate such striking switches in compartmentalization. To justify claims of metabolites changing cellular compartments, explicit verification against independent molecular/histological data, ideally with additional immunohistochemical staining for cellular markers (e.g., glial fibrillary acidic protein, NeuN), is necessary. The mere presence of literature correlations (such as the reported visual comparisons to morphometric reconstructions, page 24, lines 883-884) does not constitute rigorous validation at the required standard for high-impact publication. The revised manuscript remains fundamentally weakened without such validation. To properly improve, the authors must consider incorporating independent ex vivo experiments or, if this is no longer feasible, extensively temper their compartment-switching claims, acknowledging explicitly and prominently the speculative nature of current interpretations.

Normalization of Metabolite Concentrations (Reviewer #1 - point R1.3):

The authors clearly responded to a reviewer wish for justification of metabolite normalisation to macromolecular concentrations (page 13, lines 493-503, Figure S2). However, the rationale provided remains only partially convincing. While the authors appropriately acknowledge the unusual nature of their methodological choice and possible confounding factors, they opt to supplement rather than substitute this approach with a more standard method (normalisation by water) in the main body of the manuscript. The additional supplementary Figure S2 is helpful, yet the conclusions derived with macromolecular normalization still remain potentially confounded by age-dependent macromolecular changes (Tkac et al., 2003). The justification given in the revised manuscript remains vague, unsatisfactory, and somewhat contradictory-authors accept macromolecules changes likely with age, yet largely overlook this effect. At least, the comparison between normalization by macromolecules and water should be explicitly discussed in the main text, and conclusions drawn from macromolecular normalization must be cautiously framed.

Choice and Justification of Biophysical Model (Reviewer #1 - point R1.4):

The reviewers questioned model assumptions, particularly ignoring macroscopic anisotropy effects due to white matter presence, myelination, and fibre orientation dispersion in the cerebellar voxel. Authors provided newly included DTI data and acknowledged this limitation explicitly (R1.4, Figure S8, page 25, lines 921-924). However, the addition of these poor-quality DTI data with limited interpretability paradoxically weakens rather than strengthens the manuscript as a whole, since the authors now present unclear supplementary results with little additional interpretative value. Recognizing poor data quality in this scenario, although intellectually honest, does not substantially increase the current robustness of their chosen model nor improve justification. To address this fully, either higher-quality data should be collected to robustly probe anisotropy or fibre dispersion effects, or the authors must much further restrict their interpretations in view of this clear limitation. Currently, the solution proposed is incomplete and insufficient to clarify the consequences of their chosen model.

Logical Flow and Clarity (Reviewer #2 - points R2.1 and R2.3):

The authors attempted to respond to reviewer comments on logical flow and accessibility (page 3, introduction restructuring). While the manuscript readability has improved, the introduction and discussion remain overly intricate, and at times, detail-oriented without clear links into central claims. In particular, the biological rationale for choosing the specific metabolite markers (especially tCho, Ins, Tau, etc.) and their known relevance must be further streamlined and simplified to increase accessibility and directness. Although some helpful restructuring was carried out, further careful paragraph-level revision for logical flow and readability remains necessary.

Translation to Human Studies (Reviewer #2 - point R2.4):

The authors have extended contextual discussion on translational potential regarding taurine as a developmental marker in humans (pages 24-25, lines 906-917). However, mention remains vague and cursory, without presenting sufficiently solid arguments nor drawing from human developmental studies adequately. Translational potential must be assessed within the realistic limitations inherent in clinical translation of MRS studies, particularly given the technical complexities clearly identified even in preclinical studies of this paper. Discussion remains relatively superficial, and if retained, must be expanded to fully discuss realistic human translational hurdles and requirements.

Reviewer #2 (Public review):

This article addresses the question of how complex behavior is maintained despite perturbations in underlying motor circuits. Using zebra finch song production as a model system, the authors employ a genetic approach to perturb activity in GABAergic neurons within the vocal control nucleus HVC. Specifically, they use AAV to deliver the tetanus toxin light chain (TeNT) under the interneuron-specific DLX promoter, with the goal of silencing interneurons. This manipulation causes rapid degradation of song, followed by recovery over several weeks.

The authors characterize the recovery using a combination of transcriptomic analysis, electrophysiology, and lesion studies. Notably, the recovery does not require the lMAN, which is typically considered critical for vocal learning and plasticity. The authors speculate that homeostatic mechanisms within the motor pathway - potentially involving microglial remodeling -may mediate this recovery.

The strength of the study lies in the striking behavioral effects - both degradation and recovery - resulting from a specific circuit perturbation, and the use of complementary approaches (gene expression, neurophysiology, behavior, and lesions) to link circuit changes to behavior. The approach is creative, and the findings are intriguing. More detailed comments are provided below that may help enhance the manuscript's value to the community.

(1) In Figure 1b, the authors show changes in the relative abundance of cell types following TeNT expression in HVC. The most prominent change, as noted by the authors, is an increase in microglia. However, there are also apparent changes in the proportions of other cell types-particularly decreases in neurons and radial glia. How do the authors interpret the observed reductions in GABAergic and glutamatergic cells, as well as radial glia? Are these decreases statistically significant? Given the magnitude of these changes, could they reflect sampling differences (e.g., inclusion of tissue outside HVC) or neuronal cell death? Alternatively, is it possible that the absolute number of mature neurons remains constant, and increases in other cell types shift the relative proportions? The authors should clarify how to interpret the Y-axis of this plot. It appears to reflect relative abundance rather than absolute cell numbers, which has important implications for interpretation.

(2) The authors appear to define their own cell type clusters and labels, rather than using standard classifications (e.g., Colquitt et al. 2021; Colquitt et al. 2023). This makes cross-study comparisons difficult. For example, Colquitt describes four classes of putative immature neurons (pre2-pre4, GABA-pre). In contrast, the authors refer to "neuroblasts" in Figure 1b. Are these equivalent to pre2-pre4 and/or to "GABA-pre"? What about "migrating neuroblasts" in Supplementary Figure 11? The authors could consider using the standard nomenclature, or if they disagree with that classification, explain why an alternative scheme is warranted.

(3) The transcriptomic data are underexplored. Many genes appear differentially expressed (e.g., in Figure 1c), however, the main text contains little discussion of differential gene expression beyond MHC I and B2M. It would be useful to discuss whether transcriptomic data support or rule out any other specific mechanistic hypotheses for recovery.

(4) The authors attribute increased microglial markers to interneuron silencing rather than inflammation from viral injection, based on control virus results (lines 143-146). However, is it plausible that TeNT expression itself, or batch variability, could drive differences in inflammation? The authors could address these alternatives with additional evidence or discussion.

Reviewer #3 (Public review):

Summary:

Eapen and coworkers use a rational design approach to generate new peptide-inspired ligands at the D-box interface of cdc20. These new peptides serve as new starting points for blocking APC/C in the context of cancer, as well as manipulating APC/C for targeted protein degradation therapeutic approaches.

Strengths:

The characterization of new peptide-like ligands is generally solid and multifaceted, including binding assays, thermal stability enhancement in vitro and in cells, X-ray crystallography, and degradation assays.

Comments on revisions:

I am satisfied with the changes in response to the first round of review.

Reviewer #2 (Public review):

Summary:

The authors use yeast genetics, lipidomic and biochemical approaches to demonstrate the DAG isoforms (36:0 and 36:1) can specifically activate PKC. Further, these DAG isoforms originate from PI and PI(4,5)P2. The authors propose that the Psi1-Plc1-Dip2 functions to maintain a normal level of specific DAG species to modulate PKC signalling.

Strengths:

Data from yeast genetics are clear and strong. The concept is potentially interesting and novel.

Weaknesses: More evidence is needed to support the central hypothesis. The authors may consider the following:

(1) Figure 2: the authors should show/examine C36:1 DAG. Also, some structural evidence would be highly useful here. What is the structural basis for the assertion that the PKC C1 domain can only be activated by C36:0/1 DAG but not other DAGs? This is a critical conclusion of this work and clear evidence is needed.

(2) Does Dip2 colocalize with Plc1 or Pkc1? Does Dip2 reach the plasma membrane upon Plc activation?

Comments on revisions:

The authors have addressed my concerns.

Reviewer #2 (Public review):

In this paper, the authors successfully incorporated the 49 dimensions found in a human similarity judgment task to better train DNNs to perform accurate human-like object similarity judgments. The results of the model performance are impressive but I am not totally convinced that the present modeling approach may bring new insights regarding the mental and neural representations of visual objects in the human brain. I have a few thoughts that I would like the authors to consider.

(1) Can the authors provide a detailed description of what these off-the-shelf DNNs are trained on? For models trained on visual images only, because semantic information was never present during training, it is not surprising they fail to capture such information, even with additional DimPred training. For the CLIP models, because visual-sematic associations were included during training, it again comes as no surprise that these models can do better even without DimPred training. Similarly, the results of homogenous image sets are not particularly surprising. In this regard, I am finding the paper reports many obvious results. Better motivations should be used to justify why particular models and analyses were performed, what predictions can be made, and how the results may be informative beyond what we already know.

(2) I am curious as to what DimPred training is doing exactly. If you create an arbitrary similarity structure (i.e., not the one derived from human similarity judgment) by, e.g., shuffling the values during training or creating 49 arbitrary dimensions, can the models be trained to follow this new arbitrary structure? In other words, do the models intrinsically contain a human-like structure, but we just have to find the right parameters to align them with the human structure or do we actually impose/force the human similarity structure onto the model with DimPred training?

Is it also an issue that you are including more parameters during DimPred training and that increased parameters alone can increase performance?

(3) There is very little information on how Figure 8 is generated. I couldn't find in the Methods any detailed descriptions of how the values were calculated. Are results from both the category-insensitive and category-sensitive embedding obtained from the same OpenCLIP-RN50x64? Figure 8 reports the relative improvement. What do the raw activation maps look like for the category-insensitive and category-sensitive embedding? I am surprised that the improvement is seen primarily in the early visual cortex (EVC) and higher visual areas but not more extensively in association areas sensitive to semantics. Why should EVC show such large improvements, given that category information is stored elsewhere?

Related to this point, how do other DNN models account for human brain fMRI responses in the present study? Many prior studies have documented the similarities and differences between DNN and human fMRI visual object representations. Do category-sensitive CLIP models outperform other DNN models? It is important to report the full results. Even though category-sensitive CLIP models outperform category-insensitive CLIP ones, if the overall model performance is low compared to the other DNNs, the results would not be very meaningful/impressive. I am just wondering if, in the process of achieving better human-like similarity judgment performance, these models lose some of the ability to account for visual object representations in the human ventral visual cortex.

(4) I am wondering how precisely the present results may yield new insights into the mental and neural representations of visual objects in the human brain. Prior human studies have already identified 49 dimensions that can capture human similarity judgment. Beyond predicting performance for new pairs of objects, how would the present modeling approach help us understand more about the human brain? The authors discussed this, but I am not sure the arguments are convincing.

Reviewer #2 (Public review):

This manuscript investigates the question of cellular heterogeneity using the response of Drosophila wing imaginal discs to ionizing radiation as a model system. A key advance here is the focus on quantitatively expressing various measures of heterogeneity, leveraging single-cell RNAseq approaches. To achieve this goal, the manuscript creatively uses a metric from the social sciences called the HHI to quantify the spatial heterogeneity of expression of individual genes across the identified cell clusters. Inter- and intra-regional levels of heterogeneity are revealed. Some highlights include the identification of spatial heterogeneity in the expression of ligands and transcription factors after IR. Expression of some of these genes shows dependence on p53. An intriguing finding, made possible by using an alternative clustering method focusing on cell cycle progression, was the identification of a high-trbl subset of cells characterized by concordant expression of multiple apoptosis, DNA damage repair, ROS-related genes, certain ligands, and transcription factors, collectively representing HIX genes. This high-trbl set of cells may correspond to an IR-induced G2/M arrested cell state.

Overall, the data presented in the manuscript are of high quality but are largely descriptive. This study is therefore perceived as a resource that can serve as an inspiration for the field to carry out follow-up experiments.

Reviewer #2 (Public review):

Summary:

Aldridge et al. aim to demonstrate the role of IL27 in limiting emergency myelopoiesis in response to Toxoplasma gondii infection by acting directly at the level of early haematopoietic progenitors.

They used different mouse genetic models, such as HSC lineage tracing, IL27 and IL27R-deficient mice, to show that:

(1) HSCs actively participate in emergency myelopoiesis during Toxoplasma gondii infection.

(2) The absence of IL27 and IL27R increases monocyte progenitors and monocytes, mainly inflammatory monocytes CCR2hi.

(3) At steady state, loss of IL27 impairs HSC fitness as competitive transplantation shows long-term engraftment deficiency of IL27 BM cells. This impairment is exacerbated after infection.

(4) IL27 is produced by various BM and other tissue cells at steady state, and its expression increases with infection, mainly by increasing the number of monocytes producing it.

Although it is indisputable that IL27 has a role in emergency myelopoiesis by limiting the number of pro-inflammatory monocytes in response to infection, the authors' claim that it acts only on HSCs and not on more committed progenitors (CMP, GMP, MP) is not supported by the quality of the data presented here, as described below in the weakness section. In addition, this study highlights a role for IL27 during infection, but does not focus on trained immunity, which is the focus of the targeted elife issue.

Weaknesses:

(1) In Figure 4, MFI quantification is required. This figure also shows the expression level (FACS and RNA) in progenitors (GMP and CMP, GP, MP), which is quite similar to that of HSC at this level, so it is really surprising that CMP does not respond at all to IL27 (S5C).

(2) Total BM was used to test the direct effect of IL27 on HSC. There could be an indirect effect from other more mature BM cells, even if they show lower receptor expression than HSC. This should be done on a different sorted population to prove the direct effect of IL27 on HSC. The authors need to look more closely at some stat-dependent genes or stat itself in different sorted cell populations, not just irgm1. It is also known that Stat is associated with increased HSC proliferation in response to IFN, which is the opposite of what is observed here.

(3) The decrease in HSC fitness in IL27R KO at steady state could be an indirect effect of the increase in proinflammatory monocytes contributing to high levels of inflammatory cytokines in the BM and thus chronic HSC activation that is enhanced in response to infection. What is the pro-inflammatory cytokine profile of the BM of IL27 or IL27R deficient mice and of mixed chimera mice?

(4) Furthermore, the FACS profile of KI67/brdu of Figure 7 is doubtful, as it is shown in different literature that KSL are not predominantly quiescent as shown here, but about 50% are KI67-. This is also inconsistent with the increase of HSC observed in Figure 1. Quantification of total BruDU+ HSC and other progenitors is also important to quantify all cells that have proliferated during infection. As the repopulation of IL27-deficient BM is also lower in the absence of infection, the proliferation of HSC in IL27R KO mice in the absence of infection is also important.

(5) The immunofluorescence in Figure 3 shows a high level of background and it is difficult to see the GFP and tomato positive cells. In this sense, the number of HSCs quantified as Procr+ (more than 8000 on a single BM section) is inconsistent with the total number of HSCs that a BM can contain (i.e., around 6000 per BM as quantified in Figure 1).

(6) The addition of arrows to the figure will help to visualise positive cells. It is also not clear why the author normalised the GFP+ cells to the tomato+ cells in Figure 3D.

(7) Furthermore, even if monocytes represent a high proportion of IL27-producing cells, they are only 50% of the cells at 5dpi, as shown in Figure 3 and S4. Without other monocyte markers, line 307 is incorrect.

(8) How do the authors explain that in Figure 1, 5-10% of labelled precursors and monocytes can give 100% of monocytes? This would mean that only labelled HSC can differentiate into PEC monocytes.

Reviewer #2 (Public review):

Summary:

In this manuscript, Grier, Salimian, and Kaufman characterize the relationship between the activity of neurons in sensorimotor cortex and forelimb kinematics in mice performing a reach-to-grasp task. First, they train animals to reach to two cued targets to retrieve water reward, measure limb motion with high resolution, and characterize the stereotyped kinematics of the shoulder, elbow, wrist, and digits. Next, they find that inactivation of the caudal forelimb motor area severely impairs coordination of the limb and prevents successful performance of the task. They then use calcium imaging to measure the activity of neurons in motor and somatosensory cortex, and demonstrate that fine details of limb kinematics can be decoded with high fidelity from this activity. Finally, they show reach direction (left vs right target) can be decoded earlier in the trial from motor than from somatosensory cortex.

Strengths:

In my opinion, this manuscript is technically outstanding and really sets a new bar for motor systems neurophysiology in the mouse. The writing and figures are clear, and the claims are supported by the data. This study is timely, as there has been a recent trend towards recording large numbers of neurons across the brain in relatively uncontrolled tasks and inferring a widespread but coarse encoding of high-level task variables. The central finding here, that sensorimotor cortical activity reflects fine details of forelimb movement, argues against the resurgent idea of cortical equipotentiality, and in favor of a high degree of specificity in the responses of individual neurons and of the specialization of cortical areas.

Weaknesses:

It would be helpful for the authors to be more explicit about which models of mouse cortical function their results support or rule out, and how their findings break new conceptual ground.

Reviewer #2 (Public review):

In the manuscript by Fu et al., the authors developed a chemo-immunological method for the reliable detection of Kacac, a novel post-translational modification, and demonstrated that acetoacetate and AACS serve as key regulators of cellular Kacac levels. Furthermore, the authors identified the enzymatic addition of the Kacac mark by acyltransferases GCN5, p300, and PCAF, as well as its removal by deacetylase HDAC3. These findings indicate that AACS utilizes acetoacetate to generate acetoacetyl-CoA in the cytosol, which is subsequently transferred into the nucleus for histone Kacac modification. A comprehensive proteomic analysis has identified 139 Kacac sites on 85 human proteins. Bioinformatics analysis of Kacac substrates and RNA-seq data reveals the broad impacts of Kacac on diverse cellular processes and various pathophysiological conditions. This study provides valuable additional insights into the investigation of Kacac and would serve as a helpful resource for future physiological or pathological research.

The following concerns should be addressed:

(1) A detailed explanation is needed for selecting H2B (1-26) K25 sites over other acetylation sites when evaluating the feasibility of the chemo-immunological method.

(2) In Figure 2(B), the addition of acetoacetate and NaBH4 resulted in an increase in Kbhb levels. Specifically, please investigate whether acetoacetylation is primarily mediated by acetoacetyl-CoA and whether acetoacetate can be converted into a precursor of β-hydroxybutyryl (bhb-CoA) within cells. Additional experiments should be included to support these conclusions.

(3) In Figure 2(E), the amount of pan-Kbhb decreased upon acetoacetate treatment when SCOT or AACS was added, whereas this decrease was not observed with NaBH4 treatment. What could be the underlying reason for this phenomenon?

(4) The paper demonstrates that p300, PCAF, and GCN5 exhibit significant acetoacetyltransferase activity and discusses the predicted binding modes of HATs (primarily PCAF and GCN5) with acetoacetyl-CoA. To validate the accuracy of these predicted binding models, it is recommended that the authors design experiments such as constructing and expressing protein mutants, to assess changes in enzymatic activity through western blot analysis.

(5) HDAC3 shows strong de-acetoacetylation activity compared to its de-acetylation activity. Specific experiments should be added to verify the molecular docking results. The use of HPLC is recommended, in order to demonstrate that HDAC3 acts as an eraser of acetoacetylation and to support the above conclusions. If feasible, mutating critical amino acids on HDAC3 (e.g., His134, Cys145) and subsequently analyzing the HDAC3 mutants via HPLC and western blot can further substantiate the findings.

(6) The resolution of the figures needs to be addressed in order to ensure clarity and readability.

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Reviewer #2 (Public review):

In this manuscript, Epiney et al., present a single-nucleus sequencing analysis of Drosophila adult central brain neurons and glia. By employing an ingenious permanent labeling technique, they trace the progeny of T2 neuroblasts, which play a key role in the formation of the central complex. This transcriptomic dataset is poised to become a valuable resource for future research on neurogenesis, neuron morphology, and behavior.

The authors further delve into this dataset with several analyses, including the characterization of neurotransmitter expression profiles in T2-derived neurons. While some of the bioinformatic analyses are preliminary, they would benefit from additional experimental validation in future studies.

Comments on revisions:

We appreciate the authors' efforts to address some of the comments. While these revisions have improved the clarity of certain sections, some of the larger concerns remain unaddressed. Specifically, the manuscript still lacks the additional analyses that would allow for more specific conclusions, rather than the general observations currently presented. Although the revisions have certainly made the text clearer, the core issue of needing more detailed analysis to draw more concrete conclusions still stands.

Reviewer #2 (Public review):

Summary:

The authors performed a series of population genetic analyses in Lantana camara using 19,008 genome-wide SNPs data from 359 individuals in India. They found a clear population structure that did not show a geographical pattern, and that flower color was rather associated with population structure. Excess of homozygosity indicates a high selfing rate, which may lead to fixation of alleles in local populations and explain the presence of population structure without a clear geographic pattern. The authors also performed a forward simulation analysis, theoretically confirming that selfing promotes fixation of alleles (higher Fst) and reduction in genetic diversity (lower heterozygosity).

Strengths:

Biological invasion is a critical driver of biodiversity loss, and it is important to understand how invasive species adapt to novel environments despite limited genetic diversity (genetic paradox of biological invasion). Lantana camara is one of the hundred most invasive species in the world (IUCN 2000), and the authors collected 359 plants from a wide geographical range in India, where L. camara has invaded. The scale of the dataset and the importance of the target species are the strengths of the present study.

Weaknesses:

One of the most critical weaknesses of this study would be that the output modelling analysis is largely qualitative, which cannot be directly comparable to the empirical data. The main findings of the SLiM-based simulation were that selfing promotes the fixation of alleles and the reduction of genetic diversity. These are theoretically well-reported knowledge, and such findings themselves are not novel, although it may have become interesting these findings are quantitatively integrated with their empirical findings in the studied species. In that sense, a coalescent-based analysis such as an Approximate Bayesian Computation method (e.g. DIY-ABC) utilizing their SNPs data would be more interesting. For example, by ABC-based methods, authors can infer the split time between subpopulations identified in this study. If such split time is older than the recorded invasion date, the result supports the scenario that multiple introductions may have contributed to the population structure of this species. In the current form of the manuscript, multiple introductions were implicated but not formally tested.

I also have several concerns regarding the authors' population genetic analyses. First, the authors removed SNPs that were not in Hardy-Weinberg equilibrium (HWE), but the studied populations would not satisfy the assumption of HWE, i.e., random mating, because of a high level of inbreeding. Thus, the first screening of the SNPs would be biased strongly, which may have led to spurious outputs in a series of downstream analyses. Second, in the genetic simulation, it is not clear how a set of parameters such as mutation rate, recombination rate, and growth rate were determined and how they are appropriate. Importantly, while authors assume the selfing rate in the simulation, selfing can also strongly influence the effective mutation rate (e.g. Nordborg & Donnelly 1997 Genetics, Nordborg 2000 Genetics). It is not clear how this effect is incorporated in the simulation. Third, while the authors argue the association between flower color and population structure, their statistical associations were not formally tested. Also, it is not mentioned how flower color polymorphisms are defined. Could it be possible to distinguish many flower color morphs shown in Figure 1b objectively? I am concerned particularly because the authors also mentioned that flower color may change temporally and that a single inflorescence can have flowers of different colors (L160).

Reviewer #3 (Public review):

Summary:

The authors utilized ChIP-seq on strains containing tagged transcription factor (TF)-overexpression plasmids to identify binding sites for 172 transcription factors in P. aeruginosa. High-quality binding site data provides a rich resource for understanding regulation in this critical pathogen. These TFs were selected to fill gaps in prior studies measuring TF binding sites in P. aeruginosa. The authors further perform a structured analysis of the resulting transcriptional regulatory network, focusing on regulators of virulence and metabolism, in addition to performing a pangenomic analysis of the TFs. The resulting dataset has been made available through an online database. While the implemented approach to determining functional TF binding sites has limitations, the resulting dataset still has substantial value to P. aeruginosa research.

Strengths:

The generated TF binding site database fills an important gap in regulatory data in the key pathogen P. aeruginosa. Key analyses of this dataset presented include an analysis of TF interactions and regulators of virulence and metabolism, which should provide important context for future studies into these processes. The online database containing this data is well organized and easy to access. As a data resource, this work should be of significant value to the infectious disease community.

Weaknesses:

Drawbacks of the study include 1) challenges interpreting binding site data obtained from TF overexpression due to unknown activity state of the TFs on the measured conditions, 2) limited practical value of the presented TRN topological analysis, and 3) lack of independent experimental validation of the proposed master regulators of virulence and metabolism.

Reviewer #2 (Public review):

Summary:

Earlier behavioral data in the budgerigar have suggested frequency selectivity that was different from that in many other avian species, showing particularly good selectivity at around 3-4 kHz. It was unknown whether this unusual selectivity was determined in the inner ear, or whether it was a more central adaptation. The results using direct auditory-nerve tuning curves and less invasive stimulus-frequency otoacoustic emissions, suggest fairly normal-looking cochlear tuning in the budgerigar, implying that any behavioral/perceptual differences in frequency selectivity are likely more central in original.

Strengths:

- The study presents novel data in budgerigar, comparing the bandwidths of auditory-nerve tuning curves with the latencies of stimulus-frequency otoacoustic emissions (SFOAEs), which are thought to reflect the sharpness of cochlear tuning.<br /> - Using a conversion factor taken from previous data in the chicken to avoid circularity of reasoning, the study shows quite good correspondence between the non-invasive estimates obtained from SFOAEs and the tuning obtained from auditory-nerve fibers. Similarity between budgerigar and chicken are harder to ascertain with the way the data are presented.

Weaknesses:

- The comparison of SFOAEs and auditory-nerve tuning curves in the most interesting regions (beyond 3.5 kHz, where some perceptual anomalies seem to occur in some previous data), relies on an extrapolation of the data from the chicken.<br /> - No new behavioral data are presented, so the comparisons made in the paper are between studies separated by decades. None of the behavioral studies cited used the more current techniques that have been claimed to provide a behavioral estimate of cochlear tuning.

Reviewer #3 (Public review):

In this study, the authors employ both computational and experimental methods to reveal functional conservation of RIP family kinases and associated proteins in animals, with particular focus on mammals and other major groups of vertebrates. The bionformatic part of the work involves genomic data from diverse animal groups, providing insightful data on loss and duplications patterns for RIP and other necroptosis-related genes, and positive selection signals for RIPK1/3 genes in certain mammalian clades. These findings are then extensively used for selecting species and RHIM tetrad candidates for further experiments, in which the authors demonstrate different modes of functional conservation for RIPK proteins in necroptosis and NF-kB signaling across vertebrate species.

As an only major drawback, I would mention several important findings which the authors make in the course of their research but do not pursue further in the experimental part of the paper. These include:

• An additional copy for RIPK2 (RIPK2B) found in monotremes and non-mammalian vertebrates and its functions;<br /> • The entire diversity of RHIM functional tetrad variants; of particular interest here are IQFG and IQLG tetrads specific for bats, which are known to harbor human-affecting viruses and were demonstrated to have their RIPK1/3 genes under positive selection in this study;<br /> • Functions and involvement of RIPK3 protein in NF-kB pathway in lampreys;<br /> • The mode of NF-kB activation in non-mammalian species retaining ZBP1 copies.

Further elucidation of some or all of these points in the experimental part would facilitate conceptualizing the paper's numerous findings, which otherwise might appear insufficiently scrutinized. On the other hand, I agree that at least some of them require separate studies to be elucidated in. Given the importance of the results presented in this paper, I believe these points will be further addressed in future works.

Reviewer #2 (Public review):

Summary:

The revised manuscript by Zhao and colleagues presents a novel and compelling investigation into the p53 isoforms, Δ133p53 and Δ160p53, which are implicated in aggressive cancer phenotypes. The primary goal of this study was to elucidate how these isoforms exert a dominant-negative impact on the activity of full-length p53 (FLp53). The authors demonstrate that the Δ133p53 and Δ160p53 isoforms display impaired binding to p53-regulated promoters. Their findings suggest that the dominant-negative effects observed are primarily due to the co-aggregation of FLp53 with Δ133p53 and Δ160p53.

Overall, the study is innovative, thoroughly executed, and supported by robust data analysis. The authors have effectively addressed the reviewers' criticisms and incorporated their suggestions in this revised manuscript.

Significance:

The manuscript by Zhao and colleagues presents a novel and compelling study on the p53 isoforms, Δ133p53 and Δ160p53, which are associated with aggressive cancer types. The main objective of the study was to understand how these isoforms exert a dominant negative effect on full-length p53 (FLp53). The authors discovered that the Δ133p53 and Δ160p53 proteins exhibit impaired binding to p53-regulated promoters. The data suggest that the predominant mechanism driving the dominant-negative effect is the co-aggregation of FLp53 with Δ133p53 and Δ160p53.

Reviewer #2 (Public review):

Summary:

Prével et al. present an in vivo study in which they reveal an interesting aspect of β-glucan, a known inducer of enhanced immune responses termed trained immunity in sterile inflammation. The authors can show that β-glucan's can reprogram alveolar macrophages (AMs) in the lungs through neutrophils and IFNγ signaling and independent of Dectin1. This reprogramming occurs at both transcriptional and metabolic levels. After β-glucan training, LPS induced sterile inflammation exacerbated acute lung injury via enhanced immunopathology. These findings highlight a new aspect of β-glucan's role in trained immunity and its potential detrimental effects when enhanced pathogen clearance is not required.

Strengths:

- This manuscript is well-written and effectively conveys its message.

- The authors provide important evidence that β-glucan training is not solely beneficial but depending on the context can also enhance immunopathology. This will be important to the field for two reasons. It shows again that trained immunity can also be harmful. Jentho et al. 2021 had already provided further evidence for this aspect. And it highlights anew that LPS application is an insufficient infection model.

Original weaknesses noted:

- Only a little physiological data from the in vivo models is provided.

- Effects in histology appear to be rather weak.

Comments on latest version:

The authors have revised the new version according to my suggestions or responded in a sufficient manner to my requests, with one exception. I recommend to rename TNF as explained by Grimstad in JAMA Dermatol. 2016;152(5):557.

Reviewer #2 (Public review):

Summary:

Kunkel et al aim to answer a fundamental question: Do placebo and nocebo effects differ in magnitude or longevity? To address this question, they used a powerful within-participants design, with a very large sample size (n=104), in which they compared placebo and nocebo effects - within the same individuals - across verbal expectations, conditioning, testing phase, and a 1-week follow-up. With elegant analyses, they establish that different mechanisms underlie the learning of placebo vs nocebo effects, with the latter being acquired faster and extinguished slower. This is an important finding for both the basic understanding of learning mechanisms in humans and for potential clinical applications to improve human health.

Strengths:

Beyond the above - the paper is well-written and very clear. It lays out nicely the need for the current investigation and what implications it holds. The design is elegant, and the analyses are rich, thoughtful, and interesting. The sample size is large which is highly appreciated, considering the longitudinal, in-lab study design. The question is super important and well-investigated, and the entire manuscript is very thoughtful with analyses closely examining the underlying mechanisms of placebo versus nocebo effects.

Weaknesses:

There were two highly addressable weaknesses in my opinion:

(1) I could not find the preregistration - this is crucial to verify what analyses the authors have committed to prior to writing the manuscript. Please provide a link leading directly to the preregistration - searching for the specified number in the suggested website yielded no results.

(2) There is a recurring issue which is easy to address: because the Methods are located after the Results, many of the constructs used, analyses conducted, and even the main placebo and nocebo inductions are unclear, making it hard to appreciate the results in full. I recommend finding a way to detail at the beginning of the results section how placebo and nocebo effects have been induced. While my background means I am familiar with these methods, other readers will lack that knowledge. Even a short paragraph or a figure (like Figure 4) could help clarify the results substantially. For example, a significant portion of the results is devoted to the conditioning part of the experiment, while it is unknown which part was involved (e.g., were temperatures lowered/increased in all trials or only in the beginning).

Reviewer #2 (Public review):

Summary:

In this work, Monroe JG and colleagues show a compelling case of convergent evolution in the fusion between an important mismatch repair protein (MSH6) and histone reader domains across the tree of life. These fused MSH6 readers have been shown to be important for the recruitment of MSH6 to exon-rich genome locations, therefore improving the efficiency of reducing mutation rates in coding regions.

Comparative genomic analyses here performed revealed independent instances of MSH6 fusion with histone readers in plants and metazoa with several instances of putative loss (or gain) across the phylogeny. The work also unveiled instances of MSH6 fusion putatively interesting domains in fungi which might be worth exploring in the future.

The authors also show potential signatures of purifying selection in functional amino acids MSH6 histone readers.

Overall the approach is adequate for the questions proposed to be answered, the analyses are rigorous and support the authors' claims.

DNA repair genes are essential to maintain genome stability and fidelity, and alterations in these pathways have been associated with hypermutation phenotypes in the context for instance of cancer in humans, with sometimes implications in treatment resistance. This is an important work that contributes to our understanding of the evolutionary consequences of the evolution of epigenome-targeted DNA repair.

Strengths:

The methods used are adequate for the questions and support the results. The search for MSH6 fusions was rigorous and conservative, which strengthens the significance of the claims on the evolutionary history of these fusion events.

Weaknesses:

I did not identify any major weaknesses, but please see my suggestions/recommendations.

Reviewer #2 (Public review):

Summary:

The authors used a visual flash discrimination task in which two flashes are presented one after another with different inter-stimulus intervals. Participants either perceive one flash or two flashes. The authors show that the simultaneous presence of an auditory input extends the temporal window of integration, meaning that two flashes presented shortly after one another are more likely to be perceived as a single flash. Auditory inputs are accompanied by a reduction in alpha frequency over visual areas. Prestimulus alpha frequency predicts perceptual outcomes in the absence of auditory stimuli, whereas prestimulus alpha phase becomes the dominant predictor when auditory input is present. A computational model based on phase-resetting theory supports these findings. Additionally, a transcranial stimulation experiment confirms the causal role of alpha frequency in unimodal visual perception but not in cross-modal contexts.

Strengths:

The authors elegantly combined several approaches-from behavior to computational modeling and EEG-to provide a comprehensive overview of the mechanisms involved in visual integration in the presence or absence of auditory input. The methods used are state-of-the-art, and the authors attempted to address possible pitfalls.

Weaknesses:

The use of Bayesian statistics could further strengthen the paper, especially given that a few p-values are close to the significance threshold (lines 162 & 258), but they are interpreted differently in different cases (absence of effect vs. trend).

Overall, these results provide new insights into the role of alpha oscillations in visual processing and offer an interesting perspective on the current debate regarding the roles of alpha phase and frequency in visual perception. More generally, they contribute to our understanding of the neural dynamics of multisensory integration.