Reviewer #1 (Public review):

Summary:

The authors present results and analysis of an experiment studying the genetic architecture of phenology in two geographically and genetically distinct populations of switchgrass when grown in 8 common gardens spanning a wide range of latitudes. They focused primarily on two measures of phenology - the green-up date in the spring, and the date of flowering. They observed generally positive correlations of flowering date across the latitudinal gradient, but negative correlations between northern and southern (i.e. Texas) green-up dates. They use GWAS and multivariate meta-analysis methods to identify and study candidate genetic loci controlling these traits and how their effect sizes vary across these gardens. They conclude that much of the genetic architecture is garden-specific, but find some evidence for photoperiod and rainfall effects on the locus effect sizes.

Strengths:

The strengths of the study are in the large scale and quality of the field trials, the observation of negative correlations among genotypes across the latitudinal gradient, and the importance of the central questions: Can we predict how genetic architecture will change when populations are moved to new environments? Can we breed for more/less sensitivity to environmental cues?

Weaknesses:

I have tried hard to understand the concept of the GxWeather analysis presented here, but still do not see how it tests for interactions between weather and genetic effects on phenology. I may just not understand it correctly, but if so, then I think more clarity in the logical model would help - maybe a figure explaining how this approach can detect genotype-weather interactions. Also, since this is a proposal for a new approach to detecting gene-environment effects, simulations would be useful to show power and false positive rates, or other ways of validating the results. The QTL validation provided is not very convincing because the same trials and the same ways of calculating weather values are used again, so it's not really independent validation, plus the QTL intervals are so large overlap between QTL and GWAS is not very strong evidence.

The term "GxWeather" is never directly defined, but based on its pairing with "GxE" on page 5, I assumed it means an interaction between genotypes (either plant lines or genotypes at SNPs) and weather variables, such that different genotypes alter phenology differently as a response to a specific change in weather. For example, some genotypes might initiate green-up once daylengths reach 12 hours, but others require 14 hours. Alternatively (equivalently), an SNP might have an effect on greenup at 12 hours (among plants that are otherwise physiologically ready to trigger greenup on March 21, only those with a genotype trigger), while no effect on greenup with daylengths of 14 hours (e.g., if plants aren't physiologically ready to greenup until June when daylengths are beyond 14 hours, both aa and AA genotypes will greenup at the same time, assuming this locus doesn't affect physiological maturity).

Either way, GxE and (I assume) GxWeather are typically tested in one of two ways. Either genotype effects are compared among environments (which differ in their mean value for weather variables) and GxWeather would be inferred if environments with similar weather have similar genotype effects. Or a model is fit with an environmental (maybe weather?) variable as a covariate and the genotype:environment interaction is measured as a change of slope between genotypes. Basically, the former uses effect size estimates across environments that differ in mean for weather, while the latter uses variation in weather within an experiment to find GxWeather effects.

However, the analytical approach here seems to combine these in a non-intuitive way and I don't think it can discover the desired patterns. As I understand from the methods, weather-related variables are first extracted for each genotype in each trial based on their green-up or flowering date, so within each trial each genotype "sees" a different value for this weather variable. For example, "daylength 14 days before green-up" is used as a weather variable. The correlation between these extracted genotype-specific weather variables across the 8 trials is then measured and used as a candidate mixture component for the among-trial covariance in mash. The weight assigned to these weather-related covariance matrices is then interpreted as evidence of genotype-by-weather interactions. However, the correlation among genotypes between these weather variables does not measure the similarity in the weather itself across trials. Daylengths at green-up are very different in MO than SD, but the correlation in this variable among genotypes is high. Basically, the correlation/covariance statistic is mean-centered in each trial, so it loses information about the mean differences among trials. Instead, the covariance statistic focuses on the within-trial variation in weather. But the SNP effects are not estimated using this within-trial variation, they're main effects of the SNP averaged over the within-trial weather variation. Thus it is not clear to me that the interpretation of these mash weights is valid. I could see mash used to compare GxWeather effects modeled in each trial (using the 2nd GxE approach above), but that would be a different analysis. As is, mash is used to compare SNP main effects across trials, so it seems to me this comparison should be based on the average weather differences among trials.

A further issue with this analysis is that the weather variables don't take into account the sequence of weather events. If one genotype flowers after the 1st rain event and the second flowers after the 2nd rain event, they can get the same value for the cumulative rainfall 7d variable, but the lack of response after the 1st rain event is the key diagnostic for GxWeather. There's also the issue of circularity. Since weather values are defined based on observed phenology dates, they're effectively caused by the phenology dates. So then asking if they are associated with phenology is a bit circular. Also, it takes a couple of weeks after flowering is triggered developmentally before flowers open, so the < 2-week lags don't really make developmental sense.

Thus, I don't think this sentence in the abstract is a valid interpretation of the analysis: "in the Gulf subpopulation, 65% of genetic effects on the timing of vegetative growth covary with day length 14 days prior to green-up date, and 33% of genetic effects on the timing of flowering covary with cumulative rainfall in the week prior to flowering". There's nothing in this analysis that compares the genetic effects under 12h days to genetic effects under 14h days (as an example), or genetic effects with no rainfall prior to flowering to genetic effects with high rainfall prior to flowering. I think the only valid conclusion is: "65% of SNPs for green-up have a GxE pattern that mirrors the similarity in relationships between green-up and day length among trials." However I don't know how to interpret that statement in terms of the overall goals of the paper.

Next, I am confused about the framing in the abstract and the introduction of the GxE within and between subpopulations. The statement: "the key expectation that different genetic subpopulations, and even different genomic regions, have likely evolved distinct patterns of GxE" needs justification or clarification. The response to an environmental factor (ie plasticity) is a trait that can evolve between populations. This happens through the changing frequencies of alleles that cause different responses. But this doesn't necessarily mean that patterns of GxE are changing. GxE is the variance in plasticity. When traits are polygenic, population means can change a lot with little change in variance within each population. Most local adaptation literature is focused on changes in mean trait values or mean plasticities between populations, not changes in the variance of trait values or plasticities within populations. Focusing on the goal of this paper, differences in environmental or weather responses between the populations are interesting (Figure 1). However the comparisons of GxE between populations and with the combined population are hard to interpret. GxE within a population means that that population is not fixed for this component of plasticity, meaning that it likely hasn't been strongly locally selected. Doesn't this mean that in the context of comparing the two populations, loci with GxE within populations are less interesting than loci fixed for different values between populations? Also, if there is GxE in the Gulf population, by definition it is also present in the "Both" population. Not finding it there is just a power issue. If individuals in the two subpopulations never cross, the variance across the "Both" population isn't relevant in nature, it's an artificial construct of this experimental design. I wonder if there is confusion about the term "genetic" in GxE and as used in the first paragraph of the intro ("Genetic responses" and "Genetic sensitivity"). These sentences would be most clear if the "genetic" term referred to the mechanistic actions of gene products. But the rest of the paper is about genetic variation, ie the different effects of different alleles at a locus. I don't think this latter definition is what these first uses intend, which is confusing.

Note that the cited paper (26) is not relevant to this discussion about GxE patterns. This paper discusses the precision of estimating sub-group-specific genetic effects. With respect to the current paper, reference 26 shows that you might get more accurate measures of the SNP effects in the Gulf population using the full "Both" population dataset because i) the sample size is larger, and ii) as long as the true effects are not that different between populations. That paper is not focused on whether effect size variation is caused by evolution but on the technical question of whether GxG or GxE impacts the precision of within-group effect size estimates. The implication of paper 26 is that comparing SNP effects estimated in the "Both" population among gardens might be more powerful for detecting GxE than using only Gulf samples, even if there is some difference in SNP effects among populations. But if there magnitudes (or directions) of SNP effects change a lot among populations (ie not just changes in allele frequency), then modeling the populations separately will be more accurate.

Reviewer #1 (Public review):

Summary

This work performed Raman spectral microscopy at the single-cell level for 15 different culture conditions in E. coli. The Raman signature is systematically analyzed and compared with the proteome dataset of the same culture conditions. With a linear model, the authors revealed correspondence between Raman pattern and proteome expression stoichiometry indicating that spectrometry could be used for inferring proteome composition in the future. With both Raman spectra and proteome datasets, the authors categorized co-expressed genes and illustrated how proteome stoichiometry is regulated among different culture conditions. Co-expressed gene clusters were investigated and identified as homeostasis core, carbon-source dependent, and stationary phase-dependent genes. Overall, the authors demonstrate a strong and solid data analysis scheme for the joint analysis of Raman and proteome datasets.

Strengths and major contributions

(1) Experimentally, the authors contributed Raman datasets of E. coli with various growth conditions.

(2) In data analysis, the authors developed a scheme to compare proteome and Ramen datasets. Protein co-expression clusters were identified, and their biological meaning was investigated.

Weaknesses

The experimental measurements of Ramen microscopy were conducted at the single-cell level; however, the analysis was performed by averaging across the cells. The author did not discuss if Ramen microscopy can used to detect cell-to-cell variability under the same condition.

Discussion and impact on the field

Ramen signature contains both proteomic and metabolomic information and is an orthogonal method to infer the composition of biomolecules. It has the advantage that single-cell level data could be acquired and both in vivo and in vitro data can be compared. This work is a strong initiative for introducing the powerful technique to systems biology and providing a rigorous pipeline for future data analysis.

https://www.reddit.com/r/typewriters/comments/1jhle1t/typewriter_in_videogame/

Reviewer #1 (Public review):

Summary:

This work shows that a specific adenosine deaminase protein in Dictyostelium generates the ammonia that is required for tip formation during Dictyostelium development. Cells with an insertion in the ADGF gene aggregate but do not form tips. A remarkable result, shown in several different ways, is that the ADGF mutant can be rescued by exposing the mutant to ammonia gas. The authors also describe other phenotypes of the ADGF mutant such as increased mound size, altered cAMP signaling, and abnormal cell type differentiation. It appears that the ADGF mutant has defects in the expression of a large number of genes, resulting in not only the tip defect but also the mound size, cAMP signaling, and differentiation phenotypes.

Strengths:

The data and statistics are excellent.

Weaknesses:

The key weakness is understanding why the cells bother to use a diffusible gas like ammonia as a signal to form a tip and continue development. The rescue of the mutant by adding ammonia gas to the entire culture indicates that ammonia conveys no positional information within the mound. By the time the cells have formed a mound, the cells have been starving for several hours, and desperately need to form a fruiting body to disperse some of themselves as spores, and thus need to form a tip no matter what. One can envision that the local ammonia concentration is possibly informing the mound that some minimal number of cells are present (assuming that the ammonia concentration is proportional to the number of cells), but probably even a minuscule fruiting body would be preferable to the cells compared to a mound. This latter idea could be easily explored by examining the fate of the ADGF cells in the mound - do they all form spores? Do some form spores? Or perhaps the ADGF is secreted by only one cell type, and the resulting ammonia tells the mound that for some reason that cell type is not present in the mound, allowing some of the cells to transdifferentiate into the needed cell type. Thus elucidating if all or some cells produce ADGF would greatly strengthen this puzzling story.

Joint Public Review:

Summary:

In this manuscript, the authors investigate how different domains of the presynaptic protein UNC-13 regulate synaptic vesicle release in the nematode C. elegans. By generating numerous point mutations and domain deletions, they propose that two membrane-binding domains (C1 and C2B) can exhibit "mutual inhibition," enabling either domain to enhance or restrain transmission depending on its conformation. The authors also explore additional N-terminal regions, suggesting that these domains may modulate both miniature and evoked synaptic responses. From their electrophysiological data, they present a "functional switch" model in which UNC-13 potentially toggles between a basal state and a gain-of-function state, though the physiological basis for this switch remains partly speculative.

Strengths:

(1) The authors conduct a thorough exploration of how mutations in the C1, C2B, and other regulatory domains affect synaptic transmission. This includes single, double, and triple mutations, as well as domain truncations, yielding a large, informative dataset.

(2) The study includes systematically measure both spontaneous and evoked synaptic currents at neuromuscular junctions, under various experimental conditions (e.g., different Ca²⁺ levels), which strengthens the reliability of their functional conclusions.

(3) Findings that different domain disruptions produce distinct effects on mEPSCs, mIPSCs, and evoked EPSCs suggest UNC-13 may adopt an elevated functional state to regulate synaptic transmission.

Reviewer #2 (Public review):

The authors have constructively responded to previous referee comments and I believe that the manuscript is a useful addition to the literature. I particularly appreciate the quantitative approach to social behavior, but have two cautionary comments.

(1) Conceptually it is important to further justify why this particular maximum entropy model is appropriate. Maximum entropy models have been applied across a dizzying array of biological systems, including genes, neurons, the immune system, as well as animal behavior, so would seem quite beneficial to explain the particular benefits here, for mouse social behavior as coarse-grained through the eco-hab chamber occupancy. This would be an excellent chance to amplify what the models can offer for biological understanding, particularly in the realm of social behavior

(2) Maximum entropy models of even intermediate size systems involve a large number of parameters. The authors are transparent about that limitation here, but I still worry that the conclusion of the sufficiency of pairwise interactions is simply not general, and this may also relate to the differences from previous work. If, as the authors suggest in the discussion, this difference is one of a choice of variables, then that point could be emphasized. The suggestion of a follow up study with a smaller number of mice is excellent.

Reviewer #2 (Public review):

Summary:

The authors present a new model for animal pose estimation. The core feature they highlight is the model's stability compared to existing models in terms of keypoint drift. The authors test this model across a range of new and existing datasets. The authors also test the model with two mice in the same arena. For the single animal datasets the authors show a decrease in sudden jumps in keypoint detection and the number of undetected keypoints compared with DeepLabCut and SLEAP. Overall average accuracy, as measured by root mean squared error, generally shows generally similar but sometimes superior performance to DeepLabCut and better performance compared to SLEAP. The authors confusingly don't quantify the performance of pose estimation in the multi (two) animal case instead focusing on detecting individual identity. This multi-animal model is not compared with the model performance of the multi-animal mode of DeepLabCut or SLEAP.

Strengths:

The major strength of the paper is successfully demonstrating a model that is less likely to have incorrect large keypoint jumps compared to existing methods. As noted in the paper, this should lead to easier-to-interpret descriptions of pose and behavior to use in the context of a range of biological experimental workflows.

Weaknesses:

There are two main types of weaknesses in this paper. The first is a tendency to make unsubstantiated claims that suggest either model performance that is untested or misrepresents the presented data, or suggest excessively large gaps in current SOTA capabilities. One obvious example is in the abstract when the authors state ADPT "significantly outperforms the existing deep-learning methods, such as DeepLabCut, SLEAP, and DeepPoseKit." All tests in the rest of the paper, however, only discuss performance with DeepLabCut and SLEAP, not DeepPoseKit. At this point, there are many animal pose estimation models so it's fine they didn't compare against DeepPoseKit, but they shouldn't act like they did. Similar odd presentation of results are statements like "Our method exhibited an impressive prediction speed of 90{plus minus}4 frames per second (fps), faster than DeepLabCut (44{plus minus}2 fps) and equivalent to SLEAP (106{plus minus}4 fps)." Why is 90{plus minus}4 fps considered "equivalent to SLEAP (106{plus minus}4 fps)" and not slower? I agree they are similar but they are not the same. The paper's point of view of what is "equivalent" changes when describing how "On the single-fly dataset, ADPT excelled with an average mAP of 92.83%, surpassing both DeepLabCut and SLEAP (Figure 5B)" When one looks at Figure 5B, however, ADPT and DeepLabCut look identical. Beyond this, oddly only ADPT has uncertainty bars (no mention of what uncertainty is being quantified) and in fact, the bars overlap with the values corresponding to SLEAP and DeepPoseKit. In terms of making claims that seem to stretch the gaps in the current state of the field, the paper makes some seemingly odd and uncited statements like "Concerns about the safety of deep learning have largely limited the application of deep learning-based tools in behavioral analysis and slowed down the development of ethology" and "So far, deep learning pose estimation has not achieved the reliability of classical kinematic gait analysis" without specifying which classical gait analysis is being referred to. Certainly, existing tools like DeepLabCut and SLEAP are already widely cited and used for research.

The other main weakness in the paper is the validation of the multi-animal pose estimation. The core point of the paper is pose estimation and anti-drift performance and yet there is no validation of either of these things relating to multi-animal video. All that is quantified is the ability to track individual identity with a relatively limited dataset of 10 mice IDs with only two in the same arena (and see note about train and validation splits below). While individual tracking is an important task, that literature is not engaged with (i.e. papers like Walter and Couzin, eLife, 2021: https://doi.org/10.7554/eLife.64000) and the results in this paper aren't novel compared to that field's state of the art. On the other hand, while multi-animal pose estimation is also an important problem the paper doesn't engage with those results either. The two methods already used for comparison in the paper, SLEAP and DeepPoseKit, already have multi-animal modes and multi-animal annotated datasets but none of that is tested or engaged with in the paper. The paper notes many existing approaches are two-step methods, but, for practitioners, the difference is not enough to warrant a lack of comparison. The authors state that "The evaluation of our social tracking capability was performed by visualizing the predicted video data (see supplement Videos 3 and 4)." While the authors report success maintaining mouse ID, when one actually watches the key points in the video of the two mice (only a single minute was used for validation) the pose estimation is relatively poor with tails rarely being detected and many pose issues when the mice get close to each other.

Finally, particularly in the methods section, there were a number of places where what was actually done wasn't clear. For example in describing the network architecture, the authors say "Subsequently, network separately process these features in three branches, compute features at scale of one-fourth, one-eight and one-sixteenth, and generate one-eight scale features using convolution layer or deconvolution layer." Does only the one-eight branch have deconvolution or do the other branches also? Similarly, for the speed test, the authors say "Here we evaluate the inference speed of ADPT. We compared it with DeepLabCut and SLEAP on mouse videos at 1288 x 964 resolution", but in the methods section they say "The image inputs of ADPT were resized to a size that can be trained on the computer. For mouse images, it was reduced to half of the original size." Were different image sizes used for training and validation? Or Did ADPT not use 1288 x 964 resolution images as input which would obviously have major implications for the speed comparison? Similarly, for the individual ID experiments, the authors say "In this experiment, we used videos featuring different identified mice, allocating 80% of the data for model training and the remaining 20% for accuracy validation." Were frames from each video randomly assigned to the training or validation sets? Frames from the same video are very correlated (two frames could be just 1/30th of a second different from each other), and so if training and validation frames are interspersed with each other validation performance doesn't indicate much about performance on more realistic use cases (i.e. using models trained during the first part of an experiment to maintain ids throughout the rest of it.)

Editors' note: None of the original reviewers responded to our request to re-review the manuscript. The attached assessment statement is the editor's best attempt at assessing the extent to which the authors addressed the outstanding concerns from the previous round of revisions.

Reviewer #1 (Public review):

Summary:

This study aims to uncover molecular and structural details underlying the broad substrate specificity of glycosaminoglycan lyases belonging to a specific family (PL35). They determined the crystal structures of two such enzymes, conducted in vitro enzyme activity assays, and a thorough structure-guided mutagenesis campaign to interrogate the role of specific residues. They made progress towards achieving their aims and I appreciate the attempt of the authors to address my initial comments on the paper.

Impact on the field:

I expect this work will have limited impact on the field, although it does stand on its own as a solid piece of structure-function analysis.

Strengths:

The major strengths of the study were the combination of structure and enzyme activity assays, comprehensive structural analysis, as well as a thorough structure-guided mutagenesis campaign.

Weaknesses:

(Before revision) -the authors claim to have done a ICP-MS experiment to show Mn2+ binds to their enzyme, but did not present the data. The authors could have used the anomalous scattering properties of Mn2+ at the synchrotron to determine the presence and location of this cation (i.e. fluorescence spectra, and/or anomalous data collection at the Mn2+ absorption peak).<br /> *comment after revision: I appreciate that the authors included this data now, and it looks fine.

(Before revision) -the authors have an over-reliance on molecular docking for understanding the position of substrates bound to the enzyme. The docking analysis performed was cursory at best; Autodock Vina is a fine program but more rigorous software could have been chosen, as well we molecular dynamics simulations. As well the authors do not use any substrate/product-bound structures from the broader PL enzyme family to guide the placement of the substrates in the GAGases, and interpret the molecular docking models.<br /> *comment after revision: the authors used another docking program, which is fine, but did not do any MD analysis or comment on why not. Also maybe it is just me but I still do not see a figure explicitly showing an overlay/superposition of the docking results with crystal structures of similar enzymes with similar ligands. The authors do have a statement in this regard but I believe a figure (e.g. an additional panel on S2) would be very helpful to the reader.

(Before revision)-the conclusion that the structures of GAGase II and VII are most similar to the structures of alginate lyases (Table 2 data), and the authors' reliance on DALI, are both questioned. DALI uses a global alignment algorithm, which when used for multi-domain enzymes such as these tends to result in sub-optimal alignment of active site residues, particularly if the active site is formed between the two domains as is the case here. The authors should evaluate local alignment methods focused on optimization of the superposition of a single domain; these methods may result in a more appropriate alignment of the active site residues, and different alignment statistics. This may influence the overall conclusion of the evolutionary history of these PL35 enzymes.<br /> *comment after revision: I'm not sure the authors understood my suggestion as the reply reiterates the original conclusions. I suggest local structural alignment of *only* the toroid and antiparallel β-sheet domains, not global alignment of both domains, as this would improve the accuracy of the structural similarity conclusions.

(Before revision)-the data on the GAGase III residue His188 is not well interpreted; substitution of this residue clearly impacts HA and HS hydrolysis as well. The data on the impact on alginate hydrolysis is weak, which could be due to the fact that the WT enzyme has poor activity against alginate to start with.<br /> *comment after revision: I appreciate that the authors used higher amounts of H188A variants and still do not see activity on alginate, which strengthens the conclusions regarding this substrate. However this variant also has decreased activity against HS (Figure 5C) and thus H188 appears to be important for more substrates than just alginate. The discussion section should be updated accordingly.

(Before revision)-the authors did not use the words "homology", "homologous", or "homolog" correctly (these terms mean the subjects have a known evolutionary relationship, which may or may not be known in the contexts the authors used these targets); the words "similarity" and "similar" are recommended to be used instead.<br /> *comment after revision: I thank the authors for addressing this.

(Before revision)-the authors discuss a "shorter" cavity in GAGases, which does not make sense, and is not supported by any figure or analysis. I recommend a figure with a surface representation of the various enzymes of interest, with dimensions of the cavity labeled (as a supplemental figure). The authors also do not specifically define what subsites are in the context of this family of enzymes, nor do they specifically label or indicate the location of the subsites on the figures of the GAGase II and IV enzyme structures.<br /> *comment after revision: I thank the authors for improving their figures and text description on this point.

Reviewer #1 (Public review):

Summary:

The manuscript under review investigates the role of periosteal stem cells (P-SSC) in bone marrow regeneration using a whole bone subcutaneous transplantation model. While the model is somewhat artificial, the findings were interesting, suggesting the migration of periosteal stem cells into the bone marrow and their potential to become bone marrow stromal cells. This indicates a significant plasticity of P-SSC consistent with previous reports using fracture models (Cell Stem Cell 29:1547, Dev Cell 59:1192).

Major comments from previous round of review:

(1) The authors assert that the periosteal layer was completely removed in their model, which is crucial for their conclusions. To substantiate this claim, it is recommended that the authors provide evidence of the successful removal of the entire periosteal stem cell (P-SSC) population. A colony-forming assay, with and without periosteal removal, could serve as a suitable method to demonstrate this.

(2) The observation that P-SSCs do not express Kitl or Cxcl12, while their bone marrow stromal cell (BM-MSC) derivatives do, is a key finding. To strengthen this conclusion, the authors are encouraged to repeat the experiment using Cxcl12 or Scf reporter alleles. Immunofluorescence staining that confirms the migration of periosteal cells and their transformation into Cxcl12- or Scf-reporter-positive cells would significantly enhance the paper's key conclusion.

(3) On page 8, line 20, the authors' statement regarding the detection of Periostin+ cells outside the periosteum layer could be misinterpreted due to the use of the periostin antibody. Given that periostin is an extracellular matrix protein, the staining may not accurately represent Periostin-expressing cells but rather the presence of periostin in the extracellular matrix. The authors should revise this section for greater precision.

Comments on revised version:

My comments from the previous round of review have mostly been addressed.

Reviewer #1 (Public review):

In this study, Tiang et al. explore the role of ubiquitination of non-structural protein 16 (nsp16) in the SARS-CoV-2 life cycle. nsp16, in conjunction with nsp10, performs the final step of viral mRNA capping through its 2'-O-methylase activity. This modification allows the virus to evade host immune responses and protects its mRNA from degradation. The authors demonstrate that nsp16 undergoes ubiquitination and subsequent degradation by the host E3 ubiquitin ligases UBR5 and MARCHF7 via the ubiquitin-proteasome system (UPS). Specifically, UBR5 and MARCHF7 mediate nsp16 degradation through K48- and K27-linked ubiquitination, respectively. Notably, degradation of nsp16 by either UBR5 or MARCHF7 operates independently, with both mechanisms effectively inhibiting SARS-CoV-2 replication in vitro and in vivo. Furthermore, UBR5 and MARCHF7 exhibit broad-spectrum antiviral activity by targeting nsp16 variants from various SARS-CoV-2 strains. This research advances our understanding of how nsp16 ubiquitination impacts viral replication and highlights potential targets for developing broadly effective antiviral therapies.

Strengths:

The proposed study is of significant interest to the virology community because it aims to elucidate the biological role of ubiquitination in coronavirus proteins and its impact on the viral life cycle. Understanding these mechanisms will address broadly applicable questions about coronavirus biology and enhance our overall knowledge of ubiquitination's diverse functions in cell biology. Employing in vivo studies is a strength.

Weaknesses:

Minor comments:<br /> Figure 5A- The authors should ensure that the figure is properly labeled to clearly distinguish between the IP (Immunoprecipitation) panel and the input panel.

Reviewer #1 (Public review):

Summary:

The authors investigated causal inference in the visual domain through a set of carefully designed experiments, and sound statistical analysis. They suggest the early visual system has a crucial contribution to computations supporting causal inference.

Strengths:

(1) I believe the authors target an important problem (causal inference) with carefully chosen tools and methods. Their analysis rightly implies the specialization of visual routines for causal inference and the crucial contribution of early visual systems to perform this computation. I believe this is a novel contribution and their data and analysis are in the right direction.<br /> (2) Authors sufficiently discuss the alternative perspective to causal inference.<br /> (3) The authors also expand the discussions beyond pure psychophysics and also include neural aspects.

Weaknesses:

I would not call them weaknesses, perhaps a different perspective:

(1) Authors arguing pro a mere bottom-up contribution of early sensory areas for causal inference. Certainly, as the authors suggested, early sensory areas have a crucial contribution, and the authors expand it to other possibilities in their discussion (but more for more complex scenario). It would say, even in simple cases, we can still consider the effect of top down processes. This particularly makes sense in light of recent studies. These studies progressively suggest perception as an active process that also weighs in strongly, the top-down cognitive contributions. For instance, the most simple cases of perception have been conceptualized along this line (Martin, Solms, and Sterzer 2021) and even some visual illusions (Safavi and Dayan 2022), and other extensions (Kay et al. 2023). Thus, I believe it would be helpful to extend the discussion on the top-down and cognitive contributions of causal inference (of course that can also be hinted at, based on recent developments). Even adaptation, which is central in this study, can be influenced by top-down factors (Keller et al. 2017).

Lastly, I hope the authors find this review helpful. I generally want to try to end all of my reviews with areas of the paper I liked because I think this should be part of the feedback. Certainly, there were many in this manuscript as well (clever questions, experimental design and statistical analysis) that I had to highlight further. I congratulate the authors again on their manuscript and hope they will find it helpful.

Bibliography

Aller, Mate, and Uta Noppeney. 2018. "To Integrate or Not to Integrate: Temporal Dynamics of Bayesian Causal Inference." Biorxiv, December, 504118. .

Cao, Yinan, Christopher Summerfield, Hame Park, Bruno Lucio Giordano, and Christoph Kayser. 2019. "Causal Inference in the Multisensory Brain." Neuron 102 (5): 1076-87.e8. .

Coen, Philip, Timothy P. H. Sit, Miles J. Wells, Matteo Carandini, and Kenneth D. Harris. 2021. "The Role of Frontal Cortex in Multisensory Decisions." Biorxiv, April. Cold Spring Harbor Laboratory, 2021.04.26.441250. .

Kay, Kendrick, Kathryn Bonnen, Rachel N. Denison, Mike J. Arcaro, and David L. Barack. 2023. "Tasks and Their Role in Visual Neuroscience." Neuron 111 (11). Elsevier: 1697-1713. .

Keller, Andreas J, Rachael Houlton, Björn M Kampa, Nicholas A Lesica, Thomas D Mrsic-Flogel, Georg B Keller, and Fritjof Helmchen. 2017. "Stimulus Relevance Modulates Contrast Adaptation in Visual Cortex." Elife 6. eLife Sciences Publications, Ltd: e21589.

Kording, K. P., U. Beierholm, W. J. Ma, S. Quartz, J. B. Tenenbaum, and L. Shams. 2007. "Causal Inference in Multisensory Perception." PloS One 2: e943. .

Martin, Joshua M., Mark Solms, and Philipp Sterzer. 2021. "Useful Misrepresentation: Perception as Embodied Proactive Inference." Trends Neurosci. 44 (8): 619-28. .

Safavi, Shervin, and Peter Dayan. 2022. "Multistability, Perceptual Value, and Internal Foraging." Neuron, August. .

Shams, L. 2012. "Early Integration and Bayesian Causal Inference in Multisensory Perception." In The Neural Bases of Multisensory Processes, edited by M. M. Murray and M. T. Wallace. Frontiers in Neuroscience. Boca Raton (FL).

Shams, Ladan, and Ulrik Beierholm. 2022. "Bayesian Causal Inference: A Unifying Neuroscience Theory." Neuroscience & Biobehavioral Reviews 137 (June): 104619.

Reviewer #1 (Public review):

Summary:

Machii et al. reported a possible molecular mechanism underlying the parallel evolution of lip hypertrophy in African cichlids. The multifaceted approach taken in this manuscript is highly valued, as it uses histology, proteomics, and transcriptomics to reveal how phylogenetically distinct thick-lips have evolved in parallel. Findings from histology and proteomics connected to wnt signaling through the transcriptome are very exciting.

Strengths:

There is consistency between the results and it is possible to make a strong argument from the results.

Comments on revised version:

The issues I pointed out in the previous review have been carefully answered, and all issues have been addressed. The main points of the manuscript are clear, and the conclusions are easy to understand. The enlarged lips are a notable example of convergent evolution in African cichlids.

Reviewer #1 (Public review):

Summary:

The manuscript focuses on the olfactory system of Pieris brassicae larvae and the importance of olfactory information in their interactions with the host plant Brassica oleracea and the major parasitic wasp Cotesia glomerata. The authors used CRISPR/Cas9 to knockout odorant receptor co-receptors (Orco), and conducted a comparative study on the behavior and olfactory system of the mutant and wild-type larvae. The study found that Orco-expressing olfactory sensory neurons in antennae and maxillary palps of Orco knockout (KO) larvae disappeared, and the number of glomeruli in the brain decreased, which impairs the olfactory detection and primary processing in the brain. Orco KO caterpillars show weight loss and loss of preference for optimal food plants; KO larvae also lost weight when attacked by parasitoids with the ovipositor removed, and mortality increased when attacked by untreated parasitoids. On this basis, the authors further studied the responses of caterpillars to volatiles from plants attacked by the larvae of the same species and volatiles from plants on which the caterpillars were themselves attacked by parasitic wasps. Lack of OR-mediated olfactory inputs prevents caterpillars from finding suitable food sources and from choosing spaces free of enemies.

Strengths:

The findings help to understand the important role of olfaction in caterpillar feeding and predator avoidance, highlighting the importance of odorant receptor genes in shaping ecological interactions.

Weaknesses:

There are the following major concerns:

(1) Possible non-targeted effects of Orco knockout using CRISPR/Cas9 should be analyzed and evaluated in Materials and Methods and Results.

(2) Figure 1E: Only one olfactory receptor neuron was marked in WT. There are at least three olfactory sensilla at the top of the maxillary palp. Therefore, to explain the loss of Orco-expressing neurons in the mutant (Figure 1F), a more rigorous explanation of the photo is required.

(3) In Figure 1G, H, the four glomeruli are circled by dotted lines: their corresponding relationship between the two figures needs to be further clarified.

(4) Line 130: Since the main topic in this study is the olfactory system of larvae, the experimental results of this part are all about antennal electrophysiological responses, mating frequency, and egg production of female and male adults of wild type and Orco KO mutant, it may be considered to include this part in the supplementary files. It is better to include some data about the olfactory responses of larvae.

(5) Line 166: The sentences in the text are about the choice test between " healthy plant vs. infested plant", while in Fig 3C, it is "infested plant vs. no plant". The content in the text does not match the figure.

(6) Lines 174-178: Figure 3A showed that the body weight of Orco KO larvae in the absence of parasitic wasps also decreased compared with that of WT. Therefore, in the experiments of Figure 3A and E, the difference in the body weight of Orco KO larvae in the presence or absence of parasitic wasps without ovipositors should also be compared. The current data cannot determine the reduced weight of KO mutant is due to the Orco knockout or the presence of parasitic wasps.

(7) Lines 179-181: Figure 3F shows that the survival rate of larvae of Orco KO mutant decreased in the presence of parasitic wasps, and the difference in survival rate of larvae of WT and Orco KO mutant in the absence of parasitic wasps should also be compared. The current data cannot determine whether the reduced survival of the KO mutant is due to the Orco knockout or the presence of parasitic wasps.

(8) In Figure 4B, why do the compounds tested have no volatiles derived from plants? Cruciferous plants have the well-known mustard bomb. In the behavioral experiments, the larvae responses to ITC compounds were not included, which is suggested to be explained in the discussion section.

(9) The custom-made setup and the relevant behavioral experiments in Figure 4C need to be described in detail (Line 545).

(10) Materials and Methods Line 448: 10 μL paraffin oil should be used for negative control.

Reviewer #1 (Public review):

The study introduces an open-source, cost-effective method for automating the quantification of male social behaviors in Drosophila melanogaster. It combines machine-learning-based behavioral classifiers developed using JAABA (Janelia Automatic Animal Behavior Annotator) with inexpensive hardware constructed from off-the-shelf components. This approach addresses the limitations of existing methods, which often require expensive hardware and specialized setups. The authors demonstrate that their new "DANCE" classifiers accurately identify aggression (lunges) and courtship behaviors (wing extension, following, circling, attempted copulation, and copulation), closely matching manually annotated ground-truth data. Furthermore, DANCE classifiers outperform existing rule-based methods in accuracy. Finally, the study shows that DANCE classifiers perform as well when used with low-cost experimental hardware as with standard experimental setups across multiple paradigms, including RNAi knockdown of the neuropeptide Dsk and optogenetic silencing of dopaminergic neurons.

The authors make creative use of existing resources and technology to develop an inexpensive, flexible, and robust experimental tool for the quantitative analysis of Drosophila behavior. A key strength of this work is the thorough benchmarking of both the behavioral classifiers and the experimental hardware against existing methods. In particular, the direct comparison of their low-cost experimental system with established systems across different experimental paradigms is compelling. While JAABA-based classifiers have been previously used to analyze aggression and courtship (Tao et al., J. Neurosci., 2024; Sten et al., Cell, 2023; Chiu et al., Cell, 2021; Isshi et al., eLife, 2020; Duistermars et al., Neuron, 2018), the demonstration that they work as well without expensive experimental hardware opens the door to more low-cost systems for quantitative behavior analysis.

Although the study provides a detailed evaluation of DANCE classifier performance, its conclusions would be strengthened by a more comprehensive analysis. The authors assess classifier accuracy using a bout-level comparison rather than a frame-level analysis, as employed in previous studies (Kabra et al., Nat Methods, 2013). They define a true positive as any instance where a DANCE-detected bout overlaps with a manually annotated ground-truth bout by at least one frame. This criterion may inflate true positive rates and underestimate false positives, particularly for longer-duration courtship behaviors. For example, a 15-second DANCE-classified wing extension bout that overlaps with ground truth for only one frame would still be considered a true positive. A frame-level analysis performance would help address this possibility.

In summary, this work provides a practical and accessible approach to quantifying Drosophila behavior, reducing the economic barriers to the study of the neural and molecular mechanisms underlying social behavior.

"Soil transfers naturally from a person's clothing and shoes as they move between locations"

Reviewer #1 (Public Review):

Summary:

In this manuscript, Quach et al. report a detailed investigation into the defense mechanisms of Caenorhabditis elegans in response to predatory threats from Pristionchus pacificus. Based on principles from predatory imminence and prey refuge theories, the authors delineate three defense modes (pre-encounter, post-encounter, and circa-strike) corresponding to increasing levels of threat proximity. These modes are observed in a controlled but naturalistic setup and are quantified by multiple behavioral outputs defined in time and/or space domains allowing nuanced phenotypic assays. The authors demonstrate that C. elegans displays graded defense behavioral responses toward varied lethality of threats and that only life-threatening predators trigger all three defense modes. The study also offers a narrative on the behavioral strategies and underlying molecular regulation, focusing on the roles of SEB-3 receptors and NLP-49 peptides in mediating responses in these defense modes. They found that the interplay between SEB-3 and NLP-49 peptides appears complex, as evidenced by the diverse outcomes when either or both genes are manipulated in various behavioral modes.

Strengths:

The paper presents an interesting story, with carefully designed experiments and necessary controls, and novel findings and implications about predator-induced defensive behaviors and underlying molecular regulation in this important model organism. The design of experiments and description of findings are easy to follow and well-motivated. The findings contribute to our understanding of stress response systems and offer broader implications for neuroethological studies across species.

Weaknesses:

Although overall the study is well designed and movitated, the paper could benefit from further improvements on some of the methods descriptions and experiment interpretations.

Reviewer #1 (Public review):

Summary:

This paper describes molecular dynamics simulations (MDS) of the dynamics of two T-cell receptors (TCRs) bound to the same major histocompatibility complex molecule loaded with the same peptide (pMHC). The two TCRs (A6 and B7) bind to the pMHC with similar affinity and kinetics, but employ different residue contacts. The main purpose of the study is to quantify via MDS the differences in the inter- and intra-molecular motions of these complexes, with a specific focus on what the authors describe as catch-bond behavior between the TCRs and pMHC, which could explain how T-cells can discriminate between different peptides in the presence of weak separating force.

Strengths:

The authors present extensive simulation data that indicates that, in both complexes, the number of high-occupancy inter-domain contacts initially increases with applied load, which is generally consistent with the authors' conclusion that both complexes exhibit catch-bond behavior, although to different extents. In this way, the paper expands our understanding of peptide discrimination by T-cells. The conclusions of the study are generally well supported by data. Further, the paper makes predictions about the relative strength of the catch-bond response of the two TCRs, which could be tested experimentally through protein mutagenesis and force application in Atomic Force Microscopy.

Joint public review

Summary:

The authors examine the eigenvalue spectrum of the covariance matrix of neural recordings in the whole-brain larval zebrafish during hunting and spontaneous behavior. They find that the spectrum is approximately power law, and, more importantly, exhibits scale-invariance under random subsampling of neurons. This property is not exhibited by conventional models of covariance spectra, motivating the introduction of the Euclidean random matrix model. The authors show that this tractable model captures the scale invariance they observe. They also examine the effects of subsampling based on anatomical location or functional relationships. Finally, they discuss the benefit of neural codes which can be subsampled without significant loss of information.

Strengths:

With large-scale neural recordings becoming increasingly common, neuroscientists are faced with the question: how should we analyze them? To address that question, this paper proposes the Euclidean random matrix model, which embeds neurons randomly in an abstract feature space. This model is analytically tractable and matches two nontrivial features of the covariance matrix: approximate power law scaling, and invariance under subsampling. It thus introduces an important conceptual and technical advance for understanding large-scale simultaneously recorded neural activity.

Comment:

Are there quantitative comparisons of the collapse indices for the null models in Figure 2 and the data covariance in 2F? If so, this could be potentially useful to report.

Reviewer #1 (Public review):

Based on previous publications suggesting a potential role for miR-26b in the pathogenesis of metabolic dysfunction-associated steatohepatitis (MASH), the researchers aim to clarify its function in hepatic health and explore the therapeutical potential of lipid nanoparticles (LNPs) to treat this condition. First, they employed both whole-body and myeloid cell-specific miR-26b KO mice and observed elevated hepatic steatosis features in these mice compared to WT controls when subjected to WTD. Moreover, livers from whole-body miR-26b KO mice also displayed increased levels of inflammation and fibrosis markers. Kinase activity profiling analyses revealed distinct alterations, particularly in kinases associated with inflammatory pathways, in these samples. Treatment with LNPs containing miR-26b mimics restored lipid metabolism and kinase activity in these animals. Finally, similar anti-inflammatory effects were observed in the livers of individuals with cirrhosis, whereas elevated miR-26b levels were found in the plasma of these patients in comparison with healthy control. Overall, the authors conclude that miR-26b plays a protective role in MASH and that its delivery via LNPs efficiently mitigates MASH development.

The study has some strengths, most notably, its employ of a combination of animal models, analyses of potential underlying mechanisms, as well as innovative treatment delivery methods with significant promise. However, it also presents certain weaknesses that could be improved. The precise role of miR-26b in a human context remains elusive, hindering direct translation to clinical practice.

Comments on revised version:

Some of the recommendations provided by this Reviewer in the first version of the manuscript have been successfully addressed in the revision. However, others, particularly those related to human translation, remain unresolved due to the lack of additional samples for analysis. Since the revised title now indicates that the mechanisms described were primarily observed in mice, it seems reasonable to defer addressing this issue to future studies.

Reviewer #1 (Public review):

Summary:

This paper explores how diverse forms of inhibition impact firing rates in models for cortical circuits. In particular, the paper studies how the network operating point affects the balance of direct inhibition from SOM inhibitory neurons to pyramidal cells, and disinhibition from SOM inhibitory input to PV inhibitory neurons. This is an important issue as these two inhibitory pathways have largely been studies in isolation. A combination of analytical calculations and direct numerical simulations provide convincing evidence that the interplay of these inhibitory circuits can separately control network gain and stability.

Strengths

The paper has improved in revision, and the intuitive summary statements added to the end of each results section are quite helpful. The addition of numerical simulations to extend the conclusions beyond the linear range of network behavior are also quite helpful.

Weaknesses

None

Reviewer #1 (Public review):

Summary:

In this article, the authors set out to understand how people's food decisions change when they are hungry vs. sated. To do so, they used an eye-tracking experiment where participants chose between two food options, each presented as a picture of the food plus its "Nutri-Score". In both conditions, participants fasted overnight, but in the sated condition, participants received a protein shake before making their decisions. The authors find that participants in the hungry condition were more likely to choose the tastier option. Using variants of the attentional drift diffusion model, they further find that the best fitting model has different attentional discounts on the taste and health attributes, and that the attentional discount on the health information was larger for the hungry participants.

Strengths:

The article has many strengths. It uses a food-choice paradigm that is established in neuroeconomics. The experiment uses real foods, with accurate nutrition information, and incentivized choices. The experimental manipulation is elegant in its simplicity - administering a high-calorie protein shake. It is also commendable that the study was within-participant. The experiment also includes hunger and mood ratings to confirm the effectiveness of the manipulation. The modeling work is impressive in its rigor - the authors test 8 different variants of the DDM, including recent models like the maaDDM, as well as some completely new variants (maaDDM2phi and 2phisp). The model fits decisively favor the maaDDM2phi.

Weaknesses:

While I do appreciate the within-participant design, it does raise a small concern about potential demand effects. The authors' results would have been more compelling if they had replicated when only analyzing the first session from each participant. However, the authors did demonstrate that there was no effect of order on the results, which helps to alleviate this concern.

Reviewer #1 (Public Review):

The authors recorded from multiple mossy cells (MCs) of the dentate gyrus in slices or in vivo using anesthesia. They recorded MC spontaneous activity during spontaneous sharp waves (SWs) detected in area CA3 (in vitro) or in CA1 ( in vivo). They find variability of the depolarization of MCs in response to a SW. They then used deep learning to parse out more information. They conclude that CA3 sends different "information" to different MCs. However, this is not surprising because different CA3 neurons project to different MCs and it was not determined if every SW reflected the same or different subsets of CA3 activity.

The strengths include recording up to 5 MCs at a time. The major concerns are in the finding that there is variability. This seems logical, not surprising. Also it is not clear how deep learning could lead to the conclusion that CA3 sends different "information" to different MCs. It seems already known from the anatomy because CA3 neurons have diverse axons so they do not converge on only one or a few MCs. Instead they project to different MCs. Even if they would, there are different numbers of boutons and different placement of boutons on the MC dendrites, leading to different effects on MCs. There also is a complex circuitry that is not taken into account in the discussion or in the model used for deep learning. CA3 does not only project to MCs. It also projects to hilar and other dentate gyrus GABAergic neurons which have complex connections to each other, MCs, and CA3. Furthermore, MCs project to MCs, the GABAergic neurons, and CA3. Therefore at any one time that a SW occurs, a very complex circuitry is affected and this could have very different effects on MCs so they would vary in response to the SW. This is further complicated by use of slices where different parts of the circuit are transected from slice to slice.

It is also not discussed if SWs have a uniform frequency during the recording session. If they cluster, or if MC action potentials occur just before a SW, or other neurons discharge before, it will affect the response of the MC to the SW. If MC membrane potential varies, this will also effect the depolarization in response to the SW.

In vivo, the SWs may be quite different than in vivo but this is not discussed. The circuitry is quite different from in vitro. The effects of urethane could have many confounding influences.

Furthermore, how much the in vitro and in vivo SWs tell us about SWs in awake behaving mice is unclear.

Also, methods and figures are hard to understand.

Reviewer #1 (Public review):

Summary:

This manuscript described a structure-guided approach to graft important antigenic loops of the neuraminidase to a homotypic but heterologous NA. This approach allows the generation of well-expressed and thermostable recombinant proteins with antigenic epitopes of choice to some extent. The loop-grafted NA was designated hybrid.

Strengths:

The hybrid NA appeared to be more structurally stable than the loop-donor protein while acquiring its antigenicity. This approach is of value when developing a subunit NA vaccine which is difficult to express. So that antigenic loops could be potentially grafted to a stable NA scaffold to transfer strain-specific antigenicity.

Weaknesses:

However, major revisions to better organize the text, and figure and make clarifications on a number of points, are needed. There are a few cases in which a later figure was described first, data in the figures were not sufficiently described, or where there were mismatched references to figures.

More importantly, the hybrid proteins did not show any of the advantages over the loop-donor protein in the format of VLP vaccine in mouse studies, so it's not clear why such an approach is needed to begin with if the original protein is doing fine.

Reviewer #1 (Public review):

Summary:

In this manuscript, Wu et al. introduce a novel approach to reactivate the Muller glia cell cycle in the mouse retina by simultaneously reducing p27Kip1 and increasing cyclin D1 using a single AAV vector. The approach effectively promotes Muller glia proliferation and reprogramming without disrupting retinal structure or function. Interestingly, reactivation of the Muller glia cell cycle downregulates IFN pathway, which may contribute to the induced retinal regeneration. The results presented in this manuscript may offer a promising approach for developing Müller glia cell-mediated regenerative therapies for retinal diseases.

Comments on revisions:

The authors have revised the manuscript and addressed my concerns.

Reviewer #1 (Public review):

Summary:

Mehmet Mahsum Kaplan et al. demonstrate that Meis2 expression in neural crest-derived mesenchymal cells is crucial for whisker follicle (WF) development, as WF fails to develop in wnt1-Cre;Meis2 cKO mice. Advanced imaging techniques effectively support the idea that Meis2 is essential for proper WF development and that nerves, while affected in Meis2 cKO, are dispensable for WF development and not the primary cause of WF developmental failure. The study also reveals that although Meis2 significantly downregulates Foxd1 in the mesenchyme, this is not the main reason for WF development failure. The paper presents valuable data on the role of mesenchymal Meis2 in WF development. However, it is still not known what is the molecular mechanisms that link Meis2 to impact the epithelial compartment.

Strengths:

(1) The authors describe a novel molecular mechanism involving Mesenchymal Meis2 expression, which plays a crucial role in early WF development.<br /> (2) They employ multiple advanced imaging techniques to illustrate their findings beautifully.<br /> (3) The study clearly shows that nerves are not essential for WF development.

Weaknesses:

The paper lacks clarity on how Meis2 loss, along with the observed general reduction in proliferation and changes in extracellular matrix and cell adhesion, leads specifically to the loss of whisker follicles. Future studies addressing this gap, perhaps with methods enabling higher cell recovery or epithelial cell inclusion in the sequenced cells, could provide valuable insights into the specific roles of Meis2 in this context.

Reviewer #1 (Public Review):

Summary:

In this work, the authors present a novel, multi-layer computational model of motor control to produce realistic walking behaviour of a Drosophila model in the presence of external perturbations and under sensory and motor delays. The novelty of their model of motor control is that it is modular, with divisions inspired by the fly nervous system, with one component based on deep learning while the rest are based on control theory. They show that their model can produce realistic walking trajectories. Given the mostly reasonable assumptions of their model, they convincingly show that the sensory and motor delays present in the fly nervous system are the maximum allowable for robustness to unexpected perturbations.

Their fly model outputs torque at each joint in the leg, and their dynamics model translates these into movements, resulting in time-series trajectories of joint angles. Inspired by the anatomy of the fly nervous system, their fly model is a modular architecture that separates motor control at three levels of abstraction:<br /> (1) oscillator-based model of coupling of phase angles between legs,<br /> (2) generation of future joint-angle trajectories based on the current state and inputs for each leg (the trajectory generator), and<br /> (3) closed-loop control of the joint-angles using torques applied at every joint in the model (control and dynamics).

These three levels of abstraction ensure coordination between the legs, future predictions of desired joint angles, and corrections to deviations from desired joint-angle trajectories. The parameters of the model are tuned in the absence of external perturbations using experimental data of joint angles of a tethered fly. A notable disconnect from reality is that the dynamics model used does not model the movement of the body and ground contacts as is the case in natural walking, nor the movement of a ball for a tethered fly, but instead something like legs moving in the air for a tethered fly.

In order to validate the realism of the generated simulated walking trajectories, the authors compare various attributes of simulated to real tethered fly trajectories and show qualitative and quantitative similarities, including using a novel metric coined as Kinematic Similarity (KS). The KS score of a trajectory is a measure of the likelihood that the trajectory belongs to the distribution of real trajectories estimated from the experimental data. While such a metric is a useful tool to validate the quality of simulated data, there is some room for improvement in the actual computation of this score. For instance, the KS score is computed for any given time-window of walking simulation using a fraction of information from the joint-angle trajectories. It is unclear if the remaining information in joint-angle trajectories that are not used in the computation of the KS score can be ignored in the context of validating the realism of simulated walking trajectories.

The authors validate simulated walking trajectories generated by the trained model under a range of sensorimotor delays and external perturbations. The trained model is shown to generate realistic joint-angle trajectories in the presence of external perturbations as long as the sensorimotor delays are constrained within a certain range. This range of sensorimotor delays is shown to be comparable to experimental measurements of sensorimotor delays, leading to the conclusion that the fly nervous system is just fast enough to be robust to perturbations.

Strengths:

This work presents a novel framework to simulate Drosophila walking in the presence of external perturbations and sensorimotor delay. Although the model makes some simplifying assumptions, it has sufficient complexity to generate new, testable hypotheses regarding motor control in Drosophila. The authors provide evidence for realistic simulated walking trajectories by comparing simulated trajectories generated by their trained model with experimental data using a novel metric proposed by the authors. The model proposes a crucial role in future predictions to ensure robust walking trajectories against external perturbations and motor delay. Realistic simulations under a range of prediction intervals, perturbations, and motor delays generating realistic walking trajectories support this claim. The modular architecture of the framework provides opportunities to make testable predictions regarding motor control in Drosophila. The work can be of interest to the Drosophila community interested in digitally simulating realistic models of Drosophila locomotion behaviors, as well as to experimentalists in generating testable hypotheses for novel discoveries regarding neural control of locomotion in Drosophila. Moreover, the work can be of broad interest to neuroethologists, serving as a benchmark in modelling animal locomotion in general.

Weaknesses:

As the authors acknowledge in their work, the control and dynamics model makes some simplifying assumptions about Drosophila physics/physiology in the context of walking. For instance, the model does not incorporate ground contact forces and inertial effects of the fly's body. It is not clear how these simplifying assumptions would affect some of the quantitative results derived by the authors. The range of tolerable values of sensorimotor delays that generate realistic walking trajectories is shown to be comparable with sensorimotor delays inferred from physiological measurements. It is unclear if this comparison is meaningful in the context of the model's simplifying assumptions. The authors propose a novel metric coined as Kinematic Similarity (KS) to distinguish realistic walking trajectories from unrealistic walking trajectories. Defining such an objective metric to evaluate the model's predictions is a useful exercise, and could potentially be applied to benchmark other computational animal models that are proposed in the future. However, the KS score proposed in this work is calculated using only the first two PCA modes that cumulatively account for less than 50% of the variance in the joint angles. It is not obvious that the information in the remaining PCA modes may not change the log-likelihood that occurs in the real walking data.

Comments on revisions:

The authors have addressed the concerns and questions raised in the original review.

Reviewer #1 (Public review):

The authors introduces DIPx, a deep learning framework for predicting synergistic drug combinations for cancer treatment using the AstraZeneca-Sanger (AZS) DREAM Challenge dataset. While the approach is innovative, I have following concerns and comments, and hopefully will improve the study's rigor and applicability, making it a more powerful tool in real clinical world.

(1) In the abstract: "We trained and validated DIPx in the AstraZeneca-Sanger (AZS) DREAM Challenge dataset using two separate test sets: Test Set 1 comprised the combinations already present in the training set, while Test Set 2 contained combinations absent from the training set, thus indicating the model's ability to handle novel combinations". Test Set 1 comprises combinations already present in the training set, likely leading overfitting issue. The model might show inflated performance metrics on this test set due to prior exposure to these combinations, not accurately reflecting its true predictive power on unknown data, which is crucial for discovering new drug synergies. The testing approach reduces the generalizability of the model's findings to new, untested scenarios.

(2) The model struggles with predicting synergies for drug combinations not included in its training data (showing only Spearman correlation 0.26 in Test Set 2). This limits its potential for discovering new therapeutic strategies. Utilizing techniques such as transfer learning or expanding the training dataset to encompass a wider range of drug pairs could help to address this issue.

(3) The use of pan-cancer datasets, while offering broad applicability, may not be optimal for specific cancer subtypes with distinct biological mechanisms. Developing subtype-specific models or adjusting the current model to account for these differences could improve prediction accuracy for individual cancer types.

(4) Line 127, "Since DIPx uses only molecular data, to make a fair comparison, we trained TAJI using only molecular features and referred to it as TAJI-M.". TAJI was designed to use both monotherapy drug-response and molecular data, and likely won't be able to reach maximum potential if removing monotherapy drug-response from the training model. It would be critical to use the same training datasets and then compare the performances. From the Figure 6 of TAJI's paper (Li et al., 2018, PMID: 30054332) , i.e., the mean Pearson correlation for breast cancer and lung cancer are around 0.5 - 0.6.

The following 2 concerns had been include in the Discussion section which are great:

(1) Training and validating the model using cell lines may not fully capture the heterogeneity and complexity of in vivo tumors. To increase clinical relevance, it would be beneficial to validate the model using primary tumor samples or patient-derived xenografts.

(2) The Pathway Activation Score (PAS) is derived exclusively from primary target genes, potentially overlooking critical interactions involving non-primary targets. Including these secondary effects could enhance the model's predictive accuracy and comprehensiveness.

Comments on revisions:

The authors replied to my concerns but they did not address my comments/concerns. Especially for my concern #1: They trained and validated DIPx in the AstraZeneca-Sanger (AZS) DREAM Challenge dataset using two separate test sets: Test Set 1 comprised the combinations already present in the training set. Therefore, test Set 1 comprises combinations already present in the training set, likely leading overfitting issue but they claimed "There is no danger overfitting here" in their "Author Response" letter.

All my other concerns are unchanged too.

Reviewer #1 (Public review):

Summary:

Jocher, Janssen, et al examine the robustness of comparative functional genomics studies in primates that make use of induced pluripotent stem cell-derived cells. Comparative studies in primates, especially amongst the great apes, are generally hindered by the very limited availability of samples, and iPSCs, which can be maintained in the laboratory indefinitely and defined into other cell types, have emerged as promising model systems because they allow the generation of data from tissues and cells that would otherwise be unobservable.

Undirected differentiation of iPSCs into many cell types at once, using a method known as embryoid body differentiation, requires researchers to manually assign all cell types in the dataset so they can be correctly analysed. Typically, this is done using marker genes associated with a specific cell type. These are defined a priori, and have historically tended to be characterised in mice and humans and then employed to annotate other species. Jocher, Janssen, et al ask if the marker genes and features used to define a given cell type in one species are suitable for use in a second species, and then quantify the degree of usefulness of these markers. They find that genes that are informative and cell type specific in a given species are less valuable for cell type identification in other species, and that this value, or transferability, drops off as the evolutionary distance between species increases.

This paper will help guide future comparative studies of gene expression in primates (and more broadly) as well as add to the growing literature on the broader challenges of selecting powerful and reliable marker genes for use in single-cell transcriptomics.

Strengths:

Marker gene selection and cell type annotation is a challenging problem in scRNA studies, and successful classification of cells often requires manual expert input. This can be hard to reproduce across studies, as, despite general agreement on the identity of many cell types, different methods for identifying marker genes will return different sets of genes. The rise of comparative functional genomics complicates this even further, as a robust marker gene in one species need not always be as useful in a different taxon. The finding that so many marker genes have poor transferability is striking, and by interrogating the assumption of transferability in a thorough and systematic fashion, this paper reminds us of the importance of systematically validating analytical choices. The focus on identifying how transferability varies across different types of marker genes (especially when comparing TFs to lncRNAs), and on exploring different methods to identify marker genes, also suggests additional criteria by which future researchers could select robust marker genes in their own data.

The paper is built on a substantial amount of clearly reported and thoroughly considered data, including EBs and cells from four different primate species - humans, orangutans, and two macaque species. The authors go to great lengths to ensure the EBs are as comparable as possible across species, and take similar care with their computational analyses, always erring on the side of drawing conservative conclusions that are robustly supported by their data over more tenuously supported ones that could be impacted by data processing artefacts such as differences in mappability, etc. For example, I like the approach of using liftoff to robustly identify genes in non-human species that can be mapped to and compared across species confidently, rather than relying on the likely incomplete annotation of the non-human primate genomes. The authors also provide an interactive data visualisation website that allows users to explore the dataset in depth, examine expression patterns of their own favourite marker genes and perform the same kinds of analyses on their own data if desired, facilitating consistency between comparative primate studies.

Weaknesses and recommendations:

(1) Embryoid body generation is known to be highly variable from one replicate to the next for both technical and biological reasons, and the authors do their best to account for this, both by their testing of different ways of generating EBs, and by including multiple technical replicates/clones per species. However, there is still some variability that could be worth exploring in more depth. For example, the orangutan seems to have differentiated preferentially towards cardiac mesoderm whereas the other species seemed to prefer ectoderm fates, as shown in Figure 2C. Likewise, Supplementary Figure 2C suggests a significant unbalance in the contributions across replicates within a species, which is not surprising given the nature of EBs, while Supplementary Figure 6 suggests that despite including three different clones from a single rhesus macaque, most of the data came from a single clone. The manuscript would be strengthened by a more thorough exploration of the intra-species patterns of variability, especially for the taxa with multiple biological replicates, and how they impact the number of cell types detected across taxa, etc.

The same holds for the temporal aspect of the data, which is not really discussed in depth despite being a strength of the design. Instead, days 8 and 16 are analysed jointly, without much attention being paid to the possible differences between them. Are EBs at day 16 more variable between species than at day 8? Is day 8 too soon to do these kinds of analyses? Are markers for earlier developmental progenitors better/more transferable than those for more derived cell types?

(2) Closely tied to the point above, by necessity the authors collapse their data into seven fairly coarse cell types and then examine the performance of canonical marker genes (as well as those discovered de novo) across the species. However some of the clusters they use are somewhat broad, and so it is worth asking whether the lack of specificity exhibited by some marker genes and driving their conclusions is driven by inter-species heterogeneity within a given cluster.

Reviewer #1 (Public review):

Summary:

This is an important and very well-presented set of experiments following up on prior work from the lab investigating knock-down (KD) of EMC10 in restoration of neuronal and cognitive deficits in 22q11.2 Del models, including now both human iPSCs and a mouse model in vivo now with ASOs.

The valuable progress in this current manuscript is the development of ASOs, and the proof of efficacy in vivo in mouse of the ASO in knock-down of EMC10 and amelioration of in vivo behavioral phenotypes.

The experiments include: iPSC studies demonstrating elevations of EMC10 in a solid collection of paired iPSC lines. These studies also provide evidence of manipulation of EMC10 by overexpression and inhibition of miRNAs that exist in the 22q11 interval. The iPSC studies also nicely demonstrate rescue of impairments with KD of EMC10 in neuronal arborization as well as KCl induced neuronal activity. The major in vivo contributions reflect impressive demonstration of efficacy of two ASOs in vivo on both KD of EMC10 in vivo and through improvement in behavioral abnormalities in the 22q11 mouse in a range of different behaviors, including social behavior and learning behaviors.

Overall, there are many strengths reflected in this study, including in particular the synergy between in vitro studies in human cell models and in vivo studies in the well characterized mouse model. The experiments are generally rigorously performed and well powered, and nicely presented. The claims with regard to the mechanisms of EMC10 elevations and the importance of restoration of EMC10 expression to neuronal morphology and behavior are well supported by the data. The work may be further supported in future studies, by investigation of rescue by ASOs of circuit dysfunction in vivo or ex vivo through electrophysiology in the mouse model. Also, in future studies, investigation of the mechanism by which EMC10, an ER protein involved in protein processing, may function in the observed neuronal abnormalities; however, these studies are clearly for future investigations.

The potential impact of the work is found in the potential value of the ASO approach to the treatment of 22q11, or the pre-clinical evidence that knock-down of this protein may lead to some amelioration of cognitive symptoms. Overall, a very convincing and complementary set of experiments to support EMC10 KD as a therapeutic strategy.

Review of revision: The authors have addressed the questions from the prior review.

Reviewer #2 (Public review):

This manuscript by Yu et al. demonstrates that activation of caspase-3 is essential for synapse elimination by microglia, but not by astrocytes. This study also reveals that caspase-3 activation-mediated synapse elimination is required for retinogeniculate circuit refinement and eye-specific territories segregation in dLGN in an activity-dependent manner. Inhibition of synaptic activity increases caspase-3 activation and microglial phagocytosis, while caspase-3 deficiency blocks microglia-mediated synapse elimination and circuit refinement in the dLGN. The authors further demonstrate that caspase-3 activation mediates synapse loss in AD, loss of caspase-3 prevented synapse loss in AD mice. Overall, this study reveals that caspase-3 activation is an important mechanism underlying the selectivity of microglia-mediated synapse elimination during brain development and in neurodegenerative diseases.

A previous study (Gyorffy B. et al., PNSA 2018) has shown that caspase-3 signal correlates with C1q tagging of synapses (mostly using in vitro approaches), which suggests that caspase-3 would be an underlying mechanism of microglial selection of synapses for removal. The current study provides convincing in vivo evidence demonstrating that caspase-3 activation is essential for microglial elimination of synapses during both brain development and neurodegeneration.

Reviewer #2 (Public review):

The authors investigated the similarity (or lack thereof) of neural dynamics while monkeys reached to and manipulated one of 4 objects in each trial, compared to observing similar movements performed by experimenters. They focused on mirror neurons (MNs) and rather convincingly showed that MNs dynamics are dissimilar during executing vs. observing actions. The manuscript has improved quite significantly compared to the previous version and I congratulate the authors for that. However, there are still a few points I would like to raise that I think will improve the manuscript scientifically and make it more pleasant to read.

- I appreciate the nicely compiled literature review which provides the context for the manuscript.<br /> - Message: The takeaway message of the paper is inconsistent and changes throughout the paper. To me, the main takeaway is that observation and execution subspaces progress during the trial (Fig 4), and that they are distinct processes and rather dissimilar, as stated in #440-441, #634-635, etc. But the title of the paper implies the opposite. Some of the interpretations of the results (e.g., Fig 8) also imply similarity of dynamics.<br /> - Readability: I have many issues with the readability/organisation of the paper. Unfortunately, I still find the quality of data presentation low. Below I list a few points:<br /> (1) In 5 sessions out of 9, there are fewer than 20 neurons categorised as AE. This means this population is under-sampled in the data which makes applying any neural population techniques questionable. Moreover, the relevance of the AE analysis is also sometimes unclear: In Fig 4, the AE-related panels are just referred to once in the paper. Yet AE results are presented right next to the main results throughout the paper.<br /> (2) Figures are low resolution and pixelated. There are some faded horizontal and vertical lines in Fig1B that are barely visible. Moreover, it may be my personal preference, but I think Fig1 is more confusing than helpful. Although panel A shows some planes rotating, indicating time-varying dynamics, I couldn't understand what more panel B is trying to convey. The arrow of time is counterclockwise, but the planes progress clockwise (i > ii > iii). Similarly, panel C just seems to show some points being projected to orthogonal subspaces (even though later in the paper we'll see that observation and execution subspaces are not orthogonal), and the CCA subspace illustrated in the same high-d space, which mathematically may be inaccurate, as CCA projects the data to a new space.<br /> In Fig 2A, the objects are too small and pixelated as well. I suggest an overhaul of the figures to make the paper more accessible.<br /> (3) Clarity of the text: The manuscript text could be more concise, to the point, avoiding repetitions, self-consistent, and simply readable. To name a few issues: Single letter acronyms were used to refer to trial epochs (I/G/M/H). M alone has been re-defined 13 different times in the text as in: ...Movement (M)..., excluding every related figure. The acronym (I) refers to the instruction epoch, the high-d space in Fig 1, and panel I of some figures. The acronym MN for Mirror Neurons was defined 4 separate times in the text yet spelled out as Mirror Neuron more than 2 dozen times. CD is defined in the caption of Fig 3 and never used, despite condition-dependent being a common term in the text. Many sentences, e.g., "In contrast, throughout..." in #265-#269, and "To summarize,..." in #270-#275, are too long with difficult wording. To get the point from these sentences, I had to read them many times, and go back and forth between them and the figure. Rewriting such sentences makes the manuscript much more accessible.<br /> - Figure 3: It appears that the condition independent signal has been calculated by subtracting the average of the 4 neural trajectories in Fig 3A, corresponding to different objects. Whereas #133 suggests that it should be calculated by subtracting the average firing rate of different conditions. Assuming I got the methods right, dynamics being "knotted" (#234) after removing the condition independent signal could be because they are similar, so subtracting the condition independent signal leaves us with the noise component. This matters for the manuscript especially since this is the reason for performing the more sensitive instantaneous subspaces.<br /> - Decoding results: I appreciate that the authors improved the decoding results in this version of the manuscript. Now it is much more interesting. However oddly, it appears that only data from 1 monkey is shown. #370 says the results from the other 2 are similar. The decoding data from every monkey must be shown. If the results are similar, they must be at least in Supplements. Currently, only 1 session (out of 3) in the Observation condition seems to decode the object type. This effect, if consistent across animals and session, is very interesting on its own and challenges other claims in the paper.<br /> - Figure8: I reiterate the issue #7 in my previous review. I appreciate the authors clearing some methods, but my concern persists. As per line #839, spiking activity has been smoothed with a 50ms kernel. Thus, unless trial data is concatenated, I suspect the 100ms window used for this analysis is too short (small sample size), thus the correlation values (CCs) might be spurious. References cited in this section use a smaller smoothing kernel (30ms) and a much longer window (~450ms).<br /> Moreover, I don't know why the authors chose to show correlation values in 3D space! Values of Fig8C-red are impossible to know. Furthermore, the manuscript insists on CC values of the Hold period being high, which is probably correct. But I wonder why the focus on the Hold period? I think the most relevant epoch for analysing the MNs is the Movement where the actual action happens. Interestingly, in the movement epoch, the CC values are visibly low. The reason why Hold results are more important and why the CCs in Movement are so low should be clarified in the text. Especially, statements like that in #661 seem particularly unjustified.

Reviewer #1 (Public review):

Summary:

From a forward genetic mosaic mutant screen using EMS, the authors identify mutations in glucosylceramide synthase (GlcT), a rate-limiting enzyme for glycosphingolipid (GSL) production, that result in EE tumors. Multiple genetic experiments strongly support the model that the mutant phenotype caused by GlcT loss is due to by failure of conversion of ceramide into glucosylceramide. Further genetic evidence suggests that Notch signaling is comprised in the ISC lineage and may affect the endocytosis of Delta. Loss of GlcT does not affect wing development or oogenesis, suggesting tissue-specific roles for GlcT. Finally, an increase in goblet cells in UGCG knockout mice, not previously reported, suggests a conserved role for GlcT in Notch signaling in intestinal cell lineage specification.

Strengths:

Overall, this is a well-written paper with multiple well-designed and executed genetic experiments that support a role for GlcT in Notch signaling in the fly and mammalian intestine. I do, however, have a few comments below.

Weaknesses:

(1) The authors bring up the intriguing idea that GlcT could be a way to link diet to cell fate choice. Unfortunately, there are no experiments to test this hypothesis.

(2) Why do the authors think that UCCG knockout results in goblet cell excess and not in the other secretory cell types?

(3) The authors should cite other EMS mutagenesis screens done in the fly intestine.

(4) The absence of a phenotype using NRE-Gal4 is not convincing. This is because the delay in its expression could be after the requirement for the affected gene in the process being studied. In other words, sufficient knockdown of GlcT by RNA would not be achieved until after the relevant signaling between the EB and the ISC occurred. Dl-Gal4 is problematic as an ISC driver because Dl is expressed in the EEP.

(5) The difference in Rab5 between control and GlcT-IR was not that significant. Furthermore, any changes could be secondary to increases in proliferation.

Reviewer #1 (Public review):

Summary:

The authors propose a transformer-based model for the prediction of condition - or tissue-specific alternative splicing and demonstrate its utility in the design of RNAs with desired splicing outcomes, which is a novel application. The model is compared to relevant existing approaches (Pangolin and SpliceAI) and the authors clearly demonstrate its advantage. Overall, a compelling method that is well thought out and evaluated.

Strengths:

(1) The model is well thought out: rather than modeling a cassette exon using a single generic deep learning model as has been done e.g. in SpliceAI and related work, the authors propose a modular architecture that focuses on different regions around a potential exon skipping event, which enables the model to learn representations that are specific to those regions. Because each component in the model focuses on a fixed length short sequence segment, the model can learn position-specific features. Another difference compared to Pangolin and SpliceAI which are focused on modeling individual splice junctions is the focus on modeling a complete alternative splicing event.

(2) The model is evaluated in a rigorous way - it is compared to the most relevant state-of-the-art models, uses machine learning best practices, and an ablation study demonstrates the contribution of each component of the architecture.

(3) Experimental work supports the computational predictions.

(4) The authors use their model for sequence design to optimize splicing outcomes, which is a novel application.

Weaknesses:

No weaknesses were identified by this reviewer, but I have the following comments:

(1) I would be curious to see evidence that the model is learning position-specific representations.

(2) The transformer encoders in TrASPr model sequences with a rather limited sequence size of 200 bp; therefore, for long introns, the model will not have good coverage of the intronic sequence. This is not expected to be an issue for exons.

(3) In the context of sequence design, creating a desired tissue- or condition-specific effect would likely require disrupting or creating motifs for splicing regulatory proteins. In your experiments for neuronal-specific Daam1 exon 16, have you seen evidence for that? Most of the edits are close to splice junctions, but a few are further away.

(4) For sequence design, of tissue- or condition-specific effect in neuronal-specific Daam1 exon 16 the upstream exonic splice junction had the most sequence edits. Is that a general observation? How about the relative importance of the four transformer regions in TrASPr prediction performance?

(5) The idea of lightweight transformer models is compelling, and is widely applicable. It has been used elsewhere. One paper that came to mind in the protein realm:<br /> Singh, Rohit, et al. "Learning the language of antibody hypervariability." Proceedings of the National Academy of Sciences 122.1 (2025): e2418918121.

Reviewer #1 (Public review):

Summary

Fleming et al. present the first, proteomics-based attempt to identify the possible mechanism of action of ALS-linked DNAJC7 molecular chaperone in pathology. Impressively, it is the first report of DNAJC7 interactome studies, using a suitable iPSC-derived lower motor neuron model. Using a co-immunoprecipitation approach the authors identified that the interactome of DNAJC7 is predominantly composed of proteins engaged in response to stress, but also that this interactome is enriched in RNA-binding proteins. The authors also created a DNAJC7 haploinsufficiency cellular model and show the resulting increased insolubility of HNRNPU protein which causes disruptions in its functionality as shown by analysis of its transcriptional targets. Finally, this study uses pharmacological agents to test the effect of decreased DNAJC7 expression on cell response to proteotoxic stress and finds evidence that DNAJC7 regulates the activation of Heat shock factor 1 (HSF1) protein upon stress conditions.

Strengths

(1)This study uses the best so far model to study the interactome and possible mechanism of action of DNAJC7 molecular chaperone in an iPSC-derived cellular model of motor neurons. Furthermore, the authors also looked into available transcriptome databases of ALS patient samples to further test whether their findings may yield relevance to pathology.

(2) The extent to which the authors are explicit about the sample sizes, protocols, and statistical tests used throughout this manuscript, should be applauded. This will help the whole field in their efforts to reliably replicate the results in this study.

Weaknesses

(1) The most significant caveat of interactome experiments inherently comes from the method of choice. It is possible that by using the co-purification approach of DNAJC7 IP the resulting pool of binding partners is depleted in proteins that interact with DNAJC7 weakly or transiently. An alternative approach presumably more sensitive towards weaker binders could use the TurboID-based proximity-labeling method.

(2) The authors mention in Results (and Figure 2D) that HNRNPA1 was identified as DNAJC7-interacting protein in their co-IP experiments, however, an identifier for this protein cannot be found in Figure 1C and Table S1 listing the proteomics results. Could the authors appropriately update Figure 1C and Table S1, or if HNRNPA1 wasn't really a hit then remove it from listed HNRNPs?

(3) No further validation of DNAJC7-interacting proteins from the heat-shock protein (HSP) family. Current validation of mass spectrometry-identified proteins comes from IP-western blots with antibodies against HSPs. It would be interesting to further inspect possible interactions of these proteins by inspecting co-localization with immunocytochemistry.

(4) Similarly, the observation of DNAJC7 haploinsufficiency causing an increase in HNRNPU insolubility could be also easily further confirmed by checking for the emergence of "puncta" under a fluorescence microscope, in addition to provided WB experiments from MN lysates.

(5) I would like to recommend the authors to also provide with this manuscript a complete dataset (possibly in the form of a table, presented similarly as Table S1) resulting from experiments presented in Figures 2F and S2D. The information on upregulated and downregulated targets in their DNAJC7 haploinsufficiency model would be a valuable resource for the field and enable further investigations.

Reviewer #1 (Public review):

Summary:

The study shows that Zizyphi spinosi semen (ZSS), particularly its non-extracted simple crush powder, has significant therapeutic effects on neurodegenerative diseases. It removes Aβ, tau, and α-synuclein oligomers, restores synaptophysin levels, enhances BDNF expression and neurogenesis, and improves cognitive and motor functions in mouse AD, FTD, DLB, and PD models. Additionally, ZSS powder reduces DNA oxidation and cellular senescence in normal-aged mice, increases synaptophysin, BDNF, and neurogenesis, and enhances cognition to levels comparable to young mice.

Weaknesses:

(1) While the study demonstrates that ZSS has protective effects across a wide range of animal models, including AD, FTD, DLB, PD, and both young and aged mice, it is broad and lacks a detailed investigation into the underlying mechanisms. This is the most significant concern.

(2) The authors highlight that the non-extracted simple crush powder of ZSS shows more substantial effects than its hot water extract and extraction residue. However, the manuscript provides very limited data comparing the effects of these three extracts.

(3) The authors have not provided a rationale for the dosing concentrations used, nor have they tested the effects of the treatment in normal mice to verify its impact under physiological conditions.

(4) Regarding the assessment of cognitive function in mice, the authors only utilized the Morris Water Maze (MWM) test, which includes a five-day spatial learning training phase followed by a probe trial. The authors focused solely on the learning phase. However, it is relevant to note that data from the learning phase primarily reflects the learning ability of the mice, while the probe trial is more indicative of memory. Therefore, it is essential that probe trial data be included for a more comprehensive analysis. A justification should be included to explain why the latency of 1st is about 50s not 60s.

(5) The BDNF immunohistochemical staining in the manuscript appears to be non-specific.

(6) The central pathological regions in PD are the substantia nigra and striatum. Please replace the staining results from the cortex and hippocampus with those from these regions in the PD model.

Reviewer #1 (Public review):

Summary:

This study aims to provide imaging methods for users of the field of human layer-fMRI. This is an emerging field with 240 papers published so far. Different than implied in the manuscript, 3T is well represented among those papers. E.g. see the papers below that are not cited in the manuscript. Thus, the claim on the impact of developing 3T methodology for wider dissemination is not justified. Specifically, because some of the previous papers perform whole brain layer-fMRI (also at 3T) in more efficient, and more established procedures.

The authors implemented a sequence with lots of nice features. Including their own SMS EPI, diffusion bipolar pulses, eye-saturation bands, and they built their own reconstruction around it. This is not trivial. Only a few labs around the world have this level of engineering expertise. I applaud this technical achievement. However, I doubt that any of this is the right tool for layer-fMRI, nor does it represent an advancement for the field. In the thermal noise dominated regime of sub-millimeter fMRI (especially at 3T) it is established to use 3D readouts over 2D (SMS) readouts. While it is not trivial to implement SMS, the vendor implementations (as well as the CMRR and MGH implementations) are most widely applied across the majority of current fMRI studies already. The author's work on this does not serve any previous shortcomings in the field.

The mechanism to use bi-polar gradients to increase the localization specificity is doubtful to me. In my understanding, killing the intra-vascular BOLD should make it less specific. Also, the empirical data do not suggest a higher localization specificity to me.

Embedding this work in the literature of previous methods is incomplete. Recent trends of vessel signal manipulation with ABC or VAPER are not mentioned. Comparisons with VASO are outdated and incorrect.

The reproducibility of the methods and the result is doubtful (see below).

I don't think that this manuscript is in the top 50% of the 240 layer-fmri papers out there.

3T layer-fMRI papers that are not cited:

Taso, M., Munsch, F., Zhao, L., Alsop, D.C., 2021. Regional and depth-dependence of cortical blood-flow assessed with high-resolution Arterial Spin Labeling (ASL). Journal of Cerebral Blood Flow and Metabolism. https://doi.org/10.1177/0271678X20982382

Wu, P.Y., Chu, Y.H., Lin, J.F.L., Kuo, W.J., Lin, F.H., 2018. Feature-dependent intrinsic functional connectivity across cortical depths in the human auditory cortex. Scientific Reports 8, 1-14. https://doi.org/10.1038/s41598-018-31292-x

Lifshits, S., Tomer, O., Shamir, I., Barazany, D., Tsarfaty, G., Rosset, S., Assaf, Y., 2018. Resolution considerations in imaging of the cortical layers. NeuroImage 164, 112-120. https://doi.org/10.1016/j.neuroimage.2017.02.086

Puckett, A.M., Aquino, K.M., Robinson, P.A., Breakspear, M., Schira, M.M., 2016. The spatiotemporal hemodynamic response function for depth-dependent functional imaging of human cortex. NeuroImage 139, 240-248. https://doi.org/10.1016/j.neuroimage.2016.06.019

Olman, C.A., Inati, S., Heeger, D.J., 2007. The effect of large veins on spatial localization with GE BOLD at 3 T: Displacement, not blurring. NeuroImage 34, 1126-1135. https://doi.org/10.1016/j.neuroimage.2006.08.045

Ress, D., Glover, G.H., Liu, J., Wandell, B., 2007. Laminar profiles of functional activity in the human brain. NeuroImage 34, 74-84. https://doi.org/10.1016/j.neuroimage.2006.08.020

Huber, L., Kronbichler, L., Stirnberg, R., Ehses, P., Stocker, T., Fernández-Cabello, S., Poser, B.A., Kronbichler, M., 2023. Evaluating the capabilities and challenges of layer-fMRI VASO at 3T. Aperture Neuro 3. https://doi.org/10.52294/001c.85117

Scheeringa, R., Bonnefond, M., van Mourik, T., Jensen, O., Norris, D.G., Koopmans, P.J., 2022. Relating neural oscillations to laminar fMRI connectivity in visual cortex. Cerebral Cortex. https://doi.org/10.1093/cercor/bhac154

Strengths:

See above. The authors developed their own SMS sequence with many features. This is important to the field. And does not leave sequence development work to view isolated monopoly labs. This work democratises SMS.<br /> The questions addressed here are of high relevance to the field: getting tools with good sensitivity, user-friendly applicability, and locally specific brain activity mapping is an important topic in the field of layer-fMRI.

Weaknesses:

(1) I feel the authors need to justify why flow-crushing helps localization specificity. There is an entire family of recent papers that aims to achieve higher localization specificity by doing the exact opposite. Namely, MT or ABC fRMRI aims to increase the localization specificity by highlighting the intravascular BOLD by means of suppressing non-flowing tissue. To name a few:

Priovoulos, N., de Oliveira, I.A.F., Poser, B.A., Norris, D.G., van der Zwaag, W., 2023. Combining arterial blood contrast with BOLD increases fMRI intracortical contrast. Human Brain Mapping hbm.26227. https://doi.org/10.1002/hbm.26227.

Pfaffenrot, V., Koopmans, P.J., 2022. Magnetization Transfer weighted laminar fMRI with multi-echo FLASH. NeuroImage 119725. https://doi.org/10.1016/j.neuroimage.2022.119725

Schulz, J., Fazal, Z., Metere, R., Marques, J.P., Norris, D.G., 2020. Arterial blood contrast ( ABC ) enabled by magnetization transfer ( MT ): a novel MRI technique for enhancing the measurement of brain activation changes. bioRxiv. https://doi.org/10.1101/2020.05.20.106666

Based on this literature, it seems that the proposed method will make the vein problem worse, not better. The authors could make it clearer how they reason that making GE-BOLD signals more extra-vascular weighted should help to reduce large vein effects.

The empirical evidence for the claim that flow crushing helps with the localization specificity should be made clearer. The response magnitude with and without flow crushing looks pretty much identical to me (see Fig, 6d).<br /> It's unclear to me what to look for in Fig. 5. I cannot discern any layer patterns in these maps. It's too noisy. The two maps of TE=43ms look like identical copies from each other. Maybe an editorial error?

The authors discuss bipolar crushing with respect to SE-BOLD where it has been previously applied. For SE-BOLD at UHF, a substantial portion of the vein signal comes from the intravascular compartment. So I agree that for SE-BOLD, it makes sense to crush the intravascular signal. For GE-BOLD however, this reasoning does not hold. For GE-BOLD (even at 3T), most of the vein signal comes from extravascular dephasing around large unspecific veins and the bipolar crushing is not expected to help with this.

(2) The bipolar crushing is limited to one single direction of flow. This introduces a lot of artificial variance across the cortical folding pattern. This is not mentioned in the manuscript. There is an entire family of papers that perform layer-fmri with black-blood imaging that solves this with a 3D contrast preparation (VAPER) that is applied across a longer time period, thus killing the blood signal while it flows across all directions of the vascular tree. Here, the signal cruising is happening with a 2D readout as a "snap-shot" crushing. This does not allow the blood to flow in multiple directions.<br /> VAPER also accounts for BOLD contaminations of larger draining veins by means of a tag-control sampling. The proposed approach here does not account for this contamination.

Chai, Y., Li, L., Huber, L., Poser, B.A., Bandettini, P.A., 2020. Integrated VASO and perfusion contrast: A new tool for laminar functional MRI. NeuroImage 207, 116358. https://doi.org/10.1016/j.neuroimage.2019.116358

Chai, Y., Liu, T.T., Marrett, S., Li, L., Khojandi, A., Handwerker, D.A., Alink, A., Muckli, L., Bandettini, P.A., 2021. Topographical and laminar distribution of audiovisual processing within human planum temporale. Progress in Neurobiology 102121. https://doi.org/10.1016/j.pneurobio.2021.102121

If I would recommend anyone to perform layer-fMRI with blood crushing, it seems that VAPER is the superior approach. The authors could make it clearer why users might want to use the unidirectional crushing instead.

(3) The comparison with VASO is misleading.<br /> The authors claim that previous VASO approaches were limited by TRs of 8.2s. The authors might be advised to check the latest literature of the last years.<br /> Koiso et al. has performed whole brain layer-fMRI VASO at 0.8mm at 3.9 seconds (with reliable activation) and 2.7 seconds (with unconvincing activation pattern, though), and 2.3 (without activation).<br /> Also, whole brain layer-fMRI BOLD at 0.5mm and 0.7mm has been previously performed by the Juelich group at TRs of 3.5s (their TR definition is 'fishy' though).

Koiso, K., Müller, A.K., Akamatsu, K., Dresbach, S., Gulban, O.F., Goebel, R., Miyawaki, Y., Poser, B.A., Huber, L., 2023. Acquisition and processing methods of whole-brain layer-fMRI VASO and BOLD: The Kenshu dataset. Aperture Neuro 34. https://doi.org/10.1101/2022.08.19.504502

Yun, S.D., Pais‐Roldán, P., Palomero‐Gallagher, N., Shah, N.J., 2022. Mapping of whole‐cerebrum resting‐state networks using ultra‐high resolution acquisition protocols. Human Brain Mapping. https://doi.org/10.1002/hbm.25855

Pais-Roldan, P., Yun, S.D., Palomero-Gallagher, N., Shah, N.J., 2023. Cortical depth-dependent human fMRI of resting-state networks using EPIK. Front. Neurosci. 17, 1151544. https://doi.org/10.3389/fnins.2023.1151544

The authors are correct that VASO is not advised as a turn-key method for lower brain areas, incl. Hippocampus and subcortex. However, the authors use this word of caution that is intended for inexperienced "users" as a statement that this cannot be performed. This statement is taken out of context. This statement is not from the academic literature. It's advice for the 40+ user base that want to perform layer-fMRI as a plug-and-play routine tool in neuroscience usage. In fact, sub-millimeter VASO is routinely being performed by MRI-physicists across all brain areas (including deep brain structures, hippocampus etc). E.g. see Koiso et al. and an overview lecture from a layer-fMRI workshop that I had recently attended: https://youtu.be/kzh-nWXd54s?si=hoIJjLLIxFUJ4g20&t=2401

Thus, the authors could embed this phrasing into the context of their own method that they are proposing in the manuscript. E.g. the authors could state whether they think that their sequence has the potential to be disseminated across sites, considering that it requires slow offline reconstruction in Matlab?<br /> Do the authors think that the results shown in Fig. 6c are suggesting turn-key acquisition of a routine mapping tool? In my humble opinion it looks like random noise, with most of the activation outside the ROI (in white matter).

(4) The repeatability of the results is questionable.<br /> The authors perform experiments about the robustness of the method (line 620). The corresponding results are not suggesting any robustness to me. In fact the layer profiles in Fig. 4c vs. Fig 4d are completely opposite. Location of peaks turn into locations of dips and vice versa.<br /> The methods are not described in enough detail to reproduce these results.<br /> The authors mention that their image reconstruction is done "using in-house MATLAB code" (line 634). They do not post a link to github, nor do they say if they share this code.

It is not trivial to get good phase data for fMRI. The authors do not mention how they perform the respective coil-combination.<br /> No data are shared for reproduction of the analysis.

(5) The application of NODRIC is not validated.<br /> Previous applications of NORDIC at 3T layer-fMRI have resulted in mixed success. When not adjusted for the right SNR regime it can result in artifactual reductions of beta scores, depending on the SNR across layers. The authors could validate their application of NORDIC and confirm that the average layer-profiles are unaffected by the application of NORDIC. Also, the NORDIC version should be explicitly mentioned in the manuscript.

Akbari, A., Gati, J.S., Zeman, P., Liem, B., Menon, R.S., 2023. Layer Dependence of Monocular and Binocular Responses in Human Ocular Dominance Columns at 7T using VASO and BOLD (preprint). Neuroscience. https://doi.org/10.1101/2023.04.06.535924

Knudsen, L., Guo, F., Huang, J., Blicher, J.U., Lund, T.E., Zhou, Y., Zhang, P., Yang, Y., 2023. The laminar pattern of proprioceptive activation in human primary motor cortex. bioRxiv. https://doi.org/10.1101/2023.10.29.564658

Comments on revisions:

Among all the concerns mentioned above, I think there is only one of the specific issues that was sufficiently addressed.<br /> The authors implemented a combination of three consecutive-dimensional flow crushers. Other concerns were not sufficiently addressed to change my confidence level of the study.<br /> - While the abstract is still focusing on the utility of using 3T, they do not give credit to early 3T layer-fMRI papers leading the way to larger coverage and connectivity applications.<br /> - While the author's choice of using custom SMS 2D readout is justified for them. I do not think that this very method will utilize widespread 3T whole brain connectivity experiments across the global 3T community. This lowers the impact of the paper.<br /> - The images in Fig. 5 are still suspiciously similar. To the level that the noise pattern outside the brain is identical across large parts of the maps with and without PR.<br /> - Maybe it's my ignorance, but I still do not agree why flow crushing focuses the local BOLD responses to small vessels.<br /> - While my feel of a misleading representation of the literature had been accompanied by explicit references, the authors claim that they cannot find them?!? Or claim that they are about something else (which they are not, in my viewpoint).<br /> Data and software are still not shared (not even example data, or nii data).

Reviewer #1 (Public review):

Summary:

In this study, Millard and colleagues investigated if the analgesic effect of nicotine on pain sensitivity, assessed with two pain models, is mediated by Peak Alpha Frequency (PAF) recorded with resting state EEG. The authors found indeed that nicotine (4 mg, gum) reduced pain ratings during phasic heat pain but not cuff pressor algometry compared to placebo conditions. Nicotine also increased PAF (globally). However, mediation analysis revealed that the reduction in pain ratings elicited by the phasic heat pain after taking nicotine was not mediated by the changes in PAF. Also, the authors only partially replicated the correlation between PAF and pain sensitivity at baseline (before nicotine treatment). At the group-level no correlation was found, but an exploratory analysis showed that the negative correlation (lower PAF, higher pain sensitivity) was present in males but not in females. The authors discuss the lack of correlation.<br /> In general, the study is rigorous, methodology is sound and the paper is well written. Results are compelling and sufficiently discussed.

Strengths:

Strengths of this study are the pre-registration, proper sample size calculation and data analysis. But also the presence of the analgesic effect of nicotine and the change in PAF.

Weaknesses:

It would even be more convincing if they had manipulated PAF directly.

Reviewer #1 (Public review):

Summary:

This work investigated the role of CXXC-finger protein 1 (CXXC1) in regulatory T cells. CXXC1-bound genomic regions largely overlap with Foxp3-bound regions and regions with H3K4me3 histone modifications in Treg cells. CXXC1 and Foxp3 interact with each other, as shown by co-immunoprecipitation. Mice with Treg-specific CXXC1 knockout (KO) succumb to lymphoproliferative diseases between 3 to 4 weeks of age, similar to Foxp3 KO mice. Although the immune suppression function of CXXC1 KO Treg is comparable to WT Treg in an in vitro assay, these KO Tregs failed to suppress autoimmune diseases such as EAE and colitis in Treg transfer models in vivo. This is partly due to the diminished survival of the KO Tregs after transfer. CXXC1 KO Tregs do not have an altered DNA methylation pattern; instead, they display weakened H3K4me3 modifications within the broad H3K4me3 domains, which contain a set of Treg signature genes. These results suggest that CXXC1 and Foxp3 collaborate to regulate Treg homeostasis and function by promoting Treg signature gene expression through maintaining H3K4me3 modification.

Strengths:

Epigenetic regulation of Treg cells has been a constantly evolving area of research. The current study revealed CXXC1 as a previously unidentified epigenetic regulator of Tregs. The strong phenotype of the knockout mouse supports the critical role CXXC1 plays in Treg cells. Mechanistically, the link between CXXC1 and the maintenance of broad H3K4me3 domains is also a novel finding.

Weaknesses:

The authors addressed the reviewer's critiques fully in the revised manuscript.

Reviewer #1 (Public review):

In this study, the authors developed a mathematical model to predict human biological ages using physiological traits. This model provides a way to identify environmental and genetic factors that impact aging and lifespan.

Strength:

(1) The topic addressed by the authors - human age predication using physiological traits - is an extremely interesting, important, and challenging question in the aging field. One of the biggest challenges is the lack of well-controlled data from a large number of humans. However, the authors took this challenge and tried their best to extract useful information from available data.<br /> (2) Some of the findings can provide valuable guidelines for future experimental design for human and animal studies. For example, it was found that this mathematical model can best predict age when all different organ and physiological systems are sampled. This finding makes scenes in general, but can be, and have been, neglected when people use molecular markers to predict age. Most of those studies have used only one molecular trait or different traits from one tissue.

Weakness:

(1) As I mentioned above, the Biobank data used here are not designed for this current study, so there are many limitations for model development using these data, e.g., missing data points and irrelevant measurements for aging. This is a common caveat for human studies and has been discussed by the authors.<br /> (2) There is no validation dataset to verify the proposed model. The authors suggested that human biological age can be predicted with a high accuracy using 12 simple physiological measurements. It will be super useful and convincing if another biobank dataset containing those 12 traits can be applied to the current model.

Comments on revisions:

In this revision, the authors improved the manuscript by adding discussion of two main weaknesses about human data limitation and model validation. My several other specific concerns and suggestions are all properly resolved.

Reviewer #2 (Public review):

The fledgling field of epitranscriptomics has encountered various technical roadblocks with implications as to the validity of early epitranscriptomics mapping data. As a prime example, the low specificity of (supposedly) modification-specific antibodies for the enrichment of modified RNAs, has been ignored for quite some time and is only now recognized for its dismal reproducibility (between different labs), which necessitates the development of alternative methods for modification detection. Furthermore, early attempts to map individual epitranscriptomes using sequencing-based techniques are largely characterized by the deliberate avoidance of orthogonal approaches aimed at confirming the existence of RNA modifications that have been originally identified.

Improved methodology, the inclusion of various controls, and better mapping algorithms as well as the application of robust statistics for the identification of false-positive RNA modification calls have allowed revisiting original (seminal) publications whose early mapping data allowed making hyperbolic claims about the number, localization and importance of RNA modifications, especially in mRNA. Besides the existence of m6A in mRNA, the detectable incidence of RNA modifications in mRNAs has drastically dropped.

As for m5C, the subject of the manuscript submitted by Zhou et al., its identification in mRNA goes back to Squires et al., 2012 reporting on >10.000 sites in mRNA of a human cancer cell line, followed by intermittent findings reporting on pretty much every number between 0 to > 100.000 m5C sites in different human cell-derived mRNA transcriptomes. The reason for such discrepancy is most likely of a technical nature. Importantly, all studies reporting on actual transcript numbers that were m5C-modified relied on RNA bisulfite sequencing, an NGS-based method, that can discriminate between methylated and non-methylated Cs after chemical deamination of C but not m5C. RNA bisulfite sequencing has a notoriously high background due to deamination artifacts, which occur largely due to incomplete denaturation of double-stranded regions (denaturing-resistant) of RNA molecules. Furthermore, m5C sites in mRNAs have now been mapped to regions that have not only sequence identity but also structural features of tRNAs. Various studies revealed that the highly conserved m5C RNA methyltransferases NSUN2 and NSUN6 do not only accept tRNAs but also other RNAs (including mRNAs) as methylation substrates, which in combination account for most of the RNA bisulfite-mapped m5C sites in human mRNA transcriptomes. Is m5C in mRNA only a result of the Star activity of tRNA or rRNA modification enzymes, or is their low stoichiometry biologically relevant?

In light of the short-comings of existing tools to robustly determine m5C in transcriptomes, other methods, like DRAM-seq, aiming to map m5C independently of ex situ RNA treatment with chemicals, are needed to arrive at a more solid "ground state", from which it will be possible to state and test various hypotheses as to the biological function of m5C, especially in lowly abundant RNAs such as mRNA.

Importantly, the identification of >10.000 sites containing m5C increases through DRAM-Seq, increases the number of potential m5C marks in human cancer cells from a couple of 100 (after rigorous post-hoc analysis of RNA bisulfite sequencing data) by orders of magnitude. This begs the question, whether or not the application of these editing tools results in editing artefacts overstating the number of actual m5C sites in the human cancer transcriptome.

[Editors' note: earlier reviews have been provided here: https://doi.org/10.7554/eLife.98166.3.sa1; https://doi.org/10.7554/eLife.98166.2.sa1; https://doi.org/10.7554/eLife.98166.1.sa1]

for - carbon inequality - stats - carbon inequality - 5 months in our carbon budget - if everyone emitted like the top 1% - source - Oxfam - Carbon Inequality kills - 2024

Reviewer #1 (Public review):

Summary:

Tamoxifen resistance is a common problem in partially ER-positive patients undergoing endocrine therapy, and this manuscript has important research significance as it is based on clinical practical issues. The manuscript discovered that the absence of FRMD8 in breast epithelial cells can promote the progression of breast cancer, thus proposing the hypothesis that FRMD8 affects tamoxifen resistance and validated this hypothesis through a series of experiments. The manuscript has certain theoretical reference value.

Strengths:

At present, research on the role of FRMD8 in breast cancer is very limited. This manuscript leverages the MMTV-Cre+;Frmd8fl/fl;PyMT mouse model to study the role of FRMD8 in tamoxifen resistance, and single-cell sequencing technology discovered the interaction between FRMD8 and ESR1. At the mechanistic level, this manuscript has demonstrated two ways in which FRMD8 affects ERα, providing some new insights into the development of ER-positive breast cancer in patients who are resistant to tamoxifen.

Limitations:

Whether FRMD8 can become a biomarker should be verified in large clinical samples or clinical data.

Reviewer #1 (Public review):

Summary:

The article entitled "Pu.1/Spi1 dosage controls the turnover and maintenance of microglia in zebrafish and mammals" by Wu et al., identifies a role for the master myeloid developmental regulator Pu.1 in the maintenance of microglial populations in the adult. Using a non-homologous end joining knock-in strategy, the authors generated a pu.1 conditional allele in zebrafish, which reports wildtype expression of pu.1 with EGFP and truncated expression of pu.1 with DsRed after Cre-mediated recombination. When crossed to existing pu.1 and spi-b mutants, this approach allowed the authors to target a single allele for recombination and induce homozygous loss-of-function microglia in adults. This identified that although there is no short-term consequence to loss of pu.1, microglia lacking any functional copy of pu.1 are depleted over the course of months, even when spi-b is fully functional. The authors go on to identify reduced proliferation, increased cell death, and higher expression of tp53 in the pu.1 deficient microglia, as compared to the wild-type EGFP+ microglia. To extend these findings to mammals, the authors generated a conditional Pu.1 allele in mice and performed similar analyses, finding that loss of a single copy of Pu.1 resulted in similar long-term loss of Pu.1-deficient microglia. The conclusions of this paper are overall well supported by the data.

Strengths:

The genetic approaches here for visualizing the recombination status of an endogenous allele are very clever, and by comparing the turnover of wildtype and mutant cells in the same animal the authors can make very convincing arguments about the effect of chronic loss of pu.1. Likely this phenotype would be either very subtle or nonexistent without the point of comparison and competition with the wildtype cells.

Using multiple species allows for more generalizable results, and shows conservation of the phenomena at play.

The demonstration of changes to proliferation and cell death in concert with higher expression of tp53 is compelling evidence for the authors' argument.

Weaknesses:

This paper is very strong. It would benefit from further investigating the specific relationship between pu.1 and tp53 specifically. Does pu.1 interact with the tp53 locus? Specific molecular analysis of this interaction would strengthen the mechanistic findings.

Reviewer #1 (Public review):

Summary:

It is well known that neurons in the medial prefrontal cortex (mPFC) are involved in higher cognitive functions such as executive planning, motivational processing, and internal state-mediated decision-making. These internal states often correlate with the emotional states of the brain. While several studies point to the role of mPFC in regulating behavior based on such emotional states, the diversity of information processing in its sub-populations remains a less explored territory. In this study, the authors try to address this gap by identifying and characterizing some of these sub-populations in mice using a combination of projection-specific imaging, function-based tagging of neurons, multiple behavioral assays, and ex-vivo patch clamp recordings.

Strengths:

The authors targeted mPFC projections to the nucleus accumbens (NAc) and basolateral amygdala (BLA). Using the open field task (OFT), the authors identified four relevant behavioral states as well as neurons active while the animal was in the center region ("center-ON neurons"). By characterizing single-unit activity and using dimensionality reduction, the authors show differentiated coding of behavioral events at both the projection and functional levels. They further substantiate this effect by showing higher sensitivity of mPFC-BLA center-ON neurons during time spent in the open arms of the elevated plus maze (EPM). The authors then pivoted to the three-chamber social interaction (SI) assay to show the different subsets of neurons encode preference for social stimulus over non-social. This reveals an interesting diversity in the function of these sub-populations on multiple levels. Lastly, the authors used the tube test as a manipulation of the anxiety state of mice and compared behavioral differences before/after the OFT and social interaction tasks. This experiment revealed that "losers" of the tube test spend less time in the center of the open field while "winners" show a stronger preference for the familiar mouse over the object. Using patch-clamp experiments, the authors also found that "winners" exhibit stronger synaptic transmission in the mPFC-NAc projection while "losers" exhibit stronger synaptic transmission in the mPFC-BLA projection. Given the popularity of the tube test assay in rank determination, this provides useful insights into possible effects on anxiety levels and synaptic plasticity. Overall, the many experiments performed by the authors reveal interesting differences in mPFC neurons relative to their involvement in high or low anxiety behaviors, social preference, and social rank.

Weaknesses:

The authors focused primarily on female mice without commenting on the effect that sex differences would have on their results. While the authors have identified relevant behavioral states across the various behavioral tasks, there is still a missing link between them and "emotional states" - the phrase used by them emphatically throughout the manuscript. The authors have neither provided adequate references to satisfy this gap nor shared any data pertaining to relevant readouts such as cortisol levels. Both the projection-specific recordings and patch-clamp experiments, including histology reports in the manuscript, would provide essential information for anyone trying to replicate the results, especially since it's known that sub-populations in the BLA and NAc can have vastly different functions. The population-level analysis in the manuscript requires more rigor to reduce bias and statistical controls for establishing the significance of their results. Lastly, the tube test is used as a manipulation of the "emotional state" in several of the experiments. While the tube test can cause a temporary spike in anxiety of the participating mice, it is not known to produce a sustained effect - unless there are additional interventions such as forced social defeat. Thus, additional controls for these experiments are essential to support claims based on changes in the emotional state of mice. Apart from the methodology, the manuscript could also be improved with the addition of clear scatter points in all the plots along with detailed measures of the statistical tests such as exact p values and size of groups being compared.

Reviewer #1 (Public review):

Summary:

The authors in this study extensively investigate how telomere length (TL) regulates hTERT expression via non-telomeric binding of the telomere-associated protein TRF2. They conclusively show that TRF2 binding to long telomeres results in a reduction in its binding to the hTERT promoter. In contrast, short telomeres restore TRF2 binding in the hTERT promoter, recruiting repressor complexes like PRC2, and suppressing hTERT expression. The study presents several significant findings revealing a previously unknown mechanism of hTERT regulation by TRF2 in a TL-dependent manner

Strengths:

(1) A previously unknown mechanism linking telomere length and hTERT regulation through the non-telomeric TRF2 protein has been established strengthening the telomere biology understanding.

(2) The authors used both cancer cell lines and iPSCs to showcase their hypothesis and multiple parameters to validate the role of TRF2 in hTERT regulation.

(3) Comprehensive integration of the recent literature findings and implementation in the current study.

(4) In vivo validation of the findings.

(5) Rigorous controls and well-designed assays have been use.

Weaknesses:

(1) The authors should comment on the cell proliferation and morphology of the engineered cell lines with ST or LT.

(2) Also, the entire study uses engineered cell lines, with artificially elongated or shortened telomeres that conclusively demonstrate the role of hTERT regulation by TRF2 in telomere-length dependent manner, but using ALT negative cell lines with naturally short telomere length vs those with long telomeres will give better perspective. Primary cells can also be used in this context.

(3) The authors set up time-dependent telomere length changes by dox induction, which may differ from the gradual telomere attrition or elongation that occurs naturally during aging, disease progression, or therapy. This aspect should be explored.

(4) How does the hTERT regulation by TRF2 in a TL-dependent manner affect the ETS binding on hTERT mutant promoter sites?

(5) Stabilization of the G-quadruplex structures in ST and LT conditions along with the G4 disruption experimentation (demonstrated by the authors) will strengthen the hypothesis.

(6) The telomere length and the telomerase activity are not very consistent (Figure 2A, and S1A, Figure 4B and S3). Please comment.

(7) Please comment on the other telomere-associated proteins or regulatory pathways that might contribute to hTERT expression based on telomere length.

for - Christine Wamsler - Lund University - homepage - from - youtube - Mindfulness World Community - Awareness, Care and Sustainability for Our Earth - https://hyp.is/GCUJ1APHEfCcr_vvv3lAFw/www.youtube.com/watch?v=CTUc_0GroGM

• to - paper - An Interdisciplinary Model to Foster Existential Resilience and Transformation

  • https://hyp.is/iKxTmgPJEfCkN2PkMDmg1g/www.mdpi.com/2078-1547/16/1/5

• to - paper - Engaging high-income earners in climate action : Policy insights from survey experiments

  • for Deep Humanity Wealth 2 Wellth program
  • https://hyp.is/MIc0DgPKEfC_Z5v_n8P8mA/www.sciencedirect.com/science/article/pii/S0921800924002842

• to - paper - Revolutionising sustainability leadership and education : addressing the human dimension to support flourishing, culture and system transformation

  • for - LCE leadership academy
  • https://hyp.is/nLBHtAPLEfCvUUNZrc_uqw/link.springer.com/article/10.1007/s10584-023-03636-8

• to - The System Within : Addressing the inner dimensions of sustainability and systems change

  • https://hyp.is/VDAcFgPMEfCBPkvnTCjp8w/www.clubofrome.org/wp-content/uploads/2024/05/Earth4All_Deep_Dive_Jamie_Bristow.pdf
• to - paper - Transformative Climate Resilience Education for Children and Youth: From Climate Anxiety to Resilience, Creativity and Regeneration, Literature review conducted for the ERASMUS+ Project 2023-1-SE01-KA220-SCH-000158705

  - for - SRG/TPF/LCE ward-level afterschool outreach program but it's currently a dead link and inaccessible

• to - IMAGINE sustainability : integrated inner-outer transformation in research, education and practice
  • for - Deep Humanity open source praxis
  • Human Interior Transformation (HIT) and
  • Social Exterior Transformation (SET) //
  • https://hyp.is/5_GsSAPNEfC82DMDillDTw/link.springer.com/article/10.1007/s11625-023-01368-3

research areas - sustainable cities - collaborative governance - city-citizen collaboration - citizen participation - sustainability and wellbeing - sustainability transformation - inner development goals - inner transformation - inner transition - existential sustainability

Reviewer #1 (Public review):

Summary:

This paper introduces a new class of machine learning models for capturing how likely a specific nucleotide in a rearranged IG gene is to undergo somatic hypermutation. These models modestly outperform existing state-of-the-art efforts, despite having fewer free parameters. A surprising finding is that models trained on all mutations from non-functional rearrangements give divergent results from those trained on only silent mutations from functional rearrangements.

Strengths:

(1) The new model structure is quite clever and will provide a powerful way to explore larger models.

(2) Careful attention is paid to curating and processing large existing data sets.

(3) The authors are to be commended for their efforts to communicate with the developers of previous models and use the strongest possible versions of those in their current evaluation.

Weaknesses:

(1) 10x/single cell data has a fairly different error profile compared to bulk data. A synonymous model should be built from the same `briney` dataset as the base model to validate the difference between the two types of training data.

(3) The decision to test only kernels of 7, 9, and 11 is not described. The selection/optimization of embedding size is not explained. The filters listed in Table 1 are not defined.

Reviewer #1 (Public review):

In this manuscript, Purzner and colleagues examine the role of Ezh2 in cerebellar development and tumorigenesis using animal models of SHH medulloblastoma (MB). While Ezh2 plays a relatively minor role in granule neuron development and SHH MB, the authors demonstrate that Ezh2 inhibition, when combined with enforced cell cycle exit, promotes MB cell differentiation and potentially reduces malignancy. Overall, this study is solid and provides valuable insights into Ezh2 regulation in cerebellar development and SHH-MB tumorigenesis.

Strengths:

The authors investigate the role of Ezh2 in granule neuronal differentiation during cerebellar development and medulloblastoma (MB) progression, integrating multi-omics for a comprehensive epigenetic analysis. The use of Ezh2 conditional knockout (cKO) mice and combination therapy with Ezh2 and CDK4/6 inhibitors shows a promising strategy to induce terminal differentiation in MB cells, with potential therapeutic implications. Additionally, analysis of human SHH-MB samples reveals that higher EZH2 expression correlates with worse survival, indicating the clinical relevance.

Weaknesses:

The study does not fully explore compensatory mechanisms of PRC2 given that the phenotype of Ezh2 conditional knockout (cKO) in GNP development and MB tumor formation is relatively mild.

Reviewer #1 (Public review):

Summary:

This study provides valuable and comprehensive information about the SARS-CoV-2 seroprevalence during 2021 and 2022 in different regions of Bolivia. Moreover, data on immune responses against the SARS-CoV-2 variants based on neutralization tests denotes the presence of several virus variants circulating in the Bolivian population. Evidence for seroprevalence data provided by the authors is solid, across the study period, while data regarding variant circulation is limited to the early stages of the pandemic.

Strengths:

The major strength of this study is that it provided nationwide seroprevalence estimates from infection and/or vaccination based on antibodies against both spike and the nucleocapsid protein in a large representative sample of sera collected at two time points from all departments of Bolivia, gaining insight into COVID-19 epidemiology. On the other hand, data from virus neutralization assays inferred the circulation during the study period of four SARS-CoV-2 variants in the population. Overall, the study results provide an overview of the level of viral transmission and vaccination and insights into the spread across the country of SARS-CoV-2 variants.

Weaknesses:

The assessment of a Lambda variant that circulated in several neighboring countries (Peru, Chile, and Argentina), which had a significant impact on the COVID-19 pandemic in the region, may have strengthened the study to contrast Gamma spread. In addition, even though neutralizing antibodies can certainly reveal previous infections of SARSCOV2 variants in the population, it is of limited value to infer from this information some potential timing estimates of specific variant circulation, considering the heterogeneous effects that past infections, vaccinations, or a combination of both could have on the level of variant-specific neutralizing antibodies and/or their cross-neutralization capacity.

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

The conclusions of this paper are well supported by data, particularly regarding seroprevalence that reliably reflects the epidemiology of COVID-19 in Bolivia, and seroprevalence trends in other low- and middle-income countries.

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

Since this is the first study that has been conducted to assess indicators of immunity against SARS-CoV-2 in the population of Bolivia at a nationwide scale, seroprevalence data provided by geographic regions at two time points can be useful as a reference for potential retrospective global meta-analysis and to further explore and compare the risk factors for infection, variant distribution, and the impact on infection and vaccination, gaining deeper insights into understanding the evolution of the COVID-19 pandemic in Bolivia and in the region.

Reviewer #1 (Public review):

Summary:

This study demonstrates the significant role of secretory leukocyte protease inhibitor (SLPI) in regulating B. burgdorferi-induced periarticular inflammation in mice. They found that SLPI-deficient mice showed significantly higher B. burgdorferi infection burden in ankle joints compared to wild-type controls. This increased infection was accompanied by infiltration of neutrophils and macrophages in periarticular tissues, suggesting SLPI's role in immune regulation. The authors strengthened their findings by demonstrating a direct interaction between SLPI and B. burgdorferi through BASEHIT library screening and FACS analysis. Further investigation of SLPI as a target could lead to valuable clinical applications.

The conclusions of this paper are mostly well supported by data. And the authors were responsive to the reviewers' comments.

Comments on revised version:

The authors have thoroughly addressed the previous concerns and improved the manuscript. The revisions have strengthened both the conclusions. I have no additional suggestions for improvement and recommend this manuscript for publication.

Reviewer #2 (Public review):

Summary:

In this manuscript, authors have tried to repurpose cipargamin (CIP), a known drug against Plasmodium and Toxoplasma against Babesia. They proved the efficacy of CIP on Babesia in nanomolar range. In silico analyses revealed the drug resistance mechanism through a single amino acid mutation at amino acid position 921 on the ATP4 gene of Babesia. Overall, the conclusions drawn by the authors are well justified by their data. I believe this study opens up a novel therapeutic strategy against babesiosis.

Strengths:

Authors have carried out a comprehensive study. All the experiments performed were carried out methodically and logically.

Reviewer #1 (Public review):

Summary:

As our understanding of the immune system increases it becomes clear that murine models of Immunity cannot always prove an accurate model system for human immunity. However, mechanistic studies in humans are necessarily limited. To bridge this gap many groups have worked on developing humanised mouse models in which human immune cells are introduced into mice allowing their fine manipulation. However, since human immune cells will attack murine tissues, it has proven complex to establish a human-like immune system in mice. To help address this Vecchione et al, have previously developed several models using human cell transfer into mice with or without human thymic fragments that allow negative selection of autoreactive cells. In this report they focus on the examination of the function of the B-helper CD4 T-cell subsets T-follicular helper (Tfh) and T-peripheral helper (Tph) cells. They demonstrate that these cells are able to drive both autoantibody production and can also induce B-cell independent autoimmunity.

Strengths:

A strength of this paper is that currently there is no well-established model for Tfh or Tph in HIS mice and that currently there is no clear murine Tph equivalent making new models for the study of this cell type of value. Equally, since many HIS mice struggle to maintain effective follicular structures Tfh models in HIS mice are not well established giving additional value to this model.

Weaknesses:

A weakness of the paper is that the models seem to lack a clear ability to generate germinal centres in which Tfh may exert some of their key functions. In some cases, the definition of Tph-like does not seem to differentiate well between Tph and highly activated CD4 T-cells in general, partly since the literature around these cells has not fully resolved this point.

Reviewer #1 (Public review):

This paper by Ionescu et al. applies novel brain connectivity measures based on fMRI and serotonin PET both at baseline and following ecstasy use in rats. There are multiple strengths to this manuscript. First, the use of connectivity measures using temporal correlations of 11C-DASB PET, especially when combined with resting state fMRI, is highly novel and powerful. The effects of ecstasy on molecular connectivity of the serotonin network and salience network are also quite intriguing.

The authors discussed their use of high-dose (1.3%) isolfurane in the context of a recent consensus paper on rat fMRI (Grandjean et al., "A Consensus Protocol for Functional Connectivity Analysis in the Rat Brain.") which found that medetomidine combined with low dose isoflurane provided optimal control of physiology and fMRI signal. The authors acknowledge their suboptimal anaesthetic regimen, which was chosen before the publication of the consensus paper. This likely explains, in part, why fMRI ICs in figure 2A appear fairly restricted.

The PET ICs appear less bilateral than the fMRI ICs, which the authors attribute to lower SNR.

Reviewer #1 (Public review):

Summary:

This manuscript aimed to study the role of Rudhira (also known as Breast Carcinoma Amplified Sequence 3), an endothelium-restricted microtubules-associated protein, in regulating of TGFβ signaling. The authors demonstrate that Rudhira is a critical signaling modulator for TGFβ signaling by releasing Smad2/3 from cytoskeletal microtubules and how that Rudhira is a Smad2/3 target gene. Taken together, the authors provide a model of how Rudhira contributes to TGFβ signaling activity to stabilize the microtubules, which is essential for vascular development.

Strengths:

The study used different methods and techniques to achieve aims and support conclusions, such as Gene Ontology analysis, functional analysis in culture, immunostaining analysis, and proximity ligation assay. This study provides unappreciated additional layer of TGFβ signaling activity regulation after ligand-receptor interaction.

Weaknesses:

(1) It is unclear how current findings provide a better understanding of Rudhira KO mice, which the authors published some years ago.

(2) Why do they use HEK cells instead of SVEC cells in Fig 2 and 4 experiments?

(3) A model shown in Fig 5E needs improvement to grasp their findings easily.

Reviewer #2 (Public review):

Summary:

The authors provide a compelling method for characterizing communication within brain networks. The study engages important, biologically pertinent, concerns related to the balance of dynamics and structure in assessing the focal points of brain communication. The methods are clear, and seem broadly applicable, although they require some forethought about data and modeling choices.

Strengths:

The study is well-developed, providing overall clear exposition of relevant methods, as well as in-depth validation of the key network structural and dynamical assumptions. The questions and concerns raised in reading the text were always answered in time, with straightforward figures and supplemental materials.

Weaknesses:

In earlier drafts of the work, the narrative structure at times conflicts with the interpretability, however, this was greatly improved during revisions. The only remaining limitation for broad applicability lies in the full observability required in the current paradigm, however, the authors point at avenues for relaxing this assumption, which could be fruitful next steps for researchers aiming to deploy this work to EM or two-photon based datasets.

Reviewer #1 (Public review):

Summary:

The paper addresses the problem of optimising the mapping of serum antibody responses against a known antigen. It uses the croEM analysis of polyclonal Fabs to antibody genes, with the ultimate aim of getting complete and accurate antibody sequences. The method, commonly termed EMPEM, is becoming increasingly used to understand responses in convalescent sera and optimisation of the workflows and provision of openly available tools is of genuine value to a growing number of people.

The authors do not address the experimental aspects of the methods and do not present novel computational tools, rather they use a series of established computational methods to provide workflows that simplify the interpretation of the EM map in terms of the sequences of dominant antibodies.

Strengths:

The paper is well-written and clearly argued. The tests constructed seem appropriate and fair and demonstrate that the workflow works pretty well. For a small subset (~17%) of the EMPEM maps analysed the workflow was able to get convincing assignments of the V-genes.

Reviewer #2 (Public review):

Summary:

Mehta et al., in constructing E. coli strains unable to synthesize polyamines, noted that strains deficient in putrescine synthesis showed decreased movement on semisolid agar. They show that strains incapable of synthesizing putrescine have decreased expression of Type I pilin and, hence, decreased ability to perform pilin-dependent surface motility.

Strengths:

The authors characterize the specific polyamine pathways that are important for this phenomenon. RNAseq provides a detailed overview of gene expression in the strain lacking putrescine. They rule out potential effects of pilin phase variation on the phenotype. The data suggest homeostatic control of polyamine synthesis and metabolic changes in response to putrescine.

Weaknesses:

The authors do not, in the end, uncover the molecular details of pilin expression per se, but that would require significantly more analyses and data; the mechanisms of pilin regulation are complicated and still not completely understood.

Reviewer #1 (Public review):

Summary:

In this interesting and original paper, the authors examine the effect that heat stress can have on the ability of bacterial cells to evade infection by lytic bacteriophages. Briefly, the authors show that heat stress increases the tolerance of Klebsiella pneumoniae to infection by the lytic phage Kp11. They also argue that this increased tolerance facilitates the evolution of genetically encoded resistance to the phage. In addition, they show that heat can reduce the efficacy of phage therapy. Moreover, they define a likely mechanistic reason for both tolerance and genetically encoded resistance. Both lead to a reorganization of the bacterial cell envelope, which reduces the likelihood that phage can successfully inject their DNA.

Strengths:

I found large parts of this paper well-written and clearly presented. I also found many of the experiments simple yet compelling. For example, the experiments described in Figure 3 clearly show that prior heat exposure can affect the efficacy of phage therapy. In addition, the experiments shown in Figures 4 and 6 clearly demonstrate the likely mechanistic cause of this effect. The conceptual Figure 7 is clear and illustrates the main ideas well. I think this paper would work even without its central claim, namely that tolerance facilitates the evolution of resistance. The reason is that the effect of environmental stressors on stress tolerance has to my knowledge so far only been shown for drug tolerance, not for tolerance to an antagonistic species.

Weaknesses:

I did not detect any weaknesses that would require a major reorganization of the paper, or that may require crucial new experiments. However, the paper needs some work in clarifying specific and central conclusions that the authors draw. More specifically, it needs to improve the connection between what is shown in some figures, how these figures are described in the caption, and how they are discussed in the main text. This is especially glaring with respect to the central claim of the paper from the title, namely that tolerance facilitates the evolution of resistance. I am sympathetic to that claim, especially because this has been shown elsewhere, not for phage resistance but for antibiotic resistance. However, in the description of the results, this is perhaps the weakest aspect of the paper, so I'm a bit mystified as to why the authors focus on this claim. As I mentioned above, the paper could stand on its own even without this claim.

More specific examples where clarification is needed:

(1) A key figure of the paper seems to be Figure 2D, yet it was one of the most confusing figures. This results from a mismatch between the accompanying text starting on line 92 and the figure itself. The first thing that the reader notices in the figure itself is the huge discrepancy between the number of viable colonies in the absence of phage infection at the two-hour time point. Yet this observation is not even mentioned in the main text. The exclusive focus of the main text seems to be on the right-hand side of the figure, labeled "+Phage". It is from this right-hand panel that the authors seem to conclude that heat stress facilitates the evolution of resistance. I find this confusing, because there is no difference between the heat-treated and non-treated cells in survivorship, and it is not clear from this data that survivorship is caused by resistance, not by tolerance/persistence. (The difference between tolerance and resistance has only been shown in the independent experiments of Figure 1B.) Figure 2F supports the resistance claim, but it is not one of the strongest experiments of the paper, because the author simply only used "turbidity" as an indicator of resistance. In addition, the authors performed the experiments described therein at small population sizes to avoid the presence of resistance mutations. But how do we know that the turbidity they describe does not result from persisters?

I see three possibilities to address these issues. First, perhaps this is all a matter of explaining and motivating this particular experiment better. Second, the central claim of the paper may require additional experiments. For example, is it possible to block heat induced tolerance through specific mutations, and show that phage resistance does not evolve as rapidly if tolerance is blocked? A third possibility is to tone down the claim of the paper, and make it about heat tolerance rather than the evolution of heat resistance.

A minor but general point here is that in Figure 2D and in other figures, the labels "-phage" and "+phage" do not facilitate understanding, because they suggest that cells in the "-phage" treatment have not been exposed to phage at all, but that is not the case. They have survived previous phage treatment and are then replated on media lacking phage.

(2) Another figure with a mismatch between text and visual materials is Figure 5, specifically Figures 5B-F. The figure is about two different mutants, and it is not even mentioned in the text how these mutants were identified, for example in different or the same replicate populations. What is more, the two mutants are not discussed at all in the main text. That is, the text, starting on line 221 discusses these experiments as if there was only one mutant. This is especially striking as the two mutants behave very differently, as, for example, in Figure 5C. Implicitly, the text talks about the mutant ending in "...C2", and not the one ending in "...C1". To add to the confusion, the text states that the (C2) mutant shows a change in the pspA gene, but in Figure 5f, it is the other (undiscussed) mutant that has a mutation in this gene. Only pspA is discussed further, so what about the other mutants? More generally, it is hard to believe that these were the only mutants that occurred in the genome during experimental evolution. It would be useful to give the reader a 2-3 sentence summary of the genetic diversity that experimental evolution generated.

Reviewer #1 (Public review):

This manuscript presents an interesting exploration of the potential activation mechanisms of DLK following axonal injury. While the experiments are beautifully conducted and the data are solid, I feel that there is insufficient evidence to fully support the conclusions made by the authors.

In this manuscript, the authors exclusively use the puc-lacZ reporter to determine the activation of DLK. This reporter has been shown to be induced when DLK is activated. However, there is insufficient evidence to confirm that the absence of reporter activation necessarily indicates that DLK is inactive. As with many MAP kinase pathways, the DLK pathway can be locally or globally activated in neurons, and the level of DLK activation may depend on the strength of the stimulation. This reporter might only reflect strong DLK activation and may not be turned on if DLK is weakly activated.

As noted by the authors, DLK has been implicated in both axon regeneration and degeneration. Following axotomy, DLK activation can lead to the degeneration of distal axons, where synapses are located. This raises an important question: how is DLK activated in distal axons? The authors might consider discussing the significance of this "synapse connection-dependent" DLK activation in the broader context of DLK function and activation mechanisms.

Reviewer #1 (Public review):

Summary:

The authors of this study set out to find RNA binding proteins in the CNS in cell-type specific sequencing data and discover that the cardiomyopathy-associated protein RBM20 is selectively expressed in olfactory bulb glutamatergic neurons and PV+ GABAergic neurons. They make an HA-tagged RBM20 allele to perform CLIP-seq to identify RBM20 binding sites and find direct targets of RBM20 in olfactory bulb glutmatergic neurons. In these neurons, RBM20 binds intronic regions. RBM20 has previously been implicated in splicing, but when they selectively knockout RBM20 in glutamatergic neurons they do not see changes in splicing, but they do see changes in RNA abundance, especially of long genes with many introns, which are enriched for synapse-associated functions. These data show that RBM20 has important functions in gene regulation in neurons, which was previously unknown, and they suggest it acts through a mechanism distinct from what has been studied before in cardiomyocytes.

Strengths:

The study finds expression of the cardiomyopathy-associated RNA binding protein RBM20 in specific neurons in the brain, opening new windows into its potential functions there.

The study uses CLIP-seq to identify RBM20 binding RNAs in olfactory bulb neurons.

Conditional knockout of RBM20 in glutamatergic or PV neurons allows the authors to detect mRNA expression that is regulated by RBM20.

The data include substantial controls and quality control information to support the rigor of the findings.

Weaknesses:

The authors do not fully identify the mechanism by which RBM20 acts to regulate RNA expression in neurons, though they do provide data suggesting that neuronal RBM20 does not regulate alternate splicing in neurons, which is an interesting contrast to its proposed mechanism of function in cardiomyocytes. Discovery of the RNA regulatory functions of RBM20 in neurons is left as a question for future studies.

The study does not identify functional consequences of the RNA changes in the conditional knockout cells, so this is also a question for the future.

Reviewer #1 (Public review):

Summary:

The aim of this paper is to develop a simple method to quantify fluctuations in the partitioning of cellular elements. In particular, they propose a flow-cytometry-based method coupled with a simple mathematical theory as an alternative to conventional imaging-based approaches.

Strengths:

The approach they develop is simple to understand and its use with flow-cytometry measurements is clearly explained. Understanding how the fluctuations in the cytoplasm partition vary for different kinds of cells is particularly interesting.

Weaknesses:

The theory only considers fluctuations due to cellular division events. This seems a large weakness because it is well known that fluctuations in cellular components are largely affected by various intrinsic and extrinsic sources of noise and only under particular conditions does partitioning noise become the dominant source of noise.

Reviewer #1 (Public review):

Summary:

This study was motivated by the general claim that delayed development of cognitive control can be beneficial for learning, and investigated this claim in the specific domain of conceptual development. A comprehensive set of computational model simulations showed that delaying the onset of semantic control produces faster learning with only minimal effects on conceptual abstraction. The simulations also showed that control was most effective at intermediate levels between modality-specific "spokes" and the multimodal "hub". A meta-analysis of developmental data was consistent with the claim of delayed onset of semantic control: young children show substantially better semantic knowledge than the ability to constrain that knowledge to a specific task at hand.

Strengths:

The computational modelling is based on a very well-established model of semantic cognition, which means that the simulations allow exploring the specific issues under investigation here in the context of a model that accounts for a very large set of semantic cognition phenomena. The simulations are comprehensive - manipulating different parameters of the model provides important insights into how (and why) it works.

In addition to simulations exploring delayed maturation, there is an exploration of where semantic control is most effective, yielding the interesting result that control is most effective when it targets intermediate levels of semantic processing. To my knowledge, this is a novel finding and a concrete prediction for future testing.

The meta-analysis is designed in a very clever way that allows extracting evidence of semantic control from a large body of prior work. The results are quite clear and compelling in showing that semantic knowledge is acquired before children are able to use task demands to constrain the use of that knowledge.

Weaknesses:

Computational models of cognition inherently require simplification in order to focus on the mechanisms under investigation. However, it is also important to keep these simplifications in mind because they limit the generality of the inferences that can be made from the simulation results. Two aspects are important in this context:

(1) The multimodal structure was orthogonal to the surface similarity structure of the concepts to be learned. It is certainly true that multimodal structure does not perfectly mirror surface similarity, but closely related things tend to be perceptually similar. There are exceptions (whales, penguins, etc.), but they are *exceptional*, not typical. It may be that the somewhat extreme dissociation of multimodal and surface similarity structures creates demands that are not faced in natural conceptual development.

(2) Much of the benefit of delayed semantic control seems to be because the model is not penalised for activating task-irrelevant features. This blurs the distinction between being aware of a feature and making a response based on that feature. A full model that also includes a response layer could become a lot more complicated and more difficult to understand, so maybe there is an advantage to using a simpler architecture.

In addition, there is a bit of a misalignment between the model simulations and the meta-analysis. In the model, there are distinct modality-specific "spokes" and control is required in order to focus on modality/spoke in a task-appropriate way. The meta-analysis does not compare a task-defined selection of a modality; it compares the selection of taxonomic vs thematic relations, both of which are multimodal. One way to resolve this is to say that taxonomic and thematic relations are also represented in distinct sub-systems of semantic knowledge and semantic control is needed to select between them in a task-appropriate way.

This is particularly relevant to the inference at the bottom of p. 38: "taxonomic and thematic relationships ...[are]... both being encoded within the same system of representation", which seems in direct contradiction to the present results, or at least to the logic of combining these simulations with this meta-analysis. The simulations are based on semantic control being used to select/constrain the correct distinct sub-system (modality-specific spoke); the meta-analysis is based on semantic control being used to select/constrain the correct relationship type. If these two things are analogous in some way, then the relationship type has to be something like a distinct sub-system.

Reviewer #1 (Public review):

Summary:

Pavel et al. analyzed a cohort of atrial fibrillation (AF) patients from the University of Illinois at Chicago, identifying TTN truncating variants (TTNtvs) and TTN missense variants (TTNmvs). They reported a rare TTN missense variant (T32756I) associated with adverse clinical outcomes in AF patients. To investigate its functional significance, the authors modeled the TTN-T32756I variant using human induced pluripotent stem cell-derived atrial cardiomyocytes (iPSC-aCMs). They demonstrated that mutant cells exhibit aberrant contractility, increased activity of the cardiac potassium channel KCNQ1 (Kv7.1), and dysregulated calcium homeostasis. Interestingly, these effects occurred without compromising sarcomeric integrity. The study further identified increased binding of the titin-binding protein Four-and-a-Half Lim domains 2 (FHL2) with KCNQ1 and its modulatory subunit KCNE1 in the TTN-T32756I iPSC-aCMs.

Strengths:

This work has translational potential, suggesting that targeting KCNQ1 or FHL2 could represent a novel therapeutic strategy for improving cardiac function. The findings may also have broader implications for treating patients with rare, disease-causing variants in sarcomeric proteins and underscore the importance of integrating genomic analysis with experimental evidence to advance AF research and precision medicine.

Weaknesses:

(1) Variant Identification: It is unclear how the TTN missense variant (T32756I) was identified using REVEL, as none of the patients' parents reportedly carried the mutation or exhibited AF symptoms. Are there other TTN variants identified in the three patients carrying TTN-T32756I? Clarification on this point is necessary.

(2) Patient-Specific iPSC Lines: Since the TTN-T32756I variant was modeled using only one healthy iPSC line, it is unclear whether patient-specific iPSC-derived atrial cardiomyocytes would exhibit similar AF-related phenotypes. This limitation should be addressed.

(3) Hypertension as a Confounding Factor: The three patients carrying TTN-T32756I also have hypertension. Could the hypertension associated with this variant contribute secondarily to AF? The authors should discuss or rule out this possibility.

(4) FHL2 and KCNQ1-KCNE1 Interaction: Immunostaining data demonstrating the colocalization of FHL2 with the KCNQ1-KCNE1 (MinK) complex in TTN-T32756I iPSC-aCMs are needed to strengthen the mechanistic findings.

(5) Functional Characterization of FHL2-KCNQ1-KCNE1 Interaction: Additional functional assays are necessary to characterize the interaction between FHL2 and the KCNQ1-KCNE1 complex in TTN-T32756I iPSC-aCMs to further validate the proposed mechanism.

Reviewer #1 (Public review):

Polymers of orthophosphate of varying lengths are abundant in prokaryotes and some eukaryotes where they regulate many cellular functions. Though they exist in metazoans, few tools exist to study their function. This study documents the development of tools to extract, measure, and deplete inorganic polyphosphates in *Drosophila*. Using these tools, the authors show:

(1) that polyP levels are negligible in embryos and larvae of all stages while they are feeding. They remain high in pupae but their levels drop in adults.

(2) that many cells in tissues such as the salivary glands, oocytes, haemocytes, imaginal discs, optic lobe, muscle, and crop, have polyP that is either cytoplasmic or nuclear (within the nucleolus).

(3) that polyP is necessary in plasmatocytes for blood clotting in Drosophila.

(4) that ployP controls the timing of eclosion.

The tools developed in the study are innovative, well-designed, tested, and well-documented. I enjoyed reading about them and I appreciate that the authors have gone looking for the functional role of polyP in flies, which hasn't been demonstrated before. The documentation of polyP in cells is convincing as its role in plasmatocytes in clotting. Its control of eclosion timing, however, could result from non-specific effects of expressing an exogenous protein in all cells of an animal. The RNAseq experiments and their associated analyses on polyP-depleted animals and controls have not been discussed in sufficient detail. In its current form, the data look to be extremely variable between replicates and I'm therefore unsure of how the differentially regulated genes were identified.

It is interesting that no kinases and phosphatases have been identified in flies. Is it possible that flies are utilising the polyP from their gut microbiota? It would be interesting to see if these signatures go away in axenic animals.

Reviewer #1 (Public review):

Summary:

This manuscript uses a diverse isolate collection of Streptococcus pneumoniae from hospital patients in the Netherlands to understand the population-level genetic basis of growth rate variation in this pathogen, which is a key determinant of S. pneumoniae within-host fitness. Previous efforts have studied this phenomenon in strain-specific comparisons, which can lack the statistical power and scope of population-level studies. The authors collected a rigorous set of in vitro growth data for each S. pneumoniae isolate and subsequently paired growth curve analysis with whole-genome analyses to identify how phylogenetics, serotype, and specific genetic loci influence in vitro growth. While there were noticeable correlations between capsular serotype and phylogeny with growth metrics, they did not identify specific loci associated with altered in vitro growth, suggesting that these phenotypes are controlled by the collective effect of the entire genetic background of a strain. This is an important finding that lays the foundation for additional, more highly-powered studies that capture more S. pneumoniae genetic diversity to identify these genetic contributions.

Strengths:

(1) The authors were able to completely control the experimental and genetic analyses to ensure all isolates underwent the same analysis pipeline to enhance the rigor of their findings.

(2) The isolate collection captures an appreciable amount of S. pneumoniae diversity and, importantly, enables disentangling the contributions of the capsule and phylogenetic background to growth rates.

(3) This study provides a population-level, rather than strain-specific, view of how genetic background influences the growth rate in S. pneumoniae. This is an advance over previous studies that have only looked at smaller sets of strains.

(4) The methods used are well-detailed and robust to allow replication and extension of these analyses. Moreover, the manuscript is very well written and includes a thoughtful and thorough discussion of the strengths and limitations of the current study.

Weaknesses:

(1) As acknowledged by the authors, the genetic diversity and sample size of this newly collected isolate set are still limited relative to the known global diversity of S. pneumoniae, which evidently limits the power to detect loci with smaller/combinatorial contributions to growth rate (and ultimately infection).

(2) The in vitro growth data is limited to a single type of rich growth medium, which may not fully reflect the nutritional and/or selective pressures present in the host.

(3) The current study does not use genetic manipulation or in vitro/in vivo infection models to experimentally test whether alteration of growth rates as observed in this study is linked to virulence or successful infection. The availability of a naturally diverse collection with phylogenetic and serotype combinations already identified as interesting by the authors provides a strong rationale for wet-lab studies of these phenotypes.

Reviewer #1 (Public review):

Summary:

This work integrates two timepoints from the Adolescent Brain Cognitive Development (ABCD) Study to understand how neuroimaging, genetic, and environmental data contribute to the predictive power of mental health variables in predicting cognition in a large early adolescent sample. Their multimodal and multivariate prediction framework involves a novel opportunistic stacking model to handle complex types of information to predict variables that are important in understanding mental health-cognitive performance associations.

Strengths:

The authors are commended for incorporating and directly comparing the contribution of multiple imaging modalities (task fMRI, resting state fMRI, diffusion MRI, structural MRI), neurodevelopmental markers, environmental factors, and polygenic risk scores in a novel multivariate framework (via opportunistic stacking), as well as interpreting mental health-cognition associations with latent factors derived from partial least squares. The authors also use a large well-characterized and diverse cohort of adolescents from the ABCD Study. The paper is also strengthened by commonality analyses to understand the shared and unique contribution of different categories of factors (e.g., neuroimaging vs mental health vs polygenic scores vs sociodemographic and adverse developmental events) in explaining variance in cognitive performance

Weaknesses:

The paper is framed with an over-reliance on the RDoC framework in the introduction, despite deviations from the RDoC framework in the methods. The field is also learning more about RDoC's limitations when mapping cognitive performance to biology. The authors also focus on a single general factor of cognition as the core outcome of interest as opposed to different domains of cognition. The authors could consider predicting mental health rather than cognition. Using mental health as a predictor could be limited by the included 9-11 year age range at baseline (where many mental health concerns are likely to be low or not well captured), as well as the nature of how the data was collected, i.e., either by self-report or from parent/caregiver report.

Reviewer #1 (Public review):

Summary:

The current study by Xing et al. establishes the methodology (machine vision and gaze pose estimation) and behavioral apparatus for examining social interactions between pairs of marmoset monkeys. Their results enable unrestrained social interactions under more rigorous conditions with detailed quantification of position and gaze. It has been difficult to study social interactions using artificial stimuli, as opposed to genuine interactions between unrestrained animals. This study makes an important contribution for studying social neuroscience within a laboratory setting that will be valuable to the field.

Strengths:

Marmosets are an ideal species for studying primate social interactions due to their prosocial behavior and the ease of group housing within laboratory environments. They also predominantly orient their gaze through head movements during social monitoring. Recent advances in machine vision pose estimation set the stage for estimating 3D gaze position in marmosets but require additional innovation beyond DeepLabCut or equivalent methods. A six-point facial frame is designed to accurately fit marmoset head gaze. A key assumption in the study is that head gaze is a reliable indicator of the marmoset's gaze direction, which will also depend on the eye position. Overall, this assumption has been well supported by recent studies in head-free marmosets. Thus the current work introduces an important methodology for leveraging machine vision to track head gaze and demonstrates its utility for use with interacting marmoset dyads as a first step in that study.

Weaknesses:

One weakness that should be easily addressed is that no data is provided to directly assess how accurate the estimated head gaze is based on calibrations of the animals, for example, when they are looking at discrete locations like faces or video on a monitor. This would be useful to get an upper bound on how accurate the 3D gaze vector is estimated to be, for planned use in other studies. Although the accuracy appears sufficient for the current results, it would be difficult to know if it could be applied in other contexts where more precision might be necessary.

for - Great Separations, Three Great Separations, alienation, alienation - industrial revolution, John Ikerd, 3 separation - from - Post Capital Philanthropy Webinar 1 - Alnoor Ladha - Lynn Murphy - 2023 - Title - The Three “Great Separations” that Unravelled Our Connection to Earth and Each Other - Author - John Kkerd

from - story of separation - Post Capitalist Philanthropy Webinar 1 - Alnoor Ladha - Lynn Murphy - 2023 - https://hyp.is/kSvpDre2Ee-CsF-EO4pwTg/www.youtube.com/watch?v=dk6F4IlEbAk

Reviewer #1 (Public review):

The current manuscript by Bendeker et al. (2024) presents a new platform, MorphoCellSorter, for performing population wide microglial morphological analyses. This method adds to the many programs/platforms available to determine characteristics of microglial morphology; however, MorphoCellSorter is unique in that it uses Andrew's plotting to rank populations of cells together (in control and experimental groups) and present "big picture" views of how entire populations of microglia alter under different conditions. In their ranking system, Bendeker et al. (2024) use PCA to determine which of the morphological characteristics most define microglial populations, avoiding user subjective biases to determine these parameters. Compared to "expert" evaluators, MorphoCellSorter appears to perform consistently and accurately, including in different types of tissue preservation methods and in live cells, a key feature of the program. In addition, the researchers point out that this platform can be used across a wide array of imaging techniques and most microscopes that are available in a basic research lab. There are minor concerns about the platform's utility in analyzing embryonic microglia and primary microglial cultures, but overall, this platform will be another useful tool for microglial researchers to consider using in future studies. Furthermore, the method of morphological assessment aligns with the current direction of the field in identifying microglial cells in more nuanced ways.

In their current revision, the authors have done an excellent job responding to concerns and have updated the manuscript accordingly.

Reviewer #1 (Public review):

Summary:

This paper shows that the synthetic opioid fentanyl induces respiratory depression in rodents. This effect is revised by the opioid receptor antagonist naloxone, as expected. Unexpectedly, the peripherally restricted opioid receptor antagonist naloxone methiodide also blocks fentanyl-induced respiratory depression.

Strengths:

The paper reports compelling physiology data supporting the induction of respiratory distress in fentanyl-treated animals. Evidence suggesting that naloxone methiodide reverses this respiratory depression is compelling. This is further supported by pharmacokinetic data suggesting that naloxone methiodide does not penetrate into the brain, nor is it metabolized into brain-penetrant naloxone.

Weaknesses:

The paper would be further strengthened by establishing the functional significance of the altered neural activity detected in the nTS (as measured by cFos and GcAMP/photometry) in the context of opioid-induced respiratory depression.

Reviewer #1 (Public review):

Summary:

The manuscript co-authored by Pál Barzó et al is very clear and very well written, demonstrating the electrophysiological and morphological properties of the human cortical layer 2/3 pyramidal cells across a wide age range, from age 1 month to 85 years using whole-cell patch clamp. To my knowledge, this is the first study that look at the cross-age differences biophysical and morphological properties of human cortical pyramidal cells. The community will also appreciate the significant effort involved in recording data from 485 cells, given the challenges associated with collecting data from human tissue. Understanding the electrophysiological properties of individual cells, which are essential for brain function, is crucial for comprehending human cortical circuits. I think this research enhances our knowledge of how biophysical properties change over time in the human cortex. I also think that by building models of human single cells at different ages using these data, we can develop more accurate representations of brain function. This, in turn, provides valuable insights into human cortical circuits and function and helps in predicting changes in biophysical properties in both health and disease.

Strengths:

The strength of this work lies in demonstrating how the electrophysiological and morphological features of human cortical layer 2/3 pyramidal cells change with age, offering crucial insights into brain function throughout life.

Comments on revisions:

Thanks to the authors for addressing my comments and providing greater clarity in the methodology. The analysis is much clearer now. I also appreciate their additional data analysis, particularly on morphology, which strengthens the paper.

Reviewer #1 (Public Review):

Summary:

Shi and colleagues report the use of modified Cre lines in which the coding region of Cre is disrupted by rox-STOP-rox or lox-STOP-lox sequences to prevent the expression of functional protein in the absence of Dre or Cre activity, respectively. The main purpose of these tools is to enable intersectional or tamoxifen-induced Cre activity with minimal or no leaky activity from the second, Cre-expressing allele. It is a nice study but lacks some functional data required to determine how useful these alleles will be in practice, especially in comparison with the figure line that stimulated their creation.

Strengths:

The new tools can reduce Cre leak in vivo.

Weaknesses:

(1) Activity of R26-loxCre line. As the authors point out, the greatest value of this approach is to accomplish a more complete Cre-mediated gene deletion using CreER transgenes that are combined with low-efficiency floxed alleles using their R26-loxCre line that is similar to the iSure Cre reported by Benedito and colleagues. The data in Figure 5 show strong activity at the Confetti locus, but the design of the newly reported R26-loxCre line lacks a WPRE sequence that was included in the iSure-Cre line to drive very robust protein expression. Thus while the line appears to have minimal leak, as the design would predict, the question of how much of a deletion increase is obtained over simple use of the CreER transgene alone is a key question for use by investigators. This is further addressed in Figure 6 where it is compared with Alb-CreER alone to recombine the Ctnnb1 floxed allele. They demonstrate that recombination frequency is clearly improved, but the western blot in Figure 6E does not look like there was a large amount of remaining b-catenin to remove. These data are certainly promising, but the most valuable experiment for such a new tool would be a head-to-head comparison with iSure (or the latest iSure version from the Benedito lab) using the same CreER and target floxed allele. At the very least a comparision of Cre protein expression between the two lines using identical CreER activators is needed.

(2) In vivo analysis of mCre activities. Why did the authors not use the same driver to compare mCre 1, 4, 7, and 10? The study in Figure 2 uses Alb-roxCre for 1 and 7 and Cdh5-roxCre for 4 and 10, with clearly different levels of activity driven by the two alleles in vivo. Thus whether mCre1 is really better than mCre4 or 10 is not clear.

(3) Technical details are lacking. The authors provide little specific information regarding the precise way that the new alleles were generated, i.e. exactly what nucleotide sites were used and what the sequence of the introduced transgenes is. Such valuable information must be gleaned from schematic diagrams that are insufficient to fully explain the approach.

Reviewer #3 (Public review):

Summary:

The authors are interested in the relative importance of PRL versus GH and their interactive signaling in breast cancer. After examining GHR-PRLR interactions in response to ligands, they suggest that a reduction in cell surface GHR in response to PRL may be a mechanism whereby PRL can sometimes be protective against breast cancer.

Strengths:

The strengths of the study include the interesting question being addressed and the application of multiple complementary techniques, including dSTORM, which is technically very challenging, especially when using double labeling. Thus, dSTORM is used to analyze co-clustering of GHR and PRLR, and, in response to PRL, rapid internalization of GHR and increased cell surface PRLR. Conclusions from Proximity ligation assays are that some GHR and PRLR are within 40 nm (≈ 4 plasma membranes) of each other and that upon ligand stimulation, they move apart. Intact receptor knockin and knockout approaches and receptor constructs without the Jak2 binding domain demonstrate a) a requirement for the PRLR for there to be PRL- driven internalization of GHR, and b) that Jak2-PRLR interactions are necessary for stability of the GHR-PRLR colocalizations.

Weaknesses:

Although improved over the first version, the manuscript still suffers from a lack of detail, which in places makes it difficult to evaluate the data and would make it very difficult for the results to be replicated by others.

Comments on revised version:

Points for improvement of the manuscript:

(1) There is still insufficient detail about the proximity ligation assay. For example, PLAs that use reagents from Sigma (as now reported) require primary antibodies from two different species and yet both the anti-PRLR and anti-GHR used for dSTORM were mouse monoclonals. On line 356 it says that the ECD antibodies were used for microscopy and the PLA is microscopy. Were instead the ICD antibodies used for the PLA? If so, how do we know that one or more of the proteins in the very strong "non-specific" bands seen on Figure 5A are not what is being localized? Could you do a Western blot of just cell membrane proteins? There needs to be further clarity/explanation.

(2) Although the manuscript now shows a Western blot using the antibodies against intracellular regions of the receptor, a full Western blot is not provided for the antibodies against the S2 extracellular domain used for the dSTORM. While I haven't checked the papers showing characterization of the anti-GHR, I did re-check reference 70, which the authors say shows full characterization of the PRLR antibody, and this does not show a full Western (only portions of gels). How do we know that this antibody is not recognizing some other cell surface molecule, the surface expression of which increases upon stimulation of the cells with PRL? Is there only one band when blotting whole cell extracts with either the GHR or PRLR ECD antibodies so we can be sure of specificity? Figure S2 helps some, but these are different cells and the relative expression of the PRLR versus some other potential cell surface protein in these engineered cells may well be completely different.

Joint Public Review:

The Lee et al. study has been revised in response to reviewer comments. It presents a valuable investigation into the role of the Hippo signaling pathway (specifically wts-1/LATS and yap) in age-dependent neurodegeneration and microtubule dynamics in C. elegans TRNs. The authors convincingly demonstrated that disruption of wts-1/LATS leads to age-associated neuronal abnormalities and enhanced microtubule stabilization, with a genetic link to yap. While the study was praised for its well-conducted and well-controlled approaches, reviewers raised concerns about the specificity of the Hippo pathway's effects to TRNs, the correlation of Hpo signaling decline in TRNs with age, and the mechanistic link between Hpo-mediated gene expression and microtubule regulation. The authors addressed the TRN specificity by suggesting the unique microtubule structure of these neurons might contribute to their susceptibility. They acknowledged the difficulty in detecting Hpo signaling decline specifically in aged TRNs but noted increased YAP-1 nuclear localization in other tissues. Importantly, the authors provided evidence suggesting that YAP-TEAD-mediated transcriptional regulation is responsible for neuronal degeneration, as loss of yap-1 or egl-44 restored the wts-1 mutant phenotype. However, the specific transcriptional targets of YAP-1 regulating microtubule stability remain unidentified, representing a key limitation. The authors also discussed the possibility of non-cell-autonomous effects of YAP-1 and offered explanations for the seemingly moderate impairment of the touch response despite structural damage. Finally, they attributed the shorter lifespan of wts-1 and wts-1; yap-1 mutants to roles of wts-1 beyond TRNs and potential synergistic effects of yap-1. Overall, the study provides significant insights into the Hippo pathway's role in neuronal aging and microtubule dynamics, while acknowledging remaining mechanistic gaps.

Reviewer #1 (Public review):

Summary:

Summary of what author's were trying to achieve: In the manuscript by Hoisington et al., the authors utilized a novel conditional neuronal prosap2-interacting protein 1 (Prosapip1) knockout mouse to delineate the effects of both neuronal and dorsal hippocampal (dHP)-specific knockout of Prosapip1 impacts biochemical and electrophysiological neuroadaptations within the dHP that may mediate behaviors associated with this brain region.

Strengths:

(1) Methodological Strengths

a) The generation and use of a conditional neuronal knockout of Prosapip1 is a strength. These mice will be useful for anyone interested in studying or comparing and contrasting the effects of loss of Prosapip1 in different brain regions or in non-neuronal tissues.<br /> b) The use of biochemical, electrophysiological, and behavioral approaches are a strength. By providing data across multiple domains, a picture begins to emerge about the mechanistic role for Prosapip1. While questions still remain, the use of the 3 domains is a strength.<br /> c) The use of both global, constitutive neuronal loss of Prosapip1 and postnatal dHP-specific knockout of Prosapip1 help support and validate the behavioral conclusions.

(2) Strengths of the results

a) It is interesting that loss of Prosapip1 leads to specific alterations in the expression of GluN2B and PSD95 but not GluA1 or GluN2A in a post homogenization fraction that the author's term a "synaptic" fraction. Therefore, these results suggest protein-specific modulation of glutamatergic receptors within a "synaptic" fraction.<br /> b) The electrophysiological data demonstrate an NMDAR-dependent alteration in measures of hippocampal synaptic plasticity, including long-term potentiation (LTP) and NMDAR input/output. These data correspond with the biochemical data demonstrating a biochemical effect on GluN2B localization. Therefore, the conclusion that loss of Prosapip1 influences NMDAR function is well supported.<br /> c) The behavioral data suggest deficits in memory in particular novel object recognition and spatial memory, in the Prosapip1 knockout mice. These data are strongly bolstered by both the pan neuronal knockout and the dHP Cre transduction.

The authors highlight potential future studies to further the understanding of Prosapip1.

Reviewer #1 (Public review):

Summary:

This study addresses the issue of rapid skill learning and whether individual sequence elements (here: finger presses) are differentially represented in human MEG data. The authors use a decoding approach to classify individual finger elements, and accomplish an accuracy of around 94%. A relevant finding is that the neural representations of individual finger elements dynamically change over the course of learning. This would be highly relevant for any attempts to develop better brain machine interfaces - one now can decode individual elements within a sequence with high precision, but these representations are not static but develop over the course of learning.

Strengths:

The work follows a large body of work from the same group on the behavioural and neural foundations of sequence learning. The behavioural task is well established a neatly designed to allow for tracking learning and how individual sequence elements contribute. The inclusion of short offline rest periods between learning epochs has been influential because it has revealed that a lot, if not most of the gains in behaviour (ie speed of finger movements) occur in these so-called micro-offline rest periods.

The authors use a range of new decoding techniques, and exhaustively interrogate their data in different ways, using different decoding approaches. Regardless of the approach, impressively high decoding accuracies are observed, but when using a hybrid approach that combines the MEG data in different ways, the authors observe decoding accuracies of individual sequence elements from the MEG data of up to 94%.

Weaknesses:

A formal analysis and quantification of how head movement may have contributed to the results should be included in the paper or supplemental material. The type of correlated head movements coming from vigorous key presses aren't necessarily visible to the naked eye, and even if arms etc are restricted, this will not preclude shoulder, neck or head movement necessarily; if ICA was conducted, for example, the authors are in the position to show the components that relate to such movement; but eye-balling the data would not seem sufficient. The related issue of eye movements is addressed via classifier analysis. A formal analysis which directly accounts for finger/eye movements in the same analysis as the main result (ie any variance related to these factors) should be presented.

This reviewer recommends inclusion of a formal analysis that the intra-vs inter parcels are indeed completely independent. For example, the authors state that the inter-parcel features reflect "lower spatially resolved whole-brain activity patterns or global brain dynamics". A formal quantitative demonstration that the signals indeed show "complete independence" (as claimed by the authors) and are orthogonal would be helpful

Reviewer #1 (Public review):

Summary:

In this work, the authors investigate the functional difference between the most commonly expressed form of PTH, and a novel point mutation in PTH identified in a patient with chronic hypocalcemia and hyperphosphatemia. The value of this mutant form of PTH as a potential anabolic agent for bone is investigated alongside PTH(1-84), which is a current anabolic therapy. The authors have achieved the aims of the study.

Strengths:

The work is novel, as it describes the function of a novel, naturally occurring, variant of PTH in terms of its ability to dimerise, to lead to cAMP activation, to increase serum calcium, and its pharmacological action compared to normal PTH.

Comments on revisions: No further recommendations for revisions. Acceptable as the paper stands.

[Editors' note: the original reviews are here, https://doi.org/10.7554/eLife.97579.1.sa1]

Reviewer #1 (Public review):

Summary:

In this paper, the authors have performed an antigenic assay for human seasonal N1 neuraminidase using antigens and mouse sera from 2009-2020 (with one avian N1 antigen). This shows two distinct antigen groups. There is poorer reactivity with sera from 2009-2012 against antigens from 2015-2019, and poorer reactivity with sera from 2015-2020 against antigens from 2009-2013. There is a long branch separating these two groups. However, 321 and 423 are the only two positions that are consistently different between the two groups. Therefore these are the most likely cause of these antigenic differences.

Strengths:

(1) A sensible rationale was given for the choice of sera, in terms of the genetic diversity.

(2) There were two independent batches of one of the antigens used for generating sera, which demonstrated the level of heterogeneity in the experimental process.

(3) Replicate of the Wisconsin/588/2019 antigen (as H1 and H6) is another useful measure of heterogeneity.

(4) The presentation of the data, e.g. Figure 2, clearly shows two main antigenic groups.

(5) The most modern sera are more recent than other related papers, which demonstrates that has been no major antigenic change.

Weaknesses:

(1) Issues with experimental methods<br /> As I am not an experimentalist, I cannot comment fully on the experimental methods. However, I note that BALB/c mice sera were used, whereas outbred ferret sera are typically used in influenza antigenic characterisation, so the antigenic difference observed may not be relevant in humans. Similarly, the mice were immunised with an artificial NA immunogen where the typical approach would be to infect the ferret with live virus intra-nasally.

(2) Five mice sera were generated per immunogen and then pooled, but data was not presented that demonstrated these sera were sufficiently homogenous that this approach is valid.

(3) There were no homologous antigens for most of the sera. This makes the responses difficult to interpret as the homologous titre is often used to assess the overall reactivity of a serum. The sequence of the antigens used is not described, which again makes it difficult to interpret the results.

(4) To be able to untangle the effects of the individual substitutions at 321, 386, and 432, it would have been useful to have included the naturally occurring variants at these positions, or to have generated mutants at these positions. Gao et al clearly show an antigenic difference with ferret sera correlated separately with N386K and I321V/K432E.

(5) The challenge experiments in Gao et al showed that NI titre was not a good correlate of protection, so that limits the interpretation of these results.

Issues with the computational methods

(6) The NAI titres were normalised using the ELISA results, and the motivation for this is not explained. It would be nice to see the raw values.

(7) It is not clear what value the random forest analysis adds here, given that positions 321 and 432 are the only two that consistently differ between the two groups.

(8) As with the previous N2 paper, the metric for antigenic distance (the root mean square of the difference between the titres for two sera) is not one that would be consistent when different sera are included. More usual metrics of distance are Archetti-Horsfall, fold down from homologous, or fold down from maximum.

(9) Antigenic cartography of these data is fraught. I wonder whether 2 dimensions are required for what seems like a 1-dimensional antigenic difference - certainly, the antigens, excluding the H5N1, are in a line. The map may be skewed by the high reactivity Brisbane/18 antigen. It is not clear if the column bases (normalisation factors for calculating antigenic distance) have been adjusted to account for the lack of homologous antigens. It is typical to present antigenic maps with a 1:1 x:y ratio.

Issues with interpretation

(10) Figure 2 shows the NAI titres split into two groups for the antigens, however, A/Brisbane is an outlier in the second antigenic group with high reactivity.

(11) Following Gao et al, I think you can claim that it is more likely that the antigenic change is due to K432E than I321V, based on a comparison of the amino acid change.

Appraisal:

Taking into account the limitations of the experimental techniques (which I appreciate are due to resource constraints), this paper meets its aim of measuring the antigenic relationships between 2009-2020 seasonal N1s, showing that there were two main groups. The authors discovered that the difference between the two antigenic groups was likely attributable to positions 321 and 432, as these were the only two positions that were consistently different between the two groups. They came to this finding by using a random forest model, but other simpler methods could have been used.

Impact:

This paper contributes to the growing literature on the potential benefit of NA in the influenza vaccine.

Reviewer #1 (Public review):

Summary:

Shi and colleagues report the use of modified Cre lines in which the coding region of Cre is disrupted by rox-STOP-rox or lox-STOP-lox sequences to prevent the expression of functional protein in the absence of Dre or Cre activity, respectively. The main purpose of these tools is to enable intersectional or tamoxifen-induced Cre activity with minimal or no leaky activity from the second, Cre-expressing allele. It is a nice study but lacks some functional data required to determine how useful these alleles will be in practice, especially in comparison with the figure line that stimulated their creation.

Strengths:

The new tools can reduce Cre leak in vivo.

Comments on revisions:

The major improvement in my mind is the inclusion of Supp Fig 7 where the authors compare their loxCre to iSureCre. The discussion is somewhat improved, but still fails to discuss significant issues such as Cre toxicity in detail. As noted by most reviewers, without a biological question the paper is entirely a technical description of a a couple of new tools. However, I do feel that these tools will be of use to the field.

Reviewer #1 (Public review):

Summary:

In this article, Chunharas and colleagues compared the representational differences of orientation information during a sensory task and a working memory task. By reanalyzing data from a previous fMRI study and applying representational similarity analysis (RSA), they observed that orientation information was represented differently in the two tasks: during visual perception, orientation representation resembled the veridical model, which captures the known naturalistic statistics of orientation information; whereas during visual working memory, a categorical model, which assumes different psychological distances between orientations, better explained the data, particularly in more anterior retinotopic regions. The authors suggest fundamental differences in the representational geometry of visual perception and working memory along the human retinotopic cortex.

Strengths:

Examining the differences in representational geometry between perception and working memory has important implications for the understanding of the nature of working memory. This study presents a carefully-executed reanalysis of previous data to address this question. The authors developed a novel method (model construction combined with RSA) to examine the representational geometry of orientation information under different tasks, and the control analyses provide rich, convincing support for their claims.

Weaknesses:

Although the control analyses are convincing, I still have alternative explanations for some of the results. I'm also concerned about the low sample size (n = 6 in the fMRI experiment). Overall, I think additional analyses may help to further clarify the issues and strengthen the claims.

(1) The central claim of the current study is that orientation information is represented in a veridical manner during the sensory task, and in a categorical manner during working memory. However, In the sensory task, a third type of representational geometry was observed, especially in brain regions from V3AB and beyond. These regions showed a symmetric pattern in which oblique orientations (45 and 135 degrees) appeared more similar to each other. In fact, a similar pattern can even be found in V1-V3, although the effect looked weaker. The authors raised two possible explanations for this in the discussion, one being that participants might have used verbal labels (e.g., diagonal) for both orientations, and the other being a lack of attention to orientation. Either way, this suggests that a veridical model may not be the best fit for these ROIs. How would this symmetric model explain the sensory data, in comparison to the veridical model?

(2) If the symmetric model also explains the sensory data well, I wonder whether this result challenges the authors' central claim, or instead suggests that the sensory task is not ideal for the purpose of the study. One way to address this issue might be to use the sample period of the working memory task as the perception task, as some other studies have been doing (e.g., Kwak & Curtis, 2022). This epoch of data might function as a stronger version of the attention task as the authors discussed in the discussion. What would the representational geometry look like in the sample period? I would also like to note that the current analyses used 5.6-13.6 s after stimulus onset for the memory task, which I think may reflect a mix of sample- and delay-related activity.

(3) When comparing the veridical and categorical models, it is important to first show the significance of each model before making comparisons. For instance, was the veridical model significant in different ROIs in the memory task? And was either model significant in IPS1-3 in the two tasks? I'm asking about this because the two models appear to be both significant in the memory task, whereas only the veridical model was significant in the sensory task (with overall lower correlation coefficients than the categorical model in the memory task).

(4) The current study has a low sample size of six participants. With such a small sample, it would be helpful to show results from individual participants. For example, I appreciate that Figures 2D and 3C showed individual data points, but additionally showing the representational geometry plot (i.e., Figure 1C) for each subject could better illustrate the robustness of the effect. Alternatively, the original paper from which the fMRI data were drawn actually had two fMRI experiments with similar task designs. I wonder if the authors could replicate these patterns using data from the second experiment with seven participants. This might provide even stronger support for the current findings with a more reasonable sample size.

Reviewer #1 (Public review):

Summary:

This work tried to map the synaptic connectivity between the inputs and outputs of the song premotor nucleus, HVC in zebra finches to understand how sensory (auditory) to motor circuits interact to coordinate song production and learning. The authors optimized the optogenetic technique via AAV to manipulate auditory inputs from a specific auditory area one-by-one and recorded synaptic activity from a neuron with whole-cell recording from slice preparation with identification of the projection area by retrograde neuronal tracing. This thorough and detailed analysis provides compelling evidence of synaptic connections between 4 major auditory inputs (3 forebrain and 1 thalamic region) within three projection neurons in the HVC; all areas give monosynaptic excitatory inputs and polysynaptic inhibitory inputs, but proportions of projection to each projection neuron varied. They also find specific reciprocal connections between mMAN and Av. Taken together the authors provide the map of the synaptic connection between intercortical sensory to motor areas which is suggested to be involved in zebra finch song production and learning.

Strengths:

The authors optimized optogenetic tools with eGtACR1 by using AAV which allow them to manipulate synaptic inputs in a projection-specific manner in zebra finches. They also identify HVC cell types based on projection area. With their technical advance and thorough experiments, they provided detailed map synaptic connections.

Weaknesses:

As it is the study in brain slice, the functional implication of synaptic connectivity is limited. Especially as all the experiments were done in the adult preparation, there could be a gap in discussing the functions of developmental song learning.

Reviewer #1 (Public review):

Summary:

In this manuscript, Shao et al. investigate the contribution of different cortical areas to working memory maintenance and control processes, an important topic involving different ideas about how the human brain represents and uses information when no longer available to sensory systems. In two fMRI experiments, they demonstrate that human frontal cortex (area sPCS) represents stimulus (orientation) information both during typical maintenance, but even more so when a categorical response demand is present. That is, when participants have to apply an added level of decision control to the WM stimulus, sPCS areas encode stimulus information more than conditions without this added demand. These effects are then expanded upon using multi-area neural network models, recapitulating the empirical gradient of memory vs control effects from visual to parietal and frontal cortices. Multiple experiments and analysis frameworks provide support for the authors' conclusions, and control experiments and analysis are provided to help interpret and isolate the frontal cortex effect of interest. While some alternative explanations/theories may explain the roles of frontal cortex in this study and experiments, important additional analyses have been added that help ensure a strong level of support for these results and interpretations.

Strengths:

- The authors use an interesting and clever task design across two fMRI experiments that is able to parse out contributions of WM maintenance alone along with categorical, rule-based decisions. Importantly, the second experiments only uses one fixed rule, providing both an internal replication of Experiment 1's effects and extending them to a different situation when rule switching effects are not involved across mini-blocks.

- The reported analyses using both inverted encoding models (IEM) and decoders (SVM) demonstrate the stimulus reconstruction effects across different methods, which may be sensitive to different aspects of the relationship between patterns of brain activity and the experimental stimuli.

- Linking the multivariate activity patterns to memory behavior is critical in thinking about the potential differential roles of cortical areas in sub-serving successful working memory. Figure 3's nicely shows a similar interaction to that of Figure 2 in the role of sPCS in the categorization vs. maintenance tasks. This is an important contribution to the field when we consider how a distributed set of interacting cortical areas support successful working memory behavior.

- The cross-decoding analysis in Figure 4 is a clever and interesting way to parse out how stimulus and rule/category information may be intertwined, which would have been one of the foremost potential questions or analyses requested by careful readers.

- Additional ROI analyses in more anterior regions of the PFC help to contextualize the main effects of interest in the sPCS (and no effect in the inferior frontal areas, which are also retinotopic, adds specificity). And, more explanation for how motor areas or preparation are likely not involved strengthens the takeaways of the study (M1 control analysis).

- Quantitative link via RDM-style analyses between the RNNs constructed and fMRI data.

Weaknesses:

- In the given tasks, multiple types of information codes may be present, and more detail on this possibility could always be added analytically or in discussion. However, the authors have added beneficial support to this comparison in this version of the manuscript.

- The space of possible RNN architectures and their biological feasibility could always be explored more, but links between the fMRI and RNN data provide a good foundation for this work moving forward.

Reviewer #1 (Public review):

Here, the authors propose that changes in m6A levels may be predictable via a simple model that is based exclusively on mRNA metabolic events. Under this model, m6A mRNAs are "passive" victims of RNA metabolic events with no "active" regulatory events needed to modulate their levels by m6A writers, readers, or erasers; looking at changes in RNA transcription, RNA export, and RNA degradation dynamics is enough to explain how m6A levels change over time.

The relevance of this study is extremely high at this stage of the epitranscriptome field. This compelling paper is in line with more and more recent studies showing how m6A is a constitutive mark reflecting overall RNA redistribution events. At the same time, it reminds every reader to carefully evaluate changes in m6A levels if observed in their experimental setup. It highlights the importance of performing extensive evaluations on how much RNA metabolic events could explain an observed m6A change.

Reviewer #1 (Public review):

Summary:

Sattin, Nardin, and colleagues designed and evaluated corrective microlenses that increase the useable field of view of two long (>6mm) thin (500 um diameter) GRIN lenses used in deep-tissue two-photon imaging. This paper closely follows the thread of earlier work from the same group (esp. Antonini et al, 2020; eLife), filling out the quiver of available extended-field-of-view 2P endoscopes with these longer lenses. The lenses are made by a molding process that appears practical and easy to adopt with conventional two-photon microscopes.

Simulations are used to motivate the benefits of extended field of view, demonstrating that more cells can be recorded, with less mixing of signals in extracted traces, when recorded with higher optical resolution. In vivo tests were performed in piriform cortex, which is difficult to access, especially in chronic preparations.

The design, characterization, and simulations are clear and thorough, but they do not break new ground in optical design or biological application. However, the approach shows much promise, including for applications such as miniaturized GRIN-based microscopes. Readers will largely be interested in this work for practical reasons: to apply the authors' corrected endoscopes to their own research.

Strengths:

The text is clearly written, the ex vivo analysis is thorough and well supported, and the figures are clear. The authors achieved their aims, as evidenced by the images presented, and were able to make measurements from large numbers of cells simultaneously in vivo in a difficult preparation.

The authors did a good job of addressing issues I raised in initial review, including analyses of chromaticity and the axial field of view, descriptions of manufacturing and assembly yield, explanations in the text of differences between ex vivo and in vivo imaging conditions, and basic analysis of the in vivo recordings relative to odor presentations. They have also shortened the text, reduced repetition, and better motivated their approach in the introduction.

Weaknesses:

As discussed in review and nicely simulated by the authors, the large figure error indicated by profilometry (~10 um in some cases on average) is inconsistent with the optical performance improvements observed, suggesting that those measurements are inaccurate. I see no reason to include these inaccurate measurements.

Reviewer #1 (Public review):

The IBL here presents an important paper that aims to assess potential reproducibility issues in rodent electrophysiological recordings across labs and suggests solutions to these. The authors carried out a series of analyses on data collected across 10 laboratories while mice performed the same decision-making task, and provided convincing evidence that basic electrophysiology features, single-neuron functional properties, and population-level decoding were fairly reproducible across labs with proper preprocessing. This well-motivated large-scale collaboration allowed systematic assessment of lab-to-lab reproducibility of electrophysiological data, and the suggestions outlined in the paper for streamlining preprocessing pipelines and quality metrics will provide general guidance for the field, especially with continued effort to benchmark against standard practices (such as manual curation).

The authors have carefully incorporated our suggestions. As a result, the paper now better reflects where reproducibility is affected when using common, simple, and more complex analyses and preprocessing methods, and it is more informative-and more reflective of the field overall. We thank the reviewers for this thorough revision. We have 2 remaining suggestions on text clarification:

(1) Regarding benchmarking the automated metrics to manual curation of units: although we appreciate that a proper comparison may require a lot of effort potentially beyond the scope of the current paper; we do think that explicit discussion regarding this point is needed in the text, to remind the readers (and indeed future generations of electrophysiologists) the pros and cons of different approaches.

In addition to what the authors have currently stated (line 469-470):<br /> "Another significant limitation of the analysis presented here is that we have not been able to assess the extent to which other choices of quality metrics and inclusion criteria might have led to greater or lesser reproducibility."

Maybe also add:<br /> "In particular, a thorough comparison of automated metrics against a careful, large, manually-curated dataset, is an important benchmarking step for future studies.

(2) The authors now include in Figure 3-Figure Supplement 1 that highlight how much probe depth is adjusted by using electrophysiological features such as LFP power to estimate probe and channel depth. This plot is immensely informative for the field, as it implies that there can be substantial variability-sometimes up to 1 mm discrepancy between insertions-in depth estimation based on anatomical DiI track tips alone. Using electrophysiological features in this way for probe depth estimation is currently not standard in the field and has only been made possible with Neuropixels, which span several millimeters. These figures highlight that this should be a critical step in preprocessing pipelines, and the paper provides solid evidence for this.

Currently, this part of the figure is only subtly referenced to in the text. We think it would be helpful to explicitly reference this particular panel with discussions of its implication in the text.

Reviewer #1 (Public review):

The manuscript consists of two separate but interlinked investigations: genomic epidemiology and virulence assessment of Salmonella Dublin. ST10 dominates the epidemiological landscape of S. Dublin, while ST74 was uncommonly isolated. Detailed genomic epidemiology of ST10 unfolded the evolutionary history of this common genotype, highlighting clonal expansions linked to each distinct geography. Notably, North American ST10 was associated with more antimicrobial resistance compared to others. The authors also performed long read sequencing on a subset of isolates (ST10 and ST74), and uncovered a novel recombinant virulence plasmid in ST10 (IncX1/IncFII/IncN). Separately, the authors performed cell invasion and cytotoxicity assays on the two S. Dublin genotypes, showing differential responses between the two STs. ST74 replicates better intracellularly in macrophage compared to ST10, but both STs induced comparable cytotoxicity levels. Comparative genomic analyses between the two genotypes showed certain genetic content unique to each genotype, but no further analyses were conducted to investigate which genetic factors likely associated with the observed differences. The study provides a comprehensive and novel understanding on the evolution and adaptation of two S. Dublin genotypes, which can inform public health measures. The methodology included in both approaches were sound and written in sufficient detail, and data analysis were performed with rigour. Source data were fully presented and accessible to readers.

Comments on revised version:

The authors have addressed all the points raised by the reviewer. The manuscript is now much enhanced in clarity and accuracy. The re-written Discussion is more relevant and brings in comparison with other invasive Salmonella serotypes.

Comments:

In light of the metadata supplied in this revision, for Australian isolates, all human cases of ST74 (n=7) were from faeces (assuming from gastroenteritis) while 18/40 of ST10 were from invasive specimen (blood and abscess). This may contradict with the manuscript's finding and discussion on different experiment phenotypes of the two STs, with ST74 showing more replication in macrophages and potentially more invasive. Thus, the reviewer suggests the authors to mention this disparity in the Discussion, and discuss possible reasons underlying this disparity. This can strengthen the author's rationale for further in vivo studies.

Reviewer #1 (Public review):

Summary:

The main observation that the sperm from CRISP proteins 1 and 3 KO lines are post-fertilization less developmentally competent is convincing. The data showing progressive acquisition of the sperm defects during epididymal transport and the exchange fluid studies showing the altered epididymal environment are important. However, the molecular characterization of the mechanism(s) that leads to these defects requires additional studies.

Strengths:

The generation of these double mutant mice is valuable for the field. Moreover, the fact that the double mutant line of Crisp 1 and 3 is phenotypically different from the Crisp 1 and 4 line suggests different functions of these epididymis proteins. The methods used to demonstrate that developmental defects are largely due to post-fertilization defects are also a considerable strength. The initial characterization that these sperm have altered intracellular Ca2+ levels, and increased rates of DNA fragmentation are valuable. The increase fragmentation of control sperm DNA when exposed to mutant epididymal fluid is significant and an excellent platform for future studies.

Weaknesses:

The study is mechanistically incomplete because evidence of how these proteins alter the environment is not shown. What are the target(s) of these proteins that result in increased Ca2+?

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors investigate the role of BEND2, a novel regulator of meiosis, in both male and female fertility. Huang et al have created a mouse model where the full-length BEND2 transcript is depleted but the truncated BEND2 version remains. This mouse model is fertile, and the authors used it to study the role of BEND2 on both male and female meiosis. Overall, the full-length BEND2 appears dispensable for male meiosis. The more interesting phenotype was observed in females. Females exhibit a lower ovarian reserve suggesting that full-length BEND2 is involved in the establishment of the primordial follicle pool.

Strengths:

The authors generated a mouse model that enabled them to study the role of BEND2 in meiosis. The role of BEND2 in female fertility is novel and enhances our knowledge of genes involved in the establishment of the primordial follicle pool.

Weaknesses highlighted previously:

The manuscript extensively explores the role of BEND2 in male meiosis; however, a more interesting result was obtained from the study of female mice.

Reviewer #1 (Public review):

Turi, Teng and the team used state of the art techniques to provide convincing evidence on the infraslow oscillation of DG cells during NREM sleep, and how serotonergic innervation modulates hippocampal activity pattern during sleep and memory. First, they showed that the glutamatergic DG cells become activated following an infraslow rhythm during NREM sleep. In addition, the infraslow oscillation in the DG is correlated with rhythmic serotonin release during sleep. Finally, they found that specific knockdown of 5-HT receptors in the DG impairs the infraslow rhythm and memory, suggesting that serotonergic signaling is crucial for regulating DG activity during sleep. Given that the functional role of infraslow rhythm still remains to be studied, their findings deepen our understanding on the role of DG cells and serotonergic signaling in regulating infraslow rhythm, sleep microarchitecture and memory.

Reviewer #1 (Public review):

Summary:

Using sequences of short videos to elicit emotional changes in participants, Malamud & Huys demonstrate how a brief, controlled emotion regulation intervention (distancing) can effectively alter subsequent emotion ratings. The authors employ latent state-space models to capture the trajectories of emotion ratings, leveraging tools from control theory to quantify the intervention's impact on emotion dynamics.

Strengths:

The experiment is well-designed and tailored to the computational modeling approach advanced in the paper. It also relies on a selection of stimuli that were previously validated. Within the constraints of a controlled experiment, the intervention successfully implements a relatively common tool of psychotherapeutic treatment, ensuring its clinical relevance.

The computational modeling is grounded in the well-established framework of dynamical systems and control theory. This foundation offers a conceptually clear formalization along with powerful quantification tools that go beyond previous more data-driven approaches.

Overall, the study presents a coherent approach that bridges concepts from clinical psychology and computational theories, providing a timely stepping stone toward advancing quantified, evidence-based psychological interventions targetting emotion control.

Weaknesses:

A primary limitation of this study, acknowledged by the authors, is its reliance on self-reports of participants' emotional states. Although considerable effort was made to minimize expectation effects, further research is needed to confirm that the observed behavioral changes reflect genuine alterations in emotional states. Additionally, the generalizability of the findings to long-term remediation strategies remains an open question.

Second, the statistical analysis, particularly the computational approach, sometimes lacks sufficient detail and refinement. While I will not elaborate on specific points here, one notable issue is the interpretation of the intrinsic matrix (A). The model-free analysis reveals correlations between emotions at a given time or within an emotional state across time points. However, it does not provide evidence to support lagged interactions across states that would justify non-diagonal elements in A. The other result concerning the dynamics matrix only highlights a trend in the dominant eigenvalue, which is difficult to interpret in isolation. The absence of a statistically significant group x intervention interaction furthermore makes this finding a little compelling. This weakens the study's conclusions about the importance of intrinsic dynamics, as claimed in the title.

Finally, to avoid potential misunderstandings of their work, the authors should be more careful about their use of terms pertaining to the control theory and take the time to properly define them. For example, the "controllability" of emotional states can either denote that those states are more changeable (control theory definition), or, conversely, more tightly regulated (common interpretation, as used in the abstract). This is true for numerous terms (stability, sensitivity, Gramian, etc.) for which no clear definition nor references are provided. Readers unfamiliar with the framework of control theory will likely be at a loss without more guidance.

DOI: 10.1016/j.isci.2025.112155

Resource: (ZFIN Cat# ZDB-GENO-060207-1,RRID:ZFIN_ZDB-GENO-060207-1)

Curator: @areedewitt04

SciCrunch record: RRID:ZFIN_ZDB-GENO-060207-1

What is this?

Reviewer #1 (Public review):

Summary:

The nuclear protein SATB-1 was originally identified as a protein of the 'nuclear matrix', an aggregate of nuclear components that arose upon extracting nuclei with high salt. While the protein was assumed to have a global function in chromatin organization, it has subsequently been linked to a variety of pathological conditions, notably cancer. The mapping of the factor by conventional ChIP procedures showed strong enrichment in active, accessible chromatin, suggesting a direct role in gene regulation, perhaps in enhancer-promoter communication. These findings did not explain why SATB-1-chromatin interaction resisted the 2 M salt extraction during early biochemical fractionation of nuclei.

The authors, who have studied SATB-1 for many years, now developed an unusual variation of the ChIP procedure, in which they purify crosslinked chromatin by centrifugation through 8 M urea. Remarkably, while they lose all previously mapped signals for SATB-1 in active chromatin, they now gain many binding events in silent regions of the genome, represented by lamin-associated domains (LADs).

SATB-1 had previously been shown by the authors and others to bind to DNA with special properties, termed BUR (for 'base-unpairing regions'). BURs are AT-rich and apparently enriched in equally AT-rich LADs. The 'urea-ChIP' pattern is essentially complementary to the classical ChIP pattern. The authors now speculate that the previously known SATB-1 binding pattern, which does not overlap BURs particularly well, is due to indirect chromatin binding, whereas they consider the urea-ChIP profile that fits better to the BUR distribution on the chromosome to be due to direct binding.

Building on the success with urea-ChIP the authors adapted the 4C-procedure of chromosome conformation mapping to work with urea-purified chromatin. The data suggest that BUR-bound SATB-1 in heterochromatin mediates long-distance interaction with loci in active chromatin. They close with a model, whereby SATB-1 tethers active chromatin to the nuclear lamina. Because cell type-specific differences are observed, they suggest that the SATB-1 interactions are functionally relevant.

Strengths:

Given the unusual finding of essentially mutually exclusive 'standard ChIP' and 'urea-ChIP' profiles for SATB-1, the authors conducted many appropriate controls. They showed that all SATB-1 peaks in urea-ChIP and 96% of peaks in standard-ChIP represent true signals, as they are not observed in a SATB-1 knockout cell line. They also show that urea-ChIP and standard ChIP yield similar profiles for CTCF. The data appear reproducible, judged by at least two replicates and triangulation. The SATB-1 KO cells provide a nice control for the specificity of signals, including those that arise from their elaborately modified 4C protocol.

Weaknesses:

The weaknesses mainly relate to missing qualifier statements and overinterpretations. I also found some aspects of the model not yet well supported by the data.

(1) Under high urea conditions the BUR elements should be rendered single-stranded, and one wonders whether this has any effect on the procedure. The authors should alert the reader of these circumstances.

(2) An important conclusion is that urea-ChIP reveals direct DNA binding events, whereas standard ChIP shows indirect binding (which is stripped off by urea). I do not yet see any evidence for direct binding. It cannot be excluded, for example, that the binding is RNA-mediated. The authors mention in passing that urea-ChIP material still contains (specific!) RNA. Given that this is a new procedure, the authors should document the RNA content of urea-ChIP and RNase-treat their samples prior to ChIP to monitor an RNA contribution.

(3) An important aspect of the model is that SATB-1 tethers active genes to inactive LADs. However, in the 4C experiment the BUR elements used to anchor the looping are both in the accessible, active chromatin domain.

Reviewer #1 (Public review):

Summary:

In the manuscript entitled 'A comparative analysis of planarian regeneration specificity reveals tissue polarity contributions of the axial cWnt signalling gradient.' Cleland et al. study the robustness of regenerating a head or a tail in the proper position in two different planarian species (S. mediterranea and G. sinensis). The authors find that the expression of notum, a Wnt inhibitor that is triggered after any cut, shows different dynamics of expression in both planarian species, being more symmetrical in the species that display a higher number of double-headed or Janus heads (G. sinenesis), which they refer to a less robust regeneration. The authors claim that the reduced robustness of G. sinensis regeneration is partially explained by this anterior-posterior symmetric expression of notum, since in S. mediterranea, which shows a 'robust regeneration' it appears asymmetric. So, the first claim of the manuscript is that the symmetry in notum expression could underlie the poor robustness of regenerating a head/tail in small bipolar regenerating planarian fragments.

Then, they analyse the role of a proposed tail-to-head cWnt signalling gradient during the regeneration of heads and tails in the same planarian species. To do so they develop an antibody that allows the quantification of b-catenin activity along the AP axis, together with a pharmacological approach that reduces the pre-existent cWnt gradient without affecting the wound-induced. Through this strategy the authors can demonstrate the slope of the b-catenin activity, which is a very nice result, and that it changes according to the size of the animal. Furthermore, they are able to demonstrate that by reducing the cWnt signalling in the pre-existent tissue, there is an increase in the number of double-headed regenerates (Janus heads) and that it depends on the body size and on the decreasing steepness of the cWnt gradient. This result relies on G. sinensis species since the drug is not so effective in S. mediterranea. Thus, the authors' second claim is that the slope of the cWnt gradient may contribute to head-tail regeneration specificity in planarians.

To conclude, it is proposed that regeneration of the correct identity in each wound depends on multiple cues acting in parallel and that their species-specificity provides variations in the regenerative capability of the different planarian species.

The study has great potential to have a high impact on the regeneration community, since the opportunity to compare mechanisms between close species provides the framework for understanding the essential mechanism of regeneration.

Strengths:

The project has several strengths. The authors are able to reproduce the Janus heads phenotypes described by Morgan TH by analysing different planarian species. This is of great importance in the planarian field, because with the current model species, S. mediterranea, this could not be reproduced. So, these results demonstrate that small planarian fragments do make errors during regeneration, giving rise to double-headed animals, which supports the well-known hypothesis that it exists an anteroposterior gradient underlying anteroposterior identity during regeneration. However, and importantly, it does not occur in all planarian species. So, there are differences between planarian species in the robustness of regeneration and may be in the mechanisms that drive this regeneration. The finding of different behaviours and gene expressions in different planarian species is very interesting and promising in the field of regeneration.

A second strength of the study is the demonstration of the b-catenin1 slope in planarians and how it changes with the animal size, and also the establishment of a method to decrease it in the pre-existent tissue but not in the wound. This strategy allows us to examine specifically the role of the pre-existent cWnt signal, demonstrating that it does have a role in the decision of making head or tail during regeneration, which was an essential question in the field of planarians and animal regeneration.

Weaknesses:

(1) The finding that notum, which is the main head determinant identified in planarians, has a different dynamic in both planarian species is very suggestive. However, the different dynamics of notum expression during regeneration, which is the basis of the subsequent rationale, is not properly demonstrated, nor is its correlation with the robustness in regenerating a proper head/tail identity. Main concerns regarding this point:

a) The authors observe that 'In regenerating S. mediterranea 2 mm trunk pieces cut from 6 mm animals, notum expression was induced predominantly at anterior-facing wounds as early as 6 h post-amputation (Figure 2A), as previously reported (Petersen and Reddien 2011)'. However, in the graphics in Figures 2B and C, the expression of notum at 6h is shown as symmetric. It definitely does not agree with the in situ, with the text, or with the published data. How was it measured? It should be corrected and explained since it is the basis of the subsequent rationale.

b) Then, when measuring notum in G. sinensis the authors conclude: 'Strikingly and in sharp contrast to S. mediterranea, the number of notum expressing cells was nearly identical between anterior and posterior wounds without any discernible A/P asymmetry at any of the examined time points (Figures 2E-F)'. However, in the in situ results of 12 h regenerating G. sinensis, there is a clear difference in notum expression between anterior and posterior wounds. Is it not representative of the image? Again, how exactly the measurements were performed? Are dots or pixels quantified? It is not explained in the text. This is a crucial result that has to be consistent.

c) A more general weakness of this part of the manuscript is that even if the authors demonstrate that in G. sinensis the expression of notum is symmetrical in contrast to S. mediterranea, this is just an observation of 1 species that has symmetrical notum and regenerates less robustly than 1 species that has asymmetrical expression and regenerates more robustly. If they for instance look at the expression of wnt1, maybe they also see differences between both species that could be linked to their different regeneration properties (related to this, see below the comment on wnt1 expression). That is to say, comparing 1 to 1 species cannot give any cause-effect evidence.<br /> Furthermore, the authors rely on the fact that notum inhibition rescues the wild-type phenotype to conclude that is the symmetric expression of notum that underlies the appearance of Janus heads. This is what can be read in the results: 'Significantly, the rescue of wild-type regenerates by notum(RNAi) suggests that the symmetric G. sinensis notum expression contributes to the formation of double-heads and thus to reduced regeneration specificity'; and in the Summary: We found that the reduced regeneration robustness of G. sinensis was partially explained by wound site-symmetric expression of the head determinant notum, which is highly anterior-specific in S. mediterranea.' However, notum RNAi decreases notum in both wounds, so it does not produce an asymmetric expression (at least this is not shown). So, it does not link the symmetry or asymmetry of notum with the appearance of Janus heads.

d) If the authors want to maintain the claim that the symmetry of notum is one of the reasons that explain the increase in Janus head phenotype in G. sinensis, there are several possibilities to test it. For instance:

i) Analyse notum expression in different planarian species and relate its symmetry or asymmetry with the appearance of Janus heads. If the claim is true, the species that are more robust should show more asymmetric expression of notum. This would sustain strongly the first claim, and would really be a breakthrough in the field of regeneration.

ii) Another possibility is a more in-depth analysis of notum expression in the species of the study. If the authors show that larger fragments show fewer Janus heads, and also that it depends on the anteroposterior level of the fragments, they could try to relate the rate of Janus heads with the degree of asymmetry in notum expression in both wounds. For instance, they could analyze notum expression in bipolar regenerating fragments along the anteroposterior axis in both species; it should be more symmetric in G sinenesis, in all fragments, according to Figure 2 L. Or they could analyze notum expression in bipolar regenerating fragments of different sizes, mainly in 1 or 2 mm fragments of big planarians, since they are the fragments analyzed that form or not the Janus heads. In G sinensis the expression of notum should be more symmetrical than in S. mediterranea in these fragments.

iii) The authors could design an experiment to demonstrate that the symmetry in the expression of notum affects the rate of Janus heads. The experiment that the authors show is the rescue of the Janus heads in G. sinensis after notum RNAi. However, notum RNAi suppresses notum in both wounds, thus not making them asymmetric. Furthermore, the rescue could be explained by the posteriorizing effect that notum RNAi has in planarians, as reported by several authors. A possibility could be to inhibit APC, which increases notum expression in S. mediterranea (Petersen and Reddien 2011). If APC RNAi in G. sinenesis produces an increase in notum in both wounds and the rate of Janus heads is not rescued, then it would support the hypothesis that notum symmetry is the cause of the Janus heads. However, if it produces an increase of notum in an asymmetric manner, then the Janus phenotype should be rescued.

(2) The second weakness of the study is related to the methodology used to support the second claim, that the slope of bcatenin1 activity has a role in the decision of regeneration - a head and a tail in the correct tip. The main concerns relate to the specificity of the anti-bcatenin1 antibody and to the broad effect of C59 in the secretion of all Wnts.

a) Raising an antibody against beta-catenin1 that allows the quantification by western blot is a strength of the study, since beta-catenin1 is the key element of the cWnt pathway, and their levels are directly associated with the activation of the pathway. Since this is one of the tools that support the second claim of the study, a characterization of the antibody and additional tests to prove its specificity are required. The authors show a Western blot in which the band intensity decreases after beta-catenin1 inhibition in both species. Further analysis should be shown:<br /> i) Demonstration that the intensity of the band increases after APC or Axin inhibition.<br /> ii) Does the antibody work in immunohistochemistry? It would provide further evidence of the specificity of a nuclear signal could be demonstrated.<br /> iii) Explanation and discussion of the protocol used to analyse the levels of b-catenin1 activity along the anteroposterior axis is required. It has been reported that beta-catenin1 is highly expressed and required in the brain in planarians, and also in the pharynx, and in the sexual organs (Hill and Petersen 2015, Sureda-Gomez et al 2016). How is it then explained the anterior-to-posterior gradient of expression of beta-catenin1 seen in this study in both species? Has the pharynx been removed before the protein extraction? What about the beta-catenin1 activity demonstrated in the brain? Why is it not reflected in the western blot analysis using the antibody? This point should be clarified.

b) The second tool used in the second part of the manuscript is the drug C59, which inhibits Porcupine, a protein required for palmitoylation and secretion of Wnts. Because Porcupine could be required for the secretion of all Wnts, the phenotype obtained with the drug could be the sum of the inhibition of cWNT signal (wnt1 for instances) and non-canonical WNT (as wnt5). This is in fact the phenotype resulting after the inhibition of Wntless in planarians (Adell et al. 2009), which is also required for the secretion of Wnts. Thus, in the phenotypes resulting from C59 treatment the analysis of the nervous system and posterior/anterior markers is required. Looking at the in vivo phenotype it appears that in fact the drug is affecting both canonical and no canonical pathways since the animal with protrusions in the lateral part (Figure 4B-double head, or Supplementary Figure 3A) is very similar to the one reported after Wntless inhibition. In case the phenotypes observed also show non-canonical Wnt inhibition, this should be clearly shown and discussed.

The above-mentioned weaknesses are the most important concerns about the present manuscript. However, there are other concerns related to a further analysis of the phenotypes and the analysis of additional Wnt elements as wnt1, which are essential to complete the study and are directly discussed with the authors.

Tour city nha trang 1 ngày do Nha Trang Travel tổ chức với lịch trình hợp lý trong 1 ngày giúp du khách khám phá các địa danh nổi bật như Bảo tàng Hải Dương Học, Hòn Chồng, Tháp Bà Ponagar và Nhà thờ Đá. Mỗi địa điểm mang nét đặc trưng riêng: Bảo tàng Hải Dương Học trưng bày hơn 20.000 mẫu vật từ năm 1922 với kiến trúc Pháp cổ; Hòn Chồng là bãi đá tự nhiên độc đáo; Tháp Bà Ponagar nằm trên đồi cao 10m mang đậm kiến trúc Chăm Pa và Nhà thờ Đá với phong cách Gothic nổi bật tại trung tâm thành phố.

Reviewer #1 (Public review):

Summary:

The authors analyzed the bacterial colonization of human sperm using 16S rRNA profiling. Patterns of microbiota colonization were subsequently correlated with clinical data, such as spermiogram analysis, presence of reactive oxygen species (ROS), and DNA fragmentation. The authors identified three main clusters dominated by Streptococcus, Prevotella, and Lactobacillus & Gardnerella, respectively, which aligns with previous observations. Specific associations were observed for certain bacterial genera, such as Flavobacterium and semen quality. Overall, it is a well-conducted study that further supports the importance of the seminal microbiota.

Strengths:

- The authors performed the analysis on 223 samples, which is the largest dataset in semen microbiota analysis so far

- Inclusion of negative controls to control contaminations.

- Inclusion of a positive control group consisting of men with proven fertility.

[Editors' note: the authors addressed the concerns raised in the previous round of review.]

Reviewer #1 (Public review):

Summary:

This work is a continuation of a previous paper from the Arnold group, where they engineered GFE3, which allows to specifically ablate inhibitory synapses. Here, the authors generate 3 different actuators:

(1) An excitatory synapse ablator.<br /> (2) A photoactivatable inhibitory synapse ablator.<br /> (3) A chemically inhibitory synapse ablator.

Following initial engineering, the authors present characterization and optimization data to showcase that these new tools allow one to specifically ablate synapses, without toxicity and with specificity. Furthermore, they showcase that these manipulations are reversible.

Altogether, these new tools would be important for the neuroscience community.

Strengths:

The authors convincingly demonstrate the engineering, optimization and characterization of these new probes. The main novelty here is the new excitatory synapse ablator, which has not been shown yet and thus could be a valuable tool for neuroscientists.

Weaknesses:

The authors have convincingly demonstrated the use of these tools in cultured neurons. The biggest weakness is the limited information given for the use of these tools for in vivo studies. The authors provide one example of the use of these new tool to study retinal circuits, and show evidence that the excitatory synapse ablator reduces synaptic transmission in retinal slices. Still, more work will be required to use this tool in intact neuronal circuits. It remains unclear if it would be trivial to characterize how well these tools express and operate in vivo. This could be substantially different and present some limitations as to the utility of these tools.

Reviewer #1 (Public review):

Summary:

The paper develops a phase method to obtain the excitatory and inhibitory afferents to certain neuron populations in the brainstem. The inferred contributions are then compared to the results of voltage clamp and current clamp experiments measuring the synaptic contributions to post-I, aug-E and ramp-I neurons.

Strengths:

The electrophysiology part of the paper is sound and reports novel features with respect to earlier work by JC Smith et al 2012, Paton et al 2022 (and others) who have mapped circuits of the respiratory central pattern generator. Measurements on ramp-I neurons, late-I neurons and two types of post-I neurons in Fig.2 besides measurements of synaptic inputs to these neurons in Fig.5 are to my knowledge new.

Weaknesses:

The phase method for inferring synaptic conductances fails to convince. The method rests on many layers of assumptions and the inferred connections in Fig.4 remain speculative. To be convincing, such method ought to be tested first on a model CPG with known connectivity to assess how good it is at inferring known connections back from the analysis of spatio-temporal oscillations. For biological data, once the network connectivity has been inferred as claimed, the straightforward validation is to reconstruct the experimental oscillations (Fig.2) noting that Rybak et al (Rybak, Paton Schwaber J. Neurophysiol. 77, 1994 (1997)) have already derived models for the respiratory neurons.

The transformation from time to phase space, unlike in the Kuramoto model, is not justified here (L.94) and is wrong. The underpinning idea that "the synaptic conductances depend on the cycle phase and not on time explicitly" is flawed because synapses have characteristic decay times and delays to response which remain fixed when the period of network oscillations increases. Synaptic properties depend on time and not on phase in the network. One major consequence relevant to the present identification of excitatory or inhibitory behaviour, is that it cannot account for change in behaviour of inhibitory synapses - from inhibitory to excitatory action - when the inhibitory decay time becomes commensurable to the period of network oscillations (Wang & Buzsaki Journal of Neuroscience 16, 6402 (1996), van Vreeswijk et al. J. Comp. Neuroscience 1,313 (1994), Borgers and Kopell Neural Comput. 15, 2003). In addition, even small delays in the inhibitory synapse response relative to the pre-synaptic action potential also produce in-phase synchronization (Chauhan et al., Sci. Rep. 8, 11431 (2018); Borgers and Kopell, Neural Comput. 15, 509 (2003)). The present assumption are way too simplistic because you cannot account for these commensurability effects with a single parameter like the network phase. There is therefore little confidence that this model can reliably distinguish excitatory from inhibitory synapses when their dynamics properties are not properly taken into account.

L..82, Eq.1 makes extremely crude assumptions that the displacement current (CdV/dt) is negligible and that the ion channel currents are all negligible. Vm(t) is also not defined. The assumption that the activation/inactivation times of all ion channels are small compared to the 10-20ms decay time of synaptic currents is not true in general. Same for the displacement current. The leak conductance is typically g~0.05-0.09ms/cm^2 while C~1uF/cm^2. Therefore the ratio C/g leak is in the 10-20ms range - the same as the typical docking neurotransmitter time in synapses.

Models of brainstem CPG circuits have been known to exist for decades: JC Smith et al 2012, Paton et al 2022, Bellingham Clin. Exp. Pharm. And Physiol. 25, 847 (1998); Rubin et al., J. Neurophysiol. 101, 2146 (2009) among others. The present paper does not discuss existing knowledge on respiratory networks and gives the impression of reinventing the wheel from scratch. How will this paper add to existing knowledge?

Comments on revisions:

The authors have done a good job at revising the manuscript to put this work into the context of earlier work on brainstem central pattern generators.

I still believe the case for the method is not as convincing as it would have been if the method had been validated first on oscillations produced by a known CPG model. Why would the inference of synaptic types from the model CPG voltage oscillations be predetermined? Such inverse problems are quite complicated and their solution is often not unique or sufficiently constrained. Recovering synaptic weights (or CPG parameters) from limited observations of a highly nonlinear system is not warranted (Gutenkunst et al., Universally sloppy parameter sensitivities in systems biology models, PLoS Comp. Biol. 2007; www.doi.org/10.1371/journal.pcbi.0030189) especially when using surrogate biological models like Hodgkin-Huxley models.

In p.2, the edited section refers to the interspike interval being much smaller than the period of the network. More important is to mention the relationship between the decay time of inhibitory synapses and the period of the network.

Reviewer #1 (Public review):

Summary

In this human neuroimaging and electrophysiology study, the authors aimed to characterise effects of a period of visual deprivation in the sensitive period on excitatory and inhibitory balance in the visual cortex. They attempted to do so by comparing neurochemistry conditions ('eyes open', 'eyes closed') and resting state, and visually evoked EEG activity between ten congenital cataract patients with recovered sight (CC), and ten age-matched control participants (SC) with normal sight. First, they used magnetic resonance spectroscopy to measure in vivo neurochemistry from two locations, the primary location of interest in the visual cortex, and a control location in the frontal cortex. Such voxels are used to provide a control for the spatial specificity of any effects because the single-voxel MRS method provides a single sampling location. Using MR-visible proxies of excitatory and inhibitory neurotransmission, Glx and GABA+ respectively, the authors report no group effects in GABA+ or Glx, no difference in the functional conditions 'eyes closed' and 'eyes open'. They found an effect of group in the ratio of Glx/GABA+ and no similar effect in the control voxel location. They then perform multiple exploratory correlations between MRS measures and visual acuity and report a weak positive correlation between the 'eyes open' condition and visual acuity in CC participants. The same participants then took part in an EEG experiment. The authors selected two electrodes placed in the visual cortex for analysis and report a group difference in an EEG index of neural activity, the aperiodic intercept, as well as the aperiodic slope, considered a proxy for cortical inhibition. Control electrodes in the frontal region did not present with the same pattern. They report an exploratory correlation between the aperiodic intercept and Glx in one out of three EEG conditions.

The authors report the difference in E/I ratio and interpret the lower E/I ratio as representing an adaptation to visual deprivation, which would have initially caused a higher E/I ratio. Although intriguing, the strength of evidence in support of this view is not strong. Amongst the limitations are the low sample size, a critical control cohort that could provide evidence for higher E/I ratio in CC patients without recovered sight for example, and lower data quality in the control voxel. Nevertheless, the study provides a rare and valuable insight into experience-dependent plasticity in the human brain.

Strengths of study

How sensitive period experience shapes the developing brain is an enduring and important question in neuroscience. This question has been particularly difficult to investigate in humans. The authors recruited a small number of sight-recovered participants with bilateral congenital cataracts to investigate the effect of sensitive period deprivation on the balance of excitation and inhibition in the visual brain using measures of brain chemistry and brain electrophysiology. The research is novel, and the paper was interesting and well-written.

Limitations

Low sample size. Ten for CC and ten for SC, and further two SC participants were rejected due to lack of frontal control voxel data. The sample size limits the statistical power of the dataset and increases the likelihood of effect inflation.

In the updated manuscript, the authors have provided justification for their sample size by pointing to prior studies and the inherent difficulties in recruiting individuals with bilateral congenital cataracts. Importantly, this highlights the value the study brings to the field while also acknowledging the need to replicate the effects in a larger cohort.

Lack of specific control cohort. The control cohort has normal vision. The control cohort is not specific enough to distinguish between people with sight loss due to different causes and patients with congenital cataracts with co-morbidities. Further data from a more specific populations, such as patients whose cataracts have not been removed, with developmental cataracts, or congenitally blind participants, would greatly improve the interpretability of the main finding. The lack of a more specific control cohort is a major caveat that limits a conclusive interpretation of the results.

In the updated version, the authors have indicated that future studies can pursue comparisons between congenital cataract participants and cohorts with later sight loss.

MRS data quality differences. Data quality in the control voxel appears worse than in the visual cortex voxel. The frontal cortex MRS spectrum shows far broader linewidth than the visual cortex (Supplementary Figures). Compared to the visual voxel, the frontal cortex voxel has less defined Glx and GABA+ peaks; lower GABA+ and Glx concentrations, lower NAA SNR values; lower NAA concentrations. If the data quality is a lot worse in the FC, then small effects may not be detectable.

In the updated version, the authors have added more information that informs the reader of the MRS quality differences between voxel locations. This increases the transparency of their reporting and enhances the assessment of the results.

Because of the direction of the difference in E/I, the authors interpret their findings as representing signatures of sight improvement after surgery without further evidence, either within the study or from the literature. However, the literature suggests that plasticity and visual deprivation drives the E/I index up rather than down. Decreasing GABA+ is thought to facilitate experience dependent remodelling. What evidence is there that cortical inhibition increases in response to a visual cortex that is over-sensitised to due congenital cataracts? Without further experimental or literature support this interpretation remains very speculative.

The updated manuscript contains key reference from non-human work to justify their interpretation.

Heterogeneity in patient group. Congenital cataract (CC) patients experienced a variety of duration of visual impairment and were of different ages. They presented with co-morbidities (absorbed lens, strabismus, nystagmus). Strabismus has been associated with abnormalities in GABAergic inhibition in the visual cortex. The possible interactions with residual vision and confounds of co-morbidities are not experimentally controlled for in the correlations, and not discussed.

The updated document has addressed this caveat.

Multiple exploratory correlations were performed to relate MRS measures to visual acuity (shown in Supplementary Materials), and only specific ones shown in the main document. The authors describe the analysis as exploratory in the 'Methods' section. Furthermore, the correlation between visual acuity and E/I metric is weak, not corrected for multiple comparisons. The results should be presented as preliminary, as no strong conclusions can be made from them. They can provide a hypothesis to test in a future study.

This has now been done throughout the document and increases the transparency of the reporting.

P.16 Given the correlation of the aperiodic intercept with age ("Age negatively correlated with the aperiodic intercept across CC and SC individuals, that is, a flattening of the intercept was observed with age"), age needs to be controlled for in the correlation between neurochemistry and the aperiodic intercept. Glx has also been shown to negatively correlates with age.

This caveat has been addressed in the revised manuscript.

Multiple exploratory correlations were performed to relate MRS to EEG measures (shown in Supplementary Materials), and only specific ones shown in the main document. Given the multiple measures from the MRS, the correlations with the EEG measures were exploratory, as stated in the text, p.16, and in Fig.4. yet the introduction said that there was a prior hypothesis "We further hypothesized that neurotransmitter changes would relate to changes in the slope and intercept of the EEG aperiodic activity in the same subjects." It would be great if the text could be revised for consistency and the analysis described as exploratory.

This has been done throughout the document and increases the transparency of the reporting.

The analysis for the EEG needs to take more advantage of the available data. As far as I understand, only two electrodes were used, yet far more were available as seen in their previous study (Ossandon et al., 2023). The spatial specificity is not established. The authors could use the frontal cortex electrode (FP1, FP2) signals as a control for spatial specificity in the group effects, or even better, all available electrodes and correct for multiple comparisons. Furthermore, they could use the aperiodic intercept vs Glx in SC to evaluate the specificity of the correlation to CC.

This caveat has been addressed. The authors have added frontal electrodes to their analysis, providing an essential regional control for the visual cortex location.

Comments on revisions:

In the first revision, the authors made reasonable adjustments to their manuscript that addressed most of my comments by adding further justification for their methodology, essential literature support, pointing out exploratory analyses, limitations and adding key control analyses. Their revised manuscript was overall improved, providing valuable information, though the evidence that supports their claims is still incomplete.

In their second revision, the authors pointed to justifications for their analyses, careful interpretation and tempered claims to clarify their response to the initial feedback. However, my assessment of the first revision has not been changed after the second revision, because there were no further modifications of their responses to my feedback.

Reviewer #2 (Public review):

van Vliet and colleagues present results of a study correlating internal states of a convolutional neural network trained on visual word stimuli with evoked MEG potentials during reading.

In this study, a standard deep learning image recognition model (VGG-11) trained on a large natural image set (ImageNet) that begins illiterate but is then further trained on visual word stimuli, is used on a set of predefined stimulus images to extract strings of characters from "noisy" words, pseudowords and real words. This methodology is used in hopes of creating a model which learns to apply the same nonlinear transforms that could be happening in different regions of the brain - which would be validated by studying the correlations between the weights of this model and neural responses. Specifically, the aim is that the model learns some vector embedding space, as quantified by the spread of activations across a layer's weights (L2 Norm prior to ReLu Activation Function), for the different kinds of stimuli, that creates a parameterized decision boundary that is similar to amplitude changes at different times for a MEG signal. More importantly, the way that the stimuli are ordered or ranked in that space should be separable to the degree we see separation in neural activity. This study does show that the layer weights corresponding to five different broad classes of stimuli do statistically correlate with three specific components in the ERP. However, I believe there are fundamental theoretical issues that limit the implications of the results of this study.

As has been shown over many decades, there are many potential computational algorithms, with varied model architectures, that can perform the task of text recognition from an image. However, there is no evidence presented here that this particular algorithm has comparable performance to human behavior (i.e. similar accuracy with a comparable pattern of mistakes). This is a fundamental prerequisite before attempting to meaningfully correlate these layer activations to human neural activations. Therefore, it is unlikely that correlating these derived layer weights to neural activity provides meaningful novel insights into neural computation beyond what is seen using traditional experimental methods.

One example of a substantial discrepancy between this model and neural activations is that, while incorporating frequency weighting into the training data is shown to slightly increase neural correlation with the model, Figure 7 shows that no layer of the model appears directly sensitive to word frequency. This is in stark contrast to the strong neural sensitivity to word frequency seen in EEG (e.g. Dambacher et al 2006 Brain Research), fMRI (e.g. Kronbichler et al 2004 NeuroImage), MEG (e.g. Huizeling et al 2021 Neurobio. Lang.), and intracranial (e.g. Woolnough et al 2022 J. Neurosci.) recordings. Figure 7 also demonstrates that late stages of the model show a strong negative correlation with font size, whereas later stages of neural visual word processing are typically insensitive to differences in visual features, instead showing sensitivity to lexical factors.

Another example of the mismatch between this model and visual cortex is the lack of feedback connections in the model. Within visual cortex there are extensive feedback connections, with later processing stages providing recursive feedback to earlier stages. This is especially evident in reading, where feedback from lexical level processes feeds back to letter level processes (e.g. Heilbron et al 2020 Nature Comms.). This feedback is especially relevant for reading of words in noisy conditions, as tested in the current manuscript, as lexical knowledge enhances letter representation in visual cortex (the word superiority effect). This results in neural activity in multiple cortical areas varying over time, changing selectivity within a region at different measured time points (e.g. Woolnough et al 2021 Nature Human Behav.), which in the current study is simplified down to three discrete time windows, each attributed to different spatial locations.

The presented model needs substantial further development to be able to replicate, both behaviorally and neurally, many of the well-characterized phenomena seen in human behavior and neural recordings that are fundamental hallmarks of human visual word processing. Until that point it is unclear what novel contributions can be gleaned from correlating low dimensional model weights from these computational models with human neural data.

The revised version of this manuscript has not addressed these concerns.

Reviewer #1 (Public review):

Summary:

Insects and their relatives are commonly infected with microbes that are transmitted from mothers to their offspring. A number of these microbes have independently evolved the ability to kill the sons of infected females very early in their development; this male killing strategy has evolved because males are transmission dead-ends for the microbe. A major question in the field has been to identify the genes that cause male killing and to understand how they work. This has been especially challenging because most male-killing microbes cannot be genetically manipulated. This study focuses on a male-killing bacterium called Wolbachia. Different Wolbachia strains kill male embryos in beetles, flies, moths, and other arthropods. This is remarkable because how sex is determined differs widely in these hosts. Two Wolbachia genes have been previously implicated in male-killing by Wolbachia: oscar (in moth male-killing) and wmk (in fly male-killing). The genomes of some male-killing Wolbachia contain both of these genes, so it is a challenge to disentangle the two.

This paper provides strong evidence that oscar is responsible for male-killing in moths. Here, the authors study a strain of Wolbachia that kills males in a pest of tea, Homona magnanima. Overexpressing oscar, but not wmk, kills male moth embryos. This is because oscar interferes with masculinizer, the master gene that controls sex determination in moths and butterflies. Interfering with the masculinizer gene in this way leads the (male) embryo down a path of female development, which causes problems in regulating the expression of genes that are found on the sex chromosomes.

Strengths:

The authors use a broad number of approaches to implicate oscar, and to dissect its mechanism of male lethality. These approaches include: a) overexpressing oscar (and wmk) by injecting RNA into moth eggs, b) determining the sex of embryos by staining female sex chromosomes, c) determining the consequences of oscar expression by assaying sex-specific splice variants of doublesex, a key sex determination gene, and by quantifying gene expression and dosage of sex chromosomes, using RNASeq, and d) expressing oscar along with masculinizer from various moth and butterfly species, in a silkmoth cell line. This extends recently published studies implicating oscar in male-killing by Wolbachia in Ostrinia corn borer moths, although the Homona and Ostrinia oscar proteins are quite divergent. Combined with other studies, there is now broad support for oscar as the male-killing gene in moths and butterflies (i.e. order Lepidoptera).

Joint Public Review:

Summary:

Jia and colleagues developed a fluorescence resonance energy transfer (FRET)-based biosensor to study programmed cell death in the zebrafish spinal cord. They applied this tool to study death of zebrafish spinal motor neurons.

Strengths:

Their analysis shows that the tool is a useful biosensor of motor neuron apoptosis in living zebrafish and can reveal which part of the neuron undergoes caspase activation first.

Weaknesses:

As far as it is possible to tell, the authors focus on death of motor neurons innervating axial muscles. Previous work from over 30 years ago revealed that only a small number of these motor neurons die early in development. So this is not new, although following the cells and learning details of their apoptosis is new. Most of the work on motor neuron death in tetrapods was carried out on limb innervating motor neurons. Zebrafish have paired pectoral and pelvic fins, homologs of tetrapod paired limbs. These fins are innervated by distinct sets of motor neurons in zebrafish, as they are in tetrapods. However, the authors have not focused on these particular motor neurons, and thus have not made a fair comparison with tetrapods. In fact, they do not tell us which spinal levels they observed or whether they have been consistent from animal to animal. Pelvic fins emerge much later than pectoral fins in zebrafish, so it is possible that the time frame during which the authors imaged motor neuron death does not include motor neurons innervating pelvic fins.

Reviewer #1 (Public review):

Experiments in model organisms have revealed that the effects of genes on heritable traits are often mediated by environmental factors -- so-called gene-by-environment (or GxE) interactions. In human genetics, however, where indirect statistical approaches must be taken to detect GxE, limited evidence has been found for pervasive GxE interactions. The present manuscript argues that the failure of statistical methods to detect GxE may be due to how GxE is modelled (or not modelled) by these methods.

The authors show, via re-analysis of an existing dataset in Drosophila, that a polygenic 'amplification' model can parsimoniously explain patterns of differential genetic effects across environments. (Work from the same lab had previously shown that the amplification model is consistent with differential genetic effects across the sexes for a number of traits in humans.) The parsimony of the amplification model allows for powerful detection of GxE in scenarios in which it pertains, as the authors show via simulation.

Before the authors consider polygenic models of GxE, however, they present a very clear analysis of a related question around GxE: When one wants to estimate the effect of an individual allele in a particular environment, when is it better to stratify one's sample by environment (reducing sample size, and therefore increasing the variance of the estimator) versus using the entire sample (including individuals not in the environment of interest, and therefore biasing the estimator away from the true effect specific to the environment of interest)? Intuitively, the sample-size cost of stratification is worth paying if true allelic effects differ substantially between the environment of interest and other environments (i.e., GxE interactions are large), but not worth paying if effects are similar across environments. The authors quantify this trade-off in a way that is both mathematically precise and conveys the above intuition very clearly. They argue on its basis that, when allelic effects are small (as in highly polygenic traits), single-locus tests for GxE may be substantially underpowered.

The paper is an important further demonstration of the plausibility of the amplification model of GxE, which, given its parsimony, holds substantial promise for the detection and characterization of GxE in genomic datasets. However, the empirical and simulation examples considered in the paper (and previous work from the same lab) are somewhat "best-case" scenarios for the amplification model, with only two environments and with these environments amplifying equally the effects of only a single set of genes. It would be an important step forward to demonstrate the possibility of detecting amplification in more complex scenarios, with multiple environments each differentially modulating the effects of multiple sets of genes. This could be achieved via simulations similar to those presented in the current manuscript.

Comments on revisions:

The authors have (with reasonable justification) said that my main recommendations for strengthening the conclusions of the paper are beyond its scope, and they have thoughtfully responded to my (and the other reviewer's) other comments. The paper is now more clearly written---in particular, the connection between the single-locus bias-variance tradeoff calculations and the polygenic results is much more transparent than before. Given that the authors have (again, with fair justification) chosen not to address my major comment, my broad assessment of the paper is unchanged---I think it is an important contribution to a critical topic---and I have no further comments for its improvement (though I note an issue with figure referencing in the captions of Supplementary Figs S2 and S3).

Reviewer #1 (Public review):

Summary:

The authors report an inability to reproduce a transgenerational memory of avoidance of the pathogen PA14 in C. elegans. Instead, the authors demonstrate intergenerational inheritance for a single F1 generation, in embryos of mothers exposed to OP50 and PA14, where embryos isolated from these mothers by bleaching are capable of remembering to avoid PA14 in a manner that is dependent on systemic RNAi proteins sid-1 and sid-2. This could reflect systemic sRNAs generated by neuronal daf-7 signaling that are transmitted to F1 embryos. The authors note that transgenerational memory of PA14 was reported by the Murphy group at Princeton, but that environmental or strain variation (worms or bacteria) might explain the single generation of inheritance observed at Harvard. The Hunter group tried different bacterial growth conditions and different worm growth temperatures for independent PA14 strains, which they show to be strongly pathogenic. However, the authors could not reproduce a transgenerational effect at Harvard. This paper honestly alters expectations and indicates that the model that avoidance of PA14 is remembered for multiple generations is not robust enough to be replicated in all laboratories.

Overall, this paper that demonstrates that one model for transgenerational inheritance in C. elegans is not robust. The author do demonstrate an avoidance memory for F1 embryos that could be a maternal effect, and the authors confirm that this is mediated by a systemic small RNA response. There are several points in the manuscript where a more positive tone might be helpful.

Strengths:

The authors note that the high copy number daf-7::GFP transgene used by the Murphy group displayed variable expression and evidence for somatic silencing or transgene breakdown in the Hunter lab, as confirmed by the Murphy group. The authors nicely use single copy daf-7::GFP to show that neuronal daf-7::GFP is elevated in F1 but not F2 progeny with regards to memory of PA14 avoidance, speaking to an intergenerational phenotype.

The authors nicely confirm that sid-1 and sid-2 are generally required for intergenerational avoidance of F1 embryos of moms exposed to PA14. However, these small RNA proteins did not affect daf-7::GFP elevation in the F1 progeny. This result is unexpected given previous reports that daf-7::GFP is not elevated in F1 progeny of sid mutants.

The authors studied antisense small RNAs that change in Murphy data sets, identifying 116 mRNAs that might be regulated by sRNAs in response to PA14. The authors show that the maco-1 gene, putatively targeted by piRNAs according to the Kaletsky 2020 paper, displays few siRNAs that change in response to PA14. The authors conclude that the P11 ncRNA of PA14, which was proposed to promote interkingdom RNA communication by the Murphy group, may not affect maco-1 expression in C. elegans, although they did not formally demonstrate this. The authors define 8 genes based on their analysis of sRNAs and mRNAs that might promote resistance to PA14, but they do not further characterize these genes' role in pathogen avoidance. Others might wish to consider following up on these genes and their possible relationship with P11.

Weaknesses: