Reviewer #1 (Public Review):

This manuscript presents a fascinating "connectome" dataset of the Octopus vulgaris vertical lobe (VL), a brain region involved in learning and memory with a unique structure. It presents the cell types and connectivity of several major classes of cells in this region. One of the most notable findings is that the most numerous neurons, the SAMs, receive only one synaptic input, while another much less numerous class, the CAMs, receive many. Both of these feed onto an output layer of neurons named LNs. This organization is strikingly different from many other associative learning areas in other species.

Overall, the paper presents an interesting and important collection of anatomical results that will be of interest to those working on this system, as well as (at least at first glance) related systems like the insect mushroom body or mammalian cerebellum. The authors do a good job of highlighting the key properties of this system and contrasting them to other systems. My detailed suggestions are largely about the presentation, but I do have some conceptual comments.

This paper raises an interesting question about learning signals. The most intriguing property of this system is the one-to-one convergence, plasticity, and apparently linear input/output function of the SFL-to-SAM relay. These properties suggest that, unlike structures like the insect mushroom body or mammalian cerebellum, in which the intermediate layer is thought to increase the dimensionality of the representation, the SAMs should be thought of more like the weights of a linear readout of the SFL inputs by the LNs. What learning signal guarantees appropriate weight changes? In a few places (the section on "associativity" and the section on AFs), it is suggested that SAMs can themselves, through coordinated local activity, cause LTP, which the authors call "self LTP-induction." But what is the purpose of such plasticity? It doesn't seem like it would permit, for example, LTP which associates a pattern of SFL activity with the appropriate LNs for the correct vs. the incorrect action. Presumably, appropriately routed information from the NMs and AFs sends the appropriate learning signals to the right places. Does the pattern of innervation of NMs and AFs reveal how these signals are distributed across association modules? Does this lead to a prediction for the logic of the organization of the association modules?

One challenge for a reader who is not an expert on the VL is that the manuscript in its present form lacks discussion about the impact (or hypothesized impact) of the VL on behavior. There is a reference to a role for LNs suppressing attack behavior, but a more comprehensive picture of what the readout layer of this system is likely controlling would be helpful.

The authors do a thorough job of characterizing the "fan-out" architecture from SFL axons to SAMs and CAMs. A few key numbers remain to characterize the "fan-in" architecture of LNs. There appears to be a 400:1 convergence from AMs to LNs. Is it possible to estimate the approximate number of presynaptic inputs per LN? The text around Figure 7 states a median of 162 sites per 100μm dendrite length. One could combine this with an estimate of the total dendritic length for one of these cells from previously available data to estimate the number of inputs per LN. This would help determine the degree of overlap of different association modules in Figure 11, which would be interesting from a computational perspective.

This is an exciting and intriguing set of results that contributes significantly to our knowledge about the brain regions that control learning and memory.

Reviewer #1 (Public Review):

Insect chemosensory receptors function as ligand-gated ion channels, while vertebrate and nematode chemoreceptors are G-protein coupled receptors. This difference led to multiple questions. One was whether there are vertebrate homologs of insect chemosensory receptors or receptor-like proteins. This manuscript of Benton and Himmel titled "Structural screens identify candidate human homologs of insect chemoreceptors and cryptic Drosophila gustatory receptor-like proteins" addressed this key question. First, it showed consistent results using the new tool for protein structure prediction, AlphaFold2, and confirmed the previously identified OR, GR, GRL, and DUF proteins in the 7TMIC superfamily as structural homologs of Orco. Then the authors identified human/vertebrate homologs: PHTF, but the function of this protein is not clear. Finally, they further expanded drosophilid-specific GRL proteins. It is great to see new members of the 7TMIC superfamily!

Reviewer #1 (Public Review):

The authors sequence some of the oldest maize macroremains found to date, from lowland Peru. They find evidence that these specimens were already domesticated forms. They also find a lack of introgression from wild maize populations. Finally, they find evidence the Par_N16 sample already carried alleles for lowland adaptation.<br /> Overall I think this is an interesting topic, the study is well-written and executed for the most part.

I have a variety of comments, most important of which revolve around methodological clarity. I will give those comments first.

The authors should say in the Results section how "alleles previously reported to be adaptive to highlands and lowlands, specifically in Mesoamerica or South America" were identified in Takuno et al. 2015. What method was used? I see this partly comes in the Discussion eventually, but it would help to have it in the Results with more detail. The answer to this question would help a skeptical reader decide the appropriateness of the resource, given that many selection scans have been performed on maize genomes, the choice would ideally not be arbitrary.

How were the covered putative adaptive SNPs distributed in the genome? Were any clustered and linked? The random sampled SNPs should be similarly distributed to give an appropriate null.

How is genetic similarity calculated? It should be briefly described in the Results.

It would help for the authors to state why they focus on Par_N16, I did not see this in my reading. Presumably, the analyses done are because of the higher quality data, but it would also help to mention why Par_N16 was sequenced in an additional run.

In the sections on phylogenetic analysis, introgression, and D statistics, the authors could do a better job specifically indicating how the results support their conclusions.

Reviewer #1 (Public Review):

The authors investigated state-dependent changes in evoked brain activity, using electrical stimulation combined with multisite neural activity across wakefulness and anesthesia. The approach is novel, and the results are compelling. The study benefits from an in-depth sophisticated analysis of neural signals. The effects of behavioral state on brain responses to stimulation are generally convincing.

It is possible that the authors' use of "an average reference montage that removed signals common to all EEG electrodes" could also remove useful components of the signal, which are common across EEG electrodes, especially during deep anesthesia. For example, it is possible (in fact from my experience I would be surprised if it is not the case) that under isoflurane anesthesia, electrical stimulation induces a generalized slow wave or a burst of activity across the brain. Subtracting the average signal will simply remove that from all channels. This does not only result in signals under anesthesia being affected more by the referencing procedure than during waking but also will have different effects on different channels, e.g. depending on how strong the response is in a specific channel.

Reviewer #1 (Public Review):

This manuscript studies the representation by gender and name origin of authors from Nature and Springer Nature articles in Nature News. The representation of author identities is an important step towards equality in science, and the authors found that women are underrepresented in news quotes and mentions with respect to the proportion of women authors.

Strengths:

The research is rigorously conducted. It presents relevant questions and compelling answers. The documentation of the data and methods is thoroughly done, and the authors provide the code and data for reproduction.

Weaknesses:

The article is not so clearly structured, which makes it hard to follow. A better framing, contextualization, and conceptualization of their analysis would help the readers to better understand the results. There are some unclear definitions and wrong wording of key concepts.

Reviewer #1 (Public Review):

Ibar and colleagues investigate the function of spectrin in Drosophila wing imaginal discs and its effect on the Hippo pathway and myosin activity. The authors find that both βH-Spec and its canonical binding partner α-Spec reduce junctional localization of the protein Jub and thereby restrict Jub's inhibitory effect on Hippo signaling resulting in activation of the Hippo effector Yorkie regulating tissue shape and organ size. From genetic epistasis analysis and analysis of protein localization, the authors conclude that βH-Spec and α-Spec act independently in this regulation. The major point of this study is that the apical localization of βH-Spec and myosin is mutually exclusive and that the proteins antagonize each other's activity in wing discs. In vitro co-sedimentation assays and in silico structural modeling suggest that this antagonization is due to a competition of βH-Spec and myosin for F-actin binding.

The study's strengths are the genetic perturbation that is the basis for the epistasis analysis which includes specific knockdowns of the genes of interest as well as an elegant CRISPR-based overexpression system with great tissue specificity. The choice of the model for such an in-depth analysis of pathway dependencies in a well-characterized tissue makes it possible to identify and characterize quantitative differences between closely entangled and mutually dependent components. The method of quantifying protein localization and abundance is common for multiple figures which makes it easy to assess differences across experiments.

A weakness in the methodology is the link to tissue tension and conclusions about tissue mechanics. Methods that directly affect tissue tension and a more thorough and systematic application of laser ablation experiments would be needed to profoundly investigate mechanosensation and consequential effects on tissue tension by the various genetic perturbations. While the in-silico analysis of competing for F-actin binding sites for βH-Spec and myosin appears logical and supports the authors' claims, no point mutation or truncations were used to test these results in vivo. In its current structure the manuscript's strength, the genetic perturbations, is compromised by missing clear assessments of knockdown efficiencies early in the manuscript and other controls such as the actual effect on myosin by ROCK overactivation.

The flow of experiments is logical and in general, the author's conclusions are supported by the presented data. The findings are very well embedded into the context of relevant literature and both confronting and confirming literature are discussed.

The study shows how components of the cytoskeleton are directly involved in the regulation of the mechanosensitive Hippo pathway in vivo and thus ultimately regulate organ size supporting previous data in other contexts. The molecular mechanism regulating myosin activity by out-competing it for F-actin binding has been observed for small actin-binding proteins such as cofilin but is a new mode for such a big, membrane-associated actin-binding protein. This may inspire future experiments in different morphogenetic contexts for the investigation of similar mechanisms. For example, the antagonistic activity of βH-Spec and myosin in this tissue context might help explain phenomena in other systems such as spectrin-dependent ratcheting of apical constriction during mesoderm invagination (as the authors discuss). Against the classical view, the work shows that βH-Spec can act independently of α-Spec. Together the results will be of interest to the cell biology community with a focus on the cytoskeleton and mechanotransduction.

Reviewer #1 (Public Review):

Weber et al. collect locus coeruleus (LC) tissue blocks from 5 neurotypical European men, dissect the dorsal pons around the LC and prepare 2-3 tissue sections from each donor on a slide for 10X spatial transcriptomics. From three of these donors, they also prepared an additional section for 10x single nucleus sequencing. Overall, the results validate well-known marker genes for the LC (e.g. DBH, TH, SLC6A2), and generate a useful resource that lists genes which are enriched in LC neurons in humans, with either of these two techniques. A comparison with publicly available mouse and rat datasets identifies genes that show reliable LC-enrichment across species. Their analyses also support recent rodent studies that have identified subgroups of interneurons in the region surrounding the LC, which show enrichment for different neuropeptides. In addition, the authors claim that some LC neurons co-express cholinergic markers, and that a population of serotonin (5-HT) neurons is located within or near the LC. These last two claims must be taken with great caution, as several technological limitations restrict the interpretation of these results. Overall, there is limited integration between the spatial and single-nucleus sequencing, thus the data does not yet provide a conclusive list of bona fide LC-specific genes. The authors transparently present limitations of their work in the discussion, but some points discussed below warrant further attention.

Specific comments:

1) snRNAseq:

a. Major concerns with the snRNAseq dataset are A) the low recovery rate of putative LC-neurons in the snRNAseq dataset, B) the fact that the LC neuron cluster is contaminated with mitochondrial RNA, and C) that a large fraction of the nuclei cannot be assigned to a clear cell type (presumably due to contamination or damaged nuclei). The authors chose to enrich for neurons using NeuN antibody staining and FACS. But it is difficult to assess the efficacy of this enrichment without images of the nuclear suspension obtained before FACS, and of the FACS results. As this field is in its infancy, more detail on preliminary experiments would help the reader to understand why the authors processed the tissue the way they did. It would be nice to know whether omitting the FACS procedure might in fact result in higher relative recovery of LC-neurons, or if the authors tried this and discovered other technical issues that prompted them to use FACS.

b. It is unclear what percentage of cells that make up each cluster.

c. The number of subjects used in each analysis was not always clear. Only 3 subjects were used for snRNAseq, and one of them only yielded 4 LC-nuclei. This means the results are essentially based on n=2. The authors report these numbers in the corresponding section, but the first sentence of the results section (and Figure 1C specifically!) create the impression that n=5 for all analyses. Even for spatial transcriptomics, if I understood it correctly, 1 sample had to be excluded (n=4).

2) Spatial transcriptomics:

a. It is not clear to me what the spatial transcriptomics provides beyond what can be shown with snRNAseq, nor how these two sets of results compare to each other. It would be more intuitive to start the story with snRNAseq and then try to provide spatial detail using spatial transcriptomics. The LC is not a homogeneous structure but can be divided into ensembles based on projection specificity. Spatial transcriptomics could - in theory - offer much-needed insights into the spatial variation of mRNA profiles across different ensembles, or as a first step across the spatial (rostral/caudal, ventral/dorsal) extent of the LC. The current analyses, however, cannot address this issue, as the orientation of the LC cannot be deduced from the slices analyzed.

b. Unfortunately, spatial transcriptomics itself is plagued by sampling variability to a point where the RNAscope analyses the authors performed prove more powerful in addressing direct questions about gene expression patterns. Given that the authors compare their results to published datasets from rodent studies, it is surprising that a direct comparison of genes identified with spatial transcriptomics vs snRNAseq is lacking (unless this reviewer missed this comparison). Supplementary Figure 17 seems to be a first step in that direction, but this is not a gene-by-gene comparison of which analysis identifies which LC-enriched genes. Such an analysis should not compare numbers of enriched genes using artificial cutoffs for significance/fold-change, but rather use correlations to get a feeling for which genes appear to be enriched in the LC using both methods. This would result in one list of genes that can serve as a reference point for future work.

c. Maybe the spatial transcriptomics could be useful to look at the peri-LC region, which has generated some excitement in rodent work recently, but remains largely unexplored in humans.

3) The comparison of snRNAseq data to published literature is laudable. Although the authors mention considerable methodological differences between the chosen rodent work and their own analyses, this needs to be further explained. The mouse dataset uses TRAPseq, which looks at translating mRNAs associated with ribosomes, very different from the nuclear RNA pool analyzed in the current work. The rat dataset used single-cell LC laser microdissection followed by microarray analyses, leading to major technical differences in terms of tissue processing and downstream analyses. The authors mention and reference a recent 10x mouse LC dataset (Luskin et al, 2022), however they only pick some neuropeptides from this study for their analysis of interneuron subtypes (Figure S13). Although this is a very interesting part of the manuscript, a more in-depth analysis of these two datasets would be very useful. It would likely allow for a better comparison between mouse and human, given that the technical approach is more similar (albeit without FACS), and Luskin et al have indicated that they are willing to share their data.

4) Statements in the manuscript about the unexpected identification of a 5-HT (serotonin) cell-cluster seem somewhat contradictory. Figure S14 suggests that 5-HT markers are expressed in the LC-regions just as much as anywhere else, but the RNAscope image in Figure S15 suggests spatial separation between these two populations. And Figure S17 again suggests almost perfect overlap between the LC and 5HT clusters. Maybe I misunderstood, in which case the authors should better clarify/explain these results.

Reviewer #1 (Public Review):

The authors sought to assess how not only RNA but also protein changes across the developmental time course of cortical organoid development. The methods used included reporter lines to label progenitor and neuronal populations, RNA-sequencing, protein quantification using mass spectrometry, and analysis of these results. The primary findings included the identification of RNA sequences that impact translation, the most significant of which was a 5'-TOP cassette that is mediated by mTOR.

Strengths of the paper include strong experimental design, replicates, and images to show the quality of the organoids used in the studies. Additionally, the analysis of elements regulating translation was strong, and the polysome experiments exploring an impact when TSC is deleted were interesting.

Potential limitations include technical challenges related to the specificity of the reporters, ambiguity about the impact of normalization on the actual protein/RNA data, and potential over-interpretation of the TSC result to encompass all of the mTOR signalings.

The paper validates already observed and documented results in translational regulation whereby RNA does not fully predict protein levels. The impact of the specific examples upon functional significance in cortical development is currently unclear but this work could set the stage for additional future impactful work.

Rainbow money

Reviewer #1 (Public Review):

This paper presents the results of two fragment screens of PTP1B using room-temperature (RT) crystallography, and compares these results with a previously published fragment screen of PTP1b using cryo-temperature crystallography. The RT screen identified fewer fragment hits and lower occupancy compared to the cryo screen, consistent with prior publications on other proteins. The authors attempted to identify additional hits by applying two additional layers of data processing, which resulted in a doubling in the number of possible hits in one of the screens. Because I am not an expert in panDDA modeling, however, I am unable to evaluate the reproducibility and potential potency of these fragment hits as protein binders or their potential use as starting points for follow-up chemistry.

The fragment library used in this study was larger than those used in previously published RT crystallography experiments. Among the cryo hits that bound in RT, most fragments bound in the same manner as they did in cryo, while some bound in altered orientations or conformations, and two bound at different locations in RT compared to cryo. This level of variability is not surprising. However, one fragment was observed to bind covalently to lysines in RT, even though it showed no density in the cryo crystallization attempt. It is unclear from the provided information whether this fragment decayed during storage or if the higher temperatures accelerated the covalent chemistry. The authors also observed temperature-dependent changes in the solvation shell, and modifications to the protein structure upon fragment binding, including a distal modification.

The current version of the paper is somewhat repetitive in its presentation of the results and could be clearer in its presentation of the variations and comparisons of the two different protocols. It would be helpful to have a more concise summary of the differences between the two protocols in the current paper, as well as a discussion of how they compare to the protocol used in the previously published cryo-temperature fragment screen.

While I appreciate the speculative nature of the discussion at the end of the paper, the evidence presented by the authors does not instil confidence that these results will correspond to meaningful binders that could be used to train future machine learning models. However, depending on the intended use, it may be acceptable to train ML models to predict expected densities under typical experimental conditions.

Reviewer #1 (Public Review):

Autoantibodies to nuclear proteins are commonly associated with autoimmune conditions. Since their discovery, several reports have suggested that T-follicular regulatory cells (Tfr) Tfr cells have the capacity to preferentially suppress autoimmune antibody responses. Tfr have a TCR repertoire strongly skewed to self-antigens and in this report Ke et al. probe the idea that Tfr directly recognize nuclear proteins and inhibit nuclear protein specific B-cells. They find that vaccination of mice with an ongoing GC reaction to a foreign antigen using nuclear proteins causes expansion of Tfr and a Tfr dependent inhibition of the germinal center. Overall, this is a well written paper that significantly advances the idea that Tfr can control autoreactive B-cells in a selective manner. Most experiments are convincing. Some of the novel methods regarding the use of nuclear proteins during sequential vaccinations in mice or Tfr-B-cell doublet formation will be of interest to members of the same fields.

A primary weakness of the paper is that despite detailed analysis of cells involved in antibody production, there is very little analysis of the antibodies themselves. Particularly when Tfr deficient mice are used in figure 5 analysis of both anti-SA and anti-NucPr antibodies between the Tfr cKO and other groups would significantly advance the findings.

Reviewer #1 (Public Review):

The authors have succeeded in demonstrating that they can further extend the methodology and value of Mendelian randomization by combining their two recently developed novel approaches to Mendelian randomization studies (1) Lifecourse MR which relates the genetic instruments to the outcome, eg obesity, at different stages of life eg childhood and adulthood and (2) Tissue partitioned MR to determine if the genetic instruments have different effects on different tissues such as the brain and adipose tissue. They have successfully combined these two to investigate the influence of adiposity on circulating leptin to demonstrate the value/proof of concept of these techniques in extending the use of MR.

This is a very clearly presented and well-conducted work showing both new methodology and clear-cut results on the impact of adiposity at age 10 and in middle life and the weight gain in between on leptin levels and that the effect is mediated via the brain. They show that childhood obesity has a direct effect on leptin levels at age 10 years and an indirect effect on adult leptin along a causal pathway involving adulthood body size. They also show that BMI exerts its effect on leptin levels at both life stages via brain-tissue-mediated pathways.

Major strengths are the well-characterized data sets used and in particular, having a comprehensive data set for children and the successful use of a new approach to address a complex issue. There are no major weaknesses

The authors have achieved their two aims - the use of the new methodology and its application to the specific issue to demonstrate how it works ie proof of concept. Their results support their conclusions.

The main advance here is a demonstration of a new further enhanced approach to Mendelian randomization. This is likely to end up being used by other researchers to address complex questions.

Reviewer #1 (Public Review):

This work endeavours to delineate the relationship between IL-7R+ and IL-7R- ILC1 in the liver. They elegantly utilize a PLZF reporting system to identify the progenitor/product relationship between ILC subsets and show that ILC1s emerge separately from NK cells and LTi cells.

Furthermore, ILC1 are enriched in the liver. Extending this work in Rora-deficient mice, they demonstrate that over time, these cells are poorly replaced in the liver, and that IL-7R+ cells did not convert into IL-7R- cells at steady-state. Fetal liver IL-7R+ ILC1s were shown to partially contribute to mature ILC1s. Interestingly, they show that there were localization changes between ILC1 precursors and mature ILC1s in the liver. They then analysed the factors that might underpin these different localizations by examining IL-15 which is highly produced by macrophages and endothelial cells. They identify that hepatocyte-derived IL-15 supports the development of 7R− ILC1s in the parenchyma to maintain adult 7R− ILC1s within the sinusoids. Finally, the authors addressed the discrepancy in understanding of cytotoxicity expressed by ILC1s and identify that constitutive expression of mTOR was necessary to effect this function, thereby providing a mechanistic explanation for variable cytotoxicity observed in other studies. Overall, this study advances our knowledge of how ILC1 are generated and maintained in the liver, and how they acquire their effector functions.

Reviewer #1 (Public Review):

In this manuscript, Scagliotti and colleagues investigate the role of Dlk1 in regulating pituitary size in multiple mouse models with different Dlk1 gene dosages in order to understand the mechanisms of organ size control. They find that overexpression of Dlk1 leads to pituitary overgrowth and loss of Dlk1 causes undergrowth. Authors find two compartments of Dlk1 expression in the pituitary, in the marginal zone stem cell compartment and the parenchymal differentiated cell compartment, and by combing genetic mouse models show that a specific interaction of Dlk1 expression in both regions is necessary to affect pituitary organ size. They present to suggest that Dlk1 may repress Wnt signaling during development to control a shift from progenitor proliferation to differentiation. The data are meticulous, high quality, and clear.

I have some questions about the interpretation of their data regarding the mechanism of Dlk1 regulation of pituitary organ size, as I believe there could be potential alternative explanations for their observations:

I was wondering about the cause of the enlargement of the pituitary gland in Fig 1E, and whether it is caused by an increased number of cells (hyperplasia), an increased cell size (hypertrophy), or both. Line 104 states it is hyperplasia, and that cell size was not affected in WT-TG ('not shown', line 121). However, line 444 says the TG is hypertrophic. It would be good if the authors could elaborate on this and show or state how cell size was determined. Figs 5/6 show that WT-Tg proliferation is generally similar to WT, which suggests the increased size is not hyperplasia. It would be good to know whether this is correct. Some previous studies have shown that in pregnancy, lactotroph hypertrophy can be responsible for pituitary enlargement without hyperplasia (Castrique 2010, Hodson 2012).

Related to the organ size question above, I had a question about the cell number and proportions in Fig 1D/E/F, which shows the maintenance of endocrine cell proportions and an increase in the volume of ~30% in WT-Tg. For the cell proportions to be maintained, I thought the increase in volume per cell type (Fig 1G) would therefore have to also increase proportionally in every cell type, while 1G appears to show an increase in GH (sig) and PRL/TSH cells (ns). It would be good if the authors could discuss this briefly.

This study is impactful and will be of interest to several research communities, including those interested in pituitary development and function, organ size control, and gene imprinting mechanisms.

Reviewer #1 (Public Review):

The authors of this study sought to test whether the optogenetic induction of context-related freezing behavior could be enhanced by synchronizing light pulses to the ongoing hippocampal theta rhythm. Theta is a hippocampus-wide oscillation that strongly modulates almost every cell in this structure, which suggests that causal interventions locked to theta could have a more pronounced impact than open-loop ones. Indeed, the authors found that activating engram-associated dentate gyrus (DG) neurons at the trough of theta resulted in an increase in freezing relative to baseline when averaging across all stimulation epochs. In contrast, open-loop stimulation and peak-locked stimulation had weaker effects. Analysis of local field potentials showed that only the theta-locked stimulation facilitated coupling between theta and mid-gamma, indicating that this manipulation likely enhances the flow of activity from DG to CA1 via CA3 (as opposed to promoting transmission from entorhinal cortex to CA1). Previous results from mice, rats, and humans support the hypothesis that memory encoding and recall occur at distinct phases of theta. This work further strengthens the case for phase-specific segregation of memory-related functions and opens up a path toward more precise clinical interventions that take advantage of intrinsic theta rhythm.

Strengths:

This study recognizes that, when artificially reactivating a context-specific memory, the brain's internal context matters. In contrast to previous attempts at optogenetically inducing recall, this work adds an additional layer of precision by synchronizing the light stimulus to the ongoing theta rhythm. This approach is more challenging, because, in addition to viral expression and bilateral optical fibers, it also requires a recording electrode and real-time signal processing. The results indicate that this additional effort is worth it, as it results in a more effective intervention.

The findings on theta-gamma cross-frequency coupling suggest a possible mechanism underlying the observed behavioral effects: trough stimulation enhances DG to CA1 interactions via CA3. LFP recordings showed that stimulation increases the coupling between theta and mid-gamma (though not in all mice), and the percentage of freezing during reactivation is correlated with the gamma modulation index.

Weaknesses:

Given the precision of the intervention being performed, one might expect to see a stronger behavioral impact. Instead, the overall effect is subtle, and quite variable across mice. Looking at individual data points, the biggest overall increase in freezing actually occurred in 2 mice during the 6 Hz stimulation condition. Furthermore, trough stimulation decreased freezing in 3 mice This is not a weakness in itself; rather, the weakness lies in the lack of an attempt to make sense of this variability. There are a number of factors that could explain these differences, such as viral expression levels, electrode/fiber placement, and behavior during baseline. There is of course a risk of over-interpreting results from a few mice, but there is also a chance that the results will appear more consistent after accounting for these additional sources of variation.

While trough-locked optogenetic stimulation significantly increases freezing, the effects are much weaker than placing the mouse in the actual fear-conditioned context (average time freezing of 15% vs. 50%). The discussion would benefit from additional treatment of ways to further increase the specificity and effectiveness of artificial memory reactivation.

Using an open-source platform (RTXI) for real-time signal processing is commendable; however, more work could be done to make it easier to adopt these methods and make them compatible with other tools. The RTXI plugin used for closed-loop stimulation should be fully documented and publicly available, to allow others to replicate these results.

Reviewer #1 (Public Review):

In this article, Prassad and colleagues describe a new mechanism involved in the elimination of misspecified/mislocated cells in the wing imaginal disc. This study follows a previous study from the same group (Bilmeier et al. Curr Biol 2016) which showed that a large panel of genetic backgrounds changing locally cell fate can trigger aberrant sorting of the misspecified cells triggered by the increased of contractility at clone interfaces. This process was suggested to directly participate to clone elimination below a certain clone size. However, the mechanism involved in apoptosis induction was not really studied per se. Here, they use similar genetic backgrounds and showed that JNK activation occurs specifically at the interface of the misspecified clones on both side (inside and outside the clone) hence leading to a local increase of cell death both in the WT and misspecified cells. This local activation of cell death participates to clone elimination, although the authors also delineate an alternative mechanism of death induction in the center of the clone that may correlate with the local buckling and the deformation. Importantly, this mechanism seems quite specific of these misspecified backgrounds and is unrelated to other more classical cell competition scenarios which trigger the elimination of Minute mutant (affecting ribosomes) or based on differential levels of Myc.<br /> The model proposed is interesting and clearly delineate a distinctive feature of this quality control mechanism which triggers local JNK activation. It is based on solid genetic evidences and use a large panel of genetic backgrounds and careful quantifications. The demonstration is overall very convincing. Moreover, these results provide a novel perspective for the field of cell competition and quality control mechanism which has been dominated by the concept of absolute fitness, which is not at all required in this context (where both WT or altered cells can be eliminated provided they are in minority in the tissue).

Admittedly, the unicity and novelty is bit tuned down by former studies showing similar patterns of JNK activity upon local distortion of morphogens (so called morphogenetic apoptosis, Adachi-Yamada and O'Connor Dev Biol 2002), or the pattern of JNK activation observed near polarity mutant clones (Ohsawa et al, Dev Cell 2011) suggesting that this bilateral JNK activation might not be completely unique to these contexts. But non of these studies characterised such large range of genetic backgrounds and this study clearly provide new mechanistic insights.

It is important to note that at this stage, it is not clear whether there is any link between the sorting behaviour and the activation of JNK (they could be both activated by unknown upstream factors), while the terminology "interfacial contractility" used to define this type of clone elimination may convey the idea that this is the most upstream factor in the process. Also further quantifications may be required to see to which extend JNK activation is indeed restricted to cell directly contacting clone border and also to support the final proposed model suggesting that the number of contact could influence the levels of JNK (actually alternative models could also explain why smaller clones get eliminated). Finally, while the JNK levels clearly influence death in the clone, further experiments may be required to test how the line of JNK activation in WT cells contribute to their death and their elimination similar to mispecified cells, specially in the context where the majority of tissue is covered by mispecified clones.

Joint Public Review:

Hepatitis E virus (HEV) causes over 20 million infections per year. The open reading frame 1 (ORF1) is responsible for genome replication, however very little is known about the structure and functions of several of the components. The author use a diverse a diverse number of techniques (molecular virology, structure prediction using AlphaFold, site directed mutagenesis and biochemistry) to probe ORF1 activity. The work is thorough, well prepared, and discusses the strength and weakness of the structural information. Interestingly, AlphaFold prediction of the papain-like cysteine protease domain did not identify a classic papain-like fold. Lastly, the authors demonstrate the necessity of six conserved cysteines within the putative PCP domain.

The presence and necessity of proteolysis for genome replication or cleavage of other host factors still remains an uncharacterized problem, which is beyond the scope of this manuscript. My only concern relates to the presence of a zinc ion in ORF1.<br /> The authors use extensive triplet alanine scanning to test for virus replication capacity and in some cases see gains above WT (Figure 3). Do these patterns match natural variation observed in comparisons of HEV sequences un any way?

Overall, the study presents an intriguing hypothesis for HEV ORF1 function not involving protease processing as assumed by early bioinformatic analysis. The alternate hypothesis of metal ion coordination is supported by increasingly sophisticated structural modeling tools and related experiments. However, a lack of direct evidence leaves, as the authors note, alternate hypotheses such as disulfide bond coordination or protease functions that occur intramolecularly within ORF1.

The study will likely have an impact on the field, especially if evidence builds in the future directly supporting the mechanism proposed. HEV is an impactful pathogenic virus that is relatively underappreciated. In addition to a major revision in HEV biology, the idea that many proteins initially annotated with canonical functions might instead have different mechanisms is also of high interest beyond the field of virology.

Reviewer #1 (Public Review):

Of course, many of the most important aspects of feeding happen post-ingestion. As digested food moves through the intestines specialized epithelial cells (called Enterochromaffin Cells or EECs) sense and respond to the constituent chemicals. The function of EECs initiates physiological responses to facilitate nutrient absorption, protect from toxins and encourage proper waste removal. EECs are sparse and heterogenous and release a variety of transmitters and diffusible signaling molecules that signal to peripheral neurons and the brain. Their collective activity slows or speeds gut transit and promotes feelings of satiety or malaise. The current work by Liberles and colleagues seeks to provide deeper insight into the function of EECs. They build on previous work by further categorizing these cells by their unique gene expression signatures. The work utilizes single-cell transcriptomic analyses and intersectional approaches to define and genetically manipulate subsets of EECs. A key aspect of the study is behavioral assays used to investigate how direct stimulation of EEC subtypes influences key aspects of feeding, specifically gut transit, ingestion, and food preference.

The work has several strengths. A new mouse line (Villin-flp) is developed and used intersectionally with Cre mouse lines to manipulate different subsets of epithelial cells. The authors characterize these compound mouse strains and how the labeled cells map onto transcriptomic class. These data are reasonably comprehensive and show the exclusion of marker expression from the central nervous system, important controls. The chemogenetic activation strategy is an elegant way to probe the consequences of EEC stimulation by Gq coupled GPCR signalling. The gut transit experiments show clear effects.

The weakness is it remains unclear whether stimulation of the DREADD receptor outside the intestinal EECs really has consequences (e.g. in the tongue), the behaviors tested are somewhat limited, the responses to CNO administration variable between animals, and the effect sizes are small.

Overall, this is an interesting study and provides useful tools for the field.

Reviewer #1 (Public Review):

To explore possible functions of SA proteins in the absence of cohesin, authors use conditional AII-dependent proteins SA1 and SA2, after whose degradation they observe the phenotypes just indicated. 3D analysis shows that SA proteins cluster at specific regions. In addition, it is shown that SA proteins not only interact with CTCF after RAD21 degradation but with other F/YXF-motif containing proteins such as CHD6, MCM3 or HRNPUL2 as determined by ChIP. Mass spectrometry of proteins co-immunoprecipitated with SA1 reveals 136 interactor proteins that include a number of chromatin remodeling factors, transcription factors and RNA binding proteins including factors involved in RNA processing and modification, ribosome biogenesis and translation. After these results, authors perform CLIP to show that SA1 protein binds RNA in the absence of cohesin. Different analysis using RNH, mainly IF and IP and the S9.6 antibody, are used to conclude that SA1 binds to R-loop regions. The authors conclude that SA proteins are loaded to chromatin via NIPBL/mMAu complex at RNA:DNA hybrid regions. Further analyses suggest that SA proteins stabilize RNA via interaction with other RNA-binding proteins, some of which have been shown by other authors to be enriched at R loop-containing regions, a property that localizes to exon 32 in SA2. The manuscript provides a large amount of work that has been put together in a large collaboration to bring new roles for SA in RNA metabolism, even though this is not investigated.

Reviewer #1 (Public Review):

This manuscript by Koropouli et al. is a much-needed study that provides novel mechanistic insight of how signaling receptors can be targeted to distinct subcellular domains or membrane locations that, in part, confer their functional specificity. It is well-established that members of the class 3 secreted semaphorins guidance cues can bind to the receptors the neuropilins (Nrp1 and Nrp2) to elicit numerous cellular processes important for circuit assembly. Previously, it was demonstrated that Sema3F signaling with Nrp2 and its co-receptor Plexin-A3 is required for the removal of excess excitatory synaptic spines on the apical dendrite of layer V cortical neurons, while the closely related member Sema3A signaling with Nrp1/Plexin-A4 promotes the elaboration of the basal dendritic arbor on the same neuron. The question is then how do the two different signaling pathways convey such precise and opposite cellular function of eliminating spines and promoting dendritic elaboration in distinct subcellular compartments of the same neuron? While some hints were provided that the Nrp2 receptor is localized to the apical dendrite and Nrp1 is distributed widely along all dendrites on the same cortical neuron in vitro, this has not been shown in vivo and the mechanism of such targeted subcellular localization is not known. In the current study, the authors used biochemical, cellular, and molecular assays in combination with mouse genetics and live-cell imaging to demonstrate that the post-translational modification of S-palmitoylation dictates the proper subcellular localization and trafficking of Nrp2, but not Nrp1, and is required for Sema3F-dependent pruning of spines on the apical dendrites of layer V cortical neurons. The following are the strength and novel findings of this study.

1. This study confirms previous findings and adds new information by mapping the specific locations of the cysteine amino acid residues to the transmembrane/juxtamembrane region of neuropilin receptors for palmitoylation, which confers the subcellular localization specificity for Nrp2 but not Nrp1, in cortical neurons and non-neuronal cells.<br /> 2. The study also found that select cysteine residues on Nrp2 are palmitoylated by the palmitoyltransferase DHHC15, and palmitoylation of these sites are required for the homo-oligomerization of the Nrp2 receptor but not for the association with the co-receptor Plexin-A3.<br /> 3. The authors demonstrated that Sema3F signaling itself seems to enhance the level of Nrp2 palmitoylation in some sort of positive feedback loop. It would be interesting for future experiments to determine how Sema3F signaling promotes this palmitoylation.

Although most of the key claims are supported by data presented in the paper, clarification of the following concerns would further strengthen the overall conclusion of the study.

1. While some of the qualitative micrograph images are very convincingly in illustrating the drastic difference in Nrp2 versus Nrp1 expression patterns/cell-surface localization, such as Fig. 1A and 1D, many of the quantitative analyses have a low n number and/or low sample size, with only 2 replicate experiments or only 2 brains/animals per genotype analyzed. To increase the rigor of this study, the authors should add a few more replicates to the experiments with low n numbers.<br /> 2. The substitutions of C878, C885, and C887 to serines caused an ~80%, ~50%, and ~60% reduction, respectively, in Nrp2 palmitoylation compared to WT neuroblastoma-2a cells (as show in Fig. 2D and 2E). However, when mutating all three of these cysteine sites (the TCS plasmid), there is only ~80% total reduction in Nrp2 palmitoylation (Fig. 2F and 2G), just about equal to the C878S substitution alone. One would expect that the reduction in palmitoylation to be more severe with the TCS plasmid, but might this be due to the low n number in quantifications shown in Fig. 2E and 2G. It would add substantially to support the specificity of these cysteine residues' function if the single C878 was demonstrated to be required for either subcellular localization of Nrp2 leading to the rescue of the dendritic spine phenotype in Nrp2-/- primary neurons or in an in utero experiment.

Reviewer #1 (Public Review):

The manuscript by Curtis et al. reports the interaction between CaMKII and alpha-actinin-2. The authors found that the interaction was elevated after NMDA receptor activation in dendritic spines. In addition, this study reveals NMDA receptor binding to CaMKII facilitates alpha-actinin-2 access to the CaMKII regulatory segment, indicating that the NMDA receptor is involved in this interaction. The authors identified the EF1-4 motifs mediated this interaction, and overexpression of this motif inhibited structural LTP. Moreover, biochemical measurements of affinities from various combination of protein fragments including autoinhibited CaMKII 1-315, regulatory segments of CaMKII, and the EF-hand motif reveals that autoinhibited CaMKII has limited access to alpha-actinin-2. The authors also solved the structure of the interaction, supporting their finding in neurons at the molecular level. The authors claim that the interaction between CaMKII and alpha-actinin-2 is essential for structural LTP through cooperative action by the NMDA receptor and actin cytoskeleton.

Overall, the experiments are well-designed and the results are largely convincing and well-interpreted. But some aspects of the experiments need to be clarified.

1. Time resolution of the interaction analysis appears to be poor, as calcium elevation in a dendritic spine would be at milli-second order. What is the time window to interact alpha-actinin-2 with CaMKII during NMDA receptor activation or LTP?<br /> 2. The authors analyzed the binding of CaMKII and alpha-actinin-2 with partial fragments. It remains to be unknown whether CaMKII can form a protein complex with GluN2B and alpha-actinin-2 in a single CaMKII protomer.<br /> 3. Besides synaptic localization, the effect of the interaction on the enzymatic activity of CaMKII is not known.<br /> 4. Although the authors quantify the effect of the EF-hand disruptor by measuring numbers of the dendritic spine by its shape, the specificity of the EF-hand disruptor needs to be clarified.

Reviewer #1 (Public Review):

The study provides mechanistic insight into molecular events occurring at the onset of differentiation mediated by the kinase PASK. Specifically, the work focuses on the multiple steps that converge on post-translational modifications of PASK and its translocation to the nucleus during myogenesis. The authors present evidence that glutamine-fueled, CPB/EP300-mediated acetylation of PASK is required for its nuclear translocation. This allows (nuclear) PASK to interact with Wdr5 and consequently disrupt its association with the anaphase-promoting complex/cyclosome and inhibit Pax7 transcription, marking the onset of muscle differentiation. The conclusions are supported by an analysis of the effects of glutamine modulation on differentiation and maintenance of stemness in primary muscle stem cells; PASK localization in myoblasts and primary muscle stem cells as well as detailed biochemistry with modified forms of PASK to interrogate molecular interactions. C2C12 myoblast cells and primary muscle stem cells are cellular systems employed in the study with observations confirmed in cells derived from mice with genetic ablation of PASK. The study provides molecular detail on events linking glutamine metabolism to the transcriptional control of lineage differentiation, through the regulation of PASK. The analysis of these events in other systems would be of value to understanding their broader applicability.

Reviewer #1 (Public Review):

The authors of this study used SMART-seq to study differentiating B cells. Then they performed extensive in silico analyses to validate that a subset of the cells mimicked human antibody-secreting cells. For example, they compared gene expression profile of each cluster in B cell developmental trajectory (Figs 1, 2), investigated gene enrichment in ASC-like cluster (Fig 3), adopted independent dataset (Fig 3), and compared gene expression signatures of their cells to those of GC ASCs (Fig 4). Overall, the results from these analyses are convincing and valuable, but still do not seem to be a big leap from their Unger 2021 paper and therefore making this study preliminary.

The methodology that they established should be described more clearly so that it can be shared with the research community. For example, they say cells how many donors were recruited for this experiment? are there differences in efficiency in B cell differentiation by individual?

Also, it would be important to assay for antibodies in the culture media. How would you suggest to improve the culture system to be used to model diseases?

At the beginning the largest contributing factor for cell culstering was cell cycle. But B cell differentiation may also influence to cell cycle regulation. Rather than normalize its effect, can authors analyze effect of cell cycle in B cell differentiation? For example, identify sub-clusters shown in supple Fig 1g.

Reviewer #1 (Public Review):

Doostani et al. present work in which they use fMRI to explore the role of normalization in V1, LO, PFs, EBA, and PPA. The goal of the manuscript is to provide experimental evidence of divisive normalization of neural responses in the human brain. The manuscript is well written and clear in its intentions; however, it is not comprehensive and limited in its interpretation. The manuscript is limited to two simple figures that support its concussions. There is no report of behavior, so there is no way to know whether participants followed instructions. This is important as the study focuses on object-based attention and the analysis depends on the task manipulation. The manuscript does not show any clear progression towards the conclusions and this makes it difficult to assess its scientific quality and the claims that it makes.

Strengths:<br /> The intentions of the paper are clear and the design of the experiment itself is simple to follow. The paper presents some evidence for normalization in V1, LO, PFs, EBA, and PPA. The presented study has laid the foundation for a piece of work that could have importance for the field once it is fleshed out.

Weakness:<br /> The paper claims that it provides compelling evidence for normalization in the human brain. Very broadly, the presented data support this conclusion; for the most part, the normalization model is better than the weighted sum model and a weighted average model. However, the paper is limited in how it works its way up to this conclusion. There is no interpretation of how the data should look based on expectations, just how it does look, and how/why the normalization model is most similar to the data. The paper shows a bias in focusing on visualization of the 'best' data/areas that support the conclusions whereas the data that are not as clear are minimized, yet the conclusions seem to lump all the areas in together and any nuanced differences are not recognized. It is surprising that the manuscript does not present illustrative examples of BOLD series from voxel responses across conditions given that it is stated that that it is modeling responses to single voxels; these responses need to be provided for the readers to get some sense of data quality. There are also issues regarding the statistics; the statistics in the paper are not explicitly stated, and from what information is provided (multiple t-tests?), they seem to be incorrect. Last, but not least, there is no report of behavior, so it is not possible to assess the success of the attentional manipulation.

Reviewer #1 (Public Review):

The article by Mann et al. describes a knockin (KI) mouse model of mitofusin 2- related lipodystrophy, in mice carrying MFN2 R707W. The mice recapitulate some but not all aspects of the human phenotype, as summarized in Table 2. The phenotypic characterization is extensive and is generally well done. There was an adipose-specific alteration of mitochondrial morphology, accompanied by activation of the integrated stress response and reduced adipokine secretion. These findings are consistent with the human phenotype. The alteration in fat distribution that is present in humans with this mutation was not observed, and the mice did not have the insulin resistance seen in humans. The transcriptome analyses revealed a reduced epithelial-mesenchymal transition (EMT) in the KI mice, suggesting possible involvement of TGF-beta related pathways. There was also upregulation of the mTorc signaling pathway, suggesting that a possible therapeutic approach in humans may involve the mTORC1 inhibitor sirolimus. The reason for the largely adipose -specific effect of the mutation remains unexplained. As well, the hypothesis that changes in EMT pathways reflect altered activity of TGF-beta pathways must remain somewhat speculative at this point. Notwithstanding these weaknesses, the manuscript provides an important advance in understanding this lipodystrophy (and potentially other lipodystrophies), and the model that has been generated will enable further studies to further characterize the pathophysiology.

Reviewer #1 (Public Review):

In this study, Barthe et al. developed an approach to selectively activate beta-adrenergic receptors in the sarcolemma of ventricular myocytes. The approach involved the linking of a 5Kd PEG chain to the beat agonist isoprenaline. This prevents the agonist from entering transverse tubules. Using this approach, the authors find that activation of beta-adrenergic receptors in the surface sarcolemma of ventricular myocytes leads to lower cytosolic cAMP levels but longer-lasting effects on EC coupling than when TT receptors were activated.

Strengths of the study:<br /> 1) The PEG-ISO, size exclusion approach is very interesting and useful.<br /> 2) The observation that activation of beta-adrenergic receptors in the surface sarcolemma of ventricular myocytes leads to lower cytosolic cAMP levels, but longer-lasting effects on EC coupling than when TT receptors were activated is interesting.<br /> 3) The observation that beta-adrenergic receptors in the TT lead to stronger nuclear activation of nuclear cAMP/PKA signaling is interesting.

Weaknesses of the study:<br /> 1) There seems to be a paucity of mechanistic insights into the study.<br /> 2) It is unclear what would be the ideal control for these experiments. Would the addition of the PEG chain, by itself, alter the binding of and activation of beta-adrenergic receptors regardless of their location?<br /> 3) The novelty of the findings is unclear, as other studies have suggested differential effects of beta-adrenergic receptors in membrane compartments.

Impact on the field:<br /> 1) PEG-ISO may become a useful strategy to selectively activate surface sarcolemmal beta-adrenergic receptors.

Reviewer #1 (Public Review):

In this manuscript, Braet et al provide a rigorous analysis of SARS-CoV-2 spike protein dynamics using hydrogen/deuterium exchange mass spectrometry. Their findings reveal an interesting increase in the dynamics of the N-terminal domain that progressed with the emergence of new variants. In addition, the authors also observe an increase in the stabilization of the spike trimeric core, which they identify originates from the early D614G mutation.

Overall this is a timely and interesting exploration of spike protein dynamics, which have so far remained largely unexplored in the literature.<br /> What I find a bit missing in this manuscript is a link between how the identified changes in protein dynamics lead to increased viral fitness. While there are some possibilities listed in the discussion, I think these should be elaborated upon further. In addition, it should also be discussed how understanding the changes in the spike protein dynamics could have implications for the development of small molecule inhibitors for the virus.

Reviewer #1 (Public Review):

This is an exceptional paper that investigates a 208.6 kb region of the Burkholderia thailandensis chromosome that had previously been thought to excise itself and form extrachromosomal circles. Through a series of elegant experiments , the authors conclusively show that (i) the 208.6 kb region in fact forms tandem duplications, (ii) the region can switch between duplicated and non-duplicated forms via RecA-mediated homologous recombination, and (iii) duplication provides a selective advantage in biofilms. The data are of uniformly high quality and the conclusions are fully supported by the data. The significance of the work is high because it identifies a novel form of phase variation in bacteria that represents a bet-hedging strategy to facilitate growth in diverse environments.

Reviewer #1 (Public Review):

This work aims to understand whether MSCs support the resistance in tumor cells upon CAR T cell treatment and whether the expression of STC1 in MSCs contributes to those changes. Overall, the in vivo data is interesting. However, the mechanistic understandings are correlated and based on many assumptions. Furthermore, the differences in Treg changes presented in Figure 2 are not convincing. It is also not clear the underlying mechanisms by which the presence of MSCs leads to these changes.

Major points:

1. How STC1 controls changes in MSCs' ability for hampering CAR T cell-mediated anti-tumor responses is unclear.

2. Is ROS important? It is not tested directly.

3. The changes in CD8 and Treg are not convincing. Moreover, it is not tested how these changes can be elicited by the presence of MSCs.

Reviewer #1 (Public Review):

This theoretical (computational modelling) study explores a mechanism that may underlie beta (13-30Hz) oscillations in the primate motor cortex. The authors conjecture that traveling beta oscillation bursts emerge following dephasing of intracortical dynamics by extracortical inputs. This is a well written and illustrated manuscript that addressed issues that are both of fundamental and translational importance. Unfortunately, existing work in the field is not well considered and related to the present work. The rationale of the model network follows closely the description in Sherman et al (2016). The relation (difference/advance) to this published and available model needs to be explicitly made clear. Does the Sherman model lack emerging physiological features that the new proposed model exhibits? The authors may also note the stability analysis in: Yaqian Chenet et al., "Emergence of Beta Oscillations of a Resonance Model for Parkinson's Disease", Neural Plasticity, vol. 2020, https://doi.org/10.1155/2020/8824760

The model-based analysis of the traveling nature of the beta frequency bursts appears to be the most original component of the manuscript. Unfortunately, this is also the least worked out component. The phase velocity analysis is limited by the small number (10 x 10) of modeled (and experimentally recorded) sites and this needs to be acknowledged. How much of the phase velocities are due to unsynchronized random fluctuations? At least an analysis of shuffled LFPs needs to be performed. How were border effects treated in the model and which are they? Is there a relationship between the localizations of the non-global external input and the starting sites of the traveling waves?

In summary, this work could benefit from a widening of its scope to eventually inspire new experimental research questions. While the model is constructed well, there is insufficient evidence to conclude that the presented model advances over another published model (e.g. Sherman et al., 2016).

Reviewer #1 (Public Review):

Luckey et al. used a sophisticated, multimodal approach to test the hypothesis that engaging LC-hippocampal pathways promote behavioral tagging processes in humans. To activate this mechanism in a causal manner, they apply transcutaneous electrical stimulation of the greater occipital nerve (NITESGON), a relatively novel and non-invasive technique for stimulating brainstem pathways linked to arousal-related neuromodulation. To test the behavioral tagging hypothesis, they use a variety of indirect methods, including pharmacology, EEG, fMRI, saliva assays, and eye-tracking to measure LC-related activity, hippocampal activity/connectivity, and potential dopamine states/release. At the behavioral level, they demonstrate that NITESGON stimulation during or after learning benefits long-term but not immediate associative memory. These long-term memory improvements were related to increased gamma power in the MTL. In another set of experiments, they show that NITESGON during associative learning promotes associative learning on a subsequent unrelated (object-location) or highly overlapping (paired word associates) task. Consistent with prior VNS and other NITESGON studies, they show robust evidence that this intervention leads to significant increases in salivary alpha-amylase, a putative marker of central noradrenergic activity. This increase in sAA was also correlated with long-term associative memory across several experiments using paired word associates. Using fMRI, they demonstrate resting-state increases in local hippocampal, LC, and VTA low-frequency fluctuations as well as increased rs-FC between the LC and hippocampus during and after stimulation. Finally, they show that NISTESGON does not enhance long-term associative memory in individuals taking a dopamine antagonist medication, implicating a potential dopamine mechanism in these stimulation-induced memory effects.

This paper is impressive in scope and takes advantage of both causal and indirect methods to cross-validate their results. Behavioral tagging is a relatively nascent area of research in humans, and this paper provides compelling evidence for the role of noradrenergic activity (whether related to behavioral tagging or more general arousal-related consolidation processes) in facilitating memory encoding and consolidation. Beyond basic science research, these findings also have important clinical implications. In recent years, there has been intense interest in studying the LC's role in promoting healthy cognitive function and its involvement in AD-related neuropathology. The LC is one of the earliest sites of tau pathology and thereby represents an important target for clinical intervention in early AD. The current study advances our understanding of a non-invasive technique that may be used to bolster learning in both healthy populations and potentially in older individuals with AD.

The key claims of the manuscript are generally well supported by the data. However, while the large number of studies is a significant virtue of this paper, it is also - at times - a potential weakness. There are many measures and pieces to this puzzle to assemble. While the multimodal approach is admirable and rigorous, the fit between some of these pieces is sometimes overstated. The correlational nature of the data helps cross-validate some of the predictions about the LC mechanisms involved in behavioral tagging. But the most compelling test of this hypothesis would be to link the LC/hipp/VTA fMRI data - arguably the most direct outcome measure in this study - to long-term memory performance and the other neurophysiological measures (e.g., sAA, blink rate, etc.). Many of the results are compelling but they are often observed in parallel studies. Thus, interpreting them as engaging a common mechanism is tenuous. This important shortcoming notwithstanding, there is still a strong replication in other findings (e.g., sAA-memory correlations) across experiments that lend support to some of the hypotheses.

A related issue is that the reliability of these indirect measures of noradrenergic signaling and dopaminergic receptors, including salivary alpha-amylase and spontaneous eyeblink rate, is oversold. While this stimulation technique elicits parallel increases in many of the neurophysiological and behavioral measures, these patterns might not reflect the engagement of a shared underlying mechanism. It's an especially big stretch to interpret the eyeblink effects as relating to LC-DA, which cannot be verified using the current methods. In addition, the spatial resolution of the neuroimaging data is poorly suited for testing predictions about such a small brain structure. This represents a potential weakness of the paper, as the large smoothing kernel in the fMRI data may capture the contributions of other brainstem nuclei and regions activated by NITESGON. It is also worth noting that many of the individual differences findings are confounded by group clustering effects. That is, the between-group effects belie whether the same linear relationships exist in the sham and stimulation groups individually. This necessitates additional correlation analyses within groups to verify that stimulation doesn't decorrelate the relationship between physiological measures and performance.

While the behavioral tagging predictions are intriguing and supported by some findings in the literature, they may not be entirely appropriate for this study. In short, I'm not fully convinced these data satisfy all assumptions of BT (see Dunsmoor et al., 2022 for an overview). Behavioral tagging is thought to be a process that stabilizes weak learning. While it's very difficult to operationalize the "strength" of a memory representation, I'm not sure if the current paired-associates paradigm yields weak learning. Participants have multiple opportunities to learn the memoranda, which casts some doubt as to whether these are weak memory representations. This possibility is supported by the generally high memory performance (~80% on average) during the immediate test and even accurate recall after 7 days.

Behavioral tagging also does not make any explicit predictions about interference effects. Much of this theory centers upon the idea that arousing learning events lead to memory enhancements/benefits; but it does not speak directly as to whether these events confer protection from memory interference (and there was no baseline condition in Dunsmoor et al., 2015 to test any predictions regarding reduced retroactive interference for CS+ stimuli, for example). I find the protective effects of stimulation in Experiment 4 very interesting, and they speak to the importance of this technique as a memory intervention. However, I think this is an example of the authors relying too heavily on a behavioral tagging framework when these could simply reflect arousal-related (Nielson et al., 1996; 2014) and/or noradrenergic-related (e.g., McGaugh, 2013) consolidation benefits more broadly. In summary, I think it would strengthen the paper to walk back claims related to behavioral tagging specifically and address the possibility of alternative (but related) mechanisms.

To summarize, the results of this study are very interesting and the project is very ambitious. There is much therapeutic potential for NITESGON to improve memory and this study represents an important advance towards achieving that goal. The work would primarily be improved by not relying on too many assumptions or inferences, and being more agnostic with respect to certain mechanisms (e.g., whether this is behavioral tagging or general consolidation mechanisms).

Reviewer #1 (Public Review):

Ras is the first discovered oncogene and KRAS is the most frequently mutated isoform. Recent studies led to the development of mutation specific inhibitors, especially against the KRASG12C mutant. However, unfortunately the patients treated with Adagrasib or others develop resistance due to further gain of function mutations and amplification of KRASG12C allele apart from mutations in the downstream signaling components. One of the oldest approaches to target Rho GTPases like RAS is to compete with the nucleotide binding of RAS and it has for a long time remained difficult owing to the picomolar affinity for GTD/GDP. Gray and colleagues in 2014 tried to overcome these issues by employing GDP derivatives that can undergo covalent reaction with disease specific mutations but Muller etal reported in their previous work (Sci.reports 2017) that the issue with these derivatives was with the loss of reversible affinities for beta modified derivatives for RAS of atleast 10000 fold compared to GDP and GTP. Here the authors present novel GDP derivatives different from Gray and colleagues and demonstrate that they could lock KRASG13C covalently, another important mutant of KRAS in an inactive form with a multiple set of biochemical, structural and cellular assays.

However, the issue is a lack of evidence to demonstrate "target engagement" in cells and these derivatives need to be developed further as they cannot pass through cell membranes. The complete covalent modification of the compound is achieved at very high pH. Also its not clear if addition of edaGDP would disrupt KRASG13C and effector interaction directly.

Finally, a culture that rewards big personal accomplishments over smaller social ones threatens to create a cohort of narcissists

Stadium Mentioned

Mention of a wall and council chamber

Another Description of a piller

Town Hall and Metroum Descriptions

Further Description of the Temple of Hera

Temple of Hera Described.

Alter of Artemis mentioned next to Leonidaeum

Leonidaeum is described.

Alters near the stadium.

Temple of pelopium

Description of the Temple of Zeus

Description of the river near Olympia

The starting point for the description of Olympia and from view we have at the start.

Reviewer #1 (Public Review):

In this work, Aggad et al. focused on the multi-folded membrane structure (termed meisosomes) located between the apical extracellular matrix and the epidermal cells of the C. elegans. The authors performed detailed analysis on the morphology and 3D distribution of the meisosomes at different developmental stages of the C. elegans skin. They also investigated factors affecting the biogenesis and reorganization of the meisosomes, as well as the involvement of meisosomes in cuticle synthesis and maintenance. The meisosomes are particularly intriguing membrane structures connecting the epidermis to the extracellular matrix, which potentially have vital functions but were given very little attention before this study. Therefore, the work presented by Aggad et al. is rich in novelty and may greatly benefit the related fields if the main conclusions stand. However, the authors' claims are not very well-supported by the data due to improper use of reporters and mutants, as well as some flaws in experimental design.

1. One major problem with this manuscript is the investigation about meisosome functions. Instead of generating knockdown animals or mutants that directly and specifically disrupt meisosome structures, the authors used several cuticular collagen mutants, which harbor multiple complex cuticular and epidermal defects. Therefore, the main conclusions drawn from the analysis using collagen mutants, such as "meisosomes may play an important role in attaching the cuticle to the underlying epidermal cell" or "furrow collagens are required for stiffness potentially as they are essential for the presence of normal meisosomes" do not stand well. In fact, it is not surprising that the collagen mutants display a detached cuticle, because the extracellular domains of MUP-4 and MUA-3 (the transmembrane receptors of apical hemidesmosomes that are primarily responsible for tethering the epidermis to the cuticle) both contain vWFA collagen-binding domain (Hong et al., JCB 2001; Bersher et al., JCB 2001). Hence loss of certain collagens in the cuticle directly affects cuticle-epidermis attachment due to defective ligand-receptor interactions is a much more plausible explanation. Likewise, it is more resonable to propose that lack of certain collagens in the cuticle directly affects cuticle stiffness, rather than working indirectly through epidermal meisosomes. In a word, this study did not answer the long-standing question since the 1980s: what are the primary functions of the apical membrane stacks (AKA meisosomes) in the C. elegans epidermis?

2. Another problem with this manuscript is the representation of meisosome structures by VHA-5::GFP reporter alone from Figure 3 to Figure 7. The authors claim that VHA-5::GFP is a meisosome-specific marker, but only provided indirect and superficial evidence to support this claim: 1) VHA-5::GFP signal is distributed in the same general epidermal area as the majority of meisosomes (so are many other membrane organelles in the C. elegans epidermis);2. VHA-5::GFP does not co-localize with fluorescent markers for MVB, recycling endosomes and autophagolysosomes. By claiming this, the authors made a huge assumption that the overexpressed VHA-5::GFP fusion protein can only possibly associate with four types of organelles (meisosomes, MVB, recycling endosomes and autophagolysosomes) but not any other known or to-be-identified subcellular structures. In addition, a previous study did report that VHA-5 is localized in several other places besides the apical membrane stacks (Liegeois et al., JCB 2006). In a word, there is no solid, direct evidence showing that VHA-5::GFP can specifically represent meisosomes and faithfully visualize meisosome morphology in the C. elegans epidermis. There are also no alternative approaches for meisosome morphological analysis to back up the results obtained from VHA-5::GFP reporter. Therefore, most of the data from Figure 3-7 can only be interpreted as the influence of various factors on the distribution patterns of VHA-5::GFP, not just meisosomes.

Reviewer #1 (Public Review):

In this manuscript, Wang et al provide a pathway required for the production and degradation of exophers - large neuronal extrusions proposed to discard toxic cargo. Exophers were fairly recently described by this group and have now been observed in mammalian neurons, suggesting a broad importance in neuronal health. How exophers were disposed of by surrounding tissues was not known. Here, the authors identify a pathway required for exopher degradation into small debris (starry night), and intriguingly, genes proposed to be required in the degrading cells (hypodermis) for exopher production in neurons.

Strengths of the manuscript include significant new insights into a problem that had not been investigated in mechanistic detail, and the combined use of genetics and cell biology to sort genes into pathways involved in exopher production and degradation. Several differences are found between exopher and cell corpse disposal, highlighting the importance of the study. The findings should be of interest to a broad audience.

Reviewer #1 (Public Review):

This study investigated the roles of sams-1 and sams-4, two enzymes that generate the major methyl donor SAM, in heat stress response and the associated molecular changes. The authors provided evidence that loss of sams-1 resulted in enhanced resistance to heat stress, whereas loss of sams-4 resulted in heightened sensitivity to heat stress. The authors further showed that whereas the basal level of the histone modification H3K4me3 in intestinal nuclei was substantially reduced in sams-1 loss-of-function mutants, H3K4me3 level greatly increased upon heat stress, and this increase depended on sams-4. Additional RNA-seq results revealed largely distinct heat stress-induced RNA expression changes in the sams-1 mutant and sams-4 knockdown worms. The authors further profiled genomic locations of H3K4me3 in sams-1 mutant and sams-4 knockdown worms. Unfortunately, the lack of sufficient technical detail made it difficult to evaluate the H3K4me3 profiling data.

The paper provided several conceptual advances:<br /> - Uncovering interesting and opposing heat stress phenotype associated with the loss of two related SAM synthases. Thus, even though both SAMS-1 and SAMS-4 produce SAM, the source of SAM production appears to have distinct consequences on the organismal heat stress response.<br /> - Demonstration that SAMS-4 appeared able to compensate for the loss of SAMS-1 upon heat shock, resulting in restoration of the histone mark H3K4me3 in intestinal cells.<br /> - Revealing largely different gene expression changes upon heat shock in animals lacking sams-1 or sams-4. Thus, the gene expression profiles corroborated the differential heat stress response.

This paper describes one of the first adaptations of CUT&TAG in C. elegans, which can be of high impact on the field. Unfortunately, the lack of experimental detail made it difficult to evaluate the quality of the CUT&TAG data and the consequent interpretations.

Overall, the paper reported a number of interesting findings that will be of substantial interest to the field. However, the paper in its current form has substantial shortcomings, particularly related to the difficulty in evaluating the validity of H3K4me3 profiling data. The paper would also benefit from further discussion that attempts to reconcile some of the inconsistent results.

Reviewer #1 (Public Review):

Castelán-Sánchez et al. analyzed SARS-CoV-2 genomes from Mexico collected between February 2020 and November 2021. This period spans three major spikes in daily COVID-19 cases in Mexico and the rise of three distinct variants of concern (VOCs; B.1.1.7, P.1., and B.1.617.2). The authors perform careful phylogenetic analyses of these three VOCs, as well as two other lineages that rose to substantial frequency in Mexico, focusing on identifying periods of cryptic transmission (before the lineage was first detected) and introductions to and from the neighboring United States. The figures are well presented and described, and the results add to our understanding of SARS-CoV-2 in Mexico. However, I have some concerns and questions about sampling that could affect the results and conclusions:

1) The authors do not provide any details on the distribution of samples across the various Mexican States, making it hard to evaluate several key conclusions. Although this information is provided in Supplementary Data 2, it is not presented in a way that enables the reader to evaluate if lineages were truly predominant in certain regions of the country, or if these results are attributable purely to sampling bias. Specifically, each lineage is said to be dominant in a particular state or region, but it was not clear to me if sampling across states was even at all time points. For example, the authors state that most B.1.1.7 genome sampling is from the state of Chihuahua, but it is not clear if this was due to more sequenced samples from that region during the time that B.1.1.7 was circulating, or if the effects of B.1.1.7 were truly differential across the country. The authors do mention sequencing biases several times but need to be more specific about the nature of this bias and how it could affect their conclusions.

2) It is surprising to see in this manuscript that the B.1.1.7 lineage did not rise above 25% prevalence in the data presented, despite its rapid rise in prevalence in many other parts of the world. This calls into question if the presented frequencies of each lineage are truly representative of what was circulating in Mexico at the time, especially since the coordinated sampling and surveillance program across Mexico did not start until May 2021.

Reviewer #1 (Public Review):

Animal colour evolution is hard to study because colour variation is extremely complex. Colours can vary from dark to light, in their level of saturation, in their hue, and on top of that different parts of the body can have different colours as well, as can males and females. The consequence of this is that the colour phenotype of a species is highly dimensional, making statistical analyses challenging.

Herein the authors explore how colour complexity and island versus mainland dwelling affect the rates of colour evolution in a colourful clade of birds: the kingfishers. Island-dwelling has been shown before to lead to less complex colour patterns and darker coloration in birds across the world, and the authors hypothesise that lower plumage complexity should lead to lower evolutionary rates. In this paper, the authors explore a variety of different and novel statistical approaches in detail to establish the mechanism behind these associations.

There are three main findings: (1) rates of colour evolution are higher for species that have more complex colour phenotypes (e.g. multiple different colour patches), (2) rates of colour evolution are higher on island kingfishers, but (3) this is not because island kingfishers have a higher level of plumage complexity than their mainland counterparts.

I think that the application of these multivariate methods to the study of colour evolution and the results could pave the way for new studies on colour evolution.

I do, however, have a set of suggestions that should hopefully improve the robustness of results and clarity of the paper as detailed below:

1) The two main hypotheses tested linking plumage complexity and island-dwelling to rates of colour evolution seem rather disjointed in the introduction. This section should integrate these two aspects better justifying why you are testing them in the same paper. In my opinion, the main topic of the paper is colour evolution, not island-mainland comparisons. I would suggest starting with colours and the challenges associated with the study of colour evolution and then introducing other relevant aspects.

2) Title: the title refers to both complex plumage and island-dwelling, but the potential effects of complexity should apply regardless of being an island or mainland-dwelling species, am I right? Consider dropping the reference to islands in the title.

3) The results encompass a large variety of statistical results some closely related to the main hypothesis (eg island/mainland differences) tested and others that seem more tangential (differences between body parts, sexes). Moreover, quite a few different approaches are used. I think that it would be good to be a bit more selective and concentrate the paper on the main hypotheses, in particular, because many results are not mentioned or discussed again outside the Results section.

4) Related to the previous section, the variety of analytical approaches used is a bit bewildering and for the reader, it is unclear why different options were used in different sections. Again, streamlining would be highly desirable, and given the novel nature of the analytical approach (as far as I know, many analytical approaches are applied for the first time to study colour evolution) it would be good to properly explain them to the reader, highlighting their strengths and weaknesses.

5) The Results section contains quite a bit of discussion (and methods) despite there being a separate Discussion section. I suggest either separating them better or joining them completely.

6) The main analyses of colour evolutionary rates only include chromatic aspects of colour variation. Why was achromatic variation (i.e. light to dark variation) not included in the analyses? I think that such variation is an important part of the perceived colour (e.g. depending on their lightness the same spectral shape could be perceived as yellow or green, black or grey or white). I realize that this omission is not uncommon and I have done so myself in the past, but I think that in this case, it is highly relevant to include it in the analyses (also because previous work suggests that island birds are darker than their mainland counterparts). This should be possible, as achromatic variation may be estimated using double cone quantum catches (Siddiqi et al., 2004) and the appropriate noise-to-signal ratios (Olsson et al., 2018). Adding one extra dimension per plumage patch should not pose substantial computational difficulties, I think.

7) The methods need to be much better explained. Currently, some methods are explained in the main text and some in the methods section. All methods should be explained in detail in the methods section and I suggest that it would be better to use a more traditional manuscript structure with Methods before Results (IMRaD), to avoid repetition (provided this is allowed by the journal). Whenever relevant the authors need to explain the choice of alternative approaches. Many functions used have different arguments that affect the outcome of the analyses, these need to be properly explained and justified. In general, most readers will not check the R script, and the methods should be understandable to readers that are not familiar with R. This is particularly important because I think that the methodological approach used will be one of the main attractions of the manuscript, and other researchers should be able to implement it on their own data with ease. Judging from the R script, there are quite a few analyses that were not reported in the manuscript (e.g. multivariate evolutionary rates being higher in forest species). This should be fixed/clarified.

Reviewer #1 (Public Review):

In this manuscript, Huang et al., assess cognitive flexibility in rats trained on an animal model of anorexia nervosa known as activity-based anorexia (ABA). For the first time, they do this in a way that is fully automated and free from experimenter interference, as apparently experimenter interference can affect both the development of ABA as well as the effect on behaviour. They show that animals that are more cognitively flexible (i.e. animals that had received reversal training) were better able to resist weight loss upon exposure to ABA, whereas animals exposed to ABA first show poorer cognitive flexibility (reversal performance).

Strengths:<br /> - The development of a fully-automated, experimenter-free behavioural assessment paradigm that is capable of identifying individual rats and therefore tracking their performance.<br /> - The bidirectional nature of the study - i.e. the fact that animals were tested for cognitive flexibility both before and after exposure to ABA, so that direction of causality could be established.<br /> - The analyses are rigorous and the sample sizes sufficient.<br /> - The use of touchscreens increases the translational potential of the findings.

Weaknesses<br /> - Some descriptions of methods and results are confusing or insufficiently detailed.<br /> - It seems to me that performance on the pairwise discrimination task cannot be directly (statistically) compared to performance on reversal (as in Figure 4E), as these are tapping into fundamentally different cognitive processes (discrimination versus reversal learning). I think comparing groups on each assessment is valid, however.<br /> - Not necessarily a 'weakness' but I would have loved to see some assessment of the alterations in neural mechanisms underlying these effects, and/or some different behavioural assessments in addition to those used here. In particular, the authors mention in the discussion that this manipulation can affect cholinergic functioning in the dorsal striatum We (Bradfield et al., Neuron, 2013) and a number of others have now demonstrated that cholinergic dysfunction in the dorsomedial striatum impairs a different kind of reversal learning that based on alterations in outcome identity and thus relies on a different cognitive process (i.e. 'state' rather than 'reward' prediction error). It would be interesting perhaps in the future to see if the ABA manipulation also alters performance on this alternative 'cognitive flexibility' task.

Nevertheless, I certainly think the manuscript provides a solid appraisal of cognitive flexibility using more traditional tasks, and that the authors have achieved their aims. I think the work here will be of importance, certainly to other researchers using the ABA model, but perhaps also of translational importance in the future, as the causal relationship between ABA and cognitive inflexibility is near impossible to establish using human studies, but here evidence points strongly towards this being the case.

Reviewer #1 (Public Review):

This article describes simultaneous surface recordings with a transparent electrode array and two-photon calcium imaging in the mouse cortex. The study shows that spiking activity recorded by surface electrodes or imaged layer 2/3 activity is decoupled. Moreover, simulations indicate that this decoupling may be due to a dominance of L1 projecting axons (input to the cortex) in surface spiking activity.

This is a rigorous study capitalizing on the new Windansee surface recording device, which provides extremely useful evidence that surface electrodes may not be able to capture information processed in the cortical layers. Recordings and simulations seem adequately performed. The indication that axons contribute significantly to multiunit activity is extremely important for the interpretation of multiunit activity in surface recordings. Here the claim is limited to surface recording, and one wonders to which extent this conclusion would transpose to recordings made with penetration electrodes.

Reviewer #1 (Public Review):

This is an interesting manuscript that highlights the potential for 'clogging' of import channels by mutant proteins to promote mitochondrial dysfunction in disease. One of the challenges with this study is deconvoluting potential loss-of-function phenotypes associated with reductions in ANT1/AAC2 from gain-of-toxicity phenotypes linked to import clogging. This was addressed primarily in yeast, showing that phenotypes associated with overexpression of mutants (e.g., reduced growth on glucose media). The experiment showing that yeast AAC2 clogs import was also convincing including both in vitro and in vivo characterization, although it isn't clear why the proteomic experiments were performed with acute expression of A128P instead of the 'superclogger' double mutant. The extension of this work to mammalian cells and then mice is also admirable. However, the quality of characterization does begin to decline when moving into mammalian models. For example, there is no clear evidence that observed phenotypes can be attributed to gain of toxicity instead of loss of function in mammalian cells and mice. There are similarities to yeast, but this needs to be better defined in my opinion. Lastly, I have questions related to the mouse model, such as how do these phenotypes compare to KO animals and why were homozygous mice used in some situations and heterozygous mice used in others.

Overall, this manuscript is interesting, as it describes a mechanism whereby mutant proteins can lead to import deficiencies in the context of disease. The strengths primarily reside with the yeast work, where the demonstration of import clogging and the functional implications of this clogging are best defined. The transition to mammalian cells and mice is admirable as well, but doesn't reach the same level of characterization, leaving open the possibility that the observed effects could be attributed (at least in part) to loss of function of ANT1.

Meaning of Float in Python proramming language

I typically like to use PascalCase to indicate variables in my code. It is common in large development environments to have a coding standard document that defines how each programmer on the team will use various conventions

Reviewer #1 (Public Review):

This manuscript presents a comparison between models that may explain psychophysical performance in sensory integration tasks, where a subject essentially has to count stimulus samples and make a motor report about the final count.

The work has many technical strengths:

- The problem of model mimicry is clearly articulated.

- The work shows that the use of discrete sample stimulus (DSS) is key for being able to disambiguate multiple candidate mechanisms that could possibly underlie the observed behavioral data.

- The authors use rigorous model comparison and analysis techniques, some (like the integration maps) newly developed for the current application.

- The model comparison involves both qualitative and qualitative contrasts between alternative models.

- Consistent results are obtained with several data sets involving humans, monkeys, and rats.

- The results provide insight into why the simpler alternative models (the snapshot and extrema detection models) fail.

No glaring weaknesses were found in this manuscript. However, there are some limitations that are worth noting, to put things into context:

- The results are consistent with what has become a well-known principle of operation of sensory-motor circuits, namely, that they are highly effective at integrating sensory evidence over time. Thus, the results are not particularly surprising.

- The results are valuable in that they specifically refute two mechanisms that had been recently proposed as potential alternatives to the more standard temporal integration. To some, these alternative mechanisms may have seemed somewhat far-fetched to begin with, as they would lead to suboptimal performance in general. Nevertheless, settling the question was important.

- Temporal integration and accumulation of evidence have been the focus of many computational studies in systems neuroscience. Although these are certainly important functions, sensory-guided choices require the deployment and coordination of numerous sensory, motor, and cognitive mechanisms, of which integration is just one.

Overall, this is a valuable study that has important theoretical implications in the field of computational neuroscience. It presents a compelling case that temporal integration is a common capability of sensory-motor circuits and that it explains a variety of behavioral data sets much better than two simpler, alternative mechanisms.

Reviewer #1 (Public Review):

Jordan and Keller investigated the possibility that sensorimotor prediction error (mismatch between expected and actual inputs) triggers locus coeruleus (LC) activation, which in turn drives plasticity of cortical neurons that detect the mismatch (e.g. layer 2/3 neurons in V1), thus updating the internal presentation (expected) to match more the sensory input. Using genetic tools to selectively label LC neurons in mice and in vivo imaging of LC axonal calcium responses in the V1 and motor cortex in awake mice in virtual reality training, they showed that LC axons responded selectively to a mismatch between the visual input and locomotion. The greater the mismatch (the faster the locomotion in relation to the visual input), the larger the LC response. This seemed to be a global response as LC responses were indistinguishable between sensory and motor cortical areas. They further showed that LC drove learning (updating the internal model) despite that LC optical stimulation failed to alter acute cellular responses. Responses in the visual cortex increased with locomotion, and this was suppressed following LC phasic stimulation during visuomotor coupled training (closed loop). In the last section, they showed that artificial optogenetic stimulation of LC permitted plasticity over minutes, which would normally take days in non-stimulated mice trained in the visuomotor coupling mode. These data enhance our understanding of LC functionality in vivo and support the framework that LC acts as a prediction error detector and supervises cortical plasticity to update internal representations.

The experiments are well-designed and carefully conducted. The conclusions of this work are in general well supported by the data. There are a couple of points that need to be addressed or tested.

1) It is unclear how LC phasic stimulation used in this study gates cortical plasticity without altering cellular responses (at least at the calcium imaging level). As the authors mentioned that Polack et al 2013 showed a significant effect of NE blockers in membrane potential and firing rate in V1 layer2/3 neurons during locomotion, it would be useful to test the effect of LC silencing (coupled to mismatch training) on both cellular response and cortical plasticity or applying NE antagonists in V1 in addition to LC optical stimulation. The latter experiment will also address which neuromodulator mediates plasticity, given that LC could co-release other modulators such as dopamine (Takeuchi et al. 2016 and Kempadoo et al. 2016). LC silencing experiment would establish a causal effect more convincingly than the activation experiment.

2) The cortical responses to NE often exhibit an inverted U-curve, with higher or lower doses of NE showing more inhibitory effects. It is unclear how responses induced by optical LC stimulation compare or interact with the physiological activation of the LC during the mismatch. Since the authors only used one frequency stimulation pattern, some discussion or additional tests with a frequency range would be helpful.

Reviewer #1 (Public Review):

This is a quite nice work equipped with healthy scientific substance underpinned by a solid mathematical approach.

The authors based on a PGG with the threshold; M (that ranges; 1 < M < N, where N indicates the game size), whether cooperation bringing fruit or not, in which, according to the commonly used parameterization, b and c mean the cooperation fruit and the cost for cooperation. As a kernel in their model, they presumed that an individual will lose his endowment (cooperation fruit in this context) with a probability r, which represents the risk level of collective failure (Eqs. (1 & 2)). Let alone, they presumed a well-mixed and infinite mother-population to ensure their analytical formulation and analysis, and to apply the replicator dynamics. Subsequently, they presumed the co-evolution of cooperation fraction; x, and risk level; r, by introducing another dynamical system for r, of which the general form is defined by Eq. (3).

For a down-to-earth discussion, they presumed two types of concrete forms for non-linear function; U(x,r). Both types premise the so-called logistic type form; containing r*(1 - r). One is what-they-called Linear; Eq. (5). Another is Eq. (7), called Exponential. Up to here, all the modeling approach is well depicted and quite understandable.

By exploring some numerical results backed by their theoretical ground, the authors got phase diagram (Figs. 3 and 5); whether a co-evolutionary destiny evaluated by (x,r) being absorbed by the dominance of unwilling (less cooperative) situation (say, D-dominant); (0,1), or by bi-stable equilibrium (either better state or D-dominant depending on an initial condition) along u (parameter appeared in the dynamical equation for r) and c/b (roughly speaking; it implies dilemma strength).

The result seems interesting and conceivable. As a rough sketch, the two types of U(x,r) seem less different. But the higher absorbing point of (x,r) out of the two cases of bi-stable equilibria is mutually different (yellow region). The authors deliberately illustrated the time-series of properties and trajectory of (x,r) in some representative cases in Figs. 4 and 6.

As a whole, I really evaluate this work as impressive.

Reviewer #1 (Public Review):

The role of increased temperature on immunity and homeostasis in cold-blooded vertebrates is an understudied yet important field. This work not only examines how immunity is impacted by fever, but also incorporates an infection model and examines resolution of the response. This work can serve as a model for other groups interested in the study of hyperthermia and immunity.

Generally speaking, I agree with the authors' strategy and interpretations of the data.

- In the Introduction, the authors chose to begin with how fever in endotherms impact the immune system. Considering that this work exclusively examines the response of a teleost (goldfish), the authors might consider flipping the way they present this work. After all, cold-blooded vertebrates rely on this response because of their basic physiology.

- I thought the set up of the work in figure 1 was innovative and could provide an example of how to study such a problem.

- Figure 2 was (to me) unexpected. One would not expect such tight response to hyperthermia and infection. This experiment in and of itself was quite interesting, and worth following up in future experiments (by the authors and other groups).

- The other work, on the response to infection and the resolution of infection were unique to this paper, and (sorry to be repetitive) can be an example of how to devise such studies.

- On the other hand, I am not sure this is a study of "fever." That implies how increased temperature impacts immunity and resolution in endotherms. Perhaps the authors could temper the comparisons between cold- and warm-blooded vertebrates regarding the response to hyperthermia.

Reviewer #1 (Public Review):

In this report, Yeung et al studied a mutation in Orai1 channels (L138F) that is associated with constitutive CRAC channel activity and tubular aggregate myopathy (TAM) in humans. They put forth a model whereby substitution with large amino acids at position L138 on TM2 or the neighboring T92 on TM1 causes a steric clash between TM1 and TM2 and elicits a highly Ca2+ selective current in the absence of STIM1, the ER Ca2+ sensor protein that is the physiological activator of Orai channels. The authors went on to study one typical biophysical property of Orai1-mediated CRAC channels which is the fast Ca2+-dependent inactivation (CDI), after the surprising finding of the presence of CDI in CRAC currents mediated by T92 and L138 Orai1 mutants in the absence of STIM1. The authors showed differences in CDI between WT and mutants when using weak vs strong buffers and through computation and experimentation, they show that the Orai1 mutants have enhanced cytosolic Ca2+ sensitivity, which could be normalized when STIM1 was present. The experiments are carefully conducted and the manuscript is clearly written. The study has significant novelty and impact.

Reviewer #1 (Public Review):

FLOWERING LOCUS C (FLC) is a key repressor of flowering in Arabidopsis thaliana. FLC expression creates a requirement for vernalization which is the acquisition of competence to flower after exposure to the prolonged cold of winter. Vernalization in Arabidopsis and other Brassicas results in the suppression of FLC expression.

How exposure to winter cold initiates the vernalization process (i.e., the silencing of FLC) is not fully understood. It is known that cold exposure causes several long non-coding RNAs, including COOLAIR and COLDAIR, to be transcribed from FLC. this work shows that COOLAIR induction by cold results requires the binding of CRT/DRE-binding factors (CBFs) to their cognate recognition elements which reside at the 3' end of the FLC locus. The authors demonstrate this regulation in many ways including studying the effect on vernalization of knocking out all CBFs and also by showing that constitutive CBF expression causes COOLAIR levels to be elevated even without cold exposure. Intriguingly, plants with genetic alterations that eliminate COOLAIR expression (loss of CBF activity and FLC deletion mutants that eliminate COOLAIR expression) do not have a significant impairment in becoming vernalized.

The work appears to be done properly and provides much important information about how this remarkable environmentally-induced epigenetic switch operates.

Joint Public Review:

In this study, the authors transcriptomically characterize TIL from head and neck cancers and associate their transcriptional programs with overall survival as a function of HPV positivity. Specifically, they study the impact of CDK4 inhibition on TIL from these tumors. They find an exhausted T cell subset that preferentially expresses CDK4. They then perform some in vitro studies to test the function of exhausted T cells and the impact of CDK4 inhibition on different TIL subsets from head and neck tumors. Understanding the functional impact of different cancer therapies on cells in the TME is of high importance and interest to the field.

1. Line 215: The authors state that pairing TCRseq with RNAseq reflects the magnitude of TCR signaling. This is absolutely not the case. TCR sequencing does not reflect TCR signaling strength.<br /> 2. A lot of discussion around "activation" is presented, but there is no evidence to support which genes or gene programs are associated with "activation".<br /> 3. Line 249: It is unclear why the authors are indicating that TCRseq was used in pseudotime analysis. This type of analysis does not take TCRs into account but rather looks at the proportion of spliced mRNA of individual genes from the DGE data.<br /> 4. There is no way to know if the differences in proliferation and cell viability shown in Figs. 4a and b, respectively, are meaningful or not. Proper controls or replicates should be provided to fully understand if this difference is biologically meaningful. Likewise, what is the evidence that P-Tex cells are self-renewing rather than expanding?

DOI: 10.1101/2023.01.13.523942

Resource: RRID:ZFIN_ZDB-ALT-071016-1

Curator: @scibot

SciCrunch record: RRID:ZFIN_ZDB-ALT-071016-1

What is this?

Reviewer #1 (Public Review):

This study reports the results of a computational and EEG analysis of altruistic decision making. The authors intend to examine whether fundamentally different mechanisms operate to drive altruistic decision making in different contexts, which they here manipulate by examining choices in the realm of advantageous and disadvantageous inequality. The authors find that changes in self payoff are encoded in opposite manners in the two contexts, but that a similar evidence accumulation mechanism leading up to the time of response seems to operate equally in both. In addition, they find that individual differences in generosity are predicted more by differences in sensitivity to change in the other's payoff in the disadvantageous inequality condition, and by stronger phase coupling between sensors related to this delta-other signal and sensors related to the evidence accumulation signal.

This study makes a valuable contribution by combining a sophisticated suite of modelling and neurophysiological analyses to shed light on the decision parameter adjustments that inform altruistic decisions in different contexts. The conclusions regarding those adjustments appear well supported by the data. One aspect that could be clarified is that there is an apparent discrepancy between the cross-condition bound adjustments identified by the modelling and the absence of any corresponding neural evidence accumulation signal amplitude difference.

One of the stated overarching goals of this study is to determine whether the neural mechanisms and circuits for altruistic decisions are context-specific or general. The manuscript would benefit from greater clarity on this point, in particular defining what is meant by 'mechanisms' and what qualitative and quantitative criteria should be applied when identifying them as distinct versus common. As all decisions in this study are reported via the same manual actions it seems implausible that there would be no overlap at all in the circuits and mechanisms involved. In addition, the prior literature has demonstrated that even individual neurons can trace different computations depending on the circumstances. Therefore, it is necessary to clarify whether the authors are searching for context-dependence in the brain areas/signals that are recruited and/or in the computations that are performed within a brain area.

Reviewer #1 (Public Review):

In this study, the authors examine the function of Tomosyn, in dense core vesicle fusion using CRE-mediated deletion in neuronal cultures from mice expressing conditional alleles of tomosyn and tomosyn-2. Tomosyn is a large soluble SNARE protein, where earlier work in multiple species suggested that it functions as a competitive inhibitor of cognate SNARE interactions impairing fusion. The authors show that while loss of tomosyns did not affect dense core vesicle exocytosis, it reduced the expression of several key dense core cargos, including BDNF. Limited (if anything opposite) impact of tomosyn loss-of-function on intracellular vesicle trafficking or Golgi function.

The authors concluded that tomosyns regulate neuropeptide and neurotrophin secretion by regulating dense core vesicle cargo production but not exocytosis.

Reviewer #1 (Public Review):

These findings for the first time provide a comprehensive multiscale assessment of the arrhythmogenic potential of elite exercise training.

The authors trained canines using a treadmill over 16 weeks, and compared these animals (n=12) to sedentary animals (n=13). The authors found global evidence of electrophysiologic remodeling ECG indices and heart rate, as well as repolarization variability in trained animals relative to controls.

The authors also demonstrate a range of effects of ventricular cardiomyocyte ion channels and fibrosis. Finally, using an induction protocol, the authors show enhanced risk for ventricular fibrillation as well as spontaneous arrhythmias in trained dogs.

The authors conclude that structural and electrophysiologic remodeling of ventricles in elite trained athletes is associated with ventricular arrhythmogenesis.

First, this is a difficult study to achieve given the logistical challenges of managing a large animal set up as utilized in this study. Further protocols that involve in vivo and subsequently in vitro studies of tissues from large animals are challenging to accomplish. Finally, the multimodal assessments undertaken in this study to achieve these comprehensive objectives are an additional strength.

Weaknesses include the descriptive nature of the work and somewhat low level of rigor in presenting the observed data. The presentation of the data in the text could also be improved. Finally, some of the counterintuitive/conflicting findings e.g. enhanced HCN4 expression with reduced heart rate.

Reviewer #1 (Public Review):

This article is aimed at constructing a recurrent network model of the population dynamics observed in the monkey primary motor cortex before and during reaching. The authors approach the problem from a representational viewpoint, by (i) focusing on a simple center-out reaching task where each reach is predominantly characterised by its direction, and (ii) using the machinery of continuous attractor models to construct network dynamics capable of holding stable representations of that angle. Importantly, M1 activity in this task exhibits a number of peculiarities that have pushed the authors to develop important methodological innovations which, to me, give the paper most of its appeal. In particular, M1 neurons have dramatically different tuning to reach direction in the movement preparation and execution epochs, and that fact motivated the introduction of a continuous attractor model incorporating (i) two distinct maps of direction selectivity and (ii) distinct degrees of participation of each neuron in each map. I anticipate that such models will become highly relevant as neuroscientists increasingly appreciate the highly heterogeneous, and stable-yet-non-stationary nature of neural representations in the sensory and cognitive domains.

As far as modelling M1 is concerned, however, the paper could be considerably strengthened by a more thorough comparison between the proposed attractor model and the (few) other existing models of M1 (even if these comparisons are not favourable they will be informative nonetheless). For example, the model of Kao et al (2021) seems to capture all that the present model captures (orthogonality between preparatory and movement-related subspaces, rotational dynamics, tuned thalamic inputs mostly during preparation) but also does well at matching the temporal structure of single-neuron and population responses (shown e.g. through canonical correlation analysis). In particular, it is not clear to me how the symmetric structure of connectivity within each map would enable the production of temporally rich responses as observed in M1. If it doesn't, the model remains interesting, as feedforward connectivity between more than two maps (reflecting the encoding of many more kinematic variables) or other mechanisms (such as proprioceptive feedback) could well explain away the observed temporal complexity of neural responses. Investigating such alternative explanations would of course be beyond the scope of this paper, but it is arguably important for the readers to know where the model stands in the current literature.

Below is a summary of my view on the main strengths and weaknesses of the paper:

1. From a theoretical perspective, this is a great paper that makes an interesting use of the multi-map attractor model of Romani & Tsodyks (2010), motivated by the change in angular tuning configuration from the preparatory epoch to the movement execution epoch. Continuous attractor models of angular tuning are often criticised for being implausibly homogeneous/symmetrical; here, the authors address this limitation by incorporating an extra dimension to each map, namely the degree of participation of each neuron (the distribution of which is directly extracted from data). This extension of the classical ring model seems long overdue! Another nice thing is the direct use of data for constraining the model's coupling parameters; specifically, the authors adjust the model's parameters in such a way as to match the temporal evolution of a number of "order parameters" that are explicitly manifested (i.e. observable) in the population recordings.

I believe the main weakness of this continuous attractor approach is that it - perhaps unduly - binarises the configuration of angular tuning. Specifically, it assumes that while angular tuning switches at movement onset, it is otherwise constant within each epoch (preparation and execution). I commend the authors for carefully motivating this in Figure 2 (2e in particular), by showing that the circular variance of the distribution of preferred directions is higher across prep & move than within either prep or move. While this justifies a binary "two-map model" to first order, the analysis nevertheless shows that preferred directions do change, especially within the preparatory epoch. Perhaps the authors could do some bootstrapping to assess whether the observed dispersion of PDs within sub-periods of the delay epoch is within the noise floor imposed by the finite number of trials used to estimate tuning curves. If it is, then this considerably strengthens the model; otherwise, the authors should say that the binarisation reflects an approximation made for analytical tractability, and discuss any important implications.

2. While it is great to constrain the model parameters using the data, there is a glaring "issue" here which I believe is both a weakness and a strength of the approach. The model has a lot of freedom in the external inputs, which leads to relatively severe parameter degeneracies. The authors are entirely forthright about this: they even dedicate a whole section to explaining that depending on the way the cost function is set up, the fit can land the model in very different regimes, yielding very different conclusions. The problem is that I eventually could not decide what to make of the paper's main results about the inferred external inputs, and indeed what to make of the main claim of the abstract. It would be great if the authors could discuss these issues more thoroughly than they currently do, and in particular, argue more strongly about the reasons that might lead one to favour the solutions of Fig 6d/g over that of Fig 6a. On the other hand, I see the proposed model as an interesting playground that will probably enable a more thorough investigation of input degeneracies in RNN models. Several research groups are currently grappling with this; in particular, the authors of LFADS (Pandarinath et al, 2018) and other follow-up approaches (e.g. Schimel et al, 2022) make a big deal of being able to use data to simultaneously learn the dynamics of a neural circuit and infer any external inputs that drive those dynamics, but everyone knows that this is a generally ill-posed problem (see also discussion in Malonis et al 2021, which the authors cite). As far as I know, it is not yet clear what form of regularisation/prior might best improve identifiability. While Bachschmid-Romano et al. do not go very far in dissecting this problem, the model they propose is low-dimensional and more amenable to analytical calculations, such that it provided a valuable playground for future work on this topic.

3. As an addition to the motor control literature, this paper's main strengths lie in the model capturing orthogonality between preparatory and movement-related activity subspaces (Elsayed et al 2016), which few models do. However, one might argue that the model is in fact half hand-crafted for this purpose, and half-tuned to neural data, in such a way that it is almost bound to exhibit the phenomenon. Thus, some form of broader model cross-validation would be nice: what else does the model capture about the data that did not explicitly inspire/determine its construction? As a starting point, I would suggest that the authors apply the type of CCA-based analysis originally performed by Sussillo et al (2015), and compare qualitatively to both Sussillo et al. (2015) and Kao et al (2021). Also, as every recorded monkey M1 neuron can be characterized by its coordinates in the 4-dimensional space of angular tuning, it should be straightforward to identify the closest model neuron; it would be very compelling to show side-by-side comparisons of single-neuron response timecourses in model and monkey (i.e., extend the comparison of Fig S6 to the temporal domain).

4. The paper's clarity could be improved.

Reviewer #1 (Public Review):

DeRisi and colleagues used a new phage-display peptide platform, with 238,068 tiled 62-amino acid peptides covering all known P falciparum coding regions (and numerous other entities), to survey seroreactivity in 198 Ugandan children and adults from two cohorts. They find that breadth of responses to repeat-containing peptides was twofold higher in children living in the high versus moderate exposure setting, while no such differences were observed for peptides without repeats. Additionally, short motifs associated with seroreactivity were extensively shared among hundreds of antigens, with much of this driven by motifs shared with PfEMP1 antigens.

Malaria immunity is complex, and this new platform is a potentially valuable addition to the toolkit for understanding humoral responses. The two cohorts differed in fundamental ways: 1) high versus moderate exposure to infective bites; 2) samples drawn at the time of malaria for most donors in the high zone versus ~100 days after the last malaria episode in the moderate zone. The effect of acute malaria to boost short-term cross-reactive antibodies can confound the ability to draw inferences when comparing the two cohorts, and this should be further explored to understand its role in the patterns of seroreactivity observed.

Reviewer #1 (Public Review):

Osteoclasts, giant multinucleated bone-resorbing cells, are crucial regulators of bone homeostasis and pathology. An underestimated aspect of their biology is that they are very heterogeneous, with at least 2 sub-populations (inflammatory osteoclasts and tolerogenic osteoclasts) existing, and exerting different actions, especially in the context of inflammatory bone loss. In this report, Madel, Halper (co-first authors), and colleagues present an interesting report investigating this heterogeneity, and showing that the probiotic yeast S. boulardii (probably through β-glucans) may be useful in managing inflammation-mediated bone loss, including oestrogen deprivation-mediated osteoporosis, as the authors show in vivo using an OVX mouse model.

The authors first evaluate the differences in the transcriptional landscape of tolerogenic vs inflammatory osteoclasts with RNAseq, and then they evaluate the differences in miRNA expression between the two. Finding that some of the pathways/genes that vary are related to pattern recognition receptors (PRRs), specialized in recognizing non-self antigens including those arising from bacteria and yeasts, they wonder if the probiotic yeast S. boulardii could influence the balance between tolerogenic and inflammatory osteoclasts. Indeed, when the authors treated OVX mice, characterised by an increase in inflammatory osteoclasts and estrogen deprivation/inflammation-induced bone loss, with the probiotic, the bone loss is avoided and inflammatory osteoclasts are reduced. This challenges the classical way in which osteoclast-mediated bone loss is treated, since targeting specifically the inflammatory osteoclasts could allow the good osteoclasts to keep working and improving bone health and immunity, while only the bad osteoclasts are targeted. Current treatments are not able to distinguish between the two, which can cause a paradoxical degradation in bone health and atypical fractures. The report is therefore potentially very important for the field, and although quite focused on a specific strain, it can pave the way to treating bone diseases with probiotics, or specific molecules derived from them including beta-glucans.

Reviewer #1 (Public Review):

This well-done platform trial identifies that ivermectin has no impact on SARS-CoV-2 viral clearance rate relative to no study drug while casirivimab lead to more rapid clearance at 5 days. The figures are simple and appealing. The study design is appropriate and the analysis is sound. The conclusions are generally well supported by the analysis. Study novelty is somewhat limited by the fact that ivermectin has already been definitively assessed and is known to lack efficacy against SARS-CoV-2. Several issues warrant addressing:

1) Use of viral load clearance is not unique to this study and was part of multiple key trials studying paxlovid, remdesivir, molnupiravir, and monoclonal antibodies. The authors neglect to describe a substantial literature on viral load surrogate endpoints of therapeutic efficacy which exist for HIV, hepatitis B and C, Ebola, HSV-2, and CMV. For SARS-CoV-2, the story is more complicated as several drugs with proven efficacy were associated with a decrease in nasal viral loads whereas a trial of early remdesivir showed no reduction in viral load despite a 90% reduction in hospitalization. In addition, viral load kinetics have not been formally identified as a true surrogate endpoint. For maximal value, a reduction in viral load would be linked with a reduction in a hard clinical endpoint in the study (reduction in hospitalization and/or death, decreased symptom duration, etc...). This literature should be discussed and data on the secondary outcome, and reduction in hospitalization should be included to see if there is any relationship between viral load reduction and clinical outcomes.

2) The statement that oropharyngeal swabs are much better tolerated than nasal swabs is subjective. More detail needs to be paid to the relative yield of these approaches.

3) The stopping rules as they relate to previously modeled serial viral loads are not described in sufficient detail.

4) The lack of blinding limits any analysis of symptomatic outcomes.

5) It is unclear whether all 4 swabs from 2 tonsils are aggregated. Are the swabs placed in a single tube and analyzed?

6) In supplementary Figure 7, both models do well in most circumstances but fail in the relatively common event of non-monotonic viral kinetics (multiple peaks, rebound events). Given the importance of viral rebound during paxlovid use, an exploratory secondary analysis of this outcome would be welcome.

Reviewer #1 (Public Review):

In the study, Zhao et al. investigated loop conformational changes in the active site of L1 Metallo-beta-lactamase. Antibiotic resistance is on the rise and beta-lactamases are enzymes that cleave a lactam ring. Authors investigate class B3 MBLs since these could be used for designing drugs for treating antibacterial resistance. Authors find specific loops that act as gates to the shape and access to the active site of the enzymes. They study these loops via MD simulations, Markov state models, and CVAE-based deep learning to experimentally reveal how each residue affects activity as well as remodeling of the active site.

Strengths<br /> - The authors make a good case for why MD is important for this scaffold and protein class. The study performs MD simulations coupled with Markov State Models - this coupled with CVAE to understand the different states the protein exists in shapes the state-of-the-art study. Authors are able to isolate three different states that the protein exists in and pinpoint which interactions cause a reshaping of the active site.<br /> - Furthermore, they isolate the likely states that also correspond with lower free energy indicating why these states might be more populated. This study adds to the depth of their work.

Weaknesses<br /> - Overall, the impact of work on the currently used antibiotic classes is unclear since the total market presence of all antibiotics is discussed not the carbapenem-based antibiotics class. Statistics related to broad antibiotic class reduce the impact statement instead of improving it.<br /> - Finally in the experimental testing only a few variants at each position were tested, leading to limited learning of the impact of active site interactions.<br /> - Authors state from previous studies on TEM-1 that disruption of the salt bridge between the two loops would alter the binding site, thus reducing antibiotic resistance. The authors continue on to hypothesize that this would hold true for the structure in consideration for this paper as well. While a good hypothesis, this cannot be inferred until we see experimental evidence for the same or a sequence comparison discussing how similar TEM1 is to the L1 MBL in question.<br /> - The authors do not explain how different splits of this data in terms of splitting (80:20 vs 70:30 or others) and reducing interaction matrix lower than 22 x 22 residues can impact their results. Also, the effect of changing the distance shell (8A) for matrix generation is not described. This variation is unaccounted for and can enable authors to pressure test their method and learnings.

Reviewer #1 (Public Review):

Bornstein and colleagues address an important question regarding the molecular makeup of the different cellular compartments contributing to the muscle spindle. While work focusing on single components of the spindle in isolation - proprioceptors, gamma-motor neurons, and intrafusal muscle fibres - have been recently published, a comprehensive analysis of the transcriptome and proteome of the spindle was missing and it fills an important gap considering how local translation and protein synthesis can affect the development and function of such a specialised organ.

The authors combine bulk transcriptome and proteome analysis and identify new markers for neuronal, intrafusal, and capsule compartments that are validated in vivo and are shown to be useful for studying aspects of spindle differentiation during development. The methodology is sound and the conclusions in line with the results. I feel a bit more analysis regarding the specificity and developmental expression profiles of the identified markers would be a great addition. In particular:

- Are any of the proprioceptive sensory neurons markers specific for fibres innervating the muscle spindles or also found in Golgi tendon organs?

- On the same line are any of the gamma motor neurons markers found also in alpha?

- How early expression of ATP1A3 is found in neurons at the spindle or fibres starting to innervating the muscle? A couple of late embryonic timepoints would be great.

- Given that the approach used allows to obtain insights on whether local translation plays a major role into the differentiation of the spindle it would be interesting to assess whether the proprioceptor and gamma motor neuron markers identified are also found in the cell body or exclusively at the spindle.

Altogether, this is a novel and important work that will benefit scientists studying the neuromuscular and musculoskeletal systems by pushing the field toward an holistic understanding of the muscle spindle. These datasets in combination with the previous ones can be used to develop new genetic and viral strategies to study muscle spindle development and function in healthy and pathological states by analysing the roles and relative contributions of different components of this fascinating and still mysterious organ.

Reviewer #1 (Public Review):

The authors devised a new mRNA imaging approach, MASS, and showed that it can be applied to investigate the activation of gene expression and the dynamics of endogenous mRNAs in the epidermis of live C. elegans. The approach is potentially useful, but this manuscript will benefit by addressing the following questions:

Major comments:

1. In Figure 1-figure supplement 1, the authors claimed that MASS could verify the lamellipodia-localization of beta-actin mRNAs. However, the image showed the opposite of the authors' claim as the concentration of beta-actin mRNA was lower in lamellipodia than the rest of the cytosol. This result disagreed with ref. 17 (Katz, Z.B. et al., Genes and Development, 2012). Hence, the authors cannot make the statement that "MASS can be readily used to image RNA molecules in live cells without affecting RNA subcellular localization". To thoroughly test this notion, the authors should image beta-actin mRNA using MASS and the conventional MS2 system side by side and calculate the polarization index in the same way as shown in Katz, Z.B. et al., Genes and Development, 2012.

2. The experiments that validate this new RNA imaging method are not sufficient. The authors need to systematically compare MASS and the MS2 system, including their RNA signal intensity, signal-to-background ratio.

3. In line with this, does beta-actin mRNA display the same behavior as in (Figure 1C-F) when the mRNA was imaged with the MS2 system? The movies do not indicate the type of motility expected of mRNA. For instance, it seems that almost all of the GFP dots, which are presumably single beta-actin mRNAs, stayed stationary over a time course of tens of seconds (Movie 1). This seems to be very different from what has been observed before. It's not clear that the dots are real mRNAs molecules. This further stresses the importance for them to compare their new imaging system with the conventional MS2 application.

4. The authors claimed that a major advantage of MASS is that it has only 8xMS2 stem loops (350 nt) and overcomes "the previous obstacle of the requirement of inserting a long 1,300 nt 24xMS2". This statement lacks experimental support in this manuscript. The authors need to quantitatively compare the genomic tagging efficiency of 8xMS2 and 24xMS2.

5. MASS has the same strategy as SunRISER (Guo, Y. & Lee, R.E.C., Cell Reports Methods, 2022). Both methods use Suntag to amplify signals of MS2- or PP7-tagged RNA. The authors need to elaborate the discussions and describe the similarities and differences of the two studies. In particular, the Guo paper needs to be properly referenced.

6. In Guo, Y. & Lee, R.E.C., Cell Reports Methods, 2022, they showed that 8XPP7 with 24XSunTag configuration led to fewer mRNA per cell (Figure 5B of the Cell Reports Methods paper). Does MASS, which has 8xMS2 with 24xSunTag, similarly lead to few mRNAs? The authors should compare the number of mRNAs detected by MASS and the conventional MS2, or by FISH.

Reviewer #1 (Public Review):

Auxin-induced degradation is a strong tool to deplete CHK-2 and PLK-2 in the C. elegans germ line. The authors strengthen their conclusions through multiple approaches, including rescuing mutant phenotypes and biochemical analyses of CHK-2 and PLK-2.

The authors overcame a technical limitation that would hinder in vitro analysis (low quantity of CHK-2) through the clever approach of preventing its degradation via the proteasome. In vitro phosphorylation assays and mass spectrometry analysis that establishes that CHK-2 is a substrate of PLK-2 nicely complement the genetic data.

The authors argue that the inactivation of CHK-2 by PLK-2 promotes crossover designation; however, the data only indicate that PLK-2 promotes proper timing of crossover designation.

It is not clear whether the loss of CHK-2 function with the S116A and T120A mutations is the direct result of the inability to phosphorylate these residues or whether it is caused by the apparent instability of these proteins, as their abundance was reduced in IPs compared to wild-type.

The mechanism of CHK-2 inactivation in the absence of PLK-2 remains unclear, though the authors were able to rule out multiple candidates that could have played this role.

Reviewer #1 (Public Review):

In this manuscript, Li et al identify sleep and circadian regulatory role for ecdysone signaling in cortex glia. Prior to this report, numerous studies have linked ecdysone to sleep regulation, though these have primarily focused on its function in neurons. The manuscript is of high interest for a number of reasons. First, it provides a systematic analysis of how NHRs impact sleep. Second, the identification of ecdysone as a critical regulator of both sleep and circadian neurons provides new avenues to study how glia regulate sleep. Finally, the link to lipid accumulation is interesting, but perhaps preliminary. The manuscript is well written, and the data are clearly presented with appropriate controls. Overall this is an exciting manuscript that opens up new directions for the field.

Reviewer #1 (Public Review):

The manuscript entitled "Endo-lysosomal assembly variations among Human Leukocyte 1 Antigen class I (HLA-I) allotypes" by Eli Olson and co-workers reports an interesting observation that HLA-I alleles known not to require the standard peptide-loading complex for assembly and egress from the endoplasmic reticulum, may assemble with peptide ligands within the endo/lysosomes and are more adept at antigen cross-presentation to the CD8+ subset of T cells.

The strengths of the work are (a) a novel hypothesis that HLA-I allotype variations caused by HLA-I gene polymorphisms control endo/lysosomal HLA-I assembly and antigen cross-presentation even though there is ample evidence for cross-presentation using the endo/lysosomal pathway; and (b) new evidence to support this hypothesis.

Weaknesses are (a) the use of qualitative serologic assays in which specificity of broadly reactive antibodies such as the anti-Bw6 antibody cannot be easily controlled; (b) poor resolution of co-localization micrographs and quantification based on such data; (c) evidence that endo/lysosomal pathway dominates in cross-presentation by B35.1 allotype is weak as the data suggest a significant role for the standard cytoplasmic pathway itself in this immunologic process; and (d) narrow focus on a single member of the B7 supertype that is prevalent at low frequency in the African American (AA: 0.05) and White American (WA: 0.07) populations. These weaknesses can be addressed by using (a) more quantitative biochemical assays; (b) high resolution microscopy; & (c) extending cellular biochemical studies to one or more additional allotypes in the B7 superfamily-e.g., B7.2 (AA: 0.08; WA: 0.155) itself &/or B35.3 (AA: 0.005; WA: 0.027) or B53.1 (AA: 0.133; WA: 0.004).

Reviewer #1 (Public Review):

This study used MEG to investigate the neural changes induced by two weeks of reading instruction in pre-literate children. The study addresses a topic of great importance, measuring neural changes resulting from learning to read. While there have been several previous studies investigating this question, this may be the first study to use a truly experimental approach (i.e., involving random assignment).

There are some weaknesses in the current presentation of results that limit the conclusions that can be drawn. First, there is no control region (e.g., the right FFA or object-selective LO) to show that learning to read specifically affected tuning in a region corresponding to the VWFA, as hypothesized. This is important also to exclude more general differences between conditions (e.g., increased attention to letters after two weeks of training to recognize letters). Second, the statistical pattern of results is closely linked to the specific time window of interest (135-235 ms after stimulus onset) but there is no evidence that this time window is selective for words in this age group. For comparison, the face-selective response in children of this age is only observed at around 250 ms after onset (Taylor et al., Clinical Neurophysiology 1999). Third, the power analysis is very optimistic, with an estimated effect size of d=4.65. Considering the between-subjects design, the relatively low SNR of data in young children, and the multiple comparisons that are inherent to neuroimaging data, the study may be underpowered to detect the likely subtle effects of the 2 weeks of training.

Reviewer #1 (Public Review):

This study comprehensively categorizes the olivocochlear efferents, using single nucleus RNA-sequencing and 3D reconstructions of individual fibers and their pre-synaptic contacts onto target neurons in the cochlea.

The major strengths of the methods and results are the gene expression studies, which reveal 5 clusters of olivocochlear neurons. Traditionally, efferents have been divided into two groups, medial olivocochlear neurons that terminate on outer hair cells, and the lateral olivocochlear neurons, that terminate on spiral ganglion neurons postsynaptic to the auditory hair cells. The analyses here revealed 3 main clusters, one large cluster of medial olivocochlear neurons, and two clusters of lateral olivocochlear neurons.

In a second major strength, the study shows changing patterns of physiologically relevant gene expression over development. The authors further showed changes in the neuropeptide expression in the lateral olivocochlear neurons days after acoustic trauma.

There are no significant weaknesses, barring the issue of a gap between gene and protein expression. This is mitigated by a close match with previous protein expression studies.

Thus, the authors have achieved their aims to characterize the phenotypes and arborization patterns of the cochlear efferents. They have confirmed and enlarged upon what has previously known about this important population.

Since these neurons have been difficult to characterize, and are important for auditory function, particularly in noise, the likely impact of the work on the field is high.

Reviewer #1 (Public Review):

In this study, the authors describe an elegant genetic screen for mutants that suppress defects of MCT1 deletions which are deficient in mitochondrial fatty acid synthesis. This screen identified many genes, including that for Sit4. In addition, genes for retrograde signaling factors (Rtg1, Rtg2 and Rtg3), proteins influencing proteasomal degradation (Rpn4, Ubc4) or ribosomal proteins (Rps17A, Rps29A) were found. From this mix of components, the authors selected Sit4 for further analysis. In the first part of the study, they analyzed the effect of Sit4 in context of MCT1 mutant suppression. This more specific part is very detailed and thorough, the experiments are well controlled and convincing. The second, more general part of the study focused on the effect of Sit4 on the level of the mitochondrial membrane potential. This part is of high general interest, but less well developed. Nevertheless, this study is very interesting as it shows for the first time that phosphate export from mitochondrial is of general relevance for the membrane potential even in wild type cells (as long as they live from fermentation), that the Sit4 phosphatase is critical for this process and that the modulation of Sit4 activity influences processes relying on the membrane potential, such as the import of proteins into mitochondria. However, some aspects should be further clarified.

1. It is not clear whether Sit4 is only relevant under fermentative conditions. Does Sit4 also influence the membrane potential in respiring cells? Fig. S2D shows the membrane potential in glucose and raffinose. Both carbon sources lead to fermentative growths. The authors should also test whether Sit4 levels influence the membrane potential when cells are grown under respirative conditions, such in ethanol, lactate or glycerol. Even if deletions of Sit4 affect respiration, mutants with altered activity can be easily analyzed.<br /> 2. The authors should give a name to the pathway shown in Fig. 4D. This would make it easier to follow the text in the results and the discussion. This pathway was proposed and characterized in the 90s by George Clark-Walker and others, but never carefully studied on a mechanistic level. Even if the flux through this pathway cannot be measured in this study, the regulatory role of Sit4 for this process is the most important aspect of this manuscript.<br /> 3. To further support their hypothesis, the authors should show that deletion of Pic1 or Atp1 wipes out the effect of a Sit4 deletion. In these petite-negative mutants, the phosphate export cycle cannot be carried out and thus, Sit4, should have no effect.<br /> 4. What is the relevance of Sit4 for the Hap complex which regulates OXPHOS gene expression in yeast? The supplemental table suggests that Hap4 is strongly influenced by Sit4. Is this downstream of the proposed role in phosphate metabolism or a parallel Sit4 activity? This is a crucial point that should be addressed experimentally.<br /> 5. The authors use the accumulation of Ilv2 precursors as proxy for mitochondrial protein import efficiency. Ilv2 was reported before as a protein which, if import into mitochondria is slow, is deviated into the nucleus in order to be degraded (Shakya,..., Hughes. 2021, Elife). Is it possible that the accumulation of the precursor is the result of a reduced degradation of pre-Ilv2 in the nucleus rather than an impaired mitochondrial import? Since a number of components of the ubiquitin-proteasome system were identified with Sit4 in the same screen, a role of Sit4 in proteasomal degradation seems possible. This should be tested.

Reviewer #1 (Public Review):

The authors optimize a live cell imaging method based on the detection of FAD/NAD(P)H adopted from the fast-growing field of live metabolic imaging. They build upon a method described by KreiB et al 2020 that used metabolic ratio and collagen fiber second harmonic generation imaging. They follow by combining metabolic imaging with morphologic measurements to train a machine-learning model that is able to identify cell types accurately. Upon visualization, authors detected structures hypothesized and then proven to resemble the "goblet cell associated antigen passages" previously studied in intestinal epithelia.

STRENGTHS<br /> - The manuscript is succinct, well written, and overall done rigorously.<br /> - The optimization of the method at multiple levels to the point of identifying both common and rare cell types is impressive.<br /> - Describes the elegant implementation of a sorely needed method in epithelial biology.<br /> - Provides an approach to studying the cholinergic response in epithelial cells, a poorly understood phenomenon despite broad clinical use for diagnosis and treatment.

WEAKNESSES<br /> A) For what is in large part a methods-development paper, the methods are not explained or shared in a manner that facilitates reproducibility. For example:<br /> A.1.) The training and validation datasets seem to come from the same sample (or the source is not clearly described). Therefore, it is not clear whether the "96% accuracy" refers to accuracy within the sample measured, or whether it can extrapolate to other samples.<br /> A.2.) It is unclear whether the model needs to be re-trained within each new sample measured, or if it's applicable to others. This has implications for method adoption by others. Either way is useful but needs to be clarified.<br /> A.3.) Code was only listed in a PDF file, which makes reproducing the analysis very cumbersome.

B) Whereas the optimization to improve cell type detection is very well described, the implementability of the approach could benefit from exploration (using the data already obtained) of the minimal set of measurements needed to identify cell types. For example, is the FAD/NAD(P)H ratio necessary? Or could just morphologic measurements achieve the same goal?

C) Whereas the conclusions are overall supported by the data, need small adjustments in some cases:<br /> C.1.) For example, P3L80: Claims autofluorescence imaging is more specific than "functional markers", however, this is done in the setting of a very specific intervention that massively affects a protein often used as a secretory cell marker (CCSP aka SCGB1A1), which is known to be secreted (and depleted) in secretory cells upon stimulation.<br /> C.2.) Relatedly, it is unclear how the method's accuracy would be affected in conditions that affect redox/metabolic state; the approach may be highly affected in inflammation and injury, for example.

D) The data used to describe "SAPs" is very cursory.<br /> D.1.) Unclear if FITC dextran uptake occurs in other cells too, or in secretory cells prior to methacholine stimulation, or induced nonspecifically due to epithelia manipulation. Secretory and goblet cells are very sensitive to stimulation and often considered minimal, for example, see the paper by Abdullah et al DOI:10.1007/978-1-61779-513-8_16 in which extreme care had to be applied to prevent any secretion at all.<br /> D.2.) A single image is provided for the SAP timeline (Figure 5C), which appears to be the same cell shown in the supplementary video.

IMPACT AND UTILITY<br /> This is well-done work with high potential for widespread adoption within the epithelial biology community, particularly if the methods and code are shared in better detail.

Reviewer #1 (Public Review):

This study used GWAS and RNAseq data of TCGA to show a link between telomere length and lung cancer. Authors identified novel susceptibility loci that are associated with lung adenocarcinoma risk. They showed that longer telomeres were associated with being a female nonsmoker and early-stage cancer with a signature of cell proliferation, genome stability, and telomerase activity.

Major comments:

1. It is not clear how are the signatures captured by PC2 specific for lung adenocarcinoma compared to other lung subtypes. In other words, why is the association between long telomeres specific to lung adenocarcinoma?

2. The manuscript is lacking specific comparisons of gene expression changes across lung cancer subtypes for identified genes such as telomerase etc since all the data is presented as associations embedded within PCs.

3. It is not clear how novel are the findings given that most of these observations have been made previously i.e. the genetic component of the association between telomere length and cancer.

Reviewer #1 (Public Review):

The authors set out to answer the standing mystery of an origin of a unique and complex system that is hagfish slime. They formulated a cogent scenario for the co-option of epidermal thread cells and mucous cells into slime and slime glands. Both histology and EM images back this up. It is a delight to see detailed and careful morphological analysis of both the cells and the secretion.

The weakness of the manuscript lies in: a) the absence of an alternative hypothesis (therefore the lacking sense of hypothesis testing); and b) oversimplification and insufficient description of results in transcriptomic and phylogenetic comparison. These are both key elements of the narrative. Because all the data "support" the only scenario considered in this paper, it could risk giving the impression of a just-so story. My reading of the results of their transcriptomic and phylogenetic analyses is more nuanced than explained in the paper. For example, the authors didn't explain in sufficient detail how the data summary in Fig. 5 "demonstrate" that the epidermal thread cells are "ancestral", and that the diversity of alpha and gamma thread biopolymer genes is a prerequisite to slime (without a functional analysis), or that the gene duplication events facilitated the origin of hagfish slime.

This work stands unique. I am not aware of any other study that attempted to explain the origin of this truly bewildering adaptation in hagfish with such a multifaceted approach.

Reviewer #1 (Public Review):

The manuscript aims to provide a comprehensive insight into the development of the tuberal hypothalamus of the chick by carefully analyzing the expression patterns of a plethora of proteins involved and perturbation of BMP signaling.

Strengths:<br /> This manuscript presents the results of an in-depth analysis aimed to unravel the expression of a variety of transcription factors, and the role of signaling molecules, in particular BMP, SHH and Notch, and, and the role of BMP for the development of the tubular hypothalamus. For this, the authors applied a variety of methods, including in-situ RNA hybridizations to chick embryos, fate mapping, explant cultures, and loss and gain-functions studies in embryos, complemented by carefully mining previously performed scRNA-Seq data. From the data they derive a model, which explains the dynamic changes of expression of signaling molecules and transcription factors from anterior to posterior during chick development. In addition, they show that fate specification and growth occur concomitantly.<br /> Overall, the data provide a plethora of information on expression patterns and consequences of BMP signaling perturbation, which will be valuable for scientists interested in the events taking place during the development of the chick tubular hypothalamus.

Weaknesses:<br /> The plethora of data presented makes it very difficult for a reader, who is not familiar with this system, to follow the major conclusions from each of the panels. This difficulty is enhanced by the lack of a concise, simple and focused summary at the end of most chapters, which, from my point of view, still contains too many details. Similarly, the discussion too often refers to details presented in the figures of the Results section, rather than giving a broader and focused summary and pointing out to novel conclusions.

I also suggest that the authors check the Materials and Methods section, which does not always contain the information required. For example, in the chapter on "Chicken HCR": I guess they used the HCR IHC kit from Molecular Instruments? What kind of "modification" of the Molecular Instruments protocol did they introduce?

Reviewer #1 (Public Review):

In this work, Zhang et al. test neutralizing antibody immunity elicited by a primary vaccination series and homologous boosting with the Sinovac-inactivated COVID-19 vaccine CoronaVac.

While the interpretation of the data is complicated by how some of the experiments were done, it seems that boosting with CoronaVac has only a marginal effect on Omicron (BA.1 subvariant) neutralization.

After primary vaccination comprising two doses, SARS-CoV-2 neutralization, as assessed by a live virus neutralization assay and pseudovirus neutralization assay, are low in absolute terms at peak response 1-month post-second dose (~GMT ~20), then wane. Boosting with a third dose of CoronaVac results in neutralization levels about an order of magnitude higher relative to 1-month post-primary vaccination. However, neutralizing capacity against Omicron (subvariant BA.1) is very limited even at the peak response from the boost, and the great majority of participant samples neutralize less than 50% of Omicron infection with relatively concentrated plasma (1:50).

Form an immunogenicity perspective, puts the utility of homologous boosting with CoronaVac into question given the current Omicron circulating subvariants.

While the strength of this study lies in the implications of the results, a weakness is how the pseudovirus results were done, and these are key to interpreting the data. For these, the authors did not fit a dose-response curve to a dilution series but rather used one plasma concentration (1:50 dilution) and measured percent inhibition. Not doing the measurement with multiple dilutions make the results less accurate and conclusions weaker.

Reviewer #1 (Public Review):

In this paper Lei et al analyzed the interaction between HIV-1 Gag and the viral RNA packaging signal Psi in living cells using the CLIP-seq method. The authors convincingly showed that NC alone is not sufficient to bind specifically to Psi sequence, while CANC does. They further showed that CANC mutants that are deficient in CA multimerization failed to bind specifically to the Psi sequence. The results indicate that correct assembly of Gag is required for specific binding of the protein to the Psi sequence.

Most of the data are convincing and support the conclusions. My only concern is that the authors analyzed the binding of some CA mutant proteins to the Psi sequence, but it is not so clear whether the specific binding of these mutants would lead to effective packaging of the RNA into virions. Measuring RNA/Gag ratios of some of the mutants in Figure 4 might help to address this concern.

Reviewer #1 (Public Review):

There is growing precedent for the utility of GWAS-type analyses in elucidating otherwise cryptic genotypic associations with specific Mtb phenotypes, most commonly drug resistance. This study represents the latest instalment of this type of approach, utilizing a large set of WGS data from clinical Mtb isolates and refining the search for DR-associated alleles by restricting the set to those predicted (or known) to be phenotypically DR. This revealed a number of potential candidate mutations, including some in nucleotide excision repair (uvrA, uvrB), in base excision repair (mutY), and homologous recombination (recF). In validating these leads functional assays, the authors present evidence supporting the impact of the identified mutations on antibiotic susceptibility in vitro and in macrophage and animal infection models. These results extend the number of candidate mutations associated with Mtb drug resistance, however the following must be considered:

(i) The GWAS analysis is the basis of this study, yet the description of the approach used and presentation of results obtained is occasionally obscure; for example, the authors report the use of known drug resistance phenotypes (where available) or inferences of drug-resistance from genotypic data to enhance the potential to identify other mutations that might be implicated in enabling the DR mutations, yet their list of known DR mutations seem to be predominantly rare or unusual mutations, not those commonly associated with clinical DR-TB. In addition, the distribution of the identified resistance-associated mutations across the different lineages need to be explained more clearly.

(ii) By combining target gene deletions with different complementation alleles, the authors provide compelling microbiological evidence supporting the inferred role of the mutY and uvrB mutations in enhanced survival under antibiotic treatment. The experimental work, however, is limited to assessments of competitive survival in various models, with/without antibiotic selection, or to mutant frequency analyses; there is no direct evidence provided in support of the proposed mechanism.

(iii) The low drug concentrations used (especially of rifampicin against M. smegmatis) suggest the identified mutations confer low-level resistance to multiple antimycobacterial agents - in turn implying tolerance rather than resistance. If correct, it would be interesting to know how broadly tolerant strains containing these mutations are; that is, whether susceptibility is decreased to a broad range of antibiotics with different mechanisms of action (including both cidal and static agents), and whether the extent of the decrease be determined quantitatively (for example, as change in MIC value).

Reviewer #1 (Public Review):

In this manuscript, Wang et al focused on defining the importance of the ER proteostasis factor HSP47 in regulating the folding, assembly, trafficking, and activity of GABAA receptors. Previous mass spectrometry-based interactomics identified HSP47 as the most enriched GABAA interacting chaperone in HEK293T cells. Here, the authors expand this study, demonstrating that HSP47 interacts with GABAA subunits in mouse brain homogenates and in vitro, demonstrating that HSP47 binds the alpha1 GABAA subunit with high affinity. They went on to show that depletion of HSP47 reduces the surface expression and activity of GABAA receptors in primary hippocampal neurons. Alternatively, overexpression of HSP47 increased the trafficking of GABAA receptors in HEK293T cells. Interestingly, chemical or genetic disruption of critical disulfide bonds within the alpha1 subunit of GABAA decreased interactions with HSP47, while increasing interactions with the ATP-dependent ER chaperone BiP, suggesting that HSP47 binds folded GABAA subunits in the ER lumen and promoting receptor assembly. Consistent with this, the authors employed a FRET-based system and biochemical assays to demonstrate that HSP47 enhances the assembly of GABAA receptors. Further, they demonstrate that overexpression of HSP47 could enhance the trafficking and surface activity of the epilepsy-associated alpha1(A322D) GABAA mutant. Finally, the authors show that HSP47 promotes the assembly and activity of other Cys-loop receptors including nAchR.

Overall, this work expands our understanding of how membrane receptors including GABAA and nAchRs are folded and assembled. In particular, the demonstration that HSP47 works after canonical ATP-dependent chaperones such as BiP in promoting the assembly of GABAA receptors is intriguing, as it is beginning to demonstrate the sequence of events important for ER quality control of these membrane proteins. The use of multiple biochemical and genetic approaches to manipulate GABAA receptors and following the assembly, trafficking, and activity of these receptors is also a strength. However, one outstanding question is how does manipulation of HSP47 (with either overexpression or depletion) influence overall ER proteostasis and function. Can these effects be specifically attributed to HSP47 or does this reflect more global impairment of ER function induced by altered signaling through pathways such as the UPR? This is important because, while the authors do demonstrate direct interactions with HSP47, the direct importance of these interactions on the assembly and activity of Cys loop receptors remains somewhat unclear. Additional efforts addressing the specific impact of HSP47 manipulation on overall ER proteostasis should address this comment and allow for a more complete understanding of the role of HSP47 in regulating the assembly and trafficking of these proteins. Regardless, this is a solid manuscript that reviews new insights into membrane protein quality control and the importance of HSP47 in regulating ER proteostasis and function.

Reviewer #1 (Public Review):

This is an outstanding manuscript that takes a comprehensive approach to studying allosteric modulation at the M4R. I think it is an important addition to the literature and provides important insights into allosteric modulation. Overall the pharmacological approaches are very rigorous and are the types of analyses that need to be performed to move this field forward.

Reviewer #1 (Public Review):

The authors set out to extend modeling of bispecific engager pharmacology through explicit modelling of the search of T cells for tumour cells, the formation of an immunological synapse and the dissociation of the immunological synapse to enable serial killing. These features have not been included in prior models and their incorporation may improve the predictive value of the model.

The model provides a number of predictions that are of potential interest- that loss of CD19, the target antigen, to 1/20th of its initial expression will lead to escape and that the bone marrow is a site where the tumour cells may have the best opportunity to develop loss variants due to the limited pressure from T cells.

A limitation of the model is that adhesion is only treated as a 2D implementation of the blinatumomab mediated bridge between T cell and B cells- there is no distinct parameter related to the distinct adhesion systems that are critical for immunological synapse formation. For example, CD58 loss from tumours is correlated with escape, but it is not related to the target, CD19. While they begin to consider the immunological synapse, they don't incorporate adhesion as distinct from the engager, which is almost certainly important.

While the random search is a good first approximation, T cell behaviour is actually guided by stroma and extracellular matrix, which are non-isotropic. In a lymphoid tissue the stroma is optimised for a search that can be approximated as brownian, or more accurately, a correlated random walk, but in other tissues, particularly tumours, the Brownian search is not a good approximation and other models have been applied. It would be interesting to look at observations from bone marrow or other sites to determine the best approximating for the search related to BiTE targets.

Reviewer #1 (Public Review):

Sex determination and dosage compensation are two fundamental mechanisms in organisms with distinct sexes. These mechanisms vary greatly across the various model organisms in which they have been studied. Comparisons across more closely related members of the same genus have already proven productive in the past, to understand how these essential mechanisms evolve. In this study, the authors compare some aspects of the dosage compensation and sex determination mechanisms across two Caenorhabditis species that diverged ~15-30 MYA.

Previously, the authors have studied dosage compensation and sex determination extensively in C. elegans. Here, they first identify the homologs of some key factors in C. briggsae, a species that independently evolved hermaphroditism. The authors show that some of the key players in these processes play the same roles in C. briggsae as they do in C. elegans. Namely, they show that the nematode-specific SDC-2 protein plays a role in both dosage compensation and sex determination also in C. briggsae, they find the homologs of some of the SMC protein complex that performs dosage compensation also in C. elegans and they study the binding specificity on the X chromosome.

Overall, the work is thorough and compelling and is very clearly presented. The authors generate a number of genetic tools in C. briggsae and the careful genetic analyses together with a number of binding assays in vivo and in vitro, support the authors' main conclusions: that the main players and genetic regulatory hierarchy are conserved between these two nematodes, but the binding sites for the DCC on the X chromosome have diverged and the mode of binding has changed as well. Whereas in C. elegans the DCC binds sites in the X chromosome that contain multiple sequence motifs in a synergistic manner, in briggsae they seem to do so additively. This latter point is supported by the data, but it could be explored a bit more deeply using the available ChIP-seq data that the authors have generated. In addition, it would be interesting to discuss the possible implications of this difference.

One minor weakness of this work is that it could be better put in the context of other related comparisons of these mechanisms. For example, the comparison of sex determination pathway by Haag et al. in Genetics 2008, and the comparison of dosage compensation across Drosophila species (Ellison and Bachtrog, Plos Genetics, 2019), and possibly others. The other point that the authors could provide deeper insight into, is the rate of divergence of proteins like SDC-2 (which is thought to be the protein that contacts DNA), versus some other proteins in the DCC and in general other proteins not involved in sex determination or dosage compensation (this doesn't need to be limited to comparing elegans and briggsae as there are numerous Caenorhabditis genomes available). This would provide a more complete view of the evolution of these processes.

Reviewer #1 (Public Review):

Several new observations on the fascinating marine midge system are provided. The results are robust and have broad interest. First, multiple polymorphic chromosomal inversions are shown to be segregating in the study populations but these inversions are not strongly associated with ecotype differentiation. At least 4 QTL are detected that together explain a large part of the timing difference between co-located populations that emerge at full and new moon. Good candidate genes under these QTL are identified, with unusually high differentiation between populations. These are involved in the circadian clock (period) and in nervous system rewiring. The involvement of period suggests a link between the circadian and circalunar clocks.

The major context provided by the authors is the idea of 'magic traits' that influence multiple components of reproductive isolation and so are potentially important in population differentiation because associations between traits do not need to be built and maintained in the face of recombination. This idea is not described very clearly in the current MS. In particular, the authors suggest that magic traits are expected to have simple genetic basis, an expectation that they say should be re-evaluated on the basis of their results. However, there is no strong justification for this expectation. It tends to confuse the magic trait idea with the possibility of pleiotropy and with the advantage of recombination suppression where local adaptation is opposed by gene flow. The latter is relevant here because of the involvement of inversions, which might be expected to capture multiple alleles contributing to local adaptation but here apparently do not do so.

Reviewer #1 (Public Review):

The manuscript is of importance for vaccine design and understanding tissue microenvironmental influence on the functionality of monocytes and DCs to respiratory viruses such as Influenza A virus or SARS-CoV-2 virus. The methods used were mainly flow cytometry, ELISA, Luminex as well as TNFα secretion Assay Detection. The authors wanted to evaluate if and how the tissue microenvironment might impact DC and monocyte subset presence and functionality during Influenza A virus infection.

Strength:<br /> The study is summarizing a large cohort of human samples of blood, nasal swabs and nasopharyngeal aspirates. This is very uncommon as most of the time studies focus on the blood and serum of patients. Within the study, 3 monocyte and 3 DC subsets have been followed in healthy and Influenza A virus-infected persons. The study also includes functional data on the responsiveness of Influenza A virus-infected DC and monocyte populations. The authors achieved their aims in that they were able to show that the tissue microenvironment is important to understand subset specific migration and activation behavior in Influenza A virus infection and in addition that it matters with which kind of agent a person is infected. Thus, this study also impacts a better understanding of vaccine design for respiratory viruses.

Weakness:<br /> In the described study, the authors used a different nomenclature to introduce the DC subsets. This is confusing and the authors should stick to the nomenclature introduced by Guilliams et al., 2014 (doi.org/10.1038/nri3712) and commented in Ginhoux et al., 2022 (DOI: 10.1038/s41577-022-00675-7 ) or at least should introduce the alternative names (cDC1, cDC2, expression markers XCR1, CD172a/Sirpa). Further, Segura et al., 2013 (doi: 10.1084/jem.20121103) showed that all three DC subpopulations were able to perform cross-presentation when directly isolated. Overall, a more up-to-date introduction would be useful.<br /> As the data of this was already obtained in 2016-2018 it is clear that the FACS panel was not developed to study DC3. If possible, the authors might be able to speculate about the role of this subset in their data set. Moreover, there were other studies on SARS-CoV-2 infection and DC subset analyses in blood (line 87, and line 489) e.g. Winheim et al., (DOI: 10.1371/journal.ppat.1009742 ), which the authors should introduce and discuss in regard to their own data. Taken together, although the data are very important and very interesting, my overall impression of the manuscript is that in the era of RNA seq and scRNA seq analyses the study lacks a bit of comprehensiveness.

Reviewer #1 (Public Review):

In this manuscript, the authors propose a model to explain how oxysterols provide protection against bacteria and viruses by modulating a cell's "accessible cholesterol". The paper concentrates on one particular oxysterol, 25-hydroxycholesterol (25HC) which provides an example of a wider group of side-chain oxysterols. Previous studies have shown that 25HC can protect cells against microbial infection and have suggested that this is achieved by depleting "un-sequestered" or "accessible" cholesterol from the plasma membrane. Here, Heisler et al provide convincing evidence that this is achieved initially by activation of the enzyme acyl coenzyme A: cholesterol acyltransferase (ACAT also known as Sterol O-acyltransferase, SOAT, not to be confused with acetyl-coenzyme A acetyltransferase) to rapidly reduce plasma membrane accessible cholesterol by conversion of cholesterol to its cholesteryl ester. This is followed by 25HC-induced inhibition of the processing of SREBPs, the master transcription factors for genes of the cholesterol biosynthesis pathway and also the LDL receptor, to maintain cholesterol depletion.

The data presented throughout are solid, however, some of the structures drawn of the oxysterols in Figure 1 are not chemically correct. 24(S)HC is drawn as 24(R)HC and visa versa, also the oxysterol sulfate should have a bond between C-3 and the O of OSO3H. It would also help the reader if the vehicle for oxysterol additions was clarified.<br /> The data presented in Figures 2 and 3 show that inhibition of SREBP processing by 25HC is important for the long-term maintenance of depletion of plasma membrane accessible cholesterol, but I wonder if activation of LXR may also be important here. I appreciate that the data in Figure 2 points against LXR being involved in the rapid depletion of accessible cholesterol in HEK293 cells, but perhaps it is important for the long-term depletion of accessible cholesterol. Could there be some cell type specificity here?<br /> Something that always concerns me when the antimicrobial activity of 25HC is discussed is the fact that 25HC is usually a minor side-chain oxysterol compared to 24(S)HC and 27HC (and 22(R)HC in steroidogenic tissue), except for a short time after infection. Perhaps any long-term antimicrobial activity, and diminishment of accessible cholesterol, results from these other side-chain oxysterols. This may be worthy of some additional discussion.

In summary, the authors present a convincing model for the depletion of accessible cholesterol by oxysterols and their involvement in antimicrobial activities.

Reviewer #1 (Public Review):

This work provides a new multimodal blastocyst evaluation method utilising both blastocyst images and patient couple's clinical features (e.g., maternal age, hormone profiles, endometrium thickness, and semen quality) to predict live birth outcomes.<br /> The manuscript was reviewed using the checklist from the "Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): The TRIPOD statement" (https://www.equator-network.org/reporting-guidelines/tripod-statement/ ). Generally, the authors have achieved their aims, and the results support their conclusions.

The major study strengths are as follows:

The study dataset consists of a huge amount (17,580) of blastocysts with known live birth outcomes, as well as blastocyst images, and data included the clinical features of couples.<br /> The authors developed a new artificial intelligence model consisting of a convolutional neural network to process blastocyst images and a multilayer perceptron to process patient couple's clinical features. This model demonstrated an AUC of 0.77 for live birth prediction, which is significantly higher than that achieved by the previously developed models. The conclusions of this paper are mainly well supported by the data.

Nevertheless, there are some weaknesses:

Regarding testosterone, the method of testosterone assessment is essential. The statistical significance of testosterone as a predictor could change when calculated free T or bioavailable testosterone is used.

According to the data presented in Supplementary Table 1, there are more than 15 statistically significant predictors of live birth. However, the value of predictive significance is presented only for 15 (Fig. 3).

Reviewer #1 (Public Review):

Chen and colleagues report the results of 3 experiments assessing how one or both eyes open under a patch influence resting EEG activity, contrast sensitivity, and binocular balance in normally sighted subjects. They found that keeping an eye open (as opposed to closed) under a patch enhances contrast sensitivity and evoked responses through the unpatched eye as well as interocular shifts in contrast sensitivity and binocular balance in favor of the patched eye once the patch is removed. These results suggest that the state of eye opening temporarily, but significantly, influences shifts in ocular dominance with relevance for treatment of binocular visual disorders such as amblyopia that are treated with periodic monocular occlusion.

Strengths:<br /> 1. Elegant simplicity in study design.<br /> 2. Well-designed and executed psychophysical assessments of contrast sensitivity and binocular balance. More than one assay for binocular balance is used.<br /> 3. Cross-modality relationships are analyzed and support the underlying hypothesis.

Weaknesses:<br /> 1. The investigators demonstrate an effect of eye open status under the patch on occipital oscillatory activity, but subsequent results cannot be directly attributed to these changes since occipital oscillation are not directly manipulated. Therefore, the extent to which the oscillatory activity in visual cortex mediates differential open versus closed eye effects on contrast sensitivity and binocular balance cannot be concluded based on these data alone.<br /> 2. Long-term effects produced or enabled through open or closed eye patching are not reported, limiting translational potential for visual disorders such as amblyopia.

Reviewer #1 (Public Review):

The contribution of disease-specific factors to the capacity of iPSCs for chondrogenic differentiation is unknown. A better understanding of the underlying mechanism will facilitate approaches to design more effective therapies and interventions to benefit cartilage regeneration.<br /> The authors adequately characterized the stemness of OA-derived iPSC clones compared with previously generated healthy iPSC (AC-iPSCs) based on accepted molecular markers, progenitor properties, and chondrogenic potential pointing to undifferentiated pluripotent phenotype. Clones from AC and OA-iPSCs were then successfully differentiated into mesenchymal progenitor intermediates and displayed similar phenotype characteristics. Immunophenotypic analyses were also performed and confirmed the expression of typical MSC markers in both population progenitors and the lack of hematopoietic and endothelial markers. In terms of multipotency, both iMSCs differentiated into OBs, adipocytes, and chondrocytes, although AC-iPSCs displayed enhanced chondrogenic potential compared with OA-iPSCs. This was confirmed in the chondrogenic differentiation assay using the pellet culture method and 3D-micromass culture wherein iPSCs derived from healthy chondrocytes displayed significantly higher chondrogenic potential compared with OA-iPSCs. The authors logically concluded that the reduced ECM generation by OA-iMSCs is likely due to retention (or memory) of OA phenotype of the original cell source.

RNA-seq analysis of the transcriptome of both AC and OA-iPSCs revealed significant differences between the two cell clones. Similarly, PC analysis suggested that the two populations are genomically distinct. Enrichment of GO terms and KEGG pathway analysis revealed metabolic pathways, epigenetic regulation, and chromatin organization are mostly enriched in AC-iPSCs. These findings suggested that metabolic and epigenetic pathways in AC cells support enhanced chondrogenic differentiation. It should be also noted that the profile of metabolic and epigenetic gene networks exhibited significant differences not only in the terminally differentiated cells but also in the undifferentiated state, further highlighting their distinct chondrogenic potential.

Altogether, using advanced pan-transcriptomic analyses, the authors convincingly demonstrate that distinct expression signature of epigenetic and metabolic marks was detected in healthy iPSCs different from OA-derived iPSCs.

The Implication of epigenetic pre-disposition in OA-iPSC is critically important for designing appropriate strategies to control chondrogenesis and potential cartilage regenerative approaches.

Reviewer #1 (Public Review):

Sorkac et al. devised a genetically encoded retrograde synaptic tracing method they call retro-Tango based on their previously developed anterograde synaptic tracing method trans-Tango. The development of genetically encoded trans-synaptic tracers has long been a difficult stumbling block in the field, and the development of trans-Tango a few years back was a breakthrough that was immediately, widely, and successfully applied. The recent development of the retrograde tracer method BActrace was also exciting for the field, but requires lexA driver lines and required by its design the test of candidate presynaptic neurons instead of an unbiased test for connectivity.

Retro-Tango now provides an unbiased retrograde tracer. They cleverly used the same reporter system as for trans-Tango by reversing the signaling modules to be placed in pre-synaptic neurons instead of post-synaptic neurons. Therefore, synaptic tracing leads to the labeling of pre-synaptic neurons under the regulation of the QUAS system. Using visual, olfactory as well sexually dimorphic circuits authors went about providing examples of specificity, efficiency, and usefulness of the retro-Tango method. The authors successfully demonstrated that many of the known pre-synaptic neurons can be successfully and specifically labelled using the retro-Tango method.

Most importantly, because it is based on the most used, very well tested and widely adopted trans-Tango method, retro-Tango promises to not just be a clever development, but a really widely and well-used technique as well. This is an outstanding contribution.

Reviewer #1 (Public Review):

The authors in this manuscript investigate the effect of co-substrate cycling on the metabolic flow. The main finding is that this cycling can limit the flux through a pathway. The authors examine implications of this effect in different simple configurations to highlight the potential impact on metabolic pathways. Overall, the manuscript follows logical steps and is accessible. Once the main point-reduction in flux of a pathway with limited pool of a cycled co-substrate-is established, some of the following steps become expected (e.g. the fraction of the flux in a branched pathway). Nevertheless, it is understandable that the authors have picked a few simple examples of the metabolic network motifs to highlight the implications. The results presented in the manuscript overall support the conclusions. One weakness is that some of the details of the assumptions (e.g. the choices of rates) are not explicitly spelt out in the manuscript. This work is impactful because it brings into light how cycling of some of the intermediates in a pathway can influence metabolic fluxes and dynamics. This is a factor in addition to (and separate from) reaction rates which are often considered as the main driver of metabolic fluxes.

Reviewer #1 (Public Review):

This study analyses associations between different blood groups and 1,312 hospital diagnosis codes, among >480,000 Danish patients who had their blood type determined in hospitals. While biological relationships between blood types and disease are of substantial interest, unfortunately, the analyses do not adjust for ethnicity (which is correlated with both blood types and many diseases). Thus it is unclear to which extent disease associations represent relationships with the blood types, as opposed to possible differences in disease incidence or severity between people with different ethnic backgrounds (which could also be due to socioeconomic differences as well as any other factors correlated with ethnicity).

Reviewer #1 (Public Review):

It has recently been shown that the HIV-1 protease can cleave and activate the inflammasome-forming sensor CARD8 upon treatment of infected cells with non-nucleoside reverse-transcriptase inhibitors (Wang et al., Science 2021). Here, Kulsuptrakul and colleagues show that the high susceptibility to proteolytic activation by the HIV-1 protease is a specific feature of human CARD8. They show that changes in human-specific F-F motif render the CARD8 protein of non-human primates largely resistant to cleavage. Interestingly, the protease of SIVcpz the direct precursor of pandemic HIV-1 strains are also capable of cleaving human but not chimpanzee CARD8. Thus, the authors propose that a human-specific CARD8 motif may contribute to the increased levels of inflammation and disease progression in HIV-infected humans compared to non-human primates that are naturally infected with SIV.

Strengths of the study are that the authors convincingly show that a single human-specific amino acid change in CARD8 determines its susceptibility to cleavage by the HIV-1 protease and that the results shown are well controlled and presented. It is also interesting that SIVcpz can cleave human CARD8 and activate an inflammatory response. The major weakness is that it remains unclear whether HIV-1 of SIVcpz may induce CARD8-dependent inflammatory responses in primary CD4+ T cells or macrophages. The most relevant setting in the study was the infection of THP-1 cells with the T cell line-adapted X4-tropic HIV-1 LAI molecular clone. However, the effects on cell death were modest (Figure 3A) and on IL-1ß secretion was not dose-dependent (Figure 3B). Altogether, stronger effects were observed with VSV-G-pseudotyped HIV-1 and only those were used in subsequent experiments involving human CARD8 cleavage mutants (Figure 4). Additional evidence that primary HIV-1 molecular clones and/or SIVcpz may indeed induce CARD8-dependent inflammatory responses in primary viral target cells would greatly increase the significance of the study. In the absence of such data, conclusions about the potential role of CARD8 sensing of the viral protease for the pathogenesis of AIDS should be cautioned throughout.

Reviewer #1 (Public Review):

In this study, Moulana et al. measured the binding affinity of four antibodies, Ly-CoV016, REGN10987, Ly-CoV555, and S309, against ~30,000 RBD variants that represent the possible intermediates between the ancestral SARS-CoV-2 RBD and Omicron BA.1 RBD. Mutational pathway to antibody escape and the importance of epistasis in antibody binding were examined. By comparing the data here with a previous study by the same authors (ref 23), the authors also conclude that escape mutations with deleterious effects on ACE2 affinity can be compensated by Q498R and N501Y. Overall, the results are clearly presented and provide important insights into antibody escape.

Reviewer #1 (Public Review):

The therapeutic effects of NSC transplantation is limited by the low survival and differentiation rates of NSCs due to the harsh environment in the brain after ischemic stroke. To solve this technical challenge, the authors employed NSCs derived from human induced pluripotent stem cells (iPSCs) together with NSC-derived exosomes extracted from NSCs to treat cerebral ischemia induced by middle cerebral artery occlusion/reperfusion (MCAO/R) in mice. In the current study, the authors attempt to demonstrate that NSC-derived exosomes could act as a supportive adjuvant for NSC transplantation after stroke. They showed that NSC-derived exosomes significantly reduced the inflammatory response, alleviated oxidative stress after NSC transplantation, and facilitated NSCs differentiation in vivo. The combination of NSCs with exosomes ameliorated the injury of brain tissue including cerebral infarct, neuronal death and glial scarring, and promoted the motor function recovery. To explore the underlying mechanisms, they analyzed the miRNA profiles of NSC-derived exosomes and the potential downstream genes. Overall, the study provided solid rationale supporting the application of exosomes during stem cell-based therapy. The data quality is good and convincingly supports the major claims. The impact is high for the NSC-transplantation for treating various neurological diseases.

Reviewer #1 (Public Review):

RNA-based self-replication systems might have been concentrated and compartmentalized with peptides by forming droplet-like complexes before the emergence of cellular organisms enveloped by lipid membranes. This report clearly shows that the physical properties of such droplets (phenotypes) can be affected by the activities of a ligase ribozyme in the droplets. This suggests that sequences of such ribozymes (genotypes) might have been selected not only for their direct activities (e.g., elongation of RNA) but also for their indirect effects on the droplet phenotypes (e.g., more viscous/solid droplets formed by the elongated RNAs) on the ancient earth. However, the exact requirements (e.g., average/maximum length of the ligated RNAs + double strand formation) for such phenotypic changes are not assessed in this report. It is not demonstrated whether the droplet property changes caused by the ribozyme activity can be advantageous for the survival of the RNA-based system (e.g., for the ribozyme activity itself). Follow-up studies would be desired to clarify these points and the true values of this report.

Reviewer #1 (Public Review):

After giving a very accessible introduction to cellular processes during brain development, the authors present the computational model used in this study. It combines the kinematics of cell proliferation with the mechanic of brain tissue growth and is essentially equal to their model presented in Zarzor et al (2021), but extended for the outer subventricular zone (OSVZ), see for example Figs. 2 in the present manuscript and in Zarzor et al (2021). This zone, which is specific to humans, provides a second zone of cell proliferation. The division rate in the OSVZ is smaller and at most equal to that in the ventricular zone.

The authors present two main findings: The distance between sulci in the cortex is decreased whereas the cell density in the ventricular zone is increased in presence of the OSVZ. Furthermore, the "folding evolution", which is the ratio between the outer perimeter at time t and the initial perimeter increases in presence of the OSVZ. The strongest effect is seen, when division rates in both proliferating zones are equal. The authors compare the cases of varying and constant cortical stiffness, which they had also done in Zarzor et al (2021). Finally, they consider the feedback of cortical folding on OSVZ thickness.

The computational model provides a sound description of how cell proliferation and migration combined with tissue mechanics yield cortical folding patterns. However, only a few parameter values are varied in a limited range. Also, it remains unclear to me, how important the specific functional dependencies of, for example, the cell division rate on the radial coordinate are. This point seems of particular importance because the effect of the presence of the OSVZ on the folding patterns seems rather minute, see Fig. 5. The authors do not propose experiments that could be used to test their description and results. Finally, the analysis is restricted to 2 dimensions.

Reviewer #1 (Public Review):

In this work, Roche et al. study a 13-year long time series of microbiome samples from wild baboons from Kenya. The data used in this work challenge a previous finding from the same authors that temporal dynamics in microbiome changes are largely individualized. Using a multinomial logistic-normal modeling approach, the authors detect that co-variance in temporal dynamics in microbial pair-wise associations among individuals occurs more frequently between relatives. Furthermore, the authors identify that microbial phylogenetic proximity is associated with consistent co-abundance changes over time and that their metric of universal microbial relationships is robust across hosts and is detected even in human longitudinal data. The authors conduct a thorough statistical revision of publicly available results, highlighting this time (e.g. compared to Björk et al, doi: 10.1038/s41559-022-01773-4) the consistently shared microbial properties between individuals, rather that the individual microbial signatures highlighted in their previous work.

Strengths:<br /> This work is foundational in its compelling effort to generate a rigorous method to evaluate co-abundance dynamics in longitudinal microbiome data. The approach taken will likely inspire developments that will sharpen the capacity to extract co-varying microbial features, taking into account seasonality, diet, age, relatedness, and more. To the best of my understanding, their hierarchical model integrated into the Gaussian process to analyze microbial dynamics is reasonably robust and they clearly explain the implementation. Furthermore, this work introduces and defines the concept of a universality score for microbial taxon pairs.<br /> Overall, the work presented is clear and convincing and provides tools for the community to benefit from both methods and results. Furthermore, conceptually, this work stresses the value of consistent and shared microbial dynamics in groups, which enriches our understanding of host-associated microbial ecology, otherwise understood to be largely dependent on external fluctuations.

Weakness:<br /> It is not entirely clear the extent to which the presented results revise, refute, or support the previously published analysis performed by the authors on the same dataset (doi: 10.1038/s41559-022-01773-4), which was more focused on individuality.

Reviewer #1 (Public Review):

The synaptonemal complex (SC) is a meiosis-specific tripartite chromosome structure for chromosome synapsis and regulates crossover formation essential for proper chromosome segregation during meiosis. In this interesting paper, the authors studied the dynamic behavior of two components of SC central regions, SYP-2 and SYP-3, in both oocytes and spermatocytes in C. elegans and also the effect of the dosage of the proteins on meiotic recombination and found sex-dimorphic and/or SYP-2/3 dosage sensitive dynamics of the SC components and proteins involved in crossover formation on the meiotic chromosomes, suggesting the intimate relationship between SC central regions and meiotic recombination.

Reviewer #1 (Public Review):

The authors set out to achieve two overarching objectives: 1) to demonstrate that BAFF is a bona fide senescence-associated factor and 2) to expand the field's understanding of senescence outcomes across cell types and models. By inducing senescence in a multitude of ways and across cell culture and animal models, the authors demonstrate that BAFF is robustly upregulated in response to senescence induction. Beyond mere association, by knocking down, overexpressing, or ectopically adding BAFF, the authors demonstrate that various senescence-associated phenotypes can be altered, suggesting that it is an effector of the senescent state. Moreover, by comparing transcriptomic and proteomic profiles in two very different types of cells-diploid WI-38 human fibroblasts and cancerous THP-1 monocytes-the authors identify two parallel trajectories, one involving p53 and one involving NF-kB.

Although trajectory differences may stem from cell type differences, it is possible that the cancerous vs non-cancerous status of the cell lines used may be a more important variable in this case. One question the reader may be left with is: would the two trajectories be different if non-cancerous monocytes with intact p53 were profiled?

Regardless, this study establishes a precedent for characterizing senescence responses in additional cell types of either healthy or diseased origin. Though a number of technical and statistical issues exist in the current version of the manuscript (i.e. use of only a single reference gene for RT-qPCR and inconsistent fold change thresholding in RNA-seq analyses), the results appear robust enough to remain statistically significant after modification. Moreover, many analyses are carried out at both the transcriptomic and proteomic levels with consistent results, highlighting the robustness of their observations.

Ultimately, the results strongly suggest that BAFF plays a senomorphic role in senescence, modulating downstream senescence-associated phenotypes, and may be an interesting candidate for senomorphic therapy.

Reviewer #1 (Public Review):

Cryo-EM structures of respiratory complex I have in recent years have a large impact on our understanding of its mechanism, regulation, assembly, and evolution. However, the coupling mechanism of complex I is still not clear, and controversies exist about whether certain conformations are part of the catalytic cycle or arise from the deactivation of the enzyme. Padavannil and colleagues now add to the story with the first structures of insect complex I, from the model organism Drosophila melanogaster. One of the rationales for choosing this organism is that it lacks the active-to-deactive (A-to-D) transition that prevents the enzyme from going in reverse, which should make the interpretation of any different conformations more straightforward.

The authors showed that the A-D transition seen in mammals and fungi was indeed not present in Drosophila complex I and they determined the cryo-EM structure. In contrast to especially mammalian complex I, which is often found in an "open" and a "closed" state, there was only a single conformation. Drosophila complex I has lost two accessory subunits compared to the mammalian complex, and several other subunits have lost or gained elements, with possible implications for the assembly, stability, or regulation of the complex. The interface of the two peripheral and membrane arms was poorly resolved. A focused classification on this region yielded distinct structures, differing in the angle of the two arms and in the presence or absence of an alpha helix at the N terminus of subunit NDUFS4 (the "lock helix"), a region that is not present in mammalian or yeast complex I. The authors observe a transition between two states named "closed" and "locked open" and speculate that the transition constitutes a deactivation mechanism in insect complex I.

The conclusions of the paper are for the most part solid and supported by the data. Only the interpretation of the significance of the "lock helix" is not convincing: without any evidence, it is assumed to be a regulatory element responsible for an off-pathway deactive state. The nomenclature "closed" and "locked open" is unfortunate, as most of the structural features that differ between the states are reversed compared to the mammalian closed and open states: the disorder of several loops in the quinone binding regions and the presence of absence of a π bulge in helix 4 of the ND6 subunit. Thus, the "locked open" state, which the authors assign as an off-pathway resting state, shares the features of the mammalian closed state, which in all catalysis models is considered an "active" state. An especially important feature in the closed state is the alpha-helical conformation of ND6-helix 4, which has been shown to support a water wire connection from the Q site to the membrane arm, suggesting a role in proton transfer. Conversely, all structures considered as possible D states in mammalian or yeast complex I are open and show disordered loops and a π bulge. These features as shared by the "closed" state of Drosophila, which is however assumed to be on-pathway.

Reviewer #1 (Public Review):

Most previous studies about burn injuries only considered systemic inflammation with analyses of blood specimens from patients. The current study is unique in the fact that it utilizes skin samples. The authors used single-cell analyses by flow cytometry and RNA-seq to characterize in detail the different T-cell populations. The differences are striking. Burned skins have higher degrees of CD69-negative T cells, which indicates that these are recruited from probably blood circulation. They are also substantially more responsive to stimulation by producing higher amounts of immunologic molecules, such as IFNG and TNFA. The results are compelling because they indicate that following burn injury, T cells infiltrate the lesions to potentially protect the damaged tissue from secondary infections.

However, there is an important aspect missing. What does induce T-cell infiltration into the burned skins? A potential explanation is that resident myeloid cells directly or indirectly promote chemokine-mediated recruitment of T cells.

Another important consideration is the impact on other leukocyte populations. While the study is well focused on T cells, the immune system consists of a complex network of cells and molecules that interact with each other. The study does not address myeloid cells and innate lymphoid cells, which could also play important roles and display altered functions in burned injuries.

Nevertheless, the study provides important information about the "activation" statuses of several T cell populations following burned injuries and could help guide the development of better treatments.

Reviewer #1 (Public Review):

The authors studied Eurasian perch in an experimental setup facilitated by a nuclear cooling plant to provide a natural laboratory. The heated area of the ecosystem raised in temperature by 8 degrees centigrade, while a reference area remained unheated. The authors provide a thorough and convincing description that the two areas are segregated such that individuals could not escape from one area to another prior to 2004, and such use data only until 2003 to test their hypotheses. The authors used both length-at-catch and age-increment data in a series of Bayesian mixed effects models to estimate the growth rate and length-at-age. They find that in the warmed area, both younger, smaller fish and older adults grew faster, contrary to the prediction of the temperature-size rule as well as many predictions and observations from other systems that fish reach smaller terminal body sizes in warmer environments due to increased metabolic demands. The authors furthermore combine the estimated body sizes with a mortality rate to determine the size-spectrum slope for both areas and determine the increased growth and increased mortality combine to essentially leave the size-spectrum slope observed in the ecosystem unchanged.

This is a thorough and interesting paper presented clearly and succinctly. These authors present a strong and thorough analysis of how temperature affects growth when all other ecosystem factors remain unchanged in a population. The dataset is a powerful one to support this type of analysis, and the statistical analysis methods the authors used appear to be robust and thorough. The diagnostics and visualizations are complete and inspire confidence in the convergence and accuracy of the modeling approach. The use of the size spectrum exponent to roll up individual-level changes across the population into a single metric was useful and interesting.

The estimates of the von Bertalanffy growth parameters in the results and discussion are less convincing than the growth increment and length-at-age estimates which seem much more robust. The presentation of estimates of the von Bertalanffy growth parameters in Figure S6 exhibit the high negative correlation between the k and L infinity parameters that are typical whenever multiple VBGF models are fit to subsets of data. It is difficult to determine which changes in parameters correspond to actual differences in early vs late life stage growth when, in any given year, if k is estimated low, L infinity will skew high simply due to the model structure. An example of this can be seen in 1995-1997 where L infinity is quite high but k is estimated quite low concurrently - in this case, it seems more reasonable to conclude the likelihood surface is quite flat between different parameter values than that fish suddenly reached a larger asymptotic size in these three years than all of the rest. The data in this case so strongly show larger growth in the heated area even without the VBGF results, and it would be more credible to base the discussion and results of this paper on the growth rate or observed length-at-age (e.g. Figure S4) estimates which are so clear.

Reviewer #1 (Public Review):

Caetano and colleagues describe the changes caused by periodontal inflammation in terms of tissue structure and provide additional evidence to understand the involvement of fibroblasts in altering the immune microenvironment.

While interesting and a concise study, the authors should improve their work on two major points:

1. To improve the resolution, the authors introduced a method that addresses improving the resolution by combining more information from the neighbour structure and the existing database. This raises the question of whether the lack of previous gingival tissue spatial transcriptome sequencing results weakens the reliability of this method. Does it miss the identification of some gingival tissue-specific cells? Is the failure to match two populations of fibroblasts between single-cell sequencing and spatial transcriptome sequencing of gingival tissue fibroblasts related to this?

2. Although the authors did the identification of the captured tissues, the results seem to require more analysis. Take Figure 5A as an example, there is a clear overlap between endothelial cells and basal cells. In addition, it is suggested that the authors indicate the specific location of the 10 clusters of cells in Figures 1D and 2C.

Reviewer #1 (Public Review):

In this manuscript, the authors employed an adult-trained variational autoencoder deep learning model on a relatively large sample (over 700) of human fetal-neonatal resting fMRI data to enhance the individual non-linear compression of functional activity patterns of baby brains. This approach showed better performance in the reconstruction of functional fluctuation maps, age prediction accuracy, and age prediction generalizability in fetal and neonatal fMRI data compared with conventional linear models such as spatial independent component analysis. This method also revealed distinct baby brain functional networks spanning primary and high-level systems.

This is an inspired attempt to represent non-linear changes in fetal-neonatal brain fMRI data. Considering the high noises and inconsistent functional spatial distributions in baby fMRI images, stable and sensitive feature extraction approaches are urgently needed in the field of early brain studies. This work is well designed and well written in general.

Reviewer #1 (Public Review):

By performing immunopeptidomics of macrophages infected with virulent M. tuberculosis, the authors were able to appropriately address whether Mtb proteins are able to enter the MHC-I antigen processing pathway. Their interrogation provides convincing evidence that substrates of Mtb's type VII secretion systems (T7SS) are a significant contributor to the Mtb-derived peptides presented on MHC-I. Compelling data are provided to demonstrate that ESX-1 activity is required for the MHC-1 presentation of these newly identified peptides.

Strength:

Employing a virulent strain of Mtb for infection of human monocyte-derived macrophages to identify Mtb proteins that access the MHC-I antigen processing pathways and the associated mechanisms.

Weakness:

The immunogenicity of at least some of the identified peptides should have been evaluated.

Reviewer #1 (Public Review):

The accessory protein Orf3a from severe acute respiratory syndrome coronavirus (SARS-CoV-1 or SARS-CoV-2) was initially suggested to be a viroporin and function as a cation channel. In this study, Miller et.al performed a comprehensive structural and functional investigation of SARS-CoV-2 Orf3a utilizing a multidisciplinary approach, including extensive electrophysiological analysis using different systems and determination of multiple single-particle EM structures of the protein under different conditions. Their findings demonstrated that Orf3a has no channel function and is unlikely to be a viroporin. In addition, they tried, but failed to record any channel activity of Orf3a claimed in other studies. They demonstrated that large single-channel currents measured from vesicle-reconstituted Orf3a are due to transient membrane leakiness caused by high protein/lipid ratio and/or channel contamination. Furthermore, they found that SARS-CoV-2 Orf3a, but not SARS-CoV-1 Orf3a, interacts with VPS39, a host HOPS protein involved in autophagosome/late endosome fusion with the lysosome. They proposed that the interaction between SARS-CoV-2 Orf3a and VPS39 may function to assist with SARS-CoV-2 exit and host intracellular immune evasion. This is a meticulously executed research work. I appreciate the tremendous effort the authors spent in the study to clarify some misconceptions related to the role and function of Orfsa from coronavirus.