Reviewer #2 (Public Review):

Summary: The authors seek to elucidate the early evolution of cnidarians through computer modeling of fluid flow in the oral region of very small, putative medusozoan polyps. They propose that the evolutionary advent of the free-swimming medusoid life stage was preceded by a sessile benthic life stage equipped with circular muscles that originally functioned to facilitate feeding and that later became co-opted for locomotion through jet propulsion.

Strengths: Assumptions of the modeling exercise laid out clearly; interpretations of the results of the model runs in terms of functional morphology plausible. An intriguing investigation that should stimulate further discussion and research.

Weaknesses: Speculation on the origin of the medusoid life stage in cnidarians heavily dependent on prior assumptions concerning the soft part anatomy and material properties of the skeleton of the modeled fossil organism that may be open to alternative interpretations.

Reviewer #2 (Public Review):

This is a thorough and convincing body of work that represents an incremental but significant improvement on iterations of this method of CRISPR-based Sterile Insect Technique ('pgSIT'). In this version, compared to previous, the authors target more genes than previously, in order to induce both female inviability (targeting the genes intersex and doublesex, compared to fem-myo previously) and male sterility (targeting a beta-tubulin, as previously in the release generation.<br /> The characterization of the lines is extensive and this data will be useful to the field. However, what is lacking is some context as to how this formulation compares to the previous iteration. Mention is made of the possible advantage of removing most females, compared to just making them flightless (as previously) but there is no direct comparison, either experimental, or theoretical i.e. imputing the life history traits into a model. For me this is a weakness, yet easily addressed. In a similar vein, much is made in alluding to the 'safety concerns of gene drive' and how this is a more palatable half-way house, just because it has CRISPR component within it; it is not. It would be much more sensible, and more informative, to compare this pgSIT technology to RIDL (release of insects carrying a dominant lethal), which is essentially a transgene-based version of the Sterile Insect Technique, as is the work presented here.

The authors achieve impressive results and show that these strains, under a scenario of high levels of release ratios compared to WT, could achieve significant local suppression of mosquito populations. The sensitivity analysis that examines the effect of changing different biological or release parameters is well performed and very informative.

The authors are honest in acknowledging that there are still challenges in bringing this to field release, namely in developing sexing strains and optimizing release strategies - a question I have here is how to actually release eggs, and could variability in the efficiency of this aspect be modelled in the sensitivity analysis? It seems to me like this could be a challenge and inherently very variable.

Reviewer #2 (Public Review):

The authors were trying to survey reservoir viral sequences in different anatomical sites in the body, with the brain being of special interest. This is a study that is technically demanding and here is well done, providing insights that prompt new and more sophisticated questions.

The authors use end-point dilution PCR to identify individual proviruses that can then be sequenced with high accuracy. These are high quality data sets but given the technical requirements of this approach the number of sequenced proviruses is limiting given the scope of questions this study addresses. Nonetheless, there is a lot of data here to draw many useful conclusions.

It will be important to realize how clones of infected T cells can move around the body, including into the CNS compartment. It will also be important to remember that there are limits in sampling depth of proviruses in any one tissue meaning the failure to detect something has a limit in sensitivity of detection when trying to interpret a negative result.

As noted in the next section, it is important to emphasize that there is another entry phenotype beyond X4 that will ultimately be important in interpreting these results. Macrophage-tropic viruses are often found in the CNS compartment and it will be important to understand whether these CNS-derived sequences are macrophage-tropic viruses there infecting macrophages and microglia or if they are all T-tropic viruses brought in by wandering infected T cells (or both).

Reviewer #2 (Public Review):

Summary:<br /> In the current study, the authors tested the hypothesis that Aβ42 toxicity arises from its proven affinity for γ-secretases. Specifically, the increases in Aβ42, particularly in the endolysosomal compartment, promote the establishment of a product feedback inhibitory mechanism on γ-secretases, and thereby impair downstream signaling events. They showed that human Aβ42 peptides, but neither murine Aβ42 nor human Aβ17-42 (p3), inhibit γ-secretases and trigger accumulation of unprocessed substrates in neurons, including (CTFs of APP, p75 and pan-cadherin. Moreover, Aβ42 dysregulated cellular homeostasis by inducing p75-dependent neuronal death. Because γ-secretases process many other membrane proteins, including NOTCH, ERB-B2<br /> receptor tyrosine kinase 4 (ERBB4), N-cadherin (NCAD) and p75 neurotrophin receptor (p75-NTR), revealing a broad range of downstream signaling pathways, including those critical for neuronal structure and function. Hence, they propose to identification of a selective role for the Aβ42 peptide, and raise the intriguing possibility that compromised γ-secretase activity against the CTFs of APP and/or other neuronal substrates contributes to the pathogenesis of AD. Overall, the data are not very convincing to support the main claim.

Strengths.

Different in vitro and cellular approaches are employed to test the hypothesis.

Weaknesses.

The experimental concentrations for Aβ42 peptide in the assay are too high, which are far beyond the physiological concentrations or pathological levels. The artificial observations are not supported by any in vivo experimental evidence.

Reviewer #2 (Public Review):

The authors describe the synthesis and testing of the anti-cancer activity of a new molecule CK21 against pancreatic cancer mouse models. This part of the study is very strong showing regression of pancreatic tumors at non-toxic concentrations, which is very hard to achieve for practically uncurable pancreatic cancer. Authors synthesized CK21 as an analog of a known inhibitor of RNA synthesis which is very toxic. The authors did very little attempt to understand whether the mechanism of anti-cancer efficacy of CK2 is similar to this known inhibitor of transcription or not. One cannot compare gene expression profiles between untreated and CK21-treated cells, taking into account that CK2 may inhibit the expression of all genes. The effect of CK2 on general transcription needs to be tested first, and then based on this data absolute changes in the expression of genes may be considered for the revealing of the mechanism of activity of CK21.

Reviewer #2 (Public Review):

In this manuscript, Ruesseler and colleagues use a continuous task to examine how neural correlates of decision-making change when subjects face conditions with different durations and frequencies of occurrence of signals embedded in noise. The authors develop a novel task where subjects must report the direction of relatively sustained (3 or 5 s) signal changes in average coherence of a random dot kinetogram that are intermittent among relatively transient noise fluctuations (<1 s) of motion coherence that is continuous. Subjects adjust their behavior to changes in the duration of signal events and the frequency of their occurrence. The authors estimate a decay time constant of leaky integration of evidence based on the average coherence leading up to decision responses. Interestingly, there is considerable inter-subject variability in decay time constants even under identical conditions. In addition, the average time constants are shorter when signal periods occur more frequently as opposed to when they are more rare. The authors use EEG to find that a component of the Centroparietal Positivity (CPP) regressed to the magnitude of changes in the noise coherence is larger in conditions when the signal periods occur less frequently. Using a control condition, the authors show that this component of the CPP is not simply based on surprise because it is smaller for changes in motion coherence in irrelevant directions with matched statistics as the changes in relevant directions. The authors also find that a different component of the CPP related to the magnitude of the motion coherence co-varies with the inter-subject variability in decay time constants estimated from behavior.

Overall, the authors use a clever experimental design and approach to tackle an important set of questions in the field of decision-making. The manuscript is easy to follow with clear writing. The analyses are well thought-out and generally appropriate for the questions at hand. From these analyses, the authors have a number of intriguing results. So, there is considerable potential and merit in this work. That said, I have a number of important questions and concerns that largely revolve around putting all the pieces together. I describe these below.

1) Quite sensibly, the authors hypothesize that "decay time constant" for past evidence and "decision threshold" would be altered between the different task conditions. They find clear and compelling evidence of behavioral alterations with the conditions. They also have a method to estimate the decay time constant. However, it is unclear to what extent the decision threshold is changing between subjects and conditions, how that might affect the empirical integration kernel, and how well these two factors can together explain the overall changes in behavior.

To be more specific, the authors state that the lower false alarm rates and slower reaction times for the LONG condition are consistent with a more cautious response threshold for LONG. The empirical integration kernels lead to the suggestion that the decay time constant is not changing between SHORT and LONG, while it is changing between FREQUENT and RARE. Does the lack of change in false alarm rate between FREQUENT and RARE imply no change in the decision threshold? Is this consistent with the behavior shown in Figure 2? I would expect that less decay in RARE would have led to more false alarms, higher detection rates, and faster RTs unless the decision threshold also increased (or there was some other additional change to the decision process). The CPP for motor preparatory activity reported in Fig. 5 is also potentially consistent with a change in the decision threshold between RARE and FREQUENT. If the decision threshold is changing, how would that affect the empirical integration kernel? These are important questions on their own and also for interpreting the EEG changes.

2) The authors find an interesting difference in the CPP for the FREQUENT vs RARE conditions where they also show differences in the decay time constant from the empirical integration kernel. As mentioned above, I'm wondering what else may be different between these conditions. Do the authors have any leverage in addressing whether the decision threshold differs? What about other factors that could be important for explaining the CPP difference between conditions? Big picture, the change in CPP becomes increasingly interesting the more tightly it can be tied to a particular change in the decision process.

I'll note that I'm also somewhat skeptical of the statements by the authors that large shifts in evidence are less frequent in the RARE compared to FREQUENT conditions (despite the names) - a central part of their interpretation of the associated CPP change. The FREQUENT condition obviously has more frequent deviations from the baseline, but this is countered to some extent by the experimental design that has reduced the standard deviation of the coherence for these response periods. I think a calculation of overall across-time standard deviation of motion coherence between the RARE and FREQUENT conditions is needed to support these statements, and I couldn't find that calculation reported. The authors could easily do this, so I encourage them to check and report it.

3) The wide range of decay time constants between subjects and the correlation of this with another component of the CPP is also interesting. However, in trying to interpret this change in CPP, I'm wondering what else might be changing in the inter-subject behavior. For instance, it looks like there could be up to 4 fold changes in false alarm rates. Are there other changes as well? Do these correlate with the CPP? Similar to my point above, the changes in CPP across subjects become increasingly interesting the more tightly it can be tied to a particular difference in subject behavior. So, I would encourage the authors to examine this in more depth.

Reviewer #2 (Public Review):

The study by Yang et al. examines the interactions between a model host, the nematode C. elegans, and its gut bacteria during aging, focusing on how the host responds to progressing bacterial colonization. In a sense, this work follows up on a previous report describing the activation of DAF-16 in middle-aged worms. Here they test the importance of DAF-16 for aging-dependent accumulation of E. coli in the worm gut, as a model for responses to, and mitigation of, dysbiosis, which in humans is associated with pathology.

The mechanism unraveled in this study includes the sensing of increasing concentrations of indole, a tryptophan metabolite that is secreted by the accumulating gut bacteria, which dependent on the neuronal cation channel TRPA-1 (and NOT through the known indole receptor AHR-1), activates intestinal DAF-16, driving its nuclear translocation and leading to subsequent induction of downstream targets, of which LYS-7 and LYS-8 are essential for diminishing bacterial colonization and mitigating the associated damage.

The authors provide very clean and very strong evidence to support the described mechanism, clean identification of indole as the metabolite responsible for DAF-16 nuclear localization, and good indole supplementation experiments and measurements of indole levels inside of worms to support its function. At the same time, some of the methods are not completely clear - for example, how did the authors obtain pure bioactive fraction to run their NMR analysis and identify indole as the activating molecule (this should be clarified in, or added to the method section); or how were indole supplementation experiments carried out? On solid media, i.e. NGM plates, or in solution; with live bacteria, or heat-killed ones? (this is important for figuring out if indole sensing is from the outside or from the gut); and in a few cases the results appear too clear-cut, like the contribution of lys-7 and lys-8 to controlling gut bacteria - these two lysozymes seem to be sufficient to account for the entire contribution of DAF-16, which is surprising considering the large number of downstream targets this transcription factor has, as well as the very redundant nature of innate immune protection, which would have suggested the partial ability to protect at best; this should be considered and discussed.

Overall, though, the study is strong, and the conclusions are well supported. Given this, its potential impact is high, to inform our understanding of how animals respond to dysbiosis and the mechanisms aimed at mitigating potential detrimental effects of dysbiosis. Here, dysbiosis is manifested as increased colonization of aging worms by bacteria that cannot colonize young adults. In humans, dysbiosis manifests as imbalances in microbiome composition, which may include the proliferation of some gut bacteria at the expense of others. Thus, the mechanisms characterized here, which are conserved in humans, may play similar roles in human pathology and may offer handles to try and mitigate the detrimental effects of dysbiosis.

Reviewer #2 (Public Review):

Hybridization events between species are known to result in substantial genomic upheaval, requiring subsequent coordination between gene copies to ensure proper control of gene expression and embryonic viability. An example of such an event happened over 18 million years ago between two frog species that resulted in Xenopus laevis-an allotetraploid that has largely retained copies of both genes from this event, known as L-alleles and S-alleles. Often, the presence of both copies presents an experimental and bioinformatic hurdle for researchers and is a feature of the biology of X. laevis that renders cross-species comparisons difficult. Phelps et al, however, take advantage of this feature of Xenopus biology and use it to their advantage to ask how the hybridization event in this species altered gene regulatory architecture. They find that a handful of pluripotency genes are largely responsible for activating gene expression in the early embryo, but that L and S alleles are differentially activated in many cases. Moreover, they find extensive differences in cis-regulatory architecture between L/S alleles. Despite these differences in alleles, however, they find that their combined gene expression output is largely conserved, possibly reflecting strong selection pressures acting to maintain gene expression output at specific levels. This work represents a significant advance in how hybridization events are something greatly understudied in developmental biology-influence gene regulatory programs and how evolutionary pressures have shaped these programs in response to such events.

Reviewer #2 (Public Review):

Zou et al. presented a comprehensive study where they generated single-cell RNA profiling of 138,982 cells from 13 samples of six patients including AK, squamous cell carcinoma in situ (SCCIS), cSCC, and their matched normal tissues, covering comprehensive clinical courses of cSCC. Using bioinformatics analysis, they identified keratinocytes, CAFs, immune cells, and their subpopulations. The authors further compared signatures within subpopulations of keratinocytes along with the clinical progression, especially basal cells, and identified many interesting genes. They also further validate some of the markers in an independent cohort using IHC, followed by some knockdown experiments using cSCC cell lines.

The strength of this study is the unique data set they have created, providing the community with invaluable resources to study and validate their findings. However, a lot of analyses were not robust enough to support the claims and conclusions in the paper. More clarification and cross-comparison with polished data are needed to further strengthen the study and claims.

1) Stemness markers were used. The authors used COL17A1, TP63, ITGB1, and ITGA3 to represent stemness markers. However, these were not common classic stemness markers used in cSCC. What is the source claiming these genes were stemness markers in cSCC? TP63 is a master regulator and early driver event in SCC, while COL17A1, ITGB1, and ITGA3 are all ECM genes. The authors need to use commonly well-known stem cell markers in cSCC, e.g., LGR5, to mark stem-like cells.

2) Cell proportion analysis. The authors used the mean proportions to compare different clinical groups for subpopulations of keratinocytes, e.g., Figure 2B, and Figure 5B. This is not robust, as no statistics can be derived from this. For example, from Fig 2A, it is clearly shown there is a high level of heterogeneity of cellular compositions for normal samples. One cannot say which group is higher or lower simply based on mean not variance as well.

3) Basal tumour cells in SCCIS and SCC. To make the findings valid, authors need to compare these cells/populations with the keratinocyte cell populations defined by Ji et al. Cell 2020. Do basal-SCCIS-tumours cells, also in SCC samples, resemble any of the population defined in Ji et al. Ji et al. also had 10 match normal, thus the authors need to validate their findings of SCC vs normal analysis using the Ji et al. dataset.

4) Copy number analysis. Authors used inferCNV to perform copy number analysis using scRNA-seq data and identified CNVs in subpopulations of keratinocytes in SCCIS and SCC. To ensure these CNVs were not artefacts, were some of the CNVs identified by inferCNV well-known copy number changes previously reported in cSCC?

5) Pseudotime analysis lines 308-313. Not sure the pseudotime analysis added much as, as it is unclear two distinct subgroups were identified from this analysis. Suggest removing this to keep it neater

6) Selection of candidate genes for validation using IHC and cell line work. For example, lines 205-206, lines 352-356 and lines 437-441, authors selected several genes associated with AK and SCC to further validate using IHC and cell line knockdown work. What are the criteria for selecting those genes for validation? It is unclear to readers how these were selected. It reads like a fishing experiment, then followed by a knockdown. Clear rationale/criteria need to be elaborated.

7) TME. Compared to keratinocytes populations, the investigation of TME cells was weak. (a) can authors produce UMAP files just for T cells, DC cells, and fibroblasts separately? Figure 7B is not easy to see those subclusters. (b) similar to what was done for keratinocytes, can authors find differentially expressed clusters and genes among the different clinical groups, associated with disease progression? (c) where are the myeloid cell populations, also B cells?

8) Heat shock protein genes line 327-329. HSP signature was well-known to be induced via tissue dissociation and library prep during the scRNA experiment. How could the authors be sure these were not artefacts induced by the experiment? If authors regress their gene expression against HSP gene signatures, would this cluster still be identified?

9) Cell-cell communication analysis. The authors claimed that that cell-to-cell interaction was significantly enhanced in poorly-differentiated cSCC, and multiple interaction pathways were significantly active. How was this kind of analysis carried out? How did the authors define significance? what statistical method was used? these were all unclear. Furthermore, it is difficult to judge the robustness of the cell-cell communication analysis. Were these findings also supported by another method, such as celltalker, and cellphoneDB?

10) Statistics and significance. In general, the detail of statistics and significance was lacking throughout the paper. Authors need to specify what statistical tests were used, and the p-values. It is difficult to judge the correctness of the test, and robustness without seeing the stats.

11) Overall, this manuscript needs a lot of re-writing. A lot of discussion was also included in the results, making it really difficult to read overall. The authors should simplify the results sections, remove the discussion bits, and further highlight and streamline with the key results of this paper.

Reviewer #2 (Public Review):

The manuscript employs multiple approaches, including molecular docking, molecular dynamic simulations, and functional experiments to uncover a distinct uridine diphosphate-sugar-binding site on P2Y14 - a key drug target for inflammation and immune responses. Overall, the manuscript is clearly written and the experimental techniques are well-documented. However, it may benefit from further analysis, particularly in terms of validating the binding pose.

Reviewer #2 (Public Review):

There currently are several hundreds of kinase inhibitors described and available for purchase. However, most of the target the ATP binding site of the protein kinase domain and, since it is pretty well conserved across the whole protein family, it means that the inhibitors are rarely selective, and most are able to simultaneously inhibit several kinases with, sometimes, different binding affinities. In this m/s, the authors present a strategy to combine kinase inhibitors with the aim of reducing off-target effects while preserving the inhibition potency in the intended target. To develop the methodology, the authors have used a set of publicly available data (protein kinase inhibitor set-2, or PKIS-2) containing affinity data on 406 kinases and 645 inhibitors. The authors run a series of simulations suggesting that, in a few cases, the identified combination of inhibitors is superior to the most specific single kinase inhibitor (i.e. show fewer off-target effects while maintaining the inhibition of the on-target). Finally, they test one of these examples in cells using nanoBRET.

The manuscript tackles an interesting problem (i.e. poor selectivity of kinase inhibitors) that, in some cases, has important clinical bearings. The approach is novel, interesting, and well-executed. However, unfortunately, I am not convinced that the strategy presents a real advantage over the most selective inhibitor.

Reviewer #2 (Public Review):

Respiratory chain complexes assemble in higher-ordered structures termed supercomplexes or respirasomes. The functional significance of these assemblies is currently investigated, there are two main hypothesis tested, namely that supercomplexes provide kinetic advantages or structural stability. Here, the authors use the fruitfly to reveal that, while the respiratory chain in the organism normally does not form higher-order assemblies, it does so under conditions when their assembly is impaired. Because the rather moderate increase in supercomplex formation does not change oxygen consumption stimulated by CI or CII substrate, the authors conclude that supercomplex formation has more a structural than a functional role. The main strength of this work is that the technical quality of the experiments is high and that the authors induced defects in respiratory chain assembly through sets of well-controlled genetic models. The obtained data are mostly descriptive using standard approaches and are very well executed. The authors claim that their experiments allow to conclude that the role of supercomplex formation is restricted to a structural role and, hence, exclude a function directly related to electron transport efficiency. However, while the authors can show convincingly that supercomplexes form in the mutants, but not in the wild type, the main questions still remain, namely what is the structural mechanism of supercomplex formation and what is the significance of their formation. Given that the fly system does not show supercomplex formation under normal conditions, it is likely that it evolved functionally to work different than systems having supercomplexes. Because these differences are yet unknown, it remains questionable whether the fly system can be used to inform about the general significance of supercomplexes found in the other systems.

Reviewer #2 (Public Review):

This manuscript by Martin-Flores et al. has examined the role of DKK3 in Alzheimer's disease, focusing on the regulation of synaptic numbers. By using human AD brain databases and tissue samples, the authors showed that DKK3 protein and mRNA levels are increased in the brains of AD patients. DKK3 is expressed in the excitatory neurons in WT mouse brains and accumulates at atrophic neurites around amyloid plaques in AD mouse brains. Interestingly, secretion of DKK3 appears to be regulated by NMDAR antagonist as well as chemical LTD. Through gain and loss of function studies, the authors showed that DKK3 regulates the number of excitatory as well as inhibitory synapses with distinct downstream pathways. Finally, the authors investigated the contribution of DKK3 to synaptic changes in AD and found that DKK3 loss of function rescues both the excitatory and inhibitory synaptic defects, resulting in the improvement of memory function in J20 mice.

Overall, the data is clearly presented and deals with novel roles of DKK3 in controlling excitatory and inhibitory synapses. The finding that shRNA expression of DKK3 in AD model mice rescues synaptic phenotypes and memory impairment is potentially interesting and may provide a new strategy for AD treatment.

Reviewer #2 (Public Review):

Summary:<br /> Zung et al. use a comparative approach to examine the volatile headspace of diverse mammals and host species to understand the differences in chemical profiles that may provide mosquitoes with signatures of appropriate hosts. The authors collect the volatiles from hair samples and conduct qualitative analyses of the headspace composition. The authors' results suggest that mammals share overlapping volatile signatures, although the sampling method and statistical approaches reduce the veracity of the authors' findings. Additional comparisons between mammalian and floral odours were conducted, although the datasets were limited.

The inter-species comparisons will be helpful in the field, although the data pipeline and approaches may underestimate the headspace chemical diversity, and sampling artifacts and contaminants occur in the datasets, which further weakens the study's findings.

Strengths:<br /> The comparative approach is a strength of the manuscript. The authors identify an important gap in mosquito natural history by attempting to characterize the odours from various mammalian, bird, and reptile species that mosquitoes may use as blood hosts. Although others have compared the skin volatiles of humans, apes, and ungulates (Verhulst et al., 2018, not cited in the current manuscript), Zung and coworkers expand this sampling by using hair samples from collections and zoos. Unfortunately, the sampling approach leads to potential artifacts associated with the collected volatiles and statistical analyses.

Weaknesses:<br /> There are three major points of weakness associated with the manuscript: (1) sampling approach and analysis pipeline; (2) statistical analyses; and (3) premise and prior work.

1. Sampling approach and pipeline<br /> A. The authors have described their sampling and analysis as quantitative, but they use a qualitative approach by not quantifying their samples and using a low-res MS. I outline several approaches that would allow the authors to quantitate their samples. The authors must run synthetic standards for peak verification (the mass spectra alone are insufficient for compound identification). The authors are also encouraged to run the standards in a concentration curve to allow quantification of the compounds. The authors have only tentatively identified 120 compounds. Using an autosampler and standard analyses in the software, the authors could easily quantify their samples which would take less than a week's time (this is not impossible, as the authors state in the methods). Based on the volatile fragmentation and the MS detector, the compounds will differ in their relative abundances - running calibration curves, co-injection of authentic standards, and using multiple column types are necessary for the resulting statistical analyses to prevent mischaracterization of the abundances in the hair samples. Using an internal standard, by spiking the Tenax before collection, would also allow determination if column conditions change over the course of the experiment. These measurements would provide some quantitative measures to explore the differences in host odors. Details on these approaches can be found in Methods in Chemical Ecology, Techniques in Pheromone Research, and article reviews that describe more recent approaches and analyses (Tholl and Rose, 2006; Stashenko and Martínez, 2008; Spicer et al., 2017; Tholl et al., 2020; Eisen et al., 2021; Schulz and Mollerke, 2022).

B. Abundant contaminants in the samples. In the supplemental table of partially identified compounds, many contaminants are associated with the headspace collection method and environmental contaminants. Under thermal deadsorption, Tenax degradation produces many compounds, including quinolones and benzenoid compounds. Phenyl-substituted carbonyl compounds (benzaldehyde, acetophenone, benzene acetaldehyde) are formed as artifacts from the oxidation of Tenax with environmental contaminants. Other compounds, like phenol or -ethyl and methylated benzene compounds, are known to be released from the Tenax traps. The authors' pipeline and blank subtraction should have identified these compounds.

C. Hair and live headspace volatiles. I appreciate the authors' experiments comparing the composition and abundance of volatiles from live collections and hair samples. However, the results demonstrate that the hair does not always match the volatiles from the live animal. Humans 1, 3, and 4 differ significantly in their aldehyde abundances, especially nonanal. The hamster and mice samples also differ significantly. The matrix of the hair will adsorb and modify the emissions and ratios of compounds, which makes the inter-species comparisons difficult if not impossible if the headspace collection approaches differ. The authors need to change their phrasing of the host odours to "hair odours", and soften their statements associated with the complete host odour profile, and use hair samples as a standard matrix for the headspace collections. The comparison of human odour collections relative to hair samples is like the comparison of apples and oranges.

D. The authors need to use another column type to characterize their peaks further. Some of the compounds are enantiomers or closely elute from the column. Although the authors suggest their methods may separate these compounds, they may be misidentified without a different GC temperature ramp or column.

E. The authors should replace their retention indices with KRI values to further identify their compounds. The methods section does not describe whether the alkane standards were run parallel to the hair samples, and the manuscript's retention indices do not match published KRI values.

F. The number of compounds across species (including flower compounds) is very low (approximately 120 compounds) and surprising. This suggests that the analysis pipeline and thresholding may miss many compounds in the headspace. I would encourage the authors to lower their threshold to 10^-5 AU, or to perform a sensitivity analysis on their ability to identify the peaks. Running authentic standards would also allow the identification of compounds missed in the analysis.

G. I understand the difficulty in obtaining these samples across the different species. However, additional information is needed for those species that are limited in the number of replicates (individuals). Sampling the individual multiple times may indicate the variability in the hair volatiles. Although the authors and many others have shown the reproducibility of human skin volatiles through time, additional sampling would indicate this also occurs for other mammals while strengthening the authors' approach.

H. An important measure of natural odour statistics is the odor emission rates, and normalizing across samples by the sample mass. More information on the methods would have clarified these aspects. It needs to be clarified why the samples were collected for different time periods (5 to 80 minutes). The sample mass for each specimen should also be included as this would allow normalization by time and mass, and should be described in the methods. This would allow quantitative measurements of the samples.

I. A critical missing component in the headspace is the acids. Tenax does not perform well at collecting these compounds. However, Gerstel Twisters and other collection matrices can capture those compounds. The authors must use these other collection methods to sample the hair specimens and identify those compounds to include in their table and analyses. Without this information, the manuscript lacks a critical dimension in the human odour landscape that is critical for mosquito attraction.

2. Statistical Analyses<br /> A. Sampling effort and the replicate numbers used in the analyses is an important consideration that the authors do not address, but should be discussed in more detail. In many subfields of chemical ecology, a minimum of ten replicates per species has been suggested to accurately identify the composition of compounds, and even with ten samples, this may not be enough to characterize the volatile profile (Raguso and Pellmyr, 1998; Campbell et al 2019). The authors could perform a power analysis, or an accumulation curve to represent the needed sample number to identify the number of compounds in the hair headspace accurately.

B. It would be worthwhile for the authors to provide more detail on their supervised and unsupervised approaches, and how their data fits the assumptions of the analyses. The PCA parametric method may require log or square root transformation of the data to make residuals fit the normality assumption, but it's unclear if this was the case with the authors' datasets.

C. PCA is also not appropriate when many samples have zero values in the data matrix, which occurs in the authors' data. In such a case, the approaches of NMDS or canonical analysis of principal coordinates would be more appropriate, and allow distance measures (the Bray-Curtis distance) to define dissimilarity of different groups. An analysis of similarity (ANOSIM) could be used to determine if the data clustered significantly by species or by mosquito host.

D. The authors are encouraged to use alternate approaches, such as random forest (ML) approach, to determine if the odor classification is based on host or non-host. This method has been used for the last fifteen years in chemical ecology and human odor analysis (Cutler et al, 2007, Kwak et al 2008).

E. The authors use a phylogenetic framework for their analyses. Multivariate methods are now available to test evolutionary hypotheses about scent composition in a phylogenetic framework (Goolsby, 2017), and the authors are encouraged to use these approaches.

F. Comparison to floral odour space section. I would encourage the authors to examine other datasets of plant headspace samples, including plants used by mosquitoes. There are many datasets out there that the authors could use (El-Sayed 2021, Farré-Armengol et al 2020). Expanding the authors' dataset would provide more statistical power, and provide control of differences in plant visitor and plant phylogenetic relatedness.

G. Adding context related to mosquito olfaction. The authors describe how their work could provide insight into the coding of olfactory information by the mosquito. I would encourage the authors to analyze their data further by collapsing the host volatiles into groups based on biochemical pathways, or knowledge of the detection of the volatiles by the mosquitoes (such as using electroantennogram responses) to filter and identify only those responsive volatiles to keep in their dataset.

Premise and Background Knowledge<br /> A. Analyses of odour headspace have been known for the last three decades, e.g. (Methods in Chemical Ecology, Techniques in Pheromone Research, George Petri's work, Tholl and Rose, 2006; Stashenko and Martínez, 2008; Spicer et al., 2017; Tholl et al., 2020; Eisen et al., 2021; Schulz and Mollerke, 2022). But in many places, the paper conveys the impression that these are new discoveries and analyses. For example,<br /> -"Yet we remain remarkably ignorant of the composition of the chemical world."<br /> -"Our work provides one of the first quantitative descriptions of a natural odour space"<br /> -"Progress in understanding natural odours has also been hindered by the technical challenges of capturing and analyzing odour, especially the complex blends that constitute most natural odours"<br /> The Introduction and Discussion are rife with these overblown statements. I found this frustrating as the authors were not giving due credit to prior work on that topic while (maybe unintentionally) giving an impression that this specific idea was a new contribution. More care is needed to delineate which aspects of the study are 1) based on prior understanding, or 2) totally new). The authors are adding to an already extensive field of chemical ecology and olfactory processing of mixtures, and are contributing to this knowledge by adding datasets related to mammalian odor. I plead that the authors clearly describe these gaps, and place their results into proper context.

B. Similarly to the above statements relating to chemical ecology, the authors have numerous statements about gaps in odour processing. Mixture processing has been an important topic of study for the last forty years (Shorey, 1973, Caprio, 1988, Riffell et al 2009, Su et al 2009, Rokni et al 2014, Mathis et al 2016), which is based on encoding the temporal and concentration-dependent statistics of the odour.<br /> -"Yet compared to visual and auditory scenes, we know very little about the statistics of natural olfactory scenes"<br /> As described above, this is surprising and frustrating because of the rich literature on these topics (searching for "odour mixtures" provides 32,000 articles). In their manuscript, the authors are providing a strawman argument for their analyses by focusing on single odorant signatures, when the literature has repeatedly demonstrated the importance of odour mixtures for behavior and combinatorial processing.

C. There are increasing studies examining the mosquito behavioral and electrophysiological responses to hosts and other odours. However, this literature is not cited or included in the authors' analyses. The chemical ecology of mosquito attractants and natural odours has been studied in the Carde, Leal, Ignell, Carlson, Kline, Riffell, Takken, Torto, Verlhurst, Vosshall labs, and many others. The authors could use this information in their analyses and cite the literature.

Reviewer #2 (Public Review):

It is well known that DMRT proteins and more specifically, DMRT1 plays a key role in the sex determination processes of many species. While DMRT1 has been shown to be critical for the sex determination of fish, birds, and reptiles, it seems less crucial at the sex determination stages of the mice. It is important though for adult sex maintenance in mice.

Unlike its minor role in mouse sex determination, it seems that variants in DMRT1 in humans cause 46, XY DSD and sex reversal.

The paper by Dujardin et al. is a beautiful study that provides an answer to this long-lasting discrepancy of the difference between the two common mammal species: human and mouse. It is a really nice example of how working with other mammal species, like the rabbit, could serve as a nice model for understanding mammalian sex determination.

In this study the researchers first described the expression patterns of DMRT1 in the rabbit XY and XX gonads throughout the window of sex determination.

They then used CRISPR/Cas9 to generate DMRT1 KO rabbits and analysed the phenotype in XY and XX rabbits. They show that XY rabbits present with complete XY male-to-female sex reversal, very similar to what observed in human 46, XY DSD patients (but not the mice model). They further show that in the XY sex reversed gonads, germ cells fail to enter meiosis. They next analysed XX gonads and while there is no major effect on sex determination (as expected), the germ cells in these ovaries fail to enter meiosis, highlighting the critical role that DMRT1 has in germ cells.

I think it is really important that we start to embrace other mammal models that are not the mouse as we find many instances that the mouse is not the optimal system for understanding human sex determination.

The study is well explained and presented. The data is clear, and the paper is fluent to read.

Reviewer #2 (Public Review):

Summary:<br /> The authors used next-generation sequencing approaches combined with ribosome trapping to investigate gene expression in neurons and glia in the heads of adult fruit flies. Ribosome footprinting was further used to investigate the translational efficiency (TE) of particular RNAs in these two tissues. The evidence convincingly demonstrated that translation of specific messages is repressed in glia while others are repressed in neurons. Further evidence suggests that cis-acting elements within the 5'UTR of neuronal transcripts cause the repression of translation in glia. For instance, a fluorescent reporter using the 5'UTR of Rhodopsin-1 is highly translated in neurons but fluorescence from this reporter is nearly undetectable in glia. Furthermore, pausing of ribosomes on start codons of upstream Open Reading Frames (uORFs) is seen on the 5'UTR of this and other messages in glia but not in neurons.

Strengths:<br /> The main strength of the manuscript is its use of cutting-edge next-generation sequencing and bioinformatic approaches to investigate the tissue-specific translatome of Drosophila.

Weaknesses:<br /> A minor weakness is that little insight is provided into the mechanism that leads to ribosome stalling on uORFs in glia but not in neurons. The manuscript could be improved by some discussion on potential pathways that might control the differential TE through uORF pausing.

Reviewer #2 (Public Review):

Summary:<br /> This manuscript by Xu et al., is an interesting study aiming to identify novel features of macaque cortical development. This study serves as a valuable atlas of single cell data during macaque neurogenesis, which extends the developmental stages previously explored. Overall, the authors have achieved their aim of collecting a comprehensive dataset of macaque cortical neurogenesis and have identified a few unknown features of macaque development.

Strengths:<br /> The authors have accumulated a robust dataset of developmental time points and have applied a variety of informatic approaches to interrogate this dataset. One interesting finding in this study is the expression of previously unknown receptors on macaque oRG cells. Another novel aspect of this paper is the temporal dissection of neocortical development across species. The identification that the regulome looks quite different, despite similar expression of transcription factors in discrete cell types, is intriguing.

Weaknesses:<br /> Due to the focus on demonstrating the robustness of the dataset, the novel findings in this manuscript are underdeveloped. There is also a lack of experimental validation. This is a particular weakness for newly identified features (like receptors in oRG cells). It's important to show expression in relevant cell types and, if possible, perform functional perturbations on these cell types. The presentation of the data highlighting novel findings could also be clarified at higher resolution, and dissected through additional informatic analyses. Additionally, the presentation of ideas and goals of this manuscript should be further clarified. A major gap in the study rationale and results is that the data was collected exclusively in the parietal lobe, yet the rationale and interpretation of what this data indicates about this specific cortical area was not discussed. Last, a few textual errors about neural development are also present and need to be corrected.

Reviewer #2 (Public Review):

Summary:<br /> The authors examined several defensive responses elicited during Pavlovian conditioning using a serial compound stimulus (SCS) as the conditioned stimulus (CS) and a shock unconditioned stimulus (US) in male and female mice. The SCS consisted of tone pips followed by white noise. Their design included 3 treatment groups that were either exposed to the CS and US in a paired fashion, in an unpaired fashion, or only exposed to the shock US. They compared freezing, jumping, darting, and tail rattling across all groups during conditioning and extinction. During conditioning, strong freezing responses to the tone pips followed by strong jumping and darting responses to the white noise were present in the paired group but less robust or not present in the unpaired or shock only groups. During extinction, tone-induced freezing diminished while the jumping was replaced by freezing and darting in the paired group. Together, these findings support the idea that associative pairings are necessary for conditioned defensive responses.

Strengths:<br /> The study has strong control groups including a group that receives the same stimuli in an unpaired fashion and another control group that only receives the shock US and no CS to test the associative value of the SCS to the US. The authors examine a wide variety of defensive behaviors that emerge during conditioning and shift throughout extinction: in addition to the standard freezing response, jumping, darting, and tail rattling were also measured.

Weaknesses:<br /> This study could have greater impact and significance if additional conditions were added (e.g., using other stimuli of differing salience during the SCS), and determining the neural correlates or brain regions that are differentially recruited during different phases of the task across the different groups.

Reviewer #2 (Public Review):

The manuscript investigates the function of basal forebrain cholinergic axons in mouse primary visual cortex (V1) during locomotion using two-photon calcium imaging in head-fixed mice. Cholinergic modulation has previously been proposed to mediate the effects of locomotion on V1 responses. The manuscript concludes that the activity of basal forebrain cholinergic axons in visual cortex provides a signal which is more correlated with binary locomotion state than locomotion velocity of the animal. Cholinergic axons did not seem to respond to grating stimuli or visuomotor prediction error. Optogenetic stimulation of these axons increased the amplitude of responses to visual stimuli and decreased the response latency of layer 5 excitatory neurons, but not layer 2/3 neurons. Moreover, optogenetic or chemogenetic stimulation of cholinergic inputs reduced pairwise correlation of neuronal responses. These results provide insight into the role of cholinergic modulation to visual cortex and demonstrate that it affects different layers of visual cortex in a distinct manner. The experiments are well executed and the data appear to be of high quality. However, further analyses are required to fully support several of the study's conclusions.

1) In experiments analysing the activity of V1 neurons, GCaMP6f was expressed using a ubiquitous Ef1a promoter, which is active in all neuronal cell types as well as potentially non-neuronal cells. The manuscript specifically refers to responses of excitatory neurons but it is unclear how excitatory neuron somata were identified and distinguished from that of inhibitory neurons or other cell types.

2) The manuscript concludes that cholinergic axons convey a binary locomotion signal and are not tuned to running speed. The average running velocity of mice in this study is very slow - slower than 15 cm/s in the example trace in Figure 1D and speeds <6 cm/s were quantified in Figure 2E. However, mice can run at much faster speeds both under head-fixed and freely moving conditions (see e.g. Jordan and Keller, 2020, where example running speeds are ~35 cm/s). Given that the data in the present manuscript cover such a narrow range of running speeds, it is not possible to determine whether cholinergic axons are tuned to running speed or convey a binary locomotion signal.

3) The analyses in Figure 4 only consider the average response to all grating orientations and directions. Without further analysing responses to individual grating directions it is unclear how stimulation of cholinergic inputs affects visual responses. Previous work (e.g. Datarlat and Stryker, 2017) has shown that locomotion can have both additive and multiplicative effects and it would be valuable to determine the type of modulation provided by cholinergic stimulation.

4) The difference between the effects of locomotion and optogenetic stimulation of cholinergic axons in Figure 5 may be confounded by differences in the visual stimulus. These experiments are carried out under open-loop conditions, where mice may adapt their locomotion based on the speed of the visual stimulus. Consequently, locomotion onsets are likely to occur during periods of higher visual flow. Since optogenetic stimulation is presented randomly, it is likely to occur during periods of lower visual flow speed. Consequently, the difference between the effect of locomotion and optogenetic stimulation may be explained by differences in visual flow speed and it is important to exclude this possibility.

5) It is unclear why chemogenetic manipulations of cholinergic inputs had no effect on pairwise correlations of L2/3 neuronal responses while optogenetic stimulation did.

6) The effects of locomotion and optogenetic stimulation on the latency of L5 responses in Figure 7 are very large - ~100 ms. Indeed, typical latencies in mouse V1 measured using electrophysiology are themselves shorter than 100 ms (see e.g. Durand et al., 2016). Visual response latencies in stationary conditions or without optogenetic stimulation appear surprisingly long - much longer than reported in previous studies even under anaesthesia. Such large and surprising results require careful analysis to ensure they are not confounded by artefacts. However, as in Figure 4, this analysis is based only on average responses across all gratings and no individual examples are shown.

Reviewer #2 (Public Review):

Summary:

The authors develop a computational approach-avoidance-conflict (AAC) task, designed to overcome the limitations of existing offer based AAC tasks. The task incorporated likelihoods of receiving rewards/ punishments that would be learned by the participants to ensure computational validity and estimated model parameters related to reward/punishment and task induced anxiety. Two independent samples of online participants were tested. In both samples participants who experienced greater task induced anxiety avoided choices associated with greater probability of punishment. Computational modelling revealed that this effect was explained by greater individual sensitivities to punishment relative to rewards.

Strengths:

Large internet-based samples, with discovery sample (n = 369), pre-registered replication sample (n = 629) and test-retest sub group (n = 57). Extensive compliance measures (e.g. audio checks) seek to improve adherence.

There is a great need for RL tasks that model threatening outcomes rather than simply loss of reward. The main model parameters show strong effects and the additional indices with task based anxiety are a useful extension. Associations were broadly replicated across samples. Fair to excellent reliability of model parameters is encouraging and badly needed for behavioral tasks of threat sensitivity.

The task seems to have lower approach bias than some other AAC tasks in the literature.

Appraisal and impact:<br /> Overall this is a very strong paper, describing a novel task that could help move the field of RL forward to take account of threat processing more fully. The large sample size with discovery, replication and test-retest gives confidence in the findings. The task has good ecological validity and associations with task-based anxiety and clinical self-report demonstrate clinical relevance. Test-retest of the punishment learning parameter is the only real concern. Overall this task provides an exciting new probe of reward/threat that could be used in mechanistic disease models.

Additional context:

The sex differences between the samples are interesting as effects of sex are commonly found in AAC tasks. It would be interesting to look at the main model comparison with sex included as a covariate.

Reviewer #2 (Public Review):

This manuscript links the distinctive stinging behavior of sea anemones in different ecological niches to varying inactivation properties of voltage-gated calcium channels that are conferred by the identity of auxiliary Cavbeta subunits. Previous work from the Bellono lab established that the burrowing anemone, Nematostella vectensis, expresses a CaV channel that is strongly inactivated at rest which requires a simultaneous delivery of prey extract and touch to elicit a stinging response, reflecting a precise stinging control adapted for predation. They show here that by contrast, the anemone Exaiptasia diaphana which inhabits exposed environments, indiscriminately stings for defense even in the absence of prey chemicals, and that this is enabled by the expression of a CaVbeta splice variant that confers weak inactivation. They further use the heterologous expression of CaV channels with wild type and chimeric anemone Cavbeta subunits to infer that the variable N-termini are important determinants of Cav channel inactivation properties.

Reviewer #2 (Public Review):

Summary:

C. difficile infection (CDI) is clinically important as a hospital-acquired infection and a frequent cause of antibiotic-associated diarrhea, which is associated with high morbidity and mortality and increases in prevalence. It is also the prime example of a disease that is associated with gut microbiome dysbiosis and successfully treated with fecal microbiota transfer, highlighting the important but unclear functional or structural role of this bacterial pathogen and the condition of CDI for the gut microbiome, which is the focus of this study.

Ferretti et al. assembled an impressive gut metagenome dataset from previous and ongoing microbiome studies, which involves a large number of samples from patients with CDI or other diarrheal and non-diarrheal diseases and from healthy individuals, as well as from infants, adolescents, and adults. The authors analyze the prevalence and relative abundance of C. difficile in this dataset in relation to CDI diagnosis, host age and disease background, and the composition of the remaining microbiota. They detect C. difficile only in a minority of samples labelled as originating from CDI patients but frequently identify other pathogens and their toxin genes in the same samples. In infants, they detect C. difficile at high frequency and relative abundance in samples without clinical symptoms. They associate C. difficile presence in infant samples with "multiple indicators of healthy gut microbiome maturation' and suggest 'distinct biotic and physiological contexts in infants and adults' for C. difficile.

Strengths:

The manuscript provides an important overview of the complex relationship of C. difficile with the gut microbiome of healthy and diseased infants and adults, mostly due to the large studied dataset and convincing applied analysis that underlies the presented findings. This includes a number of interesting findings including, for example, that CDI can be reliably predicted based on taxonomic microbiota compositions, without including C. difficile itself or that C. difficile in infants appears not to originate from maternal sources.

Weaknesses:

Inconsistent associations of C. difficile with what is clinically labeled CDI, as well as the frequent detection of C. difficile in healthy infants, have been reported before and the manuscript does not reveal to what extent this bacterium reflects or even directly influences the gut microbiome of infants and adults. Whether the increased microbiota diversity, richness, and compositional similarity of C. difficile-positive infants to their mothers is sufficient to associate this bacterium with "healthy gut microbiome maturation" seems questionable, since C. difficile was also found to be more prevalent in preterm infants, formula-fed or antibiotically treated infants, and infants born by C-section, all of which are typically considered detrimental influences on microbiota development. The conclusion that "C. difficile may be a transient hallmark of healthy gut microbiome maturation" therefore appears too strong.

In addition, the statement that "its asymptomatic carriage in adults depends on microbial context" is not sufficiently supported by the presented data. Apparently, the authors are unable to define or measure "asymptomatic carriage", as they convincingly show that many patients diagnosed with "CDI" appear not to carry C. difficile, suggesting that neither asymptomatic nor symptomatic "CDI" conditions are necessarily linked to C. difficile.

The manuscript includes a large number of samples from poorly defined, but diverse patient backgrounds. It might be helpful to better define these samples (e.g. fecal samples vs. other gut samples) and to specify subcategories for samples from "diseased control subjects without CDI". Maybe this information could help validate the interesting suggestion from the manuscript that C. difficile may be (one of several) dysbiosis marker rather than the cause of (CDI) dysbiosis.

The phylogenetic analysis of C. difficile from metagenomic sequence data seems to suggest that there is a large mostly toxin gene-free cluster that is only identified in infants (Supplementary Figure 13). Could this indicate that there are, in fact, less pathogenic C. difficile lineages that are more prevalent in infants?

The authors argue in the Discussion that "Differential diagnosis against multiple enteropathogens may therefore stratify patients with CDI-like symptoms, towards adapted therapeutic interventions." It might be helpful to expand this discussion of different clinical options that could be adapted to highlight the clinical applicability of the presented findings.

Reviewer #2 (Public Review):

In this work, the authors reported cryo-EM structures of four types of zinc-binding site mutants of a bacterial Zn2+/H+ antiporter YiiP, and proposed distinct structural/functional roles of each of the binding sites in the intramolecular Zn2+ relay and the integrity of the homodimeric structure of YiiP. MST analysis using the mutants with a single Zn2+-binding site at different pH further clarified the pH dependence of Zn2+ binding affinity of each site. Moreover, the inverse Multibind approach refined the CpHMD pKa values of the key Zn2+-binding residues so that they agreed with the MST data. Consequently, energetic coupling of Zn2+ export to the proton-motive force has been suggested. These findings definitely provide new mechanistic insight into this Zn2+/H+ antiporter.

Reviewer #2 (Public Review):

This paper makes important and novel advances that significantly enhance our understanding of the ClC-2 channel. The EM data are of high quality, and the most important argument, concerning the role of the N-terminus of the protein as an occluding inactivation gate, is very well supported by structural, computational, and functional data (some of which is previously published). The proposal that the "run up" observed in patch clamp experiments represents relief of inactivation is interesting and compelling. The model predicts that mutations at the hairpin binding site should influence this "run up", which should be tested in the near future. Finally, the confirmation of the AK-42 binding site further solidifies evidence that this is a pore-blocking compound; the authors' argument about determinants of specificity is convincing.

Reviewer #2 (Public Review):

Using standard and widely used tools, the author revealed the factors (cultural, phenotypic, phylogenetic, etc.) shaping societal and scientific interest in natural species around the globe. The strength of this ms (and the authors) lies in its command of the available literature, database and variable management and analysis, and its solid discussion. The authors thus achieved a manuscript that was pleasant to read.

While I agree that doing a global study requires losing details of local patterns, maybe this is exactly the biggest shortcoming of the manuscript, oblivious to how different cultures (compare USA to PNG, for example) are reflected in these global patterns.

Reviewer #2 (Public Review):

The paper presents new mitochondrial sequence data from baboons from a museum collection and from one ancient Egyptian mummified baboon. By comparing the mitochondrial sequence of the mummified baboon with the new and existing data, they conclude that it originated from present-day Eritrea, specifically the ancient city of Adulis.

The paper is well-written and an interesting read. The background and details of the study are well-described and logical. Not knowing much about the history of the region I learned a lot. The data also seem sound and the analysis robust, with the exception of one check that should be added (in particular, to assess contamination by looking at mismatching reads).

The main limitation of the paper is just down to the N=1 sample and the limits of mitochondrial phylogeography. Based on the present-day distribution of hamadryas, the baboon must either come from the area of Africa around present-day Eritrea/Ethiopia/Sudan, or from Arabia. All the authors can really reasonably establish here is that this particular baboon did not come from Arabia. But beyond that, there is not much more they can say. Fig 2b makes it clear that the G3Y clade extends over a large range. Given the limited sampling, this is a minimum bound for the range, which probably includes most of the non-Arabian hamadryas range. The link to Adulis is speculative. There may be historical or archaeological evidence to support this but the genetic data really do not come close to establishing this. The authors do acknowledge this in the text, though the abstract makes a much stronger claim. And of course, it also remains possible that other baboons in the assemblage came from other places.

Reviewer #2 (Public Review):

The study by Ciabatti et al examined the mutation issue for self-inactivating rabies (SiR), which was found by other labs. The authors identified the mutations in the rabies genome and showed that this mutation occurred more frequently after multiple passage of production cell lines with suboptimal TEVp expressions. The authors further showed that such mutation did not accumulate in vivo and that SiR-labeled cells remained alive across longitudinal imaging in vivo.

In this study, the rabies genome is rigorously examined by sequencing many viral particles from independent preparations. The rabies with point mutation in the PEST domain is directly engineered for sequencing and infection test. Overall, the mutation issue is well addressed by the authors and the conclusions are well supported, but some more aspects of discussion and data analysis need to be extended for an easier production of SiR in a condition not that optimal.

1) The authors stated that one should produce SiR from cDNA in order to avoid the potential mutation in SiR. From a practical point of view, it would be much better to amplify the rabies from a stock virus directly in the production cell lines. Any discussion or exploration on this direction would be appreciated in the field.

2) 6 passages of production cell lines are not that extensive. In Fig.2C, there was already some level of TEVp activity reduction at 2nd passage. It is not clear to me that how the TEVp activity reduction naturally happens. Is there some room to play around puromycin concentration to maintain high TEVp activity?

Reviewer #2 (Public Review):

Wang et al. investigate the LGN in the tree shrew as a potential target for artificial vision. They report that (a) animals pre-trained on a visual detection task can generalize from visual to optogenetic detection and (b) optogenetic activation of the LGN results in reliable field potential activity in V1.

In this revised version of the manuscript, the authors have done a commendable job of addressing the critiques from the previous round of reviews.

Among the new results, the analysis of V1 LFP entrainment with optogenetic stimulation in the LGN is quite interesting and convincing. However, I found the spiking results in V1 to be underwhelming (which the authors also acknowledge). I find this a little surprising, given the robustness of the LFP results. Was this a matter of finding a better alignment of LGN and V1 sites? Might the authors have found more convincing spiking activity results if they use laminar electrodes in V1 to find monosynaptic connectivity between the LGN injection sites and their targets in V1?

Reviewer #2 (Public Review):

While the hypothesis that MEMO1 plays a key role in cell iron homeostasis remains to be directly tested, the data presented herein clearly support further delineation of the underlying mechanisms. The key findings in this regard are the facts, as established herein, that: 1) MEMO1 binds ferrous iron (the appropriate valence state for cell iron) along with glutathione (Fig. 5A); 2) the structure of MEMO1 in complex with Fe(II)-GSH reveals the coordination site within the protein for this complex (Fig. 5B/c); 3) oxidative stress and sensitivity to ferroptosis correlate with MEMO1 protein abundance in a consistent fashion (Fig. 4); and 4) while the effect is limited, there are data that indicate a relation between cell iron content and MEMO1 abundance (Fig. 4A/B).

Experimentally, it is thorough and well-documented and offers a new look at a protein that has been at the edges of iron metabolism (and copper, but I agree with the authors that this is not likely to be the case). This work and its subject will stimulate much further research.

Reviewer #2 (Public Review):

In this study, the authors validated a positive feedback loop between ZEB2 and ACSL4 in breast cancer, which regulates lipid metabolism to promote metastasis.

Overall, the study is original, well structured, and easy to read.

Reviewer #2 (Public Review):

Summary:

Molecular dynamics (MD) data is deposited in public, non-specialist repositories. This work starts from the premise that these data are a valuable resource as they could be used by other researchers to extract additional insights from these simulations; it could also potentially be used as training data for ML/AI approaches. The problem is that mining these data is difficult because they are not easy to find and work with. The primary goal of the authors was to discover and index these difficult-to-find MD datasets, which they call the "dark matter of the MD universe" (in contrast to data sets held in specialist databases).

The authors developed a search strategy that avoided the use of ill-defined metadata but instead relied on the knowledge of the restricted set of file formats used in MD simulations as a true marker for the data they were looking for. Detection of MD data marked a data set as relevant with a follow-up indexing strategy of all associated content. This "explore-and-expand" strategy allowed the authors for the first time to provide a realistic census of the MD data in non-specialist repositories.

As a proof of principle, they analyzed a subset of the data (primarily related to simulations with the popular Gromacs MD package) to summarize the types of simulated systems (primarily biomolecular systems) and commonly used simulation settings.

Based on their experience they propose best practices for metadata provision to make MD data FAIR (findable, accessible, interoperable, reusable).

A prototype search engine that works on the indexed datasets is made publicly available. All data and code are made freely available as open source/open data.

Strengths:

- The novel search strategy is based on relevant data to identify full datasets instead of relying on metadata and thus is likely to have many true positives and few false positives.

- The paper provides a first glimpse at the potential hidden treasures of MD simulations and force field parametrizations of molecules.

- Analysis of parameter settings of MD simulations from how researchers *actually* run simulations can provide valuable feedback to MD code developers for how to document/educate users. This approach is much better than analyzing what authors write in the Methods sections.

- The authors make a prototype search engine available.

- The guidelines for FAIR MD data are based on experience gained from trying to make sense of the data.

Weaknesses:

- So far the work is a proof-of-concept that focuses on MD data produced by Gromacs (which was prevalent under all indexed and identified packages).

As discussed in the manuscript, some types of biomolecules are likely underrepresented because different communities have different preferences for force fields/MD codes (for example: carbohydrates with AMBER/GLYCAM using AMBER MD instead of Gromacs).

- Materials sciences seem to be severely under-represented --- commonly used codes in this area such as LAMMPS are not even detected, and only very few examples could be identified. As it is, the paper primarily provides an insight into the *biomolecular* MD simulation world.

The authors succeed in providing a first realistic view on what MD data is available in public repositories. In particular, their explore-expand approach has the potential to be customized for all kinds of specialist simulation data, whereby specific artifacts are<br /> used as fiducial markers instead of metadata. The more detailed analysis is limited to Gromacs simulations and primarily biomolecular simulations (even though MD is also widely used in other fields such as the materials sciences). This restricted view may simply be correlated with the user community of Gromacs and hopefully, follow-up studies from this work will shed more light on this shortcoming.

The study quantified the number of trajectories currently held in structured databases as ~10k vs ~30k in generalist repositories. To go beyond the proof-of-principle analysis it would be interesting to analyze the data in specialist repositories in the same way as the one in the generalist ones, especially as there are now efforts underway to create a database for MD simulations (Grant 'Molecular dynamics simulation for biology and chemistry research' to establish MDDB' DOI 10.3030/101094651). One should note that structured databases do not invalidate the approach pioneered in this work; if anything they are orthogonal to each other and both will likely play an important role in growing the usefulness of MD simulations in the future.

Reviewer #2 (Public Review):

Summary:<br /> This work investigates how increased temperature affects pollen production and fertility of Arabidopsis thaliana plants grown at selected temperature conditions ranging from 16C to 30C. They report that pollen production and fertility decline with increasing temperature. To identify the cause of reduced pollen and fertility, they resort to living cell imaging of male meiotic cells to identify that the duration of meiosis increases with an increase in temperature. They also show that pollen sterility is associated with the increased presence of micronuclei likely originating from heat stress-induced impaired meiotic chromosome segregation. They correlate abnormal meiosis to weakened centromere caused by meiosis-specific defective loading of the centromere-specific histone H3 variant (CenH3) to the meiotic centromeres. Similar is the case with kinetochore-associated spindle assembly checkpoint(SAC) protein BMF1. Intriguingly, they observe a reverse trend of strong CENH3 presence in the somatic cells of the tapetum in contrast to reduced loading of CENH3 in male meiocytes with increasing temperature. In contrast to CENH3 and BMF1, the SAC protein BMF3 persists for longer periods than the WT control, based on which authors conclude that the heat stress prolongs the duration of SAC at metaphase I, which in turn extends the time of chromosome biorientation during meiosis I. The study provides preliminary insights into the processes that affect plant reproduction with increasing temperatures which may be relevant to develop climate-resilient cultivars.

Strengths:<br /> The authors have mastered the live cell imaging of male meiocytes which is a technically demanding exercise, which they have successfully employed to examine the time course of meiosis in Arabidopsis thaliana plants exposed to different temperature conditions. In continuation, they also monitor the loading dynamics and resident time of fluorescently tagged centromere/kinetochore proteins and spindle assembly checkpoint proteins to precisely measure the time duration of respective proteins to study their precise dynamics and function in male meiosis.

Weaknesses:<br /> Here the authors use only one representative centromere protein CENH3, one kinetochore-associated SAC protein BMF1, and the SAC protein BMF3 to conclude that heat stress impairs centromere function and prolongs SAC with increased temperatures. Centromere and its associated protein complex the kinetochores and the SAC contain a multitude of proteins, some of which are well characterized in Arabidopsis thaliana. Hence the authors could have used additional such tagged proteins to further strengthen their claim. Though the results presented here are interesting and solid, the study lacks a deeper mechanistic understanding of what causes the defective loading of CenH3 to the centromeres, and why the SAC protein BMF3 persists only at meiotic centromeres to prolong the spindle assembly checkpoint. Also, this observation should be interpreted in light of the fact that SAC is not that robust in plants as several null mutants of plant SAC components are known to grow as healthy as wild-type plants at normal growth conditions without any vegetative and reproductive defects. One of the immediate responses to heat stress is the production of heat shock proteins(Hsps), which act as molecular chaperones to safeguard the proteome. It will be interesting to see if the expression levels of known HsPs can be correlated with their role in stabilizing the structure of SAC proteins like BMF1 to prolong its presence at the meiotic kinetochores.

Reviewer #2 (Public Review):

Summary:<br /> The manuscript highlights a mechanistic insight into meiotic initiation in budding yeast. In this study, the authors addressed a genetic link between mitotic cell cycle regulator SBF (the Swi4-Swi6 complex) and a meiosis inducing regulator Ime1 in the context of meiotic initiation. The authors' comprehensive analyses with cytology, imaging, RNA-seq using mutant strains lead the authors to conclude that Swi4 levels regulates Ime1-Ume6 interaction to activate expression of early meiosis genes for meiotic initiation. The major findings in this paper are that (1) the higher level of Swi4, a subunit of SBF transcription factor for mitotic cell cycle regulation, is the limiting factor for mitosis-to-meiosis transition; (2) G1 cyclins (Cln1, Cln2), that are expressed under SBF, inhibit Ime1-Ume6 interaction under overexpression of SWI4, which consequently leads to downregulation of early meiosis genes; (3) expression of SWI4 is regulated by LUTI-based transcription in the SWI4 locus that impedes expression of canonical SWI4 transcripts; (4) expression of SWI4 LUTI is likely negatively regulated by Ime1; (5) Action of Swi4 is negatively regulated by Whi5 (homologous to Rb)-mediated inhibition of SBF, which is required for meiotic initiation. Thus, the authors proposed that meiotic initiation is regulated under the balance of mitotic cell cycle regulator SBF and meiosis-specific transcription factor Ime1.

Strengths:<br /> The most significant implication in their paper is that meiotic initiation is regulated under the balance of mitotic cell cycle regulator and meiosis-specific transcription factor. This finding will provide a mechanistic insight in initiation of meiosis not only into the budding yeast also into mammals. The manuscript is overall well written, logically presented and raises several insights into meiotic initiation in budding yeast. Therefore, the manuscript should be open for the field. I would like to raise the following concerns, though they are not mandatory to address. However, it would strengthen their claims if the authors could technically address and revise the manuscript by putting more comprehensive discussion.

Weaknesses:<br /> The authors showed that increased expression of the SBF targets, and reciprocal decrease in expression of meiotic genes upon SWI4 overexpression at 2 h in SPO (Figure 2F). However, IME1 was not found as a DEG in Supplemental Table 1. Meanwhile, IME1 transcript level was decreased at 2 h SPO condition in pATG8-CLN2 cells in Fig S4C.

Now this reviewer still wonders with confusion whether expression of IME1 transcripts per se is directly or in directly suppressed under SBF-activated gene expression program at 2 h SPO in pATG8-SWI4 and pATG8-CLN2 cells. This reviewer wonders how Fig S4C data reconciles with the model summarized in Fig 6F.

One interpretation could be that persistent overexpression of G1 cyclin caused active mitotic cell cycle, and consequently delayed exit from mitotic cell cycle, which may have given rise to an apparent reduction of cell population that was expressing IME1. For readers to better understand, it would be better to explain comprehensively this issue in the main text.

The % of cells with nuclear Ime1 was much reduced in pATG8-CLN2 cells (Fig 2B) than in pATG8-SWI4 cells (Fig 4C). Is the Ime1 protein level comparable or different between pATG8-CLN2 strain and pATG8-SWI4 strain? Since it is difficult to compare the quantifications of Ime1 levels in Fig S1D and Fig S4B, it would be better to comparably show the Ime1 protein levels in pATG8-CLN2 and pATG8-SWI4 strains.<br /> Further, it is uncertain how pATG8-CLN2 cells mimics the phenotype of pATG8-SWI4 cells in terms of meiotic entry. It would be nice if the authors could show RNA-seq of pATG8-CLN2/WT and/or quantification of the % of cells that enter meiosis in pATG8-CLN2.

The authors stated that reduced Ime1-Ume6 interaction is a primary cause of meiotic entry defect by CLN2 overexpression (Line 320-322, Fig 4J-L). This data is convincing. However, the authors also showed that GFP-Ime1 protein level was decreased compared to WT in pATG8-CLN2 cells by WB (Fig S4A). Further, GFP-Ime1 signals were overall undetectable through nuclei and cytosol in pATG8-CLN2 cells (Fig 4B), and accordingly cells with nuclear Ime1 were reduced (Fig 4C). Although the authors raised a possibility that the meiotic entry defect in the pATG8-CLN2 mutant arises from downregulation of IME1 expression (Line 282-283), causal relationship between meiotic entry defect and CLN2 overexpression is still not clear. Is the Ime1 protein level reduced in the pATG8-CLN2;UME6-⍺GFP strain compared to WT? It would be better to comparably show the Ime1 protein levels in the pATG8-CLN2 strain and the pATG8-CLN2;UME6-⍺GFP strain by WB. Also, it would be nice if the authors could show quantification of the % of cells that enter meiosis in the pATG8-CLN2;UME6-⍺GFP strain to see how and whether artificial tethering of Ime1 to Ume6 rescued normal meiosis program rather than simply showing % sporulation in Fig4A.

The authors showed Ume6 binding at the SWI4LUTI promoter (Figure 5K). However, since Ume6 forms a repressive form with Rpd3 and Sin3a and binds to target genes independently of Ime1, Ume6 binding at the SWI4LUTI promoter bind does not necessarily represent Ime1-Ume6 binding there. Instead, it would be better to show Ime1 ChIP-seq at the SWI4LUTI promoter.

The authors showed ∆LUTI mutant and WHI5-AA mutant did not significantly change the expression of SBF targets nor early meiotic genes relative to wildtype (Figure 6A, C). Accordingly, they concluded that LUTI- or Whi5-based repression of SBF alone was not sufficient to cause a delay in meiotic entry (Line451-452), and perturbation of both pathways led to a significant delay in meiotic entry (Figure 6E). This reviewer wonders whether Ime1 expression level and nuclear localization of Ime1 was normal in ∆LUTI mutant and WHI5-AA mutant.

Reviewer #2 (Public Review):

Nagy et al investigated the role of volume increase and swelling in neutrophils in response to the chemoattractant. Authors show that following chemoattractant response cells lose their volume slightly owing to the cell spreading phase and then have a relatively rapid increase in the cell volume that is concomitant with cell migration. The authors performed an impressive genome-wide CRISPR screen and buoyant density assay to identify the regulators of neutrophil swelling. This assay showed that stimulating cells with chemoattractant fMLP led to an increase in the cell volume that was abrogated with the FPR1 receptor knockout. The screen revealed a cascade that could potentially be involved in cell swelling including NHE1 (sodium-proton antiporter) and PI3K. NHE1 and PI3K are required for chemoattractant-induced swelling in human primary neutrophils. Authors also suggest slightly different functions of NHE1 and PI3K activity where PI3K is also required to maintain chemoattractant-induced cell shape changes. The authors convincingly show that chemoattractant-induced cell swelling is linked to cell migration and NHE1 is required for swelling at the later stages of swelling since the cells at the early point work on low-volume and low-velocity regime. Interestingly, the authors also show that lack of swelling in NHE1-inhibited cells could be rescued by mild hypo-osmotic swelling strengthening the argument that water influx followed chemoattractant stimulation is important for potentiation for migration.

The conclusions of this paper are mostly well supported by data and are pretty convincing, but some aspects of image acquisition and data analysis need to be clarified and extended.

Weaknesses<br /> 1) It would really help if the authors could add the missing graph for the footprint area when cells are treated with Latranculin. Graph S1F for volume changes with Lat treatment should be compared with DMSO-treated controls.<br /> 2) The authors show inhibition of NHE1 blocked cell swelling using Coulter counter, a similar experiment should be done with PI3K inhibitions especially since they see PI3K inhibition impact chemoattractant-induced cell shape change.<br /> 3) It would be more convincing visually if the authors could also include the movie of cell spreading (footprint) and then mobility with PI3K inhibition.<br /> 4) It is not clear how cell spreading and later volume increase are linked to overall mobility of neutrophils. Are authors suggesting that cell spreading is not required for cell mobility in neutrophils?<br /> 5) Volume fluctuations associated with motility were impacted by NHE1 inhibition at the baselines, what about PI3K inhibitions? Does that impact the actual fluctuations?<br /> 6) It would really help if the authors compared similar analyses and drew conclusions from that, for example, it is unclear what the authors mean by they found no change in the angular persistence of WT and NHE1 inhibited cells which is in contrast to PI3K inhibition since they do not really have an analysis for angular persistence in PI3K inhibited cells. (S4A and S4B).

Reviewer #2 (Public Review):

The authors present a pipeline for generating strain-specific genome-scale metabolic models for bacteria using Klebsiella spp. as the demonstrative data. This paper claims to provide a high-throughput tool for generating strain-specific models for bacteria. However, in reality, the tool requires a reference pan-genome-based complete model to generate the strain-specific model of the species of interest, which in this study is Klebsiella pneumoniae. This requirement renders the tool redundant for high-throughput purposes since the process of building or generating the pan-genome reference model is performed separately. Additionally, the quality of the newly built strain-specific model will depend on the reference model used. Therefore, this tool, on its own, can only work specifically with the available pan-genome model of reference, which in this case is only applicable to Klebsiella pneumoniae. Its effectiveness with other bacteria has not been proven. I would suggest that the authors either reframe the performance and results to be applicable only to Klebsiella or consider adding more reference pan-genome models for the study.

Reviewer #2 (Public Review):

In this manuscript, Funabiki and colleagues investigated the co-evolution of DNA methylation and nucleosome remolding in eukaryotes. This study is motivated by several observations: (1) despite being ancestrally derived, many eukaryotes lost DNA methylation and/or DNA methyltransferases; (2) over many genomic loci, the establishment and maintenance of DNA methylation relies on a conserved nucleosome remodeling complex composed of CDCA7 and HELLS; (3) it remains unknown if/how this functional link influenced the evolution of DNA methylation. The authors hypothesize that if CDCA7-HELLS function was required for DNA methylation in the last eukaryote common ancestor, this should be accompanied by signatures of co-evolution during eukaryote radiation.

To test this hypothesis, they first set out to investigate the presence/absence of putative functional orthologs of CDCA7, HELLS and DNMTs across major eukaryotic clades. They succeed in identifying homologs of these genes in all clades spanning 180 species. To annotate putative functional orthologs, they use similarity over key functional domains and residues - such as ICF related mutations for CDCA7 and SNF2 domains for HELLS - as well as maximum likelihood phylogenetic analyses. Using established eukaryote phylogenies, the authors conclude that the CDCA7-HELLS-DNMT axis arose in the last common ancestor to all eukaryotes. Importantly, they found recurrent loss events of CDCA7-HELLS-DNMT in at least 40 eukaryotic species, most of them lacking DNA methylation.

Having identified these factors, they successfully identify signatures of co-evolution between DNMTs, CDCA7 and HELLS using CoPAP analysis - a probabilistic model inferring the likelihood of interactions between genes given a set of presence/absence patterns. As a control, such interactions are not detected with other remodelers or chromatin modifying pathways also found across eukaryotes. Expanding on this analysis, the authors found that CDCA7 was more likely to be lost in species without DNA methylation.

In conclusion, the authors suggest that the CDCA7-HELLS-DNMT axis is ancestral in eukaryotes and raise the hypothesis that CDCA7 becomes quickly dispensable upon the loss of DNA methylation and/or that CDCA7 might be the first step toward the switch from DNA methylation-based genome regulation to other modes.

The data and analyses reported are significant and solid. Overall, this work is a conceptual advance in our understanding of the evolutionary coupling between nucleosome remolding and DNA methylation. It also provides a useful resource to study the early origins of DNA methylation related molecular process. Finally, it brings forward the interesting hypothesis that since eukaryotes are faced with the challenge of performing DNA methylation in the context of nucleosome packed DNA, loosing factors such as CDCA7-HELLS likely led to recurrent innovations in chromatin-based genome regulation.

Strengths:<br /> - The hypothesis linking nucleosome remodeling and the evolution of DNA methylation.<br /> - Deep mapping of DNA methylation related process in eukaryotes.<br /> - Identification and evolutionary trajectories of novel homologs/orthologs of CDCA7.<br /> - Identification of CDCA7-HELLS-DNMT co-evolution across eukaryotes.

Reviewer #2 (Public Review):

In this manuscript, Funabiki and colleagues investigated the co-evolution of DNA methylation and nucleosome remolding in eukaryotes. This study is motivated by several observations: (1) despite being ancestrally derived, many eukaryotes lost DNA methylation and/or DNA methyltransferases; (2) over many genomic loci, the establishment and maintenance of DNA methylation relies on a conserved nucleosome remodeling complex composed of CDCA7 and HELLS; (3) it remains unknown if/how this functional link influenced the evolution of DNA methylation. The authors hypothesize that if CDCA7-HELLS function was required for DNA methylation in the last eukaryote common ancestor, this should be accompanied by signatures of co-evolution during eukaryote radiation.

To test this hypothesis, they first set out to investigate the presence/absence of putative functional orthologs of CDCA7, HELLS and DNMTs across major eukaryotic clades. They succeed in identifying homologs of these genes in all clades spanning 180 species. To annotate putative functional orthologs, they use similarity over key functional domains and residues - such as ICF related mutations for CDCA7 and SNF2 domains for HELLS - as well as maximum likelihood phylogenetic analyses. Using established eukaryote phylogenies, the authors conclude that the CDCA7-HELLS-DNMT axis arose in the last common ancestor to all eukaryotes. Importantly, they found recurrent loss events of CDCA7-HELLS-DNMT in at least 40 eukaryotic species, most of them lacking DNA methylation.

Having identified these factors, they successfully identify signatures of co-evolution between DNMTs, CDCA7 and HELLS using CoPAP analysis - a probabilistic model inferring the likelihood of interactions between genes given a set of presence/absence patterns. As a control, such interactions are not detected with other remodelers or chromatin modifying pathways also found across eukaryotes. Expanding on this analysis, the authors found that CDCA7 was more likely to be lost in species without DNA methylation.

In conclusion, the authors suggest that the CDCA7-HELLS-DNMT axis is ancestral in eukaryotes and raise the hypothesis that CDCA7 becomes quickly dispensable upon the loss of DNA methylation and/or that CDCA7 might be the first step toward the switch from DNA methylation-based genome regulation to other modes.

The data and analyses reported are significant and solid. Overall, this work is a conceptual advance in our understanding of the evolutionary coupling between nucleosome remolding and DNA methylation. It also provides a useful resource to study the early origins of DNA methylation related molecular process. Finally, it brings forward the interesting hypothesis that since eukaryotes are faced with the challenge of performing DNA methylation in the context of nucleosome packed DNA, loosing factors such as CDCA7-HELLS likely led to recurrent innovations in chromatin-based genome regulation.

Strengths:<br /> - The hypothesis linking nucleosome remodeling and the evolution of DNA methylation.<br /> - Deep mapping of DNA methylation related process in eukaryotes.<br /> - Identification and evolutionary trajectories of novel homologs/orthologs of CDCA7.<br /> - Identification of CDCA7-HELLS-DNMT co-evolution across eukaryotes.

Reviewer #2 (Public Review):

Summary:<br /> This work follows previous work from the group where they have demonstrated the role of TASK1 in the regulation of glucose-stimulated insulin secretion. Moreover, a recent study links a mutation in KCNK16, the gene encoding TALK-1 channels to MODY. Here the authors have constructed a mouse model with the specific mutation (TALK-1 L114P mutation) and investigated the phenotype. They have to perform a couple of breeding tricks to find a model that is lethal in adult which might complicate the conclusions, however, the phenotype of the heterozygote model used has a MODY-like phenotype. The study is convincing and solid.

Strengths:<br /> 1) The work is a natural follow-up from previous studies from the groups.

2) The authors present convincing and solid data that in the long perspective will help patients with these mutations.

3) Both in vivo and in vitro data are presented to give the full picture of the phenotype.

4) Data from both female and male mice are presented.

Weaknesses:<br /> 1) The authors perform an RNA-sequencing showing that the cAMP amplifying pathway is upregulated. A weakness is that this is not further followed up. The remaining questions include; Is this also true in humans with this mutation? Would treatment with incretins improve glucose-stimulated insulin secretion and and lower blood glucose?<br /> 2) The authors avoid further investigating what it means that the glucagon area and secretion are increased in the model.<br /> 3) The performance of measurements in both male and female mice is praiseworthy. However, despite differences in the response, the authors do not investigate the potential reason for this. Are hormonal differences of importance?

Reviewer #2 (Public Review):

Summary:

The paper presents a novel approach to expand iPSC-derived pdx1+/nkx6.1+ pancreas progenitors, making them potentially suitable for GMP-compatible protocols. This advancement represents a significant breakthrough for diabetes cell replacement therapies, as one of the current bottlenecks is the inability to expand PP without compromising their differentiation potential. The study employs a robust dataset and state-of-the-art methodology, unveiling crucial signaling pathways (eg TGF, Notch...) responsible for sustaining pancreas progenitors while preserving their differentiation potential in vitro.

Strengths:

This paper has strong data, guided omics technology, clear aims, applicability to current protocols, and beneficial implications for diabetes research. The discussion on challenges adds depth to the study and encourages future research to build upon these important findings.

Weaknesses:

The paper does have some weaknesses that could be addressed to improve its overall clarity and impact. The writing style could benefit from simplification, as certain sections are explained in a convoluted manner and difficult to follow, in some instances, redundancy is evident. Furthermore, the legends accompanying figures should be self-explanatory, ensuring that readers can easily understand the presented data without the need to be checking along the paper for information.

The culture conditions employed in the study might benefit from more systematic organization and documentation, making them easier to follow.

Another important aspect is the functionality of the expanded cells after differentiation. While the study provides valuable insights into the expansion of pancreas progenitors in vitro and does the basic tests to measure their functionality after differentiation the paper could be strengthened by exploring the behavior and efficacy of these cells deeper, and in an in vivo setting.

Quantifications for immunofluorescence (IF) data should be displayed.

Some claims made in the paper may come across as somewhat speculative.

Additionally, while the paper discusses the potential adaptability of the method to GMP-compatible protocols, there is limited elaboration on how this transition would occur practically or any discussion of the challenges it might entail.

Reviewer #2 (Public Review):

Summary: Walker et al have proposed that the tumor suppressor TMEM127 converges with RET activation to drive adrenal phenochromocytoma. RET is a common oncogene both in familial and sporadic forms of this cancer, and TMEM127 has also been observed as a loss of function mutation in sporadic disease. The authors hypothesize that loss of the TMEM127 might signal stabilization of RET on the cell surface, mimicking an activating mutation. Through a nice set of experiments, they show that TMEM127 loss impairs endosome function and promotes RET surface accumulation. This expression was resistant to GDNF, suggesting that recycling via endosome recirculation was impaired such that the half-life of RET on the cell surface was extended. RET interaction with clathrin-coated pits was also disrupted, as the CCPs themselves were significantly smaller, and plasma membrane organization was affected by the impaired endosome recycling. Notably, a number of proteins were found to be accumulating on the cell surface via the purported mechanism, EGFR, TFR1, N cadherin, integrin beta 3. The authors applied a RET inhibitor to cells, showing decreased cellular proliferation.

Strengths: In summary, this is an interesting finding, that is preliminary in nature and is incompletely validated currently. It is certainly worth further investigation as a central feature linking TMEM127 mutations and pheochromocytoma through a common pathway of RET activation by fixing this factor in an active state on the cell surface.

Weaknesses: Although this is a provocative finding, and the authors test the interaction in a number of ways, there are several factors that limit the enthusiasm for this work as currently presented. The work is limited to one isogenic cell line with limited validation.

Reviewer #2 (Public Review):

The authors tried to diagnose cancers and pinpoint tissues of origin using cfDNA. To achieve this goal, they developed a framework to assess methylation, CNA, and other genomic features. They established discovery and validation cohorts for systematic assessment and successfully achieved robust prediction power.

Reviewer #2 (Public Review):

Summary:<br /> This study is quite thorough, tackling this NO-dependent UV avoidance circuit with both breadth and depth. There are several novel discoveries throughout, but the whole package represents perhaps even more than the sum of these parts.

Strengths:<br /> The presentation of the work is compelling. The introduction sets up the question and the state of the field very nicely. The discovery of the non-canonical NO receptor pathway in the ciliary photoreceptors is fascinating and will likely open up new avenues for future research into NO-pathways in different species. The use of genetic and pharmacological manipulations of circuit components was well thought-out. The authors applied different experimental techniques expertly throughout the study so that they could develop a comprehensive view from the molecular to the behavioral levels.

Weaknesses:<br /> While I appreciate the intent of bringing together a large set of measurements from connectomics and calcium imaging in the framework of a model, the model seemed rather poorly constrained. How many parameters are in the model shown in Figure 6A? How many of them are well constrained by experimental measurements? The authors also don't perform sensitivity analysis on the parameters of the model. And ultimately, the conclusion over the model in Figure 7 is somewhat trivial within the unitless construction: larger amplitude and longer duration stimuli lead to increased activation of the downstream neuron thought to lead to the downward swim behavior. I could imagine that a large family of models would arrive at this same result, and without units, there is no way to really test it with new behavioral experiments.

Reviewer #2 (Public Review):

Kleinman and colleagues conducted an analysis of two datasets, one recorded from DLPFC in one monkey and the other from PMD in two monkeys. They also performed similar analyses on trained RNNs with various architectures.

The study revealed four main findings. (1) All task variables (color coherence, target configuration, and choice direction) were found to be encoded in DLPFC. (2) PMD, an area downstream of PFC, only encoded choice direction. (3) These empirical findings align with the celebrated 'information bottleneck principle,' which suggests that FF networks progressively filter out task-irrelevant information. (4) Moreover, similar results were observed in RNNs with three modules.

While the analyses supporting results 1 and 2 were convincing and robust, I have some concerns and recommendations regarding findings 3 and 4, which I will elaborate on below. It is important to note that findings 2 and 4 had already been reported in a previous publication by the same authors (ref. 43).

Major recommendation/comments:<br /> The interpretation of the empirical findings regarding the communication subspace in relation to the information bottleneck theory is very interesting and novel. However, it may be a stretch to apply this interpretation directly to PFC-PMd, as was done with early vs. late areas of a FF neural network.

In the RNN simulations, the main finding indicates that a network with three or more modules lacks information about the stimulus in the third or subsequent modules. The authors draw a direct analogy between monkey PFC and PMd and Modules 1 and 3 of the RNNs, respectively. However, considering the model's architecture, it seems more appropriate to map Area 1 to regions upstream of PFC, such as the visual cortex, since Area 1 receives visual stimuli. Moreover, both PFC and PMd are deep within the brain hierarchy, suggesting a more natural mapping to later areas. This contradicts the CCA analysis in Figure 3e. It is recommended to either remap the areas or provide further support for the current mapping choice.

Reviewer #2 (Public Review):

Summary:<br /> One often wishes to combine activation of a neural population via red light with simultaneous modulation of a different population via blue light, or simultaneous imaging of a blue-excited fluorescent reporter. The problem is that all red-shifted opsins have an action spectrum with a long blue tail, leading to spurious opsin activation by blue light.

This valuable paper presents a clever solution to this problem, by pairing an engineered blue-shifted inhibitory chloride-conducting opsin with a red-shifted excitatory opsin. The combined effect is excitation by red light and shunting inhibition by blue light. The paper is very thorough, with convincing spectroscopic and patch clamp characterization of the tools, and tests in brain slices and in vivo. This tool is likely to be useful in the neuroscience community.

Strengths:<br /> The methods are solid, including the complete characterization of each tool separately, as well as the combination in vivo. The array of testing gives a strong degree of confidence that this tool will work as expected.

Weaknesses:<br /> There are two discussion points and one experimental point which would make the paper stronger.

1) In the Introduction or Discussion, the authors could better motivate the need for a red-shifted actuator that lacks blue crosstalk, by giving some specific examples of how the tool could be productively used, e.g. pairing with another blue-shifted excitatory opsin in a different population, or pairing with a GFP-based fluorescent indicator, e.g. GCaMP. The motivation for the current tool is not obvious to non-experts.

2) Simultaneous excitation and inhibition are not the same as non-excitation. The authors mentioned shunting briefly. Another possible issue is changes in osmotic balance. Activation of a Na+ channel and a Cl- channel will lead to net import of NaCl into the cell, possibly changing osmotic pressure. Please discuss.

3) The authors showed that in ZipT-IvfChr, orange light drives excitation and blue light does not. But what about simultaneous blue and orange light? Can the blue light overwhelm the effect of the orange light? Since the stated goal is to open the blue part of the spectrum for other applications, one is now worried about "negative" crosstalk. Please discuss and, ideally, characterize this phenomenon.<br /> 3.1) Does the use of the new tool require careful balancing of the expression levels of the ZipT and the IvfChr? Does it require careful balancing of blue and orange light intensities?<br /> 3.2) Also, many opsins show complex and nonlinear responses to dual-wavelength illumination, so each component should be characterized individually under simultaneous blue + orange light.<br /> 3.3) I was expecting to see photocurrents at different holding potentials as a function of illumination wavelength for the co-expressed construct (i.e. to see at what wavelength it switches from being excitatory to inhibitory); and also to see I-V curves of the photocurrent at blue and orange wavelengths for the co-expressed constructs (i.e. to see the reversal potential under blue excitation). Overall, the patch clamp and spectroscopic characterization of the individual constructs was stronger than that of the combined constructs.

Reviewer #2 (Public Review):

Summary:<br /> Silva et al. describe an experimental study conducted on cerebellar parallel fiber-to-molecular interneuron synapses to investigate the size of the readily releasable pool (RRP) of synaptic vesicles (SVs) per docking site in response to trains of action potentials. The study aims to determine whether there are multiple binding sites for SVs at each docking site, which could lead to a higher RRP size than previously thought.

The researchers used this glutamatergic synapse to conduct their experiments. They employed various techniques and manipulations to enhance release probability, docking site occupancy, and synaptic depression. By counting the number of released SVs in response to action potential trains and normalizing the results based on the number of docking sites, they estimated the RRP size per docking site.

The key findings and observations in the manuscript are as follows:

Docking Site Occupancy and Release Probability Enhancement: The researchers used 4-amidopyridine (4-AP) and post-tetanic potentiation (PTP) protocols to enhance the release probability of docked SVs and the occupancy of docking sites, respectively.

Synchronous and Asynchronous Release: Synchronous release refers to SVs released in response to individual action potentials, while asynchronous release involves SVs released after the initial release response due to calcium elevation. The study observed changes in the balance between synchronous and asynchronous release under different conditions, revealing the degree of filling of the RRP.

Modeling of Release Dynamics: The researchers employed a modeling approach based on the "replacement site/docking site" (RS/DS) model, where SVs bind to a replacement site before moving to a docking site and eventually undergoing release. The model was adjusted to experimental conditions to estimate parameters like docking site occupancy and release probabilities.

Comparison of Different Models: The study compared the RS/DS model with an alternative model known as the "loosely docked/tightly docked" (LS/TS) model. The LS/TS model assumes that a docking site can only accommodate one SV at a time, while the RS/DS model considers the possibility of accommodating multiple SVs.

Maximum RRP Size: Through a combination of experimental results and model simulations, the study revealed that the maximum RRP size per docking site reached close to two SVs under certain conditions, supporting the idea that each docking site can accommodate multiple SVs.

Strengths:<br /> The study is rigorously conducted and takes into consideration the previous work on RRP size and SV docking site estimation. The study addresses a long-standing question in synaptic physiology.

Weaknesses:<br /> It remains unclear how generalizable the findings are to other types of synapses.

Reviewer #2 (Public Review):

Pak et al. report on a study using a computational method to assess differences in the relative proportion of six canonical brain cell types, across eleven neurodegenerative classes (defined as both clinical syndromes (e.g. FTD, PD), groups of neurogenerative diseases (e.g. 4-repeat tauopathies) or distinct neuropathological entities (e.g. FTLD-TDP type C), as they relate to a standard map of class-dependent volume loss. The study uses innovative methods and is commendable in its goal to highlight the contribution of non-neuronal cell types to the pathobiology of neurodegeneration. The findings of the study are in part contradicting expected results based on extensive literature on the biology of these diseases. The authors based their methodology on the use of a deconvolutional cell classifier; however, do not extensively recognize that their data on gene expression are based on normal brain levels rather than on diseased ones. Also, while predicted levels are uniquely based on patterns of brain atrophy, it is not possible to know whether this strategy is generalizable to all diseases (for instance, it is known that pure DLB, PD and ALS are not associated with extensive brain atrophy), or even adequately comparable between subtypes of diseases within the same class (e.g., different forms of FTLD). The authors do not acknowledge that only data based on true neuropathological assessment may prove whether their findings are true. Subject characteristics, numbers, and diagnostic criteria are hard to assess and only described in the methods section. This format prevents the reader from assessing data robustness while going through the results, especially when fundamental biological bases of nomenclature and differences between clinical syndromes and pathological entities are omitted or uncharacteristically provided.

Reviewer #2 (Public Review):

Summary:<br /> This study links rare human loss of function mutations in the zinc transporter family member SLC39A5 to increased circulating and hepatic concentrations of this trace element. Beneficial metabolic changes were observed in a corresponding convincing mouse model relevant to the development of NASH.

Strengths:<br /> Authors combine human exome sequencing data, meta-analysis of four large European cohorts, and a patient recall approach to link the rare loss of function variants of SLC39A5 to the phenotype and protection from T2DM.

Using a SLC39A5-null mouse model challenged either by cross-breeding with Lepr-/- mice or diet-induced obesity they unravel the metabolic impact of elevated circulating and hepatic zinc concentration with respect to T2DM, glucose homeostasis, hepatic steatosis, and NASH development. Some mechanistic aspects and a remarkable sex difference in the outcome are identified from mouse ex vivo readouts and supported by in vitro hepatocyte cellular studies. Authors present evidence that increased hepatic zinc concentrations inhibit zinc-regulated phosphatases resulting in activation of AMPK and AKT signalling with consequences for lipid and glucose metabolism and insulin sensitivity.

Weaknesses:<br /> The reasons for the observed sex differences in the metabolic consequences of SLC39A5 inactivation in the mouse models remain unclear. While heterozygous rare SLC39A5 variants show distinct phenotypes only SLC39A5-null mice and no heterozygous mice are studied. The role of SLC39A5 in pancreatic islets and on insulin secretion remains unclear because authors do not address data published recently that claim a relevant role of SLC39A5 in b-cell function and glucose tolerance.

Reviewer #2 (Public Review):

Medwig-Kinney et al. explore the role of the transcription factor NHR-67 in distinguishing between AC and VU cell identity in the C. elegans gonad. NHR-67 is expressed at high levels in AC cells where it induces G1 arrest, a requirement for the AC fate invasion program (Matus et al., 2015). NHR-67 is also present at low levels in the non-invasive VU cells and, in this new study, the authors suggest a role for this residual NHR-67 in maintaining VU cell fate. What this new role entails, however, is not clear.

The authors present two models: 1) That NHR-67 switches from a transcriptional activator in ACs to a transcriptional repressor in VUs by virtue of recruiting translational repressors, or 2) that these interactions sequester NHR-67 away from its transcription targets in VU cells. Neither model is fully supported by the data, leaving a paper with extensive data but no single compelling conclusions, and leaving open the question of what is the function, if any, of NHR-67 condensates in VU cells?

While the authors report on interesting observations, in particular the co-localization of NHR-67 with UNC-37/Groucho and POP-1 in nuclear puncta, the functional significance of these observations remains unclear. The authors have not demonstrated that the "repressive condensates" are functional and play a role in the suppression of AC fate in VU cells as claimed. The colocalization data suggest that NHR-67 interacts with repressors, but additional experiments are needed to demonstrate that these interactions are specific to VUs, impact VU fate, and sequester NHR-67 from its targets or transform NHR-67 into a transcriptional repressor.

[Editor's note: we feel that the current state of the data with respect to this question is best captured in the response by the authors to the original concerns expressed by reviewer 2, which we include in abbreviated form here]

1) The authors report that NHR-67 forms "repressive condensates" (aka. puncta) in the nuclei of VU cells and imply that these condensates prevent VU cells from becoming ACs. However, there are also examples of AC cells presented that have NHR-67 puncta (these are less obvious simply due to the higher levels of NHR-67 in ACs). Similarly, there also are UNC-37 and LSY-22 also puncta in ACs. The presence of NHR-67 puncta in the AC seems to directly contradict the author's assumption that the puncta repress the AC fate.

RESPONSE: The puncta formed by NHR-67 in the AC are different in appearance than those observed in the VU cells and furthermore do not exhibit strong colocalization with that of UNC-37 or LSY-22. The Manders' overlap coefficient between NHR-67 and UNC-37 is 0.181 in the AC, whereas it is 0.686 in the VU cells. Likewise, the Manders' overlap coefficient between NHR-67 and LSY-22 is 0.189 in the AC compared to 0.741 in the VU cells. We speculate that the areas of NHR-67 subnuclear enrichment in the AC may represent concentration around transcriptional targets, but testing this would require knowledge of direct targets of NHR-67.

2) While a pool of NHR-67 localizes to "repressive condensates", it appears that a substantial portion of NHR-67 also exists diffusively in the nucleoplasm. This would appear to contradict a "sequestration model" since, for such a model to work, a majority of NHR-67 should be in puncta? What proportion of NHR-67 is in puncta? Is the concentration of NHR-67 in the nucleoplasm lower in VUs compared to ACs and does this depend on the puncta?

RESPONSE: The proportion of NHR-67 localizing to puncta versus the nucleoplasm is dynamic, as these puncta form and dissolve over the course of the cell cycle. However, we estimate that approximately 25-40% of NHR-67 protein resides in puncta based on segmentation and quantification of fluorescent intensity. We also measured NHR-67 concentration in the nucleoplasm of VU cells and found that it is only 28% of what is observed in ACs (n = 10). We also disagree with the notion that the majority of NHR-67 protein should be located in puncta to support the sequestration model. As one example, previously published work examining phase separation of endogenous YAP shows that it is present in the nucleoplasm in addition to puncta (Cai et al., 2019, doi: 10.1038/s41556-019-0433-z). In our system, it is possible that the combination of transcriptional downregulation and partial sequestration away from DNA is sufficient to disrupt the normal activity of NHR-67.

3) The authors do not report whether NHR-67, UNC-37, LSY-22, or POP-1 localization to puncta is interdependent, as implied by their model.

RESPONSE: We based our model, shown in Fig. 7E, on known or predicted protein-protein interactions, which we confirmed through yeast two-hybrid analyses (Fig. 7D; Fig. 7-figure supplement 1). It is difficult to test whether localization of these proteins to puncta is interdependent, as a perturbation of UNC-37, LSY-22, and POP-1 result in ectopic ACs. Trying to determine if loss of puncta results in VU-to-AC transdifferentiation or vice versa becomes a chicken-egg argument. It is also possible that UNC-37 and LSY-22 are at least partially redundant in this context.

4) The evidence that the "repressor condensates" suppress AC fate in VUs is presented in Fig. 4D where the authors deplete the presumed repressor LSY-22. First, the authors do not examine whether NHR-67 forms puncta under these conditions. Second, the authors rely on a single marker (cdh-3p::mCherry::moeABD) to score AC fate: this marker shows weak expression in cells flanking one bright cell (presumably the AC) which the authors interpret as a VU AC transformation. The authors, however, do not identify the cells that express the marker by lineage analyses and dismiss the possibility that the marker-positive cells could arise from the division of an AC-committed cell. Finally, the authors did not test whether marker expression was dependent on NHR-67, as predicted by the model shown in Fig. 7.

RESPONSE: For the auxin-inducible degron experiments, strains contained labeled AID-tagged proteins, a labeled TIR1 transgene, and a labeled AC marker. Thus, we were limited by the number of fluorescent channels we could covisualize and therefore could not also visualize NHR-67 (to assess for puncta formation) or another AC marker (such as LAG-2). We could have generated an AID-tagged LSY-22 strain without a fluorescent protein, but then we would not be able to quantify its depletion, which this reviewer points out is important to measure. We did visualize NHR-67::GFP expression following RNAi-induced knockdown of POP-1 and observed consistent loss of puncta in ectopic ACs. However, it is unclear whether cell fate change causes loss of puncta or vice-versa.

5) Interaction between NHR-67 and UNC-37 is shown using Y2H, but not verified in vivo. Furthermore, the functional significance of the NHR-67/UNC-37 interaction is not tested.

We attempted to remove the intrinsically disordered region found at the C-terminus of the endogenous nhr-67 locus, using CRISPR/Cas9, as this would both confirm the NHR-67/UNC-37 interaction in vivo and allow us to determine the functional significance of this interaction. However, we were unable to recover a viable line after several attempts, suggesting that this region of the protein is vital.

6) Throughout the manuscript, the authors do not use lineage analysis to confirm fate transformation as is the standard in the field. There are 4 multipotential gonadal cells with the potential to differentiate into VUs or ACs. Which ones contribute to the extra ACs in the different genetic backgrounds examined was not determined, which complicates interpretation. The authors should consider and test the following possibilities: disruption of NHR-67 regulation causes 1) extra pluripotent cells to directly become ACs early in development, 2) causes VU cells to gradually trans-fate to an AC-like fate after VU fate specification (as implied by the authors), or 3) causes an AC to undergo extra cell division(s)? In Fig. 1F, 5 cells are designated as ACs, which is one more that the 4 precursors depicted in Fig. 1A, implying that some of the "ACs" were derived from progenitors that divided.

The timing between AC/VU cell fate specification and AC invasion (the point at which we look for differentiated ACs) is approximately 10-12 hours at 25 {degree sign}C. With our imaging setup, we are limited to approximately 3-4 hours of live-cell imaging. Therefore, lineage tracing was not feasible for our experiments. Instead, we relied on visualization of established markers of AC and VU cell fate to determine how ectopic ACs arose. In Fig. 6B,C we show that the expression of two AC markers (cdh-3 and lag-2) turn on while a VU marker (lag-1) gets downregulated within the same cell. In our opinion, live-imaging experiments that show in real time changes in cell fate via reporters was the most definitive way to observe the phenotype.

7) There are 4 multipotential gonadal cells with the potential to differentiate into VUs or ACs. Which ones contribute to the extra ACs in the different genetic backgrounds examined was not determined, which complicates interpretation. The authors should consider and test the following possibilities: disruption of NHR-67 regulation causes 1) extra pluripotent cells to directly become ACs early in development, 2) causes VU cells to gradually trans-fate to an AC-like fate after VU fate specification (as implied by the authors), or 3) causes an AC to undergo extra cell division(s)?? In Fig. 1F, 5 cells are designated as ACs, which is one more that the 4 precursors depicted in Fig. 1A, implying that some of the "ACs" were derived from progenitors that divided.

RESPONSE: When trying to determine the source of the ectopic ACs, we considered the three possibilities noted by the reviewer: (1) misspecification of AC/VU precursors, (2) VU-to-AC transdifferentiation, or (3) proliferation of the AC. We eliminated option 3 as a possibility, as the ectopic ACs we observed here were invasive and all of our previous work has shown that proliferating ACs cannot invade and that cell cycle exit is necessary for invasion (Matus et al., 2015; MedwigKinney & Smith et al., 2020; Smith et al., 2022). Specifically, NHR-67 is upstream of the cyclin dependent kinase CKI-1 and we found that induced expression of NHR-67 resulted in slow growth and developmental arrest, likely because of inducing cell cycle exit. For our experiment using hsp::NHR-67, we induced heat shock after AC/VU specification. For POP-1 perturbation, we explicitly acknowledged that misspecification of the AC/VU precursors could also contribute to ectopic ACs (Fig. 6A; lines 368-385). We could not achieve robust protein depletion through delayed RNAi treatment, so instead we utilized timelapse microscopy and quantification of AC and VU cell markers (Fig. 6B,C; see response 2.7 above).

Reviewer #2 (Public Review):

This work clarifies neural mechanisms that can lead to a phenomenology consistent with motor preparation in its broader sense. In this context, motor preparation refers to an activity that occurs before the corresponding movement. Another property often associated with preparatory activity is a correlation with global movement characteristics such as reach speed (Churchland et al., Neuron 2006), reach angle (Sun et al., Nature 2022), or grasp type (Meirhaeghe et al., Cell Reports 2023). Such activity has notably been observed in premotor and primary motor cortices, and it has been hypothesized to serve as an input to a motor execution circuit. The timing and mechanisms by which such 'preparatory' inputs are made available to motor execution circuits remain however unclear in general, especially in light of the presence of a 'trigger-like' signal that appears to relate to the transition from preparatory dynamics to execution activity (Kaufman et al. eNeuron 2016, Iganaki et al., Cell 2022, Zimnik and Churchland, Nature Neuroscience 2021).

The preparatory inputs have been hypothesized to fulfill one or several (non-mutually-exclusive) possible objectives. Two notable hypotheses are that these inputs could be shaped to maximize output accuracy under regularization of the input magnitude; or that they may help the flexible re-use of the neural machinery involved in the control of movements in different contexts.

Here, the authors investigate in detail how the former hypothesis may be compatible with the presence of early inputs in recurrent network models driving arm movements, and compare models to data.

Strengths:

The authors are able to deploy an in-depth evaluation of inputs that are optimized for producing an accurate output at a pre-defined time while using a regularization term on the input magnitude, in the case of movements that are thought to be controlled in a quasi-open loop fashion such as reaches.

First, the authors have identified that optimal control theory is a great framework to study this question as it provides methods to find and analyze exact solutions to this cost function in the case of models with linear dynamics. The authors not only use this framework to get an exact assessment of how much activity before movement start happens in large recurrent networks, but also give insight into the mechanisms by which it happens by dissecting in detail low-dimensional networks. The authors find that two key network properties - observability of the readout's nullspace and limited controllability - give rise to optimal inputs that are large before the start of the movement (while the corresponding network activity lies in the nullspace of the readout). Further, the authors numerically investigate the timing of optimized inputs in models with nonlinear dynamics, and find that pre-movement inputs can also arise in these more general networks. Finally, the authors point out some coarse-grained similarities between the pre-movement activity driven by the optimized inputs in some of the models they studied, and the phenomenology of preparation observed in the brain during single reaches and reach sequences. Overall, the authors deploy an impressive arsenal of tools and a very in-depth analysis of their models.

Limitations:

1. Though the optimal control theory framework is ideal to determine inputs that minimize output error while regularizing the input norm, it however cannot easily account for some other varied types of objectives - especially those that may lead to a complex optimization landscape. For instance, the reusability of parts of the circuit, sparse use of additional neurons when learning many movements, and ease of planning (especially under uncertainty about when to start the movement), may be alternative or additional reasons that could help explain the preparatory activity observed in the brain. It is interesting to note that inputs that optimize the objective chosen by the authors arguably lead to a trade-off in terms of other desirable objectives. Specifically, the inputs the authors derive are time-dependent, so a recurrent network would be needed to produce them and it may not be easy to interpolate between them to drive new movement variants. In addition, these inputs depend on the desired time of output and therefore make it difficult to plan, e.g. in circumstances when timing should be decided depending on sensory signals. Finally, these inputs are specific to the full movement chain that will unfold, so they do not permit reuse of the inputs e.g. in movement sequences of different orders.

2. Relatedly, if the motor circuits were to balance different types of objectives, the activity and inputs occurring before each movement may be broken down into different categories that may each specialize into one objective. For instance, previous work (Kaufman et al. eNeuron 2016, Iganaki et al., Cell 2022, Zimnik and Churchland, Nature Neuroscience 2021) has suggested that inputs occurring before the movement could be broken down into preparatory inputs 'stricto sensu' - relating to the planned characteristics of the movement - and a trigger signal, relating to the transition from planning to execution - irrespective of whether the movement is internally timed or triggered by an external event. The current work does not address which type(s) of early input may be labeled as 'preparatory' or may be thought of as a part of 'planning' computations.

3. While the authors rightly point out some similarities between the inputs that they derive and observed preparatory activity in the brain, notably during motor sequences, there are also some differences. For instance, while both the derived inputs and the data show two peaks during sequences, the data reproduced from Zimnik and Churchland show preparatory inputs that have a very asymmetric shape that really plummets before the start of the next movement, whereas the derived inputs have larger amplitude during the movement period - especially for the second movement of the sequence. In addition, the data show trigger-like signals before each of the two reaches. Finally, while the data show a very high correlation between the pattern of preparatory activity of the second reach in the double reach and compound reach conditions, the derived inputs appear to be more different between the two conditions. Note that the data would be consistent with separate planning of the two reaches even in the compound reach condition, as well as the re-use of the preparatory input between the compound and double reach conditions. Therefore, different motor sequence datasets - notably, those that would show even more coarticulation between submovements - may be more promising to find a tight match between the data and the author's inputs. Further analyses in these datasets could help determine whether the coarticulation could be due to simple filtering by the circuits and muscles downstream of M1, planning of movements with adjusted curvature to mitigate the work performed by the muscles while permitting some amount of re-use across different sequences, or - as suggested by the authors - inputs fully tailored to one specific movement sequence that maximize accuracy and minimize the M1 input magnitude.

4. Though iLQR is a powerful optimization method to find inputs optimizing the author's cost function, it also has some limitations. First, given that it relies on a linearization of the dynamics at each timestep, it has a limited ability to leverage potential advantages of nonlinearities in the dynamics. Second, the iLQR algorithm is not a biologically plausible learning rule and therefore it might be difficult for the brain to learn to produce the inputs that it finds. It remains unclear whether using alternative algorithms with different limitations - for instance, using variants of BPTT to train a separate RNN to produce the inputs in question - could impact some of the results.

5. Under the objective considered by the authors, the amount of input occurring before the movement might be impacted by the presence of online sensory signals for closed-loop control. It is therefore an open question whether the objective and network characteristics suggested by the authors could also explain the presence of preparatory activity before e.g. grasping movements that are thought to be more sensory-driven (Meirhaeghe et al., Cell Reports 2023).

Reviewer #2 (Public Review):

Summary<br /> In this experiment, Voltage Sensitive Dye Imaging (VSDI) was used to measure neural activity in macaque primary visual cortex in monkeys trained to detect an oriented grating target that was presented either alone or against an oriented mask. Monkeys' ability to detect the target (indicated by a saccade to its location) was impaired by the mask, with the greatest impairment observed when the mask was matched in orientation to the target, as is also the case in human observers. VSDI signals were examined to test the hypothesis that the target-evoked response would be maximally suppressed by the mask when it matched the orientation of the target. In each recording session, fixation trials were used to map out the spatial response profile and orientation domains that would then be used to decode the responses on detection trials. VSDI signals were analyzed at two different scales: a coarse scale of the retinotopic response to the target and a finer scale of orientation domains within the stimulus-evoked response. Responses were recorded in three conditions: target alone, mask alone, and target presented with mask. Analyses were focused on the target evoked response in the presence of the mask, defined to be the difference in response evoked by the mask with target (target present) versus the mask alone (target absent). These were computed across five 50 msec bins (total, 250 msec, which was the duration of the mask (target present trials, 50% of trials) / mask + target (target present trials, 50% of trials). Analyses revealed that in an initial (transient) phase the target evoked response increased with similarity between target and mask orientation. As the authors note, this is surprising given that this was the condition where the mask maximally impaired detection of the target in behavior. Target evoked responses in a later ('sustained') phase fell off with orientation similarity, consistent with the behavioral effect. When analyzed at the coarser scale the target evoked response, integrated over the full 250 msec period showed a very modest dependence on mask orientation. The same pattern held when the data were analyzed on the finer orientation domain scale, with the effect of the mask in the transient phase running counter to the perceptual effect of the mask and the sustained response correlating the perceptual effect. The effect of the mask was more pronounced when analyzed at the scale.

Strengths<br /> The work is on the whole very strong. The experiments are thoughtfully designed, the data collection methods are good, and the results are interesting. The separate analyses of data at a coarse scale that aggregates across orientation domains and a more local scale of orientation domains is a strength and it is reassuring that the effects at the more localized scale are more clearly related to behavior, as one would hope and expect. The results are strengthened by modeling work shown in Figure 8, which provides a sensible account of the population dynamics. The analyses of the relationship between VSDI data and behavior are well thought out and the apparent paradox of the anti-correlation between VSDI and behavior in the initial period of response, followed by a positive correlation in the sustained response period is intriguing.

Points to Consider / Possible Improvements<br /> The biphasic nature of the relationship between neural and behavioral modulation by the mask and the surprising finding that the two are anticorrelated in the initial phase are left as a mystery. The paper would be more impactful if this mystery could be resolved.

The finding is based on analyses of the correlation between behavior and neural responses. This appears in the main body of the manuscript and is detailed in Figures S1 and S2, which show the correlation over time between behavior and target response for the retinotopic and columnar scale.

One possible way of thinking of this transition from anti- to positive correlation with behavior is that it might reflect the dynamics of a competitive interaction between mask and target, with the initial phase reflecting predominantly the mask response, with the target emerging, on some trials, in the latter phase. On trials when the mask response is stronger, the probability of the target emerging in the latter phase, and triggering a hit, might be lower, potentially explaining the anticorrelation in the initial phase. The sustained response may be a mixture of trials on which the target response is or is not strong enough to overcome the effect of the mask sufficiently to trigger target detection.

It would, I think, be worth examining this by testing whether target dynamics may vary, depending on whether the monkey detected the target (hit trials) or failed to detect the target (miss trials). Unless I missed it I do not think this analysis was done. Consistent with this possibility, the authors do note (lines 226-229) that "The trajectories in the target plus mask conditions are more complex. For example, when mask orientation is at +/- 45 deg to the target, the population response is initially dominated by the mask, but then in mid-flight, the population response changes direction and turns toward the direction of the target orientation." This suggests (to this reviewer, at least) that the emergence of a positive correlation between behavioral and neural effects in the latter phase of the response could reflect either a perceptual decision that the target is present or perhaps deployment of attention to the location of the target.

It may be that this transition reflected detection, in which it might be more likely on hit trials than miss trials. Given the SNR it would presumably be difficult to do this analysis on a trial-by-trial basis, but the hit and miss trials (which make each make up about 1/2 of all trials) could be averaged separately to see if the mid-flight transition is more prominent on hit trials. If this is so for the +/- 45 degree case it would be good to see the same analysis for other combinations of target and mask. It would also be interesting to separate correct reject trials from false alarms, to determine whether the mid-flight transition tends to occur on false alarm trials.

If these analyses do not reveal the predicted pattern, they might still merit a supplemental figure, for the sake of completeness.

Reviewer #2 (Public Review):

The authors of this study investigated the relationship between (under)confidence and the anxious-depressive symptom dimension in a longitudinal intervention design. The aim was to determine whether confidence bias improves in a state-like manner when symptoms improve. The primary focus was on patients receiving internet-based CBT (iCBT; n=649), while secondary aims compared these changes to patients receiving antidepressants (n=82) and a control group (n=88).

The results support the authors' conclusions, and the authors convincingly demonstrated a weak link between changes in confidence bias and anxious-depressive symptoms (not specific to the intervention arm)

The major strength and contribution of this study is the use of a longitudinal intervention design, allowing the investigation of how the well-established link between underconfidence and anxious-depressive symptoms changes after treatment. Furthermore, the large sample size of the iCBT group is commendable. The authors employed well-established measures of metacognition and clinical symptoms, used appropriate analyses, and thoroughly examined the specificity of the observed effects.

However, due to the small expected effect sizes, the comparisons with the antidepressant and control groups were underpowered, reducing comparability between interventions and the generalizability of the results. The lack of interaction effect with treatment makes it harder to interpret the observed differences in confidence.

Reviewer #2 (Public Review):

This work explored the biological functions of a small family of RNA-binding proteins that was previously studied in animals, but was uncharacterized in plants. Combinatorial T-DNA insertional mutants disrupting the expression of the four Mushashi-like (MSIL) genes in Arabidopsis revealed that only the msil2 msil4 double mutant visibly alters plant development. The msil2/4 plants produced stems that could not stand upright. Transgene complementation, site-directed mutagenesis of MSIL4 conserved RNA-binding motifs, and in vitro RNA binding assays support the conclusion that the loss of MSIL2 and MISL4 function is responsible for the observed morphological defects. MSIL2/4 interact with proteins associated with mRNA 3'UTR binding and translational regulation.

The authors present compelling biochemical evidence that Mushashi-like2 (MSIL2) and MSIL4 jointly regulate secondary cell wall biosynthesis in the Arabidopsis stem. Quantitative analyses of proteins and transcripts in msil2/4 stems uncovered transcriptional upregulation of several xylan-related enzymes (despite WT-like RNA levels). Consistent with MALDI-TOF data for released xylan oligosaccharides, the authors propose a model in which MSIL2/4 negatively regulate the translation of GXM (glucuronoxylan methyltransferase), a presumed rate-limiting step. The molecular links between overmethylated xylans and the observed stem defects (which include subtle reductions in lignin and increases beta-glucan polymer distribution) warrants further investigation in future studies. Similarly, as the authors point out, it is intriguing that the loss of the broadly expressed MSIL2/4 genes only significantly affects specific cell types in the stem.

Reviewer #2 (Public Review):

Summary: The authors provide a nice summary on the possibility to study genetic heterogeneity and how to measure the dynamics of stem cells. By combining single cell and bulk sequencing analyses, they aim to use a stochastic process and inform on different aspects of genetic heterogeneity.

Strengths: Well designed study and strong methods

Weaknesses: Minor<br /> Further clarification to Figure 3 legend would be good to explain the 'no association' of number of samples and mutational burden estimate as per line 180-182 p.8

Reviewer #2 (Public Review):

Summary:<br /> The authors set out to characterise "trust" in terms of a spatial pattern of neural responses, and then validate whether different tasks, in different datasets, express this pattern or do not express it, according to their hypotheses. They based their approach on linear classifiers (Support Vector Machines), which they trained to distinguish trust from distrust in an investment game, and then applied the classifier to other datasets. Additionally, they performed visualisations of the similarity among participants and among tasks in their neural responses, using dimensionality reduction techniques.

Strengths:<br /> The key strength of this study is the use of multiple datasets to test whether a single study's characterisation of trust, in terms of a spatial pattern of neural responses, generalises to other tasks and populations. This is a nice use for existing data, which bolsters the interpretation of fMRI results, demonstrating that they are generalisable. While I am not a specialist in decoding methods, the analyses appear to have been performed conscientiously and to a high standard. The manuscript is also clearly written.

Weaknesses:<br /> It's worth noting an obvious but important statistical point. In this study, the *inability* of a classifier to distinguish between conditions in particular datasets is taken as evidence that those conditions do not differ in terms of the effect of interest (trust). In this case, these results make sense, in that they are consistent with the authors' hypotheses. However, there are various reasons why the classifier may not work well on particular datasets - e.g. differences in noise, or a lack of linear separability between patterns (which might mandate a non-linear classifier or a different SVM kernel). Therefore, any null result obtained with classical statistics should be interpreted with caution.

Reviewer #2 (Public Review):

Summary:

This study by Park and Gross investigates the spatiotemporal neural representation of semantic information most pertinent to the gist of speech materials presented to subjects as magnetoencephalography was recorded. Participants heard and saw naturalistic continuous speech recordings (with the auditory component presented to one ear), while also presented with distractor auditory speech (presented in the other ear). Participants were instructed to attend to the speech stream that matched the video of the speaker. The stimuli were semantically parsed to create short segments to which topic probabilities were assigned. These segments were then organized into high and low topic probabilities for each of the four topics (determined using Latent Dirichlet Allocation (LDA) analysis). The results suggest clear differences in the fidelity of neural encoding of the speech envelope during high-topic probability segments, which is interpreted as the brain representing key information for a story whether that information is explicitly attended to.

Strengths:<br /> The use of LDA analysis makes possible the quantification of whether a particular speech segment is relevant to a particular topic and enables analysis based on this high-temporal resolution of semantic salience. The authors show clear differences between attended and unattended speech conditions, as well as, surprisingly, differences between semantically salient unattended speech and attended, less semantically relevant speech.

Weaknesses:<br /> Though the effect sizes of the results of this study show clear differences between stimulus conditions, clarification of the experimental methods is needed to appreciate their interpretation. Broadly, I would suggest adding a clearer description of the task during data collection, even though it has been published elsewhere.

One key piece of information that is missing is how semantically relevant topics are assigned, so that salient semantic information can be compared between attended and unattended stories. It's unclear to me how results are combined across topics and stories. If a particular speech segment is assigned 4 topic probabilities, that segment has both a high probability of belonging to one topic and a low probability of belonging to another. I understand how this can be used to create the experimental conditions for a single topic, but how are results combined across topics?

I think some discussion of using the encoding and decoding of the speech envelope as a measure of what is semantically relevant is warranted. The fidelity with which the speech envelop is represented has been used as a proxy for how well that speech is attended to, but it is unclear to me whether we should expect to see high-fidelity encoding of speech envelop outside of the primary and secondary auditory regions of the brain, or how it relates to the semantic information contained in the speech signal.

Additionally, I wonder if it might be more informative to decode the topic labels themselves directly by building a model to predict the topic probabilities from the neural data? This might give a more direct measure of where and when semantically relevant information is represented.

Reviewer #2 (Public Review):

In the current study, Fischer and colleagues extensively examined the role of parthenolide in inhibiting microtubule detyrosination and making the mechanistic link for the compound to facilitate the role of IL6 and PTEN/KO in promoting neurite outgrowth and axon regeneration. The in vitro and mechanistic work laid the foundation for the authors to reach several key predictions that such detyrosination can be applied for in vivo applications. Thus the authors extended the work to optic nerve regeneration and spinal cord recovery. The in vivo compound that the authors utilized is DMAPT, which plays a synergistic role with existing pro-regeneration therapies, such as Il6 treatment.

The major strength of the work is the first half of the mechanistic inquiries, where the authors combined cell biology and biochemistry approaches to dissect the mechanistic link from parthenolide to microtube dynamics. The shortcoming is that the in vivo data is limited, and the effects might be considered mild, especially by benchmarking with other established and effective strategies.

The work is solid and prepares a basis for others to test the role of DMAPT in other settings, especially in the setting of other effective pro-regenerative approaches. With the goal of comprehensive and functional recovery in vivo, the impact of the work and the utilities of the methods remain to be tested broadly in other models in vivo.

Reviewer #2 (Public Review):

Place cells fire sequentially during hippocampal theta oscillations, forming a spatial representation of behavioral experiences in a temporally-compressed manner. The firing sequences during theta cycles are widely considered as essential assemblies for learning, memory, and planning. Many theoretical studies have investigated the mechanism of hippocampal theta firing sequences; however, they are either entirely extrinsic or intrinsic. In other words, they attribute the theta sequences to external sensorimotor drives or focus exclusively on the inherent firing patterns facilitated by the recurrent network architectures. Both types of theories are inadequate for explaining the complexity of the phenomena, particularly considering the observations in a previous paper by the authors: theta sequences independent of animal movement trajectories may occur simultaneously with sensorimotor inputs (Yiu et al., 2022).

In this manuscript, the authors concentrate on the CA3 area of the hippocampus and develop a model that accounts for both mechanisms. Specifically, the model generates extrinsic sequences through the short-term facilitation of CA3 cell activities, and intrinsic sequences via recurrent projections from the dentate gyrus. The model demonstrates how the phase precession of place cells in theta sequences is modulated by running direction and the recurrent DG-CA3 network architecture. To evaluate the extent to which firing sequences are induced by sensorimotor inputs and recurrent network architecture, the authors use the Pearson correlation coefficient to measure the "intrinsicity" and "extrinsicity" of spike pairs in their simulations.

I find this research topic to be both important and interesting, and I appreciate the clarity of the paper. The idea of combining intrinsic and extrinsic mechanisms for theta sequences is novel, and the model effectively incorporates two crucial phenomena: phase precession and directionality of theta sequences. I particularly commend the authors' efforts to integrate previous theories into their model and conduct a systematic comparison. This is exactly what our community needs: not only the development of new models, but also understanding the critical relationships between different models.

Reviewer #2 (Public Review):

Summary:<br /> This work investigates the effects of various antipsychotic drugs on cortical responses during visuomotor integration. Using wide-field calcium imaging in a virtual reality setup, the researchers compare neuronal responses to self-generated movement during locomotion-congruent (closed loop) or locomotion-incongruent (open loop) visual stimulation. Moreover, they probe responses to unexpected visual events (halt of visual flow, sudden-onset drifting grating). The researchers find that, in contrast to a variety of excitatory and inhibitory cell types, genetically defined layer 5 excitatory neurons distinguish between the closed and the open loop condition and exhibit activity patterns in visual cortex in response to unexpected events, consistent with unsigned prediction error coding. Motivated by the idea that prediction error coding is aberrant in psychosis, the authors then inject the antipsychotic drug clozapine, and observe that this intervention specifically affects closed loop responses of layer 5 excitatory neurons, blunting the distinction between the open and closed loop conditions. Clozapine also leads to a decrease in long-range correlations between L5 activity in different brain regions, and similar effects are observed for two other antipsychotics, aripripazole and haloperidol, but not for saline or the stimulant amphetamine. The authors suggest that altered prediction error coding in layer 5 excitatory neurons due to reduced long-range correlations in L5 neurons might be a major effect of antipsychotic drugs and speculate that this might serve as a new biomarker for drug development.

Strengths:<br /> - Relevant and interesting research question:<br /> The distinction between expected and unexpected stimuli is blunted in psychosis but the neural mechanisms remain unclear. Therefore, it is critical to understand whether and how antipsychotic drugs used to treat psychosis affect cortical responses to expected and unexpected stimuli. This study provides important insights into this question by identifying a specific cortical cell type and long-range interactions as potential targets. The authors identify layer 5 excitatory neurons as a site where functional effects of antipsychotic drugs manifest. This is particularly interesting as these deep layer neurons have been proposed to play a crucial role in computing the integration of predictions, which is thought to be disrupted in psychosis. This work therefore has the potential to guide future investigations on psychosis and predictive coding towards these layer 5 neurons, and ultimately improve our understanding of the neural basis of psychotic symptoms.

- Broad investigation of different cell types and cortical regions:<br /> One of the major strengths of this study is quasi-systematic approach towards cell types and cortical regions. By analysing a wide range of genetically defined excitatory and inhibitory cell types, the authors were able to identify layer 5 excitatory neurons as exhibiting the strongest responses to unexpected vs. expected stimuli and being the most affected by antipsychotic drugs. Hence, this quasi-systematic approach provides valuable insights into the functional effects of antipsychotic drugs on the brain, and can guide future investigations towards the mechanisms by which these medications affect cortical neurons.

- Bridging theory with experiments<br /> Another strength of this study is its theoretical framework, which is grounded in the predictive coding theory. The authors use this theory as a guiding principle to motivate their experimental approach connecting visual responses in different layers with psychosis and antipsychotic drugs. This integration of theory and experimentation is a powerful approach to tie together the various findings the authors present and to contribute to the development of a coherent model of how the brain processes visual information both in health and in disease.

Weaknesses:<br /> - Unclear relevance for psychosis research<br /> From the study, it remains unclear whether the findings might indeed be able to normalise altered predictive coding in psychosis. Psychosis is characterised by a blunted distinction between predicted and unpredicted stimuli. The main results of this study indicate that antipsychotic drugs further blunt the distinction between predicted and unpredicted stimuli, which would suggest that antipsychotic drugs would deteriorate rather than ameliorate the predictive coding deficit found in psychosis. However, these findings were based on observations in wild-type mice at baseline. Given that antipsychotics are thought to have little effects in health but potent antipsychotic effects in psychosis, it seems possible that the presented results might be different in a condition modelling a psychotic state, for example after a dopamine-agonistic or a NMDA-antagonistic challenge. Therefore, future work in models of psychotic states is needed to further investigate the translational relevance of these findings.

- Incomplete testing of predictive coding interpretation<br /> While the investigation of neuronal responses to different visual flow stimuli is interesting, it remains open whether these responses indeed reflect internal representations in the framework of predictive coding. While the responses are consistent with internal representation as defined by the researchers, i.e., unsigned prediction error signals, an alternative interpretation might be that responses simply reflect sensory bottom-up signals that are more related to some low-level stimulus characteristics than to prediction errors. Moreover, this interpretational uncertainty is compounded by the fact that the used experimental paradigms were not suited to test whether behaviour is impacted as a function of the visual stimulation which makes it difficult to assess what the internal representation of the animal actually was. For these reasons, the observed effects might reflect simple bottom-up sensory processing alterations and not necessarily have any functional consequences. While this potential alternative explanation does not detract from the value of the study, future work would be needed to explain the effect of antipsychotic drugs on responses to visual flow. For example, experimental designs that systematically vary the predictive strength of coupled events or that include a behavioural readout might be more suited to draw from conclusions about whether antipsychotic drugs indeed alter internal representations.

Conclusion:<br /> Overall, the results support the idea that antipsychotic drugs affect neural responses to predicted and unpredicted stimuli in deep layers of cortex. Although some future work is required to establish whether this observation can indeed be explained by a drug-specific effect on predictive coding, the study provides important insights into the neural underpinnings of visual processing and antipsychotic drugs, which is expected to guide future investigations on the predictive coding hypothesis of psychosis. This will be of broad interest to neuroscientists working on predictive coding in health and disease.

Reviewer #2 (Public Review):

Bilgic et al first explored cellular diversity in the developing cerebral cortex of ferret, honing in on progenitor cell diversity by employing FACS sorting of HES5-positive cells. They have generated a novel single cell transcriptomic dataset capturing the diversity of cells in the developing ferret cerebral cortex, including diverse radial glial and excitatory neuron populations. Unexpectedly, this analysis revealed the presence of CRYAB-positive truncated radial glia previously described only in humans. Using bioinformatic analyses, the investigators proposed that truncated radial glia produce ependymal cells, astrocytes, and to a lesser degree, neurons. Of particular interest to the field, they identify enriched expression of FOXJ1 in late truncated radial glia strongly indicating that towards the end of neurogenesis, these cells likely give rise to ependymal cells. This study represents a major advancement in the field of cortical development and a valuable dataset for future studies of ferret cortical development.

Reviewer #2 (Public Review):

Summary:<br /> In this article, the authors provide a method of evaluating the safety of orthopedic implants in relation to radiofrequency-induced heating issues. The authors provide an open-source computational heterogeneous human model and explain computational techniques in a finite element method solver to predict the RF-induced temperature increase due to an orthopedic implant while being exposed to MRI RF fields at 1.5 T.

Strengths:<br /> The open-access computational human model along with their semiautomatic algorithm to position the implant can help realistically model the implant RF exposure in patients avoiding over- or under-estimation of RF heating measured using rectangular box phantoms such as ASTM phantom. Additionally, using numerical simulation to predict radiofrequency-induced heating will be much easier compared to the experimental measurements in an MRI scanner, especially when the scanner availability is limited.

Weaknesses:<br /> The proposed method only used radiofrequency (RF) field exposure to evaluate the heating around the implant. However, in the case of bulky implants, the rapidly changing gradient field can also produce significant heating due to large eddy currents. So the gradient-induced heating still remains an issue to be evaluated to decide on the safety of the patient. Moreover, the method is limited to a single human model and might not be representative of patients with different age, sex, and body weights. Additionally, the authors compare the temperature rise predicted by their method to an earlier study. However, there is no information about how they controlled the input power in their simulation testbed compared to the earlier study in showing validation of the method.

Reviewer #2 (Public Review):

This paper illustrates that PSCs can model myogenesis in vitro by mimicking the in vivo development of the somite and dermomyotome. The advantages of this 3D system include (1) better structural distinctions, (2) the persistence of progenitors, and (3) the spatial distribution (e.g. migration, confinement) of progenitors. The finding is important with the implication in disease modeling. Indeed the authors tried DMD model although it suffered the lack of deeper characterization.

The differentiation protocol is based on a current understanding of myogenesis and is compelling. They characterized the organoids in depth (e.g. many time points and immunofluorescence). The evidence is solid.

Reviewer #2 (Public Review):

Catabolic conditions lead to increased formation of ketone bodies in the liver, which under these conditions play an important role in supplying energy to metabolically active organs. In this manuscript, the authors explore the concept of whether and to what extent hepatic formation of acetate might contribute to energy supply under metabolic stress conditions. The authors show that patients with diabetes have increased acetate levels, which is explained as a consequence of the increased fatty acid flux from adipose tissue to the liver. This is confirmed in a preclinical model for type 1 diabetes, where acetate concentrations are in a similar range to ketone bodies. Acetate concentrations also increase under physiological conditions of fasting. Using stable isotopes, the authors show that palmitate is used as the primary source for acetate production in primary hepatocytes. Using cell culture studies and adenoviral-mediated knockdown in mice, it can be shown that the conversion of acetyl-CoA to acetate is catalyzed in peroxisomes by acyl-CoA thioesterase8 (ACOT8) and after transport of citrate from mitochondria and subsequent conversion to acetyl-CoA in the cytosol by ACOT12. Remarkably, ACOT8/12 not only regulates the formation of acetate but plays a crucial role in the maintenance of cellular CoA concentration. Accordingly, depletion of ACOT8/12 activity leads to a reduction of other CoA derivatives such as HMG-CoA, which resulted in the inhibition of ketone body synthesis. In diabetic mice, ACOT 8 or ACOT12 knockdown appears to lead to some limitations in strength and behavior.

In summary, the authors clearly demonstrate that hepatic release-mediated by ACOT8 and ACOT12-determines the plasma concentration of acetate. This is a very remarkable observation since most studies assume that short-chain fatty acids in plasma are primarily generated by fermentation of dietary fiber by intestinal bacteria. The authors demonstrate in very well performed studies the metabolic changes that result from impaired thiolysis. On the other hand, the ACOT12 phenotype has been demonstrated in a recently published study (PMID: 34285335). In this study, ACOT12 deficiency caused NAFLD, thus it would be worth determining whether deficiency of ACOT12 and/or ACOT8 promotes de novo lipogenesis under the conditions of the present study. As a further limitation, it should be noted that the relevance of acetate production for the energy supply of peripheral organs including the central nervous system could not be clearly demonstrated. For instance, impaired ketone body production due to impaired CoA availability could affect the metabolic activity of various organs. Moreover, the human cohort is not very well described, e.g. it is unclear whether the patients have type 1 or type 2 diabetes.

Reviewer #2 (Public Review):

The hard work of the authors is much appreciated. With overexpression of a-arrestin Txnip in RPE, cones and the combined respectively, the authors show a potential gene agnostic treatment that can be applied to retinitis pigmentosa. Furthermore, since Txnip is related to multiple intracellular signaling pathway, this study is of value for research in the mechanism of secondary cone dystrophy as well.

There are a few areas in which the article may be improved through further analysis and application of the data, as well as some adjustments that should be made in to clarify specific points in the article.

Reviewer #2 (Public Review):

Summary:

Conceptually, this study is interesting and is the first attempt to account for the potentially interactive effects of seasonality and blood source on mosquito fitness, which the authors frame as a possible explanation for previously observed host-switching of Culex quinquefasciatus from birds to mammals in the fall. The authors hypothesize that if changes in fitness by blood source change between seasons, higher fitness in birds in the summer and on mammals in the autumn could drive observed host switching. To test this, the authors fed individuals from a colony of Cx. quinquefasciatus on chickens (bird model) and mice (mammal model) and subjected each of these two groups to two different environmental conditions reflecting the high and low temperatures and photoperiod experienced in summer and autumn in Córdoba, Argentina (aka seasonality). They measured fecundity, fertility, and hatchability over two gonotrophic cycles. The authors then used a generalized linear mixed model to evaluate the impact of host species, seasonality, and gonotrophic cycle on fecundity and fertility and a null model analysis via data randomization for hatchability. The authors were trying to test their hypothesis by determining whether there was an interactive effect of season and host species on mosquito fitness. This is an interesting hypothesis; if it had been supported, it would provide support for a new mechanism driving host switching. While the authors did report an interactive impact of seasonality and host species, the directionality of the effect was the opposite of that hypothesized. While this finding is interesting and worth reporting, there are significant issues with the experimental design and the conclusions that are drawn from the results, which are described below. These issues should be addressed to make the findings trustworthy.

Strengths:

1. Using a combination of laboratory feedings and incubators to simulate seasonal environmental conditions is a good, controlled way to assess the potentially interactive impact of host species and seasonality on the fitness of Culex quinquefasciatus in the lab.<br /> 2. The driving hypothesis is an interesting and creative way to think about a potential driver of host switching observed in the field.

Weaknesses:

1. There is no replication built into this study. Egg lay is a highly variable trait, even within treatments, so it is important to see replication of the effects of treatment across multiple discrete replicates. It is standard practice to replicate mosquito fitness experiments for this reason. Furthermore, the sample size was particularly small for some groups (e.g. 15 egg rafts for the second gonotrophic cycle of mice in the autumn, which was the only group for which a decrease in fecundity and fertility was detected between 1st and 2nd gonotrophic cycles). Replicates also allow investigators to change around other variables that might impact the results for unknown reasons; for example, the incubators used for fall/summer conditions can be swapped, ensuring that the observed effects are not artifacts of other differences between treatments. While most groups had robust sample sizes, I do not trust the replicability of the results without experimental replication within the study.<br /> 2. Considering the hypothesis is driven by the host switching observed in the field, this phenomenon is discussed very little. I do not believe Cx. quinquefasciatus host switching has been observed in Argentina, only in the northern hemisphere, so it is possible that the species could have an entirely different ecology in Argentina. It would have been helpful to conduct a blood meal analysis prior to this experiment to determine whether using an Argentinian population was appropriate to assess this question. If the Argentinian populations don't experience host switching, then an Argentinian colony would not be the appropriate colony to use to assess this question. Given that this experiment has already been conducted with this population, this possibility should at least be acknowledged in the discussion. Or if a study showing host switching in Argentina has been conducted, it would be helpful to highlight this in the introduction and discussion.<br /> 3. The impacts of certain experimental design decisions are not acknowledged in the manuscript and warrant discussion. For example, the larvae were reared under the same conditions to ensure adults of similar sizes and development timing, but this also prevents mechanisms of action that could occur as a result of seasonality experienced by mothers, eggs, and larvae.<br /> 4. There are aspects of the data analysis that are not fully explained and should be further clarified. For example, there is no explanation of how the levels of categorical variables were compared.<br /> 5. The results show the opposite trend as was predicted by the authors based on observed feeding switches from birds to mammals in the autumn. However, they only state this once at the end of the discussion and never address why they might have observed the opposite trend as was hypothesized.<br /> 6. Generally speaking, the discussion has information that isn't directly related to the results and/or is too detailed in certain parts. Meanwhile, it doesn't dig into the meaning of the results or the ways in which the experimental design could have influenced results.<br /> 7. Beyond the issue of lack of replication limiting trust in the conclusions in general, there is one conclusion reached at the end of the discussion that would not be supported, even if additional replicates are conducted. The results do not show that physiological changes in mosquitoes trigger the selection of new hosts. Host selection is never measured, so this claim cannot be made. The results don't even suggest that fitness might trigger selection because the results show that physiological changes are in the opposite direction as what would be hypothesized to produce observed host switches. Similarly, the last sentence of the abstract is not supported by the results.<br /> 8. Throughout the manuscript, there are grammatical errors that make it difficult to understand certain sentences, especially for the results.

This study is driven by an interesting question and has the potential to be a valuable contribution to the literature.

Reviewer #2 (Public Review):

Summary:<br /> The study introduces BRAID, a novel approach for targeting drugs to specific cell types, addressing the challenges of pleiotropic drug actions. Unlike existing methods, this one involves breaking a protein drug molecule into inactive parts that are then put back together using a bridging receptor on the target cell. The individual components of this assembly are not required to be together, thereby affording it a degree of flexibility. The authors applied this idea to the WNT/-catenin signaling pathway by splitting a WNT mimic into two parts with FZD and LRP binding domains and bridging receptors. This combined method, which is called SWIFT, showed that WNT signaling was turned on in target cells, showing cell-specific targeting. The technique shows promise for the development of therapeutics, as it provides a way to more precisely target signaling pathways.

The authors have effectively elucidated their strategy through visually appealing diagrams, providing clear and thorough visual aids that facilitate comprehension of the concept. In addition, the authors have provided convincing evidence that the C-terminal region of FGF21 is essential for the binding process. Their meticulous and thorough presentation of experimental results emphasizes the significance of this specific binding domain and validates their findings.

Strengths:<br /> BRAID, a novel cell targeting method, divides an active drug molecule into inactive components formed by a bridging receptor. This novel approach to cell-specific drug action may reduce systemic toxicity.

The SWIFT approach successfully targets cells in the WNT/β-catenin signaling pathway. The approach activates WNT signaling only in target cells (hepatocytes), proving its specificity.

The study indicates that the BRAID approach can target various signaling systems beyond WNT/β-catenin, indicating its versatility. Therapeutic development may benefit from this adaptability.

Weaknesses:<br /> The study shows the SWIFT approach works in vitro using cell lines, primary human hepatocytes, and human intestinal organoids, but it lacks an in vivo animal model or clinical validation. The applicability of this approach to therapy is still unknown.

The success of SWIFT depends on the presence and expression of the bridging receptor (βKlotho) on target cells. The approach may fail if the target receptor is not expressed or available.

Reviewer #2 (Public Review):

This paper by Lucas et al follows on from earlier work by the same group. They use high-resolution 2D template matching (2DTM) to find particles of a given target structure in 2D cryo-EM images, either of in vitro single-particle samples or of more complicated samples, such as FIB-milled cells (which would otherwise perhaps be used for 3D electron tomography). One major concern for high-resolution template matching has been the amount of model bias that gets introduced into a reconstruction that is calculated straight from the orientations and positions identified by the projection matching algorithm. This paper assesses the amount of model bias that gets introduced in high-resolution features of such maps.

For a high-signal-to-noise in vitro single-particle cryo-EM data set, the authors show that their approach does not yield much model bias. This is probably not very surprising, as their method is basically a low false-positive particle picker, which works very well on such data. Still, I guess that is the whole point of it, and it is good to see that they can reconstruct density for a small-molecule compound that was not present in the original template.

For FIB-milled lamella of yeast cells with stalled ribosomes, the SNR is much lower and the dangers of model bias will be higher. This is also evidenced by the observation that further refinement of initial 2DTM-identified orientations and positions worsens the map. This is obviously a more relevant SNR regime to assess their method. Still, they show convincing density for the GHX compound that was not present in the template but was there in the reconstruction from the identified particles.

Quantification of the amount of model bias is then performed using omit maps, where every 20th residue is removed from the template and corresponding reconstructions are compared (for those residues) with the full-template reconstructions. As expected, model bias increases with lower thresholds for the picking. Some model bias (Omega=8%) remains even for very high thresholds. The authors state this may be due to overfitting of noise when template-matching true particles, instead of introducing false positives. Probably, that still represents some sort of problem. Especially because the authors then go on to show that their expectation of the number of false positives does not always match the correct number of false positives, probably due to inaccuracies in the noise model for more complicated images. This may warrant further in-depth discussion in a revised manuscript.

Overall, I think this paper is well written and it has made me think differently (again) about the 2DTM technique and its usefulness in various applications, as outlined in the Discussion. Therefore, it will be a constructive contribution to the field.

Reviewer #2 (Public Review):

In this study, Koesters et al. investigated whether Rab3A, a small GTPase that regulates synaptic vesicle fusion pore opening, is required for excitatory synaptic scaling in response to TTX-induced activity suppression in dissociated mouse cortical neuronal culture. They first show that, while pyramidal neurons from wild-type (WT) littermates show normal synaptic scaling in response to 48h of TTX treatment (~30% increase in the mean mEPSC amplitude), those from two different mouse lines with either deletion (Rab3A-/-) or loss-of-function mutation of Rab3A (Rab3AEbd/Ebd) fail to engage this homeostatic compensation. They perform cumulative distribution analysis to show that the mEPSC population has gone through divergent scaling in WT neurons. Similarly, this phenomenon is absent in neurons from the two Rab3A mouse lines. They further demonstrate that GluA2-containing AMPARs likely account for the increase in mEPSC amplitudes by comparing measurements before and after washing in blockers specific for GluA2-lacking AMPARs. Subsequently, they perform electrophysiology and immunohistochemistry side by side for WT neurons from the same culture following TTX treatment, and find that both mEPSC amplitudes and GluA2 cluster sizes have shifted towards higher values, while GluA2 cluster intensity remains unchanged. Importantly, all these homeostatic compensations are absent in Rab3A-/- neurons. Finally, they mix neurons and astrocyte feeders either from WT or Rab3A-/- mice, which reveals that neuronal but not astrocytic Rab3A knockout leads to impaired scaling up of mEPSCs. They conclude that Rab3A is required for homeostatic scaling up of mEPSC amplitude in cortical neurons, most likely from the presynaptic side.

Although the authors have raised an interesting question, their conclusion is not well supported by the data presented. I list my technical and conceptual concerns below.

Technical concerns:

1. The culture condition is questionable. The authors saw no NMDAR current present during spontaneous recordings, which is worrisome since NMDARs should be active in cultures with normal network activity (Watt et al., 2000; Sutton et al., 2006). It is important to ensure there is enough spiking activity before doing any activity manipulation. Similarly, it is also unknown whether spiking activity is normal in Rab3A KO/Ebd neurons.

2. Selection of mEPSC events is not conducted in an unbiased manner. Manually selecting events is insufficient for cumulative distribution analysis, where small biases could skew the entire distribution. Since the authors claim their ratio plot is a better method to detect the uniformity of scaling than the well-established rank-order plot, it is important to use an unbiased population to substantiate this claim.

3. Immunohistochemistry data analysis is problematic. The authors only labeled dendrites without doing cell-fills to look at morphology, so it is questionable how they differentiate branches from pyramidal neurons and interneurons. Since glutamatergic synapses on these two types of neuron scale in the opposite directions, it is crucial to show that only pyramidal neurons are included for analysis.

Conceptual concerns:

The only novel finding here is the implicated role for Rab3A in synaptic scaling, but insights into mechanisms behind this observation are lacking. The author claims that Rab3A likely regulates scaling from the presynaptic side, yet there is no direct evidence from data presented. In its current form, this study's contribution to the field is very limited.

1. Their major argument for this is that homeostatic effects on mEPSC amplitudes and GluA2 cluster sizes do not match. This is inconsistent with reports from multiple labs showing that upscaling of mEPSC amplitude and GluA2 accumulation occur side by side during scaling (Ibata et al., 2008; Pozo et al., 2012; Tan et al., 2015; Silva et al., 2019). Further, because the acquisition and quantification methods for mEPSC recordings and immunohistochemistry imaging are entirely different (each with its own limitations in signal detection), it is not convincing that the lack of proportional changes must signify a presynaptic component.

2. The authors also speculate in the discussion that presynaptic Rab3A could be interacting with retrograde BDNF signaling to regulate postsynaptic AMPARs. Without data showing Rab3A-dependent presynaptic changes after TTX treatment, this argument is not compelling. In this retrograde pathway, BDNF is synthesized in and released from dendrites (Jakawich et al., 2010; Thapliyal et al., 2022), and it is entirely possible for postsynaptic Rab3A to interfere with this process cell-autonomously.

3. The authors propose that a change in AMPAR subunit composition from GluA2-containing ones to GluA1 homomers may account for the distinct changes in mEPSC amplitudes and GluA2 clusters. However, their data from the Naspm wash-in experiments clearly show that GluA1 homomer contributions have not changed before and after TTX treatment.

Ibata K, Sun Q, Turrigiano GG (2008) Rapid synaptic scaling induced by changes in postsynaptic firing. Neuron 57:819-826.

Jakawich SK, Nasser HB, Strong MJ, McCartney AJ, Perez AS, Rakesh N, Carruthers CJL, Sutton MA (2010) Local Presynaptic Activity Gates Homeostatic Changes in Presynaptic Function Driven by Dendritic BDNF Synthesis. Neuron 68:1143-1158.

Pozo K, Cingolani LA, Bassani S, Laurent F, Passafaro M, Goda Y (2012) β3 integrin interacts directly with GluA2 AMPA receptor subunit and regulates AMPA receptor expression in hippocampal neurons. Proceedings of the National Academy of Sciences 109:1323-1328.

Silva MM, Rodrigues B, Fernandes J, Santos SD, Carreto L, Santos MAS, Pinheiro P, Carvalho AL (2019) MicroRNA-186-5p controls GluA2 surface expression and synaptic scaling in hippocampal neurons. Proceedings of the National Academy of Sciences 116:5727-5736.

Sutton MA, Ito HT, Cressy P, Kempf C, Woo JC, Schuman EM (2006) Miniature Neurotransmission Stabilizes Synaptic Function via Tonic Suppression of Local Dendritic Protein Synthesis. Cell 125:785-799.

Tan HL, Queenan BN, Huganir RL (2015) GRIP1 is required for homeostatic regulation of AMPAR trafficking. Proceedings of the National Academy of Sciences 112:10026-10031.

Thapliyal S, Arendt KL, Lau AG, Chen L (2022) Retinoic acid-gated BDNF synthesis in neuronal dendrites drives presynaptic homeostatic plasticity. eLife 11:e79863.

Watt AJ, Rossum MCW van, MacLeod KM, Nelson SB, Turrigiano GG (2000) Activity Coregulates Quantal AMPA and NMDA Currents at Neocortical Synapses. Neuron 26:659-670.

Reviewer #2 (Public Review):

Summary:

In this manuscript, Mure et al investigated host-microbe interactions in wild-mimicked settings. They analyzed microbiome composition using bananas that had been fed on by wild larvae and found that the microbiota composition shifted from the early stage of feeding to the later stage of the fermentation process. They isolated several yeast and bacterial species from the food, and examined larval growth on banana-based food, mimicking a natural setting where germ-free larvae cannot grow on it. The authors found that a yeast, Hanseniaspora uvarum, can support larval growth sufficiently, and insisted that branched-chain amino acids (BCAAs) provided by the yeast may partly account for the growth support. Interestingly, in other isolated yeast species, some were non-supportive strains in terms of larval growth, which can assist larval development when they are heat-killed. Besides, they showed that acetic acid bacteria, isolated from well-fermented banana (later-stage food), is sufficiently supportive but their presence depended on other microbes, lactic acid bacteria or yeast.

Strengths:

So far, host-microbe studies using Drosophila melanogaster have focused relatively less on the roles of fungi, and many studies used only "model" yeasts. In the experimental setting where natural conditions may be well mimicked, the authors successfully isolated wild yeast species and convincingly showed that wild yeast plays a critical role in promoting host growth. In addition, the authors provided intriguing observations that all of the heat-killed yeast promoted larval growth even though some of the yeast never supported the development when they were alive, suggesting that wild yeasts produce the necessary nutrients for larval development, but the nutrients of non-supportive yeasts are not accessible to the host. This might be an interesting indication for further studies revealing host-fungi interactions.

Weaknesses:

The experimental setting that, the authors think, reflects host-microbe interactions in nature is one of the key points. However, it is not explicitly mentioned whether isolated microbes are indeed colonized in wild larvae of Drosophila melanogaster who eat bananas. Another matter is that this work is rather descriptive and a few mechanical insights are presented. The evidence that the nutritional role of BCAAs is incomplete, and molecular level explanation is missing in "interspecies interactions" between lactic acid bacteria (or yeast) and acetic acid bacteria that assure their inhabitation. Apart from these matters, the future directions or significance of this work could be discussed more in the manuscript.

Reviewer #3 (Public Review):

In their study, Purandare & Mehta analyze large-scale single unit recordings from the visual system (LGN, V1, extrastriate regions AM and PM) and hippocampal system (DG, CA3, CA1 and subiculum) while mice monocularly viewed repeats of a 30s movie clip. The data were part of a larger release of publicly available recordings from the Allen Brian Observatory. The authors found that cells in all regions exhibited tuning to specific segments of the movie (i.e. "movie fields") ranging in duration from 20ms to 20s. The largest fractions of movie-responsive cells were in visual regions, though analyses of scrambled movie frames indicated that visual neurons were driven more strongly by visual features of the movie images themselves. Cells in the hippocampal system, on the other hand, tended to exhibit fewer "movie fields", which on average were a few seconds in duration, but could range from >50ms to as long as 20s. Unlike the visual system "movie fields" in the hippocampal system disappeared when the frames of the movie were scrambled, indicating that the cells encoded more complex (episodic) content, rather than merely passively reading out visual input.

The paper is conceptually novel since it specifically aims to remove any behavioral or task engagement whatsoever in the head-fixed mice, a setup typically used as an open-loop control condition in virtual reality-based navigational or decision making tasks (e.g. Harvey et al., 2012). Because the study specifically addresses this aspect of encoding (i.e. exploring effects of pure visual content rather than something task-related), and because of the widespread use of video-based virtual reality paradigms in different sub-fields, the paper should be of interest to those studying visual processing as well as those studying visual and spatial coding in the hippocampal system.

Comments on latest version:

The revised manuscript by Purandare et al. has been improved with the inclusion of additional analyses and discussion, and the changes mainly satisfy the concerns raised in the initial version of the manuscript.

Regarding the methods, it was particularly helpful that the authors took measures to consider the impact of different states of arousal (pupil diameter), mobility, and SWRs on the expression and significance of movie field tuning, considering the lack of a task structure or behavioral report. Relatedly, the additional metrics applied (information rate and depth of movie field modulation) substantiate the results as based on z-scored sparsity. The explanation of lifetime sparseness as used here vs. in the work of de Vries et al. 2020 was also helpful.

The addition of more clearly tuned cells also helps the study feel more rooted in solid ground. For clarity, and consistency with the rest of the paper, it would be helpful to add the sparseness metrics above the newly added neural data in the Figure supplements.

The Discussion also contains elements that help balance both it and the paper as a whole. It draws a clearer distinction between the representation of visual scenes rather than encoding the contents of episodic memory, clarifying that hippocampal neurons were more likely doing the former than the latter. It is also appreciated that the authors added discussion acknowledging that the cortical processing did not quite follow an apparent hierarchical order.

As a last observation, though the authors assert in their rebuttal that analysis of the visual content encoded in the movie fields is beyond the scope of the study, this would add an interesting dimension to the work. Because, to my awareness, much less is known regarding how the visual and hippocampal systems in rodents encode visual information when the visual input is dynamic and chunked, as with movies. It would prove an interesting addition to the more extensive work on the processing of static visual scenes.

Reviewer #2 (Public Review):

This paper extends prior work demonstrating the importance of K145 acetylation of TDP-43 as a post-translational modification that impacts its RNA-binding capacity and may contribute to pathology in FTLD-ALS. The main strengths of this paper are the generation of a novel mouse model, using CRISPR gene editing, in which an acetylation-mimetic mutation (K to Q) is introduced at position 145. Behavioral, biochemical, and genetic analyses indicate that these mice display phenotypes relevant to TDP-43-associated disease and will be a valuable contribution to the field.

Reviewer #2 (Public Review):

Gillespie et al. introduced a novel neurofeedback (NF) procedure to train rats in enhancing their sharp-wave ripple (SWR) rate within a short duration, a key neural mechanism associated with memory consolidation. The training, embedded within a spatial memory task, spanned 20-30 days and utilized food rewards as positive reinforcement upon SWR detection. Rats were categorized into NF and control groups, with the NF group further divided into NF and delay trials for within-subject control. While single trial differences were elusive due to the variability of SWR occurrence, the study revealed that statistically rats in NF trials exhibited a notably higher SWR rate before receiving rewards compared to delay trials. This difference was even more pronounced when juxtaposed with rats not exposed to NF training (control group). The unique design of blending the NF phase with the memory dependent spatial task enabled the authors to analyze whether the NF training influence the task performance and replay content during SWRs across three different conditions (NF trials, delay trials and control group). Interestingly, despite the NF training, there was no significant improvement or decline in the performance of the spatial memory task, and the replay content remained consistent across all three conditions. Hence, the operant conditioning only amplified the SWR rate before reward in NF trials without altering the task performance and the replay content during SWR. Moreover, considering the post-reward period, the total SWR count was consistent across all conditions as well, meaning the NF training also do not affect the total SWR count. The study concludes with the hypothesis of a potential homeostatic mechanism governing the total SWR production in rats. This research significantly extends previous work by Ishikawa et al. (2014), offering insights into the NF training with external reward on the SWR rate/counts, replay content and task performance.

Strengths:

- Integration of NF task and spatial memory task in a single trial<br /> The integration of NF training within a spatial memory task poses significant challenges. Gillespie and colleagues overcame this by seamlessly blending the NF task and the spatial memory task into a single trial. Each trial involved a rat undergoing three steps: First, initiating a trial. Second, moving to either the NF port or the delay trial port, as indicated by an LED, and then maintaining a nosepoke at one of the center ports. During this step, the rat had to keep its nose (in the NF port) until a sharp-wave ripple (SWR) exceeding a set threshold was detected, which then triggered a reward, or until a variable time elapsed (in the delay port). Third, the rat would choose one of eight arms to explore before starting the next trial. This integration of the two tasks (step two as the NF task and step three as the spatial memory task) facilitated a direct analysis of the impact of NF training on behaviorally relevant replay content during SWRs and the performance in the spatial memory task.

- Clear Group Separation<br /> A robust study design necessitates clear distinctions between experimental conditions to ensure that observed differences can be attributed to the variable under investigation. This study meticulously categorized rats into three distinct conditions: NF trials, delay trials (for within-subject control), and a control group (for across-subject control). Furthermore, for each trial, the times of interest (TOI) were separated into pre-reward and post-reward periods. This clear separation ensures that any observed differences in SWR rates and other outcomes can be confidently attributed to the effects of neurofeedback training during specific time periods, minimizing potential confounding factors.

- Evidence of SWR rate modulation<br /> The study's results offer compelling evidence that rats can be trained to modulate their SWR rates during the pre-reward period. This is evident from the observation that rats in the NF trials consistently displayed a higher SWR rate before receiving rewards compared to those in delay trials or the control group (Fig. 2). Such findings not only validate the efficacy of the NF paradigm but also underscore the potential of operant conditioning in influencing neural mechanisms. The observation that rats were able to produce larger SWR events by modulating their occurrence rate, rather than merely waiting for these events, suggests a learned strategy to generate them more efficiently.

- Evidence of SWR count homeostasis<br /> A notable finding from the study was the observation of a consistent total SWR count during both pre-reward and post-reward periods across all conditions, despite the evident increase in SWR rates during the pre-reward period in NF trials. This points to a potential homeostatic mechanism governing SWR production in rats. This balance suggests that while NF training can modulate the timing and rate of SWRs over a short duration, it doesn't influence the overall count of SWRs over a longer period. Such a mechanism might be essential in ensuring that the brain neither overcompensates nor depletes its capacity for SWRs, maintaining the overall neural balance and functionality. This discovery deepens our understanding of neural mechanisms and highlights potential avenues for future research into the regulatory processes governing neural activity.

Weaknesses:

- Misleading Title<br /> The title, "Neurofeedback training can modulate task-relevant memory replay in rats," implies that through neurofeedback training, rats can learn to modulate the content of their memory replay. However, the study's findings contradict this implication. Particularly, one of the subtitles of this paper is "Neurofeedback training preserves replay content during SWRs," which directly contrasts with the main title's suggestion. The authors conclusively demonstrated that there was no discernible difference in the replay content between animals that underwent NF training and those that did not. The current title easily leads to misinterpretations about the study's primary outcomes, especially for readers who might not delve into the detailed findings.

- Lack of control analysis baseline for each animal<br /> While the authors meticulously categorized trial types into three distinct conditions: NF trials, delay trials, and control groups, they did not clearly establish a baseline for each animal. The animal could have a total different baseline SWR rates. The paper appears to operate under the assumption that each animal possesses a consistent SWR rate baseline, leading to only the final comparisons being presented.

- Vagueness of what animal really control during NF trials after training<br /> The authors state that, "Moreover, although we did observe a slightly lower mean speed during the pre-reward period on neurofeedback trials compared to delay trials and trials from the control cohort (Supplementary Figure 2F), movement differences could not explain the difference in SWR rates (Supplementary Figure 2G, H)." This assertion raises questions about the underlying mechanisms at play. In a typical operant conditioning scenario, training could result in direct neural modulation, behavioral changes, or a combination of both. For instance, rats might adopt a more stationary posture during the pre-reward period on NF trials compared to other conditions, or they might actively influence the occurrence rate of SWRs during this period. The paper would benefit from a clearer delineation of what the animals are specifically controlling or modulating during the NF trials, ensuring a more comprehensive understanding of the observed effects.

- Clinical Implications<br /> The study was conducted on healthy, young animals but suggests potential benefits for older, cognitively impaired animals. However, it's possible that older or deficit animals might not respond to the NF protocol in the same way.

Reviewer #2 (Public Review):

Summary:<br /> Tian et al. aimed to assess differences in biological motion (BM) perception between children with and without ADHD, as well as relationships to indices of social functioning and possible predictors of BM perception (including demographics, reasoning ability and inattention). In their study, children with ADHD showed poorer performance relative to typically developing children in three tasks measuring local, global, and general BM perception. The authors further observed that across the whole sample, performance in all three BM tasks was negatively correlated with scores on the social responsiveness scale (SRS), whereas within groups a significant relationship to SRS scores was only observed in the ADHD group and for the local BM task. Local and global BM perception showed a dissociation in that global BM processing was predicted by age, while local BM perception was not. Finally, general (local & global combined) BM processing was predicted by age and global BM processing, while reasoning ability mediated the effect of inattention on BM processing.

Strengths:<br /> Overall, the manuscript is presented in a relatively clear fashion and methods and materials are presented with sufficient detail so the study could be reproduced by independent researchers. The study uses an innovative, albeit not novel, paradigm to investigate two independent processes underlying BM perception. The results are novel and have the potential to have wide-reaching impact on multiple fields.

Weaknesses:<br /> Except for the main analysis, it is unclear what the authors' specific predictions are regarding the three different tasks they employ. The three BM tasks are used to probe different processes underlying BM perception, but it is difficult to gather from the introduction why these three specific tasks were chosen and what predictions the authors have about the performance of the ADHD group in these tasks. Relatedly, the authors do not report whether (and if so, how) they corrected for multiple comparisons in their analyses. As the number of tests one should control for depends on the theoretical predictions (http://daniellakens.blogspot.com/2016/02/why-you-dont-need-to-adjust-you-alpha.html), both are necessary for the reader to assess the statistical validity of the results and any inferences drawn from them. The same is the case for the secondary analyses exploring relationships between the 3 individual BM tasks and social function measured by the social responsivity scale (SRS).

In relation to my prior point, the authors could provide more clarity on how the conclusions drawn from the results relate to their predictions. For example, it is unclear what specific conclusions the authors draw based on their findings that ADHD show performance differences in all three BM perception tasks, but only local BM is related to social function within this group. Here, the claim is made that their results support a specific hypothesis, but it is unclear to me what hypothesis they are actually referring to (see line 343 & following). This lack of clarity is aggravated by the fact that throughout the rest of the discussion, in particular when discussing other findings to support their own conclusions, the authors often make no distinction between the two processes of interest. Lastly, some of the authors' conclusions related to their findings on local vs global BM processing are not logically following from the evidence: For instance, the authors conclude that their data supports the idea that social atypicalities are likely to reduce with age in ADHD individuals. However, according to their own account, local BM perception - the only measure that was related to social function in their study - is understood to be age invariant (and was indeed not predicted by age in the present study).

Results reported are incomplete, making it hard for the reader to comprehensively interpret the findings and assess whether the conclusions drawn are valid. Whenever the authors report negative results (p-values > 0.05), the relevant statistics are not reported, and the data not plotted. In addition, summary statistics (group means) are missing for the main analysis.

Some of the conclusions/statements in the article are too strong and should be rephrased to indicate hypotheses and speculations rather than facts. For example, in lines 97-99 the authors state that the finding of poor BM performance in TD children in a prior study 'indicated inferior applicability' or 'inapplicable experimental design'. While this is one possibility, a perhaps more plausible interpretation could be that TD children show 'poor' performance due to outstanding maturation of the underlying (global) BM processes (as the authors suggest themselves that BM perception can improve with age). There are several other examples where statements are too strong or misleading, which need attention.

Reviewer #2 (Public Review):

Summary:<br /> In this manuscript, the authors introduced ADSE, a SELEX-based protocol to explore the mechanism of emergency of species. They used DNA hybridization (to the bait pool, "resources") as the driving force for selection and quantitatively investigated the factors that may contribute to the survival during generation evolution (progress of SELEX cycle), revealing that besides individual-resource binding, the inter- and intra-individual interactions were also important features along with mutualism and parasitism.

Strengths:<br /> The design of using pure biochemical affinity assay to study eco-evolution is interesting, providing an important viewpoint to partly explain the molecular mechanism of evolution.

Weaknesses:<br /> Though the evidence of the study is somewhat convincing, some aspects still need to be improved, mostly technical issues.

Reviewer #2 (Public Review):

Summary:<br /> The main conclusion of the manuscript is that the presence of linker Histone H1 protects Arabidopsis pericentromeric heterochromatic regions and longer transposable elements via chromatin compaction from encroachment by other repressive pathways. The manuscript focuses on the RNA-dependent DNA-methylation (RdDM) pathway but indirectly finds that other pathways must also be ectopically enriched.

Strengths:<br /> The authors present diverse sets of genomic data comparing Arabidopsis wild-type and h1 mutant background allowing an analysis of differential recruitment of RdDM component NPRE1, which is related to changes in DNA methylation and H1 coverage. As an addendum, the manuscript also contains recruitment data for SUVH1 in wild-type and h1 mutant backgrounds.

Furthermore, the authors make use of a line that recruits NRPE1 ectopically to show that H1 occupancy is not altered because of this recruitment. These are negative data, but well supported.

Weaknesses:<br /> The manuscript mostly confirms earlier observations but shows very limited novelty. It has already been reported that different classes of TEs show a differential response with respect to DNA methylation in absence of H1. Furthermore, the fact that loss of H1 affect global chromatin accessibility was recently published by Teano et al. in Cell reports (Volume 42, Issue 8, 29 August 2023). The authors have neither cited this report (that had been available since 2021 in BioRxiv), nor set their work in context to this study. The study by Teano showed that for some TEs, loss of H1 is related to a switch from DNA-methylation dependent repressive pathways to Polycomb Group-dependent pathways. The current manuscript could have looked at overlapping classes and integrated information from both studies, which would be particularly interesting for the examples illustrated in Figure 5b, showing examples of TEs that lose NRPE1 targeting and methylation in all contexts in H1 deletion mutants.

The proposed mechanism is that RdDM along with many other chromatin factors re-distribute to heterochromatic regions in h1 mutants because these regions are more accessible. There is a general problem with measuring the "difference in chromatin compaction" with methods that mostly resolve highly accessible chromatin in contrast to any other chromatin, such as ATAC-seq or DNAse-seq (employed in this manuscript). The changes in the regions of interest are so subtle that they are not easily detected at the level of individual genes, although they become usually more obvious in metagene plots. The general question is if this inadequate method is sufficient to draw strong conclusions on chromatin compaction, but to be fair, the current manuscript is not alone in using this method without pointing out certain caveats.

As a consequence of redistribution to heterochromatic sites, the authors postulate that there are also sites that lose RdDM coverage in h1, but these sites are not really evidenced in the report.<br /> Unfortunately, another weakness is that it is not possible to make easy use of the analysis from the available material as the current manuscript does not contain supplemental data indicating which TEs were and DMRs were considered in classes such as "long", "short", "heterochromatic", "euchromatic", "Class A", "Class B", "CMT2 dependent hypo-CHH", "DRM2 dependent CHH", "dynamic RdDM" etc. Since the bioinformatics pipelines are poorly documented (absence of dedicated script archive), the analysis cannot be easily recapitulated.

Reviewer #2 (Public Review):

This study examines the construct of "cognitive spaces" as they relate to neural coding schemes present in response conflict tasks. The authors use a novel experimental design in which different types of response conflict (spatial Stroop, Simon) are parametrically manipulated. These conflict types are hypothesized to be encoded jointly, within an abstract "cognitive space", in which distances between task conditions depend only on the similarity of conflict types (i.e., where conditions with similar relative proportions of spatial-Stroop versus Simon conflicts are represented with similar activity patterns). Authors contrast such a representational scheme for conflict with several other conceptually distinct schemes, including a domain-general, domain-specific, and two task-specific schemes. The authors conduct a behavioral and fMRI study to test which of these coding schemes is used by prefrontal cortex. Replicating the authors' prior work, this study demonstrates that sequential behavioral adjustments (the congruency sequence effect) are modulated as a function of the similarity between conflict types. In fMRI data, univariate analyses identified activation in left prefrontal and dorsomedial frontal cortex that was modulated by the amount of Stroop or Simon conflict present, and representational similarity analyses (RSA) that identified coding of conflict similarity, as predicted under the cognitive space model, in right lateral prefrontal cortex.

This study tackles an important question regarding how distinct types of conflict might be encoded in the brain within a computationally efficient representational format. The ideas postulated by the authors are interesting ones and the statistical methods are generally rigorous. The evidence supporting the authors claims, however, is limited by confounds in the experimental design and by lack of clarity in reporting the testing of alternative hypotheses within the method and results.

(1) Model comparison

The authors commendably performed a model comparison within their study, in which they formalized alternative hypotheses to their cognitive space hypothesis. We greatly appreciate the motivation for this idea and think that it strengthened the manuscript. Nevertheless, some details of this model comparison were difficult for us to understand, which in turn has limited our understanding of the strength of the findings.

The text indicates the domain-general model was computed by taking the difference in congruency effects per conflict condition. Does this refer to the "absolute difference" between congruency effects? In the rest of this review, we assume that the absolute difference was indeed used, as using a signed difference would not make sense in this setting. Nevertheless, it may help readers to add this information to the text.

Regarding the Stroop-Only and Simon-Only models, the motivation for using the Jaccard metric was unclear. From our reading, it seems that all of the other models --- the cognitive space model, the domain-general model, and the domain-specific model --- effectively use a Euclidean distance metric. (Although the cognitive space model is parameterized with cosine similarities, these similarity values are proportional to Euclidean distances because the points all lie on a circle. And, although the domain-general model is parameterized with absolute differences, the absolute difference is equivalent to Euclidean distance in 1D.) Given these considerations, the use of Jaccard seems to differ from the other models, in terms of parameterization, and thus potentially also in terms of underlying assumptions. Could authors help us understand why this distance metric was used instead of Euclidean distance? Additionally, if Jaccard must be used because this metric seems to be non-standard in the use of RSA, it would likely be helpful for many readers to give a little more explanation about how it was calculated.

When considering parameterizing the Stroop-Only and Simon-Only models with Euclidean distances, one concern we had is that the joint inclusion of these models might render the cognitive space model unidentifiable due to collinearity (i.e., the sum of the Stroop-Only and Simon-Only models could be collinear with the cognitive space model). Could the authors determine whether this is the case? This issue seems to be important, as the presence of such collinearity would suggest to us that the design is incapable of discriminating those hypotheses as parameterized.

(2) Issue of uniquely identifying conflict coding

We certainly appreciate the efforts that authors have taken to address potential confounders for encoding of conflict in their original submission. We broach this question not because we wish authors to conduct additional control analyses, but because this issue seems to be central to the thesis of the manuscript and we would value reading the authors' thoughts on this issue in the discussion.

To summarize our concerns, conflict seems to be a difficult variable to isolate within aggregate neural activity, at least relative to other variables typically studied in cognitive control, such as task-set or rule coding. This is because it seems reasonable to expect that many more nuisance factors covary with conflict --- such as univariate activation, level of cortical recruitment, performance measures, arousal --- than in comparison with, for example, a well-designed rule manipulation. Controlling for some of these factors post-hoc through regression is commendable (as authors have done here), but such a method will likely be incomplete and can provide no guarantees on the false positive rate.

Relatedly, the neural correlates of conflict coding in fMRI and other aggregate measures of neural activity are likely of heterogeneous provenance, potentially including rate coding (Fu et al., 2022), temporal coding (Smith et al., 2019), modulation of coding of other more concrete variables (Ebitz et al., 2020, 10.1101/2020.03.14.991745; see also discussion and reviews of Tang et al., 2016, 10.7554/eLife.12352), or neuromodulatory effects (e.g., Aston-Jones & Cohen, 2005). Some of these origins would seem to be consistent with "explicit" coding of conflict (conflict as a representation), but others would seem to be more consistent with epiphenomenal coding of conflict (i.e., conflict as an emergent process). Again, these concerns could apply to many variables as measured via fMRI, but at the same time, they seem to be more pernicious in the case of conflict. So, if authors consider these issues to be germane, perhaps they could explicitly state in the discussion whether adopting their cognitive space perspective implies a particular stance on these issues, how they interpret their results with respect to these issues, and if relevant, qualify their conclusions with uncertainty on these issues.

(3) Interpretation of measured geometry in 8C

We appreciate the inclusion of the measured similarity matrices of area 8C, the key area the results focus on, to the supplemental, as this allows for a relatively model-agnostic look at a portion of the data. Interestingly, the measured similarity matrix seems to mismatch the cognitive space model in a potentially substantive way. Although the model predicts that the "pure" Stroop and Simon conditions will have maximal self-similarity (i.e., the Stroop-Stroop and Simon-Simon cells on the diagonal), these correlations actually seem to be the lowest, by what appears to be a substantial margin (particularly the Stroop-Stroop similarities). What should readers make of this apparent mismatch? Perhaps authors could offer their interpretation on how this mismatch could fit with their conclusions.

Reviewer #2 (Public Review):

In this study, Hernandez-Hernandez et al developed a gender-dependent mathematical model of arterial myocytes based on a previous model and new experimental data. The ionic currents of the model and its sex difference were formulated based on patch-clamp experimental data, and the model properties were compared with single-cell and tissue scale experimental results. This is a study that is of importance for the modeling field as well as for experimental physiology.

Reviewer #2 (Public Review):

Summary: The current draft by Deischel et.al., entitled "Inhibition of Notch activity by phosphorylation of CSL in response to parasitization in Drosophila" decribes the role of Pkc53E in the phosphorylation of Su(H) to downregulate its transcriptional activity to mount a successful immune response upon parasitic wasp-infection. Overall, I find the study interesting and relevant especially the identification of Pkc53E in phosphorylation of Su(H) is very nice. However, I have a number of concerns with the manuscript which are central to the idea that link the phosphorylation of Su(H) via Pkc53E to implying its modulation of Notch activity. I enlist them one by one subsequently.

Strengths: I find the study interesting and relevant especially because of the following:<br /> 1. The identification of Pkc53E in phosphorylation of Su(H) is very interesting.<br /> 2. The role of this interaction in modulating Notch signaling and thereafter its requirement in mounting a strong immune response to wasp infection is also another strong highlight of this study.

Weaknesses:1. Epistatic interaction with Notch is needed: In the entire draft, the authors claim Pkc53E role in the phosphorylation of Su(H) is down-stream of notch activity. Given the paper title also invokes Notch, I would suggest authors show this in a direct epistatic interaction using a Notch condition. If loss of Notch function makes many more lamellocytes and GOF makes less, then would modulating Pkc53E (and SuH)) in this manifest any change? In homeostasis as well, given gain of Notch function leads to increased crystal cells the same genetic combinations in homeostasis will be nice to see.<br /> While I understand that Su(H) functions downstream of Notch, but it is now increasingly evident that Su(H) also functions independent of Notch. An epistatic relationship between Notch and Pkc will clarify if this phosphorylation event of Su(H) via Pkc is part of the canonical interaction being proposed in the manuscript and not a non-canoncial/Notch pathway independent role of Su(H).

This is important, as I worry that in the current state, while the data are all discussed inlight of Notch activity, any direct data to show this affirmatively is missing. In our hands we do find Notch independent Su(H) function in immune cells, hence this is a suggestion that stems from our own personal experience.

2. Temporal regulation of Notch activity in response to wasp-infection and its overlapping dynamics of Su(H) phosphorylation via Pkc is needed: First, I suggest the authors to show how Notch activity post infection in a time course dependent manner is altered. A RT-PCR profile of Notch target genes in hemocytes from infected animals at 6, 12, 24, 48 HPI, to gauge an understanding of dynamics in Notch activity will set the tone for when and how it is being modulated. In parallel, this response in phospho mutant of Su(H) will be good to see and will support the requirement for phosphorylation of Su(H) to manifest a strong immune response. Second, is the dynamics of phosphorylation in a time course experiment is missing. While the increased phosphorylation of Su(H) in response to wasp-infestation shown in Fig.2B is using whole animal, this implies a global down-regulation of Su(H)/Notch activity. The authors need to show this response specifically in immune cells. The reader is left to the assumption that this is also true in immune cells. Given the authors have a good antibody, characterizing this same in circulating immune cells in response to infection will be needed. A time course of the phosphorylation state at 6, 12, 24, 48 HPI, to guage an understanding of this dynamics is needed. The authors suggest, this mechanism may be a quick way to down-regulate Notch, hence a side by side comparison of the dynamics of Notch down-regulation (such as by doing RT-PCR of Notch target genes following different time point post infection) alongside the levels of pS269 will strengthen the central point being proposed. Last, in Fig7. the authors show Co-immuno-precipitation of Pkc53EHA with Su(H)gwt-mCh 994 protein from Hml-gal4 hemocytes. I understand this is in homeostasis but since this interaction is proposed to be sensitive to infection, then a Co-IP of the two in immune cells, upon infection should be incorporated to strengthen their point.

3. In Fig 5B, the authors show the change in crystal cell numbers as read out of PMA induced activation of Pkc53E and subsequent inhibition of Su(H) transcriptional activity, I would suggest the authors use more direct measures of this read out. RT-PCR of Su(H) target genes, in circulating immune cells, will strengthen this point. Formation of crystal cells is not just limited to Notch, I am not convinced that this treatment or the conditions have other affect on immune cells, such as any impact on Hif expression may also lead to lowering of CC numbers. Hence, the authors need to strengthen this point by showing that effects are direct to Notch and Su(H) and not non-specific to any other pathway also shown to be important for CC development.

4. In addition to the above mentioned points, the data needs to be strengthened to further support the main conclusions of the manuscript. I would suggest the authors present the infection response with details on the timing of the immune response. Characterization of the immune responses at respective time points (as above or at least 24 and 48 HPI, as norms in the field) will be important. Also, any change in overall cell numbers, other immune cells, plasmatocytes or CC post infection is missing and is needed to present the specificity of the impact. The addition of these will present the data with more rigor in their analysis.

5. Finally, what is the view of the authors on what leads to activation of Pkc53E, any upstream input is not presented. It will be good to see if wasp infection leads to increased Pkc53 kinase activity.

Overall, I think the findings in the current state are interesting and fill an important gap, but the authors will need to strengthen the point with more detailed analysis that includes generating new data and also presenting the current data with more rigor in their approach. The data have to showcase the relationship with Notch pathway modulation upon phosphorylation of CSL in a much more comprehensive way, both in homeostasis and in response to infection which is entirely missing in the current draft.

Reviewer #2 (Public Review):

Breast cancer is the most common malignant tumor in women. One of subtypes in breast cancer is so called triple-negative breast cancer (TNBC), which represents the most difficult subtype to treat and cure in the clinic. Chemotherapy drugs including epirubicin and cisplatin are widely used for TNBC treatment. However, drug resistance remains as a challenge in the clinic. The authors uncovered a molecular pathway involved in chemotherapy drug resistance, and molecular players in this pathway represent as potential drug targets to overcome drug resistance. The experiments are well designed and the conclusions drawn mostly were supported by the data. The findings have potential to be translated into the clinic.

Reviewer #2 (Public Review):

Pheochromocytoma (PCC), a rare neuroendocrine tumor, is currently considered malignant, but non-surgical treatment options are very limited and there is an urgent need for more basic research to support the development of new therapeutic approaches. In the present work, the authors described the intra- and inter-tumor heterogeneity by performing scRNA-seq on tumor samples from five patients with PCC, and evaluated the corresponding PASS scores.

Strengths: The tumor microenvironment of PCC was characterized and potential molecular classification criteria based on single-cell transcriptomics were proposed, offering new theoretical possibilities for the treatment of PCC. The article is logically written and the results are clearly presented.

Weaknesses: I still have concerns about some of the article's content. My main concerns are: In this study, the authors seem to have demonstrated the inaccuracy of a subjective score (PASS) by another objective means (scRNA-seq). In fact, the multiparametric scoring systems such as PASS are no longer endorsed in the 2022 WHO guidelines. The PASS scoring system does not have a high positive predictive value for risk stratification of PCC metastasis, but "rule-out" of metastasis risk with a PASS score of <4 seems to be fairly reliable. Could the authors please explain why the PASS scores were chosen rather than the GAPP, m-GAPP, or COPPS scoring systems? If possible, please try to emphasize the importance and necessity of using the PASS scoring system, either by replacing it with a more acceptable scoring system or by deleting the relevant part, which does not seem to be very relevant to the subject of the article.

Moreover, I noted the following statement in the text "There are no studies reporting the composition of immune cells in PCCs. The few published studies investigating the immune microenvironment of PCCs have been limited to the expression of PDL1 at the histological level and to assessment of the tumor mutation burden (TMB) at the genomic level, and these results only seem to suggest that PCCs are immune-cold (Bratslavsky et al, 2019; Guo et al, 2019; Pinato et al, 2017)." This statement is very wrong. The reason for this error may be that the authors did not adequately search and read the relevant literature. I noticed that almost all references in this paper are dated 2021 and earlier, which is surprising. Please update the references cited in this paper in a comprehensive and detailed manner; referring to literature published too early may lead to inadequate discussion or even one-sided or incorrect conclusions and conjectures.

For example, the text statement "Combined with previously reported negative regulatory effects of kinases (such as RET, ALK, and MEK) on HLA-I expression on tumor cells (Brea et al., 2016; Oh et al., 2019), we speculate that the possible reason for inability in recruiting CD8+ T cells of kinase-type PCCs is the downregulation of HLA-I in tumor cells regulated by RET, while the mechanism of immune escape in metabolism-type PCCs (with antigen presentation ability) needs to be further explored. Our results also indicate that the application of immunotherapy to metabolism-type PCCs is likely unsuitable, while kinase-type PCCs may have the potential of combined therapy with kinase inhibitors and immunotherapy." is rather one-sided; in fact, the presence of immune escape in PCC, as the malignancy with the lowest tumor mutation compliance, has been well characterized, and the low number of infiltrating T cells in tumor tissue may be influenced by a variety of factors, such as the release of catecholamines, the expression of inhibitory receptors on the surface of T cells, and so on, although genetic mutation still plays the most crucial role. The Discussion section also has a lot of information that needs to be updated or corrected and expanded, so please rewrite the above section with sufficiently updated references.

Below I have listed some references for the authors to read:<br /> Tufton N, Hearnden RJ, Berney DM, et al. The immune cell infiltrate in the tumour microenvironment of phaeochromocytomas and paragangliomas. Endocr Relat Cancer. 2022;29(11):589-598. Published 2022 Sep 19. doi:10.1530/ERC-22-0020<br /> Jin B, Han W, Guo J, et al. Initial characterization of immune microenvironment in pheochromocytoma and paraganglioma. Front Genet. 2022;13:1022131. Published 2022 Dec 7. doi:10.3389/fgene.2022.1022131<br /> Celada L, Cubiella T, San-Juan-Guardado J, et al. Pseudohypoxia in paraganglioma and pheochromocytoma is associated with an immunosuppressive phenotype. J Pathol. 2023;259(1):103-114. doi:10.1002/path.6026<br /> Calsina B, Piñeiro-Yáñez E, Martínez-Montes ÁM, et al. Genomic and immune landscape Of metastatic pheochromocytoma and paraganglioma. Nat Commun. 2023;14(1):1122. Published 2023 Feb 28. doi:10.1038/s41467-023-36769-6

Reviewer #2 (Public Review):

In this manuscript by Kang et. al., the authors investigated the mechanisms of K+-efflux-coupled SOCE in NLRP3 inflammasome activation by LP（LPS+PA, and identified an essential role of TRPM2-mediated lysosomal Ca2+ release and subsequent IP3Rs-mediated ER Ca2+ release and store depletion in the process. K+ efflux is shown to be mediated by a Ca2+-activated K+ channel (KCa3.1). LP-induced cytosolic Ca2+ elevation also induced a delayed activation of ASK1 and JNK, leading to ASC oligomerization and NLRP3 inflammasome activation. Overall, this is an interesting and comprehensive study that has identified several novel molecular players in metabolic inflammation. The manuscript can benefit if the following concerns could be addressed:

1. The expression of TRPM2 in the lysosomes of macrophages needs to be more definitively established. For instance, the cADPR-induced TRPM2 currents should be abolished in the TRPM2 KO macrophages. Can you show the lysosomal expression of TRPM2, either with an antibody if available or with a fluorescently-tagged TRPM2 overexpression construct?

2. Can you use your TRPM2 inhibitor ACA to pharmacologically phenocopy some results, e.g., about [Ca2+]ER, [Ca2+]LY, and [Ca2+]i from the TRPM2 knockout?

3. In Fig. S4A, bathing the cells in zero Ca2+ for three hours might not be ideal. Can you use a SOCE inhibitor, e.g, YM-58483, to make the point?

4. In Fig. 1A, you need a positive control, e.g., ionomycin, to show that the GPN response was selectively reduced upon LP treatment.

Reviewer #2 (Public Review):

Summary:<br /> The authors identified a new chloride-conducting Channelrhodopsin (MsACR1) that can be activated at low light intensities and within the red part of the visible spectrum. Additional engineering of MsACR1 yielded a variant (raACR1) with increased current amplitudes, accelerated kinetics, and a 20nm red-shifted peak excitation wavelength. Stimulation of MsACR1 and raACR1 expressing neurons with 635nm in mice's primary motor cortices inhibited the animals' locomotion.

Strengths:<br /> The in vitro characterization of the newly identified ACRs is very detailed and confirms the biophysical properties as described by the authors. Notably, the ACRs are very light sensitive and allow for efficient in vitro inhibition of neurons in the nano Watt/mm^2 range. These new ACRs give neuroscientists and cell biologists a new tool to control chloride flux over biological membranes with high temporal and spatial precision. The red-shifted excitation peaks of these ACRs could allow for multiplexed application with blue-light excited optogenetic tools such as cation-conducting channelrhodopsins or green-fluorescent calcium indicators such as GCaMP.

Weaknesses:<br /> The in-vivo characterization of MsACR1 and raACR1 lacks critical control experiments and is, therefore, too preliminary. The experimental conditions differ fundamentally between in vitro and in vivo characterizations. For example, chloride gradients differ within neurons which can weaken inhibition or even cause excitation at synapses, as pointed out by the authors. Notably, the patch pipettes for the in vitro characterization contained low chloride concentrations that might not reflect possible conditions found in the in vivo preparations, i.e., increasing chloride gradients from dendrites to synapses.

Interestingly, the authors used soma-targeted (st) MsACR1 and raACR1 for some of their in vitro characterization yielding more efficient inhibition and reduction of co-incidental "on-set" spiking. Still, the authors do not seem to have utilized st-variants in vivo.

Most importantly, critical in vivo control experiments, such as negative controls like GFP or positive controls like NpHR, are missing. These controls would exclude potential behavioral effects due to experimental artifacts. Moreover, in vivo electrophysiology could have confirmed whether targeted neurons were inhibited under optogenetic stimulations.

Some of these concerns stem from the fact that the pulsed raACR stimulation at 635 nm at 10Hz (Fig. 3E) was far less efficient compared to MsACR1, yet the in vivo comparison yielded very similar results (Fig. 4D).

Also, the cortex is highly heterogeneous and comprises excitatory and inhibitory neurons. Using the synapsin promoter, the viral expression paradigm could target both types and cause differential effects, which has not been investigated further, for example, by immunohistochemistry. An alternative expression system, for example, under VGLUT1 control, could have mitigated some of these concerns.

Furthermore, the authors applied different light intensities, wavelengths, and stimulation frequencies during the in vitro characterization, causing varying spike inhibition efficiencies. The in vivo characterization is notably lacking this type of control. Thus, it is unclear why the 635nm, 2s at 20Hz every 5s stimulation protocol, which has no equivalent in the in vitro characterization, was chosen.

In summary, the in vivo experiments did not confirm whether the observed inhibition of mouse locomotion occurred due to the inhibition of neurons or experimental artifacts.

In addition, the author's main claim of more efficient neuronal inhibition would require them to threshold MsACR1 and raACR1 against alternative methods such as the red-shifted NpHR variant Jaws or other ACRs to give readers meaningful guidance when choosing an inhibitory tool.

The light sensitivity of MsACR1 and raACR1 are impressive and well characterized in vitro. However, the authors only reported the overall light output at the fiber tip for the in vivo experiments: 0.5 mW. Without context, it is difficult to evaluate this value. Calculating the light power density at certain distances from the light fiber or thresholding against alternative tools such as NpHR, Jaws, or other ACRs would allow for a more meaningful evaluation.

Reviewer #2 (Public Review):

This paper presents a novel measure of complexity that can be applied to recorded neurophysiological time series. The paper first introduces an existing measure, Lempel-Ziv complexity, reviewing its computation, application, and potential issues. They then present their new metric: CSER. They show CSER values change similarly to LZ under psychedelics, sleep, and general anaesthesia. A key advantage of CSER is that it can be decomposed in both time and frequency. They give example applications for each of these. They show the differences in CSER in the previous examples are mostly located in the gamma band. For a temporal example, they consider monkey ecog in an oddball task and so CSER changes between oddballs and deviants.

Major comments<br /> Most of the technical details are rightly in the methods, but it would be nice as a reader to have more of a concrete idea of the type of state space model used in the main text, the assumptions underlying this, and typical orders used perhaps with a schematic diagram etc. I appreciate they have written the paper to appeal to a broad general audience, but it seems like this is an important part of the method that anyone using the method should understand in more detail.

It might be nice to cover some other methods of signal variation e.g. as reviewed in Washke et al. Neuron 2021 and how CSER fits into the broader taxonomy of measures of neural variability (even if restricted to information-theoretic ones e.g. multi-scale entropy and permutation entropy, which have also been linked to prediction in the brain Washke et al. elife 2019).

While the examples are clear and well-motivated, the novel parts could be more developed in terms of interpretation, or linking to existing measures. For example, the frequency results show the complexity changes in "gamma" which is defined as >25Hz. From a biological point of view, it would be nice to understand this better, perhaps splitting low gamma (including 40Hz oscillations) from high gamma (ie MUA). How is the frequency measure affected by the width of the frequency band considered? I understand the sum of the shown terms equals the broadband result but e.g. in Figure 3 if the values were normalised by the bandwidth of each band, gamma might not stand out so much (as it is by far the widest band, 75Hz vs 3Hz for the delta). So if gamma is not contributing more per-unit of frequency, the interpretation might be different. What is it about the gamma band activity that is changing between the conditions: autocorrelation of power, more variability in phase procession? What would this measure give for simulated systems with known changes (for example, changes in oscillatory power, or changes in 1/f slope). What sort of system would give the profiles in Figure 3?

For the temporal example, the result is a nice proof of concept. It looks quite reminiscent of "novel mutual information" time-course (e.g. compare the absolute value of CSER difference to Figure 13, Ince et al HBM 2017, which also showed two peaks of novel information at the time where the gradient of the ERP starts to change, 20-30ms prior to the ERP peak, but in a task with no predictive component). It might be nice to explicitly compare the statistical power to this existing method (conditional mutual information between signal+gradient and experimental condition, conditioning out the selection of previous time points with peak conditional MI). Deviant stimuli initially seem to decrease entropy - by eye, it's surprising this isn't significant (stands out a lot from baseline). Was a two-sided or one-sided (matching the prior hypothesis) test performed here? Could it be that the change in entropy rate is a property of any ERP signal (ie it looks like the change in CSER reflects the following difference in peak ERP - for the first negative peak, the deviant amplitude is lower, for the second positive peak the deviant amplitude is higher), and a lower level signal interpretation (ie amplitude of CSER difference is related to the difference in ERP amplitude, rather than directly reflecting neural mechanisms of prediction).

Reviewer #3 (Public Review):

Summary:<br /> In the current manuscript, Dekraker and colleagues have demonstrated the ability to align hippocampal subfield parcellations across disparate 3D histology samples that differ in contrast, resolution, and processing/staining methods. In doing so, they validated the previously generated Big-Brain atlas by comparing across seven different ground-truth subfield definitions. This is an impressive effort that provides important groundwork for future in vivo multi-atlas methods.

Strengths:<br /> DeKraker and colleagues have provided novel evidence for the tremendously complicated curvature/gyrification of the hippocampus. This work underscores the challenge that this complicated anatomy presents in our ability to co-register other types of hippocampal data (e.g. MRI data) to appropriately align and study a structure in which the curvature varies considerably across individuals.

This paper is also important in that it highlights the utility of using post-mortem histological datasets, where ground truth histology is available, to inform our rigorous study of the in vivo brain.

This work may encourage readers to consider the limitations of the current methods that they currently use to co-register and normalize their MRI data and to question whether these methods are adequate for the examination of subfield activity, microstructure, or perfusion in the hippocampal head, for example. Thus the implications of this work could have a broad impact on the study of hippocampal subfield function in humans.

Weaknesses:<br /> As the authors are well aware, hippocampal subfield definitions vary considerably across laboratories. For example, some neuroanatomists (Ding, Palomero-Gallagher, Augustinack) recognize that the prosubiculum is a distinct region from subiculum and CA1 but others (e.g. Insausti, Duvernoy) do not include this as a distinct subregion. Readers should be aware that there is no universal consensus about the definition of certain subfields and that there is still disagreement about some of the boundaries even among the agreed upon regions.

Reviewer #2 (Public Review):

In this paper, the authors utilize optogenetic stimulation and imaging techniques with fluorescent reporters for pH and membrane voltage to examine the extent of intracellular acidification produced by different ion-conducting opsins. The commonly used opsin CheRiff is found to conduct enough protons to alter intracellular pH in soma and dendrites of targeted neurons and in monolayers of HEK293T cells, whereas opsins ChR2-3M and PsCatCh2.0 are shown to produce negligible changes in intracellular pH as their photocurrents are mostly carried by metal cations. The conclusion that ChR2-3M and PsCatCh2.0 are more suited than proton conducting opsins for optogenetic applications is well supported by the data.

Reviewer #2 (Public Review):

In this study, Moore et al. utilise resting-state fMRI data from the Developing Human Connectome Project, applying a recently developed technique ("connectopic mapping") to identify gradients of functional connectivity within resting-state networks in the human foetal brain. Whilst such gradients have previously been identified in adults, this is the first study to explore the topographic organisation of functional connectivity in the foetal brain. Furthermore, the authors describe localised changes within these gradients over the course of gestation, particularly in brain regions implicated in multisensory processing. Together, these results imply that topographic gradients of brain function are present within the developing foetal brain, and continue to develop through gestation. However, the study does not consider critical confounds inherent in the connectopic mapping technique, and as such I do not believe that the data as presented are sufficient to support the conclusions.

Recent evidence (Watson & Andrews, 2023, Neuroimage) has indicated that the connectopic mapping technique employed here can be substantially confounded by spatial autocorrelations present within the data (for instance, occurring naturally due to the inherent smoothness of the BOLD response, and/or introduced artificially during standard data pre-processing steps such as spatial smoothing or interpolation between co-ordinate spaces). These confounds allow connectopic gradients to be obtained even from random data, and which appear highly similar to those obtained from real data, suggesting that these gradients are strongly influenced by such confounds. Consequently, the resulting gradients may be an inevitability of the way the connectopic mapping technique works, rather than reflecting underlying brain functions per se.

In the current study, all of the gradients flow smoothly and continuously along a single axis within every network region, typically oriented relative to the long axis of the region. To put it another way - the connectopic mapping gives fundamentally the same answer in every network region. Such an organisation does feel a bit biologically implausible, and could be more consistent with the gradients representing an inevitable solution of the analysis technique, rather than necessarily reflecting brain function. Indeed, in some cases the gradients do not correspond well to known organisational principles of the regions. For instance, the primary gradient in the principal visual network flows smoothly along a superior to inferior axis, which the authors suggest corresponds to retinotopic polar angle maps - however, polar angle maps would be expected to reverse direction between each visual region, yet such reversals are not present in this connectopic map. The authors note that the foetal gradients appear highly similar to those previously obtained within similar regions in adult participants - this could be indicative of a consistent organisation across development, but would also be consistent with the same confound affecting foetal and adult participants. The reported changes in the gradients across gestation could reflect changes in the extent of these spatial autocorrelations or in the shape of the regions of interest (perhaps in turn resulting from changes in the underlying brain geometry) rather than necessarily reflecting development of brain function or specialisation. None of this precludes the possibility that these connectopic gradients may (at least partially) also reflect genuine brain functions, but it does obfuscate the extent to which they do so. It would be useful for the authors to give some consideration to this issue.

On a different note, could the authors comment on their reason for studying these gradients at the network level. The authors argue (and I agree) that brain function is likely to be organised topographically, rather than split into discrete parcellated regions. Nevertheless, the brain networks the authors choose to use are themselves discrete regions of interest (albeit fairly large ones). Other groups (e.g., Margulies et al, 2016, PNAS) have described coarser-scale connectopic gradients spanning the whole brain. Is there a reason that the authors have chosen to extract network-level gradients, rather than say coarser-scale whole-brain gradients? Have the authors considered examining how whole-brain gradients change over gestation?

Lastly, the correlated changes between gradients and gestation week appear to occur within small localised clusters. Does this reflect local perturbations of the gradient, or is there perhaps a wider change in the gradient as a whole and these clusters reflect extreme points within this that have changed the most (for instance corresponding to an expansion/contraction of the gradient)?

Reviewer #2 (Public Review):

Summary:<br /> In this study, the authors sought to understand how the receptive fields of bipolar cells contribute to direction selectivity in starburst amacrine cell (SAC) dendrites, their post synaptic partners. In previous literature, this contribution is primarily conceptualized as the 'space-time wiring model', whereby bipolar cells with slow-release kinetics synapse onto proximal dendrites while bipolar cells with faster kinetics synapse more distally, leading to maximal summation of the slow proximal and fast distal depolarizations in response to motion away from the soma. The space-time wiring contribution to SAC direction selectivity has been extensively tested in previous literature using connectomic, functional, and modeling approaches. However, the authors argue that previous functional studies of bipolar cell kinetics have focused on static stimuli, which may not accurately represent the spatiotemporal properties of the bipolar cell receptive field in response to movement. Moreover, this group and others have recently shown that bipolar cell signal processing can change directionally when visual stimuli starts within the receptive field rather than passing through it, complicating the interpretation of moving stimuli that start within a bipolar cell of interest's receptive field (e.g. stimulating only one branch of a SAC or expanding/contracting rings). Thus, the authors choose to focus on modeling and functionally mapping bipolar cell kinetics in response to moving stimuli across the entire SAC dendritic field.

General Comments<br /> There have been several studies that have addressed the contribution of space-time wiring to SAC process direction selectivity. The impact of this project is to show that this contribution is limited. First, the optimal solution obtained by the evolutionary algorithm to generate DS processes is slow proximal and fast distal inputs - exactly what is predicted by space-time wiring, which is exactly what is required of the HRC model. Hence, this result seems expected and it's not clear what the alternative hypothesis is. Second, the experimental results based on glutamate imaging to assess the kinetics of glutamate release under conditions of visual stimulation across a large region of retina confirm previous observations but were important to test. Third, by combining their model model with this experiment data, they conclude that even the optimal space-time wiring is not sufficient to explain the SAC process DS. The results of this approach might be more impactful if the authors come to some conclusion as to what factors do determine the direction selectivity of the SAC process since they have argued that all the current models are not sufficient.

Reviewer #2 (Public Review):

Summary:<br /> In this paper by de Guglielmo and colleagues, the authors were interested in analyzing addiction-like behaviors using a very large number of heterogeneous outbred rats in order to determine the relationships among these behaviors. The paper used both males and females on the order of hundreds of rats, allowing for detailed and complex statistical analyses of the behaviors. The rats underwent cocaine self-administration, first via 2-hour access and then via 6-hour access. The rats also underwent a test of punishment resistance in which footshocks were administered a portion of the time a lever was pressed. The authors also conducted a progressive ratio test to determine the break point for "giving up" pressing the lever and a bottle-brush test to determine the rats' "irritability". Ultimately, principal component analysis revealed that escalation of intake during 6-hour access, punishment resistance, and breakpoint all loaded onto the same principal component. Moreover, the authors also identified a subgroup of "resilient" rats that qualitatively differed from the "vulnerable" rats and also identified sex differences in their work.

Strengths:<br /> The use of heterogeneous rats and the use of so many rats are major strengths of this paper. Moreover, the statistical analyses are particular strengths as they enabled the identification of the three measures as likely reflecting a single underlying construct. The behavioral methods themselves are also strong, as the authors used behavioral measures commonly used in the field that will enable comparison with the field at large. In general, the results support most of the conclusions and provide a wealth of data to the field.

Weaknesses:<br /> Because the authors used so many rats (~600), it is not clear how strong the effects are. That is, a large n makes it easy to identify small effect sizes, but no effect sizes are presented regarding the findings.

The Discussion includes parts that argue that the extended access model is a better model of addiction than short access and suggests that this paper provides support for that. However, there were no rats given short-access for the same period of time as the rats in this paper - i.e., no comparison group. Rather, the only comparison that can be made is as the rats transition from short to long access. The data in Figure 1B appear to show that the rats continue their increase in cocaine intake when they transition from short access to long access. The authors do not provide any statistical analyses about this escalation of intake during short access. However, they claim that "measures related to short-term cocaine intake" were orthogonal to those collected during longer access periods, yet it is not clear to me what measures those are. Nonetheless, as indicated in Figure 1H, it appears that the rats consistently shift from PC1 to PC2 across self-administration, regardless of whether they are in the short or long access period. That is, the long-access measures appear to simply be a continuation of the pattern begun during short access. As a result, notwithstanding the lack of a true short-access control group, it is difficult to see how the authors can draw conclusions about short vs. long access in this paper.

Moreover, as illustrated in Figure 3A, the resilient vs. vulnerable subtypes are apparent during short access self-administration (i.e., they do not require long-access self-administration to develop or be revealed). This suggests, if anything, that short access would be sufficient for identifying such groups. Similarly, Figure 5 shows that short access would be sufficient to identify the "low" vulnerability quartile vs. the other three groups.

During the discussion, the authors briefly discuss gender differences with regard to cocaine use disorder, with the authors trying to claim that women may be more vulnerable to cocaine use disorder. However, the two papers cited do not support that, as they are papers with rodents. A recent comprehensive review on humans with regard to cocaine craving and relapse noted no reliable gender differences (Nicolas et al., 2022, Pharmacological Reviews) and, as the authors themselves noted, men suffer from cocaine use disorder at higher rates than women.

The authors noted that the rats received 0.5 mg/kg/infusion of cocaine but provided no explanation for how this dosing was maintained (or whether it was maintained) across the length of the study. Considering that rats, especially males, increase in size quite a bit during this stage, this could affect measures like intake as well as skew sex difference results. Likewise, the data are presented strictly in the number of cocaine infusions, which does not allow for consideration of body weight.

In the Introduction, the authors make a number of arguments in the second paragraph that have no citations and, therefore, are unsupported.

Reviewer #2 (Public Review):

Summary:<br /> The idea of harnessing small molecules that may affect protein-protein interactions to promote axon regeneration is interesting and worthy of study. In this manuscript, Liu et al. explore a 14-3-3-Spastin complex and its role in axon regeneration.

Strengths:<br /> Some of the effects of FC-A on locomotor recovery after spinal cord contusion look interesting.

Weaknesses:<br /> The manuscript falls short of establishing that a 14-3-3-Spastin complex is important for any FC-A-dependent effects and there are several issues with data quality that make it difficult to interpret the results. Importantly, the effects of the Spastin inhibitor have a major impact on neurite outgrowth suggesting that cells simply cannot grow in the presence of the inhibitor and raising serious questions about any selectivity for FC-A - dependent growth. Aspects of the histology following spinal cord injury were not convincing.

Reviewer #2 (Public Review):

Summary: Franke et al. characterize the representation of color in the primary visual cortex of mice and how it changes across the visual field, with a particular focus on how this may influence the ability to detect aerial predators. Using calcium imaging in awake, head-fixed mice, they characterize the properties of V1 neurons (layer 2/3) using a large center-surround stimulation where green and ultra-violet were presented in random combinations. Using a clustering approach, a set of functional cell-types were identified based on their preference to different combinations of green and UV in their center and surround. These functional types were demonstrated to have varying spatial distributions in V1, including one neuronal type (Green-ON/UV-OFF) that was much more prominent in the posterior V1 (i.e. upper visual field). Modelling work suggests that these neurons likely support the detection of predator-like objects in the sky.

Strengths:<br /> The large-scale single-cell resolution imaging used in this work allows the authors to map the responses of individual neurons across large regions of the visual cortex. Combining this large dataset with clustering analysis enabled the authors to group V1 neurons into distinct functional cell types and demonstrate their relative distribution in the upper and lower visual fields. Modelling work demonstrated the different capacity of each functional type to detect objects in the sky, providing insight into the ethological relevance of color opponent neurons in V1.

Weaknesses:<br /> While the study presents solid evidence a few weaknesses exist, including the size of the dataset, clarity regarding details of data included in each step of the analysis and discussion of caveats of the work. The results presented here are based on recordings of 3 mice. While the number of neurons recorded is reasonably large (n > 3000) an analysis that tests for consistency across animals is missing. Related to this, it is unclear how many neurons at each stage of the analysis come from the 3 different mice (except for Suppl. Fig 4). Finally, the paper would greatly benefit from a more in depth discussion of the caveats related to the conclusion drawn at each stage of the analysis. This is particularly relevant regarding the caveats related to using spike triggered averages to assess the response preferences of ON-OFF neurons, and the conclusions drawn about the contribution of retinal color opponency.

The authors provide solid evidence to support an asymmetric distribution of color opponent cells in V1 and a reduced color contrast representation in lower light levels. Some statements would benefit from more direct evidence such as the integration of upstream visual signals for color opponency in V1.

Overall, this study will be a valuable resource for researchers studying color vision, cortical processing, and the processing of ethologically relevant information. It provides a useful basis for future work on the origin of color opponency in V1 and its ethological relevance.

Reviewer #2 (Public Review):

In this work, Dasgupta et al. investigates the role of Sema7a in the formation of peripheral sensory circuit in the lateral line system of zebrafish. They show that Sema7a protein is present during neuromast maturation and localized, in part, to the base of hair cells (HCs). This would be consistent with pre-synaptic Sema7a mediating formation and/or stabilization of the synapse. They use sema7a loss-of-function strain to show that lateral line sensory terminals display abnormal arborization. They provide highly quantitative analysis of the lateral line terminal arborization to show that a number of specific topological parameters are affected in mutants. Next, they ectopically express a secreted form of Sema7a to show that lateral line terminals can be ectopically attracted to the source. Finally, they also demonstrate that the synaptic assembly is impaired in the sema7a mutant. Overall, the data are of high quality and properly controlled. The availability of Sema7a antibody is a big plus, as it allows to address the endogenous protein localization as well to show the signal absence in the sema7a mutant. The quantification of the arbor topology should be useful to people in the field who are looking at the lateral line as well as other axonal terminals. I think some results are overinterpreted though. The authors state: "Our findings demonstrate that Sema7A functions both as a juxtracrine and as a secreted cue to pattern neural circuitry during sensory organ development." However, they have not actually demonstrated which isoform functions in HCs (also see comments below). In addition, they have to be careful in interpreting their topology analysis, as they cannot separate individual axons. Thus, such analysis can generate artifacts. They can perform additional experiments to address these issues or adjust their interpretations.

Reviewer #2 (Public Review):

Summary:<br /> In an fMRI study requiring participants to attend to one or another object category, either when the object was presented in isolation or with another object superimposed, the authors compared measured univariate and multivariate activation from object-selective and early visual cortex to predictions derived from response gain and tuning sharpening models. They observed a consistent result across higher-level visual cortex that more-divergent responses to isolated stimuli from category pairs predicted a greater modulation by attention when attending to a single stimulus from the category pair presented simultaneously, and argue via simulations that this must be explained by tuning sharpening for object categories.

Strengths:<br /> - Interesting experiment design & approach - testing how category similarity impacts neural modulations induced by attention is an important question, and the experimental approach is principled and clever.

- Examination of both univariate and multivariate signals is an important analysis strategy.

- The acquired dataset will be useful for future modeling studies.

Weaknesses:<br /> - The experimental design does not allow for a neutral 'baseline' estimate of neural responses to stimulus categories absent attention (e.g., attend fixation), nor of the combination of the stimulus categories. This seems critical for interpreting results (e.g., how should readers understand univariate results like that plotted in Fig. 4C-D, where the univariate response is greater for 2 stimuli than one, but the analyses are based on a shift between each extreme activation level?).

- Related, simulations assume there exists some non-attended baseline state of each individual object representation, yet this isn't measured, and the way it's inferred to drive the simulations isn't clearly described.

- Some of the simulation results seem to be algebraic (univariate; Fig. 7; multivariate, gain model; Fig. 8).

- Cross-validation does not seem to be employed - strong/weak categories seem to be assigned based on the same data used for computing DVs of interest - to minimize the potential for circularity in analyses, it would be better to define preferred categories using separate data from that used to quantify - perhaps using a cross-validation scheme? This appears to be implemented in Reddy et al. (2009), a paper implementing a similar multivariate method and cited by the authors (their ref 6).

- Multivariate distance metric - why is correlation/cosine similarity used instead of something like Euclidean or Mahalanobis distance? Correlation/cosine similarity is scale-invariant, so changes in the magnitude of the vector would not change distance, despite this likely being an important data attribute to consider.

- Details about simulations implemented (and their algebraic results in some cases) make it challenging to interpret or understand these results. E.g., the noise properties of the simulated data aren't disclosed, nor are precise (or approximate) values used for simulating attentional modulations.

- Eye movements do not seem to be controlled nor measured. Could it be possible that some stimulus pairs result in more discriminable patterns of eye movements? Could this be ruled out by some aspect of the results?

- A central, and untested/verified, assumption is that the multivariate activation pattern associated with 2 overlapping stimuli (with one attended) can be modeled as a weighted combination of the activation pattern associated with the individual stimuli. There are hints in the univariate data (e.g., Fig. 4C; 4D) that this might not be justified, which somewhat calls into question the interpretability of the multivariate results.

- Throughout the manuscript, the authors consistently refer to "tuning sharpening", an idea that's almost always used to reference changes in the width of tuning curves for specific feature dimensions (e.g., motion direction; hue; orientation; spatial position). Here, the authors are assaying tuning to the category (across exemplars of the category). The link between these concepts could be strengthened to improve the clarity of the manuscript.

Reviewer #2 (Public Review):

This study used coarse-grained molecular dynamics simulation to explain how the binding of polyPR might interfere with distinct stages of the transport cycle. This finding shows that the interaction between polyPR and transport components is driven by electrostatic interactions and is correlated with the salt concentration and the length of polyPR, providing an important basis for subsequent exploration of the impact of C9orf72 R-DPRs on NCT disruption.

Reviewer #2 (Public Review):

Summary:<br /> This study builds upon previous work that demonstrated that brain injury results in leakage of albumin across the blood-brain barrier, resulting in activation of TGF-beta in astrocytes. Consequently, this leads to decreased glutamate uptake, reduced buffering of extracellular potassium, and hyperexcitability. This study asks whether such a process can play a physiological role in cortical plasticity. They first show that stimulation of a forelimb for 30 minutes in a rat results in leakage of the blood-brain barrier and extravasation of albumin on the contralateral but not ipsilateral cortex. The authors propose that the leakage is dependent upon neuronal excitability and is associated with an enhancement of excitatory transmission. Inhibiting the transport of albumin or the activation of TGF-beta prevents the enhancement of excitatory transmission. In addition, gene expression associated with TGF-beta activation, synaptic plasticity, and extracellular matrix are enhanced on the "stimulated" hemisphere. That this may translate to humans is demonstrated by a breakdown in the blood-brain barrier following activation of brain areas through a motor task.

Strengths:<br /> This study is novel and the results are potentially important as they demonstrate an unexpected breakdown of the blood-brain barrier with physiological activity and this may serve a physiological purpose, affecting synaptic plasticity.

The strengths of the study are:<br /> 1) The use of an in vivo model with multiple methods to investigate the blood-brain barrier response to a forelimb stimulation.<br /> 2) The determination of a potential functional role for the observed leakage of the blood-brain barrier from both a genetic and electrophysiological viewpoint.<br /> 3) The demonstration that inhibiting different points in the putative pathway from activation of the cortex to transport of albumin and activation of the TGF-beta pathway, the effect on synaptic enhancement could be prevented.<br /> 4) Preliminary experiments demonstrating a similar observation of activity-dependent breakdown of the blood-brain barrier in humans.

Weaknesses:<br /> There are both conceptual and experimental weaknesses.

1) The stimulation is in an animal anesthetized with ketamine, which can affect critical receptors (ie NMDA receptors) in synaptic plasticity.

2) The stimulation protocol is prolonged and it would be helpful to know if briefer stimulations have the same effect or if longer stimulations have a greater effect ie does the leakage give a "readout" of the stimulation intensity/length.

3) For some of the experiments (see below), the numbers of animals are low and the statistical tests used may not be the most appropriate, making the results less clear cut.

4) The experimental paradigms are not entirely clear, especially the length of time of drug application and the authors seem to try to detect enhancement of a blocked SEP.

4) It is not clear how long the enhancement lasts. There is a remark that it lasts longer than 5 hours but there is no presentation of data to support this.

5) It is not clear if this enhancement of synaptic transmission has any physiological role.

6) The spatial and temporal specificity of this effect is unclear (other than hemispheric in rats) and even less clear in humans.

7) It is not clear to what extent the experimenters and those doing the analysis were blinded to group. If neither were blind to group, then considerable biases could be introduced.

8) The experimenters rightly use separate controls for most of the experiments but this is not always the case, also raising the possibility that the application of drugs was not done randomly or interleaved, but possibly performed in blocks of animals, which can also affect results.

9) Methyl-beta-cyclodextrin clears cholesterol so the effect on albumin transport is not specific, it could be mediating its effect through some other pathway.

10) Since the breakdown of the blood-brain barrier can be inhibited by a TGF-beta inhibitor, then this implies that TGF-beta is necessary for the breakdown of the blood-brain barrier. This does not sit well with the hypothesis that TGF-beta activation depends upon blood-brain barrier leakage.

Reviewer #2 (Public Review):

Summary:<br /> The paper entitled "PAK3 downregulation induces cognitive 1 impairment following cranial irradiation" by Lee et al. aimed at investigating the functional impact of cranial irradiation in mouse and propose PAK3 as molecular element involved in radiation-induced cognitive decrement. The results provided in this paper are problematic as both the irradiation paradigm (5X2 Gy) as well as the timing of investigation (3 to 8 days post-IR) are completely irrelevant to investigate radiation induced neurocognitive impairment. This testifies to the team's lack of knowledge in radiobiology/radiotherapy and the methodology to explore radiation induced neurocognitive damages. It precludes any further relevance of the molecular results.

Weaknesses:<br /> First and according to the BED equation a single dose of 10 Gy cannot not be approximated by 5 fractions of 2 Gy, as fractionation is known to decrease normal tissue toxicity. Note that in radiobiology/radio-oncology, the BED stands for "Biologically Effective Dose." This equation is used to compare the effects of different radiation treatments on biological tissues, taking into account the dose, fractionation, and the overall biological response of the tissue to radiation.<br /> The BED equation is commonly used to calculate the equivalent dose of a fractionated radiation treatment, which is the dose that would produce the same biological effect as a single, higher dose delivered in a single fraction.<br /> The general formula for BED is:BED = D * (1 + d / α/β)<br /> D is the total physical dose of radiation delivered in Grays (Gy)<br /> d is the dose per fraction in Gy<br /> α/β is the tissue-specific ratio of the linear (α) and quadratic (β) components of the radiation response. It is measured in Gy and describes how the tissue responds to different fractionation schedules (usually equal to 3 for the normal brain).<br /> Please refers to radiobiology/radiotherapy textbooks by Hall or Joiner.

Second, the brain is a late responding organ. GBM patients treated with 60 Gy exhibit progressive and debilitating impairments in memory, attention and executive function several month post-irradiation. In mice, neurocognitive decrements after a single dose of 10 Gy delivered to the whole brain does occur at late time point, usually > 2 months post-exposure. Multiple publications such as the one by Limoli C lab, Rossi S lab, Britten R lab or earlier Fike J lab and Robin M lab support this. Next, 5 fractions of 2 Gy will be more protective than a single dose of 10 Gy and neurocognitive decrements will require at least 5-6 months to occur if they ever occur. In Figure 1, the decrement reported is marginal, the number of animals included (4 to 5 at most?) The number of animals is not specified) is too low to draw any significant conclusions. In addition to the timing issue, the strategy described for NOR analysis shows methodological issues with the habituation period being too short and exploration level being very low.

Reviewer #2 (Public Review):

Summary:

Spargo and colleagues present an analysis of the shared genetic architectures of Schizoprehnia and several late-onset neurological disorders. In contrast to many polygenic traits for which global genetic correlation estimates are substantial, global genetic correlation estimates for neurological conditions are relatively small, likely for several reasons. One is that assortative mating, which will spuriously inflate genetic correlation estimates, is likely to be less salient for late-onset conditions. Another, which the authors explore in the current manuscript, is that some loci affecting two or more conditions (i.e., pleiotropic loci) may have effects in opposite directions, or shared loci are sparse, such that the global genetic correlation signal washes out.

The authors apply a local genetic correlation approach that assesses the presence and direction of pleiotropy in much smaller spatial windows across the genome. Then, within regions evidencing local genetic correlations for a given trait pair, they apply fine-mapping and colocalization methods to attempt to differentiate between two scenarios: that the two traits share the same causal variant in the region or that distinct loci within the region influence the traits. Interestingly, the authors only discover one instance of the former: an SNP in the HLA region appearing to confer risk for both AD and ALS. This is in contrast to six regions with distinct causal loci, and twenty regions with no clear shared loci.

Finally, the authors have published their analysis pipeline such that other researchers might easily apply the same techniques to other collections of traits.

Strengths:<br /> - All such analysis pipelines involve many decision points where there is often no clear correct option. Nonetheless, the authors clearly present their reasoning behind each such decision.<br /> - The authors have published their analytic pipeline such that future researchers might easily replicate and extend their findings.

Weaknesses:<br /> - The majority of regions display no clear candidate causal variants for the traits, whether shared or distinct. Further, despite the potential of local genetic correlation analysis to identify regions with effects in opposing directions, all of the regions for causal variants were identified for both traits evidenced positive correlations. The reasons for this aren't clear and the authors would do well to explore this in greater detail.<br /> - The authors very briefly discuss how their findings differ from previous analyses because of their strict inclusion for "high-quality" variants. This might be the case, but the authors do not attempt to demonstrate this via simulation or otherwise, making it difficult to evaluate their explanation.

Reviewer #2 (Public Review):

The authors characterized the recombinase-based cumulative fate maps for vesicular glutamate transporters (Vglut1, Vglut2 and Vglut3) expression and compared those maps to their real-time expression profiles in central NA neurons by RNA in situ hybridization in adult mice. Authors have revealed a new and intriguing expression pattern for Vglut2, along with an entirely uncharted co-expression domain for Vglut3 within central noradrenergic neurons. Interestingly, and in contrast to previous studies, the authors demonstrated that glutamatergic signaling in central noradrenergic neurons does not exert any influence on breathing and metabolic control either under normoxic/normocapnic conditions or after chemoreflex stimulation. Also, they showed for the first-time the Vglut3-expressing NA population in C2/A2 nuclei. In addition, they were also able to demonstrate Vglut2 expression in anterior NA populations, such as LC neurons, by using more refined techniques, unlike previous studies.

A major strength of the study is the use of a set of techniques to investigate the participation of NA-based glutamatergic signaling in breathing and metabolic control. The authors provided a full characterization of the recombinase-based cumulative fate maps for Vglut transporters. They performed real-time mRNA expression of Vglut transporters in central NA neurons of adult mice. Further, they evaluated the effect of knocking down Vglut2 expression in NA neurons using a DBH-Cre; Vglut2cKO mice on breathing and control in unanesthetized mice. Finally, they injected the AAV virus containing Cre-dependent Td tomato into LC of v-Glut2 Cre mice to verify the VGlut2 expression in LC-NA neurons. A very positive aspect of the article is that the authors combined ventilation with metabolic measurements. This integration holds particular significance, especially when delving into the exploration of respiratory chemosensitivity. Furthermore, the sample size of the experiments is excellent.

Despite the clear strengths of the paper, some weaknesses exist. It is not clear in the manuscript if the experiments were performed in males and females and if the data were combined. I believe that the study would have benefited from a more comprehensive analysis exploring the sex specific differences. The reason I think this is particularly relevant is the developmental disorders mentioned by the authors, such as SIDS and Rett syndrome, which could potentially arise from disruptions in central noradrenergic (NA) function, exhibit varying degrees of sex predominance. Moreover, some of the noradrenergic cell groups are sexually dimorphic. For instance, female Wistar rats exhibit a larger LC size and more LC-NA neurons than male subjects (Pinos et al., 2001; Garcia-Falgueras et al., 2005). More recently, a detailed transcriptional profiling investigation has unveiled the identities of over 3,000 genes in the LC. This revelation has highlighted significant sexual dimorphisms, with more than 100 genes exhibiting differential expression within LC-NA neurons at the transcript level. Furthermore, this investigation has convincingly showcased that these distinct gene expression patterns have the capacity to elicit disparate behavioral responses between sexes (Mulvey et al., 2018). Therefore, the authors should compare the fate maps, Vglut transporters in males and females, at least considering LC-NA neurons. Even in the absence of identified sex differences, this information retains significant importance.

An important point well raised by the authors is that although suggestive, these experiments do not definitively rule out that NA-Vglut2 based glutamatergic signaling has a role in breathing control. Subsequent experiments will be necessary to validate this hypothesis.

An improvement could be made in terms of measuring body temperature. Opting for implanted sensors over rectal probes would circumvent the need to open the chamber, thereby preventing alterations in gas composition during respiratory measurements. Further, what happens to body temperature phenotype in these animals under different gas exposures? These data should be included in the Tables.

Is it plausible that another neurotransmitter within NA neurons might be released in higher amounts in DBH-Cre; Vglut2 cKO mice to compensate for the deficiency in glutamate and prevent changes in ventilation?

Continuing along the same line of inquiry is there a possibility that Vglut2 cKO from NA neurons not only eliminates glutamate release but also reduces NA release? A similar mechanism was previously found in VGLUT2 cKO from DA neurons in previous studies (Alsio et al., 2011; Fortin et al., 2012; Hnasko et al., 2010). Additionally, does glutamate play a role in the vesicular loading of NA? Therefore, could the lack of effect on breathing be explained by the lack of noradrenaline and not glutamate?

Reviewer #2 (Public Review):

In this work, the authors found in the mouse line of GABA a1 subunit KO in thalamic neurons, which was previously reported lacking ocular dominance (OD) plasticity in juvenile V1 and dLGN (Sommeijer et al., 2017), the adult V1 and dLGN OD plasticity was also missing. Through muscimol inhibiting the V1 feedback, thalamic OD plasticity was unaffected in both WT and KO adult mice. However, during the critical period, the thalamic OD plasticity was dependent on V1 feedback in WT mice.

Strengths:

1. The experiments were well designed. The authors used both MD and No MD controls with both WT and KO mice. The authors used in vivo SU recording, which is broadly accepted as the major method for evaluating OD plasticity.

2. The data analysis was solid. The authors used proper statistical tests for non-parametric data set.

Weaknesses:

1. In my previous review I pointed out that an alternative interpretation of the results is that the lack of OD plasticity in adult V1 and dLGN was caused by an early blockade of the development of the inhibitory circuit in dLGN, which causes life-long deficits in the functional connection of dLGN. The best way to rule out this possibility is by using conditional KO mice that dLGN synaptic inhibition was only interfered in adulthood. In response to my concern, the authors replied with a long text of reasoning why the current results are solid enough and the proposed experiment was unnecessary. I agree with most of the explanation that the current conclusion is solid, but I still think that the cKO experiment will be a good supplement to the current study, and if we do see a similar result in the cKO mice, the conclusion that the adult perturbation of thalamic inhibitory circuit interfere with the OD plasticity will be more convincing. However, I do understand that repeating the experiments again in another mouse line will be difficult and time-consuming, so the authors could choose if they want to perform the experiment or not.

2. Now the discussion part is very long and complex. Rearranging the discussion with sub-sections will make it easy to read.

Reviewer #2 (Public Review):

This manuscript by Xu et al. explores the potential joint storage/retrieval of associated signals in learning/memory and how that is encoded by some associative memory neurons using a mouse model. The authors examined mouse associative learning by pairing multimodal mouse learning including olfactory, tactile, gustatory, and pain/tail heating signals. The key finding is that after associative learning, barrel neurons respond to other multi-model stimulations. They found these barrel cortical neurons interconnect with other structures including piriform cortex, S1-Tr and gustatory cortical neurons. Further studies showed that Neuroligin 3 mediated the recruitment of associative memory neurons during paired stimulation group. The authors found that knockdown Neuroligin 3 in the barrel cortex suppressed the associative memory cell recruitment in the paired stimulation learning. Overall, while the findings of this study are interesting, the concept of associative learning involving multiple functionally connective cortical regions is not that novel. While some data presented are convincing, the other seems to lack rigor. In addition, more details and clarification of the experimental methods are needed.

Reviewer #2 (Public Review):

Starting from the observation that difficulty estimation lies at the core of human cognition, the authors acknowledge that despite extensive work focusing on the computational mechanisms of decision-making, little is known about how subjective judgments of task difficulty are made. Instantiating the question with a perceptual decision-making task, the authors found that how humans pick the easiest of two stimuli, and how quickly these difficulty judgments are made, are best described by a simple evidence accumulation model. In this model, perceptual evidence of concurrent stimuli is accumulated and difficulty is determined by the difference between the absolute values of decision variables corresponding to each stimulus, combined with a threshold crossing mechanism. Altogether, these results strengthen the success of evidence accumulation models in describing human decision-making, now extending it to judgments of difficulty.

The manuscript addresses a timely question and is very well written, with its goals, methods and findings clearly explained and directly relating to each other. The authors are specialists of evidence accumulation tasks and models. Their modelling of human behaviour within this framework is state-of-the-art. In particular, their model comparison is guided by qualitative signatures which are diagnostic to tease apart different models (e.g., the RT criss-cross pattern). Human behaviour is then inspected for these signatures, instead of relying exclusively on quantitative comparison of goodness-of-fit metrics.

The study has potential limitations well flagged by the authors after the revision process. The main limitation pertains to the (dis)similarity between the behavioural task used in the study and difficulty judgments people actually do in real world (and which are well illustrated in the introduction). First, difficulty judgments made in the task never impact the participant (a new trial simply follows) while difficulty judgments in the wild often determine whether to pursue or quit the corresponding task, which can have consequences years after the difficulty estimation (e.g., deciding to engage in a particular academic path as a function of the estimated difficulty). Second, while trial-by-trial feedback is delivered in the task, difficulty estimation in the wild has to be made with partial information and feedback is either absent or delayed. How much these differences are key in providing an accurate computational description of human difficulty judgments will likely require further research.

Another limitation is the absence of models based on computational principles other than evidence accumulation. Although there are good reasons to favour evidence accumulation models in these settings (as mentioned by the authors in their manuscript), showing that evidence accumulation models would have won against competitors would have further strengthened the authors' claim that difficulty judgment about perceptual information are firmly anchored in the principles of evidence accumulation.

These limitations should not distract the reader from the impact of the present work, which will likely be wide, spanning the whole field of decision-making, and this across species. It will echo in particular with the many other seminal studies that have relied on a similar theoretical account of behaviour and brain activity (evidence accumulation). In addition, this study will hopefully inspire novel task designs aiming at addressing difficulty judgment estimations in controlled lab experiments, possibly with features closer to real world difficulty estimation (e.g., long-term consequences of difficulty estimation and absence of feedback).

Reviewer #2 (Public Review):

Summary:<br /> In the present study, van Gerwen et al. perform deep phosphoproteomics on muscle from saline or insulin-injected mice from 5 distinct strains fed a chow or HF/HS diet. The authors follow these data by defining a variety of intriguing genetic, dietary, or gene-by-diet phosphor-sites that respond to insulin accomplished through the application of correlation analyses, linear mixed models, and a module-based approach (WGCNA). These findings are supported by validation experiments by intersecting results with a previous profile of insulin-responsive sites (Humphrey et al, 2013) and importantly, mechanistic validation of Pfkfb3 where overexpression in L6 myotubes was sufficient to alter fatty acid-induced impairments in insulin-stimulated glucose uptake. To my knowledge, this resource provides the most comprehensive quantification of muscle phospho-proteins which occur as a result of diet in strains of mice where genetic and dietary effects can be quantifiably attributed in an accurate manner. Utilization of this resource is strongly supported by the analyses provided highlighting the complexity of insulin signaling in muscle, exemplified by contrasts to the "classically-used" C57BL6/J strain. As it stands, I view this exceptional resource as comprehensive with compelling strength of evidence behind the mechanism explored. Therefore, most of my comments stem from curiosity about pathways within this resource, many of which are likely well beyond the scope of incorporation in the current manuscript. These include the integration of previous studies investigating these strains for changes in transcriptional or proteomic profiles and intersections with available human phospho-protein data, many of which have been generated by this group.

Strengths:<br /> Generation of a novel resource to explore genetic and dietary interactions influencing the phospho-proteome in muscle. This is accompanied by the elegant application of in silico tools to highlight the utility.

Weaknesses:<br /> Some specific aspects of integration with other data among the same fixed strains could be strengthened and/or discussed.

Reviewer #2 (Public Review):

Summary:<br /> This manuscript provides microprobe serial oxygen isotope data from thin-sectioned modern and fossil orangutan teeth in an effort to reconstruct the seasonality of rainfall in Borneo and Sumatra. The authors also explore the hypothesis that nursing could affect early tooth (first molar) isotope values. They find that all molars yield similar oxygen isotope values and therefore conclude that future research need not exclude the use of first molars. With regard to seasonality, the modern orangutans yield similar results from both islands. The authors suggest differences between modern and fossil orangutan teeth, but the comparisons could be more fully explored.

Strengths:<br /> The study employs a sampling method that captures serial isotope values within thin sections of teeth using a microprobe that provides a much higher resolution than traditional hand-held drilling.

Weaknesses:<br /> The study only examines six modern and six fossil orangutan individuals. Of those, only four modern individuals were samples across multiple molars. The comparisons between modern and fossil teeth are difficult to follow, making unclear the conclusion that climate has changed.

Reviewer #2 (Public Review):

Summary:<br /> Radial spokes are evolutionarily conserved protein complexes that are important for cilia motility. So far, the composition of certain radial spokes was investigated in the algae Chlamydomonas, mice, and humans. This work by Bicka et al. investigated the composition of radial spokes in the ciliate Tetrahymena by analyzing knockouts and strains that express tagged radial spoke proteins, using mass spectrometry and cryo-electron tomography. While three specific types of radial spokes have been reported thus far, this study suggests that in Tetrahymena, there is another layer to the variability in radial spokes. Additionally, many proteins with predicted enzymatic folds have now been assigned to radial spokes. The comparison of ciliary complexes between species is important to define the basic principles that govern cilia motility, as well as to reveal the differences that enable cilia of various organisms to beat in diverse environments.

Strengths:<br /> The manuscript includes a thorough bioinformatic analysis of radial spoke proteins in Tetrahymena and reveals the presence of multiple orthologs to certain algae and mammalian radial spoke proteins. The mass spectrometry analysis and cryo-electron tomography experiments are solid and informative. This work provides a lot of important data and thus, opens the door to resolve the exact composition and structures of radial spokes in Tetrahymena and perhaps other species.

Weaknesses:<br /> The assignment of the three RSP3 orthologs to RS1, RS2, and RS3 is based only on missing structures in the knockouts. Although this method is informative, it is not sufficient to draw conclusions regarding the positions of the missing proteins. There are numerous examples where a structure was missing, but the absent protein was localized elsewhere (i.e., absence of central pair protrusions in patients with mutations in radial spoke proteins). To directly demonstrate the position of an RSP3 ortholog in a certain radial spoke, the protein can be labeled with a tag that is visualized in subtomogram averages (as was done in Oda et al., 2014 and other studies). Relying on the data from knockouts alone, the model for radial spoke composition in Tetrahymena (Fig. 6) may be incomplete.

The control for the bio-ID experiment was WT cells. Since there are many hits in the experiment, a better control would have been a strain with free BirA, or BirA fused to a protein that is distant from the radial spokes, such as one of the outer-dynein arm proteins, or a ciliary membrane protein.

Reviewer #2 (Public Review):

It is well known that introducing clusters in balanced random networks leads to metastable dynamics that potentially span long time scales. The authors build on their previous work (Stern et al. 2014) and here show that the lifetime of metastable states depends on the size of the individual activated clusters. Showing qualitative similarities between clustered spiking networks and networks of bistable rate units, the authors further derive dynamic mean-field predictions for the separation of time scales of the dynamics in relation to differences in the strength of self-couplings in rate networks. Further, they confirm these results in simulations of spiking networks and compare them to time scales observed in the orbitofrontal cortex. Finally, the authors show that assemblies of a particular size (and thus time scale) get entrained by specific external input frequencies, allowing the network to demix temporal signals in a spatial manner.

The manuscript is in general well written and addresses a timely and important topic in neuroscience. However, there are concerns related to the discussion of alternative mechanisms for a large repertoire of time scales as well as the relation between the spiking and rate network model.

Reviewer #2 (Public Review):

The work is very clearly designed, executed, and written. The transcription output data is rigorous and well quantified, and the fit of the TF binding model clearly shows agreement with experiments in the case of cooperativity, but not in its absence, making a strong case for the authors' conclusion.

How the Hidden Markov Model fit results (promoter kon and koff values) lead to the observed effects on transcription output is less clear. For instance, Dl1 deletion results in a small increase in kon and a moderate increase in koff, which seems at odds with the other variants. Yet all variants exhibit similar transcription output profiles. One other intriguing observation is that the promoter states in Fig. 4C&D do not look dramatically different in their kinetics, yet the input transcription traces exhibit a 3-fold amplitude difference. Maybe the authors can clarify these apparent discrepancies.

The authors observe cooperativity between TF binding sites and transcription output, which their model suggests is driven by TF binding cooperativity ("We propose that the cooperativity allows TF binding sites with moderate or weak affinities to recruit more TFs to the enhancer"). This is plausible and likely, but not rigorously demonstrated; another possibility could be cooperativity at the step of transcription activation. One could verify that the binding step is the cooperative one via ChIP-qPCR in the different variants, but given the cautious wording of the paper, this is not absolutely necessary.

Reviewer #2 (Public Review):

In this paper, the authors carry out neural circuit modeling to theoretically elucidate the mechanism underlying the empirically observed (in a previous study by some of the current authors) reduction in neural synchrony in the monkey prefrontal cortex (PFC), as a result of NMDAR blockade. Empirically it was previously found that in monkeys performing a cognitive control task, PFC neurons exhibit precisely timed synchronous firing, especially in the short period before the monkey's response, leading to "0-lag" (zero in the 1-2 millisecond timescale) spiking correlations. This signature of synchrony was then found to be extinguished or diminished with the systemic administration of an NMDAR antagonist.

In the current study, the authors simulate and analyze a network of excitatory and inhibitory spiking neurons as a model of a local PFC circuit, to elucidate the mechanism underlying this effect. The model network is composed of leaky integrate-and-fire neurons with conductance-based synaptic inputs and is sparsely and randomly connected as in the classic studies of balanced networks in which neurons fire irregularly as observed in the cortex. Using mean-field theory, the authors start by mapping out the phase boundary between the asynchronous irregular and synchronous irregular states in the network as a function of network parameters controlling synaptic connectivity and external background inputs (which they parametrize as ratios of recurrent or external currents mediated by AMPAR, NMDAR or GABAA). The transition between the two phases corresponds to a Hopf-like bifurcation above which synchronous oscillations with frequency in the gamma-band (or above) emerge. It is found that with an increase in external inputs, a network in the asynchronous state (but close to criticality) can switch to the synchronous state. Based on this, the authors hypothesize that an increase in the external drive is the mechanism underlying the empirically observed increase in synchrony before the behavioral response. It is then shown that a reduction in NMDAR conductance (keeping AMPAR or GABAR conductances fixed) has the opposite effect, and pushes the network towards the asynchronous state, and can counteract or weaken the effect of increased external input. In both cases increase or decrease in synchrony is quantified by an increase or decrease in 0-lag pairwise correlations; transition to synchrony is shown to also lead to the development of nonzero-lag peaks in the average spiking correlation reflecting gamma-band oscillations. The authors then show that (with the appropriate choice of primary network parameters) their proposed mechanisms for the (natural) increase in synchrony via an increase in external inputs and the weakening of this effect with the weakening of NMDA conductances do semi-quantitatively match the observed changes in 0-lag synchrony and nonzero lag peaks in spiking correlations. Finally, they discuss the effect of the balance between average NMDA and GABA currents in the primary (baseline) network on the above effects.

Strengths:<br /> - The modeling and analysis are solid and overall this work succeeds in providing a convincing mechanistic explanation for the specific empirically observed effects in monkey PFC: the natural task-dependent modulation of 0-lag synchrony and its extinction with NMDA blockage.

- The manuscript is very readable and the figures and plots are clearly described.

- The mathematical mean-field analysis in the Methods section is also sound and well written and does/can (see below) provide a sufficient mathematical explanation of the simulation results.

Weaknesses:<br /> 1) I found the intuitive explanation of the effects of external input or NMDAR conductance on synchrony incomplete. While simulations and mean-field analysis both predict this effect, the mean-field theory and the linearization analysis and stability analysis can be used to further shed light on the precise mechanism by which external input and NMDAR conductance promote synchrony (or destabilization of the asynchronous state).

2) An important natural question (which is relevant to the connection with schizophrenia) is what are the distinct roles of AMPAR-based and NMDAR-based excitation on the transition to synchrony, and this is not addressed in this study. It would be important to clarify what is special/distinct about NMDAR in the current findings.

3) In the Introduction and Discussion, the authors speculate on the possible connection between their empirical and theoretical findings (on the effect of NMDAR hypofunction on synchronous spiking) and the pathogenesis of schizophrenia. While this is not central to the findings of the paper, because it is relevant to the broader significance and impact of this work I will note the following. Their proposed specific link to pathogenesis is as follows: the reduction in precisely timed synchrony resulting from NMDAR hypofunction can disrupt spike-timing dependent plasticity (STDP) and lead to "disconnection" of cortical circuits as observed in schizophrenia. Letting aside the fact that observations in schizophrenia relate to functional connectivity and not synaptic connectivity, previous theoretical studies of STDP in spiking networks do not support the claim that lack of synchronous activity would lead to disconnection of the circuit.

Reviewer #2 (Public Review):

This study is impressive in several ways and will be of interest to behavioral and brain scientists working on diverse topics.

First, from a theoretical point of view, it very convincingly integrates several lines of research (confidence, interpersonal alignment, psychophysical, and neural evidence accumulation) into a mechanistic computational framework that explains the existing data and makes novel predictions that can inspire further research. It is impressive to read that the corresponding model can account for rather non-intuitive findings, such as that information about high confidence by your collaborators means people are faster but not more accurate in their judgements.

Second, from a methodical point of view, it combines several sophisticated approaches (psychophysical measurements, psychophysical and neural modelling, electrophysiological and pupil measurements) in a manner that draws on their complementary strengths and that is most compelling (but see further below for some open questions). The appeal of the study in that respect is that it combines these methods in creative ways that allow it to answer its specific questions in a much more convincing manner than if it had used just either of these approaches alone.

Third, from a computational point of view, it proposes several interesting ways by which biologically realistic models of perceptual decision-making can incorporate socially communicated information about other's confidence, to explain and predict the effects of such interpersonal alignment on behavior, confidence, and neural measurements of the processes related to both. It is nice to see that explicit model comparison favor one of these ways (top-down driving inputs to the competing accumulators) over others that may a priori have seemed more plausible but mechanistically less interesting and impactful (e.g., effects on response boundaries, no-decision times, or evidence accumulation).

Fourth, the manuscript is very well written and provides just the right amount of theoretical introduction and balanced discussion for the reader to understand the approach, the conclusions, and the strengths and limitations.

Finally, the manuscript takes open science practices seriously and employed preregistration, a replication sample, and data sharing in line with good scientific practice.

Having said all these positive things, there are some points where the manuscript is unclear or leaves some open questions. While the conclusions of the manuscript are not overstated, there are unclarities in the conceptual interpretation, the descriptions of the methods, some procedures of the methods themselves, and the interpretation of the results that make the reader wonder just how reliable and trustworthy some of the many findings are that together provide this integrated perspective.

First, the study employs rather small sample sizes of N=12 and N=15 and some of the effects are rather weak (e.g., the non-significant CPP effects in study 1). This is somewhat ameliorated by the fact that a replication sample was used, but the robustness of the findings and their replicability in larger samples can be questioned.

Second, the manuscript interprets the effects of low-confidence partners as an impact of the partner's communicated "beliefs about uncertainty". However, it appears that the experimental setup also leads to greater outcome uncertainty (because the trial outcome is determined by the joint performance of both partners, which is normally reduced for low-confidence partners) and response uncertainty (because subjects need to consider not only their own confidence but also how that will impact on the low-confidence partner). While none of these other possible effects is conceptually unrelated to communicated confidence and the basic conclusions of the manuscript are therefore valid, the reader would like to understand to what degree the reported effects relate to slightly different types of uncertainty that can be elicited by communicated low confidence in this setup.

Third, the methods used for measurement, signal processing, and statistical inference in the pupil analysis are questionable. For a start, the methods do not give enough details as to how the stimuli were calibrated in terms of luminance etc so that the pupil signals are interpretable. Moreover, while the authors state that the traces were normalized to a value of 0 at the start of the ITI period, the data displayed in Figure 2 do not show this normalization but different non-zero values. Are these data not normalized, or was a different procedure used? Finally, the authors analyze the pupil signal averaged across a wide temporal ITI interval that may contain stimulus-locked responses (there is not enough information in the manuscript to clearly determine which temporal interval was chosen and averaged across, and how it was made sure that this signal was not contaminated by stimulus effects).

Fourth, while the EEG analysis in general provides interesting data, the link to the well-established CPP signal is not entirely convincing. CPP signals are usually identified and analyzed in a response-locked fashion, to distinguish them from other types of stimulus-locked potentials. One crucial feature here is that the CPPs in the different conditions reach a similar level just prior to the response. This is either not the case here, or the data are not shown in a format that allows the reader to identify these crucial features of the CPP. It is therefore questionable whether the reported signals indeed fully correspond to this decision-linked signal.

Fifth, the authors present some effective connectivity analysis to identify the neural mechanisms underlying the possible top-down drive due to communicated confidence. It is completely unclear how they select the "prefrontal cortex" signals here that are used for the transfer entropy estimations, and it is in fact even unclear whether the signals they employ originate in this brain structure. In the absence of clear methodical details about how these signals were identified and why the authors think they originate in the prefrontal cortex, these conclusions cannot be maintained based on the data that are presented.

Sixth, the description of the model fitting procedures and the parameter settings are missing, leaving it unclear for the reader how the models were "calibrated" to the data. Moreover, for many parameters of the biophysical model, the authors seem to employ fixed parameter values that may have been picked based on any criteria. This leaves the impression that the authors may even have manually changed parameter values until they found a set of values that produced the desired effects. The model would be even more convincing if the authors could for every parameter give the procedures that were used for fitting it to the data, or the exact criteria that were used to fix the parameter to a specific value.

Seventh, on a related note, the reader wonders about some of the decisions the authors took in the specification of their model. For example, why was it assumed that the parameters of interest in the three competing models could only be modulated by the partner's confidence in a linear fashion? A non-linear modulation appears highly plausible, so extreme values of confidence may have much more pronounced effects. Moreover, why were the confidence computations assumed to be finished at the end of the stimulus presentation, given that for trials with RTs longer than the stimulus presentation, the sensory information almost certainly reverberated in the brain network and continued to be accumulated (in line with the known timing lags in cortical areas relative to objective stimulus onset)? It would help if these model specification choices were better justified and possibly even backed up with robustness checks.

Eight, the fake interaction partners showed several properties that were highly unnatural (they did not react to the participant's confidence communications, and their response times were random and thus unrelated to confidence and accuracy). This questions how much the findings from this specific experimental setting would transfer to other real-life settings, and whether participants showed any behavioral reactions to the random response time variations as well (since several studies have shown that for binary choices like here, response times also systematically communicate uncertainty to others). Moreover, it is also unclear how the confidence convergence simulated in Figure 3d can conceptually apply to the data, given that the fake subjects did not react to the subject's communicated confidence as in the simulation.

Reviewer #2 (Public Review):

This study looks at how optomotor turning in fruit flies varies with stimulus conditions. Although the response has usually been observed in the same direction of rotation as the stimulus, they find that in many situations the flies turn strongly in the opposite direction to the stimulus. This 'anti-directional' turning increases with stimulus brightness, contrast, and duration of the stimulus, and also varies with many factors such as rearing temperature, lab, strain, and developmental stage. They show that the anti-directional response depends on neurons in the visual system that are also important for the more standard response, but they don't find clear changes in the activity of these neurons that could explain the directional switch. The main conclusion is that supposedly simple behaviors may be more complicated than they first appear, and careful consideration needs to be given to the precise stimulus conditions and the response dynamics when measuring such behaviors, and especially when comparing data across labs.

Reviewer #2 (Public Review):

This is a very interesting study with a potential impact on understanding the 3D mechanics of cells in epithelia. The assay that the authors developed is novel and quite useful for future studies. However, I was hoping to see more experimental results in the manuscript. For example, there is a zoo of mutants that the community speculates about possible mechanical changes in cells. I was hoping to see if the authors can settle some of these arguments by using their novel technique and analysis.

Reviewer #2 (Public Review):

Plasmodium falciparum RH5 (PfRH5) is an integral membrane protein of P. falciparum merozoites that acts as an essential ligand involved in host erythrocyte invasion, functioning by binding to the erythrocyte surface protein basigin. Previous work by the authors of this study and other groups has demonstrated that antibodies to PfRH5 can block invasion and can be protective in in vivo challenge studies, so PfRH5 is a promising malaria vaccine candidate. This study by Jamwal et al addresses the paradoxical observation, made in earlier work by these authors, that certain antibodies to PfRH5 efficiently inhibit parasite invasion of erythrocytes yet does not block the binding of PfRH5 to recombinant basigin ectodomain. The authors first demonstrate through a range of approaches that most native erythrocyte basigin is expressed in the form of detergent-stable complexes with one of two distinct erythrocyte membrane proteins, plasma membrane calcium ATPase (PMCA) or monocarboxylate transporter (MCT). Using in vitro biophysical techniques, they then show that recombinant PfRH5 binds more tightly (and with slower off-rates) to the native basigin-PMCA or basigin-MCT1 complexes than to the isolated recombinant basigin ectodomain. Finally and crucially, the authors then show that 2 of these known invasion-inhibitory anti-PfRH5 antibodies (called R5.016 and 9AD4) that do not block the interaction between recombinant basigin and PfRH5 do in contrast block the interaction between PfRH5 and basigin-PMCA and basigin-MCT1 complexes. By docking known atomic structures of the R5.016 and 9AD4 Fab-basigin structures onto the known or modelled basigin complex structures, the authors present a convincing argument that the invasion-inhibitory antibodies function through steric hindrance, preventing PfRH5 binding to the basigin-PMCA or basigin-MCT1 complexes. The work provides a rational explanation for the invasion-inhibitory activity of this class of PfRH5-specific antibodies and demonstrates the potential complexity underlying the mode of action of invasion-inhibitory anti-malarial antibodies.

Reviewer #2 (Public Review):

This is a review of "Effect of an enhanced public health contact tracing intervention on the secondary transmission of SARS-CoV-2 in educational settings: the four-way decomposition analysis", by Djuric et al.

In late 2020, a province in northern Italy implemented a new testing regimen for all contacts of people known to have COVID-19, offering them SARS-CoV-2 testing immediately after the detection of the index case instead of at the end of a quarantine period. The authors of this study investigated whether this policy change reduced secondary transmission of SARS-CoV-2 in schools. In addition to studying this primary outcome, they examined two "process" outcomes; whether this policy of testing earlier enabled public health officials to more successfully identify the source of infection of the index case, and if the time interval from detection of the index case to testing of contacts in the educational setting reduced.

They concluded that the time between detection of the index case and testing of contacts did reduce before and after the policy change. Similarly, the proportion of cases for which the source of infection was identified also increased after the policy change. Both of these "process" indicators correlated with reduced secondary transmission, though only identifying the source of infection was associated with a statistically significant (at the 5% level) reduction in secondary transmission.

Strengths of this paper

Educational settings experienced significant disruption during the COVID-19 pandemic, and efforts to better understand the spread of SARS-CoV-2 in schools - and how to mitigate this spread - are of significant public health importance. This paper, therefore, addresses an important topic.

Additionally, the authors describe a detailed dataset comprising case and contact tracing data from over 1,600 index cases with in-school contacts. The richness of the data described in Table 1 provides a good opportunity to conduct a natural experiment on the potential impact of testing contacts immediately after exposure on secondary transmission. The authors also appropriately acknowledge that this interrupted time series study would be insufficient to provide causal information, given the potential for confounders.

Finally, the primary statistical method (a four-way decomposition analysis) was new to me, but - from the references cited - seems appropriate. Given the relative novelty of this method, more space could be dedicated to explaining it in the methods.

Weakness of this paper

Although the paper tackles an important topic with an appropriate dataset, the analyses feel insufficient to fully support the authors' conclusions.

First and most critically, it is difficult to understand exactly what the primary outcome of the study is. Both the median number of secondary cases per class and the proportion of classes that experienced any secondary transmission are presented in Table 1, but - at least in the unadjusted analyses - point in different directions regarding the impact of the effect of the intervention (albeit neither strongly). For example, before the policy change, the median number of secondary cases per index case is 2, while after the policy change, it has reduced to 1. In contrast, before the policy change 37% of classes experienced any secondary transmission, but after the policy change, this had increased to 39% of classes. In some of the adjusted analyses, "number of secondary cases" is stated as the outcome variable, but that is not fully defined. The "attack rate", which is well defined in the methods, could be one option for use as a consistent primary outcome, however, it is only provided for the total study population and the attack rates pre- or post-policy change are not presented or compared.

Additionally, although using a "process measure" as a secondary outcome could be valuable - especially in a natural experiment like this, where identifying a causal relationship with a complex outcome like secondary transmission will be difficult - it was somewhat unclear how the process measures described in this study were measured, or their validity. For example, the reduced time between detection of the index case and testing of contacts seems unsurprising, since the intervention itself is to test contacts immediately after the index case is identified. Additionally, the results describe reductions in median testing delay and median tracing delay, but only testing delay is defined in the methods.

Finally, there is existing published literature that provides additional context on the impact of testing on secondary transmission within schools that arguably provides a higher level of evidence than the current study, but is not cited by the authors. A key limitation of this study - which the authors acknowledge - is the interrupted time series nature of their study, which is open to confounding by other important factors that happened at the same time, including but not limited to: changes in overall incidence of COVID-19; viral evolution (e.g. the emergence of the Alpha variant (B.1.1.7) which occurred during this study and which significantly altered the risk of secondary transmission); the efficiency of the contact tracing system (including skill and size of the contact tracing workforce); and the availability of non-molecular diagnostic tests (e.g. lateral flow devices) that might allow individuals to change their behaviors even without enrolling in this study. Examples of alternative studies which might reduce some of this potential confounding include around 400 schools in Los Angeles County, California, USA, that implemented "test to stay" in 2021 and were compared to 1,600 schools that did not implement "test to stay" [https://www.cdc.gov/mmwr/volumes/70/wr/mm705152e1.htm] and a cluster-randomized trial of daily testing of exposed contacts to study in-school transmission in England, UK, also in 2021 [https://www.sciencedirect.com/science/article/pii/S0140673621019085]. Although these examples describe slightly different interventions involving enhanced testing of exposed contacts, they both compared educational settings with and without the intervention across the same time periods; and the UK study in particular has methodological advantages over this current paper, including randomization. While the findings in the current paper did not contradict these earlier, stronger papers, the example from this province should be placed in context with the totality of evidence around testing in schools.

Reviewer #2 (Public Review):

In their present work, Briggs et al. combine biophysical simulations and experimental recordings of beta cell activity with analyses of functional network parameters to determine the role played by gap-junctional coupling, metabolism, and KATP conductance in defining the functional roles that the cells play in the functional networks, assess the structure-function relationship, and to resolve an important current open question in the field on the role of so-called hub cells in islets of Langerhans.

Combining differential equation-based simulations on 1000 coupled cells with demanding calcium, NAPDH, and FRAP imaging, as well as with advanced network analyses, and then comparing the network metrics with simulated and experimentally determined properties is an achievement in its own right and a major methodological strength. The findings have the potential to help resolve the issue of the importance of hub cells in beta cell networks, and the methodological pipeline and data may prove invaluable for other researchers in the community.<br /> However, methodologically functional networks may be based on different types of calcium oscillations present in beta cells, i.e., fast oscillations produced by bursts of electrical activity, slow oscillations produced by metabolic/glycolytic oscillations, or a mixture of both. At present, the authors base the network analyses on fast oscillations only in the case of simulated traces and on a mixture of fast and slow oscillations in the case of experimental traces. Since different networks may depend on the studied beta cell properties to a different extent (e.g., fast oscillation-based networks may, more importantly, depend on electrical properties and slow oscillation-based networks may more strongly depend on metabolic properties), it is important that in drawing the conclusions the authors separately address the influence of a cell's electrical and metabolic properties on its functional role in the network based on fast oscillations, slow oscillations, or a mixture of both.