Reviewer #2 (Public Review):

This study presents a useful inventory of essential genes from an antibiotic-resistant K. pneumoniae strain to grow in a rich medium. The study also includes a catalogue of genes required to grow/survive in urine and in serum. The former is particularly interesting. The data is analyzed using adequate tools.

The authors leveraged TraDIS to identify essential genes of K. pneumoniae in LB, and those required to survive in urine, and serum. TraDIS is a well-established approach to investigate these aspects, and in fact, has also been already exploited in the case of K. pneumoniae to identify essential genes and those required for serum resistance. The strain used by the team is not probed by many other laboratories, making it difficult to assess the relevance in the context of K. pneumoniae population biology. Nonetheless, the authors have tried to compare their results against other published studies.

The descriptions of the method and analysis of the data are quite detailed; however considering that this work is mostly a bioinformatics one, it would have been interesting to go beyond the Ecl8 strain and make a detailed comparison against the other published data sets as well as consider the genes identified in the wider population structure of K. pneumonaie and other Enterobactericease (particularly E. coli and Salmonella).

The catalogue of genes may spark additional research to provide mechanistic insights into the contribution of the loci to the phenotypes (either urine and/or serum survival). These experiments are not included in the manuscript beyond the validation level achieved by constructing additional mutants using the Red system.

Reviewer #2 (Public Review):

The authors use a series of elegant methods to describe the nature of the interrelationship among CD8+ T cells and fibrocytes in the airways of COPD patients. They find an increased presence of these interactions in COPD and show that CXCL8-CXCR2 interactions are crucial for this interaction, leading to increased CD8+ T cell proliferation.

Major strengths of the work include the detailed functional experiments used to describe the nature of the CD8+ T cell - fibrocyte interaction. Another key strength is the translational approach of the work, building on clinical data and connecting back to these same clinical data. The conclusions of the authors are supported by the data. The impact of the work is significant and key to our understanding of the interrelationship between inflammation and tissue remodeling in COPD. Understanding this relationship holds strong potential for the identification of new drug targets and for the identification of patients at risk.

Reviewer #2 (Public Review):

The authors tried to support the hypothesis that early Homo still had a primitive condition of Broca's cap (the region in fossil endocasts corresponding to Broca's area in the brain), being more similar to the condition in chimpanzees than in humans. The evidence from the described individual points to this direction but there are some flaws in the argumentation.

First, only one human and one chimpanzee were used for comparison, although we know that patterns of brain convolutions (and in addition how they leave imprints in the endocranial bones) are very variable.

Second, the evidence from this fossil specimen adds to the evidence of previously describe individuals but still not yet fully prove the hypothesis.

Third, there is a vicious circle in using primitive and derived features to define a fossil species and then using (the same or different) features to argue that one feature is primitive or derived in a given species. In this case, we expect members of early Homo to be derived compared to their predecessors of the genus Australopithecus and that's why it seems intriguing and/or surprising to argue that early Homo has primitive features. However, we should expect that there is some kind of continuum or mosaic in a time in which a genus "evolves into" another genus. This discussion requires far more discussions about the concepts we use, maybe less discussion about what is different between the two groups but more discussion about the evolutionary processes behind them.

Fourth, the data of convolutional imprints presented are rather subjective when identifying which impressions represent which brain convolutions. Not seeing an impression does not necessarily mean that the corresponding brain feature did not exist. Interestingly, the manuscript does not mention and discuss at all the frontoorbital sulcus. This is a sulcus that usually runs from the orbital surface of the frontal lobe up to divide the inferior frontal gyrus in chimpanzees, a condition totally different than in humans who do not have a frontoorbital sulcus. Could such a sulcus be identified, this would provide a far more convincing argument for a primitive condition in this specimen. In Australopithecus sediba, e.g., the condition in this region seems to be a mosaic in which some aspects of the morphology seem to be more modern while one of the sulcual impressions can well be interpreted as a short frontoorbital sulcus. For this specimen, by the way, I would come back to my third point above: some experts in the field might argue that this specimen could belong to Homo rather than Australopithecus...

According to my arguments above, I think that this manuscript might revive interesting discussions about this topic but it is not likely to settle them because the data presented are not strong enough to fully support the hypothesis.

Reviewer #2 (Public Review):

This work by Hannon and Eisen focuses on the sequence and structural features of transcription factors (TFs) that dictate their sub-nuclear localization. The authors test the hypothesis that intrinsically disordered regions (IDRs) in TFs are drivers of subnuclear localization and clustering by first identifying IDRs in the drosophila proteome using a novel approach and then expressing a subset of IDRs from TFs important during the development of an early embryo. The authors then perform an extensive and high-throughput imaging screen in S2 cells and drosophila embryos and find that subnuclear clustering does not occur when IDRs are expressed alone but happens frequently in full-length TFs, even sometimes without the IDRs. A significant strength of the study is the extensive amount of imaging data that support well the conclusions in the paper. A potential weakness is that the conclusions are based on qualitative analysis only; the work would be strengthened considerably if the authors could provide quantification that allows the reader to distinguish clearly between a homogenous distribution and clustering of TFs. The work tackles an important functional question regarding IDRs in TFs and is of high relevance to the field. There is an impressive amount of data that generally support the conclusion of the paper, which is that IDRs are insufficient to drive TF clustering in the nucleus. The manuscript is very well written, pleasing to read, and easy to follow. This work advances the field considerably, providing valuable mechanistic insights into transcription.

Reviewer #2 (Public Review):

The authors found FOXC2 is mainly expressed in As of mouse undifferentiated spermatogonia (uSPG). About 60% of As uSPG were FOXC2+ MKI67-, indicating that FOXC2 uSPG were quiescent. Similar spermatogonia (ZBTB16+ FOXC2+ MKI67-) were also found in human testis.

The lineage tracing experiment using Foxc2CRE/+;R26T/Gf/f mice demonstrated that all germ cells were derived from the FOXC2+ uSPG. Furthermore, specific ablation of the FOXC2+ uSPGs using Foxc2Cre/+;R26DTA/+ mice resulted in the depletion of all uSPG population. In the regenerative condition created by busulfan injection, all FOXC2+ uSPG survived and began to proliferate at around 30 days after busulfan injection. The survived FOXC2+ uSPGs generated all germ cells eventually. To examine the role of FOXC2 in the adult testis, spermatogenesis of Foxc2f/-;Ddx4-cre mice was analyzed. From a 2-month-old, the degenerative seminiferous tubules were increased and became Sertoli cell-only seminiferous tubules, indicating FOXC2 is required to maintain normal spermatogenesis in adult testes. To get insight into the role of FOXC2 in the uSPG, CUT&Tag sequencing was performed in sorted FOXC2+ uSPG from Foxc2CRE/+;R26T/Gf/f mice 3 days after TAM diet feeding. The results showed some unique biological processes, including negative regulation of the mitotic cell cycle, were enriched, suggesting the FOXC2 maintains a quiescent state in spermatogonia.

Lineage tracing experiments using transgenic mice of the TAM-inducing system was well-designed and demonstrated interesting results. Based on all data presented, the authors concluded that the FOXC2+ uSPG are primitive SSCs, an indispensable subpopulation to maintain adult spermatogenesis. The conclusion of the mouse study is supported by the data presented.

Reviewer #2 (Public Review):

In this paper, Budinská et al. consider whether morphological heterogeneity in colorectal cancer (CRC) might impact gene-expression based classifiers typically applied to bulk CRC tissues. To investigate this, the authors generated and analysed whole transcriptome microarrray profiling data from macro-dissected morphotype-specific tumour regions, bulk tumor and surrounding normal and stromal tissues.

The authors make a number of claims based on their analyses. Namely that<br /> (1) morphotype-specific gene expression profiles and active molecular pathways can be identified and that (2) most gene expression-based classifiers make different predictions when applied to different morphotypes within the same tumour and when applied to morphotype-specific tumor regions versus bulk tumor tissue.

Overall, the manuscript provides an interesting histological/morphological framework through which we can consider heterogeneity in colorectal carcinoma and an approach by which we might improve the performance of gene expression-based classifiers in predicting clinical behaviour and/or responses to therapy. Exploration of CRC morphotypes and their differences was quite interesting. However, more work is needed to support the claims made by the authors. While I appreciate that the authors themselves identify limitations of their study within the manuscript, I believe awareness of these limitations is not reflected in some of the claims made in the abstract and at points in the main text when discussing the use of expression-based classifiers.

Reviewer #2 (Public Review):

Early career funding success has an immense impact on later funding success and faculty persistence, as evidenced by well-documented "rich-get-richer" or "Matthew effect" phenomena in science (e.g., Bol et al. 2018, PNAS). Woitowich et al. examined publicly available data on the distribution of the National Institutes of Health's K99/R00 awards - an early career postdoc-to-faculty transition funding mechanism - and showed that although 85% of K99 awardees successfully transitioned into faculty, disparities in subsequent R01 grant obtainment emerged along three characteristics: researcher mobility, gender, and institution. Men who moved to a top-25 NIH funded institution in their postdoc-to-faculty transition experienced the shortest median time to receiving a R01 award, 4.6 years, in contrast to the median 7.4 years for women working at less well-funded schools who remained at their postdoc institutions. This result is consistent with prior evidence of funding disparities by gender and institution type. The finding that researcher mobility has the largest effect on subsequent funding success is key and novel, and enhances previous work showing the relationship between mobility and ones' access to resources, collaborators, or research objects (e.g., Sugimoto and Larivière, 2023, Equity for Women in Science (Harvard University Press)).

These results empirically demonstrate that even after receiving a prestigious early career grant, researchers with less mobility belonging to disadvantaged groups at less-resourced institutions continue to experience barriers that delay them from receiving their next major grant. This result has important policy implications aimed at reducing funding disparities - mainly that interventions that focus solely on early career or early stage investigator funding alone will not achieve the desired outcome of improving faculty diversity.

The authors also highlight two incredible facts: No postdoc at a historically Black college or university (HBCU) has been awarded a K99 since the program's launch. And out of all 2,847 R00 awards given thus far, only two have been made to faculty at HBCUs. Given the track record of HBCUs for improving diversity in STEM contexts, this distribution of awards is a massive oversight that demands attention.

At no fault of the authors, the analysis is limited to only examining K99 awardees and not those who applied but did not receive the award. This limitation is solely due to the lack of data made publicly available by the NIH. If this data were available, this study would have been able to compare the trajectory of winners versus losers and therefore could potentially quantify the impact of the award itself on later funding success, much like the landmark Bol et al. (2018) paper that followed the careers of winners of an early career grant scheme in the Netherlands. Such an analysis would also provide new insights that would inform policy.

Although data on applications versus awards for the K99/R00 mechanism are limited, there exists data for applicant race and ethnicity for the 2007-2017 period, which were made available by a Freedom of Information Act request through the now defunct Rescuing Biomedical Research Initiative: https://web.archive.org/web/20180723171128/http://rescuingbiomedicalresearch.org/blog/examining-distribution-k99r00-awards-race/ These results are not presently discussed in the paper, but are highly relevant given the discussion of K99 award impacts on the sociodemographic composition of U.S. biomedical faculty. From 2007 to 2017, the K99 award rate for white applicants was 31.0% compared to 26.7% for Asian applicants and 16.2% for Black applicants. In terms of award totals, these funding rates amount to 1,384 awards to white applicants, 610 to Asian applicants, and 25 to Black applicants for the entire 2007-2017 period. And in terms of R00 awards, or successful faculty transitions: whereas 77.0% of white K99 awardees received an R00 award, the conversion rate for Asian and Black K99 awardees was lower, at 76.1% and 60.0%, respectively. Regarding this K99-to-R00 transition rate, Woitowich et al. found no difference by gender (Table 2). These results are consistent with a growing body of literature that shows that while there have been improvements to equity in funding outcomes by gender, similar improvements for achieving racial equity are lagging.

The conclusions are well-supported by the data, and limitations of the data and the name-gender matching algorithm are described satisfactorily.

One aspect that the authors should expand or comment on is the change in the rate of K99 to R00 conversions. Since 2016, while the absolute number of K99 and R00 awards has been increasing, the percentage of R00 conversions appears to be decreasing, especially in 2020 and 2021. This observation is not clearly stated or shown in Figure 1 but is an important point - if the effectiveness of the K99/R00 mechanism for postdoc-to-faculty transitions has been decreasing lately, then something is undermining the purpose of this mechanism. This result bears emphasis and potentially discussion for possible reasons for why this is happening.

Reviewer #2 (Public Review):

DeKraker et al. propose a new method for hippocampal registration using a surface-based approach that preserves the topology of the curvature of the hippocampus and boundaries of hippocampal subfields. The surface-based registration method proved to be more precise and resulted in better alignment compared to traditional volumetric-based registration. Moreover, the authors demonstrated that this method can be performed across image modalities by testing the method with seven different histological samples. While the conclusions of this paper are mostly well supported by data, some aspects of the method need to be clarified. This work has the potential to be a powerful new registration technique that can enable precise hippocampal registration and alignment across subjects, datasets, and image modalities.

Regarding the methodological clarification of the surfaced-based registration method, the last step of the process needs further clarification. Specifically, after creating the averaged 2D template, it is unclear how each individual sample is registered to sample1's space. If I understand correctly, after creating the averaged 2D template, each individual sample is then registered to sample1's space via the transform from each sample to the averaged template and then the inverse transform from the template to sample1's space. Samples included both left and right hemispheres, so were all samples being propagated to left hemisphere sample 1 space? The authors also note that a measure of the subfield labels overlap with that sample's ground-truth subfield definitions was calculated. Is this a measure of overlap, for example, between sample 3 (registered to sample 1 space) and the ground-truth (unfolded, not registered) sample 3 labels? It would be beneficial to provide a full walkthrough of one example sample to clarify the steps. Clarification of this aspect of the method is critical for understanding the evaluation of the method.

Reviewer #2 (Public Review):

Mignerot et al. study variations in egg retention in a large set of wild C. elegans strains using detailed analysis of a subset of these strains to those that these variations in egg retention appear to arise from variations in egg-laying behavior. The authors then take advantage of the advanced genetic technology available in C. elegans, and the fact that the cellular and molecular mechanisms that drive egg-laying behavior in the N2 laboratory strain of C. elegans have been studied intensely for decades. Thus, they demonstrate that variations in multiple genetic loci appear to drive variations in egg laying across species, although they are unable to identify the specific genes that vary other than a potassium channel already identified in a previous study from some of these same authors (Vigne et al., 2021). Mignerot et al. also present evidence that variations in the response of the egg-laying system to the neuromodulator serotonin appear to underlie variations in egg-laying behavior across species. Finally, the authors present a series of studies examining how the retention of eggs in utero affects the fertility and survival of mothers versus the survival of their progeny in a variety of adverse conditions, including limiting food, and the presence of acute environmental insults such as alcohol or acid. The results suggest that variations in egg-laying behavior evolved as a response to adverse environmental conditions that impose a trade-off between survival of the mothers versus their progeny.

Strengths:

The analysis of variations in egg laying by a large set of wild species significantly extends the previous work of Vigne et al. (2021), who focused on just one wild variant strain. Mignerot finds that variations in egg laying are widespread across C. elegans strains and result from changes in multiple genetic loci.

To determine why various strains vary in their egg-laying behavior, the authors take advantage of the genetic tractability of C. elegans and the huge body of previous studies on the cellular and molecular basis of egg-laying behavior in the laboratory N2 strain. Since serotonin is one signal that induces egg laying, the authors subject various strains to serotonin and to drugs thought to alter serotonin signaling, and they also use CRISPR induced gene editing to mutate a serotonin reuptake transporter in some strains. The results are largely consistent with the idea that variations across strains alter how the egg-laying system responds to serotonin.

The final figures in the paper present a far more detailed analysis than Vigne et al. (2021) of how variations in egg retention across species can affect fitness under various environmental stresses. Thus, Mignerot et al. look at competition under conditions of limiting food, and response to acute environmental insults, and compare the ability of adults, in utero eggs, and ex vivo eggs to survive. The results lead to an interesting discussion of how variations in behavior result in a trade-off in survival of mothers versus their progeny. The authors in their Discussion do a good job describing the challenges in interpreting the relevance of these laboratory results to the poorly-understood environmental conditions that C. elegans may experience in the wild. The Discussion also had an excellent section about how the ability of a single species to strongly regulate egg-laying behavior in response to its environment, and how this ability could be adaptive. Overall, these were the strongest and most interesting aspects of Mignerot et al.

Weaknesses<br /> The specific potassium channel variation studied by Vigne et al. (2021) has by far the strongest effect on egg laying seen in the Mignerot et al. study and remains the only genetic variation that has been molecularly identified. So, Mignerot et al. were not able to identify any additional specific genes that vary across species to cause changes in egg laying, and this limited their ability to generate new insights into the specific cellular and molecular mechanisms that have changed across species to result in changes in egg laying behavior.

The authors' use of drug treatments and CRISPR to alter serotonin signaling yielded some insights into mechanistic variations in how the egg-laying system functions across strains, but these experiments only allow very indirect inferences into what is going on. The analysis in Figures 4 and 5 generates a complex set of results that are not easy to interpret. The clearest result seems to be that strains carrying the KCNL-1 point mutation lay eggs poorly and exogenous serotonin inhibits rather than stimulates egg laying in these strains. This basic result was to a large extent reported previously in Vigne et al. 2021.

The analysis of egg-laying behavior in Figure 3 is relatively weak. Whereas the state of the art in analyzing this behavior is to take videos of animals and track exactly when they lay eggs, the authors used a lower-tech method of just examining how many eggs were laid within 5 minute intervals. It is not clear that this allows adequate resolution to determine if the strains examined actually have clusters of egg-laying events (i.e. active phases) or not, so the entire analysis of active and inactive phase intervals seemed dubious. It was unclear that this analysis demonstrated differences in the patterns of egg-laying behavior between strains that could be sufficient to explain the differences in accumulation of unlaid eggs between these strains. In contrast, the variations in Fig 3G and 3H between strains were very strong. It is not clear why the authors did not focus more on these differences as being possibly largely responsible for the differences in egg retention between strains. In the discussion, the authors extensively write about the work of the Collins lab showing that retained eggs stretch the uterus to produce a signal that activates egg-laying muscles. Could it be that really this mechanism is the main one that varies between strains, leading to the observed variations in time to laying the first egg as well as variations in the number of retained eggs throughout adulthood?

Reviewer #2 (Public Review):

In this manuscript, Scheer and Bargmann investigate how behavioral arousal state affects foraging decisions in the nematode C. elegans. Previous work has shown that when placed on a lawn of bacterial food, C. elegans spontaneously switch between two behavioral states, termed roaming and dwelling, during which they exploit or explore the food environment, respectively. It has also been shown that animals spontaneously leave bacterial lawns depending on factors such as food quality or mate availability.

Here, the authors use quantitative behavioral analyses to describe in unprecedented detail the various behavioral choices animals make when encountering the lawn edge. They report that leaving the lawn is a rare outcome compared to other choices such as pausing or reversing back into the lawn. It occurs predominantly out of the roaming state and has a characteristic preceding fast crawling profile. They developed a refined analysis method, the result of which suggests that the arousal state of animals on food can be described by a 4-state behavior (as opposed to the 2-state roaming - dwelling classification); leaving the lawn occurs predominantly from "state 3", which corresponds to the highest level of arousal during roaming. They further show that various manipulations, such as optogenetic inhibition of feeding, stimulation of RIB neurons, or mutations of neuromodulator pathways, all of which have previously been reported to affect crawling speed and/or roaming/dwelling, maintain the coupling between roaming states and leaving, suggesting a dedicated mechanism for coupling leaving to the roaming state. Finally, they use genetics to implicate chemosensory neurons as neuronal circuit elements mediating this coupling.

How arousal states affect decision making is an active area of neuroscience research; therefore, the current manuscript will impact the field beyond the small community of C. elegans researchers. Also, in the past, roaming/dwelling and leaving have been treated as independent behaviors; the current manuscript is very intriguing, demonstrating both the interconnectedness of different behavioral programs and the importance of the animal's behavioral context for specific decisions.

Reviewer #2 (Public Review):

The manuscript examined the behavioural and neural profile of weak and strong fear memories. The data provide strong evidence that weak but not strong fear memories are subject to extinction and reconsolidation disruption. Strong memories also show greater generalization. These differences were echoed in differential neural connectivity with weak fear memories showing greater connectivity between brains areas than strong fear memories.

Strengths:

The findings are of great importance and offer insight into why resistance to extinction and reconsolidation may underlie fear-related psychopathology.<br /> The study uses key behavioural tests to study the durability of weak vs strong memories (extinction and reconsolidation) as well as studies the generalisation of those memories. These behavioural effects nicely dovetail with the neural connectivity analyses that were performed.

The data presented in this paper will be the basis for future hypothesis driven examinations on the causal influence of specific pathways involved in contextual fear.<br /> Excellent use of the open field to control for motor effects.

Weaknesses:

One alternative account to the weak vs. strong memory distinction made in the paper is the opportunity for extinction in the 2S compared to the 10S group. In the 2S group, the last shock occurs in the 3rd minute, leaving 9 minutes of context exposure without reinforcement to follow. This is not the case for the 10S group. If context fear extinction is engaged during this time, then this would mean that two memories (acquisition and extinction) are taking place in the 2S group, weakening the fear memory in this group, setting up the ground for stronger effects of extinction, less generalization and of course potential greater connectivity required for representing and linking these memories. Indeed, the IL, a brain area linked to extinction, is more predominant in the connectivity map of the 2S compared to the 10S group. While testing this alternative is beyond the scope of this paper, it will need to be discussed.<br /> Methodological detail is lacking re the timeline of study, and connectivity analyses.

Reviewer #2 (Public Review):

Mitochondria are essential cellular organelles that generate ATPs as the energy source for maintaining regular cellular functions. However, the degradation of sperm-borne mitochondria after fertilization is a conserved event known as mitophagy to ensure the exclusively maternal inheritance of the mitochondrial DNA genome. Defects on post-fertilization sperm mitophagy will lead to fatal consequences in patients. Therefore, understanding the cellular and molecular regulation of the post-fertilization sperm mitophagy process is critically important. In this study, Zuidema et. al applied mass spectrometry in conjunction with a porcine cell-free system to identify potential autophagic cofactors involved in post-fertilization sperm mitophagy. They identified a list of 185 proteins that might be candidates for mitophagy determinants (or their co-factors). Despite the fact that 6 (out of 185) proteins were further studied, based on their known functions, using a porcine cell-free system in conjunction with immunocytochemistry and Western blotting, to characterize the localization and modification changes these proteins, no further functional validation experiments were performed. Nevertheless, the data presented in the current study is of great interest and could be important for future studies in this field.

Reviewer #2 (Public Review):

Whether and how molecularly defined neuronal groups in the spinal cord process distinct modalities are of great interest. In this study, Boyle et al. characterized roles of inhibitory neurons expressing NPY in adult mice. By using chemogenetic, electrophysiological tools and behavioral measurements, the authors discovered that activating NPY+ interneurons strongly reduced pruritogen-evoked itch and reflexive behaviors (acute nociception or under inflammation / neuropathic pain states). Silencing NPY+ spinal interneurons enhanced spontaneous and chemical itch in a GRPR+ neurons dependent manner. The authors concluded that, unlike previous findings suggesting that these neurons are selective for mechanical itch, adult NPY+ interneurons play dual roles in gating various types of itch and pain.

The authors performed careful characterization and comparisons between development lineage and adult spinal neurons expressing NPY. This lays the foundation of the current study. The behavioral measurements were also well designed with proper controls.

Reviewer #2 (Public Review):

The manuscript describes more fully the relationship between zinc fluxes and calcium oscillations during egg activation by directly manipulating the level of zinc ions inside and outside the cell with chelators and ionophores and then measuring resulting changes in Ca++ oscillations. The authors have provided solid evidence consistent with their hypothesis that zinc ions regulate Ca++ oscillations by directly modulating the gating of the IP3-R which is the main calcium channel responsible for calcium release into the cytoplasm. The authors employ well established methods of calcium measurement along with various chelators, ionophores and a wide variety of methods that cause egg activation to demonstrate that an optimal level of zinc ions are required for Ca++ oscillations to occur.

Helpfully, the authors provide a model to explain their observations in Figure 7. In the model, the increase in zinc during maturation is permissive for later IP3-R gating in response to IP3 generated at fertilization. The experiments with TPEN solidly demonstrate that Zn is required because lowering free zinc, as indicated by Fluozin staining), abrogates Ca++ oscillations. This is true regardless of the method of activation. What is not clearly described in the model or in the manuscript is whether the levels of zinc at MII are simply permissive for IP3-R gating or whether there is a more acute relationship between zinc fluxes and Ca++ oscillations. In the original paper describing the zinc spark (Kim et al., ACS Chem Biol 6:716-723), the authors show that zinc efflux very closely mirrors Ca++ oscillations suggesting a more active relationship such that zinc efflux associate with each calcium spike could be necessary for terminating the Ca spike by depleting cytoplasmic Zn. There is some evidence in the present manuscript to support this. For example, in figure 3B, TPEN appears to acutely terminate a Ca spike. Whether this is repeatable is not known. Conversely, in Figure 5C and 5E, PyT leads to a rapid restoration of Ca oscillations within minutes demonstrating that changes in free Zn can cause rapid changes in Ca++ oscillations. Perhaps, rather than simply a permissive role, the normal Zn fluxes during activation may be acutely changing IP3-R gating sensitivity.

The role of TRPv3 and Trpm7 in Zn homeostasis during egg activation seems to be minor and the results in the dKO oocytes compared to TPEN are a bit confusing. In the dKO oocytes, zinc acquisition was sufficient to make it to MII suggesting Zn transport through these channels is dispensable for maturation. During activation, however, the response to Tg in dKO eggs was opposite that of TPEN, higher cytosolic Ca and increase amplitude (Figure 4G) vs lower cytoplasmic Ca and frequency for TPEN (Figure 4A). Perhaps loss of these two channels changes Ca gating independent of Zinc.

The effect of PyT on the apparent rise in cytoplasmic Ca++ in figure 6 is interpreted as caused by an artifact of high Zn concentrations. However, it is not clear that 0.05 uM PyT would necessarily increase cytoplasmic Zn to the point where FURA-2 fluorescence would increase. A simpler interpretation is that PyT allows sufficient Zn to enter the cell and keeps the IP3-R channels open causing a sustained rise in cytoplasmic Ca and preventing oscillations in Ca++. This interpretation would also preclude inhibitory effects of high Zn concentrations as shown in figure 7 which may or may not be present but are simply speculation.

Overall, this study significantly advances our understanding of egg activation and could lead to better ways of in vitro egg activation in women undergoing assisted reproduction.

Reviewer #2 (Public Review):

The axon initial segment (AIS) is the axonal domain where most neurons integrate inputs and generate action potentials. Though structural and electrophysiological studies have allowed to better understand the mechanisms of assembly and maintenance of this domain, as well as its functions, there is still a need for efficient tools to study its structural organization and plasticity in vivo.

In this article, the authors describe the generation of a knock-in mouse reporter line allowing the conditional expression of a GFP-tagged version of AnkyrinG (Ank-G), which is a major protein of the axon initial segment and the nodes of Ranvier in neurons. This reporter line can in particular be used to study axon initial segment assembly and plasticity, by combining it with mouse lines or viruses expressing the Cre recombinase under the control of a neuronal promoter. Furthermore, the design of the line should allow to preserve the expression of the main Ank-G isoforms observed in neurons and could thus allow to study Ank-G related mechanisms in various neuronal subcompartments.

Some mouse lines allowing the neuronal expression of AIS/node of Ranvier markers coupled to a fluorescent protein exist, however they correspond to transgenic lines leading to potential overexpression of the tagged protein. Depending on the promoter used, their expression can vary and be absent in some neuronal populations (in particular, the Thy-1 promoter can lead to variable expression depending on the transgene insertion locus). Furthermore, these lines do not allow conditional expression of the protein regarding neuronal subtypes nor controlled temporal expression. Finally, a thorough description of the in vivo expression of the tagged protein at the AIS, and its impact on the structural and electrophysiological properties of the AIS are missing for these lines.

The present reporter line is thus definitely of interest, as the authors convincingly show that it can be used to visualize AIS ans Nodes of Ranvier in various contexts (from in vitro to in vivo). It could in particular be useful to study the assembly and plasticity of the domains where Ank-G is expressed. In this work, the authors thoroughly characterize the Ank-G-GFP reporter line generated and show that the structural and electrophysiological properties of the labeled neurons are not altered by the expression of the tagged Ank-G.

Reviewer #2 (Public Review):

In the manuscript entitled "Linking the evolution of two prefrontal brain regions to social and foraging challenges in primates" the authors measure the volume of the frontal pole (FP, related to metacognition) and the dorsolateral prefrontal cortex (DLPFC, related to working memory) in 16 primate species to evaluate the influence of socio-ecological factors on the size of these cortical regions. The authors select 11 socio-ecological variables and use a phylogenetic generalized least squares (PGLS) approach to evaluate the joint influence of these socio-ecological variables on the neuro-anatomical variability of FP and DLPFC across the 16 selected primate species; in this way, the authors take into account the phylogenetic relations across primate species in their attempt to discover the influence of socio-ecological variables on FP and DLPF evolution.

The authors run their studies on brains collected from 1920 to 1970 and preserved in formalin solution. Also, they obtained data from the Mussée National d´Histoire Naturelle in Paris and from the Allen Brain Institute in California. The main findings consist in showing that the volume of the FP, the DLPFC, and the Rest of the Brain (ROB) across the 16 selected primate species is related to three socio-ecological variables: body mass, daily traveled distance, and population density. The authors conclude that metacognition and working memory are critical for foraging in primates and that FP volume is more sensitive to social constraints than DLPFC volume.

The topic addressed in the present manuscript is relevant for understanding human brain evolution from the point of view of primate research, which, unfortunately, is a shrinking field in neuroscience. But the experimental design has two major weak points: the absence of lissencephalic primates among the selected species and the delimitation of FP and DLPFC. Also, a general theoretical and experimental frame linking evolution (phylogeny) and development (ontogeny) is lacking.

Major comments.<br /> 1.- Is the brain modular? Is there modularity in brain evolution?: The entire manuscript is organized around the idea that the brain is a mosaic of units that have separate evolutionary trajectories:

"In terms of evolution, the functional heterogeneity of distinct brain regions is captured by the notion of 'mosaic brain', where distinct brain regions could show a specific relation with various socio-ecological challenges, and therefore have relatively separate evolutionary trajectories".

This hypothesis is problematic for several reasons. One of them is that each evolutionary module of the brain mosaic should originate in embryological development from a defined progenitor (or progenitors) domain [see García-Calero and Puelles (2020)]. Also, each evolutionary module should comprise connections with other modules; in the present case, FP and DLPFC have not evolved alone but in concert with, at least, their corresponding thalamic nuclei and striatal sector. Did those nuclei and sectors also expand across the selected primate species? Can the authors relate FP and DLPFC expansion to a shared progenitor domain across the analyzed species? This would be key to proposing homology hypotheses for FP and DLPFC across the selected species. The authors use all the time the comparative approach but never explicitly their criteria for defining homology of the cerebral cortex sectors analyzed.

Contemporary developmental biology has showed that the selection of morphological brain features happens within severe developmental constrains. Thus, the authors need a hypothesis linking the evolutionary expansion of FP and DLPFC during development. Otherwise, the claims form the mosaic brain and modularity lack fundamental support.

Also, the authors refer most of the time to brain regions, which is confusing because they are analyzing cerebral cortex regions.

2.- Definition and delimitation of FP and DLPFC: The precedent questions are also related to the definition and parcellation of FP and DLPFC. How homologous cortical sectors are defined across primate species? And then, how are those sectors parcellated?

The authors delimited the FP:

"...according to different criteria: it should match the functional anatomy for known species (macaques and humans, essentially) and be reliable enough to be applied to other species using macroscopic neuroanatomical landmarks".

There is an implicit homology criterion here: two cortical regions in two primate species are homologs if these regions have similar functional anatomy based on cortico-cortical connections. Also, macroscopic neuroanatomical landmarks serve to limit the homologs across species.

This is highly problematic. First, because similar function means analogy and not necessarily homology [for further explanation see Puelles et al. (2019); García-Cabezas et al. (2022)]. Second, because there are several lissencephalic primate species; in these primates, like marmosets and squirrel monkeys, the whole approach of the authors could not have been implemented. Should we suppose that lissencephalic primates lack FP or DLPFC? Do these primates have significantly more simplistic ways of life than gyrencephalic primates? Marmosets and squirrel monkeys have quite small brains; does it imply that they have not experience the influence of socio-ecological factors on the size of FP, DLPFC, and the rest of the brain?

The authors state that:

"the strong development of executive functions in species with larger prefrontal cortices is related to an absolute increase in number of neurons, rather than in an increase in the ration between the number of neurons in the PFC vs the rest of the brain".

How does it apply to marmosets and squirrel monkeys?

References:<br /> García-Cabezas MA, Hacker JL, Zikopoulos B (2022) Homology of neocortical areas in rats and primates based on cortical type analysis: an update of the Hypothesis on the Dual Origin of the Neocortex. Brain structure & function Online ahead of print. doi:doi.org/10.1007/s00429-022-02548-0

García-Calero E, Puelles L (2020) Histogenetic radial models as aids to understanding complex brain structures: The amygdalar radial model as a recent example. Front Neuroanat 14:590011. doi:10.3389/fnana.2020.590011

Nieuwenhuys R, Puelles L (2016) Towards a New Neuromorphology. doi:10.1007/978-3-319-25693-1

Puelles L, Alonso A, Garcia-Calero E, Martinez-de-la-Torre M (2019) Concentric ring topology of mammalian cortical sectors and relevance for patterning studies. J Comp Neurol 527 (10):1731-1752. doi:10.1002/cne.24650

Reviewer #2 (Public Review):

Schnell et al. performed two extensive behavioral experiments concerning the processing of objects in rats and humans. To this aim, they designed a set of objects parametrically varying along alignment and concavity and then they used activations from a pretrained deep convolutional neural network to select stimuli that would require one of two different discrimination strategies, i.e. relying on either low- or high-level processing exclusively. The results show that rodents rely more on low-level processing than humans.

Strengths:

1. The results are challenging and call for a different interpretation of previous evidence. Indeed, this work shows that common assumptions about task complexity and visual processing are probably biased by our personal intuitions and are not equivalent in rodents, which instead tend to rely more on low-level properties.<br /> 2. This is an innovative (and assumption-free) approach that will prove useful to many visual neuroscientists. Personally, I second the authors' excitement about the proposed approach, and its potential to overcome the limits of experimenters' creativity and intuitions. In general, the claims seem well supported and the effects sufficiently clear.<br /> 3. This work provides an insightful link between rodent and human literature on object processing. Given the increasing number of studies on visual perception involving rodents, these kinds of comparisons are becoming crucial.<br /> 4. The paper raises several novel questions that will prompt more research in this direction.

Weaknesses:

1. There are a few inconsistencies in the number of subjects reported. Sometimes 45 humans are mentioned and sometimes 50. Probably they are just typos, but it's unclear.<br /> 2. A few aspects mentioned in the introduction and results are only defined in the Methods thus making the manuscript a bit hard to follow (e.g. the alignment dimension), htus I had to jump often from the main text to the methods to get a sense of their meaning.<br /> 3. The choices related to the stimulus design and the network used to categorize them are not fully described and would benefit from some further clarification/justification. The choice of alignment and concavity as baseline properties of the stimuli is not properly discussed. Also, from the low-correlations I got the feeling that AlexNet is just not a good model of rat visual processing. Which indeed can be interpreted as further evidence of what the authors are trying to demonstrate, but it might also be an isolated case.<br /> 4. Many important aspects of the task are not fully described in the Methods (e.g. size of the stimuli, reaction times and basic statistics on the responses).

Reviewer #2 (Public Review):

The manuscript by Zhu et al explored molecular mechanisms by which Ebola virus (EBOV) evades host innate immune response. EBOV has a number of means to shut down the type I interferon induction (by viral VP35 protein) and block type I interferon action (by viral VP24 protein). This study reported a new mechanism that inclusion body (IB) used for viral replication sequesters IRF3, a key transcription factor involved in the interferon signaling, resulting in blockade of downstream type I interferon gene transcription. This finding is potentially interesting and may provide a new insight into EBOV's evasion of innate immunity. However, there are some flaws in the experimentations and analyses that need to be addressed.

1) Most of experiments were performed by transfection of trVLP plasmids, which is very different from virus infection. The conclusions should be examined and verified in the context of virus infection.

2) Fig 1 - VP35 displayed a classical IB staining only in Panel A, while much less so in Panel C and not in panel B. It seemed that the VP35 staining images were chosen in a way towards the authors' favor. The statistical analysis of co-localization of VP35 and IRF3, TBK1 or IKKe should be performed to draw the conclusion. Another concern is that IKKe is normally lowly expressed under a rest condition and becomes induced only when the interferon signaling is activated. It seemed to be expressed at a high level even when the interferon signaling is blocked in Panel C. The authors should comment on this discrepancy.

3) Fig 2 - Was this experiment done by transfection or infection? The description of result is not consistent with the figure legend. The labeling was also not consistent between panel A and B. I would suggest performing Western blot to analyze the expression level of IRF3.

4) Fig 3 and 4 - As VP35 is well known for its highly efficient blockade of type I interferon activation, how would the authors differentiate the effect of VP35 alone from the sequestration of IRF3 in IBs in these experiments?

5) Fig 3 - PolyIC can activate both RLR and TLR signaling pathways. Can the author comment on which pathway it activates in this experiment?

6) The authors demonstrated that VP35 interacts with STING and recruit the latter to IBs. How would this affect the function of STING given that STING plays essential roles in cGAS/cGAMP pathway?

7) It is difficult to follow the logics of Fig 7. The expression level of each viral protein should be determined. Ideally, a mutation in VP35 that disrupts its ability to antagonize the interferon signaling but still allows for the IB formation can be used to assess the relative contribution of IB sequestering IRF3.

Reviewer #2 (Public Review):

The authors aimed to connect SIRT-1 to EV-D68 virus release through mediating ER stress. They are successful in robustly connecting these pathways experimentally and show a new role for SIRT-1 in EV-D68 infection. These results extend to additional viruses, suggesting role(s) for SIRT-1 in diverse virus infection.

The authors note that EV-D68 does not significantly impact SIRT-1 protein levels (Fig 1E and F), though this has been described for other picornaviruses (Xander et al., J Immunol 2019; Han et al., J Cell Sci 2016; Kanda et al Biochem Biophys Res Commun 2015). This may be of interest to note in the manuscript.

The data regarding CVB3 (Fig S4) are especially interesting because they show no discernable impact on infection. The manuscript should describe this further and perhaps speculate on potential reasons. Could it be due to inefficient knockdown?

SIRT-1 (and other sirtuins) have been linked to an innate interferon response. Are any of the phenotypes observed here due to IFN responses? The use of H1HeLa cells would suggest this is not the case.

Reviewer #2 (Public Review):

The data presented support and extend some previously published data using Drosophila as a model to unravel the cellular and genetic basis of human Autosomal dominant optic atrophy (DOA). In human, mutations in OPA1, a mitochondrial dynamin like GTPase (amongst others), are the most common cause for DOA. By using a Drosophila loss-of-function mutations, RNAi-mediated knockdown and overexpression, the authors could recapitulate some aspects of the disease phenotype, which could be rescued by the wild-type version of the human gene. Their assays allowed them to distinguish between mutations causing human DOA, affecting the optic system and supposed to be loss-of-function mutations, and those mutations supposed to act as dominant negative, resulting in DOA plus, in which other tissues/organs are affected as well.

Based on the lack of information in the Materials and Methods section and in several figure legends, it was not in all cases possible to follow the conclusions of the authors. Similarly, how the knowledge gained could help to "inform early treatment decisions in patients with mutations in hOPA1" (Line 38) cannot be followed.

Reviewer #2 (Public Review):

The authors investigate the origin of asexual reproduction through hybridization between species. In loaches, diploid, polyploid, and asexual forms have been described in natural populations. The authors experimentally cross multiple species of loaches and conduct an impressively detailed characterization of gametogenesis using molecular cytogenetics to show that although meiosis arrests early in male hybrids, a subset of cells in females undergo endoreplication before meiosis, producing diploid eggs. This only occurred in hybrids of parental species that were of intermediate divergence. This work supports an expanding view of speciation where asexuality could emerge during a narrow evolutionary window where genomic divergence between species is not too high to cause hybrid inviability, but high enough to disrupt normal meiotic processes.

I enjoyed reading this study and I appreciate the amount of work it takes to conduct these types of cytogenetic experiments. But, my main concern with this study is I was left wondering if the sample sizes are large enough to get a sense how variable endoreplication is in these loach species. Most of the hybrids between species are the result of crosses between 1-2 families. Within males and females, meiocyte observations are limited to a handful of pachytene and diplotene stages. I think it would be helpful to be more transparent about the sample sizes in the main text.

Along these lines, the authors argue against the possibility that endoreplication may be predisposed to occur at a higher rate in some species (line 291). Instead, they suggest that endoreplication is a result of perturbing the cell cycle by combining the genomes of two different species. Their main argument is based on gonocyte counts from parental females in a previous reference. It is essential to include counts from the parents used in this study to make a clear comparison with the F1s.

In the discussion (lines 320-333), the authors postulate the sex-specific clonality they observe could be a result of Haldane's rule. Given these fish do not have known sex chromosomes, I do not find this argument strong. Haldane's rule refers to the exposure of recessive incompatibilities with the sex chromosomes in the hybrid heterogametic sex. This effect would therefore be limited to degenerated sex chromosomes where much of the sequence content on the Y or W has been lost. These species may have homomorphic sex chromosomes, but if this is the case, they likely are not very degenerated. Instead, it seems more plausible that the sex-specific effect the authors observe is due to intrinsic differences of spermatogenesis and oogenesis. Is there any information about sex-specific differences in the fidelity of gametogenesis from other species that would support a higher likelihood of endoreplication?

The final thing I was left wondering about was this missing link between endoreplication and activating embryonic development of the diploid egg. In these loach species, a sperm is required to activate egg development, but the sperm genome is discarded (line 100). What is the mechanism of this and how does it evolve concurrently during hybridization?

Reviewer #2 (Public Review):

This preprint presents a compelling study examining the relationship between genotypic changes and phenotypic traits in bacteria over an extended period using the Long-Term Evolution Experiment (LTEE) as a model. The primary advances in methodology include employing high-resolution mass spectrometry for comprehensive metabolic profiling and combining it with previous gene expression and DNA sequencing datasets. This approach provides insight into how specific genetic mutations can alter metabolic pathways over 50,000 generations, enabling a deeper understanding of how genetic changes lead to observed differences in evolved bacterial strains. The findings reveal that evolved bacteria possess more diverse metabolic profiles compared to their ancestors, suggesting that these populations have uniquely adapted to their environment. The work also attempts to uncover the molecular basis for this adaptive evolution, demonstrating how specific genetic changes have influenced the bacteria's metabolic pathways.

Overall, this is a significant and well-executed research study. It offers new insights into the complex relationship between genetic changes and observable traits in evolving populations and utilizes metabolomics in the LTEE, a novel approach in combination with RNA-seq and mutation datasets.

Reviewer #2 (Public Review):

In this study, the authors used ANM-LD and GNM-based Transfer Entropy to investigate the allosteric communications network of CFTR. The modeling results are validated with experimental observations. Key residues were identified as pivotal allosteric sources and transducers and may account for disease mutations.

The paper is well written and the results are significant for understanding CFTR biology.

Reviewer #2 (Public Review):

Using fNIRS and resting state recordings of brain activity, authors have compared functional network organization in infants with congenital sensorineural hearing loss (SNHL) as well as typically developing infants. The manuscript reports a disruption in the development of leftward hemispheric lateralization in SNHL infants as compared to typically developing infants, across several network measures. The study used an adapted methodology for infants, and involved an adequate number of infants for cross-sectional studies and the findings are valuable. However, a number of methodological points and controls need to be taken into account to better explain the results and to remove redundancy. Moreover, the discussion can be improved by a more detailed comparison between the current work and the past literature.

- My major concern is that functional connectivity patterns change importantly depending on the sleep stage (Uchitel et al., 2021 Pediatric Research; Tóth et al., 2017 Human Brain mapping), it is therefore not enough to have all infants sleep, but to have them on the same sleep stage. Therefore, authors need to re-analyze their dataset taking into account sleep stage as a factor, i.e. grouping infants based on the sleep stage (otherwise it can be a confounding factor - as one can imagine that infants with sensorineural hearing loss may enter "quiet sleep" faster in a short recording session - given the environmental noise does not bother them etc.). This could completely change the interpretation of the results. Do authors have a mean in the data or via additional recordings (respiration, EMG, ECG?) to separate the sleep stages?

- Several statistical analyses are performed with redundancy, i.e. several effects are looked at in more than one test: for example one ANOVA analysis with several factors including group (SNHL/typical) as a factor, is followed by two other separate ANOVAs with the same variables as before but redone for each group separately. The latter tests are redundant. This has happened across different sections, making the manuscript unnecessarily long while also reporting effects that are redundant.

- Given the number of statistical comparisons performed, it would be helpful that authors better explain how corrections are performed: number of comparisons for each correction or which tests are considered independent (i.e. across which correction of multiple comparisons are not performed).

- The discussion generally needs to be improved: both for the position of the current study/novelty/strength and its limitations with respect to the previous works (Cui et al 2022- also looking into early functional organization in SNHL, etc) and also in terms of the differences in findings (i.e. associations of functional connectivity measures to hearing loss severity)

Reviewer #2 (Public Review):

The authors examine the transport of chemical compounds from a surrounding fluid environment to the surface of the polyp Hydra. They propose that spontaneous contractions of the body, which are known to occur roughly three times per hour, provide a new fluid environment near the body surface and thereby increase the total rate of compound uptake. Experimental measurements and a mathematical model are used to support the main claim. Active probes of the system involve the use of ion channel inhibitors, which can affect the frequency of contractions. But there is a useful feature of Hydra already present which the authors also use for a comparative study, namely the different microbial environments near the Hydra's motionless foot and near its moving head. The evidence which is provided puts the claim on solid footing. The main result represents an important observation about the role of hydrodynamics on organism behavior, in particular in its relation to diffusive chemical transport processes.

Reviewer #2 (Public Review):

The authors wanted to determine if the mRNA modification m6A is involved in axonal regeneration pathways. They performed a small-scale siRNA screen targeting major components of this pathway to determine if not down if any of these genes would influence axonal regeneration. They identified ALKBH5, an m6A demethylating enzyme, as a gene that represses axonal regeneration after injury, and when knocked down, promotes axonal growth. They identify a putative mRNA target of ALKBH5, Lpin2, which they believe is demethylated by ALKBH5, resulting in higher levels of m6A on this transcript and thus greater mRNA degradation and reduced expression.

This study has major weaknesses. The ALKBH5 knockout mouse is not used. Thus the experiment relies on the selectivity of the siRNA. Many experiments relied on the single siRNA. The knockdown efficiency was relatively poor, with only a small change in ALKBH5 protein levels. The authors never assess whether m6A levels are indeed affected by ALKBH5 depletion using their approach. The results are therefore unconvincing because of not using the appropriate mouse model. Additionally, the authors' attempt to identify a target of ALKBH5 was not done using the appropriate approach, which would involve globally profiling m6A levels in control and ALKBH5 knockout conditions. Since they did not do global profiling of m6A, the authors cannot report how the exact stoichiometry of m6A sites in Lpin2 is affected (and if other mRNAs are affected which might be the true targets of ALKBH5). Attempts by other investigators to identify bona fide targets of ALKBH5 have been difficult, and the authors did not do the appropriate unbiased transcriptome-wide screen but instead used generic gene expression approaches to come to their target. It is not clear if they have a direct or indirect target of ALKBH5 based on the presented data.

Overall, the authors have not achieved their aims and the results do not support the overall conclusions. However, some studies related to Lpin2 overexpression and not down suggest that this gene indeed can influence axonal regeneration in some way. But whether it is a direct target of ALKBH5 and whether ALKBH5 indeed has any role in axonal regeneration is still not clear.

Reviewer #2 (Public Review):

Neutrophils are not known to be the cells responsible for removal of apoptotic cells through efferocytosis. This report provides strong evidence that neutrophils can remove apoptotic hepatocytes in vivo and in vitro. In addition, neutrophils, which are much smaller in size than hepatocytes, can burrow into apoptotic hepatocytes.

Neutrophils are the most abundant circulating leukocytes in human. They play important roles in innate immune responses to infections and tissue injuries. Although they are dept in phagocytosis of microbes, neutrophils are not known to normally conduct efferocytosis or phagocytose host cells including apoptotic cells and play a significant role in apoptotic cell removal. In this report the authors provide evidence to suggest that neutrophils are involved in removal of apoptotic hepatocytes with certain specificity (i.e., they do not remove HEK293 or HUVEC endothelial cells). Moreover, the authors also show that neutrophils can burrow into the target cells and possibly ingest the target cells from the inside. The authors thus term this neutrophil-mediated efferocytosis process as "perforocytosis". Furthermore, evidence is provided to suggest that this neutrophil-mediated efferocytosis process keeps the number of apoptotic cells low in the livers and that defects in the processes may associate with autoimmune liver (AIL) disease phenotypes. Therefore, many of these findings are novel and the study is of important implications in our understanding of the role of neutrophils in autoimmune disease. Overall speaking, as the first report describing this novel finding, the authors have provided reasonably strong evidence for the conclusion that neutrophils burrow into apoptotic hepatocytes to perform "perforocytosis" to eliminate apoptotic hepatocytes. The importance, particularly in vivo significance, of this phenomenon needs to be further substantiated in future studies.

Reviewer #2 (Public Review):

MotorNet aims to provide a unified interface where the trained RNN controller exists within the same TensorFlow environment as the end effectors being controlled. This architecture provides a much simpler interface for the researcher to develop and iterate through computational hypotheses. In addition, the authors have built a set of biomechanically realistic end effectors (e.g., an 2 joint arm model with realistic muscles) within TensorFlow that are fully differentiable.

MotorNet will prove a highly useful starting point for researchers interested in exploring the challenges of controlling movement with realistic muscle and joint dynamics. The architecture features a conveniently modular design and the inclusion of simpler arm models provides an approachable learning curve. Other state-of-the-art simulation engines offer realistic models of muscles and multi-joint arms and afford more complex object manipulation and contact dynamics than MotorNet. However, MotorNet's approach allows for direct optimization of the controller network via gradient descent rather than reinforcement learning, which is a compromise currently required when other simulation engines (as these engines' code cannot be differentiated through).

The paper could be reorganized to provide clearer signposts as to what role each section plays (e.g., that the explanation of the moment arms of different joint models serves to illustrate the complexity of realistic biomechanics, rather than a novel discovery/exposition of this manuscript). Also, if possible, it would be valuable if the authors could provide more insight into whether gradient descent finds qualitatively different solutions to RL or other non gradient-based methods. This would strengthen the argument that a fully differentiable plant is useful beyond improving training time / computational power required (although this is a sufficiently important rationale per se).

Reviewer #2 (Public Review):

Summary

The authors conducted a study where participants were perceiving near-threshold touch at either the thumb or ring finger while lying in the MR scanner. Prior to stimulation, a visual cue indicated to them with 80% probability which finger would be touched next (thumb or ring finger), or did not provide meaningful information on which finger would be touched. Subsequently, participants were asked to indicate which finger was actually touched via button press. By showing that 1. participants were more accurate in responding which finger was touched in the congruent compared to the incongruent and neutral conditions, 2. S1 responses were higher in the incongruent compared to the congruent and neutral conditions, 3. decoding accuracies were higher for the congruent compared to incongruent and neutral conditions, and 4. decoding was also successful in the period after cueing and before stimulation, the authors argue that similar to V1, S1 shows decreased BOLD activation in response to expected versus non-expected stimuli, whereas the finger-specific response is more precise for expected versus non-expected stimuli. The authors also argue that behavioral improvement is associated to a tactile stimulus being predicted in location.

Strengths

The manuscript combines a behavioral threshold task that can be analyzed using psychophysics with BOLD responses in S1, providing a rich paradigm to understand the relationship between S1 responsively and tactile perception. The authors combine GLM with both ROI-based and whole-brain searchlight-based decoding analyses, and therefore offer different analyses methods to obtain a comprehensive picture of the S1 responsively during expected versus non-expected touch. It is also a strength of the paper that two different fingers were investigated, hence addressing the aspect of topography.

Weaknesses

The behavioral paradigm that was chosen is not ideal to address the authors' questions on whether or not behavior improves for expected versus non-expected touch. More precisely, in 80% of the cases when it was indicated that the ring finger would be touched, in fact later the ring finger was touched, whereas in 80% of the cases when it was indicated that the thumb would be touched, in fact later the thumb was touched. In the congruent conditions where later the indicated finger was indeed touched, participants showed on average 70% accuracy. Therefore, they could have reached this accuracy level simply by choosing the indicated finger unless they had a strong sensation that indicated to them to respond otherwise. In order to show that the cueing can improve behavioral performance, one would have to choose a tactile task that is not related to finger identity (which was cued), such as frequency detection or spatial acuity.

The correlation between accuracy and decoding accuracies as shown in Figure 3b does not seem to be correct. The decoding accuracies indicate how well the algorithm can differentiate between D1 versus D4 stimulation in the congruent condition, whereas the behavior indicates the difference between congruent and incongruent responses. I think those two measures should not directly be compared, in addition to the general problem that is inherent in the behavioral paradigm, as outlined above. I would therefore treat this correction and the behavioral analyses in general with great caution.

Alternative ways to interpret the data

It is worth noting that the incongruent stimulation condition did not reveal significant D1 versus D4 decoding results neither when ROI-based decoding was used nor when searchlight-based decoding was used (see Figure 3a,c). Therefore, it seems that when the wrong finger was cued, the finger representation of the actually touched finger did not respond. Given the decoding accuracy is even below 50% for the incongruent ROI-based decoding, this seems to indicate that the finger-specific response in S1 to the cued finger is even stronger than the finger-specific response in S1 to the actually touched finger. This may be the major take-home-message of the paper. This hypothesis could be directly tested by showing the the plot in Figure 2c for each finger: The results may show that the higher activation in the incongruent condition is actually due to the fact that in this condition, both the non-touched and finger the touched finger respond, whereas this is not the case for the other conditions.

When discussing this finding, the authors write that "finger representations of congruent vibrotactile stimulations are associated with higher multivariate information content, are more aligned with the somatotropin organization in contralateral S1, and that the enhanced representation of these stimuli is strongly associated with behavioral detection performance." - A better formulation may be that for threshold tactile stimulation, the expectation of finger touch can override the actual finger touch, indicating a strong influence of top-down control on S1 finger maps. This is also supported by the analyses that there is finger-specific activation in the cue-stimulation interval. However, as indicated above, finger- and condition-specific BOLD activation needs to be shown to explore this in more detail.

Reviewer #2 (Public Review):

Olszyński et al. claim that they identified a "new-type" ultrasonic vocalization around 44 kHz that occurs in response to prolonged fear conditioning (using foot-shocks of relatively high intensity, i.e. 1 mA) in rats. Typically, negative 22-kHz calls and positive 50-kHz calls are distinguished in rats, commonly by using a frequency threshold of 30 or 32 kHz. Olszyński et al. now observed so-called "44-kHz" calls in a substantial number of subjects exposed to 10 tone-shock pairings, yet call emission rate was low (according to Fig. 1G around 15%, according to the result text around 7.5%). They also performed playback experiments and concluded that "the responses to 44-kHz aversive calls presented from the speaker were either similar to 22-kHz vocalizations or in-between responses to 22-kHz and 50-kHz playbacks".

Strengths: Detailed spectrographic analysis of a substantial data set of ultrasonic vocalizations recorded during prolonged fear conditioning, combined with playback experiments.

Weaknesses: I see a number of major weaknesses.

While the descriptive approach applied is useful, the findings have only focused importance and scope, given the low prevalence of "44 kHz" calls and limited attempts made to systematically manipulate factors that lead to their emission. In fact, the data presented appear to be derived from reanalyses of previously conducted studies in most cases and the main claims are only partially supported. While reading the manuscript, I got the impression that the data presented here are linked to two or three previously published studies (Olszyński et al., 2020, 2021, 2023). This is important to emphasize for two reasons: 1) It is often difficult (if not impossible) to link the reported data to the different experiments conducted before (and the individual experimental conditions therein). While reanalyzing previously collected data can lead to important insight, it is important to describe in a clear and transparent manner what data were obtained in what experiment (and more specifically, in what exact experimental condition) to allow appropriate interpretation of the data. For example, it is said that in the "trace fear conditioning experiment" both single- and group-housed rats were included, yet I was not able to tell what data were obtained in single- versus group-housed rats. This may sound like a side aspect, however, in my view this is not a side aspect given the fact that ultrasonic vocalizations are used for communication and communication is affected by the social housing conditions. 2) In at least two of the previously published manuscripts (Olszyński et al., 2021, 2023), emission of ultrasonic vocalizations was analyzed (Figure S1 in Olszyński et al., 2021, and Fig. 1 in Olszyński et al., 2023). This includes detailed spectrographic analyses covering the frequency range between 20 and 100 kHz, i.e. including the frequency range, where the "new-type" ultrasonic vocalization, now named "44 kHz" call, occurs, as reflected in the examples provided in Fig. 1 of Olszyński et al. (2023). In the materials and methods there, it was said: "USV were assigned to one of three categories: 50-kHz (mean peak frequency, MPF >32 kHz), short 22-kHz (MPF of 18-32 kHz, <0.3 s duration), long 22-kHz (MPF of 18-32 kHz, >0.3 s duration)". Does that mean that the "44 kHz" calls were previously included in the count for 50-kHz calls? Or were 44 kHz calls (intentionally?) left out? What does that mean for the interpretation of the previously published data? What does that mean for the current data set? In my view, there is a lack of transparency here.

Moreover, whether the newly identified call type is indeed novel is questionable, as also mentioned by the authors in their discussion section. While they wrote in the introduction that "high-pitch (>32 kHz), long and monotonous ultrasonic vocalizations have not yet been described", they wrote in the discussion that "long (or not that long (Biały et al., 2019)), frequency-stable high-pitch vocalizations have been reported before (e.g. Sales, 1979; Shimoju et al., 2020), notably as caused by intense cholinergic stimulation (Brudzynski and Bihari, 1990) or higher shock-dose fear conditioning (Wöhr et al., 2005)" (and I wish to add that to my knowledge this list provided by the authors is incomplete). Therefore, I believe, the strong claims made in abstract ("we are the first to describe a new-type..."), introduction ("have not yet been described"), and results ("new calls") are not justified.

In general, the manuscript is not well written/ not well organized, the description of the methods is insufficient, and it is often difficult (if not impossible) to link the reported data to the experiments/ experimental conditions described in the materials and methods section. For example, I miss a clear presentation of basic information: 1) How many rats emitted "44 kHz" calls (in total, per experiment, and importantly, also per experimental condition, i.e. single- versus group-housed)? 2) Out of the ones emitting "44 kHz" calls, what was the prevalence of "44 kHz" calls (relative to 22- and 50-kHz calls, e.g. shown as percentage)? 3) How did this ratio differ between experiments and experimental conditions? 4) Was there a link to freezing? Freezing was apparently analyzed before (Olszyński et al., 2021, 2023) and it would be important to see whether there is a correlation between "44-kHz" calls and freezing. Moreover, it would be important to know what behavior the rats are displaying while such "44-kHz" calls are emitted? (Note: Even not all 22-kHz calls are synced to freezing.) All this could help to substantiate the currently highly speculative claims made in the discussion section ("frequency increases with an increase in arousal" and "it could be argued that our prolonged fear conditioning increased the arousal of the rats with no change in the valence of the aversive stimuli"). Such more detailed analyses are also important to rule out the possibility that the "new-type" ultrasonic vocalization, the so-called "44 kHz" call, is simply associated with movement/ thorax compression.

The figures currently included are purely descriptive in most cases - and many of them are just examples of individual rats (e.g. majority of Fig. 1, all of Fig. 2 to my understanding, with the exception of the time course, which in case of D is only a subset of rats ("only rats that emitted 44-kHz calls in at least seven ITI are plotted" - is there any rationale for this criterion?)), or, in fact, just representative spectrograms of calls (all of Fig. 3, with the exception of G, all of Fig. 4). Moreover, the differences between Fig. 5 and Fig. 6 are not clear to me. It seems Fig. 5B is included three times - what is the benefit of including the same figure three times? A systematic comparison of experimental conditions is limited to Fig. 7 and Fig. 8, the figures depicting the playback results (which led to the conclusion that "the responses to 44-kHz aversive calls presented from the speaker were either similar to 22-kHz vocalizations or in-between responses to 22-kHz and 50-kHz playbacks", although it remains unclear to me why differences were seen b e f o r e the experimental manipulation, i.e. the different playback types in Fig. 8B).

Related to that, I miss a clear presentation of relevant methodological aspects: 1) Why were some rats single-housed but not the others? 2) Is the experimental design of the playback study not confounded? It is said that "one group (n = 13) heard 50-kHz appetitive vocalization playback while the other (n = 16) 22-kHz and 44-kHz aversive calls". How can one compare "44 kHz" calls to 22- and 50-kHz calls when "44 kHz" calls are presented together with 22-kHz calls but not 50-kHz calls? What about carry-over effects? Hearing one type of call most likely affects the response to the other type of call. It appears likely that rats are a bit more anxious after hearing aversive 22-kHz calls, for example. Therefore, it would not be very surprising to see that the response to "44 kHz" calls is more similar to 22-kHz calls than 50-kHz calls. Of note, in case of the other playback experiment it is just said that rats "received appetitive and aversive ultrasonic vocalization playback" but it remains unclear whether "44 kHz" calls are seen as appetitive or aversive. Later it says that "rats were presented with two 10-s-long playback sets of either 22-kHz or 44-kHz calls, followed by one 50-kHz modulated call 10-s set and another two playback sets of either 44-kHz or 22-kHz calls not previously heard" (and wonder what data set was included in the figures and how - pooled?). Again, I am worried about carry-over effects here. This does not seem to be an experimental design that allows to compare the response to the three main call types in an unbiased manner. Of note, what exactly is meant by "control rats" in the context of fear conditioning is also not clear to me. One can think of many different controls in a fear conditioning experiment. More concrete information is needed.

Reviewer #2 (Public Review):

Oemisch and Seo set out to examine the effects of low-dose ketamine on reinforcement learning, with the idea that alterations in reinforcement learning and/or motivation might inform our understanding of what alterations co-occur with potential antidepressant effects. Macaques performed a reinforced/punished matching pennies task while under effects of saline or ketamine administration and the data were fit to a series of reinforcement learning models to determine which model described behavior under saline most closely and then what parameters of this best-fitting model were altered by ketamine. They found a mixed effect, with two out of three macaques primarily exhibiting an effect of ketamine on processing of losses and one out of three macaques exhibiting an effect of ketamine on processing of losses and perseveration. They found that these effects of ketamine appeared to be dissociable from the nystagmus effects of the ketamine.<br /> The findings are novel and the data suggesting that ketamine is primarily having its effects on processing of losses (under the procedures used) are solid. However, it is unclear whether the connection between processing of losses and the antidepressant effects of ketamine is justified and the current findings may be more useful for those studying reinforcement learning than those studying depression and antidepressant effects. In addition, the co-occurrence of different behavioral procedures with different patterns of ketamine effects, with one macaque tested with different parameters than the other two exhibiting effects of ketamine that were best fit with a different model than the other two macaques, suggests that there may be difficulty in generalizing these findings to reinforcement learning more generally.

1) First, the authors should be more explicit and careful in the connection they are trying to make about the link between loss processing and depression. The authors call their effect a "robust antidepressant-like behavioral effect" but there are no references to support this or discussion of how the altered loss processing would relate directly to the antidepressant effects.<br /> 2) It appears that the monkey P was given smaller rewards and punishers than the other two monkeys and this monkey had an effect of ketamine on perseveration that was not observed in the other two monkeys. Is this believed to be due to the different task, or was this animal given a different task because of some behavioral differences that preceded the experiment? The authors should also discuss what these differences may mean for the generality of their findings. For example, might there be some set of parameters where ketamine would only alter perseveration and not processing of losses?<br /> 3) The authors should discuss whether the plasma ketamine levels they observed are similar to those seen with rapid antidepressant ketamine or are higher or lower.<br /> 4) For Figure 4 or S3, the authors should show the data fitted to model 7, which was the best for one of the animals.

Reviewer #2 (Public Review):

Theta-nested gamma oscillations (TNGO) play an important role in hippocampal memory and cognitive processes and are disrupted in pathology. Deep brain stimulation has been shown to affect memory encoding. To investigate the effect of pulsed CA1 neurostimulation on hippocampal TNGO the authors coupled a physiologically realistic model of the hippocampus comprising EC, DG, CA1, and CA3 subfields with an abstract theta oscillator model of the medial septum (MS). Pathology was modeled as weakened theta input from the MS to EC simulating MS neurodegeneration known to occur in Alzheimer's disease. The authors show that if the input from the MS to EC is strong (the healthy state) the model autonomously generates TNGO in all hippocampal subfields while a single neurostimulation pulse has the effect of resetting the TNGO phase. When the MS input strength is weaker the network is quiescent but the authors find that a single CA1 neurostimulation pulse can switch it into the persistent TNGO state, provided the neurostimulation pulse is applied at the peak of the EC theta. If the MS theta oscillator model is supplemented by an additional phase-reset mechanism a single CA1 neurostimulation pulse applied at the trough of EC theta also produces the same effect. If the MS input to EC is weaker still, only a short burst of TNGO is generated by a single neurostimulation pulse. The authors investigate the physiological origin of this burst and find it results from an interplay of CAN and M currents in the CA1 excitatory cells. In this case, the authors find that TNGO can only be rescued by a theta frequency train of CA1 pulses applied at the peak of the EC theta or again at either the peak or trough if the MS oscillator model is supplemented by the phase-reset mechanism.

The main strength of this model is its use of a fairly physiologically detailed model of the hippocampus. The cells are single-compartment models but do include multiple ion channels and are spatially arranged in accordance with the hippocampal structure. This allows the understanding of how ion channels (possibly modifiable by pharmacological agents) interact with system-level oscillations and neurostimulation. The model also includes all the main hippocampal subfields. The other strength is its attention to an important topic, which may be relevant for dementia treatment or prevention, which few modeling studies have addressed.

The work has several weaknesses. First, while investigations of hippocampal neurostimulation are important there are few experimental studies from which one could judge the validity of the model findings. All its findings are therefore predictions. It would be much more convincing to first show the model is able to reproduce some measured empirical neurostimulation effect before proceeding to make predictions. Second, the model is very specific. Or if its behavior is to be considered general it has not been explained why. For example, the model shows bistability between quiescence and TNGO, however what aspect of the model underlies this, be it some particular network structure or particular ion channel, for example, is not addressed. Similarly for the various phase reset behaviors that are found. We may wonder whether a different hippocampal model of TNGO, of which there are many published (for example [1-6]) would show the same effect under neurostimulation. This seems very unlikely and indeed the quiescent state itself shown by this model seems quite artificial. Some indication that particular ion channels, CAN and M are relevant is briefly provided and the work would be much improved by examining this aspect in more detail. In summary, the work would benefit from an intuitive analysis of the basic model ingredients underlying its neurostimulation response properties. Third, while the model is fairly realistic, considerable important factors are not included and in fact, there are much more detailed hippocampal models out there (for example [5,6]). In particular, it includes only excitatory cells and a single type of inhibitory cell. This is particularly important since there are many models and experimental studies where specific cell types, for example, OLM and VIP cells, are strongly implicated in TNGO. Other missing ingredients one may think might have a strong impact on model response to neurostimulation (in particular stimulation trains) include the well-known short-term plasticity between different hippocampal cell types and active dendritic properties. Fourth the MS model seems somewhat unsupported. It is modeled as a set of coupled oscillators that synchronize. However, there is also a phase reset mechanism included. This mechanism is important because it underlies several of the phase reset behaviors shown by the full model. However, it is not derived from experimental phase response curves of septal neurons of which there is no direct measurement. The work would benefit from the use of a more biologically validated MS model.

[1] Hyafil A, Giraud AL, Fontolan L, Gutkin B. Neural cross-frequency coupling: connecting architectures, mechanisms, and functions. Trends in neurosciences. 2015 Nov 1;38(11):725-40.

[2] Tort AB, Rotstein HG, Dugladze T, Gloveli T, Kopell NJ. On the formation of gamma-coherent cell assemblies by oriens lacunosum-moleculare interneurons in the hippocampus. Proceedings of the National Academy of Sciences. 2007 Aug 14;104(33):13490-5.

[3] Neymotin SA, Lazarewicz MT, Sherif M, Contreras D, Finkel LH, Lytton WW. Ketamine disrupts theta modulation of gamma in a computer model of hippocampus. Journal of Neuroscience. 2011 Aug 10;31(32):11733-43.

[4] Ponzi A, Dura-Bernal S, Migliore M. Theta-gamma phase-amplitude coupling in a hippocampal CA1 microcircuit. PLOS Computational Biology. 2023 Mar 23;19(3):e1010942.

[5] Bezaire MJ, Raikov I, Burk K, Vyas D, Soltesz I. Interneuronal mechanisms of hippocampal theta oscillations in a full-scale model of the rodent CA1 circuit. Elife. 2016 Dec 23;5:e18566.

[6] Chatzikalymniou AP, Gumus M, Skinner FK. Linking minimal and detailed models of CA1 microcircuits reveals how theta rhythms emerge and their frequencies controlled. Hippocampus. 2021 Sep;31(9):982-1002.

Reviewer #2 (Public Review):

In this study, the researchers employed a recently developed smartphone application to provide 30 days of training on action sequences to both OCD patients and healthy volunteers. The study tested learning and automaticity-related measures and investigated the effects of several factors on these measures. Upon training completion, the researchers conducted two preference tests comparing a learned and unlearned action sequences under different conditions. While the study provides some interesting findings, I have a few substantial concerns:

1. Throughout the entire paper, the authors' interpretations and claims revolve around the domain of habits and goal-directed behavior, despite the methods and evidence clearly focusing on motor sequence learning/procedural learning/skill learning. There is no evidence to support this framing and interpretation and thus I find them overreaching and hyperbolic, and I think they should be avoided. Although skills and habits share many characteristics, they are meaningfully distinguishable and should not be conflated or mixed up. Furthermore, if anything, the evidence in this study suggests that participants attained procedural learning, but these actions did not become habitual, as they remained deliberate actions that were not chosen to be performed when they were not in line with participants' current goals.<br /> 2. Some methodological aspects need more detail and clarification.<br /> 3. There are concerns regarding some of the analyses, which require addressing.

Please see details below, ordered by the paper sections.

Introduction:<br /> It is stated that "extensive training of sequential actions would more rapidly engage the 'habit system' as compared to single-action instrumental learning". In an attempt to describe the rationale for this statement the authors describe the concept of action chunking, its benefits and relevance to habits but there is no explanation for why sequential actions would engage the habit system more rapidly than a single-action. Clarifying this would be helpful.

In the Hypothesis section the authors state: "we expected that OCD patients... show enhanced habit attainment through a greater preference for performing familiar app sequences when given the choice to select any other, easier sequence." I find it particularly difficult to interpret preference for familiar sequences as enhanced habit attainment.

A few notes on the task description and other task components:<br /> It would be useful to give more details on the task. This includes more details on the time/condition of the gradual removal of visual and auditory stimuli and also on the within practice dynamic structure (i.e., different levels appear in the video).

Some more information on engagement-related exclusion criteria would be useful (what happened if participants did not use the app for more than one day, how many times were allowed to skip a day etc.).

According to the (very useful) video demonstrating the task and the paper describing the task in detail (Banca et al., 2020), the task seems to include other relevant components that were not mentioned in this paper. I refer to the daily speed test, the daily random switch test, and daily ratings of each sequence's enjoyment and confidence of knowledge.<br /> If these components were not included in this procedure, then the deviations from the procedure described in the video and Banca al. (2020) should be explicitly mentioned. If these components were included, at least some of them may be relevant, at least in part, to automaticity, habitual action control, formulation of participants' enjoyment from the app etc. I think these components should be mentioned and analyzed (or at least provide an explanation for why it has been decided not to analyze them).<br /> This is also true for the reward removal (extinction) from the 21st day onwards which is potentially of particular relevance for the research questions.

Training engagement analysis:<br /> I find referring to the number of trials including successful and unsuccessful trials as representing participants "commitment to training" (e.g. in Figure legend 2b) potentially inadequate. Given that participants need at least 20 successful trials to complete each practice, more errors would lead to more trials. Therefore, I think this measure may mostly represent weaker performance (of the OCD patients as shown in Figure 2b). Therefore, I find the number of performed practice runs, as used in Figure 2a (which should be perfectly aligned with the number of successful trials), a "clean" and proper measure of engagement/commitment to training.

Also, to provide stronger support for the claim about different diurnal training patterns (as presented in Figure 2c and the text) between patients and healthy individuals, it would be beneficial to conduct a statistical test comparing the two distributions. If the results of this test are not significant, I suggest emphasizing that this is a descriptive finding.

Learning results:<br /> When describing the Learning results (p10) I think it would be useful to provide the descriptive stats for the MT0 parameter (as done above for the other two parameters).

Sensitivity of sequence duration and IKI consistency (C) to reward:<br /> I think it is important to add details on how incorrect trials were handled when calculating ∆MT (or C) and ∆R, specifically in cases where the trial preceding a successful trial was unsuccessful. If incorrect trials were simply ignored, this may not adequately represent trial-by-trial changes, particularly when testing the effect of a trial's outcome on performance change in the next trial.

I have a serious concern with respect to how the sensitivity of sequence duration to reward is framed and analyzed. Since reward is proportional to performance, a reduction in reward essentially indicates a trial with poor performance, and thus even regression to the mean (along with a floor effect in performance [asymptote]) could explain the observed effects. It is possible that even occasional poor performance could lead to a participant demonstrating this effect, potentially regardless of the reward. Accordingly, the reduced improvement in performance following a reward decrease as a function of training length described in Figure 5b legend may reflect training-induced increased performance that leaves less room for improvement after poor trials, which are no longer as poor as before. To address this concern, controlling for performance (e.g., by taking into consideration the baseline MT for the previous trial) may be helpful. If the authors can conduct such an analysis and still show the observed effect, it would establish the validity of their findings."<br /> Another way to support the claim of reward change directionality effects on performance (rather than performance on performance), at least to some extent, would be to analyze the data from the last 10 days of the training, during which no rewards were given (pretending for analysis purposes that the reward was calculated and presented to participants). If the effect persists, it is less unlikely that the effect in question can be attributed to the reward dynamics.<br /> This concern is also relevant and should be considered with respect to the Sensitivity of IKI consistency (C) to reward (even though the relationship between previous reward/performance and future performance in terms of C is of a different structure).<br /> This concern is also relevant and should be considered with respect to the sensitivity of IKI consistency (C) to reward. While the relationship between previous reward/performance and future performance in terms of C is of a different structure, the similar potential confounding effects could still be present.

Another related question (which is also of general interest) is whether the preferred app sequence (as indicated by the participants for Phase B) was consistently the one that yielded more reward? Was the continuous sequence the preferred one? This might tell something about the effectiveness of the reward in the task.

Regarding both experiments 2 and 3:<br /> The change in context in experiment 2 and 3 is substantial and include many different components. These changes should be mentioned in more detail in the Results section before describing the results of experiments 2 and 3.

Experiment 2:<br /> In Experiment 2, the authors sometimes refer to the "explicit preference task" as testing for habitual and goal-seeking sequences. However, I do not think there is any justification for interpreting it as such. The other framings used by the authors - testing whether trained action sequences gain intrinsic/rewarding properties or value, and preference for familiar versus novel action sequences - are more suitable and justified. In support of the point I raised here, assigning intrinsic rewarding properties to the learned sequences and thereby preferring these sequences can be conceptually aligned with goal-directed behavior just as much as it could be with habit.

Experiment 3:<br /> Similar to Experiment 2, I find the framing of arbitration between goal-directed/habitual behavior in Experiment 3 inadequate and unjustified. The results of the experiment suggest that participants were primarily goal-directed and there is no evidence to support the idea that this re-evaluation led participants to switch from habitual to goal-directed behavior.<br /> Also, given the explicit choice of the sequence to perform participants had to make prior to performing it, it is reasonable to assume that this experiment mainly tested bias towards familiar sequence/stimulus and/or towards intrinsic reward associated with the sequence in value-based decision making.

Mobile-app performance effect on symptomatology: exploratory analyses:<br /> Maybe it would be worth testing if the patients with improved symptomatology (that contribute some of their symptom improvement to the app) also chose to play more during the training stage.

Discussion:<br /> Based on my earlier comments highlighting the inadequacy and mis-framing of the work in terms of habit and goal-directed behavior, I suggest that the discussion section be substantially revised to reflect these concerns.

In the sentence "Nevertheless, OCD patients disadvantageously preferred the previously trained/familiar action sequence under certain conditions" the term "disadvantageously" is not necessarily accurate. While there was potentially more effort required, considering the possible presence of intrinsic reward and chunking, this preference may not necessarily be disadvantageous. Therefore, a more cautious and accurate phrasing that better reflects the associated results would be useful.

Materials and Methods:<br /> The authors mention: "The novel sequence (in condition 3) was a 6-move sequence of similar complexity and difficulty as the app sequences, but only learned on the day, before starting this task (therefore, not overtrained)." - for the sake of completeness, more details on the pre-training done on that day would be useful.

Minor comments:<br /> In the section discussing the sensitivity of sequence duration to reward, the authors state that they only analyzed continuous reward trials because "a larger number of trials in each subsample were available to fit the Gaussian distributions, due to feedback being provided on all trials." However, feedback was also provided on all trials in the variable reward condition, even though the reward was not necessarily aligned with participants' performance. Therefore, it may be beneficial to rephrase this statement for clarity.

With regard to experiment 2 (Preference for familiar versus novel action sequences) in the following statement "A positive correlation between COHS and the app sequence choice (Pearson r = 0.36, p = 0.005) further showed that those participants with greater habitual tendencies had a greater propensity to prefer the trained app sequence under this condition." I find the use of the word "further" here potentially misleading.

Reviewer #2 (Public Review):

In this study, researchers aim to understand the computational principles behind attention allocation in goal-directed reading tasks. They explore how deep neural networks (DNNs) optimized for reading tasks can predict reading time and attention distribution. The findings show that attention weights in transformer-based DNNs predict reading time for each word. Eye tracking reveals that readers focus on basic text features and question-relevant information during initial reading and rereading, respectively. Attention weights in shallow and deep DNN layers are separately influenced by text features and question relevance. Additionally, when readers read without a specific question in mind, DNNs optimized for word prediction tasks can predict their reading time. Based on these findings, the authors suggest that attention in real-world reading can be understood as a result of task optimization.

The research question pursued by the study is interesting and important. The manuscript was well written and enjoyable to read. However, I do have some concerns.

1. In the first paragraph of the manuscript, it appears that the purpose of the study was to test the optimization hypothesis in natural tasks. However, the cited papers mainly focus on covert visual attention, while the present study primarily focuses on overt attention (eye movements). It is crucial to clearly distinguish between these two types of attention and state that the study mainly focuses on overt attention at the beginning of the manuscript.

2. The manuscript correctly describes attention in DNN as a mechanism to selectively extract useful information. However, eye-movement measures such as gaze duration and total reading time are primarily influenced by the time needed to process words. Therefore, there is a doubt whether the argument stating that attention in DNN is conceptually similar to the human attention mechanism at the computational level is correct. It is strongly suggested that the authors thoroughly discuss whether these concepts describe the same or different things.

EL PROCESO DE APRENDIZAJE: PASOS a) Tener las necesarias condiciones físicas, psicológicas y de planificación que requiere el aprendizaje. b) Definir con claridad lo que hay que aprender (los objetivos). c)Atender de modo selectivo a la información a aprender. d) Comprender y almacenar la información a aprender, se¬leccionada mediante la atención. Esto implica: — La representación mental de los conocimientos. — La organización de esos conocimientos. — La integración de los mismos en sus esquemas cogniti¬vos, asumiéndolos, modificándolos y enriqueciéndolos. si procede. — La transferencia del aprendizaje. — El autocontrol de su aprendizaje — Saber pensar de modo reflexivo y crítico, y ser creativo. e) Memorizar los conocimientos integrados, que supone: — Almacenar comprensiva y significativamente la infor¬mación organizada y elaborada. 1. Andragogía Es la disciplina educativa que trata de comprender al adulto(a), desde todos los componentes humanos, es decir, como un ente psicológico, biológico y social. La praxis andragógica es un conjunto de acciones, actividades y tareas que al ser administradas aplicando principios y estrategias andragógicas adecuadas, sea posible facilitar el proceso de aprendizaje en el adulto. 1. La Andragogía Es el arte y ciencia de ayudar a aprender a los adultos, basándose en suposiciones acerca de las diferencias entre niños y adultos. 1. Elementos Fundamentales de la Andragogía

1) Ambiente 2) Facilitador y participante 3) Trabajo y dinámicas de grupo 4) Sistema semi-presencial. 5) Teoría sinérgica. 6) Comunicación efectiva (Feed-back y escucha activa). 7) Sistema evaluación

Principios de Aprendizaje en el Adulto

La Horizontalidad y la Participación La horizontalidad, significa la igualdad de condiciones entre el facilitador (orientador-acompañante) y los participantes. Igualdad en cuanto a la adultez con experiencias, no así en cuanto a sus roles donde el facilitador acompaña al participante en el proceso de orientación-aprendizaje.

La participación, es el acto de compartir algo, es un dar y recibir, involucrarse en un proyecto común. Es aportar de sus propios conocimientos, de su experiencia, personas activas, críticas y respetuosas dentro de un proceso de orientación-aprendizaje.

Aprendizaje de Adultos PRINCIPIOS DEL APRENDIZAJE DEFINICIÓN Principio del reforzamiento” Todo ser humano aprende las conductas que son recompensadas o aquellas que reportan consecuencias agradables. Principio de la” intencionalidad” Las actividades que se realizan intencionalmente se aprenden mejor que las actividades “no intencionales” Principio de la organización por configuraciones globales El aprendizaje se facilita cuando la persona organiza los elementos de una información, adecuándolos a su propia estructura mental; en esta organización el contexto es el elemento que da a la información gran parte de su significado. Principio de la retroalimentación El conocimiento de los resultados de la propia actividad favorece el aprendizaje.

Características del Alumno Adulto Participación voluntaria: Los adultos aprenden mejor en situaciones donde se vean involucrados. Respeto mutuo: En el proceso de aprendizaje los adultos necesitan sentirse valorados y respetados. Colaboración: Los adultos aprenden mejor en situaciones en las que puedan compartir criterios y así retroalimentarse unos de otros. Acción y Reflexión: Para ser efectivos en las oportunidades de desarrollo profesional. Selección organizativa: Los programas de desarrollo profesional necesitan ser adquiridos y avalados por la institución a su debido tiempo. Alternativos y cambios: Los adultos aprenden mejor cuando se le presentan alternativas para el aprendizaje que los conduzcan al éxito. Motivación: El adulto se involucra en el aprendizaje cuando existe una oportunidad que lo ayuda a mejorar el nivel de vida

Características del Alumno Adulto

Amplitud del saber Amplitud de experiencias: Adaptación de métodos pedagógicos Ejercicio intelectual

Aprendizaje Conceptual

El aprendizaje conceptual involucra el reconocer y asociar características comunes a un grupo de objetos o acontecimientos. Es un proceso activo en el que los educandos construyen nuevas ideas o conceptos basados en el conocimiento. Aprendizaje Apreciativo

Es una corriente psicopedagógica que tiene como objetivo desarrollar la capacidad apreciativa de los alumnos ante un valor.

Aprendizaje Asociativo

Consiste en adquirir tendencias de asociación que aseguren el recuerdo de detalles particulares en una sucesión definida y fija, en el cual se asocian dos o más estímulos, en el aprendizaje no asociativo se modifica la conducta del sujeto por la mera presencia de un solo estímulo, sin que este se asocie a ningún otro.

Aprendizaje Creativo

Es una forma de captar o ser sensible a los problemas, deficiencias, lagunas del conocimiento, elementos pasados por alto, faltas de armonía. Describe un proceso humano natural en cuyas etapas están implicadas fuertes motivaciones.

Aprendizaje innovador:

Es aquel que puede soportar cambios, renovación, reestructuración y reformulación de problemas. Propone nuevos valores en vez de conservar los antiguos.

Aprendizaje Reflexivo

Es el estilo de razonamiento donde predomina la observación y el análisis de los resultados de las experiencias realizadas. Se caracteriza por el deseo de tomar decisiones sin contradicciones de tiempo. Por la importancia del retroceso y de la distancia tomada en relación a las personas y a las cosas. Es marcado por la prudencia y la reflexión profundizada antes de tomar una decisión para actuar, escucha la acumulación exhaustiva de datos antes de dar una opinión.

Reviewer #2 (Public Review):

This study found that MECOM, PAX8, SOX17, and WT1, as the main regulators of high-grade serous ovarian cancer (HGSC), their transcriptional regulation related to the super-enhancer, were reconnected in the process of tumor development. These four TFS are essential for the clonality and survival of HGSC, while the absence of PAX8 and WT1 in non-cancerous fallopian tube secretory epithelium (FTSEC) can impair the survival of cells. These four TFS are only pharmacologically inhibited by transcriptional inhibitors in HGSCs, while not in FTSECs, making them potential targets for tumor-specific therapy.

I am thrilled to see such an exciting and scientific manuscript. The results will significantly impact the basic theory of cancer occurrence and clinical applications.

However, there were some issues with the data presentation. We hope that the author will carefully and rigorously review the data and visualization results. In addition, there is key information missing in the methods section, which does not meet the current requirements for the repeatability of scientific conclusions.

Reviewer #2 (Public Review):

In this study the authors confirm that one of the genes classified as essential in a Tn-mutagenesis study in A. baumannii is in fact an essential gene. It is also present in other closely related Gram negative bacteria and the authors designated it Aeg1. Depletion of Aeg1 leads to cell filamentation and it appears that the requirement for Aeg1 can be suppressed by what appear to be activation mutations in various genes. Overall, it appears that Aeg1 is involved in cell division but many of the images suffer from poor quality - it may be due to conversion to PDF. One of the main issues is that depletion of Aeg1 is carried out for such long times (18 hr) (Fig. 2, 4 and 5). Depleting a cell division protein for such long times may have pleiotropic effects on cell physiology. A. baumannii grows quite fast and even with a small inoculum, cells will probably be in stationary phase. If Aeg1 is that essential cells should be quite filamentous 2-3 hours after Ara removal when they are still in exponential phase. Also, it would be better to see the recovery to small cells if cells are not grown such a long time before Ara is added back. Overall, Aeg1 is potentially interesting but studies are needed to define its place in the assembly pathway. What proteins are at the division site when Aeg1 is depleted and what proteins are required for Aeg1 to localize to the division site. These experiments should be done when cell are depleted of proteins for only 1 -2 hours.

Reviewer #2 (Public Review):

In Bolumar, Moncayo-Arlandi et al. the authors explore whether endometrium-derived extracellular vesicles contribute mtDNA to embryos and therefore influence embryo metabolism and respiration. The manuscript combines techniques for isolating different populations of extracellular vesicles, DNA sequencing, embryo culture, and respiration assays performed on human endometrial samples and mouse embryos.

Vesicle isolation is technically difficult and therefore collection from human samples is commendable. Also, the influence of maternally derived mtDNA on the bioenergetics of embryos is unknown and therefore novel. However, several experiments presented in the manuscript fail to reach statistical significance, likely due to the small sample sizes. Additionally, the experiments do not demonstrate a direct effect of mtDNA transfer on embryo bioenergetics. This has the unfortunate consequence of making several of the authors' conclusions speculative.

In my opinion the manuscript supports the following of the authors' claims:

1. Different amounts of mtDNA are shed in human endometrial extracellular vesicles during different phases of the menstrual cycle.<br /> 2. Endometrial microvesicles are more enriched for mitochondrial DNA sequences compared to other types of microvesicles present in the human samples.<br /> 3. Fluorescently labelled DNA from extracellular vesicles derived from an endometrial adenocarcinoma cell line can be incorporated into hatched mouse embryos.<br /> 4. Culture of mouse embryos with endometrial extracellular vesicles can influence embryo respiration and the effect is greater when cultured with isolated exosomes compared to other isolated microvesicles.

My main concerns with the manuscript:

1. The authors demonstrate that microvesicles contain the most mtDNA, however, they also demonstrate that only isolated exosomes influence embryo respiration. These are two separate populations of extracellular vesicles.<br /> 2. mtDNA is not specifically identified as being taken up by embryos only DNA.<br /> 3. The authors do not rule out that other components packaged in extracellular vesicles could be the factors influencing embryo metabolism.

Taken together, these concerns seem to contradict the implication of the title of the manuscript - the authors do not demonstrate that inheritance of maternal mtDNA has a direct causative effect on embryo metabolism.

Reviewer #2 (Public Review):

The authors of this study levered large-scale genomics data on SARS-CoV2, and extracted non-synonymous mutations of NSP10. The overall frequency was little, compared to other significantly mutating Spike protein. Further they performed stability and binding analysis to report changes in three variants and found modest differences. However, crystallography and simulations study reported almost no changes.

The strength of the work clearly is merging genomics data and reporting quantitative frequencies with high-resolution structural data. Some open ended questions remain. For instance, The DynaMut2 and thermal shift assays point towards less stable variants than wild type, with Tm values slightly lower. On the other hand, the Kd value of variants reported stronger binding of NSP10 with NSP16. How do authors explain this, as the change due to point mutation may not fall within error range?

The crystal structures and the simulations have been under-analysed. For instance, the conformational ensemble could be utilized for docking with NSP16 and NSP14 . There could be a potential alternative pathway for explaining the above changes in Kd. This should be attempted for understanding the role in its functional activity.

Previous extensive EM work on Spike protein variants also displayed subtle differences locally. However, allosteric pathways with D614G have been reported. Therefore, more quantitative analysis is required to explain structural changes. The free energy landscape reported in the paper may not capture rare transition events or slight rearrangements in side chain dynamics, both these could offer better understanding of mutations.

Reviewer #2 (Public Review):

In this paper the authors present an existing information theoretic framework to assess the ability of single cells to encode external signals sensed through membrane receptors.

The main point is to distinguish actual noise in the signaling pathway from cell-cell variability, which could be due to differences in their phenotypic state, and to formalize this difference using information theory.

After correcting for this cellular variability, the authors find that cells may encode more information than one would estimate from ignoring it, which is expected. The authors show this using simple models of different complexities, and also by analyzing an imaging dataset of the IGF/FoxO pathway.

The implications of the work are limited because the analysed data is not rich enough to draw clear conclusions. Specifically,<br /> - the authors do not distinguish what could be methodological noise inherent to microscopy techniques (segmentation etc), and actual intrinsic cell state. It's not clear that cell-cell variability in the analyzed dataset is not just a constant offset or normalization factor. Other authors (e.g. Gregor et al Cell 130, 153-164) have re-centered and re-normalized their data before further analysis, which is more or less equivalent to the idea of the conditional information in the sense that it aims to correct for this experimental noise.<br /> - in the experiment, each condition is shown only once and sequentially. This means that the reproducibility of the response upon repeated exposures in a single cell was not tested, casting doubt on the estimate of the response fidelity (estimated as the variance over time in a single response).<br /> - another dataset on the EGF/EGFR pathway is analyzed, but no conclusion can be drawn from it because single-cell information cannot be directly estimated from it. The authors instead use a maximum-entropy Ansatz, which cannot be validated for lack of data.

Reviewer #2 (Public Review):

The authors combine the use of fluorogenic tools with fluorescence bioimaging to visualize how changes in the folding states of the RBPs TDP-43, FUS and TAF15 affect their subcellular localization and recruitment inside nuclear bodies, as well as protein fate. While the development of SNAP-tag substrates coupled with confocal microscopy in living cells (including FLIM) to monitor changes in protein folding states represents an important conceptual and technical advance for the field, I am not convinced that the authors fully achieved their aim. The authors cannot conclude on protein fate only based on the experiments performed here. Showing a correlation between a decrease in TDP-43 levels upon Hsp70 inhibition and colocalization at nuclear bodies with Hsp70 and DNAJA2 is not supporting their conclusion about protein degradation. A number of additional control experiments are needed to support their claims.

Yet, the optimization of these methods has unlimited potential since it may provide new ways to visualize and monitor a large variety of fundamental intracellular processes, including protein aggregation and fate.

Reviewer #2 (Public Review):

Synaptic scaling has long been proposed as a homeostatic mechanism for the regulation for the activity of individual neurons and networks. The question of whether homeostasis is controlled by neuronal spiking or by the activation of specific receptor populations in individual synapses has remained open. In a previous work, the Wenner group had shown that upscaling of glutamatergic transmission is triggered by direct blockade of glutamate receptors rather than by the concomitant reduction in firing rate (Nat Comm 2015). In this manuscript they investigate the mechanisms regulating scaling of GABA-mediated responses in cortical cell cultures using whole-cell recordings to detect GABAergic currents and multielectrode arrays to monitor global firing activity, and find that spiking plays a fundamental role in scaling.

Initially, the authors show that chronic blockade (24 h) of glutamatergic transmission by CNQX first reduces spontaneous spiking (at 2 h), but later (24 h) firing grows back towards higher frequencies, suggesting a compensatory mechanism. Then it is shown that either chronic CNQX treatment or TTX cause a reduction in the amplitude of GABAergic mIPSCs. Effects of CNQX on IPSCs are then reverted by replacing spontaneous network firing by chronic optogenetic stimulation of the entire culture, also indicating that GABAergic transmission is homeostatically regulated by global firing. Enhancing glutamatergic transmission with CTZ increases mIPSC amplitude, while addition of TTX in the presence of CTZ causes the opposite effect. Finally, increasing spiking activity using bicuculline also increases mIPSC amplitude, and the authors conclude that spiking activity rather than neurotransmission control homeostatic GABA scaling. The manuscript shows interesting properties in the regulation of global GABAergic transmission and highlight the important role of spiking activity in triggering GABA scaling. However, it is strongly recommended to address some caveats in order to better support the conclusions presented in the manuscript.

Major points:

1. The reason why CNQX does not completely eliminate spiking is unclear (Fig. 1). What is the circuit mechanism by which spiking continues, although at lower frequency, in the absence of AMPA-mediated transmission and what the mechanism by which spiking frequency grows back after 24h (still in the absence of AMPA transmission)?<br /> Is it possible that NMDA-mediated transmission takes over and triggers a different type of network plasticity?

2. A possible activation of NMDARs should be considered. One would think that experiments involving chronic glutamatergic blockade could have been conducted in the presence of NMDAR blockers. Why this was not the case?

Also, experiments with global ChR2 stimulation with coincident pre and postsynaptic firing might also activate NMDARs and result in additional effects that should be taken into consideration for the global scaling mechanism.

3. Cultures exposed to CTZ to enhance AMPA receptors generated variable results (Fig. 5), somewhat increasing spiking activity in a non-significant manner but, at the same time, strengthening mIPSC amplitude. This result seems to suggest that spiking might be involved in GABAergic scaling, but it does not seem to prove it.

Then, addition of TTX that blocked spiking reduced mIPSC amplitude. It was concluded here that the ability of CTZ to enhance GABAergic currents was primarily due to spiking, rather than the increase in AMPA-mediated currents. However, in addition to blocking action potentials, TTX would also prevent activation of AMPARs in the presence of CTZ due to the lack of glutamatergic release. Therefore, under these conditions, an effect of glutamatergic activation on GABAergic scaling cannot be ruled out.

4. The sample size is not mentioned in any figure. How many cells/culture dishes were used in each condition?

5. Cortical cultures may typically contain about 5-10% GABAergic interneurons and 90-95 % pyramidal cells. One would think that scaling mechanisms occurring in pyramidal cells and interneurons could be distinct, with different impact on the network. Although for whole-cell recordings the authors selected pyramidal looking cells, which might bias recordings towards excitatory neurons, naked eye selection of recording cells is quite difficult in primary cultures. Some of the variability in mIPSC amplitude values (Fig. 2A for example) might be attributed to the cell type? One could use cultures where interneurons are fluorescently labeled to obtain an accurate representation. The issue of the possible differential effects of scaling in pyramidal cells vs. interneurons and the consequences in the network should be discussed.

Reviewer #2 (Public Review):

Maternal infection by Rubella virus (RV) early during pregnancy is a serious threat to the health of the fetus. It can cause brain malformation and later expose the newborn to a constellation of symptoms collectively named Congenital Rubella Syndrome (CRS). In this manuscript, the authors provide novel exciting findings on the pathophysiological mechanisms of RV infection during human brain development. By combining analyses of human fetal brain material and cerebral organoids, Popova and colleagues uncovered a selective tropism of RV for microglial cells. Their results suggest that the infection of microglia by RV relies on the presence of diffusible factors secreted by neighboring brain cells. Moreover, the authors showed that RV infection of human cerebral organoids leads to a strong interferon response and dysregulation of neurodevelopmental genes, which both may contribute to brain malformation. Altogether, these data shed some new light on the cellular tropism and the pathophysiological mechanisms triggered by RV infection in the developing brain. This study also raises the importance of using human cell-based models to further understand the pathophysiological mechanisms of CRS. Identifying the cellular and molecular targets of Rubella virus will also pave the way to develop therapies against CRS.

Reviewer #2 (Public Review):

In their recent manuscript, Broca-Brisson et al. deliver a multidisciplinary approach to investigate creatine transporter deficiency (CTD) using human-derived brain organoids. The authors have provided a compelling CTD human brain organoid model using induced pluripotent stem cells (iPSCs) derived from individuals with CTD. This model shows distinct differences in creatine uptake between organoids originating from CTD patients and their healthy counterparts. Furthermore, the researchers effectively restored creatine uptake by reintroducing the wild-type CRT in the iPSCs.

The team used advanced molecular biology techniques and sophisticated mass spectrometry to identify changes in protein regulation within these CTD brain organoids. They propose an intriguing theory linking reduced creatine uptake to abnormalities in the GSK3β kinase pathway and mitochondrial function, which might underlie intellectual disability seen in CTD patients.<br /> This study is well-structured and easy to follow, with clear and concise explanations of the experiments. The authors present an important idea: a dysfunction in just one protein transporter (CRT) can cause significant biochemical changes in the brain. Their findings are well-presented and backed by high-quality figures and comprehensive data analysis.

Reviewer #2 (Public Review):

In this work, the authors found in the mouse line of GABAA 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. The current work was basically a follow-up of a previous study in juvenile mice, and the results were also very similar to the juvenile results (Sommeijer et al., 2017). One possible 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 retains the dLGN in an immature stage till adulthood. The authors indeed claimed in the discussion that the 2-day OD shift is intact in juvenile dLGN and V1 in KO mice, and provided evidence in supplementary figure that GABAergic and cholinergic synapse amount are similar between WT and KO mice. However, the 7-day OD shift is indeed defected in juvenile V1 and dLGN in KO mice (Sommeijer et al., 2017), and it is possible that this early functional deficit didn't induce a structural remodeling in adulthood. To better support the author's claim that the lack of adult V1 OD plasticity is specifically due to reduced dLGN synaptic inhibition, the author should generate conditional KO mice that dLGN synaptic inhibition was only interfered in adulthood.

2. The authors found that in juveniles, dLGN OD shift is dependent on V1 feedback, but not in adults. However, a recent work showed that the effects of V1 silencing on dLGN OD plasticity could differ with various starting points and duration of the V1 silencing and MD (Li et al., 2023). Could the authors provide more details of the MD and V1 silencing for an in-depth discussion?

References<br /> Li, N., Liu, Q., Zhang, Y., Yang, Z., Shi, X., and Gu, Y. (2023). Cortical feedback modulates distinct critical period development in mouse visual thalamus. iScience 26, 105752.<br /> Sommeijer, J.P., Ahmadlou, M., Saiepour, M.H., Seignette, K., Min, R., Heimel, J.A., and Levelt, C.N. (2017). Thalamic inhibition regulates critical-period plasticity in visual cortex and thalamus. Nat Neurosci 20, 1715-1721.

Reviewer #2 (Public Review):

To characterize the relationship between Na+ and K+ binding to LeuT, the effect of K+ on Na+- dependent [3 H] leucine binding was studied using a scintillation proximity assay. In the presence of K+ the apparent affinity for sodium was reduced but the maximal binding capacity for this ion was unchanged, consistent with a competitive mechanism of inhibition between Na+ and K+.

To obtain a more direct readout of K+ binding to LeuT, tmFRET was used. This method relies on the distance-dependent quenching of a cysteine-conjugated fluorophore (FRET donor) by a transition metal (FRET acceptor). This method is a conformational readout for both ion- and ligand-binding. Along with the effect of K+ on Na+-dependent [3 H] leucine binding, the findings support the existence of a specific K+ binding site in LeuT and that K+ binding to this site induces an outward closed conformation.

It was previously shown that in liposomes inlaid with LeuT by reconstitution, intra-vesicular K+ increases the concentrative capacity of [ 3 H] alanine. To obtain insights into the mechanistic basis of this phenomenon, purified LeuT was reconstituted into liposomes containing a variety of cations, including Na+ and K+ followed by measurements of [ 3 H] alanine uptake driven by a Na+ gradient. The ionic composition of the external medium was manipulated to determine if the stimulation of [3 H] alanine uptake by K+ was due to an outward directed potassium gradient serving as a driving force for sodium-dependent substrate transport by moving in the direction opposite to that of sodium and the substrate. Remarkably it was found that it is the intra-liposomal K+ per se that increases the transport rate of alanine and not a K+ gradient, suggesting that binding of K+ to the intra-cellular face of the transporter could prevent the rebinding of sodium and the substrate thereby reducing their efflux from the cell. These conclusions assume that the measured radioactive transport is via right-side-out liposomes rather than from their inverted counterparts (in case of a random orientation of the transporters in the proteoliposomes). Even though this assumption is likely to be correct, it should be tested.

Since K+- and Na+-binding are competitive and K+ excludes substrate binding, the Authors chose to focus on the Na1 site where the carboxyl group of the substrate serves as one of the groups which coordinate the sodium ion. This was done by the introduction of conservative mutations of the amino acid residues forming the Na1 site. The potassium interaction in these mutants was monitored by sodium dependent radioactive leucine binding. Moreover, the effect the effect of Na+ with and without substrate as well as that of potassium on the conformational equilibria was measured by tmFRET measurements on the mutants introduced in the construct enabling the measurements. The results suggest that K+-binding to LeuT modulates substrate transport and that the K+ affinity and selectivity for LeuT is sensitive to mutations in the Na1 site, pointing toward the Na1 site as a candidate site for facilitating the interaction between K+ in some NSS members.

The data presented in this manuscript are of very high quality. They are a detailed extension of results by the same group (Billesbolle et. al, Ref. 16 from the list) providing more detailed information on the importance of the Na1 site for potassium interaction. Clearly this begs for the identification of the binding site in a potassium bound LeuT structure in the future. Presumably LeuT was studied here because it appears that it is relatively easy to determine structures of many conformational states. Furthermore, convincing evidence showed that the stimulatory effect of K+ on transport is not because of energization of substrate accumulation but is rather due to the binding of this cation to a specific site.

Reviewer #2 (Public Review):

In the present manuscript, Golf et al. investigate the consequences of astrocyte-specific deletion of Neuroligin family cell adhesion proteins on synapse structure and function in the brain. Decades of prior research had shown that Neuroligins mediate their effects at synapses through their role in the postsynaptic compartment of neurons and their transsynaptic interaction with presynaptic Neurexins. More recently, it was proposed for the first time that Neuroligins expressed by astrocytes can also bind to presynaptic Neurexins to regulate synaptogenesis (Stogsdill et al. 2017, Nature). However, several aspects of the model proposed by Stogsdill et al. on astrocytic Neuroligin function conflict with prior evidence on the role of Neuroligins at synapses, prompting Golf et al. to further investigate astrocytic Neuroligin function in the current study. Using postnatal conditional deletion of Neuroligins 1, 2 and 3 specifically from astrocytes, Golf et al. show that virtually no changes in the expression of synaptic proteins or in the properties of synaptic transmission at either excitatory or inhibitory synapses are observed. Moreover, no alterations in the morphology of astrocytes themselves were found. The authors conclude that while Neuroligins are indeed expressed in astrocytes and are hence likely to play some role there, this role does not include any direct consequences on synaptic structure and function, in direct contrast to the model proposed by Stogsdill et al.

Overall, this is a strong study that addresses an important and highly relevant question in the field of synaptic neuroscience. Neuroligins are not only key regulators of synaptic function, they have also been linked to numerous psychiatric and neurodevelopmental disorders, highlighting the need to precisely define their mechanisms of action. The authors take a wide range of approaches to convincingly demonstrate that under their experimental conditions, no alterations in the levels of synaptic proteins or in synaptic transmission at excitatory or inhibitory synapses, or in the morphology of astrocytes, are observed.

One caveat to this study is that the authors do not directly provide evidence that their Tamoxifen-inducible conditional deletion paradigm does indeed result in efficient deletion of all three Neuroligins from astrocytes. Using a Cre-dependent tdTomato reporter line, they show that tdTomato expression is efficiently induced by the current paradigm, and they refer to a prior study showing efficient deletion of Neuroligins from neurons using the same conditional Nlgn1-3 mouse lines but a different Cre driver strategy. However, neither of these approaches directly provide evidence that all three Neuroligins are indeed deleted from astrocytes in the current study. In contrast, Stogsdill et al. employed FACS and qPCR to directly quantify the loss of Nlgn2 mRNA from astrocytes. This leaves the current Golf et al. study somewhat vulnerable to the criticism, however unlikely, that their lack of synaptic effects may be a consequence of incomplete Neuroligin deletion, rather than a true lack of effect of astrocytic Neuroligins.

Reviewer #2 (Public Review):

In this manuscript, Scholz et al., adopt a set of tasks to study how brain regions are differentially activated with temporal context clues. In one task, the first item in a two item sequence will dictate the value of the second. In another task, there is no hierarchy in temporal order, though subjects must still maintain information across the delay to add the value of the two presented items. Using univariate analyses, the authors found many regions that showed an interaction between item position and task, including: the mPFC, anterior hippocampus and the left prefrontal and posterior temporal cortices. The results are interpreted as evidence for a dedicated system for understanding hierarchical relationships across domains as various as spatial cognition, music, and language.

The question raised by the authors is important and fMRI may be an appropriate means of studying the neural basis for hierarchical computations. The main limitation of the manuscript, and one that is briefly mentioned and dismissed in the discussion is the task design, which confounds whether or not a hierarchical relationship must be formed, and the content of the information that must be held across working memory (color in the hierarchy task and number in the iterative task).

The authors also report an interesting difference between the activation observed in the head and tail of the hippocampus during the different tasks. However, the authors compare each region independently, show one is significant and the other is not, and then conclude "the effect of hierarchical context representation in the hippocampus is specific to its anterior regions." Such a conclusion requires direct comparison of the regions.

Finally, it isn't clear if the motivating prior work makes a simple univariate prediction. A strong prediction however is that the representational similarity should be very different for objects in the first versus second position in the hierarchy task and much less so in the iterative task. Such a representational similarity analysis would better connect this study to prior research and to the hypothesis that hierarchical processing affects the coding of items in sequence.

Reviewer #2 (Public Review):

The manuscript of Duewell et al has made critical observations that help to understand the mechanisms of activation of the class IA PI3Ks. By using single-molecule kinetic measurements, the authors have made outstanding progress toward understanding how PI3Kbeta is uniquely activated by phosphorylated tyrosine kinase receptors, Gbeta/gamma heterodimers and the small G protein Rac1. While previous studies have defined these as activators of PI3Kbeta, the current manuscript makes clear the quantitative limitations of these previous observations. Most previous quantitative in vitro studies of PI3Kbeta activation have used soluble peptides derived from bis-phosphorylated receptors to stimulate the enzyme. These soluble peptides stimulate the enzyme, and even stimulate membrane interaction. Although these previous studies showed that the release of p85-mediated autoinhibition unmasks an intrinsic affinity of the enzyme for lipid membranes, they ignored what would be the consequence of these peptide sequences being present in the context of intrinsic membrane proteins. The current manuscript shows that the effect of membrane-conjugated peptides on the enzyme activity is profound, in terms of recruiting the enzyme to membranes. In this context, the authors show that G proteins associated with the membranes have an important contribution to membrane recruitment, but they also have a profound allosteric effect on the activity on the membrane, These are observations that would not have been possible with bulk measurements, and they do not simply recapitulate observations that were made for other class IA PI3Ks.

An important observation that the authors have made is that Gbeta/gamma heterodimers and RAc1 alone have almost no ability to recruit PI3Kbeta to the membranes that they are using, and this is central to one of the most profoundly novel activation mechanisms offered by the manuscript. The authors propose that the nSH2- and Gbeta/gamma binding sites partially overlap, so that Gbeta/gamma can only bind once the nSH2 domain releases the p110beta subunit. This mechanism would mean that once the nSH2 is engaged by membrane-congugated pY, the Gbg heterodimer can bind and increase the association of the enzyme with membranes. Indeed, this increased membrane association is observed by the authors. However, the authors also show that this increased recruitment to membranes accounts for relatively little increase in activity, and that the far greater component of activation is due to an allosteric effect of the membrane association on the activity of the enzyme. The proposal for competition between Gbg binding and the nSH2 is consistent with the behavior of an nSH2 mutant that cannot bind to pY and which, consequently, does not vacate the Gbg-binding site. In addition to the outstanding contribution to understanding the kinetics of activation of PI3Kbeta, the authors have offered the first structural interpretation for the kinetics of Gbg activation in synergy with pY activation. The proposal for an overlapping nSH2/Gbg binding site is supported by predictions made by John Burke, using alphafold multimer. Although there is no experimental structure to support this structural model, it is consistent with HDX-MS analyses that were published previously.

Reviewer #2 (Public Review):

Fiedler and colleagues set out to establish an analog-sensitive approach for selective inhibition of the mammalian IP6K isozymes. IP6Ks are inositol hexakisphosphate kinases, and the authors found that the classic glycine and alanine gatekeeper mutation (established by Kevan Shokat as the "bump and hole approach" for various protein kinases) resulted in limited catalytic efficiency. Therefore, the authors decided to use a leucine-to-valine mutation, which did not affect kinase activity, but, unfortunately, was less amenable to any of the well-established analog-sensitive kinase inhibitors such as PP1 and naphthyl-PP1. To overcome this limitation, the authors performed an elegant HT screen and identified a benzimidazole-based mutant-selective small molecule inhibitor. A focused SAR analysis combined with detailed kinetic studies revealed the hit molecule FMP-201300 as an allosteric inhibitor of IP6K mutants. While co-crystallization experiments failed, the authors used high-end HDX-MS measurements to gain insight into the structural and conformational determinants of mutant selectivity.

Overall, this is an excellent study of high quality. The identified FMP-201300 has the potential for further compound and probe development. My only minor comment is that the authors could spend more time discussing the proposed allosteric binding mode of FMP-201300 and provide more detailed figures to highlight the proposed interactions with the protein and the conformational changes that must ultimately take place to accommodate the allosteric modulator. I appreciate that the co-crystallization experiments did not yield bound inhibitor structures, but perhaps the authors could consider MD simulations to complete their study.

Reviewer #2 (Public Review):

Bhanja et al have examined how actin polymerization switch B-cell receptor (BCR) signaling from amplification to attenuation. The authors have examined B cell spreading and contraction using lipid bilayers to assess the molecular regulation of BCR signalling during the contraction phase. Their data provide evidence for that N-WASP activated Arp2/3 generates centripetally moving actin foci and contractile actomyosin from lamellipodia actin networks. This generates BCR dense foci that pushes out both stimulatory kinases and inhibitory phosphatases. The study provides novel insight into how B cells upon activation attenuate BCR signalling by contraction of the actin cytoskeleton and clustering of BCR foci and this dynamic response is mediated by N-WASP and Arp2/3.

Strengths: The manuscript is well written and results, methods, figures and legends described in detail making it easy to follow the experimental setup, analysis, and conclusions. The authors achieved their aims, and the results support their conclusions.

Weaknesses: Minor as listed below. The working hypothesis of molecular crowding as a way to push out signalling molecules from the BCR dense foci is interesting. The authors provide evidence for that this is an active process mediated by N-WASP - Arp2/3 induced actin foci. Another possibility is that BCR dense foci formation is an indirect consequence of lamellipodia retraction. Future works should define the specific role of N-WASP, Arp2/3 and actin in the process to form BCR dense foci, especially as the BCR continue to signal in the cytoplasm.

Reviewer #2 (Public Review):

In this manuscript, the authors examined the role of transcription readout and intron retention in increasing transcription of transposable elements during aging in mammals. It is assumed that most transposable elements have lost the regulatory elements necessary for transcription activation. Using available RNA-seq datasets, the authors showed that an increase in intron retention and readthrough transcription during aging contributes to an increase in the number of transcripts containing transposable elements.

Previously, it was assumed that the activation of transposable elements during aging is a consequence of a gradual imbalance of transcriptional repression and a decrease in the functionality of heterochromatin (de repression of transcription in heterochromatin). Therefore, this is an interesting study with important novel conclusion. However, there are many questions about bioinformatics analysis and the results obtained.

Major comments:

1. In Introduction the authors indicated that only small fraction of LINE-1 and SINE elements are expressed from functional promoters and most of LINE-1 are co-expressed with neighboring transcriptional units. What about other classes of mobile elements (LTR mobile element and transposons)?

2. Results: Why authors considered all classes of mobile elements together? It is likely that most of the LTR containing mobile elements and transposons contain active promoters that are repressed in heterochromatin or by KRAB-C2H2 proteins.

3. Fig. 2. A schematic model of transposon expression is not presented clearly. What is the purpose of showing three identical spliced transcripts?

4. The study analyzed the levels of RNA from cell cultures of human fibroblasts of different ages. The annotation to the dataset indicated that the cells were cultured and maintained. (The cells were cultured in high-glucose (4.5mg/ml) DMEM (Gibco) supplemented with 15% (vol/vol) fetal bovine serum (Gibco), 1X glutamax (Gibco), 1X non-essential amino acids (Gibco) and 1% (vol/vol) penicillin-streptomycin (Gibco). How correct that gene expression levels in cell cultures are the same as in body cells? In cell cultures, transcription is optimized for efficient division and is very different from that of cells in the body. In order to correlate a result on cells with an organism, there must be rigorous evidence that the transcriptomes match.

5. The results obtained for isolated cultures of fibroblasts are transferred to the whole organism, which has not been verified. The conclusions should be more accurate.

6. The full pipeline with all the configuration files IS NOT available on github (pabisk/aging_transposons).

7. Analysis of transcripts passing through repeating regions is a complex matter. There is always a high probability of incorrect mapping of multi-reads to the genome. Things worsen if unpaired short reads are used, as in the study (L=51). Therefore, the authors used the Expectation maximization algorithm to quantify transposon reads. Such an option is possible. But it is necessary to indicate how statistically reliable the calculated levels are. It would be nice to make a similar comparison of TE levels using only unique reads. The density of reads would drop, but in this case it would be possible to avoid the artifacts of the EM algorithm.

Reviewer #2 (Public Review):

In this research article a new allosteric mechanism for T cell receptor (TCR) triggering upon peptide-MHC complex binding is presented in which conformational change in the TCR facilitates activation by controlling CD3 dynamics around the TCR. The authors find that the Cb FG loop acts as a gatekeeper and Cb connecting peptide acts as a hinge to control TCR flexibility.

As an initial result, the authors set up two sets of simulations - TCR-CD3 and pMHC-TCR-CD3 in POPC bilayers and identified that the CD3e chains exhibit a wider range of mobility in the pMHC-TCR-CD3 system as compared to the TCR-CD3 system. Next, they examined the contacts between all subunits during the course of both simulations and established that CD3g and CD3eg made far fewer contacts with TCRb in the pMHC-TCR-CD3 simulations. Next, they identified that the TCR is extended in the pMHC-TCR-CD3 simulations with larger tilt angle of 150º and FG loop acts as gatekeeper that allows CD3 movements upon pMHC binding. Finally, Mutations in Cb connecting peptide regions indicated rigidified TCR leading to hypersensitive TCR, proved both by simulations and in vitro experiments.

The following major concerns must be addressed.

Major concerns:

1) The simulations were performed with intracellular regions unfolded and free from the membrane. A more complete system should have the intracellular regions embedded in the membrane. An NMR structure of CD3e is available (Xu et al., Cell, 2008) and could have been modeled into the TCR-CD3 system before the simulation. Prakaash et al., (PLoS, Comput Biol, 2021) studied cytoplasmic domain motions during in their simulation experiments.

2) Comparing Fig. 2C and Fig.7C, the movement of CD3eg is more restricted in Fig.7C. Is this because the simulation time is lower in the mutation experiments?

3) Only TCR-CD3 simulation were performed for PP and AA mutants. A simulation with pMHC (pMHC-TCRmutants-CD3) should be performed to show increased CD3 mobility.

4) Using CD3e antibody, OKT3, for activation instead of pMHC as a separate experiment would add more value to this study. They can look at CD3 mobility and TCR elongation in the system with OKT3 antibody and compare it to the CD3 mobility and TCR elongation with the pMHC system. They can also use OKT3 with AA and PP mutants and perform both simulation and in vitro activation experiments.

5) The activation experimental data is rather underwhelming. The difference between WT and PP in 2hr experiment at 0.016 ug/mL looks exceedingly low. A stronger TCR-pMHC system should be considered for the in vitro activation experiments.

6) There is some concern that the scientific work lacks solid experimental functional data and lack of novelty due to earlier TCR-CD3 simulation studies (Pandey et al., 2021, eLife) that already reported flexibility and elongation of the complex.

Reviewer #2 (Public Review):

• The central component of the Nuclear Pore Complex (NPC) that controls nucleocytoplasmic transport is the assembly of the intrinsically disordered proteins (IDPs) that line its passageway. Nanopore based mimics functionalized with these IDPs have been an important tool in understanding the mechanisms of protein transport through the NPC. This paper develops a new type of nanopore NPC mimic that acts as Zero Mode Waveguide enabling optical detection of protein translocations on the single molecule level in pores of different diameters. This is a significant improvement over previous mimics, where optical detection was used only for measurement of bulk fluxes, while single molecule detection relied on electrochemical methods that potentially introduce substantial artifacts. Studying the dependence of transport on the pore diameter is interesting because of its important connections to mechanosensitivity of protein partitioning in cells, which can be difficult to directly control and study in live cells.

• The authors study the transport of individual transport proteins in the dilute regime, and compare the transport of the transport proteins that naturally carry cargoes through the NPC with the transport of BSA that serves as a neutral control. The paper confirms the insights of previous work by the same and other authors - IDP functionalized nanopores are selective in a sense that they conduct the transport proteins well while blocking the passage of BSA. As reported in the paper, the selectivity disappears at large pore diameters which become similar to empty pores because the IDPs don't stretch far enough to cover the pore cross-section.

• The authors use one-bead-per-amino acid coarse grained modeling of the IDPs that they developed and validated previously, to model the distribution of the IDPs in the pores. Combining the simulations with the recently developed "void" model of transport through IDP network and phenomenological transport models, they provide an explanation for the observed reduction in the flux of the neutral control proteins compared to that of transport proteins. The translocation of transport proteins is not modeled directly.

• Together, the experimental and the computational results constitute convincing evidence that points toward the correctness of our current understanding of the physical mechanisms of NPC transport.

• The authors study interference between the transport proteins and the neutral control proteins at high concentrations of the latter, where the pore is occupied by multiple transport proteins. The results appear to be different from previous observations (but more study is needed). I think more discussion of how the results seem with the previous work and what are the potential implication for NPC transport would be welcome.

• The authors use simulations and phenomenological models of transport to analyze the crowded regime. It appears there are some inconsistencies in the application of these models in the dilute and crowded regimes, that should be clarified.

• Some details of the experimental system and the appropriateness of the transport models should be explained more - such as the role of the hydrodynamic pressure gradient.

Reviewer #2 (Public Review):

This paper presents improved, chromosome level assemblies of the hadal snailfish and Tanaka's snailfish. This is an extension and update of previous work from the group on the hadal snailfish genome. The chromosomal assemblies allow comparisons of genome architecture between a shallow water snailfish and the hadal snailfish to aid inference on timing of colonization of trenches and genomic changes that may have been adaptive for that move.

The comparisons in genomic architecture are compelling: genes present in Tanaka's snailfish that are lost in hadal snailfish that involve whole regions of the genome that no longer map even though adjacent regions do map between the species and across a large evolutionary distance to stickleback. Or genes that are duplicated in hadal snailfish but only appear as single copy in other fishes. The paper focuses on genes in the eye, in hearing, in circadian rhythms, and in ROS scavaging. These are all functions that could play a role in adapting to the hadal environment.

The genomic comparisons all seem sound. Stylistically I would prefer if the authors could introduce the gene product and protein function every time they introduce a gene locus. They introduce a gene and general function, but don't usually note what the protein encoded by the gene is and what it's specific function is.

I found the paper generally well written, and the data compelling and creatively displayed. There is room for improvement in places where additional details could be added (e.g. the choice to show expression data as TPMs) and the writing could be clarified.

Reviewer #2 (Public Review):

In the present study, Liu et al present an analysis of benign and HCC liver samples which were subjected to a new technology (LOOP-Seq) and paired WES.  By integrating these data, the authors find isoforms, fusions and mutations which uniquely cluster within HCC samples, such as in the HLA locus, which serve as candidate leads for further investigation.  The main appeal of the study is in the potential of LOOP-Seq as a method to present isoform-resolved data without actually performing long-read sequencing.   While this presents an exciting new method, the current study lacks systematic comparisons with other technologies/data to test the robustness, reproducibility and utility of LOOP-Seq.  Further, this study could be further improved by giving more physiologic context and examples from the analyses, thus providing a new resource to the HCC community.  A few suggestions based on these are below:    

A primary consideration is that this seems to be the first implementation of LOOP-Seq, where the technology, while intriguing, has not been evaluated systematically.  It seems like a standard 10x workflow is performed, where exons are selectively pulled down and amplified.  Subsequent ultra-deep sequencing is assumed to give isoform-resolution of the sc-seq data.  To demonstrate the utility of the approach it would benefit the study to compare the isoform-resolved results with studies where long-read sequencing was actually performed (ex: https://journals.lww.com/hep/Fulltext/2019/09000/Long_Read_RNA_Sequencing_Identifies_Alternative.19.aspx, https://www.jhep-reports.eu/article/S2589-5559(22)00021-0/fulltext,  https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1010342).  Presumably, a fair amount of overlap should occur to justify the usage.  

Related to this point, the sc-seq cell types and benign vs HCC genes should be compared with the wealth of data available for HCC sc-seq  (https://www.nature.com/articles/s41467-022-32283-3, https://www.nature.com/articles/s41598-021-84693-w).  These seem to be important to benchmark the technology in order to demonstrate that the probe-based selection and subsequent amplification does not bias cell type definition and clustering.  In particular, https://www.nature.com/articles/s41586-021-03974-6 seems quite relevant to compare mutational landscapes from the data.<br /> <br /> From the initial UMAP clustering, it will be important to know what the identities are of the cells themselves.  Presumably there is quite a bit of immune cells and hepatocytes, but without giving identities, downstream mechanistic interpretation is difficult.  

In general, there are a fair amount of broad analyses, such as comparisons of hierarchical clustering of cell types, but very little physiologic interpretations of what these results mean.  For example, among the cell clusters from Fig 6, knowing the pathways and cell annotations would help to contextualize these results.  Without more biologically-meaningful aspects to highlight, most of the current appeal for the manuscript is dependent on the robustness of LOOP-seq and its implementation.  

Many of the specific analyses are difficult and the methods are brief.  Especially given that this technology is new and the dataset potentially useful, I would strongly recommend the authors set up a git repository, galaxy notebook or similar to maximize utility and reproducibility 

The authors claim that clustering between benign and HCC samples was improved by including isoform & gene (Suppl fig 8).  This seems like an important conclusion if true, especially to justify the use of long-read implementation.  Given that the combination of isoform + gene presents ~double the number of variables on which to cluster, it would be important to show that the improved separation on UMAP distance is actually due to the isoforms themselves and not just sampling more variables from either gene or isoform

SQANTI implementation to identify fusions relevant for the HCC/benign comparison. How do the fusions compare with those already identified for HCC?  These analyses can be quite messy when performed on WES alone so it seems that having such deep RNA-seq would improve the capacity to see which fused genes are strongly expressed/suppressed.  This doesn't seem as evident from current analysis.  There are quite a bit of WES datasets which could be compared:  https://www.nature.com/articles/ng.3252, https://www.nature.com/articles/s41467-018-03276-y

Figure 4 is fairly unclear.  The matrix graphs showing gene position mutations are tough to interpret and make out.  Usually, gene track views with bars or lollipop graphs can make these results more readily interpretable.  Also, how Figure 4 B infers causal directions from mutations is unclear.

Reviewer #2 (Public Review):

Souaiaia et al. attempt to use sibling phenotype data to infer aspects of genetic architecture affecting the extremes of the trait distribution. They do this by considering deviations from the expected joint distribution of siblings' phenotypes under the standard additive genetic model, which forms their null model. They ascribe excess similarity compared to the null as due to rare variants shared between siblings (which they term 'Mendelian') and excess dissimilarity as due to de-novo variants. While this is a nice idea, there can be many explanations for rejection of their null model, which clouds interpretation of Souaiaia et al.'s empirical results.

The authors present their method as detecting aspects of genetic architecture affecting the extremes of the trait distribution. However, I think it would be better to characterize the method as detecting whether siblings are more or less likely to be aggregated in the extremes of the phenotype distribution than would be predicted under a common variant, additive genetic model.

Exactly how the rareness and penetrance of a genetic variant influence the conditional sibling phenotype distribution at the extremes is not made clear. The contrast between de-novo and 'Mendelian' architectures is somewhat odd since these are highly related phenomena: a 'Mendelian' architecture could be due to a de-novo variant of the previous generation. The fact that these two phenomena are surmised to give opposing signatures in the authors' statistical tests seems suboptimal to me: would it not be better to specify a parameter that characterizes the degree or sharing between siblings of rare factors of large effect? This could be related to the mixture components in the bimodal distribution displayed in Fig 1. In fact, won't the extremes of all phenotypes be influenced by all three types of variants (common, rare, de-novo) to greater or lesser degree? By framing the problem as a hypothesis testing problem, I think the authors are obscuring the fact that the extremes of real phenotypes likely reflect a mixture of causes: common, de-novo, and rare variants (and shared and non-shared environmental factors).

To better enable interpretation of the results of this method, a more comprehensive set of simulations is needed. Factors that may influence the conditional distribution of siblings' phenotypes beyond those considered include: non-normal distribution, assortative mating, shared environment, interactions between genetic and shared environmental factors, and genetic interactions.

In summary, I think this is a promising method that is revealing something interesting about extreme values of phenotypes. Determining exactly what is being revealed is going to take a lot more work, however.

Reviewer #2 (Public Review):

The manuscript points out that TMB cut-offs are not strong predictors of response to immunotherapy or overall survival. By randomly shuffling TMB values within cohorts to simulate a null distribution of log-rank test p-values, they show that under correction, the statistical significance of previously reported TMB cut-offs for predicting outcomes is questionable. There is a clinical need for a better prediction of treatment response than TMB alone can provide. However, no part of the analysis challenges the validity of the well-known pan-cancer correlation between TMB and immunotherapy response. The failure to detect significant TMB cut-offs may be due to insufficient power, as the examined cohorts have relatively low sample sizes. A power analysis would be informative of what cohort sizes are needed to detect small to modest effects of TMB on immune response.

The manuscript provides a simple model of immunogenicity that is tailored to be consistent with a claimed lack of relationship between TMB and response to immunotherapy. Under the model, if each mutation that a tumor has acquired has a relatively high probability of being immunogenic (~10%, they suggest), and if 1-2 immunogenic mutations is enough to induce an immune response, then most tumors produce an immune response, and TMB and response should be uncorrelated except in very low-TMB tumors. The question then becomes whether the response is sufficient to wipe out tumor cells in conjunction with immunotherapy, which is essentially the same question of predicting response that motivated the original analysis. While TMB alone is not an excellent predictor of treatment response, the pan-cancer correlation between TMB and response/survival is highly significant, so the model's only independent prediction is wrong. Additionally, experiments to predict and validate neoepitopes suggest that a much smaller fraction of nonsynonymous mutations produce immune responses1,2.

A key idea that is overlooked in this manuscript is that of survivorship bias: self-evidently, none of the mutations found at the time of sequencing have been immunogenic enough to provoke a response capable of eliminating the tumor. While the authors suggest that immunoediting "is inefficient, allowing tumors to accumulate a high TMB," the alternative explanation fits the neoepitope literature better: most mutations that reach high allele frequency in tumor cells are not immunogenic in typical (or patient-specific) tumor environments. Of course, immunotherapies sometimes succeed in overcoming the evolved immune evasion of tumors. Higher-TMB tumors are likely to continue to have higher mutation rates after sequencing; increased generation of new immunogenic mutations may partially explain their modestly improved responses to therapy.

Reviewer #2 (Public Review):

In their manuscript, Keramidioti and co-authors investigate the cellular architecture of the nervous system in the freshwater polyp Hydra. Specifically, the authors attempt to improve the resolution, which is lacking in the previous studies, yet to generate a comprehensive overview of the entire nervous system's spatial organization and to infer communication between cells. To this end, Keramidioti et al. use state-of-the-art imaging approaches, such as confocal microscopy combined with the use of transgenic animals, transmission electron microscopy, and block face scanning electron microscopy. The authors present three major observations: i) A novel hyCADab antibody may be used to detect the entire nervous system of Hydra; ii) Nerve cells in the ectoderm and in the endoderm are organized in two separate nerve nets, which do not interact; iii) Both nerve nets are composed of bundles of overlapping nerve processes.

The manuscript addresses a long-standing and currently intensively studied question in developmental neurobiology biology - it attempts to reveal structural properties and principles that govern the function of the nervous systems in non-bilaterian animals. Hence, this study contributes to understanding the nervous system evolution trajectories. Therefore, the manuscript may represent interest to researchers interested in evolutionary and developmental neurobiology.

The manuscript reports a remarkably meticulous study and presents stunning imaging results. However, the manuscript would benefit from a more thorough presentation of immunochemical and electron microscopy data. The work would also greatly benefit from a more straightforward presentation of truly novel findings and a more concise summary of already-known aspects.

Major comments:

1) The novelty of findings.<br /> The authors present a lot of findings and illustrate them with numerous very impressive images. However, most observations have been actually reported before, and genuinely novel discoveries are obscured. For instance, the findings on the elongated morphology of the endodermal sensory cell (entire passage starting with "Figure 2B shows..."), qualitative ("Figure 3 shows..."), and quantitative estimation of neuronal densities in the different body compartments of Hydra - all these observations do not provide novel insights. Some co-authors of this manuscript or other authors have previously published all these features. A substantial advance would be performing in vivo experiments, addressing directly, for instance, the question of what is the function of sensory neurons reaching into the gastric cavity. What signals do they detect there? If the authors have access to such functional assays, any additional in vivo experiments will substantially improve the study.

2) The utility of the hyCADab as a pan-neuronal antibody.<br /> Most of the analysis in the manuscript relies on immunostaining of fixed polyps with a novel polyclonal antibody. The authors claim that this antibody recognizes a neuron-specific cadherin protein of Hydra and stains all neurons in the nerve net. However, a brief search in the publicly available resources (such as the Hydra Genome Portal: https://research.nhgri.nih.gov/HydraAEP/) indicates that the gene encoding a protein with a sequence similar to the epitope used by Keramidioti and co-authors is, in fact, not a neuron-specific. It is strongly expressed in nematocytes. Furthermore, the cytoplasmic staining hyCADab is puzzling. Given that the target Cadherin protein is a membrane-associated protein, one would anticipate the immunochemical signal to be localized on the cell's periphery, under the surface.

The authors compare the density of neurons related to epithelial cells detected in whole mounts by the antibody with counts on macerates. Perhaps, a more direct and accurate approach would be to stain macerates with the antibody. In this way, one would be able to identify neurons by their morphology and validate whether 100% of them are hyCADab-positive.

The nGreen strain used by the authors is a mosaic one (see Materials and Methods). Hence, not all neurons are, in fact, labeled by GFP. Therefore, the argument that 51/51 GFP-positive cells are also hyCADab-positive is not convincing and insufficient to claim that hyCADab is a pan-neuronal antibody.

Finally, it is truly surprising that transgenic GFP-positive neurons are, in most cases, hyCADab-negative. (It is particularly evident in Fig. 11B. If the hyCADab antibody is indeed a pan-neuronal one, the red signal in the transgenic neurons should be as high as in the surrounding cells, and the cells would appear yellow).

3) The apparent absence of contact between the ectodermal and endodermal nerve nets.<br /> A central claim of the manuscript is that there are no contacts between the nervous networks in the ectoderm and the endoderm. Therefore, the activities of these networks appear to be not coordinated. In support of these claims, the authors provide images of sections from the polyps' body column (Fig. 4). However, the mesoglea itself is not visible in these images.

Another limitation of the study by Keramidioti and co-authors is that they investigate sections only from the gastric region of a polyp. Earlier studies (for instance, Westfall, 1973) using TEM provided compelling evidence for communication between the ectodermal and endodermal nerve networks via neurites that cross the mesoglea. These neurites traversing mesoglea have been detected specifically in the hypostome of Hydra - the region not thoroughly investigated by Keramidioti et al. It is also surprising that transmesogleal bridges between ectodermal and endodermal epithelial cells, abundantly present not only in the hypostome but in the body column as well, can not be detected on any of the images provided by the authors. This suggests that their approach overall might be in general not suitable for addressing the question of connection and communication between the ectodermal and endodermal structures.

4) Formation of neurite bundles<br /> The most intriguing finding of the study by Keramidioti et al. is that neurites of nerve cells often run parallel to each other, forming conspicuous bundles in both ectodermal and endodermal nerve nets. The formation of such bundles per se is not surprising. It has already been documented by Takahashi-Iwanaga et al.,1994 (this study definitely did not escape the authors' attention) in Hydra's body column. Moreover, neurite bundles have been previously described in the hypostomes of other Hydra species (e.g., Davis et al., 1968; Grimmelikhuijzen, 1985; Yaross et al., 1986) and in other cnidarians (e.g., Mackie 1973, 1989; Garm et al., 2007). Hence, this appears to be a common, universal principle of the nervous system architecture in Cnidaria. I agree with the authors that such an organization of the nerve net is surprising and contrasts the neuronal architecture of most Bilateria. Could these observations, taken together, lead to a view of an alternative design of a nerve system? (a recently published description of the syncytial nerve net in Ctenophora is another revolutionary example of a nervous system architecture). The authors might compare the organization of the Hydra nerve plexus with the architecture of the vertebrate enteric nervous system - where bundles of neurites are also highly abundant, stimulating some thoughts on the evolutionary roots of the peripheral NS.

Another aspect worth discussing in this context is whether the nerve system of Hydra can be organized in any other way. Given the architecture of epithelia in Hydra, there's virtually no other way for the neurites to run other than to form bundles - they occupy the narrow spaces between the epithelial cells and between their muscular fibers. The growth of the neurites thus appears constrained.

Finally, the functional implications of such bundle formation appear extremely interesting. Do neurons really form contacts in these bundles? Unfortunately, the authors provide no evidence for synaptic contacts within the bundles. This is somehow surprising given that numerous studies have effectively localized chemical and electric synapses in Hydra cells (e.g., Westfall et al., 1971). Overlapping of neurites may suggest an alternative, non-synaptic mechanism of signal propagation - via ephaptic coupling. It would be beneficial if the authors provided more TEM data on the presence or absence of synapses between neurites in the body column of Hydra. Some experiments, such as the dye coupling approach, may also help probe the existence of synaptic connections between the neurons forming a bundle.

Reviewer #2 (Public Review):

Voda et al examined the role of multiple co-stimulations on gene expression and chromatin accessibility of T cells. They further linked the roles of co-stimulatory proteins to genetic variants associated with IBD. They reported a shared effect of co-stimulatory proteins on gene expression and chromatin accessibility. In particular they reported the induction of genes associated with lysosome production with alternative co-stimulatory proteins. In linking human genetics to the effect of costimulation, they reported the largest enrichment of IBD risk variants in open chromatin regions shared by all costimulatory molecules.

The question that is being investigated in this manuscript is significant considering the requirement of costimulatory proteins in controlling T cell responses. However, the data presented and analyzes performed remain exploratory and it is not clear how it can advance our understanding of the link between IBD risk association and immune responses. At least one locus ( a target of shared/unique costimulatory molecules) should be selected and mechanistic investigation of the locus, transcription factors involved, and perturbation studies for understanding gene regulation should be performed.

Reviewer #2 (Public Review):

The work presented here by Morgun et al is performed in the context of vaccine development, a field especially active in the context of tuberculosis (TB). The generation of a new vaccine either enhancing or replacing the 100-year-old BCG is urgently needed.

Most subunit vaccines integrate protein antigens formulated with adjuvants and there are few examples on the performance of subunit vaccines integrating lipid antigens. Considering the hydrophobic and lipid nature of the mycobacterial cell envelope studies assessing the suitability of mycobacterial lipids in vaccine formulations may contribute to generate new vaccines to tackle the disease.

The mycobacterial lipid antigens under study are mycolic acids (MA), which are located at the cell wall covalently linked to arabinogalactan. These lipids carry extremely long chain fatty acids of up to 60-90 carbons.

The group has previously shown that formulating MA into micellar nanocarriers and vaccinating mice intranasally it could activate CD1-restricted T cells. However, this formulation did not allow for the incorporation of protein antigens.

This work is novel, and it brings new data of high relevance for the TB vaccine field pointing to alternative formulations and antigens and immune mechanisms.

Authors assay different routes of vaccination but the main results are obtained using non-conventional vaccination routes. Although, it maybe out of the scope of the paper, no protection studies are provided.

Several recommendations are given to improve the quality and the readability of the manuscript.

1. Authors elaborate the introduction solely highlighting the relevance of antigen persistence in the context of vaccination. However, it is well known that several mycobacterial antigens (Lipids and proteins) can cause detrimental responses when overexposed to the immune system. In this regard, it would be appropriate to introduce the possibility of the occurrence of exhaustion when prolonged exposure to antigens is happening, which is the main theme of this paper.

2. Authors need to provide more information about the source of MA. It is briefly mentioned in the materials and methods section that it was obtained from Sigma. If that is the case, it would be ideal to show the integrity of the polysaccharide in term of balance and abundance between different MA species.

3. Building up on the previous comment, MA is a complex mixture of polysaccharides including multiple lengths of fatty acids and modifications. Could the authors comments on the potential variability of MA structure and potential impact on immune responses?

4. How do the authors explain the lack of stimulation of cell proliferation induced by MA-PLGA formulation? Does this result contradict previous findings?

5. Fig 3. Authors switch to IT administration simply arguing against the limitation of IN delivery regarding its low volume. However, administration via IN could be done in an iterative manner. According to this change, this reviewer asks whether the performance of MA-PLGA could now be comparable to BCN-MA using IT instead.

6. What would be the reasons of the no role of encapsulating NP in the persistence of MA?

7. Authors need to discuss to what extent the MA location into AM is route dependent.

8. Also, AM are programmed to sustain low immune responses because of their unique location in the lung. In fact, Mtb uses this to replicate while immune response is mounted. In this regard, accumulation of MA into this compartment may not be relevant for the overall immune response. In other words, what would be the contribution of this population to the T cell activation?

9. Could the T cells responses measured be due to the reduced fraction of DC loaded with BCN-MA at initial time points?

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 regulate the formation of acetate but play 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 to determine 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):

In this manuscript authors make an important contribution to the diversity of mosquito specific viruses, describing the genetic diversity of RNA viruses from the family Culicidae, along an anthropogenic-disturbance gradient in Côte d'Ivoire in 2004.<br /> The manuscript is methodologically rigorous from the virologic perspective; molecular techniques were standardized to perform virus detection, increasing the detection potential from a previous published work by the team from five to 49 viruses (331 viral sequences pertaining to 49 viruses of ten RNA-virus families).<br /> It is rich in terms of the genetic diversity of mosquito specific viruses, but not as strong from the entomological and ecological perspectives. Mosquito specific viruses are analyzed under the lens of pathogens with public health importance, which is confusing.<br /> One of the major information gaps are the potential transmission routes or sources of infection of the detected viruses. Mosquito specific viruses can be transmitted vertically or horizontally, and are in general strongly associated with the environment, but not related with other hosts such as vertebrates. From this perspective, the ecology of transmission of these viruses should not be compared to pathogens that use vertebrate hosts. The authors found 49 viruses, but emphasize the ecological relevance of their findings to five viruses with increased prevalence from pristine to disturbed habitats, to show a dilution effect.<br /> Another suggested important contribution is the finding of an "abundance effect", suggesting that higher prevalence in degraded ecosystems is the result of host abundance, but additional ecological information is missing on the potential mechanisms leading to this effect. Breeding sites may be a main source of variation in species composition and abundances among habitats, but no comments on this are found on the manuscript.<br /> Some additional useful information could be provided to better understand mosquito sampling, for instance: the number of traps used, duration of sampling in each locality, and sampling dates to understand if there could be seasonal variation.<br /> In conclusion the manuscript is interesting and well written. The virologic component is strong, but its relation to the ecological determinants should be improved.

Reviewer #2 (Public Review):

The mitotic spindle of eukaryotic cells is a microtubule-based assembly responsible for chromosome segregation during cell division. For a given cell type, the steady-state size and shape of this structure are remarkably consistent. How this morphologic consistency is achieved, particularly when one considers the complex interplay between dynamic microtubules, spatial and temporal regulation of microtubule nucleation, and the activities of several microtubule-based motor proteins, remains a fundamental unanswered question in cell biology. In this work by Richter et al., the authors use biochemical and biophysical perturbations to explore the feedback between mitotic spindle shape and the dynamics of one of its main structural elements, kinetochore fibers (k-fibers) - bundles of microtubules that extend from kinetochores to spindle poles. Overexpression of the p50 dynactin subunit in mammalian tissue culture cells (Ptk2) was used to inhibit the microtubule motor cytoplasmic dynein resulting in misshapen spindles with unfocused poles. Measurements of k-fiber lengths in control and unfocused conditions showed that although mean k-fiber length was not statistically different, the variation of length was significantly higher in unfocused spindles, suggesting that k-fiber length is set locally, occurring in the absence of focused poles. With a clever combination of live-cell imaging with photoablation and/or photobleaching of fluorescently-labeled k-fibers, the authors went on to explore the mechanistic bases of this length regulation. K-fiber regrowth following ablation occurred in both conditions, albeit more slowly in unfocused spindles. Paired ablation and localized photobleaching on the same k-fiber revealed that microtubule dynamics, specifically those at the plus-end, can be tuned at the level of individual k-fiber. Lastly, the authors show that chromosome segregation is severely impaired when cells with unfocused spindles are forced to enter mitosis. The work's biggest strength is the application of an innovative experimental approach to address thoughtful and well-articulated hypotheses and predictions. Conclusions stemming from the experiments are generally well-supported, though the experiments addressing the "tuning" of k-fiber dynamics could be bolstered by additional data points and perhaps better presented. The manuscript would also benefit from the inclusion of some investigation of spatial differences in the observed effects as well as the molecular and biophysical basis of the observed feedback between k-fiber length and focused poles.

Comments/Concerns/Questions:

1) In the discussion, the authors acknowledge that the changes in spindle morphology resulting from p50 overexpression are likely also causing changes in the well-characterized RanGTP/SAF gradients that radiate from chromosome surfaces. Why did the authors did not include an analysis of k-fiber length as a function of positioning within the spindle? The inclusion of this data would not require more experimentation and could be added as a plot showing K-fiber length versus distance from the geometric center of the spindle (defined by the intersection of the major and minor axes perhaps?).<br /> 2) The authors also acknowledge the established relationship between MT length and MT end dynamics, yet in their ablation studies, the average initial k-fiber length at ablation in control spindles was higher than that for k-fibers in unfocused spindles. It seems that this difference makes the interpretation of the data, particularly the conclusion that fiber growth rates differ due to the absence of focused poles, a bit tenuous. To address this, the authors should consider including plots of grow-back rates versus k-fiber length (again, this should not require additional experiments, just more analysis).<br /> 3) As presented, the data shown in Figure 4 is confusing and does not seem very compelling. The relationship between the kymographs and time series is unclear as is the relationship between the dashed lines in the kymographs and the triangles and the plots in the 4B time series and 4C, respectively. Furthermore, it's not always clear what the triangles are pointing to (e.g. in the unfocused condition time series). The authors might want to consider reworking this figure and providing more measurements of flux following ablation in both the control and unfocused conditions. Lastly, the authors should clarify what negative displacement means.

Reviewer #2 (Public Review):

To provide context into the HIV epidemic in Botswana over the latter half of the 20th century and the beginning of the 21st, the authors have analyzed micro census data to examine patterns of migration. They use this dataset to show how patterns between urban and rural areas have changed over several decades, and the demographic characteristics of migrants. The dataset used for this study is a very reliable source, and the insights in terms of migration patterns are interesting. The primary weakness of the analyses regards the link to HIV transmission: micro-census data only examine mobility that leads to individuals changing residence for longer periods of time, without accounting for shorter-term trips that may also lead to HIV transmission, such as seasonal migration or short trips. This is likely less of an issue with HIV than other diseases, however, due to its transmission often involving new sexual partners, which will generally be less likely to occur during short trips. Broadly, however, this is an interesting report on the migration patterns during a critical period for HIV transmission nationwide.

Reviewer #2 (Public Review):

This paper addresses the specific function of p38γ/p38δ isoforms in inflammation. This was achieved by developing a novel mouse model in which p38γ was replaced by a kinase-inactive mutant (D171A mutation in a p38δ knock out background (p38γ/δKIKO). The results demonstrate that the p38γ/p38δ MAPKs are required for regulating the expression of inflammatory mediators implicated in the innate immune response. The phosphorylation of the transcription factor MEF2D at Ser444 constitutes one potential mechanism by which p38γ/p38δ suppresses iNOS and IL-1β mRNA expression.

The strength of this paper resides in the novelty of the mouse model that permitted to assess the specific requirement of p38γ/p38δ isoforms independently of the loss of TPL2 expression caused by compound deletion of the p38γ/p38δ alleles. The finding that p38γ/p38δ MAPKs inhibit MEF2D activity by phosphorylation at Ser444 is also novel.

One weakness lies in the lack of consistency between the expression profiles performed by RNA-seq/qPCR/cytokine arrays to identify inflammatory mediators whose expression is dependent on p38γ/δ in the two in vivo models of septic shock (i.e. fungal infection and induced by LPS) and in LPS activated macrophages in vitro.

The other issue is that gene expression analyses are performed using bone marrow-derived macrophages (BMDM) (Figs. 3 and 5A), whereas the proteomic analysis employs peritoneal macrophages given that "p38γ and p38δ are expressed at much higher levels in these macrophages than in BMDM (p11)" (Fig. 4). Although the authors state on p11 "Additionally, the LPS-induced cytokine production in peritoneal macrophages was comparable to that of BMDM", only two cytokines were measured, i.e. IL1b and IFNg (SI Appendix Fig. S4B). This really emphasises the importance of verifying that i) MEF2D is indeed a substrate of p38δ in macrophages and ii) p38γ/δ-mediated phosphorylation of MEF2D at Ser444 negatively regulates the expression of iNOS and IL-1β transcripts in macrophages.

Finally, no experiment was performed to demonstrate that the lower fungal burden or increased survival rate following LPS-induced sepsis in p38γ/δKIKO mice (Fig. 1) is a consequence of impaired production of inflammatory mediators by p38γ/δKIKO macrophages. This important issue should be addressed.

Reviewer #2 (Public Review):

The significance of these findings is that the role of B cells in mediating cardiometabolic complications in PCOS is not completely understood. The approach taken by this research group is both innovative and translational. One of the clear strengths of this manuscript is that it combines basic research with clinical studies in PCOS women.

Reviewer #2 (Public Review):

This study explores the variability of cerebellar anatomy in the mammal. By capturing a set of anatomical measures in the cerebellum and including previously reported cerebral and cerebellar metrics in a set of 58 different mammalian species, this study depicts both consistency and heterogeneity in the co-occurrence of different brain features, with a focus on cerebellar structures such as folial wavelength or median depth of the molecular layer. This is very informative as the cerebellum is currently under-explored and the phylogenetic aspect of this work gives insights into evolutionary processes linked to the morphology of the cerebellum.

Strengths:

- The methods used to capture the different brain features are relevant, and include the reuse of previously reported metrics, which makes sense and valorises the previous work of other teams.<br /> - One interesting novel method to detect the depth of the molecular layer is implemented.<br /> - A generous amount of results are reported (including correlations, phylogenetic principal component analyses, ancestor character state estimation, and allometries), with visually effective figures to support them.<br /> - A remarkable effort has been made to make data and code available, which will be of great use to the community.

Weaknesses:

- The methods section does not address all the numerical methods used to make sense of the different brain metrics. In the results section, it sometimes makes it difficult for the reader to understand the reason for a sub-analysis and the interpretation of the numerical findings.<br /> - The originality of the article is not sufficiently brought forward:<br /> a) the novel method to detect the depth of the molecular layer is not contextualized in order to understand the shortcomings of previously-established methods. This prevents the reader from understanding its added value and hinders its potential re-use in further studies.<br /> b) The numerous results reported are not sufficiently addressed in the discussion for the reader to get a full grasp of their implications, hindering the clarity of the overall conclusion of the article.

Reviewer #2 (Public Review):

Root growth is driven by cell elongation, and its local control allows roots to navigate the complex soil environment. Cell growth is driven by the relaxation of the cell wall, a process requiring a drop in pH. Auxin is a key regulator of root development that inhibits root growth. Auxin effects on proton dynamics are complex, it can promote both acidification and alkalinization of the extracellular space through different signaling modules, some only recently uncovered. Serre et al. report on using a new dye to monitor extracellular pH in the region surrounding the Arabidopsis thaliana root. Their manuscript aims to clarify the relationships between pH around the root, proton flux, auxin, cell elongation, and root growth with this tool. They show a typical zonation of pH values along the root: a more acidic domain corresponding to the transit-amplifying compartment, followed by a more alkaline one at the transition and early elongation zones and a more acidic one in the late elongation/root hair zone. This zonation is in agreement with previous reports obtained by other methods. A particularly puzzling aspect is the origin of the more alkaline domain. Serre et al. present evidence supporting the involvement of the AUX1-AFB1-CNGC14 module for the emergence of this more alkaline domain and how it can contribute to the ability of the root to navigate its environment.

Serre et al. show that the more alkaline domain in the transition zone is not directly determined by the activity or localization of the AHA proton pumps but rather by the auxin influx carrier AUX1. They show that the components of the rapid auxin response pathway, in particular, the auxin co-receptor AFB1 and the calcium channel CNGC14, contribute to the emergence of this more alkaline domain. Finally, they show that mutants in these two genes, impaired in the rapid auxin response pathway, show less efficient navigation of the root tip.

The manuscript is clear and well-written. The logic is sound, and the conclusions are supported by the data.

The new dye appears as a promising tool for monitoring the pH in the rhizosphere with advantages over the previous ones. Yet, as pointed out by the authors in the discussion, it reports on pH at the organ scale in the region around the root, not in the apoplast or the cell wall, which can eventually complexify the elaboration of a mechanistic model joining auxin, proton efflux, cell wall properties, cell elongation, and root growth. Although several of the findings confirm previous reports, the manuscript brings novelty by demonstrating the involvement of the rapid auxin response. I am overall supportive of the manuscript. Yet, several points should be addressed:

- The presentation of the more acidic and alkaline domains could be easier to visualize.<br /> - The authors refer to acidic and alkaline domains but do not report on absolute pH values; they monitor the emission ratio of the dye. They justify why to use relative pH value in the discussion and refer there to internal controls that are not clearly defined. In my opinion, the wording should be more consistent across the text and figures and refer to *more* acidic and *more* alkaline domains rather than acidic (pH<7) and alkaline (pH>7) domains.<br /> - The data related to the unaltered distribution of AHA using antibody staining should be backed up.<br /> - The way the pH profile and the statistical analyses should be improved.<br /> - The authors should test the effect of extracellular auxin perception (tmk, abp) mutants on pH zonation.<br /> - Conclusion could be strengthened by moving several pieces of data currently in supplemental material to the main text.

Reviewer #2 (Public Review):

Mitchell and colleagues examined the contribution of a UV-sensitive cone photoreceptor to chromatic detection in Amphiprion ocellaris, a type of anemonefish. First, they used biophysical measurements to characterize the response properties of the retinal receptors, which come in four spectrally-distinct subtypes: UV, M1, M2, and L. They then used these spectral sensitivities to construct a 4-dimensional (tetrahedral) color space in which stimuli with known spectral power distributions can be represented according to the responses they elicit in the four cone types. A novel five-LED display was used to test the fish's ability to detect "chromatic" modulations in this color space against a background of random-intensity, "achromatic" distractors that produce roughly equal relative responses in the four cone types. A subset of stimuli, defined by their high positive UV contrast, were more readily detected than other colors that contained less UV information. A well-established model was used to link calculated receptor responses to behavioral thresholds. This framework also enabled statistical comparisons between models with varying number of cone types contributing to discrimination performance, allowing inferences to be drawn about the dimensionality of color vision in anemonefish.

The authors make a compelling case for how UV light in the anemonefish habitat is likely an important ecological source of information for guiding their behavior. The authors are to be commended for developing an elegant behavioral paradigm to assess visual performance and for incorporating a novel display device especially suited to addressing hypotheses about the role of UV light in color perception. While the data are suggestive of behavioral tetrachromacy in anemonefish, there are some aspects of the study that warrant additional consideration:

1) One challenge faced by many biological imaging systems is longitudinal chromatic aberration (LCA) - that is, the focal power of the system depends on wavelength. In general, focal power increases with decreasing wavelength, such that shorter wavelengths tend to focus in front of longer wavelengths. In the human eye, at least, this focal power changes nonlinearly with wavelength, with the steepest changes occurring in the shorter part of the visible spectrum (Atchison & Smith, 2005). In the fish eye, where the visible spectrum extends to even shorter wavelengths, it seems plausible that a considerable amount of LCA may exist, which could in turn cause UV-enriched stimuli to be more salient (relative to the distractor pixels) due to differences in perceived focus rather than due solely to differences in their respective spectral compositions. Such a mechanism has been proposed by Stubbs & Stubbs (2016) as a means for supporting "color vision" in monochromatic cephalopods (but see Gagnon et al. 2016). It would be worth discussing what is known about the dispersive properties of the crystalline lens in A. ocellaris (or similar species), and whether optical factors could produce sufficient cues in the retinal image that might explain aspects of the behavioral data presented in the current study.

2) The authors provide a quantitative description of anemonefish visual performance within the context of a well-developed receptor-based framework. However, it was less clear to me what inferences (if any) can be drawn from these data about the post-receptoral mechanisms that support tetrachromatic color vision in these organisms. Would specific cone-opponent processes account for instances where behavioral data diverged from predictions generated with the "receptor noise limited" model described in the text? The general reader may benefit from more discussion centered on what is known (or unknown) about the organization of cone-opponent processing in anemonefish and related species.

Reviewer #2 (Public Review):

This manuscript develops a new microfluidic platform to study how the chemotactic response of motile cells varies in relation to its strength. Typically, chemotaxis is assayed using one microfluidic channel at a time, which limits throughput when researchers want to how to resolve how chemotaxis varies with chemoeffector concentration/gradient strength. The authors have automated this process by designing a device that can logarithmically dilute a chemoaffector with a buffer "on chip", simultaneously generating five different chemical gradients in five different channels where the maximum concentration varies by five orders of magnitude (in addition to a control lacking a gradient).

Technically, this is a major feat, requiring the design of a two-layered device, the use of herringbone mixers, and the careful consideration of the hydraulic resistance of each section to ensure that flow splits at junctions in a defined way to achieve the desired dilutions. It is clear the authors had to overcome many challenges before obtaining the final design. The authors have achieved their intended aims and the results from the multiplexed device are consistent with that from lower throughput devices.

Strengths:

- The multiplexed device allows researchers to greatly increase their experimental throughput when mapping out how a microbe responds to chemicals at different concentrations. While such data might be useful in its own right, such a device might make it much easier to quantify how chemotaxis varies in a multidimensional parameter space using multiple runs of this device (e.g. in analyses of fold-change detection where both the background concentration and gradient strength are varied, or in analyses that compare how the sensitivity of a microbe's chemosensory system varies in response to different chemoaffectors). Currently, it is difficult to map out how multiple parameters affect chemotaxis by running only one microfluidic experiment at a time.

- The same exact cell culture can be used in simultaneous experiments. This could potentially dramatically reduce biological variability, as cells obtained from batch cultures often differ in their metabolic state and significant variability is often observed in cultures inoculated on different days. The reduction of such variability is expected to be particularly important for strains that are very difficult/slow to grow in the laboratory or when testing cells obtained directly from environmental/clinical samples.

Weaknesses:

- Given the complexity of the device, it appears difficult to validate that the concentrations within multiplexed are the ones that are expected. It is not clear whether these devices can be used directly "off the shelf" or whether each device would need to be calibrated individually with dye beforehand. In contrast, it is relatively straightforward to serially dilute chemoaffectors manually using pipettors and obtain accurate results. It is not clear whether the on-chip dilution is a distinct advantage or whether it might add additional uncertainty/complexity.

- It is not feasible to track swimming cells in six channels simultaneously, as one cannot automatically move the microscope stage from one channel to another rapidly enough (e.g. the data collected here have 8 seconds between subsequent frames). Thus, multiplexed devices are best suited to measuring independent snapshots of the distribution of track swimming cells, rather than resolving the cellular behaviours that generate chemotaxis. However, tracking the response of slower moving, surface attached cells (e.g. eukaryotes that use ameboid movement on surfaces or bacteria that chemotax using pili) might be feasible if the gradient is maintained with constant flow. This is not explored by the authors, but if feasible it would open up a completely new avenue. Surface-attached cells move ~1000 times slower than swimming cells and experiments last for ~10-15 hours. Thus, using these multiplexed devices with surface-attached cells might facilitate much larger time savings compared to swimming cell assays, which only last for several minutes.

Reviewer #2 (Public Review):

In the current manuscript, the authors select 24 surgically resected pancreatic cancer samples from patients who had a poor outcome (survival of less than one year) or better outcome (survival of at least 3 years). They use a Nanostring Geomx Digital Spatial profiler using a panel of 94 probes. The authors identify a proximal fibroblast population that expresses high levels of PDPN, while a distal fibroblast population expresses high levels of inflammatory genes such as IL6 and IL11, as well as complement genes. Using single-cell RNA sequencing, the authors are able to identify fibroblast populations reflecting those identified in the spatial data and identify other pathways that distinguish the two populations, and that define better or poorer outcomes (for instance, Hif signaling is associated with a poorer prognosis while markers of T cell activation are associated with better prognosis).

The manuscript addresses an important topic, namely whether fibroblasts, a heterogenous and relatively poorly understood cell population within the pancreatic cancer microenvironment, predict poor response. Further, the manuscript integrates spatial and single-cell data, in the quest to identify how the tissue composition of a tumor affects the overall prognosis. Some weaknesses are also noted and should be addressed. Most notably, the prognostic predictions are based on a relatively small number of samples. Further, as spatial transcriptomics is not a single cell-level technology, the authors could use co-immunofluorescence to validate their cell populations and specifically prove that the signatures correspond to genes expressed by fibroblasts, rather than infiltrating immune cells. Finally, the author shows that my-CAF-like fibroblasts correlate with worse prognosis, while inflammatory CAFs predict better prognosis: this finding should be discussed in the context of other CAF literature, some indicating that iCAFs are a negative prognostic predictor.

Reviewer #2 (Public Review):

The study makes a useful contribution by showing that the classical binary discrimination task cannot distinguish different sources of suboptimality (perceptual vs. categorical bias; observation noise vs. approximate inference) in contrast to another task that is more complex (cue combination task). The paper provides the computational framework to define and quantify those sources of suboptimality and report the results of a task in which those different sources are disentangled indeed, in both model fitting and qualitative features of the data.

Strengths:<br /> - A very timely question: How to characterize the sources of suboptimality in (human) perceptual decisions?<br /> - The text is very clear and although the content is technical, the main ideas are conveyed in simple terms and figures, and the detail of mathematical derivations is restricted to the methods section.<br /> - The design of the cue-combination task is very interesting because the posterior distributions over categories predict no difference between the central and matched conditions in the case of perfect inference, but a difference whenever not too many samples are used in approximate inference, making it possible to disentangle different sources of suboptimality in the task.<br /> - The results from the first experiment are followed up by another experiment that includes manipulation of the stimulus duration, which should change the accuracy of approximate inference (and perceptual noise). The results are compatible with those predictions.<br /> - Effects are characterized by model fitting and model comparison, but different models also make qualitatively different predictions, making it possible to adjudicate between models simply by looking at the data (shape of the psychometric curves in different conditions).

Weaknesses:<br /> - There is no parameter recovery analysis based on the generative model in the multi-modal task.<br /> - Several results are not conclusive in most subjects. They are clearly visible only in a few participants and the aggregated data. It is not clear whether this is specific to this dataset (and task design) or whether it is a general conclusion.<br /> - The dataset is reused from a previous study and includes 20 participants. A replication of the result in an independent group of participants would make the result much more robust.<br /> - A replication attempt could use a different task (the current results are based on multi-modal sound localization), which would make the conclusion even more convincing.

Reviewer #2 (Public Review):

The manuscript reports the triploid and haploid productions using an ecs1ecs2 mutant as the maternal donor, in addition to the evaluation of the sexual process observed in the mutant. The indicated data show exquisite quality. To improve the content, I recommend carefully reconsidering the descriptions because some of the insights would cause a stir in the controversy regarding EC1&2 functions in plant reproduction.

Strengths<br /> Triploid production by a combination of ecs1ecs2 mutant and HIPOD system has potential as a future plant breeding tool. Moreover, it's intriguing that both triploid and haploid productions were achieved using the same mutant as a maternal donor. I think authors can claim the value of their results more by adding descriptions about the usefulness of the aneuploid plants in plant breeding history.

The evidence of the persistent synergid nucleus (Figure 3A) is critical insight reported by this study. As Maruyama et al. (2013) reported by live cell imaging, synergid-endosperm fusion had occurred at the two endosperm nuclei stage. It would be valuable to claim the observed fact by citing Maruyama's previous observation.

Weakness<br /> As the authors suggested, the higher triploid frequency observed in ecs1ecs2 than WT was likely caused by the increased polyspermy. However, it also could be that reduction of normal seed number in ecs1ecs2 (whichever is due to failure of fertilization or embryo development arrest) accounts for the increased frequency of the triploid compared to WT.

The results in Figure 3C-E suggested the single fertilization for both egg and central cells at similar frequencies. This is an exciting result, but it is still possible that the fertilized egg or central cell degenerated after fertilization resulting in the disappearance of paternally inherited fluorescence. Evaluation of fertilization patterns at 7-10HAP in ecs1ecs2 mutant may provide more confident insight, although unfused sperm cell was evaluated at 1DAP (Figure 3-figure supplement 1B). The fertilization states can be distinguished depending on the HTR10RFP sperm nuclei morphology and their positions, as reported by Takahashi et al (2018).

Several recent studies have reported exciting insights on ECS1&2 functions; however, various results from different laboratories have raised controversy. Though, the commonly found feature is the repression of polytubey. For readers, it would be helpful to organize the explanation about which insights are concordant or different. In addition, a drawing that explains the time course in the process from pollination to seed development (up to 6DAP) based on WT would help to understand which point is evaluated in each data.

Reviewer #2 (Public Review):

The field of monoclonal antibody therapeutics for the treatment of clinical diseases is undergoing rapid growth in recent years and becoming a dominant force in the therapeutics market. In previous studies, Mone Zaidi's group has reported the development of a first-of-its-kind humanized FSH-blocking antibody, MS-Hu6, based on the established importance of FSH in bone loss, adiposity, and neurodegeneration. This study reports the creation of a unique formulation of highly concentrated MS-HU6 preparation and evaluates detailed physiochemical properties of formulated MS-Hu6 including viscosity, turbidity, and clarity. Furthermore, the structural integrity of the formulated MS-HU6 is confirmed through Circular Dichroism and Fourier Transform Infrared (FTIR). The manuscript is succinctly written, and the methods and results are well described. The authors' conclusions are largely supported by the experimental data. The methods described are highly relevant to the goal of future manufacturing of highly concentrated monoclonal antibody therapeutics for human trials, and, therefore, the study is significant.

Reviewer #2 (Public Review):

De Gieter et al.'s structural report follows a previous screening effort, which identified pLGIC from Alvinella pompejana as suitable for structural studies.<br /> In the present manuscript, the authors report several structures of one homopentamer named Alpo4. The manuscript is organized around a thoughtful, convincing, description of the common points shared by Alpo4 with the mammalian homologues of known structures, and of its distinctive features. The most striking differences are 1. the unexpected presence of a CHAPS detergent molecule bound to the orthosteric site; 2. the unique rotamer switch of a conserved tryptophan in the apo binding pocket, creating what the authors call a 'self-liganded' state; 3. a tightly closed hydrophobic gate with a ring of methionine residues within the M2 helices. 4. A reversed ECD twist associated with the binding of CHAPS

The principal strength of the manuscript is to extend the structural knowledge of the pLGIC family beyond the mammalian receptors to invertebrates, for which structural information has remained scarce. In particular, the binding of CHAPS to an 'extended' binding site is shown. That site does not only comprise the place where neurotransmitter usually binds but is prolonged by a hydrophobic patch underneath loop C and in contact with loop F/beta 8.

In the discussion, the authors suggest that the binding of CHAPS could be an inspiration to develop compounds, targeting for instance mammalian receptors, that would bind to both the orthosteric site and a potential groove underneath loop C (where the sterol moiety of CHAPS binds in Alpo4). A figure (SI4) shows a few homologues in surface representation, giving an idea of whether this groove is generally present in the family. Seeing this figure, I wondered if it would be relevant to compare several conformations of one or a few chosen homologues. Given that gating always impacts the quaternary assembly, is this groove more pronounced in say the inhibited state of a given homologue than in its agonist-bound state?<br /> A related thought was that some of the protein binders affecting pLGIC function (toxins, VHH) contact two subunits and wrap around/below loop C. Do these have binding sites that overlap with the groove?

Very interestingly, the binding of CHAPS stabilizes a conformation that differs from the apo one. It includes a twist of the ECDs but does not lead to a significant opening of the M2 bundle. The authors note that the direction of the twist is reversed to that often associated with the binding of ligands in homologues. This reversion is quite a feature, which deserves to be shown in a supplementary movie (e.g overlay of the Alpo apo>CHAPs transition with the nico>apo transition of a7). My mental framework was that in this family 1. inhibitors do not trigger much of a quaternary conformational change 2. agonists trigger changes always in the same direction (even if the amplitude and exact rotation vary from receptor to receptor). So it's interesting to see a compound (of unknown functional effect) triggering a reversed change.

The principal weakness of the manuscript lies in the absence of a known agonist for Alpo4, The authors do a good job at explaining what they tried and why (and they did perform quite an array of unsuccessful functional experiments), yet it remains frustrating to be unable to link the observed structures to some function.

Reviewer #2 (Public Review):

Geuzebroek and colleagues use computational modeling and EEG to investigate how people adjust continuous decision-making across different contexts. By neurally informing computational models of decision-making, they reject models in which in contexts with weaker sensory evidence a lower decision threshold or greater leak is applied, in favor of a model implementing a novel control mechanism, in which an adjustable sensory criterion determines which samples are considered evidence to be accumulated. This work was rigorously performed and in a compelling manner teases apart competing mechanisms to reveal a significant novel one.

The contributions of this work are at least two-fold: First, the work outlines a novel mechanism by which decision-makers adjust to different environments by taking expectations about sensory evidence into account. Second, they demonstrate how behavior alone can be insufficient to tease apart competing models and lead to misattribution of observed behavioral differences and how neural measures can help arbitrate between models and avoid misattribution.

This work is of great relevance for the decision-neuroscience community, calls for a re-examination of previous findings, and opens exciting new avenues for future research.

Reviewer #2 (Public Review):

Here, a simple model of cerebellar computation is used to study the dependence of task performance on input type: it is demonstrated that task performance and optimal representations are highly dependent on task and stimulus type. This challenges many standard models which use simple random stimuli and concludes that the granular layer is required to provide a sparse representation. This is a useful contribution to our understanding of cerebellar circuits, though, in common with many models of this type, the neural dynamics and circuit architecture are not very specific to the cerebellum, the model includes the feed-forward structure and the high dimension of the granule layer, but little else. This paper has the virtue of including tasks that are more realistic, but by the paper's own admission, the same model can be applied to the electrosensory lateral line lobe and it could, though it is not mentioned in the paper, be applied to the dentate gyrus and large pyramidal cells of CA3. The discussion does not include specific elements related to, for example, the dynamics of the Purkinje cells or the role of Golgi cells, and, in a way, the demonstration that the model can encompass different tasks and stimuli types is an indication of how abstract the model is. Nonetheless, it is useful and interesting to see a generalization of what has become a standard paradigm for discussing cerebellar function.

Reviewer #2 (Public Review):

The manuscript focuses on the cholinergic modulation of TRPM4 channels in the CA1 pyramidal neurons. The authors presented solid convincing evidence that TRPM4 but not TRPC channels are the Ca2+-activated nonselective cation channel in CA1 pyramidal neurons being modulated by activation of muscarinic receptors. Using bi-directional ramp protocol, the authors revealed that ACh modulation could lead to forward shifts in place field center of mass, whereas decreased ACh modulation could contribute to backward shifts. This represents a significant molecular/cellular finding that links neuromodulation of intrinsic properties to place field shifts, a phenomenon seen in vivo. The authors used a computational approach to model this CA1 neuron spiking to further reveal the mechanism.

To further improve the manuscript, I have the following suggestions/questions:<br /> 1. The triangular ramp stimulation (introduced by the same group; Upchurch et al., 2022) makes it possible to emulate the hill-shaped depolarization during place field firing. However, one concern is the time scale/duration of the ramp (2 sec) compared to the physiological pattern (100ms~200ms in the in vivo recording in freely moving rat, Epsztein et al., 2011). Using a longer ramp to generate more spikes for calculating the adaptation index is understandable. However, considering the Ca entry/accumulation during prolonged depolarization, repeating one set of experiments with a shorter ramp is crucial to verify the major findings.

2. Strictly speaking, the term "Ca2+-induced Ca2+ release (CICR)" is only used in ER Ca2+ release via ryanodine receptors (RyR) rather than IP3Rs. The author should be careful since it is used in the abstract (Line 36). In addition, pharmacology inhibition experiments should be incorporated to further dissect the role of RyR-induced CICR.

3. Applying strong buffering BAPTA not only removed the IP3R-TRPM nanodomain but also hindered Ca entry via VGCC. To validate the role of ER Ca2+ release in regulating TRPM, depletion of ER Ca2+ pool with SERCA inhibitor (e.g. thapsigargin) would be a more direct way to test the model (also make sure to add TRPC inhibitor to avoid the store-operated Ca2+ entry).

4. How does the TRPM current overcome the long-term inactivation of Nav? A channel state model should be added to the manuscript to make it easier to understand.

Reviewer #2 (Public Review):

The manuscript by Brunetti et al. represents an important contribution where SARS-CoV-2 infection of T-helper cells is implicated and found to be mediated by CD4. Interestingly and appealingly, the work progressed through a computationally driven hypothesis, by analysing the interaction partners of SARS-CoV-2 spike glycoprotein (as initially modelled through similar SARS-CoV-1), followed by experimental validations, and further computational and experimental insights on the mechanism of binding. I find most of the computational outcomes well validated, and the results and claims well supported by the performed experiments. There are a few points where the manuscript will benefit from dedicated discussion and additional simulation/exploratory plots to establish and validate the adopted methodology for analogous future usage in protein binding characterisations by others.

Major comments:

1) The bioinformatics selection method to arrive at CD4 as the main interaction partner is interesting, and the zoomed-in finding is well justified by the whole body of the experimentation as brought in the manuscript. However, it is interesting from a computational biology perspective that were we to remove GO database (too unvalidated), and "Cell surface" component of the Jensen database (considering its more dedicated "Plasma membrane" and "External side of plasma membrane" components considered in the work) out of the Venn diagram (Extended Data Fig. 3), then we would be left with more interaction partners shared between the remaining 3 databases. Interestingly, these additional partners would include CD8A and CD8B. However, the authors show that the interaction was experimentally noted to happen with CD4+ T cells but not with CD8+ ones. This warrants some discussion on why this might be the case. I wonder what would be the computational docking/MD results were you to attempt modelling an interaction between the spike glycoprotein and CD8? Should you not arrive at stable complexes with your MD workflow and 4 Angstrom cutoff for temperature-induced stability scrutinization, that would be extra validation and weight on the adopted computational scheme for the discovery.

2) Looking at the last complex in Figure 2, where the full-length sCov2 is recovered on top of the modelled fragment, one can see some additional interaction points or potential clashes with CD4 NTD. Were some of the models discarded on the ground of the orientation between CD4 NTD and sCov2 RBD being incompatible with the full-length sCov2 due to possible steric clashes?

3) The 4 Angstrom cutoff for the temperature gradient-based structural stability check sounds reasonable, but would be more justifiable if the authors would also present a histogram of all RMSDs (of final aberrations) for all the tried models and show how outlying the 4 Angstrom is in the whole distribution, additionally attributing a p-value on the selected cutoff.

Reviewer #2 (Public Review):

Diabetes mellitus is a worldwide public health menace, and the fracture healing is usually impaired in diabetic patients. Metformin is the first-line medicine for type-2 diabetes (T2D). However, its effects on bone in T2D patients remain unclear. To assess the impacts of metformin on fracture healing, the authors study the healing process after injuries caused by three different types of bone fractures in diabetic mouse models with or without metformin treatment. The authors studied three fracture models and looked at various aspects of the bone healing process and concluded that metformin rescues the delayed bone healing and remodeling in T2D mice. Moreover, the authors present novel information on the impact of metformin on the bone proliferation, bone formation, and cartilage formation in the bone marrow stromal cells (BMSCs) derived from T2D mice. Administration of metformin in T2D mice can rescue the impaired differentiation potential and lineage commitment of BMSCs both in vitro and in vivo, compromised by the hyperglycemic conditions. In addition, several key chondrocyte transcript factors such as SOX9 and PGC1α, are upregulated in callus tissue isolated at the fracture site of metformin-treated diabetic mice during the healing process after the fracture. In summary, the authors present convincing evidence that metformin facilitates bone healing, bone formation and chondrogenesis in diabetic mice. The prior literature has focused on the effects on mesenchymal stem cells (MSCs) and this paper's data is novel as it's using MKR models for studying Metformin 's role in bone formation under diabetes condition. The paper's conclusions and results are strong, but more attention needs to be paid to the introduction and description of the prior literature and understanding of the potential specific targets and signaling pathway of metformin in the MKR mouse model bone healing.

Reviewer #2 (Public Review):

Dhekne and colleagues present an unbiased genome-wide screen by systematic CRISPR-Cas9 gene knock-out in mouse NIH-3T3 fibroblasts to identify regulators of the LRRK2 pathway which is relevant for Parkinson's disease. The screen identified Rab12 as the most potent regulator of the LRRK2 activity. Phosphorylation of the well-established LRRK2 substrate Rab10 has been used as a read-out. To allow a large-scale screen, the authors established a flow cytometry-based assay using phospho-Rab10-specific antibodies. Subsequently, Rab12 has been confirmed as an upstream effector of LRRK2 acting in a similar way as Rab29. Using computational modelling by Alphafold in conjunction with Colabfold the authors could model the Rab12:LRRK2 complex and identify a third Rab binding site within the N-terminal Armadillo repeats which is distinct from the two sites, previously identified for Rab8a/Rab10 and Rab29. The predicted interaction epitope could be experimentally confirmed by systematic mutational analysis.

The experimental setting and the data presented are overall sound. It should however be considered that the selected cell model is most likely not covering the full set of LRRK2 pathway regulators as these are likely expressed in a tissue and cell-type-specific manner. It could therefore be interesting to also include more disease-relevant models, such as neuronal or immune cells. Nevertheless, Rab12 is an important effector, which is also expressed in cell types relevant to Parkinson's disease.<br /> To validate their computational model of the Rab12 binding epitope within the N-terminal Armadillo domain of LRRK2, the authors determined the binding affinity of Rab12 which is in the lower µM range and similar to the affinities of Rab10 and Rab29 to LRRK2. The authors conducted a mutational screen mutating surface exposed residues within the predicted Rab12 binding epitope in the N-terminus of LRRK2. The study could identify critical residues, which significantly contribute to the affinity of LRRK2 for Rab12. Corresponding alanine mutations could significantly reduce the enhanced LRRK2-mediated Rab10 phosphorylation observed upon Rab12 co-expression. The effect size is similar to the previously identified Rab29 effector. Furthermore, the authors could convincingly demonstrate that Rab12 and Rab29 bind to different LRRK2 epitopes.

Noteworthy, besides disrupting mutations targeting the predicted Rab12 binding epitope, the authors also found one mutation enhancing the cellular effect of Rab12 overexpression demonstrated by increased phospho-Rab10 levels. For a better evaluation of the presented computational model of the Rab12:LRRK2 complex, it would be interesting, if the authors could study the binding affinity of that mutant (F283A), as well.

Overall, the authors could convincingly demonstrate that Rab12, previously identified as LRRK2 substrate, acts upstream of LRRK2 similar to Rab29 but via a distinct binding site. The site located within the N-terminal Ankyrin domain has been predicted by a computational 3D model of the complex structure and experimentally validated. The interaction epitope might be an interesting target for the future development of allosteric modulators to treat LRRK2-mediated PD.

Reviewer #2 (Public Review):

In this manuscript, Castanera et al. investigated how transposable elements (TEs) altered gene expression in rice and how these changes were selected during the domestication of rice. Using GWAS, the authors found many TE polymorphisms in the proximity of genes to be correlated to distinct gene expression patterns between O. sativa ssp. japonica and O. sativa ssp. indica and between two different growing conditions (wet and drought). Thereby, the authors found some evidence of positive selection on some TE polymorphisms that could have contributed to the evolution of the different rice subspecies. These findings are underlined by some examples, which illustrate how changes in the expression of some specific genes could have been advantageous under different conditions. In this work, the authors manage to show that TEs should not be ignored when investigating the domestication of rise as they could have played an important role in contributing to the genetic diversity that was selected. However, this study stops short of identifying causations as the used method, GWAS, can only identify promising correlations. Nevertheless, this study contributes interesting insights into the role TEs played during the evolution of rice and will be of interest to a broader audience interested in the role TEs played during the evolution of plants in general.

Reviewer #2 (Public Review):

In this manuscript, Hoffmann et al. introduce a novel and innovative method to validate and study the mechanism of action of essential genes and novel putative drug targets. In the wake of many functional genomics approaches geared towards identifying novel drug targets or synthetic lethal interactions, there is a dire need for methods that allow scientists to ablate a gene of interest and study its immediate effect in culture or in xenograft models. In general, these genes are lethal, rendering conventional genetic tools such as CRISPR or RNAi inept.

The ARTi system is based on expression of a transgene with an artificial RNAi target site in the 3'-UTR as well as a TET-inducible miR-E-based shRNAi. Using this system, the authors convincingly show that they can target strong oncogenes such as EGFRdel19 or KRasG12 as well as synthetic lethal interactions (STAG1/2) in various human cancer cell lines in vivo and in vitro.

The system is very innovative, likely easy to be established and used by the scientific community and thus very meaningful.

Reviewer #2 (Public Review):

Fuijino et al provide interesting data describing the RNA-binding protein, FUS, for its ability to bind the RNA produced from the hexanucleotide repeat expansion of GGGGCC (G4C2). This binding correlates with reductions in RNA foci formation, the production of toxic dipeptides and concomitant reductions in toxic phenotypes seen in (G4C2)30+ expressing Drosophila. Both FUS and G4C2 repeats of >25 are associated with ALS/FTD spectrum disorders. Thus, these data are important for increasing our understanding of potential interactions between multiple disease genes.

Reviewer #2 (Public Review):

This important work presents an example of a contextual computation in a navigation task through a comparison of task driven RNNs and mouse neuronal data. Authors perform convincing state of the art analyses demonstrating compositional computation with valuable properties for shared and distinct readouts. This work will be of interest to those studying contextual computation and navigation in biological and artificial systems.

This work advances intuitions about recent remapping results. Authors trained RNNs to output spatial position and context given velocity and 1-bit flip-flops. Both of these tasks have been trained separately, but this is the first time to my knowledge that one network was trained to output both context and spatial position. This work is also somewhat similar to previous work where RNNs were trained to perform a contextual variation on the Ready-Set-Go with various input configurations (Remington et al. 2018). Additionally findings in the context of recent motor and brain machine interface tasks are consistent with these findings (Marino et al in prep). In all cases contextual input shifts neural dynamics linearly in state space. This shift results in a compositional organization where spatial position can be consistently decoded across contexts. This organization allows for generalization in new contexts. These findings in conjunction with the present study make a consistent argument that remapping events are the result of some input (contextual or otherwise) that moves the neural state along the remapping dimension.

The strength of this paper is that it tightly links theoretical insights with experimental data, demonstrating the value of running simulations in artificial systems for interpreting emergent properties of biological neuronal networks. For those familiar with RNNs and previous work in this area, these findings may not significantly advance intuitions beyond those developed in previous work. It's still valuable to see this implementation and satisfying demonstration of state of the art methods. The analysis of fixed points in these networks should provide a model for how to reverse engineer and mechanistically understand computation in RNNs.

I'm curious how the results might change or look the same if the network doesn't need to output context information. One prediction might be that the two rings would collapse resulting in completely overlapping maps in either context. I think this has interesting implications about the outputs of the biological system. What information should be maintained for potential readout and what information should be discarded? This is relevant for considering the number of maps in the network. Additionally, I could imagine the authors might reproduce their current findings in another interesting scenario: Train a network on the spatial navigation task without a context output. Fix the weights. Then provide a new contextual input for the network. I'm curious whether the geometric organization would be similar in this case. This would be an interesting scenario because it would show that any random input could translate the ring attractor that maintains spatial position information without degradation. It might not work, but it could be interesting to try!

I was curious and interested in the authors choice to not use activity or weight regularization in their networks. My expectation is that regularization might smooth the ring attractor to remove coding irrelevant fluctuations in neural activity. This might make Supplementary Figure 1 look more similar across model and biological remapping events (Line 74). I think this might also change the way authors describe potential complex and high dimensional remapping events described in Figure 2A.

Overall this is a nice demonstration of state-of-the-art methods to reverse engineer artificial systems to develop insights about biological systems. This work brings together concepts for various tasks and model organisms to provide a satisfying analysis of this remapping data.

Reviewer #2 (Public Review):

The ATPase protein machine cohesin shapes the genome by loop extrusion and holds sister chromatids together by topological entrapment. When executing these functions, cohesin is tightly regulated by multiple cofactors, such as Scc2/Nipbl, Pds5, Wapl, and Eco1/Esco1/2, and it undergoes dynamic conformational changes with ATP binding and hydrolysis. The mechanisms by which cohesin extrudes DNA loops and medicates siter-chromatid cohesion are still not understood. A major reason for the lack of understanding of cohesin dynamics and regulation is the failure to capture the structures of intact cohesin in different nucleotide-bound states and in complex with various regulators. So far only the ATP state cohesin bound to NIPBL and DNA have been experimentally determined.

In this manuscript, Nasmyth et al. made use of the powerful protein structure prediction tool, AlphaFold2 (AF), to predict the models of tens of cohesin subcomplexes from different species. The results provide important insight into how the Smc3-Scc1 DNA exiting gate is opened, how Pds5 and Wapl maintain the opened gate, how Pds5 and Scc3/SA recruit different cofactors, how Eco1 and Sororin antagonize Wapl, and how Scc2/Nipbl interacts with Scc3/SA. The models are for the most part consistent with published mutations in these proteins that affect cohesin's functions in vitro and in vivo and raise testable hypotheses of cohesin dynamics and regulation. This study also serves as an example of how to use AF to build models of protein complexes that involve the docking of flexible regions to globular domains.

Major points<br /> (1) As it stands, the manuscript is simply too long and not readable. The authors should streamline their presentations and remove excessive speculations and models of minor importance.

(2) AF has been accurate in predicting both the fold and sidechain conformations of globular domains. It is less accurate in predicting structural regions with conformational flexibility. Comparisons of predicted and determined structures of large protein complexes have shown considerable differences, particularly with respect to regions lacking tertiary fold. The authors should be more cautious in interpreting some of their models, particularly when the predicted models are inconsistent with determined structures and published biochemical data. For example, human WAPL-C in isolation does not interact with the SA-SCC1 complex while the N-terminal region of WAPL does.

(3) The predicted SA/Scc3-Pds5-Scc1-WaplC quaternary complex is fascinating. Can the authors provide some experimental evidence to support the formation of this quaternary complex or at least the formation of the SA/Scc3-Pds5-WaplC ternary complex? In vitro pulldown or gel filtration can be used to test their predictions.

Reviewer #2 (Public Review):

In this manuscript, González-Segarra et al. investigated how ISNs regulate sugar and water ingestion in Drosophila.

Strengths:

• In their previous paper, authors have shown that inhibiting neurotransmission in ISNs has opposite effects on sugar and water ingestion. In this new manuscript, they investigated the downstream neurons connected to ISNs.

• The authors first identified the effector molecules released by ISNs. Their RNAi screen found that, surprisingly, ISNs use ilp3 as a neuromodulator.

• Next, using light and electron microscopy, they investigated the downstream neural circuits ISNs connect with to regulate water or sugar ingestion. These analyses identified a new group of neurons named Bilateral T-shaped neurons (BiT) as the main output of ISNs, and several other peptidergic neurons as downstream effectors of ISNs. While BiT activity regulated both sugar and water ingestion, BiT downstream neurons, such as CCHa2R, only impacted water ingestion.

• These results suggested that ISNs might interact with distinct neural circuits to control sugar or water ingestion.

• The authors also investigated other ISN downstream neurons, such as ilp2 and CCAP, and revealed that their activity also contributes to ingestive behaviors in flies.

Areas for further development:

• Does BIT inhibit all of the IPCs or some of them? I think it is critical to indicate the ROIs used for each neuron in the methods. Which part of the neuron is used for imaging experiments? Dendrites, cell bodies, or synaptic terminals?

• The discussion section is not giving big picture explanation of how these neurons work together to regulate sugar and water ingestion. Silencing and activation experiments are good, but without showing the innate activity of these neural groups during ingestion, it is not clear what their functions are in terms of regulating fly behavior.

Reviewer #2 (Public Review):

This paper presents an extensive numerical study of microbial evolution using a model of fitness inspired by spin glass physics. It places special emphasis on elucidating the combined effects of microscopic epistasis, which dictates how the fitness effect of a mutation depends on the genetic background on which it occurs, and clonal interference, which describes the proliferation of and competition between multiple strains. Both microscopic epistasis and clonal interference have been observed in microbial evolution experiments, and are chief contributors to the complexity of evolutionary dynamics. Correlations between random mutations and nonlinearities associated with interactions between sub-populations consisting of competing strains make it extremely challenging to make quantitative theoretical predictions for evolutionary dynamics and associated observables such as the mean fitness. While the body of theoretical and computational research on modeling evolutionary dynamics is extensive, most theoretical efforts rely on making simplifications such as the strong selection weak mutation (SSWM) limit, which neglects clonal interference, or assumptions about the distribution of fitness effects that are not experimentally verifiable.

The authors have addressed this challenge by running a numerical microbial evolution experiment over realistic population sizes (~ 100 million cells) and timescales (~ 10,000 generations) using a spin glass model of fitness that considers pairwise interactions between mutations on distinct genetic loci. By independently tuning mutation rate as well as the strength of epistasis, the authors have shown that epistasis generically slows down the growth of fitness trajectories regardless of the amount of clonal interference. On the other hand, in the absence of epistasis, clonal interference speeds up the growth of fitness trajectories, but leaves the growth unchanged in the presence of epistasis. The authors quantitatively characterize these observations using asymptotic power law fits to the mean fitness trajectories. Further, the authors employ more simplified macroscopic models that are informed by their empirical findings, to reveal the mechanistic origins of the epistasis mediated slowing down of fitness growth. Specifically, they show that epistasis leads to a broadening of the distribution of fitness increments, leading to the fixation of a large number of mutations that confer small benefits. Effectively, this leads to an increase in the number of fixed mutations required to climb the fitness peak. This increased number of required beneficial mutations together with the decreasing availability of beneficial mutations at high fitness lead to the slowdown of fitness growth. The authors' data analysis is quite solid and their conclusions are well supported by quantitative macroscopic models. The paper can be strengthened further by conducting a deeper analysis of correlations between mutations, using tools for analyzing dynamical correlations developed in the spin glass literature.

One of the highlights of this paper is the author's astute choice of model, which strikes an impressive balance between complexity, flexibility, and numerical accessibility. In particular, the authors were able to achieve results over realistic population sizes and timescales largely because of the amenability of the model to the implementation of an efficient simulation algorithm. At the same time, the strength of epistasis and clonal interference can be tuned in a facile manner, enabling the authors to map out a phase diagram spanning these two axes. One could argue that the numerical scheme employed here would only work for a specific class of models, and is therefore not generalizable to all models of evolutionary dynamics. While this is likely true, the model is capable of recapitulating several complex aspects of microbial evolution, and is therefore not unduly restrictive.

Spin glass physics has already provided significant insights into a wide range of topics in the life sciences including protein folding, neuroscience, ecology and evolution. The present work carries this approach forward, with immediate implications for microbial evolution, and potential implications in related areas of research such as microbial ecology. In addition to the theoretical value of spin glass physics, the high performance algorithm developed in this work lays the foundation for formulating data driven approaches aimed at understanding evolutionary dynamics. In the future, there is considerable scope for utilizing data generated by such models to train machine learning algorithms for quantifying parameters associated with epistasis, clonal interference, and the distribution of fitness effects in laboratory experiments.

I didn't realize how hard it was to retain information in the earlier times before the internet became a thing. This made me appreciate how much easier our generation has to gather information. I attached a picture of how the stock photo industry is growing and people are no longer traveling all over trying to get in contact with people from different places for information. In 2020 the stock photography market value was at 3.3 billion dollars.

Reviewer #2 (Public Review):

Ibar and colleagues address the role of the spectrin cytoskeleton in the regulation of tissue growth and Hippo signaling in an attempt to elucidate the underlying molecular mechanism(s) and reconcile existing data. Previous reports in the field have suggested three distinct mechanisms by which the Spectrin cytoskeleton regulates Hippo signaling and this is, at least in part, due to the fact that different groups have mainly focused on different spectrins (alpha, beta, or beta-heavy) in previous reports.

The authors start their investigation by trying to reconcile their previous data on the role of Ajuba in the regulation of Hippo signaling via mechanotransduction and previous observations suggesting that Spectrins affect Hippo signaling independently of any effect on myosin levels or Ajuba localization. Contrary to previous reports, the authors reveal that, indeed, depletion of alpha- and beta-heavy-spectrin leads to an increase in myosin levels at the apical membrane. Moreover, the authors also reveal that the depletion of spectrins leads to an increase in Ajuba levels.

Reviewer #2 (Public Review):

This manuscript reports on the use of Optogenetics to influence endothelial barrier integrity by light. Light-induced membrane recruitment of GTPase GEFs is known to stimulate GTPases and modulate cell shape, and here this principle is used to modulate endothelial barrier function. It shows that Rac and CDc42 activating constructs enhance barrier function and do this even when a major junctional adhesion molecule, VE-cadherin, is blocked. Activation of Rac and Cdc42 enhanced lamellipodia formation and cellular overlaps, which could be the basis for the increase in barrier integrity.

The authors aimed at developing a light driven technique with which endothelial barrier integrity can be modulated on the basis of activating certain GTPases. They succeeded in using optogenetic tools that recruit GEF exchange domains to membranes upon light induction in endothelial cell monolayers. Similar tools were in principle known before to modulate cell shape/morphology upon light induction, but were used here for the first time as regulators of endothelial barrier integrity. In this way it was shown that the activation of Cdc42 and Rac can increase barrier integrity even if VE-cadherin, a major adhesion molecule of endothelial junctions, is blocked. Although it was shown before that stimulation of S1P1 receptor or of Tie-2 can enhance endothelial barrier integrity in dependence of Cdc42 or Rac1 and can do this independent of VE-cadherin, the current study shows this with tools directly targeting these GTPases.

Furthermore, this study presents very valuable tools. The immediate and repeatable responses of barrier integrity changes upon light-on and light-off switches are fascinating and impressive. It will be interesting to use these tools in the future in the context of analyzing other mechanisms which also affect endothelial barrier function and modulate the formation of endothelial adherens junctions.

Reviewer #2 (Public Review):

This paper addresses an important computational problem in learning and memory. Why do related memory representations sometimes become more similar to each other (integration) and sometimes more distinct (differentiation)? Classic supervised learning models predict that shared associations should cause memories to integrate, but these models have recently been challenged by empirical data showing that shared associations can sometimes cause differentiation. The authors have previously proposed that unsupervised learning may account for these unintuitive data. Here, they follow up on this idea by actually implementing an unsupervised neural network model that updates the connections between memories based on the amount of coactivity between them. The goal of the authors' paper is to assess whether such a model can account for recent empirical data at odds with supervised learning accounts. For each empirical finding they wish to explain, the authors built a neural network model with a very simple architecture (two inputs layers, one hidden layer, and one output layer) and with prewired stimulus representations and associations. On each trial, a stimulus is presented to the model, and inhibitory oscillations allow competing memories to pop up. Pre-specified u-shaped learning rules are used to update the weights in the model, such that low coactivity leaves model connections unchanged, moderate coactivity weakens connections, and high coactivity strengthens connections. In each of the three models, the authors manipulate stimulus similarity (following Chanales et al), shared vs distinct associations (following Favila et al), or learning strength (a stand in for blocked versus interleaved learning schedule; following Schlichting et al) and evaluate how the model representations evolve over trials.

As a proof of principle, the authors succeed in demonstrating that unsupervised learning with a simple u-shaped rule can produce qualitative results in line with the empirical reports. For instance, they show that pairing two stimuli with a common associate (as in Favila et al) can lead to *differentiation* of the model representations. Demonstrating these effects isn't trivial and a formal modeling framework for doing so is a valuable contribution. Overall, the authors do a good job of both formally describing their model and giving readers a high level sense of how their critical model components work, though there are some places where the robustness of the model to different parameter choices is unclear. In some cases, the authors are very clear about this (e.g. the fast learning rate required to observe differentiation). However, in other instances, the paper would be strengthened by a clearer reporting of the critical parameter ranges. For instance, it's clear from the manipulation of oscillation strength in the model of Schlichting et al that this parameter can dramatically change the direction of the results. The authors do report the oscillation strength parameter values that they used in the other two models, but it is not clear how sensitive these models are to small changes in this value. Similarly, it's not clear whether the 2/6 hidden layer overlap (only explicitly manipulated in the model of Chanales et al) is required for the other two models to work. Finally, though the u-shaped learning rule is essential to this framework, the paper does little formal investigation of this learning rule. It seems obvious that allowing the u-shape to collapse too much toward a horizontal line would reduce the model's ability to account for empirical results, but there may be other more interesting features of the learning rule parameterization that are essential for the model to function properly.

There are a few other points that may limit the model's ability to clearly map onto or make predictions about empirical data. The model(s) seems very keen to integrate and do so more completely than the available empirical data suggest. For instance, there is a complete collapse of representations in half of the simulations in the Chanales et al model and the blocked simulation in the Schlichting et al model also seems to produce nearly complete integration. Even if the Chanales et al paper had observed some modest behavioral attraction effects, this model would seem to over-predict integration. The author's somewhat implicitly acknowledge this when they discuss the difficulty of producing differentiation ("Practical Advice for Getting the Model to Show Differentiation") and not of producing integration, but don't address it head on. Second, the authors choice of strongly prewiring associations in the Chanales and Favila models makes it difficult to think about how their model maps onto experimental contexts where competition is presumably occurring while associations are only weakly learned. In the Chanales et al paper, for example, the object-face associations are not well learned in initial rounds of the color memory test. While the authors do justify their modeling choice and their reasons have merit, the manipulation of AX association strength in the Schlichting et al model also makes it clear that the association strength has a substantial effect on the model output. Given the effect of this manipulation, more clarity around this assumption for the other two models is needed.

Overall, this is strong and clearly described work that is likely to have a positive impact on computational and empirical work in learning and memory. While the authors have written about some of the ideas discussed in this paper previously, a fully implemented and openly available model is a clear advance that will benefit the field. It is not easy to translate a high-level description of a learning rule into a model that actually runs and behaves as expected. The fact that the authors have made all their code available makes it likely that other researchers will extend the model in numerous interesting ways, many of which the authors have discussed and highlighted in their paper.

Reviewer #2 (Public Review):

This study highlights the importance of including not only spatio-termporal scales to biodiversity assessments, but also to include some of the possible drivers of biodiversity loss and to study their joint contribution as environmental stressors.

Introduction - Well written and placed within the current trends of unprecedented biodiversity loss, with an emphasis on freshwater ecosystems. The authors identify three important points as to why biodiversity action plans have failed. Namely, community changes occur over large spatio-temporal scales and monitoring programs capture a fraction of these long-term dynamics (e.g. few decades) which although good at capturing trends in biodiversity change, they often fail at identifying the drivers of these changes. Additionally, most of these rely on manual sorting of samples, overlooking cryptic diversity, or state-of-the-art techniques such as sedimentary DNA (sedaDNA) which allow studying decade-long dynamics, usually focus on specific taxonomic groups unable to represent community-level changes. Secondly, the authors identify that biodiversity is threatened by multiple factors and are rarely studied in tandem. Finally, the authors stress the need for high-throughput approaches to study biodiversity changes since historically, most conservation efforts rely on highly specialized skills for biodiversity monitoring, and even well-studied species have relatively short time series data. The authors identify a model freshwater lake (Lake Ring, Denmark) - suitable due to its well-documented history over the last 100 years - to present a comprehensive framework using metabarcoding, chemical analysis and climatic records for identifying past and current impacts on this ecosystem arising from multiple abiotic environmental stressors.

Results - They are brief and should expand some more. Particularly, there are no results regarding metabarcoding data (number of reads, filtering etc.). These details are important to know the quality of the data which represents the bulk of the analyses. Even the supplementary material gives little information on the metabarcoding results (e.g. number of ASVs - whether every ASV of each family were pooled etc.). The drivers of biodiversity change section could be restructured and include main text tables showing the families positively or negatively correlated with the different variables (akin to table S2 but simplified).

Discussion<br /> The discussion is well written, identifying first some of the possible caveats of this study, particularly regarding the classification of metabarcoding data, its biases and the possible DNA degradation of ancient sediment DNA. The authors discuss how their results fit to general trends showing how agricultural runoff and temperature drive changes in freshwater functional biodiversity primarily due to their synergistic effects on bioavailability, adsorption, etc. The authors highlight the advantage of using a system-level approach rather than focusing on taxa-specific studies due to their indicator status. Similarly, the authors justify the importance of studying community composition as far back as possible since it reveals unexpected patterns of ecosystem resilience. Lake Ring, despite its partially recovered status, has not returned to its semi-pristine levels of biodiversity and community assemblage. Additionally, including enzyme activity allows to assess the functional diversity of the studied environment, although reference databases of these pathways are still lacking. Finally, the authors discuss the implications of their findings under a conservation and land management framework suggesting that by combining these different approaches, drivers of biodiversity stressors can be derived with high accuracy allowing for better-informed mitigation and conservation efforts.

Reviewer #2 (Public Review):

Chen et. al investigated the effects of natural tannins, proanthocyanidins, and punicalagin, against infection by the SARS-CoV-2 virus and its variants. The authors found that these two compounds affect different parts of the SARS-CoV-2 viral infection mechanisms, namely that punicalagin may act ACE2-spike protein interaction and repress Main protease activity, whereas tannic acid and OPC inhibits TMPRSS2 activity. Additionally, the authors show that these tannic compounds can act upon multiple variants of the virus, which suggests a pan-inhibitory effect on SARS-CoV-2 viruses. The studies performed herein present a novel alternative to inhibiting viral infection by SARS-CoV-2 which may be of interest to patients with concerns about reinfection.

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

1) All compounds should be tested in vivo to test not only safety but efficacy and whether these compounds elicit any acute liver toxicity when administered in proposed doses.

2) Efficacy in vaccinated patients would be of great interest, especially since many reinfections occur in the vaccinated population (especially by variants such as Delta).

Reviewer #2 (Public Review):

The molecular mechanisms by which monoaminergic antidepressants exert their therapeutic effects are unknown. An emerging hypothesis in this regard is that these antidepressants work by modulating the glutamatergic system, yet the precise links remain unclear. In this manuscript, Lin et al. describe one such link. First, they observe that the small nucleolar RNA (snoRNA), SNORD90 is consistently elevated following antidepressant treatments in peripheral blood samples, in postmortem brain samples of individuals that received antidepressant treatments, mouse models of depression, and in induced neurons treated with antidepressants in culture. To test whether the elevation of SNORD90 could be significant for antidepressive-like behaviors, the authors perform bilateral injections of viral vectors carrying either SNORD90 or scrambled controls into the mouse cg1/2 and show that overexpression of SNORD90 reduces anxiety and depressive-like behaviors. Using in-silico analysis of base complementarity, the authors predict that the growth factor, neuregulin 3 (NRG3), could be a potential target of SNORD90, and they then validate this prediction by directly showing that SNORD90 overexpression results in the reduction of NRG3 in human neural progenitor cells, whereas knockdown of SNORD90 upregulates NRG3. The authors then show that the binding of SNORD90 to NRG3 pre-mRNA and mature mRNA results in their methylation and subsequent decay. Finally, they show that SNORD90 overexpression in the mouse anterior cingulate cortex is sufficient to increase the levels of glutamatergic neurotransmission.

Overall, the experiments described in the manuscript are well executed and their conclusions are fairly drawn. The observations that SNORD90 overexpression is sufficient to reduce anxiety and depression-like behaviors are indeed exciting, as are the links between SNORD90, and m6A methylation of NRG3, and glutamatergic neurotransmission. There are a few weaknesses in the data and the text, but these should be addressable by the authors.

Reviewer #2 (Public Review):

This work is significant as it provides insights into the global transcriptomic changes of Borrelia burgdorferi during tick feeding. The manuscript also provides methodological advances for the study of the transcriptome of Borrelia burgdorferi in the tick host.

This manuscript documents the study of the transcriptome of Borrelia burgdorferi at 1, 2, 3 and 4 days post-feeding in nymphs of Ixodes scapularis. The authors use antibody-based pull-downs to separate bacteria from tick and mouse cells to perform an enrichment. The data presented support that the transcriptome of B. burgdorferi changes over time in the tick. This work is important as, until now, only limited information on specific genes had been collected. The methodological advances described in this study are valuable for the field.

Reviewer #2 (Public Review):

This paper explores the mechanisms by which cells in tissues use the extracellular matrix (ECM) to reinforce and establish connections. This is a mechanistic and quantitative paper that uses imaging and genetics to establish that the Type IV collagen, DDR-2/collagen receptor discoidin domain receptor 2, signaling through Ras to strengthen an adhesion between two cell types in C. elegans. This connection needs to be strong and robust to withstand the pressure of the numerous eggs that pass through the uterus. The major strengths of this paper are in crisply designed and clear genetic experiments, beautiful imaging, and well supported conclusions. I find very few weaknesses, although, perhaps the evidence that DDR-2 promotes utse-seam linkage through regulation of MMPs could be stronger. This work is impactful because it shows how cells in vivo make and strengthen a connection between tissues through ECM interactions involving collaboration between discoidin and integrin.

Reviewer #2 (Public Review):

Numerous neurodegenerative diseases are thought to be driven by the aggregation of proteins into insoluble filaments known as "amyloids". Despite decades of research, the mechanism by which proteins convert from the soluble to insoluble state is poorly understood. In particular, the initial nucleation step is has proven especially elusive to both experiments and simulation. This is because the critical nucleus is thermodynamically unstable, and therefore, occurs too infrequently to directly observe. Furthermore, after nucleation much faster processes like growth and secondary nucleation dominate the kinetics, which makes it difficult to isolate the effects of the initial nucleation event. In this work Kandola et al. attempt to surmount these obstacles using individual yeast cells as microscopic reaction vessels. The large number of cells, and their small size, provides the statistics to separate the cells into pre- and post-nucleation populations, allowing them to obtain nucleation rates under physiological conditions. By systematically introducing mutations into the amyloid-forming polyglutamine core of huntingtin protein, they deduce the probable structure of the amyloid nucleus. This work shows that, despite the complexity of the cellular environment, the seemingly random effects of mutations can be understood with a relatively simple physical model. Furthermore, their model shows how amyloid nucleation and growth differ in significant ways, which provides testable hypotheses for probing how different steps in the aggregation pathway may lead to neurotoxicity.

In this study Kandola et al. probe the nucleation barrier by observing a bimodal distribution of cells that contain aggregates; the cells containing aggregates have had a stochastic fluctuation allowing the proteins to surmount the barrier, while those without aggregates have yet to have a fluctuation of suitable size. The authors confirm this interpretation with the selective manipulation of the PIN gene, which provides an amyloid template that allows the system to skip the nucleation event.

In simple systems lacking internal degrees of freedom (i.e., colloids or rigid molecules) the nucleation barrier comes from a significant entropic cost that comes from bringing molecules together. In large aggregates this entropic cost is balanced by attractive interactions between the particles, but small clusters are unable to form the extensive network of stabilizing contacts present in the larger aggregates. Therefore, the initial steps in nucleation incur an entropic cost without compensating attractive interactions (this imbalance can be described as a surface tension). When internal degrees of freedom are present, such as the conformational states of a polypeptide chain, there is an additional contribution to the barrier coming from the loss of conformational entropy required to the adopt aggregation-prone state(s). In such systems the clustering and conformational processes do not necessarily coincide, and a major challenge studying nucleation is to separate out these two contributions to the free energy barrier. Surprisingly, Kandola et al. find that the critical nucleus occurs within a single molecule. This means that the largest contribution to the barrier comes from the conformational entropy cost of adopting the beta-sheet state. Once this state is attained, additional molecules can be recruited with a much lower free energy barrier.

There are several caveats that come with this result. First, the height of the nucleation barrier(s) comes from the relative strength of the entropic costs compared to the binding affinities. This balance determines how large a nascent nucleus must grow before it can form interactions comparable to a mature aggregate. In amyloid nuclei the first three beta strands form immature contacts consisting of either side chain or backbone contacts, whereas the fourth strand is the first that is able to form both kinds of contacts (as in a mature fibril). This study used relatively long polypeptides of 60 amino acids. This is greater than the 20-40 amino acids found in amyloid-forming molecules like ABeta or IAPP. As a result, Kandola et al.'s molecules are able to fold enough times to create four beta strands and generate mature contacts intramolecularly. The authors make the plausible claim that these intramolecular folds explain the well-known length threshold (L~35) observed in polyQ diseases. The intramolecular folds reduce the importance of clustering multiple molecules together and increase the importance of the conformational states. Similarly, manipulating the sequence or molecular concentrations will be expected to manipulate the relative magnitude of the binding affinities and the clustering entropy, which will shift the relative heights of the entropic barriers.

The authors make an important point that the structure of the nucleus does not necessarily resemble that of the mature fibril. They find that the critical nucleus has a serpentine structure that is required by the need to form four beta strands to get the first mature contacts. However, this structure comes at a cost because residues in the hairpins cannot form strong backbone or zipper interactions. Mature fibrils offer a beta sheet template that allows incoming molecules to form mature contacts immediately. Thus, it is expected that the role of the serpentine nucleus is to template a more extended beta sheet structure that is found in mature fibrils.

A second caveat of this work is the striking homogeneity of the nucleus structure they describe. This homogeneity is likely to be somewhat illusory. Homopolymers, like polyglutamine, have a discrete translational symmetry, which implies that the hairpins needed to form multiple beta sheets can occur at many places along the sequence. The asparagine residues introduced by the authors place limitations on where the hairpins can occur, and should be expected to increase structural homogeneity. Furthermore, the authors demonstrate that polyglutamine chains close to the minimum length of ~35 will have strict limitations on where the folds must occur in order to attain the required four beta strands.

A novel result of this work is the observation of multiple concentration regimes in the nucleation rate. Specifically, they report a plateau-like regime at intermediate regimes in which the nucleation rate is insensitive to protein concentration. The authors attribute this effect to the "self-poisoning" phenomenon observed in growth of some crystals. This is a valid comparison because the homogeneity observed in NMR and crystallography structures of mature fibrils resemble a one-dimensional crystal. Furthermore, the typical elongation rate of amyloid fibrils (on the order of one molecule per second) is many orders of magnitude slower than the molecular collision rate (by factors of 10^6 or more), implying that the search for the beta-sheet state is very slow. This slow conformational search implies the presence of deep kinetic traps that would be prone to poisoning phenomena. However, the observation of poisoning in nucleation during nucleation is striking, particularly in consideration of the expected disorder and concentration sensitivity of the nucleus. Kandola et al.'s structural model of an ordered, intramolecular nucleus explains why the internal states responsible for poisoning are relevant in nucleation.

To achieve these results the authors used a novel approach involving a systematic series of simple sequences. This is significant because, while individual experiments showed seemingly random behavior, the randomness resolved into clear trends with the systematic approach. These trends provided clues to build a model and guide further experiments.

Reviewer #2 (Public Review):

This is an interesting paper from a reputable group in the field of islet physiology. The authors have provided the results from extensive studies, which will contribute to the knowledge of islet dysfunction and diabetes pathophysiology. One major critique is that the authors studied "the human orthologues of the correlated mouse proteins that are proximal to the glycemia-associated SNPs in human GWAS". This implies two assumptions - (1) human and mouse proteins do not differ in terms of islet physiology and calcium signaling; (2) the proteins proximal to the SNPs are the causal factors for functional differences, though the SNPs could affect protein/gene function distant from the SNPs.

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 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):

This manuscript by Daly et al., probes the emerging paradigm of GPCR signaling from endosomes using the V2R as a model system with an emphasis on Gq/11 and β-arrestins. The study employs cellular imaging, enzyme complementation assays and energy transfer-based sensors to probe the potential formation of GPCR-G-protein-β-arrestin megaplexes. While the study is certainly very interesting, it appears to be very preliminary at many levels, and clearly requires further development in order to make robust conclusions.

1. The use of mini-G-proteins in these experiments is a major concern as these are highly engineered and may not represent the true features of G-proteins. While these have been used as a readout in other publications, their use in demonstrating megaplex formation is sub-optimal, and native, full-length G-proteins should be used.<br /> 2. The interpretation of complementation (NanoLuc) or proximity (BRET) as evidence of signaling not appropriate, especially when overexpression system and engineered constructs are being used.<br /> 3. After the original work from the same corresponding authors on megaplex formation, the major challenge in the field is to demonstrate the existence and relevance of megaplex formation at endogenous levels of components, and the current study focuses solely on showing the proximity of Gq and β-arrestins.<br /> 4. The study lacks a coherent approach, and the assays are often shifted back and forth between the two β-arrestin isoforms (1 and 2), for example, confocal vs. complementation etc.<br /> 5. In every assay, only the G-proteins and β-arrestins are monitored without a direct assessment of the presence of receptor, and absent that data, it is difficult to justify calling these entities megaplexes.

In conclusion, the authors should consider expanding on this work further to make the points more convincingly to make the work solid and impactful. The two corresponding authors are among the leaders in the field having demonstrated the existence of megaplexes, and building on the work in a systematic fashion should certainly move the paradigm forward. As the work presented in the current manuscript is already pre-printed, the authors should take this opportunity to present a completer and more comprehensive story to the field.

Reviewer #2 (Public Review):

Bernou et al use a FACS-based method to sort different cells along the neurogenesis trajectory. They identify cells that are LeX+EGFR+CD24+ which they call i-NBs. The authors suggest these cells proliferate performing neurosphere assays, and that they can make all NSC-derived differentiated cell types through transplantation into mice. They performed microarrays on the different cell subtypes, which led them to their interest in RNA splicing proteins. They additionally performed single-cell analyses to try to identify the cluster of i-NBs compared to other cell types. Further, they performed an irradiation experiment to initiate quiescence exit and depletion of the dividing cell types to create a directionality in the progression through cell types. Comparison with other published sequencing datasets of the same cell type revealed that the i-NBs were most similar to Mitotic TAPs. The authors use their single cell sequencing data to observe expression changes of the RNA splicing factors in different clusters. They also suggest that the i-NB population is heterogeneous in their DCX mRNA levels, with a high group and a low group that have different characteristics. They erroneously use a DCX-Cre-ERT2 line to identify GFP+ or GFP- cells to transplant, and find no GFP+ cells at the end of 5 weeks after transplantation, and draw the conclusion that the high DCX cells don't have the same NSC potential. The authors propose they have identified a new cell type, and that there should be a rewrite of the SVZ neurogenesis cascade to include this population.

Summary of response<br /> This manuscript postulates the identification of a new cell type in the adult neurogenesis cascade. However, all of the author's analyses point to this population of sorted cells being the late mitotic TAPs on their way to becoming neuroblasts. This would suggest that these cells are in the trajectory between TAPs and NBs, so a pivot point, but not a unique cell type in its own. In their sequencing analyses, cell cycle becomes the defining factor of the clustering. Indeed, their cell type as compared to other datasets suggests this population is a mitotic TAP, which is supported by their own transcriptome data (Fig S2) showing that i-NBs are just further in mitosis than the TAPs.

Reviewer #2 (Public Review):

This paper tried to assess the link between genetic and environmental factors on psychotic-like experiences, and the potential mediation through cognitive ability. This study was based on data from the ABCD cohort, including 6,602 children aged 9-10y. The authors report a mediating effect, suggesting that cognitive ability is a key mediating pathway in the link between several genetic and environmental (risk and protective) factors on psychotic-like experiences.

While these findings could be potentially significant, a range of methodological unclarities and ambiguities make it difficult to assess the strength of evidence provided.

Strengths of the methods:

The authors use a wide range of validated (genetic, self- and parent-reported, as well as cognitive) measures in a large dataset with a 2-year follow-up period. The statistical methods have the potential to address key limitations of previous research.

Weaknesses of the methods:

The rationale for the study is not completely clear. Cognitive ability is probably a more likely mediator of traits related to negative symptoms in schizophrenia, rather than positive symptoms (e.g., psychosis, psychotic-like symptom). The suggestion that cognitive ability might lead to psychotic-like symptoms in the general population needs further justification.

Terms are used inconsistently throughout (e.g., cognitive development, cognitive capacity, cognitive intelligence, intelligence, educational attainment...). It is overall not clear what construct exactly the authors investigated.

Not the largest or most recent GWASes were used to generate PGSes.<br /> It is not fully clear how neighbourhood SES was coded (higher or lower values = risk?). The rationale, strengths, and assumptions of the applied methods are not fully clear. It is also not clear how/if variables were combined into latent factors or summed (weighted by what). It is not always clear when genetic and when self-reported ethnicity was used. Some statements might be overly optimistic (e.g., providing unbiased estimates, free even of unmeasured confounding; use of representative data).

It appears that citations and references are not always used correctly.

Strengths of the results:

The authors included a comprehensive array of analyses.

Weaknesses of the results:

Many results, which are presented in the supplemental materials, are not referenced in the main text and are so comprehensive that it can be difficult to match tables to results. Some of the methodological questions make it challenging to assess the strength of the evidence provided in the results.

Appraisal:

The authors suggest that their findings provide evidence for policy reforms (e.g., targeting residential environment, family SES, parenting, and schooling). While this is probably correct, a range of methodological unclarities and ambiguities make it difficult to assess whether the current study provides evidence for that claim.

Impact:

The immediate impact is limited given the short follow-up period (2y), possibly concerns for selection bias and attrition in the data, and some methodological concerns.

Reviewer #2 (Public Review):

The manuscript by Petroccione et al., examines the modulatory role of the neuronal glutamate transporter EAAC1 on glutamatergic and GABAergic synaptic strength at D1- and D2-containing medium spiny neurons within the dorsolateral striatum. They find that pharmacological and genetic disruption of EAAC1 function increases glutamatergic synaptic strength specifically at D1-MSNs. They show that this is due to a structural change in release sites, not release probability. They also show that EAAC1 is critical in maintaining lateral inhibition specifically between D1-MSNs. Taken together, the authors conclude that EAAC1 functions to constrain D1-MSN excitation. Using a computational modeling technique, they posit that EAAC1's modulatory role at glutamatergic and GABAergic inputs onto D1-MSNs ultimately manifests as a reduction of gain of the input-output firing relationship and increases the offset. They go on to show that EAAC1 deletion leads to enhanced switching behavior in a probabilistic operant task. They speculate that this is due to a dysregulated E/I balance at D1-MSNs in the DLS.

Overall, this is a very interesting study focused on an understudied glutamate transporter. Generally, the study is done in a very thorough and methodical manner and the manuscript is well written.

Major Comments/Concerns:<br /> 1. Regional/Local manipulations in behavior study: The manuscript would be greatly improved if they provided data linking the ex vivo electrophysiological findings within the DLS with the behavior. Although they are using a DLS-dependent task, they are nonetheless, using a constitutive EAAC1 KO mouse. Thus, they cannot make a strong conclusion that the behavioral deficits are due to the EAAC1 dysfunction in the DLS (despite the strong expression levels in the DLS).

2. Statistics used in the study: There are some missing details regarding the precise stats using for the different comparisons. I am particularly concerned that the electrophysiology studies that were a priori designed as a 2-factor analysis did not have 2-way ANOVAs performed, but rather a series of t-tests. For example, in Figure 3b, the two factors are 1) cell type and 2) genotype. Was a 2-way ANOVA performed? It is hard for me to tell from the text.

Moderate Concerns:<br /> 3. Control mice: I am moderately concerned that littermates were not used for controls for the EAAC1 KO, but rather C57Bl/6NJ presumably ordered from a vendor. It has been shown that issues like transit and rearing conditions can have long term affects on behavior. Were the control mice reared in house? How long was the acclimation time before use?

4. OCD framework: I generally find the OCD framework unnecessary, particularly in the introduction. Compulsive behaviors are not restricted to OCD. Indeed, the link between the behavioral observations and OCD phenotype seems a bit tenuous. In addition, studying the mechanisms of behavioral flexibility in and of itself is interesting. I don't think such a strong link needs to be made to OCD throughout the entirety of the paper. The authors should consider tempering this language or restricting it to the discussion and end of the abstract.

Reviewer #2 (Public Review):

This paper explores the mechanisms by which cells in tissues use the extracellular matrix (ECM) to reinforce and establish connections. This is a mechanistic and quantitative paper that uses imaging and genetics to establish that the Type IV collagen, DDR-2/collagen receptor discoidin domain receptor 2, signaling through Ras to strengthen an adhesion between two cell types in C. elegans. This connection needs to be strong and robust to withstand the pressure of the numerous eggs that pass through the uterus. The major strengths of this paper are in crisply designed and clear genetic experiments, beautiful imaging, and well supported conclusions. I find very few weaknesses, although, perhaps the evidence that DDR-2 promotes utse-seam linkage through regulation of MMPs could be stronger. This work is impactful because it shows how cells in vivo make and strengthen a connection between tissues through ECM interactions involving collaboration between discoidin and integrin.

Reviewer #2 (Public Review):

Harris et al. have described the cryo-EM structure of PI3K p110gamma in a complex with a nanobody that inhibits the enzyme. This provided the first structure of full-length of PI3Kgamma in the absence of a regulatory subunit. This nanobody is a potent allosteric inhibitor of the enzyme, and might provide a starting point for developing allosteric, isotype-specific inhibitors of the enzyme. One distinct effect of the nanobody is to greatly decrease the dynamics of the enzyme as shown by HDX-MS, which is consistent with a growing body of observations suggesting that for the whole PI3K superfamily, enzyme activators increase enzyme dynamics.

The most remarkable outcome of the study is that upon observing the site of nanobody binding, the authors searched the literature and found that there was a previous report of a PKCbeta phosphorylation of PI3Kgamma in the helical domain that is near the nanobody binding site. This led the authors to re-examine the consequence of the phosphorylation armed with better structural models and the tools to study the effects of this phosphorylation on enzyme dynamics. They found that the site of phosphorylation is buried in the helical domain, suggesting that a large conformational change would have to take place to enable the phosphorylation. HDX-MS showed that phosphorylation at three sites clustered in the helical domain generate a distinctly different conformation with rapid deuterium exchange. This suggests that the phosphorylation locks the enzyme in a more dynamic state. Their enzyme kinetics show that the phosphorylated, dynamic enzyme is activated.

While this phosphorylation was reported before, the authors have provided a mechanism for why this activates the enzyme, and they have shown why binders that stabilise the helical domain (such as binding to the p101 regulatory subunit and the nanobody) prevent the phosphorylation. It is this insight into the dynamics of the PI3Kgamma that will likely be the long-lasting influence of the work.

The paper is well written and the methods are clear.

Reviewer #2 (Public Review):

In recent years, the role of the ECM in synaptic organization has been increasingly studied, leading to a better appreciation of how proteins that comprise the ECM influence synaptic structure and function. How the ECM affects neuronal structure and axonal biology is less well understood, however. Guss and colleagues begin to remedy this by assessing the role of Perlecan in the maintenance of NMJ terminals in the fly. They demonstrate a role for Perlecan in synaptic NMJ stability - loss of Perlecan results in a drastic increase in synaptic retractions. These retractions occur as a result of multiple non-cell-autonomous sources of Perlecan, as neither one tissue RNAi induces phenotypes nor does neuronal cDNA rescue a mutant. They advocate that multiple cellular mechanisms, including Wallerian degeneration and Wnt signaling, are not involved and demonstrate cytoskeletal and functional deficits. They also show that entire nerve bundles degenerate in a coordinated manner, likely due to the disruption of the neural lamella.

This is a strong and thorough genetic analysis of the role of Perlecan in neuronal stability and axonal retraction. The conclusions are largely valid, and the controls and experiments reasonable to answer the stated questions. I have some requests for additional experiments to bolster the existing conclusions.

Reviewer #2 (Public Review):

This manuscript describes an interesting study assessing the impact of acute stress on neural activity and helping behavior in young, healthy men. Strengths of the study include a combination of neuroimaging and psychoneuroendocrine measures, as well as computational modeling of prosocial behavior. Weaknesses include complex, difficult to understand 3-way interactions that the sample size may not be large enough to reliably test. Nonetheless, the study and results provide useful information for researchers seeking to better understand the influence of stress on the neural bases of complex behavior.

The stressor was effective at eliciting physiological and psychological stress responses as shown in Figure 2.

Higher perceived stress in more selfish participants (lower social value orientation (SVO) angle) was associated with lower prosocial responding (Figure 4). How can we reconcile this finding with the finding (presented on page 15) that those with a more prosocial SVO showed a significant decline in dACC activation to subjective value at increasing levels of perceived stress? This seems contrary to the behavioral response.

A larger issue with the study is that the power analysis presented on page 23 is based on a 2 (between: stress v. control) by 2 (within: self v. other) design. Most of the reported findings come from analyses of 3-way interactions. How can the readers have confidence in the reliability of results from 3-way interaction analyses, which were not powered to detect such effects?

Reviewer #2 (Public Review):

This paper describes the results of a set of complementary and convergent experiments aimed at describing roles for the non-selective cation channels NALCN and TRPC6 in mediating subthreshold inward depolarizing currents and action potential generation in VTA DA neurons under normal physiological conditions. That said, some datasets are underpowered, and general flaws in statistical reporting make assessment difficult. There is also a lack of clarity at various points throughout the manuscript, as well as overinterpretation of the data generated in these experiments. Specific comments follow:

1. These results do not show that TRPC6 mediates stress effects on depression-like behavior. As stated by the authors in the first sentence of the final paragraph, "downregulation of TRPC6 proteins was correlated with reduced firing activity of the VTA DA neurons, the depression-like behaviors, and that knocking down of TRPC6 in the VTA DA neurons confer the mice with depression behaviors." Therefore, the results show associations between TRPC6 downregulation and stress effects on behavior, occlusion of the effects of one by the other on some outcome measures, and cell manipulation effects that resemble stress effects. There is no experiment that shows reversal of stress effects with cell/circuit-specific TRPC6 manipulations. Please adjust the title, abstract and interpretation accordingly.<br /> 2. Statistical tests and results are unclear throughout. For all analyses, please report specific tests used, factors/groups, test statistic and p-value for all data analyses reported. In some cases, the chosen test is not appropriate. For example, in Figure 6E, it is not clear how an experiment with 2 factors (stress and drug) can be analyzed with a 1-way RM ANOVA. The potential impact of inappropriate statistical tests on results makes it difficult to assess the accuracy of data interpretation.<br /> 3. Why were only male mice used? Please justify and discuss in the manuscript. Also, change the title to reflect this.<br /> 4. Number of recorded cells is very low in Figure 1. Where in VTA did recordings occur? Given the heterogeneity in this brain region, this n may be insufficient. Additional information (e.g., location within VTA, criteria used to identify neurons) should be included. Report the number of mice (i.e., n = 6 cells from X mice) in all figures.<br /> 5. Authors refer to VTA DA neurons as those that are DAT+ in line 276, although TH expression is considered the standard of DAergic identity, and studies (e.g., Lammel et al, 2008) have shown that a subset of VTA DA neurons have low levels of DAT expression. Authors should reword/clarify that these are DAT-expressing VTA DA neurons.<br /> 6. Neuronal subtype proportions should be quantified and reported (Fig. 1Aii).<br /> 7. In addition to reporting projection specificity of neurons expressing specific channels, it would be ideal to report these data according to spatial location in VTA.<br /> 8. The authors state that there are a small number of Glut neurons in VTA, then they state that a "significant proportion" of VTA neurons are glutamatergic.<br /> 9. It is an overstatement that VTA DA neurons are the key determinant of abnormal behaviors in affective disorders.

Reviewer #2 (Public Review):

In this study, Li et al. examined the involvement of astrocyte-like glia in responding to traumatic brain injury in Drosophila. Using a previously-established method that induces high-impact, whole-body trauma to flies (HIT device), the authors observed increased blood-brain-barrier permeabilization, neuronal cell death, and hypertrophy of astrocyte-like cells in the fly brain following injury. The authors provide compelling evidence implicating a signaling pathway involving the PDGF/VEGF-like Pvr receptor tyrosine kinase, the AP-1 transcription factor, and the matrix metalloprotease Mmp1 in the astrocytic cell response to TBI. The authors' data was generally high-quality data and combined multiple experimental approaches (microscopy, RNA sequencing, and transgenic), increasing the rigor of the study. The identification of injury-induced gene expression changes in astrocytic cells helps increase our limited understanding of roles this glial subtype plays in the adult fly brain. Limitations of the study include a reliance on RNAi-mediated gene silencing without validation via genetic mutants and a limited examination of how astrocyte-like and ensheathing glia could interact following TBI, especially given that several genes identified in this study are known to mediate ensheathing glial responses to axotomy. The conclusions are generally well-supported by the presented data, however some further clarification of quantitative methods and analyses will help to strengthen the findings:

1. The significance and quantification method for the astrocytic cell body sizes in Fig. 2C, D and appearance of GFP+ accumulations in Fig. 2F should be better defined - how were cell bodies and GFP+ puncta identified relative to other astrocytic cell structures, are they homogeneous in size/intensity in different brain regions following injury, and what could the GFP+ puncta represent?<br /> 2. The relative contributions of astrocyte-like and ensheathing glia in the brain's response to TBI is unclear. RNA sequencing identified Mmp1 and Draper as genes upregulated following TBI, however, these genes have previously been implicated in ensheathing glial (and not astrocytic) responses to acute nerve injury. The authors provide convincing evidence that their transcriptomic data is devoid of neuronal genes, but what about the possibility of ensheathing glial contaminants? Figures 2I-Q suggest that the majority of Mmp1 protein co-localizes with ensheathing rather than astrocytic glial membranes following TBI. Does knockdown of Pvr, Jra, or kay in ensheathing glia affect Mmp1 upregulation following injury? A closer examination of how these two glial subtypes contribute to and interact-and what proportion of Mmp1 is cell autonomous to astrocytes-during injury responses would be valuable.<br /> 3. The authors rely on RNAi and overexpression methods to manipulate expression of candidate genes in Figures 4, 5, and 7. In most cases, only a single RNAi line is used to reduce expression of a candidate gene, increasing the possibilities of off-target effects or insufficient gene knockdown. These data could be strengthened by using multiple RNAi lines as well as mutants to validate findings for Pvr, Jra, and kay knockdown in Figures 4 and 5, and perhaps confirmation of knockdown efficiency, particularly in Fig. 7.<br /> 4. Single channel images should be included in Fig. 1L and M to help strengthen the conclusion that Dcp-1+ puncta are elav+ and repo-.<br /> 5. Sample sizes and a description of power analysis should be included in figure legends/methods. Based on the graphs, some sample sizes appear low (e.g., Fig. 1H+K and 2D+Q).