Reviewer #1 (Public Review):

Summary:

In their article, the authors delve into the therapeutic potential of a newly identified liver-specific lncRNA, FincoR, regulated by the Farnesoid X Receptor (FXR) and induced by the agonist tropifexor, in treating nonalcoholic steatohepatitis (NASH). They demonstrate that FincoR significantly enhances tropifexor's effectiveness in reducing liver fibrosis and inflammation in NASH, presenting it as a promising therapeutic target. The manuscript revisions broaden the study to include both mouse and human data, showing elevated FincoR levels in various mouse models of liver disease and identifying a similar lncRNA in humans, potentially indicating a conserved therapeutic mechanism. This research offers valuable insights into FincoR's role in NASH and suggests further exploration into its functions and mechanisms in liver disease treatment.

Strengths:

This study enhances our understanding of FincoR, a liver-specific lncRNA, and its therapeutic potential in treating NASH through a multifaceted research approach. The revised manuscript further strengthens this contribution by incorporating additional experiments and human relevance, summarized as follows: 1) The use of GRO-seq and RNA-seq technologies has provided an in-depth and unbiased view of the transcriptional alterations driven by the FXR agonist tropifexor, especially emphasizing FincoR's pivotal role. 2) The research expands on the original findings by including diverse mouse models of NAFLD/NASH and cholestatic liver injury. These models demonstrate significant increases in hepatic FincoR levels across various conditions, such as diets high in fat and fructose, chemical induction of liver cholestasis with ANIT, and surgical induction via bile duct ligation. This broadened scope underscores FincoR's involvement in liver disease mechanisms beyond the initial models of FXR knockout (KO) and FincoR liver-specific knockdown (FincoR-LKD). 3) Incorporation of tropifexor, an FDA-approved FXR agonist, alongside these experimental models bridges experimental findings to potential therapeutic applications for NASH patients. 2) The manuscript revision includes promising data on the sequence similarity between mouse FincoR and a human locus, identifying a partially conserved human lncRNA (XR_007061585.1) with elevated levels in NAFLD and PBC patients. This addition enhances the study's relevance to human health. 3) The study's design, with the inclusion of both negative and positive controls and now enriched with a wider array of mouse models and human data, ensures that the observed therapeutic effects can be confidently attributed to FincoR's modulation by tropifexor.

Weaknesses:

The authors acknowledge that certain questions remain unanswered within the scope of this study on FincoR, due to feasibility and technical challenges. While it's important to note that such limitations are rooted in the practical and technical complexities, these unresolved issues might limit the study's immediate impact. The decision to focus on the discovery and initial characterization of FincoR, is strategically but not scientifically justified.

Reviewer #3 (Public Review):

Summary:

In their paper Li et al. investigate the transcriptome of satellite cells obtained from different muscle types including hindlimb, diaphragm and extraocular muscles (EOM) from wild type and G93A transgenic mice (end stage ALS) in order to identify potential factors involved in the maintenance of the neuromuscular junction. The underlying hypothesis being that since EOMs are largely spared from this debilitating disease, they may secrete NMJ-protective factors. The results of their transcriptome analysis identified several axon guidance molecules including the chemokine Cxcl12, which are particularly enriched in EOM-derived satellite cells. Transduction of hindlimb-derived satellite cells with AAV encoding Cxcl12 reverted hindlimb-derived myotubes from the G93A mice into myotubes sharing phenotypic characteristics similar to those of EOM-derived satellite cells. Additionally, the authors were able to demonstrate that EOM-derived satellite cell myotube cultures are capable of enhancing axon extensions and innervation in co-culture experiments.

Strengths:

The strength of the paper is that the authors successfully isolated and purified different populations of satellite cells, compared their transcriptomes, identified specific factors release by EOM-derived satellite cells, overexpressed one of these factors (the chemokine Cxcl12) by AAV-mediated transduction of hindlimb-derived satellite cells. The transduced cells were then able to support axon guidance and NMJ integrity. They also show that administration of Na butyrate to mice decreased NMJ denervation and satellite cell-depletion of hind limbs. Furthermore, addition of Na Butyrate to hindlimb derived satellite cell myotube cultures increased Cxcl12 expression. These are impressive results providing important insights for the development of therapeutic targets to slow the loss on neuromuscular function characterizing ALS.

Weaknesses:

Several important aspects have not been addressed by the authors, these include the following points which weaken the conclusions and interpretation of the results.<br /> (a) Na Butyrate was shown to extend the survival of G93A mice by Zhang et al. Na butyrate has a variety of biological effects. For example, anti-inflammatory effects, inhibits mitochondrial oxidative stress, positively influences mitochondrial function, is a class I / II HDAC inhibitor etc. What is the mechanism underlying its beneficial effects both in the context of mouse muscle function in the ALS G93A mice and in the in vitro myotube assay? Cytokine quantification as well as histone acetylation/methylation can be assessed experimentally and this is an important point that has not been appropriately investigated.<br /> (b) In the context of satellite cell characterization, on line 151-152 the authors state that soleus muscles were excluded from further studies since they have a higher content of slow twitch fibers and are more similar to diaphragm. This justification is not valid in the context of ALS as well as many other muscle disorders. Indeed, soleus and diaphragm muscles contain a high proportion of slow twitch fibers (up to 80% and 50% respectively) but soleus muscles are more spared than diaphragm muscles. What makes soleus muscles (and EOMs) more resistant to ALS NMJ injury? Satellite cells from soleus muscles need to be characterized in detail as well.<br /> Furthermore, EOMs are complex muscles, containing many types of fibers and expressing different myosin heavy chain isoforms and muscle proteins. The fact that in mouse both the globular layer and orbital layers of EOMs express slow myosin heavy chain isoform as well as myosin heavy chain 2X, 2A and 2B (Zhou et al., 2010 IOVIS 51:6355-6363) also indicates that the sparing is not directly linked to the fast or slow twitch nature of the muscle fiber. This needs to be considered.<br /> (c) In the context of myotube formation from cultured satellite cells on line 178-179 the authors stained the myotubes for myosin heavy chain. Because of the diversity of myosin heavy chain isoforms and different muscle origin of the satellite cells investigated, the isoform of myosin heavy chain expressed by the myotubes needs to be tested and described. It is not sufficient to state anti-MYH.<br /> (d) The original RNAseq results have not been deposited and while it is true that the authors have analyzed the results and described them in Figures 6 and 7 and relative supplements, the original data needs to be shown both as an xls list as a Volcano plots (q value versus log2 fold change). This will facilitate the independent interpretation of the results by the readers as some transcripts may not be listed. As presented it is rather difficult to identify which transcripts aside Cxcl12 are commonly upregulated. Can the data be presented in a more visual way?<br /> (e) There is no section describing the statistical analysis methods used. In many figures more than 2 groups are compared so the authors need to use an ANOVA followed by a post hoc test.

The authors have achieved their aim in showing that satellite cells derived from EOMs have a distinct transcriptome and that this may be the basis of their sparing in ALS. Furthermore, this work may help develop future therapeutic interventions for patients with ALS.

Reviewer #1 (Public Review):

Summary:

In this manuscript, the authors set up a pipeline to predict insect repellents that are pleasant and safe for humans. This is done by daisy-chaining a new classification model based on predicting repellents with a published model on predicting human perception. Models use a feature-engineered selection of chemical features to make their predictions. The predicted molecules are then validated against a proxy humanoid (heated brick) and its safety is tested by molecular assays of human cells. The humanistic approach to modeling these authors have taken (which considers cosmetic/aesthetic appeal and safety) is novel and a necessary step for consumer usage. However, the importance of pleasantness over effectiveness is still up for debate (DEET is unpleasant but still used often) and the generalization of safety tests is unknown and assumed. The effectiveness of the prediction models is also still warranted. They pass the authors' own behavioral tests, but their contribution to the field is unknown as both models (new and published) have not been rigorously benchmarked to previous models. Moreover, the author's breadth of literature in this field is sparse, ignoring directly related studies.

Strengths:

Humanistic approach to modeling considers pleasantness and safety. Chaining models can help limit the candidate odorants from the vastness of odor space.

Weaknesses:

The current models need to be bench-marked against leading models predicting similar outcomes. Similarly, many of these papers need to be addressed and discussed in the introduction. The authors might even consider their data sources for model training to increase performance and lexical categorization for interoperability. For instance, the Dravnikes data lexicon, currently used in the human perception lexicon, has been highly criticized for its overlapping and hard-to-interpret descriptive terms ("FRAGRANT", "AROMATIC").

Human Perception

Khan, R. M., Luk, C. H., Flinker, A., Aggarwal, A., Lapid, H., Haddad, R., & Sobel, N. (2007). Predicting odor pleasantness from odorant structure: pleasantness as a reflection of the physical world. Journal of Neuroscience, 27(37), 10015-10023.

Keller, A., Gerkin, R. C., Guan, Y., Dhurandhar, A., Turu, G., Szalai, B., ... & Meyer, P. (2017). Predicting human olfactory perception from chemical features of odor molecules. Science, 355(6327), 820-826.

Gutiérrez, E. D., Dhurandhar, A., Keller, A., Meyer, P., & Cecchi, G. A. (2018). Predicting natural language descriptions of mono-molecular odorants. Nature communications, 9(1), 4979.

Lee, B. K., Mayhew, E. J., Sanchez-Lengeling, B., Wei, J. N., Qian, W. W., Little, K. A., ... & Wiltschko, A. B. (2023). A principal odor map unifies diverse tasks in olfactory perception. Science, 381(6661), 999-1006.<br /> Related cleaned data: https://github.com/BioMachineLearning/openpom

Insect Repellents:

Wright, R. H. (1956). Physical basis of insect repellency. Nature, 178(4534), 638-638.

Katritzky, A. R., Wang, Z., Slavov, S., Tsikolia, M., Dobchev, D., Akhmedov, N. G., ... & Linthicum, K. J. (2008). Synthesis and bioassay of improved mosquito repellents predicted from chemical structure. Proceedings of the National Academy of Sciences, 105(21), 7359-7364.

Bernier, U. R., & Tsikolia, M. (2011). Development of Novel Repellents Using Structure− Activity Modeling of Compounds in the USDA Archival Database. In Recent Developments in Invertebrate Repellents (pp. 21-46). American Chemical Society.

Wei, J. N., Vlot, M., Sanchez-Lengeling, B., Lee, B. K., Berning, L., Vos, M. W., ... & Dechering, K. J. (2022). A deep learning and digital archaeology approach for mosquito repellent discovery. bioRxiv, 2022-09.

The current study assumes that insect repellents repel via their odor valence to the insect, but this is not accurate. Insect repellents also mask the body odor of humans making them hard to locate. The authors need to consult the literature to understand the localization and landing mechanisms of insects to their hosts. Here, they will understand that heat alone is not the attractant as their behavioral assay would have you believe. I suggest the authors test other behaviour assays to show more convincing evidence of effectiveness. See the following studies:

De Obaldia, M. E., Morita, T., Dedmon, L. C., Boehmler, D. J., Jiang, C. S., Zeledon, E. V., ... & Vosshall, L. B. (2022). Differential mosquito attraction to humans is associated with skin-derived carboxylic acid levels. Cell, 185(22), 4099-4116.

McBride, C. S., Baier, F., Omondi, A. B., Spitzer, S. A., Lutomiah, J., Sang, R., ... & Vosshall, L. B. (2014). Evolution of mosquito preference for humans linked to an odorant receptor. Nature, 515(7526), 222-227.

Wei, J. N., Vlot, M., Sanchez-Lengeling, B., Lee, B. K., Berning, L., Vos, M. W., ... & Dechering, K. J. (2022). A deep learning and digital archaeology approach for mosquito repellent discovery. bioRxiv, 2022-09.

Reviewer #1 (Public Review):

Summary:

In this report, the authors investigated the effects of reproductive secretions on sperm function in mice. The authors attempt to weave together an interesting mechanism whereby a testosterone-dependent shift in metabolic flux patterns in the seminal vesicle epithelium supports fatty acid synthesis, which they suggest is an essential component of seminal plasma that modulates sperm function by supporting linear motility patterns.

Strengths:

The topic is interesting and of general interest to the field. The study employs an impressive array of approaches to explore the relationship between mouse endocrine physiology and sperm function mediated by seminal components from various glandular secretions of the male reproductive tract.

Weaknesses:

Unfortunately, support for the proposed mechanism is not convincingly supported by the data, and the experimental design and methodology need more rigor and details, and the presence of numerous (uncontrolled) confounding variables in almost every experimental group significantly reduce confidence in the overall conclusions of the study.

The methodological detail as described is insufficient to support replication of the work. Many of the statistical analyses are not appropriate for the apparent designs (e.g. t-tests without corrections for multiple comparisons). This is important because the notion that different seminal secretions will affect sperm function would likely have a different conclusion if the correct controls were selected for post hoc comparison. In addition, the HTF condition was not adjusted to match the protein concentrations of the secretion-containing media, likely resulting in viscosity differences as a major confounding factor on sperm motility patterns.

There is ambiguity in many of the measurements due to the lack of normalization (e.g. all Seahorse Analyzer measurements are unnormalized, making cell mass and uniformity a major confounder in these measurements). This would be less of a concern if basal respiration rates were consistently similar across conditions and there were sufficient independent samples, but this was not the case in most of the experiments.

The observation that oleic acid is physiologically relevant to sperm function is not strongly supported. The cellular uptake of 10-100uM labeled oleic acid is presumably due to the detergent effects of the oleic acid, and the authors only show functional data for nM concentrations of exogenous oleic acid. In addition, the effect sizes in the supporting data were not large enough to provide a high degree of confidence given the small sample sizes and ambiguity of the design regarding the number of biological and technical replicates in the extracellular flux analysis experiments.

Overall, the most confident conclusion of the study was that testosterone affects the distribution of metabolic fluxes in a cultured human seminal vesicle epithelial cell line, although the physiological relevance of this observation is not clear.

In the introduction, the authors suggest that their analyses "reveal the pathways by which seminal vesicles synthesize seminal plasma, ensure sperm fertility, and provide new therapeutic and preventive strategies for male infertility." These conclusions need stronger or more complete data to support them.

Reviewer #1 (Public Review):

The manuscript investigates the role of membrane contact sites (MCSs) and sphingolipid metabolism in regulating vacuolar morphology in the yeast Saccharomyces cerevisiae. The authors show that tricalbin (1-3) deletion leads to vacuolar fragmentation and the accumulation of the sphingolipid phytosphingosine (PHS). They propose that PHS triggers vacuole division through MCSs and the nuclear-vacuolar junction (NVJ). The study presents some solid data and proposes potential mechanisms underlying vacuolar fragmentation driven by this pathway. Although the manuscript is clear in what the data indicates and what is more hypothetical, the story would benefit from providing more conclusive evidence to support these hypothesis. Overall, the study provides valuable insights into the connection between MCSs, lipid metabolism, and vacuole dynamics.

Reviewer #1 (Public Review):

The authors investigate the alpha chain t cell receptor landscape in conventional vs regulatory CD4 T cells. Overall I think it is a very well thought out and executed study with interesting conclusions. Findings are valuable and are supported by convincing evidence. This work will be of interest for immunologists studying T cells.

Strengths:

- One of a kind evidence and dataset.

- State of the art analyses using well accepted in the literature tools.

- Interesting conclusions on the breadth of immune response to challenges across different types of challenges (tumor, viral and parasitic).

Reviewer #1 (Public Review):

In this manuscript, Shimonty and colleagues study the effects of FNDC5/irisin deletion on osteocytes in a sex-specific manner using models of lactation induced bone loss and bone loss due to low calcium diet (LCD). Consistent with the previous findings of Kim et al. (2018), the authors report 'protective' effects of irisin deficiency in lactating female FNDC5-null mice due to reduced osteocytic osteolysis. Interestingly, FNDC5 null mice show distinct changes when placed on LCD, with mutant females showing some protection from hyperparathyroidism-induced bone loss, while mutant males (which have more cortical bone at baseline) show increased LCD-induced bone loss. Furthermore, new insights into irisin's role in osteocytes regarding cellular energetic metabolism were provided by sex and gene-dependent transcriptomic datasets. Strengths of the well-written manuscript include clear description of sex-dependent effects, strong transcriptomic datasets, and focus on cortical bone changes using microCT, histomorphometry, BSEM, and serum analysis. Despite these strengths, important weaknesses are noted (below) which could be addressed to improve the impact of the work for a broad audience.

Major comments:

(1) Overall, the magnitude of the effect size due to FNDC5 deficiency in both male and female mice is rather modest at the level of bone mass. Looking at the data from a qualitative perspective, it is clear that knockout females still lose bone during lactation and on the low calcium diet (LCD). It is difficult to assess the physiologic consequence of the modest quantitative 'protection' seen in FNDC5 mutants since the mutants still show clear and robust effects of lactation and LCD on all parameters measured. Similarly, the magnitude of the 'increased' cortical bone loss in FNDC5 mutant males is also modest, and perhaps could be related to the fact that these mice are starting with slightly more cortical bone. Since the authors do not provide a convincing molecular explanation for why FNDC5 deficiency causes these somewhat subtle changes, I would like to offer a suggestion for the authors to consider (below, point #2) which might de-emphasize the focus of the manuscript on FNDC5. If the authors chose not to follow this suggestion, the manuscript could be strengthened by addressing the consequences of the modest changes observed in WT versus FNDC5 KO mice. I understand that the effects of FNDC5 are more obvious at the level of osteocyte morphology, and it is reasonable to emphasize these findings here.

(2) The bone RNA-seq findings reported in Figures 4-6 are quite interesting. Although Youlten et al previously reported that the osteocyte transcriptome is sex-dependent, the work here certainly advances that notion to a considerable degree, and likely will be of high interest to investigators studying skeletal biology and sexual dimorphism in general. To this end, one direction for the authors to consider might be to refocus their manuscript towards sexually-dimorphic gene expression patterns in osteocytes and the different effects of LCD on male versus female mice. This would allow the authors to better emphasize these major findings, and then to use FNDC5 deficiency as an illustrative example of how sexually-dimorphic osteocytic gene expression patterns might be affected by deletion of an osteocyte-acting endocrine factor. Ideally, the authors would confirm RNA-seq data comparing male versus female mice in osteocytes using in situ hybridization or immunostaining. Of course, this point is only a suggestion for the authors to consider.

(3) It would be appreciated if the authors could provide additional serum parameters (if possible) to clarify incomplete data in both lactation and low-calcium diet models: RANKL/OPG ratio, Ctx, PTHrP, and 1,25-dihydroxyvitamin D levels. I understand that this may not be possible due to lack of available material.

Reviewer #1 (Public Review):

The authors present a number of deep learning models to analyse the dynamics of epithelia. In this way they want to overcome the time-consuming manual analysis of such data and also remove a potential operator bias. Specifically, they set up models for identifying cell division events and cell division orientation. They apply these tools to the epithelium of the developing Drosophila pupal wing. They confirm a linear decrease of the division density with time and identify a burst of cell division after healing of a wound that they had induced earlier. These division events happen a characteristic time after and a characteristic distance away from the wound. These characteristic quantities depend on the size of the wound.

Strengths:

The methods developed in this work achieve the goals set by the authors and are a very helpful addition to the toolbox of developmental biologists. They could potentially be used on various developing epithelia. The evidence for the impact of wounds on cell division is compelling.

The methods presented in this work should prove to be very helpful for quantifying cell proliferation in epithelial tissues.

Reviewer #1 (Public Review):

This is a clear account of some interesting work. The experiments and analyses seem well done and the data are useful. It is nice to see that VSDI results square well with those from prior extracellular recordings.

The authors have done a good job responding to the main points of my previous review. One important question remains, as stated in that review:

"My reading is that this is primarily a study of surround suppression with results that follow pretty directly from what we already know from that literature, and although they engage with some of the literature they do not directly mention surround suppression in the text. Their major effect - what they repeatedly describe as a "paradoxical" result in which the responses initially show a stronger response to matched targets and backgrounds and then reverse - seems to pretty clearly match the expected outcome of a stimulus that initially evokes additional excitation due to increased center contrast followed by slightly delayed surround suppression tuned to the same peak orientation. Their dynamics result seems entirely consistent with previous work, e.g. Henry at al 2020, particularly their Fig. 3 https://elifesciences.org/articles/54264, so it seems like a major oversight to not engage with that work at all, and to explain what exactly is new here."

Their rebuttal of my first review is not convincing -- I still believe that surround influences are important and perhaps predominant in determining the outcome of the experiments. This is particularly clear for the "paradoxical" dynamics that they observe, which seem exactly to reflect the behavior of the surround.

The authors' arguments to the contrary are based on three main points. First, their stimuli cover the center and surround, unlike those of many previous experiments, so they argue that this somehow diminishes the impact of the surround. But the argument is not accompanied by data showing the effects of center stimuli alone or surround stimuli alone. Second, their model -- a normalization model -- does not need surround influences to account for the masking effect. Third, they cite human psychophysical masking results from their collaborators (Sebastian et al 2017), but do not cite an equally convincing demonstration that surround contrast creates potent orientation selective masking when presented alone (Petrov et al 2005, https://doi.org/10.1523/JNEUROSCI.2871-05.2005).

At the end of the day, these issues will be resolved by further experiments, not argumentation. The paper stands as an excellent contribution, but it might be wise for the authors to be less doctrinaire in their interpretations.

Reviewer #1 (Public Review):

Summary:

In this work, the authors utilize recurrent neural networks (RNNs) to explore the question of when and how neural dynamics and the network's output are related from a geometrical point of view. The authors found that RNNs operate between two extremes: an 'aligned' regime in which the weights and the largest PCs are strongly correlated and an 'oblique' regime where the output weights and the largest PCs are poorly correlated. Large output weights led to oblique dynamics, and small output weights to aligned dynamics. This feature impacts whether networks are robust to perturbation along output directions. Results were linked to experimental data by showing that these different regimes can be identified in neural recordings from several experiments.

Strengths:

A diverse set of relevant tasks.

A well-chosen similarity measure.

Exploration of various hyperparameter settings.

Weaknesses:

One of the major connections found BCI data with neural variance aligned to the outputs. Maybe I was confused about something, but doesn't this have to be the case based on the design of the experiment? The outputs of the BCI are chosen to align with the largest principal components of the data.

Proposed experiments may have already been done (new neural activity patterns emerge with long-term learning, Oby et al. 2019). My understanding of these results is that activity moved to be aligned as the manifold changed, but more analyses could be done to more fully understand the relationship between those experiments and this work.

Analysis of networks was thorough, but connections to neural data were weak. I am thoroughly convinced of the reported effect of large or small output weights in networks. I also think this framing could aid in future studies of interactions between brain regions.

This is an interesting framing to consider the relationship between upstream activity and downstream outputs. As more labs record from several brain regions simultaneously, this work will provide an important theoretical framework for thinking about the relative geometries of neural representations between brain regions.

It will be interesting to compare the relationship between geometries of representations and neural dynamics across connected different brain areas that are closer to the periphery vs. more central.

It is exciting to think about the versatility of the oblique regime for shared representations and network dynamics across different computations.

The versatility of the oblique regime could lead to differences between subjects in neural data.

Reviewer #1 (Public Review):

Summary:

The pioneering work of Eve Marder on central pattern generators in the stomatogastric ganglion (STG) has made a strong case for redundancy as a biological mechanism for ensuring functional robustness, where multiple configurations of biophysical parameters are equivalent in terms of their ability to generate desired patterns of periodic circuit activity. In parallel, normative theories of synaptic plasticity have argued for functional equivalences between learning objectives and corresponding plasticity rules in implementing simple unsupervised learning (see Brito & Gerstner 2016, although similar arguments have been made long before e.g. in Aapo Hyvarinen's ICA book). This manuscript argues that similar notions of redundancy need to be taken into account in the study of synaptic plasticity rules in the brain, more specifically in the context of data-driven approaches to extract the "true" synaptic plasticity rule operating in a neural circuit from neural activity recordings. Concretely, the modeling approach takes a set of empirical measurements of the evolution of neural activity and trains a flexibly parametrized model to match that in statistical terms. Instead of being predefined by the experimenter, the features that determine this match are themselves extracted from data using a generative adversarial network framework (GAN). They show that the flexible models manage to reproduce the neural activity to a reasonable degree (though not perfectly), but lead to very different synaptic trajectories.

Strengths:

The idea of learning rule redundancy is a good one, and the use of GANs for the learning rule estimation is a good complement to other data-driven approaches to extract synaptic plasticity ruled from neural data.

Weaknesses:

(1) Numerics provide only partial support to the statements describing the results.

(2) Even if believing the results, I don't necessarily agree with the interpretation. First: unlike the Marder example where there is complementary evidence to argue that the parameter variations actually reflect across animal biophysical variations, here the statements are really about uncertainty that the experimenter has about what is going on in a circuit observed through a certain measurement lens. Second, while taking into account this uncertainty when using the outcomes of this analysis for subsequent scientific goals is certainly sensible, the biggest punchline for me is that simply observing neural activity in a simple and very restricted context does not provide enough information about the underlying learning mechanism, especially when the hypothesis space is very large (as is the case for the MLP). So it seems more useful to use this framework to think about how to enrich the experimental design/ learning paradigms/ or the measurements themselves to make the set of hypotheses more discriminable (in the spirit of the work by Jacob Portes et al, 2022 for instance). Conversely, one should perhaps think about other ways in which to use other forms of experimental data to reasonably constrain the hypothesis space in the first place.

Reviewer #2 (Public Review):

Summary:

This study from Bamgbose et al. identifies a new and important interaction between H4K20me and Parp1 that regulates inducible genes during development and heat stress. The authors present convincing experiments that form a mostly complete manuscript that significantly contributes to our understanding of how Parp1 associates with target genes to regulate their expression.

Strengths:

The authors present 3 compelling experiments to support the interaction between Parp1 and H4K20me, including:

(1) PR-Set7 mutants remove all K4K20me and phenocopy Parp mutant developmental arrest and defective heat shock protein induction.

(2) PR-Set7 mutants have dramatically reduced Parp1 association with chromatin and reduced poly-ADP ribosylation.

(3) Parp1 directly binds H4K20me in vitro.

Weaknesses:

(1) The RNAseq analysis of Parp1/PR-Set7 mutants is reasonable, but there is a caveat to the author's conclusion (Line 251): "our results indicate H4K20me1 may be required for PARP-1 binding to preferentially repress metabolic genes and activate genes involved in neuron development at co-enriched genes." An alternative possibility is that many of the gene expression changes are indirect consequences of altered development induced by Parp1 or PR-Set7 mutants. For example, Parp1 could activate a transcription factor that represses metabolic genes. The authors counter this model by stating that Parp1 directly binds to "repressed" metabolic genes. While this argument supports their model, it does not rule out the competing indirect transcription factor model. Therefore, they should still mention the competing model as a possibility.

(2) The section on inducibility of heat shock genes is interesting but missing an important control that might significantly alter the author's conclusions. Hsp23 and Hsp83 (group B genes) are transcribed without heat shock, which likely explains why they have H4K20me without heat shock. The authors made the reasonable hypothesis that this H4K20me would recruit Parp-1 upon heat shock (line 270). However, they observed a decrease of H4K20me upon heat shock, which led them to conclude that "H4K20me may not be necessary for Parp1 binding/activation" (line 275). However, their RNA expression data (Fig4A) argues that both Parp1 and H40K20me are important for activation. An alternative possibility is that group B genes indeed recruit Parp1 (through H4K20me) upon heat shock, but then Parp1 promotes H3/H4 dissociation from group B genes. If Parp1 depletes H4, it will also deplete H4K20me1. To address this possibility, the authors should also do a ChIP for total H4 and plot both the raw signal of H4K20me1 and total H4 as well as the ratio of these signals. The authors could also note that Group A genes may similarly recruit Parp1 and deplete H3/H4 but with different kinetics than Group B genes because their basal state lacks H4K20me/Parp1. To test this possibility, the authors could measure Parp association, H4K20methylation, and H4 depletion at more time points after heat shock at both classes of genes.

Reviewer #1 (Public Review):

Summary:

Knudstrup et al. use two-photon calcium imaging to measure neural responses in the mouse primary visual cortex (V1) in response to image sequences. The authors presented mice with many repetitions of the same four-image sequence (ABCD) for four days. Then on the fifth day, they presented unexpected stimulus orderings where one stimulus was either omitted (ABBD) or substituted (ACBD). After analyzing trial-averaged responses of neurons pooled across multiple mice, they observed that stimulus omission (ABBD) caused a small, but significant, strengthening of neural responses but observed no significant change in the response to stimulus substitution (ACBD). Next, they performed population analyses of this dataset. They showed that there were changes in the correlation structure of activity and that many features of sequence ordering could be reliably decoded. This second set of analyses is interesting and exhibited larger effect sizes than the first results about predictive coding. However, concerns about the design of the experiment temper my enthusiasm.

Strengths:

(1) The topic of predictive coding in the visual cortex is exciting, and this task builds on previous important work by the senior author (Gavornik and Bear 2014) where unexpectedly shuffling sequence order caused changes in LFPs recorded from the visual cortex.

(2) Deconvolved calcium responses were used appropriately here to look at the timing of the neural responses.

(3) Neural decoding results showing that the context of the stimuli could be reliably decoded from trial-averaged responses were interesting. However I have concerns about how the data was formatted for performing these analyses.

Weaknesses:

(1) All analyses were performed on trial-averaged neural responses that were pooled across mice. Owing to differences between subjects in behavior, experimental preparation quality, and biological variability, it seems important to perform at least some analyses on individual analyses to assess how behavioral training might differently affect each animal.

(2) The correlation analyses presented in Figure 3 (labeled the second Figure 2 in the text) should be conducted on a single-animal basis. Studying population codes constructed by pooling across mice, particularly when there is no behavioral readout to assess whether learning has had similar effects on all animals, appears inappropriate to me. If the results in Figure 3 hold up on single animals, I think that is definitely an interesting result.

(3) On Day 0 and Day 5, the reordered stimuli are presented in trial blocks where each image sequence is shown 100 times. Why wasn't the trial ordering randomized as was done in previous studies (e.g. Gavornik and Bear 2014)? Given this lack of reordering, did neurons show reduced predictive responses because the unexpected sequence was shown so many times in quick succession? This might change the results seen in Figure 2, as well as the decoder results where there is a neural encoding of sequence order (Figure 4). It would be interesting if the Figure 4 decoder stopped working when the higher-order block structure of the task was disrupted.

(4) A primary advantage of using two-photon calcium imaging over other techniques like extracellular electrophysiology is that the same neurons can be tracked over many days. This is a standard approach that can be accomplished by using many software packages-including Suite2P (Pachitariu et al. 2017), which is what the authors already used for the rest of their data preprocessing. The authors of this paper did not appear to do this. Instead, it appears that different neurons were imaged on Day 0 (baseline) and Day 5 (test). This is a significant weakness of the current dataset.

Reviewer #1 (Public Review):

Summary:

The authors show that SVZ-derived astrocytes respond to a middle carotid artery occlusion (MCAO) hypoxia lesion by secreting and modulating hyaluronan at the edge of the lesion (penumbra) and that hyaluronan is a chemoattractant to SVZ astrocytes. They use lineage tracing of SVZ cells to determine their origin. They also find that SVZ-derived astrocytes express Thbs-4 but astrocytes at the MCAO-induced scar do not. Also, they demonstrate that decreased HA in the SVZ is correlated with gliogenesis. While much of the paper is descriptive/correlative they do overexpress Hyaluronan synthase 2 via viral vectors and show this is sufficient to recruit astrocytes to the injury. Interestingly, astrocytes preferred to migrate to the MCAO than to the region of overexpressed HAS2.

Strengths:

The field has largely ignored the gliogenic response of the SVZ, especially with regard to astrocytic function. These cells and especially newborn cells may provide support for regeneration. Emigrated cells from the SVZ have been shown to be neuroprotective via creating pro-survival environments, but their expression and deposition of beneficial extracellular matrix molecules are poorly understood. Therefore, this study is timely and important. The paper is very well written and the flow of results is logical.

Weaknesses:

The main problem is that they do not show that Hyaluronan is necessary for SVZ astrogenesis and or migration to MCAO lesions. Such loss of function studies have been carried out by studies they cite (e.g. Girard et al., 2014 and Benner et al., 2013). Similar approaches seem to be necessary in this work.

Major points:

(1) How good of a marker for newborn astrocytes is Thbs4? Did you co-label with B cell markers like EGFr? Is the Thbs4 gene expressed in B cells? Do scRNAseq papers show it is expressed in B cells? Are they B1 or B2 cells?

(2) It is curious that there was no increase in Type C cells after MCAO - do the authors propose a direct NSC-astrocyte differentiation?

(3) The paper would be strengthened with orthogonal views of z projections to show co-localization.

(4) It is not clear why the dorsal SVZ is analysed and focused on in Figure 4. This region emanates from the developmental pallium (cerebral cortex anlagen). It generates some excitatory neurons early postnatally and is thought to have differential signalling such as Wnt (Raineteau group).

(5) Several of the images show the lesion and penumbra as being quite close to the SVZ. Did any of the lesions contact the SVZ? If so, I would strongly recommend excluding them from the analysis as such contact is known to hyperactivate the SVZ.

(6) The authors switch to a rat in vitro analysis towards the end of the study. This needs to be better justified. How similar are the molecules involved between mouse and rat?

(7) Similar comment for overexpression of naked mole rat HA.

Reviewer #1 (Public Review):

The present study examines whether one can identify kinematic signatures of different motor strategies in both humans and non-human primates (NHP). The Critical Stability Task (CST) requires a participant to control a cursor with complex dynamics based on hand motion. The manuscript includes datasets on performance of NHPs collected from a previous study, as well as new data on humans performing the same task. Further human experiments and optimal control models highlight how different strategies lead to different patterns of hand motion. Finally, classifiers were developed to predict which strategy individuals were using on a given trial.

There are several strengths to this manuscript. I think the CST task provides a very useful behavioural task to explore the neural basis of voluntary control. While reaching is an important basic motor skill and commonly studied, there is much to learn by looking at other motor actions to address many fundamental issues on the neural basis of voluntary control.

I also think the comparison between human and NHP performance is important as there is a common concern that NHPs can be overtrained in performing motor tasks leading to differences in their performance as compared to humans. The present study highlights that there are clear similarities in motor strategies of humans and NHPs. While the results are promising, I would suggest that the actual use of these paradigms and techniques likely need some improvement/refinement. Notably, the threshold or technique to identify which strategy an individual is using on a given trial needs to be more stringent given the substantial overlap in hand kinematics between different strategies.

The most important goal of this study is to set up future studies to examine how changes in motor strategies impact neural processing. The revised manuscript has improved the technique for identifying which strategy appears to be performed by the individual. A pivotal assumption is that one can identify control strategies from differences in behaviour. As I'm sure the authors know, this inversion of the control problem is not trivial and so success requires that there are only a few 'reasonable' strategies to solve the control problem, and that these strategies lead to distinct patterns of behavior. Many of the concerns raised by myself and the other reviewers relate to this challenge. The revised manuscript now uses a more strict criteria which is good improvement.

One of the values of this paper is to start to develop the tools and approaches to address neural basis of control. The strength of the present manuscript is that it includes modelling, explicit strategy instructions in humans, and then analysis of free-form performance in humans and non-human primates. Given the novelty of this question and approach, there likely are many ways that the techniques and approaches could be improved, but I think they've done a great start. Their approach is quite clever and provides an important blueprint for future studies.

One weakness at this point is that there is still substantial overlap in behavoural performance predicted between strategies, as some human participants given an explicit strategy were almost equally categorized as reflecting the other strategy. I'm glad to see the addition of the model performance on perturbation trials as this additional figure clearly highlights much greater separation in performance than when observing natural behavior. While it is not reasonable to expand beyond this for the present manuscript, I think it is essential for this group to develop the perturbation paradigm (and potentially other approaches) that can better isolate behavioral signatures of different control strategies. I think future work will be strengthened by having multiple experimental angles to interpret the neural activity.

Reviewer #1 (Public Review):

Summary:<br /> In this manuscript, Fister et. al. investigate how amputational and burn wounds affect sensory axonal damage and regeneration in a zebrafish model system. The authors discovered that burn injury results in increased peripheral axon damage and impaired regeneration. Convincing experiments show altered axonal morphology and increased Ca2+ fluxes as a result of burn damage. Further experimental proof supports that early removal of the burnt tissue by amputation rescues axonal damage. Burn damage was also shown to markedly increase keratinocyte migration and increase localized ROS production as measured by the dye Pfbsf. These responses could be inhibited by Arp 2/3 inhibition and isotonic treatment.

Strengths:<br /> The authors use state-of-the-art methods to study and compare transection and burn-induced tissue damage. Multiple experimental approaches (morphology, Ca2+ fluxing, cell membrane labeling) confirm axonal damage and impaired regeneration time. Furthermore, the results are also accompanied by functional response tests of touch sensitivity. This is the first study to extend the role of tissue-damage-related osmotic exposure beyond wound closure and leukocyte migration to a novel layer of pathology: axonal damage and regeneration.

Weaknesses:<br /> The conclusions of the paper claiming a link between burn-induced epithelial cell migration, spatial redox signaling, and sensory axon regeneration are mainly based on correlative observations. Arp 2/3 inhibition impairs cell migration but has no significant effect on axon regeneration and restoration of touch sensitivity.

Pharmacological or genetic approaches should be used to prove the role of ROS production by directly targeting the known H2O2 source in the system: DUOX.

While the authors provide clear and compelling proof that osmotic responses lie at the heart of the burn-induced axonal damage responses, they did not consider the option of further exploring any biology related to osmotic cell swelling. Could osmotic ATP release maybe play a role through excitotoxicity? Could cPLA2 activation-dependent eicosanoid production relate to the process? Pharmacological tests using purinergic receptor inhibition or blockage of eicosanoid production could answer these questions.

The authors provide elegant experiments showing that early removal of the burnt tissue can rescue damage-induced axonal damage, which could also be interpreted in an osmotic manner: tail fin transections could close faster than burn wounds, allowing for lower hypotonic exposure time. Axonal damage and slow regeneration in tail fin burn wounds could be a direct consequence of extended exposure time to hypotonic water.

Reviewer #1 (Public Review):

This manuscript proposes a new bioinformatics approach identifying several hundreds of previously unknown inhibitory immunoreceptors. When expressed in immune cells (such as neutrophils, monocytes, CD8+, CD4+, and T-cells), such receptors inhibit the functional activity of these cells. Blocking inhibitory receptors represents a promising therapeutic strategy for cancer treatment.

As such, this is a high-quality and important bioinformatics study. One general concern is the absence of direct experimental validation of the results. In addition to the fact that the authors bioinformatically identified 51 known receptors, providing such experimental evaluation (of at least one, or better few identified receptors) would, in my opinion, significantly strengthen the presented evidence.

I will now briefly summarize the results and give my comments.

First, using sequence comparison analysis, the authors identify a large set of putative receptors based on the presence of immunoreceptor tyrosine-based inhibitory motifs (ITIMs), or immunoreceptor tyrosine-based switch motifs (ITSMs). They further filter the identified set of receptors for the presence of the ITIMs or ITSMs in an intracellular domain of the protein. Second, using AlphaFold structure modeling, the authors select only receptors containing ITIMs/ITSMs in structurally disordered regions. Third, the evaluation of gene expression profiles of known and putative receptors in several immune cell types was performed. Fourth, the authors classified putative receptors into functional categories, such as negative feedback receptors, threshold receptors, threshold disinhibition, and threshold-negative feedback. The latter classification was based on the available data from Nat Rev Immunol 2020. Fifth, using publicly available single-cell RNA sequencing data of tumor-infiltrating CD4+ and CD8+ cells from nearly twenty types of cancer, the authors demonstrate that a significant fraction of putative receptors are indeed expressed in these datasets.

In summary, in my opinion, this is an interesting, important, high-quality bioinformatics work. The manuscript is clearly written and all technical details are carefully explained.

One comment/suggestion regarding the methodology of evaluating gene expression profiles of putative receptors: perhaps it might be important to look at clusters of genes that are co-expressed with putative inhibitory receptors.

Reviewer #1 (Public Review):

Summary:

In the paper entitled "PI3K/HSCB axis facilitates FOG1 nuclear translocation to promote erythropoiesis and megakaryopoiesis", the authors sought to determine the role of HSCB, a known regulator of iron-sulfur cluster transfer, in the generation of erythrocytes and megakaryocytes. They utilized a human primary cell model of hematopoietic differentiation to identify a novel mechanism whereby HSCB is necessary for the activation of erythroid and megakaryocytic gene expression through regulation of the nuclear localization of FOG-1, an essential transcription co-regulator of the GATA transcription factors. Their work establishes this novel regulatory axis as a mechanism by which cytokine signaling through EPO-R and MPL drives the lineage-specification of hematopoietic progenitors to erythrocytes and megakaryocytes, respectively.

Impact:

The major impact of this work is in a greater understanding of how cytokine signaling through EPO/TPO functions to promote lineage specification of hematopoietic stem/progenitor cells. While the major kinase cascades downstream of the EPO/TPO receptors have been elucidated, how those cascades affect gene expression to promote a specific differentiation program is poorly understood. For this work, we now understand that nuclear localization of FOG is a critical regulatory node by which EPO/TPO signaling is required to launch FOG-dependent gene expression. However, these cytokine receptors have many overlapping and redundant targets, so it still remains to be elucidated how signaling through the different receptors promotes divergent gene expression programs. Perhaps similar regulatory mechanisms exist for other lineage-specifying transcription factors.

Strengths:

The authors use two different cellular models of erythroid differentiation (K562 and human primary CD34+ cells) to elucidate the multi-factorial mechanism controlling FOG-1 nuclear localization. The studies are well-controlled and rigorously establish their mechanism through complementary approaches. The differentiation effects are established through cell surface marker expression, protein expression, and gene expression analyses. Novel protein interactions discovered by proteomics analyses were validated through bi-directional co-IP experiments in multiple experimental systems. Protein cellular localization findings are supported by both immunofluorescence and cell fractionation immunoblot analyses. The robustness of their experimental findings gives great confidence in the likelihood that the methods and findings can be reproduced in future work based on their conclusions.

Weaknesses:

The one unexplained step in this intricately described mechanism is how HSCB functions to promote TACC3 degradation. It appears that the proteasome is involved since MG-132 reverses the effect of HSCB deficiency, but no other details are provided. Does HSCB target TACC3 for ubiquitination somehow? Future studies will be required to understand this portion of the mechanism.

One weakness of the study design is that no in vivo experiments are conducted. The authors comment that the HSCB mouse phenotype is too dramatic to permit studies of erythropoiesis in vivo; however, a conditional approach could have been pursued.

It should also be noted that a previous study had already shown that TACC3 regulates the nuclear localization of FOG-1, so this portion of the mechanism is not entirely novel. However, the role of HSCB and the proteasomal degradation of TACC3 is entirely novel to my knowledge.

Reviewer #1 (Public Review):

Summary:

The authors developed a new viral 'gene drive' based on an alternate CRISPR Cas system: UNCas12f1. They show in HSV-1 that the gene drive virus can transmit as hypothesized and is superior to Cas9 in terms of evolutionary robustness.

Strengths:

No doubt this is an impressive technological achievement and UNCas12f1 does appear superior to Cas9 in terms of taking longer to develop resistance. This is a strong body of work and Fig 3B is the crux of the paper for me showing that resistance does take longer in terms of % of viruses that are wildtype versus UNCas12f1 gene drive. I applaud the authors and I think this is a nice technological contribution.

Weaknesses:

I will focus on major conceptual issues.

(1) Mechanism. It is not really that clear to me why the UNCas12f1 has a higher barrier to the evolution of resistance. Is this simply a temporal delay or is there something intrinsic about UNCas12f1 that does not allow resistance to arise? There is a some discussion about this but it is speculative and I could not understand why resistance would not develop.

(2) Evolution. Fig 3B is the crux of the paper for me showing that resistance does take longer in terms of % of viruses that are wildtype versus UNCas12f1 gene drive. The authors did a nice job, however, I think they need to temper the claims somewhat as longer studies (other studies typically go out to >40 days) might show resistance arising. Also, I think absolute viral titers need to be shown in addition to percentage of viruses.

(3) Therapeutic Utility. Is this proposed as a therapeutic strategy? If so, how would it work? Could it lower overall total viral burden (i.e., wt + gene drive)? Another issue that I think needs to be specifically addressed is the issue of MOI as typically HSV-1 is thought to be (i.e. shown to be) a low MOI infection in vivo and in patients, whereas this strategy appears to rely on high MOI. Overall, to me, this is probably the major weakness: i.e., whether this strategy has therapeutic potential.

(4) Title. I don't think the subordinate clause of the title "virus that 'infect' viruses" is quite correct. This needs to be be reworded. This strategy converts the viral population from wild type to a gene drive virus but "infect" does not seem accurate.

Reviewer #2 (Public Review):

Summary:

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

Strengths:

This study shows that the centromere function is affected under heat stress in meiotic cells by modulating the dynamics of the centromere specific histone H3 (CENH3) that in turn compromises the assembly of kinetochore complex proteins. This they have demonstrated by the way of live cell imaging of male meiocytes by tracking the loading dynamics and resident time of fluorescently tagged centromere/kinetochore proteins and spindle assembly checkpoint proteins.

Weaknesses:

Though the results presented here are interesting and solid, the current study lacks a deeper mechanistic understanding of what causes the defective loading of CenH3 to the centromeres, and why the SAC protein BMF3 persists only at meiotic centromeres to prolong the spindle assembly checkpoint, which will be interesting to delve further to completely understand the process.

Here the authors monitor one representative centromere protein CENH3, one kinetochore-associated SAC protein BMF1, and the SAC protein BMF3 to conclude that heat stress impairs centromere/kinetochore function and prolongs SAC with increased temperatures. Centromere and its associated protein complex the kinetochores and the SAC contains a multitude of proteins, some of which are well characterized in Arabidopsis thaliana. Hence the authors could have used additional such tagged proteins to further strengthen their claim.

Reviewer #1 (Public Review):

The authors aim to develop an easy-to-use image analysis tool for the mother machine that is used for single-cell time-lapse imaging. Compared with related software, they tried to make this software more user-friendly for non-experts with a design of "What You Put Is What You Get". This software is implemented as a plugin of Napari, which is an emerging microscopy image analysis platform. The users can interactively adjust the parameters in the pipeline with good visualization and interaction interface.

Strengths:

- Updated platform with great 2D/3D visualization and annotation support.<br /> - Integrated one-stop pipeline for mather machine image processing.<br /> - Interactive user-friendly interface.<br /> - The users can have a visualization of intermediate results and adjust the parameters.

Weaknesses:

- Based on the presentation of the manuscript, it is not clear that the goals are fully achieved.<br /> - Although there is great potential, there is little evidence that this tool has been adopted by other labs.<br /> - the diversity of datasets used in this study is limited.<br /> - Some paragraphs in the Discussion section are like blogs with general recommendations. Although the suggestions look pretty useful, it is not the focus of this manuscript. It might be more appropriate to put it in the GitHub repo or a documentation page. The discussion should still focus on the software, such as features, software maintenance, software development roadmap, and community adoption.

A discussion of the likely impact of the work on the field, and the utility of the methods and data to the community.<br /> - The impact of this work depends on the adoption of the software MM3. Napari is a promising platform with an expanding community. With good software user experience and long-term support, there is a good chance that this tool could be widely adopted in the mother machine image analysis community.<br /> - The data analysis in this manuscript is used as a demo of MM3 features, rather than scientific research.

Reviewer #1 (Public Review):

Zhang et al. investigate the hypothesis that tRNA methyl transferase 1 (TRMT1) is cleaved by NSP5 (nonstructural protein 5 or MPro), the SARS-CoV-2 main protease, during SARS-CoV-2 infection. They provide solid evidence that TRMT1 is a substrate of Nsp5, revealing an Nsp5 target consensus sequence and evidence of TRMT1 cleavage in cells. Their conclusions are exceptionally strong given the co-submission by D'Oliveira et al showing cleavage of TRMT1 in vitro by Nsp5. The detection of the N-terminal TRMT1 fragment by western blot is not robust; however, the authors provide corroborating assays and detailed densitometry methods, providing confidence to this reviewer that a TRMT1 fragment is produced under some conditions. Separately, the authors convincingly demonstrate widespread downregulation of RNA modifications during CoV-2 infection, including a requirement for TRMT1 in efficient viral replication. This finding is congruent with the authors' previous work defining the impact of TRMT1 and m2,2g on global translation, which is most likely necessary to support infection and virion production. Based on the data provided here, TRMT1 cleavage may be an act by CoV-2 to self-limit replication, as expression of a non-cleavable TRMT1 (versus wild type TRMT1) supports enhanced viral RNA expression at certain MOIs. The authors propose a few fascinating ideas to why this may be so in "Ideas and Speculation." Theoretically, TRMT1 cleavage should inactivate the modification activity of TRMT1, which the authors thoroughly and elegantly investigate with rigorous biochemical assays. However, only a minority of TRMT1 undergoes cleavage during infection at low MOIs and thus whether TRMT1 cleavage serves an important functional role during CoV-2 replication will be an important topic for future work. The authors fairly assess their work in this regard. In summary, this study demonstrates an important finding that the tRNA modification landscape is altered during CoV-2 infection, and that TRMT1 is an important host factor supporting CoV-2 replication. Their data pushes forward the idea that control of tRNA expression and functionality is an important and understudied area of host-pathogen interaction.

Reviewer #1 (Public Review):

The study by Vengayil et al. presented a role for Ubp3 for mediating inorganic phosphate (Pi) compartmentalization in cytosol and mitochondria, which regulates metabolic flux between cytosolic glycolysis and mitochondrial processes. Although the exact function of increased Pi in mitochondria is not investigated, findings have valuable implications for understanding the metabolic interplay between glycolysis and respiration under glucose-rich conditions. They showed that UBP3 KO cells regulated decreased glycolytic flux by reducing the key Pi-dependent-glycolytic enzyme abundances, consequently increasing Pi compartmentalization to mitochondria. Increased mitochondria Pi increases oxygen consumption and mitochondrial membrane potential, indicative of increased oxidative phosphorylation. In conclusion, the authors reported that the Pi utilization by cytosolic glycolytic enzymes is a key process for mitochondrial repression under glucose conditions.

Comments on revised version:

This reviewer appreciates the author's responses addressing some of the concerns.

However, the concern of reproducibility and experimental methods applied to the study is still valid, particularly considering that many conclusions were drawn from western blot analysis. The authors used separate gel loading controls for western blot analysis, which is not a valid method. Considering loading and other errors/discrepancies during the transfer phase of the assay, the direct control should be analyzing the membrane after transfer or using an internal control antibody on the same membrane. None of the western blots are indicated with marker sizes, and it isn't very clear how many repeats there are and whether those repeats are biological or technical repeats.

Concern regarding citing the Ouyang et al. paper is still valid. This paper is an essential implication in phosphate metabolism and is directly related to some of the findings associated with mitochondrial function, along with conflicting results, which should be discussed in the discussion section. As a reviewer, I do not request citing any paper from the authors in general; however, considering some of the conflicting results here, citing and discussing paper from Ouyang et al. will improve the interoperation/value of their findings.

Considering these factors, the presented results do not fully support the findings.

Reviewer #1 (Public Review):

This study explores whether the extreme polygenicity of common traits (the fact that variation in such traits is explained by a very large number of genetic variants) could be explained in part by competition among genes for limiting molecular resources involved in gene regulation, which would cause the expression of most genes to be correlated. While the hypothesis is interesting, I still have some concerns about the analysis and interpretation.

As the authors say in their rebuttal, assuming extreme resource limitation, i.e., going from equation 2 to 5 essentially assumes assuming that 1/(gtot [G] ) <<1 and that terms that are order [ 1/(gtot [G] ) ] can neglected. However, then the authors derive so-called resource competition terms that are order (1/m) where m is the number of genes, so that gtot is proportional to m. My main criticism (which I am not sure was addressed) is thus: can we reliably derive small order (1/m) effects while neglecting order [ 1/(gtot [G] ) ] terms, when both are presumably similar in order of magnitude? Is this mathematically sound?

I do not think the supplement that the authors have added actually gets to this. For example, section 7.1 just gives the textbook derivation of Michelis-Menten kinetics, and does not address my earlier criticism that the terms neglected in going from eq. 16 to eq. 17 (or from eq. 2 to 3) may be similar in magnitude to the terms being derived and interpreted in eqs. 6 and 7.<br /> Similarly, it is unclear from section 7.2 how the authors are doing the simulations. Are these true Michelis-Menten simulations involving equation 2? If yes, then what is the value of [G] and [P_0] in the simulations? If these are not true Michelis-Menten simulations, but instead something that already uses equation 5, then this still does not address my earlier criticism.

Reviewer #2 (Public Review):

Summary:

Two early Cambrian taxa of linguliform brachiopods are assigned to the family Eoobolidae. The taxa exhibit a columnar shell structure and the phylogenetic implications of this shell structure in relation to other early Cambrian families is outlined.

Strengths:

Interesting idea regarding the evolution of shell structure.

Weaknesses:

The early record of shell structures of linguliform brachiopods is incomplete and partly contradictory. The authors maintain silence regarding contradictory information throughout the article to an extend that information is cited wrongly. The article is written under the assumption that all eoobolids have a columnar shell structure. Thus, the previously claimed columnar structure of Eoobolus incipiens which has been re-illustrated in the paper is not convincing and could be interpreted in other ways.

The article still needs a proper results section. The Discussion is mainly a review of published data. Other potential results are hidden in this "discussion". Large sections of the paper appear irrelevant and can be deleted.

A critical revision of the family Eoobolidae and Lingulellotretidae including a revision of the type species of Eoobolus and Lingulellotreta is needed first.

The potential evolutionary patterns that are presented towards the end (summarized in Fig 6) are interesting but rather unconvincing. The stated numbers of shell laminae, whose origin has now been clarified in a still rather short Methods section, represent a mix of data and are not comparable. Achieved numbers of laminae based on literature data include laminae from the secondary and tertiary shell layer, a distinction between the two would be crucial for the proposed claims.<br /> The obtained evolutionary patterns as presented in Fig. 6 must, after the second revision and clarification of the methods used, be regarded as misleading and reflects a limited understanding of shell growths in linguliform brachiopods (despite the extensive review of the literature).

Reviewer #1 (Public Review):

Summary:

This study by Lee et al. is a direct follow-up on their previous study that described an evolutionary conservancy among placental mammals of two motifs (a transmembrane motif and a juxtamembrane palmitoylation site) in CD4, an antigen co-receptor, and showed their relevance for T-cell antigen signaling. In this study, they describe the contribution of these two motifs to the CD4-mediated antigen signaling in the absence of CD4-LCK binding. Their approach was the comparison of antigen-induced proximal TCR signaling and distal IL-2 production in 58-/- T-cell hybridoma expressing exogenous truncated version of CD4 (without the interaction with LCK), called T1 and T1 version with the mutations in either or both of the conserved motifs. They show that the T1 CD4 can support signaling to extend similar to WT CD4, but the mutation of the conserved motifs substantially reduced the signaling. The authors conclude that the role of these motifs is independent of the LCK-binding.

Strengths:

The authors convincingly show that CD4 is capable of contributing to TCR signaling in a manner independent of LCK, but dependent on the two studied motifs in CD4.

Weaknesses:

(1) Experiments in primary T cells are required to estimate the relative contribution of LCK-dependent and LCK-independent mechanisms of CD4 signaling.

(2) The mechanistic explanation (beyond the independence of LCK binding) of the role of these motifs is unclear at the moment.

Reviewer #1 (Public Review):

The authors have addressed most of the concerns I had about the original version in this revised version.

Reviewer #1 (Public Review):

Caprylic acid (CAP), i.e., octanoic acid, is a saturated fatty acid. CAP is commonly used as a food contact surface sanitizer. In mammals, caprylic acid is related to hunger sensation (i.e., food consumption). serine hydroxymethyl transferase (SHMT) has been previously known as a potential herbicidal target. The present study involves a huge amount of work. The results are useful and contribute well to the literature. The data does support the conclusion. It does not seem that SHMT is the only target of CAP though (CAP may act on other proteins as well). A major deficiency of this manuscript is that there are many unclear, inaccurate, or unconcise descriptions.

Reviewer #1 (Public Review):

Summary:

This study used a unique acute HIV-1 infection cohort, RV217, to study the evolution of transmitted founder viral Envelope sequences under nascent immune pressure. The striking feature of the RV217 cohort is the ability to detect viremia in the first week of infection, which can be followed at discrete Fiebig stages over long time intervals. This study evaluated Env sequences at 1 week, 4 weeks, and 24 weeks to provide a picture of viral and immunological co-evolution from Fiebig Stage I (1 week), Fiebig Stages IV (4 weeks), and Fiebig Stage VI (>24 weeks). This study design enabled lineage tracing of viral variants from a single transmitted founder (T/F) over the Fiebig Stages I, IV, and VI under nascent immune pressure generated in response to the T/F virus and its subsequent mutants.

Strengths:

As expected, there were temporal differences in the appearance of virus quasispecies among the individuals, which were located predominantly in solvent-exposed residues of Env, which is consistent with prior literature. Interestingly, two waves of antibody reactivity were observed for variants with mutations in the V2 region that harbors V2i and V2p epitopes correlated with protection in the RV144 clinical trial. Two waves of antibody response, detected by SPR, were observed, with the first wave being predominated by antibodies specific for the T/F07 V2 epitope associated with H173 located on the C -strand in the V2 region. The second wave was dominated by antibodies specific for an H to Y mutation at 173 that emerged due to antibody-mediated pressure to the original H173 virus. This is a remarkable finding in three ways.

First, the mutation is in the C β-strand, an unlikely paratope contact residue, as this region of the V2 loop is shielded by glycans in Env trimer structures with full glycan representation (see PDB:5t3x). The structure used for modeling in the current study was an earlier structure, PDB:4TVP, that had many truncated glycans. This does not detract from the finding that the H173Y mutation likely causes a conformational shift from a more rigid helical/coil conformation to a more dynamic conformation with a β-stranded and -sheet core preference as indicated by the literature and by the MD simulations carried out by the authors. This observation suggests that using V2 scaffolds with both the H173 and H173Y variants will increase the breadth of potentially protective antibody responses to HIV-1, as indicated in reference 42, cited by the authors. Interestingly, the H173Y mutation abrogates reactivity to mAb CH58 and attenuates reactivity to mAb CH59 isolated from RV144 volunteers. These mAbs recognize conformationally distinct V2 epitopes, adding further credence to the conclusion that the H173Y mutation results in a conformational switch of the V2 region.

Second, the H173Y mutation affects the conformation of V2 epitopes recognized by mAbs that do not neutralize T/F HIV-1 while mediating potent ADCC. The ADCC data in the manuscript provides strong support for this hypothesis and augers for further exploration of the V2 epitopes as HIV-1 vaccine targets.

Third, it is striking that immunogens based on the H173Y mutation successfully recapitulated the observed human antibody responses in wild-type Balb/c mice. The investigators used their extensive knowledge of V2 structures and scaffold-immunogens to create the library of constructs used for this study. In this case, the ΔDSV mutation increased the breadth and magnitude of the murine antibody responses.

Reviewer #2 (Public Review):

Summary:

Liao and colleagues generated tagged SMAD1 and SMAD5 mouse models and identified genome occupancy of these two factors in the uterus of these mice using the CUT&RUN assay. The authors used integrative bioinformatic approaches to identify putative SMAD1/5 direct downstream target genes and to catalog the SMAD1/5 and PGR genome co-localization pattern. The role of SMAD1/5 on stromal decidualization was assayed in vitro on primary human endometrial stromal cells. The new mouse models offer opportunities to further dissect SMAD1 and SMAD5 functions without the limitation from SMAD antibodies, which is significant. The CUT&RUN data further support the usefulness of these mouse models for this purpose.

Strengths:

The strength of this study is the novelty of new mouse models and the valuable cistromic data derived from these mice. This revised manuscript provides lots of food for thought inside and outside of the field of reproductive biology.

Weaknesses:

Causal effects of SMAD1/5 on the genome occupancy of other major uterine transcription factors were discussed but not experimentally examined in the present manuscript, which is understandable.

Reviewer #1 (Public Review):

Summary:

Wang and colleagues presented an investigation of pig-origin bacteria Bacillus velezensis HBXN2020, for its released genome sequence, in vivo safety issue, probiotic effects in vitro, and protection against Salmonella infection in a murine model. Various techniques and assays are performed.

Strengths:

An extensive study on the probiotic properties of the Bacillus velezensis strain HBXN2020.

Weaknesses:

- The main results are all descriptive, without new insight advancing the field or a mechanistic understanding of the observed protection.

- Most of the results and analysis parts are separated without a link or any story-telling to deliver a concise message.

- For the Salmonella Typhimurium-induced mouse model of colitis, it is not clear how an oral infection of C57BL/6 would lead to colitis. Streptomycin is always pretreated (https://link.springer.com/protocol/10.1007/978-1-0716-1971-1_17).

Reviewer #1 (Public Review):

Summary:

In this paper, Hackwell and colleagues performed technically impressive, long-term, GCaMP fiber photometry recordings from Kiss1 neurons in the arcuate nucleus of mice during multiple reproductive states. The data show an immediate suppression of activity of arc Kiss1 neuronal activity during pregnancy that is maintained during lactation. In the absence of any apparent change in suckling stimulus or milk production, mice lacking prolactin receptors in arcuate Kiss1 neurons regained Kiss1 episodic activity and estrous cyclicity faster than control mice, demonstrating that direct prolactin action on Kiss1 neurons is at least partially responsible for suppressing fertility in this species. The effect of loss of prolactin receptors from CamK2a expressing neurons was even greater, indicating either that prolactin sensitivity in Kiss1 neurons of the RP3V contributes to lactational infertility or that other prolactin-sensitive neurons are involved. These data demonstrate the important role of prolactin in suppressing Kiss1 neuron activity and thereby fertility during the lactational period in the mouse.

Strengths:

This is the first study to monitor the activity of the GnRH pulse-generating system across different reproductive states in the same animal. Another strength in the study design is that it isolated the effects of prolactin by maintaining normal lactation and suckling (assessed indirectly using pup growth curves). The study also offers insight into the phenomenon of postpartum ovulation in mice. The results showed a brief reactivation of arcuate Kiss1 activity immediately prior to parturition, attributed to falling progesterone levels at the end of pregnancy. This hypothesis will be of interest to the field and is likely to inspire testing in future studies. With the exceptions mentioned below, the conclusions of the paper are well supported by the data, and the aims of the study were achieved. This paper is likely to raise the standard for technical expectations in the field and spark new interest in the direct impact of prolactin on Kiss1 neurons during lactation in other species.

Weaknesses:

A weakness in the approach is the use of genetic models that do not offer complete deletion of the prolactin receptor from targeted neuronal populations. A substantial proportion of Kiss1 neurons in both models retain the receptor. As a result, it is not clear whether the partial maintenance of cyclicity during lactation in the genetic models is due to incomplete deletion or to the involvement of other factors. This weakness should be more fully discussed in the text. In addition, results showing no impact of progesterone on LH secretion during lactation are surprising, given the effectiveness of progesterone-containing birth control in lactating women. The progesterone-related experiments were not well justified or discussed in the text. While the authors assert their findings may reflect an important role for prolactin in lactational infertility in other mammalian species, that remains to be seen. Hyperprolactinemia is known to suppress GnRH release, but its importance in the suppression of cyclicity during lactation is controversial. Indeed, in several species, the stimulus of suckling is considered to be the main driver of lactational fertility suppression. Data from rats shows that exogenous prolactin was unable to suppress LH release in dams deprived of their pups shortly after birth; both suckling and prolactin were necessary to suppress a post ovariectomy rise in LH levels. The duration of amenorrhea does not correlate with average prolactin levels in humans, and suckling but not prolactin was required to suppress the postpartum rise in LH in the rhesus monkey. The authors should discuss more thoroughly whether the protocol of this or other studies might result in discordant results and whether mice are likely to be an outlier in their mechanism of cycle suppression.

Reviewer #1 (Public Review):

Summary:

The study investigates the role of cylicin-1 (CYLC1) in sperm acrosome-nucleus connections and its clinical relevance to male infertility. Using mouse models, the researchers demonstrate that cylicin-1 is specifically expressed in the post acrosomal sheath-like region in spermatids and plays a crucial role in mediating acrosome-nucleus connections. Loss of CYLC1 results in severe male subfertility, characterized by acrosome detachment and aberrant head morphology in sperm. Further analysis of a large cohort of infertile men reveals CYLC1 variants in patients with sperm head deformities. The study provides valuable insights into the role of CYLC1 in male fertility and proposes CYLC1 variants as potential risk factors for human male infertility, emphasizing the importance of mouse models in understanding the pathogenicity of such variants.

Strengths:

This article demonstrates notable strengths in various aspects. Firstly, the clarity and excellent writing style contribute to the accessibility of the content. Secondly, the employed techniques are not only relevant but also complementary, enhancing the robustness of the study. The precision in their experimental design and the meticulous interpretation of results reflect the scientific rigor maintained throughout the study. Furthermore, the decision to create a second mouse model with the exact CYLC1 mutation found in humans adds significant qualitative value to the research. This approach not only validates the clinical relevance of the identified variant but also strengthens the translational impact of the findings.

Weaknesses:

There are no obvious weaknesses. While a few minor refinements, as suggested in the recommendations to authors, could enhance the overall support for the data and the authors' messages, these suggested improvements in no way diminish the robustness of the already presented data.

Reviewer #1 (Public Review):

Summary:

In this study, Nishi et al. claim that the ratio of long-term hematopoietic stem cell (LT-HSC) versus short-term HSC (ST-HSC) determines the lineage output of HSCs and reduced ratio of ST-HSC in aged mice causes myeloid-biased hematopoiesis. The authors used Hoxb5 reporter mice to isolate LT-HSC and ST-HSC and performed molecular analyses and transplantation assays to support their arguments. How the hematopoietic system becomes myeloid-biased upon aging is an important question with many implications in the disease context as well. However, their study is descriptive with remaining questions.

Weaknesses:

(1) The authors may need conceptual re-framing of their main argument because whether the ST-HSCs used in this study are functionally indeed short-term "HSCs" is questionable. The data presented in this study and their immunophenotypic definition of ST-HSCs (Lineage negative/Sca-1+/c-Kit+/Flk2-/CD34-/CD150+/Hoxb5-) suggest that authors may find hematopoietic stem cell-like lymphoid progenitors as previously shown for megakaryocyte lineage (Haas et al., Cell stem cell. 2015) or, as the authors briefly mentioned in the discussion, Hoxb5- HSCs could be lymphoid-biased HSCs. The authors disputed the idea that Hoxb5- HSCs as lymphoid-biased HSCs based on their previous 4 weeks post-transplantation data (Chen et al., 2016). However, they overlooked the possibility of myeloid reprogramming of lymphoid-biased population during regenerative conditions (Pietras et al., Cell stem cell., 2015). In other words, early post-transplant ST-HSCs (Hoxb5- HSCs) can be seen as lacking the phenotypic lymphoid-biased HSCs. Thinking of their ST-HSCs as hematopoietic stem cell-like lymphoid progenitors or lymphoid-biased HSCs makes more sense conceptually as well. ST-HSCs come from LT-HSCs and further differentiate into lineage-biased multipotent progenitor (MPP) populations including myeloid-biased MPP2 and MPP3. Based on the authors' claim, LT-HSCs (Hoxb5- HSCs) have no lineage bias even in aged mice. Then these LT-HSCs make ST-HSCs, which produce mostly memory T cells. These memory T cell-producing ST-HSCs then produce MPPs including myeloid-biased MPP2 and MPP3. This differentiation trajectory is hard to accept. If we think Hoxb5- HSCs (ST-HSCs by authors) as a sub-population of immunophenotypic HSCs with lymphoid lineage bias or hematopoietic stem cell-like lymphoid progenitors, the differentiation trajectory has no flaw.

(2) Authors' experimental designs have some caveats to support their claims. Authors claimed that aged LT-HSCs have no myeloid-biased clone expansion using transplantation assays. In these experiments, authors used 10 HSCs and young mice as recipients. Given the huge expansion of old HSC by number and known heterogeneity in immunophenotypically defined HSC populations, it is questionable how 10 out of so many old HSCs can faithfully represent the old HSC population. The Hoxb5+ old HSC primary and secondary recipient mice data (Figure 2C and D) support this concern. In addition, they only used young recipients. Considering the importance of the inflammatory aged niche in the myeloid-biased lineage output, transplanting young vs old LT-HSCs into aged mice will complete the whole picture.

(3) The authors' molecular data analyses need more rigor with unbiased approaches. They claimed that neither aged LT-HSCs nor aged ST-HSCs exhibited myeloid or lymphoid gene set enrichment but aged bulk HSCs, which are just a sum of LT-HSCs and ST-HSCs by their gating scheme (Figure 4A), showed the "tendency" of enrichment of myeloid-related genes based on the selected gene set (Figure 4D). Although the proportion of ST-HSCs is reduced in bulk HSCs upon aging, since ST-HSCs do not exhibit lymphoid gene set enrichment based on their data, it is hard to understand how aged bulk HSCs have more myeloid gene set enrichment compared to young bulk HSCs. This bulk HSC data rather suggests that there could be a trend toward certain lineage bias (although not significant) in aged LT-HSCs or ST-HSCs. The authors need to verify the molecular lineage priming of LT-HSCs and ST-HSCs using another comprehensive dataset.

(4) Some data are too weak to fully support their claims. The authors claimed that age-associated extramedullary changes are the main driver of myeloid-biased hematopoiesis based on no major differences in progenitor populations upon transplantation of 10 young HSCs into young or old recipient mice (Figure 7F) and relatively low donor-derived cells in thymus and spleen in aged recipient mice (Figure 7G-J). However, they used selected mice to calculate the progenitor populations in recipient mice (8 out of 17 from young recipients denoted by * and 8 out of 10 from aged recipients denoted by * in Figure 7C). In addition, they calculated the progenitor populations as frequency in c-kit positive cells. Given that they transplanted 10 LT-HSCs into "sub-lethally" irradiated mice and 8.7 Gy irradiation can have different effects on bone marrow clearance in young vs old mice, it is not clear whether this data is reliable enough to support their claims. The same concern applies to the data Figure 7G-J. Authors need to provide alternative data to support their claims.

Reviewer #1 (Public Review):

Summary:

Given knowledge of the amino acid sequence and of some version of the 3D structure of two monomers that are expected to form a complex, the authors investigate whether it is possible to accurately predict which residues will be in contact in the 3D structure of the expected complex. To this effect, they train a deep learning model which takes as inputs the geometric structures of the individual monomers, per-residue features (PSSMs) extracted from MSAs for each monomer, and rich representations of the amino acid sequences computed with the pre-trained protein language models ESM-1b, MSA Transformer, and ESM-IF. Predicting inter-protein contacts in complexes is an important problem. Multimer variants of AlphaFold, such as AlphaFold-Multimer, are the current state of the art for full protein complex structure prediction, and if the three-dimensional structure of a complex can be accurately predicted then the inter-protein contacts can also be accurately determined. By contrast, the method presented here seeks state-of-the-art performance among models that have been trained end-to-end for inter-protein contact prediction.

Strengths:

The paper is carefully written and the method is very well detailed. The model works both for homodimers and heterodimers. The ablation studies convincingly demonstrate that the chosen model architecture is appropriate for the task. Various comparisons suggest that PLMGraph-Inter performs substantially better, given the same input, than DeepHomo, GLINTER, CDPred, DeepHomo2, and DRN-1D2D_Inter.<br /> The authors control for some degree of redundancy between their training and test sets, both using sequence and structural similarity criteria. This is more careful than can be said of most works in the field of PPI prediction.<br /> As a byproduct of the analysis, a potentially useful heuristic criterion for acceptable contact prediction quality is found by the authors: namely, to have at least 50% precision in the prediction of the top 50 contacts.

Weaknesses:

The authors check for performance drops when the test set is restricted to pairs of interacting proteins such that the chain pair is not similar *as a pair* (in sequence or structure) to a pair present in the training set. A more challenging test would be to restrict the test set to pairs of interacting proteins such that *none* of the chains are separately similar to monomers present in the training set. In the case of structural similarity (TM-scores), this would amount to replacing the two "min"s with "max"s in Eq. (4). In the case of sequence similarity, one would simply require that no monomer in the test set is in any MMSeqs2 cluster observed in the training set. This may be an important check to make, because a protein may interact with several partners, and/or may use the same sites for several distinct interactions, contributing to residual data leakage in the test set.

The training set of AFM with v2 weights has a global cutoff of 30 April 2018, while that of PLMGraph-Inter has a cutoff of March 7 2022. So there may be structures in the test set for PLMGraph-Inter that are not in the training set of AFM with v2 weights (released between May 2018 and March 2022). The "Benchmark 2" dataset from the AFM paper may have a few additional structures not in the training or test set for PLMGraph-Inter. I realize there may be only few structures that are in neither training set, but still think that showing the comparison between PLMGraph-Inter and AFM there would be important, even if no statistically significant conclusions can be drawn.

Finally, the inclusion of AFM confidence scores is very good. A user would likely trust AFM predictions when the confidence score is high, but look for alternative predictions when it is low. The authors' analysis (Figure 6, panels c and d) seems to suggest that, in the case of heterodimers, when AFM has low confidence, PLMGraph-Inter improves precision by (only) about 3% on average. By comparison, the reported gains in the "DockQ-failed" and "precision-failed" bins are based on knowledge of the ground truth final structure, and thus are not actionable in a real use-case.

Reviewer #1 (Public Review):

Summary:

In this paper, Li and colleagues overcome solubility problems to determine the structure of FtsEX bound to EnvC from E. coli.

Strengths:

The structural work is well done and the work is consistent with previous work on the structure of this complex from P. aerugionsa.

Weaknesses:

The model does not take into account all information that the authors obtained as well as known in vivo data.

The work lacks a clear comparison to the Pseudomonas structure highlighting new information that was obtained so that it is readily available to the reader.

The authors set out to obtain the structure of FtsEX-EnvC complex from E. coli. Previously, they were unable to do so but were able to determine the structure of the complex from P. aeruginosa. Here they persisted in attacking the E. coli complex since more is known about its involvement in cell division and there is a wealth of mutants in E. coli. The structural work is well done and recapitulates the results this lab obtained with this complex from P. aeruginosa. It would be helpful to compare more directly the results obtained here with the E. coli complex with the previously reported P. aeruginosa complex - are they largely the same or has some insight been obtained from the work that was not present in the previous complex from P. aeruginosa. This is particularly the case in discussing the symmetrical FtsX dimer binding to the asymmetrical EnvC, since this is emphasized in the paper. However, Figures 3C & D of this paper appear similar to Figures 2D & E of the P. aeruginosa structure. Presumably, the additional information obtained and presented in Figure 4 is due to the higher resolution, but this needs to be highlighted and discussed to make it clear to a general audience.

The main issue is the model (Figure 6). In the model ATP is shown to bind to FtsEX before EnvC, however, in Figure 1c it is shown that ADP is sufficient to promote binding of FtsEX to EnvC.

The work here is all done in vitro, however, information from in vivo needs to be considered. In vivo results reveal that the ATP-binding mutant FtsE(D162N)X promotes the recruitment of EnvC (Proc Natl Acad Sci U S A 2011 108:E1052-60). Thus, even FtsEX in vivo can bind EnvC without ATP (not sure if this mutant can bind ADP).

Perhaps the FtsE protein from E. coli has to have bound nucleotides to maintain its 3D structure.

Reviewer #1 (Public Review):

Summary:

The authors present a new application of the high-content image-based morphological profiling Cell Painting (CP) to single cell type classification in mixed heterogeneous induced pluripotent stem cell-derived mixed neural cultures. Machine learning models were trained to classify single cell types according to either "engineered" features derived from the image or from the raw CP multiplexed image. The authors systematically evaluated experimental (e.g., cell density, cell types, fluorescent channels) and computational (e.g., different models, different cell regions) parameters and convincingly demonstrated that focusing on the nucleus and its surroundings contains sufficient information for robust and accurate cell type classification. Models that were trained on mono-cultures (i.e., containing a single cell type) could generalize for cell type prediction in mixed co-cultures, and describe intermediate states of the maturation process of iPSC-derived neural progenitors to differentiation neurons.

Strengths:

Automatically identifying single-cell types in heterogeneous mixed-cell populations holds great promise to characterize mixed-cell populations and to discover new rules of spatial organization and cell-cell communication. Although the current manuscript focuses on the application of quality control of iPSC cultures, the same approach can be extended to a wealth of other applications including an in-depth study of the spatial context. The simple and high-content assay democratizes use and enables adoption by other labs.

The manuscript is supported by comprehensive experimental and computational validations that raise the bar beyond the current state of the art in the field of high-content phenotyping and make this manuscript especially compelling. These include (i) Explicitly assessing replication biases (batch effects); (ii) Direct comparison of feature-based (a la cell profiling) versus deep-learning-based classification (which is not trivial/obvious for the application of cell profiling); (iii) Systematic assessment of the contribution of each fluorescent channel; (iv) Evaluation of cell-density dependency; (v) Explicit examination of mistakes in classification; (vi) Evaluating the performance of different spatial contexts around the cell/nucleus; (vii) Generalization of models trained on cultures containing a single cell type (mono-cultures) to mixed co-cultures; (viii) Application to multiple classification tasks.

I especially liked the generalization of classification from mono- to co-cultures (Figure 4C), and quantitatively following the gradual transition from NPC to Neurons (Figure 5H).

The manuscript is well-written and easy to follow.

Weaknesses:

I am not certain how useful/important the specific application demonstrated in this study is (quality control of iPSC cultures), this could be better explained in the manuscript. Another issue that I feel should be discussed more explicitly is how far can this application go - how sensitively can the combination of cell painting and machine learning discriminate between cell types that are more subtly morphologically different from one another?

Regarding evaluations, the use of accuracy, which is a measure that can be biased by class imbalance, is not the most appropriate measurement in my opinion. The confusion matrices are a great help, but I would recommend using a measurement that is less sensitive for class imbalance for cell-type classification performance evaluations. Another issue is that the performance evaluation is calculated on a subset of the full cell population - after exclusion/filtering. Could there be a bias toward specific cell types in the exclusion criteria? How would it affect our ability to measure the cell type composition of the population?

I am not entirely convinced by the arguments regarding the superiority of the nucleocentric vs. the nuclear representations. Could it be that this improvement is due to not being sensitive/ influenced by nucleus segmentation errors?

GRADCAM shows cherry-picked examples and is not very convincing.

There are many missing details in the figure panels, figure legend, and text that would help the reader to better appreciate some of the technical details, see details in the section on recommendations for the authors.

Reviewer #1 (Public Review):

Summary:

SUMO proteins are processed and then conjugated to other proteins via a C-terminal di-glycine motif. In contrast, the N-terminus of some SUMO proteins (SUMO2/3) contains lysine residues that are important for the formation of SUMO chains. Using NMR studies, the N-terminus of SUMO was previously reported to be flexible (Bayer et al., 1998). The authors are investigating the role of the flexible (referred to as intrinsically disordered) N-terminus of several SUMO proteins. They report their findings and modeling data that this intrinsically disordered N-terminus of SUMO1 (and the C. elegans Smo1) regulates the interaction of SUMO with SUMO interacting motifs (SIMs).

Strengths:

Among the strongest experimental data suggesting that the N-terminus plays an inhibitory function are their observations that<br /> (1) SUMO1∆N19 binds more efficiently to SIM-containing Usp25, Tdp2, and RanBp2,<br /> (2) SUMO1∆N19 shows improved sumoylation of Usp25,<br /> (3) changing negatively-charged residues, ED11,12KK in the SUMO1 N-terminus increased the interaction and sumoylation with/of USP25.

The paper is very well-organized, clearly written, and the experimental data are of high quality. There is good evidence that the N-terminus of SUMO1 plays a role in regulating its binding and conjugation to SIM-containing proteins. Therefore, the authors are presenting a new twist in the ever-evolving saga of SUMO, SIMs, and sumoylation.

Weaknesses:

Much has been learned about SUMO through structure-function analyses and this study is another excellent example. I would like to suggest that the authors take some extra time to place their findings into the context of previous SUMO structure-function analyses. Furthermore, it would be fitting to place their finding of a potential role of N-terminally truncated Smo1 into the context of the many prior findings that have been made with regard to the C. elegans SUMO field. Finally, regarding their data modeling/simulation, there are questions regarding the data comparisons and whether manipulations of the N-terminus also have an effect on the 70/80 region of the core.

Reviewer #1 (Public Review):

Summary:

In this manuscript, Ngo et al. report a peculiar effect where a single base mismatch (CC) can enhance the mechanical stability of a nucleosome. In previous studies, the same group used a similar state-of-the-art fluorescence-force assay to study the unwrapping dynamics of 601-DNA from the nucleosome and observed that force-induced unwrapping happens more slowly for DNA that is more bendable because of changes in sequence or chemical modification. This manuscript appears to be a sequel to this line of projects, where the effect of CC is tested. The authors confirmed that CC is the most flexible mismatch using the FRET-based cyclization assay and found that unwrapping becomes slower when CC is introduced at three different positions in the 601 sequence. The CC mismatch only affects the local unwrapping dynamics of the outer turn of nucleosomal DNA.

Strengths:

These results are in good agreement with the previously established correlation between DNA bendability and nucleosome mechanical stability by the same group. This well-executed, technically sound, and well-written experimental study contains novel nucleosome unwrapping data specific to the CC mismatch and 601 sequence, the cyclizability of DNA containing all base pair mismatches, and the unwrapping of 601-DNA from xenophus and yeast histones. Overall, this work will be received with great interest by the biophysics community and is definitely worth attention.

Weaknesses:

The scope and impact of this study are somewhat limited due to the lack of sequence variation. Whether the conclusion from this study can be generalized to other sequences and other bendability-enhancing mismatches needs further investigation.

Major questions:

(1) As pointed out by the authors, the FRET signal is not sensitive to nucleosome position; therefore, the increasing unwrapping force in the presence of CC can be interpreted as the repositioning of the nucleosome upon perturbation. It is then also possible that CC-containing DNA is not positioned exactly the same as normal DNA from the start upon nucleosome assembly, leading to different unwrapping trajectories. What is the experimental evidence that supports identical positioning of the nucleosomes before the first stretch?

(2) The authors chose a constant stretching rate in this study. Can the authors provide a more detailed explanation or rationale for why this rate was chosen? At this rate, the authors found hysteresis, which indicates that stretching is faster than quasi-static. But it must have been slow and weak enough to allow for reversible unwrapping and wrapping of a CC-containing DNA stretch longer than one helical turn. Otherwise, such a strong effect of CC at a single location would not be seen. I am also curious about the biological relevance of the magnitude of the force. Can such force arise during nucleosome assembly in vivo?

(3) In this study, the CC mismatch is the only change made to the 601 sequence. For readers to truly appreciate its unique effect on unwrapping dynamics as a base pair defect, it would be nice to include the baseline effects of other minor changes to the sequence. For example, how robust is the unwrapping force or dynamics against a single-bp change (e.g., AT to GC) at the three chosen positions?

(4) The last section introduces yeast histones. Based on the theme of the paper, I was expecting to see how the effect of CC is or is not preserved with a different histone source. Instead, the experiment only focuses on differences in the unwrapping dynamics. Although the data presented are important, it is not clear how they fit or support the narrative of the paper without the effect of CC.

(5) It is stated that tRNA was excluded in experiments with yeast-expressed nucleosomes. What is the reason for excluding it for yeast nucleosomes? Did the authors rule out the possibility that tRNA causes the measured difference between the two nucleosome types?

Reviewer #1 (Public Review):

Summary:<br /> TMC7 knockout mice were generated by the authors and the phenotype was analyzed. They found that Tmc7 is localized to Golgi and is needed for acrosome biogenesis.

Strengths:<br /> The phenotype of infertility is clear, and the results of TMC7 localization and the failed acrosome formation are highly reliable. In this respect, they made a significant discovery regarding spermatogenesis.

Weaknesses:<br /> There are also some concerns, which are mainly related to the molecular function of TMC7 and Figure 5. It is understandable that TMC7 exhibits some channel activity in the Golgi and somehow affects luminal pH or Ca2+, leading to the failure of acrosome formation. On the other hand, since they are conducting the pH and calcium imaging from the cytoplasm, I do not think that the effect of TMC7 channel function in Golgi is detectable with their methods. Rather, it is more likely that they are detecting apoptotic cells that have no longer normal ion homeostasis. Another concern is that n is only 3 for these imaging experiments.

Reviewer #1 (Public Review):

Among the many challenges in the cilia field, is the question of how multicellular organisms assemble a variety of structurally and functionally specialized cilia, including cilia of different lengths. This study addresses the important question of how ciliary length differences are established in vertebrates. Specifically, the authors analyzed the role of intraflagellar transport (IFT) in ciliary length regulation in zebrafish, exploiting the transparency of the embryos. Zebrafish possess functionally specialized motile and non-motile cilia in a variety of tissues. Expression of GFP-tagged IFT88, a component of the IFT-B subcomplex, in a corresponding mutant, allowed the authors to image IFT in five distinct types of cilia. They note that IFT moves faster in longer cilia. Tagging and imaging of the IFT-A protein IFT43 further support this observation. IFT speed was largely unaffected in knock-out and morphants targeting the BBSome, various kinesin-2 motors, and the posttranslational modifications of tubulin polyglycylation and polyglutamylation. Using high-resolution STED imaging, the authors observe that IFT signals (likely, corresponding to IFT trains) are smaller in the shorter spinal cord cilia compared to the long cristae cilia. Based on these observations, the authors test the hypothesis that larger IFT trains recruit more motors or coordinate the motors better, resulting in faster trains, and causing cilia to be longer. This is further tested using partial knock-down of IFT88-GFP, which resulted in shorter crista cilia, reduced IFT particle number, size, and velocity. Some parts of the manuscript show "negative" data (e.g., ciliary length and IFT are not affected by the loss of BBS4) but these add beautifully to the overall story and allow for additional conclusions such as the minor role of ttll3 and ccp knockouts on ciliary length in this model. This is an excellent study, which documents IFT in a vertebrate species and explores its regulation. The data are of high quality and support most of the conclusions.

(1) The main hypothesis/conclusion is summarized in the abstract: "Our study presents an intriguing model of cilia length regulation via controlling IFT speed through the modulation of the size of the IFT complex." The data clearly document the remarkable correlation between IFT velocity and ciliary length in the different cells/tissues/organs analyzed. The experimental test of this idea, i.e., the knock-down of GFP-IFT88, further supports the conclusion but needs to be interpreted more carefully. While IFT particle size and train velocity were reduced in the IFT88 morphants, the number of IFT particles is even more decreased. Thus, the contributions of the reduction in train size and velocity to ciliary length are, in my opinion, not unambiguous. Also, the concept that larger trains move faster, likely because they dock more motors and/or better coordinating kinesin-2 and that faster IFT causes cilia to be loner, is to my knowledge, not further supported by observations in other systems (see below).

(2) I think the manuscript would be strengthened if the IFT frequency would also be analyzed in the five types of cilia. This could be done based on the existing kymographs from the spinning disk videos. As mentioned above, transport frequency in addition to train size and velocity is an important part of estimating the total number of IFT particles, which bind the actual cargoes, entering/moving in cilia.

(3) Here, the variation in IFT velocity in cilia of different lengths within one species is documented - the results document a remarkable correlation between IFT velocity and ciliary length. These data need to be compared to observations from the literature. For example, the velocity of IFT in the quite long (~ 100 um) olfactory cilia of mice is similar to that observed in the rather short cilia of fibroblasts (~0.6 um/s). In Chlamydomonas, IFT velocity is not different in long flagella mutants compared to controls. Probably data are also available for C. elegans or other systems. Discussing these data would provide a broader perspective on the applicability of the model outside of zebrafish.

Reviewer #1 (Public Review):

Summary:

The study "Effect of alpha-tubulin acetylation on the doublet microtubule structure" by S. Yang et al employs a multi-disciplinary approach, including cryo-electron microscopy (cryo-EM), molecular dynamics, and mass spectrometry, to investigate the impact of α-tubulin acetylation at the lysine 40 residue (αK40) on the structure and stability of doublet microtubules in cilia. The work reveals that αK40 acetylation exerts a small-scale, but significant, effect by influencing the lateral rotational angle of the microtubules, thereby affecting their stability. Additionally, the study provided an explanation of the relationship between αK40 acetylation and phosphorylation within cilia, despite that the details still remain elusive. Overall, these findings contribute to our understanding of how post-translational modifications can influence the structure, composition, stability, and functional properties of important cellular components like cilia.

Strengths:

(1) Multi-Disciplinary Approach: The study employs a robust combination of cryo-electron microscopy (cryo-EM), molecular dynamics, and mass spectrometry, providing a comprehensive analysis of the subject matter.<br /> (2) Significant Findings: The paper successfully demonstrates the impact of αK40 acetylation on the lateral rotational angles between protofilaments (inter-PF angles) of doublet microtubules in cilia, thereby affecting their stability. This adds valuable insights into the role of post-translational modifications in cellular components.<br /> (3) Exploration of Acetylation-Phosphorylation Relationship: The study also delves into the relationship between αK40 acetylation and phosphorylation within cilia, contributing to a broader understanding of post-translational modifications.<br /> (4) High-quality data: The authors are cryo-EM experts in the field and the data quality presented in the manuscript is excellent.<br /> (5) Depth of analysis: The authors analyzed the effects of αK40 acetylation in excellent depth which significantly improved our understanding of this system.

Weaknesses:

I have no major concerns about this paper.

Reviewer #1 (Public Review):

Summary:<br /> In the present study, authors found the ternary complex formed by NCAN, TNC, and HA as an important factor facilitating the multipolar to bipolar transition in the intermediate zone (IZ) of the developing cortex. NCAM binds HA via the N-terminal Link modules, meanwhile, TNC cross-links NCAN through the CDL domain at the C-terminal. The expression and right localization of these three factors facilitate the multipolar-bipolar transition necessary for immature neurons to migrate radially. TNC and NCAM are also involved in neuronal morphology. The authors used a wide range of techniques to study the interaction between these three molecules in the developing cortex. In addition, single and double KO mice for NCAN and TNC were analyzed to decipher the role of these molecules in neuronal migration and morphology.

Strengths:<br /> The study of the formation of the cerebral cortex is crucial to understanding the pathophysiology of many neurodevelopmental disorders associated with malformation of the cerebral cortex. In this study, the authors showed, for the first time, that the ternary complex formed by NCAN, TNC, and HA promotes neuronal migration. The results regarding the interaction between the three factors forming the ternary complex are convincing.

Reviewer #1 (Public Review):

Summary:

The manuscript by Sztangierska et al explores how the Hsp70 chaperone together with its JDP-NEF cofactors and Hsp104 disentangle aggregated proteins. Specifically, the study provides mechanistic findings that explain what role the NEF class Hsp110 has in protein disaggregation. The results explain several previous observations related to Hsp110 in protein disaggregation. Importantly, the study provides compelling evidence that Hsp110 acts early in the disaggregation process.

Strengths:<br /> (1) This is a very well-performed study with multiple in vitro experiments that provide convincing support for the claims.

(2) An important finding is that the study places the Hsp110 function early in the disaggregation process.

(3) The study has an important value in that it picks up on a number of observations in the field that have not been explored or directly tested by experiment. The presented results settle questions and controversy regarding Hsp110 function in disaggregation.

Weaknesses:

(1) While the key finding of this manuscript is that it places Hsp110 early in the disaggregation process, the other findings are advancing the field less.

(2) A claim in the paper is that Hsp110 NEFs improve disaggregation by Hsp70 in a manner dependent on the class of JDP (class A vs class B). However, it rather appears that in the experiments class B JDPs support robust disaggregation, while class A JDPs are not as effective. This simple fact may very well underly the differences and questions if class specificity should be in focus in the interpretation of the data.

(3) The experiments differ somewhat in regard to the aggregated protein used. For example, in Figure 1A, FFL is used with only limited reactivation (10% reactivated at the last timepoint and the curve is flattening), while in Figure 2B FFL-EGFP is used to monitor microscopically what appears to be complete disaggregation. Does FFL-EGFP behave the same as FFL in assays such as the one in Figure 1A or are there major differences that may impact how the data should be interpreted?

Reviewer #1 (Public Review):

Summary:

In this manuscript, the authors show compelling data indicating that ExoIII has significant ssDNA nuclease activity that is posited to interfere with biosensor assays. This does not come as a surprise as other published works have indeed shown the same, but in this work, the authors provide a deeper analysis of this underestimated activity.

Strengths:

The authors used a variety of assays to examine the ssDNA nuclease activity of ExoIII and its origin. Fluorescence-based assays and native gel electrophoresis, combined with MS analysis clearly indicate that both commercial and laboratory purified ExoIII contain ssDNA nuclease activity. Mutational analysis identifies the residues responsible for this activity. Of note is the observation in this submitted work that the sites of ssDNA and dsDNA exonuclease activity overlap, suggesting that it may be difficult to identify mutations that affect one activity but not the other. In this regard, it is of interest the observation by the authors that the ssDNA nuclease activity depends on the sequence composition of the ssDNA, and this may be used as a strategy to suppress this activity when necessary. For example, the authors point out that a 3′ A4-protruding ssDNA could be employed in ExoIII-based assays due to its resistance to digestion. However, this remains an interesting suggestion that the authors do not test, but that would have strengthened their conclusion.

Weaknesses:

The authors provide a wealth of experimental data showing that E. coli ExoIII has ssDNA nuclease activities, both exo- and endo-, however this work falls short in showing that indeed this activity practically interferes with ExoIII-driven biosensor assays, as suggested by the authors. Furthermore, it is not clear what new information is gained compared to the one already gathered in previously published works (e.g. references 20 and 21). Also, the authors show that ssDNA nuclease activity has sequence dependence, but in the context of the observation that this activity is driven by the same site as dsDNA Exo, how does this differ from similar sequence effects observed for the dsDNA Exo? (e.g. see Linxweiler, W. and Horz, W. (1982). Nucl. Acids Res. 10, 4845-4859).

Because of the claim that the underestimated ssDNA nuclease activity can interfere with commercially available assays, it would have been appropriate to test this. The authors only show that ssDNA activity can be identified in commercial ExoIII-based kits, but they do not assess how this affects the efficiency of a full reaction of the kit. This could have been achieved by exploiting the observed ssDNA sequence dependence of the nuclease activity. In this regard, the work cited in Ref. 20 showed that indeed ExoIII has ssDNA nuclease activity at concentrations as low as 50-fold less than what test in this work. Ref 20 also tested the effect of the ssDNA nuclease activity in Targeted Recycle Assays, rather than just testing for its presence in a kit.

Because of the implication that the presence of ssDNA exonuclease activity may have in reactions that are supposed to only use ExoIII dsDNA exonuclease, it is surprising that in this submitted work no direct comparison of these two activities is done. Please provide an experimental determination of how different the specific activities for ssDNA and dsDNA are.

Reviewer #1 (Public Review):

Summary:<br /> In this study, the authors set out to determine whether colorectal cancer surgery site (right, left, rectal) and chemotherapy impact the subsequent risk of developing T2DM in the Danish national health register.

Strengths:<br /> - The research question is conceptually interesting<br /> - The Danish national health register is a comprehensive health database<br /> - The data analysis was thorough and appropriate<br /> -The findings are interesting, and a little surprising that there was no impact of chemotherapy on the development of T2DM<br /> - The authors have addressed my previous clarifications and questions.

- Regarding the generalizability of this study, as the authors discuss the prevalence of T2DM and obesity are lower in Denmark than in a number of other high income countries. Therefore, similar studies in other populations would be of interest.<br /> - The study includes individuals who filled a prescription for diabetes medication, so likely includes some individuals with transient hyperglycemia/steroid induced diabetes during chemotherapy, rather than those with new onset longterm T2DM.

Overall, the authors achieved their aims, and the conclusions are supported by their results as reported.<br /> The results are unlikely to significantly impact clinical practice or T2DM screening in this population, however are of interest to the community.

Reviewer #2 (Public Review):

Yanagihara and colleagues investigated the immune cell composition of bronchoalveolar lavage fluid (BALF) samples in a cohort of patients with malignancy undergoing chemotherapy and with lung adverse reactions including Pneumocystis jirovecii pneumonia (PCP) and immune-checkpoint inhibitors (ICIs) or cytotoxic drug induced interstitial lung diseases (ILDs). Using mass cytometry, their aim was to characterize the cellular and molecular changes in BAL to improve our understanding of their pathogenesis and identify potential biomarkers and therapeutic targets. In this regard, the authors identify a correlation between CD16 expression in T cells and the severity of PCP and an increased infiltration of CD57+ CD8+ T cells expressing immune checkpoints and FCLR5+ B cells in ICI-ILD patients.

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

The authors should elaborate on why different sets of markers were selected for each analysis step. E.g., Different sets of markers were used for UMAP, CITRUS and viSNE in the T cell and myeloid analysis.

Reviewer #1 (Public Review):

When writing a short review on the function of Pin1 some 15 years ago (Lippens et al., Febs J 2007), we concluded the introduction by the following sentence: "..., it seems that further analysis is required to determine whether binding or catalysis is the primary mechanism through which Pin1 affects cell cycle progression." In the present manuscript, the authors provide experimental evidence for the Pin1/PKC interaction that tips the balance towards interaction and not catalysis.

Their main data concern the interaction between the V5 domains of two PKC isoenzymes (alpha and betaII) and Pin1. This V5 domain can be further separated into a Turn Motif (TM) and a Hydrophobic Motif (HM), that both can be phosphorylated on specific positions. Phosphorylation in the TM occurs on a TPP motif, and in agreement with previous results on the same motif in Tau, Pin1 cannot isomerize efficiently the TP amide bond when the residue following the proline is another proline. Phosphorylation of the HM is not proline directed but occurs on a serine flanked by 2 aromatic residues (FSF or FSY, according to the isoenzyme). They dissect in detail the interaction of both motifs with the WW and PPIase domains and conclude that the fully phosphorylated V5 peptide binds Pin1 in a directional mode, with the TM binding to the WW domain and the HM to the PPIase domain.

In the absence of crystals of the complex, they solve a structure by NMR, and use selectively labeled peptides (and probably a lot of NMR time) to obtain a structural model. Finally, they provide functional data by silencing/overepxressing Pin1 and inactive mutants (both at the level of its WW domain and the PPIase domain) in HEK293T cells and evaluating the PKCalpha homeostasis.

The structural part of this work is interesting, as it is the first structure of Pin1 with a ligand that bridges both domains. They might want to underline this - all other structures in the PDB have a single domain complex, but never both domains by a single longer peptide. I would however question the static representation of this structure - the 90{degree sign} kink in the peptide when complexed is probably one single snapshot, but I hardly believe the PPIase/WW domain orientation to be static. Unless the authors have additional information to stand by this static structure, this point merits being commented on in the manuscript.

I would like to point out to literature that described for example the non-canonical binding (Yeh ES, Lew BO & Means AR (2006) The loss of PIN1 deregulates cyclin E and sensitizes mouse embryo fibroblasts to genomic instability. J Biol Chem 281, 241-251. Pin1 recognizes cyclin E via a noncanonical pThr384- Gly385 motif [33] rather than the pThr380-Pro381 motif.). They mention briefly the absence of isomerase activity in similar TPP motifs, but this information might already come in the Results section.

The weakest part seems the in vivo data. Although this is not the main focus of this lab, there is some issues that could be addressed. The expression levels of Pin1 and PKCa are amazingly linear (Fig 7A), but when they overexpress WT Pin1 in a KO line, with 3-4 times higher overexpression, the PKCa levels are hardly higher than in the original WT cell line. Also, the levels in the W34A/R68A/R69A (abolishing both WW and PPIase binding functions) are surprising, why would PKCa levels rise above the level found in the Pin1 KO cells? Finally, if even slight overexpression of the C113S catalytically inactive mutant leads to more efficient PKCa degradation than overexpression of the WT Pin1 (Figure 7C), it is hard to interpret. The conclusion that Pin1-mediated regulation of PKCa requires a bivalent interaction mode of Pin1 with PKCa independent of its catalytic activity do depend on these data, so they merit further analysis.

Reviewer #1 (Public Review):

By using deep convolutional neural networks (CNNs) as model for the visual system, this study aims at understanding and explaining the emergence of mirror-symmetric viewpoint tuning in the brain.

Major strengths of the methods and results:

(1) The paper presents comprehensive, insightful and detailed analyses investigating how mirror-symmetric viewpoint tuning emergence in artificial neural networks, providing significant and novel insights into this complex process.<br /> (2) The authors analyze reflection equivariance and invariance in both trained and untrained CNNs' convolutional layers. This elucidates how object categorization training gives rise to mirror-symmetric invariance in the fully-connected layers.<br /> (3) By training CNNs on small datasets of numbers and a small object set excluding faces, the authors demonstrate mirror-symmetric tuning's potential to generalize to untrained categories and the necessity of view-invariant category training for its emergence.<br /> (4) A further analysis probes the contribution of local versus global features to mirror-symmetric units in the first fully-connected layer of a network. This innovative analysis convincingly shows that local features alone suffice for the emergence of mirror-symmetric tuning in networks.<br /> (5) The results make a clear prediction that mirror-symmetric tuning should also emerge for other bilaterally symmetric categories, opening avenues for future neural studies.

Major weaknesses of the methods and results:

(1) The authors propose a mirror-symmetric viewpoint tuning index, which, although innovative, complicates comparison with previous work and this choice is not well motivated. This index is based on correlating representational dissimilarity matrices (RDMs) with their flipped versions, a method differing from previous approaches.<br /> (2) Faces exhibit unique behavior in terms of the progression of mirror-symmetric viewpoint tuning and their training task and dataset dependency. Given that mirror-symmetric tuning has been identified in the brain for faces, it would be beneficial to discuss this observation and provide potential explanations.<br /> (3) Previous work reported critical differences between CNNs and neural representations in area AL indicating that mirror-symmetric viewpoint tuning is less present than view invariance in CNNs compared to area AL. While such findings could potentially limit the usefulness of CNNs as models for mirror-symmetric viewpoint tuning in the brain, they are not addressed in the study.<br /> (4) The study's results, while informative, are qualitative rather than quantitative, and lack direct comparison with neural data. This obscures the implications for neural mechanisms and their relevance to the broader field.

The study provides compelling evidence that learning to discriminate bilaterally symmetric objects (beyond faces) induces mirror-symmetric viewpoint tuning in the networks, qualitatively similar to the brain. Moreover, the results suggest that this tuning can, in principle, generalize beyond previously trained object categories. Overall, the study provides important conclusions regarding the emergence of mirror-symmetric viewpoint tuning in networks, and potentially the brain. However, the conducted analyses and results do not entirely address the question why mirror-symmetric viewpoint tuning emerges in networks or the brain. Specifically, the results leave open whether mirror-symmetric viewpoint tuning is indeed necessary to achieve view invariance for bilaterally symmetric objects.

Taken together, this study moves us a step closer to uncovering the origins of mirror-symmetric tuning in networks, and has implications for more comprehensive investigations into this neural phenomenon in the brain. The methods of probing CNNs are innovative and could be applied to other questions in the field. This work will be of broad interest to cognitive neuroscientists, psychologists, and computer scientists.

Reviewer #1 (Public Review):

In this manuscript, the authors perform a very thorough, extensive characterization of the impact of an iron-rich diet on multiple phenotypes in a wide range of inbred mouse strains. While a work of this type does not offer mechanistic insights, the value of the study lies not only in its immediate results but also in what it can offer to future researchers as they explore the genetic basis of iron levels and other related phenotypes in rodent studies. The creation of a web resource and the offer from the authors to share all available samples is particularly laudable, and helps to increase the accessibility of the work to other scientists. There is one shortcoming to the work however. To induce iron overload in mice in the main study in this work, mice were placed on an iron-rich diet that differed in its composition from the baseline diet in more than just iron. This could influence some of the phenotypes observed in this study.

Reviewer #1 (Public Review):

Summary:<br /> Cell-to-cell communication is essential for higher functions in bacterial biofilms. Electrical signals have proven effective in transmitting signals across biofilms. These signals are then used to coordinate cellular metabolisms or to increase antibiotic tolerance. Here, the authors have reported for the first time coordinated oscillation of membrane potential in E. coli biofilms that may have a functional role in photoprotection.

Strengths:<br /> - The authors report original data.<br /> - For the first time, they showed that coordinated oscillations in membrane potential occur in E. Coli biofilms.<br /> - The authors revealed a complex two-phase dynamic involving distinct molecular response mechanisms.<br /> - The authors developed two rigorous models inspired by 1) Hodgkin-Huxley model for the temporal dynamics of membrane potential and 2) Fire-Diffuse-Fire model for the propagation of the electric signal.<br /> - Since its discovery by comparative genomics, the Kch ion channel has not been associated with any specific phenotype in E. coli. Here, the authors proposed a functional role for the putative K+ Kch channel : enhancing survival under photo-toxic conditions.

Weaknesses:<br /> - Since the flow of fresh medium is stopped at the beginning of the acquisition, environmental parameters such as pH and RedOx potential are likely to vary significantly during the experiment. It is therefore important to exclude the contributions of these variations to ensure that the electrical response is only induced by light stimulation. Unfortunately, no control experiments were carried out to address this issue.<br /> - Furthermore, the control parameter of the experiment (light stimulation) is the same as that used to measure the electrical response, i.e. through fluorescence excitation. The use of the PROPS system could solve this problem.<br /> - Electrical signal propagation is an important aspect of the manuscript. However, a detailed quantitative analysis of the spatial dynamics within the biofilm is lacking. In addition, it is unclear if the electrical signal propagates within the biofilm during the second peak regime, which is mediated by the Kch channel. This is an important question, given that the fire-diffuse-fire model is presented with emphasis on the role of K+ ions.<br /> - Since deletion of the kch gene inhibits the long-term electrical response to light stimulation (regime II), the authors concluded that K+ ions play a role in the habituation response. However, Kch is a putative K+ ion channel. The use of specific drugs could help to clarify the role of K+ ions.<br /> - The manuscript as such does not allow us to properly conclude on the photo-protective role of the Kch ion channel.<br /> - The link between membrane potential dynamics and mechanosensitivity is not captured in the equation for the Q-channel opening dynamics in the Hodgkin-Huxley model (Supp Eq 2).<br /> - Given the large number of parameters used in the models, it is hard to distinguish between prediction and fitting.

Reviewer #1 (Public Review):

Summary:

Zheng et al. study the 'glass' transitions that occur in proteins at ca. 200K using neutron diffraction and differential isotopic labeling (hydrogen/deuterium) of the protein and solvent. To overcome limitations in previous studies, this work is conducted in parallel with 4 proteins (myoglobin, cytochrome P450, lysozyme, and green fluorescent protein) and experiments were performed at a range of instrument time resolutions (1ns - 10ps). The author's data looks compelling, and suggests that transitions in the protein and solvent behavior are not coupled and contrary to some previous reports, the apparent water transition temperature is a 'resolution effect'; i.e. instrument response is limited. This is likely to be important in the field, as a reassessment of solvent 'slaving' and the role of the hydration shell on protein dynamics should be reassessed in light of these findings.

Strengths:

The use of multiple proteins and instruments with a rate of energy resolution/ timescales.

Weaknesses:

The paper could be organised to better allow the comparison of the complete dataset collected.<br /> The extent of hydration clearly influences the protein transition temperature. The authors suggest that "water can be considered here as lubricant or plasticizer which facilitates the motion of the biomolecule." This may be the case, but the extent of hydration may also alter the protein structure.

Reviewer #1 (Public Review):

Summary:

This Research Advance is an extension of this group's prior eLife paper published in 2022 on the conserved roles of the Hippo pathway effector Yorkie in C. owczarzaki (PMID: 35659869). This species is an amoeba that holds an important phylogenetic position as a close relative of multicellular animals. The prior study used genome editing to delete the C. owczarzaki Yki (termed coYki) and found that Yki is not required for proliferation but instead regulates cell contractility and cell aggregation. In the current study, the authors wanted to address whether Hippo pathway kinases - coHippo (coHpo) and coWarts (coWts) - regulate coYki and whether they are dispensable for proliferation but instead regulate cell contractility and cell aggregation. They used genome editing to delete coHpo and coWts singly in C. owczarzaki. Both mutant strains had increased nuclear location of transfected coYki (tagged with Scarlet), suggesting that Hippo kinase pathway regulation of Yki is conserved in this organism. Neither kinase is required for proliferation. Either kinase mutant strain had a significantly increased percentage of cells that were elongated, which was relatively rare in a control population. The incident of elongation could be enhanced in both kinase-mutant and in control cells when myosin inhibitors were added to the media. coHpo and coWts-mutant aggregates were more tightly packed than control cell aggregates, which they hypothesize is due to the increased contractility seen in kinase-mutant cells. They could reduce the density of packing in kinase-mutant aggregates when they treated the cells with myosin or F-actin inhibitors. To test whether the effects observed in kinase-mutant strains were due to increased Yki activation, they generated a coYki with four S to A substitutions (termed coYki4SA), which should produce a dominant-active Yki impervious to phosphorylation and hence inactivation by Hippo kinases. Control C. owczarzaki cells transfected with coYki4SA had increased cell density in aggregates and elongation in adherent cells. These results support their conclusions that coHpo and coWts regulate cell contractility and cell packing through coYki.

Strengths:

The major strengths of the paper include high quality data, robust analyses of the data, and a well-written manuscript. The combination of genome editing in C. owczarzaki, transfection of C. owczarzaki, and time-lapse movies of adherent cells generally support the conclusions (1) that control of cell density is an ancient function of the Hippo pathway; (2) that Hippo pathway control of cytoskeletal properties and contractile behavior underlie its regulation of cell density, and (3) that Hippo kinase control of Yki localization is likely an ancient function of the pathway.

Weaknesses:

There are no weaknesses.

Reviewer #1 (Public Review):

Summary:

In "Prediction error determines how memories are organized in the brain: a study of Pavlovian fear 2 extinction in rats", Kennedy et al examine how new information is organized in memory. They tested an idea based on latent theory that suggests that a large prediction error leads to the formation of a new memory, whereas a small prediction error leads to memory updating. They directly tested the prediction by extinguishing fear-conditioned rats with gradual extinction. For their experiment, gradual extinction was carried out by progressively reducing the intensity of shocks that were co-terminated with the CS, until the CS was presented alone. Doing so resulted in diminished spontaneous recovery and reinstatement compared to Standard Extinction. The results are compelling, and have important implications for the field of fear learning and memory as well as translation to anxiety-related disorders.

The authors carried out the Spontaneous Recovery experiment in 2 separate experiments. In one, they found differences between the Gradual and Standard Extinction groups, but in the second, they did not. It seems that their reinstatement test was more robust, and showed significant differences between the Gradual and Standard Extinction groups.

The authors carried out important controls that enable proper contextualization of the findings. They included a "Home" group, in which rats received fear conditioning, but not extinction manipulation. Relative to this group, the Gradual and Standard extinction groups showed a reduction in freezing.

In Experiments 3 and 4, the authors essentially carried out clever controls that served to examine whether shock devaluation (Experiment 4) and reduction in shock intensity (rather than a gradual decrease in shock intensity) (Experiment 3) would also yield a decrease in the return of fear. In line with a latent-cause updating explanation for accounting for the Gradual Extinction, they did not.

In Experiment 5, the authors examined whether a prediction error produced by a change of context might contribute interference to the latent cause updating afforded by the Gradual Extinction. Such a prediction would align with a more flexible interpretation of a latent-cause model, such as those proposed by Redish (2007) and Gershman et al (2017), but not the latent-cause interpretation put forth by the Cochran-Cisler model (2019). Their findings showed that whereas Gradual Extinction carried out in the same context as acquisition resulted in less return of fear than Standard Extinction, it actually yielded a greater degree of return of fear when carried out in a different context, in support of the Redish and Gershman accounts, but not Cochran-Cisler.

Experiment 6 extended the findings from Experiment 5 in a different state-splitting modality: timing. In this experiment, the authors tested whether a shift in temporal context also influenced the gradual extinction effect. They thus carried out the extinction sessions 21 days after conditioning. They found that while Gradual Extinction was indeed effective when carried out one day after fear conditioning, it did not when conducted 21 days later.

The authors next carried out an omnibus analysis which included all the data from their 6 experiments, and found that overall, Gradual Extinction resulted in diminished return of fear relative to Standard Extinction. I thought the omnibus analysis was a great idea and an appropriate way to do their data justice.

Strengths:

Compelling findings. The data support the conclusions. 6 rigorous experiments were conducted which included clever controls. Data include male and female rats. I really liked the omnibus analysis.

Weaknesses:

None noted.

Reviewer #1 (Public Review):

Summary:

This is an interesting study that performs scRNA-Seq on infected and uninfected wounds. The authors sought to understand how infection with E. faecalis influences the transcriptional profile of healing wounds. The analysis demonstrated that there is a unique transcriptional profile in infected wounds with specific changes in macrophages, keratinocytes, and fibroblasts. They also speculated on potential crosstalk between macrophages and neutrophils and macrophages and endothelial cells using NicheNet analysis and CellChat. Overall the data suggest that infection causes keratinocytes to not fully transition which may impede their function in wound healing and that the infection greatly influenced the transcriptional profile of macrophages and how they interact with other cells.

Strengths:

It is a useful dataset to help understand the impact of wound infection on the transcription of specific cell types. The analysis is very thorough in terms of transcriptional analysis and uses a variety of techniques and metrics.

Weaknesses:

Some drawbacks of the study are the following. First, the fact that it only has two mice per group, and only looks at one time point after wounding decreases the impact of the study. Wound healing is a dynamic and variable process so understanding the full course of the wound healing response would be very important to understand the impact of infection on the healing wound. Including unwounded skin in the scRNA-Seq would also lend a lot more significance to this study. Another drawback of the study is that mouse punch biopsies are very different than human wounds as they heal primarily by contraction instead of re-epithelialization like human wounds. So while the conclusions are generally supported the scope of the work is limited.

Reviewer #1 (Public Review):

Abreo et al. performed a detailed multidisciplinary analysis of a pathogenic variant of the KCNQ2 ion channel subunit identified in a child with neonatal-onset epilepsy and neurodevelopmental disorders. These analyses revealed multiple molecular and cellular mechanisms associated with this variant and provided important insights into what distinguishes distinct pathogenic variants of KCNQ2 associated with self-limited familial neonatal epilepsy versus those leading to developmental and epileptic encephalopathy, and how they may mechanistically differ, to result in different extents of developmental impairment.

The authors first provide a detailed clinical description of the patient heterozygous for a novel pathogenic variant encoding KCNQ2 G256W. They then model the structure of the G256W variant based on recent cryo-EM structures of KCNQ2 and other ion channel subunits and find that while the affected position is quite distinct from the channel pore, it participates in a novel, evolutionarily conserved set of amino acids that form a network of hydrogen bonds that stabilize the structure of the pore domain.

They then undertake a series of rigorous and quantitative laboratory experiments in which the KCNQ2 G256W variant is coexpressed exogenously with WT KCNQ2 and KCNQ3 subunits in heterologous cells, and endogenously in novel gene-edited mice generated for this study. This includes detailed electrophysiological analyses in the transfected heterologous cells revealing the dominant-negative phenotype of KCNQ2 G256W. They found altered firing properties in hippocampal CA1 neurons in brain slices from the heterozygous KCNQ2 G256W mice.

They next showed that the expression and localization of KCNQ channels are altered in brain neurons from heterozygous KCNQ2 G256W mice, suggesting that this variant impacts KCNQ2 trafficking and stability.

Together, these laboratory studies reveal that the molecular and cellular mechanisms shaping KCNQ channel expression, localization, and function are impacted at multiple levels by the variant encoding KCNQ2 G256W, likely contributing to the clinical features of the child heterozygous for this variant relative to patients harboring distinct KCNQ2 pathogenic variants.

Reviewer #1 (Public Review):

Summary:

Thayer et al build upon their prior findings that ASAR long noncoding RNAs (lncRNAs) are chromatin-associated and are implicated in control of replication timing. To explore the mechanism of function of ASAR transcripts, they leveraged the ENCODE RNA binding protein eCLIP datasets to show that a 7kb region of ASAR6-141 is bound by multiple hnRNP proteins. Deletion of this 7kb region resulted in delayed chromosome 6 replication. Furthermore, ectopic integration of the ASAR6-141 7kb region into autosomes or the inactive X-chromosome also resulted in delayed chromosome replication. They then use RNA FISH experiments to show that the knockdown of these hnRNP proteins disrupts ASAR6-141 localization to chromatin and in turn replication timing.

Strengths:

Given prior publications showing HNRNPU to be important for chromatin retention of XIST and Firre, this work expands upon our understanding of the role of hnRNP proteins in lncRNA function.

Weaknesses:

The work presented is mechanistically interesting, however, one must be careful with the over-interpretation that hnRNP proteins can regular chromosome replication directly. Furthermore, the work could be strengthened by including a few controls and clarifications.

Reviewer #2 (Public Review):

This article is focused on investigating incremental speech processing, as it pertains to building higher order syntactic structure. This is an important question because speech processing in general is lesser studied as compared to reading, and syntactic processes are lesser studied than lower-level sensory processes. The authors claim to shed light on the neural processes that build structured linguistic interpretations. The authors apply modern analysis techniques, and use state-of-the-art large language models in order to facilitate this investigation. They apply this to a cleverly designed experimental paradigm of EMEG data, and compare neural responses of human participants to the activation profiles in different layers of the BERT language model.

Comments on revised version:

Similar to my original review, I find the paper hard to follow, and it is not clear to me that the use of the LLM is adding much to the findings. Using complex language models without substantial motivation dampens my enthusiasm significantly. This concern has not been alleviated since my original review.

Reviewer #1 (Public Review):

Summary:

Information transfer between the hippocampus and prefrontal cortex is thought to be critical for spatial working memory, but most of the prior evidence for this hypothesis is correlational. This study attempts to test this causally by linking trial start times to theta-band coherence between these two structures. The authors find that trials initiated during periods of high coherence led to a dramatic improvement in performance. This applied not only to a spatial working memory task, but also to a cue-guided navigation task, suggesting that coherence in these regions may be a signature of a heightened attentional or preparatory state. The authors supplement this behavioral result with electrophysiological recordings and optogenetic manipulations to test whether ventral midline thalamus is likely to mediate hippocampal-prefrontal coherence.

Strengths:

This study demonstrates a striking behavioral effect; by changing the moment at which a trial is initiated, performance on a spatial working memory task improves dramatically, from around 80% correct to over 90% correct. A smaller but nonetheless robust increase in accuracy was also seen in a texture discrimination task. Therefore, prefrontal-hippocampal synchronization in the theta band may not only be important for spatial navigation, but may also be associated with improved performance in a range of tasks. If these results can be replicated using noninvasive EEG, it would open up a powerful avenue for modulating human behavior.

Weaknesses:

Ventral midline thalamic nuclei, such as reuniens, have reciprocal projections to both prefrontal cortex and hippocampus and are therefore well-situated to mediate theta-band interactions between these structures. However, alternative mechanisms cannot be ruled out by the results of this study. For example, theta rhythms are globally coherent across the rodent hippocampus, and ventral hippocampus projects directly to prefrontal cortex. Theta propagation may depend on this pathway, and may only be passively inherited by VMT.

The optogenetic manipulations are intended to show that theta in VMT propagates to PFC and also affects HPC-PFC coherence. However, the "theta" induced by driving thalamic neurons at 7 Hz is extremely artificial. To demonstrate that VMT is causally involved in coordinating activity across HPC and PFC, it would have been better to optogenetically inhibit, rather than excite, these nuclei. If the authors were able to show that the natural occurrence of theta in PFC depends on activity in VMT, that would be much more convincing test of their hypothesis.

Reviewer #1 (Public Review):

In this study, Lin et al developed a protocol termed MOCAT, to perform tissue clearing and labelling on large-scale FFPE mouse brain specimens. They have optimised protocols for dewaxing and adequate delipidation of FFPE tissues to enable deep immunolabelling, even for whole mouse brains. This was useful for the study of disease models such as in an astrocytoma model to evaluate spatial architecture of the tumour and its surrounding microenvironment. It was also used in a traumatic brain injury model to quantify changes in vasculature density and differences in monoaminergic innervation. They have also demonstrated the potential of multi-round immunolabelling using photobleaching, as well as expansion microscopy with FFPE samples using MOCAT.

Comments on revised version:

The revised manuscript by Lin et al is much improved with a more detailed methods description. There are only a few minor comments for the authors:

- The new figures provided in Supplementary figure 5 did demonstrate a good level of transparency for the mouse brain tissue. However, quite marked tissue expansion can be seen following antigen retrieval and RI matching and this should be mentioned in the manuscript.<br /> - The authors have provided comparison between mouse and human brain samples in Figure S12. However, it is misleading to mention that the "fluorescent signals are comparable at varying depth" as the figure clearly showed a lack of continuous staining especially for SMI312 at 900um depth, and human brain tissue showed considerably increased background signal (likely due to endogenous lipofuscin which has autofluorescent properties).<br /> - It is understandable the authors cannot provide the full detail of the RI matching reagent as it is a commercialised product. However, it may still be useful if they can quote the refractive index +/- pH of the solution.

Reviewer #1 (Public Review):

Summary:

Mice can learn to associate sensory cues (sound and light) with a reward or activation of dopamine neurons in the ventral tegmental area (VTA), and then anticipate the reward from the sensory cue only. Using this paradigm, Harada et al. showed that after learning, the cue is able to induce dopamine release in the projection targets of the VTA, namely the nucleus accumbens and lateral hypothalamus (LH). Within the LH, dopamine release from VTA neurons (either by presentation of the cue or direct optical stimulation of VTA neurons) activates orexin neurons, measured as an increase in intracellular calcium levels.

Strengths:

This study utilized genetically encoded optical tools to selectively stimulate dopamine neurons and to monitor dopamine release in target brain areas and calcium response of orexin neurons. This allowed a direct assessment of the relationship between the behavioral response of the animals, release of a key neurotransmitter in select brain areas and its effect on target cells with the precision previously not possible. The results shed light onto the mechanism underlying reward-related learning and expectation.

Weaknesses:

Supplementary Fig.2: While the differences in time course are analyzed and extensively discussed, there is also a large discrepancy in the magnitude of change in DA levels in the two areas that is not mentioned. Specifically, DA increases is about 90-fold of baseline in NAc while it is about 2-fold in the LH. This could be because the DA level is either higher during baseline or lower during peak in the LH. Is there a known difference in the DA fiber density or extracellular DA levels in the two areas?

The DA antagonist i.p. study (Fig.5E and suppl fig 4) appears to be repeated measurements in same animals. If so, is it possible that repeated opto-sessions result in desensitization of the response, and therefore the smaller response is not due to the antagonist? Ideally, the order of experiments (i.e. vehicle, SCH23390 and raclopride) would be randomized, and a control group should be shown where DA terminal-stimulation induces consistent response in orexin neurons when applied three times without any antagonists. The result should be assessed using one-way repeated measures ANOVA.

Importantly, only 5 minutes were allowed for i.p. injected drugs to be absorbed and distributed to the brain before DA release was evoked and ORX neuron activity were monitored. Unfortunately, this is too short (In Ref 13, ip injection of SCH 23390 was 30 minutes prior to optogenetics/photometry experiments. In Ref 70, no effect on behavior was detected at 10 min post-i.p. injection of SCH 23390; In Ref 71, the effect of raclopride on behavior was measured 30 min post-ip injection).

Overall, it seems premature to make a conclusion about a role for D2 receptors or lack of involvement of D1 receptors in the observed phenomenon.

Reciprocal activation of VTA DA neurons and LH orexin neurons is an interesting idea. However, if this is the case, the activity of these two types of cells should show similar pattern and time course. This manuscript shows that extracellular DA levels decays quickly following the cessation of optical stimulation (Fig. 3B) whereas orexin neuron activity is long-lasting (Fig. 5). Thus, the hypothesis does not seem to be fully supported by experimental data.

Reviewer #1 (Public Review):

While I acknowledge the authors' effort in conducting Southern blot analysis to address my prior concern regarding the presence of dual copies of torA and tapA, I find their current resolution inadequate. Specifically, the simple deletion of the respective result sections for torA and tapA significantly impacts the overall significance of this study. The repeated unsuccessful attempts to generate correct mutants only offer circumstantial evidence, as technical issues may have been a contributing factor. Therefore, instead of merely removing these sections, it is essential for the authors to present more compelling experimental data demonstrating that torA and tapA are indeed vital for the viability of A. flavus. Such data would enhance the overall significance of this study.

Reviewer #1 (Public Review):

The authors have identified the predicted EBE of PthA4 in the promoter of Cs9g12620, which is induced by Xcc. The authors identified a homolog of Cs9g12620, which has variations in the promoter region. The authors show that PthA4 suppresses Cs9g12620 promoter activity independent of the binding action. The authors also show that CsLOB1 binds to the promoter of Cs9g12620. Interestingly, the authors show that PthA4 interacts with CsLOB1 at the protein level. Finally, it shows that Cs9g12620 is important for canker symptoms. Overall, this study has reported some interesting discoveries and the writing is generally well done. However, the discoveries are affected by the reliability of the data and some flaws in the experimental designs.

Here are some major issues:<br /> The authors have demonstrated that Cs9g12620 contains the EBE of PthA4 in the promoter region, to show that PthA4 controls Cs9g12620, the authors need to compare to the wild type Xcc and pthA4 mutant for Cs9g12620 expression. The data in Figure 1 is not enough.

The authors confirmed the interaction between PthA4 and the EBE in the promoter of Cs9g12620 using DNA electrophoretic mobility shift assay (EMSA). However, Figure 2B is not convincing. The lane without GST-PthA4 also clearly showed a mobility shift. For the EMSA assay, the authors need also to include a non-labeled probe as a competitor to verify the specificity. The description of the EMSA in this paper suggests that it was not done properly. It is suggested the authors redo this EMSA assay following the protocol: Electrophoretic mobility shift assay (EMSA) for detecting protein-nucleic acid interactions PMID: 17703195.

The authors also claimed that PthA4 suppresses the promote activity of Cs9g12620. The data is not convincing and also contradicts with their own data that overexpression of Cs9g12620 causes canker and silencing of it reduces canker considering PthA4 is required for canker development. The authors conducted the assays using transient expression of PthA4. It should be done with Xcc wild type, pthA4 mutant, and negative control to inoculate citrus plants to check the expression of Cs9g12620.

Figure 6 AB is not convincing. There are no apparent differences. The variations shown in B are common in different wild-type samples. It is suggested that the authors conduct transgenic instead of transient overexpression.

Gene silencing data needs more appropriate controls. Figure D seems to suggest canker symptoms actually happen for the RNAi treated. The authors need to make sure the same amount of Xcc was used for both CTV empty vector and the RNAi. It is suggested a blink test is needed here.

Reviewer #1 (Public Review):

Summary:

Doxorubincin has long been known to cause bone loss by increasing osteoclast and suppressing osteoblast activities. The study by Wang et al. reports a comprehensive investigation into the off-target effects of doxorubicin on bone tissues and potential mechanisms.. They used a tumor-free model with wild type mice and found that even a single dose of doxorubicin has a major influence by increasing leukopenia and DAMPs and inflammasomes in macrophages and neutrophils, and inflammation-related cell death (pyroptosis and NETosis). The gene knockout study shows that AIM2 and NLRP3 are the major contributors to bone loss. Overall, the study confirmed previous findings regarding the impact of doxorubicin on tissue inflammation and expands the research further into bone tissue. The presented data presented are consistent; however, a major question remains regarding whether doxorubicin drives inflammation and its related events. Most in vitro study showed that the effect of doxorubincin cannot be demonstrated without LPS priming. This observation raises the question of whether doxorubincin itself could activate the inflammasome and the related events. In vivo study, on the other hand, suggested that it doesn't require LPS. The inconsistency here was not explained further. Moreover, a tumor-free mouse model was used for the study; however, immune responses in tumor bearing models would likely be distinct from tumor-free ones. The justification for using tumor-free models is not well-established.

Strengths:<br /> The paper includes a comprehensive study that shows the effects of doxorubincin on cytokine levels in serum, release of DAMPs and NETosis, and leukopenia using both in vivo and in vitro models. Bone marrow cells, macrophages and neutrophils were isolated from the bone marrow, and the levels of cytokines in serum were also determined.

They employed multiple knockout models with deficiency in Aim 2, Nlirp3, and double deficiencies to dissect the functional involvement of these two inflammasomes.

The experiments in general are well designed. The paper is also logically written, and figures were clearly labeled.

Weaknesses:<br /> Most of the data presented are correlative, and there is not much effort to dissect the underlying molecular mechanism.

It is not entirely clear why a tumor free model is chosen to study immune responses, as immune responses can differ significantly with or without tumor-bearing.

Immune responses in isolated macrophages, neutrophils and bone marrow cells require priming with LPS, while such responses are not observed in vivo. There is no explanation for these differences.

The band intensities on Western blots in Fig. 4 and Fig. 5 are not quantified, and the numbers of repeats are also not provided.

Many abbreviations are used throughout the text, and some of the full names are not provided.

Fig. 5B needs a label on X axis.

Reviewer #1 (Public Review):

Summary:<br /> The manuscript by Jiayun Li and colleagues aims to provide insight into adipokinetic hormone signaling that mediates the fecundity of Diaphorina citri infected by 'Candidatus Liberibacter asiaticus'. CLas-positive D. citri are more fecund than their CLas-negative counterparts and require extra energy expenditure. Using FISH, qRT-PCR, WB, RNAi, and miRNA-related methods, authors found that knockdown of DcAKH and DcAKHR not only resulted in triacylglycerol accumulation and a decline of glycogen but also significantly decreased fecundity and CLas titer in ovaries. miR-34 suppresses DcAKHR expression by binding to its 3' untranslated region, whilst overexpression of miR-34 resulted in a decline of DcAKHR expression and CLas titer in ovaries and caused defects that mimicked DcAKHR knockdown phenotypes. Most of the methods and results are solid and valuable, but I have a number of concerns with this paper, relating to the writing and lack of sufficient information about data analysis.

Reviewer #1 (Public Review):

Summary:

Satoshi Yamashita et al., investigate the physical mechanisms driving tissue bending using the cellular Potts Model, starting from a planar cellular monolayer. They argue that apical length-independent tension control alone cannot explain bending phenomena in the cellular Potts Model, contrasting with the vertex model. However, the evidence supporting this claim is incomplete. They conclude that an apical elastic term, with zero rest value (due to endocytosis/exocytosis), is necessary in constricting cells and that tissue bending can be enhanced by adding a supracellular myosin cable. Notably, a very high apical elastic constant promotes planar tissue configurations, opposing bending.

Strengths:

- The finding of the required mechanisms for tissue bending in the cellular Potts Model provides a more natural alternative for studying bending processes in situations with highly curved cells.

- Despite viewing cellular delamination as an undesired outcome in this particular manuscript, the model's capability to naturally allow T1 events might prove useful for studying cell mechanics during out-of-plane extrusion.

Weaknesses:

- The authors claim that the cellular Potts Model is unable to obtain the vertex model simulation results, but the lack of a substantial comparison undermines this assertion. No references are provided with vertex model simulations, employing similar setups and rules, and explaining tissue bending solely through an increase in a length-independent apical tension.

- The apparent disparity between the two models is attributed to straight versus curved cellular junctions, with cells with a curved lateral junction achieving lower minimum energies at steady-state. However, a critical discussion on the impact of T1 events, allowing cellular delamination, is absent. Note that some of the cited vertex model works do not allow T1 events while allowing curvature.

- The suggested mechanism for inducing tissue bending in the cellular Potts Model, involving an apical elastic term, has been utilized in earlier studies, including a cited vertex model paper (Polyakov 2014). Consequently, the physical concept behind this implementation is not novel and warrants discussion.

- The absence of information on parameter values, initial condition creation, and boundary conditions in the manuscript hinders reproducibility. Additionally, the explanation for the chosen values and their unit conversion is lacking.

Reviewer #1 (Public Review):

Summary:<br /> "Expanding the Drosophila toolkit for dual control of gene expression" by Zirin et al. aims to develop resources for simultaneous independent manipulation of multiple genes in Drosophila. The authors use CRISPR knock-ins to establish a collection of T2A-LexA and T2A-QF2 transgenes with expression patterns in a number of commonly studied organs and tissues. In addition to the transgenic lines that are established, the authors describe a number of plasmids that can be used to generate additional transgenes, including a plasmid to generate a dual insert of LexA and QF that can be resolved into a single insert using FLP/FRT-mediated recombination, and plasmids to generate RNAi reagents for the LexA and QF systems. Finally, the authors demonstrate that a subset of the LexA and QF lines that they generated can induce RNAi phenotypes when paired with LexAop or QUAS shRNA lines. In general, the claims of the paper are well supported by the evidence and the authors do a thorough job of validating the transgenic lines and characterizing their expression patterns.

Reviewer #1 (Public Review):

Summary:

The authors use an innovative behavior assay (chamber preference test) and standard calcium imaging experiments on cultured dorsal root ganglion (DRG) neurons to evaluate the consequences of global knockout of TRPV1 and TRPM2, and overexpression of TRPV1, on warmth detection. They find a profound effect of TRPM2 elimination in the behavioral assay, whereas elimination of TRPV1 has the largest effect on neuronal responses. These findings are of importance, as there is still substantial discussion in the field regarding the contribution of TRP channels to different aspects of thermosensation.

Strengths:

The chamber preference test is an important innovation compared to the standard two-plate test, as it depends on thermal information sampled from the entire skin, as opposed to only the plantar side of the paws. With this assay, and the detailed analysis, the authors provide strong supporting evidence for the role of TRPM2 in warmth avoidance. The conceptual framework using the Drift Diffusion Model provides a first glimpse of how this decision of a mouse to change between temperatures can be interpreted and may form the basis for further analysis of thermosensory behavior.

Weaknesses:

The authors juxtapose these behavioral data with calcium imaging data using isolated DRG neurons. Here, there are a few aspects that are less convincing.

(1) The authors study warmth responses using DRG neurons after three days of culturing. They propose that these "more accurately reflect the functional properties and abundance of warm-responsive sensory neurons that are found in behaving animals." However, the only argument to support this notion is that the fraction of neurons responding to warmth is lower after three days of culture. This could have many reasons, including loss of specific subpopulations of neurons, or any other (artificial?) alterations to the neurons' transcriptome due to the culturing. The isolated DRGs are not selected in any way, so also include neurons innervating viscera not involved in thermosensation. If the authors wish to address actual changes in sensory nerves involved in warmth sensing in TRPM2 or TRPV1 KO mice without disturbing the response profile as a result of the isolation procedure, other approaches would be needed (e.g. skin-nerve recordings or in vivo DRG imaging).

(2) The authors state that there is a reduction in warmth-sensitive DRG neurons in the TRPM2 knockout mice based on the data presented in Figure 2D. This is not convincing for the following reasons. First, the authors used t-tests (with FDR correction - yielding borderline significance) whereas three groups are compared here in three repetitive stimuli. This would require different statistics (e.g. ANOVA), and I am not convinced (based on a rapid assessment of the data) that such an analysis would yield any significant difference between WT and TRPM2 KO. Second, there seems to be a discrepancy between the plot and legend regarding the number of LOV analysed (21, 17, and 18 FOV according to the legend, compared to 18, 10, and 12 dots in the plot). Therefore, I would urge the authors to critically assess this part of the study and to reconsider whether the statement (and discussion) that "Trpm2 deletion reduces the proportion of warmth responders" should be maintained or abandoned.

(3) It remains unclear whether the clear behavioral effect seen in the TRPM2 knockout animals is at all related to TRPM2 functioning as a warmth sensor in sensory neurons. As discussed above, the effects of the TRPM2 KO on the proportion of warmth-sensing neurons are at most very subtle, and the authors did not use any pharmacological tool (in contrast to the use of capsaicin to probe for TRPV1 in Figures S3 and S4) to support a direct involvement of TRPM2 in the neuronal warmth responses. Behavioral experiments on sensory-neuron-specific TRPM2 knockout animals will be required to clarify this important point.

(4) The authors only use male mice, which is a significant limitation, especially considering known differences in warmth sensing between male and female animals and humans. The authors state "For this study, only male animals were used, as we aimed to compare our results with previous studies which exclusively used male animals (7, 8, 17, 43)." This statement is not correct: all four mentioned papers include behavioral data from both male and female mice! I recommend the authors to either include data from female mice or to clearly state that their study (in comparison with these other studies) only uses male mice.

Reviewer #1 (Public Review):

Summary:

In this manuscript, the authors suggest that Keratin 17 (K17) a component of intermediate filaments that is highly expressed in the more aggressive basal subtype of pancreatic cancer, is functionally involved in tumor promotion. They use mouse and human cell lines and overexposed wild type or mutant K17 (the latter a form that accumulates in the nuclei) and show a modest reduction in survival and increase in tumor size and metastasis. The authors use in vitro work to show that phosphorylation, through a PKC/MEK/RSK kinase cascade, leads to K17 phosphorylation and K17 disassembly.

Strengths:

K17 is an intriguing protein, as it becomes part of intermediate filaments but it has also been described to have a role in the nucleus. Whether K17 functionally drives the malignant phenotype of pancreatic cancer is unclear. Thus, the article addresses an important area of research.

Weaknesses:

Some shortcomings with the interpretation of results and the strength of the evidence provided are notes. Among those, evidence that nuclear K17 is a feature of basal pancreatic cancer in human tumors is missing. Further, the survival effects observed in the mouse experiments are modest, especially with the L3.6 cell line. Lastly, while the authors point at some potentially intriguing gene expression changes in pancreatic cancer cells expressing K17, such as the expression of genes related to epithelial mesenchymal transition (EMT) they do not provide evidence that these genes are K17 targets, not that they mediate the nuclear function of K17 in experimental models, nor that they are associated with K17-high human tumors.

Reviewer #1 (Public Review):

Anobile and colleagues present a manuscript detailing an account of numerosity processing with an appeal to a two-channel model. Specifically, the authors propose that the perception of numerosity relies on (at least) two distinct channels for small and large numerosities, which should be evident in subject reports of perceived numerosity. To do this, the authors had subjects reproduce visual dot arrays of numerosities ranging from 8 to 32 dots, by having subjects repetitively press a response key at a pre-instructed rate (fast or slow) until the number of presses equaled the number of perceived dots. The subjects performed the task remarkably well, yet with a general bias to overestimate the number of presented dots. Further, no difference was observed in the precision of responses across numerosities, providing evidence for a scalar system. No differences between fast and slow tapping were observed. For behavioral analysis, the authors examined correlations between the Weber fractions for all presented numerosities. Here, it was found that the precision at each numerosity was similar to that at neighboring numerosities, but less similar to more distant ones. The authors then went on to conduct PCA and clustering analyses on the weber fractions, finding that the first two components exhibited an interaction with the presented numerosity, such that each were dominant at distinct lower and upper ranges and further well-fit by a log-Gaussian model consistent with the channel explanation proposed at the beginning.

Overall, the authors provide compelling evidence for a two-channel system supporting numerosity processing that is instantiated in sensorimotor processes. A strength of the presented work is the principled approach the authors took to identify mechanisms, as well as the controls put in place to ensure adequate data for analysis.

One remaining question regards the secondary timing task that was used as a control. There may be interesting findings here to pursue, and so I encourage the authors or other researchers to examine those findings and explore further studies there as well.

Reviewer #2 (Public Review):

Summary

The authors report an extensive series of neuroimaging experiments (at both 3T and 7T) to provide evidence for a scene-selective visual area in human posterior parietal cortex (PIGS) that is distinct from the main three (parahippocampal place area, PPA; occipital place area, OPA; medial place area, MPA) typically reported in the literature. Further, they argue that in comparison with the other three, this region may specifically be involved in representing ego-motion in natural contexts. The characterization of this scene-selective region provides a useful reference point for studies of scene processing in humans.

Strengths

One of the major strengths of the work is the extensive series of experiments reported, showing clear reproducibility of the main finding and providing functional insight into the region studied. The results are clearly presented and convincing with careful comparison to retinotopic and scene-selective regions described in prior studies.

Weaknesses

While the results are strong and clear, the claim in the title ("A previously undescribed scene-selective site is the key to encoding ego-motion in naturalistic environments") is not fully supported. The results show that this scene-selective region is sensitive to visual cues that reflect ego-motion but not that it is "key" to encoding ego-motion. Further, there are many differences between the two types of stimuli used to test ego-motion and greater characterization of this scene-selective region will be needed to confirm this conclusion.

Reviewer #1 (Public Review):

Summary:

The authors examined whether archerfish have the capacity for motor adaptation in response to airflow perturbations. Through two experiments, they demonstrated that archerfish could adapt. Moreover, when the fish flipped its body position with the perturbation remaining constant, it did not instantaneously counteract the error. Instead, the archerfish initially persisted in correcting for the original perturbation before eventually adapting, consistent with the notion that the archerfish's internal model has been adapted in egocentric coordinates.

Evaluation:

This important study demonstrates the remarkable capacity for motor adaptation in archer fish. I found the results of both experiments to be convincing, given the observable learning curve and the clear aftereffect. Nonetheless, within the current set of experiments, no quantitative is provided to demonstrate that the archer fish is sensitive to the relative change in body position, making it unclear whether motor adaptation in archer fish indeed generalizes in egocentric coordinates.

The authors have cited a previous study to claim that archer fish are sensitive to their relative position in the water tank. However, given the absence of clear visual referents on the screen (e.g., squares with different colors in the corners) and/or some behavioral indication that the fish are sensitive to their relative change in body position, I remain sceptical of the claim that archer fish indeed generalize in egocentric rather than allocentric coordinates. The current results do not rule out the idea that archerfish are ostensibly unaware of changes in body position, they continue with previously successful actions, masquerading as egocentric generalization.

Reviewer #1 (Public Review):

Summary:

In this study, Osiurak and colleagues investigate the neurocognitive basis of technical reasoning. They use multiple tasks from two neuroimaging studies and overlap analysis to show that the area PF is central for reasoning, and plays an essential role in tool-use and non-tool-use physical problem-solving, as well as both conditions of mentalizing task. They also demonstrate the specificity of the technical reasoning and find that the area PF is not involved in the fluid-cognition task or the mentalizing network (INT+PHYS vs. PHYS-only). This work suggests an understanding of the neurocognitive basis of technical reasoning that supports advanced technologies.

Strengths:

-The topic this study focuses on is intriguing and can help us understand the neurocognitive processes involved in technical reasoning and advanced technologies.

-The researchers obtained fMRI data from multiple tasks. The data is rich and encompasses the mechanical problem-solving task, psychotechnical task, fluid-cognition task, and mentalizing task.

-The article is well written.

Weaknesses:

- Limitations of the overlap analysis method: there are multiple reasons why two tasks might activate the same brain regions. For instance, the two tasks might share cognitive mechanisms, the activated regions of the two tasks might be adjacent but not overlapping at finer resolutions, or the tasks might recruit the same regions for different cognition functions. Thus, although overlap analysis can provide valuable information, it also has limitations. Further analyses that capture the common cognitive components of activation across different tasks are warranted, such as correlating the activation across different tasks within subjects for a region of interest (i.e. the PF).

-Control tasks may be inadequate: the tasks may involve other factors, such as motor/ action-related information. For the psychotechnical task, fluid-cognition task, and mentalizing task, the experiment tasks need not only care about technical-cognition information but also motor-related information, whereas the control tasks do not need to consider motor-related information (mainly visual shape information). Additionally, there may be no difference in motor-related information between the conditions of the fluid-cognition task. Therefore, the regions of interest may be sensitive to motor-related information, affecting the research conclusion.

-Negative results require further validation: the cognitive results for the fluid-cognition task in the study may need more refinement. For instance, when performing ROI analysis, are there any differences between the conditions? Bayesian statistics might also be helpful to account for the negative results.

Joint Public Review:

The molecular mechanisms that mediate the regulated exocytosis of neuropeptides and neurotrophins from neurons via large dense-core vesicles (LDCVs) are still incompletely understood. Motivated by their earlier discovery that the Rab3-RIM1 pathway is essential for neuronal LDCV exocytosis, the authors now examined the role of the Rab3 effector Rabphilin-3A in neuronal LDCV secretion. Based on multiple live and confocal imaging approaches, the authors provide evidence for a synaptic enrichment of Rabphilin-3A and for independent trafficking of Rabphilin-3A and LDCVs. Using an elegant NPY-pHluorin imaging approach, they show that genetic deletion of Rabphilin-3A causes an increase in electrically triggered LDCV fusion events and increased neurite length. Finally, knock-out-replacement studies, involving Rabphilin-3A mutants deficient in either Rab3- or SNAP25-binding, indicate that the synaptic enrichment of Rabphilin-3A depends on its Rab3 binding ability, while its ability to bind to SNAP25 is required for its effects on LDCV secretion and neurite development. The authors conclude that Rabphilin-3A negatively regulates LDCV exocytosis and propose that this mechanism also affects neurite growth, e.g. by limiting neurotrophin secretion. These are important findings that advance our mechanistic understanding of neuronal large dense-core vesicle (LDCV) secretion.

The major strengths of the present paper are:

(i) The use of a powerful Rabphilin-3A KO mouse model.<br /> (ii) Stringent lentiviral expression and rescue approaches as a strong genetic foundation of the study.<br /> (iii) An elegant FRAP imaging approach.<br /> (iv) A cutting-edge NPY-pHluorin-based imaging approach to detect LDCV fusion events.

Weaknesses that somewhat limit the convincingness of the evidence provided and the corresponding conclusions include the following:

(i) The limited resolution of the various imaging approaches introduces ambiguity to several parameters (e.g. LDCV counts, definition of synaptic localization, Rabphilin-3A-LDCV colocalization, subcellular and subsynaptic localization of expressed proteins, AZ proximity of Rabphilin-3A and LDCVs) and thereby limits the reliability of corresponding conclusions. Super-resolution approaches may be required here.<br /> (ii) The description of the experimental approaches lacks detail in several places, thus complicating a stringent assessment.<br /> (iii) Further analyses of the LDCV secretion data (e.g. latency, release time course) would be important in order to help pinpoint the secretory step affected by Rabphilin-3A.<br /> (iv) It remains unclear why a process that affects a general synaptic SNARE fusion protein - SNAP25 - would specifically affect LDCV but not synaptic vesicle fusion.<br /> (v) The mechanistic links between Rabphilin-3A function, LDCV density in neurites, neurite outgrowth, and the proposed underlying mechanisms involving trophic factor release remain unclear.

Reviewer #1 (Public Review):

Summary:<br /> Codol et al. present a toolbox that allows simulating biomechanically realistic effectors and training Artificial Neural Networks (ANNs) to control them. The paper provides a detailed explanation of how the toolbox is structured and several examples demonstrating its utility.

Main comments:<br /> (1) The paper is well-written and easy to follow. The schematics facilitate understanding of the toolbox's functionality, and the examples give insight into the potential results users can achieve.<br /> (2) The toolbox's latest version, developed in PyTorch, is expected to offer greater benefits to the community.<br /> (3) The new API, being compatible with Gymnasium, broadens the toolbox's application scope, enabling the use of Reinforcement Learning for training the ANNs.

Impact:<br /> MotorNet is designed to simplify the process of simulating complex experimental setups, enabling the rapid testing of hypotheses on how the brain generates specific movements. Implemented in PyTorch and compatible with widely-used machine learning toolboxes, including Gymnasium, it offers an end-to-end pipeline for training ANNs on simulated setups. This can greatly assist experimenters in determining the focus of their subsequent efforts.

Additional context:<br /> The main outcome of the work, a toolbox, is supplemented by a GitHub repository and a documentation webpage. Both the repository and the webpage are well-organized and user-friendly. The webpage guides users through the toolbox installation process, as well as the construction of effectors and Artificial Neural Networks (ANNs).

Reviewer #1 (Public Review):

Summary: Leanza et al. investigated the regulation of Wnt signaling factors in the bone tissue obtained from individuals with or without type 2 diabetes. They showed that typical canonical Wnt ligands and downstream factors (Wnt10b, LEF1) are down-regulated, while Wnt5a and sclerostin mRNA is unregulated in diabetic bone tissue. Further, Wnt5a and sclerostin associated with the content of AGEs and SOST mRNA levels also correlated with glycemic control and disease duration.

Strengths:

- A strength of the study is the investigation of Wnt signaling in bone tissue from humans with type 2 diabetes. Most studies measure only serum levels of Wnt inhibitors, but this study takes it further and looks into bone specifically.<br /> - The measurement of AGEs and its correlation to the Wnt signaling molecules is interesting and important. The correlation of sclerostin and Wnt5a with AGEs and disease duration suggests that inhibited Wnt signaling is paralleled by higher AGE levels and potentially weaker bone.<br /> - The methodology in terms of obtaining the bone samples and the rigorous evaluation of RNA integrity is great and provides a solid basis for further analyses.

Weaknesses:

- A weakness may include the rather limited number of samples.

Overall, this study validates findings from the group that have reported similar findings in 2020. This validates their methodology and shows that alterations in Wnt signaling are reproducible in human bone tissue.

Reviewer #1 (Public Review):

Summary:

The authors attempt to validate Fisher Kernels on the top of HMM as a way to better describe human brain dynamics at resting state. The objective criterion was the better prediction of the proposed pipeline of the individual traits.

Strengths:<br /> The authors analyzed rs-fMRI dataset from the HCP providing results also from other kernels.<br /> The authors also provided findings from simulation data.

Weaknesses:

(1) The authors should explain in detail how they applied cross-validation across the dataset for both optimization of parameters, and also for cross-validation of the models to predict individual traits.

(2) They discussed throughout the paper that their proposed (HMM+Fisher) kernel approach outperformed dynamic functional connectivity (dFC). However, they compared the proposed methodology with just static FC.

(3) If the authors wanted to claim that their methodology is better than dFC, then they have to demonstrate results based on dFC with the trivial sliding window approach.

Reviewer #1 (Public Review):

Summary:

This study uses whole genome sequencing to characterise the population structure and genetic diversity of a collection of 58 isolates of E. coli associated with neonatal meningitis (NMEC) from seven countries, including 52 isolates that the authors sequenced themselves and a further 6 publicly available genome sequences. Additionally, the study used sequencing to investigate three case studies of apparent relapse. The data show that in all three cases, the relapse was caused by the same NMEC strain as the initial infection. In two cases they also found evidence for gut persistence of the NMEC strain, which may act as a reservoir for persistence and reinfection in neonates. This finding is of clinical importance as it suggests that decolonisation of the gut could be helpful in preventing relapse of meningitis in NMEC patients.

Strengths:

The study presents complete genome sequences for n=18 diverse isolates, which will serve as useful references for future studies of NMEC. The genomic analyses are high quality, the population genomic analyses are comprehensive and the case study investigations are convincing. The full data set (including phylogenetic tree, annotated with source, lineage and virulence factor information) are publicly available in interactive form via the MicroReact platform.

Weaknesses:

The NMEC collection described in the study includes isolates from just seven countries. The majority (n=51/58, 88%) are from high-income countries in Europe, Australia or North America; the rest are from Cambodia (n=7, 12%). Therefore it is not clear how well the results reflect the global diversity of NMEC, nor the populations of NMEC affecting the most populous regions.

The virulence factors section highlights several potentially interesting genes that are present at apparently high frequency in the NMEC genomes; however without knowing their frequency in the broader E. coli population it is hard to know the significance of this.

Reviewer #1 (Public Review):

Summary:

The emergence of catalytic self-replication of polymers is an important question in the context of the origin of life. Tkachenko and Maslov present a model in which such a catalytic polymer sequence emerges from a random pool of replicating polymers.

Strengths:

The model is part of a theme from many previous papers from the same authors and their colleagues. The model is interesting, technically correct and demonstrates qualitatively new phenomena. It is good that the paper also makes a connection with possible experimental scenarios - specifically, concrete proposals are made for testing the core ideas of the model. It would indeed be an exciting demonstration when such an experiment does indeed materialize.

Weaknesses:

Unlike the rest of the paper which is very tight in its arguments, I find that the discussion section is not so. Specifically, sentences such as " In fact, this can be seen as a special case of the classical error catastrophe" are a bit loose and not well substantiated -- although these are in the discussion section, I find this to be a weakness of an otherwise good paper and tightening some of the arguments here will make it an excellent paper in my opinion.

Reviewer #1 (Public Review):

Ye et al. used Mendelian randomization method to evaluate the causative association between circulating immune cells and periodontitis, and finally screened out three risk immune cells related to periodontitis. Overall, this is an important and novel piece of work that has the potential to contribute to our understanding of the causal relationship between circulating immune cells related to periodontitis.

Reviewer #1 (Public Review):

Summary:<br /> In this manuscript the authors re-examine the developmental origin of cortical oligodendrocyte (OL) lineage cells using a combination of strategies, focussing on the question of whether the LGE generates cortical OL cells. The paper is interesting to myelin biologists, the methods used are appropriate and, in general, the study is well-executed, thorough, and persuasive, but not 100% convincing.

Strengths, weaknesses, and recommendations:<br /> The first evidence presented that the LGE does not generate OLs for the cortex is that there are no OL precursors 'streaming' from the LGE during embryogenesis, unlike the MGE (Figure 1A). This in itself is not strong evidence, as they might be more dispersed. In fact, in the images shown, there is no obvious 'streaming' from the MGE either. Note that in Figure 1 there is no reference to the star that is shown in the figure.

The authors then electroporate a reporter into the LGE at E13.5 and examine the fate of the electroporated cells (Figures 1C-E). They find that electroporated cells became neurons in the striatum and in the cortex but no OLs for the cortex. There are two issues with this: first, there is no quantification, which means there might indeed be a small contribution from the LGE that is not immediately obvious from snapshot images. Second, it is unexpected to find labelled neurons in the cortex at all since the LGE does not normally generate neurons for the cortex! Electroporations are quite crude experiments as targeting is imprecise and variable and not always discernible at later stages. For example, in Figure 1D, one can see tdTOM+ cells near the AEP, as well as the striatum. Hence, IUE cannot on its own be taken as proof that there is no contribution of the LGE to the cortical OL population.

The authors then use an alternative fate-mapping approach, again with E13.5 electroporations (Figure 2). They find only a few GFP+ cells in the cortex at E18 (Figures 2C-D) and P10 (Figure 2E) and these are mainly neurons, not OL lineage cells. Again, there is no quantification.

Figure 3 is more convincing, but the experiments are incomplete. Here the authors generate triple-transgenic mice expressing Cre in the cortex (Emx1-Cre) and the MGE (Nkx2.1-Cre) as well as a strong nuclear reporter (H2B-GFP). They find that at P0 and P10, 97-98% of OL-lineage cells (SOX10+ or PDGFRA+) in the cortex are labelled with GFP (Figure 3). This is a more convincing argument that the LGE/CGE might not contribute significant numbers of OL lineage cells to the cortex, in contrast to the Kessaris et at. (2006) paper, which showed that Gsh2-Cre mice label ~50% of SOX10+ve cells in the motor cortex at P10. The authors of the present paper suggest that the discrepancy between their study and that of Kessaris et al. (2006) is based on the authors' previous observation (Zhang et al 2020) (https://doi.org/10.1016/j.celrep.2020.03.027) that GSH2 is expressed in intermediate precursors of the cortex from E18 onwards. If correct, then Kessaris et al. might have mistakenly attributed Gsh2-Cre+ lineages to the LGE/CGE when they were in fact intrinsic to the cortex. However, the evidence from Zhang et al 2020 that GSH2 is expressed by cortical intermediate precursors seems to rest solely on their location within the developing cortex; a more convincing demonstration would be to show that the GSH2+ putative cortical precursors co-label for EMX1 (by immunohistochemistry or in situ hybridization), or that they co-label with a reporter in Emx1-driven reporter mice. This demonstration should be simple for the authors as they have all the necessary reagents to hand. Without these additional data, the assertion that GSX2+ve cells in the cortex are derived from the cortical VZ relies partly on an act of faith on the part of the reader.

Note that Tripathi et al. (2011, "Dorsally- and ventrally-derived oligodendrocytes have similar electrical properties but myelinate preferred tracts." J. Neurosci. 31, 6809-6819) found that the Gsh-Cre+ OL lineage contributed only ~20% of OLs to the mature cortex, not ~50% as reported by Kessaris et al. (2006). If it is correct that these Gsh2-derived OLs are from the cortical anlagen as the current paper claims, then it would raise the possibility that the ventricular precursors of GSH2+ intermediate progenitors are not uniformly distributed through the cortical VZ but are perhaps localized to some part of it. Then the contribution of Gsh2-derived OLs to the cortical population could depend on precisely where one looks relative to that localized source. It would be a nice addition to the current manuscript if the authors could explore the distribution of their GSH2+ intermediate precursors throughout the developing cortex. In any case, Tripathi et al. (2011) should be cited.

Finally, the authors deleted Olig2 in the MGE and found a dramatic reduction of PDGFRA+ and SOX10+ cells in the cortex at E14 and E16 (Figure 4A-F). This further supports their conclusion that, at least at E16, there is no significant contribution of OLs from ventral sources other than the MGE/AEP. This does not exclude the possibility that the LGE/CGE generates OLs for the cortex at later stages. Hence, on its own, this is not completely convincing evidence that the LGE generates no OL lineage cells for the cortex.

Reviewer #1 (Public Review):

Summary:

The manuscript of Zhao et al. aimed at investigating the relationships between type 2 diabetes, bone mineral density (BMD) and fracture risk using Mendelian Randomization (MR) approach.<br /> The authors found that genetically predicted T2D was associated with higher BMD and lower risk of fracture, and suggested a mediated effect of RSPO3 level. Moreover, when stratified by the risk factors secondary to T2D, they observed that the effect of T2D on the risk of fracture decreased when the number of risk factors secondary to T2D decreased.

Strengths:

- Important question<br /> - Manuscript is overall clear and well-written<br /> - MR analyses have been conducted properly, which include the usage of various MR methods and sensitivity analyses, and likely meet the criteria of the MR-strobe checklist to report MR results.

Weaknesses:

- Interpretation of MR findings should be more nuanced given the modest (almost neutral) relationship between T2D and fracture risk in MR

Reviewer #1 (Public Review):

Hu et al. performed sc-RNA-seq analyses of kidney cells with or without virus infection, vaccines, and vaccines+virus infections from pooled adult zebrafish. They compared within these experimental groups as well as kidney vs spleen. Their analyses identified expected populations but also revealed new hematopoietic stem/progenitor cell (HSPC), even in spleen. Their analyses show that HSPCs in kidney can respond to virus infection differentially and can be trained to recognize the same infection and argue that zebrafish kidney can serve as a secondary immune organ. The findings are important and interesting. The manuscript is well written and a pleasure to read.

Reviewer #1 (Public Review):

Summary:

In this study, the authors used both the commonly used neonatal hyperoxia model as well as cell-type-specific genetic inactivation of Tgfbr2 models to study the basis of BPD. The bulk of the analyses focus on the mesenchymal cells. Results indicate impaired myofibroblast proliferation, resulting in decreased cell number. InactzXivation of Etc2 in Pdgfra-lineaged cells, preventing cytokinesis of myofibroblasts, led to alveolar simplification. Together, the findings demonstrate that disrupted myofibroblast proliferation is a key contributor to BPD pathogenesis.

Strengths:

Overall, this comprehensive study of BPD models advances our understanding of the disease. The data are of high quality.

Weaknesses:

The critiques are mostly minor and can be addressed without extensive experimentation.

Reviewer #1 (Public Review):

Summary:

In this study, Xie and colleagues aimed to explore the function and potential mechanisms of the gut microbiota in a hamster model of severe leptospirosis. The results demonstrated that Leptospira infection was able to cause intestine damage and inflammation. Leptospira infection promoted an expansion of Proteobacteria, increased gut barrier permeability, and elevated LPS levels in the serum. Thus, they proposed an LPS-neutralization therapy which improved the survival rate of moribund hamsters combined with antibody therapy or antibiotic therapy.

Strengths:

The work is well-designed and the story is interesting to me. The gut microbiota is essential for immunity and systemic health. Many life-threatening pathogens, such as SARS-CoV-2 and other gut-damaged infection, have the potential to disrupt the gut microbiota in the later stages of infection, causing some harmful gut microbiota-derived substances to enter the bloodstream. It is emphasized that in addition to exogenous pathogenic pathogens, harmful substances of intestinal origin should also be considered in critically ill patients.

Weaknesses:

(1) There are many serotypes of Leptospira, it is suggested to test another pathogenic serotype of Leptospira to validate the proposed therapy.

(2) Authors should explain why the infective doses of leptospires was not consistent in different study.

(3) In the discussion section, it is better to supplement the discussion of the potential link between the natural route of infection and leptospirosis.

(4) Line 231, what is the solvent of thioglycolate?

(5) Lines 962-964, there are some mistakes which are not matched to Figure 7.

Reviewer #1 (Public Review):

Summary:<br /> The manuscript by Rowell et al aims to identify differences in TCR recombination and selection between foetal and adult thymus in mice. Authors sequenced the unpaired bulk TCR repertoire in foetal and adult mice thymi and studied both TCRB and TCRa characteristics in the double positive (DP, CD4+CD8+) and single positive (SP4 CD4+CD8-CD3+ and SP8 CD4-CD8+CD3+) populations. They identified age-related differences in TCRa and TCRB segment usage, including a preferential bias toward 3'TRAV and 5' TRAJ rearrangements in foetal cells compared to adults who had a larger perveance for 5'TRAV segments. By depleting the thymocyte population in adult thymi using hydrocortisone, the authors demonstrated that the repertoire became more foetal like, they therefore argue that the preferential 5'TRAV rearrangements in adults may be resulting from prolonged/progressive TCRa rearrangements in the adult thymocytes. In line with previous studies, Authors demonstrate that the foetal TCR repertoire was less diverse, less evenly distributed and had fewer non-template insertions while containing more clonal expansions. In addition, the authors claim that changes in V-J usage and CDR1 and CDR2 in the DP vs SP repertoires indicated that positive selection of foetal thymocytes are less dependent on interactions with the MHC.

Strengths:<br /> Overall, the manuscript provides an extensive analysis of the foetal and adult TCR repertoire in the thymus, resulting in new insights in T cell development in foetal and adult thymi.

Weaknesses:<br /> Three major concerns arise: 1) the authors have analysed TCR repertoires of only 4 foetal and 4 adult mice, considering the high spread the study may have been underpowered. 2) Gating strategies are missing and 3) the manuscript is very technical and clearly aimed for a highly specialised audience with expertise in both thymocyte development and TCR analysis. Authors are recommended to provide schematics of the TCR rearrangements/their findings and include a summary conclusions/implications of their findings at the end of each results section rather than waiting till the discussion. This will help the reader to interpret their findings while reading the results.

Reviewer #1 (Public Review):

The author's goal was to determine the role of O-GlcNAc modification in associate learning in Drosophila using an odor discriminatory task. In particular, they sought to determine the population of O-GlcNAc modified proteins in a region of the brain critical for memory, the mushroom body. They provide compelling evidence that there are brain-region-specific populations of O-GlcNAc modified proteins and that in the mushroom body, proteins involved in translation represent a sizable, and larger fraction than elsewhere in the central nervous system. Using expression of a bacterial protein that cleaves O-GlcNAc in the mushroom body, they show both reductions in the levels of this modification and effects on associative learning. Further exploration of new protein synthesis in situ supports the hypothesis that O-GlcNAc modification affects the activity of the translational machinery and could provide the basis for learning deficits when O-GlcNAc levels are compromised. Rescue of deficits resulting from reductions in O-GlcNAc was achieved by over-expression of dMyc, a known regulator of ribosome biogenesis and translation. While the critical role of protein synthesis in learning is long established, and that O-GlcNAc modification regulates protein synthesis, this work connects O-GlcNAc modification in a specialized region of the brain to translation regulation and associative learning. The authors also provide a method for identification of O-GlcNAc modified proteins using a tissue-specific and inducible proximity-labelling method. This will provide a useful tool for further functional studies of O-GlcNAc modification.

Reviewer #1 (Public Review):

Analysis of a sizable number of matched primary AML samples from diagnosis and relapse was done with ATAC-seq and showed that epigenetic changes are seen at relapse. Meta-analysis of multiple studies showed that relapse is not associated generally with changes in mutational burden. The authors also performed clonal tracking with mitochondrial clones and show that heterogeneity in clonal expansions is seen in various cases. Overall, these are novel findings with translational relevance.

Reviewer #1 (Public Review):

Summary:

The paper combines phenotypic and genomic analyses of the "sheltered load" (i.e. the accumulation of deleterious mutations linked to S-Loci that are hidden from selection in the homozygous state) in Arabidopsis. The authors compare results to previous theoretical predictions concerning the extent of the load in dominant vs recessive S-alleles, and further develop exciting theory to reconcile differences between previous theory and observed results.

Strengths:

This is a very nice combination of theory and data to address a classical question in the field.

Weaknesses:

The "genetic load" is a poorly defined concept in general, and its quantification via the number of putatively deleterious mutations is quite difficult. Furthermore counting up the number of derived mutations at fully constrained nucleotides may not be a great estimate of the load, and certainly does not allow for evaluation of recessivity -- a concept critical to ideas concerning the sheltered load. Alternative approaches - including estimating the severity of mutations - could be helpful as well. This imperfection in available approaches to test theory must be acknowledged more strongly by the authors.

Reviewer #1 (Public Review):

Summary:

Based on a "dichoptic-background-movie" paradigm that modulates ocular dominance, the present study combines fMRI and TMS to examine the role of the frontoparietal attentional network in ocular dominance shifts. The authors claimed a causal role of FEF in generating the attention-induced ocular dominance shift.

Strengths:

A combination of fMRI, TMS, and "dichoptic-background-movie" paradigm techniques is used to reveal the causal role of the frontoparietal attentional network in ocular dominance shifts. The conclusions of this paper are well supported by data.

Weaknesses:

My previous concerns have been addressed.

Joint Public Review:

This study is concerned with the general question as to how pools of synaptic vesicles are organized in presynaptic terminals to support different types of transmitter release, such as fast synchronous and asynchronous release. To address this issue, the authors employed the classical method of loading synaptic vesicle membranes with FM-styryl dyes and assessing dye destaining during repetitive synapse stimulation by live imaging as a readout of the mobilization of vesicles for fusion. Among other findings, the authors provide evidence indicating that there are multiple reserve vesicle pools, that quickly and slowly mobilized reserves do not mix, and that vesicle fusion does not follow a mono-exponential time course, leading to the notion that two separate reserve pools of vesicles - slowly vs. rapidly mobilizing - feed two distinct releasable pools - reluctantly vs. rapidly releasing. These findings are valuable to the field of synapse biology, where the organization of synaptic vesicle pools that support synaptic transmission in different temporal and stimulation regimes has been a focus of intense experimentation and discussion for more than two decades.

On the other hand, the present study has limitations, so that the authors' key conclusions remain incompletely supported by the data, and alternative interpretations of the data remain possible. The approach of using bulk FM-styryl dye destaining as a readout of precise vesicle arrangements and pools in a population of functionally very diverse synapses bears problems. In essence, the approach is 'blind' to many additional processes and confounding factors that operate in the background, from other forms of release to inter-synaptic vesicle exchange. Further, averaging signals over many - functionally very diverse - synapses makes it difficult to distinguish the dynamics of separate vesicle pools within single synapses from a scenario where different kinetics of release originate from different types of synapses with different release probabilities.

The reviewers commented on the revised version of your paper, in essence reiterating the limitations of the approach of bulk imaging of FM de-staining:

(1) The authors sincerely addressed many of the previous concerns, mainly by clarification. The data are consistent with the authors' hypothesis. The pool concept is somewhat similar to that of Richards et al (2000) and Rey et al (2015). The authors further propose that two reserve pools feed vesicles to two readily-releasable pools independently. Unfortunately, the heterogeneity among individual synapses remains a concern as shown in (some of) the raw data (Fig. 3 and supplements). Bulk imaging of FM de-staining does not really measure the fraction of non-stained vesicles, which changes dynamically during stimulation, so that the situation calls for an independent readout of stained and non-stained vesicles. Moreover, direct correspondence between two specific stimulation frequencies (with long stimulation) and vesicle pools is not straightforward. These issues make the experimentally measured pools not well-defined.

(2) The authors' latest round of responses did not alleviate most of my major previous concerns. The additional data now shown in Fig 3 rely on conceptually the same type of bulk measurements and thus suffer from the same limitations as outlined in the earlier review. Moreover, the image of neuronal cultures shown in Fig. 3 might be problematic. It shows very bright staining with large round lumps, which may be indicative of unhealthy cultures.

Reviewer #1 (Public Review):

Summary:

This study presents fundamental new insights into vesicular monoamine transport and the binding pose of the clinical drug tetrabenazine (TBZ) to the mammalian VMAT2 transporter. Specifically, this study reports the first structure for the mammalian VMAT (SLC18) family of vesicular monoamine transporters. It provides insights into the mechanism by which this inhibitor traps VMAT2 into a 'dead-end' conformation. The structure also provides some evidence for a novel gating mechanism within VMAT2, which may have wider implications for understanding the mechanism of transport in the wider SLC18 family.

Strengths:

The structure is high quality, and the method used to determine the structure via fusing mVenus and the anti-GFP nanobody to the amino and carboxyl termini is novel. The binding and transport data are convincing and provide new insights into the role of conserved side chains within the SLC18 members. The binding position of TBZ is of high value, given its role in treating Huntington's chorea and for being a 'dead-end' inhibitor for VMAT2.

Reviewer #1 (Public Review):

The propagation of electrical signals within neuronal circuits is tightly regulated by the physical and molecular properties of neurons. Since neurons vary in size across species, the question arises whether propagation speed also varies to compensate for it. The present article compares numerous speed-related properties in human and rat neurons. They found that the larger size of human neurons seems to be compensated by a faster propagation within dendrites but not the axons of these neurons. The faster dendritic signal propagation was found to arise from wider dendritic diameters and greater conductance load in human neurons. In addition, the article provides a careful characterization of human dendrites and axons, as the field has only recently begun to characterize post-operative human cells. There are only a few studies reporting dendritic properties and these are not all consistent, hence there is the added value of reporting these findings, particularly given that the characterization is condensed in a compartmental model.

Strengths:<br /> The study was performed with great care using standard techniques in slice electrophysiology (pharmacological manipulation with somatic patch-clamp) as well as some challenging ones (axonal and dendritic patch-clamp). Modeling was used to parse out the role of different features in regulating dendritic propagation speed. The finding that propagation speed varies across species is novel as previous studies did not find a large change in membrane time constant or axonal diameters (a significant parameter affecting speed). A number of possible, yet less likely factors were carefully tested (Ih, membrane capacitance). The main features outlined here are well-known to regulate speed in neuronal processes. The modeling was also carefully done to verify that the magnitude of the effects is consistent with the difference in biophysical properties. Hence, the findings appear very solid to me.

Weaknesses:<br /> The role of diameter in regulating propagation speed is well-known in the axon literature.

Reviewer #1 (Public Review):

In this manuscript, Lebedeva et al. report the input/output wiring diagram of a population of previously identified giant excitatory neurons (abbreviated as ExNr) in the CA1 region of the rat hippocampus. Overall, Lebedeva et al. report that 1) ExNr are driven by Schaffer collaterals; 2) ExNr do not contact CA1Pyrs; 3) ExNr innervate PV interneurons; 4) ExNr received inhibition from bistratified cells, but not basket cells; and 5) ExNr -> PV synapse is strong enough to massively inhibit CA1Pyrs. Some of the findings reported here appear interesting. However, my appreciation of this manuscript was dampened by the limited scientific novelty, strong statements that are sometimes not supported by data, and vague, imprecise, and oversimplified narratives used throughout.

(1) The identity of ExNr reported here is unclear. It is unclear how ExNr are identified, and how robust the identification criteria are. A single anatomical reconstruction is provided together with depolarization-induced firing. However, whether all cells are consistent with the examples provided is unclear. Giant radiatum cells (previously known as RGCs, here abbreviated as ExNr) were previously identified by Maccaferri (1996) and Gulyas (1998). Based on anatomical criteria alone, it was suggested that these cells could take 4 different forms. The current manuscript mostly ignores this past finding. Given the topic of this paper, a careful anatomical and electrophysiological examination of ExNr is required.

(2) The identity of recorded interneurons is unclear. A major and potentially interesting finding reported here is the differential connectivity of ExNr to basket and bistratified neurons. However, it seems like basket and bistratified cells were mostly identified on the basis of electrophysiological criteria, and that 'only 5 neurons of each group were filed with biocytin, and the identity of interneurons was confirmed by axonal arborization pattern.' First, this significantly departs from the general current practices in the field where interneurons are identified based on combined anatomical and electrophysiological properties. This is because multiple examples in the literature support the extreme heterogeneity of interneurons, and that a combination of criteria is usually required for their appropriate identification. Second, the reconstruction of these neurons should be provided. Since the circuit wiring diagram proposed by the authors is based on these results, proper interneuron classification is necessary.

(3) Multiple conclusions are overstatements. For example, the interpretation that ExNr escapes perisomatic inhibition, as reported in the title, seems to ignore large families of cholecystokinin- or Sncg-expressing basket cells.

(4) Some of the more exciting findings appear preliminary, and the robustness of the findings is hard to evaluate. An example of that is found on Page 8, line 179: 'Thus, ExNR can operate as an amplification relay station for feed-forward inhibition of neurons in the CA area.' This conclusion appears only loosely supported by a few observations, (n = 3), as stated above. Similarly, the next section investigates the downstream effect of ExNr firing on CA1 pyramidal cells. The author reports that 'In 24% of the slices unitary APs in ExNr generated an fIPSP, delayed relative to the peak of the AP by 5.5 ms (n=6; Fig 3D-F).' In my opinion, 24% is a relatively low occurrence, even if we consider potentially cut axons (rightfully acknowledged by the authors) during the slicing procedure. Overall, this clearly doesn't fit the 'massive inhibition of downstream CA1Pyrs' proposed by the authors.

(5) The abstract and introduction are often too vague or oversimplified.

Reviewer #1 (Public Review):

Summary:<br /> Fiber photometry has become a very popular tool in recording neuronal activity in freely behaving animals. Despite the number of papers published with the method, as the authors rightly note, there are currently no standardized ways to analyze the data produced. Moreover, most of the data analyses confine to simple measurements of averaged activity and by doing so, erase valuable information encoded in the data. The authors offer an approach based on functional linear mixed modeling, where beyond changes in overall activity various functions of the data can also be analyzed. More in-depth analysis, more variables taken into account, and better statistical power all lead to higher quality science.

Strengths:<br /> The framework the authors present is solid and well-explained. By reanalyzing formerly published data, the authors also further increase the significance of the proposed tool opening new avenues for reinterpreting already collected data.

Weaknesses:<br /> However, this also leads to several questions. The normalization method employed for raw fiber photometry data is different from lab to lab. This imposes a significant challenge to applying a single tool of analysis. Does the method that the authors propose work similarly efficiently whether the data are normalized in a running average dF/F as it is described in the cited papers? For example, trace smoothing using running averages (Jeong et al. 2022) in itself may lead to pattern dilution. The same question applies if the z-score is calculated based on various responses or even baselines. How reliable the method is if the data are non-stationery and the baselines undergo major changes between separate trials?

Finally, what is the rationale for not using non-linear analysis methods? Following the paper's logic, non-linear analysis can capture more information that is diluted by linear methods.

Reviewer #1 (Public Review):

Summary:

There has been substantial prior work trying to understand the transcriptional control of proteasome expression as an adaptive response to proteasome inhibition. This field has been mired by fierce debates over the role of the protease Ddi2 in activating the transcription factor Nrf1/NFE2L1. As the authors of this manuscript point out, most of the previous research centers on the continuous treatment of cells with proteasome inhibitors rather than a brief pulse of inhibition that better models the situation when these drugs are used clinically. The authors find that the initial recovery of proteasome activity is independent of Ddi2 and involves a mechanism distinct from transcription. The authors intriguingly point to a model in which the assembly of proteasomes is regulated. If true, this would be a significant finding, but for now, this model remains more speculative.

Strengths:

The pulsed treatment of proteasome inhibitors is a strength of this lab that few others use. It better mimics the clinical use of these inhibitors and allows for a more detailed analysis of the initial response to inhibition. The authors have used multiple different clones of Ddi2 knockouts and siRNA against Ddi2 to rule out the necessity of Ddi2 in the early production of proteasomes when cells are inhibited with proteasomes. establishing a thorough knockout approach while also avoiding compensatory mutations. These experiments are well controlled, showing both the levels of Ddi2 upon knockout or knockdown and demonstrating that the cleavage of Nrf1, one of two known targets of Ddi2, is impaired. However, it should be noted that faint bands for Ddi2 mysteriously remain even in the knockout.

This article sensitively monitors the recovery of proteasome function with the β5 activity assay and for the production of new proteasome transcripts by qPCR. This precision and a detailed analysis of the timing are strengths that pointed to a more rapid recovery than transcription alone.

Weaknesses:

This paper's major weakness is the difficulty in establishing the authors' model that assembly is regulating this process. They do a convincing job demonstrating that activity recovers before transcription. The evidence that translation is unaffected depends entirely on the polysome RNA profiling from two replicates. Clearer and orthogonal data would help establish this finding. The stability of subunits is interesting and important in its own right.

In short, the authors establish that Ddi2 is unnecessary for the initial, non-transcriptional recovery of proteasome activity after a pulse of proteasome inhibition.

It is not clear what clinical impact this work will have. Although it models the pulse of proteasome inhibition more perfectly, it only looks at a single pulse rather than multiple treatments. Thus, ruling out Ddi2's importance for clinical benefit may be premature. More significantly, this work suggests that assembling proteasomes might be a regulated process worth substantial follow-up that will be interesting to follow.

Reviewer #2 (Public Review):

Harnessing macrophages to attack cancer is an immunotherapy strategy that has been steadily gaining interest. Whether macrophages alone can be powerful enough to permanently eliminate a tumor is a high-priority question. In addition, the factors making different tumors more vulnerable to macrophage attack have not been completely defined. In this paper, the authors find that MSP1 inhibition, most notable for causing chromosomal instability (CIN), in cancer cells improves the effect of macrophage targeted immunotherapies. They demonstrate that MSP1 inhibited tumors secrete factors that polarize macrophages to a more tumoricidal fate through several methods. The most compelling experiment is transferring conditioned media from MSP1 inhibited and control cancer cells, then using RNAseq to demonstrate that the MSP1-inhibited conditioned media causes a shift towards a more tumoricidal macrophage phenotype. In mice with MSP1 inhibited (CIN) B16 melanoma tumors, a combination of CD47 knockdown and anti-Tyrp1 IgG is sufficient for long term survival in nearly all mice. This combination is a striking improvement from conditions without CIN.

Like any interesting paper, this study leaves several unanswered questions. First, how do CIN tumors repolarize macrophages? The authors demonstrate that conditioned media is sufficient for this repolarization, implicating secreted factors, but the specific mechanism is unclear. The main caveat of the study is that chromosomal instability is driven by MSP1 inhibition in all the experiments, leaving open the possibility that some effects are due to MSP1 inhibition specifically rather than CIN more generally. To specifically connect CIN and macrophage repolarization, future studies will need to examine tumors with CIN unrelated to MSP1 inhibition to determine if these are also able to repolarize macrophages.

Overall, this is a thought-provoking study that will be of broad interest to many different fields including cancer biology, immunology and cell biology.

Reviewer #2 (Public Review):

Summary:

The work by Varadharajan et. al. explored a previously known genetic variant and its pathophysiology in the development of alcohol-associated liver injury. It provides a plausible mechanism for how varying levels of MBOAT7 could impact the lipid metabolomics of the cell, leading to a deleterious phenotype in MBOAT7 knockout. The authors further characterized the impact of the lipidomic changes and raised lysosomal biogenesis and autophagic flux as mechanisms of how MBOAT7 deletion causes the progression of ALD.

Strengths:

Connecting the GWAS data on MBOAT7 variants with plausible pathophysiology greatly enhances the translational relevance of these findings. The global lipidomic profiling of ALD mice is also very informative and may lead to other discoveries related to lipid handling pathways.

Weaknesses:

The rationale of why MBOAT7 metabolites are lower in heavy drinkers than in normal individuals is not well explained. MBOAT7 loss of function drives ALD, but unclear if MBOAT7 deletion also drives preference for alcohol or if alcohol inhibits MBOAT7 function. Presuming most individuals studied here were WT and expressed an appropriate level of MBOAT7?

Also, discussion of mechanisms of MBOAT7-induced dysregulation of lysosomal biogenesis/autophagy, while very interesting, seems incomplete. It is not clear how MBOAT7 an enzyme involved in membrane phospholipid remodeling increases mTOR which leads to decreased TFEB target gene transcription. Furthermore, given the significant disturbances of global lipidomic profiling in MBOAT7 knockout, many pathways are potentially affected by this deletion. Further in vivo modeling that specifically addresses these pathways (TFEB targeting, mTOR inhibitor) would help strengthen the conclusions of this paper.

Reviewer #2 (Public Review):

Summary:

The Meiri group previously showed that Notch1-activated human T-ALL cell lines are sensitive to a cannabis extract in vitro and in vivo (Ref. 32). In that article, the authors showed that Extract #12 reduced NICD expression and viability, which was partially rescued by restoring NICD expression. Here, the authors have identified three compounds of Extract #12 (CBD, 331-18A, and CBDV) that are responsible for the majority of anti-leukemic activity and NICD reduction. Using a pharmacological approach, the authors determined that Extract #12 exerted its anti-leukemic and NICD-reducing affects through the CB2 and TRPV1 receptors. To determine mechanism, the authors performed RNA-seq and observed that Extract #12 induces ER calcium depletion and stress-associated signals -- ATF4, CHOP, and CHAC1. Since CHAC1 was previously shown to be a Notch inhibitor in neural cells, the authors assume that the cannabis compounds repress Notch S1 cleavage through CHAC1 induction. The induction of stress-associated signals, Notch repression, and anti-leukemic effects were reversed by the integrated stress response (ISR) inhibitor ISRIB. Interestingly, combining the 3 cannabinoids gave synergistic anti-leukemic effects in vitro and had growth inhibitory effects in vivo.

Strengths:

(1) The authors show novel mechanistic insights that cannabinoids induce ER calcium release and that the subsequent integrated stress response represses activated NOTCH1 expression and kills T-ALL cells.

(2) This report adds to the evidence that phytocannabinoids can show a so-called "entourage effect" in which minor cannabinoids enhance the effect of the major cannabinoid CBD.

(3) This report dissects out the main cannabinoids in the previously described Extract #12 that contribute to T-ALL killing.

(4) The manuscript is clear and generally well-written.

(5) The data are mostly high quality and with adequate statistical analyses.

(6) The data generally support the authors' conclusions. The main exception is the experiments related to Notch.

(7) The authors' discovery of the role of the integrated stress response might explain previous observations that SERCA inhibitors block Notch S1 cleavage and activation in T-ALL (Roti Cancer Cell 2013). The previous explanation by Roti et al was that calcium depletion causes Notch misfolding, which leads to impaired trafficking and cleavage. Perhaps this explanation is not entirely sufficient?

Weaknesses:

(1) Given the authors' previous Cancer Communications paper on the anti-leukemic effects and mechanism of Extract #12, the significance of the original manuscript was reduced. To increase significance, the authors provided a new Fig. S7 in the revision showing that Extract #12 inhibits PDX growth in vivo. This experiment is nicely supportive of the anti-leukemic effects of Extract #12, raising the significance of their previous Cancer Communication paper by using in vivo patient-derived cells. However, this reviewer had suggested testing the combination of 333-18A+CBVD+CBD since the combination is the focus of the current manuscript. For unclear reasons, the combination was not tested.

(2) It would be important to connect the authors' findings and a wealth of literature on the role of ER calcium/stress on Notch cleavage, folding, trafficking, and activation. The several references suggested by this reviewer were not included in the revised manuscript for unclear reasons. These references are important to show the current status of the field and help readers appreciate what this manuscript brings that is new to T-ALL. In particular, Roti et al (Cancer Cell 2013) showed that SERCA inhibitors like thapsigardin reduce ER calcium levels and block Notch signaling by inhibiting NOTCH1 trafficking and inhibiting Furin-mediated (S1) cleavage of Notch1 in T-ALL. Multiple EGF repeats and all three Lin12/Notch repeats in the extracellular domains of Notch receptors require calcium for proper folding (Aster Biochemistry 1999; Gordon Nat. Struct. Mol. Biol. 2007; Hambleton Structure 2004; Rand Protein Sci 1997). Thus, Roti et al concluded that ER calcium depletion blocks NOTCH1 S1 cleavage in T-ALL. This effect seems to be conserved in Drosophila as Periz and Fortiin (EMBO J, 1999) showed impaired Notch cleavage in Ca2+/ATPase-mutated Drosophila cells.

(3) There is an overreliance of the data on single cell line -- MOLT4. MOLT4 is a good initial choice as it is Notch-mutated, Notch-dependent, and representative of the most common T-ALL subtype -- TAL1. However, there is no confirmatory data in other TAL1-positive T-ALLs or interrogation of other T-ALL subtypes. While this reviewer appreciates that the authors showed that multiple T-ALL cell lines were killed in response to Extract #12 in a previous study, the current manuscript is a separate study that should stand on its own. T-ALLs can be killed by multiple mechanisms. It would be important to show a few pieces of key data illustrating that the mechanism of killing found in MOLT4 applies to other T-ALLs.

(4) Fig. 6H. The effects of the cannabinoid combination might be statistically significant but seems biologically weak.

(5) Fig. 3. Based on these data, the authors conclude that the cannabinoid combination induces CHAC1, which represses Notch S1 cleavage in T-ALL cells. The concern is that Notch signaling is highly context dependent. CHAC1 might inhibit Notch in neural cells (Refs. 34-35), but it might not do this in a different context like T-ALL. It would be important to show evidence that CHAC1 represses S1 cleavage in the T-ALL context. More importantly, Fig. 3H clearly shows the cannabinoid combination inducing ATF4 and CHOP protein expression, but the effects on CHAC1 protein do not seem to be satisfactory as a mechanism for Notch inhibition. Perhaps something else is blocking Notch expression?

In the rebuttal, the two references provided by the authors do not alleviate concern that CHAC1 might not be acting as a Notch cleavage inhibitor in the T-ALL context. The Meng et al paper studied B-ALL not T-ALL and did not evaluate CHAC1 as a possible Notch cleavage inhibitor. Likewise, the Chang et al paper did not evaluate CHAC1 as a possible Notch cleavage inhibitor. Therefore, whether CHAC1 is a Notch cleavage inhibitor in the T-ALL context remains an open question. While the authors are correct that Supplementary Fig. S4G-I show that Extract #12 clearly induces CHAC1 protein expression, Main Fig. 3H shows that the extract combination 333-18A+CBVD+CBD, which is the focus of this manuscript, has unclear effects. If the extract combination has no effect on CHAC1 but has the same effects on Notch1 expression as the full extract, then there is reduced support for the authors' conclusion that the full extract and the 333-18A+CBVD+CBD combination inhibit Notch through CHAC1 induction.

(6) The authors provide a new figure on page 5 of the rebuttal that was not requested. It is supposed to show that CHAC1 loss protects T-ALL cells from Extract #12-induced cell population decline. Unfortunately, this figure is not conclusive. The empty vector PLKO is not an appropriate negative control. The field uses non-targeting shRNA controls like pLKO-luciferase to control for induction of the RNA interference pathway. Further, the viability data in panel B is normalized such that the effect of shCHAC1 on viability is masked. Showing non-normalized data is important, because if shCHAC1 impairs viability compared to control shRNA, then CHAC1might have effects on non-Notch pathways, which would reinforce the above concern in Point #5 that CHAC1 might not act as a Notch inhibitor in the T-ALL context. Separately, if this experiment had tested whether CHAC1 knockdown increases Notch cleavage and Notch target gene expression like DTX1, HES1 and MYC, then such data would have helped address Point #5.

(7) Fig. 4B-C/S5D-E. These Western blots of NICD expression are consistent with the cannabinoid combination blocking Furin-mediated NOTCH1 cleavage, which is reversed by ISR inhibition. However, there are many mechanisms that regulate NICD expression. To support their conclusion that the effects are specifically Furin-medated, the authors should probe full length (uncleaved) NOTCH1 in their Western blots. While the authors showed that the full extract (#12) increased uncleaved NOTCH1 expression in their Cancer Communications paper, a major conclusion of the manuscript is that the cannabinoid combination 333-18A+CBVD+CBD reproduces the effect of the full extract (#12). To support this conclusion, the authors should probe key blots for full-length Notch to show that the cannabinoid combination increases uncleaved NOTCH1 just like Extract #12 did in the authors' Cancer Communications paper.

(8) Fig. S4A-B. While these pharmacologic data are suggestive that Extract #12 reduces NICD expression through the CB2 receptor and TRPV1 channel, the doses used are very high (50uM). To exclude off-target effects, these data should be paired with genetic data to support the authors' conclusions. In the rebuttal, the authors provide dose response cell viability curves of the CB2 and TRPV1 inhibitors. These curves do not exclude the possibility that 50uM has off-target effects. This reviewer notes that Reviewer #1 had similar concerns and that both reviewers requested genetic validation of the pharmacological data. These data were not provided in the revision.

(9) Since the authors have performed gene expression profiling, an orthogonal test to confirm that Extract #12 acts through the Notch pathway is to perform enrichment analysis using Notch target gene signatures in T-ALL (e.g. Wang PNAS 2013). In contrast to the authors' rebuttal, this reviewer does not see any enrichment analysis (e.g. GSEA plots) performed on the microarray data to show that Extract #12 inhibits the Notch pathway.

(10) The revised manuscript still retains references that microarray data are "RNA-seq" data, which is inaccurate (see page 10, line 160; Figure 3 legend; page 12, line 169; page 27, line 428; page 36, line 741)

Reviewer #1 (Public Review):

Weinberger et al. use different fate-mapping models, the FIRE model and PLX-diet to follow and target different macrophage populations and combine them with single-cell data to understand their contribution to heart regeneration after I/R injury. This question has already been addressed by other groups in the field using different models. However, the major strength of this manuscript is the usage of the FIRE mouse model that, for the first time, allows specific targeting of only fetal-derived macrophages.

The data show that the absence of resident macrophages is not influencing infarct size but instead is altering the immune cell crosstalk in response to injury, which is in line with the current idea in the field that macrophages of different origins have distinct functions in tissues, especially after an injury.

To fully support the claims of the study, specific targeting of monocyte-derived macrophages or the inhibition of their influx at different stages after injury would be of high interest.

In summary, the study is well done and important for the field of cardiac injury. But it also provides a novel model (FIRE mice + RANK-Cre fate-mapping) for other tissues to study the function of fetal-derived macrophages while monocyte-derived macrophages remain intact.

Reviewer #1 (Public Review):

Klupt, Fam, Zhang, Hang, and colleagues present a novel study examining the function of sagA in E. faecium, including impacts on growth, peptidoglycan cleavage, cell separation, antibiotic sensitivity, NOD2 activation, and modulation of cancer immunotherapy. This manuscript represents a substantial advance over their prior work, where they found that sagA-expressing strains (including naturally-expressing strains and versions of non-expressing strains forced to overexpress sagA) were superior in activating NOD2 and improving cancer immunotherapy. Prior to the current study, an examination of sagA mutant E. faecium was not possible and sagA was thought to be an essential gene.

The study is overall very carefully performed with appropriate controls and experimental checks, including confirmation of similar densities of ΔsagA throughout. Results are overall interpreted cautiously and appropriately.

I have only two comments that I think addressing would strengthen what is already an excellent manuscript.

In the experiments depicted in Figure 3, the authors should clarify the quantification of peptidoglycans from cellular material vs supernatants. It should also be clarified whether the sagA need to be expressed endogenously within E. faecium, and whether ambient endopeptidases (perhaps expressed by other nearby bacteria or recombinant enzymes added) can enzymatically work on ΔsagA cell wall products to produce NOD2 ligands?

In the murine experiments depicted in Figure 4, because the bacterial intervention is being performed continuously in the drinking water, the investigators have not distinguished between colonization vs continuous oral dosing of the mice peptidoglycans. While I do not think additional experimentation is required to distinguish the individual contributions of these 2 components in their therapeutic intervention, I do think the interpretation of their results should include this perspective.

Reviewer #1 (Public Review):

Summary:<br /> This study unveils a novel role for ferritin in Drosophila larval brain development. Furthermore, it pinpoints that the observed defects in larval brain development resulting from ferritin knockdown are attributed to impaired Fe-S cluster activity and ATP production. In addition, knocking down ferritin genes suppressed the formation of brain tumors induced by brat or numb RNAi in Drosophila larval brains. Similarly, iron deficiency suppressed glioma in the mice model. Overall, this is a well-conducted and novel study.

Strengths:<br /> Thorough analyses with the elucidation of molecular mechanisms.

Weaknesses:<br /> Some of the conclusions are not well supported by the results presented.

Reviewer #1 (Public Review):

Summary:<br /> The authors have created a system for designing and running experimental pipelines to control and coordinate different programs and devices during an experiment, called Heron. Heron is based around a graphical tool for creating a Knowledge Graph made up of nodes connected by edges, with each node representing a separate Python script, and each edge being a communication pathway connecting a specific output from one node to an input on another. Each node also has parameters that can be set by the user during setup and runtime, and all of this behavior is concisely specified in the code that defines each node. This tool tries to marry the ease of use, clarity, and self-documentation of a purely graphical system like Bonsai with the flexibility and power of a purely code-based system like Robot Operating System (ROS).

Strengths:<br /> The underlying idea behind Heron, of combining a graphical design and execution tool with nodes that are made as straightforward Python scripts seems like a great way to get the relative strengths of each approach. The graphical design side is clear, self-explanatory, and self-documenting, as described in the paper. The underlying code for each node tends to also be relatively simple and straightforward, with a lot of the complex communication architecture successfully abstracted away from the user. This makes it easy to develop new nodes, without needing to understand the underlying communications between them. The authors also provide useful and well-documented templates for each type of node to further facilitate this process. Overall this seems like it could be a great tool for designing and running a wide variety of experiments, without requiring too much advanced technical knowledge from the users.

The system was relatively easy to download and get running, following the directions and already has a significant amount of documentation available to explain how to use it and expand its capabilities. Heron has also been built from the ground up to easily incorporate nodes stored in separate Git repositories and to thus become a large community-driven platform, with different nodes written and shared by different groups. This gives Heron a wide scope for future utility and usefulness, as more groups use it, write new nodes, and share them with the community. With any system of this sort, the overall strength of the system is thus somewhat dependent on how widely it is used and contributed to, but the authors did a good job of making this easy and accessible for people who are interested. I could certainly see Heron growing into a versatile and popular system for designing and running many types of experiments.

Weaknesses:<br /> The number one thing that was missing from the paper was any kind of quantification of the performance of Heron in different circumstances. Several useful and illustrative examples were discussed in depth to show the strengths and flexibility of Heron, but there was no discussion or quantification of performance, timing, or latency for any of these examples. These seem like very important metrics to measure and discuss when creating a new experimental system.

After downloading and running Heron with some basic test Nodes, I noticed that many of the nodes were each using a full CPU core on their own. Given that this basic test experiment was just waiting for a keypress, triggering a random number generator, and displaying the result, I was quite surprised to see over 50% of my 8-core CPU fully utilized. I don't think that Heron needs to be perfectly efficient to accomplish its intended purpose, but I do think that some level of efficiency is required. Some optimization of the codebase should be done so that basic tests like this can run with minimal CPU utilization. This would then inspire confidence that Heron could deal with a real experiment that was significantly more complex without running out of CPU power and thus slowing down.

I was also surprised to see that, despite being meant specifically to run on and connect diverse types of computer operating systems and being written purely in Python, the Heron Editor and GUI must be run on Windows. This seems like an unfortunate and unnecessary restriction, and it would be great to see the codebase adjusted to make it fully cross-platform-compatible.

Lastly, when I was running test experiments, sometimes one of the nodes, or part of the Heron editor itself would throw an exception or otherwise crash. Sometimes this left the Heron editor in a zombie state where some aspects of the GUI were responsive and others were not. It would be good to see a more graceful full shutdown of the program when part of it crashes or throws an exception, especially as this is likely to be common as people learn to use it. More problematically, in some of these cases, after closing or force quitting Heron, the TCP ports were not properly relinquished, and thus restarting Heron would run into an "address in use" error. Finding and killing the processes that were still using the ports is not something that is obvious, especially to a beginner, and it would be great to see Heron deal with this better. Ideally, code would be introduced to carefully avoid leaving ports occupied during a hard shutdown, and furthermore, when the address in use error comes up, it would be great to give the user some idea of what to do about it.

Overall I think that, with these improvements, this could be the beginning of a powerful and versatile new system that would enable flexible experiment design with a relatively low technical barrier to entry. I could see this system being useful to many different labs and fields.

Reviewer #1 (Public Review):

In this study by Yaghmaeian Salmani et al., the authors performed single-nuclei RNA sequencing of a large number of cells (>70,000) in the ventral midbrain. The authors focused on cells in the ventral tegmental area (VTA) and substantia nigra (SN), which contain heterogeneous cell populations comprising dopaminergic, GABAergic, and glutamatergic neurons. Dopamine neurons are known to consist of heterogeneous subtypes, and these cells have been implicated in various neuropsychiatric diseases. Thus, identifying specific marker genes across different dopamine subpopulations may allow researchers in future studies to develop dopamine subtype-specific targeting strategies that could have substantial translational implications for developing more specific therapies for neuropsychiatric diseases.

A strength of the authors' approach compared to previous work is that a large number of cells were sequenced, which was achieved using snRNA-seq, which the authors found to be superior compared to scRNA-seq for reducing sampling bias. A weakness of the study is that relatively little new information is provided as the results are largely consistent with previous studies (e.g., Poulin et al., 2014). Nevertheless, it should be noted that the authors found some more nuanced subdivisions in several genetically identified DA subtypes.

Lastly, the authors performed molecular analysis of ventral midbrain cells in response to 6-OHDA exposure, which leads to the degeneration of SN dopamine neurons, whereas VTA dopamine neurons are largely unaffected. Based on this analysis, the authors identified several candidate genes that may be linked to neuronal vulnerability or resilience.

Overall, the authors present a comprehensive mouse brain atlas detailing gene expression profiles of ventral midbrain cell populations, which will be important to guide future studies that focus on understanding dopamine heterogeneity in health and disease.

Comments on the revised version

The authors have addressed all of my concerns.

Reviewer #1 (Public Review):

Summary:

This is a short self-contained study with a straightforward and interesting message. The paper focuses on settling whether PKA activation requires dissociation of the catalytic and regulatory subunits. This debate has been ongoing for ~ 30 years, with renewed interest in the question following a publication in Science, 2017 (Smith et al.). Here, Xiong et al demonstrate that fusing the R and C subunits together (in the same way as Smith et al) prevents the proper function of PKA in neurons. This provides further support for the dissociative activation model - it is imperative that researchers have clarity on this topic since it is so fundamental to building accurate models of localised cAMP signalling in all cell types. Furthermore, their experiments highlight that C subunit dissociation into spines is essential for structural LTP, which is an interesting finding in itself. They also show that preventing C subunit dissociation reduces basal AMPA receptor currents to the same extent as knocking down the C subunit. Overall, the paper will interest both cAMP researchers and scientists interested in fundamental mechanisms of synaptic regulation.

Strengths:

The experiments are technically challenging and well executed. Good use of control conditions e.g untransfected controls in Figure 4.

Weaknesses:

The novelty is lessened given the same team has shown dissociation of the C subunit into dendritic spines from RIIbeta subunits localised to dendritic shafts before (Tillo et al., 2017). Nevertheless, the experiments with RII-C fusion proteins are novel and an important addition.

Reviewer # 1 (Public Review):

Summary:<br /> The paper nicely confirms the phenotype of Lama2 knockout mice and extends the phenotypic description with a set of new molecular studies (transcriptomics) that might serve as a resource for other scientists interested in the LAMA2-MD.

Strengths:<br /> Set of new molecular studies (transcriptomics) that might serve as a resource for other scientists interested in the LAMA2-MD.

Weaknesses:<br /> Some of the figures are of rather poor quality. For example, the H&E and Sirius Red stainings in Figures 3 and 4 are quite poor so it is difficult to see what is going on in the muscles. The authors should take note of another publication on dy3K/dy3K mice of similar age (PMID: 31586140) where such images are of much higher quality. Similarly, the Western blot for laminin-alpha2 (Figure 4B) of the wild-type mouse needs improvement. If the single laminin-alpha2 protein is not detected, there is an issue with the denaturation buffer used to load the protein.

My biggest concern is, however, the many overstatements in the manuscript and the over-interpretation of the data. This already starts with the first sentence in the abstract where the authors write: "Understanding the underlying pathogenesis of LAMA2-related muscular dystrophy (LAMA2-MD) have been hampered by lack of genuine mouse model." This is not correct as the dy3K/dy3K, generated in 1997 (PMID: 9326364), are also Lama2 knockout mice; there are also other strains (dyW/dyW mice) that are severely affected and there are the dy2J/dy2J mice that represent a milder form of LAMA2-MD.

Similarly, the last two sentences of the abstract "This is the first reported genuine model simulating human LAMA2-MD. We can use it to study the molecular pathogenesis and develop effective therapies." are a clear overstatement. The mechanisms of the disease are well studied and the above-listed mouse models have been amply used to develop possible treatment options.

The overinterpretation concerns the results from transcriptomics. The fact that Lama2 is expressed in particular cell types of the brain does not at all imply that Lama2 knockout mice have a defect in the blood-brain barrier as the authors state. If there are no functional data, this cannot be stated. Indications for a blood-brain barrier defect come from work in dy3K/dy3K mice (PMID: 25392494) and this needs to be written like this.

Finally, the bulk RNA-seq data also needs to be presented in a disease context. The authors, again, mix up changes in expression with functional impairment. All gene expression changes are interpreted as direct evidence of an involvement of the cytoskeleton. In fact, changes in the cytoskeleton are more likely a consequence of the severe muscle phenotype and the delay in muscle development. This is particularly possible as muscle samples from 14-day-old mice are compared; a stage at which muscle still develops and grows tremendously. Thus, all the data need to be interpreted with caution.

In summary, the authors need to improve data presentation and, most importantly, they need to tone down the interpretation and they must be fully aware that their work is not as novel as they present it.

Reviewer #1 (Public Review):

In this manuscript, the authors investigated the dynamics of a neural network model characterized by sparsely connected clusters of neuronal ensembles. They found that such a network could intrinsically generate sequence preplay and place maps, with properties like those observed in the real-world data. Strengths of the study include the computational model and data analysis supporting the hippocampal network mechanisms underlying sequence preplay of future experiences and place maps.

Previous models of replay or theta sequences focused on circuit plasticity and usually required a pre-existing place map input from the external environment via upstream structures. However, those models failed to explain how networks support rapid sequential coding of novel environments or simply transferred the question to the upstream structure. On the contrary, the current proposed model required minimal spatial inputs and was aimed at elucidating how a preconfigured structure gave rise to preplay, thereby facilitating the sequential encoding of future novel environments.

In this model, the fundamental units for spatial representation were clusters within the network. Sequential representation was achieved through the balance of cluster isolation and their partial overlap. Isolation resulted in a self-reinforced assembly representation, ensuring stable spatial coding. On the other hand, overlap-induced activation transitions across clusters, enabling sequential coding.

This study is important when considering that previous models mainly focused on plasticity and experience-related learning, while this model provided us with insights into how network architecture could support rapid sequential coding with large capacity, upon which learning could occur efficiently with modest modification via plasticity.

I found this research very inspiring and, below, I provide some comments aimed at improving the manuscript. Some of these comments may extend beyond the scope of the current study, but I believe they raise important questions that should be addressed in this line of research.

(1) The expression 'randomly clustered networks' needs to be explained in more detail given that in its current form risks to indicate that the network might be randomly organized (i.e., not organized). In particular, a clustered network with future functionality based on its current clustering is not random but rather pre-configured into those clusters. What the authors likely meant to say, while using the said expression in the title and text, is that clustering is not induced by an experience in the environment, which will only be later mapped using those clusters. While this organization might indeed appear as randomly clustered when referenced to a future novel experience, it might be non-random when referenced to the prior (unaccounted) activity of the network. Related to this, network organization based on similar yet distinct experiences (e.g., on parallel linear tracks as in Liu, Sibille, Dragoi, Neuron 2021) could explain/configure, in part, the hippocampal CA1 network organization that would appear otherwise 'randomly clustered' when referenced to a future novel experience.

(2) The authors should elaborate more on how the said 'randomly clustered networks' generate beyond chance-level preplay. Specifically, why was there preplay stronger than the time-bin shuffle? There are at least two potential explanations:

(1) - When the activation of clusters lasts for several decoding time bins, temporal shuffle breaks the continuity of one cluster's activation, thus leading to less sequential decoding results. In that case, the preplay might mainly outperform the shuffle when there are fewer clusters activating in a PBE. For example, activation of two clusters must be sequential (either A to B or B to A), while time bin shuffle could lead to non-sequential activations such as a-b-a-b-a-b where a and b are components of A and B;

(2) - There is a preferred connection between clusters based on the size of overlap across clusters. For example, if pair A-B and B-C have stronger overlap than A-C, then cluster sequences A-B-C and C-B-A are more likely to occur than others (such as A-C-B) across brain states. In that case, authors should present the distribution of overlap across clusters, and whether the sequences during run and sleep match the magnitude of overlap. During run simulation in the model, as clusters randomly receive a weak location cue bias, the activation sequence might not exactly match the overlap of clusters due to the external drive. In that case, the strength of location cue bias (4% in the current setup) could change the balance between the internal drive and external drive of the representation. How does that parameter influence the preplay incidence or quality?

(3). The manuscript is focused on presenting that a randomly clustered network can generate preplay and place maps with properties similar to experimental observations. An equally interesting question is how preplay supports spatial coding. If preplay is an intrinsic dynamic feature of this network, then it would be good to study whether this network outperforms other networks (randomly connected or ring lattice) in terms of spatial coding (encoding speed, encoding capacity, tuning stability, tuning quality, etc.)

(4) The manuscript mentions the small-world connectivity several times, but the concept still appears too abstract and how the small-world index (SWI) contributes to place fields or preplay is not sufficiently discussed.

For a more general audience in the field of neuroscience, it would be helpful to include example graphs with high and low SWI. For example, you can show a ring lattice graph and indicate that there are long paths between points at opposite sides of the ring; show randomly connected graphs indicating there are no local clustered structures, and show clustered graphs with several hubs establishing long-range connections to reduce pair-wise distance.

How this SWI contributes to preplay is also not clear. Figure 6 showed preplay is correlated with SWI, but maybe the correlation is caused by both of them being correlated with cluster participation. The balance between cluster overlap and cluster isolation is well discussed. In the Discussion, the authors mention "...Such a balance in cluster overlap produces networks with small-world characteristics (Watts and Strogatz, 1998) as quantified by a small-world index..." (Lines 560-561). I believe the statement is not entirely appropriate, a network similar to ring lattice can still have the balance of cluster isolation and cluster overlap, while it will have small SWI due to a long path across some node pairs. Both cluster structure and long-range connection could contribute to SWI. The authors only discuss the necessity of cluster structure, but why is the long-range connection important should also be discussed. I guess long-range connection could make the network more flexible (clusters are closer to each other) and thus increase the potential repertoire.

(5) What drives PBE during sleep? Seems like the main difference between sleep and run states is the magnitude of excitatory and inhibitory inputs controlled by scaling factors. If there are bursts (PBE) in sleep, do you also observe those during run? Does the network automatically generate PBE in a regime of strong excitation and weak inhibition (neural bifurcation)?

(6) Is the concept of 'cluster' similar to 'assemblies', as in Peyrache et al, 2010; Farooq et al, 2019? Does a classic assembly analysis during run reveal cluster structures?

(7) Can the capacity of the clustered network to express preplay for multiple distinct future experiences be estimated in relation to current network activity, as in Dragoi and Tonegawa, PNAS 2013?