Joint Public Review

In this manuscript, the authors develop a multi-scale agent-based model (ABM) capable of reproducing the self-organizing behavior observed in the intestinal crypt. By considering just the signaling pathways -previously reported as regulatory in the intestinal crypt- and local physical cell-to-cell interactions, the proposed model not only explains the emergence of the spatial organization, but also recapitulates cell composition dynamics in the crypt (proliferation, migration, and differentiation of cells), as previously characterized in the complex tissue of the small intestine epithelium in mice. The authors show that the self-organized system resulting from the model displays a stable composition over time. Additionally, the authors show how this model can be effectively used to test different conditions, such as biomedically relevant perturbations (e.g. stem cell ablation, cell cycle inhibition, and toxicity of particular drug treatments) and the posterior recovery, allowing to predict the safety of potential oncotherapies.

In summary, the authors provide a powerful and versatile model, which can be applied to better understand the formation and response of the intestinal crypt, as well as the functional heterogeneity of the intestinal epithelium at multiple scales. The proposed mathematical model simulates features across scales in the intestinal crypt such as multiple signaling pathways, the mechanical environment and its forces, and cell cycle regulation. The model demonstrates the stability of the homeostatic crypt and recovery following stem cell ablation. The model also simulates the cell cycle protein network and demonstrates that CDK1 inhibition creates oversized cells. In sum, the model generated by the authors increases the understanding of how these biological processes take place in vivo, exploring not only healthy cell behavior but also cell response to injury by oncotherapies or other external factors. Additionally, the authors provide a series of fascinating movies that show the spatial organization of the crypt during these processes, and the manuscript has clear applications for the clinics.

Nevertheless, in its current form, the manuscript has some weaknesses that are worth mentioning:

(1) The developed model considers the interaction of multiple signaling networks that are essential for morphogenesis and homeostasis in the intestinal tissue, as well as other elements that had been proposed as relevant in the literature. Nevertheless, the details of how these interactions are modeled couldn't be evaluated in the current revision as the model was not shared with the reviewers and it is not available yet online, nor specified in any detail in the current manuscript. Additionally, how quantitative information from Wnt and BMP signaling pathways is incorporated in a quantitative way in the model is not clear.

(2) Some conclusions by the authors are not properly justified in the text, as "Paneth cells are the main driver behind the differential mechanical environment in the niche", "Wnt-mediated feedback loop prevents the uncontrolled expansion of the niche", the specific effect of p27 in contrast with Wee1 phosphorylation over the cell cycle length, and "their recovery [absorptive progenitors] started before the end of the treatment, driven by a negative feedback loop from mature enterocytes to their progenitors".

(3) Only the results of the "main" model are shown, with no information about its sensitivity to parameter values, and how their conclusions depend on specific decisions on the model. For example, the authors said that "an optimal crypt cell composition is achieved when BMP and Wnt differentiation thresholds result in progenitors dividing approximately four times before differentiating into enterocytes", but the results of alternative scenarios are not shown.

(4) Regarding the construction of the model, the authors used "counts of Ki-67 positive cells recorded by position" while the original data reported "overall cell counts per crypt and villus". Some explanation about how this conversion was made, why it is valid, as well as any potential problems, is needed. Additionally, the model is based on experiments done by others in mouse models; the similarity to the response in human intestinal crypts is not discussed.

(5) The authors imply that their mathematical model of the intestinal crypt is an improvement over those already published but there is no direct comparison or review of the literature to substantiate this claim.

(6) The authors claim that the simulated data and the available mouse data match up. Nevertheless, the data vs the model still appear both quantitatively and qualitatively different (as presented in Figures 2E, F, and 5C, D). This puts in doubt how much the model can actually reproduce the experimental data. In conclusion, the model would benefit from further refinement, particularly if the goal is to use the model for predicting the dynamics of oncogenic drug candidates.

Reviewer #1 (Public Review):

In their manuscript, Brischigliaro et al. show that the disruption of respiratory complex assembly results in Drosophila melanogaster results in the accumulation of respiratory supercomplexes. Further, they show that the change in the supercomplex abundance does not impact respiratory function suggesting that the main role of supercomplex formation is structural. Overall, the manuscript is well written and the results and conclusion are supported. The D. melanogaster system, in which the abundance of supercomplexes can be altered through the genetic disruption of the assembly of the individual complexes, will be important for the field to discover the role of the supercomplexes. This manuscript will be of broad interest to the field of mitochondrial bioenergetics. The findings are valuable and the evidence is convincing.

Strengths<br /> The system developed in which the relative levels of SCs can be varied will be extremely useful for studying SC physiology.

The experiments are clearly described and interpreted.

Weaknesses<br /> The previous weaknesses identified have been addressed.

Reviewer #1 (Public Review):

DMRT1 is essential in testis development in different species. While Dmrt1 is the testis-determining factor in chicken and deletion encompassing this gene lead to gonadal dysgenesis in human, the role of DMRT1 in testis development remains to be clarified. Despite an early expression of Dmrt1 in the mouse gonad and a potential function as a pioneer factor, DMRT1 is only required for the maintenance of the Sertoli cell identity in the postnatal testis. The use of a new animal model could provide new insights into the role of this factor in humans. Here the authors have generated a knockout model of DMRT1 in rabbits. They show that the XY mutant gonads differentiate as ovary indicating that DMRT1 is required for testis differentiation in rabbits. In addition, most of the germ cells remain pluripotent as evidenced by the maintenance of POU5F1 in both XY and XX mutant gonads. These are very important results potentially explaining gonadal dysgenesis associated with the DMRT1 locus in disorders of sex development in humans.

The experiments are meticulous and convincing. I find the arguments of the authors about the role of DMRT1 in germ cells in addition to its function in Sertoli cell differentiation, both comprehensible and compelling. Clearly, this is an important insight in sex determination and gametogenesis.

Reviewer #1 (Public Review):

This study assesses the volatile profiles from the hair and bodies of 64 vertebrate species to compare odor constituents across taxa. Compared to a similar data set for floral volatiles, the study suggests that vertebrate odors are significantly less diverse and show little phylogenetic relationship regarding profile similarity. Human odors were particularly unique from other species. It is concluded that this may influence the odor coding of organisms (like vectors) who respond to these odors compared to plant-feeding organisms like most other insects. While the study is compelling, several methodological issues leave the conclusions less convincing. It is suggested that the paper be tempered accordingly with these issues mentioned.<br /> The study makes several assumptions about the methodology to be considered when interpreting the results:

Major Concerns:

1) Body hair as a proxy for animals. "Hair odour is likely a reasonable proxy for mammalian body odour, but may lose some volatile compounds during storage. Live-animal odour, on the other hand, can be contaminated with compounds from faeces or urine occasionally excreted during sampling." The study has addressed this by testing hair against the bodies of 4 humans, two rats, and one guinea pig (Figure S1). However, the results show that there are both quantitative and qualitative differences among all the samples. While the presence of waste accounts for some of this variation, this, too, is a natural response of the animal and could be present in natural settings. Also would not body heat in mammals have an impact on odors? The authors should support this. While this does not require reanalysis, the authors should address these differences, particularly when qualitative and quantitative differences are discussed heavily in the results.

2) Sampling medium: Tenax TA was used to sample the vertebrate odors. Please note that any sorbent will exhibit specificity regarding selectivity and sensitivity to VOCs. See https://www.eva.mpg.de/documents/Elsevier/Marcillo_Comparison_JChromA_2017_2452774.pdf for one comparison. For example, it is not surprising that "Aldehydes, ketones, alcohols, aromatics, terpenes, and hydrocarbons dominated" the samples given that these types of compounds are well retained by the Tenax polymer:<br /> https://www.sisweb.com/index/referenc/tenaxta.htm<br /> Many chemical ecology studies will employ multiple polar and non-polar polymers to retain different VOCs for better profile comparison.<br /> By itself, this limitation must be noted. However, it becomes even more relevant when compared to the floral volatile study, which used a different sorbent (Poropak) which is less hydrophobic and may retain more polar compounds than Tenax: https://hero.epa.gov/hero/index.cfm/reference/details/reference_id/2859526<br /> Such differences must be considered when comparing these two datasets, particularly when the study makes conclusions about their differences. Alternatively, a small set of experiments with poropak and a few species (like for the hair vs. body control experiments) could clarify the effect of sorbent type on VOC retention.

3) Sampling quantification: The methods note that " All extractions were run for 5-80 minutes depending on the expected odour concentration of the sample." What does this mean? Such differences in sampling timing in our lab have shown profound differences in the type and amount of volatiles collected. Generally, it is best to sample for as long as possible to ensure that the most volatiles are collected (up to 24 hours if possible). The compounds will eventually come into equilibrium with the sorbent. However, for quantification, the timing must be calibrated carefully, usually by using a representative set of likely compounds with different functional groups to determine the optimal length of sampling time. Was this done in this case? If not, how can one account for the significant variation in sampling time regarding quantification?<br /> A second issue with quantification is the need for an internal standard. Even with robotic assistance, slight variations in processing can significantly affect the quantity of volatile retained through detection at the MS. This is generally avoided by using an internal standard in the sampling arena. See this example with multiple sampling techniques (also employing TD-GCMS): https://www.frontiersin.org/articles/10.3389/fevo.2021.607555/full<br /> Without these methodological controls, it is unclear how effective quantification can be performed. It might be more prudent to confine the results to qualitative discussions.

Reviewer #1 (Public Review):

This study seeks to understand how selective mRNA translation informs cellular identity using the Drosophila brain as a model. Using drivers specific for either neurons or glia, the authors express a tagged large ribosomal subunit protein, which they then use as a handle for isolating total mRNA and ribosome footprints. Throughout the study, they compare these data sets to transcriptional and ribosome profiles from the whole fly head, which contains multiple cell types including fat tissue, pigment cells, and others, in addition to neurons and glia. Using GO term analyses, they demonstrate the specificity of their cell-type-based ribosome profiling: known glial mRNAs are efficiently translated in glia and likewise in neurons as well. In further examining their RNAseq data set, they find that "neuronal" mRNAs, such as ion channels, are expressed in both neurons and glia, but are translated at higher rates in neurons. Based on this, they hypothesize that neuronal mRNAs are actively suppressed in glia, and next seek to determine the underlying mechanism. By meta-analysis of all mapped ribosome footprints, they find that glia have higher ribosome occupancies in the 5' leader of neuronal mRNAs. This is corroborated by individual ribosome occupancy profiles for several neuronal mRNAs. In 5'leaders containing upstream AUG codons, they find that the glial data sets show enrichment of ribosomes at these upstream start sites. They thus conclude that 5' leaders containing upstream AUGs confer translational suppression in glia.

Overall, the sequencing data sets generated in this study and their subsequent bioinformatic analyses seem robust and reliable. Their data echo the trends of cell-type specific translational profiles seen in previous studies (e.g. 27380875, 30650354), and making their data sets and analyses accessible to the broader scientific community would be quite helpful. The findings are presented in a logical and methodical manner, and the data are depicted clearly. The authors' results that 5' leaders facilitate translation suppression is well-supported in literature. However, they overinterpret their data by claiming that such suppression is key for maintaining glial/neuronal identity (it is even featured in their title), but do not present any evidence that loss of such regulation has any impact on cellular identity. In many places, the authors do not acknowledge possible biases in their analytical methods, or consider alternate explanations for their data. These weaken the manuscript in its current form, but many of these issues which I describe below, are rectifiable with modest effort.

1. The authors' data in Fig. 2-S1A-B shows substantial cell-to-cell variation in RpL3::FLAG expression. The authors do not consider that this variation may cause certain neuronal/glial types to be overrepresented in their datasets. A related point is that the authors do not discuss whether RpL3::FLAG is only present in the cell body or if it is also trafficked to the neuronal/glial processes where localized translation is known to occur (reviewed in 31270476).

2. The RNA-seq data set that they use to calculate translation efficiency (TE) only represents mRNAs associated with RpL3::FLAG, which is part of the large ribosome subunit. As the authors are likely aware, there are mRNAs on which the full ribosome moiety does not assemble and these are effectively excluded from this data set. Ideally, a more complete picture of the mRNA landscape can be obtained by 40S subunit profiling but I appreciate that this is technically very challenging. At a minimum, this caveat needs to be acknowledged.

How does the TPM of differentially regulated transcripts (such as those in Fig. 2H) compare between whole heads, neurons, and glia? Since the whole head RNA-seq data was not from an enriched sample, this might serve as a decent proxy for showing that the neuron/glia RNA-seq data sets are representative of RNA abundance.

3. The analysis in Fig. 2F shows that low abundance mRNAs in glia are further translationally suppressed, which the authors point out in lines 151-152. However, this data also shows that mRNAs with a 1:1 ratio in neuron:glia (which fall in the 0.5-1 and 1-2 bin) have a TE1; this suggests that on average, mRNAs that are equally abundant are translated equally efficiently. This is the opposite of the thesis presented in Fig. 2G-H where many mRNAs of equal abundance in neurons and glia are actually poorly translated in glia. How do the authors reconcile these observations?<br /> It is also unclear from the manuscript whether all mRNAs were considered for the analysis in Fig. 2F or if some cutoff was employed.

4. Throughout the manuscript the authors favor a "translation suppression" model wherein glia (for example) actively suppress neuronal mRNAs, and this is substantiated in Fig. 3C showing higher ribosome occupancy on 5' leaders than in coding regions. However, they show no evidence that glial mRNAs (such as those indicated in Fig. 2B and 2-S2B) present a different pattern, say that of higher ribosome occupancy in CDS vs. 5' leaders. This type of positive control is a glaring omission from many of their analyses, including ribosome occupancy at upstream AUG codons (Fig. 4).<br /> In order to make a broad case (as they do in the title) that differential translation regulation specifies multiple cell types, it is necessary to show the corollary: that glial mRNAs (repo, bnb, pnt, etc) are suppressed in neurons. There is an inkling of this evidence in Fig. 3-S1 where fat body mRNAs in neurons are shown to have low ribosome occupancy in the CDS regions and enhanced occupancy in the 5' leader region. This data is not quantified, nor is a control neuron mRNA shown as a reference for what the ribosome occupancy profile of an actively translated mRNA looks like in a neuron.

5. The cell-type specific ribosome profiling data sets in the manuscript are from mRNAs associated with 80s subunits that have been treated with cycloheximide during sample preparation. Cycloheximide, and many other translation inhibitors, are known to non-uniformly bias reads towards start codons (PMID: 22056041,22927429). This important caveat and its implications on the start-codon occupancy analysis in Fig. 4 are not acknowledged in the manuscript.<br /> Again, the ideal resolution would be a ribosome profiling data set from 40S footprinting or harringtonine-treated samples (PMIDs: 32589966, 27487212, 32589964) to show the true accumulation of ribosomes at AUG codons. In the absence of such a data set, a comparative meta-analysis of the ribosome distribution around upstream and initiation AUG codons of differentially translated transcripts from neurons would be a useful control.

6. The authors chose Rhodopsin 1 (Rh1) as a model mRNA which is translated efficiently in neurons but suppressed in glia. Though the data in Fig. 2-S3B shows higher TE for Rh1 in neurons, the data in 5A show lower ribosome occupancy in the Rh1 CDS in neuron samples (at least in the fragment of the CDS visible). These data are somewhat contradictory.<br /> Further, given that the neuron data are from all nsyb-positive cells but that Rh1 is expressed only in R1-R6 photoreceptors, it is unclear what motivated them to choose Rh1 as opposed to an mRNA that is more broadly expressed in neurons.

7. Similar to the heterogeneity in nsyb- and repo-GAL4 expression in Fig. 2-S1A-B, Fig. 5C shows substantial variation in the expression of the UAS-GFP reporter driven by tub-GAL4. This variable GAL4 activity makes the mRNA abundance data difficult to interpret. Also, since the authors presume that Rh1 mRNA is expressed in glia (it is not annotated in the RNA-seq analysis in Fig. 2-S2B), would Rh1-GAL4 not be a more apt driver?<br /> These issues are further compounded by the lack of a cellular compartment marker (repo marks glial nuclei) which makes it impossible to determine which cell the mRNA signal is in. There are also no negative controls presented for the mRNA probes.<br /> Most confoundingly though, the control reporter itself seems to show variable translation efficiencies from one cell to another, with high-GFP protein cells showing lower GFP mRNA and vice versa.<br /> The mRNA:protein ratio may be easier to examine by using repo-GAL4 to specifically drive the Rh1-reporter expression in glia (such as in Fig. 5-S1A) rather than simultaneous expression in both neurons and glia using tub-GAL4.

Reviewer #1 (Public Review):

In the article "Temporal transcriptomic dynamics in developing macaque neocortex", Xu et al. analyze the cellular composition and transcriptomic profiles of the developing macaque parietal cortex using single-cell RNA sequencing. The authors profiled eight prenatal rhesus macaque brains at five timepoints (E40, E50, E70, E80, and E90) and obtained a total of around 53,000 high-quality cells for downstream analysis. The dataset provides a high-resolution view into the developmental processes of early and mid-fetal macaque cortical development and will potentially be a valuable resource for future comparative studies of primate neurogenesis and neural stem cell fate specification. Their analysis of this dataset focused on the temporal gene expression profiles of outer and ventricular radial glia and utilized pesudotime trajectory analysis to characterize the genes associated with radial glial and neuronal differentiation. The rhesus macaque dataset presented in this study was then integrated with prenatal mouse and human scRNA-seq datasets to probe species differences in ventricular radial glia to intermediate progenitor cell trajectories. Additionally, the expression profile of macaque radial glia across time was compared to those of mouse apical progenitors to identify conserved and divergent expression patterns of transcription factors.

The main findings of this paper corroborate many previously reported and fundamental features of primate neurogenesis: deep layer neurons are generated before upper layer excitatory neurons, the expansion of outer radial glia in the primate lineage, conserved molecular markers of outer radial glia, and the early specification of progenitors. Furthermore, the authors show some interesting divergent features of macaque radial glial gene regulatory networks as compared to mouse. Overall, despite some uncertainties surrounding the clustering and annotations of certain cell types, the manuscript provides a valuable scRNA-seq dataset of early prenatal rhesus macaque brain development. The dynamic expression patterns and trajectory analysis of ventricular and outer radial glia provide valuable data and lists of differentially expressed genes (some consistent with previous studies, others reported for the first time here) for future studies.

The major weaknesses of this study are the inconsistent dissection of the targeted brain region and the loss of more mature excitatory neurons in samples from later developmental timepoint due to the use of single-cell RNA-seq. The authors mention that they could observe ventral progenitors and even midbrain neurons in their analyses. Ventral progenitors should not be present if the authors had properly dissected the parietal cortex. The fact that they obtained even midbrain cells point to an inadequate dissection or poor cell classification. If this is the result of poor classification, it could be easily fixed by using more markers with higher specificity. However, if it is the result of a poor dissection, some of the cells in other clusters could potentially be from midbrain as well. The loss of more mature excitatory neurons is also problematic because on top of hindering the analysis of these neurons in later developmental periods, it also affects the cell proportions the authors use to support some of their claims. The study could also benefit from the validation of some of the genes the authors uncovered to be specifically expressed in different populations of radial glia.

Reviewer #1 (Public Review):

The main goal of the study was to tease apart the associative and non-associative elements of cued fear conditioning that could influence which defensive behaviors are expressed. To do this, the authors compared groups conditioned with paired, unpaired, or shock only procedures followed by extinction of the cue. The cue used in the study was not typical; serial presentation of a tone followed by a white noise was used in order to assess switches in behavior across the transition from tone to white noise. Many defensive behaviors beyond the typical freezing assessments were measured, and both male and female mice were included throughout. The authors found changes in behavioral transitions from freezing to flight during conditioning as the tone transitioned into white noise, and a switch in freezing during extinction such that it became high during the white noise as flight behavior decreased. Overall, this was an interesting analysis of transitions in defensive behaviors to a serially presented cue consisting of two auditory stimuli during conditioning and then extinction. There are some concerns regarding the possibility that the white noise is more innately aversive than the tone, inducing more escape-like behaviors compared to a tone, especially since the shock only group also showed increased escape-like behaviors during the white noise versus tone. This issue would have been resolved by adding a control group where the order of the auditory stimuli was reversed (white noise->tone). While the more complete assessment of defensive behaviors beyond freezing is welcomed, the main conclusions in the discussion are overly focused on the paired group and the associative elements of conditioning, which would likely not be surprising to the field. If the goal, as indicated in the title, was to tease apart the associative and non-associative elements of conditioning and defensive behaviors, there needs to be a more emphasized discussion and explicit identification of the non-associative findings of their study, as this would be more impactful to the field.

Reviewer #1 (Public Review):

The paper submitted by Yogesh and Keller explores the role of cholinergic input from the basal forebrain (BF) in the mouse primary visual cortex (V1). The study aims to understand the signals conveyed by BF cholinergic axons in the visual cortex, their impact on neurons in different cortical layers, and their computational significance in cortical visual processing. The authors employed two-photon calcium imaging to directly monitor cholinergic input from BF axons expressing GCaMP6 in mice running through a virtual corridor, revealing a strong correlation between BF axonal activity and locomotion. This persistent activation during locomotion suggests that BF input provides a binary locomotion state signal. To elucidate the impact of cholinergic input on cortical activity, the authors conducted optogenetic and chemogenetic manipulations, with a specific focus on L2/3 and L5 neurons. They found that cholinergic input modulates the responses of L5 neurons to visual stimuli and visuomotor mismatch, while not significantly affecting L2/3 neurons. Moreover, the study demonstrates that BF cholinergic input leads to decorrelation in the activity patterns of L2/3 and L5 neurons.

This topic has garnered significant attention in the field, drawing the interest of many researchers actively investigating the role of BF cholinergic input in cortical activity and sensory processing. The experiments and analyses were thoughtfully designed and conducted with rigorous standards, leading to convincing results which align well with findings in previous studies. In other words, some of the main findings, such as the correlation between cholinergic input and locomotor activity and the effects of cholinergic input on V1 cortical activity, have been previously demonstrated by other labs (Goard and Dan, 2009; Pinto et al., 2013; Reimer et al., 2016). However, the study by Yogesh and Keller stands out by combining cutting-edge calcium imaging and optogenetics to provide compelling evidence of layer-specific differences in the impact of cholinergic input on neuronal responses to bottom-up (visual stimuli) and top-down inputs (visuomotor mismatch).

Reviewer #1 (Public Review):

In this study, Nuria Martin-Flores, Marina Podpolny and colleagues investigate the role of Dickkopf-3 (DKK3), a Wnt antagonist in synaptic dysfunction in Alzheimer's disease. Loss of synapses is a feature of Alzheimer's and other forms of dementia such as frontotemporal dementia and linked amyotrophic lateral sclerosis (FTD). The authors utilise a broad range of experimental approaches. They show that DKK3 levels are increased in Alzheimer's disease and that this occurs early in disease. This is an important finding since early disease changes are believed to be the most important. They also show increases in DKK3 in transgenic mouse models of Alzheimer's disease and that DKK3 knockdown restores synapse number and memory in one such model. Finally, they link these DKK3 increases to loss of excitatory synapses via the blockade of the Wnt pathway and subsequent activation of GSK3B; GSK3B is strongly linked to both Alzheimer's disease and FTD. The quality of the data is good and the conclusions well supported by these data. There are no major weaknesses. The findings support studies that target the Wnt pathway as a potential therapeutic for Alzheimer's disease.

Reviewer #1 (Public Review):

This paper describes the development and initial validation of an approach-avoidance task and its relationship to anxiety. The task is a two-armed bandit where one choice is 'safer' - has no probability of punishment, delivered as an aversive sound, but also lower probability of reward - and the other choice involves a reward-punishment conflict. The authors fit a computational model of reinforcement learning to this task and found that self-reported state anxiety during the task was related to a greater likelihood of choosing the safe stimulus when the other (conflict) stimulus had a higher likelihood of punishment. Computationally, this was represented by a smaller value for the ratio of reward to punishment sensitivity in people with higher task-induced anxiety. They replicated this finding, but not another finding that this behavior was related to a measure of psychopathology (experiential avoidance), in a second sample. They also tested test-retest reliability in a sub-sample tested twice, one week apart and found that some aspects of task behavior had acceptable levels of reliability. The introduction makes a strong appeal to back-translation and computational validity. The task design is clever and most methods are solid - it is encouraging to see attempts to validate tasks as they are developed. The lack of replicated effects with psychopathology may mean that this task is better suited to assess state anxiety, or to serve as a foundation for additional task development.

Reviewer #1 (Public Review):

This manuscript by He et al. explores the molecular basis of the different stinging behaviors of two related anemones. The freshwater Nematostella which only stings when a food stimulus is presented with mechanical stimulation and the saltwater Exaiptasia which stings in response to mechanical stimuli. The authors had previously shown that Nematostella stinging is calcium-dependent and mediated by a voltage-gated calcium channel (VGCC) with very pronounced voltage-dependent inactivation, which gets removed upon hyperpolarization produced by taste receptors.

In this manuscript, they show that Exaiptacia and Nematostella differing stinging behavior is near optimal, according to their ecological niche, and conforms to predictions from a Markov decision model.

It is also shown that Exaiptacia stinging is also calcium-dependent, but the calcium channel responsible is much less inactivated at resting potential and can readily induce nematocyte discharge only in the presence of mechanical stimulation. To this end, the authors record calcium currents from Exaipacia nematocysts and discover that the VGCCs in this anemone are not strongly inactivated and thus are easily activated by mechanical stimuli-induced depolarization accounting for the different stinging behavior between species. The authors further explore the role of the auxiliary beta subunit in the modulation of VGCC inactivation and show that different n-terminal splice variants in Exaiptacia produce strong and weak voltage-dependent inactivation.

The manuscript is clear and well-written and the conclusions are in general supported by the experiments and analysis. The findings are very relevant to increase our understanding of the molecular basis of non-neural behavior and its evolutionary basis. This manuscript should be of general interest to biologists as well as to more specialized fields such as ion channel biophysics and physiology.

Joint Public Review:

The authors have previously established that activation of dopamine inputs to prefrontal cortex during adolescence can drive increases in mPFC DA bouton number and enhanced mPFC activity in WT mice. The current study was designed to test the hypothesis that neural circuit plasticity during adolescence can be targeted to restore cortical function under conditions of developmental disruptions that are relevant to psychiatric disorders.

Specifically, the manuscript explores how transient adolescent stimulation of ventral midbrain neurons that project to the frontal cortex may help to improve performance on certain memory tasks. The authors used DREADDs to regulate the mesofrontal cortical dopamine system in two mouse models - one with a reporter replacing the Arc gene, and another with knockout of the schizophrenia-associated gene Disc1, both of which are thought to have reduced prefrontal cortical activity. The manuscript provides an interesting set of observations that DREADD-based activation over only 3 days during adolescence provides a fast-acting and long-lasting improvement in performance on Y-maze spontaneous alternation as well as aspects of neuronal function as assessed using in vivo imaging methods.

A strength of this study is that the authors performed key manipulations using age and dose/intensity as dependent variables to show that the level of neural circuit activation during adolescence follows an inverted U-shape pattern, though the precise postsynaptic mechanisms underlying the positive impact of adolescent mesofrontal dopamine neuron stimulation were not addressed.

One limitation discussed by the reviewers is that using TH-Cre mice (as compared with DAT-Cre) to drive transgene expression in VTA neurons could lead to expression outside the dopaminergic population of neurons, though in the revision the authors have provided additional lines of evidence to support their model of dopamine regulation of frontal cortex in this study.

Collectively, this is a well-design study with many strengths and novel findings that are likely to positively impact a widespread of disciplines within the biological psychiatry and neuroscience field.

Reviewer #1 (Public Review):

Summary:

The authors present a comprehensive meta-analysis of Clostridioides difficile (CD) occurrence across 42,900 metagenomes from 253 public studies, largely representing stool samples from human adults, infants, and with a smaller fraction of samples from non-gut body sites and from environmental samples (e.g., non-human animals, wastewater, soil, etc.). In particular, the authors looked at adults who were healthy, diseased (but not with C. diff), and with diagnosed C. diff infection (CDI) and found that CD occurrence was fairly low: ~30% in adult CDI samples, ~2% in adult diseased samples, and ~1% in healthy samples. CD was much more prevalent in infants (15 and 40% in healthy and diseased infants, respectively). These findings, if they hold true, would be significant because they would suggest an over-diagnosis of CDI and an under-diagnosis of other putative enteric pathogens (also enriched in CDI samples) across the population. Furthermore, these results suggest that the asymptomatic carriage of CD in adults (~1-5%, depending on demographics) may be much lower than some prior estimates (some as high as ~30-40%).

Strengths:

The authors have done an admirable job pulling down an enormous data set for this CD-focused meta-analysis, which is a valuable service to the field. The results push against some common wisdom in the field, in terms of the prevalence of CD in CDI patients, which will be impactful if they hold up to further scrutiny. Furthermore, the identification of commensal bacteria that are positively or negatively associated with CD presence in both healthy and diseased people at different periods of the lifespan (infant, child, and adult), is a valuable synthesis with potential translational value. The manuscript is clearly written and the figures are presented well. The methodology is robust, although I have a few suggestions for improvement.

Weaknesses:

My main critique relates to detection limitations, both in terms of sequencing depth and read-mapping. Given that CD detection is the root of the main conclusions reported here, this deserves some additional care. The authors have already done some work to address this by including sequencing depth in their linear mixed effects model, which is great. Furthermore, they were conservative with how they labeled CD positive/negative individuals with multiple time points (i.e., if you had CD detected at any point, this sample was selected for the cross-sectional analysis, and that individual was labeled as CD positive). I have a few additional suggestions to explore this issue, which I outline in the recommendations for authors.

Reviewer #1 (Public Review):

The manuscript by Hussein et al. uses cryoEM structure, microscale thermophoresis (MST), and molecular dynamics simulations (conventional and CpHMD) to unravel the Zn2+ and proton role in the function of the Cation Diffusion Facilitator YiiP. First, they generate mutants that abolish each of the three Zn2+ models to study the role of each of them separately, both structurally and functionally. Next, they used a Monte Carlo approach refining the CpHMD data with the MST points to establish the Zn2+ or proton binding state depending on the pH. That predicted a stoichiometry of one Zn2+ to 2 or 3 protons (1:3 under lower pH values). Finally, they proposed a mechanism that involves first the binding of Zn2+ to one low-affinity site and then, after the Zn2+ migrates to the highest affinity site in the transmembrane portion of the protein. The lack of Zn2+ in the low-affinity site might induce occlusion of the transporter.

The manuscript is well-written it is of interest to the field of Cation Facilitator Transporters. It is also an excellent example of a combination of different techniques to obtain relevant information on the mechanism of action of a transporter.

Joint Public Review:

This study provides evidence of the ability of sublethal imidacloprid doses to affect growth and development of honeybee larva. While checking the effect of doses that do not impact survival or food intake, the authors found changes in the expression of genes related to energy metabolism, antioxidant response, and metabolism of xenobiotics. The authors also identified cell death in the alimentary canal, and disturbances in levels of ROS markers, molting hormones, weight and growth ratio. The study strengths come from exploring different aspects and impacts of imidacloprid exposure on honeybee juvenile stages and for that it demonstrates potential for assessing the risks posed by pesticides. The study weaknesses come from the lack of in depth investigation and an incomplete methodological design. For instance, many of the study conclusions are based on RT-qPCR, which show only a partial snapshot of gene expression, which was performed at a single time point and using whole larvae. There is no understanding of how different organs/tissues might respond to exposure and how they change over time. That creates a problem to understand the mechanisms of damage caused by the pesticide in the situation studied here. There is no investigation of what happens after pupation. The authors show that the doses tested have no impact on survival, food consumption and time to pupation, and the growth index drops from ~0.96 to ~0.92 in exposed larvae, raising the question of its biological significance. The origin of ROS are not investigated, nor do the authors investigate if the larvae recover from the damage observed in the gut after pupation. That is important as it could affect the adult workers' health. One of the study's central claims is that the reduced growth index is due to the extra energy used to overexpress P450s and antioxidant enzymes, but that is based on RT-qPCR only. Other options are not well explored and whether the gut damage could be causing nutrient absorption problems, or the oxidative stress could be impairing mitochondrial energy production is not investigated. These alternatives may also affect the growth index. The authors also state that the honeybee larvae has 7 instars, which is an incorrect as Apis mellifera have 5 larval instars. It is not clear from methods which precise stage of larval development was used for gut preparations. That information is important because prior to pupation larvae defecate and undergo shedding of gut lining. That could profoundly affect some of the results in case gut preparations for microscopy were made close to this stage. A more in-depth investigation and more complete methodological design that investigates the mechanisms of damage and whether the exposures tested could affect adult bees may demonstrate the damage of low insecticide doses to a vital pollinator insect species.

Reviewer #1 (Public Review):

This manuscript deftly combines cryo-EM and electrophysiology to investigate the gating mechanisms of human CLC-2. Although another structure of CLC-2 was recently reported, this is the first structure to report density for the absolutely critical gating glutamate, and - an even more exciting result - the first structure to identify the N-terminal gating peptide that is the heart of this manuscript. There has been previous controversy over such a gating peptide in CLC-2, but the combined structural/functional approach appears to establish a role for this peptide in gating and sets up exciting future experiments to understand why its effects might change under different physiological scenarios. The experiments reported here are thoughtful and well-controlled and the data presentation is excellent. For the electrophysiology experiments, the use of inhibitor AK-42 (developed by the current senior author's lab) to establish a zero current level is a welcome advance and should become standard for electrophysiological studies of CLC-2.

Joint Public Review:

The manuscript by Aguirre et al. describes an elegant approach for developing selective inhibitors of inositol hexakisphosphate kinases (IP6Ks). There are 3 IP6K isozymes (IP6K1-3) in humans, which catalyze the synthesis of inositol pyrophosphates. The lack of isozyme-selective inhibitors has hampered efforts to understand their individual physiological roles. While several inhibitors of IP6Ks have been described, they either lack isozyme selectivity or inhibit other kinases. To address this gap, Aguirre et al. used an analog-sensitive approach, which involves the identification of a mutant that, in an ideal world, doesn't impact the activity of the enzyme but renders it sensitive to an inhibitor that is absolutely selective for the engineered (analog-sensitive) enzyme. Initially, they generated the canonical gatekeeper (Leu210 in IP6K1) mutations (glycine and alanine); unfortunately, these mutations had a deleterious effect on the enzymatic activity of IP6K1. Interestingly, mutation of Leu210 to a valine, a subtly smaller amino acid, didn't affect enzymatic activity. The authors then designed a clever high-throughput assay to identify compounds that show selectivity for L210V IP6K1 versus WT IP6K1. The assay monitors the reverse reaction catalyzed by IP6Ks, monitoring the formation of ATP using a luminescence-based readout. After validating the screen, the authors screened 54,912 compounds. After culling the list of compounds using several criteria, the authors focused on one particular compound, referred to as FMP-201300. FMP-201300 was ~10-fold more potent against L210V IP6K1 compared to WT IP6K1. This selectivity was maintained for IP6K2. Mechanistic studies showed that FMP-201300 is an allosteric inhibitor of IP6K1. The authors also did a small SAR campaign to identify key functional groups required for inhibition.

Overall, this manuscript describes a unique and useful strategy for developing isozyme-selective inhibitors of IP6Ks. The serendipitous finding that subtle changes to the gatekeeper position can sensitize the IP6K1 mutant to allosteric inhibitors will undoubtedly inspire other analog-sensitive inhibitor studies. The manuscript is well-written and the experiments are generally well-controlled.

Reviewer #1 (Public Review):

In the "Drivers of species knowledge across the Tree of Life", Mammola and collaborators explore the determinants of scientific and societal interest across very wide taxonomic and spatial scales. Their work highlights our uneven knowledge of biodiversity and its potential causes.

Joint Public Review:

When the left-right asymmetry of an animal body is established, a barrier that prevents the mixing of signals or cells across the midline is essential. Such a midline barrier preventing the spreading of asymmetric Nodal signaling during early left-right patterning has been identified. However, midline barriers during later asymmetric organogenesis have remained largely unknown, except in the brain. In this study, the authors discovered an unexpected structure in the midline of the developing midgut in the chick. Using immunofluorescence, they convincingly show the chemical composition of this midline structure as a double basement membrane and its transient existence during the left-right patterning of the dorsal mesentery, which authors showed previously to be essential for forming the gut loop and guiding local vasculogenesis. Labelling experiments suggest a physical barrier function, to cell mixing and signal diffusion in the dorsal mesentery. Cell labelling and graft experiments rule out a cellular composition of the midline from dorsal mesenchyme or endoderm origin and rule out an inducing role by the notochord. Based on laminin expression pattern and Ntn4 resistance, the authors propose a model, whereby the midline basement membrane is progressively deposited by the descending endoderm.

Laterality defects encompass severe malformations of visceral organs, with a heterogenous spectrum that remains poorly understood, by a lack of knowledge of the different players of left-right asymmetry. This fundamental work significantly advances our understanding of left-right asymmetric organogenesis, by identifying an organ-specific and stage-specific midline barrier. The complexities of basement membrane assembly, maintenance, and function are of importance in several other contexts, as for example in the kidney and brain. Thus, this original work is of broad interest.

Overall, reviewers refer to a strong and elegant paper discovering a novel midline structure, combining classic but challenging techniques, to show the dynamics, chemical, and physical properties of the midline. However, reviewers also indicate that further work will be necessary to conclude on the origin and impact of the midline for asymmetric organogenesis. Three issues have been raised to strengthen the claims:

1) The function of the midline as a physical barrier requires clarification. Dextran injection here seems to label cells and not the extracellular space. By counting the proportion of dextran-labeled cells rather than dextran intensity itself, the authors do not measure diffusion per se, but rather cell mixing.

2) The descending endoderm zippering model for the formation of the midline lacks direct evidence. The claim of an endoderm origin is based on laminin expression, but the laminin observed in the midline with an antibody may not necessarily correspond to the same subtype assessed by in situ hybridization. The midline may be Ntn4 resistant until it is injected in the relevant source cells. Alternative origins could be considered, from the bilateral dorsal aortae or the paraxial mesoderm, which would explain the double layer as a meeting point of two lateral tissues.

3) The title implies a role of the midline in left-right asymmetric gut development. However, the importance of the midline is currently inferred from previously published data and stage correlations and will require more direct evidence.

Reviewer #1 (Public Review):

This work is hugely significant in the context of the debates surrounding ancient Egyptian activity on the Red Sea and voyages to the Egyptian land of Punt. Using genetic studies to provenance baboon mummified baboons in Egypt with contemporary baboon populations in the Red Sea region, the study argues persuasively that Egyptians obtained Baboons from coastal Eritrea, and thus that Egyptian baboon trade involved this region. This of course brings up the larger issue of Egyptian trade with Punt and the southern Red Sea, a place known to have furnished Egyptians with baboons. The authors argue logically for the region of the ancient port-city of Adulis as being particularly important in this baboon trade, as the region around the harbour was said to have been a baboon habitat in the Graeco-Roman period.

Along with other previous geoprovenancing scientific studies relating to baboon isotopes and obsidian trace elements, this study provides a solid foundation for considering coastal Sudan and especially Eritrea as part of the land of Punt.

Reviewer #1 (Public Review):

This manuscript describes conditions under which "Self-inactivating Rabies" (SiR) can be grown to limit mutations that would allow the virus to replicate in the absence of TEV protease. It is also shown that neurons directly infected with a non-mutated virus remain healthy and that the virus does not mutate in the brain in vivo. Remarkably there is nothing in the manuscript to address the obvious question that is raised by the observation that such mutations were occurring around the time of the initial description of circuit tracing with this virus. Can the transsynaptic tracing experiments in the absence of TEV expression (as described in their original Neuron paper) be replicated with SiR that is not mutated? This obvious omission suggests that the authors might have conducted such experiments and were unable to replicate their published results. It is imperative that the authors be forthcoming about whether they have conducted such experiments and what were the results. If they have not conducted such experiments, they should do them and include the results here. If they cannot replicate their results, then the reliability of the Neuron paper is in doubt.

How do the results presented here relate to the results published in the Neuron paper and why are they not definitive with respect to the utility of SiR? The original publication in Neuron presents results that do not appear to be plausible and are best explained by the possibility that some experiments described in that manuscript were conducted using mutated SiR. This became most apparent when shortly after the Neuron publication, the Tripodi lab shared SiR as well as TEV expressing cell lines for propagation with other labs. Several of those groups observed that when they progagated the SiR received from the Tripodi lab, there was a mutation that removed the linkage of the PEST targeting sequence to N. This would be expected to allow the virus to replicate and spread without the need for TEV protease to remove the PEST sequence - precisely the phenotype observed in the trans-synaptic tracing experiments described in the Neuron paper. In the Neuron paper, culture experiments showed that the N-PEST (SiR) rabies could not replicate in the absence of TEV. And additional experiments showed that the virus is not toxic to neurons directly infected. These are the same experiments that are replicated in this submission. But then (in the Neuron paper) comes the unlikely report that this virus can spread trans-synaptically in vivo, in the absence of TEV expression. An alternative explanation would be that the virus used for those experiments was mutated and that is why TEV expression was not needed. There are no experiments in the original Neuron paper that address this possibility. Specifically, the experiments in Neuron describing cell survival during trans-synaptic tracing are not adequate to rule this out. This is because the two timepoints during which neurons were counted correspond to an early time when labeled neurons would be expected to still be accumulating and a later time that might be past the peak and represent a time when many neurons have died. To quantify proportions of neurons that survive, it is necessary to follow the same neurons over time, as has been done to demonstrate that only about half of neurons infected with G-deleted rabies die (half survive). Until tests are conducted testing whether TEV expression is required to obtain trans-synaptic labeling with an SiR that is known to not be mutated, it is irrelevant whether mutations can be prevented under particular culture conditions. The utility of this virus depends on whether it can be used for trans-synaptic tracing without toxicity and this manuscript presents no experiments to address that. Further, the omission of such experiments is glaring, as it is difficult to imagine that they have not been attempted.

Other comments:

"A recently developed engineered version of the ΔG-Rabies, the non-toxic self-inactivating (SiR) virus, represents the first tool for open-ended genetic manipulation of neural circuits."<br /> It is not clear what the authors intend to be claiming with respect to "open-ended genetic manipulation of neural circuits" but it is clear that this assertion is overblown. There are numerous tools that are available for genetic manipulation of neural circuits. This is not the first, won't be the last, and it is arguably not the best.

"Interestingly, a fraction of tdTomato+ neurons survived in ΔG- Rab-CRE-injected brains, differing from what we observed when injecting ΔGRab-GFP, where no cells were detected at 3 weeks p.i. (Fig 3CD) (Ciabatti et al., 2017). " This is a known result (same as Chatterjee et al., 2018) with a known mechanism. GFP expression is not observed because the rabies virus transitions from transcription to replication resulting in the termination of GFP expression. But Cre-recombination of the genome permanently labels cells with TdTomato. This is how Chatterjee et al. demonstrated that half of the neurons infected with G-deleted rabies survive. They imaged cells and saw that the GFP disappeared but the cells marked by Cre-recombination and RFP expression remained healthy indefinitely. The consideration of this in the Introduction is strange. There is no reason to suppose that Cre expression would somehow protect cells from rabies infection and there is no need to propose any such mechanism to explain the observed results.

"Here we show that revertant-free SiR-CRE efficiently traces neurons in vivo without toxicity in cortical and subcortical regions for several months p.i.."<br /> This wording is disingenuous and appears to be intentionally misleading. "Trace" implies that circuits were traced by transynaptic labeling, which they were not.

Reviewer #1 (Public Review):

Wang and colleagues show that tree shrews can detect optogenetic stimulation of the lateral geniculate nucleus (LGN) using an AAV2-CamKIIα-ChR2 construct after training detection of visual stimuli. Solid evidence links optogenetic stimulation to behavioural detection and neurophysiological responses in LGN and local field potentials in V1.

The major strength is the carefully conducted optogenetic detection experiments showing that training of a visual detection task can be transferred to the the detection of focal optogenetic stimulation in the LGN. The optogenetic stimulation can evoke responses in LGN that can be transmitted to V1.

However, the behavioural results are highly variable between individual animals and different optogenetic stimulation frequencies. The nature of this variability remains unclear. A weakness of this complex in vivo study lies in the underspecified description of some of the details and the links between the histology, the neurophysiology and optogenetic results, in order to understand this variability better. The neurophysiological results are clear and important, but the distribution of significant results across the different animals studied is missing. The expression patterns across layers of the optogenetic viruses appear to differ in the histology of three different animals shown, but it is unclear except for one animal from which experimental individuals these results stem. While the methods of the behavioural and neurophysiological results are well described, the methods section is incomplete with regards to the very nice histology presented (perfusion, sectioning, staining).

The detection of optogenetic activation of LGN in this visual animal model suggests that LGN is a potential target for a neuroprosthetic device. This paper is potentially of interest to neuroscientists and clinicians working on the visual system and visual prostheses.

Reviewer #1 (Public Review):

Dolgova et al present a well-written manuscript focused on the mechanism of MEMO1 function in tumor cells. They use genome-wide analyses to predict function based on MEMO1 structure in yeast, identify MEMO1 expression in a screen of cancer cell lines, and demonstrate a correlation between MEMO1 expression and severity of disease in primary breast cancer cells. The authors focus on a breast cancer model as it overexpresses MEMO1 and melanoma as a control and uses CRISPR-Cas9 knockdown of MEMO1 in breast and melanoma cell lines and concurrently knockdown selected genes in the iron homeostasis pathway. In this data, MEMO1 appears to interact with elements involved in iron trafficking and sensing and its overexpression leads to possible hypersensitivity while knockout/knockdown leads to resistance to lipid oxidation. They also interrogate the effect of iron chelation on mitochondrial morphology and ferroptosis. In addition, they evaluate iron and copper binding loci and resolve MEMO1 structure. The work is of high quality. However, there are some inaccuracies regarding the known function of some iron-related elements. Furthermore, it is unresolved whether controlling iron per se (by modulating other importers and transporters or limiting iron availability in culture) recapitulates or ameliorates their findings, currently attributed specifically to the mechanism of action of MEMO1. In addition, the authors make claims that they have not substantiated about overexpression of MEMO1 by extrapolating from data about MEMO1 knockdown or knockout. Finally, the results show only indirect evidence for a central role for MEMO1 via regulation of iron trafficking and more targeted approaches are necessary to increase confidence in the claims.

Joint Public Review:

In this study, the authors investigate the biological function of the FK506-binding protein FKBP35 in the malaria-causing parasite Plasmodium falciparum. Like its homologs in other organisms, PfFKBP35 harbors peptidyl-prolyl isomerase and chaperoning activities, and has been considered a promising drug target due to its high affinity to the macrolide compound FK506. However, PfFKBP35 has not been validated as a drug target using reverse genetics, and the link between PfFKBP35-interacting drugs and their antimalarial activity remains elusive. The manuscript addresses the biological function of PfFKBP35 and the antimalarial activity of FK506.

The authors combine conditional genome editing, proteomics and transcriptomics analysis to investigate the effects of FKBP35 depletion in P. falciparum. The work is very well performed and clearly described. The data provide conclusive evidence that FKBP35 is essential for P. falciparum blood stage growth. Conditional knockout of PfFKBP35 leads to a delayed death-like phenotype, associated with defects in ribosome maturation as detected by quantitative proteomics and stalling of protein synthesis in the parasite. The authors clearly demonstrate that FKBP35 is essential for parasite growth and that ribosome biogenesis is disrupted, but further insights into the pathway itself would be more convincing that this is a direct consequence rather than a secondary feature of parasite death.

The knockdown of PfFKBP35 has no phenotypic consequence, showing that very low amounts of FKBP35 are sufficient for parasite survival and growth. In the absence of quantification of the protein during the course of the experiments, it remains unclear whether the delayed death-like phenotype in the knockout is due to the delayed depletion of the protein or to a delayed consequence of early protein depletion. This limitation also impacts the interpretation of the drug assays.

The authors investigate the activity of FK506 on P. falciparum, and conclude that FK506 exerts its antimalarial effects independently of FKBP35, based on the observation that FK506 has the same activity on FKBP35 wild type and knock-out parasites, indicating that FK506 activity is independent of FKBP35 levels. Using cellular thermal shift assays, the authors confirm the interaction between FK506 and FKBP35, and further identify candidate proteins bound by the compound, albeit at lower affinity. Further work is needed to validate whether these putative targets contribute to the FKBP35-independent antimalarial activity of FK506.

Reviewer #1 (Public Review):

In this study, Jiamin Lin et al. investigated the potential positive feedback loop between ZEB2 and ACSL4, which regulates lipid metabolism and breast cancer metastasis. They reported a correlation between high expression of ZEB2 and ACSL4 and poor survival of breast cancer patients, and showed that depletion of ZEB2 or ACSL4 significantly reduced lipid droplets abundance and cell migration in vitro. The authors also claimed that ZEB2 activated ACSL4 expression by directly binding to its promoter, while ACSL4 in turn stabilized ZEB2 by blocking its ubiquitination. While the topic is interesting, there are several concerns with the study:

1. My concern regarding the absence of appropriate thresholds or False Discovery Rate (FDR) adjustments for the RNA-seq analysis has not been addressed, leading to incorrect thresholds and erroneous identification of significant signals.

2. In Figure 3B and C, it appears that the knockdown efficiency of ACSL4 is inadequate in these cells, which contradicts the Western blot results presented in Figure 2F.

3. Regarding Figure 6, the discovery of consensus binding sequences (CACCT) for ZEB2 alone is insufficient evidence to support the direct binding of ZEB2 to the ACSL4 promoter.

4. For Figure 7E, there are multiple bands present, and it appears that ZEB2-HA has been cropped, which should ideally be presented with unaltered raw data. Please provide the uncropped raw data.

5. In Figure 7C, the author claimed to have used 293T cells for the ubiquitin assay, which are not breast cancer cells. Moreover, the efficiency of over-expression differs between ZEB2 and ACSL4 in 293T cell lines. Performing the experiment in an unrelated cell line to justify an important interaction is not acceptable.

Reviewer #1 (Public Review):

Summary:

Tiemann et al. have undertaken an original study on the availability of molecular dynamics (MD) simulation datasets across the Internet. There is a widespread belief that extensive, well-curated MD datasets would enable the development of novel classes of AI models for structural biology. However, currently, there is no standard for sharing MD datasets. As generating MD datasets is energy-intensive, it is also important to facilitate the reuse of MD datasets to minimize energy consumption. Developing a universally accepted standard for depositing and curating MD datasets is a huge undertaking. The study by Tiemann et al. will be very valuable in informing policy developments toward this goal.

Strengths:

The study presents an original approach to addressing a growing concern in the field. It is clear that adopting a more collaborative approach could significantly enhance the impact of MD simulations in modern molecular sciences.

The timing of the work is appropriate, given the current interest in developing AI models for describing biomolecular dynamics.

Weaknesses:

The study primarily focuses on one major MD engine (GROMACS), although this limitation is not significant considering the proof-of-concept nature of the study.

Reviewer #1 (Public Review):

Summary:<br /> Khaitova and co-workers present here an analysis of centromere composition and function during elevated temperatures in the plant Arabidopsis. The work relates to the ongoing climate change during which spikes in high temperatures will be found. Hence, the paper addresses a timely subject.

The authors start by confirming earlier studies that high temperatures reduce the fertility of Arabidopsis plants. Interestingly, a hypomorphic mutant of the centromeric histone variant CENH3 (CENP-A), which was previously described by the authors, sensitizes plants to heat and results in a drop in viable pollen and silique length. The drop in fertility coincides with the formation of micronuclei in meiosis and an extension of meiotic progression as revealed by live cell imaging. Based on this finding, the authors then show that at high temperatures, the fluorescence intensity of a YFP:CENH3 declines in meiosis but remarkably not in the surrounding cells (tapetum cells). In addition, the amount of BMF1 (a Bub1 homolog and part of the spindle assembly checkpoint) also appears to decline on the kinetochores of meiocytes as judged by BMF1 reporter line. However, whether this is dependent on a decline of CENH3 or represents a separate pathway is not clear. Finally, the authors measure the duration of the spindle checkpoint and find that it is extended under high temperatures from which they conclude that the attachment of spindle fibers to kinetochores is compromised under heat.

Strengths:<br /> This is an interesting and important paper as it links centromere organization/function to heat stress in plants. A major conclusion of the authors is that weakened centromeres, presumably by heat, may be less effective in establishing productive interactions with spindle microtubules.

Weaknesses:<br /> The paper does not explain the molecular reason why CENH3 levels in meiocyctes are reduced or why the attachment of spindle fibers to kinetochore is less efficient at high versus low temperatures.

Reviewer #1 (Public Review):

Su et al propose the existence of two mechanisms repressing SBF activity during entry into meiosis in budding yeast. First, a decrease in Swi4 protein levels by a LUTI-dependent mechanism where Ime1 would act closing a negative feedback loop. Second, the sustained presence of Whi5 would contribute to maintaining SBF inhibited under sporulation conditions. The article is clearly written and the experimental approaches used are adequate to the aims of this work. The results obtained are in line with the conclusions reached by the authors but, in my view, they could also be explained by the existing literature and, hence, would not represent a major advance in the field of meiosis regulation.

Regarding the first mechanism, Fig 1 shows that Swi4 decreases very little after 1-2h in sporulation medium, whereas G1-cyclin expression is strongly repressed very rapidly under these conditions (panel D and work by others). This fact dampens the functional relevance of Swi4 downregulation as a causal agent of G1 cyclin repression. The authors use overexpression of Swi4 in Figs 2 and 3 to test the relevance of Swi4 downregulation but the pATG8-SWI4 construct produces levels much higher (4-5 fold) than the wild-type gene at time 0, which may likely introduce artifactual effects in the resulting observations. In addition, the LUTI-deficient SWI4 mutant does not cause any noticeable relief in CLN2 repression, arguing against the relevance of this mechanism in the repression of G1-cyclin transcription during entry into meiosis.

The authors propose a second mechanism where Whi5 would maintain SBF inactive under sporulation conditions. The role of Whi5 as a negative regulator of the SBF regulon is well known. On the other hand, the double WHI5-AA SWI4-dLUTI mutant does not upregulate CLN2, the G1 cyclin with the strongest negative effect on sporulation, raising serious doubts on the functional relevance of this backup mechanism during entry into meiosis.

Reviewer #1 (Public Review):

Summary: The authors use the innovative CRISPRi method to uncover regulators of cell density and volume in neutrophils. The results show that cells require NHE activity during chemoattractant-driven cell migration. Before migration occurs, cells also undergo a rapid cell volume increase. These results indicate that water flux, driven by ion channels, appears to play a central role in neutrophil migration. The paper is very well written and clear. I suggest adding some discussion about the role of actin in the process, but this is not essential.

Strengths: The novel use of CRIPSPi to uncover cell density regulators is very novel. Some of the uncovered molecules were known before, e.g. discussed in Li & Sun, Frontiers in Cell and Developmental Biology, 2021. Others are more interesting, for example PI3K-gamma. The use of caged fMLP is also nice.

Weaknesses: One area of investigation that seems to be absent is mentioned in the introduction. I.e., actin is expected to play a role in regulating cell volume increase. Did the authors perform any experiments with LatA? What was seen there? Do cells still migrate with LatA, or is a different interplay seen? The role of PI3K is interesting, and maybe somewhat related to actin. But this may be a different line of inquiry for the future.

Reviewer #1 (Public Review):

In this work, Vezina et al. present Bactabolize, a rapid reconstruction tool for the generation of strain-specific metabolic models. Similar to other reconstruction pipelines such as CarveMe, Bactabolize builds a strain-specific draft reconstruction and subsequently gap-fills it. The model can afterwards be used to predict growth on carbon sources. The authors constructed a pan-model of the Klebsiella pneumoniae species complex (KpSC) and used it as input for Bactabolize to construct a genome-sale reconstruction of K. pneumoniae KPPR1. They compared the generated reconstruction with a reconstruction built through CarveMe as well as a manually curated reconstruction for the same strain. They then compared predictions of carbon, nitrogen, phosphor, and sulfur sources and found that the Bactabolize reconstruction had the overall highest accuracy. Finally, they built draft reconstructions for 10 clinical isolates of K. pneumoniae and evaluated their predictive performance. Overall, this is a useful tool, the data is well-presented, and the paper is well-written.

Reviewer #1 (Public Review):

Summary:

Chartampila et al. describe the effect of early-life choline supplementation on cognitive functions and epileptic activity in a mouse model of Alzheimer's disease. The cognitive abilities are assessed by the novel object recognition test and the novel object location test, performed in the same cohort of mice at 3 months and 6 months of age. Neuronal loss was tested using NeuN immunoreactivity, and neuronal hyperexcitability was examined using FosB and video-EEG recordings.

Strengths:

The study was designed as a 6-month follow-up, with repeated behavioral and EEG measurements through disease development, providing valuable and interesting findings on AD progression and the effect of early-life choline supplantation. Moreover, the behavioral data that suggest an adverse effect of low choline in WT mice are interesting and important beyond the context of AD.

Weaknesses:

1. The multiple headings and subheadings, focusing on the experimental method rather than the narrative, reduce the readability.<br /> 2. Quantification of NeuN and FosB in WT littermates is needed to demonstrate rescue of neuronal death and hyperexcitability by high choline supplementation and also to gain further insights into the adverse effect of low choline on the performance of WT mice in the behavioral test.<br /> 3. Quantification of the discrimination ratio of the novel object and novel location tests can facilitate the comparison between the different genotypes and diets.<br /> 4. The longitudinal analyses enable the performance of multi-level correlations between the discrimination ratio in NOR and NOL, NeuN and Fos levels, multiple EEG parameters, and premature death. Such analysis can potentially identify biomarkers associated with AD progression. These can be interesting in different choline supplementation, but also in the standard choline diet.

Reviewer #1 (Public Review):

In this study, authors have investigated the effects of TMEM127 depletion on RET regulation and function that could potentially contribute to PCC pathogenesis. They have demonstrated that the loss of TMEM127 leads to cell surface accumulation and constitutive activation of RET due to membrane organization, leading to reduced efficiency of endocytosis, decreased internalization of RET, and a global impairment of membrane trafficking. TMEM127 depletion has contributed to increased RET half-life, constitutive RET-mediated signaling, increased membrane protein diffusibility, impaired normal membrane transitions, and inappropriate accumulation of actively signaling RET molecules at the cell membrane. Collectively, these findings have shown that the mis-localized RET is the pathogenic mechanism in TMEM127-mutant pheochromocytoma.

Experimental design and mechanistic studies are thorough and sound. The methodological weakness lies in the lack of pheochromocytoma cell line utility to reproduce novel findings observed in generated cell lines. This may represent a significant challenge that could undermine the inferred value of these potentially paradigm-changing findings. 3-dimensional patient-derived pheochromocytoma organoid in vitro model and/or patient-derived organoid xenograft in vivo model may aid in reconciling these exciting new findings and factoring in that the pheochromocytoma is a hormonally active tumor.

Fundamentally, the authors have successfully achieved all proposed aims supported by their conclusions.

These findings carry potentially significant clinical impact and may offer new therapeutic venues in patients with pheochromocytoma.

Reviewer #1 (Public Review):

In this study, the authors aim to understand why decision formation during behavioural tasks is distributed across multiple brain areas. They hypothesize that multiple areas are used in order to implement an information bottleneck (IB). Using neural activity recorded from monkey DLPFC and PMd performing a 2-AFC task, they show that DLPFC represents various task variables (decision, color, target configuration), while downstream PMd primarily represents decision information. Since decision information is the only information needed to make a decision, the authors point out that PMd has a minimal sufficient representation (as expected from an IB). They then train 3-area RNNs on the same task and show that activity in the first and third areas resemble the neural representations of DLPFC and PMd, respectively. In order to propose a mechanism, they analyse the RNN and find that area 3 ends up with primarily decision information because feedforward connections between areas primarily propagate decision information.

The paper addresses a deep, normative question, namely why task information is distributed across several areas.

Overall, it reads well and the analysis is well done and mostly correct (see below for some comments). My major problem with the paper is that I do not see that it actually provides an answer to the question posed (why is information distributed across areas?). I find that the core problem is that the information bottleneck method, which is evoked throughout the paper, is simply a generic compression method. Being a generic compressor, the IB does not make any statements about how a particular compression should be distributed across brain areas - see major points (1) and (2).

If I ignore the reference to the information bottleneck and the question of why pieces of information are distributed, I still see a more mechanistic study that proposes a neural mechanism of how decisions are formed, in the tradition of RNN-modelling of neural activity as in Mante et al 2013. Seen through this more limited sense, the present study succeeds at pointing out a good model-data match. I point out some suggestions for improvement below.

Major points<br /> (1) It seems to me that the author's use of the IB is based on the reasoning that deep neural networks form decisions by passing task information through a series of transformations/layers/areas and that these deep nets have been shown to implement an IB. Furthermore, these transformations are also loosely motivated by the data processing inequality.

However, assuming as a given that deep neural networks implement an IB does not mean that an IB can only be implemented through a deep neural network. In fact, IBs could be performed with a single transformation just as well. More formally, a task associates stimuli (X) with required responses (Y), and the IB principle states that X should be mapped to a representation Z, such that I(X;Z) is minimal and I(Y,Z) is maximal. Importantly, the form of the map Z=f(X) is not constrained by the IB. In other words, the IB does not impose that there needs to be a series of transformations. I therefore do not see how the IB by itself makes any statement about the distribution of information across various brain areas.

A related problem is that the authors really only evoke the IB to explain the representation in PMd: Fig 2 shows that PMd is almost only showing decision information, and thus one can call this a minimal sufficient representation of the decision (although ignoring substantial condition independent activity). However, there is no IB prediction about what the representation of DLPFC should look like. Consequently, there is no IB prediction about how information should be distributed across DLPFC and PMd.

(2) Now the authors could change their argument and state that what is really needed is an IB with the additional assumption that transformations go through a feedforward network. However, even in this case, I am not sure I understand the need for distributing information in this task. In fact, in both the data and the network model, there is a nice linear readout of the decision information in dPFC (data) or area 1 (network model). Accordingly, the decision readout could occur at this stage already, and there is absolutely no need to tag on another area (PMd, area 2+3).

Similarly, I noticed that the authors consider 2,3, and 4-area models, but they do not consider a 1-area model. It is not clear why the 1-area model is not considered. Given that e.g. Mante et al, 2013, manage to fit a 1-area model to a task of similar complexity, I would a priori assume that a 1-area RNN would do just as well in solving this task.

I think there are two more general problems with the author's approach. First, transformations or hierarchical representations are usually evoked to get information into the right format in a pure feedforward network. An RNN can be seen as an infinitely deep feedforward network, so even a single RNN has, at least in theory, and in contrast to feedforward layers, the power to do arbitrarily complex transformations. Second, the information coming into the network here (color + target) is a classical xor-task. While this task cannot be solved by a perceptron (=single neuron), it also is not that complex either, at least compared to, e.g., the task of distinguishing cats from dogs based on an incoming image in pixel format.

(3) I am convinced of the author's argument that the RNN reproduces key features of the neural data. However, there are some points where the analysis should be improved.

(a) It seems that dPCA was applied without regularization. Since dPCA can overfit the data, proper regularization is important, so that one can judge, e.g., whether the components of Fig.2g,h are significant, or whether the differences between DLPFC and PMd are significant.

(b) I would have assumed that the analyses performed on the neural data were identical to the ones performed on the RNN data. However, it looked to me like that was not the case. For instance, dPCA of the neural data is done by restretching randomly timed trials to a median trial. It seemed that this restretching was not performed on the RNN. Maybe that is just an oversight, but it should be clarified. Moreover, the decoding analyses used SVC for the neural data, but a neural-net-based approach for the RNN data. Why the differences?

(4) The RNN seems to fit the data quite nicely, so that is interesting. At the same time, the fit seems somewhat serendipitous, or at least, I did not get a good sense of what was needed to make the RNN fit the data. The authors did go to great lengths to fit various network models and turn several knobs on the fit. However, at least to me, there are a few (obvious) knobs that were not tested.

First, as already mentioned above, why not try to fit a single-area model? I would expect that a single area model could also learn the task - after all, that is what Mante et al did in their 2013 paper and the author's task does not seem any more complex than the task by Mante and colleagues.

Second, I noticed that the networks fitted are always feedforward-dominated. What happens when feedforward and feedback connections are on an equal footing? Do we still find that only the decision information propagates to the next area? Quite generally, when it comes to attenuating information that is fed into the network (e.g. color), then that is much easier done through feedforward connections (where it can be done in a single pass, through proper alignment or misalignment of the feedforward synapses) than through recurrent connections (where you need to actively cancel the incoming information). So it seems to me that the reason the attenuation occurs in the inter-area connections could simply be because the odds are a priori stacked against recurrent connections. In the real brain, of course, there is no clear evidence that feedforward connections dominate over feedback connections anatomically.

More generally, it would be useful to clarify what exactly is sufficient:

(a) the information distribution occurs in any RNN, i.e., also in one-area RNNs<br /> (b) the information distribution occurs when there are several, sparsely connected areas<br /> (c) the information distribution occurs when there are feedforward-dominated connections between areas

Reviewer #1 (Public Review):

Funabiki et al, performed a co-evolutionary analysis of Lsh/HELLS and CDCA7, two factors with links to DNA methylation pathways in mammals, amphibia and fish. The authors suggest that conserved roles for the two factors in DNA methylation maintenance pathways can be traced back to the last eukaryotic common ancestor. Overall, the findings are important and the results could be useful for researchers studying DNA methylation pathways in many different organisms.

Reviewer #1 (Public Review):

Funabiki et al, performed a co-evolutionary analysis of Lsh/HELLS and CDCA7, two factors with links to DNA methylation pathways in mammals, amphibia and fish. The authors suggest that conserved roles for the two factors in DNA methylation maintenance pathways can be traced back to the last eukaryotic common ancestor. Overall, the findings are important and the results could be useful for researchers studying DNA methylation pathways in many different organisms.

Comments on current version:

In the revised version of this manuscript the authors addressed all previously raised issues. I would like to thank them for that. The data is now clearly presented and interpreted and more experimental detail has been added. Thus, the manuscript is much improved and provides an interesting basis for experimental follow-up and further functional investigations.

Reviewer #1 (Public Review):

This paper focuses on the effects of a L114P mutation in the TALK-1 channel on islet function and diabetes. This mutation is clinically relevant and a cause of MODY diabetes. This work employs a mouse model with heterozygous and homozygous mutants. The homozygous mice are homozygous lethal from severe hyperglycemia. The work shows that the mutation increases K+ currents and inhibits insulin secretion. This is a very nice paper with mechanistic insight and clear clinical importance. It is generally well-written and the data is well-presented.

Reviewer #1 (Public Review):

In this manuscript, the authors are developing a new protocol that aims at expanding pancreatic progenitors derived from human pluripotent stem cells under GMP-compliant conditions. The strategy is based on hypothesis-driven experiments that come from knowledge derived from pancreatic developmental biology.

The topic is of major interest in the view of the importance of amplifying human pancreatic progenitors (both for fundamental purposes and for future clinical applications). There is indeed currently a major lack of information on efficient conditions to reach this objective, despite major recurrent efforts by the scientific community.

Using their approach that combines stimulation of specific mitogenic pathways and inhibition of retinoic acid and specific branches of the TGF-beta and Wnt pathways, the authors claim to be able, in a highly robust and reproducible manner) to amplify in 10 passages the number of pancreatic progenitors (PP) by 2,000 folds, which is really an impressive breakthrough.

The work is globally well-performed and quite convincing. I have however some technical comments mainly related to the quantification of pancreatic progenitor amplification and to their differentiation into beta-like cells following amplification.

Reviewer #1 (Public Review):

This study provides insights into the early detection of malignancies with noninvasive methods. The study contained a large sample size with an external validation cohort, which raises the credibility and universality of this model. The new model achieved high levels of AUC in discriminating malignancies from healthy controls, as well as the ability to distinguish tumor of origin. Based on these findings, prospective studies are needed to further confirm its predictive capacity.

Reviewer #1 (Public Review):

Summary: The ciliary photoreceptor cells and its downstream neurons of larval annelid must be orchestrated in a specific pattern to promote downward swimming in response to long duration of UV exposure. The authors first conducted neuroanatomical examination of the circuit to identify NOS-expression neurons (INNOS) that are immediately downstream to the ciliary photoreceptor cells. The INNOS is activated by UV and produces NO. The NOS is required for UV avoidance by Platynereis larvae and neural dynamics of the photoreceptor cells and their downstream circuit. Following up the RNA-seq data with in situ hybridization experiments, the authors found that two unconventional guanylate cyclases, NIT-GC1 and NIT-GC2, are expressed and localized in different subcellular domain of the photoreceptor cells. Experiments using the culture cells and genetically encoded sensors demonstrated that NIT-GC1 can generate cGMP in response to nitric oxide. Finally, authors build a mathematical model that fit the live imaging data and used it to predict how the magnitude of the photoreceptor activation varied by intensity and duration of UV light.

Strengths: The authors conducted comprehensive interrogations of the UV avoidance pathway at the molecular and circuit levels, and constructed a mathematical model. The main conclusions are supported by layers of evidence from different assays.

Weaknesses: Statistics are missing in both figure legends and methods. The perturbations of genes and molecules were not cell-type-specific and therefore the observed behavioral defect could be attributed to the malfunction of the circuit elsewhere not examined in this study. I suggest adding more explanation about the functions of other NOS-expressing cells and conducting a control experiment to test behavioral response to a non-visual stimulus.

Reviewer #1 (Public Review):

Summary<br /> In this manuscript, the authors generate an AAV-deliverable tool that generates action potentials in response to red light, but not blue light, when expressed in neurons. To do this, they screen some red light-excitatory/blue light-inhibitory opsin pairs to find ones that are spectrally and temporally matched. They first show that this works with Chrimson and GtACR2, however, they expand their search after finding that the tau-off (inactivation after light cessation) kinetics of these two opsins are not well-matched. They directly examine a small set of options based on a literature search and settle on a variant of red light-excitatory Chrimson and blue light-inhibitory ZipACR. To more closely match the kinetics of this pair, the authors create a structure homology model of the ZipACR retinal binding pocket and use this to guide the generation of a small mutagenesis panel, leading to a more optimized ZipACR mutant. They then show that a bicistronically expressed fusion arrangement of these opsins, plus some functional peptides, can drive action potentials up to 20hz with red light and does not do so with blue light, in hippocampal cells transduced by AAV. They also show function in vivo, in a mouse, using a physiological readout. They conclude that their new tool may be useful for complex experimental designs requiring multiple optical channels for write-in/read-out.

The major advantage claimed by the authors over existing tools is the temporal time-locking of their inhibitory opsin - this is driven by the contrast between the tau-off kinetics of their ZipACR variant compared to gtACR2, which is used by the leading competitor tool (BiPOLES).

Big thoughts<br /> While the authors were carefully thoughtful about the potential influence of temporal kinetics on the efficiency of a tool such as this one, there were no experiments conducted that made use of the unique properties of this molecular strategy. To understand why they embarked on this engineering program, I was required to put on my neuroscientist hat and contemplate this question myself:

First, experimental designs where I require multiple optical channels of control. This appears to be aligned with the author's thoughts, as they state, correctly, that opsins utilizing retinal as a light-sensing chromophore are universally activated by blue light (the so-called 'blue shoulder'). Therefore, their tool may be useful for stimulating multiple populations using a blue excitatory opsin in neuron A and their tool for red excitation of neuron B - or, in the author's own words, "A potential solution to the problem of cross-talk...". Yet, there are no data presented that showcases their new tool for this purpose (e.g. Vierock, Johannes, et al. "BiPOLES is an optogenetic tool developed for bidirectional dual-color control of neurons." Nature Communications 12.1 (2021): 4527. Figure 4f-I; 6). The same set-up could be imagined for green GECI (or equivalent) imaging of cells in the same volume that their tool is being used in - for instance, interleaving red stimulation light and blue imaging light, (perhaps) without the typical concern of imaging light bleed-through activating the opsin itself.

Second, for high-frequency temporal control over both excitation and inhibition in the same neuron. The red light turns the cell on, and blue light turns the cell off (see, for instance, Zhang, Feng, et al. "Multimodal fast optical interrogation of neural circuitry." Nature 446.7136 (2007): 633-639. Figure 2; Vierock as above, Figure 4a,b). Again, here the authors are long on theory ("The new system...can drive time-locked high-frequency action potentials in response to red pulses") and short on data. While they do show that red light = excitation and blue light = inhibition, they neither show 1) all-optical on/off modulation of the same cell; nor 2) high-frequency inhibition or excitation (max stim rate of 20hz, which is the same as the BiPOLES paper used for their LC stimulation paradigm; Vierock, as above, Figure 7a-d).

Despite these major shortcomings, the further development and characterization of tandem opsins, such as this one, is of interest to the community. There is ongoing work by the BiPOLES team to create new iterations (e.g. Wahid, J., et al. "P-15 BiPOLES2 is a bidirectional optogenetic tool with a narrow activation spectrum and low red-light excitability." Clinical Neurophysiology 148 (2023): e16.). To make the case that the tool described in this manuscript is worth the effort that the authors are requesting the neuroscience community invest in trialing it in their own hands, they must revise the manuscript to show that their approach is both 1) different in some way when compared to BiPOLES (it is my understanding that they did not do this, as per the supplementary alignment of the BiPOLES sequence and the sequence of the BiPOLES-like construct that they did test) and 2) that the properties that the investigators specifically tailored their construct to have confer some sort of experimental advantage when compared to the existing standard.

There are a number of additional concerns and clarifications that will strengthen the manuscript that are communicated directly to the authors through this peer-review process.

Reviewer #1 (Public Review):

Summary: By elevating Ca influx and inducing PTP, the authors have maximized the release probability. In this condition, the release probability is nearly one. Under such a condition, the release site can release another vesicle in a short time. By analyzing mean, variance, and covariance, the authors propose a release model that each release site contains a docking site and a replacement site. They excluded the LS-TS model (Neher and Brose) based on a discrepancy between the model and the data (mean and covariance).

Strengths: The authors have used minimal stimulation and modeling nicely to look into the stochastic nature of release sites with good resolution. This cannot be done at other synapses. Overall conclusions are reasonable and convincing.

Weaknesses: The interpretation is somewhat model-dependent, and it is unclear if the interpretation is unique. For example, it is unclear if the heterogeneous release probability among sites, silent sites, can explain the results. N estimates out of variance-mean analysis for example may be limited by the availability of postsynaptic receptors.

Reviewer #1 (Public Review):

This study explores the relationship between the most common spatial patterns of neurodegeneration and the density of different cell types in the cerebral cortex. The authors present data showing that atrophy patterns in Alzheimer's disease and Frontotemporal dementia strongly associate with the abundance of astrocytes and microglia. While the results here may be considered preliminary, this work takes a step in the right direction by emphasizing the critical role that cells other than neurons play in the degeneration patterns observable with neuroimaging.

I have two main comments:

1) The authors make an important innovation by applying the cellular deconvolution approach to create brain-wide maps of cellular abundance, and then comparing these maps to atrophy patterns from the most common neurodegenerative diseases and dementia syndromes.

2) I would have preferred to see more figures with brain images showing the cellular abundance maps and the atrophy maps. Without being able to see these figures, it's difficult for the reader to 1) validate the atrophy patterns or 2) gain intuition about how the cellular abundance maps vary across the brain. The images in Figure 1C give a small preview, but I'd like to see these maps in their entirety on the brain surface or axial image slices.

Reviewer #1 (Public Review):

Summary:<br /> In their manuscript, Chim et al. identify an association of rare loss-of-function (LOF) SLC39A5 variants with increased circulating zink levels and decreased T2D risk and complement these observations with a notably comprehensive analysis of metabolically challenged (genetically or diet-induced) Slc39a5-/- mice that demonstrate enhanced hepatic zinc levels, improved liver function, reduced hyperglycemia, partial resistance to NASH induction, and likely involvement of AMPK and AKT signaling.

Strengths:<br /> Overall, the work appears well designed, executed, clearly presented (although navigating the 16 supplementary figures and 6 supplementary tables can be a bit of a challenge), and supports the authors' main conclusions.

Weaknesses:<br /> Nevertheless, two major concerns pertain to the characterization of LOF SLC39A5 variants as well as the seeming absence of a "pancreatic phenotype" in Slc39a5-/- mice that contrasts with earlier reports including impaired glucose tolerance and glucose-stimulated insulin secretion in mice lacking Slc39a5 specifically in beta cells; these concerns should be addressed experimentally and by more extensive discussion of previously published Slc39a5-/- mouse models, respectively.

Reviewer #1 (Public Review):

Medwig-Kinney et al perform the latest in a series of studies unraveling the genetic and physical mechanisms involved in the formation of C. elegans gonad. They have paid particular attention to how two different cell fates are specified, the ventral uterine (VU) or anchor cell (AC), and the behaviors of these two cell types. This cell fate choice is interesting because the anchor cell performs an invasive migration through a basement membrane. A process that is required for correct C. elegans gonad formation and that can act as a model for other invasive processes, such as malignant cancer progression. The authors have identified a range of genes that are involved in the AC/VC fate choice, and that impart the AC cell with its ability to arrest the cell cycle and perform an invasive migration. Taking advantage of a range of genetic tools, the authors show that the transcription factor NHR-63 is strongly expressed in the AC cell. The authors also present evidence that NHR-63 is could function as a transcriptional repressor through interactions with a Groucho and also a TCF homolog, and they also suggest that these proteins are forming repressive condensates through phase separation.

The authors have produced an extensive dataset to support their two primary claims: that NHR-67 expression levels determine whether a cell is invasive or proliferative, and also that NHR-67 forms a repressive complex through interactions with other proteins. The authors should be commended for clearly and honestly conveying what is already known in this area of study with exhaustive references. Future data unambiguously linking the formation and dissolution of NHR-67 condensates with the activation of downstream genes that NHR-67 is actively repressing would be of great interest to the transcriptional research community.

Reviewer #1 (Public Review):

In this work, the authors investigate an important question - under what circumstances should a recurrent neural network optimised to produce motor control signals receive preparatory input before the initiation of a movement, even though it is possible to use inputs to drive activity just-in-time for movement?

This question is important because many studies across animal models have shown that preparatory activity is widespread in neural populations close to motor output (e.g. motor cortex / M1), but it isn't clear under what circumstances this preparation is advantageous for performance, especially since preparation could cause unwanted motor output during a delay.

They show that networks optimised under reasonable constraints (speed, accuracy, lack of pre-movement) will use input to seed the state of the network before movement and that these inputs reduce the need for ongoing input during the movement. By examining many different parameters in simplified models they identify a strong connection between the structure of the network and the amount of preparation that is optimal for control - namely, that preparation has the most value when nullspaces are highly observable relative to the readout dimension and when the controllability of readout dimensions is low. They conclude by showing that their model predictions are consistent with the observation in monkey motor cortex that even when a sequence of two movements is known in advance, preparatory activity only arises shortly before movement initiation.

Overall, this study provides valuable theoretical insight into the role of preparation in neural populations that generate motor output, and by treating input to motor cortex as a signal that is optimised directly this work is able to sidestep many of the problematic questions relating to estimating the potential inputs to motor cortex.

However, there are a number of issues regarding framing and technical limitations that would be useful for readers to keep in mind when interpreting the conclusions.

1) It's important to keep in mind that this work involves simplified models of the motor system, and often the terminology for 'motor cortex' and 'models of motor cortex' are used interchangeably, which may mislead some readers. Similarly, the introduction fails in many cases to state what model system is being discussed (e.g. line 14, line 29, line 31), even though these span humans, monkeys, mice, and simulations, which all differ in crucial ways that cannot always be lumped together.<br /> 2) At multiple points in the manuscript thalamic inputs during movement (in mice) is used as a motivation for examining the role of preparation. However, there are other more salient motivations, such as delayed sensory feedback from the limb and vision arriving in motor cortex, as well as ongoing control signals from other areas such as premotor cortex.<br /> 3) Describing the main task in this work as a delayed reaching task is not justified without caveats (by the authors' own admission: line 687), since each network is optimised with a fixed delay period length. Although this is mentioned to the reader, it's not clear enough that the dynamics observed during the delay period will not resemble those in the motor cortex for typical delayed reaching tasks.<br /> 4) A number of simplifications in the model may have crucial consequences for interpretation.<br /> a) Even following the toy examples in Figure 4, all the models in Figure 5 are linear, which may limit the generalisability of the findings.<br /> b) Crucially, there is no delayed sensory feedback in the model from the plant. Although this simplification is in some ways a strength, this decision allows networks to avoid having to deal with delayed feedback, which is a known component of closed-loop motor control and of motor cortex inputs and will have a large impact on the control policy.<br /> 5) A key feature determining the usefulness of preparation is the direction of the readout dimension. However, all readouts had a similar structure (random gaussian initialization). Therefore, it would be useful to have more discussion regarding how the structure of the output connectivity would affect preparation, since the motor cortex certainly does not follow this output scheme.

Reviewer #1 (Public Review):

The authors aimed to develop a whole-brain multivariate pattern predicting decisions to trust and to use this pattern to assess the construct validity of the concept of trust. To this end, they used machine learning to develop and validate a whole-brain pattern capable of predicting decisions to trust in three previously published fMRI datasets in which participants played an economic trust game. They then assessed how this pattern was expressed in several other published fMRI datasets operationalizing various psychological concepts. They observed that the trust pattern could discriminate between risky or safe economic decisions and different emotional states but could not discriminate between several other concepts such as reward/losses, famous/unfamiliar face perception, etc. Spatial similarity analyses across datasets showed converging results.

This study adopts a rigorous analytical approach, examining fMRI data from thousands of participants spanning fifteen datasets to investigate the relationship between the multivariate pattern of trust and other psychological concepts. Researchers interested in the concept of trust will find this work valuable. More importantly, it exemplifies the potential of using brain data to explore the construct validity of psychological concepts through this methodological approach.

Despite the strengths of this study, there are several points that, in my view, need further attention:

1. The trust pattern developed and validated by the authors is based on one type of task, the economic trust game. This means that the multivariate trust pattern developed by the authors is heavily dependent on how trust is specifically defined and operationalized within this task, which may limit its generalizability. Without evidence that the model generalizes to other operationalizations of trust, the authors should interpret their results more conservatively. Unless additional evidence is given, this should be presented as a pattern of the "decision to trust in an economic context".

2. In datasets 1-1 and 1-2, trust is operationalized as a form of social gambling, where participants choose to share money (trust) with someone else, hoping to triple their investment but risk losing it all, with the alternative being to keep the money (distrust). However, these datasets also include non-social control conditions (the lottery condition in Fareri et al., 2012, and the computer condition in Fareri et al., 2015), which are not discussed in this paper. Evaluating how the trust model behaves in these control conditions seems crucial, as they provide the closest comparison to similar tasks that exclude the trust component. If the trust model is not specific to social decisions in the original datasets (i.e., it cannot distinguish between gambling and not gambling), this significant limitation should be addressed and discussed.

3. The analytical strategy used to establish convergent and discriminant validity is based on the significance of the average group accuracy of forced-choice tests to assess the capacity of the model to discriminate between different concepts (e.g. rewards vs. loss, safety vs. risk). The model is assumed to be specific to trust when the accuracy is not significantly different from chance and related to the other construct when the accuracy is significantly above chance. However, the absence of an effect is related to the power of the test, and in several cases, the sample sizes were relatively small. The use of one-tailed tests also exacerbates this issue since only effects in the hypothesized directions can be significant. These analyses could be improved by adopting a different approach to evaluate support for the null effect, by setting a higher bar for what is considered a generalization of the model, or by interpreting the results more carefully to recognize that lack of evidence isn't necessarily evidence of absence.

Reviewer #1 (Public Review):

It has been shown that there are relationships between a transdiagnostic construct of anxious-depression, and average confidence rating in a perceptual decision task. This study sought to investigate these results, which have been replicated several times but only in cross-sectional studies. This work applies a perceptual decision-making task with confidence ratings and a transdiagnostic psychometric questionnaire battery to participants before and after an iCBT course. The iCBT course reduced AD scores in participants, and their mean confidence ratings increased without a change in performance. Participants with larger AD changes had larger confidence changes. These results were also shown in a separate smaller group receiving antidepressant medication. A similar sized control group with no intervention did not show changes.

The major strength of the study is the elegant and well-powered data set. Longitudinal data on this scale is very difficult to collect, especially with patient cohorts, so this represents an exciting breakthrough. Analysis is straightforward and clearly presented. No multiple comparison correction is applied despite many different tests. While in general I am not convinced of the argument in the citation provided to justify this, I think in this case the key results are not borderline (p<0.001) and many of the key effects are replications, so there are not so many novel/exploratory hypothesis and in my opinion the results are convincing and robust as they are. The supplemental material is a comprehensive description of the data set, which is a useful resource.

The authors achieved their aims, and the results clearly support the conclusion that the AD and mean confidence in a perceptual task covary longitudinally.

I think this provides an important impact to the project of computational psychiatry, specifically, it shows the relationship between transdiagnostic symptom dimensions and behaviour is meaningful within as well as across individuals.

Reviewer #1 (Public Review):

Secondary cell walls support vascular plants and conduct water throughout the plant body, but are also important resources for lignocellulosic feedstocks. Secondary cell wall synthesis is under complex transcriptional control, presumably because it must only be initiated after cell growth is complete. Here, the authors found that two Musashi-type RNA-binding proteins, MSIL2 and MSIL4 are redundantly required for secondary cell wall development in Arabidopsis. The plant phenotypes could be complemented by the wild-type version of either protein, but not by a MSIL4 version that carries mutations in the conserved RNA-binding domains, and the authors localized MSIL2 & 4 to stress granules, implicating the RNA-binding function of MSIL4 in the cell wall phenotype. Upon closer inspection, the secondary cell wall phenotypes included changes in vasculature morphology, and minor changes to lignin and hemicellulose (glucuronoxylan). While there were no changes to likely cell wall target genes in the transcriptome of msil2msil4 plants, proteomics experiments found glucuronoxylan biosynthesis components were upregulated in the mutants, and they detected an increase in substituted xylan via several methods. Finally, they documented MSIL4 binding to RNA encoding one of these targets, suggesting that MSIL2 and MSIL4 act to post-transcriptionally regulate glucuronoxylan modification. Altogether, this is a new mechanism by which cell wall composition could be regulated.

Overall, the manuscript is well-written, the data are generally high-quality, and the authors typically use several independent methods to support each claim. However, several important questions remain unanswered by this work in its current state and the model presented in Figure 7 is quite speculative. For example, the link between the striking plant phenotype and GXM misregulation is unclear since GXM overexpression doesn't alter plant phenotypes or lignin content (Yuan et al 2014 Plant Science), so misregulation of GXMs in msil2msil4 mutants clearly is not the whole story. It also remains to be determined why one particular secondary cell wall synthesis enzyme is regulated likely post-transcriptionally, while so much of the pathway is regulated at the transcriptional level. There are likely other targets for MSIL2- and MSIL4-mediated regulation since it seems that MSIL2 and MSIL4 are expressed in tissues that are not synthesizing secondary cell walls.

Reviewer #1 (Public Review):

Summary:<br /> Authors propose mathematical methods for inferring evolutionary parameters of interest from bulk/single cell sequencing data in healthy tissue and hematopoiesis. In general, the introduction is well-written and adequately references the relevant and important previous literature and findings in this field (e.g. the power laws for well-mixed exponentially growing populations). The authors consider 3 phases of human development: early development, growth and maintenance, and mature phase. In particular, time-dependent mutation rates in Figure 2d is an intriguing and strong result, and the process underlying Figures 3 and 4 are generally well-explained and convincing.

Notes & suggestions:<br /> 1. The explanation of Figure 2 in Lines 101 - 111 should be expanded for clarity. First, is Figure 2a derived from stochastic simulation (line 101 suggests) or some theoretical analysis? Second, the gradual transition from f-2 to f-1 is appreciated, but the shape of the intermediates is not addressed in detail. The power laws are straight lines, and the simulations provide curved lines -- please expand in what range (low or high frequency variants) the power law approximations apply.

Additionally, I do not understand the claim in line 108, that the transition is fast for low frequency variants, as the low frequency (on the left of the graph) lines are all close together, whereas the high frequency lines are far apart.

It would be helpful to reiterate in this paragraph that these power laws are derived based on exponentially growing populations and are expected to break down under homeostatic conditions.

2. The sample vs population (blue vs orange) in Figure 3 is under-explained. How is it that the mutational burden and inferred mutation rate in A and B roughly match, but the VAF distributions in C are so different? How was the sampled set chosen? Perhaps this is an unimportant distinction based on the particular sample set, but the divergence of the two in C may serve as a distraction, here.

3. The comparison of results herein to claims by Mitchell (ref. 12) are quite important results within the paper. I appreciate the note in the final paragraph of the discussion, and I suggest adding a sentence referencing the result noted in line 248-249 to the abstract, as well.

Reviewer #1 (Public Review):

Summary:<br /> The manuscript describes a study in which younger, normal-hearing adults listened to two concurrent speech streams (audio-visual presentation) while magnetoencephalography (MEG) was recorded. They were asked to attend to one and ignore the other speech stream. Speech materials were processed using natural language processing (NLP) model approaches to categorize speech chunks of about 3.5 s duration as being of either high or low probability based on topic modeling. MEG results show that decoding performance (reconstruction of speech) was high for the high-probability speech chunks under both the attend and ignore conditions, suggesting that semantic information in the unattended speech was still processed. The conclusions of this paper are mostly well supported by the data.

Strengths:<br /> 1) The authors use sophisticated analyses using natural language processing models - that are beyond the state-of-the-art - to make inferences about semantic speech processing in the brain. The analytic methods are well described, enabling readers to possibly implement the approach for their own analyses.

2) The study shows that highly salient semantic information of speech is processed in the brain even when a listener attends to something different. The work has implications for selective attention models that are concerned with how individuals process speech.

Weaknesses:<br /> 1) The title of the manuscript may be a bit misleading: "Get the gist of the story: Neural map of topic keywords in multi-speaker environment". The study was not about the gist of the story but about the gist of speech chunks of about 3.5 s. The study shows important evidence that neural activity is sensitive to the gist of short speech segments, even in unattended speech, but the gist of the story is a yet more abstract level that cannot be reduced to the gist of short speech chunks.

2) The calculations of t-values for the spatial maps showing significant clusters were non-standard, which makes interpreting the magnitude of the t-values difficult. Better motivation for why the specific approach was chosen would be important, or perhaps replacing it with a more standard approach. It further appears that the region of interest analyses were carried out without multiple comparison corrections, possibly suggesting a note of caution about some of the source-localization results.

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. But the work may be less original than the authors propose, and their overall framing strikes me as odd. Some additional clarifications could make the contribution more clear.

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 et 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.

- In the discussion (lines 315-316), they state "in order to account for the reduced neural sensitivity with target-background similarity in the second phase of the response, the divisive normalization signal has to be orientation selective." I wonder whether they observed this in their modeling. That is, how robust were the normalization model results to the values of sigma_e and sigma_n? It would be useful to know how critical their various model parameters were for replicating the experimental effects, rather than just showing that a good account is possible.

- The majority of their target/background contrast conditions were collected only in one animal. This is a minor limitation for work of this kind, but it might be an issue for some.

- The authors point out (line 193-195) that "Because the first phase of the response is shorter than the second phase, when V1 response is integrated over both phases, the overall response is positively correlated with the behavioral masking effect." I wonder if this could be explored a bit more at the behavioral level - i.e. does the "similarity masking" they are trying to explain show sensitivity to presentation time?

- From Fig. 3 it looks like the imaging ROI may include some opercular V2. If so, it's plausible that something about the retinotopic or columnar windowing they used in analysis may remove V2 signals, but they don't comment. Maybe they could tell us how they ensured they only included V1?

- In the discussion (lines 278-283) they say "The positive correlation between the neural and behavioral masking effects occurred earlier and was more robust at the columnar scale than at the retinotopic scale, suggesting that behavioral performance in our task is dominated by columnar scale signals in the second phase of the response. To the best of our knowledge, this is the first demonstration of such decoupling between V1 responses at the retinotopic and columnar scales, and the first demonstration that columnar scale signals are a better predictor of behavioral performance in a detection task." I am having trouble finding where exactly they demonstrate this in the results. Is this just by comparison of Figs. 4E,K and 5E,K? I may just be missing something here, but the argument needs to be made more clearly since much of their claim to originality rests on it.

Reviewer #1 (Public Review):

This manuscript by Leibinger et al describes their results from testing an interesting hypothesis that microtubule detyrosination inhibits axon regeneration and its inhibitor parthenolide could facilitate axon regeneration and perhaps functional recovery. Overall, the results from in vitro studies are largely well performed. However, the in vivo data are less convincing.

Interpretation of the findings in this study are limited by several gaps:<br /> 1. It is unclear whether microtubule detyrosination a primary effect of hIL-6 and PTEN deletion or secondary to the increased axon growth?

2. Is there any direct evidence for Akt and/or JAK/Stat3 to promote microtubule detyrosination?

3. What is the impact of parthenolide on cell soma of neurons and other cell types?

4. Direct evidence that parthenolide augments PTEN deletion in optic nerve or spinal cord is not provided.

5. Serotonergic neurotoxin DHT ablates both regenerating and non-regenerating serotonergic axons, which makes spinal cord findings it difficult to interpret.

6. DMAPT was given by i.p. injection. What happens to microtubule detyrosination in other cells within and outside of CNS?

Reviewer #1 (Public Review):

In the manuscript entitled "A theory of hippocampal theta correlations", the authors propose a new mechanism for phase precession and theta-time scale generation, as well as their interpretation in terms of navigation and neural coding. The authors propose the existence of extrinsic and intrinsic sequences during exploration, which may have complementary functions. These two types of sequences depend on external input and network interactions, but differ on the extent to which they depend on movement direction. Moreover, the authors propose a novel interpretation for intrinsic sequences, namely to signal a landmark cue that is independent of direction of traversal. Finally, a readout neuron can be trained to distinguish extrinsic from intrinsic sequences.

The study puts forward novel computational ideas related to neural coding, partly based on previous work from the authors, including published (Leibold, 2020, Yiu et al., 2022) and unpublished (Ahmedi et al., 2022. bioRxiv) work. The manuscript will contribute to the understanding of the mechanisms behind phase precession, as well as to how we interpret hippocampal temporal coding for navigation and memory.

Reviewer #1 (Public Review):

The authors present a study of visuo-motor coupling primarily using wide-field calcium imaging to measure activity across the dorsal visual cortex. They used different mouse lines or systemically injected viral vectors to allow imaging of calcium activity from specific cell-types with a particular focus on a mouse-line that expresses GCaMP in layer 5 IT (intratelencephalic) neurons. They examined the question of how the neural response to predictable visual input, as a consequence of self-motion, differed from responses to unpredictable input. They identify layer 5 IT cells as having a different response pattern to other cell-types/layers in that they show differences in their response to closed-loop (i.e. predictable) vs open-loop (i.e. unpredictable) stimulation whereas other cell-types showed similar activity patterns between these two conditions. Surprisingly, they find that presentation of a visual grating actually decreases the responses of L5 IT cells in V1. They interpret their results within a predictive coding framework that the last author has previously proposed. The response pattern of the L5 IT cells leads them to propose that these cells may act as 'internal representation' neurons that carry a representation of the brain's model of its environment. Though this is rather speculative. They subsequently examine the responses of these cells to anti-psychotic drugs (e.g. clozapine) with the reasoning that a leading theory of schizophrenia is a disturbance of the brain's internal model and/or a failure to correctly predict the sensory consequences of self-movement. They find that anti-psychotic drugs strongly enhance responses of L5 IT cells to locomotion while having little effect on other cell-types. Finally, they suggest that anti-psychotics reduce long-range correlations between (predominantly) L5 cells and reduce the propagation of prediction errors to higher visual areas and suggest this maybe a mechanism by which these drugs reduce hallucinations/psychosis.

This is a large study containing a screening of many mouse-lines/expression profiles using wide-field calcium imaging. Wide-field imaging has its caveats, including a broad point-spread function of the signal and susceptibility to hemodynamic artifacts, which can make interpretation of results difficult. The authors acknowledge these problems and directly address the hemodynamic occlusion problem. It was reassuring to see supplementary 2-photon imaging of soma to complement this data-set, even though this is rather briefly described in the paper. Overall the paper's strengths are its identification of a very different response profile in the L5 IT cells compared other layers/cell-types which suggests an important role for these cells in handling integration of self-motion generated sensory predictions with sensory input. The interpretation of the responses to anti-psychotic drugs is more speculative but the result appears robust and provides an interesting basis for further studies of this effect with more specific recording techniques and possibly behavioral measures.

Reviewer #1 (Public Review):

In this manuscript, Bilgic et al aim to identify the progenitor types (and their specific progeny) that underlie the expanded nature of gyrencephalic brains. To do this, they take a comparative scRNAseq (single cell transcriptomics) approach between neurodevelopment of the gyrencephalic ferret, and previously published primary human brain and organoid data.

They first improve gene annotations of the ferret genome and then collect a time series of scRNAseq data of 6 stages of the developing ferret brain spanning both embryonic and post-natal development. Among the various cell types they identify are a small proportion of truncated radial glial cells (tRGs), a population known to be enriched in humans and macaques that emerges late in neurogenesis as the RGC scaffold splits into an oRGC that contact the pial surface and a tRG that contacts the ventricular surface. They find that the tRGs consist of three distinct subpopulations two of which are committed to ependymal and astroglial fates.

By integrating these data with publicly available data of developing human brains and human brain organoids they make some important observations. Human and ferret tRGs have very similar transcriptional states, suggesting that the human tRGs too give rise to ependymal and astroglial fates. They also find that the current culture conditions of human brain organoids seem to lack tRGs, something that will need to be addressed if they are to be used to study tRGs. While the primary human data set did contain tRGs, the stage or the region sampled were likely not appropriate, and therefore, the number of cells they could retrieve was low.

The authors have spent considerable efforts in improving gene modeling of the ferret genome, which will be important for the field. They've generated valuable time series data for the developing ferret brain, and have proposed the lineal progeny for the tRGs in the human brain. Whether tRGs actually do give rise to the ependymal and astrogial fates needs to be validated in future studies.

Reviewer #1 (Public Review):

Summary:<br /> In this work, the authors are trying to satisfy a real need in MR safety, when concerns can arise about the thermal increase due to metallic materials in patients carrying orthopedic implants. The "MR conditional" labeling of the implant obtained by ASTM in-vitro tests may help to plan the MR scan, but it is normally limited to a single specific MR sequence and a B0 value, and it is not always available. The adoption of an in-silico simulation testbed overcomes this limitation, providing a fast and reliable prediction of temperature increase from RF, in real-life scan conditions on human-like digital models. The FDA is pushing this approach.

Strengths:<br /> The presented in-silico testbed looks valuable and validated. It is based on the widely available Visible Human Project (VHP) datasets, and the testbed is available online. The approval of the testbed by the FDA as a medical device development tool (MDDT) is a good premise for the large-scale adoption of this kind of solution.

Weaknesses:<br /> There are a couple of limitations in the study that must be clearly highlighted to the readers.

While the RF-related heating is very well modeled, the gradients-related heating is out of the scope of this paper and not considered. Readers must be warned that RF causes only a part of the heating, and literature is reporting cases where also gradient switching can contribute, as correctly mentioned in this work. A cautious attitude should consider this as a significant limitation of the study.

Moreover, the way the implant is embedded in the VHP model is shortly documented in the materials and methods and mostly focuses on implant registration on bone tissue. It is not clear how to manage the empty space and the soft tissue stretching/reshaping generated by the simulated surgery (for example, by the cut of the femoral head in total hip arthroplasty). It is reported by literature that the level of accuracy in the simulated surgery can impact in some cases (RF vs. gradients heating, massive vs. thin or elongated implants) on temperature predictions.

Reviewer #1 (Public Review):

The authors investigate the roles of ACOT12/8 in the production of acetate by the liver. They observe that acetate concentration parallels ketone concentrations during fasting and T1DM. They show that acetate is produced from fatty acids in hepatocytes, but though described as a novel "ketone body", this acetate is not a product of ketogenesis or acetoacetate. They also provide serum acetate data from human subjects who were classified as either "healthy" or "diabetic,". These subjects are noted as T2DM patients, but there is no other characterization or description, making it difficult to ascertain the context in which they were studied or their relevance to the mouse studies. Although the function of ACOT12/8 is reported in the literature, they are not widely studied, and there also remains surprising uncertainties regarding the mechanism of acetate production by the liver. In this regard, the manuscript provides some important insight. The authors use ShACOT12/8 and ACOT12/8 knockout mice to demonstrate that these acetyl-CoA hydrolases are largely necessary for acetate production. Using a 3H-palmitate assay, the authors then find that loss of these ACOTs inhibit fatty acid oxidation and propose that the mechanism involves scavenging CoA, analogous to the canonical role of ketogenesis. The idea is plausible but not proven. A related finding is that loss of these ACOTs inhibit ketogenesis, which the authors attribute to the loss of function of HMGC2S, partially through acetylation. These mechanisms suffer some limitations based on the cytosolic and mitochondrial compartmentation of the two processes, but the observations appear sound. Interestingly, the loss of the ACOTs have a more profound effect on lowering ketones than acetate, which may have parallel effects but they are not investigated. Finally, the authors try to demonstrate that hepatic ACOT-mediated acetate production is necessary for normal motor function in STZ treated mice, ostensibly as compensation for impaired glucose utilization by the CNS. Injections of 13C acetate and 13C enrichment in downstream metabolites of brain are used to support the importance of acetate metabolism, but the experiment was not performed in loss of function models. In addition, the resulting 13C enrichment data is reported generically as "relative intensity" without further elaboration on how this data was generated and should not be taken at face value by the reader. Conceptually, one may also be skeptical of the rather dramatic loss of motor function in the context of a relatively minor circulating nutrient. Nevertheless, this finding may be important if more supporting evidence with proper controls for ketone concentrations can be provided. Overall, there are important data in the manuscript, but the reader may find it difficult to navigate the 20+ figure panels. The most important findings are that ACOT12/8 are critical for hepatic acetate production in mice, which will be helpful for the field, but the ramifications require more rigorous investigation.

Reviewer #1 (Public Review):

The authors aimed to establish a cell culture system to investigate muscle tissue development and homeostasis. They successfully developed a complex 3D cell model and conducted a comprehensive molecular and functional characterization. This approach represents a critical initial step towards using human cells, rather than animals, to study muscular disorders in vitro. Although the current protocol is time-consuming and the fetal cell model may not be mature enough to study adult-onset diseases, it nonetheless provides a valuable foundation for future disease modeling studies using isogenic iPSC lines or patient-derived cells with specific mutations. The manuscript does not explore whether or how this stem cell model can advance our understanding of muscular diseases, which would be an exciting avenue for future research. Overall, the detailed protocol presented in this paper will be useful for informing future studies and provide a valuable resource to the stem cells community. Future work could focus on disease modeling using isogenic iPSC lines or patient-derived cells.

Reviewer #1 (Public Review):

Summary:<br /> This is a follow-up study to the authors' previous report about the roles of an alpha-arrestin called protein thioredoxin interacting protein (Txnip) in cone photoreceptors and in the retinal pigment epithelium. The findings are important because they provide new information about the mechanism of glucose and lactate transport to cone photoreceptors and because they may become the basis for therapies for retinal degenerative diseases.

Strengths:<br /> Overall, the study is carefully done and, although the analysis is fairly comprehensive with many different versions of the protein analyzed, it is clearly enough described to follow. Figure 4 greatly facilitated my ability to follow, understand and interpret the study.

Weaknesses:<br /> I have just one concern that I would like the authors to address. It is about the text that begins at line 133: "We assayed their ability to clear GLUT1 from the RPE surface (Figure 2A)". Please provide more details about this. From the figure it appears that n = 1 for this experiment, but given how careful the authors are with these types of studies that seems unlikely. How did the authors quantify the ability to clear GLUT1 from the surface? Was it cleared from both the apical and basal surface? (It is hard to resolve the apical and basal surfaces in the images provided). The experiments shown in Fig. 1H and Fig. 1I of PMID 31365873 shows how GLUT1 disappears only from the apical surface (under the conditions of that experiment and through the mechanism described in their text). It would be helpful for the authors to discuss their current results in the context of that experiment.

Reviewer #1 (Public Review):

Summary:

This study examines the role of host blood meal source, temperature, and photoperiod on the reproductive traits of Cx. quinquefasciatus, an important vector of numerous pathogens of medical importance. The host use pattern of Cx. quinquefasciatus is interesting in that it feeds on birds during spring and shifts to feeding on mammals towards fall. Various hypotheses have been proposed to explain the seasonal shift in host use in this species but have provided limited evidence. This study examines whether the shifting of host classes from birds to mammals towards autumn offers any reproductive advantages to Cx. quinquefasciatus in terms of enhanced fecundity, fertility, and hatchability of the offspring. The authors found no evidence of this, suggesting that alternate mechanisms may drive the seasonal shift in host use in Cx. quinquefasciatus.

Strengths:

Host blood meal source, temperature, and photoperiod were all examined together.

Weaknesses:

The study was conducted in laboratory conditions with a local population of Cx. quinquefasciatus from Argentina. I'm not sure if there is any evidence for a seasonal shift in the host use pattern in Cx. quinquefasciatus populations from the southern latitudes.

Reviewer #1 (Public Review):

Summary:<br /> The goal of this study was to develop and validate novel molecules to selectively activate a cell signaling pathway, the Wnt pathway in this case, in target cells expressing a specific receptor. This was achieved through a two-component system that the authors call BRAID, where each component simultaneously binds the target cell-specific marker BKlotho and a Wnt co-receptor. These components, called SWIFT molecules, bring together the Wnt co-receptors LRP and FZD, activating the pathway specifically in cells that express BKlotho. Results presented in the study demonstrate the desired activity of SWIFT molecules; the binding assays support the simultaneous association of SWIFT with BKlotho and a Wnt co-receptor, and the Wnt reporter and qPCR assays support pathway activation in cell lines and primary cells in a BKlotho-dependent manner. In the future, the BRAID approach could be applied to activate Wnt signaling or another pathway initiated by a co-receptor complex in a cell type-specific manner, and/or in a FZD subtype-specific manner to activate distinct branches of Wnt signaling.

Strengths:<br /> • This study successfully demonstrates a novel way to activate Wnt signaling in target cells expressing a specific marker. Given the role of the Wnt signaling pathway in key processes such as cell proliferation and tissue renewal and the value of modulating cell signaling in a cell type-specific manner, the cell targeting system developed here holds great therapeutic and research potential. It will be curious to see whether the BRAID design can be applied to other cell surface markers for Wnt activation, or for activation of other signaling pathways that require co-receptor association.

• Octet assay results show simultaneous binding of SWIFT molecules to both the Wnt co-receptor FZD/LRP and BKlotho, while negative control molecules without the FZD/LRP or BKlotho-binding module show neither receptor binding nor Wnt pathway activation. These results indicate that SWIFT molecules function through the intended mechanism.

Weaknesses:<br /> • Here, the activity of SWIFT molecules was assessed in single cell types with or without BKlotho expression. Ultimately, the ability of the SWIFT molecules to activate Wnt signaling in a cell type-specific manner should be tested in the context of many different cellular identities that express BKlotho to different extents. It would be good to demonstrate that Wnt activation by SWIFT correlates with BKlotho expression level in multiple cell types - such data would strengthen the claim of cell-type specificity.

• The study does not address whether the targeted cells express FGFR1c/2c/3c and whether the FGF21 full-length moiety or the 39F7 IgG moiety of SWIFT molecules could unintentionally activate FGF signaling in these cells.

Reviewer #1 (Public Review):

This work continues a series of recent publications from the Grigorieff lab (https://doi.org/10.7554/eLife.25648, https://doi.org/10.7554/eLife.68946, https://doi.org/10.7554/eLife.79272, https://doi.org/10.1073/pnas.2301852120) showcasing the development of high-resolution 2D template matching (2DTM) for detection and reconstruction of macromolecules in cryo-electron microscopy (cryo-EM) images of crowded cellular environments. It is well known in the field of cryo-EM that searching noisy images with a template can result in retrieval of the template itself when averaging the candidate particles detected, an effect known as "Einstein-from-noise" (https://doi.org/10.1073/pnas.1314449110). Briefly, this occurs because it is statistically likely to find a match to an arbitrary motif over a large noisy dataset just by chance. The effect can be mitigated for example by limiting the resolution of the template, but this prevents the accurate detection of macromolecules in a crowded environment, as their "fingerprint" lies in the high-resolution range (https://doi.org/10.7554/eLife.25648). Here, the authors show through several experiments on in vitro and in situ data that features as small as drug compounds and water molecules can be reliably retrieved by 2DTM if they are searched by a template (the "bait") that contains expected neighboring features but not the targets themselves.

The ideas are generally clearly presented with appropriate references to related work, and claims are well supported by the data. In particular, the experiments for verifying the density of the ribosomal protein L7A as well as the systematic removal of residuals from the template model to assess bias are particularly clever.

One key point that could use further clarification is how to interpret densities in the reconstruction that do overlap with the template. If the omitted regions can be reliably reconstructed, and the density is smooth throughout, it implies the detected particles are not only (mostly) true positives but also their poses must be essentially correct. Therefore, why cannot the entire reconstruction be trusted, including portions overlapping with the template? In the "Future applications" section, the authors state that in order to obtain a reconstruction that is entirely devoid of template bias, it would be necessary to successively omit parts of the template structure through its entirety. I wonder if that is really necessary and if the presented approach of omitting template portions could be better framed as a "gold-standard" validation procedure.

In other words, given the compelling evidence provided by the reconstructions in the omitted areas, I find it hard to imagine how the procedure would be "hallucinating" features in the rest of the structure, as the entire reconstruction depends on the same pose and defocus parameters. A possible experiment to test this hypothesis would be to go the opposite way, deliberately adding an unrealistic feature to the bait and checking whether it comes up in the reconstruction, while at the same time checking how it behaves in omitted parts.

When assessing their approach to in situ data (the yeast ribosome), it is intriguing to see that the resolution downgraded from 3.1 to 8 Å when refinement of the particle poses against the current reconstruction was attempted. The authors do provide some possible explanations, such as the reduced signal of the reconstruction at high resolution and the crowded background, but it leaves one to wonder if this means that a 3.1 Å reconstruction could never be obtained from these data by conventional single-particle analysis procedures.

Furthermore, in the section "Quantifying template bias", the authors make the intriguing statement that there can still be some overfitting of noise even in true positives. I understand this overfitting would occur in the form of errors in the pose and defocus estimation, but a clarification would be helpful.

In the Discussion, the claim that "it is not necessary to use tomography to generate high-resolution reconstructions of macromolecular complexes in cells" is a misconception, at least in part. As demonstrated in works by the same group and others (https://doi.org/10.1016/j.xinn.2021.100166, https://doi.org/10.1038/s41467-023-36175-y, https://doi.org/10.1038/s41586-023-05831-0), 2D imaging of native cellular environments does offer a faster and better way to obtain high-resolution reconstructions compared to tomography. However, tomography provides the entire 3D context of the macromolecules, such as their localization to membranes and the cellular architecture, which can be readily visualized in a tomogram even at low resolution, so methods for structure determination from tilt series data such as subtomogram averaging remain of paramount importance. Most likely, a combination of 2D and 3D imaging approaches will be necessary to retrieve both the highest structural resolution and their cellular context to address biological questions.

The "Materials and Methods" section lacks a description of transmission electron microscopy data collection.

Finally, the preprint version of this work posted on bioRxiv (https://doi.org/10.1101/2023.07.03.547552) contains the following competing interests statement, which is missing from the submitted version:<br /> "The authors are listed as inventors on a closely related patent application named "Methods and Systems for Imaging Interactions Between Particles and Fragments", filed on behalf of the University of Massachusetts."

Reviewer #1 (Public Review):

Koesters and colleagues investigated the role of the presynaptic small GTPase Rab3A in homeostatic scaling of miniature synaptic transmission in primary mouse cortical cultures using electrophysiology and immunohistochemistry. The major finding is that TTX incubation for 48 hours does not induce an increase in the amplitude of excitatory synaptic miniature events in neuronal cultures derived from Rab3A KO and Rab3A Earlybird mutant mice. NASPM application had comparable effects on mEPSC amplitude in control and after TTX, implying that Ca2+-permeable glutamate receptors are unlikely modulated during synaptic scaling. Immunohistochemical analysis revealed an increase in GluA2 puncta size and intensity in wild type, but not Rab3A KO cultures. Finally, they provide evidence that loss of Rab3A in neurons, but not astrocytes, blocks homeostatic scaling. Based on these data, the authors propose a model in which presynaptic Rab3A is required for homeostatic scaling of synaptic transmission through GluA2-dependent and independent mechanisms.

While the title of the manuscript is mostly supported by data of solid quality, many conclusions, as well as the final model, cannot be derived from the results presented. Importantly, the results do not indicate that Rab3A modulates quantal size on both sides of the synapse. Moreover, several analysis approaches seem inappropriate.

The following points should be addressed:

1. The model shown in Figure 10 is not supported by the data. The authors neither provide evidence for two different functional states of Rab3A being involved in mEPSC amplitude modulation, nor for a change in glutamate content of vesicles. Furthermore, the data do not fully support the conclusion of a presynaptic role for Rab3A in homeostatic scaling.<br /> 2. The analysis of mEPSC data using quantile sampling followed by ratio calculation is not meaningful under the tested experimental conditions because of the following reasons: (i) The analysis implicitly assumes that all events have been detected. The prominent mEPSC frequency increase after TTX suggests that this is not the case, i.e., many (small) mEPSCs are likely missed under control conditions. (ii) The analysis is used to conclude how events of a certain size are altered by TTX treatment. However, this analysis compares the smallest mEPSCs of the TTX condition with the smallest control mEPSCs, but this is not a pre-post experimental design. Variation between cells and between coverslips will markedly affect the results and lead to misleading interpretations. (iii) The ratio (TTX/control) vs. control plots seem to suffer from a division by small value artifact (see Figure 6F). Correspondingly, ratio-analysis differs considerably for different control conditions (Fig. 1Giii, Fig. 2Giii, Fig. 6C, Fig. 9A).<br /> 3. As noted by the authors in a previous publication (Hanes et al. 2020), statistical analysis of CDFs suffers from n-inflation. In addition, the quantile sampling method chosen violates an important assumption of the K-S test. Indeed, p-values for these comparisons are typically several orders of magnitude smaller. Given that the statistical N most likely corresponds to the number of cultures (see, e.g., https://doi.org/10.1371/journal.pbio.2005282), CDF comparisons are not informative and should thus not be used to draw conclusions from the data. The plots can be informative, though.<br /> 4. How does recoding noise and the mEPSC amplitude threshold affect "divergent scaling"?<br /> 5. What is the justification for the line fits of the ratio data/how was the fit range chosen?<br /> 6. TTX application induces a significant increase in mEPSC amplitude in Rab3A-/- mice in two out of three data sets (Figs. 1 and 9). Hence, the major conclusion that Rab3A is required for homeostatic scaling is only partially supported by the data.<br /> 7. Line 289: A comparison of p-values between conditions does not allow any meaningful conclusions.<br /> 8. There is a significant increase in baseline mEPSC amplitude in Rab3AEbd/Ebd (15 pA) vs. Rab3Aebd/+ (11 pA) cultures, but not in Rab3A-/- (13.6 pA) vs. Rab3A+/- (13.9 pA). Although the nature of scaling was different between Rab3AEbd/Ebd vs. Rab3AEbd/+, and Rab3AEbd/Ebd with vs. without TTX, the question arises whether the increase in mEPSC amplitude in Rab3AEbd/Ebd is Rab3A dependent. Could a Rab3A independent mechanism occlude scaling?<br /> 9. Figure 4: NASPM appears to have a stronger effect on mEPSC frequency in the TTX condition vs. control (-40% vs. -15%). A larger sample size might be necessary to draw definitive conclusions on the contribution of Ca2+-permeable AMPARs.<br /> 10. The authors discuss previous papers showing changes in VGLUT1 intensity. Was VGLUT intensity altered in the stainings presented in the manuscript?<br /> 11. The change in GluA2 area or fluorescence intensity upon TTX treatment in controls is modest. How does the GluA2 integral change?<br /> 12. The quantitative comparison between physiology and microscopy data is problematic. The authors report a mismatch in ratio values between the smallest mEPSC amplitudes and smallest GluA2 receptor cluster sizes (l. 464; Figure 8). Is this comparison affected by the fluorescence intensity threshold? What was the rationale for a threshold of 400 a.u. or 450 a.u.? How does this threshold compare to the mEPSC threshold of 3 pA? The conclusion that an increase in AMPAR levels is not fully responsible for the observed mEPSC increase is mainly based on the rank-order analysis of GluA2 intensity, yielding a slope of ~0.9. There are several points to consider here: (i) GluA2 fluorescence intensity did increase on average, as did GluA2 cluster size. (ii) The increase in GluA2 cluster size is very similar to the increase in mEPSC amplitude (each approx. 18-20%). (iii) Are there any reports that fluorescence intensity values are linearly reporting mEPSC amplitudes (in this system)? Antibody labelling efficiency, and false negatives of mEPSC recordings may influence the results. The latter was already noted by the authors. (iv) It is not entirely clear if their imaging experiments will sample from all synapses. Other AMPAR subtypes than GluA2 could contribute, as could kainate or NMDA receptors.<br /> Furthermore, the statement "complete lack of correspondence of TTX/CON ratios" is not supported by the data presented (l. 515ff). First, under the assumption that no scaling occurs in Rab3A-/- , the TTX/CON ratios show a 20-30% change, which indicates the variation of this readout. Second, the two examples shown in Figure 8 for Rab3A+/+ are actually quite similar (culture #1 and #2), particularly when ignoring the leftmost section of the data, which is heavily affected by the raw values approaching zero.<br /> 13. Figure 7A: TTX CDF was shifted to smaller mEPSC amplitude values in Rab3A-/- cultures. How can this be explained?

Reviewer #1 (Public Review):

Summary:

This valuable study analyzes the contribution of fungal and bacterial microbiota species to the growth and development of Drosophila. The authors use bacterial and fungal species associated with Drosophila in the wild to analyze their respective contributions in promoting larval growth in a decaying banana, mimicking the natural niche of fruit flies. They found that some fungal species and some fungus/bacteria combinations effectively promote growth by supplementing key branched amino acids in the food substratum. Production of these amino acids by Drosophila itself is not sufficient, and only fungal species that secrete these amino acids into the medium can sustain Drosophila growth. Thus, the authors clarify how facultative symbionts contribute to host growth in a natural setting by changing the food substratum in a dynamic manner.

Strengths:

The natural setting developed by the authors to analyze the impact of the microbiota is clearly valuable, as is the focus on the role of fungal microbiota species. This complements studies of Drosophila microbiota that have previously focused on bacterial species and used a lab setting. While there has been an extensive focus on obligate endosymbionts or gut symbionts, this study analyzes how facultative symbionts shape the food substratum and influence host growth. A last strength of this study is that it analyzes the contribution of Drosophila microbiota over a dynamic timeframe, analyzing how microbial species change in decaying fruit over time.

Weaknesses:

1) The authors should better review what we know of fungal Drosophila microbiota species as well as the ecology of rotting fruit. Are the microbiota species described in this article specific to their location/setting? It would have been interesting to know if similar species can be retrieved in other locations using other decaying fruits. The term 'core' in the title suggests that these species are generally found associated with Drosophila but this is not demonstrated. The paper is written in a way that implies the microbiota members they have found are universal. What is the evidence for this? Have the fungal species described in this paper been found in other studies? Even if this is not the case, the paper is interesting, but there should be a discussion of how generalizable the findings are.

2) Can the authors clearly demonstrate that the microbiota species that develop in the banana trap are derived from flies? Are these species found in flies in the wild? Did the authors check that the flies belong to the D. melanogaster species and not to the sister group D. simulans?

3) Did the microarrays highlight a change in immune genes (ex. antibacterial peptide genes)? Whatever the answer, this would be worth mentioning. The authors described their microarray data in terms of fed/starved in relation to the Finke article. They should clarify if they observed significant differences between species (differences between species within bacteria or fungi, and more generally differences between bacteria versus fungi).

4) The whole paper - and this is one of its merits - points to a role of the Drosophila larval microbiota in processing the fly food. Are these bacterial and fungal species found in the gut of larvae/adults? Are these species capable of establishing a niche in the cardia of adults as shown recently in the Ludington lab (Dodge et al.,)? Previous studies have suggested that microbiota members stimulate the Imd pathway leading to an increase in digestive proteases (Erkosar/Leulier). Are the microbiota species studied here affecting gut signaling pathways beyond providing branched amino acids?

Reviewer #1 (Public Review):

Taking advantage of a publicly available dataset, neuronal responses in both the visual and hippocampal areas to passive presentation of a movie are analyzed in this manuscript. Since the visual responses have been described in a number of previous studies (e.g., see Refs. 11-13), the value of this manuscript lies mostly on the hippocampal responses, especially in the context of how hippocampal neurons encode episodic memories. Previous human studies show that hippocampal neurons display selective responses to short (5 s) video clips (e.g. see Gelbard-Sagiv et al, Science 322: 96-101, 2008). The hippocampal responses in head-fixed mice to a longer (30 s) movie as studied in this manuscript could potentially offer important evidence that the rodent hippocampus encodes visual episodes.

The analysis strategy is mostly well designed and executed. A number of factors and controls, including baseline firing, locomotion, frame-to-frame visual content variation, are carefully considered. The inclusion of neuronal responses to scrambled movie frames in the analysis is a powerful method to reveal the modulation of a key element in episodic events, temporal continuity, on the hippocampal activity. The properties of movie fields are comprehensively characterized in the manuscript.

Comments on latest version:

The new analysis on how behavioral states and hippocampal ripples impacted the tuning of movie fields makes the main finding substantially more convincing. Other relatively minor concerns on the methodology and interpretation are also improved. I do not have further concerns.

Reviewer #1 (Public Review):

With this work, the authors address a central question regarding the potential consequences of post-translational modifications for the pathogenesis of neurodegenerative diseases. Phosphorylation and mislocalization of the RNA binding protein TDP43 are characteristic of ~50% of frontotemporal lobar degeneration (FTLD), as well as >95% of amyotrophic lateral sclerosis (ALS). To determine if acetylation is a primary, disease-driving event, they generated a TDP-43 mutant harboring an acetylation-mimicking mutation (K145Q). Animals carrying the acetylation-mimic mutation (K145Q) displayed key pathological features of disease, including more cytoplasmic TDP43 and impaired TDP43 splicing activity, together with behavioral phenotypes reminiscent of FTLD.

This is a well-written and well-illustrated manuscript, with clear and convincing findings. The observations are significant and emphasize the importance of post-translational modifications to TDP-43 function and disease phenotypes. In addition, the TDP43(K145Q) mice may prove to be a valuable model for studying TDP-43-related mechanisms of neurodegeneration and therapeutic strategies.

Comments on the latest version:

The authors have addressed most concerns. The additional analysis demonstrating a lack of neuron loss is quite different from the original study -- it is good that the authors pursued this question. In addition, new data focusing on native TDP-43 splice targets, rather than the splicing reporter, are excellent.

Reviewer #1 (Public Review):

Summary:

This is an important study that tests the effects of using neurofeedback, in the form of reward delivery when large sharp wave-ripples (SWRs) are detected, on neurophysiological and behavioral measures. The authors report that the rate of SWRs ripples increased prior to reward delivery, but this increased rate of SWRs had no significant effect on memory performance. They also found that compensatory decreases in SWR rate occurred in the period after reward delivery such that the overall SWR rate remained stable.

Strengths:

The study has many strengths. The paradigm of closed loop detection of SWRs and reward delivery is powerful and provides an innovative way to causally test the effects of increasing SWR rates. Other studies could adopt this method to test other hypotheses or to assess the effects of increasing SWR rates prior to reward delivery in rodent models of brain disorders. The methods and results are clearly explained. The results are presented in a transparent way.

Weaknesses:

In the linear mixed effects model analysis used in Figure 2, and statistics reported in the figure legend, an interaction effect showing that neurofeedback differentially affected the SWR rate and count pre- and post-award seems to be missing in the reported statistics.

In the Discussion, the authors write, "Further, because subjects learn to modulate SWR rate, rather than simply generating a single suprathreshold event on command, it is likely that they learn to engage a SWR-permissive state during the targeted interval in which brain-wide neural activity and neuromodulatory tone also enter a SWR-permissive realm". This seems to imply that the neurofeedback is directly modulating neural activity. However, it is unclear from the paper exactly how the neurofeedback is modulating the SWR rate. Considering that SWRs occur during immobility, is it possible that the animals are learning to remain more immobile and modulating the SWR rate in that way?

Reviewer #1 (Public Review):

Summary:<br /> The paper presents a nice study investigating differences in biological motion perception in participants with ADHD in comparison with controls. Motivated by the idea that there is a relationship between biological motion perception and social capabilities, the authors investigated local and global (holistic) biological motion perception, the group, and several additional behavioral variables that are affected in ADHS (IQ, social responsiveness, and attention/impulsivity). As well as local global biological motion perception is reduced in ADHD participants. In addition, the study demonstrates a significant correlation between local biological motion perception skills and the social responsiveness score in the ADHD group, but not the controls. A path analysis in the ADHD data suggests that general performance in biological motion perception is influenced mainly by global biological motion perception performance and attentional and perceptual reasoning skills.

Strengths:<br /> It is true that there exists not much work on biological motion perception and ADHD. Therefore, the presented study contributes an interesting new result to the biological motion literature and adds potentially also new behavioral markers for this clinical condition. The design of the study is straightforward and technically sound, and the drawn conclusions are supported by the presented results.

Weaknesses:<br /> Some of the claims about the relationship between genetic factors and ADHD and the components of biological motion processing have to remain speculative at this point because genetic influences were not explicitly tested in this paper.

Reviewer #1 (Public Review):

This work describes a new and powerful approach to a central question in ecology: what are the relative contributions of resource utilisation vs interactions between individuals in the shaping of an ecosystem? This approach relies on a very original quantitative experimental set-up whose power lies in its simplicity, allowing an exceptional level of control over ecological parameters and of measurement accuracy.

In this experimental system, the shared resource corresponds to 10^12 copies of a fixed single-stranded target DNA molecule to which 10^15 random single-stranded DNA molecules (the individuals populating the ecosystem) can bind. The binding process is cycled, with a 1000x-PCR amplification step between successive binding steps. The composition of the population is monitored via high-throughput DNA sequencing. Sequence data analysis describes the change in population diversity over cycles. The results are interpreted using estimated binding interactions of individuals with the target resource, as well as estimated binding interactions between individuals and also self-interactions (that can all be directly predicted as they correspond to DNA-DNA interactions). A simple model provides a framework to account for ecosystem dynamics over cycles. Finally, the trajectory of some individuals with high frequency in late cycles is traced back to the earliest cycles at which they are detected by sequencing. Their propensities to bind the resource, to form hairpins, or to form homodimers suggest how different interaction modes shape the composition of the population over cycles.

The authors report a shift from selection for binding to the resource to interactions between individuals and self-interactions over the course of cycles as the main drivers of their ecosystem. The outcome of the experiment is far from trivial as the individual-resource binding energy initially determines the relative enrichment of individuals, and then seems to saturate. The richness of the population dynamics observed with this simple system is thus comparable to that found in some natural ecosystems. The findings obtained with this new approach will likely guide the exploration of natural ecosystems in which parameters and observables are much less accessible.

My review focuses mainly on the experimental aspects of this work given my own expertise. The introduction exposes very convincingly the scientific context of this work, justifying the need for such an approach to address questions pertaining to ecology. The manuscript describes very clearly and rigorously the experimental set-up. The main strengths of this work are (i) the outstanding originality of the experimental approach and (ii) its simplicity. With this setup, central questions in ecology can be addressed in a quantitative manner, including the possibility of running trajectories in parallel to generalize the findings, as reported here. Technical aspects have been carefully implemented, from the design of random individuals bearing flanking regions for PCR amplification, binding selection and (low error) amplification protocols, and sequencing read-out whose depth is sufficient to capture the relevant dynamics. One missing aspect in the data analysis is the quantification of the effect of PCR amplification steps in shaping the ecosystem (to be modeled if significant). In addition, as it stands the current work does not fully harness the power of the approach. For instance, with this setup, one can tune the relative contributions of binding selection vs amplification for instance (to disentangle forces that shape the ecosystem). One can also run cycles with new DNA individuals, designed with arbitrarily chosen resource binding vs self-binding, that are predicted to dominate depending on chosen ecological parameters.

Reviewer #1 (Public Review):

In this study, the authors obtained multiple, novel and compelling datasets to better understand the relationship between histone H1 and RNA-directed DNA methylation in plants. Most of the authors' claims concerning H1 and RNA polymerase V (Pol V) are backed by convincing and independent lines of evidence. However, the authors also make some overly broad conclusions, for which additional experiments/data analyses should be explored to improve confidence in their findings. Furthermore, Pol V produces noncoding transcripts that act as scaffold RNAs, which AGO4-bound siRNAs recognize in plant chromatin to mediate RNA-directed DNA methylation. Detection of Pol V transcript products at sites of Pol V redistribution in h1 mutants would significantly enhance the impact of this manuscript. Below I have listed several strengths and weaknesses of the manuscript.

Strengths<br /> 1. The authors report high-quality NRPE1 ChIP-seq data, allowing them to directly test how and where Pol V occupancy depends on histone H1 function in Arabidopsis.<br /> 2. nrpe1 mutants generated via CRISPR/Cas9 in the h1 mutant background (nrpe1 h1.1-1 h1.2-1 triple mutants), allow the authors to study the role of Pol V in ectopic DNA methylation in H1-deficient plants.<br /> 3. Pol V recruitment via ZincFinger-DMS3 expression (a modified version of Pol V's DMS3 recruitment factor) sends Pol V to new genomic loci and thus provides the authors with an innovative dataset for understanding H1 function at these sites.

Weaknesses<br /> 1. The manuscript does not include detection or quantification of Pol V transcripts generated at ectopic sites in the h1 mutant background.<br /> 2. Statistical tests are missing throughout and are needed to support several of the authors' claims.<br /> 3. The SUVH1-3xFLAG ChIP-seq analyses in Fig. 6 require additional controls and are not fully explained in the results. The broad conclusions drawn (based on those experiments) are thus not convincing.

Previous studies have charted the relationship between H1 function and RNA-directed DNA methylation (RdDM) via analyses of Pol IV-dependent 24 nt siRNAs and factors that recruit Pol IV (Choi et al., 2021 and Papareddy et al., 2020). Harris and colleagues have extended this work and shown that histone H1 function also antagonizes Pol V occupancy in the context of constitutive heterochromatin. The authors thus provide important evidence to show that H1 limits the encroachment of both polymerases Pol IV and Pol V into plant heterochromatin.

Reviewer #1 (Public Review):

People can perform a wide variety of different tasks, and a long-standing question in cognitive neuroscience is how the properties of different tasks are represented in the brain. The authors develop an interesting task that mixes two different sources of difficulty, and find that the brain appears to represent this mixture on a continuum, in the prefrontal areas involved in resolving task difficulty. While these results are interesting and in several ways compelling, they overlap with previous findings and rely on novel statistical analyses that may require further validation.

Strengths<br /> 1. The authors present an interesting and novel task for combining the contributions of stimulus-stimulus and stimulus-response conflict. While this mixture has been measured in the multi-source interference task (MSIT), this task provides a more graded mixture between these two sources of difficulty.

2. The authors do a good job triangulating regions that encoding conflict similarity, looking for the conjunction across several different measures of conflict encoding. These conflict measures use several best-practice approaches towards estimating representational similarity.

3. The authors quantify several salient alternative hypothesis and systematically distinguish their core results from these alternatives.

4. The question that the authors tackle is important to cognitive control, and they make a solid contribution.

Concerns<br /> 1. The evidence from this previous work for mixtures between different conflict sources makes the framing of 'infinite possible types of conflict' feel like a strawman. The authors cite classic work (e.g., Kornblum et al., 1990) that develops a typology for conflict which is far from infinite. I think few people would argue that every possible source and level of difficulty will have to be learned separately. This work provides confirmatory evidence that task difficulty is represented parametrically (e.g., consistent with the n-back, MOT, and random dot motion literature).

2. The degree of Stroop vs Simon conflict is perfectly negatively correlated across conditions. This limits their interpretation of an integrated cognitive space, as they cannot separately measure Stroop and Simon effects. The author's control analyses have limited ability to overcome this task limitation. While these results are consistent with parametric encoding, they cannot adjudicate between combined vs separated representations.

Reviewer #1 (Public Review):

Summary:<br /> The authors developed computational models that capture the electrical and Ca2+ signaling behavior in mesenteric arterial cells from male and female mice. A baseline model was first formulated with eleven transmembrane currents and three calcium compartments. Sex-specific differences in the L-type calcium channel and two voltage-gated potassium channels were then tuned based on experimental measurements. To incorporate the stochastic ion channel openings seen in smooth muscle cells under physiological conditions, noise was added to the membrane potential and the sarcoplasmic Ca2+ concentration equations. Finally, the models were assembled into 1D vessel representations and used to investigate the tissue-level electrical response to an L-type calcium channel blocker.

Strengths:<br /> A major strength of the paper is that the modeling studies were performed on three different scales: individual ionic currents, whole-cell, and 1D tissue. This comprehensive computational framework can help provide mechanistic insight into arterial myocyte function that might be difficult to achieve through traditional experimental methods.

The authors aimed to develop sex-specific computational models of mesenteric arterial myocytes and demonstrate their use in drug-testing applications. Throughout the paper, model behavior was both validated by experimental recordings and supported by previously published data. The main findings from the models suggested that sex-specific differences in membrane potential and Ca2+ handling are attributable to variability in the gating of a small number of voltage-gated potassium channels and L-type calcium channels. This variability contributes to a higher Ca2+ channel blocker sensitivity in female arterial vessels. Overall, the study successfully met the aims of the paper.

Weaknesses:<br /> A main weakness of the paper, as addressed by the authors, is the simplicity of the 1D vessel model; it does not take into account various signaling pathways or interactions with other cell types which could impact smooth muscle electrophysiology. Another potential shortcoming is the use of mouse data for optimizing the model, as there could be discrepancies in signaling behavior that limit the translatability to human myocyte predictions.

Reviewer #1 (Public Review):

The authors previously showed in cell culture that Su(H), the transcription factor mediating Notch pathway activity, was phosphorylated on S269 and they found that a phospho-deficient Su(H) allele behaves as a moderate gain of Notch activity in flies, notably during blood cell development. Since a downregulation of Notch signaling was proposed to be important for the production of a specialized blood cell types (lamellocytes) in response to wasp parasitism, the authors hypothesized that Su(H) phosphorylation might be involved in this cellular immune response.

Consistent with their hypothesis, the authors show that Su(H)S269A knock-in flies display a reduced response to wasp parasitism and that Su(H) is phosphorylated upon infestation. Using in vitro kinase assays and a genetic screen, they identify the PKCa family member Pkc53E as the putative kinase involved in Su(H) phosphorylation and they show that Pkc53E can bind Su(H). They further show that Pkc53E deficit or its knock-down in larval blood cells results in similar blood cell phenotypes as Su(H)S269A, including a reduced response to wasp parasitism, and their epistatic analyses indicate that Pkc53E acts upstream of Su(H).

Strengths<br /> The manuscript is well presented and the experiments are sound, with a good combination of genetic and biochemical approaches and several clear phenotypes which back the main conclusions. Notably Su(H)S269A mutation or Pkc53E deficiency strongly reduces lamellocyte production and the epistatic data are convincing.

Weaknesses<br /> The phenotypic analysis of larval blood cells remains rather superficial. Looking at melanized cells is a crude surrogate to quantify crystal cell numbers as it is biased toward sessile cells (with specific location) and does not bring information concerning the percentage of blood cells differentiated along this lineage.

In Su(H)S269A knock-in or Pkc53E zygotic mutants, the increase in crystal cells in uninfected conditions and the decreased capacity to induce lamellocytes following infection could have many origins which are not investigated. For instance, premature blood cell differentiation could promote crystal cell differentiation and reduce the pool of lamellocytes progenitors. These mutations could also affect the development and function of the posterior signaling center in the lymph gland, which plays a key role in lamellocyte induction. Similarly, the mild decrease on resistance to wasp infestation (Fig. 2A) could reflect a constitutive reduction in blood cell numbers in Su(H)S269A larvae rather than a defective down-regulation of Notch activity.<br /> Whereas the authors also present targeted-knock down/inhibition of Pkc53E suggesting that this enzyme is required in blood cells to control crystal cell fate (Fig. 6), it is somehow misleading to use lz-GAL4 as a driver in the lymph gland and hml-GAL4 in circulating hemocytes as these two drivers do not target the same blood cell populations/steps in the crystal cell development process.

In addition, the authors do not present evidence that Pkc55E function (and Su(H) phosphorylation) is required specifically in blood cells to promote lamellocyte production in response to infestation.

Finally, the conclusion that Pkc53E is (directly) responsible for Su(H) phosophorylation needs to be strengthened. Most importantly, the authors do not demonstrate that Pkc53E is required for Su(H) phosphorylation in vivo (i.e. that Su(H) is not phosphorylated in the absence of Pkc53E following infestation). In addition, the in vitro kinase assays with bacterially purified Pkc53E (in the presence of PMA or using an activated variant of Pkc53E) only reveal a weak activity on a Su(H) peptide encompassing S269 (Fig. 4). Moreover, while the authors show a coIP between an overexpressed Pkc53E and endogenous Su(H) (Fig. 7) (in the absence of infestation), it has recently been reported that Pkc53E is a cytoplasmic protein in the eye (Shieh et al. 2023), calling for a direct assessment of Pkc53E expression and localization in larval blood cells under normal conditions and upon infestation. Furthermore, the effect of the PKCa agonist PMA on Su(H)-induced reporter gene expression in cell culture and crystal cell number in vivo is somehow consistent with the authors hypothesis, but some controls are missing (notably western blots to show that PMA/Staurosporine treatment does not affect Su(H)-VP16 level) and it is unclear why STAU treatment alone promotes Su(H)-VP16 activity (in their previous reports, the authors found no difference between Su(H)S269A-VP16 and Su(H)-VP16) or why PMA treatment still has a strong impact on crystal cell number in Su(H)S269A larvae.

Joint Public Review:

The study has many limitations which need to be addressed and there is a lack of functional explanation of carriage. These limitations are: a) the lack of inclusion of non-Black patients; and b) the lack of appropriate explanation if results are false-positive since APOL1 provides risk for chronic renal disease (CRD) and patients with CRD are predisposed to sepsis. Sepsis occurred in 565 Black subjects, of whom 105 (29% ) had APOL1 high-risk genotype and 460 had-low risk genotype. Importantly, the risk for sepsis associated with APOL1 HR variants was no longer significant after adjusting for subjects pre-existing severe renal disease or after excluding these subjects. Thus, the susceptibility pathway seems to be: APOL1 variants > CKD > sepsis diathesis.

Reviewer #1 (Public Review):

In this study, Fang H et al. describe a potential pathway, ITGB4-TNFAIP2-IQGAP1-Rac1, that may involve in the drug resistance in triple negative breast cancer (TNBC). Mechanistically, it was demonstrated that TNFAIP2 bind with IQGAP1 and ITGB4 activating Rac1 and the following drug resistance. The present study focused on breast cancer cell lines with supporting data from mouse model and patient breast cancer tissues. The study is interesting. The experiments were well controlled and carefully carried out. The conclusion is supported by strong evidence provided in the manuscript. The authors may want to discuss the link between ITGB4 and Rac 1, between IQGAP1 and Rac1, and between TNFAIP2 and Rac1 as compared with the current results obtained. This is important considering some recent publications in this area (Cancer Sci 2021, J Biol Chem 2008, Cancer Res 2023). In addition, some key points need to be addressed in order to support their conclusion in full.

Reviewer #1 (Public Review):

Proposed significance: Targeted therapy in general has miraculous results.<br /> Good and detailed study of molecular characteristics and microenvironment of tumor of PCCs .However molecular classification system based on limited number of cases is not acceptable.<br /> Early diagnosis is of utmost importance in patient care and the next important is classification of tumor for treatment purposes.<br /> Further research is needed to develop Molecular signature of tumor types . This will help in targeted therapy and precision medicine.

Strength: Molecular characterisation of tumor

Weakness: The sample size is very small from a statistical point of view to derive a conclusion. Only Observations can be recorded<br /> Transcriptome profiles of 11 tumor tissues were studied but they belong to the same 5 patients.

Validation of tumor tissue: comparison is made with adjacent normal tissue (n=5 )<br /> Chromogranin IHC marker is used for identifying tumor cells. However, chromogranin marker positivity is also seen in normal adrenal medulla /chromaffin cells.<br /> Any better evidence of Validation of tumor tissue?

Tumor microenvironment:<br /> CD8+T cells: it is mentioned in the article that there is lack of CD8+ Tcells in both types of PCC, (Page 5, line 16)

However Figures 7 D, E and F show presence of CD8+T cells. Needs clarification or quantification.

Tumor heterogeneity : Page 7 Line 5<br /> PASS system is used by authors for predicting malignant potential and tumor heterogeneity.<br /> Molecular methods need to be used for evaluating tumor heterogeneity rather than histomorphology.

Ground of comparision is not valid. PASS system is based on histomorphology and present study/attempt at classification is based on molecular studies. So they cannot be compared .

Page 5 ,Line 18: HLA downregulation is observation and its regulation by RET is a possibility. Its involvement in tumor progression needs solid proof. So targeting kinase pathway for therapy is only a possibility.

Reviewer #1 (Public Review):

This manuscript proposes a complex unclear model involving Ca2+ signaling in inflammasome activation. The experimental approaches used to study the calcium dynamics are problematic and the results shown are of inadequate quality. The major claims of this manuscript are not adequately substantiated.

Major concerns:

1. The analysis of lysosomal Ca2+release is being carried out after many hours of treatment. Such evidence is not meaningful to claim that PA activates Ca2+ efflux from lysosome and even if this phenomenon was robust, it is not doubtful that such kinetics are meaningful for the regulation of inflammasome activation. Furthermore, the evidence for lysosomal Ca2+ release is indirect and relies on a convoluted process that doesn't make any conceptual sense to me. In addition to these major shortcomings, the indirect evidence of perilysosomal Ca2+ elevation is also of very poor quality and from the standpoint of my expertise in calcium signaling, the data are incredulous. The use of GCaMP3-ML1, *transiently transfected* into BMDMs is highly problematic. The efficiency of transfection in BMDMs is always extremely low and overexpression of the sensor in a few rare cells can lead to erroneous observations. The overexpression also results in gross mislocalization of such membrane-bound sensors. The accumulation of GCaMP3-ML1 in the ER of these cells would prevent any credible measurements of perilysosomal Ca2+ signals. A meaningful investigation of this process in primary macrophages requires the generation of a mouse line wherein the sensor is expressed at low levels in myeloid cells, and shown to be localized almost exclusively in the lysosomal membrane. The mechanistic framework built around these major conceptual and technical flaws is not especially meaningful and since these are foundational results, I cannot take the main claims of this study seriously.

2. The cytosolic Ca2+ imaging shown in Figure 1C doesn't make any sense. It looks like a snapshot of basal Ca2+ many hours after PA treatment - calcium elevations are highly dynamic. Snapshot measurements are not helpful and analyses of Calcium dynamics requires a recording over a certain timespan. Unfortunately, this technical approach has been used throughout the manuscript. Also, BAPTA-AM abrogates IL-1b secretion because IL-1b transcription is Ca2+ dependent - the result shown in figure 1D does not shed light on anything to do with inflammasome activation and it is misleading to suggest that.

3. Trpm2-/- macrophages are known to be hyporesponsive to inflammatory stimuli - the reduced secretion of IL-1b by these macrophages is not novel. From a mechanistic perspective, this study does not add much to that observation and the proposed role of TRPM2 as a lysosomal Ca2+ release channel is not substantiated by good quality Ca2+ imaging data (see point 3 above). Furthermore, the study assumes that TRPM2 is a lysosomal ion channel. One paper reported TRPM2 in the lysosomes but this is a controversial claim, with no replication or further development in the last 14 years. This core assumption can be highly misleading to readers unfamiliar with TRPM2 biology and it is necessary to present credible evidence that TRPM2 is functional in the lysosomal membrane of macrophages. Ideally, this line of investigation should rest on robust demonstration of TRPM2 currents in patch-clamp electrophysiology of lysosomes. If this is not technically feasible for the authors, they should at least investigate TRPM2 localization on lysosomal membranes of macrophages.

4. Apigenin and Quercetin are highly non-specific and their effects cannot be attributed to CD38 inhibition alone. Such conclusions need strong loss of function studies using genetic knockouts of CD38 - or at least siRNA knockdown. Importantly, if indeed TRPM2 is being activated downstream of CD38, this should be easily evident in whole cell patch clamp electrophysiology. TRPM2 currents can be resolved using this technique and authors have Trpm2-/- cells for proper controls. Authors attempted these experiments but the results are of very poor quality. If the TRPM2 current is being activated through ADPR generated by CD38 (in response to PA stimulation), then it is very odd that authors need to include 200 uM cADPR to see TRPM2 current (Fig. 3A). Oddly, even these data cast great doubt on the technical quality of the electrophysiology experiments. Even with such high concentrations of cADPr, the TRPM2 current is tiny and Trpm2-/- controls are missing. The current-voltage relationship is not shown, and I feel that the results are merely reporting leak currents seen in measurements with substandard seals. Also 20 uM ACA is not a selective inhibitor of TRPM2 - relying on ACA as the conclusive diagnostic is problematic.

5. TRPM2 is expressed in many different cell lines. The broad metabolic differences observed by the authors in the Trpm2-/- mice cannot be attributed to macrophage-mediated inflammation. Such a conclusion requires the study of mice wherein Trpm2 is deleted selectively in macrophages or at least in the cells of the myeloid lineage.

6. The ER-Lysosome Ca2+ refilling experiments rely on transient transfection of organelle-targeted sensors into BMDMs. See point #1 to understand why I find this approach to be highly problematic. Furthermore, the data procured are also not convincing and lack critical controls (localization of sensors has not been demonstrated and their response to acute mobilization of Ca2+ has not been shown to inspire any confidence in these results).

7. Authors claim that SCOE is coupled to K+ efflux. But there is no credible evidence that SOCE is activated in PA stimulated macrophages. The data shown in Fig 4 supp 1 do not investigate SOCE in a reliable manner - the conclusion is again based on snapshot measurements and crude non-selective inhibitors. The correct way to evaluate SOCE is to record cytosolic Ca2+ elevations over a period of time in absence and presence of extracellular Ca2+. However, even such recordings can be unreliable since the phenomenon is being investigated hours after PA stimulation. So, the only definitive way to demonstrate that Orai channels are indeed active during this process is through patch clamp electrophysiology of PA stimulated cells.

Reviewer #1 (Public Review):

Summary:<br /> The authors of this manuscript characterize new anion conducting that is more red-shifted in its spectrum than prior variants called MsACR1. An additional mutant variant of MsACR1 that is renamed raACR has a 20 nm red-shifted spectral response with faster kinetics. Due to the spectral shift of these variants, the authors proposed that it is possible to inhibit the expression of MsACR1 and raACR with lights at 635 nm in vivo and in vitro. The authors were able to demonstrate some inhibition in vitro and in vivo with 635 nm light. Overall the new variants with unique properties should be able to suppress neuronal activities with red-shifted light stimulation.

Strengths:<br /> The authors were able to identify a new class of anion conducting channelrhodopsin and have variants that respond strongly to lights with wavelength >550 nm. The authors were able to demonstrate this variant, MsACR1, can alter behavior in vivo with 635 nm light. The second major strength of the study is the development of a red-shifted mutant of MsACR1 that has faster kinetics and 20 nm red-shifted from a single mutation.

Weaknesses:<br /> The red-shifted raACR appears to work much less efficiently than MsACR1 even with 635 nm light illumination both in vivo (Figure 4) and in vitro (Figure 3E) despite the 20 nm red-shift. This is inconsistent with the benefits and effects of red-shifting the spectrum in raACR. This usually would suggest raACR either has a lower conductance than MsACR1 or that the membrane/overall expression of raACR is much weaker than MsACR1. Neither of these is measured in the current manuscript.

There are limited comparisons to existing variants of ACRs under the same conditions in the manuscript overall. There should be more parallel comparison with gtACR1, ZipACR, and RubyACR in identical conditions in cultured cell lines, cultured neurons, and in vivo. This should be in terms of overall performance, efficiency, and expression in identical conditions. Without this information, it is unclear whether the effects at 635 nm are due to the expression level which can compensate for the spectral shift.

There should be more raw traces from the recordings of the different variants in response to short pulse stimulation and long pulse stimulation to different wavelengths. It is difficult to judge what the response would be like when these types of information are missing.

Despite being able to activate the channelrhodopsin with 635 nm light, the main utility of the variant should be transcranial stimulation which was not demonstrated here.

Figure 3B is not clearly annotated and is difficult to match the explanation in the figure legend to the figure. The action potential spikings of neurons expressing raACR in this panel are inhibited as strongly as MsACR1.

For many characterizations, the number of 'n's are quite low (3-7).

Reviewer #1 (Public Review):

In this paper, the authors attempt to overcome the "fundamental limitations" of Lempel-Ziv complexity by developing and testing a complexity estimator based on state-space modelling (CSER) that they argue allows higher temporal resolution and spectral decomposition of entropy directly. They test the performance of this approach using MEG, EEG, and ECoG data from monkeys and humans. Although in principle, these developments might be useful for those already using LZ complexity in their analyses, these developments ignore much of the non-LZ entropy community which has already developed related solutions to the same issues. It is thus not clear currently whether this approach is necessary or unique per se:

• As the authors intimate, LZ is a relatively crude but efficient estimator; it leverages a simple binarization of time points above and below the time series mean to look at patterns (in turn disregarding the magnitude of the signal itself). The unique benefit of LZ in and of itself is not at all clear to this reviewer. It is nearly guaranteed that LZ will be extremely highly correlated with various other common measures of "discrete" entropy (especially permutation entropy, which ranks all time-series points prior to computing motifs/patterns rather than anchor anything by the mean (as does LZ), but nevertheless ignores the value range of the signal). The general appeal of the authors' intended developments to further improve LZ specifically would dramatically boost should they be able to make a case that LZ is somehow special, to begin with.

• Beyond this, we can now turn to the authors' rationale for the LZ developments proposed. Despite the authors' statement in the abstract that LZ complexity is "the most widely used approach complexity of neural dynamics," to my knowledge, sample entropy (and its multiscale variant, MSE) is much more commonly used in cognitive neuroscience. Such measures of entropy already enjoy several benefits over LZ. First, the continuous magnitude of the signal is relevant in sample entropy (i.e., it is not discrete in the same way as LZ because the values of each data point matter prior to the estimation of patterns). This is important for people in that community because electrophysiologists/neuroimagers often assume the values of the signal to matter (e.g., for ERPs, the magnitude of power, etc.). Ignoring the magnitude of signal values altogether, as in LZ, is a somewhat dramatic choice, especially if the authors then end up arguing that the spectral decomposition of entropy itself is valuable (after signal value ranges have been ignored!). In any case, as far as I know, LZ has never been shown the be more sensitive than e.g., sample entropy/MSE in relation to any outcome variable, but perhaps the authors can provide evidence for this and argue what LZ should practically do that is unique. Second, the use of MSE more easily allows (although not without its challenges) to directly compare spectral power and single/multiscale entropy straight away, which has been done in quite some depth already without the need for a state-space model of any kind (e.g., Kosciessa et al., 2020, PLOS CB). Instead of using a standard spectral power approach and comparing to entropy, the authors propose the spectrally decompose CSER entropy time series directly. Why? What should this do over standard multi-scale entropy approaches (like MSE, which estimate "fast" and "slow" complexity dynamics), which do not require a Fourier? And if they already believe that the spectrum cannot capture entropy (hence rationalizing the use of LZ-type measures in general), why do they want to invoke spectral estimation assumptions into the estimation of entropy when they could just compare the standard spectrum to entropy to begin with, without any complex modelling in between? I just don't see the need for a lot of what is proposed here; the authors provide solutions to problems that (at least for several in this community) may not exist at all.

• Figure 2: the authors show results descriptively comparing LZ and CSER, but without comparing the two measures directly. The patterns overall look extremely similar; why not correlate the values from the two measures in each dataset to make a case for what CSER is adding here? By eye test, it appears they will be extremely highly correlated, which leaves the reader wondering what CSER (with all of its model complexities and assumptions) has added.

• On the logic of and evidence for the use of CSER: The use of a state space model to allow estimation of "prediction errors" appears to be akin to a latent autocorrelation model with a lag/step size of 1 time-point, and trained only on prestim baseline data. When a successive time point is "deviant" from that autocorrelative function, the authors argue that this provides a measure of instantaneous entropy. This seems simple at first glance, but it is very difficult for this reviewer to wrap their head around. This approach anchors stim-related entropy estimation to prestim entropy for every subject, disallowing the direct comparison of values across subjects during the stimulus phase itself. This does not directly provide a measure of instantaneous task-related entropy, but a mixture of pre and post stim sources based on a state-space model. Does it need to be this complicated? Why does a simple window-based function not suffice to generate temporal dynamics of entropy without coupling the task-based signal to the prestim period? There are many such approaches already existing in the field.

• Figure 3: The authors show that gamma-band CSER is the most sensitive. Isn't it true that this is the exact inverse of the dominance of typical spectral effects under such conditions (that across the literature in psychedelics, sleep, and anaesthesia, there are dominant shifts in low-frequency spectral power)? Although low-frequency power is expected to be a dominant determinant of entropy in the entire signal (see Kosciessa et al., 2020, PLOS CB), something else appears to be happening here. At face value, because gamma is the spectral band with the lowest power in every imaging modality we know of, there is inherently less repeatability/autocorrelation in that same signal, which necessarily should produce more "prediction error/instantaneous entropy" in any condition. When the authors then take the "mean difference" of gamma-based entropy values from each of the two conditions in each sample, any condition-based shift in entropy should inherently be easier to detect. In any case, why not simply show these CSER spectral results next to a standard spectrum over the same conditions and then directly compare the unique utility of e.g., gamma power to CSER gamma? And if you compute something like the percent change between conditions for each spectral band, do you maintain gamma dominance?

Reviewer #2 (Public Review):

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

Reviewer #1 (Public Review):

In this manuscript, "Diminishing neuronal acidification by channelrhodopsins with low proton conduction" by Hayward and colleagues, the authors report on the properties of novel optogenetic tools, PsCatCh2.0 and ChR2-3M, that minimize photo-induced acidification. The authors point out that acidification is an undesirable side-effect of many optogenetic approaches that could be minimized using the new tools. ChRs are known to acidify cells, while Arch are known to alkalize cells. This becomes particularly important when optical stimulation is prolonged and pH changes can become significant. pH is known to affect neuronal excitability, vesicular release, and more. To develop novel optogenetic tools with minimal proton conductances, the authors combined channelrhodopsin stimulation with a red-shifted pH sensor to measure pH during optogenetic stimulation. The authors report that optogenetic activation of CheRiff caused slow cellular acidification. 150 seconds of illumination caused a 3-fold increase in protons or approximately a 0.6 unit pH change that returned to baseline very slowly. They also found that pH changes occurred more rapidly, and recovered more rapidly, in dendrites. The authors go on to robustly characterize PsCatCh2.0 and ChR2-3M in terms of their proton conductances, photocurrent, kinetics, and more. They convincingly show that these constructs induced reduced acidification while maintaining robust photocurrents. In sum, this manuscript shows important findings that convincingly characterizes 2 optogenetic tools that have reduced pH artifacts that may be of broad interest to the field of neuroscience research and optogenetic therapies.

Reviewer #1 (Public Review):

Summary:

The work studies functional connectivity gradients using advanced resting-state analyses in fetuses and sheds light on pre-existing functional topographies and their continued development during the third trimester of gestation.

Strengths:

The work is novel, and applies state of the art connectomic mapping techniques to study fetal brain organization. The work capitalizes on the existence of large, open access datasets, and shows interesting and impactful findings on the presence of functional topographies from 25GW onwards.

Weaknesses:

To better understand underlying factors in cortical functional organization, the authors could add additional exploratory analyses to assess the role of cortical microstructure/myelin and thalamic connectivity.

Reviewer #1 (Public Review):

Summary: Direction selectivity (DS) in the visual system is first observed in the radiating dendrites of starburst amacrine cells (SACs). Studies over the last two decades have aimed to understand the mechanisms that underlie these unique properties. Most recently, a 'space-time' model has garnered special attention. This model is based on two fundamental features of the circuit. First, distinct anatomical types of bipolar cells (BCs) are connected to proximal/distal regions of each of the SAC dendritic sectors (Kim et al., 2014). Second, that input across the length of the starburst is kinetically diverse, a hypothesis that has been only recently demonstrated experimentally using iGluSnFR imaging (Srivastava et al., 2022). However, the stark kinetic distinctions, i.e., the sustained/transient nature of BC input to SACs dendrites appear to be present mainly in responses to stationary stimuli. When BC receptive field properties are probed using white noise stimuli, the kinetic differences between BCs are relatively subtle or nonexistent (Gaynes et al., 2022; Strauss et al., 2022, Srivastava et al., 2022). Thus, if and how BCs contribute to direction selectivity driven by moving spots that are commonly used to probe the circuit remains to be clarified. To address this issue, Gaynes et al., combine evolutionary computational modeling (Ankri et al., 2020) with two-photon iGluSnFR imaging to address to what degree BCs contribute to the generation of direction selectivity in the starburst dendrites in response to stimuli that are commonly used experimentally.

Strengths:

Combining theoretical models and iGluSnFR imaging is a powerful approach as it first provides a basic intuition on what is required for the generation of robust DS, and then tests the extent to which the experimentally measured BC output meets these requirements.

The conclusion of this study builds on the previous literature and comprehensively considers the diverse BC receptive field properties that may contribute to DS (e.g. size, lag, rise time, decay time).

By 'evolving' bipolar inputs to produce robust DS in a model network, these authors provide a sound framework for understanding which kinetic properties could potentially be important for driving downstream DS. They suggest that response delay/decay kinetics, rather than the center/surround dynamics are likely to be most relevant (albeit the latter could generate asymmetric responses to radiating/looming stimuli).

Weaknesses: Finally, these authors report that the experimentally measured BC responses are far from optimal for generating DS. Thus, the BC-based DS mechanism does not appear to explain the robust DS observed experimentally (even with mutual inhibition blocked). Nevertheless, I feel the comprehensive description of BC kinetics and the solid assessment of the extent to which they may shape DS in SAC dendrites, is a significant advancement in the field.

Reviewer #1 (Public Review):

Guglielmo et al. characterized addiction-like behaviors in more than 500 outbred heterogeneous stock (HS) rats using extended access to cocaine self-administration (6 h/daily) and analyzed individual differences in escalation of intake, progressive-ratio (PR) responding, continued use despite adverse consequence (contingent foot shocks), and irritability-like behavior during withdrawal. By principal component analysis, they found that escalation of intake, progressive ratio responding, and continued use despite adverse consequences loaded onto the same factor, whereas irritability-like behaviors loaded onto a separate factor. Characterization of rats in four categories of resilient, mild, moderate, and severe addiction-like phenotypes showed that females had higher addiction-like behaviors, particularly due to a lower number of resilient individuals, than males. The authors suggest that escalation of intake, continued use despite adverse consequences, and progressive ratio responding are highly correlated measures of the same psychological construct and that a significant proportion of males, but not females may be resilient to addiction-like behaviors. The amount of work in this study is impressive, and the results are interesting. However, there are several issues that need to be addressed to improve their manuscript. In particular, the language should be toned down and the statistical analysis approach could be improved.

Strengths: Large dataset. Males and females included.

Weaknesses: Language and statistical analysis can be improved.

Reviewer #1 (Public Review):

The present work establishes 14-3-3 proteins as binding partners of Spastin and suggests that this binding is positively regulated by phosphorylation of Spastin. The authors show evidence that 14-3-3 - Spastin binding prevents Spastin ubiquitination and final proteasomal degradation, thus increasing the availability of Spastin. The authors measured microtubule severing activity in cell lines and axon regeneration and outgrowth as a prompt to Spastin activity. By using drugs and peptides that separately inhibit 14-3-3 binding or Spastin activity, they show that both proteins are necessary for axon regeneration in cell culture and in vivo models in rats.

The following is an account of the major strengths and weaknesses of the methods and results.

Major strengths<br /> -The authors performed pulldown assays on spinal cord lysates using GST-spastin, then analyzed pulldowns via mass spectrometry and found 3 peptides common to various forms of 14-3-3 proteins. In co-expression experiments in cell lines, recombinant Spastin co-precipitated with all 6 forms of 14-3-3 tested.<br /> -By protein truncation experiments they found that the Microtubule Binding Domain of Spastin contained the binding capability to 14-3-3. This domain contained a putative phosphorylation site, and substitutions that cannot be phosphorylated cannot bind to Spastin.<br /> -Spastin overexpression increased neurite growth and branching, and so did the phospho null spastin. On the other hand, the phospho mimetic prevents all kinds of neurite development.<br /> -Overexpression of GFP-Spastin shows a turn-over of about 12 hours when protein synthesis is inhibited by cycloheximide. When 14-3-3 is co-overexpressed, GFP-Spastin does not show a decrease by 12 hours. When S233A is expressed, a turn-over of 9 hours is observed, indicating that the ability to be phosphorylated increases the stability of the protein.<br /> -In support of that notion, the phospho-mimetic S233D makes it more stable, lasting as much as the over-expression of 14-3-3.<br /> -Authors show that Spastin can be ubiquitinated, and that in the presence of ubiquitin, Spastin-MT severing activity is inhibited.<br /> -By combining FCA with Spastazoline, the authors claim that FCA increased regeneration is due to increased Spastin Activity in various models of neurite outgrowth and regeneration in cell culture and in vivo, the authors show impressive results on the positive effect of FCA in regeneration, and that this is abolished when Spastin is inhibited.

Major weaknesses<br /> -However convincing the pull-downs of the expressed proteins, the evidence would be stronger if a co-immunoprecipitation of the endogenous proteins were included.<br /> -To better establish the impact of Spastin phosphorylation in the interaction, there is no indication that the phosphomimetic (S233D) can better bind Spastin, and this result is contradicting to the conclusion of the authors that Spastin-14-3-3 interaction is necessary for (or increases) Spastin function<br /> -To fully support the authors' suggestion that 14-3-3 and Spastin work in the same pathway to promote regeneration, I believe that some key observations are missing.<br /> 1-There is no evidence showing that 14-3-3 overexpression increases the total levels of Spastin, not only its turnover.<br /> 2- There is no indication that increasing the ubiquitination of Spastin decreases its levels. To suggest that proteasomal activity is affecting the levels of a protein, one would expect that proteasomal inhibition (with bortezomib or epoxomycin), would increase its levels.<br /> 3- Authors show that S233D increases MT severing activity, and explain that it is related to increased binding to 14-3-3. An alternative explanation is that phosphorylation at S233 by itself could increase MT severing activity. The authors could test if purified Spastin S233D alone could have more potent enzymatic activity.<br /> -Finally, I consider that there are simpler explanations for the combined effect of FC-A and spastazoline. FC-A mechanism of action can be very broad, since it will increase the binding of all 14-3-3 proteins with presumably all their substrates, hence the pathways affected can rise to the hundreds. The fact that spastazoline abolishes FC-A effect, may not be because of their direct interaction, but because Spastin is a necessary component of the execution of the regeneration machinery further downstream, in line with the fact that spastizoline alone prevented outgrowth and regeneration, and in agreement with previous work showing that normal Spastin activity is necessary for regeneration.

In summary, the evidence of the interaction of 14-3-3 and Spastin is solid, but it is weak with respect to showing evidence for the binding of endogenous proteins in neurons. Another strength of the manuscript is the important recovery of function after spinal cord injury after stimulation of 14-3-3 interactions. Although it is experimentally difficult to demonstrate that the effect of FC-A is due to the prevention of Spastin ubiquitination, the effect itself is very robust and remarkable in vivo.

Reviewer #1 (Public Review):

Summary: In this study, Franke et al. explore and characterize the color response properties across the primary visual cortex, revealing specific color opponent encoding strategies across the visual field. The authors use awake-behaving 2P imaging to define the spectral response properties of visual interneurons in Layer 2/3. They find that opponent responses are more prominent at photopic light levels, and diversity in color opponent responses exists across the visual science, with green ON/ UV OFF responses being stronger represented in the upper visual field. This is argued to be relevant for detecting certain features that are more salient when the chromatic space is used, possibly due to noise reductions.

Strengths: The work is well crafted and written and provides a thorough characterization that reveals an uncharacterized diversity of visual properties in V1. I find this characterization important because it reveals how strongly chromatic information can modulate the response properties in V1. In the upper visual field, 25% of the cells differentially relay chromatic information, and one may wonder how this information will be integrated and subsequently used to aid vision beyond the detection of color per see. I personally like the last paragraph of the discussion that highlights this fact.

Weaknesses:

One major point highlighted in this paper is the fact that Green ON/UV OFF responses are not generated in the retina. But glancing through the literature, I saw this is not necessarily true. Fig 1. of Joesch & Meister, a paper cited, shows this can be the case. Thus, I would not emphasize that this wasn't present in the retina. This is a minor point, but even if the retina could not generate these signals, I would be surprised if the diversity of responses would only arise through feed-forward excitation, given the intricacies of cortical connectivity. Thus, I would argue that the argument holds for most of the responses seen in V1; they need to be further processed by cortical circuitries. This takes me to my second point, defining center and surround. The center spot is 37.5 deg of visual angle, more than 1 mm of the retinal surface. That means that all retinal cells, at least half and most likely all of their surrounds will also be activated. Although 37.5 deg is roughly the receptive field size previously determined for V1 neurons, the one-to-one comparison with retinal recording, particularly with their center/surround properties, is difficult. This should be discussed. I assume that the authors tried a similar approach with sparse or dense checker white noise stimuli. If so, it would be interesting if there were better ways of defining the properties of V1 neurons on their complex/simple receptive field properties to define how much of their responses are due to an activation of the true "center" or a coactivation of the surround. Interestingly, at least some of the cells (Fig. 1d, cells 2 and 5) don't have a surround. Could it be that in these cases, the "center" and "surround" are being excited together? How different would the overall statistics change if one used a full-filed flicker stimulus instead of a center/surround stimulus? How stable are the results if the center/surround flicker stimulus is shifted? These results won't change the fact that chromatic coding is present in the VC and that there are clear differences depending on their position, but it might change the interpretation. Thus, I would encourage you to test these differences and discuss them.

Reviewer #1 (Public Review):

In this work, Dasguta et al. have dissected the role of Sema7a in fine tuning of a sensory microcircuit in the posterior lateral line organ of zebrafish. They attempt to also outline the different roles of a secreted verses membrane-bound form of Sema7a in this process. Using genetic perturbations and axonal network analysis, the authors show that loss of both Sema7a isoforms causes abnormal axon terminal structure with more bare terminals and fewer loops in contact with presynaptic sensory hair cells. Further, they show that loss of Sema7a causes decreased number and size of both the pre- and post-synapse. Finally, they show that overexpression of the secreted form of Sema7a specifically can elicit axon terminal outgrowth to an ectopic Sema7a expressing cell. Together, the analysis of Sema7a loss of function and overexpression on axon arbor structure is fairly thorough and revealed a novel role for Sema7a in axon terminal structure. However, the connection between different isoforms of Sema7a and the axon arborization needs to be substantiated. Furthermore, an autocrine role for Sema7a on the presynaptic cell is not ruled out as a contributing factor to the synaptic and axon structure phenotypes. Finally, critical controls are absent from the overexpression paradigm. These issues weaken the claims made by the authors including the statement that they have identified differential roles for the GPI-anchored verses secreted forms of Sema7a on synapse formation and as a chemoattractant for axon arborization respectively. The manuscript itself would benefit from the inclusion of details in the text to help the reader interpret the figures, tools, data, and analysis.

Reviewer #1 (Public Review):

Summary:<br /> The authors report an fMRI investigation of the neural mechanisms by which selective attention allows capacity-limited perceptual systems to preferentially represent task-relevant visual stimuli. Specifically, they examine competitive interactions between two simultaneously-presented items from different categories, to reveal how task-directed attention to one of them modulates the activity of brain regions that respond to both. The specific hypothesis is that attention will bias responses to be more like those elicited by the relevant object presented on its own, and further that this modulation will be stronger for more dissimilar stimulus pairs. This pattern was confirmed in univariate analyses that measured the mass response of a priori regions of interest, as well as multivariate analyses that considered the patterns of evoked activity within the same regions. The authors follow these neuroimaging results with a simulation study that favours a "tuning" mechanism of attention (enhanced responses to highly effective stimuli, and suppression for ineffective stimuli) to explain this pattern.

Strengths:<br /> The manuscript clearly articulates a core issue in the cognitive neuroscience of attention, namely the need to understand how limited perceptual systems cope with complex environments in the service of the observer's goals. The use of a priori regions of interest, and the inclusion of both univariate and multivariate analyses as well as a simple model, are further strengths. The authors carefully derive clear indices of attentional effects (for both univariate and multivariate analyses) which makes explication of their findings easy to follow.

Weaknesses:<br /> There are some relatively minor weaknesses in presentation, where the motivation behind some of the procedural decisions could be clearer. There are some apparently paradoxical findings reported -- namely, cases in which the univariate response to pairs of stimuli is greater than to the preferred stimulus alone -- that are not addressed. It is possible that some of the main findings may be attributable to range effects: notwithstanding the paradox just noted, it seems that a floor effect should minimise the range of possible attentional modulation of the responses to two highly similar stimuli. One possible limitation of the modelled results is that they do not reveal any attentional modulation at all under the assumptions of the gain model, for any pair of conditions, implying that as implemented the model may not be correctly capturing the assumptions of that hypothesis.

Reviewer #1 (Public Review):

Jafarinia et al. have made an interesting contribution to unravelling the molecular mechanisms underlying pathological phenotypes of repeat expansion of the C9orf72 gene. The repeat expression leads to the expression of polyPR proteins. Using coarse-grained molecular dynamics simulations, the authors identify putative binding partners involved in nucleocytoplasmic transport (NCT), and that conjecture that polyPR affects essential processes by binding to NCT-related proteins. The results are well-reported, but only putative, and need experimental support to be more conclusive. Also, a comparison with results from all-atom MD simulations in explicit water could help verify the results. But even without these, the work is very useful as a first step to unravel the role of polyPR and related peptides.

Reviewer #1 (Public Review):

The goal of the current study was to evaluate the effect of neuronal activity on blood-brain barrier permeability in the healthy brain, and to determine whether changes in BBB dynamics play a role in cortical plasticity. The authors used a variety of well-validated approaches to first demonstrate that limb stimulation increases BBB permeability. Using in vivo-electrophysiology and pharmacological approaches, the authors demonstrate that albumin is sufficient to induce cortical potentiation and that BBB transporters are necessary for stimulus-induced potentiation. The authors include a transcriptional analysis and differential expression of genes associated with plasticity, TGF-beta signaling, and extracellular matrix were observed following stimulation. Overall, the results obtained in rodents are compelling and support the authors' conclusions that neuronal activity modulates the BBB in the healthy brain and that mechanisms downstream of BBB permeability changes play a role in stimulus-evoked plasticity. These findings were further supported with fMRI and BBB permeability measurements performed in healthy human subjects performing a simple sensorimotor task. While there are many strengths in this study, there is literature to suggest that there are sex differences in BBB dysfunction in pathophysiological conditions. The authors only used males in this study and do not discuss whether they would also expect to sex differences in stimulation-evoked BBB changes in the healthy brain. Another minor limitation is the authors did not address the potential impact of anesthesia which can impact neurovascular coupling in rodent studies. The authors could have also better integrated the RNAseq findings into mechanistic experiments, including testing whether the upregulation of OAT3 plays a role in cortical plasticity observed following stimulation. Overall, this study provides novel insights into how neurovascular coupling, BBB permeability, and plasticity interact in the healthy brain.

Reviewer #1 (Public Review):

Summary:

Exposure to cranial irradiation (IR) leads to cognitive deficits in the survivors of brain cancer. IR upregulates miR-206-3p, which in turn reduces the PAK3-LIMK1 axis leading to the loss of F and G-actin ratio and, thereby, mature dendritic spine loss. Silencing miR-206-3p reverses these degenerative consequences.

Strengths:<br /> The authors show compelling data indicating a clear correlation between PAK3 knockdown and the loss of mature dendritic spine density. In contrast, overexpression of PAK3 in the irradiated neurons restored mature spine types and recovered the F/G ratio. These in vitro results support the authors' hypotheses that PAK3 and LIMK1-mediated downstream signaling impact neuronal structure and reorganization in vitro. These data were supported by similar experiments using differentiated human neurons. Importantly, silencing miR-206-30 using antagonist miR also reverses IR-induced downregulation of the PAK3-LIMK1 axis, preventing spine loss and cognitive deficits.

Weaknesses:

All the miR-206-3p data are presented from in vitro cortical neurons or human stem cell-derived neuron cultures. This data (IR-induced elevation of miR-206-3p) should also be confirmed in vivo using an irradiated mouse brain to correlate the cognitive dysfunction timepoint.

Antago-miR-206-3p reversed Ir-induced upregulation of miR-206 (in vitro), and prevent reductions in PAK3 and downstream markers. Importantly, it reversed cognitive deficits induced by IR. This data should be supported by in vivo staining for important dendritic markers, including cofillin, p-cofilin, PSD-95, F- and G-actin within the hippocampal and PFC regions.

Other neuronal and non-neuronal targets of miR-206-3p should be discussed and looked into as a downstream impact of IR-induced functional and physiological impairments in the brain.

Reviewer #1 (Public Review):

The authors investigate pleiotropy in the genetic loci previously associated to a range of neuropsychiatric disorders: Alzheimer's disease, amyotrophic lateral sclerosis (ALS), frontotemporal dementia, Parkinson's disease, and schizophrenia. The local statistical fine-mapping and variant colocalisation approaches they use have the potential to uncover not only shared loci but also shared causal variants between these disorders. There is existing literature describing the pleiotropy between ALS and these other disorders but here the authors apply state of the art, local genetic correlation approaches to further refine any relationships.

Complex disease and GWAS is not my area of expertise but the authors managed to present their methods and results in a clear, easy to follow manner. Their results statistically support several correlations between the disorders and, for ALS and AD, a shared variant in the vicinity of the lead SNP from the original ALS GWAS. Such findings could have important implications for our understanding of the mechanisms of such disorders and eventually the possibility of managing and treating them.

The authors have built a useful pipeline that plugs together all the gold-standard, existing software to perform this analysis and made it openly available which is commendable. However, there is little discussion of what software is available to perform global and local correlation analysis and, if there are multiple tools available, why they consider the ones they selected to be the gold-standard.

There is some mention of previous findings of genetic pleiotropy between ALS and these other disorders in the introduction, and discussion of their improved ALS-AD evidence relative to previous work. However, detailed comparisons of their other correlations to what was described before for the same pairs of disorders (if any) is missing. Adding this would strengthen the impact of this paper.

Finally, being new to this approach I found the abstract a little confusing. Initially, the shared causal variant between ALS and AD is mentioned but immediately in the following sentence they describe how their study "suggested that disease- implicated variants in these loci often differ between traits". After reading the whole paper I understood that the ALS-AD shared variant was the exception but it may be best to restructure this part of the abstract. Additionally, in the abstract the authors state that different variants "suggests the role of distinct mechanisms across diseases despite shared loci". Is it not possible that different variants in the same regulatory region or protein-coding parts of a gene could be having the same effect and mechanism? Or does the methodology to establish that different variants are involved automatically mean that the variants are too distant for this to be possible?

Reviewer #1 (Public Review):

Summary: Chang et al. provide glutamate co-expression profiles in the central noradrenergic system and test the requirement of Vglut2-based glutamatergic release in respiratory and metabolic activity under physiologically relevant gas challenges. Their experiments show that conditional deletion of Vglut2 in NA neurons does not impact steady-state breathing or metabolic activity in room air, hypercapnia, or hypoxia. Their observations challenge the importance of glutamatergic signaling from Vglut2 expressing NA neurons in normal respiratory homeostasis in conscious adult mice.

Strengths: The comprehensive Vglut1, Vglut2, and Vglut3 co-expression profiles in the central noradrenergic system and the combined measurements of breathing and oxygen consumption are two major strengths of this study. Observations from these experiments provide previously undescribed insights into (1) expression patterns for subtypes of the vesicular glutamate transporter protein in the noradrenergic system and (2) the dispensable nature of Vglut2-dependent glutamate signaling from noradrenergic neurons to breathing responses to physiologically relevant gas challenges in adult conscious mice.

Weaknesses: Although the cellular expression profiles for the vesicular glutamate transporters are provided, the study fails to document that glutamatergic-based signaling originating from noradrenergic neurons is evident at the cellular level under normal, hypoxic, and/or hypercapnic conditions. This limits the reader's understanding of why conditional Vglut2 knockdown is dispensable for breathing under the conditions tested.

Reviewer #1 (Public Review):

Qin et al., demonstrate, convincingly, that plasticity of ocular dominance of binocular neurons in the visual thalamus persists in adulthood. The adult plasticity is similar to that described in critical period juveniles in that it is absent in transgenic mice with the deletion of the GABA a1 receptor in thalamus, which also blocks ocular dominance plasticity in primary visual cortex. However, the adult plasticity is not dependent on feedback from primary visual cortex, an important difference from juveniles. These findings are an important contribution to a growing body of work identifying plasticity in the adult visual system, and identifies the visual thalamus as a potential target for therapies to reverse adult amblyopia.

Reviewer #1 (Public Review):

This manuscript by Xu and colleagues addresses the important question of how multi-modal associations are encoded in the rodent brain. They use behavioral protocols to link stimuli to whisker movement and discover that the barrel cortex can be a hub for associations. Based on anatomical correlations, they suggest that structural plasticity between different areas can be linked to training. Moreover, they provide electrophysiological correlates that link to behavior and structure. Knock-down of nlg3 abolishes plasticity and learning.

This study provides an important contribution as to how multi-modal associations can be formed across cortical regions.

Reviewer #1 (Public Review):

Meta-cognition, and difficulty judgments specifically, is an important part of daily decision-making. When facing two competing tasks, individuals often need to make quick judgments on which task they should approach (whether their goal is to complete an easy or a difficult task).

In the study, subjects face two perceptual tasks on the same screen. Each task is a cloud of dots with a dominating color (yellow or blue), with a varying degree of domination - so each cloud (as a representation of a task where the subject has to judge which color is dominant) can be seen an easy or a difficult task. Observing both, the subject has to decide which one is easier.

It is well-known that choices and response times in each separate task can be described by a drift-diffusion model, where the decision maker accumulates evidence toward one of the decisions ("blue" or "yellow") over time, making a choice when the accumulated evidence reaches a predetermined bound. However, we do not know what happens when an individual has to make two such judgments at the same time, without actually making a choice, but simply deciding which task would have stronger evidence toward one of the options (so would be easier to solve).

It is clear that the degree of color dominance ("color strength" in the study's terms) of both clouds should affect the decision on which task is easier, as well as the total decision time. Experiment 1 clearly shows that color strength has a simple cumulative effect on choice: cloud 1 is more likely to be chosen if it is easier and cloud 2 is harder. Response times, however, show a more complex interactive pattern: when cloud 2 is hard, easier cloud 1 produces faster decisions. When cloud 2 is easy, easier cloud 1 produces slower decisions.

The study explores several models that explain this effect. The best-fitting model (the Difference model is the paper's terminology) assumes that the decision-maker accumulates evidence in both clouds simultaneously and makes a difficulty judgment as soon as the difference between the values of these decision variables reaches a certain threshold. Another potential model that provides a slightly worse fit to the data is a two-step model. First, the decision maker evaluates the dominant color of each cloud, then judges the difficulty based on this information.

Importantly, the study explores an optimal model based on the Markov decision processes approach. This model shows a very similar qualitative pattern in RT predictions but is too complex to fit to the real data. Possibly, the fact that simple approaches such as the Difference model fit the data best could suggest the existence of some cognitive constraints that play a role in difficulty judgments and could be explored in future research.

The Difference model produces a well-defined qualitative prediction: if the dominant color of both clouds is known to the decision maker, the overall RT effect (hard-hard trials are slower than easy-easy trials) should disappear. Essentially, that turns the model into the second stage of the two-stage model, where the decision maker learns the dominant colors first. The data from Experiment 2 impressively confirms that prediction and provides a good demonstration of how the model can explain the data out-of-sample with a predicted change in context.

Overall, the study provides a very coherent and clean set of predictions and analyses that advance our understanding of meta-cognition. The field would benefit from further exploration of differences between the models presented and new competing predictions (for instance, exploring how the sequential presentation of stimuli or attentional behavior can impact such judgments). Finally, the study provides a solid foundation for future neuroimaging investigations.

Reviewer #1 (Public Review):

The authors focused on genetic variability in relation to insulin resistance. They used genetically different lines of mice and exposed them to the same diet. They found that genetic predisposition impacts the overall outcome of metabolic disturbances. This work provides a fundamental novel view on the role of genetics and insulin resistance.

Reviewer #1 (Public Review):

Summary:<br /> The authors measured the oxygen stable isotope ratios in six orangutan teeth using a state-of-the-art micro-sampling technique (SHRIMP SI) to gather substantial multi-year isotopic data for six modern and five fossil orangutan individuals from Borneo and Sumatra. This fine-scale sampling technique allowed them to address the fundamental question of whether breastfeeding affects the oxygen isotope ratios in teeth forming in the first one to two years of life, during which orangutans are assumed to largely depend on breastmilk. The authors provide compelling evidence that the consumption of milk does not appear to affect the overall isotopic profile in early-forming teeth. They conclude that this allows us to use these teeth as terrestrial/arboreal isotopic proxies in paleoenvironmental research, which would provide an invaluable addition to otherwise largely marine climate records in these regions.

Strengths:<br /> The overall large sample size of orangutan dental isotope records as well as the rigorous dating of the fossil specimens provide a strong dataset for addressing the outlined questions. The direct comparison of modern and fossil orangutan specimens provides a valuable evaluation of the use of these modern and past environmental proxies, with some discussion of the implications for the environmental conditions during the expansion of early modern humans into this region of the world.

Weakness:<br /> Although the overall conclusions of this paper are well supported and discussed, one important aspect could have more detailed consideration: the ecology and behavior of orangutans. As one example, orangutans are almost exclusively (~96%) arboreal creatures foraging for plant foods in the forest canopy, and as such they mostly meet their water requirements from the plants they eat, only very rarely drinking surface water (Ashbury et al. 2015). As a result, all orangutan water and foods are strongly affected by the so-called canopy effect, which could have found stronger consideration in this study. The canopy effect in primate plant foods has been demonstrated to easily exceed 5‰ within the same forest canopy and even within the same tree, mainly depending on stratigraphy/height (Lowry et al. 2021). This variation may explain the noise in the isotopic data within a given orangutan tooth, which lies well within this 5% range, and could easily obscure any possible breastfeeding effect in dental isotope ratios. If the canopy effect may indeed introduce so much noise in the oxygen isotope data, this should be also considered in the use of the data as a climate proxy. The question arises if a terrestrial long-lived mammal species may be a more suitable proxy than an arboreal one.

Reviewer #1 (Public Review):

Summary:<br /> Radial spokes (RS) are made of >20 proteins and are believed to be a transducer to coordinate axonemal dyneins to enable the beating motion of motile cilia. While the atomic structure of RS from green algae Chlamydomonas and H. Sapience has been solved by single particle cryo-EM recently, this work by Bicka et al. provided the atomic structure of RS from ciliate Tetrahymena. They identified component proteins of Tetrahymena RS, which correspond to those in the atomic structure of Chlamydomonas and human RS. These proteins were likely already guessed as RS components, based on sequence similarity, but in this work experimentally identified for the first time. Furthermore, they discovered novel isoforms of RS proteins and characterized them structurally and functionally. RSP3 has three isoforms (A, B, and C). They are distributed specifically in the three radial spokes within the repeating unit as proved by mutant analysis, cryo-EM, and proteomics. By high-speed video microscopy, they proved the essential roles of RSP3B for ciliary beating. These isoforms have never been reported in past works and this demonstrates the novelty of this work.

Strength:<br /> Their discovery of RSP3 isoforms is unexpected and, although it is still not clear why Tetrahymena needs to have these isoforms, will evoke future research. The authors characterized the multi-facet aspects of these proteins precisely, structurally by cryo-EM, functionally by waveform and velocity analysis, and in terms of protein networking by co-IP and bioID studies.

Weakness:<br /> While the first half of this manuscript about RSP3 isoforms is very well organized and described (this reviewer still has some advice to make this story convincing and attractive), the later part has room for improvement. Some results are presented in the current manuscript without mentioning figures or tables, for example in "250: The components of the Tetrahymena radial spoke stalks" no figure/table is cited. There is also inconsistency - in 327 RSP9 is mentioned as a MORN protein, but in Fig.6 Sup.3 Table.1, it is mentioned as "unknown".

Reviewer #1 (Public Review):

The authors aim to theoretically explain the wide range of time scales observed in cortical circuits in the brain -- a fundamental problem in theoretical neuroscience. They propose that the variety of time scales arises in recurrent neural networks with heterogeneous units that represent neuronal assemblies of different sizes that transition through sequences of high- and low-activity metastable states. When transitions are driven by intrinsically generated noise, the heterogeneity leads to a wide range of escape times (and hence time scales) across units. As a mathematically tractable model, they consider a recurrent network of heterogeneous bistable rate units in the chaotic regime. The model is an extension of the previous model by Stern et al (Phys. Rev. E, 2014) to the case of heterogeneous self-coupling parameters. Biologically, this heterogeneous parameter is interpreted as different assembly sizes. The chaoticity acts as intrinsically generated noise-driving transitions between bistable states with escape times that are indeed widely distributed because of the heterogeneity. The distribution is successfully fitted to experimental data. Using previous dynamic mean-field theory, the self-consistent auto-correlation function of the driving noise in the mean-field model is computed (I guess numerically). This leaves the theoretical problem of calculating escape times in the presence of colored noise, which is solved using the unified colored-noise approximation (UCNA). They find that the log of the correlation time of a given unit increases quadratically with the self-coupling strength of that unit, which nicely explains the distribution of time scales over several orders of magnitude. As a biologically plausible implementation of the theory, they consider a spiking neural network with clustered connectivity and heterogeneous cluster sizes (extension of the previous model by Mazzucato et al. J Neurosci 2015). Simulations of this model also exhibit a quadratic increase in the log dwell time with cluster size. Finally, the authors demonstrate that heterogeneous assemblies might be useful to differentially transmit different frequency components of a broadband stimulus through different assemblies because the assembly size modulates the gain.

I found the paper conceptually interesting and original, especially the analytical part on estimating the mean escape times in the rate network using the idea of probe units and the UCNA. It is a nice demonstration of how chaotic activity serves as noise-driving metastable activity. Calculating the typical time scales of such metastable activity is a hard theoretical problem, for which the authors made considerable advancement. The conclusions of this paper are mostly well supported by simulations and mathematical analysis, but some aspects need to be clarified and extended, especially concerning the biological plausibility of the rate network model and its relation to the spiking neural network model as well as the analytical calculation of the mean dwell time.

1) The theory is based on a somewhat unbiological network of bistable rate units. It seems to only loosely apply to the implementation with a spiking neural network with clustered architecture, which is used as a biological justification of the rate model. In the spiking model, a wide distribution of time scales also emerges as a consequence of noise-induced escapes in combination with heterogeneity. Apart from this analogy, however, the mechanisms for metastability seem to be quite different: firstly, the functional units in the spiking neural network are presumably not bistable themselves but multistability only emerges as a network effect, i.e. from the interaction with other assemblies and inhibitory neurons. (This difference yields anti-correlations between assemblies in the spiking model, in marked contrast to the independence of bistable rate units (if N is large).) Secondly, transitions between metastable states are presumably not driven by chaotic dynamics but by finite-size fluctuations (e.g. Litwin-Kumar & Doiron 2012). The latter is also strongly dependent on assembly size. More precisely, the mechanism of how assembly size shapes escape times T seems to be different: in the rate model the self-coupling ("assembly size") predominantly affects the effective potential, whereas in the spiking network, the assembly size predominantly affects the noise.

Furthermore, the prediction of the rate model is a quadratic increase of log(T), however, the data shown in Fig.5b do not seem to strongly support this prediction. More details and evidence that the data "was best fit with a quadratic polynomial" would be necessary to test the theoretical prediction. Therefore, the correspondence between the rate model and the spiking model should probably be regarded in a looser sense than presented in the paper.

2) The time scale of a bistable probe unit driven by network-generated "noise" is taken to be the mean dwell time T (mean escape time) in a metastable state. It seems that the expressions Eq.4 and Eq.21 for this time are incorrect. The mean dwell time is given by the mean first-passage time (MFPT) from one potential minumum to the opposite one including the full passage across the barrier. At least, the final point for the MFPT should be significantly beyond the barrier to complete the escape. However, the authors only compute the MFPT to a location -x_c slightly before the barrier is reached, at which point the probe unit has not managed to escape yet (e.g. it could go back to -x_2 after reaching -x_c instead of further going to +x_2). It is not clear whether the UCNA can be applied to such escape problems because it is valid only in regions, where the potential is convex, and thus the UCNA may break down near the potential barrier. Indeed, the effective potential is not defined near the barrier (see forbidden zone in Fig.4b), and hence it is not clear how to calculate the mean escape time. Nonetheless, the incomplete MFPT computed by the authors seems to qualitatively predict the dependence on the self-coupling parameter s, at least in the example of Fig.4c. However, if the incomplete MFPT is taken as a basis, then the incomplete MFPT should also be used for the white-noise case for a fair comparison. It seems that the corresponding white-noise case is given by Eq.4 with tau_1=0, which still has the same dependence on the self-coupling s_2, contrary to what is claimed in the paper (it is unclear how the curve for the white-noise case in Fig.4 was obtained). Note that the UCNA has been designed such that it is valid for both small and large tau_1 (thus, it is also unclear why the assumption of large tau_1 is needed).

3) The given argument that the time-scale separation arises as network effect is not very clear. Apart from the issue of a fair comparison of colored and white noise raised in point 1 above, an external colored noise with matched statistics that drives a single bistable unit would yield the same MFPT and thus would be an alternative explanation independent of the network dynamics.

4) The UCNA has assumptions and regimes of validity that are not stated in the paper. In particular, it assumes an Ornstein-Uhlenbeck noise, which has an exponential auto-correlation function, and local stability (region where potential is convex). Because the self-consistent auto-correlation function is generally not exponential and the probe unit also visits regions where the potential is concave, the validity of the UCNA is not clear. On the other hand, the assumption of large correlation time might be dropped as the UCNA's main feature is that it works for both large and small correlation times.

Reviewer #1 (Public Review):

In this work, the authors were aiming to probe why enhancers tend to have multiple binding sites for the same transcription factor (TF). As a test bed, they use the snail distal enhancer, which drives a band of expression in the early Drosophila embryo and is composed of multiple, generally weak binding sites for several activating TFs. Using the MS2-MCP reporter system, the authors characterize the live mRNA dynamics driven by the wild-type and mutant enhancers, in which individual or pairs of binding sites have been deleted. They complement these experimental measurements with two computational models - a simple thermodynamic model to explore the cooperativity of TF binding to enhancers and a Hidden Markov Model to analyze the kinetic parameters of their dynamic measurements. The key finding from the experiments is that ablating any of several TF binding sites individually or in pairs dramatically reduces the expression levels, though not the spatial extent, of the snail distal enhancer. This effect holds true in a ~600 bp minimal enhancer and a ~1800 bp extended enhancer. The bulk of this effect is due to a marked decrease in transcriptional amplitude. A simple thermodynamic model confirms the intuition that synergy between the TF binding sites can explain the experimental results and further analysis shows that the modest decline in transcriptional burst duration in mutant enhancers is likely due to more frequent dissociation of the enhancer-promoter complex.

The paper's strengths include the use of well-established measurement and analysis techniques to uncover the surprisingly dramatic effect of single TF binding site mutations, even in the extended enhancer which contains ~20 TF binding sites. This work starts to chip away at the question of why multiple TF binding sites are so frequently observed in enhancers and complement studies of other similar enhancers. It is likely to be of interest to the enhancer biology community. It also sets the stage to explore whether this observation will generalize to other enhancers with different properties, e.g. those with stronger TF binding sites or whose activity is more strongly shaped by repressive TFs.

Reviewer #1 (Public Review):

In this manuscript, the authors investigated plausible circuit mechanisms for their recently reported effect of NMDAR antagonists on the synchrony of prefrontal neurons in a cognitive task. On the basis of previously proposed computational network models of spiking excitatory and inhibitory neurons and their mean-field and linear stability analysis descriptions, they show that a specific network configuration set close to the onset of instability of the asynchronous state can replicate qualitatively key empirical observations. For such a network, a small increase in external drive causes a large increase in neuronal synchrony, and this is not happening if NMDAR-dependent transmission is reduced. This shows parallelism with the empirical data thus representing its first neural network explanation.

The paper provides valuable insights into possible mechanisms related to cortical dysfunction under NMDAR hypofunction, a topic of importance for several neuropsychiatric disorders. However, the fact that the manuscript remains at a rather abstract level and does not attempt a closer match to the experimental data is a limitation of the study.

1) The manuscript is strongly based on state diagrams and parametric descriptions of neural dynamics in a computational model that has been extensively studied before (Brunel, Wang 2003). Many of the parametric dependencies of this model shown here were already reported before, although not specifically altering concurrently external inputs and NMDAR-dependent transmission as done now. The main novelty of the study is the application of this framework to a specific empirical dataset of great scientific relevance. However, the manuscript emphasizes the model exploration in relation to a limited set of effects in the data (changes in synchrony immediately before motor response) and not so much the comparison to the neural recordings more generally (for instance, firing rates, other time periods in the task, etc.)

2) As discussed in the introduction, empirical data available suggests that 0-lag synchrony in prefrontal networks is affected by manipulations that reduce NMDAR function (Zick et al. 2018) and by manipulations that enhance NMDAR function (Zick et al. 2021). The computational model presented in this manuscript does not show this U-shaped behavior and the discussion does not mention this. It should be discussed whether the model can accommodate this or not.

Reviewer #1 (Public Review):

Esmaily and colleagues report two experimental studies in which participants make simple perceptual decisions, either in isolation or in the context of a joint decision-making procedure. In this "social" condition, participants are paired with a partner (in fact, a computer), they learn the decision and confidence of the partner after making their own decision, and the joint decision is made on the basis of the most confident decision between the participant and the partner. The authors found that participants' confidence, response times, pupil dilation, and CPP (i.e. the increase of centro-parietal EEG over time during the decision process) are all affected by the overall confidence of the partner, which was manipulated across blocks in the experiments. They describe a computational model in which decisions result from a competition between two accumulators, and in which the confidence of the partner would be an input to the activity of both accumulators. This model qualitatively produced the variation in confidence and RTs across blocks.

The major strength of this work is that it puts together many ingredients (behavioral data, pupil and EEG signals, computational analysis) to build a picture of how the confidence of a partner, in the context of joint decision-making, would influence our own decision process and confidence evaluations. Many of these effects are well described already in the literature, but putting them all together remains a challenge. However, the construction is fragile in many places: the causal links between the different variables are not firmly established, and it is not clear how pupil and EEG signals mediate the effect of the partner's confidence on the participant's behavior.

Finally, one limitation of this setting is that the situation being studied is very specific, with a joint decision that is not the result of an agreement between partners, but the automatic selection of the most confident decisions. Thus, whether the phenomena of confidence matching also occurs outside of this very specific setting is unclear.

Joint Public Review

This manuscript utilizes Drosophila melanogaster as a model system to functionally characterize the role of genes previously associated with obstructive pulmonary disease (COPD) in epithelial barrier function. Using genetic and imaging approaches, the authors characterised a previously unrecognised role of intestinal Acetylcholine receptor (AchR) signalling, in the regulation of epithelial barrier function. The working model proposes that Acetylcholine (Ach) produced by enteroendocrine cells (EEs) and enteric neurons signals to AchR in enterocytes (ECs). This signalling activates the secretion of the Peritrophic membrane (PM) through the regulation of the exocytic protein Syt4. In this way, Ach/AchR signalling works to protect epithelial barrier function and organismal tolerance to ingested damaging agents, such as those causing oxidative stress.

Overall, the data presented support the main model of the paper: EC AchR activation is necessary to maintain epithelial barrier function. The evidence, however, on the mechanisms downstream of AchR, namely, the involvement of this signalling pathway in the regulation of Syt4 is weak.

The work in this manuscript represents an important proof of concept for the use of the Drosophila midgut as a model to functionally interrogate genes from human genetic association studies in pathologies affecting epithelial homeostasis.

Reviewer #1 (Public Review):

Mano et. al. use a combination of behavioral, genetic silencing, and functional imaging experiments to explore the temporal properties of the optomotor response in Drosophila. They find a previously unreported inversion of the behavior under high contrast and luminance conditions and identify potential pathways mediating the effect.

Strengths:<br /> Quantifications of optomotor behavior have been performed for many decades. Despite a large number of previous studies, the authors still find something fundamentally novel: under high contrast conditions and extended stimulation periods, the behavior becomes dynamic over time. The turning response shows an initial transient positive following response. The amplitude of the behavior then decreases and even inverts such that animals show an anti-directional rotation response. The authors systematically explore the stimulation feature space, including large ranges of spatial and temporal frequencies and conditions with high and low contrast. They also test two wild-type fly species and even compare experiments across two different labs and setups. From these data, it seems clear that the behavior is robust and largely depends on the brightness of the stimulation, rearing conditions, and genetic background. The authors discuss that these effects have not clearly been reported elsewhere beforehand, and convincingly argue why this may be the case.

In general, the presented behavioral quantifications illustrate the importance of further experimental studies of the temporal dynamics of behavior in response to dynamically varying stimulus features, across different stimulus types, genetic backgrounds, and model animal systems. It also illustrates the importance of relating the conditions that animals experience in the laboratory to the ones they would experience in the wild. As the authors mention, the brightness during a sunny day can reach values as high as 4000 cd/m2, while experimental stimulation in the lab has so far often been orders of magnitude below that.

The study then systematically explores potential neural elements involved in the behavior. Through a set of silencing experiments, they find that T4 and T5 neurons, as expected, are required for motion behaviors. On the other hand, silencing HS cells largely abolishes the 'classical' syn-directional response but leaves anti-directional turning intact. On the other hand, silencing CH cells abolishes the anti-directional response but leaves the syn-directional behavior intact. Through functional imaging in T4, T5, HS, and CH neurons, the authors could show that none of these neurons shows a response inversion depending on contrast level. Together, these experiments nicely illustrate that the dynamics do not seem to be computed within the early parts of visual processing, but they must happen on the level of the lobula plate or further downstream.

Weaknesses:<br /> While the authors have already explored various parameters of the experiment, it would have been nice to see additional experiments regarding the initial adaptation phase. The experiments in Figure 2e, where the authors show front-to-back or back-to-front gratings before the rotation phase, are a good start. What would the behavioral dynamics look like if they had exposed animals to long periods of static high or low contrast gratings, whole field brightness, or darkness? Such experiments would surely help to better understand the stimulus features on which the adaptation elements operate. It would be interesting to explore to what degree such static stimuli impact the subsequent behavioral dynamics.

Given the dynamics of the behavior, it would probably also be worth looking at the turning dynamics after the stimulus has stopped. If direction-selective adaptation mechanisms are regulating the turning response, one may find long-lasting biases even in the absence of stimulation. If the authors have more data after the stimulus end, it would be good to further expand the time range by a few seconds to show if this is the case or not (for example, in Figure 1b).

Another important experiment could be to initially perform experiments in a closed-loop configuration, and then quickly switch to open-loop. The closed-loop configuration should allow the motion computing circuitry to adapt to the chosen environmental conditions. Explorations of the changes in turning response dynamics after such treatments should then enable further dissections of the mechanisms of adaptation. Closed-loop experiments under different contrast conditions have already been performed (for example, Leonhardt et al. 2016), which also showed complex response dynamics after stimulus on- and offset. It would be great to discuss the current open-loop experiments, and maybe some new closed-loop results, in relation to the previous work.

The authors mention the different rearing conditions, and there is one experiment in Figure S2 which mentions running experiments at 25 deg C. But it is not clear from the Methods at which temperature all other experiments have been performed. It is also not clear at which temperature the shibire block experiments were performed. As such experiments require elevated temperatures, I assume that all behavioral experiments have been performed at such levels? How high were those?

What does the fly see before and after the stimulus (i.e. the gray boxes in all figures)? Are these periods of homogenous gray levels or are these non-moving gratings with the luminance and contrast of the subsequent stimulus? It would be important to add this information to the methods and to the figure illustrations or legends.

It would be nice to discuss the potential location where the motion adaptation may be implemented in the brain. A small model scheme as an additional figure could further help to discuss how such computations may be mechanistically implemented, helping readers to think about future experimental dissections of the behavior.

For setting up similar experiments in other labs, the authors need to better describe how they measured the luminance of the arena. Do they simply report the brightness delivered by the Lightcrafter system, or did they measure this with a lux-meter? If so, at which distance was the measurement performed and with which device? Given that the behavior is sensitive to the specific properties of the stimulus, it will be important to report these numbers carefully to enable other groups to reproduce effects.

Reviewer #1 (Public Review):

In this work, Cheikh et al. develop a novel method to probe tissue mechanics in vivo, with particular application to the early Drosophila embryo. The method is based on filling a pulled micropipette with a mixture of fluorescent dye and PDMS, which is cured and allowed to harden. Etching away the tip of the glass micropipette leaves exposed the PDMS core, which, like the bristles held in a brush handle, is easily deformed. Calibration of the stiffness of the PDMS tip allows for direct measurement of forces through the tip displacement. Apart from the particular application here, this method should prove to be widely useful in biological physics.

The authors then inserted this force probe into Drosophila embryos at the stage when cellularization has occurred, and demonstrate the ability to deform the tissue (visualized by fluorescently labelled cell walls). Crucially, the time course of the deformation can be controlled by the rate at which the pipette is translated, allowing for the study of potential viscous or viscoelastic effects.

The authors find from their experiments and extensive computational analysis of mechanical models of the embryo that there must be a significant difference between the mechanical properties of the apical and basal sides of the tissue.

This is a very well executed paper that provides compelling evidence for the utility of the experimental method and the particular issues in Drosophila mechanics. A strength of the paper is the clear and simple focus on a particular deformation and its experimental and theoretical analysis. The computational section is a bit less clearly connected to the observations, in the sense that some kind of very simplified model incorporating the apicobasal differences is lacking.

Reviewer #1 (Public Review):

In this study, the authors investigate the interactions between Plasmodium falciparum RH5, an essential ligand mediating erythrocyte invasion by the malaria parasite, and its cognate receptor basigin. Based on published observations that basigin forms complexes with the plasma membrane Ca2+-ATPase PMCA1/4 or monocarboxylate transporter MCT1, the authors asked whether RH5 can interact with basigin complexed with PMCA or MCT1, whether this modulates the function of PMCA and whether these interactions may explain the mechanism of action of neutralising antibodies targeting RH5. The objectives and rationale of the study are very clear.

Using size exclusion chromatography, 2D blue native PAGE, antibody shift, and depletion assays, the authors demonstrate that native basigin in human erythrocytes is essentially found in heteromeric complexes with either PMCA4 or MCT1. They measured the binding of PfRH5 to purified basigin-PMCA and basigin-MCT1 complexes by surface plasmon resonance and found that RH5 interacts with complexed basigin with higher affinity than with isolated basigin. RH5 did not alter the ATPase activity of PMCA, either in purified PMCA-basigin complexes or in CHO cells expressing human basigin and PMCA4, leading the authors to rule out RH5-mediated alteration of PMCA-mediated calcium export as a mechanism underlying the changes in calcium flux at the interface between the erythrocyte and the invading parasite. Finally, the authors used structural modelling to show that growth-inhibitory antibodies sterically block the binding of RH5 to basigin-PMCA and basigin-MCT1 complexes, providing a molecular explanation for why most potent anti-RH5 neutralising antibodies do not prevent RH5 binding to isolated basigin.

The paper is well-written and the claims are well-supported by the data. The study provides new insight into an essential interaction during blood-stage malaria and reveals the mode of action of growth-inhibitory antibodies, with potential implications for the design of RH5-based malaria vaccines. The study does not address whether PMCA and MCT1 are required during erythrocyte invasion by P. falciparum merozoites, and does not provide direct evidence to completely rule out a role of RH5-PMCA interaction in calcium flux modulation in the context of erythrocyte invasion by the parasite.

Reviewer #1 (Public Review):

Summary:<br /> The study assesses the impact of testing contacts of cases in school classes when identified, rather than at the end of quarantine, on various outcomes such as secondary infections, tracing delay, and identification of the possible source of infection. The authors find that the intervention likely reduced tracing delay and increased the number of possible infection sources. However, due to unmeasured confounding, it remains unclear if secondary transmission actually decreased. The analysis requires clarification and further explanation in parts.

Major strengths and weaknesses:<br /> The study benefits from the assessment of various outcomes in contact tracing in addition to changes in transmission, such as tracing delay, and the identification of putative infectors; however the assumption that other cases found in households are infectors of the index case rather than putative infectees, may introduce significant bias, but this is not mentioned in the Discussion despite being significant. It is difficult to understand the intervention in Figure 1 due to unclear labelling and incomplete descriptions in the caption. The authors mention that the same school class could be included multiple times for multiple outbreaks - was there a time cutoff for inclusion? I had a lot of trouble interpreting or reproducing the values given in Table 1. Firstly, the methods used to produce the RRs given are not described in the methods section of the paper. What are the outcomes - "classes" and "indexes" are poroly defined. Is this output from univariate or multivariate regression model, and what is the link function? I was also unable to reproduce the RRs listed in the table despite attempting several methods. The closest numbers I achieved were by crudely dividing the risks (e.g. for the RR for known infection source I took the ratio of indexes for which a school contact was suspected pre and post-intervention (644/1175)/(146/429) = 1.61), but if this is the case then the unknown class is by definition not the reference category. This is the same for the other RRs stated in the table. The methods used should be clarified and results updated if erroneous. The mediation analysis components and their relevance to the study could be better explained in the methods and results.

Achievement of aims and support for conclusions:<br /> The authors partially achieved their aims by demonstrating a likely decrease in tracing delay and an increase in possible infection sources. However, the study's inability to determine if secondary transmission decreased due to unmeasured confounding limits the conclusiveness of the findings. The authors should reiterate the main numerical results in the first few paragraphs of the discussion.

Impact on the field and utility of methods and data:<br /> This study has the potential to impact the field by highlighting the benefits of testing contacts earlier in school classes. The findings on reduced tracing delay and increased identification of infection sources can inform future strategies and interventions. However, clarity on the analysis methods, as well as the results, are necessary to ensure the utility and reliability of the findings.

Reviewer #1 (Public Review):

Briggs et al use a combination of mathematical modelling and experimental validation to tease apart the contributions of metabolic and electronic coupling to the pancreatic beta cell functional network. A number of recent studies have shown the existence of functional beta cell subpopulations, some of which are difficult to fully reconcile with established electrophysiological theory. More generally, the contribution of beta cell heterogeneity (metabolism, differentiation, proliferation, activity) to islet function cannot be explained by existing combined metabolic/electrical oscillator models. The present studies are thus timely in modelling the islet electrical (structural) and functional networks. Importantly, the authors show that metabolic coupling primarily drives the islet functional network, giving rise to beta cell subpopulations. The studies, however, do not diminish the critical role of electrical coupling in dictating glucose responsiveness, network extent as well as longer-range synchronization. As such, the studies show that islet structural and functional networks both act to drive islet activity, and that conclusions on the islet structural network should not be made using measures of the functional network (and vice versa).

Strengths:

- State-of-the-art multi-parameter modelling encompassing electrical and metabolic components.

- Experimental validation using advanced FRAP imaging techniques, as well as Ca2+ data from relevant gap junction KO animals.

- Well-balanced arguments that frame metabolic and electrical coupling as essential contributors to islet function.

- Likely to change how the field models functional connectivity and beta cell heterogeneity.

Weaknesses:

- Limitations of FRAP and electrophysiological gap junction measures not considered.

- Limitations of Cx36 (gap junction) KO animals not considered.

- Accuracy of citations should be improved in a few cases.

Reviewer #1 (Public Review):

Notwithstanding that the molecular underpinnings of the mechanistic target of rapamycin complex 1 (mTORC1) signaling are relatively well understood, quantitative data pertinent to mTORC1-dependent integration of a variety of stimuli is lacking. To address this question, Sparta et al., developed a series of fluorescent reporters that in combination with live cell microscopy allowed them to determine responses of mTORC1 to several stimuli including glucose, amino acids, and insulin at the single cell resolution. Considering the central role of mTORC1 in homeostasis and its dysregulation across a variety of pathological states, it was thought that this study should be of broad interest to a wide spectrum of biomedical disciplines ranging from biochemistry, molecular and cellular biology to neurobiology and cancer research.

Strengths: This study employs powerful approach based on use of live cell imaging of multiple fluorescent reports that are indicative of alterations in mTORC1 activity. In contrast to traditional approaches based on querying phosphorylation status of mTORC1 substrates by Western blotting this approach allows time-resolved measurement of mTORC1 activity at the single cell resolution. Using this approach, the authors provide solid evidence to corroborate a model of graded activation of mTORC1 by amino acids, insulin, and combination thereof.

Weaknesses: The major weaknesses were thought to be related to the interpretation of the current model of mTORC1 regulation as AND gate and reliance on a single cell line. Some minor technical issues were also observed pertinent to the lack of controls demonstrating the effectiveness of manipulations of nutrients and/or insulin as well as the effects of such manipulation on the expression of reporters used to monitor mTORC1 activity.

Reviewer #1 (Public Review):

This paper presents extensive numerical simulations using a model that incorporates up to second-order epistasis to study the joint effects of microscopic epistasis and clonal interference on the evolutionary dynamics of a microbial population. Previous works that explicitly modeled microscopic epistasis typically assumed strong selection & weak mutation (SSWM), a condition that is generally not met in real-life evolutionary processes. Alternatively, another class of models coarse-grained the effects of microscopic epistasis into a generic distribution of fitness effects. The framework introduced in this paper represents an important advance with respect to these previous approaches, allowing for the explicit modeling of microscopic epistasis in non-SSWM scenarios. The modeling framework presented promises to be a valuable tool to study microbial evolution in silico.