Reviewer #1 (Public Review):

In this manuscript, the authors are building on their previous work showing Delta-Notch regulates the entrance and exit from embryo-larval quiescence of neural stem cells of the central brain (called CB neuroblasts (NB) (PMID: 35112131)). Here they show that continuous depletion of Notch in NBs from early embryogenesis leads to cycling NBs in the adult. This - cycling NBs in the adult - is not seen in controls. The assumption here is that these Notch-RNAi NBs in adults are those that did not undergo terminal differentiation in pupal development. The authors show that Notch is activated by its ligand Delta which is expressed on the GMC daughter cell and on cortex glia. They determine that the temporal requirement for Notch activity is 0-72 hours after larval hatching (ALH) (i.e., 1st instar through mid-3rd instar at 25C). In NBs/GMCs depleted for Notch, early temporal markers were still expressed at time points when they should be off and late markers were delayed in expression. These effects were observed in ~20-40% of NBs (Figures 5 and 6). Through mining existing data sets, they found that the early temporal factor Imp - an RNA binding protein - can bind Delta mRNA. They state that Delta transcripts decrease over time (without any reference to a Figure or to published work), leading to the hypothesis that Delta mRNA is repressed by the late temporal factors. Over-expressing late factors Syp or E93 earlier in development leads to downregulation of a Delta::GFP protein trap. These results lead to a model in which Notch regulates expression of early temporal factors and early temporal factors regulate Notch activity through translation of Delta mRNA.

There are several strengths of this study. The authors report rigorous measurements and statistical analyses throughout the study. Their conclusions are appropriate for the results. Data mining revealed an important mechanism - that Imp binds Delta mRNA - supporting the model that early temporal factors promote Delta expression, which in turn promotes Notch signaling.

There are also several weaknesses:<br /> 1. The activation of Notch in NBs by Delta in GMCs was already shown by this group in their Dev 2022 paper, reducing some of the impact of this study.<br /> 2. The authors do not explain their current results in context of their prior paper (2022 Dev) until the Discussion, but this would be useful to read in the Introduction. Similarly, it would be good to mention that in the 2022 paper, they find a significant number of wor>Notch RNAi NBs at 2 AHL that are cycling. Are the adult Notch RNAi in this study descended from those NBs at 2 hours ALH in the 2022 study? In other words, how does the early requirement for Notch between 0-72 hours ALH reported in the current study relate to the Notch-depleted NBs identified in the 2022 paper?<br /> 3. Most of the experiments rely upon continuous depletion of Notch from embryonic stage 8 until adulthood using the wor-GAL4 driver. There is no lineage tracing of this driver and there is no citation about the published expression pattern of this driver. The inclusion of these details is important for a broad audience journal.<br /> 4. Most of the experiments utilize a single RNAi transgene for Notch, Delta, Imp, Syp, E93. There are no experiments demonstrating the efficacy of the RNAi lines and no references to prior use and/or efficacy of these lines.

An appraisal: The authors use temperature shifts with Gal80TS to show that Notch is required between 0-72 hours ALH. They show with the use of known markers of the temporal factors and Delta protein trap, that Imp promotes Delta protein expression and the later temporal factors reduce Delta, although the molecular mechanisms are not clearly delineated. Overall, these data support their model that the reduction of Delta expression during larval development leads to a loss of Notch activity.

As noted in the Discussion, this study raises many questions about what Notch does in larval CB NBs. For example, does it inhibit Castor or Imp? Is Notch required in certain neural lineages and not others. These studies will be of interest in the community of developmental neurobiologists.

Reviewer #1 (Public Review):

The authors set out to investigate the hypothesis that mirror neurons in ventral premotor area F5 code actions in a common motor representation framework. To achieve this, they trained a linear discriminant classifier on the neural discharge of three types of action trials and test whether the thus trained classifier could decode the same categories of actions when observed. They showed that codes were fully matched for a small subset of neurons during the action epoch, while a wider set of "mirror neurons" showed only poorly matched codes for different epochs.

The authors controlled for potential visual object confounds by having identical objects be manipulated in three different ways and by having the animal carry out the motor execution in the dark. The main strength of the study lies in the clever decoding approach testing the matched tuning to behavioural categories in a model-free way. The central result is in the identification of the small sub-group of mirror neurons that show true matching during the execution epoch, which can dissociate the three types of action almost perfectly. This aligns well with some previous work while offering a novel avenue to identify and investigate those neurons.

The underlying neuronal mechanism and behavioural relevance of these neurons remain an open question. It would have been interesting to understand better whether the specific motor representations at a recording site, for instance identified through microstimulation prior to recording (see Methods), the reaction times on individual trials or the specific gaze targets (object/hand) had a bearing on the decoding performance for a neuron/trial. Ultimately, the uncovered matched mirror representations should in future experiments be tested with causal interventions and linked trial-by-trial to action selection performance.

The authors put the focus of their discussion on the wider, less well-matched neuronal pool to support an action selection framework, which is of course a valid view and well established in motor representations. From a sensory perspective, sparse coding, as suggested by the small group of "true" mirror neurons identified with the decoding approach, should also be considered as the basis for a possible neuronal mechanism. A particular strength of the paper is that it could give new data and impetus to the important discussion about how motor and sensory coding frameworks come together in cortical processing.

Reviewer #1 (Public Review):

Cedillo et al. address the critically important question of how biguanides exert their positive effects on longevity using the powerful C. elegans model. Biguanides metformin and phenformin have been widely prescribed in the clinic to address metabolic challenges of diabetes; more recently the value of metformin in addressing specific cancers has emerged, and testing for impact on healthy human aging is getting underway. The need to understand the mechanism of biguanide action and the metabolic consequences of biguanide administration is clear.

The authors report that three genes that suppress longevity associated with metformin or phenformin treatment affect a common pathway for ether lipid biosynthesis; this ether lipid biosynthesis pathway is required for mitochondrial lifespan extension, eat-2 mediated dietary restriction longevity, and TOR inhibition-associated longevity, but not insulin pathway mediated longevity. Authors document with lipid profiling how ether lipids and some other lipids are impacted by phenformin vs. genetic disruption of ether lipid biosynthesis, define the tissue primarily responsible for the ether lipid biosynthesis, show that over-expression of enzyme fard-1 is sufficient to confer most of the phenformin effect, and implicate conserved stress transcription factor SKN-1 as a downstream outcome of the ether lipid change.

Strengths include the exploitation of the nematode model to address requirements not readily discerned in other models, the rigor of genetic documentation, the inclusion of metabolic profiling, the testing of multiple potential pathways that have been in the general discourse regarding metformin action, and the elaboration of a reasonably supported model that ether lipid biosynthesis is required for phenformin to activate longevity-promoting metabolic defenses downstream of conserved stress-responsive transcription factor SKN-1/NRF2. The novelty includes that ether lipids are directly linked to lifespan, ether lipid biosynthesis is needed for specific longevity pathways, and that ether lipids might play a role in a shift to pro-longevity metabolism.

There are some points that require clarification and could benefit from additional study, some wording and presentation issues, and a few missing points of potential discussion.

Overall, the data reported in this paper contribute a highly valuable advance in the biguanide field and adds stimulating hypotheses to the scientific community for moving forward in this biomedically important area.

Reviewer #1 (Public Review):

The authors expand upon prior findings and show that basolateral amygdala (BLA) activity is necessary for defensive responses elicited by both innate and learned threats. The authors also show that a projection from the auditory thalamus (MGM thalamic nucleus) mediates these effects.

Learned threats were modelled with auditory fear conditioning. The authors finding showing that the MGM-BLA pathway is required for auditory fear learning is largely a replication of prior results.

The novelty in this paper is that the authors show that the auditory MGM-BLA pathway is involved in defense evoked by a visual looming stimulus.

Overall, this is a reasonably designed study. The main weakness is that the loss of function manipulations use either caspase-induced lesions or contralateral chemogenetic disconnection studies, which lack temporal resolution.

Reviewer #1 (Public Review):

It has been shown previously that there are relationships between a transdiagnostic construct of anxious-depression (AD), 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 approach represents an exciting breakthrough. Analysis is straightforward and clearly presented. However, 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 study provides an important impact to the project of computational psychiatry.Sspecifically, it shows that the relationship between transdiagnostic symptom dimensions and behaviour is meaningful within as well as across individuals.

Reviewer #1 (Public Review):

The authors consider data by the Heisenberg group on rheological properties of non-confluent tissue in zebrafish embryos. These data had shown a steep increase and subsequent saturation in viscosity with cell density. The authors introduce a physical agent-based model of such tissues that accounts for the dispersion in cell size and the softness of the cells. The model is inspired by previous models to study glassy dynamics and reveals essential physical features that can explain the observed behavior. It goes beyond previous studies that had analysed the observations in terms of a percolation problem. The numerics are thoroughly done and could have a deep impact on how we describe non-confluent tissues.

A major weakness of the manuscript is the way it is written, which gives the impression to have been done rather carelessly. Several quantities are not properly introduced and at places physical jargon is used that makes the work difficult to access for readers without a background in soft matter.

Reviewer #1 (Public Review):

Many drugs have off-target effects on the gut microbiota but the downstream consequences for drug efficacy and side effect profiles remain unclear. Herein, Wang et al. use a mouse model of liver injury coupled to antibiotic and microbiota transplantation experiments. Their results suggest that metformin-induced shifts in gut microbial community structure and metabolite levels may contribute to drug efficacy. This study provides valuable mechanistic insights that could be dissected further in future studies, including efforts to identify which specific bacterial species, genes, and metabolites play a causal role in drug response. Importantly, although some pilot data from human subjects is shown, the clinical relevance of these findings for liver disease remain to be determined.

The major strength of this work is its scope, including detailed mouse phenotyping, inter-disciplinary methods, and numerous complementary experiments. The antibiotic depletion and FMT experiments provide support for a role of the gut microbiota in this mouse model.

A major limitation is the lack of studies narrowing down which microbes are responsible. Sequencing data is shown, but no follow-up studies are done with bacterial isolates or defined communities.

The link to GABA is also somewhat tenuous. While it does match the phenotypic data, there are no targeted experiments in which GABA producing microbial communities/strains are compared to a control community/strain. As such, it seems difficult to know how much of the effects in this model are due to GABA vs. other metabolites.

My major recommendation would be to revise the title, abstract, and discussion to provide more qualification and to consider alternative interpretations.

Some key controls are also missing, which could be addressed by repeat experiments in the mouse model. The antibiotic depletion experiment would be improved by testing the effect of antibiotics in the absence of metformin, to see if the effect is just driven by the model itself as opposed to an interaction between metformin and antibiotics. The FMT experiment lacks a control group and suffers from pseudoreplication: multiple donors from metformin treated and untreated mice could be used to colonize separate groups of recipient mice.

Reviewer #1 (Public Review):

This manuscript provides important evidence on the association between sleep regularity and mortality in the UK Biobank, which is a popular topic in recent sleep and circadian research in population-based studies. The analysis reported robust associations between sleep irregularity and increased total, CVD and cancer mortality, and provided evidence to support the role of sleep and circadian health in disease progression and longevity in human populations. The Sleep Regularity Index (SRI) used in this study is a novel metric that quantifies the consistency in rest-activity rhythms over consecutive 24 hour periods, thus providing objective assessment of potential circadian disruption. The study is based on a large accelerometer study with validated follow-up of incident diseases and deaths. The data quality and large sample size strengthen the credibility of the conclusion. Overall, the analyses are appropriately done and the manuscript is clearly written. Additional justification for the assessment of nonlinearity and further subgroup analyses would further improve the manuscript.

Joint Public Review

In the presence of predators, animals display attenuated foraging responses and increased defensive behaviors that serve to protect them from potential predatory attacks. Previous studies have shown that the basolateral nucleus of the amygdala (BLA) and the periaqueductal gray matter (PAG) are necessary for the acquisition and expression of conditioned fear responses. However, it remains unclear how BLA and PAG neurons respond to predatory threats when animals are foraging for food. The authors employed single-unit recording of BLA and PAG neurons and optogenetic tools to address this question in an 'approach food-avoid predator' paradigm.

The authors observed that rats exhibited a significant increase in the latency to obtain the food pellets and a reduction in the pellet success rate when the predator robot was activated. A subpopulation of PAG neurons showing increased firing rate in response to the robot activation did not change its activity in response to food pellet retrieval during the pre- or post-robot sessions. Optogenetic stimulation of PAG neurons increased the latency to procure the food pellet in a frequency- and intensity-dependent manner, similar to what was observed during the robot test. Combining optogenetics with single-unit recordings, the authors demonstrated that photoactivation of PAG neurons increased the firing rate of 10% of BLA cells. A subsequent behavioral test in three of these same rats demonstrated that BLA neurons responsive to PAG stimulation displayed higher firing rates to the robot than BLA neurons nonresponsive to PAG stimulation. Next, because the PAG does not project monosynaptically to the BLA, the authors used a combination of retrograde and anterograde neural tracing to identify possible regions that could convey robot-related information from PAG to the BLA. They observed that neurons in specific areas of the paraventricular nucleus of the thalamus (PVT) that are innervated by PAG fibers contained neurons that were retrogradely labeled by the injection of CTB in the BLA. In addition, PVT neurons showed increased expression of the neural activity marker cFos after the robot test, suggesting that PVT may be a mediator of PAG signals to the BLA.

Strengths

Overall, the idea that the PAG interacts with the BLA via the midline thalamus during a predator vs. foraging test is new and quite interesting. The authors have used appropriate tools to address their questions. The major impact in the field would be to add evidence to claims that the BLA can be downstream of the dPAG to evoke defensive behaviors. The study also adds to a body of evidence that the PAG mediates primal fear responses.

Weaknesses

The two most significant weaknesses relate to a) anatomical concerns related to the subregions of the BLA and PAG that were targeted by manipulations and analyses and b) the correlational nature of the PVT measures and the lack of any causal role demonstrated. Other concerns are also detailed below.

Anatomical concerns:

1. The authors claim that the recordings were performed in the dorsal PAG (dPAG), but the histological images in Fig. 1B and Supplementary S2 for example show the tip of the electrode in a different subregion of PAG (ventral/lateral). They should perform a more careful histological analysis of the recording sites and explain the histological inclusion and exclusion criteria. Diagrams showing the sites of all PAG and BLA recordings, as well as all fiber optics, would be helpful.<br /> 2. Prior studies investigating the role of BLA neurons during a foraging vs. robot test similar to the one used in this study should be also cited and discussed (e.g., Amir et al 2019, PMID: 30840520; Amir et al 2015, PMID: 26400931). These two studies demonstrated that most neurons in the basal portion of the BLA exhibit inhibitory activity during foraging behavior and only a small fraction of neurons (~4%) display excitatory activity in response to the robot (in contrast to the 25% reported in the present study). A very accurate histological analysis of BLA recording sites should be performed to clarify whether distinct subregions of the BLA encode foraging and predator-related information, as previously shown in the two described studies.<br /> 3. An important claim of this study that the PAG sends predator-related signals to BLA via the PVT (Fig. 4). The authors stated that PVT neurons labeled by intra-BLA injection of the retrograde tracer CTB were activated by the predator, but a proper immunohistochemical quantification with a control group was not provided to support this claim. To provide better support for their claim, the authors should quantify the double-labeled PVT neurons (cFos plus CTB positive neurons) during the robot test.<br /> 4. The AVV anterograde tracer deposit spread to a large part of the PAG, including dorsolateral and lateral PAG, and supraoculomotor regions (Fig. 4B). Is the projection to the PVT from the dPAG or other regions of the PAG?

Concerns about the strength of the evidence supporting a role for the PVT:

5. The authors conclude in the discussion section that the dPAG-amygdala pathway is involved in generating antipredatory defensive behavior. However, the current results are entirely based on correlational analyses of neural firing rate and there is no direct demonstration that the PAG provides information about the robot to the BLA. Therefore, the authors should tone down their interpretation or provide more evidence to support it by performing experiments applying inhibitory tools in the dPAG > PVT > BLA pathway and examining the impact on behavior and downstream neural firing.

Other concerns:

6. One of the main findings of this study is the observation that BLA neurons that are responsive to PAG photostimulation are preferentially recruited during the foraging vs. robot test (Fig. 3). However, the experimental design used to address this question is problematic because the laser photostimulation of PAG neurons preceded the foraging vs. robot test. Prior photoactivation of PAG may have caused indirect short-term synaptic plasticity in BLA cells, which would favor the response of these cells to the robot. Please see Oishi et al, 2019 PMID: 30621738, which demonstrated that 10 trains of 20Hz photoactivation (300 pulses each) was sufficient to induce LTP in brain slices.<br /> 7. The authors should perform a longitudinal analysis of the behavioral responses of the rats across the trials to clarify whether the animals habituate to the robot or not. In Figure 1E, it appears that PAG neurons fire less across the trials, which could be associated with behavioral habituation to the predator robot. If that is the case, the activity of many other PAG and BLA neurons will also most likely vary according to the trial number, which would impact the current interpretation of the results.<br /> 8. In Figure 1, it is unclear why the authors compared the activity of neurons that respond to the robot activation against the activity of the neurons during the retrieval of the food pellets in the pre-robot and post-robot sessions. The best comparison would be aligning the cells that were responsive to the activation of the robot with the moment in which the animals run back to the nest after consuming the pellets during the pre-robot or post-robot sessions. This would enable the authors to demonstrate that the PAG responses are directly associated with the expression of escaping behavior in the presence of the robot rather than associated with the onset of goal-directed movement in direction to the next during the pre- and post-robot sessions. A graphic showing the correlation between PAG firing rate and escape response would be also informative.

Reviewer #1 (Public Review):

The authors performed a comparative study of the effect of the anesthetics isoflurane and ketamine on whole-brain network activation by mapping whole-brain c-fos expression in mice. Principle component analysis on the normalized Fos density showed opposite effects of the 2 anesthetics, consistent with top-down functioning for ketamine and bottom-up functioning for isoflurane. Based on the network analysis the authors suggest that isoflurane mediates anesthesia through a bottom-up mechanism activating subcortical regions and inactivating cortical regions with the locus coeruleus being the most important region while ketamine produced anesthesia through a top-down mechanism activating the cortex and subcortical nuclei with the somatosensory cortex as the most important region. Overall they show that these two anesthetics have two opposite mechanisms to induce unconsciousness, although they also have overlapping coactivation of central sleep-wake, pain, and neuroendocrine regulating areas. This manuscript highlights some interesting findings through interesting analysis. The results are likely to have a significant impact on the field of anesthesia but also on the much larger field of neuropsychopharmacology as the tools and analyses used in this report will be useful for researchers investigating the effects of any psychoactive drugs on the brain. However, there are several issues that should be addressed to support their conclusions. The two main issues of this report are the lack of behavioral/physiological measures of the depth of anesthesia produced by ketamine/isoflurane and inadequate data analysis/interpretations for some of the results.

Strengths<br /> Comparison of two different anesthetics<br /> Use of single-cell whole-brain imaging<br /> Advanced network analysis

Weaknesses<br /> Lack of behavioral/physiological measures<br /> Interpretation of the data is sometimes confusing/unclear<br /> Some statistical tests are missing and others are not controlled for multiple comparisons

Major concerns<br /> 1. The lack of behavioral/physiological measures of the depth of anesthesia (ventilation, heart rate, blood pressure, temperature, O2, pain reflexes, etc...) combined with the lack of dose-response and the use of different routes of administration makes the data difficult to interpret. Sure, there is a clear difference in network activation between KET and ISO, but are those effects due to the depth of the anesthesia, the route of administration, and the dose used? The lack of behavioral/physiological measures prevents the identification of brain regions responsible for some of the physiological effects and different effects of anesthetics.<br /> 2. Under anesthesia there should be an overall reduction of activity, is that the case? There is no mention of significantly downregulated regions. The authors use multiple transformations of the data to interpret the results (%, PC1 values, logarithm) without much explanation or showing the full raw data in Fig 1. It would be helpful to interpret the data to compare the average fos+ neurons in each region between treatment and control for each drug.<br /> 3. I do not understand their interpretation of the PCA analyses. For instance, in Fig 2 they claim that KET is associated with PC1 while ISO is associated with PC2. Looking at the distribution of points it's clear that the KET animals are all grouped at around +2.5 on PC1 and -2.0 on PC2, this means that KET is associated with both PC1 and PC2 to a similar degree (2 to 2.5). Moreover, I'm confused about why they use PCA to represent the animals/group. PCA is a powerful technique to reduce dimensionality and identify groups of variables that may represent the same underlying construct; however, it is not the best way to identify clusters of individuals or groups.<br /> 4. The actual metric used for the first PCA is unclear, is it the FOS density in each of the regions (some of those regions are large and consist of many subregions, how does that affect the analysis) is it the %-fos, or normalized cells? The wording describing this is variable causing some confusion. How would looking at these different metrics influence the analysis?<br /> 5. Based on Fig 3 the authors concludes that ISO activates the hypothalamic regions and inhibits the cortex, however, Fig 1 shows neither an activation of the hypothalamus in the ISO nor an inhibition of the cortex when compared to home cage control. If anything it suggests the opposite.<br /> 6. Control for isoflurane should be air in the induction chamber rather than home cage. It is possible that Fos activation reflects handling/stress pre-anesthesia in the animals, which would increase Fos expression in the stress-related regions such as the BST, striatum (CeA), hypothalamus (PVH) and potentially the LC.<br /> 7. In the Ket network there are a few anticorrelated regions, most of which are amongst the list of the most activated regions, does this mean that the strong correlation results from an overall decreased activation? And if so, is it possible that the ketamine anesthesia was stronger than the isoflurane, causing a more general reduction in activity?<br /> 8. Since they have established networks it would be easy and useful to look at how the different regions identified (sleep, pain, neuroendocrine, motor-related, ...) work together to maintain analgesia, are they within the same module? Do they become functionally connected and is this core network of functional connections similar for KET and ISO?<br /> 9. The naming of the function of some of the regions is very much debatable. For instance, PL/ILA are named "sleep-wakefulness regulation" regions in the paper. I can think of many more important functions of the PL/IL including executive functions, behavioral flexibility, and emotional control. It is unclear how the functions of all the regions were attributed. I am not sure that this biased labeling of structure-function is useful to the reports, it may instead suggest wrong conclusions.<br /> 10. A point of concern and confusion is the number of brain regions analyzed. In the introduction, it is mentioned that 987 brain regions are considered, but this is reduced to 53 selected brain regions in Figure 2, then 201 brain regions in Figure 3, and reduced again to 63 for the network analysis. The rationale for selecting different brain regions is not clear.<br /> 11. The statistical analysis does not seem appropriate considering the high number of comparisons. They use simple t-tests without correction for multiple comparisons.<br /> 12. There is no statistical analysis in Fig 2C,

Reviewer #1 (Public Review):

This EEG study probes the prediction of a mechanistic account of P300 generation through the presence of underlying (alpha) oscillations with a non-zero mean. In this model, the P300 can be explained by a baseline shift mechanism. That is, the non-zero mean alpha oscillations induce asymmetries in the trial-averaged amplitudes of the EEG signal, and the associated baseline shifts can lead to apparent positive (or negative) deflections as alpha becomes desynchronized at around P300 latency. The present paper examines the predictions of this model in a substantial data set (using the typical P300-generating oddball paradigm and careful analyses). The results show that all predictions are fulfilled: the two electrophysiological events (P300, alpha desynchronization) share a common time course, anatomical sources (from inverse solutions), and covariations with behaviour; plus relate (negatively) in amplitude, while the direction of this relationship is determined by the non-zero-mean deviation of alpha oscillations pre-stimulus (baseline shift index, BSI). This is indicative of a tight link of the P300 with underlying alpha oscillations through a baseline shift account, at least in older adults, and hence that the P300 can be explained in large parts by non-zero mean brain oscillations as they undergo post-stimulus changes.

Reviewer #1 (Public Review):

The present study by Berger et al. analyzes to what extent memory formation is dependent on available energy reserves. This has been dealt with extensively in the case of aversive memory formation, but only very sparsely in the case of appetitive memory formation. It has long been known that an appetitive memory in flies can only be formed by starvation. However, the authors here additionally show that not only the duration of starvation plays a role, but also determines which form of memory (short- or long-term memory) is formed. The authors demonstrated that internal glycogen stores play a role in this process and that this is achieved through insulin-like signaling in octopaminergic reward neurons that integrates internal energy stores into memory formation. Here, the authors suggest that octopamine plays a role as a negative regulator of different forms of memory.

The study sheds light on an old question, to what extent the octopaminergic neuronal system plays a role in the formation of appetitive memory, since in recent years only the dopaminergic system has been in focus. Furthermore, the data are an interesting contribution to the ongoing debate whether insulin receptors play a role in neurons themselves or in glial cells. The experiments are very well designed and the authors used a variety of behavioural experiments, genetic tools to manipulate neuronal activity and state-of-the-art imaging techniques. In addition, they not only clearly demonstrated that octopamine is a negative regulator of appetitive memory formation, but also proposed a mechanism by which the insulin receptor in octopaminergic neurons senses the internal energy status and then controls the activity of those neurons. The conclusions are mostly supported by the data, but some aspects related to the experimental design, some explanations and literature references need more clarification and revision.

1. Usually, long-term memory (LTM) is tested 24 hours after training. Here, the authors usually refer to LTM as a memory that is tested 6 hours after training. The addition of a control experiment to show that LTM that the authors observe here lasts longer would increase the power of this study immensely.

2. The authors define here another consolidated memory component as ARM, when they applied a cold-shock 2 hours after training. However, some publications showed that LTM is formed after only one training cycle (Krashes et al 2008, Tempel et al 1983). This makes it difficult to determine, whether appetitive ARM can be formed. Furthermore, one study showed that appetitive ARM is absent after massed training (Colomb et al 2009). Therefore, the conclusion could be also, that different starvation protocols, would lead to different stabilities of LTM. Therefore, additional experiments could help to clarify this opposing explanation. From these results, it can then be concluded either that different stable forms of LTM are formed depending on the starvation state, or that two differently consolidated memory phases (LTM, ARM) are formed, as has already been shown for aversive memory. This is also important for other statements in the manuscript, and therefore the authors should address this. For example, the findings about the insulin receptor (is it two opposing memories or different stabilities of LTM).

Reviewer #1 (Public Review):

She et al studied the evolution of gene expression reaction norms when individuals colonise a new environment that exposes them to physiologically challenging conditions. Their objective was to test the "plasticity first" hypothesis, which suggest that traits that are already plastic (their value changes when facing a new environment compared to the original environment) facilitates the colonisation of novel environments, which, if true, would be predicted to result in the evolution of gene expression values that are similar in the population that colonised the new environment and evolved under these particular selection pressures. To test this prediction, they studied gene expression in cardiac and muscle tissues in individuals originating from three conditions: lowland individuals in their natural environment (ancestral state), lowland individuals exposed to hypoxia (the plastic response state), and a highland population facing hypoxia for several generations (the coloniser state). They classified gene expression patterns as maladaptive or adaptive in lowland individuals responding to short term hypoxia by classifying gene expression patterns using genes that differed between the ancestral state (lowland) and colonised state (highland). Genes expressed in the same direction in lowland individuals facing hypoxia (the plastic state) as what is found in the colonised state are defined as adaptative, while genes with the opposite expression pattern were labelled as maladaptive, using the assumption that the colonised state must represent the result of natural selection. Furthermore, genes could be classified as representing reversion plasticity when the expression pattern differed between the plasticity and colonised states and as reinforcement when they were in the same direction (for example more expressed in the plastic state and the colonised state than in the ancestral state). They found that more genes had a plastic expression pattern that was labelled as maladaptive than adaptive. Therefore, some of the genes have an expression pattern in accordance with what would be predicted based on the plasticity-first hypothesis, while others do not.

As pointed out by the authors themselves, the fact that temperature was not included as a variable, which would make the experimental design much more complex, misses the opportunity to more accurately reflect the environmental conditions that the colonizer individuals face at high altitude. Also pointed out by the authors, the acclimation experiment in hypoxia lasted 4 weeks. It is possible that longer term effects would be identifiable in gene expression in the lowland individuals facing hypoxia on a longer time scale. Furthermore, a sample size of 3 or 4 individuals per group depending on the tissue for wild individuals may miss some of the natural variation present in these populations. Stating that they have a n=7 for the plastic stage and n= 14 for the ancestral and colonized stages refers to the total number of tissue samples and not the number of individuals, according to supplementary table 1.

Impact of the work:

There has been work showing that populations adapted to high altitude environments show changes in their hypoxia response that differs from the short-term acclimation response of lowland population of the same species. For example, in humans, see Erzurum et al. 2007 and Peng et al. 2017, where they show that the hypoxia response cascade, which starts with the gene HIF (Hypoxia-Inducible Factor) and includes the EPO gene, which codes for erythropoietin, which in turns activates the production of red blood cell, is LESS activated in high altitude individuals compared to the activation level in lowland individuals (which gives it its name). The present work adds to this body of knowledge showing that the short-term response to hypoxia and the long term one can affect different pathways and that acclimation/plasticity does not always predict what physiological traits will evolve in populations that colonize these environments over many generations and additional selection pressure (UV exposure, temperature, nutriment availability).

Altogether, this work provides new information on the evolution of reaction norms of genes associated with the physiological response to one of the main environmental variables that affects almost all animals, oxygen availability. It also provides an interesting model system to study this type of question further in a natural population of homeotherms.

Erzurum, S. C., S. Ghosh, A. J. Janocha, W. Xu, S. Bauer, N. S. Bryan, J. Tejero et al. "Higher blood flow and circulating NO products offset high-altitude hypoxia among Tibetans." Proceedings of the National Academy of Sciences 104, no. 45 (2007): 17593-17598.

Peng, Y., C. Cui, Y. He, Ouzhuluobu, H. Zhang, D. Yang, Q. Zhang, Bianbazhuoma, L. Yang, Y. He, et al. 2017. Down-regulation of EPAS1 transcription and genetic adaptation of Tibetans to high-altitude hypoxia. Molecular biology and evolution 34:818-830.

Reviewer #1 (Public Review):

The authors were seeking to improve understanding of how wind and wave action affect the use of energetically demanding wing flapping and running by albatross engaged in takeoff flight. To accomplish this in the complex and challenging environment in which albatross live, the authors sought to use accelerometry and geographic positioning to infer patterns of locomotion, flight orientation relative to the prevailing wind, and wave height during takeoff.

The major strength of the methods and results is that the use of accelerometry and novel interpretations of data from a geographic positioning system provides new insight into the use of waves by albatross and how the effects of wave magnitude interact with wind to modulate energy demands during takeoff. Weaknesses of the approach are due to the challenging environmental conditions in which albatross live. The interpretation of accelerometry data was not validated using a subset of the sample synchronized with video (prior validation was cited for shearwaters). The interpretation of wind direction relative to flight path is based on the behavior of the bird without concurrent measures of local wind velocity.

The authors achieved their aims, and their results support their conclusions.

Although it is generally understood that albatross and many other birds choose to takeoff into the wind to reduce energetic costs, the authors provide novel quantitative data on this behavior. Their results on the effects of wave height and the interactions between wave height and wind provide novel insight into how albatross harvest energy from their complicated and dynamic environment to reduce the energy they must output to get into the air. In particular, the new insight into the effects of wave height should revise understanding among ornithologists, ocean ecologists and those who study the mechanics of animal locomotion. The use of accelerometry and geographic positioning systems to measure flight behavior and ocean ecology should inspire other researchers to adopt similar methods.

Albatross live in a complex and poorly understood environment that is likely to be threatened by climate change. This research provides worthwhile new insight into how wind and wave action affect takeoff in albatross, and can therefore improve insight into how changes in these variables with climate change may affect the distribution of albatross populations.

Reviewer #1 (Public Review):

The manuscript provides analyses on a very complete dataset on weight and length growth, as well as several physiological markers related to growth, in bonobos. Moreover, there is a good overview of the presence of adolescent growth spurts in non-human primates, by reviewing published data, in comparison to their own dataset. They discuss the need to consider scaling laws when interpreting and comparing growth curves of different species and variables.

The manuscript is very well written, the sample is large, and the methods are well explained. It seems they have analyzed a very complete dataset. Also, the discussion and the references supporting the findings are complete.

The main weakness of this manuscript is that they do not provide a direct comparison with previously analyzed datasets in other species, using their own method (in part maybe because there is not available data, but just published figures).

On the other side, conclusions are well supported by the results, and the previously published datasets are discussed in the manuscript, although not in detail.

Reviewer #1 (Public Review):

This paper describes the discovery, functional analysis and structure of TcaP, a protein encoded by the Vibrio phage satellite PLE that forms a size-determining scaffold around PLE procapsids made from helper phage ICP1 structural proteins. The system displays a fascinating similarity to the P2/P4 system, which had previously been unique in its use of a size-determining external scaffolding protein, Sid. The work is interesting, comprehensive and of high quality. The presentation could be improved as listed in the suggestions below.

An interesting observation is that PLE appears to be dependent on small capsids for efficient transduction. This is not completely surprising if the element uses a cos site type mechanism for packaging, since this requires an integer number of genomes to be packaged when the capsid is full, and this might be more difficult to accomplish when the helper capsid is much larger than the satellite, as is the case with ICP1. The authors mention in a few places that this is the first known satellite to have this requirement. However, this is not quite correct: a similar defect was seen in phi12/SaPIbov5, where the large phi12 capsid was not quite the right size for either two or three copies of the wild-type ("unevolved") SaPIbov5 (Carpena et al. 2016).

The authors present several micrographs showing capsids formed in the presence or absence of wildtype or mutant TcaP and CP (Fig. 1, Fig 2., Fig 3). However, each micrograph shows only a handful of particles of the "correct" size, in addition to a few shells that are aberrant or of a different size. I miss a more statistically rigorous enumeration of shells of different size (PLE or ICP1 sized, or different), empty vs. full, aberrant shells etc. This could be presented as a size distribution graph, a histogram or in table form.

In the abstract, the term "divergent satellite P4" is vague and unclear. Divergent from what? Probably they mean distinct from or unrelated to PLE. Please clarify.

How do they know that gp123 is a decoration protein? Was this previously determined, does it have (sequence) similarity to other known decoration proteins, or is it simply the most likely designation based on its position in the genome?

Although the reconstruction and modeling statistics are good, it is difficult to assess the quality of the map and the model from the presented figures. Details of the density and FSC curves (half-map and model-to-map) should be shown. It is also difficult to see the TcaP structure and how it compares to Sid from the figures presented.

Introduction, Paragraph 3: "...which is the number of coat proteins divided by 60" is not strictly speaking the definition of T number. The T number corresponds to the number of subtriangles that one triangular face of the icosahedron is divided into. It corresponds to the number of coat proteins divided by 60 in the canonical case, but in tailed phages, 5 copies are removed to make way for the portal protein. (Other viruses could be described as having architecture corresponding to a specific T number, but with divergent numbers of subunits, e.g. adenoviruses or polyomaviruses.)

Reviewer #1 (Public Review):

This is a paper describing in detail the seasonal movements of a vole-eating raptor, the rough-legged buzzard, from their Arctic breeding areas to the temperate wintering areas and back, in an annual cycle perspective. The basis of the descriptions (using satellite tags) is state of the art, and so are the analyses on aspects of time and space. Of particular relevance is the degree in which this study successfully pinpoints the ecological shaping factors, food availability of course, in this case strongly affected by snow cover (which can be remotely sensed over large areas). The authors claim a new migration pattern called 'foxtrot' with phases with rapid and phases with slower migration movements.

My concern with this paper is the framing. A story on the how and why of these continental movements in response to snow and other habitat features would be a grand contribution.

Reviewer #1 (Public Review):

The authors Wang et al. present a study of a mouse model K74R that they claim can extend the life span of mice, and also has some anti-cancer properties. Importantly, this mechanism seems to be mediated by the hematopoietic system, and protective effects can be transferred with bone marrow transplantation.

The authors need to be more specific in the title and abstract as to what is actually novel in this manuscript (a single tumor model), and what relies on previously published data (lifespan). Because many of these claims derive from previously published data, and the current manuscript is an extension of previously published work. The authors need to be more specific as to the actual data they present (they only use the B16 melanoma model) and the actual novelty of this manuscript.

Especially experiments on life span are published and not sufficiently addressed in this actual paper, as the title would suggest.

Reviewer #1 (Public Review):

In this manuscript, Bockorny, Muthuswamy, and Huang et al. performed proteomics analysis of plasma extracellular vesicles (EVs) from pancreatic ductal adenocarcinoma (PDAC) patients and patients with benign pancreatic diseases (chronic pancreatitis and intraductal papillary mucinous neoplasm, IPMN) to develop a 7-EV protein signature that predicts PDAC. Moveover, the authors identified PSMB4, RUVBL2, and ANKAR as being associated with metastasis. These studies provide important insight into alterations of EVs during PDAC progression and the data supporting predict PDAC with EV protein signatures are solid. However, there are certain concerns regarding the rigor and novelty of the data analysis and interpretation, as well as the clinical implications, as detailed below.

1. Plasma EVs were characterized by transmission electron microscopy and nanoparticle tracking analysis to confirm their morphology and size. The authors should also include an analysis of putative EV markers (e.g., tetraspanins, syntenin, ALIX, etc.) to confirm that the analyzed particles are EVs.

2. The authors identified multiple over-expressed proteins in PDAC based on their fold change and p-value; however, due to the heterogeneity of PDAC, it is necessary to show a heatmap displaying their abundance in all samples. High fold change does not necessarily indicate consistently high abundance in all PDAC samples.

3. PSMB4, RUVBL2, and ANKAR were identified as being associated with metastasis. The authors state that they intended to distinguish early and late-stage cancer samples, but it is unclear why they chose to compare metastatic and non-metastatic samples, as the non-metastatic group also includes late-stage cancer samples. This sentence should be rephrased to more accurately reflect the sample types profiled.

4. Non-metastatic and metastatic patients were separated based on global protein abundance. The samples within each group display significant heterogeneity with, some samples displaying similar patterns although they were classified into different groups (Figure 3A), and the samples within the same group, particularly the metastasis group, did not consistently exhibit similar patterns of protein abundance. The authors should clarify this point.

5. The authors performed the survival analysis on a set of EV proteins but did not specify the origin of these markers or how many markers were examined. The authors should show their abundances across different groups, such as different stages and metastasis status.

6. The classification model yielded a 100% accuracy, which may refer to AUC, in their discovery cohort, but it decreased to 89% in the independent cohort. This suggests that the authors have encountered overfitting issues with their model, where it performed well on the discovery cohort but did not generalize well to the independent cohort. The authors should clarify this point. The AUC score of the 7-EV signature is 0.89 and is not equivalent to prediction accuracy. In order to demonstrate prediction accuracy, the authors should show the confusion matrix of training and testing data as well as other evaluation metrics, such as accuracy, precision, and recall.

7. The authors should include more details of their model and the process of selection of signatures to enhance the reproducibility and transparency of their methods.

Reviewer #1 (Public Review):

The study investigates the nature of "trailblazer" cells in distinct tumor models, including luminal B (MMTV/PyMT) and triple negative (TNBC) tumors (C3-TAg). The authors note that the trailblazer phenotypes in the TNBC model are more complex relative to the Luminal B model and represent distinct EMT programs associated with the expression of distinct EMT-TFs (Zeb1, Zeb2 and Fra-1). They demonstrated that of numerous EMT-TFs, Zeb1 and Fra-1 were required for increased cancer cell migration and invasion. They reveal that TGF-beta and EGF-mediated signaling are required for the diverse EMT states that are required for trailblazer cell activity and increased cell migration/invasion. TGF-beta signaling engaged Zeb 1 and Zeb2 while EGF signaling activated Fra-1. Indeed, inhibitors of either TGF-beta or EGF signaling could impair cell migration/invasion. While both pathways contributed to trailblazer phenotypes, EGF signaling was shown to interfere with certain TGF-beta induced transcriptional response, including the expression of genes encoding extracellular matrix proteins.

One concern was the heavy reliance of the C3-TAg as the sole TNBC model in which the distinct trailblazer phenotypes were described. The data in Fig. 3 of the submission reveals that the phenotypes observed in the C3-TAg model could be recapitulated in a TNBC patient-derived xenograft model (PDX). Using this PDX, the authors were able to show vimentin expression in lung metastatic TNBC cells that were intravascular, those that had extravasated and clusters of cancer cells fully within the lung parenchyma. This was an important addition to the manuscript. The additional experiments to investigate the role of Zeb1 and Zeb1 more fully, beyond the focus on Fra-1 in the initial submission was an additional strength of the new submission. Additional clarifications to the discussion also clarified the concepts articulated in the study. The study employs multiple breast cancer models, utilizes numerous in vitro and in vivo assessments of the trailblazer phenotypes, and the experimental design is rigorous and the interpretation of the data is sound. The manuscript will be of general interest to the research community.

Reviewer #1 (Public Review):

In this manuscript by Wu et al., the authors present the high-resolution cryoEM structures of the WT Kv1.2 voltage-gated potassium channel. Along with this structure, the authors have solved several structures of mutants or experimental conditions relevant to the slow inactivation process that these channels undergo and which is not yet completely understood.

One of the main findings is the determination of the structure of a mutant (W366F) that is thought to correspond to the slow inactivated state. These experiments confirm results in similar mutants in different channels from Kv1.2 that indicate that inactivation is associated with an enlarged selectivity filter.

Another interesting structure is the complex of Kv1.2 with the pore-blocking toxin Dendrotoxin 1. The results show that the mechanism of the block is different from similar toxins, in which a lysine residue penetrates the pore deep enough to empty most external potassium binding sites.

The quality of the structural data presented in this manuscript is very high and allows for the unambiguous assignment of side chains. The conclusions are supported by the data. This is an important contribution that should further our understanding of voltage-dependent potassium channel gating. Specific comments are appended below.

1) In the mains text's reference to Figure 2d residues W18' and S22' are mentioned but are not labeled in the insets.

2) On page 8 there is a discussion of how the two remaining K+ ions in binding sites S3 and S4 prevent permeation K+ in molecular dynamics. However, in Shaker, inactivated W434F channels can sporadically allow K+ permeation with normal single-channel conductance but very reduced open times and open probability at not very high voltages.

3) The structures of WT in the absence of K+ show a narrower selectivity filter, however, Figure 4 does not convey this finding. In fact, the structure in Figure 4B is constructed at such an angle that it looks as if the carbonyl distances are increased, perhaps this should be fixed. Also, it is not clear how the distances between carbonyls given in the text on page 12 are measured. Is it between adjacent or kitty-corner subunits?

4) It would be really interesting to know the authors' opinions on the driving forces behind slow inactivation. For example, potassium flux seems to be necessary for channels to inactivate, which might indicate a local conformational change is the trigger for the main twisting events proposed here.

Reviewer #1 (Public Review):

The authors have previously employed micrococcal nuclease tethered to various Mcm subunits to the cut DNA to which the Mcm2-7 double hexamers (DH) bind. Using this assay, they found that Mcm2-7 DH are located on many more sites in the S. cerevisiae genome than previously shown. They then demonstrated that these sites have characteristics consistent with origins of DNA replication, including the presence of ARS consensus sequences, location of very inefficient sites of initiation of DNA replication in vivo, are free of nucleosomes, they contain a G-C skew and they locate to intergenic regions of the genome. The authors suggest, consistent with published single molecule results, that there are many more potential origins in the S. cerevisiae genome than previously annotated.

The results are convincing and are consistent with prior observations. The analysis of the origin associated features is informative.

Reviewer #1 (Public Review):

The authors investigated the function of BATF in hepatic lipid metabolism. They found BATF alleviated high-fat diet (HFD)-induced hepatic steatosis. In addition, BATF could inhibit programmed cell death protein (PD)1 expression induced by HFD. By using over expression and transcriptional activity analysis, this study confirmed that BATF regulates fat accumulation by inhibiting PD1 expression and promoting energy metabolism. Then, they found PD1 antibodies alleviated hepatic lipid deposition. These data identified the regulatory role of BATF in hepatic lipid metabolism and that PD1 is a target for alleviation of NAFLD.

The conclusions of this manuscript are supported by data, but some remaining concerns need to be addressed.

1. There are different cells in liver tissue, in which BATF protein is expressed most.<br /> 2. The statistical data should be provided to support the liver specific over-expression of BATF.<br /> 3. For in vivo study, food intake is key data to exclude the change of energy intake.<br /> 4. For Fig.6 Since PD1 are also highly expressed in heart and spleen, how to exclude the effect of PD1 antibody on these tissues?

Reviewer #1 (Public Review):

This study delves into the impact of imidacloprid, an insecticide documented for its toxicity towards honeybees, on the development of bee larvae. The investigation involved exposing bee larvae to various concentrations of imidacloprid, and observing the resultant effects.

The findings of this study revealed that imidacloprid exerted a dose-dependent delay in the development of bee larvae, marked by reductions in body mass, width, and an overall decline in the growth index. Moreover, at elevated concentrations, imidacloprid was observed to impair neural transmission, induce oxidative stress, inflict damage to the gut, and inhibit hormones and genes essential for development. The larvae were found to engage antioxidant defense systems and deploy detoxification mechanisms to mitigate these effects.

However, the manuscript could be significantly enhanced through several improvements. Firstly, the structure of the manuscript warrants refinement to foster coherence and clarity. Additionally, there is a need for careful reevaluation of the concentrations of imidacloprid employed in the study, to ensure their relevance and applicability. In terms of references, greater attention to accuracy in citation is imperative.

Furthermore, while the authors have provided an overview of the general effects of imidacloprid on both vertebrates and invertebrates, the inclusion of a more exhaustive literature review with a specific focus on honey bees and other insects would bolster the context and significance of this research. This would be particularly beneficial in the introduction section, which should be subjected to a major revision.

In summary, this study offers preliminary evidence of the detrimental effects of imidacloprid on the development of bee larvae by interfering with molting and metabolism. This research holds potential as a valuable resource for assessing the risks posed by pesticides to juvenile stages of various animal species.

Reviewer #1 (Public Review):

This is a straightforward paper that uses TraDIS (high-density TnSeq) with Klebsiella pneumoniae to infer essential genes, and genes required for survival under various infection-relevant conditions. The gene sets identified, together with the raw sequence data, will be valuable resources for the Klebsiella research community. The evidence to support the lists of essential and conditionally-important genes is solid, although a few additional follow-up experiments would strengthen some of the claims made based on the TraDIS data.

1. The data strongly suggest that iron depletion in urine leads to conditional essentiality of some genes. It would be informative to test the single gene deletions (Figure 3G) for growth in urine supplemented with iron, to determine how many of those genes support growth in urine due to iron limitation.<br /> 2. Line 641. The authors raise the intriguing possibility that some mutants can "cheat" by benefitting from the surrounding cells that are phenotypically wild-type. Growing a fepA deletion strain in urine, either alone or mixed with wild-type cells, would address this question. Given that other mutants may be similarly "masked", it is important to know whether this phenomenon occurs.<br /> 3. In cases where there are disparities between studies, e.g., for genes inferred to be essential for serum resistance, it would be informative to test individual deletions for genes described as essential in only one study.

Reviewer #1 (Public Review):

The present study combines quantitative histomorphometry, live cell imaging and tracking, functional analyses, and computational modeling to define potentially pathologic interactions between lung CD8 T cells and fibrocytes in human COPD. The authors use multiple technical approaches to establish the close proximity of CD8 T cells with fibrocytes in peri-bronchial tissue in COPD subjects that notably correlate with functional disease parameters (FEV1/FEV). Their follow-on studies identify specific chemokine pathways and inflammatory consequences of these interactions. Collectively, these seminal data acquired in a unified experimental context, provide support for pathogenic interactions between lung CD8 T cells and fibrocytes and now offer the consideration of mediators and pathways that may be amenable to therapeutic targeting. The strength of the study is the integration of the multi-modality approach, the quality of the quantitative data, and the creation of a tenable model for the interaction role in COPD of CD8 T cells and fibrocytes. While both have been previously implicated in COPD, this new study is more definitive by using this integrated approach.

Reviewer #1 (Public Review):

The cerebral cortex, or surface of the brain, is where humans do most of their conscious thinking. In humans, the grooves (sulci) and bumps (convolutions) have a particular pattern in a region of the frontal lobe called Broca's area, which is important for language. Specialists study features imprinted on the internal surfaces of braincases in early hominins by casting their interiors, which produces so-called endocasts. A major question about hominin brain evolution concerns when, where, and in which fossils a humanlike Broca's area first emerged, the answer to which may have implications for the emergence of language. The researchers used advanced imaging technology to study the endocast of a hominin (KNM-ER 3732) that lived about 1.9 million years ago (Ma) in Kenya to test a recently published hypothesis that Broca's remained primitive (apelike) prior to around 1.5 Ma. The results are consistent with the hypothesis and raise new questions about whether endocasts can be used to identify the genus and/or species of fossils.

Reviewer #1 (Public Review):

Recent works have documented the observation that transcription factors (TFs) and other transcriptional machinery proteins, e.g., Pol2 and mediator, can form high-concentration clusters at target genes within the nucleus and such behavior plays an important role in transcriptional activation. It is also well-established that the intrinsically disordered regions (IDRs) within many of the transcriptional regulators can undergo multivalent protein-protein interactions, which can lead to phase separation under certain conditions. It is thus thought that the IDRs are essential drivers of the clustering behaviors of transcriptional regulators. However, direct proof of this hypothesis remains missing. To fill this gap, Hannon and Eisen conducted a survey of the subnuclear localization of 75 IDRs derived from Drosophila TFs. They found that many full-length TFs but not IDRs alone form subnuclear clusters. They also did not detect a change in the clustering of TFs after deleting IDRs. Based on these data, they concluded that IDRs are unlikely to be the primary molecular drivers of the clustering phenomenon observed during transcription.

This study tackles an interesting question related to transcriptional regulation and IDR behaviors. The subnuclear distribution of many Drosophila TFs and TF IDRs measured in this work provides a valuable resource for future studies of these TFs and IDRs. The authors' finding that the distribution of an IDR alone is distinct from a full-length TF containing the IDR is new and informative though not surprising. Protein-chromatin binding is known to be stoichiometric with a clear structural basis, which is likely stronger than IDR-IDR interactions that are known to be weaker and more transient. Thus, adding a chromatin-binding capability to an IDR of interest indeed likely significantly affects the distribution of the IDR. Despite being a natural hypothesis based on existing knowledge, it was not previously verified until this current work that systematically compared TF and TF IDR distributions. However, the authors' other conclusion that deleting the IDR from a TF does not affect the TF's clustering behavior is not fully supported. This is because the change of TF's clustering behavior due to IDR deletion, if any, is likely quantitative (decreasing) instead of qualitative (completely disappearing), due to the fact that protein-chromatin binding is stronger than IDR-IDR interactions. This work lacks quantitative characterization of TF clusters before and after IDR deletion. The spinning disk confocal microscopy used here likely does not provide the necessary spatial resolution to quantitatively characterize TF clusters, which often have dimensions near or below the diffraction limit of light.

Reviewer #1 (Public Review):

The expression and localization of Foxc2 strongly suggest that its role is mainly confined to As undifferentiated spermatogonia (uSPGs). Lineage tracing demonstrated that all germ cells were derived from the FOXC2+ uSPGs. Specific ablation of the FOXC2+ uSPGs led to the depletion of all uSPG populations. Full spermatogenesis can be achieved through the transplantation of Foxc2+ uSPGs. Male germ cell-specific ablation of Foxc2 caused Sertoli-only testes in mice. CUT&Tag sequencing revealed that FOXC2 regulates the factors that inhibit the mitotic cell cycle, consistent with its potential role in maintaining a quiescent state in As spermatogonia. These data made the authors conclude that the FOXC2+ uSPG may be the true SSCs, essential for maintaining spermatogenesis. The conclusion is supported by the data presented.

Joint Public Review:

The study has main limitations which need to be addressed and there is 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.

Suggestions to the authors:<br /> • The authors need to provide analysis of patients of non-Black origin.<br /> • The Table of demographics needs to include the type of infections and the underlying pathogen.<br /> • The authors need to provide convincing analysis if results are false-positive since APOL1 provides risk for chronic renal disease (CRD) and patients with CRD are predisposed to sepsis. For this purpose, they have to provide evidence if the sepsis causes (both type of infection and implicated pathogens) in patients with CRD who are carriers of APOL1 variants are different than in patients with CRD who are not carriers of APOL1 variants.<br /> • Why concentrations of APOL1 were not measured in the plasma of patients?<br /> • Why analysis towards risk for death is not done?<br /> • The authors need to explain why functional information is not provided.<br /> • n 162-172: too many assumptions have been used for the trial; thus, progression to sepsis is difficult to define. According to Sepsis-3 sepsis is no more a continuum from infection to sepsis and septic shock. Some patients presented with sepsis (-1, 0, 1 days considered by the authors) and when electronic health records are used, we are not able to detect the exact timepoint of SOFA score turning to a 2-point increase. This is a major limitation of the methodology presented.<br /> Same applies for all comorbidities and data extracted from electronic health records.<br /> • P value significance thresholds were set at 0.05, except for the PWAS where the threshold was set at 0.05/5 (p13). It would be helpful to list at this point what the 5 outcomes were that led to this adjusted threshold.<br /> "Risk of sepsis was significantly increased among patients with high-risk genotypes (OR 1.29, 1.0 to 1.67, P1.29, CI 1.00-1.67, P<0.47)." Some would argue that a confidence interval that includes 1.0 indicates non-significance.<br /> • The Discussion is too long and should be shortened.

Reviewer #1 (Public Review):

In this manuscript Budinska and colleagues aim to align morphologically distinct areas of colorectal cancers with the gene expression profiles and published signatures. They observe that distinct morphotypes such as serrated or mucinous align with certain subtypes but that these contradict the bulk subtype assignment. Although these data are of interest they may not be as novel as suggested by the authors and lack clarity in terms of patient selection and subtype definition.

1. Patient selection and tumor area selection are crucial for this study but not very carefully defined. Why are some core and others not? Figure referral is an issue here (sup figure 6 where all core and non-core samples are supposed to be according to the legend of Fig 4 is likely sup fig 7 but this is then a complete copy paste of Figure 4). In the methods it is stated that the core samples are based on limited contamination of additional morphotypes (<20%) but Fig 4 suggests that all tumours listed have multiple morphotypes.

2. CMS subtype should be performed with single sample predictor rather than CMScaller.

3. A couple of surprising observations need specification. MUC2 is a strong CMS3 reporter gene yet Mucinous tumours appear to end up in CMS4 rather than 3. Can the authors show that indeed stroma cells are very evident in these samples?

4. The SE PP and CT are assigned to CMS2, but in Figure 4 this appears a lot more variable than the authors would make the reader believe. The full data are not completely clear (see point 1)

5. The tumor response rates are rather weird as this is likely dependent on the complete tumour and not so much the subareas. It is not very well described what we see in this analysis.

6. Serrated adenomas have previously been aligned with CMS4. Is this different from serrated areas in cancers?

7. The fact that iCMS2 and iCMS3 align rather well with the current analysis of the distinct regions suggests that the analysis that was reported last year is the proper way to view tumor intrinsic signatures. The authors now propose a rather similar outcome to this issue which does take away a lot of the novelty of the findings of this study.

Reviewer #1 (Public Review):

This is an interesting, timely and informative article. The authors used publicly available data (made available by a funding agency) to examine some of the academic characteristics of the individuals recipients of the National Institutes of Health (NIH) k99/R00 award program during the entire history of this funding mechanism (17 years, total ~ 4 billion US dollars (annual investment of ~230 million USD)). The analysis focuses on the pedigree and the NIH funding portfolio of the institutions hosting the k99 awardees as postdoctoral researchers and the institutions hiring these individuals. The authors also analyze the data by gender, by whether the R00 portion of the awards eventually gets activated and based on whether the awardees stayed/were hired as faculty at their k99 (postdoctoral) host institution or moved elsewhere. The authors further sought to examine the rates of funding for those in systematically marginalized groups by analyzing the patterns of receiving k99 awards and hiring k99 awardees at historically black colleges and universities.

The goals and analysis are reasonable and the limitations of the data are described adequately. It is worth noting that some of the observed funding and hiring traits are in line with the Matthew effect in science (https://www.science.org/doi/10.1126/science.159.3810.56) and in science funding (https://www.pnas.org/doi/10.1073/pnas.1719557115). Overall, the article is a valuable addition to the research culture literature examining the academic funding and hiring traits in the United States. The findings can provide further insights for the leadership at funding and hiring institutions and science policy makers for individual and large-scale improvements that can benefit the scientific community.

Reviewer #1 (Public Review):

This paper proposes and evaluates a new approach for the registration of human hippocampal anatomy between individuals. Such registration is an essential step in group analysis of hippocampal structure and function, and in most studies to date, volumetric registration of MRI scans has been employed. However, it is known that volumetric deformable registration, due to its formulation as an optimization problem that minimizes the combination of an image similarity term and relatively simple geometric regularization terms, fails to preserve the topology of complex structures. In the cerebral cortex, surface-based registration of inflated cortical surfaces is broadly preferred over volumetric registration, which often causes voxels of different tissue types to be matched (e.g., voxels belonging to a sulcus in one individual mapping onto voxels belonging to a gurys in another). The authors recognize that hippocampal anatomy is similarly complex, and, with proper tools, can benefit from surface-based registration. They propose to first unfold the hippocampus to a two-dimensional rectangle domain using their prior HippUnfold technique, and then to perform deformable registration in this rectangle domain, matching geometric features (curvature, thickness, gyrification) between individuals. This registration approach is evaluated by comparing how well hippocampal subfields traced by experts using cytoarchitectural information align between individuals after registration. The authors indeed show that surface-based registration aligns subfields better than volumetric registration applied to binary segmentations of the hippocampal gray matter.

Overall, I find the methods and results in this paper to be convincing. The authors framed the comparison between surface-based and volumetric registration in a fair way, and the results convincingly show the advantage of surface-based registration. One slight limitation of the current study is that it is uncertain whether the benefits demonstrated here translate to in vivo MRI data for which the authors' HippUnfold algorithm is tailored. The current study utilized the unfolding technique used in HippUnfold on manual segmentations of high-resolution ex vivo MRI and blockface 3D volumes, which are likely closer to anatomical ground truth than automated segmentations of in vivo MRI. However, it is reasonable to assume that given that the volumetric registration to which the proposed approach was compared also used this high-detail data, the advantages of surface-based over volumetric registration would extend to in vivo MRI as well. However, I would encourage the authors to perform future evaluations on datasets with available in vivo and ex vivo MRI from the same individuals.

I would also like to point out the relevance of the 2021 paper "Unfolding the Medial Temporal Lobe Cortex to Characterize Neurodegeneration Due to Alzheimer's Disease Pathology Using Ex vivo Imaging" by Ravikumar et al. (https://link.springer.com/chapter/10.1007/978-3-030-87586-2_1) to the current work. This paper applied an earlier version of the unfolding method in HippUnfold to ex vivo extrahippocampal cortex and performed registration using curvature features in the rectangular unfolded space, also finding slight improvement with surface-based vs. volumetric registration, so its findings support the current paper.

Overall, the paper has the potential to significantly influence future research on hippocampal involvement in cognition and disease. Outside of simple volumetry studies, most hippocampal morphometry studies rely on volumetric deformable registration of some kind, typically applied to whole-brain T1-weighted MRI scans. With HippUnfold available for anyone to use and not requiring manual registration, the paper provides a strong impetus for using this approach in future studies, particularly where one is interested in localizing effects of interest to specific areas of the hippocampus. Additional evaluation of in vivo HippUnfold using in vivo / ex vivo datasets, would make the use of this approach even more appealing.

Reviewer #1 (Public Review):

Mignerot et al. performed a Herculean effort to measure and describe natural variation in C. elegans egg-laying behavior and egg retention. The paper is well written and organized, but almost seems like two papers in one. However, I understand the desire to put these stories together. The authors show wild strains vary in egg retention with some extremes that appear phenotypically similar to species with viviparity (or live birth / internal hatching of offspring). They previously published a rare variant in the gene kcnl-1 that plays a role in egg retention but identify common variants in this study. They classify wild strains based on egg-retention to separate out the extremely different isolates. Egg laying has been extensively studied in the laboratory strain N2, but rarely addressed in natural strains. The authors investigate egg-laying behaviors using standard assays and find that their classified egg-laying groups have differences in sub-behaviors suggesting diverse roles in the ultimate egg-laying output. Then, they turn to the egg-laying circuit using both exogenous serotonin (5-HT), 5-HT modulatory drugs (e.g. SSRIs), and even genome editing to test epistasis with the mod-5 5-HT reuptake. The effects of 5-HT modulation and mutants are not predictive based on the basal behaviors and egg-retention phenotypes with the most extreme egg-retention strains differing in their responses. Interestingly, strains with more egg retention have decreased fitness (in their laboratory) measures but also provide a protective environment for offspring when exposed to common "natural" stressors. Their final conclusion that egg retention could be a trade-off between antagonistic effects of maternal vs. offspring fitness is supported well and sets the stage for future mechanistic studies across Caenorhabditis.

Joint Public Review:

It has been shown previously that maternal aging in mice is associated with an increase in accumulation of damaged mitochondria and activation of parkin-mediated autophagy (see DOI: 10.1080/15548627.2021.1946739). It has also been shown that C-natriuretic peptide (CNP) regulates oocyte meiotic arrest and that its use during in vitro oocyte maturation can improve parameters associated with decreased oocyte quality. Here the authors tested whether use of CNP treatment in vivo could improve oocyte quality and fertility of aged mice, for which they provided convincing evidence. They also attempted to determine how CNP improves oocyte developmental competence. They showed a correlation between CNP use in vivo and the appearance (and some functional qualities) of cytoplasmic organelles more closely approximating those of oocytes from young mice. However, this correlation could not be interpreted to imply causation. Additional experiments performed using CNP during in vitro maturation were not properly controlled and so are not possible to interpret.

A strength of the manuscript is that the authors use an in vivo treatment to improve oocyte quality rather than just using CNP during oocyte maturation in vitro as has been done previously. This strategy provides more potential for improving oocyte quality - over the course of oocyte growth and maturation - rather than just the final few hours of maturation alone. This strategy also has the potential to be translated into a more generally useful clinical therapeutic method that using CNP during in vitro maturation. However, it is difficult to glean information regarding how CNP might have its effects in vivo. A range of models are used in the manuscript with a mix of in vivo studies with in vitro experiments, which results in some disconnect between systemic CNP and its reported intrafollicular action as well as in the short-term versus longer-term actions of CNP on oocyte quality. Specifically, CNP was shown to be reduced in the plasma of aged mice, but this was not shown in the granulosa cells, which are the reported source of CNP that acts on oocytes. Whether the ovarian source of CNP is reduced in aged females was not demonstrated, and CNP is not known to act on oocytes through an endocrine effect. In vivo treatments with CNP by i.p. injection were performed, but the dose (120 ug/kg) and time (14 days) of treatment were not validated by any prior experiments to give them physiological relevance.

Weaknesses:

1. There are errors in the manuscript writing that make the Results difficult to follow. Reference to the Figures in the Results section does not match what is shown in the Figure panels. For example, the Results text reports differences in CNP levels in aged and young mice shown in Figure 1C, but the relevant panel is actually shown in Figure 1F. Other Figures have the same problem.<br /> 2. The Results section is not always clear regarding what CNP treatment was done - in vivo injections or in vitro maturation. For example, what is the difference, if any, between Figures 2C-D and Figures S2A-B?<br /> 3. Immature oocytes from aged females (~1 year) were treated with a two-step culture system with a pre-IVM step with CNP. Controls included oocytes from young (6-8 weeks) females or oocytes from aged females treated by conventional IVM. The description of these methods suggests that control oocytes did not receive an equivalent pre-IVM culture, hence the relevance of comparisons of CNP-treated versus control oocyte is questionable. It was observed that aged oocytes pre-cultured in CNP improved polar body extrusion rates and meiotic spindle morphology compared to oocytes in conventional IVM, as has been well established. The description of statistical methods does not make clear whether the PBE rate in CNP-treated old oocytes remained significantly lower than young controls.<br /> 4. The main effect of the CNP 2-week treatment appears to be increasing the number of follicles that grow into secondary and antral stages, but there is no attempt made to discover the mechanism by which this occurs and therefore to understand why there might be an increase in the number of ovulated eggs, quality of the eggs, and litter size. It is also not clear how an intraperitoneal injection can guarantee its effectiveness because the half-life of CNP is very short, only a few minutes.<br /> 5. Meiotic spindle morphology, as well as a number of putative markers of cytoplasmic maturation are also suggested to be improved after pre-culture with CNP. In each case a subjective interpretation of "normal" morphology of these markers is derived from observations of the young controls and the proportions of oocytes with normal or abnormal appearance is evaluated. However, parameters that define abnormal patterns of these markers appear to be subjective judgements, and whether these morphological patterns can be mechanistically attributed to the differences in developmental potential cannot be concluded.<br /> 6. In addition to the localization patterns of mitochondria, the mitochondrial membrane potential, oocyte ATP content and ROS levels were assessed through more objective quantitative methods. These are well known to be defective in oocytes of aged females and CNP treatment improved these measures. Mitochondrial dysfunction is the most obvious link between oocyte apoptosis, autophagy, cytoplasmic organelle miss-localization and aberrant spindle morphology. Among the most intriguing results is the finding that CNP mediated a cAMP-dependent protein kinase (PKA) dependent reduction in mitochondrial autophagy mediators PINK and Parkin and reduced the recruitment of Parkin to mitochondria in oocytes. However, it may not be possible to directly link this observation to the improvements in IVM oocyte quality, since PINK/Parkin assessments were performed in oocytes from cultured follicles treated with CNP for 6 days.<br /> 7. The gold standard assay for oocyte quality is embryo transfer and live birth. The authors assessed the impact of maturing oocytes in vitro in the presence of CNP on oocyte quality by less robust assays (e.g., preimplantation embryo development in vitro), so the impact on oocyte quality is less certain.<br /> 8. The terminology used to describe many of the Results exaggerates the findings. For example, the authors claim that many of their immunofluorescent markers of the various organelles have a pattern that is "restored" by CNP. However, in most cases the pattern is "improved" toward the control condition but is not fully restored.<br /> 9. The numbers of embryos should have been corrected for the number of eggs fertilized as a starting point so that the percentage that developed to each stage could be expressed as a percentage of successfully fertilized eggs rather than overall percentages. As currently shown in the Figures and described in the Legend, there is no information regarding what the percentage on the y-axis means. For example, does Figure 4B show the number of 2C embryos divided by the number of eggs inseminated? Or is it divided by the number of successfully fertilized eggs, and if so, how was that assessed?<br /> 10. When fewer eggs are fertilized, the numbers of embryos per group are lower and so the impact of culturing multiple embryos together is lost. As a result, it is possible that culture conditions rather than oocyte quality drove the differences in the numbers of embryos that achieved each stage of development.<br /> 11. Not all claims in the Discussion are supported by the evidence provided. For example, "In addition, the findings demonstrated that CNP improved cytoplasmic maturation events by maintaining normal CG, ER and Golgi apparatus distribution and function in aged oocytes" but it was never demonstrated that the altered distribution had any functional impact.<br /> 12. Incompleteness and errors in the Methods section reduce confidence in many of the results reported.<br /> 13. The methods used for Statistical Analysis are never explained in either the Methods or the Figure legends. It is unclear whether appropriate analyses were done, and it is frequently unclear what was the sample size and how many times a particular experiment was repeated. These weaknesses detract from confidence in the data.

Reviewer #1 (Public Review):

In this manuscript, the authors used an unbiased method to identify proteins from porcine oocyte extracts associated with permeabilised boar spermatozoa in vitro. The identification of the proteins is done by mass spectrometry. A previous publication of this lab validated the cell-free extract purification methods as recapitulating early events after sperm entry in the oocyte. This novel method with mammalian gametes has the advantage that it can be done with many spermatozoa at the time and allows the identification of proteins associated with many permeabilised boar spermatozoa at the time. This allowed the authors to establish a list of proteins either enriched or depleted after incubation with the oocytes extract or even only associated with spermatozoa after incubation for 4h or 24h. The total number of proteins identified in their test is around 200 and with very few present in the sample only when spermatozoa were incubated with the extracts.

The list of proteins identified using this approach and these criteria provide a list of proteins likely associated with spermatozoa remnants after their entry and either removed or recruited for the transformation of spermatozoa-derived structures. Using WB and histochemistry labelling of spermatozoa and early embryos using specific antibodies the authors confirmed the association/dissociation of 6 proteins suspected to be involved in autophagy.

While this unique approach provides a list of potential proteins involved in sperm mitochondria clearance it is (only) a starting point for many future studies and does not provide the demonstration that any of these proteins has indeed a role in the processes leading to sperm mitochondria clearance. The protein identified may also be involved in other processes going on in the oocyte at this time of early development.

Reviewer #1 (Public Review):

The first synapses of the pain pathway are concentrated in the superficial spinal cord dorsal horn. Here peripheral inputs are processed by local interneuron circuitry before ascending to the brain. The spinal dorsal horn is organized into lamina with the resident interneurons differentiated by their anatomy, physiological and molecular properties. Over the past decade, the restricted expression of select genes has been used to assign potential function to dorsal horn neuron "cell types". This type of work has relied on the genesis of Cre-reporter mouse strains and intersectional tools to generate mice where select sets of neurons can be activated, inhibited, or ablated. The picture that has emerged from these types of experiments is murky but favors the model where there exist genetically defined cell-types play distinct roles in the detection of painful, itchy, thermal, and mechanical stimuli under normal and pathological situations. The current work by Boyle and colleagues concerns itself with the dorsal horn neurons expressing the neuropeptide NPY. This study is directly related to previously published work that demonstrated that ablating spinal cord neurons that express Npy, including those who express this gene transiently during development, resulted in mice that had heightened touch-evoked itch that seemed different from the canonical chemical itch pathways previously identified. A major conclusion from this previous work was that other modalities were unaffected. Subsequent work built on these findings to identify the potential touch inputs and spinal neuron expressing the Npy receptor as part of a mechanical itch circuit.

This current work by Boyle and colleagues challenge challenges this view by providing evidence that in adult mice, the dorsal horn neurons expressing Npy function to broadly inhibit pain and itch. The authors use direct injection of viral vectors, chemogenetics and synaptic silencing to probe the behavioral effects of stimulating or silencing Npy-expressing dorsal horn neurons in a variety of assays under normal and pathological conditions known to produce allodynia and hyperalgesia. Overall, this is a rather carefully conducted study with the appropriate controls. The data are clear, the effect sizes robust and the presentation easy to follow. These findings challenge the conclusion that these neurons are involved selectively in mechanical itch and instead reveal a potentially clinically important group of neurons for pain.

Reviewer #1 (Public Review):

The study utilizes a variety of methods, chemical and expressed probes, caged release of IP3, as well as oocytes with mutations that alter zinc availability, that provide an elegant examination of how zinc deficiency and zinc excess modulate the transient and cyclic release of calcium during egg activation. In this manuscript, the authors sought to determine if there is any interplay between zinc and calcium, two divalent cations that have been demonstrated to have important roles during fertilization. They employ agents that disrupt normal zinc homeostasis and then monitor the resulting calcium oscillations during egg activation. If zinc was made unavailable via chelation with TPEN, then the calcium oscillations halted. This occurred regardless of the activation method, which included ICSI, PLC𝛇, Acetylcholine, strontium chloride, and thimerosal. This phenotype could be rescued by introducing zinc back into the egg via an ionophore, such as zinc pyrithione; however, too much zinc pyrithione also halted calcium oscillations. Taken together, these two results demonstrate that there is a threshold level of zinc that is required for proper calcium oscillations to occur.

Furthermore, the authors sought to understand how zinc affects the IP3 receptor, IP3R1. IP3R1 is the receptor that modulates the release of calcium from the endoplasmic reticulum. The authors cited a previous study that identified zinc binding sites on IP3R1. The authors highlight that there exist no studies regarding the regulation of IP3R1 by zinc; however, such studies were cited for a similar calcium channel, the RyRs. The authors use thapsigargin to inhibit the SERCA pump, leading to calcium leak from the IP3R1. TPEN blunted the amount of calcium leaked from the ER following treatment, suggesting that zinc occupancy is necessary for IP3R1 function.

The results of these experiments support the authors conclusions that zinc is essential for the IP3R1-mediated release of calcium in an oscillatory manner during egg activation. These results provide further insight into signals necessary for proper egg activation and the ultimate success of the resulting embryo.

Reviewer #1 (Public Review):

This paper introduces a new transgenic mouse line that allows the labelling of the AIS and nodes of Ranvier (noR) by tagging Ank-G with GFP in a Cre-dependent manner. The authors characterise the properties of the AIS and noR when labelled with GFP to show that it has no adverse effects on the properties of the AIS and noR, as well as the intrinsic excitability of neurons. They also show that this mouse line can be used to follow AIS plasticity in vitro and visualise the AIS of neurons in vivo. This is a very useful and timely tool that will make an important impact in the field.

In general, it is clear that this mouse line can label the AIS and noR and will certainly be a useful tool for the community. Although the authors provide a thorough description of the intrinsic properties of neurons and some of the structural properties of the AIS and noR, there are some aspects of these experiments that could be refined to help show that tagging Ank-G with GFP is mostly inert. In particular, some of the basal properties of the AIS (length, position, molecular distribution) following tagging with GFP are not fully explored.

An important advantage of this mouse line is the ability to follow the AIS in live neurons. This is particularly important for imaging the dynamics and plasticity of the AIS, which the authors show is possible both in vitro and ex vivo. Finally, they also show that it is possible to image the AIS in vivo, a finding that opens many experimental doors for the future.

Reviewer #1 (Public Review):

Genetic, physiological, and environmental manipulations that increase roaming increase leaving rates. The connection between increased roaming and increased leaving is lost when tax4-expressing sensory neurons are inactivated. This study is conceptually important in its characterization of worm behaviors as time-series of discrete states, a promising framework for understanding behavioral decisions as algorithms that govern state transitions. This framework is well-established in other animals, thanks to Berman and others, but relatively new to worms.

A key discovery is that lawn leaving behavior is probabilistically favored in states of behavioral arousal. I like the use of response-triggered averages (triggered on leaving events) that illustrate a "state-dependent receptive field" of the behavioral response. Response-triggered averages are common in sensory neuroscience, used, for example, to characterize the diverse "stimulus-dependent receptive fields" of different retinal ganglion cell types. It's nice to adapt the idea to illustrate the state-dependence of behavioral state transitions.

The simplest metric of arousal state is crawling speed. When animals crawl faster, they are more likely to leave lawns. A more sophisticated metric of behavioral context is whether the animal is in a "roaming" or "dwelling" state, two-state HMM modeling from previous work (Flavell et al., 2013). Roaming animals are more likely to leave lawns than dwelling animals. Different autoregressive HMM tools can segment worm behavior into 4-states. Also with ARHMMs, the most aroused state is again the state that promotes lawn-leaving.

(With the AR-HMM, I have a small quibble in its characterization as "orthogonal" to the 2-state HMM. Orthogonal has a precise mathematical meaning, but here orthogonal is taken loosely to only mean "very different". I'd prefer the authors just call them "very different" and not use mathematical terms so loosely.)

HMM analysis seems to disentangle effects that were lumped by the simpler metric of overall speed. Crawling speed before lawn leaving events, when analyzed only within roaming periods, is only higher for ¡1 min before the event. I presume that the higher speed that is observed for several minutes before lawn leaving when all states are taken into account (e.g., Fig 1J, Fig 2A, and others) reflects the tendency to be in the faster roaming state than the slower dwelling state for several minutes before lawn leaving? If this is correct, it would be nice for the authors to be explicit about this interpretation, to help the reader understand what is going on.

My principal worry is about the possible artifact if worms are more likely to be at lawn boundaries when moving quickly or in an arousal state (roaming in the 2-state HMM or in state 3 in the AR-HMM)? Lawn-leaving events only occur when the animal is at lawn boundaries. If animals are more likely to be at lawn boundaries when aroused, this should artificially increase the likelihood that these states precede lawn-leaving behaviors for a trivial environment-dependent reason instead of their interesting internal state-dependent reason. The authors might consider trying to disentangle the state-dependent statistics of lawn edge proximity when assessing by how much arousal states precede lawn-leaving events. I realize this is could be a formidable analytical challenge.

One recourse is to align speed, HMM, and AR-HMM states to the other behavioral events that only happen at lawn boundaries. When they do this for head poke-reversals in Figure 2-supplement 3, they also observe an (albeit modest) increase in arousal states before head poke-reversals. It should be easy to also compare what happens with head poke-forward and head poke-pause to better understand potential artifacts in quantifying edge-associated events. In any case, this concern and their strategies to address it should be discussed for clarity and transparency.

The authors use diverse environmental, genetic, and optogenetic perturbations to regulate the roaming state, thereby regulating the statistics of leaving in the expected manner. One surprise is that feeding inhibition evokes roaming and lawn-leaving in both pdfr-1 and tph-1 mutants, even though the tph-1-expressing NSM neurons have been shown to sense bacterial ingestion and food availability. I'm curious, is there anything in these new results that is inconsistent with previous claims by Rhoades et al., 2019, or did Rhoades et al. simply not do these tests?

Another surprise is that evoking roaming does not evoke leaving in tax-4 mutants (which is something of an internal control that argues against the worry that roaming artificially increases the likelihood of leaving, see above). Without sensory neuron activity, worms are only more likely to roam for a minute before leaving rather than roaming for several minutes before leaving like wild-type (Figure 6C). ASJ seems to be the most important sensory neuron in this coupling between roaming and leaving (which is uncoupled when sensory neurons are inactivated).

I'm a little puzzled why the wild-type animals shown in Figure 6C show elevated roaming for several minutes before leaving events, whereas the wild-type animals shown in Figures 4I,J,K show elevated roaming for only about a minute, not much different than tax-4 mutants. Am I missing something? What is different about these different wild-type animals?

Reviewer #1 (Public Review):

The authors demonstrate that reactivation of mild vs strong aversive contextual associations produces dissociable effects on fos expression across a wide network of relevant brain regions. Mild, 2-shock memory recruits a 'small-world' network in which amygdalar regions are functionally connected to other regions that modulate their activity and behavioral output, whereas strong, 10-shock memory isolates amygdalar nuclei from the rest of the network. These different patterns of correlated neural activity correspond with functional/behavioral differences - the authors confirm that weak, 2-shock memory is more effectively extinguished and is susceptible to reconsolidation relative to strong, 10-shock memory.

One major drawback of the manuscript is the fact that the data were collected from male subjects only. One might expect similar behavioral outcomes from male and female rats receiving 2-shock and 10-shock training. However, increasing attention to sex as a biological variable has revealed an interesting truth, namely that males and females can engage distinct neural pathways to arrive at the same behavioral destination. It should not be taken for granted that retrieval of aversive contextual associations would reproduce the same networks in females, and, as such, the manuscript does not give a complete accounting of the phenomenon under study.

The aversive associative memories described by the authors are characterized as mild or strong. More analysis of the meaning of memory strength, and its relationship to conditioning parameters, is needed. In particular, the authors should discuss issues such as amount of training, US magnitude, and rate of shock delivery. If amount of training is important, would 2 vs 10 presentations of a milder shock produce the same networks at retrieval? Would a larger shock require fewer presentations to isolate amygdalar regions from the rest of the network? If the shocks were presented at the same rate during training, would you get the same result in both groups? More data examining these questions would be ideal, but, in the absence of that, a discussion of these issues is needed and missing from the manuscript in its current form.

Reviewer #1 (Public Review):

The present study provides a phylogenetic analysis of the size prefrontal areas in primates, aiming to investigate whether relative size of the rostral prefrontal cortex (frontal pole) and dorsolateral prefrontal cortex volume vary according to known ecological or social variables.

I am very much in favor of the general approach taken in this study. Neuroimaging now allows us to obtain more detailed anatomical data in a much larger range of species than ever before and this study shows the questions that can be asked using these types of data. In general, the study is conducted with care, focusing on anatomical precision in definition of the cortical areas and using appropriate statistical techniques, such as PGLS. That said, there are some points where I feel the authors could have taken their care a bit further and, as a result, inform the community even more about what is in their data.

The introduction sets up the contrast of 'ecological' (mostly foraging) and social variables of a primate's life that can be reflected in the relative size of brain regions. This debate is for a large part a relic of the literature and the authors themselves state in a number of places that perhaps the contrast is a bit artificial. I feel that they could go further in this. Social behavior could easily be a solution to foraging problems, making them variables that are not in competition, but simply different levels of explanation. This point has been made in some of the recent work by Robin Dunbar and Susanne Shultz.

In a similar vein, the hypotheses of relating frontal pole to 'meta-cognition' and dorsolateral PFC to 'working memory' is a dramatic oversimplification of the complexity of cognitive function and does a disservice to the careful approach of the rest of the manuscript. One can also question the predicted relationship between frontal pole meta-cognition and social abilities versus foraging, as Passingham and Wise show in their 2012 book that it is frontal pole size that correlates with learning ability-an argument that they used to relate this part of the brain to foraging abilities. I would strongly suggest the authors refrain from using such descriptive terms. Why not simply use the names of the variables actually showing significant correlations with relative size of the areas?

The major methodological judgements in this paper are of course in the delineation of the frontal pole and dorsolateral prefrontal cortex. As I said above, I appreciate how carefully the authors describe their anatomical procedure, allowing researchers to replicate and extend their work. They are also careful not to relate their regions of interest to precise cytoarchitectonic areas, as such a claim would be impossible to make without more evidence. That said, there is a judgement call made in using the principal sulcus as a boundary defining landmark for FP in monkeys and the superior frontal sulcus in apes. I do not believe that these sulci are homologous. Indeed, the authors themselves go on to argue that dorsolateral prefrontal cortex, where studied using cytoarchitecture, stretches to the fundus of principal sulcus in monkeys, but all the way to the inferior frontal sulcus in apes. That means that using the fundus of PS is not a good landmark. Of course, any definition will attract criticism, so the best solution might be to run the analysis multiple times, using different definitions for the areas, and see how this affects results.

If I understand correctly, the PGLS was run separately for the three brain measure (whole brain, FP, DLPFC). However, given that the measures are so highly correlated, is there an argument for an analysis that allows testing on residuals. In other words, to test effects of relative size of FP and DLPFC over and above brain size?

In the discussion and introduction, the authors discuss how size of the area is a proxy for number of neurons. However, as shown by Herculano-Houzel, this assumption does not hold across species. Across monkeys and apes, for instance, there is a different in how many neurons can be packed per volume of brain. There is even earlier work from Semendeferi showing how frontal pole especially shows distinct neuron-to-volume ratios.

Overall, I think this is a very valuable approach and the study demonstrates what can now be achieved in evolutionary neuroscience. I do believe that they authors can be even more thorough and precise in their measurements and claims.

Reviewer #1 (Public Review):

In this study, the authors have compared object recognition in humans and rats. To this end, they trained rats to touch a target object shown along with a distractor object. The rats were initially trained on a base pair, and then tested on sets of variant pairs where the target or distractor could be transformed through size, position, 3d rotation or lighting variations. In addition, the authors then used a cDNN to find image pairs that would elicit different performance from early vs late layers, and tested rats and humans on these pairs (zero vs high and high vs zero protocols). A similar protocol was used for humans as well to get their performance on the base pair and test pairs. Finally the authors find the correlation between cDNN performance on each layer and rat or human performance across all test protocols. The main finding is that rats show the best match to earlier cDNN layers compared to humans. Based on this the authors conclude that humans and rats show contrasting performance on object recognition.

General comments<br /> Whether rats and humans have similar object representations is an interesting and fundamental question, and I commend the authors for their extensive matched experiments on rats and humans. However, the conclusions must be tempered by the fact that the authors are testing a limited set of object variations derived from just two objects. There are also potentially substantial differences in the tasks given to rats and humans, if I understand the methods and procedures correctly. My concerns are detailed below.

My main concern is that the authors find very low agreement between rats and humans on comparable tasks, but it would be important if they can identify qualitative differences in the performance. For instance, can they say that rats are using low-level visual cues compared to humans. They could compare several low-level visual models (see below) and report how human and rat accuracy compares to each of these models. Since the visual representations of cDNNs are unknown, such a comparison would be useful.

The authors should also discuss the potential reason for the human-rat differences too, and importantly discuss whether these differences are coming from the rather unusual approach of training used in rats (i.e. to identify one item among a single pair of images), or perhaps due to the visual differences in the stimuli used (what were the image sizes used in rats and humans?). Can they address whether rats trained on more generic visual tasks (e.g. same-different, or category matching tasks) would show similar performance as humans?

I also found that a lot of essential information is not conveyed clearly in the manuscript. Perhaps it is there in earlier studies but it is very tedious for a reader to go back to some other studies to understand this one. For instance, the exact number of image pairs used for training and testing for rats and humans was either missing or hard to find out. The task used on rats was also extremely difficult to understand. An image of the experimental setup or a timeline graphic showing the entire trial with screenshots would have helped greatly.

The authors state that the rats received random reward on 80% of the trials, but is that on 80% of the correctly responded trials or on 80% of trials regardless of the correctness of the response? If these are free choice experiments, then the task demands are quite different. This needs to be clarified. Similarly, the authors mention that 1/3 of the trials in a given test block contained the old base pair - are these included in the accuracy calculations?

It would be good for the authors to articulate more clearly the nature of the differences between humans and rats. For instance, rat behaviour was found to be correlated with low-level image properties like brightness, whereas presumably, human behaviour is not. It would be useful if the authors can compare rat behaviour against several possible alternative models, including the dCNN layers in Figure 4. These models could include other rats (giving a reliability estimate), luminance based models, contrast based models, models based on V1 simple cells, etc - these models would elucidate further the nature of the rat performance. A similar analysis could be done for human performance.

The authors were injecting noise with stimuli to cDNN to match its accuracy to rat. However, that noise potentially can interacted with the signal in cDNN and further influence the results. That could generate hidden confound in the results. Can they acknowledge/discuss this possibility?

The authors claimed that discrimination task in rats was more dependent on concavity than component arrangement (figure 1 left panel). But that could be just an artifact due to sampling more values of concavity than component arrangement. In that case these two attributes are not comparable at all. Could the authors address this issue in some way.

Reviewer #1 (Public Review):

The authors were trying to investigate whether viral IBs are involved in antagonizing IFN-I production during EBOV trVLPs infection. They found that IRF3 is hijacked and sequestered into EBOV IBs after viral infection, thereby leading to the spatial isolation of IRF3 with TBK1 and IKKε. In such a progress, the activity of IRF3 is suppressed and downstream IFN-I induction is inhibited. The authors designed many experiments, such as the PLA that examined the colocalization, to support their conclusions. However, necessary negative controls were missed in several assays. More key index is needed to be examined in several assays.

The paper is well organized and most data in this paper could support the conclusions, while there are several issues that need to be further solved.

1) In Figure 2-4, authors should examine the expression of downstream IFNs as well as the phosphorylation and nuclear localization of IRF3 to further prove the suppression of IRF3 activity by infecting with trVLPs.

2) In Figure 5, to better prove the conclusion that EBOV NP and VP35 play an important role in sequestering IRF3 in IBS, authors should add the "NP+VP35+VP30" and "NP+VP35+VP24" groups to reperform the assay.

3) In Figure 6f, the expression of STING should be examined by immunostaining to show the knockdown efficiency in trVLPs-infected cells.

Reviewer #1 (Public Review):

The enteroviruses comprise a medically important genus in the large and diverse picornavirus family, and are known to be released without lysis from infected cells in large vesicles containing numerous RNA genome-containing capsids - a feature allowing for en bloc transmission of multiple viral genomes to newly infected cells that engulf these vesicles. SIRT-1 is an NAD-dependent protein deacetylase that has numerous and wide ranging effects on cellular physiology and homeostasis, and it is known to be engaged in cellular responses to stress and autophagy.

Jassey et al. show that RNAi depletion of SIRT-1 impairs the release of enterovirus D-68 (EV-D68) in EVs recovered from the supernatant fluids of infected cells using a commercial exosome isolation kit. The many functions attributed to SIRT-1 in the literature reflect its capacity to deacetylate various cell proteins engaged in transcription, DNA repair, and regulation of metabolism, apoptosis and autophagy. However, Jassey et al. make the surprising claim that the proviral role of SIRT-1 in promoting enterovirus release is not dependent on its deacetylase activity. Fig. S1C is crucial to this suggestion, as it is said to show that reconstituting expression with a catalytically-inactive mutant can rescue virus release from SIRT-1 depleted cells. However, no information is provided concerning the levels of endogenous and ectopically-expressed SIRT-1 proteins in this experiment, making it very difficult to interpret the results. Is the mutant SIRT-1 protein expressed at a higher level than the non-mutant protein? Is there a 'sponging' effect with these transfections that lessens the siRNA efficiency and reduces knockdown of the endogenous protein? Fig. S1B and Fig. 4C convincingly show that EX527, a small molecule inhibitor of the deacetylase activity of SIRT-1, inhibits extracellular release of the virus. This suggests that the deacetylase activity of SIRT-1 is in fact required for the proviral effect of SIRT-1. This is a fundamentally important question that will require more investigation.

Fig. 6 shows how SIRT-I knockdown impacts the release of enterovirus D68 in EVs recovered from cell culture supernatant using a commercial 'Total Exosome Isolation Kit'. The authors should describe the principle this kit exploits to isolate 'exosomes' (affinity isolation?) and specify which antibodies it involves (anti-phosphatidylserine, anti-CD63, others?) This could impact the outcome of these experiments, and moreover is important to include in the long-term scientific record. The authors are appropriately cautious in describing the vesicles they presume to be isolated by the kit as simply 'extracellular vesicles', since there are multiple types of EVs with very different mechanisms of biogenesis, of which 'exosomes' are but one specific type. It would have been more elegant had the authors shown that SIRT-1 is required for EV-D68 release in detergent-sensitive vesicles with low buoyant density in isopycnic gradients, and to characterize the size and number of viral capsids in these vesicles by electron microscopy.

Fig. 6 shows that SIRT-1 depletion upregulates CD63 expression, but has no apparent impact on the release of CD63-positive 'EVs' from uninfected cells. EV-D68 infection also upregulates CD63 expression in SIRT-1 replete cells, and in this case, increases the release of CD63-positive EVs. The combination of infection and SIRT-1 depletion massively upregulates CD63 expression, but appears to eliminate the enhanced release of CD63-positive EVs resulting from infection alone. These are interesting results, from which the authors infer CD63 is associated with EVs containing EV-D68. But, do we know this? Can a CD63 pulldown immunoprecipitate EV-D68 capsid proteins or viral RNA? CD63 is strongly associated with exosomes released from cells through the multi-vesicular body pathway, which are distinct from the LC3-positive EVs released by secretory autophagy that have previously been associated with enteroviruses. The authors suggest that 'knockdown of SIRT-1 may prevent the exocytosis of CD63-positive EVs", but this is a very broad claim (and not really demonstrated by Fig. 6): it requires a clearer definition of what the authors mean by 'exocytosis' and a much more detailed analysis of the size and buoyant density of EVs released in a SIRT-1-dependent process.

The authors suggest that almost all EV-D68 released from infected cells is released without cell lysis in EVs. However, they generally show data from only a single time point following infection (5 or 6 hrs post-infection). It would have been interesting to see a more complete temporal analysis, and to know whether a high proportion of virus continues to be released in EVs, or if it is swamped out ultimately by lytic release of nonenveloped virus.

Fig. 1D indicates that a small fraction of SIRT-1 leaks from the nucleus in EV-D68 infected cells. The authors suggest this is due to targeted nuclear export, rather than simply leaky nuclear pores which are well known to exist in enterovirus-infected cells. The authors present similar fluorescent microscopy data showing inhibition of TFEB export in leptomycin-B treated cells in Fig. S2A in support of their claim that this is specific SIRT-1 export, but these data are far from convincing - there is equivalent residual TFEB and SIRT-1 in the cytoplasm of the treated cells. Quantitative immunoblots of cytoplasmic and nuclear cell fractions might prove more compelling.

Finally, the authors should be more specific in describing the viruses they have studied (EV-D68 and PV). It would be preferable to describe these as 'enteroviruses' (including in the title of the manuscript), rather than more broadly as 'picornaviruses'. There is no certainty that the requirement for SIRT-1 in non-lytic release of virus extends to hepatoviruses or other picornaviral genera, for which mechanisms of nonlytic release may be quite different.

Reviewer #1 (Public Review):

Nitta et al, in their manuscript titled, "Drosophila model to clarify the pathological significance of OPA1 in autosomal dominant optic atrophy." The novelty of this paper lies in its use of human (hOPA1) to try to rescue the phenotype of an OPA1 +/- Drosophilia DOA model (dOPA). The authors then use this model to investigate the differences between dominant-negative and haploinsufficient OPA1 variants. The value of this paper lies in the study of DN/HI variants rather than the establishment of the drosophila model per se as this has existed for some time and does have some significant disadvantages compared to existing models, particularly in the extra-ocular phenotype which is common with some OPA1 variants but not in humans. I judge the findings of this paper to be valuable with regards to significance and solid with regards to the strength of the evidence.

Suggestions for improvements:

1. Stylistically the results section appears to have significant discussion/conclusion/inferences in each section with reference to existing literature. I feel that this information would be better placed in the separate discussion section. E.g. lines 149-154

2. I do think further investigation as to why a reduction of mitochondria was noticed in the knockdown. There are conflicting reports on this in the literature. My own experience of this is fairly uniform mitochondrial number in WT vs OPA1 variant lines but with an increased level of mitophagy presumably reflecting a greater turnover. There are a number of ways to quantify mitochondrial load e.g. mtDNA quantification, protein quantification for tom20/hsp60 or equivalent. I feel the reliance on ICC here is not enough to draw conclusions. Furthermore, mitophagy markers could be checked at the same time either at the transcript or protein level. I feel this is important as it helps validate the drosophila model as we already have a lot of experimental data about the number and function of mitochondria in OPA+/- human/mammalian cells.

3. Could the authors comment on the failure of the dOPA1 rescue to return their biomarker, axonal number to control levels. In Figure 4D is there significance between the control and rescue. Presumably so as there is between the mutant and rescue and the difference looks less.

4. The authors have chosen an interesting if complicated missense variant to study, namely the I382M with several studies showing this is insufficient to cause disease in isolation and appears in high frequency on gnomAD but appears to worsen the phenotype when it appears as a compound het. I think this is worth discussing in the context of the results, particularly with regard to the ability for this variant to partially rescue the dOPA1 model as shown in Figure 5.

5. I feel the main limitation of this paper is the reliance on axonal number as a biomarker for OPA1 function and ultimately rescue. I have concerns because a) this is not a well validated biomarker within the context of OPA1 variants b) we have little understanding of how this is affected by over/under expression and c) if it is a threshold effect e.g. once OPA1 levels reach x%. I think this is particularly relevant when the authors are using this model to make conclusions on dominant negativity/HI with the authors proposing that if expression of a hOPA1 transcript does not increase opa1 expression in a dOPA1 KO then this means that the variant is DN. The authors have used other biomarkers in parts of this manuscript e.g. ROS measurement and mito trafficking but I feel this would benefit from something else particularly in the latter experiments demonstrated in figure 5 and 6.

6. Could the authors clarify what exons in Figure 5 are included in their transcript. My understanding is transcript NM_015560.3 contains exon 4,4b but not 5b. According to Song 2007 this transcript produces invariably s-OPA1 as it contains the exon 4b cleavage site. If this is true, this is a critical limitation in this study and in my opinion significantly undermines the likelihood of the proposed explanation of the findings presented in Figure 6. The primarily functional location of OPA1 is at the IMM and l-OPA1 is the primary opa1 isoform probably only that localizes here as the additional AA act as a IMM anchor. Given this is where GTPase likely oligomerizes the expression of s-OPA1 only is unlikely to interact anyway with native protein. I am not aware of any evidence s-OPA1 is involved in oligomerization. Therefore I don't think this method and specifically expression of a hOPA1 transcript which only makes s-OPA1 to be a reliable indicator of dominant negativity/interference with WT protein function. This could be checked by blotting UAS-hOPA1 protein with a OPA1 antibody specific to human OPA1 only and not to dOPA1. There are several available on the market and if the authors see only s-OPA1 then it confirms they are not expressing l-OPA1 with their hOPA1 construct.

Reviewer #1 (Public Review):

Summary:

Favate et al. measure the relative levels of metabolites in 12 Escherichia coli strains isolated from different replicate populations after 50,000 generations of the Lenski long-term laboratory evolution experiment. They use untargeted LC/MS methods that include standards and report both positive and negative ionization mode measurements. They initially use principal component analysis (PCA) to broadly compare how the metabolomes of these strains are similar and different. Then, they describe several instances where the changes in metabolite abundance they see in specific pathways correlate with mutations that lead to changes in the expression of genes that encode enzymes in those pathways.

Strengths:

The statistical analyses and presentation of the high-throughput data are excellent. The most compelling results are communicated in wonderful figures that integrate their measurements of metabolite levels in this study with results from a prior study they conducted looking at changes in gene expression levels in the same bacterial strains. These sections include the ones describing large increases in NAD(P) pools due to mutations in nadR, changes in the levels of arginine and related compounds due to mutations in argR, and changes in metabolites from glycolysis and the TCA cycle related to iclR and arcB.

Weaknesses:

After addressing prior reviews, the main remaining weaknesses of the study are limitations inherent to the metabolomics approach that are noted by the authors. Namely, that it gives a static and incomplete picture of cellular metabolism, lacking any information about flux and missing measurements for many metabolites. Additional biochemical and genetic experiments will be necessary to fully test the hypotheses suggested by the metabolomics data.

Impact and Significance:

While there has been past speculation about the effects of LTEE mutations on metabolism, this study measures changes in the levels of metabolites in related metabolic pathways for the first time. Therefore, it provides useful information about how metabolism evolves, in general, and will also be a useful resource those studying other aspects of the LTEE related to metabolism, such as contingency in the evolution of citrate utilization.

Reviewer #1 (Public Review):

This paper provides new evidence on the relationship between genetic/chromosome divergence and capacity for asexual reproduction (via unreduced, clonal gametes) in hybrid males or females. Whereas previous studies have focussed just on the hybrid combinations that have yielded asexual lineages in nature, the authors take an experimental approach, analysing meiotic processes in F1 hybrids for combinations of species spanning different levels of divergence, whether or not they form asexual lineages in nature. As such, the findings here are a substantial advance towards understanding how new asexual lineages form.

The quality of the work is high, the analyses are sound, and the authors sensibly link their observations to the speciation continuum. I should also add that the cytogenetic work here is just beautiful!

A key finding is that the precondition for asexual reproduction - the formation of unreduced gametes - is not unusual among hybrid females, so that we have to consider other factors to explain the rarity of asexual species - a major unresolved issue in evolutionary biology. This work also highlights a previously overlooked effect of chromosome organisation on speciation.

Joint Public Review:

The flowering plant Capsella bursa-pastoris is an allotetraploid formed from the genomes of Capsella orientalis and Capsella grandiflora. An outstanding question in the evolution of allotetraploids is the relative contribution of immediate consequences of allopolyploidization vs. long-term evolution after the event. The authors address this question by re-synthesizing the allotetraploid in the lab using the two progenitor species, and comparing its phenotypic and gene expression variation to naturally occurring C. bursa-pastoris. They compared five categories of plant: the two progenitors of the allopolyploid, hybrids resynthesized from the progenitors with a whole-genome duplication either before or after the hybridization event, and the naturally occurring allopolyploid. Two lines of evidence were used: phenotypic data from the plants grown in a common environment, and RNAseq data from a subset of the plants.

The phenotypic data indicate that the selfing syndrome of C. bursa-pastoris likely evolved after the initial allopolyploidization event, and that pollen and seed viability recovered following the allopolyploidization event. They find evidence primarily for long-term phenotypic evolution towards a selfing syndrome in C. bursa-pastoris, and a combination of short and long-term changes to gene expression.

The manuscript is thorough and provides lots of new insights into the mechanisms driving evolution in allopolyploids. The work provides an interesting and valuable contribution to the field's understanding of how expression evolves in interaction with hybridization and polyploidy. Particularly in combination with the team's previous study on these lines, this experimental design is effective for separating the contributions of hybridization, WGD, and evolution over time.

>>The results are compelling but would benefit from small clarifications to the methods and statistics to account for possible positional effects in the growth chamber. Using a linear mixed model rather than a simple ANOVA would solve this problem.

>>The RNAseq data are used to explore overall expression patterns (using multi-dimensional scaling), patterns of differential expression (additive, dominant, or transgressive), and homeolog expression bias, and to determine the relative contributions of the original allopolyploidization event and subsequent evolution. Statistical cutoffs were used to categorize gene expression patterns, but the description and categorization of these patterns appears to have been largely qualitative and might be strengthened by including more statistical detail in questions like whether homeologous expression bias did indeed show more variation in resynthesized and evolved allopolyploids.

>>The study includes evidence that homeolog expression bias (overrepresentation of an allele from one species) results in part from homeologous synapsis (uneven inheritance of chromosome segments). These deviations from patterns consistent with 2:2 inheritance of genomic regions are highly variable between individuals in resynthesized allopolyploids but appeared to be mostly consistent within (but not between) populations in natural C. bursa-pastoris. This is intriguing evidence that segregation can be an important source of variation in allopolyploids. However, it was limited by the difficulty of inferring homeologous recombination breakpoints with RNAseq data because of the scale of recombination in wild populations (rather than resynthesized allopolyploids). In the future identifying such breakpoints will be an interesting direction for this and other allopolyploid systems.

>>The study could also valuably explore what kinds of genes experienced what forms of expression evolution. A brief description of GO terms frequently represented in genes which showed strong patterns of expression evolution might be suggestive of which selective pressures led to the changes in expression in the C. bursa-pastoris lineage, and to what extent they related to adaptation to polyploidization (e.g. cell-cycle regulators), compensating for the initial pollen and seed inviability or adapting to selfing (endosperm- or pollen-specific genes), or adaptation to abiotic conditions.

Reviewer #1 (Public Review):

The paper offers some potentially interesting insight into the allosteric communication pathways of the CTFR protein. A mutation to this protein can cause cystic fibrosis and both synthetic and endogenous ligands exert allosteric control of the function of this pivotal enzyme. The current study utilizes Gaussian Network Models (GNMs) of various substrate and mutational states of CFTR to quantify and characterize the role of individual residues in contributing to two main quantities that the authors deem important for allostery: transfer entropy (TE) and cross correlation. I found the TE of the Apo system and the corresponding statistical analysis particularly compelling. I found it difficult, however, to assess the limitations of the chosen model (GNM) and thus the degree of confidence I should have in the results. This mainly stems from a lack of a proposed mechanism by which allostery is achieved in the protein. Proposing a mechanism and presenting logical alternatives in the introduction would greatly benefit this manuscript. It would also allow the authors to place the allosteric mechanism of this protein in the broader context of protein allostery.

Reviewer #1 (Public Review):

Liu et al. investigated the brain functional lateralization in typically developing infants and infants with congenital sensorineural hearing loss (SNHL) to understand how early auditory deprivation disrupts the development of functional network organization using resting-state fNIRS imaging and the graph theory approach. They found that hemispheric asymmetry formed in early life and the initial lack of auditory exposure affected the typical development of functional network asymmetry in infants with hearing loss. Although the infants with hearing loss exhibited a balance between information segregation and integration within two hemispheres, consistent with the typically developing (TD) controls, the development of the leftward hemispheric asymmetry in network efficiency measures was disrupted. At the regional level, infants with hearing loss exhibited aberrant development of hemispheric network asymmetry especially in frontal regions.

Strengths:<br /> The strengths of this study include its focus on a relatively understudied area of research, namely the impact of hearing loss on brain network asymmetry in infants. The study used advanced neuroimaging techniques to examine the development of cerebral asymmetry in infants with hearing loss and compared their results to typically developing controls. The study's findings provide valuable insights into the importance of early auditory exposure for typical brain development. Overall, this study contributes to our understanding of the brain functional network changes underlying hearing loss and has important implications for early intervention and treatment strategies.

Weaknesses:<br /> Although this study does have strengths in principle, the weaknesses of this work are that the key claims cannot be fully supported due to inappropriate statistical analyses, the theoretical significance and the narrative logic are not well presented. In particular:

Theoretical significance: In the Introduction, the authors did not nicely explain why it is important to investigate how the brain functional network asymmetry develops in SNHL infants, and what new knowledge this analytical approach can tell the readers. It is insufficient to merely state that few studies have focused on this. The authors did not elaborate on the broader significance of studying the hemispherical asymmetry in SNHL infants.

Narrative logic: The organization of the Results part needs substantial improvement. The authors did not provide an overview of the analysis at the beginning of each results section, including the relationships between different measurements, the purpose of each analysis, the specific methods employed, and the meaning of the neural index used. It is therefore very difficult to understand why the authors conducted each analysis and how it contributes to the main narrative of the study. For instance, what is the relationship between the small-world properties within the hemisphere and the hemispherical asymmetry of network efficiency? What is the relationship between global/local efficiency and regional nodal efficiency? What global efficiency and local efficiency reflect? It is crucial to clarify and justify the analysis.

Problems on the statistics:<br /> 1) To support the major claim that the left hemisphere dominance of the functional network organization was significantly disrupted in SNHL infants, the authors should also report a statistically significant interaction (between leftward hemispheric asymmetry and type of infants), but instead they only reported that one effect (the leftward hemispheric asymmetry in the TD infants) was statistically significant, whereas the other effect (the leftward hemispheric asymmetry in the infants with SNHL) was not. And why not directly use asymmetry index and compare it between groups?<br /> 2) The necessary statistical values to support the conclusions are missing in several places. For example, Lines 111 - 113 and section 2.4.<br /> 3) The authors conducted multiple comparisons without correction in section 2.3 and section 2.5. It is likely that some of these comparisons would not survive the multiple comparison correction; therefore, the results need to be rephrased and the findings reinterpreted accordingly.<br /> 4) Inconsistent results exist. If "a significant group × age interaction effect on the mean AI of nodal efficiency was observed only in the frontal cortex, while other regions did not exhibit such an interaction" (Line 170-172), and the authors "investigated the group × age interaction effect on the mean nodal efficiencies of the frontal regions for each hemisphere" (Line 178-179), why "a significant interaction effect was observed in the frontal, temporal, parietal, and occipital regions of the left hemisphere" (Line 179-182)?

Reviewer #1 (Public Review):

Olszyński and colleagues present data showing variability from canonical "aversive calls", typically described as long 22 kHz calls rodents emit in aversive situations. Similarly long but higher-frequency (44 kHz) calls are presented as a distinct call type, including analyses both of their acoustic properties and animals' responses to hearing playback of these calls. While this work adds an intriguing and important reminder, namely that animal behavior is often more variable and complex than perhaps we would like it to be, there is some caution warranted in the interpretation of these data. The authors also do not provide adequate justification for the use of solely male rodents. With several reported sex differences in rat vocal behaviors this means caution should be exercised when generalizing from these findings.

Firstly, the authors argue that the shift to higher-frequency aversive calls is due to an increase in arousal (caused by the animals having received multiple aversive foot shocks towards the end of the protocols). However, it cannot be ruled out that this shift would be due to factors such as the passage of time and increase in fatigue of the animals as they make vocalizations (and other responses) for extended periods of time. In fact the gradual frequency increase reported for 22kHz calls and the drop in 44 kHz calls the next day in testing is in line with this.

Secondly, regarding the analysis where calls were sorted using DBSCAN based on peak frequency and duration, it is not surprising that the calls cluster based on frequency and duration, i.e. the features that are used to define the 44 kHz calls in the first place. Thus presenting this clustering as evidence of them being truly distinct call types comes across as a circular argument. The sparsity of calls in the 30-40 kHz range (shown in the individual animal panels in Figure 2C) could in theory be explained by some bioacoustics properties of rat vocal cords, without necessarily the calls below and above that range being ethologically distinct.

The behavioral response to call playback is intriguing, although again more in line with the hypothesis that these are not a distinct type of call but merely represent expected variation in vocalization parameters. Across the board animals respond rather similarly to hearing 22 kHz calls as they do to hearing 44 kHz calls, with occasional shifts of 44 kHz call responses to an intermediate between appetitive and aversive calls. This does raise interesting questions about how, ethologically, animals may interpret such variation and integrate this interpretation in their responses. However, the categorical approach employed here does not address these questions fully.

In sum, rather than describing the 44kHz long calls as a new call type, it may be more accurate to say that sometimes aversive calls can occur at frequencies above 22 kHz. Individual and situational variability in vocalization parameters seems to be expected, much more so than all members of a species strictly adhering to extremely non-variable behavioral outputs.

Reviewer #1 (Public Review):

The authors have studied the effect of temperature on the interspecific interaction strength of coastal marine fish communities, using eDNA samples. Their introduction describes the state of the art concerning the dynamics of interspecific interactions in ecological communities. This introduction is well written and highly information dense, summarizing all that the reader needs to know to further understand their study setup and execution.

The authors hypothesize that water temperature changes could have an effect on the interspecific interaction strength between marine fishes, and they studied this with a two year long, bi-weekly eDNA sampling campaign at 11 study sites in Japan with different temperature gradients. These 550 water samples were analysed for fish biodiversity through eDNA-metabarcoding using MiFish primers. By using the most abundant fish species as an internal spike in and quantifying the copy numbers from this species by qPCR, the authors were able estimate DNA copy numbers for the total dataset. From the 50 most frequently detected fish species in these samples they showed that temperature affected the interspecific interaction strength between some species. Their work provides a highly relevant approach to perform species-interaction strength analysis based on eDNA biodiversity assessments, and as such provides a research framework to study marine community dynamics by eDNA, which is highly relevant in the study of ecosystem dynamics. The models and analytical methods used are clearly described and made available, enabling application of these methods by anyone interested in applying it to their own site and species group of interest.

Strengths:

The authors have a study setup that is suitable to measure the effects of temperature of the eDNA diversity, and have taken a large number of samples and all appropriate controls to be able to accurately measure and describe these dynamics. The applied internal spike in to enable relative eDNA copy number quantification is convincing.

Weaknesses:

The authors were able to find a correlation between water temperature and interaction strengths observed. However, since water temperature is dependent on many environmental variables that are either directly or indirectly influencing ecosystem dynamics, it is hard to prove a direct correlation between the observed changes in community dynamics and the temperature alone

Reviewer #1 (Public Review):

This study by Cao et al. demonstrates role of Neutrophil in clearing apoptotic hepatocytes by directly burrowing into the apoptotic hepatocytes and ingesting the effete cells from inside without causing inflammation. The authors applied intravital microscopy, Immunostaining and electron microscopy to visualize perforocytosis of neutrophil in hepatocytes. They also found that neutrophil depletion impairs the clearance of apoptotic hepatocytes causing impaired liver function and generation of autoantibodies, implying a role of defective neutrophil- mediated clearance of apoptotic cells in Autoimmune Liver disease. The experiments were well designed and conducted, the results were reasonably interpreted, and the manuscript was clearly written with logical inputs.

Further studies to explore the signals/mechanisms that determine why neutrophil specifically target apoptotic hepatocytes in liver would be of great clinical significance.

Reviewer #1 (Public Review):

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

Main comments:<br /> 1. The paper is well written and easy to follow. The schematics help in understanding how the toolbox works and the examples provide an idea of the results that the user can obtain.

2. As I understand it, the main purpose of the paper should be to facilitate the usage of the toolbox. For this reason, I have missed a more explicit link to the actual code. As I see it, researchers will read this paper to figure out whether they can use MotorNet to simulate their experiments, and how they should proceed if they decide to use it. I'd say the paper provides an answer to the first question and assures that the toolbox is very easy to install and use. Maybe the authors could support this claim by adding "snippets" of code that show the key steps in building an actual example.

3. The results provided in Figures 1, 4, 5 and 6 are useful, because they provide examples of the type of things one can do with the toolbox. I have a few comments that might help improving them:<br /> a. The examples in Figures 1 and 5 seem a bit redundant (same effector, similar task). Maybe the authors could show an example with a different effector or task? (see point 4).<br /> b. I missed a discussion on the relevance of the results shown in Figure 4. The moment arms are barely mentioned outside section 2.3. Are these results new? How can they help with motor control research?<br /> c. The results in Figure 6 are important, since one key asset of ANNs is that they provide access to the activity of the whole population of units that produces a given behavior. For this reason, I think it would be interesting to show the actual "empirical observations" that the results shown in Fig. 6 are replicating, hence allowing a direct comparison between the results obtained for biological and simulated neurons.

4. All examples in the paper use the arm26 plant as effector. Although the authors say that "users can easily declare their own custom-made effector and task objects if desired by subclassing the base Plant and Task class, respectively", this does not sound straightforward. Table 1 does not really clarify how to do it. Maybe an example that shows the actual code (see point 2) that creates a new plant (e.g. the 3-joint arm in Figure 7) would be useful.

5. One potential limitation of the toolbox is that it is based on Tensorflow, when the field of Computational Neuroscience seems to be, or at least that's my impression, transitioning to pyTorch. How easy would it be to translate MotorNet to pyTorch? Maybe the authors could comment on this in the discussion.

6. Supervised learning (SL) is widely used in Systems Neuroscience, especially because it is faster than reinforcement learning (RL). Thus providing the possibility of training the ANNs with SL is an important asset of the toolbox. However, SL is not always ideal, especially when the optimal strategy is not known or when there are different alternative strategies and we want to know which is the one preferred by the subject. For instance, would it be possible to implement a setup in which the ANN has to choose between 2 different paths to reach a target? (e.g. Kaufman et al. 2015 eLife). In such a scenario, RL seems to be a more natural option Would it be easy to extend MotorNet so it allows training with RL? Maybe the authors could comment on this in the discussion.

Impact:<br /> MotorNet aims at simplifying the process of simulating complex experimental setups to rapidly test hypotheses about how the brain produces a specific movement. By providing an end-to-end pipeline to train ANNs on the simulated setup, it can greatly help guide experimenters to decide where to focus their experimental efforts.

Additional context:<br /> Being the main result a toolbox, the paper is complemented by a GitHub repository and a documentation webpage. Both the repository and the webpage are well organized and easy to navigate. The webpage walks the user through the installation of the toolbox and the building of the effectors and the ANNs.

Reviewer #1 (Public Review):

This study explored how expectations influence tactile perception. In summary, anticipating a tactile event enhances detection compared to when knowledge is lacking or ambiguous. However, prior information can also impair performance if the expected and actual stimuli are incongruent. The authors used fMRI and multivariate decoding analyses to investigate the underlying mechanisms of this behavioural phenomenon.

They stimulated two fingers (thumb and ring) of the left hand and analysed activity patterns in contralateral and ipsilateral somatosensory regions during and before stimulation. They were able to distinguish activity patterns for the two fingers during both stimulation and the pre-stimulation stage, specifically for the congruent condition. The authors suggest that congruent vibrotactile stimulation leads to higher multivariate information content and improved behavioural detection performance. They also found that the expectation of vibrotactile stimulation elicits somatotopic activity in contralateral S1, similar to the activity generated by actual stimulation.

I thoroughly enjoyed reading this well-written and clear work. The incorporation of multivariate decoding analysis alongside univariate analysis is a good choice for addressing the claimed questions. In the following sections, I will highlight the strengths and weaknesses of the study. While I generally agree with the authors' conclusions regarding the functional mechanisms underlying behavioural improvements, I believe there are limitations in the experimental design and chosen measures that constrain the interpretations drawn from the results. I hope that my comments can contribute to clarifying certain details and improving aspects of the study that may be considered weak. I believe this study holds significance for the field and provides a foundation for future investigations into the influence of top-down processing on tactile processing.

Strengths:<br /> 1) The research question is highly intriguing as it delves into the unexplored territory of top-down processes within the tactile domain that still needs to be well characterised.

2) The addition of multivariate decoding analysis alongside the univariate analysis was a good choice in my opinion, since activity level per se may not accurately reflect the underlying information content. Both high activity levels and absence of activity (as observed in this study) can still contain information. To be more specific, Figure 2C shows no significant activity in the congruent condition, but significant decoding for the two finger activity patterns is still possible in this condition (Figure 3A).

3) The utilization of a staircase before each functional run was also a good approach, although a potential limitation is noted (discussed below). Considering that prior knowledge can be particularly influential in the presence of weak or noisy stimuli, it is crucial to confirm that the stimulation was at threshold to maximize the likelihood of detecting differences in the pre-stimulus stage.

Weaknesses:<br /> 1) My main concern regarding this study lies in the choice of a detection paradigm, which may introduce response biases and affect the interpretation of results. If the threshold was set too low for some participants, it is possible that they reported feeling the touch more frequently on the cued finger, even when no actual sensation was present. Consequently, accuracy may be inflated for the congruent condition and reduced for the incongruent condition, making it difficult to attribute the observed improvements solely to enhanced detection. I think it would have been more appropriate to use a discriminatory task (e.g., discriminating pin patterns), as employed in Kok et al., 2012, where behavioural performance can be directly linked to decoding accuracy between related activity patterns. Additionally, incorporating trials with no stimulation (I am not sure whether this was the case in this study) and utilizing "None" responses to calculate accuracy could provide a more reliable measure of performance. Using dprime as a performance measure, which is bias-free, may be more appropriate. However, I remain concerned that participant responses are influenced more by the cue than the actual detection of stimuli.

2) While I appreciate the use of the staircase method, I was somewhat surprised by the relatively short length of each staircase (only 7 trials). I might not have extensive experience in this area, therefore this might still be ok for fingers, but I want to emphasize the importance of accurately determining the threshold for this study (as discussed in the previous point). However, I can see from Figure 1B that there seems to be consistency across runs (at least in the shown participant).

3) The absence of significant decoding in the incongruent condition (Figure 3A) raises some questions. It seems reasonable to expect that discrimination between the two finger activity patterns should still be possible in this condition, albeit with reduced accuracy as observed in Kok et al., 2012. Could this lack of significant decoding result from the detection task or possibly due to the smaller number of trials in the incongruent condition?

4) I am a bit confused about which specific region of interest (ROI) was used for both the univariate and decoding analysis during the stimulation stage, and the decoding analysis and RSA during the pre-stimulation phase. From my understanding, the entire S1 region (as defined using the SPM Anatomy toolbox) was included, encompassing not only the hand territory but the entire body. However, I may have misinterpreted the methodology. Given that an independent localizer was used to define ROIs for the univariate analysis during the pre-stimulation phase, it raises the question of why the same approach was not applied to the analyses during the stimulation phase and the multivariate analysis during the pre-stimulation phase.

5) By using a large ROI for analysis (as mentioned in point 4), the straightforward interpretation of BOLD level (i.e., no significant activity) in the congruent condition (Figure 2C) becomes less clear. It raises the question of whether there is truly no activity in the congruent condition or if the activity would be observed with a smaller region. This aligns with the findings of Kok et al., 2012, where they demonstrate activity in both expected and unexpected conditions, albeit reduced in the expected condition.

6) Point 5 raises another issue regarding the suggestion that significant decoding results imply higher multivariate information content in finger representations of congruent vibrotactile stimulations. Suppose a smaller ROI were used, revealing activity in the congruent condition and differential activity between the two finger conditions. In that case, the substantial difference in activation levels suggests that increased decoding accuracy may not necessarily require higher multivariate information content. It is conceivable that discrimination between the two conditions could be achieved with just two voxels-one in the thumb territory and one in the index territory.

Reviewer #1 (Public Review):

The modeling approaches are very sophisticated, and clearly demonstrate the selective nature of acute ketamine to reduce the impact of trial losses on subsequent performance, relative to neutral or gain outcomes. The authors then, not unreasonably, suggest that this effect is important in the context of the negative bias in interpreting events that is prominent in depression, in that if ketamine reduces the ability of negative outcomes to alter behavior, this may be a mechanism for its rapid acting antidepressant effects. However, there is a very strong assumption in this regard, as shown by the first sentence of the discussion which implies this is a systematic study of ketamine's acute antidepressant effects. In actuality, this is a study of the acute effects of ketamine on reinforcement learning (RL) modeled parameters. A primary concern here is that an effect presented as a "robust antidepressant-like behavioral effect" should be more enduring than just an alteration during the acute administration. As it is, the link to an "anti-depressant effect" is based solely on the selective effects on losses. This is not to say this is not an interesting observation, worthy of exploration. It is noted that a similar lack of enduring effects on outcome evaluation is observed in humans, as shown in supplemental fig. S4, but there is not accompanying citation for the human work. One question that comes to mind in terms of the selectivity observed is whether similar work has been done to examine the acute effects of any other drugs. If ketamine is unique in this regard, that would be quite interesting.

Reviewer #1 (Public Review):

In this article, Vardakalis et al. propose a novel model of hippocampal oscillations whereby an external input (emulating the medial septum) can drive theta rhythms. This model displays phase-amplitude coupling of gamma oscillations, as well as theta resetting, which are known features of physiological theta that have been missing in previous models. The end goal proposed by the authors is to have a framework to explore the mechanisms of neurostimulation, which have shown promising applications in pathological conditions, but for which the underlying dynamics remain largely unknown. To reach this objective, the authors implement an existing biophysical model of the hippocampus that is able to generate gamma oscillations, and receives inputs from a set of Kuramoto oscillators to emulate theta drive originating from the medial septum.

Overall, the hypotheses and results are clearly presented and supported by high quality figures. The study is presented in a didactic way, making it easy for a broad audience to understand the significance of the results. The study does present some weaknesses that could easily be addressed by the authors. First, there are some anatomical inaccuracies: line 129 and fig1C, the authors omit medial septum projections to area CA1 (in addition to the entorhinal cortex). Moreover, in addition to CA1, CA3 also provides monosynaptic feedback projections to the medial septum CA3. Finally, an indirect projection from CA1/3 excitatory neurons to the lateral septum, which in turn sends inhibitory projections to the medial septum could be included or mentioned by the authors. This could be of particular relevance to support claims related to effects of neurostimulations, whereby minutious implementation of anatomical data could be key. If not updating their model, the authors could add this point to their limitation section, where they already do a good job of mentioning some limitations of using the EC as a sole oscillatory input to CA1. The authors test conditions of low theta inputs, which they liken to pathological states (line 112). It is not clear what pathology the authors are referring to, especially since a large amount of 'oscillopathies' in the septohippocampal system are associated with decreased gamma/PAC, but not theta oscillations (e.g. Alzheimer's disease conditions). While relevant for the clinical field, there is overall a missed opportunity to explain many experimental accounts with this novel model. Although to this day, clinical use of DBS is mostly restricted to electrical (and thus cell-type agnostic) stimulation, recent studies focusing on mechanisms of neurostimulations have manipulated specific subtypes in the medial septum and observed effects on hippocampal oscillations (e.g. see Muller & Remy, 2017 for review). Focusing stimulations in CA1 is of course relevant for clinical studies but testing mechanistic hypotheses by focusing stimulation on specific cell types could be highly informative. For instance, could the author reproduce recent optogenetic studies (e.g. Bender et al. 2015 for stimulation of fornix fibers; Etter et al., 2019 & Zutshi et al. 2018 for stimulation of septal inhibitory neurons)? Cell specific manipulations should at least be discussed by the authors.

Beyond these weaknesses, this study has a strong utility for researchers wanting to explore hypotheses in the field of neurostimulations. In particular, I see value in such models for exploring more intricate, phase specific effects of continuous, as well as close loop stimulations which are on the rise in systems neuroscience.

Reviewer #1 (Public Review):

It is known that aberrant habit formation is a characteristic of obsessive-compulsive disorder (OCD). Habits can be defined according to the following features (Balleine and Dezfouli, 2019): rapid execution, invariant response topography and action 'chunking'. The extent to which OCD behavior is derived from enhanced habit formation relative to deficits in goal-directed behavior is a topic of debate in the current literature. This study examined habit-learning specifically (cf. deficits in goal-directed behavior) by regularly presenting, via smartphone, sequential learning tasks to patients with OCD and healthy controls. Participants engaged in the tasks every day over the course of a month. Automaticity, including the extent to which individual actions in the sequence become part of a unified 'chunk', was an important outcome variable. Following the 30 days of training, in-laboratory tasks were then administered to examine 1) if performing the learned sequences themselves had become rewarding 2) differences in goal-directed vs. habitual behavior.

Several hypotheses were tested, including:<br /> Patients would have impaired procedural learning vs. healthy volunteers (this was not supported, possibly because there were fewer demands on memory in the task used here)<br /> Once the task had been learned, patients would display automaticity faster (unexpectedly, patients were slower to display automaticity)<br /> Habits would form faster under a continuous (vs. variable) reinforcement schedule

Exploratory analyses were also conducted: an interesting finding was that OCD patients with higher self-reported symptoms voluntarily completed more sessions with the habit-training app and reported a reduction in symptoms.

Strengths

This paper is well situated theoretically within the habit learning/OCD literature.<br /> Daily training in a motor-learning task, delivered via smartphone, was innovative, ecologically valid and more likely to assay habitual behaviors specifically. Daily training is also more similar to studies with non-humans, making a better link with that literature. The use of a sequential-learning task (cf. tasks that require a single response) is also more ecologically valid.<br /> The in-laboratory tests (after the 1 month of training) allowed the researchers to test if the OCD group preferred familiar, but more difficult, sequences over newer, simpler sequences.

Weaknesses

The sample size was relatively small. Some potentially interesting individual differences within the OCD group could have been examined more thoroughly with a bigger sample (e.g., preference for familiar sequences). A larger sample may have allowed the statistical testing of any effects due to medication status.<br /> The authors were not able to test one criterion of habits, namely resistance to devaluation, due to the nature of the task

The authors achieved their aims in that two groups of participants (patients with OCD and controls) engaged with the task over the course of 30 days. The repeated nature of the task meant that 'overtraining' was almost certainly established, and automaticity was demonstrated. This allowed the authors to test their hypotheses about habit learning. The results are supportive of the author's conclusions.

This article is likely to be impactful -- the delivery of a task across 30 days to a patient group is innovative and represents a new approach for the study of habit learning that is superior to an in-laboratory approach.

An interesting aspect of this manuscript is that it prompts a comparison with previous studies of goal-directed/habitual responding in OCD that used devaluation protocols, and which may have had their effects due to deficits in goal-directed behavior and not enhanced habit learning per se.

Reviewer #1 (Public Review):

This manuscript describes a set of four passage-reading experiments which are paired with computational modeling to evaluate how task-optimization might modulate attention during reading. Broadly, participants show faster reading and modulated eye-movement patterns of short passages when given a preview of a question they will be asked. The attention weights of a Transformer-based neural network (BERT and variants) show a statistically reliable fit to these reading patterns above-and-beyond text- and semantic-similarity baseline metrics, as well as a recurrent-network-based baseline. Reading strategies are modulated when questions are not previewed, and when participants are L1 versus L2 readers, and these patterns are also statistically tracked by the same transformer-based network.

I should note that I served as a reviewer on an earlier version of this manuscript at a different venue. I had an overall positive view of the paper at that point, and the same opinion holds here as well.

Strengths:

- Task-optimization is a key notion in current models of reading and the current effort provides a computationally rigorous account of how such task effects might be modeled<br /> - Multiple experiments provide reasonable effort towards generalization across readers and different reading scenarios<br /> - Use of RNN-based baseline, text-based features, and semantic features provides a useful baseline for comparing Transformer-based models like BERT

Weaknesses:

- Generalization across neural network models seems, to me, somewhat limited: The transformer-based models differ from baseline models in numerous ways (model size, training data, scoring algorithm); it is thus not clear what properties of these models necessarily supports their fit to human reading patterns.<br /> - Inferential statistics are based on a series of linear regressions, but these differ markedly in model size (BERT models involve 144 attention-based regressor, while the RNN-based model uses just 1 attention-based regressor). How are improvements in model fit balanced against changes in model size? Also, it was not clear to me how participant-level variance was accounted for in the modeling effort (mixed-effects regression?) These questions may well be easily remedied by more complete reporting.<br /> - Experiment 1 was paired with a relatively comprehensive discussion of how attention weights mapped to reading times, but the same sort of analysis was not reported for Exps 2-4; this seems like a missed opportunity given the broader interest in testing how reading strategies might change across the different parameters of the four experiments.<br /> - Comparison of predictive power of BERT weights to human annotations of text relevance is limited: The annotation task asked participants to chose the 5 "most relevant" words for a given question; if >5 words carried utility in answering a question, this would not be captured by the annotation. It seems to me that the improvement of BERT over human annotations discussed around page 10-11 could well be due to this arbitrary limitation of the annotations.

Reviewer #1 (Public Review):

This manuscript describes extensive transcriptomic and epigenomic profiling for high-grade serous 'ovarian' cancer (HGSC) and its precancerous precursor the fallopian tube secretory epithelium cells (FTSEC). This study identifies MECOM, PAX8, SOX17 and WT1 as master transcription factors that regulate HGSC and FTSEC, as well as the transition from FTSEC to HGSC.

Overall, most the experiments described in the manuscript are well designed and executed. The data presented are of high quality, convincing, and in general support the conclusions made in the manuscript.

Given the complexity of the data and analysis, some clarification is needed to guide readers to better understand the results.

1) The definition of super enhancers should be clarified. In general, super enhancers are defined by large domains of enhancer clusters with high levels of H3K27ac, typically at least 10KB in size. The "super enhancers" presented in Figure 2 do not appear to be large clusters of enhancers.

2) Fig. 4D. Difficult to understand. Multiple bars seem to be represented by the same binding patterns by the four TFs. Need better description in both the text and figure legends.

3) "These data suggest that the antiproliferative effects of THZ1 and THZ531 in HGSC cells may be due to tumor-specific inhibition of MECOM, PAX8 and SOX17 expression by these drugs." Can the author expand the discussion on how CDK7/12 inhibitors could achieve tumor-specific inhibition of MECOM, PAX8 and SOX17?

Reviewer #1 (Public Review):

The authors prepared several Acinetobacter baumannii strains from which an essential protein of known or unknown function can be depleted. They chose to study one of the proteins (AdvA) in more detail. AdvA is a known essential cell division protein that accumulates at cell division sites together with other such proteins. No clear homologs are present in model bacteria such as E.coli, and the precise role(s) of AdvA is still unclear. The authors rename AdvA here as Aeg1. The authors searched for suppressors of lethality caused by AdvA-depletion and recovered an allele of ftsA (E202K) that is capable of doing so. Based on similar superfission alleles previously recovered in other division genes in E.coli, they test several mutant genes and find that certain alleles in ftsB, L and W can also suppress lethality of AdvA-minus cells.

In addition, the authors perform bacterial two-hybrid assays and protein sublocalization studies of AdvA and of other division proteins, but the results of these studies are either not new (confirming previous work) or not convincing.

Reviewer #1 (Public Review):

Bolumar et al. isolated and characterized EV subpopulations, apoptotic bodies (AB), Microvesicles (MV), and Exosomes (EXO), from endometrial fluid through the female menstrual cycle. By performing DNA sequencing, they found the MVs contain more specific DNA sequences than other EVs, and specifically, more mtDNA were encapsulated in MVs. They also found a reduction of mtDNA content in the human endometrium at the receptive and post-receptive period that is associated with an increase in mitophagy activity in the cells, and a higher mtDNA content in the secreted MVs was found at the same time. Last, they demonstrated that the endometrial Ishikawa cell-derived EVs could be taken by the mouse embryos and resulted in altered embryo metabolism.

This is a very interesting study and is the first one demonstrating the direct transmission of maternal mtDNA to embryos through EVs.

Reviewer #1 (Public Review):

Huan Wang et al. analyzed more than 10 million sequences and find that T12I, T102I and A104V were the top 3 frequently occurring mutations. They verified whether these mutations affect the stability and binding ability of NSP10, and whether there are structural changes. They find that three mutations destabilize the NSP10 by NMA prediction and determine their prediction by TSA. In addition, the Kd values shows that variants have similar binding ability or slightly improved affinity to NSP14 and NSP16 than native NSP10. Even though crystallization of the two variants is missing, the comparison of the crystallization of the T102I crystalline protein with the native shows that there is no structural change. Simultaneously, the dihedral angles in the variants do not explore any additional minima than that observed in wild-type NSP10, and there is no major conformational change.

Reviewer #1 (Public Review):

The manuscript by Goetz et al. takes a new perspective on sensory information processing in cells. In contrast to previous studies, which have used population data to build a response distribution and which estimate sensory information at about 1 bit, this work defines sensory information at the single cell level. To do so, the authors take two approaches. First, they estimate single cells' response distributions to various input levels from time-series data directly. Second, they infer these single-cell response distributions from the population data by assuming a biochemical model and extracting the cells' parameters with a maximum-entropy approach. In either case, they find, for two experimental examples, that single-cell sensory information is much higher than 1 bit, and that the reduction to 1 bit at the population level is due to the fact that cells' response functions are so different from each other. Finally, the authors identify examples of measurable cell properties that do or do not correlate with single-cell sensory information.

The work brings an important and distinct new insight to a research direction that generated strong interest about a decade ago: measuring sensory information in cells and understanding why it is so low. The manuscript is clear, the results are compelling, and the conclusions are well supported by the findings. Several contributions should be of interest to the quantitative biology community (e.g., the demonstration that single cells' sensory information is considerably larger than previously implied, and the approach of inferring single-cell data from population data with the help of a model and a maximum-entropy assumption).

Reviewer #1 (Public Review):

This manuscript sets out to implement a multi-stage fluorescence imaging essay to test two working models in understanding the folding states of RNA-binding proteins (RBPs) in stress-induced nuclear bodies. In conjunction with live-cell fluorescence lifetime imaging, the authors revealed and conformed a previously unclear phenomenon that the RBPs investigated in this work initially enter the nuclear bodies in native state in transient stress and then begin to misfold after prolonged stress. Comparing to conventional methods, the imaging strategy reported in this work is unique, comprehensive, and effective in surveying all three-stages (native, soluble oligomer, aggregates) of folding states for RBPs in one shot. Using this strategy, the authors then found that the heat shock protein 70 may protects RBPs from being degraded under stress. The manuscript is very well-written.

Reviewer #1 (Public Review):

In the manuscript titled "GABAergic synaptic scaling is triggered by changes in spiking activity rather than transmitter receptor activation," the authors present an investigation of the role of GABAergic synaptic scaling in the maintenance of spike rates in networks of cultured neurons. Their main findings suggest that GABAergic scaling exhibits features consistent with a key homeostatic mechanism that contributes to the stability of neuronal firing rates. Their data demonstrate that GABAergic scaling is multiplicative and emerges when postsynaptic spike rates are altered. Finally, their data suggest that, in contrast to their prior data on glutamatergic scaling, GABAergic scaling is driven by spike rates. The authors set the paper up as an argument that GABAergic scaling, rather than glutamatergic scaling, serves as the critical homeostatic mechanism for spike rate regulation.

While the paper is ambitious in its rhetorical scope and certainly presents intriguing findings, there are several serious concerns that need to be addressed to substantiate the interpretations of the data. For example, the CTZ data do not support the interpretations and conclusions drawn by the authors. Summarily, the authors argue that GABAergic scaling is measuring spiking (at the time scale of the homeostatic response, which they suggest is a key feature of a homeostat) yet their data in figure 5B show more convincingly that CTZ does not influence spiking levels - only one out of four time points is marginally significant (also, I suspect that the bootstrapping method mentioned in line 454-459 was conducted as a pairwise comparison of distributions. There is no mention of multiple comparisons corrections, and I have to assume that the significance at 3h would disappear with correction). Then, the fact that TTX applied on top of CTZ drives a increase in mIPSC amplitude is interpreted as a conclusive demonstration that GABAergic scaling is sensing spiking. It is inevitable, however, that TTX will also severely reduce AMAP-R activation - a very plausible alternative explanation is that the augmentation of AMPAR activation caused by CTZ is not sufficient to overcome the dramatic impact of TTX. All together, these data do not provide substantial evidence for the conclusion drawn by the authors.

Specific points:

- The logic of the basis for the argument is somewhat flawed: A homeostat does not require a multiplicative mechanism, nor does it even need to be synaptic. Membrane excitability is a locus of homeostatic regulation of firing, for example. In addition, synapse-specific modulation can also be homeostatic. The only requirement of the homeostat is that its deployment subserves the stabilization of a biological parameter (e.g., firing rate).<br /> - Line 63 parenthetically references an important, but contradictory study as a brief "however". Given the tone of the writing, it would be more balanced to give this study at least a full sentence of exposition.<br /> - The authors state (line 11) that expression of a hyperpolarizing conductance did not trigger scaling. More recent work ('Homeostatic synaptic scaling establishes the specificity of an associative memory') does this via expression of DREADDs and finds robust scaling.<br /> - Supplemental figure 1 looks largely linear to me? Out of curiosity, wouldn't you expect the left end to be aberrant because scaling up should theoretically increase the strength of some synapses that would have been previously below threshold for detection? Given that figure 2B also shows warping at the tail ends of similar distributions, how is this to be interpreted?<br /> - The readability of the figures is poor. Some of them have inconsistent boundary boxes, bizarre axes, text that appears skewed as if the figures were quickly thrown together and stretched to fit.<br /> - I'm concerned about the optogenetic restoration of activity experiment. Cortical pyramidal neuron mean firing rates are log normally distributed and span multiple orders of magnitude. The stimulation experiments can only address the total firing at a network-level - given than a network level "mean" is meaningless in a lognormal distribution, how are we to think about the effect of this manipulation when it comes to individual neurons homeostatically stabilizing their own activities? In essence, the argument is made at the single-neuron level, but the experiment is conducted with a network-level resolution.<br /> - Line 198-99: multiplicativity is not a requirement of a homeostatic mechanism.<br /> - Line 264-265 - again, neither multiplicativity and synaptic mechanisms are fundamentally any more necessary for a homeostatic locus than anything else that can modulate firing rate in via negative feedback.<br /> - 277: do you mean AMPAR?<br /> - Example: Figure 1A is frustratingly unreadable. The axes on the raster insets are microscopic, the arrows are strangely large, and it seems unnecessary to fill so much realestate with 4 rasters. Only one is necessary to show the concept of a network burst. The effect of time+CNQX on the frequency of burst is shown in B and C.<br /> - Example: Figure 2 appears warped and hastily assembled. Statistical indications are shown within and outside of bounding boxes. Axes are not aligned. Labels are not aligned. Font sizes are not equal on equivalent axes.<br /> - The discussion should include mention of the limitations and/or constraints of drawing general conclusions from cell culture.<br /> - The discussion should include mention of the role of developmental age in the expression of specific mechanisms. It is highly likely that what is studied at ~P14 is specific to early postnatal development.

It is essential to ensure that the data presented in the paper adequately supports the conclusions drawn. A more cautious approach in interpreting the results may lead to a stronger argument and a more robust understanding of the underlying mechanisms at play.

Reviewer #1 (Public Review):

The authors sought to address the longstanding question of which cell types are infected during congenital or perinatal rubella virus infection. They used brain slice and organoid-microglia experimental models to demonstrate that the main cell types targeted by rubella virus are microglia. The authors further show that infection results in augmented interferon responses in neighboring neuronal cells but not in the microglia themselves. The data convincingly support the conclusions, with major strengths being the sophisticated primary cell models and single-cell RNA-Seq used to pinpoint microglia as the main cellular targets of rubella virus, and neurons as the bystander targets of immune signaling. This study reveals a new cellular target that will have important implications for basic studies on rubella virus-host interactions and for the potential development of therapies or improved vaccines targeting this virus. As rubella virus is a pathogen of high concern during human pregnancy, this study is also relevant in the field of neonatal infectious diseases.

Joint Public Review:

As nucleoporins can function at intact nuclear pore complexes (NPCs) or outside of NPCs as individual proteins or subcomplexes, it remains challenging to molecularly define the pool of molecules that exert a specific function. To address this challenge, here the authors develop a new method for specifically mapping NPC-associated loci by DamID with a recombinant fusion protein of the Dam methylase and the nuclear transport receptor, importin b (Dam-Impb), in permeabilized cells. The authors demonstrate that Dam-Impb is active, accumulates at the NPC and, using super-resolution microscopy, methylates NPC-adjacent regions; other observations further support the assertion that the approach is specific for NPC-associate chromatin regions. Furthermore, NPC-DamID does not require genetic manipulation and they show that it can be applied to both diverse cell lines as well as tissues. The authors confirm the association of nucleoporins with super-enhancers (SEs) in line with their prior work, now confirmed to occur at NPCs based on this study. Among SEs categorized as hierarchical enhancers (Nat Commun 9, 943 (2018)), hub enhancers are over-represented for methylation by Dam-Impb. The association of such enhancers with cohesin and CTCF suggests these regions could have a critical role in chromatin folding; enhancer-associated factors and marks such as H3K27 acetylation, RNA polymerase II, P300, CTCF and BRD4 also enrich at Dam-Impb methylation peaks. Using proximity ligation, the authors provide further evidence that Tpr, which interacts with the NPC basket, colocalizes with CTCF, BRD4 and P300. Based on these observations, the authors hypothesized that nucleoporin phase separation at SEs might potentiate phase separation of other factors at these elements. Consistent with previous work, over-expression of the intrinsically disordered region (IDR) of Nup153, a component of the NPC basket, forms nuclear droplets that are largely dispersed by 1,6-hexanediol. In this same condition, colocalization RNAPII and both Tpr and BRD4 is reduced, although some interactions between IDRs were not sensitive to this treatment. Last, using a lac operator array as a tethering site, the authors show that tethered Nup153 IDR recruits the carboxy terminal domain of RNAPII and Med1. However, whether the biology of how nucleoporins at NPCs influence SEs depends on biomolecular condensation will require future study.

Overall, the reviewers agree that this is an excellent manuscript that will impact our understanding of nuclear pore complex-genome interactions and how nucleoporins impact super enhancer function. The data are generally of high quality and are reasonably interpreted. There are, however, several important controls or analyses that would strengthen the conclusions of the paper, as outlined below.

1. NPC vs nucleoplasmic interactions: One of the main claims of the paper is that it provides a way to study specifically the NPC-associated loci and contrast them to the nucleoplasmic Nup-associated loci. Unfortunately, the authors do not devote much space to this comparison and many of the manipulations involve proteins that are in both locations (see below). This seems like an important, missed opportunity. The choices of Tpr or Nup153 should be more clearly justified. The Dpn8 staining appeared in regions outside of the nuclear envelope, which is inconsistent with the text. This should be addressed.

2. The PLA experiments: Although Tpr exists both at the NPC and in the nucleoplasm, the authors interpret these experiments as if they are exclusively reporting on proximity of enhancer proteins to the NPC. The images (e.g. Figure 5a, supplementary Figure 5) make it clear that the foci are throughout the nucleus. Where are the antigens recognized by the antibodies to Tpr and what this may mean for the findings? Further, PLA experiments are prone to artefacts and, while the authors have included a knockdown of Tpr as a negative control, additional controls would strengthen their conclusions. For example, what is the result when Tpr colocalization with NPC-specific proteins is assessed? How is that affected by hexanediol? A better PLA experiment might be to assess colocalization of Dam-ImpB or Dpn8 (bound to Dam-ImpB methylated sites) with super enhancer proteins such as Med1, CTCF, Brd4, etc. With regards to the PLA with

3. Analysis of genomic data: The normalization of the DNA sequencing tracks is not sufficiently explained. Moreover, some of the correlations using meta-site plots are not convincing. For example, the peaks of Nup153 or Nup98 methylation over Imp-B peaks are apparently weak. Although the authors report local maxima, these may not be strong associations. This raises the possibility that the stronger Nup153 or Nup98 peaks are not ImpB peaks. A better way to test for this would be to correlate the ImpB peak intensity to the Nup153 or Nup98 peak intensity globally. The expectation is that there will be both correlated peaks that show strong methylation by Nup153/Nup98 and ImpB, as well as peaks that do not (i.e. those in the nucleoplasm). Along these lines, the Dam alone control can be used for comparison. Peaks identified by Dam alone should not be correlated with ImpB, Nup153, Nup98, CTCF, RNAPII, Cohesin, H3K27Ac, Brd4, Mediator, super enhancers, hubs, etc. Also, what is the source of the Nup93 CUT&RUN data? It was unclear if it was from this study or a prior publication.

4. FISH experiments: these should be in the main figures of the paper and better described. How many loci were assessed in each category? Are the differences between the three classes significant? Also, the order of the legend is the opposite of the order of the bar segments, which is confusing to the reader. Related to Figure 2j: What are the FISH probes used here? How many cells were quantified?

5. The focus on IDRs as the primary functional mechanism for the NPC-SE connection was felt to be the least well-justified of the authors' conclusions. In particular, the quantitative effects in Fig. 6 are over-stated while caveats including possible over-expression artifacts and changes in the nuclear concentration of the IDRs due to efflux out of the nucleus in response to 1,6 hexanediol treatment as a consequence of the effect on the barrier of NPCs are not addressed. Additional experimental follow-up - for example does critical depletion of Nup153 (now possible with auxin degrons) disrupt the NPC-DamID profile? - would strengthen the support for the model.

6. Recent evidence points to the fact that 1,6-HD treatment probes the presence of hydrophobic interactions, rather than distinguishing between LLPS and interactions with spatially clustered binding sites (ICBS). These possibilities should be taken into account when interpreting the data, and should be discussed more thoroughly.

Joint Public Review:

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

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

Reviewer #1 (Public Review):

This well written and designed study by Broca-Brisson et al describes the generation of a new in vitro model for creatine transporter deficiency (CTD), making use of human brain organoid cultures derived from CTD patients. This new model will certainly prove itself very useful to better understand this genetic disease essentially affecting CNS. As CTD has no satisfactory treatment so far (despite more than 20 years of research), this new model will also be very useful to design and develop new treatments.

In particular, through the use of immunohistochemistry, real time PCR, and proteomics combined with integrative bioinformatic and statistical analysis, authors provide very interesting new informations on the brain pathways affected in CTD (e.g. neurogenesis with down-regulation of SOX2 and PAX6 but up-regulation of GSK3b; and proteins involved in autistic spectrum, epilepsies or intellectual disabilities).

While the CTD human brain organoids show a decrease in Cr (in absence of Cr in the culture medium) as compared to control organoids (4 times less), they are not devoid of Cr. Do these organoids express the two enzymes allowing Cr synthesis (AGAT and GAMT), and in which brain cell types? If yes, how to explain the decrease in Cr in the CTD organoids?

The rescue experiment, re-establishing a functional Cr transporter (CRT or SLC6A8) in the CTD human brain organoids, is very interesting, as this may help the design and development of new treatments for CTD. However, authors claim that the functional CRT expressed in the rescued CTD organoids was expressed in each cell. This may be a difficulty in the development of new CTD treatments, as CRT should be expressed in neurons and oligodendrocytes, but not in astrocytes. Authors may want to comment on this point.

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 of 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 tackles an important question, namely how K+ affects substrate transport in the SLC6 family. K+ effects have previously been reported for DAT and SERT, but the prototypical SLC6-fold transporter LeuT was not known to be sensitive to the K+ concentration. In this manuscript, the authors demonstrate convincingly that K+ inhibits Na+ binding, and Na+-dependent amino acid binding at high concentrations, and that K+ inside of vesicles containing LeuT increases the transport rate. However, outside K+ apparently had very little effect. Uptake data are supplemented with binding data, using the scintillation proximity assay, and transition metal FRET, allowing the observation of the distribution of distinct conformational states of the transporter.<br /> Overall, the data are of high quality. I was initially concerned about the use of solutions of very high ionic strength (the Km for K+ is in the 200 mM range), however, the authors performed good controls with lower ionic strength solutions, suggesting that the K+ effect is specific and not caused by artifacts from the high salt concentrations.

The major issue I have with this manuscript is with the interpretation of the experimental data. Granted that the K+ effect seems to be complex. However, it seems counterintuitive that K+ competes with Na+ for the same binding site, while at the same time accelerating the transport rate. Even if K+ prevents rebinding of Na+ on the inside of vesicles, it would be expected that K+ then stabilizes this Na+-free conformation, resulting in a slowing of the transport rate. However, the opposite is found. I feel that it would be useful to perform some kinetic modeling of the transport cycle to identify a mechanism that would allow K+ to act as a competitive inhibitor of Na+ binding and rate-accelerator at the same time.

This ties into the second point: It is not mentioned in the manuscript what the configuration of the vesicles is after LeuT reconstitution. Are they right-side out? Is LeuT distributed evenly in inside-out and right-side out orientation? Is the distribution known? If yes, how does it affect the interpretation of the uptake data with and without K+ gradient?

Finally, mutations were only made to the Na1 cation binding site. These mutations have an effect mostly to be expected, if K+ would bind to this site. However, indirect effects of mutations can never be excluded, and the authors acknowledge this in the discussion section. It would be interesting to see the effect of K+ on a couple of mutants that are far away from Na+/substrate binding sites. This could be another piece of evidence to exclude indirect effects, if the K+ affinity is less affected.

Reviewer #1 (Public Review):

Astrocytes are known to express neuroligins 1-3. Within neurons, these cell adhesion molecules perform important roles in synapse formation and function. Within astrocytes, a significant role for neuroligin 2 in determining excitatory synapse formation and astrocyte morphology was shown in 2017. However, there has been no assessment of what happens to synapses or astrocyte morphology when all three major forms of neuroligins within astrocytes (isoforms 1-3) are deleted using a well characterized, astrocyte specific, and inducible cre line. By using such selective mouse genetic methods, the authors here show that astrocytic neuroligin 1-3 expression in astrocytes is not consequential for synapse function or for astrocyte morphology. They reach these conclusions with careful experiments employing quantitative western blot analyses, imaging and electrophysiology. They also characterize the specificity of the cre line they used. Overall, this is a very clear and strong paper that is supported by rigorous experiments. The discussion considers the findings carefully in relation to past work. This paper is of high importance, because it now raises the fundamental question of exactly what neuroligins 1-3 are actually doing in astrocytes. In addition, it enriches our understanding of the mechanisms by which astrocytes participate in synapse formation and function. The paper is very clear, well written and well illustrated with raw and average data.

Reviewer #1 (Public Review):

In this paper, Scholz and colleagues introduce a new paradigm aimed to bridge the gap between two domains that rely on hierarchical processing: language and memory. They find that, generally in line with their hypotheses, hierarchical processing is associated with activation in hippocampus (especially anterior), medial prefrontal cortex (mPFC), posterior superior temporal sulcus (pSTS), and inferior frontal gyrus (IFG). They also report that these effects in IFG are particularly strong late in the task, once participants have had a lot of experience and processing is presumably more automatic.

This work has many strengths. The goal to bridge these literatures by developing a new task is commendable. I appreciate also that the authors separately validated their new task behaviorally by comparing it to another accepted as tapping hierarchical processing. I also liked that the authors were transparent about their hypotheses, and certain analyses like the grid coding one that was planned but did not work out. I do however have a number of concerns about the interpretations of the findings, such as whether some patterns are ambiguous as to the true underlying effects. I also have a number of clarification questions. All concerns are described below.

1. Broadly, I would like to see the authors provide more information and logic on why hierarchical processing should be associated with a big reduction in univariate activation between P1 and P2-why would this signify item in contexts binding? How does this relate to existing work using other methods (e.g., like animal studies, which seem to make predictions more about representational structures)?

2. There are many differences between what kind of information participants are processing between Position 1 and Position 2 for the HIER but not ITER conditions, and these may not be related to the hierarchical structure specifically. Related to but I think distinct from some of the limitations mentioned in the Discussion is the fact that in the HIER condition, what is happening cognitively between Position 1 and Position 2 items is more distinct (attending to color for position 1, and shape for position 2), whereas the two positions are equivalent in the ITER condition. This is a bit different from the authors' intended manipulation of hierarchy, because it involves a specific dimension. A stronger design might have been to flip the dimensions with respect to position specifically, to make shape sometimes important for position 1, and color for position 2 (perhaps by counterbalancing across subjects, so half would see the current P1=color and P2=shape rules, and the other half P1=shape and P2=color rules). Another important difference between color and shape is that while color is a simple binary distinction that participants can make based on their preexisting knowledge of red versus green, and to which they can assign a verbal label; whereas, the shape distinction was something novel they acquired during the experiment, has no real-world validity or meaning, and would presumably rely more on visuospatial processing. The shape dimension was also much more variable, I believe. I should say that I do find comfort in a few things - (1) that behavior on this task is correlated with another one that also indexes hierarchy processing, and (2) that the results show regional specificity in a pattern at least not easily explained by this distinction. However, I do think future work will be needed to ask whether it is hierarchy processing per se or rather something to do with the particular cognitive states engaged during each phase in this particular task that is eliciting activation in this set of regions. It would strengthen the paper to discuss this issue directly so readers are alerted to the caveat.

3. I did not understand what data went into creating the schematic in Figure 2E. First, I think this depiction of a gradient might be easily misinterpreted because it seems to imply that the authors have a higher resolution analysis than they actually do. I believe the data were just analyzed in three subregions of hippocampus - head, body, and tail. Variability within each subregion (as seems to be implied by certain parts of a region being more grey and others more red/orange), is not something that could be assessed in this analysis. For example, why does the medial part of the head seem to be more "unspecific" whereas lateral regions look more HIER Pos1 specific? This type of depiction would only make sense in my mind if the authors had performed something like a voxelwise analysis to determine where specifically the interaction "peaks." I would recommend this visualization be cut or significantly changed to do away with the gradient.

4. I believe the authors have not reported enough information for us to know that hippocampus involvement indeed does not change with experience. It is interesting that hippocampus in the task x experience ROI analysis shows, if anything, bigger differentiation between the two tasks (numerically) for the late trials. This seems to go against the authors' hypothesis, and a lot of existing data, that hippocampus is preferentially involved in early (vs. late) learning. Given that the key signature in this region, though, is that it differentiates between position 1 and position 2 in HIER but not ITER, and doesn't show a big difference in magnitude across the two tasks, it makes me wonder whether the task x experience interaction collapsing across the two positions makes sense for this region. Did the authors consider a similar task x experience interaction within hippocampus, but additionally considering position? I think there are multiple ways to look at this question (e.g., either looking for a task x experience x position interaction, a task x experience within position 1, a task x position interaction separately in early vs. late portions of the task, or even a position x experience interaction only within the HIER task), and I'm sure the authors would be in a better place to decide on a specific path forward. The same logic might go for mPFC, which shows an interaction but no main effect of task. This relates to claims in the discussion as well, such as that "hippocampus was equally active in early and late trials," but given this analysis is collapsing across the dimension hippocampus (and mPFC) seem to be sensitive to (position), it seems like this could be masking an underlying effect in which hippocampus/mPFC might still be differentially involved early vs. late (i.e., they might show the task x position interaction preferentially during some task phases).

5. For the IFG regions, the task x experience interaction seems to be driven mainly by change (decrease in activation) for the ITER, rather than change in the HIER. The authors are at times careful to talk about this as "sustained" activity in IFG, which I appreciated, but other times talk about a "relative increase." I am not sure how I feel about that. I see the compelling evidence that there are task differences by experience, and that there is reduction for ITER that is interestingly not present for HIER, but I think I am still feeling uncomfortable with the term "increase" or even "relative increase" for HIER. For example, couldn't it simply be that the ITER task is requiring less processing with experience, whereas the HIER does not (perhaps because it requires more processing to begin with)? i.e., we do not know whether the reduction for ITER is simply a neural signal thing (i.e., activations diminish over time/experience) or a cognitive thing, specific to the ITER task. I think the authors are wanting to interpret the reductions as the former, but perhaps it would be more powerful to demonstrate if there was a baseline task that also showed reductions but for which not much would be expected in the way of cognitive change. Can the authors provide more justification for their choice of terminology (through either more logic or analyses), or if not, simply talk about it as sustained activity for HIER-which is especially interesting in the face of reductions for the ITER task?

6. Please define what is meant by the term "automaticity" in the introduction. A clearer definition of the concept would make the paper generally easier to follow, and it would also help foreshadow the hypotheses about mPFC activity in the introduction. To this end, it could be useful to elaborate on how learning takes place in this task, how it could foster increasing automaticity, and how automaticity maps onto behaviour (e.g., is it RT decrease alone, which happens for both conditions in this task?) the brain regions discussed.

7. There was no association between brain and behavior, which the authors interpret as a positive (as therefore task difficulty differences could not explain the effects). However in light of these null findings, it is on the flip side hard to know whether this neural engagement carries any behavioral significance. It seems to me as though the authors' framework makes predictions about brain-behavior correlations that were not tested in the manuscript. For example, I believe the authors asked whether behavior overall was correlated with activation. However, wouldn't the automaticity in IFG explanation for example predict that more engagement or an increase in engagement from early to late should be associated with e.g., faster RTs-not necessarily a relationship overall?

8. On p. 8, it is stated that "In the hippocampus, this effect is driven by higher betas for the presentation of the first object (H1 > I1) and lower betas for the second object (H2 < I2) when comparing across tasks." Can the authors confirm whether the pairwise comparisons following up on the interaction here are significant, or rather if they are referring to a numerical difference in the betas? It looked like the same (numerically) would be true for mPFC; is there a reason why the same information is not included for the mPFC ROI? Also, might the authors provide more speculation as to why one might see both enhanced and reduced activation for P1 and P2, respectively?

9. I was expecting some discussion of how hippocampus does not seem to show preferential involvement early, given that its potential role being restricted to early in learning (i.e., during acquisition only) was one of the primary motivators for using this task. As noted in my above comment (#4), I am not quite sure that I think there is evidence that the hippocampal role remains constant over this task, given the analyses provided (i.e., that they did not look at the position effect for early vs. late). However upon further analysis if it does seem to be more stable, and/or if it even increases over experience, the authors might want to talk about that in the Discussion.

10. The fact that the hierarchies in this paradigm unfolded over time makes them distinct on some level from the hierarchies present in the VRT task that was used to validate the HIER task's hierarchical processing demands. For example, there might be additional computations required to processes these temporally ordered structures, support online maintenance, and so on. It may be worth considering this aspect of the task, and whether/to what extent the results could be related to it, in the paper.

11. I also have many methodological and analytic clarification questions, which I detail in the recommendations for authors.

Reviewer #1 (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, their 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 this study, the authors demonstrated a new model that B cell contraction after antigen encountering was dependent on N-WASP-branched actin polymerization. This statement is achieved by a systemic comparison of genetic modified mice vs wild type mice or inhibitor treated cells vs control cells. By imaging how B cells interact with antigen-coated planar lipid bilayer, the authors further suggested that the contraction event may provide B cells a channel to dismiss downstream kinase for a purpose to attenuate B cell activation signaling. Even though this manuscript is well written and packaged, however there are a few points that should be carefully addressed and revised.

The first major issue is related to the imaging and tracking experiment to examine the formation and migration of F-actin foci as illustrated in figure 3. The formation and centripetally migration of F-actin foci is a significant finding of this MS for the promotion of B cells to switch from spreading to contraction response. Thus, I may suggest to recommend the authors to conduct one more rigorous fluorescent molecular tracking experiment to confirm this phenomenon. Molecular tracking usually requires low labeling density, and the lifeact-GFP labeling here do not meet this requirement which may cause misidentification of the moving molecules. Permeable dye-based fluorescent speckle microscopy is recommended here to track the actin foci if applicable (P. Risteski, Nat. Rev. Mol. Cell Biol., 2023, DOI: 10.1038/s41580-023-00588-w & K. Hu, et al, Science, 2007, 315, 111-115). Additionally, kymograph is used for foci tracking in figure3 and figure4. Kymograph is indeed a powerful tool for tracking cell protrusion and retraction but is fairly suitable here, since a F-actin focus is a concentrated point which may not move strictly along the selected eight lines generating kymograph. Other imaging processing method should be used to track the foci, for example, time series max projection is recommended if applicable.

The second major issue is about the relationship between actin foci formation and NMII recruitment in figure 5. The author concludes that 'N-WASP and Arp2/3 mediated branched actin polymerization promotes the recruitment and the reorganization of NMII ring-like structures by generating inner F-actin foci in the contact zone'. However, there is a lack of strong evidence to directly show the mechanism by which myosin is recruited and the up and down stream relationship between actin foci migration and myosin recruitment. Since myosin-induced actin retrograde flow is a classical model in adherent cells, is it possible that, here also in activated B cells, the recruited myosin driven the formation and migration of actin foci? This reviewer may recommend the author to investigate whether Myosin blocking (e.g., using Y27632) can eliminate the F-actin foci formation and migration.

Reviewer #1 (Public Review):

Transcriptional readthrough, intron retention, and transposon expression have been previously shown to be elevated in mammalian aging and senescence by multiple studies. The current manuscript claims that the increased intron retention and readthrough could completely explain the findings of elevated transposon expression seen in these conditions. To that end, they analyze multiple RNA-seq expression datasets of human aging, human senescence, and mouse aging, and establish a series of correlations between the overall expression of these three entities in all datasets.

While the findings are useful, the strength of the evidence is incomplete, as the individual analyses unfortunately do not support the claims. Specifically, to establish this claim there is a burden of proof on the authors to analyze both intron-by-intron and gene-by-gene, using internal matched regions, and, in addition, thoroughly quantify the extent of transcription of completely intergenic transposons and show that they do not contribute to the increase in aging/senescence. Furthermore, the authors chose to analyze the datasets as unstranded, even though strand information is crucial to their claim, as both introns and readthrough are stranded, and if there is causality, than opposite strand transposons should show no preferential increase in aging/senescence. Finally, there are some unclear figures that do not seem to show what the authors claim. Overall, the study is not convincing.

Major concerns:

1. Why were all datasets treated as unstanded? Strand information seems critical, and should not be discarded. Specifically, stranded information is crucial to increase the confidence in the causality claimed by the authors, since readthrough and intron retention are both strand specific, and therefore should influence only the same strand transposons and not the opposite-strand ones.

2. "Altogether this data suggests that intron retention contributes to the age-related<br /> increase in the expression of transposons" - this analysis doesn't demonstrate the claim. In order to prove this they need to show that transposons that are independent of introns are either negligible, or non-changing with age.

3. Additionally, the correct control regions should be intronic regions other than the transposon, which overall contributed to the read counts of the intron.

4. Furthermore, analysis of read spanning intron and partly transposons should more directly show this contribution.

5. "This contrasts with the almost completely even distribution of randomly permuted transposons." How was random permutation of transposons performed? Why is this contract not trivial, and why is this a good control?

6. Fig 4: the choice to analyze only the 10kb-20kb region downstream to TSE for readthrough regions has probably reduced the number of regions substantially (there are only 200 left) and to what extent this faithfully represent the overall trend is unclear at this point.

7. Fig. 5B shows the opposite of the authors claims: in the control samples there are more transposon reads than in the KCl samples.

8. "induced readthrough led to preferential expression of gene proximal transposons (i.e. those within 25 kb of genes), when compared with senescence or aging". A convincing analysis would show if there is indeed preferential proximity of induced transposons to TSEs. Since readthrough transcription decays as a function of distance from TSEs, the expression of transposons should show the same trends if indeed simply caused by readthrough. Also, these should be compared to the extent of transposon expression (not induction) in intergenic regions without any readthrough, in these conditions.

Reviewer #1 (Public Review):

The manuscript entitled: "TCR-pMHC complex formation triggers CD3 dynamics" by Van Eerden et al. mainly uses coarse-grained molecular dynamics to probe the dynamic changes, in terms of CDε spatial arrangements around 226 TCRs, before and after the engagements of MCC/I-Ek. The broader distributions of CDε iso-occupancies after pMHC binding correlate with the decreases of TCR-CD3 contacts and extensions of TCR conformations. Given the observed release of motion restrictions upon antigen recognition, the authors proposed a "drawbridge" model to describe the initial triggering processes from pMHC association to TCR straightening, FG-loop getaway, and CD3 enhanced mobility. In addition, the authors briefly investigated the functional effects of the rigidified connecting peptide (CP) in T-cell activation using in silico and in vitro mutagenesis. The manuscript raises an important and exciting hypothesis about the allostery of TCR-CD3 during TCR triggering; however, due to current not-yet-convincing evidence, both computationally and experimentally, in supporting their conclusions.

1. As mentioned by the authors, the TCR triggering and T cell activation have been illustrated by a number of models, such as mechanosensing and kinetic proofreading, "in which TCRs discriminate agonistic from antagonistic pMHCs." However, the critical feature of antigen discrimination is lacking in the drawbridge model. So far, the CDε movements qualitatively distinguish on and off states. The simulation of the antagonist or weaker binder would strengthen the manuscript by demonstrating the relevance of CDε mobility in the triggering mechanism. 226 TCR associated with K99E/I-Ek has been resolved in Ref (DOI: 10.4049/jimmunol.1100197), which can potentially serve as the "intermediate" system to formulate the gradual increase of CDε dynamics.

2. The linkage between conserved motifs in CP and CDε mobility is less apparent to this reviewer. The notion of the rigidified hinge (PP) requires further clarification. Computationally, the details of fine-grained simulations are required to justify the origin of the apparent mobility increase in PP. The direct comparison between Fig. 2 and Fig. 7 can help assess the relevance of CP through the alignment by FG-loop at a fixed direction in polar coordinates. Experimentally, anti-CD3 positive experiments and, ideally, another antagonist on 3A9 TCRs can strengthen the current functional assay. The baseline level of TCR expression (after positive selection) and 0h activation (Fig. S8) is missing.

3. Regarding the section "The TCRβ FG loop acts as a gatekeeper," besides contact analysis, additional motion analysis, such as RMSF or PCA, can further establish the importance of FG loops.

4. The discussion on anti-CD3 antibody effects and their potential contribution to CD3 mobility is highly recommended.

Reviewer #1 (Public Review):

Full activation of T cells requires not only antigen recognition through the T cell receptor, but also engagement of co-stimulation by the T cell. There are multiple co-stimulatory receptors that can be engaged by the T cell; yet, the downstream effects of signaling through these different receptors on T cell gene programs and function and are not yet fully understood. These questions are clinically important because genomic variants associated with immune and inflammatory disease map onto these different co-stimulatory receptors and, potentially, their downstream gene programs.

Based on these observations, the authors hypothesize that different modes of co-stimulation engage different genes and pathways that may be differentially associated with risk for inflammatory disease. To ask this question, the authors performs a comparative analysis of different co-stimulatory receptors, both CD28 - the most widely used form of co-stimulation for in vitro assays - as well as alternative modes of co-stimulation involving ICOS, CD6, CD27. They analyzing their effects on their T cell activation in vitro for human naive and memory CD4 cells, on gene expression using RNA-seq (at 24 hrs), on chromatin accessibility using ATAC-seq, and on specific proteins identified from transcriptomic data using flow cytometry.

From these experimental analysis, the authors conclude the following (1) alternative co-stimulation (ICOS, CD6, Cd27) can induce a *qualitatively* different gene and cellular program compared to canonical co-stim (CD28), resulting not only in less proliferation and cytokine production, as expected, but also in higher lysosome production and different metabolic programming. They also found that risk variants for inflammatory bowel disease mapped onto genes that were both shared across different modes of co-stimulation, as well as onto targets of specific co-stimulation.

This study and the authors' experimental system is well-designed to precisely identify genomic effects of co-stimulation, employing sorted subsets of human CD4 cells, as well as a in vitro setting that can effectively eliminate many confounding variables associated more complex scenarios. The transcriptome/chromatin accessibility measurements were also robustly analyzed and offer some support for the author's conclusion. However, there were two main weaknesses that limit that, if overcome, would enhance the authors' argument:

(1) It is not clear whether the qualitatively different effects of alternate co-stimulation compared to canonical CD28 co-stimulation, e.g. increased OXPHOS or lysosomal abundance for CD6, or heightened expression of genes or represent truly unique effects, or whether they simply represent effects of having quantitatively weaker strengths of CD28 co-stimulation. This concern would be addressed by an experiment doing a dose response curve for CD28 co-stimulation while measuring these variables (Fig. 6) or, more systematically, while performing RNA-seq. Also, to strengthen this argument, the authors would benefit from further in-depth literature discussion/analysis of the signaling pathways downstream of co-stimulation, to discuss molecular bases for different signaling, if any.

(2) There is no functional evidence to link differential activation of risk variant-associated genes by alternate co-stimulation with inflammatory disease. To show this, the authors can examine the activation of these genes (e.g. Bach2, Il18R1, from Table 2) using their assay, either using T cells from humans containing disease-associated variants at these gene loci, or by using T cells with a genetic disruption of the associated loci.

While providing insights for the pathogenesis of IBD, this study's main impact would be in the enhancing our understanding of how different modes of co-stimulation differ to activate T cells and prompt broader consideration of use of different co-stimulatory ligands in these in vitro assays and evaluation of their function in vivo.

Reviewer #1 (Public Review):

This manuscript provides an important case study for in-depth research on the adaptability of vertebrates in deep-sea environments. Through analysis of the genomic data of the hadal snailfish, the authors found that this species may have entered and fully adapted to extreme environments only in the last few million years. Additionally, the study revealed the adaptive features of hadal snailfish in terms of perceptions, circadian rhythms and metabolisms, and the role of ferritin in high-hydrostatic pressure adaptation. Besides, the reads mapping method used to identify events such as gene loss and duplication avoids false positives caused by genome assembly and annotation. This ensures the reliability of the results presented in this manuscript. Overall, these findings provide important clues for a better understanding of deep-sea ecosystems and vertebrate evolution.

Reviewer #1 (Public Review):

In the manuscript "Long‐read single‐cell sequencing reveals expressions of hypermutation clusters of isoforms in human liver cancer cells", S. Liu et al present a protocol combining 10x Genomics single-cell assay with Element LoopSeq synthetic long-read sequencing to study single nucleotide variants (SNVs) and gene fusions in Hepatocellular carcinoma (HCC) at single‐cell level. The authors were the first to combine LoopSeq synthetic long‐read sequencing technology and 10x Genomics barcoding for single cell sequencing. For each cell and each somatic mutation, they obtain fractions of mutated transcripts per gene and per each transcript isoform. The manuscript states that these values (as well as gene fusion information) provide better features for tumor-normal classification than gene expression levels. The authors identified many SNVs in genes of the human major histocompatibility complex (HLA) with up to 25 SNVs in the same molecule of HLA‐DQB1 transcript. The analysis shows that most mutations occur in HLA genes and suggests evolution pathways that led to these hypermutation clusters. Yet, very little is said about novel isoforms and alternative splicing in HCC cells, differences in isoform ratio between cells carrying different mutations, or diversity of alternative isoforms across cells. While the manuscript by Liu et al. presents a promising combination of technologies, it lacks significant insights, a comprehensive introduction, and has significant problems with data description and presentation.

Major comments:

1. The introduction section is scarce. It lacks description of important previous works focused on clustered mutations in cancers (for example, PMID35140399), on deriving the process of cancer development through somatic evolution (PMID32025013, from single cell data PMID32807900). Moreover, some key concepts e.g. mutational gene expression and mutational isoform expression are not defined. The introduction and the abstract contain slang expressions e.g. "protein mutation', a combination of terms I teach my students not to use.

2. In the results section, to select the mutations of interest, the authors apply UMAP dimensionality reduction to the mutation isoforms expression and cluster samples in UMAP space, then select the mutations that are present only in one cluster, then apply UMAP to the selected mutations only and cluster the samples again. The motivation for such a procedure seems unclear, could it be replaced with a more straightforward feature selection?

3. As I understand, the first "mutated isoform"-based UMAP clustering was built from expression levels of 205 "mutational isoforms". What was the purpose and outcome of the second "mutated isoform"-based UMAP clustering (Figure 2E)? In the manuscript the authors just describe the clusters and do not draw any conclusions or use the results of the clustering anywhere further.

4. The authors just cluster the data three times based on expression levels of different sets of "mutational isoforms" and describe the clusters. What do we need to gather from these clustering attempts besides the set of 113 mutations used for further analysis? What was the point of the re-clusterings? Did the authors observe improvement of the classification at each step?

5. The alignment of short reads generated from hypermutated transcriptomes is non-trivial. The proposed approach could address the issue without need for whole genome sequencing and offer insights about the cancer development through somatic evolution. Why didn't the authors use modern phylogenetic approaches in the "Evolution of mutations in HLA molecules" section or at least utilize the already performed clustering to infer cell lineages?

6. I am not sure I understood the definition of "mutated gene expression levels" and "mutated isoform expression levels" in the "Mutational gene expression and fusion transcript enhanced transcriptome clustering of benign hepatocytes and HCC" section. The authors mention that gene lists included all the isoforms within the same range of standard deviation. If I understand it correctly, they are equal if there is only one expressed transcript isoform. In that case, this overlap is not surprising at all.

7. "To investigate the roles of gene expression alterations that were not accompanied with isoform expression changes, UMAP analyses were performed based on the non‐overlapped genes." Venn diagrams (Sup Figure 8) show that there are much less "non-overlapped genes" than "genes that showed both gene and isoform level changes" for each SD threshold (for example, for SD>=0.8 59 vs 275). Could that be the reason why clustering based on the former group is worse i.e the cancer and normal cells are separated less clearly?

Reviewer #1 (Public Review):

The authors sought to craft a method, applicable to biobank-scale data but without necessarily using genotyping or sequencing, to detect the presence of de novo mutations and rare variants that stand out from the polygenic background of a given trait. Their method depends essentially on sibling pairs where one sibling is in an extreme tail of the phenotypic distribution and whether the other sibling's regression to the mean shows a systematic deviation from what is expected under a simple polygenic architecture.

Their method is successful in that it builds on a compelling intuition, rests on a rigorous derivation, and seems to show reasonable statistical power in the UK Biobank. (More biobanks of this size will probably become available in the near future.) It is somewhat unsuccessful in that rejection of the null hypothesis does not necessarily point to the favored hypothesis of de novo or rare variants. The authors discuss the alternative possibility of rare environmental events of large effect. Maybe attention should be drawn to this in the abstract or the introduction of the paper. Nevertheless, since either of these possibilities is interesting, the method remains valuable.

Reviewer #1 (Public Review):

In their manuscript entitled: "Is tumor mutational burden predictive of response to immunotherapy?", Gurjao and colleagues discuss the use of tumor mutational burden (TMB) as a predictive biomarker for cancer patients to respond to immune checkpoint blockage (ICB). By analyzing a large cohort of 882 patient samples across different tumor types they find either little or no association of TMB to the response of ICB. In addition, they showed that finding the optimal cutoff for patient stratification lead to a severe multiple testing problem. By rigorously addressing this multiple testing problem only non-small cell lung cancer out of 10 cancer types showed a statistically significant association of TMB and response to ICB. Nevertheless, it is clearly shown that in any case the rate of misclassification is too high that TMB alone would qualify as a clinically suitable biomarker for ICB response. Finally, the authors demonstrate with a simple mathematical model that only a few strong immunogenic mutations would be sufficient for an ICB response, thereby showing that also patients with a low TMB score could benefit from immunotherapy. The manuscript is clearly written, the results are well presented and the applied methods are state-of-the-art.

Reviewer #1 (Public Review):

This work presents findings on the cellular and ultrastructural organization of the nervous system in the freshwater polyp Hydra. Although the work presents potentially important data, there are several points that need to be addressed:

1) The antibody has to be properly validated as a tool for detecting all neurons. As it stands, the antibody might not recognize a cadherin and it is not clear whether it is specific and labels all neurons.

2) The lack of communication between the two nerve nets is an interesting observation, but its implications are limited due to technical reasons. This should be investigated further.

3) The apparent lack of typical terminal synaptic contacts and the predominant presence of "en passant" contacts in the neurite bundles could be the central element of the paper but this would have to be supported by more thorough observations and experiments.

4) The authors should highlight the novelty of the findings as compared to previous work that had already addressed some of these points.

Reviewer #1 (Public Review):

The contribution of Klughammer et al reports on the fabrication and functionalization of zero-mode waveguides of different diameters as a mimic system for nuclear pore complexes. Moreover, the researchers performed molecular transport measurements on these mimic systems (together with molecular dynamic simulations) to assess the contribution of pore diameter and Nsp functionalization on the translocation rates of BSA, the nuclear transport protein Kap95 and finally the impact of different Kap95 concentrations on BSA translocation and overall selectivity of the mimicked pores as a function of their diameter. In order to assess the effect of the Nsp1 on the coated pores to the translocation rates and molecular selectivity they also conducted separated experiments on bare nano-pores, i.e., without coating, and of different diameters. One of the most novel aspects of this contribution is the detection scheme used to assess the translocation rates & selectivity, i.e., the use of an optical scheme based on single molecule fluorescence detection as compared to previous works that have mostly relied on conductance measurements. The results are in general convincing, the experiments carefully performed and the procedures explained in detail. Some weaknesses are identified on the FDTD simulations and interpretation of the single molecule data since they might be affected by quenching of the dye in close proximity to the pore. These weaknesses should be clarified and discussed properly.

Importantly, this study provides new insights on the mechanisms of nuclear transport contributing to further our understanding on how real nuclear-pore complexes (i.e., in living cell) can regulate molecular transport. The recent findings that the nuclear pore complexes are sensitive to mechanical stimulation by modulating their effective diameters, adds an additional level of interest to the work reported here, since the authors thoroughly explored different nano-pore diameters and quantified their impact on translocation and selectivity. There are multiple avenues for future research based on the system developed here, including higher throughout detection, extending to truly multicolor schemes or expanding the range of FG-Nups, nuclear transport proteins or cargos that need to be efficiently l transported to the nucleus through the nuclear pore complexes. As a whole, this is an important contribution to the field.

Joint Public Review:

Chen and collaborators first analysed in sheep embryonic gene editing using CRISPR-Cas9 technology to invalidate the two alleles of Mstn and Fgf5 genes by using different ratios of Cas9 mRNA and sgRNA. They showed that a ratio of 1:10 had highest efficiency and they successfully generated two sheep with biallelic mutations of both genes. Materials and Methods on the generation of gened edited sheep is entirely missing. The data on these gene edited sheep have been already published twice by the authors in different contexts. Other groups reported on gene editing of Mstn or Fgf5 in sheep embryos and the resulting phenotypes.

Although the findings are interesting, they do not provide sufficiently new scientific information or advancements in producing genetically modified livestock with improved production characteristics. While the MSTNDel273 sheep exhibited an increased number of muscle fibers, the data provided did not demonstrate a significant improvement in meat productions, quality or quantity in the MSTNDel273 sheep vs WT.

The authors indicate that sgRNA design changes in addition to changing the molar ratio of Cas9MRNA:sgRNA improved the ability to generate biallelic homozygous mutant sheep; however, the data provided to not demonstrate any significant difference. Given the small number of sheep that were actually produced and evaluated,it is extremely difficult to demonstrate anything that was analyzed to be significantly (statistically) different between MSTNDel273 sheep and WT, yet the authors seem to ignore this in much of their discussion. There is no explanation as to why the authors started with sheep that were FGF5 knockouts. The reviewer assumes that this was simply a line of sheep available from previous studies and the goal was to produce sheep with both improved hair/wool characteristics in addition to improved muscle development. However, the use of FGF5 knockout sheep complicates the ability to accurately decipher the unique aspects associated with targeting only myostatin for knock-out. At minimum, this is a variable that has to be considered in the statistical analysis. No information is provided on the methods used to produce the MSTNDel273 sheep, which is fundamentally important. It is assumed they were produced by injecting one-cell zygotes then transferring these into surrogate females. The methods employed might have a profound effect on the outcome.

Authors genotyped one sheep with a biallelic three base pair deletion in Mstn exon 3 and a compound heterozygote mutation in Fgf5 with a 5 nucleotides deletion on one allele and 37 nucleotides deletion on the other allele, partially spanning over the same region. This sheep developed a double muscle phenotype, which was documented using photography and CT scan. The hair phenotype was not further addressed, but authors referred to a previous publication.

Authors performed morphometric studies on two distinct muscles, longissimus dorsi and gluteus medius, and found a profound fiber hypotrophy in the Mstn-/-;Fgf5-/- double mutants, with a shift from larger fiber diameter to smaller fiber sizes. Morphometric studies showed only a low percentage of fibers in wt and mutant sheep had fiber cross sectional areas larger than 800 µm2, whereas about 30% in wt and about 60% in the mutant had CSA of <400 µm2. The report of one case, without reproducing the phenotype in other sheep, is scientifically insufficient. The fiber sizes in wt sheep remains far below previously published reports in sheep (about 3-5 times smaller) and as compared to other species, which suggests a methodological error in morphometric methods.

The authors also investigated the influence of Fgf5 mutation on muscle development. They determined fiber cross sectional area in heterozygous Fgf5 mutant (number of investigated animals not given) and conclude that Mstn mutation but not Fgf5 mutation caused the double muscle phenotype. Results are insufficient to support this conclusion. Firstly, authors investigated heterozygous FGF5 sheep and not homozygous mutants. Secondly, FGF5 has previously been shown to stimulate expansion of connective tissue fibroblasts and to inhibit skeletal muscle development during limb embryonic development (Clase et al. 2000). Of note, Mstn is also expressed during embryonic development. A combined knockout could therefore entail synergistic effects and cause muscle hyperplasia that is not found in individual knockout, a hypothesis that was not addressed by the authors.

The authors generated and studied an F1 generation of mutant sheep with heterozyogous mutation in Mstn and Fgf5. In Mstn+/-;Fgf5+/-, gluteus medius muscle was found to be larger compared to wt sheep, whereas other muscles were smaller, and overall meat quantity did not change. Morphometric studies revealed a similar muscle fiber hypotrophy and muscle hyperplasia as in the Mstn-/-;Fgf5-/- gluteus muscle.

In the next part of results, authors investigated the presence of myostatin protein in homozygous Mstn muscle using immunohistochemistry and found no differences compared to wt, however, positive and negative controls are missing. The also determined Mstn transcription and protein quantity using WB in heterozygous Mstn muscle and found no difference. The authors did not provide data to explain of why the herein generated Mstn mutation causes muscle fiber hypotrophy, whereas most work on myostatin abrogation demonstrated fiber hypertrophy.

Authors then isolated myoblasts from hind limbs of 3-month-old sheep fetuses and cultured in presence of 20% fetal bovine serum before switching to differentiation medium containing 2% horse serum. The cultures showed increased proliferation of Mstn+/-;Fgf5+/- myoblasts as well as downregulation of genes associated with muscle differentiation as well as reduced fusion index. No experiments were performed to assure whether the myostatin and FGF5 pathways were inhibited. No control experiments using supplementation with recombinant proteins and using growth factor depleted culture supplements were performed. As FGF5 and myostatin are secreted factors, evidence is missing whether this led to conditioning of the culture medium. Of note, previous work in mice demonstrated that the double muscle phenotype developed independent of satellite cells activity (Amthor et al. 2009).

Authors then performed RNA seq from Mstn+/-;Fgf5+/- muscle and found a number of differentially expressed genes, but none has been previously reported being involved in the myostatin signaling pathway, so the authors chose to only focus on FOSL1 and associated genes. Authors then demonstrated that Pdpn and Ankrd2 were upregulated during myogenic differentiation, whereas FOPSL1 was downregulated. Moreover, Fosl1 transcription was upregulated in myoblasts and myotubes from Mstn+/-;Fgf5+/- muscle. Authors showed an interaction between Fosl1 and Myod1. Moreover, authors demonstrated that Polsl1 directly binds to the Myod1 promoter. Authors also found decreased p38 MARPK protein levels in proliferating myoblasts from Mstn+/-;Fgf5+/- muscle and increased p38 MARPK in differentiating myotubes.

Furthermore, gain-of-function by overexpressing FOSL1 promoted cell proliferation and inhibited differentiation, and tert-butylhydroquinone, an indirect activator of FOSL1 also inhibited myogenic differentiation. The findings do not support the idea that FOSL1 is not involved, but neither do they strongly support the involvement of FOSL1. The observations made by the authors could be co-incidental and not causative in nature.

The manuscript by Chen et al. demonstrated successful gene editing in sheep embryos to obtain biallelic mutation of Mstn and FGF5. The resulting double muscle phenotype resulted from fiber hypotrophy and hyperplasia, which contradicts findings in the literature. Chen et al. generated F1 heterozygous offsprings, in which Mstn transcription and translation did not change. Myoblasts from these animals showed increased proliferation and decreased differentiation, which authors interpreted as the underlying cellular mechanism of the double muscle phenotype. However, no work on muscle development in these animals is presented. Important in vitro control experiments are missing. Chen and collaborators found Fosl1 as a differentially expressed gene in Mstn+/-;Fgf5+/- muscle. Fosl1 drives myoblast proliferation and has direct regulatory effect on the Myod1 promoter. The cellular and molecular mechanism of Fosl1 during myogenesis is novel and solid evidence. However, data remain inadequate to conclude whether Fosl1 indeed acts downstream of myostatin.

As the significant findings are minimal, the amount of text provided, figures and tables are disproportionally excessive. A large number of different molecular techniques are employed to try and decipher the mechanism(s) that result in the observed phenotype = double muscling. The authors focus on the MEK-ERK-FOSL1 pathway an suggest this the key pathway/mechanism resulting in the phenotype observed in MSTNDel273sheep. However, they provide very little solid evidence to support this notion.

The manuscript is very long, complicated and difficult to read, given the minimum amount of significant information that is provided. Further, it misses information in material methods, on the generation of animals, on histological techniques and morphometric studies. There is no information provided on the sex of the animals produced and then analyzed. There are also a number of editorial mistakes e.g. the authors refer to tables S1-S4 in the materials and methods and results section, but and there is no table S1-S4 provided.

Reviewer #1 (Public Review):

It is well established that tuberculosis (TB), which is caused by Mycobacterium tuberculosis (Mtb), is a leading cause of mortality and morbidity worldwide. However, the only vaccine licensed against tuberculosis is Bacille Calmette Guerin (BCG), has been around for nearly a century, and has limited efficacy in adults. Herein, the authors sought to investigate the effectiveness of a nanoparticle-based formulation of a subunit vaccine composed of Mtb lipid and protein antigens. The authors found that they were able to load the lipid, mycolic acid, into their nanoparticles without disrupting the architecture, and that the loaded particles activated T cells both in vitro and in vivo. Moreover, when they vaccinated with particles loaded with both lipid and protein antigens, they found that the lipid antigen persisted, and mycolic acid-specific T cells were able to be activated 6 weeks post-vaccination, in contrast to peptide-specific T cells. The authors investigated further and found that persistence required the nanoparticle encapsulation, rather than free lipid, and that it was independent of route (intratracheal, intravenous, or subcutaneous) of administration. To address the mechanisms underlying antigen persistence, the authors loaded the nanoparticles with a dye and demonstrated that the nanoparticle encapsulated lipid antigen was primarily stored in lung alveolar macrophages and that CD1b+ dendritic cells presented the antigen to mycolic acid specific T cells. Finally, the authors conducted mixed bone marrow chimera studies to examine the phenotype of the mycolic acid specific T cells and found that the memory T cell population phenotypically resembled T follicular helper, regulatory T cells, and exhausted T cells. Interestingly, while a large percentage of these lipid antigen specific T cells in the lymph nodes, lung and spleen were CXCR5+PD1+, the cells were still proliferating (Ki67+). Overall, this is a comprehensive study that has the potential to significantly enhance the field.

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. They also provide data from human subjects who were classified as either "healthy" or "diabetic," but there is no other characterization or description of these people, making it difficult to ascertain the context by which they were studied. Nevertheless, these findings could be gleaned from the literature, and yet there remains surprising uncertainty regarding the mechanism of acetate production by the liver. The authors use ShACOT12/8 and liver-specific ACOT12/8 knockout mice to demonstrate that these acetyl-CoA hydrolases are largely necessary for acetate production. There is data on this role for ACOTs in the literature, but they have yet to be widely studied. 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 only partially 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. Finally, the authors try to demonstrate that hepatic ACOT-mediated acetate production is necessary for normal motor function. The tracer data used to support the importance of acetate metabolism do not include loss of function models and generally need to be reported more transparently. Conceptually, one may be skeptical of the rather dramatic loss of motor function in the context of a relatively minor circulating nutrient. This may be a significant finding but requires more supporting evidence. Overall, the authors convincingly show that ACOT12/8 are critical for hepatic acetate production in mice, which will be helpful for the field, but the ramifications will require further investigation.

Reviewer #1 (Public Review):

Hermanns et al., investigated the virus diversity and prevalence patterns in conjunction with mosquito community compositions in natural and disturbed ecosystems (5 habitats) within the Tai National Park in Cote d'Ivorie. The ultimate aim was to analyse the interplay between viral biodiversity and prevalence with mosquito host biodiversity and prevalence. Pools of morphologically identified mosquitoes from pristine forest habitats through to habitats of high human disturbance were analysed for the presence of viruses of 12 major mosquito-borne virus taxa. While 15 of the viruses detected have been published previously, 34 potentially new viruses were detected of which the full genome of 5 was completely elucidated for phylogenetic analysis and temperature-dependent replication of 4 was performed. Via comprehensive analyses of the biodiversity of the viruses detected in mosquitoes collected within each habitat, it was shown that i) the highest virus richness was observed in the intermediately disturbed habitats, ii) that the prevalence of viruses corresponded to the relative abundance of the main mosquito host species that carried them, but iii) when just the main host mosquito for each virus was analysed alone in each habitat, that there was no trend in increasing or decreasing virus prevalence.

The conclusions within the paper were generally well-justified, but a caveat of the study is that the (likely) mechanisms of transmission of the viruses identified in the paper were not discussed. Many of these viruses are most likely maintained in nature via vertical transmission and thus, this information needs to be taken into consideration. Due to the fact that it is likely that many of these insect-specific viruses evolve with their mosquito host, it was not surprising that if there was an increased abundance of a particular mosquito species, that there was also increased prevalence of the virus which it hosts. Of course, this may differ depending on the viral family, but requires comment in the context of what is known. Furthermore, there requires clarification as to why analysing insect-specific virus prevalence and diversity will serve as a model for the study of typical arboviruses due to the differences in their maintenance in nature.

For many of the putative new viruses, only small sequences of less than 1200 nt were analysed. Granted that the RdRp is the most conserved gene, how was the 5% demarcation for a new species determined when established criteria differ to this.

Reviewer #1 (Public Review):

In this study, the authors study the effect of dynactin disruption on kinetochore fiber (k-fiber) length in spindles of dividing cultured mammalian cells. Dynactin disruption is known to interfere with dynein function and hence spindle pole formation. The main findings are that poles are not required for correct average k-fiber length and that severed k-fibers can regrow to their correct length both in the presence and absence of poles by modulating their dynamic properties at both k-fiber ends. In the presence of poles, regrowth is faster and the variation between k-fiber lengths is smaller. This is a very interesting study with high-quality quantitative imaging data that provides important new insight into potential mechanisms of spindle scaling, extending in an original manner previous work on this topic in cultured cells and in Xenopus egg extract. The Discussion is interesting to read as several possible mechanisms for k-fiber length control are discussed. The technical quality of the study is very high, the experiments are very original, and most conclusions are well supported by the data. Especially, the experiments observing the regrowth of k-fibers after severing and the study of the dynamic properties of these k-fibers provide very novel insight. Addressing the following concerns could potentially improve the manuscript:

(1) The phenotype generated here by disrupting dynactin via overexpressing p50 appears to be different from that caused by knocking down NuMA or dynein - as previously reported by the Dumont lab (Hueschen et al., 2019). In this study here, unfocused spindles are observed whereas earlier turbulent spindles were observed. This raises the question of whether dynein activity that contributes to pole focusing is really completely inhibited here. These discrepancies in phenotypes seem to deserve an explanation. Is k-fiber length in cultured mammalian cells only maintained in the case of this specific type of inhibition?

(2) p50 addition and also p150-cc1 addition was often used in Xenopus egg extract in order to inhibit dynein function. Considerably larger concentrations of p50 than p150-cc1 needed to be used. Can the authors estimate the level of overexpression of p50 in the cells they study? It seems that could be possible given that a mCherry fusion protein can be overexpressed. Was it necessary to select cells with a particular level of mCherry-p50 overexpression to observe the reported phenotypes?

(3) Some comparison to previous experiments using p50 and p150-cc1 addition to Xenopus egg extract spindles could put this study better into the context of the available literature. It seems from previous publications that the p50 addition produced short, unfocused, barrel-shaped spindles, indicating that spindle length is maintained without poles, whereas the p150-cc1 addition produced elongating spindles (e.g. Gaetz & Kapoor, 2004).

(4) In this context, it seems that some more explanation is required for the observations presented in Fig. 1D and 1E. It appears that spindle length and k-fiber length have been measured quite differently. Not much information is provided for how spindle length was defined and measured (please expand this part of the Methods). Could the two different methods of measurement be the reason for the mean k-fiber length remaining unaltered in dynactin-disrupted spindles, whereas the spindle length increases in these cells? If not, do non-k-fiber microtubules contribute to unfocused spindles being longer or are chromosomes not aligned in the metaphase plate causing the increase in spindle length by misalignment of k-fiber sister pairs?

(5) It seems that in the Discussion it is implied that k-fibers can respond to severing in both focused and unfocused spindles by modulating their dynamics at both ends of the k-fibers, but in the Results section the wording is more cautious because of the difference in 'flux' in severed and unsevered unfocused spindles is not significant (Fig. 4D, blue data). It appears indeed that there is also a difference in flux between severed and unsevered unfocused spindles, but the number of data points is too small. Depending on how difficult these experiments are, it could be worth increasing the size of the data set to come to a clear conclusion, given that the data shown in Figs. 3 and 4 are quite remarkable and form the core of the study.

(6) Can the authors exclude that the stopping of 'flux' at minus ends after severing is due to some sort of permanent damage induced by ablation? In other words, do severed spindles begin to flux again once they have regrown to their original length?

(7) To this reader, the conceptualization of distinguishing between 'global' and 'local' effects/behavior was a little confusing, both in the title and also later in the text. The concept of 'local' regulation of k-fiber length appears to contradict the observation that k-fiber length can be regained after severing by changes in the dynamics at both ends (so at two very different locations) which is a rather remarkable finding. Maybe distinguishing between 'individual' and 'collective' k-fiber behavior could be clearer.

(8) Can the authors exclude that some of the differences between unfocused and focused spindles could be due to altered dynein activity at kinetochores? Or due to the dynein-dependent accumulation of certain spindle proteins along microtubules towards the minus ends of k-fibers or other spindle microtubules, instead of being due to only the presence versus absence of poles? Could this be tested by ablating both poles? If this is too challenging, a discussion of these possibilities could be justified.

Reviewer #1 (Public Review):

One aim of this paper was to study historical migration from Botswana during the time of the development of the HIV epidemic. The second aim was to test whether the migration networks impacted the development of the epidemic. The first aim was achieved: this paper used historical census data in a clear way, to describe the qualities of characteristics of migration in the country at four points in time, from 1981 to 2011. Very detailed data are presented in clear ways, using network chord diagrams, sharing age- and sex-specific migration rates, and urban-rural classifications. However, data was not presented to achieve the second aim. The authors reviewed some important literature about migration and HIV. They suggested that the migration patterns, such as from specific mining towns and mostly between districts, could have been important in supporting the generalized spread of HIV. But without evidence linking HIV prevalence over time in the linked districts in Botswana, this aim was not supported.

One other limitation of the paper was that very little context, outside of migration rates, was provided. Is there any additional information about economic growth, or political event for example, that could clarify or add context to these migration flows? As it stands now, these analyses are quite basic and don't take into account underlying demographic, economic, or political trends.

The data presented in this paper has potential impact. As the paper stands now, it could be quite useful for future work when linked to additional data sources on HIV prevalence over time (or other questions that could have been influenced by migration patterns).

Reviewer #1 (Public Review):

Studies of the p38g/d MAP kinase signaling pathways using loss-of-function approaches are compromised the finding that the expression of the ERK family MAP3K Tpl2 is down-regulated. Dissection of the specific roles of p38g/d is therefore difficult. Here the authors report that compound mutant mice with a kinase-inactive p38y MAPK mutation and p38d deficiency show no defects in Tpl2 expression. The importance of this study is therefore that they describe a mouse model that can be used to examine p38g/d MAP kinase function. The data presented are solid and convincing. The authors show that p38g/d MAP kinase signaling contributes to macrophage responses to endotoxin. Moreover, the authors identify Ser44 as an inhibitory site of MEF2D phosphorylation by p38d.

Reviewer #1 (Public Review):

In this manuscript, the authors have demonstrated the direct effect of androgen receptor activation on B - cell frequencies. In the clinical part of the research, they have found increased frequencies of age-associated double-negative B memory cells and elevated levels of circulating immunoglobulin M (IgM) in women with hyperandrogenic phenotypes of PCOS. The major study strengths are driven by their experimental part. It was shown that the transfer of serum IgG from women with PCOS into wild-type female mice increases body weight, whereas RAG1 knock-out mice, which lack mature T- and B cells, do not demonstrate any signs of hyperandrogenism. Simultaneously, an androgen receptor antagonist prevents increased B cell numbers induced by androgens, whereas B cell-deficient mice are not protected from developing a PCOS-like phenotype when exposed to DHT. Generally, the author's conclusions are based on evidence, and this study opens up a new direction of research in this area.

Reviewer #1 (Public Review):

This paper provides valuable (and impressive) data on the geometry of cerebellar foliation among 56 species of mammals and gives novel insights into the evolution of cerebellar foliation and its relationship with the anatomy of the cerebrum. Thus far, the majority of the research on brain folding focuses on the cerebral cortex with little research on the cerebellum. The results from Heuer et al confirm that the evolution of the cerebellum and cerebrum follows a concerted fashion across mammals. Moreover, they suggest that both the cerebrum and cerebellum folding are explained by a similar mechanistic process.

1. Although I found the introduction well written, I think it lacks some information or needs to develop more on some ideas (e.g., differences between the cerebellum and cerebral cortex, and folding patterns of both structures). For example, after stating that "Many aspects of the organization of the cerebellum and cerebrum are, however, very different" (1st paragraph), I think the authors need to develop more on what these differences are. Perhaps just rearranging some of the text/paragraphs will help make it better for a broad audience (e.g., authors could move the next paragraph up, i.e., "While the cx is unique to mammals (...)").

2. Given that the authors compare the folding patterns between the cerebrum and cerebellum, another point that could be mentioned in the introduction is the fact that the cerebellum is convoluted in every mammalian species (and non-mammalian spp as well) while the cerebrum tends to be convoluted in species with larger brains. Why is that so? Do we know about it (check Van Essen et al., 2018)? I think this is an important point to raise in the introduction and to bring it back into the discussion with the results.

3. In the results, first paragraph, what do the authors mean by the volume of the medial cerebellum? This needs clarification.

4. In the results: When the authors mention 'frequency of cerebellar folding', do they mean the degree of folding in the cerebellum? At least in non-mammalian species, many studies have tried to compare the 'degree or frequency of folding' in the cerebellum by different proxies/measurements (see Iwaniuk et al., 2006; Yopak et al., 2007; Lisney et al., 2007; Yopak et al., 2016; Cunha et al., 2022). Perhaps change the phrase in the second paragraph of the result to: "There are no comparative analyses of the frequency of cerebellar folding in mammals, to our knowledge".

5. Sultan and Braitenberg (1993) measured cerebella that were sagittally sectioned (instead of coronal), right? Do you think this difference in the plane of the section could be one of the reasons explaining different results on folial width between studies? Why does the foliation index calculated by Sultan and Braitenberg (1993) not provide information about folding frequency?

6. Another point that needs to be clarified is the log transformation of the data. Did the authors use log-transformed data for all types of analyses done in the study? Write this information in the material and methods.

7. The discussion needs to be expanded. The focus of the paper is on the folding pattern of the cerebellum (among different mammalian species) and its relationship with the anatomy of the cerebrum. Therefore, the discussion on this topic needs to be better developed, in my opinion (especially given the interesting results of this paper). For example, with the findings of this study, what can we say about how the folding of the cerebellum is determined across mammals? The authors found that the folial width, folial perimeter, and thickness of the molecular layer increase at a relatively slow rate across the species studied. Does this mean that these parameters have little influence on the cerebellar folding pattern? What mostly defines the folding patterns of the cerebellum given the results? Is it the interaction between section length and area? Can the authors explain why size does not seem to be a "limiting factor" for the folding of the cerebellum (for example, even relatively small cerebella are folded)? Is that because the 'white matter' core of the cerebellum is relatively small (thus more stress on it)?

8. One caveat or point to be raised is the fact that the authors use the median of the variables measured for the whole cerebellum (e.g., median width and median perimeter across all folia). Although the cerebellum is highly uniform in its gross internal morphology and circuitry's organization across most vertebrates, there is evidence showing that the cerebellum may be organized in different functional modules. In that way, different regions or folia of the cerebellum would have different olivo-cortico-nuclear circuitries, forming, each one, a single cerebellar zone. Although it is not completely clear how these modules/zones are organized within the cerebellum, I think the authors could acknowledge this at the end of their discussion, and raise potential ideas for future studies (e.g., analyse folding of the cerebellum within the brain structure - vermis vs lateral cerebellum, for example). I think this would be a good way to emphasize the importance of the results of this study and what are the main questions remaining to be answered. For example, the expansion of the lateral cerebellum in mammals is suggested to be linked with the evolution of vocal learning in different clades (see Smaers et al., 2018). An interesting question would be to understand how foliation within the lateral cerebellum varies across mammalian clades and whether this has something to do with the cellular composition or any other aspect of the microanatomy as well as the evolution of different cognitive skills in mammals.

Reviewer #1 (Public Review):

This is a very elegant study of the dynamics of the longitudinal surface pH profile in growing Arabidopsis roots. The authors first present a new powerful method for the visualization of the surface pH profiles using the pH-sensitive fluorescent dye fluoresceine-5 (or 6)-sulfonic acid. This is an interesting new tool for studying surface pH in plants and perhaps other organisms. The main findings are that the presence of an alkaline band at the transition zone does not depend on AHA abundance (shown by immunolocalization) or activity shown by pharmacology (FC treatment) or by using plants expressing hyperactive, or PP2CD1- inhibited AHA2 or by using KO mutants aha2 or pp2c-d respectively. This band depends on auxin and AUX1-mediated auxin influx and rapid auxin response components AFB1 and CNGC14. The latter has a distribution along the root fitting the longitudinal surface pH zonation and are both required for it. Canonical auxin signaling (TIR) has more quantitative effects on the extent of the auxin-induced alkalinization. They also observe that the rapid auxin response module is constantly activated and inactivated as shown by the time-dependent variations in surface pH within the alkaline zone on both sides of the root and the rapid AUX1, AFB1, and CNGC14-dependent acidification of the upper surface and alkalinisation of the lower surface during gravitropic responses. Finally, they provide some evidence for the role of the rapid auxin responses in avoiding physical obstacles in the environment of the root.

The data look very sound. The originality of the approach used is the observation of dynamic responses at a second-to-minute time scale and to systematically correlate between the observed changes in the longitudinal surface pH profile with changes in growth rate. The manuscript is well-written with clear figures.

Reviewer #1 (Public Review):

This paper studies color vision in anemonefish. The central conclusion of the paper is that anemonefish use signals from their UV cones to discriminate colors that would not otherwise be distinguishable; this differs from other fish in which UV cones extend the range of wavelengths of sensitivity but do not add a dimension to color vision. The work fits into a rich history of studies investigating how color vision fits into an animal's ecological niche. My primary concerns regard the microspectrophotometry data from single cones and some aspects of the presentation of the behavioral data.

Microspectrophotometry<br /> The spectral properties of the cone types are a key issue for interpreting the results. These were measured using MSP, and fits are shown in Figure 2. The raw data shown in Fig. S1 appears more complicated than indicated in the main text. The templates miss the measurements across broad wavelength bands in each cone type. Particularly concerning is the high UV absorbance across cone types and the long-wavelength absorbance in the UV cone. It is not clear how this picture supports the relatively simple description of cone types and spectral sensitivities given in the main text and which forms the basis of the modeling.

Presentation<br /> The results are not presented in a straightforward way - at least for this reviewer. What is missing for me is a clear link between the psychometric curves in Figure 3A and the discrimination thresholds indicated in Figure 3B and Figure 4. Figure 3A is only discussed in the text on line 289 - after Figure 4 has been introduced and discussed. It would have been very helpful for me if the psychometric curves were first introduced and described, then the relation to Figure 3B was clearly indicated (perhaps with a single psychometric curve as an example). Similarly for Figure 4 the relationship between specific psychometric curves and the threshold plotted would be quite helpful. Currently it takes a careful reading to understand why being below the dashed line in Figure 4 is important.

RNL model<br /> The data is fit and interpreted in the context of the receptor noise limited model. The paragraph in the discussion about complementary color pairs suggests that this model is incorrect (text around line 332). Consideration of how the results depend on the RNL model is important, especially given the interpretation here.

Figure 3B<br /> This is the key figure in the paper. But several issues make seeing the data in this figure difficult. First, the important part of the figure is buried near the origin and hard to see. Can you show a surface that connects the thresholds in the different chromatic directions, or otherwise highlight the regions of discriminable and not discriminable colors?

Reviewer #1 (Public Review):

The technical approach is novel, exciting, and very carefully calibrated, and can certainly lead to many interesting downstream applications, e.g. enhanced throughput and consistency for screening purposes. Compared to traditional single-assay designs, this solution eliminates some sources of human error associated with manual dilution of reagents and reproducibility and facilitates the study of a wide spectrum of concentrations particularly at the low-concentration (below nanomolar), high-sensitivity range.

However, the study itself does not generate any fundamentally novel insights or new understanding of the biology or biophysics of the chemotactic response. It mainly reproduces previously measured trends in a more efficient and controlled manner. The novelty of the paper is purely in the technology, whereas the major weakness is that this new technology was not used to demonstrate or discover some new biological phenomenon.

Reviewer #1 (Public Review):

Croft, Pearce, and colleagues used a combination of spatial transcriptomics and analysis of publicly available scRNA-sequencing data of patients with PDAC to assess differences in the transcriptome of tumor proximal and distal stromal cells and associated these differences with survival data. Focusing on aSMA+ cancer-associated fibroblasts (CAFs), they find that tumor-proximal CAFs were defined by high expression of PDPN and Wnt ligands, and tumor-distal CAFs expressed inflammatory, complement, and Wnt inhibitor genes. While gene expression in relation to tumor distance did not per se correlate with clinical outcome, the authors find that individual genes within the tumor proximal and distal subsets were associated with increased or decreased survival. Based on this, the authors suggest a combination of targeting tumor-proximal CAFs defined by PDPN expression and inhibition of HIF-1a in the tumor distal stroma. Using an innovative approach to combine their spatial transcriptomics with single-cell transcriptomics data, the authors further identify an association between the expression of proximal CAF marker genes with elevated expression of complement and retinoic acid metabolism genes, and that complement genes were associated with increased survival.

While spatial differences in the abundance of different CAF subsets have been suggested before, the spatial transcriptomic data presented in this study provide a fresh look at CAF heterogeneity in PDAC and will be a useful resource for hypothesis generation and testing on the spatial regulation of CAF heterogeneity. However, there are major concerns associated with the interpretation of the data given the markers used to generate it, the association with single-cell data, and an overinterpretation of transcriptomic data, as detailed below.

1) The spatial transcriptomic data on fibroblasts relies on aSMA as a fibroblast marker. However, several studies in PDAC and other tumors have shown that there are subtypes of CAFs that do not (or only weakly) express aSMA, including inflammatory CAFs (iCAFs) and antigen-presenting CAFs (apCAFs) which therefore might have been missed by the authors. While there is no universal CAF marker, more recently the pancreatic cancer field has been using PDPN as a pan-CAF marker. aSMA is a classical myofibroblast marker across tissues and tumor types and the authors should state that they focused on myofibroblasts in their study.

2) While the association of the spatial data and single-cell data is innovative, it is flawed by the use of a single marker gene (DCN) to define the fibroblast population and the small number of cells (229) within this population. The authors need to corroborate their findings using a combination of fibroblast marker genes as well as other studies comprising a larger number of cells of fibroblast origin.

3) The authors find HIF1a expression to be associated with poor survival and enriched within the tumor-distal stroma. They interpret this as a reflection of the hypoxic environment of PDAC. However, the authors only ever look at HIF1a mRNA, but hypoxic regulation of HIF-1a occurs post-transcriptionally. Transcriptional regulation of HIF1a has been reported through pro-inflammatory cytokines and NFkB signaling. Therefore, the authors should either stain for HIF1a to confirm enrichment on the protein level or adjust their discussion to reflect the important biology behind HIF1a regulation.

4) The authors often misinterpret the correlations and associations they observe as causation and explanation - they should either adjust their language or perform experiments to show causation.

Reviewer #1 (Public Review):

In this manuscript, the authors present a computational framework based on Bayesian observer models that parameterises several different sources of noise and bias in perceptual decision-making. The authors show that these sources of suboptimality cannot be dissociated in many typical decision-making tasks. They present an analysis of two previously published sets of experimental data, where the experimental design should allow them to dissociate suboptimalities parameterised in the model. They fit various versions of the model including different suboptimalities and in general show that including the suboptimalities improves the fit, depending on whether the data is aggregated across participants or not.

The major strengths of the methods and results include 1. The clear theoretical delineation of different forms of suboptimalities may help to guide research understanding them on the behavioural and neural levels. 2. The attention to scientific rigor in model fitting, including the use of power analysis and corrections for the number of model parameters. 3. Clear figures that are helpful in understanding the model.

The major weaknesses of the methods and results include 1. The lack of model/parameter recovery analysis shows the extent to which the model can separate sources of suboptimality against some ground truth. 2. The lack of generalisability, where the model parameters can only be dissociated using specific experimental manipulations, and a large number of trials. 3. It is unclear to what extent the assumptions of the model (and its parameterisation) limit the realisability of the proposed computational framework.

The authors achieve their aim of outlining a computational framework that accounts for various sources of suboptimalities and shows some evidence that this model may be useful for making inferences about these suboptimalities given careful experimental manipulation.

The work adds to the movement toward delineating the specific sources of suboptimalities as opposed to capturing 'noise' and 'bias' as overarching variables, and the model may prove useful for other researchers. However, given the model requires special experimental tasks to dissociate the parameters, it is unclear how this model improves upon the traditional approach of designing experiments to dissociate sources of suboptimalities directly.

Reviewer #1 (Public Review):

Precise regulation of gamete fusion ensures that offspring will have the same ploidy as the parents. However, breaking this regulation can be useful for plant breeding. Haploid induction followed by chemical-induced genome doubling can be used to fix desirable genotypes, while triparental hybrids where two sperm cells with two different genotypes fertilize an egg cell can be advantageous for bypassing hybridization barriers to create interspecies hybrids with increased fitness. This manuscript follows up on a previous study from the same research group that used a clever high throughput polyspermy detection assay (HIPOD) to show that wild-type Arabidopsis naturally forms triparental hybrids at very low frequencies (less than 0.05% of progeny) and that these triparental hybrids can bypass dosage barriers in the endosperm (Nakel, et al., 2017). Mao and co-authors hypothesized that mutants that conferred polytubey, the attraction of multiple pollen tubes by mutant female gametophytes, would also increase the rate of triparental hybrids. They used a double mutant in the endopeptidase genes ECS1 and ECS2 which had previously been reported to induce supernumerary pollen tube attraction to test this hypothesis with their two-component HIPOD system in which one pollen donor constitutively expresses the mGAL4-VP16 transcription factor while the second pollen donor carries an herbicide resistance gene regulated by the GAL4-responsive UAS promoter. Triparental hybrids are detected as herbicide-resistant progeny from wild-type Arabidopsis flowers that have been pollinated by the two paternal genotypes. The authors convincingly show that the ecs1 ecs2-1 double mutant more than doubled the frequency of triparental, triploid hybrids in HIPOD crosses. They next tested the hypothesis that this increase in triparental hybrids was due to a gametophytic effect by using an ecs1-/- ecs2-1/ECS2 maternal parent in the HIPOD assay and testing whether the ecs2-1 mutant allele was preferentially inherited in triparental hybrids. The mutant allele was inherited at a much higher rate than expected, confirming their hypothesis.

The triparental hybrid results with the ecs1 ecs2 mutant were not that surprising since the presence of extra sperm cells gives more opportunities for triparental hybrids to form, especially if gamete fusion is misregulated. However, an unexpected result came when the authors used aniline blue staining to analyze the ecs1 ecs2 polytubey phenotype. They confirmed that the double mutant had increased levels of polytubey compared to wild-type ovules, but they also noticed that 13% of seeds were not developing normally. This phenotype was confirmed with a second ecs2 allele and was complemented with both ECS1 and ECS2 transgenes under their native promoters. Microscopic analysis revealed normal gametophyte morphology before fertilization, but 8% of pollinated ovules failed to develop an embryo and 7% failed to develop endosperm, suggesting single fertilization events. In a logical set of experiments, they followed up on this result by crossing ecs1 ecs2 with pollen carrying a fluorescent reporter that would be expressed in developing embryos and endosperm. In this experiment, they were again surprised. Some of the wild-type-looking seeds lacked a paternal contribution (i.e. no fluorescent signal from the paternal reporter construct) in the embryo. This prompted them to look more closely at the progeny, upon which they detected small plants that were haploid. They confirmed the haploid nature by chromosome spreads. Finally, they used interaccession crosses between ecs1 ecs2 (Col-0) and Landsberg to verify that haploid progeny only carried maternal alleles of markers on all five chromosomes, indicating that the ecs1 ecs2 genotype can induce maternal haploids.

This interesting study highlights the importance of following up on unexpected results. The conclusions are well-supported by the data and quite exciting. Paternal haploid inducers have been discovered in several species, but this is one of only two examples of maternal haploid induction. While the percentage of maternal haploids is very low, this phenomenon could be useful for plant breeding.

Weaknesses<br /> The data in the manuscript is intriguing, but the question of how the same mutant combination promotes the formation of both triploid and haploid progeny remains unanswered and is not thoroughly discussed, nor is any model suggested for how the ECS1/2 peptidases could play a role in regulating gamete fusion and/or repressing parthenogenesis. A second unanswered question is whether the maternal haploids are a result of failed plasmogamy or karyogamy between the egg and sperm leading to parthenogenesis or a result of paternal genome elimination after plasmogamy. In figure 3B, the authors attempted to test whether plasmogamy occurs between the male and female gametes in ecs1 ecs2 ovules by crosses with pollen that expresses a mitochondrial marker under control of the pRPS5a promoter which is active in sperm cells as well as embryos and endosperm of fertilized ovules. This experiment allowed them to detect sperm cells that had not fused with the egg and central cell at 2 days after pollination. They also counted the percentage of seeds that expressed the mitochondrial marker in both embryo and endosperm at 2 DAP and found that ecs1 ecs2 mutants had a 20% reduction of visible mitochondria in embryo sacs compared to wildtype. They conclude that the result indicates a potential plasmogamy defect. However, the dependability of this marker is questionable since only ~55% of wild-type seeds had detectable signal in the embryo and endosperm. The authors imply that this experiment could be used to test plasmogamy, but it is not clear how any conclusions related to the abnormal seed phenotype could be drawn from examining the rate of signal in both the embryo and endosperm. Since the mitochondrial marker was not expressed from a sperm-specific promoter, the fluorescent signal at 2DAP is likely due to new gene expression from pRPS5a in the fertilized embryo and endosperm, not an indication of the presence of sperm-derived mitochondria. Perhaps an earlier timepoint could be used as well as a sperm-specific promoter instead of pRPS5a to answer the question of whether plasmogamy is happening in the ecs1 ecs2 ovules.

Reviewer #1 (Public Reviews):

The article describes the development of a highly concentrated antibody formulation for MS-Hu6, a first-in-class FSH-blocking humanized antibody proposed for clinical use in osteoporosis, obesity, and Alzheimer's disease. The authors utilized various techniques, including protein thermal shift, size exclusion chromatography, and dynamic light scattering, to examine the stability and physiochemical properties of the formulated MS-Hu6 at concentrations ranging from 1 to 100 mg/mL. They found that the thermal, monomeric, and colloidal stability of the formulated MS-Hu6 was maintained at a concentration of 100 mg/mL, and the addition of L-methionine and disodium EDTA improved its long-term colloidal and thermal stability. The authors further confirmed the thermal stability of the formulation through Nano differential scanning calorimetry (DSC). They demonstrated that MS-Hu6's structural integrity was maintained through Circular Dichroism (CD) and Fourier Transform Infrared (FTIR) spectroscopy. The formulated MS-Hu6 displayed excellent thermal and colloidal stability even after three rapid freeze-thaw cycles and storage for more than 90 days at 4{degree sign}C and 25{degree sign}C. The authors concluded that they had developed a stable, manufacturable, and transportable MS-Hu6 formulation at an ultra-high concentration, meeting acceptable industry standards. The study's findings may serve as a resource for developing biologics formulation in academic medical centers.

Reviewer #1 (Public Review):

The authors solved cryoEM structural maps for the pLGIC homolog Alpo4 from an extreme thermophile worm in apo and CHAPS-bound conditions. The data appear to be of good quality and in addition to a first structural model of Alpo4 also provide several interesting observations. Notably, the detergent CHAPS was observed to occupy the orthosteric binding pocket where it induces a quaternary twist of extracellular relative to transmembrane domains opposite to that observed for activation in canonical pLGICs. Given recent advances in lipid modulation of pLGICs, this structural model of how a detergent can bind to the orthosteric site will be of interest. Additionally, a ring of 16' methionines forms a potential alternate pore gate to the 9' leucine ring in canonical pLGICs. Unfortunately, testing these hypotheses such as the alternate pore gate remains difficult due to the fact that the activating ligand for Alpo4 remains unknown. This also makes it hard to relate the observed changes upon CHAPS binding to the Alpo4 function. Nonetheless, the structures will aid in hypotheses for functional mechanisms of Alpo4 and pLGICs.

Reviewer #1 (Public Review):

This manuscript examines how subjects change their decision strategy in a visual motion change detection task between blocks of trials where they sought to detect stronger versus weaker signals. The authors hypothesized that decision bounds would be reduced for the weaker signal condition. While behavioral changes were reasonably consistent with this hypothesis, it was challenged by EEG measures that have been previously found to relate to decision variables. In particular, a Beta-band EEG measure suggested decision bounds being reduced for the stronger signal condition, in distinct contrast to the initial hypothesis. Based on this, the authors developed an alternative behavioral model that could explain behavioral adjustments while having decision bounds that were constrained by the putative signature of the decision variable derived from the EEG Beta amplitude. This alternative model has two central features: 1) Sensory evidence is referenced to an adjustable criterion before accumulation such that evidence below the criterion provides negative input to the decision variable. 2) There is a lower reflecting bound on the decision variable such that it cannot go to negative values.

This experiment makes a strong case for the benefit of reconciling behavioral modeling with ideas in the literature about neural signatures of the corresponding decision processes. In this work, the standard behavioral modeling and the EEG-derived putative signatures of the decision process did not initially agree. This is an important finding. The authors also go further. Something must give. Either the standard modeling approach for this type of task provides an incorrect account or the putative mapping of EEG Beta amplitude to the decision process is incorrect. The authors argue for the former. They build from the starting point that the neural signatures are correct and develop alternative behavioral models that they argue to be consistent with these while also explaining behavior. One of these models (described above) fits the data as well as the standard model. I think this approach and the resulting model are interesting, but I have concerns.

1) I think the authors should give greater consideration to the possibility that the relationship between the decision process and EEG-derived neural signatures - despite having a basis in previous results - is either incorrect in some ways, not the full story, or might not fully apply to this paradigm. The authors include important analyses that already suggest that point to some degree, such as the analysis of the raw Beta amplitude in Figure 4. I give the authors credit for including that analysis and the critical discussion they have surrounding it. I suggest that the authors should include further discussion on this general point. What is the main evidence for the relationship of Beta amplitude to decision bound? Are there any differences from the previous studies that might break the relationship in this paradigm? With the approach taken here so heavily dependent on that relationship, discussing how it might not be correct seems of utmost importance.

2) My biggest concern revolves around where the Beta amplitude measurement fits into the model. Figure 3 (neurally informed modeling) shows it informing an evidence-independent component that adds to the decision variable, and it is described as such in the methods. However, Beta amplitude is clearly affected by the evidence (Figure 2A). And in the results, it is described as best corresponding to a decision variable, which would include the influence of the sensory evidence. If Beta amplitude depends on evidence, then an adjustment of the evidence criterion would influence Beta amplitude, even during the ITI. So, I don't see how it can be properly used as the constraining factor for the evidence-independent urgency in neurally-informed modeling.

To illustrate my concern, consider the evidence criterion adjustment model. In this model, the average DV value during the ITI will be closer to the decision bound in the weaker signal condition compared to the stronger signal condition - that is how the model fits the false alarm rate differences. This should be reflected in Beta amplitude if the latter reflects the DV. However, the Beta-derived urgency is highest for the condition with the lowest false alarm rate and lowest for the condition with the highest false alarm rate. It seems there is an inescapable conclusion that Beta amplitude does not fully reflect the main behavioral-driving features of the DV in this paradigm, even in the criterion-adjustment model. That said, I do think the development and consideration of the criterion-adjustment model is an important contribution, even with this shortcoming.

Additional comments:

1) The criterion-adjustment model appears equivalent to one with a constant negative drift added to the decision variable in addition to the contribution of evidence (and a lower reflecting bound). If true, it seems that there could be an alternative equivalent account that does not involve regulation of the transfer of incoming evidence.

2) I understand why one of the model parameters (e.g., noise or bound) must be fixed, but I don't understand why the authors didn't keep it the same parameter across all models. Couldn't they have fixed the noise parameters for all the models? Having it different makes it difficult to compare parameter values across the models, especially because the fitted noise term in the neurally-informed models appears dramatically reduced compared to the fixed value of noise used for the bound-adjustment model. On the topic of parameters, can the leak parameter be reported in more intuitive units? It seems to be parameterized as a fraction leak per time step, and I couldn't easily find the time step used. Reporting the leak as a time constant would be immediately understandable.

Reviewer #1 (Public Review):

This paper provides compelling and clear analyses that show that the coding level (sparsity) of the granule-cell layer of a cerebellar-like network does not only change the dimensionality of the representation, but also the inductive bias of the network: Higher sparsity biases the network to learning more high-frequency representations. Depending on the dominant frequencies of the target function, different coding levels are therefore optimal. The results are important/fundamental to theories of cerebellar learning and speak to a relevant ongoing debate in cerebellar learning, but will be of interest to readers outside of cerebellar neurophysiology.

Reviewer #1 (Public Review):

This study combines in vitro somatic and dendritic recordings and computational modeling to study how cholinergic agonists modulate the response of CA1 pyramidal neurons to triangular current injections. The authors have previously used a similar approach (Upchurch, 2022, JNeuroscience) to show that CA1 neurons exhibit asymmetric AP firing (more firing on the upward ramp) in response to such current injections and that this effect is due to Na channel inactivation. The present work builds on these results by showing that cholinergic modulation changes this response, i.e., there is more firing on the downward part of the ramp. This change appears to require an intracellular Ca2+ concentration increase (mediated via IP3 and voltage-gated Ca2+ channels), which activates TRPM4 channels. In this scheme, cholinergic activity increases IP3, and the depolarizing current injection opens voltage-gated Ca2+ channels. This study will be of some interest to cellular neurophysiology experts working on the hippocampus.

1) This study claims that the triangular current injections recapitulate hippocampal place cell activity. However, it has been shown recently that the asymmetric firing of CA1 place cells is due to synaptic weight changes resulting from synaptic plasticity (e.g., Bittner et al., 2017). This suggests that the asymmetric firing of place cells is primarily the result of asymmetric synaptic input. Therefore, the authors should test whether carbachol similarly affects a synaptically driven membrane potential ramp. If this is not the case, the strong claim that this work has implications for place cell firing is not justified, in my opinion.

2) Along the same lines, it has been shown before that the precision of spike timing depends on the stimulation pattern in vitro (Mainen and Sejnowski, 1995). Constant stimuli led to imprecise AP firing trains, whereas current injections that included fluctuations resembling synaptic input generated spike trains that were more reliable and reproducible in terms of timing. This study concluded that a low intrinsic noise level in spike generation was essential in generating informative spike sequences. Following this pivotal work, the authors could add noise to their current stimulus and observe the effect on the AP firing patterns. If this is not possible, the authors should at least report the sweep-to-sweep variability for the data shown, e.g., in panels 1A2, 1B2, 1D2, and 1E2.

3) In most of the data presented in this manuscript, Carbachol appears to induce a 3 mV hyperpolarization and increase input resistance. As a result, the amount of current injected during Carbachol is drastically lower than during the controls. This should be emphasized more, and the input resistance should be quantified for each experimental condition. It should also be discussed whether this change in input resistance can account for the changes in the firing pattern observed. Finally, it should be clearly stated how the amount of the current injected was chosen for each cell, and data from a range of injected current ramps should be shown for each cell.

4) It remains unclear how the current result that TRPM4 channels can mediate the firing pattern change relates to the previous finding that the current injection evoked CA1 neuronal firing pattern is due to long-term Na channel inactivation.

5) Figure 8: Panel C is supposed to confirm the prediction from the model that the carbachol-mediated change of firing activity is related to intracellular Ca2+ domains. However, the example cell shown is depolarized to -52 mV, and there is no hyperpolarization following Carbachol. Is this an effect of the high concentration of BAPTA? Again, what was the current injected under this experimental condition?

Reviewer #1 (Public Review):

The manuscript studies the spontaneous contractions (SC) of the Hydra body wall and presents a detailed simple mathematical model of nutrient transport to hypothesize the role of SC on maintaining the microbiota. This work provides valuable insights on the functional im- plications of the SC and the increased nutrient update obtained from mixing the local fluid environment through body wall contractions.

Reviewer #1 (Public Review):

Brunetti et al. investigated the mechanism used by the SARS CoV-2 virus to infect CD4 T cells and the potential impact on the immune system by viral infection. They find that SARS CoV-2 infects CD4 helper T cells and not CD8 T cells present in the blood and bronchoalveolar fluid of infected patients. The ACE-2 receptor expression on T lymphocytes is less compared to epithelial and endothelial cells, but still, the virus is able to establish a productive infection of T lymphocytes by some alternative mechanism. The group also demonstrated that interaction between CD4 and SARS virus spike protein further enhances viral entry and infectivity as CD4 is acting as an auxiliary molecule for viral entry.

By performing a technically impressive analysis of the infectivity of CD4 T cells isolated from healthy donors/controls invitro with the SARS CoV-2 virus and also by testing the infected population of CD4 cells invivo from COVID patients, the authors find that SARS CoV-2 infects CD4 T cells using Insitu Hybridization using probes against viral polymerase (RdRP), immunofluorescence and electron microscopy. Further, the authors also identified the region of SARS CoV-2 spike protein that interacts with CD4 by performing molecular docking analysis and found CD4 NTD interacts directly with the RBD region of the SARS Virus. The specific interaction between CD4 and SARS virus is further demonstrated by the use of anti-CD4 blocking antibodies and cell lines that over-express CD4 molecules. Interestingly by antibody inhibition of ACE-2 and camostat inhibition of TMPRSS2, the authors demonstrated that SARS CoV-2 infection of CD4 T cells requires ACE-2, TMPRSS2, and CD4. The data also show that viral infection of CD4 T cells leads to the expression of cytokines like 1L-10 that may impact cell viability and dampens immune response.

The experiments in the paper are well- performed and the conclusions of this paper are mostly well supported by data, but some aspects of the impact of viral infection of CD4 cells leading to lymphopenia need to be clarified and extended.<br /> A major weakness of the paper is the reference citations. Inconsistency in maintaining the citation style and numbering in the manuscript draft drastically impacts the readability. For example, the use of superscript format references in the introduction and results section and paraphrasing format in materials and methods could not make the readers identify the correct citations.

1. In this paper, the authors describe infection of CD4 T cells may lead to T cell death. Although the extended Fig. 9 suggests the expression of a multitude panel of gene expression, including apoptotic genes, the authors could not provide a piece of direct evidence to show how CD4 T cell death happens. What is the underlying mechanism of cell death? Is it by necrosis or apoptosis or pyroptosis? The exact mechanism of CD4 cell death needs to be discovered and adding control experiments to assess the exact mechanism of cell death would increase confidence in the presented results of the functional interaction of proteins (Ext Fig 9).

2. Some previous studies suggested that lymphocytopenia in COVID infection could be due to impaired T cell proliferation or extravasation of T cells into tissue. The exact mechanism for lymphocytopenia could be addressed by performing an animal experiment, but it would be interesting to see what are the author's opinion about other possibilities of lymphocytopenia.

3. The data on CREB-1 Ser 133 in Figure 4E is not sufficiently convincing. It is difficult to understand what is the difference between every three lanes within mock and SARS CoV-2 infection. There is a pCREB band in lane 5 (2nd lane of CoV-2), but not in the other two. Better data would have helped to substantiate the authors' conclusions.

Reviewer #1 (Public Review):

Guo et al. demonstrate that Metformin, a first-line anti-diabetic drug, significantly improves bone healing in diabetic mice. Mechanistically, they demonstrate that Metformin improves BMSC differentiation in T2D type 2 diabetic mice, potentially through an indirect mechanism. Overall the study is comprehensive and the effects of Metformin on bone healing are demonstrated by overwhelming data. The study further offers important information for management of the complications associated with type-2 diabetes. The weakness of the study is the lack of in-depth understanding of the mechanism underlying Metformin's effects on healing. The writing of the manuscript could also be improved for clarity and accuracy.

Reviewer #1 (Public Review):

In the manuscript the authors identify new players regulating cell state transitions. They show that heme biosynthesis is required for the naïve-to-primed pluripotency transition. In particular, they provide a link between heme biosynthesis inhibition and failure to activate TGFβ and MAPK pathways, two crucial regulators of the exit from the naïve pluripotent state. Heme biosynthesis inhibition increases the percentage of 2CLCs within the mESC population. The authors further show that this increased level of 2CLCs depends on the accumulation of succinate in non-mitochondrial cell compartments as a consequence of heme biosynthesis inhibition. Based on experiments using chemical inhibitors, the authors conclude that succinate acts in a paracrine and autocrine manner to enhance reprogramming of mESC into 2CLCs.

The observations provided by the authors are interesting and potentially relevant in the field of pluripotent cell state transitions. However, in the present state, neither the role of heme biosynthesis on FGF-ERK and TGF beta signalling and exit from naïve pluripotency nor the role of heme biosynthesis in controlling the 2CLC state are clear.

Below I list my main concerns:

1. The authors claim that the heme metabolic pathway is important for the naïve-to-primed transition. Interfering with its proper function appears to have developmental consequences. However, it is unclear how exactly this pathway is regulated during the exit from naïve pluripotency in WT cells. Hence the physiological relevance remains unclear. Are the levels of heme itself, or the mentioned 7 enzymes of the heme pathway regulated during differentiation?

2. The claim that "the roles of this [heme] biosynthetic pathway and this metabolite have never been studied in the context of pluripotency" is a bit misleading. It has been reported that HO1 is regulated by Oct4 (https://doi.org/10.1002/1873-3468.14138).

3. The link between heme biosynthesis and the TGFβ and MAPK pathways remains unclear. Is there any evidence for a direct link, or are these two observations simply linked through an altered cell state? Without further experiments it remains unclear whether the lack of proper Tgf beta and Fgf-ERK signalling activation are cause or consequence of the observed differentiation defects. Results must be discussed with this limitation in mind.

4. The fact that MEKi did not recapitulate the phenotype of SA treatment to prevent EpiLC differentiation should already be clarified in the results section. Moreover, the fact that SMAD inhibition seems to delay downregulation of naïve markers more than SA treatment, and the fact that SMAD inhibition combined with MEK inhibition seems weaker than SMAD inhibition alone seem counterintuitive and needs explanation. Can the authors attempt to titrate pathway inhibition to a similar level as observed in heme pathway deficient ESCs? Furthermore, can the differentiation defect be rescued upon overstimulation of Fgf-ERK and TGF beta to reach WT levels?

5. To better characterize the direct effect of heme biosynthesis inhibition it is necessary to in depth analyse any possible cell proliferation, viability of cell cycle defects after SA (or AA5) treatment. If there is an impact on cellular health, this needs to be reported and taken into careful consideration when interpreting results.

6. The authors claim that SA pre-treatment of mESC is able to enhance their differentiation ability into throphoblast like cells; however, they do not show statistically significant differences in terms of throphoblast expression markers between SA-treated and control cells (Supplemental Fig.2d). Furthermore, the variance of measurements in 2iL are not shown. Expression levels in TS cells or in trophoblast tissue must be used as control to judge the effect size. 2iL cells do also generate cells similar in morphology to 2iL+SA cells (Suppl Fig. 2b). Should these also be giant cells; this would be very surprising. Together, this makes drawing conclusions from these experiments impossible. If the statement that SA treatment expands the lineage potential of ESCs is made, it will need to be supported by appropriate and statistically strong data. A mere increase in some marker genes (which are not really specific for the TE lineage but also expressed in embryonic tissues) and statements based on morphology are no good support for this hypothesis.

7. What is the reason for calling the increase in 2C like cells 2C-like reprogramming? Is there any evidence that this is indeed a reprogramming event? There is no evidence for disruption of heme biosynthesis directly instructing cells to take on a 2CLC state, there is simply an increase in the Zscan4 expressing population, for a reason that remains unclear.

8. Addition of AA5 or SA results in absolutely striking changes in the epigenetic state of ESCs. H3K4me3, H3K27me3 and H3K9me3 together with 5mC levels appear drastically increased based on IF images in Supp. Fig. 5a. I wonder how physiological these levels are. How much data directly meaningful for 'normal' differentiation can be obtained from such a massively perturbed system? This needs to be appropriately acknowledged and discussed.