6,458 Matching Annotations
  1. Mar 2025
    1. Delegate Led Discussion - Strategies for Action and Care

      for - program event selection - 2025 - April 3 - 2-3:15pm GMT - Skoll World Forum - Delegate Led Discussion - Strategies for Action and Care in Closing Civic Space - Stop Reset Go - Indyweb autonomy - relevant to - event time conflict - with - Project Dandelion

    2. Delegate Led Discussion - Tuning In: Music

      for - program event selection - 2025 - April 3 - 2-3:15pm GMT - Skoll World Forum - Delegate Led Discussion - Tuning In: Music, Deep Listening - Stop Reset Go - Deep Humanity BEing journeys - relevant to - event time conflict - with - Project Dandelion

    3. Delegate Led Discussion - The Changing State of AI, Media

      for - program event selection - 2025 - April 2 - 2-3:15pm GMT - Skoll World Forum - The Changing State of AI, Media - Indyweb - Stop Reset Go - TPF - Eric's project - Skoll's Participatory Media project - relevant to - adjacency - indyweb - Stop Reset Go - participatory news - participatory movie and tv show reviews - Eric's project - Skoll's Particiipatory Media - event time conflict - with - Leadership in Alien Times

      adjacency - between - Skoll's Participatory Media project - Global Witness - Indyweb - Stop Reset Go's participatory news idea - Stop Reset Go's participatory movie and TV show review idea - Eric's media project - adjacency relationship - Participatory media via Indyweb and idea of participatory news and participatory movie and tv show reviews - might be good to partner with Skoll Foundation's Participatory Media group

    4. Leadership in Alien Times

      for - program event selection - 2025 - April 2 - 2-3:30pm GMT - Skoll World Forum - Leadership in Alien Times - Stop Reset Go - Deep Humanity - LCE - transition - relevant to - event time conflict - with Building Comfort with Discomfort - solution - watch one live and the other recorded

    5. Comfort with Discomfort: Practices

      for - program event selection - 2025 - April 2 - 2-3:30 pm GMT - Skoll World Forum - Comfort with Discomfort: Practices for Lasting Social Change - Stop Reset Go - Deep Humanity - Common Human Denominators - LCE - relevant to - event time conflict - with - Leadership in Alien Times

    Tags

    Annotators

    URL

    1. Reviewer #3 (Public Review):

      In their manuscript, Umetani, et al. address the question of the origin of persister bacteria using single-cell approaches. Persistence refers to a physiological state where bacteria are less sensitive to antibiotherapy, although they have not acquired a resistance mutation; importantly, the concept of persistence has been refined in the past decade to distinguish it from tolerance where bacteria are only transiently insensitive. Since persister cells are very rare in growing populations (typically 1e-5 or 1e-6), it is very challenging to observe them directly. It had been proposed that individual cells surviving antibiotics are not growing at the start of the treatment, but recent studies (nicely reviewed in the introduction) where persister bacteria were observed directly do not support this link. Following a similar line, the authors nonetheless still aim at "investigating whether non-growing cells are predominantly responsible for bacterial persistence". Based on new experimental data, they claim the contrary that most surviving cells were "actively growing before drug exposure" and that their work "reveals diverse survival pathways underlying antibiotic persistence".

      The main strengths of the manuscript are in my opinion:

      - To report on direct observation of E. coli persisters to ampicillin (200µg/mL) in 5 different growth media (typically 20 persisters or more per condition, one condition with 12 only), which constitutes without a doubt an experimental tour de force.

      - To aim at bridging the population level and the single-cell level by measuring relevant variables for each and analyzing them jointly.

      - To demonstrate that in most conditions a large fraction of surviving cells was actively growing before drug exposure.

      In addition, although it is well-known that E. coli doesn't need to maintain its rod shape for surviving and dividing, I found very remarkable in their data the extent to which morphology can be affected in persister cells and their progeny, since this really challenges our understanding of E. coli's "lifestyle" (these swimming amoeba-like cells in Supp Video 11 are mind-blowing!).

      Unfortunately, these positive aspects are counter-balanced by several shortcomings in the way experiments are analyzed and interpreted, which I explain below. Moreover, the manuscript is written in a way that makes it very hard to find important information on how experiments are done and is likely to leave the reader with an impression of confusion about what the main findings actually are.

      My major concerns are the following:

      (1) The main interpretation framework proposed by the authors is to assess whether cells not growing before drug exposure (so-called "dormant") are more or less likely to survive the treatment than growing ones ("non-dormant"). Fig 2A and Fig 3G show the main conclusions of the article from this perspective, that growing cells can survive the treatment and that the fraction of persisters in a given condition is not explained by the fraction of "dormant" cells, respectively. With this analysis, the authors essentially assume that "dormant" cells are of the same type in their different conditions, which ignores the progress in this field over the last decade (Balaban et al. 2019). I argue on the contrary that the observation of "diverse modes of survival in antibiotic persistence" is expected from their experimental design. In particular, the sensitivity of E. coli to beta-lactams such as ampicillin is expected to be much lower during the lag out of the stationary phase, a phenomenon which has been coined "tolerance"; hence in the Late Stationary condition, two subpopulations coexist for which different response to ampicillin is expected. I propose steps toward a more compelling interpretation of the experimental data. Should this point be taken seriously by the authors, it, unfortunately, implies a major rewriting of the article, including its title.

      (2) The way the authors describe their experiments with bacteria in the stationary phase is very problematic. For instance, they write that they "sampled cells from early and late stationary phases (...) and exposed them to 200 μg/mL of Amp in both batch and single-cell cultures." For any reader in a hurry (hence skipping methods and/or supplementary figure), this leads to believe that bacteria sampled in the stationary phase were exposed to the drug right away (either by adding the drug to the stationary phase sample, or more classically by transferring cells to fresh media with antibiotics). However, it turns out that, after sampling and loading in the microfluidic device, bacteria are grown 2 h in LB (or 4 h in M9) - I don't know what to think of such a blatant omission. The names chosen for each condition should reflect their most important aspects, here "stationary" is simply not appropriate - maybe something like "post early stationary" instead. In any case, I believe that this point highlights further the misconception pointed out in 1 and implies that the average reader will be at best confused, and probably misled.

      (3) Figures 4 and 5 are of very minor significance, and the methodology used in Fig 4 is questionable. The authors measure the abundance of an Rpos-mCherry translational fusion because its "high expression has been suggested to predict persistence". The rationale for this (that an RpoS-mCherry fusion would be a proxy for intracellular ppGpp levels, and in turn predict persistence) has never been firmly established, and the standards used in the article where this reporter was introduced (Maisonneuve, Castro-Camargo, and Gerdes 2013) are notoriously low (which eventually led to its retraction) - I don't know what to think of the fact that the authors cite a review by this group rather than their retracted article. While transcriptional fusions of promoters regulated by RpoS have been proposed to measure its regulatory activity (Patange et al. 2018), the combination of self-regulation and complex post-translational regulation of rpoS makes the physical meaning of the reporter used here completely unclear. Moreover, this translational fusion is introduced without doing any of the necessary controls to demonstrate that the activity of RpoS is not impaired by the addition of the fluorescent protein. Fig 5 simply reports the existence of persisters to ciprofloxacin growing before the treatment. This might be a new observation but it is not unexpected given that a similar observation has been made with a similar drug, ofloxacin (Goormaghtigh and van Melderen 2019), as pointed out in the introduction. There is no further quantitative claim on this.

      (4) The authors don't mention the dead volume nor the speed of media exchange in their device. Hopefully, it is short compared to the duration of the treatment; however, it is challenging to remove all antibiotics after the treatment and only 1e-3 or 1e-4 of the treatment concentration is already susceptible to affecting regrowth in fresh media. If this is described in another article, it would be worth adding a comment in the main text.

      (5) Fig 2A supports the main finding that a significant fraction of bacteria surviving the treatment are growing before drug exposure, but it uses a poorly chosen representation.<br /> - In order to compare between conditions, one would like to see the fraction of each type in the population.<br /> - The current representation (of a fraction of each type among surviving cells) requires a side-by-side comparison with a random sample (which will practically be equivalent to the fraction of each type among killed cells) in order to be informative.

    1. Reviewer #3 (Public review):

      Summary:

      This study by Tetenborg S et al. identifies proteins that are physically closely associated with gap junctions in retinal neurons of mice and zebrafish using BioID, a technique that labels and isolates proteins proximal to a protein of interest. These proteins include scaffold proteins, adhesion molecules, chemical synapse proteins, components of the endocytic machinery, and cytoskeleton-associated proteins. Using a combination of genetic tools and meticulously executed immunostaining, the authors further verified the colocalizations of some of the identified proteins with connexin-positive gap junctions. The findings in this study highlight the complexity of gap junctions. Electrical synapses are abundant in the nervous system, yet their regulatory mechanisms are far less understood than those of chemical synapses. This work will provide valuable information for future studies aiming to elucidate the regulatory mechanisms essential for the function of neural circuits.

      Strengths:

      A key strength of this work is the identification of novel gap junction-associated proteins in AII amacrine cells and photoreceptors using BioID in combination with various genetic tools. The well-studied functions of gap junctions in these neurons will facilitate future research into the functions of the identified proteins in regulating electrical synapses.

      Weaknesses:

      I do not see major weaknesses in this paper. A minor point is that, although the immunostaining in this study is beautifully executed, the quantification to verify the colocalization of the identified proteins with gap junctions is missing. In particular, endocytosis component proteins are abundant in the IPL, making it unclear whether their colocalization with gap junction is above chance level (e.g. EPS15l1, HIP1R, SNAP91, ITSN in Figure 3B).

    1. Reviewer #3 (Public review):

      Summary:

      The authors provide an in-depth analysis of the function of Numb in adult Drosophila midgut. Based on RNAi combinations and double mutant clonal analyses, they propose that Numb has a function in inhibiting Notch pathway to maintain intestinal stem cells, and is a backup mechanism with BMP pathway in maintaining midgut stem cell mediated homeostasis.

      Strengths:

      Overall, this is a carefully constructed series of experiments, and the results and statistical analyses provides believable evidence that Numb has a role, albeit weak compared to other pathways, in sustaining ISC and in promoting regeneration especially after damage by bleomycin, which may damage enterocytes and therefore disrupt BMP pathway more. The results overall support their claim.

      The data are highly coherent, and support a genetic function of Numb, in collaborating with BMP signaling, to maintain the number and proliferative function of ISCs in adult midguts. The authors used appropriate and sophisticated genetic tools of double RNAi, mutant clonal analysis and dual marker stem cell tracing approaches to ensure the results are reproducible and consistent. The statistical analyses provide confidence that the phenotypic changes are reliable albeit weaker than many other mutants previously studied.

      Weaknesses:

      In the absence of Numb itself, the midgut has a weak reduction of ISC number (Fig. 3 and 5), as well as weak albeit not statistically significant reduction of ISC clone size/proliferation. I think the authors published similar experiments with BMP pathway mutants. The mad1-2 allele used here as stated below may not be very representative of other BMP pathway mutants. Therefore, it could be beneficial to compare the number of ISC number and clone sizes between other BMP experiments to provide the readers a clearer picture how these two pathways individually contribute (stronger/weaker effects) to the ISC number and gut homeostasis.

      The main weakness of this manuscript is the analysis of the BMP pathway components, especially the mad1-2 allele. The mad RNAi and mad1-2 alleles (P insertion) are supposed to be weak alleles and that might be suitable for genetic enhancement assays here together with numb RNAi. However, the mad1-2 allele, and sometime the mad RNAi, showed weakly increased ISC clone size. This is kind of counter-intuitive that they should have a similar ISC loss and ISC clone size reduction.

      A much stronger phenotype was observed when numb mutants were subject to treatment of tissue damaging agents Bleomycin, which causes damage in different ways than DSS. Bleomycin as previously shown to be causing mainly enterocyte damage, and therefore disrupt BMP signaling from ECs more likely. Therefore, this treatment together with loss of numb led to highly significant reduction of ISC in clones and reduction of clone size/proliferation. One improvement is that it is not clear whether the authors discussed the nature of the two numb mutant alleles used in this study and the comparison to the strength of the RNAi allele. Because the phenotypes are weak, and more variable, the use of specific reagents is important.

      Furthermore, the use of possible activating alleles of either or both pathways to test genetic enhancement or synergistic activation will provide strong support for the claims.

      For the revision, the authors have provided detailed responses, comments, and a revised manuscript that together satisfactorily answer all my questions. The manuscript read well and the flow of information is quite clear. I do not have further concerns and support the manuscript moving forward.

    1. Reviewer #3 (Public review):

      Summary:

      This work describes how two chemosensory neurons in C. elegans drive opposite behaviors in response to a volatile cue. Because they have different concentration dependencies, this leads to different behavioral responses (attraction at low concentration and repulsion at high concentration). It has been known that many odorants that are attractive at low concentrations are aversive at high concentrations, and the implicated neurons (at least AWC for attraction and ASH for repulsion) have been well established. Nonetheless, studying behavior and neural responses in a common context (odor pulses, as opposed to gradients) provides a clear picture of how these sensory neurons may guide the dose-dependent response by separately modulating odor entry and odor exit behaviors.

      Strengths:

      (1) There is good evidence that worms are attracted to low concentrations and repelled by high concentrations of 1-oct. Calcium imaging also makes it clear that dose dependence is stronger for ASH than AWC.

      (2) There is good evidence for conc. dependent responses via ASH (Figure 4E) and attractive inhibition via tonic IAA (Figure 7A).

      (3) This work presents calcium imaging and behavior with the same stimulus (sudden pulses in volatile odor concentration), while previous studies often focus on using neuronal responses to pulses to understand the navigation of gentle gradients.

      Weaknesses:

      (1) It is not clear precisely how important AWC is (compared to other cells) for the attractive response, though the presence of odor-off behavior implicates it. This could be resolved by looking at additional mutants (tax-4 is broad).

      (2) Relatedly, dose-dependent chemotaxis data (Figure 4C, D) should be provided for osm-9 animals to get a sense of the degree to which dose-dependence is explained by ASH.

      (3) Figure 4A, B should include average traces with errors, as there are several ways the responses can vary across conditions.

      (4) The data in Figure 6G does not appear to have error bars. Also, it would help to include a more conventional demonstration of AIB responding to stimuli (e.g. averaging stimulus-aligned responses as a percent of the fluorescence value at stimulus onset to perform the desired subtraction). Subtracted calcium traces are harder to interpret. As it stands, the evidence that sensory signals are persisting in AIB and not being shunted by proprioceptive feedback in microfluidic devices is not strong.

    1. Reviewer #3 (Public review):

      Summary:

      The authors submitted a second revised manuscript that reports findings from a series of experiments suggesting that bovine oviductal fluid and species-specific oviductal glycoprotein (OVGP1 or oviductin) from bovine, murine, or human sources modulate the species specificity of bovine and murine oocytes.

      Strengths:

      The study reported in the manuscript deals with an important topic of interest in reproductive biology.

      Weaknesses:

      The authors submitted a second revised manuscript. Some of the previous questions are considered inadequate. There are still several problematic issues that require the authors' attention.

    1. Reviewer #3 (Public review):

      Summary:

      Franchet et al. sought to characterize the impact of Nora virus on host lifespan and sensitivity to a variety of infectious or stressful treatments. Through careful and rigorous analyses, they provide evidence that the Nora virus greatly impacts fly survival to infection, overall lifespan, and intestinal integrity. The authors have been thorough and rigorous, and the experimental evidence including proper isolation of the virus and Koch's Postulate reinoculation of the organism is excellent. The additional work is valuable and to the gold standard of the field, characterizing the pathology of the gut, including data showing gut leakage, the presence of the virus in the intestinal stem cells, and the importance of stem cell proliferation for virus replication and spread using elegant genetic tools to block stem cell proliferation or enterocyte death.

      Strengths:

      The authors have been rigorous and careful. The initial finding is presented through the lens of two related strains differing in virus infection. From there, the authors characterized the virus and isolated a purified culture, which they used to reinoculate a cleared strain to demonstrate proper Koch's Postulate satisfaction. The authors have also probed various parameters in terms of dietary importance in relevant conditions for many experiments. The additional work to characterize the pathology of the gut is compelling, using genetic tools to block or allow intestinal stem cell proliferation and enterocyte death through JAK-STAT and JNK signalling alongside the tracing of virus presence using a Nora virus antibody. JAK-STAT and JNK are previously described as regulators of these processes, making these tools appropriate and convincing. It is also interesting to see good evidence that the virus itself is damaging, rather than simply permitting coinfection by gut microbes (which does happen).

      Weaknesses:

      The claim that Dcr2 is not abundant in ISCs because the protein is not stable is logically consistent and reasonable. Perhaps I missed this, but the authors could additionally knock down or use somatic CRISPR to delete Dcr2 in ISCs to test whether a lack of Dcr2 underlies sensitivity. In this experiment, the expectation would be that depleting Dcr2 in ISCs genetically would make little difference to susceptibility overall compared to controls. This is not an essential experiment request.

    1. Reviewer #3 (Public review):

      Summary:

      This is an interesting investigation of the benefits of perceiving control and its impact on the subjective experience of stress. To assess a subjective sense of control, the authors introduce a novel wheel-stopping (WS) task where control is manipulated via size and speed to induce low and high control conditions. The authors demonstrate that the subjective sense of control is associated with experienced subjective stress and individual differences related to mental health measures. In a second experiment, they further show that an increased sense of control buffers subjective stress induced by a trier social stress manipulation, more so than a more typical stress buffering mechanism of watching neutral/calming videos.

      Strengths:

      There are several strengths to the manuscript that can be highlighted. For instance, the paper introduces a new paradigm and a clever manipulation to test an important and significant question. Additionally, it is a well-powered investigation that allows for confidence in replicability and the ability to show both high internal consistency and high external validity with an interesting set of individual difference analyses. Finally, the results are quite interesting and support prior literature while also providing a significant contribution to the field with respect to understanding the benefits of perceiving control.

      Weaknesses:

      There are also some questions that, if addressed, could help our readership.

      (1) A key manipulation was the high-intensity stressor (Anticipatory TSST signal), which was measured via subjective ratings recorded on a sliding scale at different intervals during testing. Typically, the TSST conducted in the lab is associated with increases in cortisol assessments and physiological responses (e.g., skin conductance and heart rate). The current study is limited to subjective measures of stress, given the online nature of the study. Since TSST online may also yield psychologically different results than in the lab (i.e., presumably in a comfortable environment, not facing a panel of judges), it would be helpful for the authors to briefly discuss how the subjective results compare with other examples from the literature (either online or in the lab). The question is whether the experienced stress was sufficiently stressful given that it was online and measured via subjective reports. The control condition (low intensity via reading recipes) is helpful, but the low-intensity stress does not seem to differ from baseline readings at the beginning of the experiment.

      (2) The neutral videos represent an important condition to contrast with WS, but it raises two questions. First, the conditions are quite different in terms of experience, and it is interesting to consider what another more active (but not controlled per se) condition would be in comparison to the WS performance. That is, there is no instrumental action during the neutral video viewing (even passive ratings about the video), and the active demands could be an important component of the ability to mitigate stress. Second, the subjective ratings of the stress of the neutral video appear equivalent to the win condition. Would it have been useful to have a high arousal video (akin to the loss condition) to test the idea that experience of control will buffer against stress? That way, the subjective stress experience of stress would start at equivalent points after WS3.

      (3) For the stress relief analysis, the authors included time points 2 and 3 (after the stressor and debrief) but not a baseline reading before stress. Given the potential baseline differences across conditions, can this decision be justified in the manuscript?

      (4) Is the increased control experience during the losses condition more valuable in mitigating experienced stress than the win condition?

      (5) The subjective measure of control ("how in control do you feel right now") tends to follow a successful or failed attempt at the WS task. How much is the experience of control mediated by the degree of experienced success/schedule of reinforcement? Is it an assessment of control or, an evaluation of how well they are doing and/or resolution of uncertainty? An interesting paper by Cockburn et al. 2014 highlights the potential for positive prediction errors to enhance the desire for control.

      (6) While the authors do a very good job in their inclusion and synthesis of the relevant literature, they could also amplify some discussion in specific areas. For example, operationalizing task controllability via task difficulty is an interesting approach. It would be useful to discuss their approach (along with any others in the literature that have used it) and compare it to other typically used paradigms measuring control via presence or absence of choice, as mentioned by the authors briefly in the introduction.

      (7) The paper is well-written. However, it would be useful to expand on Figure 1 to include a) separate figures for study 1 (currently not included) and 2, and b) a timeline that includes the measurements of subjective stress (incorporated in Figure 1). It would also be helpful to include Figure S4 in the manuscript.

    1. Reviewer #3 (Public review):

      The authors explore the role of Rec domains in a thermophilic Cas9 enzyme. They report on the crystal structure of part of the recognition lobe, its dynamics from NMR spin relaxation and relaxation-dispersion data, its interaction mode with guide RNA, and the effect of two single-point mutations hypothesised to enhance specificity. They find that mutations have small effects on Rec domain structure and stability but lead to significant rearrangement of micro- to milli-second dynamics which does not translate into major changes in guide RNA affinity or DNA cleavage specificity, illustrating the inherent tolerance of GeoCas9. The work can be considered as a first step towards understanding motions in GeoCas9 recognition lobe, although no clear hotspots were discovered with potential for future rational design of enhanced Cas9 variants.

      Strengths:

      - Detailed biophysical and structural investigation, despite a few technical limitations inherent with working with complex targets, provides converging evidence that molecular dynamics embedded in the recognition lobes allow GeoCas9 to operate on a broad range of substrates.<br /> - Since the authors and others have shown that substrate specificity is dictated by equivalent hotspot mutations in other Cas9 variants, we are one step closer to understanding this phenomenon.

      Weaknesses:

      - Since the mutations investigated here do not significantly affect substrate binding or enzymatic activity, it is difficult to rationalize anything for enzyme engineering at this point.<br /> - Further investigation of the determinants of the observed dynamic modes, and follow-up with rationally designed mutations would hopefully allow to create a real model of the mechanism, but I do understand that this goes beyond the scope of this study.

    1. Reviewer #3 (Public review):

      Summary:

      The data and experiments presented in that study convincingly show that a subpopulation of endothelial cells undergo transformation into pericyte-like cells after stroke in mice. These so-called "E-pericytes" are protective and might present a new target for stroke recovery. The authors used a huge battery of different techniques and modified signaling pathways and cellular interactions using several genetic and pharmacological tools to show that TGFbeta and EndoMT are causes of this transformation.

      Strengths:

      The amount of different genetic and pharmacological approaches in combination with sophisticated techniques such as single-cell RNAseq is impressive and convincing. The results support their conclusions and the authors achieved their aims. The findings will strongly impact the field of cerebrovascular recovery after stroke and might open up new therapeutic targets.

      Weaknesses:

      The written and graphic presentation of the findings needs substantial improvement. Language editing is strongly recommended (there are a lot of spelling and grammatical errors in the text and illustrations, including legends).

    1. Reviewer #3 (Public review):

      Summary:

      In this manuscript, Franco and colleagues describe careful analyses of Salmonella chemotactic behavior in the presence of conflicting environmental stimuli. By doing so, the authors describe that this human pathogen integrates signals from a chemoattractant and a chemorepellent into an intermediate "chemohalation" phenotype.

      Strengths:

      The study was clearly well-designed and well-executed. The methods used are appropriate and powerful. The manuscript is very well written and the analyses are sound. This is an interesting area of research and this work is a positive contribution to the field.

      Weaknesses:

      Although the authors do a great job in discussing their data and the observed bacterial behavior through the lens of chemoattraction and chemorepulsion to serine and indole specifically, the manuscript lacks, to some extent, a deeper discussion on how other effectors may play a role in this phenomenon. Specifically, many other compounds in the mammalian gut are known to exhibit bioactivity against Salmonella. This includes compounds with antibacterial activity, chemoattractants, chemorepellers, and chemical cues that control the expression of invasion genes. Therefore, authors should be careful when making conclusions regarding the effect of these 2 compounds on invasive behavior. It is important that the word invasion is used in the manuscript only in its strictest sense, the ability displayed by Salmonella to enter non-phagocytic host cells. With that in mind, authors should discuss how other signals that feed into the control of Salmonella invasion can be at play here.

    1. Reviewer #3 (Public review):

      Summary:

      The authors describe a model to mimic bat echolocation behavior and flight under high-density conditions and conclude that the problem of acoustic jamming is less severe than previously thought, conflating the success of their simulations (as described in the manuscript) with hard evidence for what real bats are actually doing. The authors base their model on two species of bats that fly at "high densities" (defined by the authors as colony sizes from tens to tens of thousands of individuals and densities of up to 33.3 bats/m2), Pipistrellus kuhli and Rhinopoma microphyllum. This work fits into the broader discussion of bat sensorimotor strategies during collective flight, and simulations are important to try to understand bat behavior, especially given a lack of empirical data. However, I have major concerns about the assumptions of the parameters used for the simulation, which significantly impact both the results of the simulation and the conclusions that can be made from the data. These details are elaborated upon below, along with key recommendations the authors should consider to guide the refinement of the model.

      Strengths:

      This paper carries out a simulation of bat behavior in dense swarms as a way to explain how jamming does not pose a problem in dense groups. Simulations are important when we lack empirical data. The simulation aims to model two different species with different echolocation signals, which is very important when trying to model echolocation behavior. The analyses are fairly systematic in testing all ranges of parameters used and discussing the differential results.

      Weaknesses:

      The justification for how the different foraging phase call types were chosen for different object detection distances in the simulation is unclear. Do these distances match those recorded from empirical studies, and if so, are they identical for both species used in the simulation? What reasoning do the authors have for a bat using the same call characteristics to detect a cave wall as they would for detecting a small insect? Additionally, details on the signal creation are also absent, but based on the sample spectrogram in Figure 2A, it appears that the authors used a synthetic linear FM chirp characterized by the call parameters. This simplification of the echolocation signals for these species is not representative of the true emitted signals, which are nonlinear FM for not only the species used within this simulation--PK (Schnitzler et al., 1987; Kalko and Schnitzler 1993 and RM (Schmidt and Joermann 1986)-but also for many other bat species that form large aggregations and undergo dense emergence. Furthermore, echolocation calls of bats emitted during dense emergence flights (see Gillam et al 2010) can be very much different from those emitted during foraging calls, so limiting the simulation to foraging calls may not be valid. Why did the authors not use actual waveforms of calls produced by these species during dense emergence to use biologically relevant signals in their simulation?

      The two species modeled have different calls. In particular, the bandwidth varies by a factor of 10, meaning the species' sonars will have different spatial resolutions. Range resolution is about 10x better for PK compared to RM, but the authors appear to use the same thresholds for "correct detection" for both, which doesn't seem appropriate. Also, the authors did not mention incorporating/correcting for/exploiting Doppler, which leads me to assume they did not model it.

      The success of the simulation may very well be due to variation in the calls of the bats, which ironically enough demonstrates the importance of a jamming avoidance response in dense flight. This explains why the performance of the simulation falls when bats are not able to distinguish their own echoes from other signals. For example, in Figure C2, there are calls that are labeled as conspecific calls and have markedly shorter durations and wider bandwidths than others. These three phases for call types used by the authors may be responsible for some (or most) of the performance of the model since the correlation between different call types is unlikely to exceed the detection threshold. But it turns out this variation in and of itself is what a jamming avoidance response may consist of. So, in essence, the authors are incorporating a jamming avoidance response into their simulation.

      The authors claim that integration over multiple pings (though I was not able to determine the specifics of this integration algorithm) reduces the masking problem. Indeed, it should: if you have two chances at detection, you've effectively increased your SNR by 3dB.

      They also claim - although it is almost an afterthought - that integration dramatically reduces the degradation caused by false echoes. This also makes sense: from one ping to the next, the bat's own echo delays will correlate extremely well with the bat's flight path. Echo delays due to conspecifics will jump around kind of randomly. However, the main concern is regarding the time interval and number of pings of the integration, especially in the context of the bat's flight speed. The authors say that a 1s integration interval (5-10 pings) dramatically reduces jamming probability and echo confusion. This number of pings isn't very high, and it occurs over a time interval during which the bat has moved 5-10m. This distance is large compared to the 0.4m distance-to-obstacle that triggers an evasive maneuver from the bat, so integration should produce a latency in navigation that significantly hinders the ability to avoid obstacles. Can the authors provide statistics that describe this latency, and discussion about why it doesn't seem to be a problem?

      The authors are using a 2D simulation, but this very much simplifies the challenge of a 3D navigation task, and there is an explanation as to why this is appropriate. Bat densities and bat behavior are discussed per unit area when realistically it should be per unit volume. In fact, the authors reference studies to justify the densities used in the simulation, but these studies were done in a 3D world. If the authors have justification for why it is realistic to model a 3D world in a 2D simulation, I encourage them to provide references justifying this approach.

      The focus on "masking" (which appears to be just in-band noise), especially relative to the problem of misassigned echoes, is concerning. If the bat calls are all the same waveform (downsweep linear FM of some duration, I assume - it's not clear from the text), false echoes would be a major problem. Masking, as the authors define it, just reduces SNR. This reduction is something like sqrt(N), where N is the number of conspecifics whose echoes are audible to the bat, so this allows the detection threshold to be set lower, increasing the probability that a bat's echo will exceed a detection threshold. False echoes present a very different problem. They do not reduce SNR per se, but rather they cause spurious threshold excursions (N of them!) that the bat cannot help but interpret as obstacle detection. I would argue that in dense groups the mis-assignment problem is much more important than the SNR problem.

      The criteria set for flight behavior (lines 393-406) are not justified with any empirical evidence of the flight behavior of wild bats in collective flight. How did the authors determine the avoidance distances? Also, what is the justification for the time limit of 15 seconds to emerge from the opening? Instead of an exit probability, why not instead use a time criterion, similar to "How long does it take X% of bats to exit?" What is the empirical justification for the 1-10 calls used for integration? The "average exit time for 40 bats" is also confusing and not well explained. Was this determined empirically? From the simulation? If the latter, what are the conditions? Does it include masking, no masking, or which species?

    1. Reviewer #3 (Public review):

      Summary:

      This paper identifies GTSE1 as a substrate of cyclin D1-CDK4/6 complexes when cyclin D1 is significantly over-expressed (as is common in cancers) rather than its endogenous level. GTSE is stabilized by phosphorylation and GTSE1 correlates with cancer prognosis, probably through an effect on cell proliferation.

      Strengths:

      There are few bonafide cyclin D1-Cdk4/6 substrates identified to be important in vivo so GTSE1 represents a potentially important finding for the field. Currently, the only cyclin D1 substrates involved in proliferation are the Rb family proteins.

      Weaknesses:

      GTSE1 is not a 'normal' target of cyclin D1-Cdk4/6, but rather only a target in a pathological situation.

    1. Reviewer #3 (Public review):

      This paper describes a new mechanism for the clearance of protein aggregates associated to endoplasmic reticulum re-organization that occurs during mitosis.

      Experimental data showing clearance of protein aggregates during mitosis is solid, statistically significant, and very interesting. The authors made several new experiments included in the revised version to address the concerns raised by reviewers. A new proteomic analysis, co-localization of the aggregates with the ER membrane Sec61beta protein, expression of the aggregate-prone protein in the nucleus does not result in accumulation of aggregates, detection of protein aggregates in the insoluble faction after cell disruption and mostly importantly knockdown of ATL proteins involved in the organization of ER shape and structure impaired the clearance mechanism. This last observation addresses one of the weakest points of the original version which was the lack of experimental correlation between ER structure capability to re-shape and the clearance mechanism.

      In conclusion, this new mechanism of protein aggregate clearance from the ER was not completely understood in this work but the manuscript presented, particularly in the revised version, an ensemble of solid observations and mechanistic information to scaffold future studies that clarify more details of this mechanism. As stated by the authors: "How protein aggregates are targeted and assembled into the intranuclear membranous structure waits for future investigation". This new mechanism of aggregate clearance from the ER is not expected to be fully understood in a single work but this paper may constitute one step to better comprehend the cell capability to resolve protein aggregates in different cell compartments.

    1. Reviewer #3 (Public review):

      Summary:

      Transcriptionally silent HIV-1 genomes integrated in the host`s genome represent the main obstacle for an HIV-1 cure. Therefore, agents aimed at promoting HIV transcription, the so-called latency reactivating agents (LRAs) might represent useful tools to render these hidden proviruses visible to the immune system. The authors successfully identified, through multiple techniques, INTS12, a component of the Integrator complex involved in 3' processing of small nuclear RNAs U1 and U2, as a factor promoting HIV-1 latency and hindering elongation of the HIV RNA transcripts. This factor hinders the activity of a previously identified combination of LRAs, one of which, AZD5582, has been validated in the macaque model for HIV persistence during therapy (https://pubmed.ncbi.nlm.nih.gov/37783968/). The other compound, I-BET151, is known to synergize with AZD5582, and is a inhibitor of BET, factors counteracting elongation of RNA transcripts.<br /> Therefore, INTS12 maight represent a target for future LRAs-

      Strengths:

      Findings were confirmed through multiple screens and multiple techniques. The authors successfully mapped the identified HIV silencing factor at the HIV promoter, Silencing of INTS12 increases the activity of small-molecule HIV latency-reversing agents such as the histone deacetylase inhibitor vorinostat. Knockdown of INTS12 does not induce toxic effects in the cells, thus rendering it a candidate a drug discovery campaign aimed at finding new agents for an HIV/AIDS cure.

      Weaknesses:

      A caveat is that the impact of INTS12 in diverse T cell functions or other in vivo functions is not yet known, but the authors acknowledge this in the revised discussion.

    1. Reviewer #3 (Public review):

      Summary:

      In this study, Sanchez-Leon et al. combined extracellular recordings of Purkinje cell activity in awake and anesthesized mice with juxtacellular recordings and Purkinje cell staining to link Purkinje cell orientation to their stimulation response. The authors find a relationship between neuron orientation and firing rate, dependent on stimulation type (anodal/cathodal). They also show effects of stimulation intensity and rebound effects.

      Strengths:

      Overall, the work is methodologically sound and the manuscript well written. The authors have taken great care to explain their rationale and methodological choices.

      Weaknesses:

      My only reservation is the lack of reporting of the precise test statistics, p-values and multiple comparison corrections. The work would benefit from adding this and other information.

    1. Reviewer #3 (Public review):

      Summary:

      Wang and van Ede investigate whether and how attention re-orients within visual working memory following expected and unexpected centrally presented memory tests. Using a combination of spatial modulations in neural activity (EEG-alpha lateralization) and gaze bias quantified as time courses of microsaccade rate, the authors examined how retro cues with varying levels of reliability influence attentional deployment and subsequent memory performance. The conclusion is that attentional re-orienting occurs within visual working memory, even when tested centrally, with distinct patterns following expected and unexpected tests. The findings provide new value for the field and are likely of broad interest and impact, by highlighting working memory as an action-bound process (in)dependent on (an ambiguous) past.

      Strengths:

      The study uniquely integrates behavioral data (accuracy and reaction time), EEG-alpha activity, and gaze tracking to provide a comprehensive analysis of attentional re-orienting within visual working memory. As typical for this research group, the validity of the findings follows from the task design that effectively manipulates the reliability of retro cues and isolates attentional processes related to memory tests. The use of well-established markers for spatial attention (i.e. alpha lateralization) and more recently entangled dependent variable (gaze bias) is commendable. Utilizing these dependent metrics, the concise report presents a thorough analysis of the scaling effects of cue reliability on attentional deployment, both at the behavioral and neural levels. The clear demonstration of prolonged attentional deployment following unexpected memory tests is particularly noteworthy, although there are no significant time clusters per definition as time isn't a factor in a statistical sense, the jackknife approach is convincing. Overall, the evidence is compelling, allowing the conclusion of a second stage of internal attentional deployment following both expected and unexpected memory tests, highlighting the importance of memory verification and re-orienting processes.

      Weaknesses:

      I want to stress upfront that these are not specific to the presented work and do not affect my recommendation to offer the report to the public in its present form.

      The sample size is consistent with previous studies, a larger sample could enhance the generalizability and robustness of the findings. The authors acknowledge high noise levels in EEG-alpha activity, which may affect the reliability of this marker. This is a general issue in non-invasive electrophysiology that cannot be handled by the authors but an interested reader should be aware of it. Effectively, the sensitivity of the gaze analysis appears "better" in part due to the better SNR. The latter also sets the boundaries for single trial analyses as the authors correctly mention. In terms of generalizability, I am convinced that the main outcome will likely generalize to different samples and stimulus types. Yet, as typical for the field, future research could explore different contexts and task demands to validate and extend the findings. The authors provide here how and why (including sharing of data and code).

      Comments on revisions:

      Really nice work, Thank you!

    1. Reviewer #3 (Public review):

      Li, Zhang, Wu and colleagues describe a new role for nuclear IDH1 in erythroid differentiation. IDH1 depletion results in a terminal erythroid differentiation defect with polychromatic and orthochromatic erythroblasts showing abnormal nuclei, nuclear condensation defects and an increased proportion of euchromatin, as well as enucleation defects. Using ChIP-seq for the histone modifications H3K79me3, H3K27me2 and H3K9me3, as well as ATAC-seq and RNA-seq in primary CD34-derived erythroblasts, the authors elucidate SIRT1 as a key dysregulated gene that is upregulated upon IDH1 knockdown. They furthermore show that chemical inhibition of SIRT1 partially rescues the abnormal nuclear morphology and enucleation defect during IDH1-deficient erythroid differentiation. The phenotype of delayed erythroid maturation and enucleation upon IDH1 shRNA-mediated knockdown was described in the group's previous co-authored study (PMID: 33535038). The authors describe this new role of IDH1 as non-canonical, but more experiments will be needed to determine whether this function of IDH1 in chromatin organization is secondary to its enzymatic-metabolic role. On the other hand, while the dependency of IDH1 mutant cells on NAD+ as well as a cell survival benefit upon SIRT1 inhibition has already been shown (see, e.g, PMID: 26678339, PMID: 32710757), previous studies focused on cancer cell lines and did not look at a developmental differentiation process, which makes this study interesting.

      The authors had initially hypothesized that IDH1 has a role in the nucleus independent of its enzymatic function, which is interesting but was not supported by the presented experiments. In the revised manuscript, the authors decided to just focus on the nuclear role of IDH1. To this end, they present a system in HUDEP-2 cells harboring a CRISPR/Cas9-mediated IDH1 knockout and overexpression of an IDH1 construct containing a nuclear export signal. While they only use this system in some of their experiments, they mostly use a global IDH1 shRNA knockdown approach is employed, which will affect both forms of IDH1, cytoplasmic and nuclear. Future work using their system that specifically depletes nuclear IDH1 could further delineate changes of the chromatin landscape upon loss of nuclear IDH1 and also address how loss of nuclear IDH1 affects the part of the TCA cycle that has recently been shown to be present in the nucleus (PMID: 36044572).

    1. Reviewer #3 (Public review):

      The paper addresses pivotal questions concerning the multifaceted functions of oyster hemocytes by integrating single-cell RNA sequencing (scRNA-seq) data with analyses of cell morphology, transcriptional profiles, and immune functions. In addition to investigating granulocyte cells, the study delves into the potential roles of blast and hyalinocyte cells. A key discovery highlighted in this research is the identification of cell types engaged in antimicrobial activities, encompassing processes such as phagocytosis, intracellular copper accumulation, oxidative bursts, and antimicrobial peptide synthesis.

      A particularly intriguing aspect of the study lies in the exploration of hemocyte lineages, warranting further investigation, such as employing scRNA-seq on embryos at various developmental stages.

    1. Reviewer #3 (Public review):

      There is an interesting mathematical connection - an "isomorphism"-between Price's equation and least-squares linear regression. Some people have misinterpreted this connection as meaning that there is a generality-limiting assumption of linearity within Price's equation, and hence that Hamilton's rule-which is derived from Price's equation-provides only an approximation of the action of natural selection. This is in contrast to the majority view that Hamilton's rule is a fully general and exact result.

      To briefly give some mathematical details: Price's equation defines the action of natural selection in relation to a trait of interest as the covariance between fitness w and the genetic breeding value g for the trait, i.e. cov(w,g); this is a fully general result that applies exactly to any arbitrary set of (g,w) data; without any loss of generality this covariance can be expressed as the product of genetic variance var(g) and a coefficient b(w,g), the coefficient simply being defined as b(w,g) = cov(w,g)/var(g) for all var(g) > 0; it happens that if one fits a straight line to the same (g,w) data by means of least-squares regression then the slope of that line is equal to b(w,g).

      All of this has already been discussed, repeatedly, in the literature.

      Now turn to the present paper: the first sentence of the Abstract says "The generality of Hamilton's rule is much debated", and then the next sentence says "In this paper, I show that this debate can be resolved by constructing a general version of Hamilton's rule". But immediately it's clear that this isn't really resolving the debate, what this paper is actually doing is asserting the correctness of the minority view (i.e. that Hamilton's rule as it currently stands is not a general result) and then attempting to build a more general form of Hamilton's rule upon that shaky foundation. Predictably, the paper erroneously interprets the standard formulation of Hamilton's rule as a linear approximation and develops non-linear extensions to improve the goodness of fit for a result that is already exactly correct.

      This is not a convincing contribution. It will not change minds or improve understanding of the topic.

      Nor is it particularly novel. Smith et al (2010, "A generalisation of Hamilton's rule for the evolution of microbial cooperation" Science 328, 1700-1703) similarly interpreted Hamilton's rule as a linear model and provided a corresponding polynomial expansion - usefully fitting the model to microbial data so as to learn something about the costs and benefits of cooperation in an empirical setting. it's odd that this paper isn't cited here.

    1. Reviewer #3 (Public review):

      Kinesin-1 is a dimeric motor protein that transports cargo along microtubules. Its movement relies on the ability of its two catalytic motor domains (heads) to couple microtubule interactions with directional conformational changes and ATP turnover in a coordinated, alternating manner. The kinetics of these processes in each head are tightly regulated (gated) to ensure that at least one motor domain remains bound to the microtubule at all times, preventing detachment.

      Niitani et al. investigated the gating mechanism by focusing on the role of the neck linker, a flexible region extending from the motor domain's C-terminus that undergoes conformational changes during stepping. They examined how the neck linker differentially regulates the microtubule affinity and ATP turnover of the front and rear heads. To do this, they designed cross-linkable monomeric motor domains mimicking the conformations of the front and rear heads and employed a combination of pre-steady-state and single-molecule analyses to measure ATP-binding and microtubule-detachment kinetics. Additionally, they studied a kinesin heterodimer with a locked rear head conformation to distinguish the kinetic properties of the front and rear heads within an active dimer.

      ATP binding rates were measured using stopped-flow experiments with mant-ATP and nucleotide-free kinesin-microtubule complexes. The results showed that crosslinking the neck linker in the forward-pointing conformation (mimicking the rear head) reduced the ATP dissociation rate, while crosslinking it in the rear-pointing conformation (mimicking the front head) had no significant effect on ATP binding kinetics. ATP dissociation from the rear head was further examined using a kinesin mutant (E236A) that stabilizes the ATP-bound state by significantly slowing ATP hydrolysis.

      To assess how neck-linker orientation affects microtubule attachment, the authors monitored turbidity changes after rapidly mixing nucleotide-free, crosslinked kinesin-microtubule complexes with ATP in a stopped-flow apparatus. Their findings demonstrated that the forward-oriented neck linker in the rear head promotes microtubule detachment, whereas the backward-oriented neck linker in the front head reduces detachment rates.

      These results indicate that neck-linker conformation governs gating of microtubule affinity and nucleotide binding. Moreover, they show that even partial docking of the neck linker onto the head is sufficient to partially open the gating mechanism. To further investigate the role of neck linker tension, the authors created kinesin dimers with neck linker insertions of varying lengths. Microtubule detachment kinetics and ATPase activity assays revealed that ATP turnover in the rear head is significantly affected by the degree of forward tension applied to its neck linker.

      Overall, Niitani et al. build upon previous kinesin gating models by introducing a neck-linker tension-based ATP binding affinity mechanism. Their findings provide a mechanistic basis for recent cryo-EM observations for kinesin-1 and kinesin-3 (KIF14) and distinguish the specific roles of neck linker tension in the front and rear heads in regulating ATP binding, hydrolysis, and microtubule detachment. This study is biochemically rigorous and makes an important contribution, though direct structural validation (e.g., cryo-EM snapshots of crosslinked or mutant kinesins bound to microtubules) would further strengthen their conclusions and clarify the asymmetry in ATP affinity between the front and rear heads.

    1. Reviewer #3 (Public review):

      Summary:

      This paper presents a method for reconstructing input videos shown to a mouse from the simultaneously recorded visual cortex activity (two-photon calcium imaging data). The publicly available experimental dataset is taken from a recent brain-encoding challenge, and the (publicly available) neural network model that serves to reconstruct the videos is the winning model from that challenge (by distinct authors). The present study applies gradient-based input optimization by backpropagating the brain-encoding error through this selected model (a method that has been proposed in the past, with other datasets). The main contribution of the paper is, therefore, the choice of applying this existing method to this specific dataset with this specific neural network model. The quantitative results appear to go beyond previous attempts at video input reconstruction (although measured with distinct datasets). The conclusions have potential practical interest for the field of brain decoding, and theoretical interest for possible future uses in functional brain exploration.

      Strengths:

      The authors use a validated optimization method on a recent large-scale dataset, with a state-of-the-art brain encoding model. The use of an ensemble of 7 distinct model instances (trained on distinct subsets of the dataset, with distinct random initializations) significantly improves the reconstructions. The exploration of the relation between reconstruction quality and the number of recorded neurons will be useful to those planning future experiments.

      Weaknesses:

      The main contribution is methodological, and the methodology combines pre-existing components without any new original components. The movie reconstructions include a learned "transparency mask" to concentrate on the most informative area of the frame; it is not clear how this choice impacts the comparison with prior experiments. Did they all employ this same strategy? If not, shouldn't the quantitative results also be reported without masking, for a fair comparison?

    1. Reviewer #3 (Public review):

      Summary:

      This well-powered study tested the effects of hunger on value-based dietary decision-making. The main hypothesis was that attentional mechanisms guide choices toward unhealthier and tastier options when participants are hungry and are in the fasted state compared to satiated states. Participants were tested twice - in a fasted state and in a satiated state after consuming a protein shake. Attentional mechanisms were measured during dietary decision-making by linking food choices and reaction times to eye-tracking data and mathematical drift-diffusion models. The results showed that hunger makes high-conflict food choices more taste-driven and less health-driven. This effect was formally mediated by relative dwell time, which approximates attention drawn to chosen relative to unchosen options. Computational modeling showed that a drift-diffusion model, which assumed that food choices result from a noisy accumulation of evidence from multiple attributes (i.e., taste and health) and discounted non-looked attributes and options, best explained observed choices and reaction times.

      Strengths:

      This study's findings are valuable for understanding how energy states affect decision-making and provide an answer to how hunger can lead to unhealthy choices. These insights are relevant to psychology, behavioral economics, and behavioral change intervention designs.

      The study has a well-powered sample size and hypotheses were pre-registered. The analyses comprised classical linear models and non-linear computational modeling to offer insight into putative cognitive mechanisms.

      In summary, the study advances the understanding of the links between energy states and value-based decision-making by showing that depleting is powerful for shaping the formation of food preferences. Moreover, the computational analysis part offers a plausible mechanistic explanation at the algorithmic level of observed effects.

      Weaknesses:

      Some parts of the positioning of the hunger state manipulation and the interpretation of its effects could be improved.

      On the positioning side, it does not seem like a 'bad' decision to replenish energy states when hungry by preferring tastier, more often caloric options. In this sense, it is unclear whether the observed behavior in the fasted state is a fallacy or a response to signals from the body. The introduction does mention these two aspects of preferring more caloric food when hungry. However, some ambiguity remains about whether the study results indeed reflect suboptimal choice behavior or a healthy adaptive behavior to restore energy stores.

      On the interpretation side, previous work has shown that beliefs about the nourishing and hunger-killing effectiveness of drinks or substances influence subjective and objective markers of hunger, including value-based dietary decision-making, and attentional mechanisms approximated by computational models and the activation of cognitive control regions in the brain. The present study shows differences between the protein shake and a natural history condition (fasted, state). This experimental design, however, cannot rule between alternative interpretations of observed effects. Notably, effects could be due to (a) the drink's active, nourishing ingredients, (b) consuming a drink versus nothing, or (c) both.

    1. Reviewer #3 (Public review):

      In general, although the authors interpret their results as pointing towards a possible role of BDNF in dentin regeneration, the results are over-interpreted due to the lack of proper controls and focus on TrkB expression, but not its isoforms in inflammatory processes. Surprisingly, the authors do not study the possible role of p75 in this process, which could be one of the mechanisms intervening under inflammatory conditions.

      (1) The authors claim that there are two Trk receptors for BDNF, TrkA and TrkB. To date, I am unaware of any evidence that BDNF binds to TrkA to activate it. It is true that two receptors have been described in the literature, TrkB and p75 or NGFR, but the latter is not TrkA despite its name and capacity to bind NGF along with other neurotrophins. It is crucial for the authors to provide a reference stating that TrkA is a receptor for BDNF or, alternatively, to correct this paragraph.

      (2) The authors discuss BDNF/TrkB in inflammation. Is there any possibility of p75 involvement in this process?

      (3) The authors present immunofluorescence (IF) images against TrkB and pTrkB in the first figure. While they mention in the materials and methods section that these antibodies were generated for this study, there is no proof of their specificity. It should be noted that most commercial antibodies labeled as anti-TrkB recognize the extracellular domain of all TrkB isoforms. There are indications in the literature that pathological and excitotoxic conditions change the expression levels of TrkB-Fl and TrkB-T1. Therefore, it is necessary to demonstrate which isoform of TrkB the authors are showing as increased under their conditions. Similarly, it is essential to prove that the new anti-p-TrkB antibody is specific to this Trk receptor and, unlike other commercial antibodies, does not act as an anti-phospho-pan-Trk antibody.

      (4) I believe this initial conclusion could be significantly strengthened, without opening up other interpretations of the results, by demonstrating the specificity of the antibodies via Western blot (WB), both in the presence and absence of BDNF and other neurotrophins, NGF, and NT-3. Additionally, using WB could help reinforce the quantification of fluorescence intensity presented by the authors in Figure 1. It's worth noting that the authors fixed the cells with 4% PFA for 2 hours, which can significantly increase cellular autofluorescence due to the extended fixation time, favoring PFA autofluorescence. They have not performed negative controls without primary antibodies to determine the level of autofluorescence and nonspecific background. Nor have they indicated optimizing the concentration of primary antibodies to find the optimal point where the signal is strong without a significant increase in background. The authors also do not mention using reference markers to normalize specific fluorescence or indicating that they normalized fluorescence intensity against a standard control, which can indeed be done using specific signal quantification techniques in immunocytochemistry with a slide graded in black-and-white intensity controls. From my experience, I recommend caution with interpretations from fluorescence quantification assays without considering the aforementioned controls.

      (5) In Figure 2, the authors determine the expression levels of TrkA and TrkB using qPCR. Although they specify the primers used for GAPDH as a control in materials and methods, they do not indicate which primers they used to detect TrkA and TrkB transcripts, which is essential for determining which isoform of these receptors they are detecting under different stimulations. Similarly, I recommend following the MIQE guidelines (Minimum Information for Publication of Quantitative Real-Time PCR experiments), so they should indicate the amplification efficiency of their primers, the use of negative and positive controls to validate both the primer concentration used, and the reaction, the use of several stable reference genes, not just one.

      (6) Moreover, the authors claim they are using the same amounts of cDNA for qPCRs since they have quantified the amounts using a Nanodrop. Given that dNTPs are used during cDNA synthesis, and high levels remain after cDNA synthesis from mRNA, it is not possible to accurately measure cDNA levels without first cleaning it from the residual dNTPs. Therefore, I recommend that the authors clarify this point to determine how they actually performed the qPCRs. I also recommend using two other reference genes like 18S and TATA Binding Protein alongside GAPDH, calculating the geometric mean of the three to correctly apply the 2^-ΔΔCt formula.

      (7) Similarly, given that the newly generated antibodies have not been validated, I recommend introducing appropriate controls for the validation of in-cell Western assays.

      (8) The authors' conclusion that TrkB levels are minimal (Figure 2E) raises questions about what they are actually detecting in the previous experiments might not be the TrkB-Fl form. Therefore, it is essential to demonstrate beyond any doubt that both the antibodies used to detect TrkB and the primers used for qPCR are correct, and in the latter case, specify at which cycle (Ct) the basal detection of TrkB transcripts occurs. Treatment with TNF-alpha for 14 days could lead to increased cell proliferation or differentiation, potentially increasing overall TrkB transcript levels due to the number of cells in culture, not necessarily an increase in TrkB transcripts per cell.

      (9) Overall, there are reasonable doubts about whether the authors are actually detecting TrkB in the first three images, as well as the phosphorylation levels and localization of this receptor in the cells. For example, in Figure 3 A to J, it is not clear where TrkB is expressed, necessitating better resolution images and a magnified image to show in which cellular structure TrkB is expressed.

      (10) In Figure 4, the authors indicate they have generated cells overexpressing BDNF after recombination using CRISPR technology. However, the WB they show in Figure 4B, performed under denaturing conditions, displays a band at approximately 28kDa. This WB is absolutely incorrect with all published data on BDNF detection via this technique. I believe the authors should demonstrate BDNF presence by showing a WB with appropriate controls and BDNF appearing at 14kDa to assume they are indeed detecting BDNF and that the cells are producing and secreting it. What antibodies have been used by the authors to detect BDNF? Have the authors validated it? There are some studies reporting the lack of specificity of certain commercial BDNF antibodies, therefore it is necessary to show that the authors are convincingly detecting BDNF.

      (11) While the RNA sequencing data indicate changes in gene expression in cells treated with TNFalpha+CTX-B compared to control, the authors do not show a direct relationship between these genetic modifications with the rest of their manuscript's argument. I believe the results from these RNA sequencing assays should be put into the context of BDNF and TrkB, indicating which genes in this signaling pathway are or are not regulated, and their importance in this context.

    1. Reviewer #3 (Public review):

      Summary:

      Soffers et al. developed a comprehensive genetic toolkit that enables researchers to access neuronal hemilineages during developmental and adult time points using scRNA-seq analysis to guide gene cassette exchange-based or CRISPR-based tool building. Currently, research groups studying neural circuit development are challenged with tying together findings in the development and mature circuit function of hemilineage-related neurons. Here, authors leverage publicly available scRNA-seq datasets to inform the development of a split-Gal4 library that targets 32 of 34 hemilineages in development and adult stages. The authors demonstrated that the split-Gal4 library, or genetic toolkit, can be used to assess the functional roles, neurotransmitter identity, and morphological changes in targeted cells. The tools presented in this study should prove to be incredibly useful to Drosophila neurobiologists seeking to link neural developmental changes to circuit assembly and mature circuit function. Additionally, some hemilineages have more than one split-Gal4 combination that will be advantageous for studies seeking to disrupt associated upstream genes.

      Strengths:

      Informing genetic tool development with publicly available scRNA-seq datasets is a powerful approach to creating specific driver lines. Additionally, this approach can be easily replicated by other researchers looking to generate similar driver lines for more specific subpopulations of cells, as mentioned in the Discussion.

      The unification of optogenetic stimulation data of 8B neurons and connectomic analysis of the Giant-Fiber-induced take-off circuit was an excellent example of the utility of this study. The link between hemilineage-specific functional assays and circuit assembly has been limited by insufficient genetic tools. The tools and data present in this study will help better understand how collections of hemilineages develop in a genetically constrained manner to form circuits amongst each other selectively.

      Weaknesses:

      Although cell position, morphology (to some extent), and gene expression are good markers to track cell identity across developmental time, there are genetic tools available that could have been used to permanently label cells that expressed genes of interest from birth, ensuring that the same cells are being tracked in fixed tissue images.

      Although gene activation is a good proxy for assaying neurochemical features, relying on whether neurochemical pathway genes are activated in a cell to determine its phenotype can be misleading given that the Trojan-Gal4 system commandeers the endogenous transcriptional regulation of a gene but not its post-transcriptional regulation. Therefore, neurochemical identity is best identified via protein detection. (strong language used in this section of the paper).

      The authors mainly rely on the intersectional expression of transcription factors to generate split-Gal4 lines and target hemilineages specifically. However, the Introduction (Lines 97-99) makes a notable point about how driver lines in the past, which have also predominantly relied on the regulatory sequences of transcription factors, lack the temporal stability to investigate hemilineages across time. This point seems to directly conflict with the argument made in the Results (Lines 126-127) that states that most transcription factors are stably expressed in hemilineage neurons that express them. It is generally known that transcription factors can be expressed stably or transiently depending on the context. It is unclear how using the genes of transcription factors in this study circumvents the issue of creating temporally stable driver lines.

    1. Reviewer #3 (Public review):

      Summary:

      This paper presents evidence from three behavioral experiments that causal impressions of "launching events", in which one object is perceived to cause another object to move, depend on motion direction-selective processing. Specifically, the work uses an adaptation paradigm (Rolfs et al., 2013), presenting repetitive patterns of events matching certain features to a single retinal location, then measuring subsequent perceptual reports of a test display in which the degree of overlap between two discs was varied, and participants could respond "launch" or "pass". The three experiments report results of adapting to motion direction, motion speed and "object identity", and examine how the psychometric curves for causal reports shift in these conditions depending on the similarity of adapter and test. While causality reports in the test display were selective for motion direction (Experiment 1), they were not selective for adapter-test speed differences (Experiment 2) nor for changes in object identity induced via color swap (Experiment 3). These results support the notion of a biological implementation of causality perception in the visual system, possibly even independently of computations of object identity.

      Strengths:

      The setup of the research question and hypotheses are exceptional. The authors thoroughly discuss relevant literature to clearly link their launch/pass paradigm to impressions of causality, strengthening their hypothesis and conclusions. The experiments are carefully performed (appropriate equipment, careful control of eye movements). The slip adaptor is a really nice control condition and effectively mitigates the need to control for motion direction with a drifting grating or similar. Participants were measured with sufficient precision, and a power curve analysis was conducted to determine the sample size. Data analysis and statistical quantification is appropriate. Data and analysis code will be shared on publication, in keeping with open science principles. The paper is concise and well written.

      Weaknesses:

      I would like to emphasise that in the employed paradigm and previously conducted similar study, the only report options are "launch" or "pass". As pointed out by the authors' reply, the adaptation to launches seems to be a highly specific process and likely is a consequence of the causal interaction between the objects. I would nonetheless be interested to see which of the stimulus features driving the adaptation effect observed here are relevant/irrelevant to subjective causal impressions in an experiment.

      References:

      Rolfs, M., Dambacher, M., & Cavanagh, P. (2013). Visual Adaptation of the Perception of Causality. Current Biology, 23(3), 250-254. https://doi.org/10.1016/j.cub.2012.12.017

    1. Reviewer #3 (Public review):

      The preprint by Yadav et al. describes a new setup to quantify a number of aggression and mating behaviors in Drosophila melanogaster. The investigation of these behaviors requires the analysis of a large number of videos to identify each kind of behavior displayed by a fly. Several approaches to automatize this process have been published before, but each of them has its limitations. The authors set out to develop a new setup that includes very low-cost, easy-to-acquire hardware and open-source machine-learning classifiers to identify and quantify the behavior.

      Strengths:

      (1) The study demonstrates that their cheap, simple, and easy-to-obtain hardware works just as well as custom-made, specialized hardware for analyzing aggression and mating behavior. This enables the setup to be used in a wide range of settings, from research with limited resources to classroom teaching.

      (2) The authors used previously published software to train new classifiers for detecting a range of behaviors related to aggression and mating and to make them freely available. The classifiers are very positively benchmarked against a manually acquired ground truth as well as existing algorithms.

      (3) The study demonstrates the applicability of the setup (hardware and classifiers) to common methods in the field by confirming a number of expected phenotypes with their setup.

      Weaknesses:

      (1) When measuring the performance of the duration-based classifiers, the authors count any bout of behavior as true positive if it overlaps with a ground-truth positive for only 1 frame - despite the minimal duration of a bout is 10 frames, and most bouts are much longer. That way, true positives could contain cases that are almost totally wrong as long there was an overlap of a single frame. For the mating behaviors that are classified in ongoing bouts, I think performance should be evaluated based on the % of correctly classified frames, not bouts.

      (2) In the methods part, only one of the pre-existing algorithms (MateBook), is described. Given that the comparison with those algorithms is a so central part of the manuscript, each of them should be briefly explained and the settings used in this study should be described.

      Taken together, this work can greatly facilitate research on aggression and mating in Drosophila. The combination of low-cost, off-the-shelf hardware and open-source, robust software enables researchers with very little funding or technical expertise to contribute to the scientific process and also allows large-scale experiments, for example in classroom teaching with many students, or for systematic screenings.

    1. Reviewer #3 (Public review):

      Summary:

      The paper by Chang-Gonzalez et al. is a molecular dynamics (MD) simulation study of the dynamic recognition (load-induced catch bond) by the T cell receptor (TCR) of the complex of peptide antigen (p) and the major histocompatibility complex (pMHC) protein. The methods and simulation protocols are essentially identical as those employed in a previous study by the same group (Chang-Gonzalez et al., eLife 2024). In the current manuscript the authors compare the binding of the same pMHC complex to two different TCRs, B7 and A6 which was investigated in the previous paper. While the binding is more stable for both TCRs under load (of about 10-15 pN) than in the absence of load, the main difference is that B7 shows a smaller amount of stable contacts with the pMHC than A6.

      Strengths:

      The topic is interesting because of the relevance of mechanosensing in biological processes including cellular immunology. The MD simulations provide strong evidence that different TCRs can respond mechanically in a different way upon binding the same pMHC complex. These findings are useful for interpreting how mechanical force is employed for modulating different function of T cells.

    1. Reviewer #3 (Public review):

      Summary:

      Bos et al study a computational model of cortical circuits with excitatory (E) and two subtypes of inhibition - parvalbumin (PV) and somatostatin (SOM) expressing interneurons. They perform stability and gain analysis of simplified models with nonlinear transfer functions when SOM neurons are perturbed. Their analysis suggests that in a specific setup of connectivity, instability and gain can be untangled, such that SOM modulation leads to both increase in stability and gain, in contrast to the typical direction in neuronal networks where increased gain results in decreased stability.

      Strengths:

      - Analysis of the canonical circuit in response to SOM perturbations. Through numerical simulations and mathematical analysis, the authors have provided a rather comprehensive picture of how SOM modulation may affect response changes.<br /> - Shedding light on two opposing circuit motifs involved in the canonical E-PV-SOM circuitry - namely, direct inhibition (SOM -> E) vs disinhibition (SOM -> PV -> E). These two pathways can lead to opposing effects, and it is often difficult to predict which one results from modulating SOM neurons. In simplified circuits, the authors show how these two motifs can emerge and depend on parameters like connection weights.<br /> - Suggesting potentially interesting consequences for cortical computation. The authors suggest that certain regimes of connectivity may lead to untangling of stability and gain, such that increases in network gain are not compromised by decreasing stability. They also link SOM modulation in different connectivity regimes to versatile computations in visual processing in simple models.

      Weaknesses:

      - Computationally, the analysis is solid, but it's very similar to previous studies (del Molino et al, 2017). Many studies in the past few years have done the perturbation analysis of a similar circuitry with or without nonlinear transfer functions (some of them listed in the references). This study applies the same framework to SOM perturbations, which is a useful computational analysis, in view of the complexity of the high-dimensional parameter space.<br /> - A general weakness of the paper is a lack of direct comparison to biological parameters or experiments. How different experiments can be reconciled by the results obtained here, and what new circuit mechanisms can be revealed? In its current form, the paper reads as a general suggestion that different combinations of gain modulation and stability can be achieved in a circuit model equipped with many parameters (12 parameters). This is potentially interesting but not surprising, given the high dimensional space of possible dynamical properties. A more interesting result would have been to relate this to biology, by providing reasoning why it might be relevant to certain circuits (and not others), or to provide some predictions or postdictions, which are currently not very strong in the manuscript.<br /> - Tuning curves are simulated for an individual orientation (same for all neurons), not considering the heterogeneity of neuronal networks with multiple orientation selectivity (and other visual features) - making the model too simplistic.

    1. Reviewer #3 (Public review):

      Summary:

      This well-powered study tested the effects of hunger on value-based dietary decision-making. The main hypothesis was that attentional mechanisms guide choices toward unhealthier and tastier options when participants are hungry, and are in the fasted state compared to satiated states. Participants were tested twice - in a fasted state and in a satiated state after consuming a protein shake. Attentional mechanisms were measured during dietary decision-making by linking food choices and reaction times to eye-tracking data and mathematical drift-diffusion models. The results showed that hunger makes high-conflict food choices more taste-driven and less health-driven. This effect was formally mediated by relative dwell time, which approximates attention drawn to chosen relative to unchosen options. Computational modeling showed that a drift-diffusion model, which assumed that food choices result from a noisy accumulation of evidence from multiple attributes (i.e., taste and health) and discounted non-looked attributes and options, best explained observed choices and reaction times.

      Strengths:

      This study's findings are valuable for understanding how energy states affect decision-making and provide an answer to how hunger can lead to unhealthy choices. These insights are relevant to psychology, behavioral economics, and behavioral change intervention designs.

      The study has a well-powered sample size and hypotheses were pre-registered. The analyses comprised classical linear models and non-linear computational modeling to offer insight into putative cognitive mechanisms.

      In summary the study advances the understanding of the links between energy states and value-based decision-making by showing that depleting is powerful for shaping the formation of food preferences. Moreover, the computational analysis part offers a plausible mechanistic explanation at the algorithmic level of observed effects.

      Weaknesses:

      Some parts of the positioning of the hunger state manipulation and the interpretation of its effects could be improved.

      On the positioning side, it does not seem like a 'bad' decision to replenish energy states when hungry by preferring tastier, more often caloric options. In this sense, it is unclear whether the observed behavior in the fasted state is a fallacy or a response to signals from the body. The introduction does mention these two aspects of preferring more caloric food when hungry. However, some ambiguity remains about whether the study results indeed reflect suboptimal choice behavior or a healthy adaptive behavior to restore energy stores.

      On the interpretation side, previous work has shown that beliefs about the nourishing and hunger-killing effectiveness of drinks or substances influence subjective and objective markers of hunger, including value-based dietary decision-making, and attentional mechanisms approximated by computational models and the activation of cognitive control regions in the brain. The present study shows differences between the protein shake and a natural history condition (fasted, state). This experimental design, however, cannot rule between alternative interpretations of observed effects. Notably, effects could be due to (a) the drink's active, nourishing ingredients, (b) to consuming a drink versus nothing, or (c) both.

      Comments on revisions:

      The authors addressed all my comments appropriately and I have no further requests. Thank you for the added discussion of findings and extra analyses.

    1. Reviewer #3 (Public Review):

      Compared to the pyramidal cells of the CA1 and CA3 regions of the hippocampus, and the granule cells of the dentate gyrus (DG), the computational role(s) of mossy cells of the DG have received much less attention over the years and are consequently not well understood. Mossy cells receive feedforward input from granule cells and feedback from CA3 cells. One significant factor is the compression of the large number of CA3 cells that input onto a much smaller population of mossy cells, which then send feedback connections to the granule cell layer. The present paper seeks to understand this compression in terms of neural coding, and asks whether the subthreshold activity of a small number of mossy cells can predict above chance levels the shapes of individual SWs produced by the CA3 cells. Using elegant multielectrode intracellular recordings of mossy cells, the authors use deep learning networks to show that they can train the network to "predict" the shape of a SW that preceded the intracellular activity of the mossy cells. Putatively, a single mossy cell can predict the shape of SWs above chance. These results are interesting, but there are some conceptual issues and questions about the statistical tests that must be addressed before the results can be considered convincing.

      Strengths<br /> (1) The paper uses technically challenging techniques to record from multiple mossy cells at the same time, while also recording SWs from the LFP of the CA3 layer. The data appear to be collected carefully and analyzed thoughtfully.<br /> (2) The question of how mossy cells process feedback input from CA3 is important to understand the role of this feedback pathway in hippocampal processing.<br /> (3) Given the concerns expressed below about proper statistical testing are resolved, the data appear supportive of the main conclusions of the authors and suggest that, to some degree, the much smaller population of mossy cells can conserve the information present in the larger population of CA3 cells, presumably by using a more compressed, dense population code.

      Weaknesses<br /> (4) Some of the statistical tests appear inappropriate because they treat each CA3 SW and associated Vm from a mossy cell as independent samples. This violates the assumptions of statistical tests such as the Kolmogorov-Smirnov tests of Figure 3C and Fig 3E. Although there is large variability among the SWs recorded and among the Vm's, they cannot be considered independent measurements if they derive from the same cell and same recording site of an individual animal. This becomes especially problematic when the number of dependent samples adds up to the tens of thousands, providing highly inflated numbers of samples that artificially reduce the p values. Techniques such as mixed-effects models are being increasingly used to factor out the effects of within cell and within animal correlations in the data. The authors need to do something similar to factor out these contributions in order to perform statistical tests, throughout the manuscript when this problem occurs.<br /> (5) A separate statistical problem occurs when comparing real data against a shuffled, surrogate data set. From the methods, I gather that Figure 3C combined data from 100 surrogate shuffles to compare to the real data. It is inappropriate to do a classic statistical test of data against such shuffles, because the number of points in the pooled surrogate data sets are not true samples from a population. It is a mathematical certainty that one can eventually drive a p value to < 0.05 just by increasing the number of shuffles sufficiently. Thus, the p value is determined by the number of computer shuffles allowed by the time and processing power of a computer, rather than by sampling real data from the population. Figures such as 4C and 5A are examples that test data against shuffle appropriately, as a single value is determined to be within or outside the 95% confidence interval of the shuffle, and this determination is not directly affected by the number of shuffles performed.<br /> (6) The last line of the Discussion states that this study provides "important insights into the information processing of neural circuits at the bottleneck layer," but it is not clear what these insights are. If the statistical problems are addressed appropriately, then the results do demonstrate that the information that is reflected in SWs can be reconstructed by cells in the MC bottleneck, but it is not certain what conceptual insights the authors have in mind. They should discuss more how these results further our understanding of the function of the feedback connection from CA3 to the mossy cells, discuss any limitations on their interpretation from recording LFPs rather than the single-unit ensemble activity (where the information is really encoded).<br /> 7) In Figure 1C, the maximum of the MC response on the first inset precedes the SW, and the onset of the Vm response may be simultaneous with SW. This would suggest that the SW did not drive the mossy cell, but this was a coincident event. How many SW-mossy cell recordings are like this? Do the authors have a technical reason to believe that these are events in which the mossy cell is driven by the CA3 cells active during the SW?

    1. Reviewer #3 (Public review):

      Summary:

      Predicting how two different drugs act together by looking at their specific gene targets and pathways is crucial for understanding the biological significance of drug combinations. This study incorporates drug-specific pathway activation scores (PASs) to estimate synergy scores as one of the key advancements for synergy prediction. The new algorithm, Drug synergy Interaction Prediction (DIPx), developed in this study, uses gene expression, mutation profiles, and drug synergy data to train the model and predict synergy between two drugs. Comprehensive comparisons with another best-performing algorithm, TAIJI-M, highlight the potential of its capabilities.

      Strengths:

      DIPx uses target and driver genes to elucidate pathway activation scores (PASs) to predict drug synergy. This approach integrates gene expression, mutation profiles, and drug synergy data to capture information about the functional interactions between drug targets, thereby providing a potential biological explanation for the synergistic effects of combined drugs. DIPx's performance was tested using the AstraZeneca-Sanger (AZS) DREAM Challenge dataset, especially in Test Set 1, where the Spearman correlation coefficient between predicted and observed drug synergy was 0.50 (95% CI: 0.47-0.53). DIPx's ability to handle novel combinations, as evidenced by its performance in Test Set 2, indicates its potential for predictions of new and untested drug combinations.

      Weaknesses:

      While the DIPx algorithm shows promise in predicting drug synergy based on pathway activation scores, it's essential to consider its limitations. One limitation is that the availability of training data for specific drug combinations may influence its predictive capability. Further testing and experimental validation of the predictions in future studies would be necessary to fully assess the algorithm's generalizability and robustness.

    1. Reviewer #4 (Public review):

      Summary:

      In this study, the authors explore the neural dynamics of mirror neurons in the premotor cortex, focusing on the relationship between neural activity during action execution and observation. The study presents a rich dataset from three monkeys, with recordings from two regions per monkey. The authors use a method to analyze instantaneous neural subspaces and track their temporal evolution. Consistent with prior literature, they report that execution and observation subspaces remain largely distinct throughout the trial. However, after applying canonical correlation analysis, they observe a notable alignment between execution and observation activities, suggesting the presence of shared neural codes. The study is well-designed, and the analyses are thoroughly documented, occasionally overly so in the main text. While most findings are compelling, I find the conclusions drawn from Figure 8 less convincing. Specifically, I am skeptical about the application of CCA in this context and the subsequent interpretations regarding execution-observation similarity, which is a central claim of the manuscript.

      • The authors cite Safaie et al. 2023 as a precedent for applying CCA to align neural population dynamics. However, in that study, CCA was used to align neural dynamics across different animals, a justifiable approach given that neural trajectories exist in separate neural state spaces for each animal. Here, CCA is applied to align execution and observation activities within the same neural state space of the same MNs. I find this application of CCA less well-justified, as it may overestimate execution-observation similarity.<br /> • The control conditions presented in Figures 8C and 8D are somewhat reassuring, as they show that the similarity introduced by CCA is not universally high. However, these controls appear to be limited to the Hold epoch. It remains unclear whether the same holds true for the Go and Movement epochs.<br /> • In Figure 5, the authors display low-dimensional representations of four objects across task epochs during execution (A) and observation (B). The diagonals of the matrices reveal clear differences between execution and observation configurations across all four epochs. The authors suggest using CCA to align these configurations; however, this alignment seems to require time-specific application of CCA for each epoch (as demonstrated in Figure 8 for the Hold epoch). The need for time-specific adjustments likely depends on the fact that execution and observation subspaces are continuously shifting over time (as authors show in Figure 4), but this approach appears to be a strained attempt to demonstrate similarity between execution and observation codes.<br /> • The authors themselves offer an alternative hypothesis (line 730): that "PM MN population activity during action observation, rather than representing movements made by another individual similar to one's own movements, instead may represent different movements one might execute oneself in response to those made by another individual". This interpretation appears more congruent with the data presented.<br /> • In the end, I am left with a sense of ambiguity: which analysis should be considered more reliable, the negligible correspondence between execution and observation activity depicted in Figure 7, or the considerable similarity shown in Figure 8? The authors should address this apparent contradiction and provide a clearer discussion to reconcile these findings.

    1. Reviewer #3 (Public review):

      Summary:

      In this paper, Tang et al report the discovery of a Glycoslyceramide synthase gene, GlcT, which they found in a genetic screen for mutations that generate tumorous growth of stem cells in the gut of Drosophila. The screen was expertly done using a classic mutagenesis/mosaic method. Their initial characterization of the GlcT alleles, which generate endocrine tumors much like mutations in the Notch signaling pathway, is also very nice. Tang et al checked other enzymes in the glycosylceramide pathway and found that the loss of one gene just downstream of GlcT (Egh) gives similar phenotypes to GlcT, whereas three genes further downstream do not replicate the phenotype. Remarkably, dietary supplementation with a predicted GlcT/Egh product, Lactosyl-ceramide, was able to substantially rescue the GlcT mutant phenotype. Based on the phenotypic similarity of the GlcT and Notch phenotypes, the authors show that activated Notch is epistatic to GlcT mutations, suppressing the endocrine tumor phenotype and that GlcT mutant clones have reduced Notch signaling activity. Up to this point, the results are all clear, interesting, and significant. Tang et al then go on to investigate how GlcT mutations might affect Notch signaling, and present results suggesting that GlcT mutation might impair the normal endocytic trafficking of Delta, the Notch ligand. These results (Fig X-XX), unfortunately, are less than convincing; either more conclusive data should be brought to support the Delta trafficking model, or the authors should limit their conclusions regarding how GlcT loss impairs Notch signaling. Given the results shown, it's clear that GlcT affects EE cell differentiation, but whether this is via directly altering Dl/N signaling is not so clear, and other mechanisms could be involved. Overall the paper is an interesting, novel study, but it lacks somewhat in providing mechanistic insight. With conscientious revisions, this could be addressed. We list below specific points that Tang et al should consider as they revise their paper.

      Strengths:

      The genetic screen is excellent.

      The basic characterization of GlcT phenotypes is excellent, as is the downstream pathway analysis.

      Weaknesses:

      (1) Lines 147-149, Figure 2E: here, the study would benefit from quantitations of the effects of loss of brn, B4GalNAcTA, and a4GT1, even though they appear negative.

      (2) In Figure 3, it would be useful to quantify the effects of LacCer on proliferation. The suppression result is very nice, but only effects on Pros+ cell numbers are shown.

      (3) In Figure 4A/B we see less NRE-LacZ in GlcT mutant clones. Are the data points in Figure 4B per cell or per clone? Please note. Also, there are clearly a few NRE-LacZ+ cells in the mutant clone. How does this happen if GlcT is required for Dl/N signaling?

      (4) Lines 222-225, Figure 5AB: The authors use the NRE-Gal4ts driver to show that GlcT depletion in EBs has no effect. However, this driver is not activated until well into the process of EB commitment, and RNAi's take several days to work, and so the author's conclusion is "specifically required in ISCs" and not at all in EBs may be erroneous.

      (5) Figure 5C-F: These results relating to Delta endocytosis are not convincing. The data in Fig 5C are not clear and not quantitated, and the data in Figure 5F are so widely scattered that it seems these co-localizations are difficult to measure. The authors should either remove these data, improve them, or soften the conclusions taken from them. Moreover, it is unclear how the experiments tracing Delta internalization (Fig 5C) could actually work. This is because for this method to work, the anti-Dl antibody would have to pass through the visceral muscle before binding Dl on the ISC cell surface. To my knowledge, antibody transcytosis is not a common phenomenon.

      (6) It is unclear whether MacCer regulates Dl-Notch signaling by modifying Dl directly or by influencing the general endocytic recycling pathway. The authors say they observe increased Dl accumulation in Rab5+ early endosomes but not in Rab7+ late endosomes upon GlcT depletion, suggesting that the recycling endosome pathway, which retrieves Dl back to the cell surface, may be impaired by GlcT loss. To test this, the authors could examine whether recycling endosomes (marked by Rab4 and Rab11) are disrupted in GlcT mutants. Rab11 has been shown to be essential for recycling endosome function in fly ISCs.

      (7) It remains unclear whether Dl undergoes post-translational modification by MacCer in the fly gut. At a minimum, the authors should provide biochemical evidence (e.g., Western blot) to determine whether GlcT depletion alters the protein size of Dl.

      (8) It is unfortunate that GlcT doesn't affect Notch signaling in other organs on the fly. This brings into question the Delta trafficking model and the authors should note this. Also, the clonal marker in Figure 6C is not clear.

      (9) The authors state that loss of UGCG in the mouse small intestine results in a reduced ISC count. However, in Supplementary Figure C3, Ki67, a marker of ISC proliferation, is significantly increased in UGCG-CKO mice. This contradiction should be clarified. The authors might repeat this experiment using an alternative ISC marker, such as Lgr5.

    1. Reviewer #3 (Public review):

      Summary:

      Fleming et al sought to better understand DNAJC7's function in motor neurons as mutations in this gene have been associated with amyotrophic lateral sclerosis (ALS). The research question is relevant and important. The authors use an induced pluripotent stem cell (iPSC) line to derive motor neurons (iMNs) finding that DNAJC7 interacts with RNA-binding proteins (RBP) in wild-type cells and a truncated mutant DNAJC7[R156*] disrupts the RBP, hnRNPU, by promoting its accumulation into insoluble fractions. Given that DNAJC7 is predicted to regulate stress responses, the authors then find that DNAJC7[R156*] expression sensitizes the iMNs to proteosomal stress by disrupting the expression of the key heat stress response regulator, HSF1. These findings support that loss-of-function mutations in DNAJC7 will indeed sensitize motor neurons to proteotoxic stress, potentially driving ALS. The association with RBPs, which routinely are found to be disrupted in ALS, is of interest and warrants further study.

      Strengths:

      (1) The research question is relevant and important. The authors provide interesting data that DNAJC7 mutations impact two important features in ALS, the dysregulation of RNA binding proteins and the sensitivity of motor neurons to proteotoxic stress.

      (2) The authors provide solid data to support their findings and the assays are appropriate.

      Weaknesses:

      (1) The authors rely on a single iPSC line throughout the text, using the same line to make the mutation-carrying cells. iPSCs are highly variable and at minimum 3 lines, typically 5 lines, should be used to define consistent findings. This work would be greatly strengthened if 3 or more lines were used to confirm consistent effects. This is particularly concerning given that iPSCs were differentiated using growth factors versus genetic induction. Growth-factor-based differentiations are more variable.

      (2) The authors argue that HSF1 and its targets are downregulated in sporadic ALS and mutant C9orf72 ALS. The first concern is that these transcriptomics data were derived from cortical tissue which does not contain motor neurons (Pineda et al. 2024 Cell 187: 1971-1989.e1916). The second concern is that the inclusion of C9orf72 mutant tissue is not well justified as (1) this mutation is associated with an upregulation of HSF1 and its targets in patients (Mordes et al, Acta Neuropathol Commun 2018 6(1):55; Lee et al Neuron 2023 111(9):1381-1390) and (2) the C9orf72 mutation is associated with a ALS/FTD spectrum disorder defined by TDP-43 pathology. Disease mechanisms associated with this spectrum disorder may not overlap with traditional ALS which is typically defined by SOD1 pathology.

      (3) As a whole, the findings are mechanistically disjointed, and additional experiments or discussion would help to connect the dots a bit more.

    1. Reviewer #3 (Public review):

      ZSS has been widely used in Traditional Chinese Medicine as a sleep-promoting herb. This study tests the effects of ZSS powder and extracts on AD, PD, and aging, and broad protective effects were revealed in mice.

      However, this work did not include a mechanistic study or target data on ZSS were included, and PK data were also not involved. Mechanisms or targets and PK study are suggested. A human PK study is preferred over mice or rats. E.g. which main active ingredients and the concentration in plasma, in this context, to study the pharmacological mechanisms of ZSS.

    1. Reviewer #3 (Public review):

      Summary:

      The authors are looking for a spatially specific functional brain response to visualise non-invasively with 3T (clinical field strength) MRI. They propose a velocity-nulled weighting to remove signal from draining veins in a submillimeter multiband acquisition.

      Strengths:

      - This manuscript addresses a real need in the cognitive neuroscience community interested in imaging responses in cortical layers in-vivo in humans.<br /> - An additional benefit is the proposed implementation at 3T, a widely available field strength.

      Weaknesses:

      - The comparison in Figure 4 for different b-values shows % signal changes. However, as the baseline signal changes with added diffusion weighting, this is rather uninformative. A plot of t-values against cortical depth would be more insightful.<br /> - Surprisingly, the %-signal change for a b-value of 0 is below 1% for 3/4 participants, even at the cortical surface. This raises some doubts about the task or ROI definition. A finger-tapping task should reliably engage the primary motor cortex, even at 3T, and even in individual participants.<br /> - The double peak patter in the BOLD weighted images in Figure 4 is unexpected given the existing literature on BOLD responses as a function of cortical depth.<br /> - Although I'd like to applaud the authors for their ambition with the connectivity analysis, the low significance threshold used in these maps (z=1,64) leads to concerns about the SNR of the underlying data.

      I remain unconvinced of the conclusion that the developed VN fMRI exhibited layer specificity - the double peak which is taken as a marker of specificity is not absent in the BOLD responses either, and overall BOLD and VN response profiles as a function of cortical depth are quite similar.

    1. Reviewer #3 (Public review):

      In this manuscript, Millard et al. investigate the effects of nicotine on pain sensitivity and peak alpha frequency (PAF) in resting state EEG. To this end, they ran a randomized, double-blind, placebo-controlled experiment involving 62 healthy adults that received either 4 mg nicotine gum (n=29) or placebo (n=33). Prolonged heat and pressure were used as pain models. Resting state EEG and pain intensity (assessed with a visual analog scale) were measured before and after the intervention. Additionally, several covariates (sex at birth, depression and anxiety symptoms, stress, sleep quality, among others) were recorded. Data was analyzed using ANCOVA-equivalent two-wave latent change score models, as well as repeated measures analysis of variance. Results do not show experimentally relevant changes of PAF or pain intensity scores for neither of the prolonged pain models due to nicotine intake.

      The main strengths of the manuscript are its solid conceptual framework and the thorough experimental design. The researchers make a good case in the introduction and discussion for the need to further investigate the association of PAF and pain sensitivity. Furthermore, they proceed to carefully describe every aspect of the experiment in great detail, which is excellent for reproducibility purposes. Finally, they analyze the data from different and provide an extensive report of their results.

      There are relevant weaknesses to highlight. Firstly, authors preregistered the study and the analysis plan, but the preregistration does not contain an estimation of the expected effect sizes or the rationale for the selected the sample size. Furthermore, the authors interpret their results in a way that is not supported by the evidence (which is notorious in the abstract and the first paragraph of the discussion). Even though some of the differences are statistically significant (e.g., global PAF, pain intensity ratings during heat pain), these differences are far from being experimentally or clinically relevant. The effect sizes observed are not sufficiently large to consider that pain sensitivity was modulated by the nicotine intake, which puts into question all the answers to the research questions posed in the study. The authors attempt to nuance this throughout the discussion, but in a way that is not compatible with the main claims.

    1. Reviewer #3 (Public review):

      Summary:

      MerQuaCo is an open-source computational tool developed for quality control in image-based spatial transcriptomics data, with a primary focus on data generated by the Vizgen MERSCOPE platform. The authors analyzed a substantial dataset of 641 fresh-frozen adult mouse brain sections to identify and quantify common imperfections, aiming to replace manual quality assessment with an automated, objective approach, providing standardized data integrity measures for spatial transcriptomics experiments.

      Strengths:

      The manuscript's strengths lie in its timely utility, rigorous empirical validation, and practical contributions to methodology and biological discovery in spatial transcriptomics.

      Weaknesses:

      While MerQuaCo demonstrates utility in large datasets and cross-platform potential, its generalizability and validation require expansion, particularly for non-MERSCOPE platforms and real-world biological impact.

    1. Reviewer #3 (Public review):

      In the report entitled "CXXC-finger protein 1 associates with FOXP3 to stabilize homeostasis and suppressive functions of regulatory T cells", the authors demonstrated that Cxxc1-deletion in Treg cells leads to the development of severe inflammatory disease with impaired suppressive function. Mechanistically, CXXC1 interacts with Foxp3 and regulates the expression of key Treg signature genes by modulating H3K4me3 deposition. Their findings are interesting and significant.

      Comments on revisions:

      In the revised manuscript, the authors have responded well to all the concerns reviewers raised. The manuscript has further improved.

    1. Reviewer #3 (Public review):

      Summary:

      This manuscript investigates the distinct contributions of mPFC→BLA and mPFC→NAc pathways in emotional regulation, with implications for understanding anxiety, exploration, and social preference behaviors. Using Ca2+ imaging, optogenetics, and patch-clamp recording, the authors demonstrate pathway-specific roles in encoding emotional states of opposite valence. They further identify subsets of neurons ("center-ON") with heightened activity under anxiety-inducing conditions. These findings challenge the traditional view of functional similarity between these pathways and provide valuable insights into neural circuit dynamics relevant to emotional disorders.

      The study is well-designed and addresses an important topic, but several methodological and interpretational issues require clarification to strengthen the conclusions.

      Weaknesses:

      Major Weaknesses:

      (1) The manuscript does not clearly and consistently specify the sex of the mice used for behavioral and imaging experiments. Given the known influence of sex on emotional behaviors and neural activity, this omission raises concerns about the generalizability of the findings. The authors should make clear throughout the manuscript whether male, female, or mixed-sex cohorts were used and provide a rationale for their choice. If only one sex was used, the potential limitations of this approach should be explicitly discussed.

      (2) Mice lacking "center-ON" neurons were excluded from analysis, yet the manuscript draws broad conclusions about the encoding of emotional states by mPFC pathways. It is critical to justify this exclusion and discuss how it may limit the generalizability of the findings. The inclusion of data or contextualization for animals without center-ON neurons would strengthen the interpretation.

      (3) The manuscript lacks baseline activity comparisons for mPFC→BLA and mPFC→NAc pathways across subjects. Providing baseline data would contextualize the observed activity changes during behavior testing and help rule out inter-individual variability as a confounding factor.

      (4) Extensive behavioral testing across multiple paradigms may introduce stress and fatigue in the animals, which could confound the induction of emotional states. The authors should describe the measures taken to minimize these effects (e.g., recovery periods, randomized testing order) and discuss their potential impact on the results.

      (5) Grooming is described as a "non-anxiety" behavior, which conflicts with its established role as a stress-relieving behavior that may indicate anxiety. This discrepancy requires clarification, as the distinction is central to the conclusions about the mPFC→BLA pathway's role in differentiating anxiety-related and non-anxiety behaviors.

      (6) While the study highlights pathway-specific neural activity, it lacks a cohesive integration of these findings with the behavioral data. Quantifying the overlap or decorrelation of neuronal activity patterns across tasks would solidify claims about the specialization of mPFC→NAc and mPFC→BLA pathways. Likewise, the discussion should be expanded to place these findings in light of prior studies that have probed the roles of these pathways in social/emotion/valence-related behaviors.

      Minor Weaknesses:

      (1) The manuscript does not explicitly state whether the same mice were used across all behavioral assays. This information is critical for evaluating the validity of group comparisons. Additionally, more detail on sample sizes per assay would improve the manuscript's transparency.

      (2) In Figure 2G, the difference between BLA and NAc activity during exploratory behaviors (sniffing) is difficult to discern. Adjusting the scale or reformatting the figure would better illustrate the findings.

      (3) While the characteristics of the first social stimulus (M1) are specified, there is no information about the second social stimulus (M2). This omission makes it difficult to fully interpret the findings from the three-chamber test.

      (4) The methods section lacks detailed information about statistical approaches and animal selection criteria. Explicitly outlining these procedures would improve reproducibility and clarity.

    1. Reviewer #3 (Public review):

      Summary:

      Modeling and estimating sequence context biases during B cell somatic hypermutation is important for accurately modeling B cell evolution to better understand responses to infection and vaccination. Sung et al. introduce new statistical models that capture a wider sequence context of somatic hypermutation with a comparatively small number of additional parameters. They demonstrate their model's performance with rigorous testing across multiple subjects and datasets. Prior work has captured the mutation biases of fixed 3-, 5-, and 7-mers, but each of these expansions has significantly more parameters. The authors developed a machine-learning-based approach to learn these biases using wider contexts with comparatively few parameters.

      Strengths:

      Well-motivated and defined problem. Clever solution to expand nucleotide context. Complete separation of training and test data by using different subjects for training vs testing. Release of open-source tools and scripts for reproducibility.

      Weaknesses:

      This study could be improved with better descriptions of dataset sequencing technology, sequencing depth, etc but this is a minor weakness.

    1. Reviewer #3 (Public review):

      Summary:

      The authors investigated the role of secretory leukocyte protease inhibitors (SLPI) in developing Lyme disease in mice infected with Borrelia burgdorferi. Using a combination of histological, gene expression, and flow cytometry analyses, they demonstrated significantly higher bacterial burden and elevated neutrophil and macrophage infiltration in SLPI-deficient mouse ankle joints. Furthermore, they also showed direct interaction of SLPI with B. burgdorferi, which likely depletes the local environment of SLPI and causes excessive protease activity. These results overall suggest ankle tissue inflammation in B. burgdorferi-infected mice is driven by unchecked protease activity.

      Strengths:

      Utilizing a comprehensive suite of techniques, this is the first study showing the importance of anti-protease-protease balance in the development of periarticular joint inflammation in Lyme disease.

      Weaknesses:

      Due to the limited sample availability, the authors investigated the serum level of SLPI in both Lyme arthritis patients and patients with earlier disease manifestations. This limitation is thoroughly discussed in the manuscript.

      Comments on revised version:

      I thank the authors for considering my comments carefully.

    1. Reviewer #3 (Public review):

      PspA, a key regulator in the phage shock protein system, functions as part of the envelope stress response system in bacteria, preventing membrane depolarization and ensuring the envelope stability. This protein has been associated in the Quorum Sensing network and biofilm formation. (Moscoso M., Garcia E., Lopez R. 2006. Biofilm formation by Streptococcus pneumoniae: role of choline, extracellular DNA, and capsular polysaccharide in microbial accretion. J. Bacteriol. 188:7785-7795; Vidal JE, Ludewick HP, Kunkel RM, Zähner D, Klugman KP. The LuxS-dependent quorum-sensing system regulates early biofilm formation by Streptococcus pneumoniae strain D39. Infect Immun. 2011 Oct;79(10):4050-60.)

      It is interesting and very well-developed.

      (1) Could the authors develop experiments about the relationship between Quorum Sensing and this protein?

      (2) It would be interesting to analyze the link to phage infection and heat stress in relation to Quorum. The authors could study QS regulators or AI2 molecules.

      (3) Include the proteins or genes in a table or figure from lytic phage Kp11 (GenBank: ON148528.1).

    1. Reviewer #3 (Public review):

      Summary:

      This manuscript seeks to understand how nerve injury-induced signaling to the nucleus is influenced, and it establishes a new location where these principles can be studied. By identifying and mapping specific bifurcated neuronal innervations in the Drosophila larvae, and using laser axotomy to localize the injury, the authors find that sparing a branch of a complex muscular innervation is enough to impair Wallenda-puc (analogous to DLK-JNK-cJun) signaling that is known to promote regeneration. It is only when all connections to the target are disconnected that cJun-transcriptional activation occurs.

      Overall, this is a thorough and well-performed investigation of the mechanism of spared-branch influence on axon injury signaling. The findings on control of wnd are important because this is a very widely used injury signaling pathway across species and injury models. The authors present detailed and carefully executed experiments to support their conclusions. Their effort to identify the control mechanism is admirable and will be of aid to the field as they continue to try to understand how to promote better regeneration of axons.

      Strengths:

      The paper does a very comprehensive job of investigating this phenomenon at multiple locations and through both pinpoint laser injury as well as larger crush models. They identify a non-hiw based restraint mechanism of the wnd-puc signaling axis that presumably is originating from the spared terminal. They also present a large list of tests they performed to identify the actual restraint mechanism from the spared branch, which has ruled out many of the most likely explanations. This is an extremely important set of information to report, to guide future investigators in this and other model organisms on mechanisms by which regeneration signaling is controlled (or not).

      Weaknesses:

      While there are many questions raised by these results that are not answered here, including the pathways upstream and downstream of DLK and how the binary switch control of DLK/puc signaling is executed, the model built in this manuscript is valuable to future work going after these important questions.

      Because the conclusions of the paper are focused on a single (albeit well validated) reporter in different types of motor neurons, it is hard to determine whether the mechanism of spared branch inhibition of regeneration requires wnd-puc (DLK/cJun) signaling, or whether this is a binary/threshold response in all contexts (for example, sensory axons or interneurons). However, the author points out in the response that there are sensory neuron examples where a spared connection does not block DLK activation. As such, it may not be a universal mechanism but could provide a model for better understanding of DLK control across different contexts.

      Comments on revisions:

      The new panels in Figure 1E do not have Y-axis labels. (mean puc-lacZ intensity?)

    1. Reviewer #3 (Public review):

      Summary:

      The authors identified RBM20 expression in neural tissues using cell type-specific transcriptomic analysis. This discovery was further validated through in vitro and in vivo approaches, including RNA fluorescent in situ hybridization (FISH), open-source datasets, immunostaining, western blotting, and gene-edited RBM20 knockout (KO) mice. CLIP-seq and RiboTRAP data demonstrated that RBM20 regulates common targets in both neural and cardiac tissues, while also modulating tissue-specific targets. Furthermore, the study revealed that neuronal RBM20 governs long pre-mRNAs encoding synaptic proteins.

      Strengths:

      • Utilization of a large dataset combined with experimental evidence to identify and validate RBM20 expression in neural tissues.<br /> • Global and tissue-specific RBM20 KO mouse models provide robust support for RBM20 localization and expression.<br /> • Employing heart tissue as a control highlights the unique findings in neural tissues.

      Weaknesses:

      • Lack of physiological functional studies to explore RBM20's role in neural tissues.<br /> • Data quality requires improvement for stronger conclusions.

      Comments on revisions:

      The authors have effectively addressed most of my concerns, which has significantly improved the quality and reliability of the data. While sufficient functional data were not provided, the current findings offer valuable and novel insights into the expression of RBM20 in neurons. I have no further concerns.

    1. Reviewer #3 (Public review):

      Summary:

      The authors describe the abnormal contractile function and cellular electrophysiology in an iPSC model of atrial myocytes with a titin missense variant. They provide contractility data by sarcomere length imaging, calcium imaging, and voltage clamp of the repolarizing current iKs. While each of the findings is separately interesting, the paper comes across as too descriptive because there is no merging of the data to support a cohesive mechanistic story/statement, especially from the electrophysiological standpoint. There is definitely not enough support for the title "A Titin Missense Variant Causes Atrial Fibrillation", since there is no strong causative evidence at all. There is some interesting clinical data regarding the variant of interest and its association with HF hospitalization, which may lead to future important discoveries regarding atrial fibrillation.

      Strengths:

      The manuscript is well written and there is a wide range of experimental techniques to probe this atrial fibrillation model.

      Weaknesses:

      (1) While the clinical data is interesting, it is extremely important to rule out heart failure with preserved EF as a confounder. HFpEF leads to AF due to increased atrial remodeling, so the fact that patients with this missense variant have increased HF hospitalizations does not necessarily directly support the variant as causative of AF. It could be that the variant is actually associated directly with HFpEF instead, and this needs to be addressed and corrected in the analyses.

      (2) All of the contractility and electrophysiologic data should be done with pacing at the same rate in both control and missense variant groups, to control for the effect of cycle length on APD and calcium loading. A claim of shorter APD cannot be claimed when the firing rate of one set of cells is much faster than the other, since shorter APD is to be expected with a faster rate. Similarly, contractility is affected by diastolic interval because of the influence of SR calcium content on the myocyte power stroke. So the cells need to be paced at the same rate in the IonOptix for any direct comparison of contractility. The authors should familiarize themselves with the concept of electrical restitution.

      (3) It is interesting that the firing rate of the myocytes is faster with the missense variant. This should lead to a hypothesis and investigation of abnormal automaticity or triggered activity, which may also explain the increased contractility since all these mechanisms are related to the calcium clock and calcium loading of the SR. See #2 above for suggestions on how to adequately probe calcium handling. Such an investigation into impulse initiation mechanisms would be very powerful in supporting the primary statement of the paper since these are actual mechanisms thought to cause AF.

      (4) The claim of shortened APD without correcting for cycle length is problematic. However, the general concept of linking shortened APD in isolated cells alone to AF causation is more problematic. To have a setup for reentry, there must be a gradient of APD from short to long, and this can only be demonstrated at the tissue level, not really at the cellular level, so reentry should not be invoked here. If shortened APD is demonstrated with correction of the cycle length problem, restitution curves can be made showing APD shortening at different cycle lengths. If restitution is abnormal (i.e. the APD does not shorten normally in relation to the diastolic interval), this may lead to triggered activity which is an arrhythmogenic mechanism. This would also tie in well with the finding of abnormally elevated iKs current since iKs is a repolarizing current directly responsible for restitution.

    1. Reviewer #3 (Public review):

      Summary:

      Sarkar, Bhandari, Jaiswal, and colleagues establish a suite of quantitative and genetic tools to use Drosophila melanogaster as a model metazoan organism to study polyphosphate (polyP) biology. By adapting biochemical approaches for use in D. melanogaster, they identify a window of increased polyP levels during development. Using genetic tools, they find that depleting polyP from the cytoplasm alters the timing of metamorphosis, accelerating eclosion. By adapting subcellular imaging approaches for D. melanogaster, they observe polyP in the nucleolus of several cell types. They further demonstrate that polyP localizes to cytoplasmic puncta in hemocytes, and further that depleting polyP from the cytoplasm of hemocytes impairs hemolymph clotting. Together, these findings establish D. melanogaster as a tractable system for advancing our understanding of polyP in metazoans.

      Strengths:

      (1) The FLYX system, combining cell type and compartment-specific expression of ScPpx1, provides a powerful tool for the polyP community.

      (2) The finding that cytoplasmic polyP levels change during development and affect the timing of metamorphosis is an exciting first step in understanding the role of polyP in metazoan development, and possible polyP-related diseases.

      (3) Given the significant existing body of work implicating polyP in the human blood clotting cascade, this study provides compelling evidence that polyP has an ancient role in clotting in metazoans.

      Limitations:

      (1) While the authors demonstrate that HA-ScPpx1 protein localizes to the target organelles in the various FLYX constructs, the capacity of these constructs to deplete polyP from the different cellular compartments is not shown. This is an important control to both demonstrate that the GTS-PPBD labeling protocol works, and also to establish the efficacy of compartment-specific depletion. While not necessary to do this for all the constructs, it would be helpful to do this for the cyto-FLYX and nuc-FLYX.

      (2) The cell biological data in this study clearly indicates that polyP is enriched in the nucleolus in multiple cell types, consistent with recent findings from other labs, and also that polyP affects gene expression during development. Given that the authors also generate the Nuc-FLYX construct to deplete polyP from the nucleus, it is surprising that they test how depleting cytoplasmic but not nuclear polyP affects development. However, providing these tools is a service to the community, and testing the phenotypic consequences of all the FLYX constructs may arguably be beyond the scope of this first study.

    1. Reviewer #3 (Public review):

      This study provides insights into the growth kinetics of a diverse collection of Streptococcus pneumoniae, identifying capsule and lineage differences. It was not able to identify any specific loci from the genome-wide association studies (GWAS) that were associated with the growth features. It does provide a useful study linking phenotypic data with large-scale genomic population data. The methods for the large part were appropriately written in sufficient detail, and data analysis was performed with rigour. The interpretation of the results was supported by the data, although some additional explanation of the significance of e.g. ancestral state reconstruction would be useful. Efforts were made to make the underlying data fully accessible to the readers although some of the supplementary material could be formatted and explained a bit better.

    1. Reviewer #3 (Public review):

      Summary

      This manuscript outlines a series of very exciting and game-changing experiments examining the role of peripheral MORs in OIRD. The authors outline experiments that demonstrate a peripherally restricted MOR antagonist (NLX Methiodide) can rescue fentanyl-induced respiratory depression and this effect coincides with a lack of conditioned place aversion. This approach would be a massive boon to the OUD community, as there are a multitude of clinical reports showing that naloxone rescue post fentanyl over-intoxication is more aversive than the potential loss-of-life to the individuals involved. This important study reframes our understanding of successful overdose rescue with a potential for reduced aversive withdrawal effects.

      Strengths:

      Strengths include the plethora of approaches arriving at the same general conclusion, the inclusion of both sexes, and the result that a peripheral approach for OIRD rescue may side-step severe negative withdrawal symptoms of traditional NLX rescue.

      Weaknesses:

      All weaknesses were addressed.

    1. Reviewer #3 (Public review):

      Summary:

      To understand the specificity of age-dependent changes in the human neocortex, this paper investigated the electrophysiological and morphological characteristics of pyramidal cells in a wide age range from infants to the elderly.

      The results show that some electrophysiological characteristics change with age, particularly in early childhood. In contrast, the larger morphological structures, such as the spatial extent and branching frequency of dendrites, remained largely stable from infancy to old age. On the other hand, the shape of dendritic spines is considered immature in infancy, i.e., the proportion of mushroom-shaped spines increases with age.

      Strengths:

      Whole-cell recordings and intracellular staining of pyramidal cells in defined areas of the human neocortex allowed the authors to compare quantitative parameters of electrophysiological and morphological properties between finely divided age groups.

      They succeeded in finding symmetrical changes specific to both infants and the elderly, and asymmetrical changes specific to either infants or the elderly. The similarity of pyramidal cell characteristics between areas is unexpected.

      Weaknesses:

      Human L2/3 pyramidal cells are thought to be heterogeneous, as L2/3 has expanded to a high degree during the evolution from rodents to humans. However, the diversity (subtyping) is not revealed in this paper.

      Comments on revisions:

      I believe that the current version has been sufficiently revised based on my comments.

    1. Reviewer #3 (Public Review):

      Summary:

      The authors report a new version of the iSuRe-Cre approach, which was originally developed by Rui Benedito's group in Spain (https://doi.org/10.1038/s41467-019-10239-4). Shi et al claim that their approach shows reduced leakiness compared to the iSuRe-Cre line. Shi et al elaborate strongly about the leakiness of iSuRe-Cre mice, although leakiness is rather minor according to the original publication and the senior author of the study wrote in a review a few years ago that there is no leakiness (https://doi.org/10.1016/j.jbc.2021.100509). Furthermore, a new R26-roxCre-tdT mouse line was established after extensive testing, which enables efficient expression of the Cre recombinase after activation of the Dre recombinase.

      Strengths:

      The authors carefully evaluated the efficiency and leakiness of the new strains and demonstrated the applicability by marking peri-central hepatocytes in an intersectional genetics approach, amongst others. I can only find very few weaknesses in the paper, which represents the result of an enormous effort. Carefully conducted technical studies have considerable value. However, I would have preferred to see a study, which uses the wonderful new tools to address a major biological question, rather than a primarily technical report, which describes the ongoing efforts to further improve Cre and Dre recombinase-mediated recombination.

      Weaknesses:

      Very high levels of Cre expression may cause toxic effects as previously reported for the hearts of Myh6-Cre mice. Thus, it seems sensible to test for unspecific toxic effects, which may be done by bulk RNA-seq analysis, cell viability, and cell proliferation assays. It should also be analyzed whether the combination of R26-roxCre-tdT with the Tnni3-Dre allele causes cardiac dysfunction, although such dysfunctions should be apparent from potential changes in gene expression.

      The R26-GFP or R26-tdT reporters, Alb-roxCre1-tdT, Cdh5-roxCre4-tdT, Alb-roxCre7-GFP, and Cdh5-roxCre10-GFP demonstrate no leakiness without Dre-rox recombination (Figure S1-S2). Is there any leakiness when the inducible DreER allele is introduced but no tamoxifen treatment is applied? This should be documented. The same also applies to loxCre mice.

      The enhanced efficiency of loxCre and roxCre systems holds promise for reducing the necessary tamoxifen dosage, potentially reducing toxicity and side effects. In Figure 6, the author demonstrates an enhanced recombination efficiency of loxCre mice, which makes it possible to achieve efficient deletion of Ctnnb1 with a single dose of tamoxifen, whereas a conventional driver (Alb-CreER) requires five dosages. It would be very helpful to include a dose-response curve for determining the minimum dosage required in Alb-CreER; R26-loxCre-tdT; Ctnnb1flox/flox mice for efficient recombination.

      In the liver panel of Figure 4F, tdT signals do not seem to colocalize with the VE-cad signals, which is odd. Is there any compelling explanation?

      The authors claim that "virtually all tdT+ endothelial cells simultaneously expressed YFP/mCFP" (right panel of Figure 5D). Well, it seems that the abundance of tdT is much lower compared to YFP/mCFP. If the recombination of R26-Confetti was mainly triggered by R26-loxCre-tdT, the expression of tdT and YFP/mCFP should be comparable. This should be clarified.

      In several cases, the authors seem to have mixed up "R26-roxCre-tdT" with "R26-loxCre-tdT". There are errors in #251 and #256. Furthermore, in the passage from line #278 to #301. In the lines #297 and #300 it should probably read "Alb-CreER; R26-loxCre-tdT;Ctnnb1flox/flox"" rather than "Alb-CreER;R26-tdT2;Ctnnb1flox/flox".

    1. Reviewer #3 (Public review):

      Summary:

      One goal of this paper is to introduce a new approach for highly accurate decoding of finger movements from human magnetoencephalography data via dimension reduction of a "multi-scale, hybrid" feature space. Following this decoding approach, the authors aim to show that early skill learning involves "contextualization" of the neural coding of individual movements, relative to their position in a sequence of consecutive movements. Furthermore, they aim to show that this "contextualization" develops primarily during short rest periods interspersed with skill training, and correlates with a performance metric which the authors interpret as an indicator of offline learning.

      Strengths:

      A strength of the paper is the innovative decoding approach, which achieves impressive decoding accuracies via dimension reduction of a "multi-scale, hybrid space". This hybrid-space approach follows the neurobiologically plausible idea of concurrent distribution of neural coding across local circuits as well as large-scale networks. A further strength of the study is the large number of tested dimension reduction techniques and classifiers.

      Weaknesses:

      A clear weakness of the paper lies in the authors' conclusions regarding "contextualization". Several potential confounds, which partly arise from the experimental design (mainly the use of a single sequence) and which are described below, question the neurobiological implications proposed by the authors, and provide a simpler explanation of the results. Furthermore, the paper follows the assumption that short breaks result in offline skill learning, while recent evidence, described below, casts doubt on this assumption.

      Specifically:<br /> The authors interpret the ordinal position information captured by their decoding approach as a reflection of neural coding dedicated to the local context of a movement (Figure 4). One way to dissociate ordinal position information from information about the moving effectors is to train a classifier on one sequence, and test the classifier on other sequences that require the same movements, but in different positions (Kornysheva et al., Neuron 2019). In the present study, however, participants trained to repeat a single sequence (4-1-3-2-4). As a result, ordinal position information is potentially confounded by the fixed finger transitions around each of the two critical positions (first and fifth press). Across consecutive correct sequences, the first keypress in a given sequence was always preceded by a movement of the index finger (=last movement of the preceding sequence), and followed by a little finger movement. The last keypress, on the other hand, was always preceded by a ring finger movement, and followed by an index finger movement (=first movement of the next sequence). Figure 4 - supplement 2 shows that finger identity can be decoded with high accuracy (>70%) across a large time window around the time of the keypress, up to at least {plus minus}100 ms (and likely beyond, given that decoding accuracy is still high at the boundaries of the window depicted in that figure). This time window approaches the keypress transition times in this study. Given that distinct finger transitions characterized the first and fifth keypress, the classifier could thus rely on persistent (or "lingering") information from the preceding finger movement, and/or "preparatory" information about the subsequent finger movement, in order to dissociate the first and fifth keypress. Currently, the manuscript provides little evidence that the context information captured by the decoding approach is more than a by-product of temporally extended, and therefore overlapping, but independent neural representations of consecutive keypresses that are executed in close temporal proximity - rather than a neural representation dedicated to context.<br /> During the review process, the authors pointed out that a "mixing" of temporally overlapping information from consecutive keypresses, as described above, should result in systematic misclassifications and therefore be detectable in the confusion matrices in Figures 3C and 4B, which indeed do not provide any evidence that consecutive keypresses are systematically confused. However, such absence of evidence (of systematic misclassification) should be interpreted with caution, and, of course, provides no evidence of absence. The authors also pointed out that such "mixing" would hamper the discriminability of the two ordinal positions of the index finger, given that "ordinal position 5" is systematically followed by "ordinal position 1". This is a valid point which, however, cannot rule out that "contextualization" nevertheless reflects the described "mixing".

      During the review process, the authors responded to my concern that training of a single sequence introduces the potential confound of "mixing" described above, which could have been avoided by training on several sequences, as in Kornysheva et al. (Neuron 2019), by arguing that Day 2 in their study did include control sequences. However, the authors' findings regarding these control sequences are fundamentally different from the findings in Kornysheva et al. (2019), and do not provide any indication of effector-independent ordinal information in the described contextualization - but, actually, the contrary. In Kornysehva et al. (Neuron 2019), ordinal, or positional, information refers purely to the rank of a movement in a sequence. In line with the idea of competitive queuing, Kornysheva et al. (2019) have shown that humans prepare for a motor sequence via a simultaneous representation of several of the upcoming movements, weighted by their rank in the sequence. Importantly, they could show that this gradient carries information that is largely devoid of information about the order of specific effectors involved in a sequence, or their timing, in line with competitive queuing. They showed this by training a classifier to discriminate between the five consecutive movements that constituted one specific sequence of finger movements (five classes: 1st, 2nd, 3rd, 4th, 5th movement in the sequence) and then testing whether that classifier could identify the rank (1st, 2nd, 3rd, etc) of movements in another sequence, in which the fingers moved in a different order, and with different timings. Importantly, this approach demonstrated that the graded representations observed during preparation were largely maintained after this cross-decoding, indicating that the sequence was represented via ordinal position information that was largely devoid of information about the specific effectors or timings involved in sequence execution. This result differs completely from the findings in the current manuscript. Dash et al. report a drop in detected ordinal position information (degree of contextualization in figure 5C) when testing for contextualization in their novel, untrained sequences on Day 2, indicating that context and ordinal information as defined in Dash et al. is not at all devoid of information about the specific effectors involved in a sequence. In this regard, a main concern in my public review, as well as the second reviewer's public review, is that Dash et al. cannot tell apart, by design, whether there is truly contextualization in the neural representation of a sequence (which they claim), or whether their results regarding "contextualization" are explained by what they call "mixing" in their author response, i.e., an overlap of representations of consecutive movements, as suggested as an alternative explanation by Reviewer 2 and myself.

      Such temporal overlap of consecutive, independent finger representations may also account for the dynamics of "ordinal coding"/"contextualization", i.e., the increase in 2-class decoding accuracy, across Day 1 (Figure 4C). As learning progresses, both tapping speed and the consistency of keypress transition times increase (Figure 1), i.e., consecutive keypresses are closer in time, and more consistently so. As a result, information related to a given keypress is increasingly overlapping in time with information related to the preceding and subsequent keypresses. The authors seem to argue that their regression analysis in Figure 5 - figure supplement 3 speaks against any influence of tapping speed on "ordinal coding" (even though that argument is not made explicitly in the manuscript). However, Figure 5 - figure supplement 3 shows inter-individual differences in a between-subject analysis (across trials, as in panel A, or separately for each trial, as in panel B), and, therefore, says little about the within-subject dynamics of "ordinal coding" across the experiment. A regression of trial-by-trial "ordinal coding" on trial-by-trial tapping speed (either within-subject, or at a group-level, after averaging across subjects) could address this issue. Given the highly similar dynamics of "ordinal coding" on the one hand (Figure 4C), and tapping speed on the other hand (Figure 1B), I would expect a strong relationship between the two in the suggested within-subject (or group-level) regression. Furthermore, learning should increase the number of (consecutively) correct sequences, and, thus, the consistency of finger transitions. Therefore, the increase in 2-class decoding accuracy may simply reflect an increasing overlap in time of increasingly consistent information from consecutive keypresses, which allows the classifier to dissociate the first and fifth keypress more reliably as learning progresses, simply based on the characteristic finger transitions associated with each. In other words, given that the physical context of a given keypress changes as learning progresses - keypresses move closer together in time, and are more consistently correct - it seems problematic to conclude that the mental representation of that context changes. To draw that conclusion, the physical context should remain stable (or any changes to the physcial context should be controlled for).

      A similar difference in physical context may explain why neural representation distances ("differentiation") differ between rest and practice (Figure 5). The authors define "offline differentiation" by comparing the hybrid space features of the last index finger movement of a trial (ordinal position 5) and the first index finger movement of the next trial (ordinal position 1). However, the latter is not only the first movement in the sequence, but also the very first movement in that trial (at least in trials that started with a correct sequence), i.e., not preceded by any recent movement. In contrast, the last index finger of the last correct sequence in the preceding trial includes the characteristic finger transition from the fourth to the fifth movement. Thus, there is more overlapping information arising from the consistent, neighbouring keypresses for the last index finger movement, compared to the first index finger movement of the next trial. A strong difference (larger neural representation distance) between these two movements is, therefore, not surprising, given the task design, and this difference is also expected to increase with learning, given the increase in tapping speed, and the consequent stronger overlap in representations for consecutive keypresses. Furthermore, initiating a new sequence involves pre-planning, while ongoing practice relies on online planning (Ariani et al., eNeuro 2021), i.e., two mental operations that are dissociable at the level of neural representation (Ariani et al., bioRxiv 2023).

      A further complication in interpreting the results stems from the visual feedback that participants received during the task. Each keypress generated an asterisk shown above the string on the screen. It is not clear why the authors introduced this complicating visual feedback in their task, besides consistency with their previous studies. The resulting systematic link between the pattern of visual stimulation (the number of asterisks on the screen) and the ordinal position of a keypress makes the interpretation of "contextual information" that differentiates between ordinal positions difficult. During the review process, the authors reported a confusion matrix from a classification of asterisks position based on eye tracking data recorded during the task, and concluded that the classifier performed at chance level and gaze was, thus, apparently not biased by the visual stimulation. However, the confusion matrix showed a huge bias that was difficult to interpret (a very strong tendency to predict one of the five asterisk positions, despite chance-level performance). Without including additional information for this analysis (or simply the gaze position as a function of the number of astersisk on the screen) in the manuscript, this important control anaylsis cannot be properly assessed, and is not available to the public.

      The authors report a significant correlation between "offline differentiation" and cumulative micro-offline gains. However, this does not address the question whether there is a trial-by-trial relation between the degree of "contextualization" and the amount of micro-offline gains - i.e., the question whether performance changes (micro-offline gains) are less pronounced across rest periods for which the change in "contextualization" is relatively low. The single-subject correlation between contextualization changes "during" rest and micro-offline gains (Figure 5 - figure supplement 4) addresses this question, however, the critical statistical test (are correlation coefficients significantly different from zero) is not included. Given the displayed distribution, it seems unlikely that correlation coefficients are significantly above zero.

      The authors follow the assumption that micro-offline gains reflect offline learning. However, there is no compelling evidence in the literature, and no evidence in the present manuscript, that micro-offline gains (during any training phase) reflect offline learning. Instead, emerging evidence in the literature indicates that they do not (Das et al., bioRxiv 2024), and instead reflect transient performance benefits when participants train with breaks, compared to participants who train without breaks, however, these benefits vanish within seconds after training if both groups of participants perform under comparable conditions (Das et al., bioRxiv 2024). During the review process, the authors argued that differences in the design between Das et al. (2024) on the one hand (Experiments 1 and 2), and the study by Bönstrup et al. (2019) on the other hand, may have prevented Das et al. (2024) from finding the assumed (lasting) learning benefit by micro-offline consolidation. However, the Supplementary Material of Das et al. (2024) includes an experiment (Experiment S1) whose design closely follows the early learning phase of Bönstrup et al. (2019), and which, nevertheless, demonstrates that there is no lasting benefit of taking breaks for the acquired skill level, despite the presence of micro-offline gains.

      Along these lines, the authors' claim, based on Bönstrup et al. 2020, that "retroactive interference immediately following practice periods reduces micro-offline learning", is not supported by that very reference. Citing Bönstrup et al. (2020), "Regarding early learning dynamics (trials 1-5), we found no differences in microscale learning parameters (micro-online/offline) or total early learning between both interference groups." That is, contrary to Dash et al.'s current claim, Bönstrup et al. (2020) did not find any retroactive interference effect on the specific behavioral readout (micro-offline gains) that the authors assume to reflect consolidation.

      The authors conclude that performance improves, and representation manifolds differentiate, "during" rest periods (see, e.g., abstract). However, micro-offline gains (as well as offline contextualization) are computed from data obtained during practice, not rest, and may, thus, just as well reflect a change that occurs "online", e.g., at the very onset of practice (like pre-planning) or throughout practice (like fatigue, or reactive inhibition). That is, the definition of micro-offline gains (as well as offline contextualization) conflates online and "offline" processes. This becomes strikingly clear in the recent Nature paper by Griffin et al. (2025), who computed micro-offline gains as the difference in average performance across the first five sequences in a practice period (a block, in their terminology) and the last five sequences in the previous practice period. Averaging across sequences in this way minimises the chance to detect online performance changes, and inflates changes in performance "offline". The problem that "offline" gains (or contextualization) is actually computed from data entirely generated online, and therefore subject to processes that occur online, is inherent in the very definition of micro-offline gains, whether, or not, they computed from averaged performance.

      A simple control analysis based on shuffled class labels could lend further support to the authors' complex decoding approach. As a control analysis that completely rules out any source of overfitting, the authors could test the decoder after shuffling class labels. Following such shuffling, decoding accuracies should drop to chance-level for all decoding approaches, including the optimized decoder. This would also provide an estimate of actual chance-level performance (which is informative over and beyond the theoretical chance level). During the review process, the authors reported this analysis to the reviewers. Given that readers may consider following the presented decoding approach in their own work, it would have been important to include that control analysis in the manuscript to convince readers of its validity.

      Furthermore, the authors' approach to cortical parcellation raises questions regarding the information carried by varying dipole orientations within a parcel (which currently seems to be ignored?) and the implementation of the mean-flipping method (given that there are two dimensions - space and time - it is unclear what the authors refer to when they talk about the sign of the "average source", line 477).

    1. Reviewer #3 (Public review):

      Shi et al describe a new set of tools to facilitate Cre or Dre-recombinase-mediated recombination in mice. The strategies are not completely novel but have been pursued previously by the lab, which is world-leading in this field, and by others. The authors report a new version of the iSuRe-Cre approach, which was originally developed by Rui Benedito's group in Spain. Shi et al describe that their approach shows reduced leakiness compared to the iSuRe-Cre line. Furthermore, a new R26-roxCre-tdT mouse line was established after extensive testing, which enables efficient expression of the Cre recombinase after activation of the Dre recombinase. The authors carefully evaluated efficiency and leakiness of the new line and demonstrated the applicability by marking peri-central hepatocytes in an intersectional genetics approach. The paper represents the result of enormous, carefully executed efforts. Although I would have preferred to see a study, which uses the wonderful new tools to address a major biological question, carefully conducted technical studies have a considerable value for the scientific community, justifying publication.

      It seems very likely that the new mouse lines generated in this study will enhance the precision of genetic manipulation in distinct cell types and greatly facilitate future work in numerous laboratories. The authors expertly have eradicated weaknesses from the initial submission. One minor issue remains. The authors did not investigate potential toxic effects that might be caused by high level expression of a combination of "foreign" genes such as recombinases and fluorescence reporters. The authors refer to published studies about toxic effects, speculating that they can only be prevented by removing recombinases in an additional step. Although this is a valid argument, I would have appreciated to see an assessment of putative toxic effects by RNA-sequencing, since different combinations of recombinases and fluorescence reporters sometimes can generate unexpected effects. However, this minor issue does not compromise the value of this important study.

    1. Reviewer #3 (Public review):

      Nucleus HVC is critical both for song production as well as learning and arguably, sitting at the top of the song control system, is the most critical node in this circuit receiving a multitude of inputs and sending precisely timed commands that determine the temporal structure of song. The complexity of this structure and its underlying organization seem to become more apparent with each experimental manipulation, and yet our understanding of the underlying circuit organization remains relatively poorly understood. In this study, Trusel and Roberts use classic whole-cell patch clamp techniques in brain slices coupled with optogenetic stimulation of select inputs to provide a careful characterization and quantification of synaptic inputs into HVC. By identifying individual projection neurons using retrograde tracer injections combined with pharmacological manipulations, they classify monosynaptic inputs onto each of the three main classes of glutamatergic projection neurons in HVC (RA-, Area X- and Av-projecting neurons). This study is remarkable in the amount of information that it generates, and the tremendous labor involved for each experiment, from the expression of opsins in each of the target inputs (Uva, NIf, mMAN, and Av), the retrograde labelling of each type of projection neuron, and ultimately the optical stimulation of infected axons while recording from identified projection neurons. Taken together, this study makes an important contribution to increasing our identification, and ultimately understanding, of the basic synaptic elements that make up the circuit organization of HVC, and how external inputs, which we know to be critical for song production and learning, contribute to the intrinsic computations within this critic circuit.

      This study is impressive in its scope, rigorous in its implementation, and thoughtful regarding its limitations. The manuscript is well-written, and I appreciate the clarity with which the authors use our latest understanding of the evolutionary origins of this circuit to place these studies within a larger context and their relevance to the study of vocal control, including human speech. My comments are minor and primarily about legibility, clarification of certain manipulations, and organization of some of the summary figures.

    1. Reviewer #3 (Public review):

      Summary:

      This manuscript works with a hypothesis where the overall m6A methylation levels in cells is influenced by mRNA metabolism (sub-cellular localization and decay). The basic assumption is that m6A causes Mrna decay and this happens in the cytoplasm. They go on to experimentally test their model to confirm its predictions. This is confirmed by sub-cellular fractionation experiments which shows high m6A levels in the nuclear RNA. Nuclear localized RNAs have higher methylation. Using a heat shock model, they demonstrate that RNAs with increased nuclear localization or transcription, are methylated at higher levels. Their overall argument is that changes in m6A levels is rather determined by passive processes that are influenced by RNA processing/metabolism. However, it should be considered that erasers have their roles under specific environments (early embryos or germline) and are not modelled by the cell culture systems used here.

      Strengths:

      This is a thought-provoking series of experiments that challenge the idea that active mechanisms of recruitment or erasure are major determinants for m6A distribution and levels.

      Comments on revisions:

      The authors have done a good job with the revision.

    1. Reviewer #3 (Public review):

      Summary:

      This work presents the development, characterization and use of new thin microendoscopes (500µm diameter) whose accessible field of view has been extended by the addition of a corrective optical element glued to the entrance face. Two microendoscopes of different lengths (6.4mm and 8.8mm) have been developed, allowing imaging of neuronal activity in brain regions >4mm deep. An alternative solution to increase the field of view could be to add an adaptive optics loop to the microscope to correct the aberrations of the GRIN lens. The solution presented in this paper does not require any modification of the optical microscope and can therefore be easily accessible to any neuroscience laboratory performing optical imaging of neuronal activity.

      Strengths:

      (1) The paper is generally clear and well written. The scientific approach is well structured and numerous experiments and simulations are presented to evaluate the performance of corrected microendoscopes. In particular, we can highlight several consistent and convincing pieces of evidence for the improved performance of corrected microendoscopes:

      - PSFs measured with corrected microendoscopes 75µm from the centre of the FOV show a significant reduction in optical aberrations compared to PSFs measured with uncorrected microendoscopes.

      - Morphological imaging of fixed brain slices shows that optical resolution is maintained over a larger field of view with corrected microendoscopes compared to uncorrected ones, allowing neuronal processes to be revealed even close to the edge of the FOV.

      - Using synthetic calcium data, the authors showed that the signals obtained with the corrected microendoscopes have a significantly stronger correlation with the ground truth signals than those obtained with uncorrected microendoscopes.

      (2) There is a strong need for high quality microendoscopes to image deep brain regions in vivo. The solution proposed by the authors is simple, efficient and potentially easy to disseminate within the neuroscience community.

      Weaknesses:

      Weaknesses that were present in the first version of the paper were carefully addressed by the authors.

    1. Reviewer #3 (Public review):

      Huang et al. investigated the phenotype of Bend2 mutant mice which expressed truncated isoform. Bend2 deletion in male showed fertility and this enabled them to analyze the BEND2 function in females. They showed that Bend2 deletion in females showed decreasing follicle number which may lead to loss of ovarian reserve.

      Strengths:

      They found the truncated isoform of Bend2 and the depletion of this isoform showed decreasing follicle number at birth.

      Weaknesses highlighted previously:

      The authors showed novel factors that impact ovarian reserve. Although the number of follicles and conception rate are reduced in mutant mice, the in vitro fertilization rate is normal and follicles remain at 40 weeks of age. It is difficult to know how critical this is when applied to the human case.

      [Editors' note: We thank the authors for considering the previous recommendations and suggested corrections.]

    1. Reviewer #3 (Public review):

      Summary:

      The manuscript takes a dynamical systems perspective on emotion regulation, meaning that rather than a simplistic model conceptualising regulation as applying to a single emotion (e.g. regulation of sadness), emotion regulation could cause a shift in the dynamics of a whole system of emotions (which are linked mathematically to one another). This builds on the idea that there are 'attractor states' of emotions between which people transition, governed by both the system's intrinsic characteristics (e.g. temporal autocorrelation of a particular emotion/person) and external driving forces (having a stressful week). Conceptually this is a very useful advance because it is very unlikely that emotions are elicited (or reduced) singly, without affecting other emotions. This paper is a timely implementation of these ideas in the context of psychotherapeutic intervention, distancing, which participants were trained (randomised) to perform while watching emotion-inducing videos.

      The authors' main conclusion is that distancing both stabilises specific emotional patterns and reduces the impact of external video clips. I would consider these results strong and believable, and to have the potential to impact models of emotion regulation as well as the field's broader views on the mechanisms of psychological therapies.

      Strengths:

      This paper has very many strengths: I would especially note the authors' very-well-matched active control condition and the robustness of their model comparison approach. One feature of the authors' approach is that they explicitly add noise - not what you typically see in an emotion time-series analysis - which allows participants to make errors in their own subjective ratings (a reasonable thing to assume); this noise can then be smoothed during filtering. In their model comparison approach, they explicitly test whether a true dynamical system explains emotion change/emotion regulation effect on emotions - demonstrating that both intrinsic dynamics and external inputs were needed to explain subjective emotion. Powerfully, they also used this approach to test the differential effects of the treatment groups (see below).

      The main result seems quite robust statistically. Verifying the effects of the distancing intervention on emotion, the authors found an interaction between time (pre- to post-intervention) and intervention group (distancing vs. relaxation) suggesting that distancing (but not relaxation) reduced ratings of almost all emotions. Participants allocated to the distancing intervention also showed decreased variability of emotion ratings compared to those in the relaxation intervention (though note this interaction was not significant).

      Using a model comparison approach, the authors then demonstrated that whilst the control group was best explained by a model that did not change its dynamics of emotions, the active intervention (distancing) group was best explained by a model that captured both changing emotion dynamics and a changing input weights (influence of the videos) - results confirmed in follow-up analyses. This is convincing evidence that emotion regulation strategies may specifically affect the dynamics of emotions - both their relationships to one another and their susceptibility to changes evoked by external influences.

      The authors also perform analyses that suggest their result is not attributable to a demand effect (finding that participants were quicker during the control intervention, which one would expect if they had already decided how to respond in advance of the emotion question). I personally also think a demand effect is unlikely given the robustness of their control intervention (which participants would be just as likely to interpret as mental health-enhancing training as distancing), and I am convinced by the notion that demand effects would be unlikely to elicit their more specific effects on the dynamic quality of emotions.

      Weaknesses:

      An interesting but perhaps at present slightly confusing aspect of their described results relates to the 'controllability' of emotions, which they define as their susceptibility to external inputs. Readers should note this definition is (as I understand it) quite distinct from, and sometimes even orthogonal to, concepts of emotional control in the emotion literature, which refer to intentional control of emotions (by emotion regulation strategies such as distancing). The authors also use this second meaning in the discussion. Because of the centrality of control/controllability (in both meanings) to this paper, at present it is key for readers to bear these dual meanings in mind for juxtaposed results that distancing "reduces controllability" while causing "enhanced emotional control".

      As above the authors use an active control - a relaxation intervention - which is extremely closely matched with their active intervention (and a major strength). However, there was an additional difference between the groups (as I currently understand it): "in the group allocated to the distancing intervention, the phrasing of the question about their feelings in the second video block reminded participants about the intervention, stating: "You observed your emotions and let them pass like the leaves floating by on the stream." I do wonder if the effects of distancing also have been partially driven by some degree of reappraisal (considered a separate emotion regulation strategy) since this reminder might have evoked retrospective changes in ratings.

      Not necessarily a weakness, but an unanswered question is exactly how distancing is producing these effects. As the authors point out, there is a possibility that eye-movement avoidance of the more emotionally salient aspects of scenes could be changing participants' exposure to the emotions somewhat. Not discussed by the authors, but possibly relevant, is the literature on differences between emotion types on oculomotor avoidance, which could have contributed to differential effects on different emotions.

    1. Reviewer #3 (Public review):

      Summary:

      In this study, the authors revisit the hypothesis of gradient-based polarity specification during planarian regeneration proposed over a century ago, but here they apply molecular techniques and a valuable comparative approach. By using a comparative analysis with classic and modern planarian model organisms, the authors have identified variable molecular mechanisms that different planarian species utilize to ensure that the proper tissues are regenerated following wounding.

      Strengths:

      The comparative approach of using 2 different planarian species allowed the study to elucidate different molecular mechanisms that planarians utilize in re-establishing anterior-posterior axis polarity during regeneration. Without this comparative approach, the mystery of T.H. Morgan's data classic studies that demonstrate mistakes in this axis re-polarization would remain unanswered. Furthermore, the use of both a modern molecular model species and another more classical planarian species, which the authors have fully developed with molecular tools and techniques, sheds light on the diversity of genetic processes that closely related species seem to utilize in regeneration. To dissect the role of a long-hypothesized canonical cWnt signaling gradient, the authors developed a novel strategy using chemical genetics to titer this gradient, which led to phenotypes with enhanced aberrant axis polarity re-establishment. Together these experimental approaches establish a well-supported initial model for explaining the molecular mechanisms that different planarian species utilize to allow for proper regeneration of lost tissues.

      Weaknesses:

      While pharmacological perturbation of signaling pathways could produce off-target effects, the authors provide well-documented evidence that canonical Wnt signaling is altered with drug treatment. The correlation between altered cWnt signaling gradients and the incidence of double-headed regeneration is strong, but it is not clear that the axial cWnt signaling gradient is the ultimate cause of the modified regeneration polarity. However, the model established here and supported by considerable data provides a useful alternative to the mechanism of notum upregulation that has been well-documented in the Schmidtea mediterranea, the workhouse model in planarian research. Throughout the manuscript, the authors suggest that Girardia sinensis lost the ability to upregulate notum at anterior-facing wounds, but until additional planarian species are evaluated, it remains plausible (and equally parsimonious) that S. mediterranea could have innovated a novel strategy to re-establish axis-polarity through asymmetric notum expression.

      The study is very well-designed with considerable confirmation of results, especially in the novel use of the pharmacological inhibitor C59. This study is invaluable in its comparative approach, finding that well-established molecular processes may not explain similar developmental outcomes for different species; this corroborates the need to study additional model organisms and how an evolutionary approach to the study of development is imperative.

    1. Reviewer #3 (Public review):

      Summary:

      This manuscript examines the impact of congenital visual deprivation on the excitatory/inhibitory (E/I) ratio in the visual cortex using Magnetic Resonance Spectroscopy (MRS) and electroencephalography (EEG) in individuals whose sight was restored. Ten individuals with reversed congenital cataracts were compared to age-matched, normally sighted controls, assessing the cortical E/I balance and its interrelationship and to visual acuity. The study reveals that the Glx/GABA ratio in the visual cortex and the intercept and aperiodic signal are significantly altered in those with a history of early visual deprivation, suggesting persistent neurophysiological changes despite visual restoration. First of all, I would like to disclose that I am not an expert in congenital visual deprivation, nor in MRS. My expertise is in EEG (particularly in the decomposition of periodic and aperiodic activity) and statistical methods. Second, although the authors addressed some of my concerns on the previous version of this manuscript, major concerns and flaws remain in terms of methodological and statistical approaches along with the (over) interpretation of the results.

      Persistent specific concerns include:<br /> (1 3.1) Response to Variability in Visual Deprivation<br /> Rather than listing the advantages and disadvantages of visual deprivation, I recommend providing at least a descriptive analysis of how the duration of visual deprivation influenced the measures of interest. This would enhance the depth and relevance of the discussion.

      (2 3.2) Small Sample Size<br /> The issue of small sample size remains problematic. The justification that previous studies employed similar sample sizes does not adequately address the limitation in the current study. I strongly suggest that the correlation analyses should not feature prominently in the main manuscript or the abstract, especially if the discussion does not substantially rely on these correlations. Please also revisit the recommendations made in the section on statistical concerns.

      (3 3.3) Statistical Concerns<br /> While I appreciate the effort of conducting an independent statistical check, it merely validates whether the reported statistical parameters, degrees of freedom (df), and p-values are consistent. However, this does not address the appropriateness of the chosen statistical methods.

      Several points require clarification or improvement:

      (4) Correlation Methods: The manuscript does not specify whether the reported correlation analyses are based on Pearson or Spearman correlation.<br /> This has been addressed in the final revision

      (5) Confidence Intervals: Include confidence intervals for correlations to represent the uncertainty associated with these estimates.<br /> This has been addressed in the final revision

      (6) Permutation Statistics: Given the small sample size, I recommend using permutation statistics, as these are exact tests and more appropriate for small datasets.

      (7) Adjusted P-Values: Ensure that reported Bonferroni corrected p-values (e.g., p > 0.999) are clearly labeled as adjusted p-values where applicable.<br /> This has been addressed in the final revision

      (8) Figure 2C<br /> Figure 2C still lacks crucial information that the correlation between Glx/GABA ratio and visual acuity was computed solely in the control group (as described in the rebuttal letter). Why was this analysis restricted to the control group? Please provide a rationale.

      (9 3.4) Interpretation of Aperiodic Signal<br /> Relying on previous studies to interpret the aperiodic slope as a proxy for excitation/inhibition (E/I) does not make the interpretation more robust.

      (10) Additionally, the authors state:<br /> "We cannot think of how any of the exploratory correlations between neurophysiological measures and MRS measures could be accounted for by a difference e.g. in skull thickness."

      (11) This could be addressed directly by including skull thickness as a covariate or visualizing it in scatterplots, for instance, by representing skull thickness as the size of the dots.

      (12 3.5) Problems with EEG Preprocessing and Analysis<br /> Downsampling: The decision to downsample the data to 60 Hz "to match the stimulation rate" is problematic. This choice conflates subsequent spectral analyses due to aliasing issues, as explained by the Nyquist theorem. While the authors cite prior studies (Schwenk et al., 2020; VanRullen & MacDonald, 2012) to justify this decision, these studies focused on alpha (8-12 Hz), where aliasing is less of a concern compared of analyzing aperiodic signal. Furthermore, in contrast, the current study analyzes the frequency range from 1-20 Hz, which is too narrow for interpreting the aperiodic signal asE/I. Typically, this analysis should include higher frequencies, spanning at least 1-30 Hz oreven 1-45 Hz (not 20-40 Hz).

      (13) Baseline Removal: Subtracting the mean activity across an epoch as a baseline removal step is inappropriate for resting-state EEG data. This preprocessing step undermines the validity of the analysis. The EEG dataset has fundamental flaws, many of which were pointed out in the previous review round but remain unaddressed. In its current form, the manuscript falls short of standards for robust EEG analysis.

      (14) The authors mention: "The EEG data sets reported here were part of data published earlier (Ossandón et al.,2023; Pant et al., 2023)." Thus, the statement "The group differences for the EEG assessments corresponded to those of a larger sample of CC individuals (n=38) " is a circular argument and should be avoided."<br /> The authors addressed this comment and adjusted the statement. However, I do not understand, why the full sample published earlier (Ossandón et al., 2023) was not used in the current study?

      Comments on revisions:

      The current version of the manuscript is almost unchanged compared to the last version. Unfortunately, I observed that the authors have not adequately addressed most of my previous suggestions; rather, they provided justifications for not incorporating them.

      Given this, I do not see the need to modify my initial assessment.

    1. Reviewer #3 (Public review):

      Summary:

      It has been previously reported in many high-profile papers, that C. elegans can learn to avoid pathogens. Moreover, this learned pathogen avoidance can be passed on to future generations - up to the F5 generation in some reports. In this paper, Gainey et al. set out to replicate these findings. They successfully replicated pathogen avoidance in the exposed animals, as well as a strong increase in daf-7 expression in ASI neurons in F1 animals, as determined by a daf-7::GFP reporter construct. However, they failed to see strong evidence for pathogen avoidance or daf-7 overexpression in the F2 generation. The failure of replication is the major focus of this work.<br /> Given their failure to replicate these findings, the authors embark on a thorough test of various experimental confounders that may have impacted their results. They also re-analyze the small RNA sequencing and mRNA sequencing data from one of the previously published papers and draw some new conclusions, extending this analysis.

      Strengths:

      • The authors provide a thorough description of their methods, and a marked-up version of a published protocol that describes how they adapted the protocol to their lab conditions. It should be easy to replicate the experiments.

      • The authors test source of bacteria, growth temperature (of both C. elegans and bacteria), and light/dark husbandry conditions. They also supply all their raw data, so that sample size for each testing plate can be easily seen (in the supplementary data). None of these variations appears to have a measurable effect on pathogen avoidance in the F2 generation, with all but one of the experiments failing to exhibit learned pathogen avoidance.

      • The small RNA seq and mRNA seq analysis is well performed and extends the results shown in the original paper. The original paper did not give many details of the small RNA analysis, which was an oversight. Although not a major focus of this paper, it is a worthwhile extension on the previous work.

      • It is rare that negative results such as these are accessible. Although the authors were unable to determine the reason that their results differ from those previously published, it is important to document these attempts in detail, as has been done here. Behavioral assays are notoriously difficult to perform and public discourse around these attempts may give clarity to the difficulties faced by a controversial field.

      Weaknesses:

      • Although the "standard" conditions have been tested over multiple biological replicates, many of the potential confounders that may have altered the results have been tested only once or twice. For example, changing the incubation temperature to 25{degree sign}C was tested in only two biological replicates (Exp 5.1 and 5.2) - and one of these experiments actually resulted in apparent pathogen avoidance inheritance in the F2 generation (but not in the F1). An alternative pathogen source was tested in only one biological replicate (Exp 3). Given the variability observed in the F2 generation, increasing biological replicates would have added to the strengths of the report.

      • A key difference between the methods used here and those published previously, is an increase in the age of the animals used for training - from mostly L4 to mostly young adults. I was unable to find a clear example of an experiment when these two conditions were compared, although the authors state that it made no difference to their results.

      • The original paper reports a transgenerational avoidance effect up to the F5 generation. Although in this work the authors failed to see avoidance in the F2 generation, it would have been prudent to extend their tests for more generations in at least a couple of their experiments to ensure that the F2 generation was not an aberration (although this reviewer acknowledges that this seems unlikely to be the case).

    1. Reviewer #3 (Public review):

      Summary:

      The work by Kalita et al. reports regulation of RecB expression by Hfq protein in E.coli cell. RecBCD is an essential complex for DNA repair and chromosome maintenance. The expression level needs to be regulated at low level under regular growth conditions but upregulated upon DNA damage. Through quantitative imaging, the authors demonstrate that recB mRNAs and proteins are expressed at low level under regular conditions. While the mRNA copy number demonstrates high noise level due to stochastic gene expression, the protein level is maintained at a lower noise level compared to expected value. Upon DNA damage, the authors claim that the recB mRNA concentration is decreased, however RecB protein level is compensated by higher translation efficiency. Through analyzing CLASH data on Hfq, they identified two Hfq binding sites on RecB polycistronic mRNA, one of which is localized at the ribosome binding site (RBS). Through measuring RecB mRNA and protein level in the ∆hfq cell, the authors conclude that binding of Hfq to the RBS region of recB mRNA suppresses translation of recB mRNA. This conclusion is further supported by the same measurement in the presence of Hfq sequestrator, the sRNA ChiX, and the deletion of the Hfq binding region on the mRNA.

      Strengths:

      (1) The manuscript is well-written and easy to understand.<br /> (2) While there are reported cases of Hfq regulating translation of bound mRNAs, its effect on reducing translation noise is relatively new.<br /> (3) The imaging and analysis are carefully performed with necessary controls.

      Comments on revisions:

      The authors have addressed my previous concerns.

    1. Reviewer #3 (Public review):

      Summary:

      Pinho et al. investigated the role of the dorsal vs ventral hippocampus and the gender differences in mediated learning. While previous studies already established the engagement of the hippocampus in sensory preconditioning, the authors here took advantage of freely-moving fiber photometry recording and chemogenetics to observe and manipulate sub-regions of the hippocampus (dorsal vs. ventral) in a cell-specific manner. The authors first found sex differences in the preconditioning phase of a sensory preconditioning procedure, where males required more preconditioning training than females for mediating learning to manifest, and where females displayed evidence of mediated learning even when neutral stimuli were never presented together within the session.

      After validation of a sensory preconditioning procedure in mice using light and tone neutral stimuli and a mild foot shock as the unconditioned stimulus, the authors used fiber photometry to record from all neurons vs. parvalbumin_positive_only neurons in the dorsal hippocampus or ventral hippocampus of male mice during both preconditioning and conditioning phases. They found increased activity of all neurons, as well as PV+_only neurons in both sub-regions of the hippocampus during both preconditioning and conditioning phases. Finally, the authors found that chemogenetic inhibition of CaMKII+ neurons in the dorsal, but not ventral, hippocampus specifically prevented the formation of an association between the two neutral stimuli (i.e., light and tone cues), but not the direct association between the light cue and the mild foot shock. This set of data: (1) validates the mediated learning in mice using a sensory preconditioning protocol, and stresses the importance of taking sex effect into account; (2) validates the recruitment of dorsal and ventral hippocampi during preconditioning and conditioning phases; and (3) further establishes the specific role of CaMKII+ neurons in the dorsal but not ventral hippocampus in the formation of an association between two neutral stimuli, but not between a neutral-stimulus and a mild foot shock.

      Strengths:

      The authors developed a sensory preconditioning procedure in mice to investigate mediated learning using light and tone cues as neutral stimuli, and a mild foot shock as the unconditioned stimulus. They provide evidence of a sex effect in the formation of light-cue association. The authors took advantage of fiber-photometry and chemogenetics to target sub-regions of the hippocampus, in a cell-specific manner and investigate their role during different phases of a sensory conditioning procedure.

      Weaknesses:

      The authors went further than previous studies by investigating the role of sub-regions of the hippocampus in mediated learning, however, there are several weaknesses that should be noted:

      (1) This work first validates mediated learning in a sensory preconditioning procedure using light and tone cues as neutral stimuli and a mild foot shock as the unconditioned stimulus, in both males and females. They found interesting sex differences at the behavioral level, but then only focused on male mice when recording and manipulating the hippocampus. The authors do not address sex differences at the neural level.

      (2) As expected in fear conditioning, the range of inter-individual differences is quite high. Mice that didn't develop a strong light-->shock association, as evidenced by a lower percentage of freezing during the Probe Test Light phase, should manifest a low percentage of freezing during the Probe Test Tone phase. It would interesting to test for a correlation between the level of freezing during mediated vs test phases.

      (3) The use of a synapsin promoter to transfect neurons in a non-specific manner does not bring much information. The authors applied a more specific approach to target PV+ neurons only, and it would have been more informative to keep with this cell-specific approach, for example by looking also at somatostatin+ inter-neurons.

      (4) The authors observed event-related Ca2+ transients on hippocampal pan-neurons and PV+ inter-neurons using fiber photometry. They then used chemogenetics to inhibit CaMKII+ hippocampal neurons, which does not logically follow. It does not undermine the main finding of CaMKII+ neurons of the dorsal, but not ventral, hippocampus being involved in the preconditioning, but not conditioning, phase. However, observing CaMKII+ neurons (using fiber photometry) in mice running the same task would be more informative, as it would indicate when these neurons are recruited during different phases of sensory preconditioning. Applying then optogenetics to cancel the observed event-related transients (e.g., during the presentation of light and tone cues, or during the foot shock presentation) would be more appropriate.

      (5) Probe tests always start with the "Probe Test Tone", followed by the "Probe Test Light". "Probe Test Tone" consists of an extinction session, which could affect the freezing response during "Probe Test Light" (e.g., Polack et al. (http://dx.doi.org/10.3758/s13420-013-0119-5)). Preferably, adding a group of mice with a Probe Test Light with no Probe Test Tone could help clarify this potential issue. The authors should at least discuss the possibility that the tone extinction session prior to the "Probe Test Light" could have affected the freezing response to the light cue.

    1. Reviewer #3 (Public review):

      Summary:

      In this study, the authors have developed a new Ca indicator conjugated to the peptide, which likely recognizes synaptic ribbons, and have measured microdomain Ca near synaptic ribbons at retinal bipolar cells. This interesting approach allows one to measure Ca close to transmitter release sites, which may be relevant for synaptic vesicle fusion and replenishment. Though microdomain Ca at the active zone of ribbon synapses has been measured by Hudspeth and Moser, the new study uses the peptide recognizing synaptic ribbons, potentially measuring the Ca concentration relatively proximal to the release sites.

      Strengths:

      The study is in principle technically well done, and the peptide approach is technically interesting, which allows one to image Ca near the particular protein complexes. The approach is potentially applicable to other types of imaging.

      Weaknesses:

      Peptides may not be entirely specific, and the genetic approach tagging particular active zone proteins with fluorescent Ca indicator proteins may well be more specific. I also feel that "Nano-physiology" is overselling, because the measured Ca is most likely the local average surrounding synaptic ribbons. With this approach, nobody knows about the real release site Ca or the Ca relevant for synaptic vesicle replenishment. It is rather "microdomain physiology" which measures the local Ca near synaptic ribbons, relatively large structures responsible for fusion, replenishment, and recycling of synaptic vesicles.

    1. Reviewer #3 (Public review):

      Summary:

      Using the approach of Myomatrix recording, the authors report that:

      (1) Motor units are recruited differently in the two types of muscles.<br /> (2) Individual units are probabilistically recruited during the locomotion strides, whereas the population bulk EMG has a more reliable representation of the muscle.<br /> (3) The recruitment of units was proportional to walking speed.

      Strengths:

      The new technique provides a unique data set, and the data analysis is convincing and well-performed.

      Weaknesses:

      The implications of "probabilistical recruitment" should be explored, addressed, and analyzed further.

      Comments:

      One of the study's main findings (perhaps the main finding) is that the motor units are "probabilistically" recruited. The authors do not define what they mean by probabilistically recruited, nor do they present an alternative scenario to such recruitment or discuss why this would be interesting or surprising. However, on page 4, they do indicate that the recruitment of units from both muscles was only active in a subset of strides, i.e., they are not reliably active in every step.

      If probabilistic means irregular spiking, this is not new. Variability in spiking has been seen numerous times, for instance in human biceps brachii motor units during isometric contractions (Pascoe, Enoka, Exp physiology 2014) and elsewhere. Perhaps the distinction the authors are seeking is between fluctuation-driven and mean-driven spiking of motor units as previously identified in spinal motor networks (see Petersen and Berg, eLife 2016, and Berg, Frontiers 2017). Here, it was shown that a prominent regime of irregular spiking is present during rhythmic motor activity, which also manifests as a positive skewness in the spike count distribution (i.e., log-normal).

    1. Reviewer #3 (Public review):

      Summary

      This is an exciting and timely study addressing the role of descending noradrenergic systems in nocifensive responses. While it is well-established that spinally released noradrenaline (aka norepinephrine) generally acts as an inhibitory factor in spinal sensory processing, this system is highly complex. Descending projections from the A6 (locus coeruleus, LC) and the A5 regions typically modulate spinal sensory processing and reduce pain behaviours, but certain subpopulations of LC neurons have been shown to mediate pronociceptive effects, such as those projecting to the prefrontal cortex (Hirshberg et al., PMID: 29027903).

      The study proposes that descending cerulean noradrenergic neurons potentiate touch sensation via alpha-1 adrenoceptors on Hes5+ spinal astrocytes, contributing to mechanical hyperalgesia. This finding is consistent with prior work from the same group (dd et al., PMID:). However, caution is needed when generalising about LC projections, as the locus coeruleus is functionally diverse, with differences in targets, neurotransmitter co-release, and behavioural effects. Specifying the subpopulations of LC neurons involved would significantly enhance the impact and interpretability of the findings.

      Strengths

      The study employs state-of-the-art molecular, genetic, and neurophysiological methods, including precise CRISPR and optogenetic targeting, to investigate the role of Hes5+ astrocytes. This approach is elegant and highlights the often-overlooked contribution of astrocytes in spinal sensory gating. The data convincingly support the role of Hes5+ astrocytes as regulators of touch sensation, coordinated by brain-derived noradrenaline in the spinal dorsal horn, opening new avenues for research into pain and touch modulation.

      Furthermore, the data support a model in which superficial dorsal horn (SDH) Hes5+ astrocytes act as non-neuronal gating cells for brain-derived noradrenergic (NA) signalling through their interaction with substantia gelatinosa inhibitory interneurons. Locally released adenosine from NA-stimulated Hes5+ astrocytes, following acute restraint stress, may suppress the function of SDH-Vgat+ inhibitory interneurons, resulting in mechanical pain hypersensitivity. However, the spatially restricted neuron-astrocyte communication underlying this mechanism requires further investigation in future studies.

      Weaknesses

      (1) Specificity of the LC Pathway targeting

      The main concern lies with how definitively the LC pathway was targeted. Were other descending noradrenergic nuclei, such as A5 or A7, also labelled in the experiments? The authors must convincingly demonstrate that the observed effects are mediated exclusively by LC noradrenergic terminals to substantiate their claims (i.e. "we identified a circuit, the descending LC→SDH-NA neurons").

      a) For instance, the direct vector injection into the LC likely results in unspecific effects due to the extreme heterogeneity of this nucleus and retrograde labelling of the A5 and A7 nuclei from the LC (i.e., Li et al., PMID: 26903420).

      b) It is difficult to believe that the intersectional approach described in the study successfully targeted LC→SDH-NA neurons using AAVrg vectors. Previous studies (e.g., PMID: 34344259 or PMID: 36625030) demonstrated that similar strategies were ineffective for spinal-LC projections. The authors should provide detailed quantification of the efficiency of retrograde labelling and specificity of transgene expression in LC neurons projecting to the SDH.

      c) Furthermore, it is striking that the authors observed a comparably strong phenotypical change in Figure 1K despite fewer neurons being labelled, compared to Figure 1H and 1N with substantially more neurons being targeted. Interestingly, the effect in Figure 1K appears more pronounced but shorter-lasting than in the comparable experiment shown in Figure 1H. This discrepancy requires further explanation.

      d) A valuable addition would be staining for noradrenergic terminals in the spinal cord for the intersectional approach (Figure 1J), as done in Figures 1F/G. LC projections terminate preferentially in the SDH, whereas A5 projections terminate in the deep dorsal horn (DDH). Staining could clarify whether circuits beyond the LC are being ablated.

      e) Furthermore, different LC neurons often mediate opposite physiological outcomes depending on their projection targets-for example, dorsal LC neurons projecting to the prefrontal cortex PFCx are pronociceptive, while ventral LC neurons projecting to the SC are antinociceptive (PMIDs: 29027903, 34344259, 36625030). Given this functional diversity, direct injection into the LC is likely to result in nonspecific effects.

      Conclusion on Specificity: The authors are strongly encouraged to address these limitations directly, as they significantly affect the validity of the conclusions regarding the LC pathway. Providing more robust evidence, acknowledging experimental limitations, and incorporating complementary analyses would greatly strengthen the manuscript.

      (2) Discrepancies in Data

      a) Figures 1B and 1E: The behavioural effect of stress on PWT (Figure 1E) persists for 120 minutes, whereas Ca²⁺ imaging changes (Figure 1B) are only observed in the first 20 minutes, with signal attenuation starting at 30 minutes. This discrepancy requires clarification, as it impacts the proposed mechanism.

      b) Figure 4E: The effect is barely visible, and the tissue resembles "Swiss cheese," suggesting poor staining quality. This is insufficient for such an important conclusion. Improved staining and/or complementary staining (e.g., cFOS) are needed. Additionally, no clear difference is observed between Stress+Ab stim. and Stress+Ab stim.+CPT, raising doubts about the robustness of the data.

      c) Discrepancy with Existing Evidence: The claim regarding the pronociceptive effect of LC→SDH-NAergic signalling on mechanical hypersensitivity contrasts with findings by Kucharczyk et al. (PMID: 35245374), who reported no facilitation of spinal convergent (wide-dynamic range) neuron responses to tactile mechanical stimuli, but potent inhibition to noxious mechanical von Frey stimulation. This discrepancy suggests alternative mechanisms may be at play and raises the question of why noxious stimuli were not tested.

      (3) Sole reliance on Von Frey testing

      The exclusive use of von Frey as a behavioural readout for mechanical sensitisation is a significant limitation. This assay is highly variable, and without additional supporting measures, the conclusions lack robustness. Incorporating other behavioural measures, such as the adhesive tape removal test to evaluate tactile discomfort, the needle floor walk corridor to assess sensitivity to uneven or noxious surfaces, or the kinetic weight-bearing test to measure changes in limb loading during movement, could provide complementary insights. Physiological tests, such as the Randall-Selitto test for noxious pressure thresholds or CatWalk gait analysis to evaluate changes in weight distribution and gait dynamics, would further strengthen the findings and allow for a more comprehensive assessment of mechanical sensitisation.

      Overall Conclusion

      This study addresses an important and complex topic with innovative methods and compelling data. However, the conclusions rely on several assumptions that require more robust evidence. Specificity of the LC pathway, experimental discrepancies, and methodological limitations (e.g., sole reliance on von Frey) must be addressed to substantiate the claims. With these issues resolved, this work could significantly advance our understanding of astrocytic and noradrenergic contributions to pain modulation.

    1. Reviewer #3 (Public review):

      Summary:

      Fujita et al build on their earlier, 2017 eLife paper that showed the role of autophagy in the developmental remodeling of a group of muscles (DIOM) in the abdomen of Drosophila. Most larval muscles undergo histolysis during metamorphosis, while DIOMs are programmed to regrow after initial atrophy to give rise to temporary adult muscles, which survive for only 1 day after eclosion of the adult flies (J Neurosci. 1990;10:403-1. and BMC Dev Biol 16, 12, 2016). The authors carry out transcriptomics profiling of these muscles during metamorphosis, which is in agreement with the atrophy and regrowth phases of these muscles. Expression of the known mitophagy receptor BNIP3/NIX is high during atrophy, so the authors have started to delve more into the role of this protein/mitophagy in their model. BNIP3 KO indeed impairs mitophagy and muscle atrophy, which they convincingly demonstrate via nice microscopy images. They also show that the already known Atg8a-binding LIR and Atg18a-binding MER motifs of human NIX are conserved in the Drosophila protein, although the LIR turned out to be less critical for in vivo protein function than the MER motif.

      Strengths:

      Established methodology, convincing data, in vivo model.

      Weaknesses:

      The significance for Drosophila physiology and for human muscles remains to be established.

    1. Reviewer #3 (Public review):

      Summary:

      Understanding the neural circuits that link sleep and memory remains a fundamental challenge in neuroscience. In this study, Lin Yan and colleagues investigate how dopamine signaling in Drosophila regulates long-term memory (LTM) formation in the context of sleep. They identify a specific microcircuit between protocerebral anterior medial dopamine neurons (PAM-DANs) and dorsal paired medial (GABAergic DPM) neurons that modulates memory consolidation. Their findings suggest that disrupting the basal activity of PAM-α1 neurons during early consolidation impairs LTM, with particularly pronounced effects under starvation conditions. Notably, sleep fragmentation caused by this disruption can be pharmacologically rescued, restoring LTM. These results provide compelling evidence that dopamine signaling plays a crucial role in linking sleep and memory, offering new insights into the underlying mechanisms.

      Strengths:

      This study presents a well-executed investigation into sleep-memory interactions, utilizing a combination of connectomics, behavioral assays, functional imaging, and pharmacological manipulations. The authors convincingly demonstrate that the PAM-α1 and DPM circuits interact, highlighting a potential mechanism by which sleep influences memory consolidation. The anatomical and functional dissection of this circuit is of high interest to the field, and the study's integration of sleep and memory processes contributes significantly to our understanding of dopamine's role in cognitive functions.

      Weaknesses:

      While the study is well-designed and presents compelling findings, some aspects require further clarification. The interpretation of dopamine receptor signaling remains incomplete, particularly regarding inhibitory pathways. The role of DPM in memory consolidation is not entirely conclusive, as different genetic approaches yield variable results. Additionally, some inconsistencies in neuronal activity patterns and experimental variability, especially regarding sleep patterns or pharmacological rescue, should be addressed to strengthen the mechanistic framework.

      Conclusion:

      Overall, this study provides valuable new insights into how sleep and dopamine circuits interact to regulate memory consolidation. While the findings are compelling, addressing the points above-particularly receptor signaling and the specific role of DPM and its activity patterns within the microcircuit would further solidify the study's conclusions.

    1. Reviewer #3 (Public review):

      Summary:

      The paper by Saito et al. studies the properties of anthozoan-specific opsins (ASO-II) from organisms found in reef-building coral. Their goal was to test if ASO-II opsins can absorb visible light, and if so, what the key factors involved are.

      The most exciting aspect of this work is their discovery that ASO-II opsins do not have a counterion residue (Asp or Glu) located at any of the previously known sites found in other animal opsins.

      This is very surprising. Opsins are only able to absorb visible (long wavelength light) if the retinal Schiff base is protonated, and the latter requires (as the name implies) a "counter ion". However, the authors clearly show that some ASO-II opsins do absorb visible light.

      To address this conundrum, they tested if the counterion could be provided by exogenous chloride ions (Cl-). Their results find compelling evidence supporting this idea, and their studies of ASO-II mutant E292A suggest E292 also plays a role in G protein activation and is a counterion for a protonated Schiff base in the light-activated form.

      Strengths:

      Overall, the methods are well-described and carefully executed, and the results are very compelling.

      Their analysis of seven ASO-II opsin sequences undoubtedly shows they all lack a Glu or Asp residue at "normal" (previously established) counter-ion sites in mammalian opsins (typically found at positions 94, 113, or 181). The experimental studies clearly demonstrate the necessity of Cl- for visible light absorbance, as do their studies of the effect of altering the pH.

      Importantly, the authors also carried out careful QM/MM computational analysis (and corresponding calculation of the expected absorbance effects), thus providing compelling support for the Cl- acting directly as a counterion to the protonated retinal Schiff base, and thus limiting the possibility that the Cl- is simply altering the absorbance of ASO-II opsins through some indirect effect on the protein.

      Altogether, the authors achieved their aims, and the results support their conclusions. The manuscript is carefully written, and refreshingly, the results and conclusions are not overstated.

      This study is impactful for several reasons. There is increasing interest in optogenetic tools, especially those that leverage G protein-coupled receptor systems. Thus, the authors' demonstration that ASO-II opsins could be useful for such studies is of interest.

      Moreover, the finding that visible light absorbance by an opsin does not absolutely require a negatively charged amino acid to be placed at one of the expected sites (94, 113, or 181) typically found in animal opsins is very intriguing and will help future protein engineering efforts. The argument that the Cl- counterion system they discover here might have been a preliminary step in the evolution of amino acid based counterions used in animal opsins is also interesting.

      Finally, given the ongoing degradation of coral reefs worldwide, the focus on these curious opsins is very timely, as is the authors' proposal that the lower Schiff base pKa they discovered here for ASO-II opsins may cause them to change their spectral sensitivity and G protein activation due to changes in their environmental pH.

    1. Reviewer #3 (Public Review):

      Summary:

      In a previous study, the authors analyzed the dynamics of the SARS-CoV2 spike protein through lengthy MD simulations and an out-of-equilibrium sampling scheme. They identified an allosteric interaction network linking a lipid-binding site to other structurally important regions of the spike. However, this study was conducted without considering the impact of glycans. It is now known that glycans play a crucial role in modulating spike dynamics. This new manuscript investigates how the presence of glycans affects the allosteric network connecting the lipid binding site to the rest of the spike. The authors conducted atomistic equilibrium and out-of-equilibrium MD simulations and found that while the presence of glycans influences the structural responses, it does not fundamentally alter the connectivity between the fatty acid site and the rest of the spike.

      Strengths:

      The manuscript's findings are based on an impressive amount of sampling. The methods and results are clearly outlined, and the analysis is conducted meticulously.

    1. Reviewer #3 (Public review):

      Summary:

      Yang et al. have investigated the role of PLSCR1, an antiviral interferon-stimulated gene (ISG), in host protection against IAV infection. Although some antiviral effects of PLSCR1 have been described, its full activity remains incompletely understood.

      This study now shows that Plscr1 expression is induced by IAV infection in the respiratory epithelium, and Plscr1 acts to increase Ifn-λr1 expression and enhance IFN-λ signaling possibly through protein-protein interactions on the cell membrane.

      Strengths:

      The study sheds light on the way Ifnlr1 expression is regulated, an area of research where little is known. The study is extensive and well-performed with relevant genetically modified mouse models and tools.

      Weaknesses:

      There are some issues that need to be clarified/corrected in the results and figures as presented.

      Also, the study does not provide much information about the role of PLSCR1 in the regulation of Ifn-λr1 expression and function in immune cells. This would have been a plus.

    1. Reviewer #3 (Public review):

      In this project, Garber and Fiser examined how the structure of incidentally learned regularities influences subsequent learning of regularities, that either have the same structure or a different one. Over a series of six online experiments, it was found that the structure (spatial arrangement) of the first set of regularities affected learning of the second set, indicating that it has indeed been abstracted away from the specific items that have been learned. The effect was found to depend on the explicitness of the original learning: Participants who noticed regularities in the stimuli were better at learning subsequent regularities of the same structure than of a different one. On the other hand, participants whose learning was only implicit had an opposite pattern: they were better in learning regularities of a novel structure than of the same one. However, when an overnight sleep separated the first and second learning phases, this opposite effect was reversed and came to match the pattern of the explicit group, suggesting that the abstraction and transfer in the implicit case were aided by memory consolidation.

    1. Reviewer #3 (Public review):

      Summary:

      In this paper, Xu, Dantu and coworkers report a protocol for analyzing coevolutionary and dynamical information to identify a subset of communities that capture functionally relevant sites in beta-lactamases.

      Strengths:

      The combination of coevolutionary information and metrics from MD simulations is interesting for capturing functionally relevant sites, which can have implications in the fields of drug discovery but also in protein design.

      Comments on latest version:

      The authors have successfully addressed all my previous comments/concerns. I am happy with the current version of the manuscript.

    1. Reviewer #3 (Public review):

      Summary:

      In this manuscript, Verd and colleagues explored how various biologically relevant factors influence the robustness of clock dynamics synchronization among neighboring cells within the context of somatogenesis, adapting a mathematical model presented by Urio et. al in 2021 in a similar context. Specifically they show that clock dynamics is robust to different biological mechanisms such as cell infusion, cellular motility, compaction-extension and cell-division. On the other hand , the length of Presomitic Mesoderm (PSM) and density of cells in it has a significant role in the robustness of clock dynamics. While the manuscript is well-written and provides clear descriptions of methods and technical details, it tends to be somewhat lengthy.

      Major comments from original round of review:

      (1) The authors mention that "...the model is three dimensional and so can quantitatively recapture the rates of cell mixing that we observe in the PSM". I am not convinced with this justification of using a 3D model. None of the effects the authors explore in this manuscript requires a three dimensional model or full physical description of the cellular mechanics such as excluded volume interaction etc. A one-dimensional model characterized by cell position along the arclength of PSM and somatic region and segmentation clock phase θ can incorporate all the physics authors described in this manuscript as well as significantly computationally cheap allowing the authors to explore the effect of different parameters in greater detail.

      (2) I am not sure about the justification for limiting the quantification of phase synchrony in a very limited (one cell diameter wide) region at one end of the somatic part (Page 33 below Fig. 9). From my understanding of the manuscript, the segments appear in significant length anterior to this region. Wouldn't an ensemble average of multiple such one cell diameter wide regions in the somatic region be a more accurate metric for quantifying synchrony?

      (3) While studying the effect of cellular ingression, the authors study three discrete modes-random, DP and DP+LV and show that in the DP+LV mode the clock synchrony becomes affected. I would like the authors to explore this in a continuous fashion from a pure DP ingression to Pure LV ingression and intermediates.

      (4) While studying the effect of length and density of cells in PSM on cellular synchrony, the authors restrict to 3 values of density and 6 values of PSM length keeping the other parameter constant. I would be interested to see a phase diagram similar to Fig. 7 in the two dimensional parameter space of L and ρ0. I am curious if a scaling relation exists for the parameter values that partition the parameter space with and without synchrony.

      (5) Both in the abstract and introduction, the authors discuss at a great length about the variability in the number of segments. I am curious how the number and width of the segments observed depend on different parameters related to cellular mechanics and the segmentation clock ?

      (6) The authors assume that the phase dynamics of the chemical network may be described by an oscillator with constant frequency. For the completeness of the manuscript, the author should discuss in detail, for which chemical networks this is a good assumption.

      (7) Figure 3 and the associated text shows no effect of the cellular motility profile in the synchrony of the segmentation clock. This may be moved to the supplementary considering the length of this manuscript.

      Significance:

      The manuscript answers some important questions in the synchrony of segmentation clock in the vertebrates utilizing a model published earlier. However, the presented result is incomplete in some aspects (points 2 to 5 of section A) and that could be overcome by a more detailed analysis using a simpler one dimensional (point 1 of section A). I believe this manuscript could be of interest to an intersecting audience of developmental biologists, systems biologists, and physicists/engineers interested in dynamical systems.

      [Editors' note: the authors have responded comprehensively to the reviews from Review Commons.]

    1. Reviewer #3 (Public review):

      Summary:

      In this manuscript, "Elucidating the mechanism underlying UBA7-UBE2L6 disulfide complex formation", Chen et al. describe the mechanism of spontaneous disulfide bond formation between the active site cysteines of UBA7 and UBE2L6. Employing state-of-the-art biochemistry, cryo-EM, and HDX mass spec approaches, the authors provide insights into how this mechanism occurs in UBA7/UBE2L6 but not in related ubiquitin enzymes. A central conclusion of the study is that the length of the catalytic cysteine loop (CCL) in UBA7 is insufficient to block access to the E1's catalytic cysteine, thereby facilitating UBE2L6 disulfide formation. In contrast, the CCL of UBA1 is sufficiently long and shields its catalytic cysteine, preventing access to the Ub E2 enzymes. In addition to the CCL, the authors also show that UBA7's specificity and strong binding affinity for UBE2L6 help promote this disulfide-linked E1-E2 complex.

      Strengths:

      The data within in manuscript is interesting and significantly contributes to our understanding of the mechanisms of the ISG15 conjugation pathway. Moreover, the biochemical and structural experiments were performed at an exceptionally high level and the data throughout the manuscript is convincing.

      Weaknesses:

      It is not clear whether this regulatory mechanism occurs in a biological context (e.g., during IFN signaling or oxidative stress). However, this weakness is somewhat offset by the last experiment of the manuscript which demonstrates the existence of UBA7-UBE2L6 disulfide complex formation in cells under overexpression conditions. If the authors could expand upon this finding, as outlined below it would further improve their study.

    1. Reviewer #3 (Public review):

      Summary:

      Shimagaki et al. investigate the virus-antibody coevolutionary processes that drive the development of broadly neutralizing antibodies (bnAbs). The study's primary goal is to characterize the evolutionary dynamics of HIV-1 within hosts that accompany the emergence of bnAbs, with a particular focus on inferring the landscape of selective pressures shaping viral evolution. To assess the generality of these evolutionary patterns, the study extends its analysis to rhesus macaques (RMs) infected with simian-human immunodeficiency viruses (SHIV) incorporating HIV-1 Env proteins derived from two human individuals.

      Strengths:

      A key strength of the study is its rigorous assessment of the similarity in evolutionary trajectories between humans and macaques. This cross-species comparison is particularly compelling, as it quantitatively establishes a shared pattern of viral evolution using a sophisticated inference method. The finding that similar selective pressures operate in both species adds robustness to the study's conclusions and suggests broader biological relevance.

      Weaknesses:

      However, the study has some limitations. The most significant weakness is that the authors do not sufficiently discuss the implications of the observed similarities. While the identification of shared evolutionary patterns (e.g., Figure 5) is intriguing, the study would benefit from a more explicit discussion of what these findings mean for instance, in the context of HIV vaccine design, immunotherapy, or fundamental viral-host interactions. Even speculative interpretations could provide valuable insights into the broader significance of these results.

      A secondary, albeit less critical, limitation is the placement of methodological details in the Supplementary Information. While it is understandable that the authors focus on results in the main text - especially since the methodology is not novel and has been previously described in earlier publications - some readers might benefit from a more thorough presentation of the method within the main paper.

      Conclusions:

      Overall, the study presents a compelling analysis of HIV-1 evolution and its parallels in SHIV-infected macaques. While the quantitative comparison between species is a notable contribution, a deeper discussion of its broader implications would strengthen the paper's impact.

    1. Reviewer #3 (Public review):

      Summary:

      The authors appear to be attempting to identify which patients with benign lesions will progress to cancer using a liquid biomarker. They used radiomics and EV miRNAs in order to assess this.

      Strengths:

      It is a strength that there are multiple test datasets. Data is batch-corrected. A relatively large number of patients is included. Only 3 miRNAs are needed to obtain their sensitivity and specificity scores.

      Weaknesses:

      This manuscript is not clearly written, making interpretation of the quality and rigor of the data very difficult. There is no indication from the methods that the patients in their cohorts who are pancreatic cancer patients (from the CT images) had prior benign lesions, limiting the power of their analysis. The data regarding the cluster subtypes is very confusing. There is no discussion or comparison if these two clusters are just representing classical and basal subtypes (which have been well described).

    1. Reviewer #3 (Public review):

      Summary:

      The authors developed a new Agbl5 KO allele, extending the deletion to the N-terminus of CCP5 to explore its function in mouse ependymal cells.

      Strengths:

      They show that the KO mice exhibit severe hydrocephalus due to disorganized and mislocated basal bodies. Additionally, they present evidence of both impaired beating coordination and a reduction in ciliary beating.

      Weaknesses:

      The manuscript is well-written but lacks specific interpretations of the results presented. Further experiments are needed to be fully convincing.

  2. southtexascollege.blackboard.com southtexascollege.blackboard.com
    1. Yet thou triumph’st, and say'st that thou <br /> Find’st not thy self, nor me the weaker now;

      In line 26, the listener explains how they feel no guilt, and there is no consequence from taking the flea's life as it took both their blood.

    2. Just so much honor, when thou yield’st to me, Will waste, as this flea’s death took life from thee.

      In connection to line 27, it seems what seems to be getting lost is the listener's honor. The speaker (?) seems to connect this, comparing the fear of loosing her honor in connection to the flea's death. By saying this, the speaker goes on to push, saying that similar to the flea's death having no consequence, their will be no consequence to them being intimate.

    3. Yet thou triumph’st, and say'st that thou <br /> Find’st not thy self, nor me the weaker now;

      In lines 23 and 24, the listener finally speaks, claiming that by killing the flea, she is not weak. By saying this, she essentially says that there was no harm in killing the flea, as it took both their blood.

    4. Cruel and sudden, hast thou since Purpled thy nail, in blood of innocence?

      In line 19, the speaker calls the listener "Cruel and sudden" because they killed the flea. In line 20, the speaker paints the picture of the flea's blood painting the purple nail of the listener, showing the violence and lost of a life.

    1. Reviewer #3 (Public review):

      This work addresses the metabolic interplay between photoreceptors and the adjacent supporting layer of the vertebrate retina, the retinal pigment epithelium (RPE). Prior work from the Hurley lab and others provided evidence, mainly in acutely dissected mouse retina and in cell culture, for the idea that although glucose enters the retina via the RPE, the photoreceptors use most of this glucose via glycolysis, producing lactate that is used by other cells such as Müller cells and RPE cells. In the current study, they build on this by showing that these same principles hold true in vivo, using organism-level stable isotope tracing, as well as in intact retina preparations. They also use several mutant mice that lack photoreceptors, or that lack glucose transporters in either rods or the whole retina, to examine the contribution of photoreceptors to retinal glucose uptake. While many of the concepts were introduced in earlier work, it is an important expansion of this work to show these same mechanisms function in vivo. The authors also use other labeled fuels, lactate, and palmitate, to characterize their use in the presence or absence of glucose transport.

      The paper presents a nice combination of in vivo experiments (with a steady infusion of labeled metabolites into the circulation of a living mouse) with ex vivo experiments that allow the monitoring of lactate production and temporal control of labeling.

      Overall, the work provides convincing evidence that in the eye of a living mouse, photoreceptors are the main consumers of glucose in the retina, and the main producers of lactate. It seems less clear that the incorporation of labeled glucose into TCA metabolites in the RPE is dependent on the photoreceptor processing of glucose to lactate. Figure 5D is cited as the evidence that "much less m+3 lactate reaches the RPE-choroid in AIPL-/- mice than in controls," and indeed there is much less labeled lactate; but the downstream labeling of citrate is not substantially affected. It is also hard to discern whether these in vivo experiments provide evidence that photoreceptor-derived lactate suppresses glucose oxidation in RPE cells (as shown in vitro in Kanow et al., 2017).

    1. Reviewer #3 (Public Review):

      This manuscript by Akabuogu et al. investigates membrane potential dynamics in E. coli. Membrane potential fluctuations have been observed in bacteria by several research groups in recent years, including in the context of bacterial biofilms where they have been proposed to play a role in cellular communication. Here, these authors investigate membrane potential in E. coli, in both single cells and biofilms. I have reviewed the revised manuscript provided by the authors, as well as their responses to the initial reviews; my opinion about the manuscript is largely unchanged. I have focused my public review on those issues that I believe to be most pressing, with additional comments included in the review to authors. Although these authors are working in an exciting research area, the evidence they provide for their claims is inadequate, and several key control experiments are still missing. In some cases, the authors allude to potentially relevant data in their responses to the initial reviews, but unfortunately these data are not shown. Furthermore, I cannot identify any traveling wavefronts in the data included in this manuscript. In addition to the challenges associated with the use of Thioflavin-T (ThT) raised by the second reviewer, these caveats make the work presented in this manuscript difficult to interpret.

      First, some of the key experiments presented in the paper lack required controls:

      (1) This paper asserts that the observed ThT fluorescence dynamics are induced by blue light. This is a fundamental claim in the paper, since the authors go on to argue that these dynamics are part of a blue light response. This claim must be supported by the appropriate negative control experiment measuring ThT fluorescence dynamics in the absence of blue light- if this idea is correct, these dynamics should not be observed in the absence of blue light exposure. If this experiment cannot be performed with ThT since blue light is used for its excitation, TMRM can be used instead.

      In response to this, the authors wrote that "the fluorescent baseline is too weak to measure cleanly in this experiment." If they observe no ThT signal above noise in their time lapse data in the absence of blue light, this should be reported in the manuscript- this would be a satisfactory negative control. They then wrote that "It appears the collective response of all the bacteria hyperpolarization at the same time appears to dominate the signal." I am not sure what they mean by this- perhaps that ThT fluorescence changes strongly only in response to blue light? This is a fundamental control for this experiment that ought to be presented to the reader.

      (2) The authors claim that a ∆kch mutant is more susceptible to blue light stress, as evidenced by PI staining. The premise that the cells are mounting a protective response to blue light via these channels rests on this claim. However, they do not perform the negative control experiment, conducting PI staining for WT the ∆kch mutant in the absence of blue light. In the absence of this control it is not possible to rule out effects of the ∆kch mutation on overall viability and/or PI uptake. The authors do include a growth curve for comparison, but planktonic growth is a very different context than surface-attached biofilm growth. Additionally, the ∆kch mutation may have impacts on PI permeability specifically that are not addressed by a growth curve. The negative control experiment is of key importance here.

      Second, the ideas presented in this manuscript rely entirely on analysis of ThT fluorescence data, specifically a time course of cellular fluorescence following blue light treatment. However, alternate explanations for and potential confounders of the observed dynamics are not sufficiently addressed:

      (1) Bacterial cells are autofluorescent, and this fluorescence can change significantly in response to stress (e.g. blue light exposure). To characterize and/or rule out autofluorescence contributions to the measurement, the authors should present time lapse fluorescence traces of unstained cells for comparison, acquired under the same imaging conditions in both wild type and ∆kch mutant cells. In their response to reviewers the authors suggested that they have conducted this experiment and found that the autofluorescence contribution is negligible, which is good, but these data should be included in the manuscript along with a description of how these controls were conducted.

      (2) Similarly, in my initial review I raised a concern about the possible contributions of photobleaching to the observed fluorescence dynamics. This is particularly relevant for the interpretation of the experiment in which catalase appears to attenuate the decay of the ThT signal; this attenuation could alternatively be due to catalase decreasing ThT photobleaching. In their response, the authors indicated that photobleaching is negligible, which would be good, but they do not share any evidence to support this claim. Photobleaching can be assessed in this experiment by varying the light dosage (illumination power, frequency, and/or duration) and confirming that the observed fluorescence dynamics are unaffected.

      Third, the paper claims in two instances that there are propagating waves of ThT fluorescence that move through biofilms, but I do not observe these waves in any case:

      (1) The first wavefront claim relates to small cell clusters, in Fig. 2A and Video S2 and S3 (with Fig. 2A and Video S2 showing the same biofilm.) I simply do not see any evidence of propagation in either case- rather, all cells get brighter and dimmer in tandem. I downloaded and analyzed Video S3 in several ways (plotting intensity profiles for different regions at different distances from the cluster center, drawing a kymograph across the cluster, etc.) and in no case did I see any evidence of a propagating wavefront. (I attempted this same analysis on the biofilm shown in Fig. 2A and Video S2 with similar results, but the images shown in the figure panels and especially the video are still both so saturated that the quantification is difficult to interpret.) If there is evidence for wavefronts, it should be demonstrated explicitly by analysis of several clusters. For example, a figure of time-to-peak vs. position in the cluster demonstrating a propagating wave would satisfy this. Currently, I do not see any wavefronts in this data.

      (2) The other wavefront claim relates to biofilms, and the relevant data is presented in Fig. S4 (and I believe also in what is now Video S8, but no supplemental video legends are provided, and this video is not cited in text.) As before, I cannot discern any wavefronts in the image and video provided; Reviewer 1 was also not able to detect wave propagation in this video by kymograph. Some mean squared displacements are shown in Fig. 7. As before, the methods for how these were obtained are not clearly documented either in this manuscript or in the BioRXiv preprint linked in the initial response to reviewers, and since wavefronts are not evident in the video it is hard to understand what is being measured here- radial distance from where? (The methods section mentions radial distance from the substrate, this should mean Z position above the imaging surface, and no wavefronts are evident in Z in the figure panels or movie.) Thus, clear demonstration of these wavefronts is still missing here as well.

      Fourth, I have some specific questions about the study of blue light stress and the use of PI as a cell viability indicator:

      (1) The logic of this paper includes the premise that blue light exposure is a stressor under the experimental conditions employed in the paper. Although it is of course generally true that blue light can be damaging to bacteria, this is dependent on light power and dosage. The control I recommended above, staining cells with PI in the presence and absence of blue light, will also allow the authors to confirm that this blue light treatment is indeed a stressor- the PI staining would be expected to increase in the presence of blue light if this is so.

      (2) The presence of ThT may complicate the study of the blue light stress response, since ThT enhances the photodynamic effects of blue light in E. coli (Bondia et al. 2021 Chemical Communications). The authors could investigate ThT toxicity under these conditions by staining cells with PI after exposing them to blue light with or without ThT staining.

      (3) In my initial review, I wrote the following: "In Figures 4D - E, the interpretation of this experiment can be confounded by the fact that PI uptake can sometimes be seen in bacterial cells with high membrane potential (Kirchhoff & Cypionka 2017 J Microbial Methods); the interpretation is that high membrane potential can lead to increased PI permeability. Because the membrane potential is largely higher throughout blue light treatment in the ∆kch mutant (Fig. 3[BC]), this complicates the interpretation of this experiment." In their response, the authors suggested that these results are not relevant in this case because "In our experiment methodology, cell death was not forced on the cells by introducing an extra burden or via anoxia." However, the logic of the paper is that the cells are in fact dying due to an imposed external stressor, which presumably also confers an increased burden as the cells try to deal with the stress. Instead, the authors should simply use a parallel method to confirm the results of PI staining. For example, the experiment could be repeated with other stains, or the viability of blue light-treated cells could be addressed more directly by outgrowth or colony-forming unit assays.

      The CFU assay suggested above has the additional advantage that it can also be performed on planktonic cells in liquid culture that are exposed to blue light. If, as the paper suggests, a protective response to blue light is being coordinated at the biofilm level by these membrane potential fluctuations, the WT strain might be expected to lose its survival advantage vs. the ∆kch mutant in the absence of a biofilm.

      Fifth, in several cases the data are presented in a way that are difficult to interpret, or the paper makes claims that are different to observe in the data:

      (1) The authors suggest that the ThT and TMRM traces presented in Fig. S1D have similar shapes, but this is not obvious to me- the TMRM curve has very little decrease after the initial peak and only a modest, gradual rise thereafter. The authors suggest that this is due to increased TMRM photobleaching, but I would expect that photobleaching should exacerbate the signal decrease after the initial peak. Since this figure is used to support the use of ThT as a membrane potential indicator, and since this is the only alternative measurement of membrane potential presented in text, the authors should discuss this discrepancy in more detail.

      (2) The comparison of single cells to microcolonies presented in figures 1B and D still needs revision:

      First, both reviewer 1 and I commented in our initial reviews that the ThT traces, here and elsewhere, should not be normalized- this will help with the interpretation of some of the claims throughout the manuscript.

      Second, the way these figures are shown with all traces overlaid at full opacity makes it very difficult to see what is being compared. Since the point of the comparison is the time to first peak (and the standard deviation thereof), histograms of the distributions of time to first peak in both cases should be plotted as a separate figure panel.<br /> Third, statistical significance tests ought to be used to evaluate the statistical strength of the comparisons between these curves. The authors compare both means and standard deviations of the time to first peak, and there are appropriate statistical tests for both types of comparisons.

      (3) The authors claim that the curve shown in Fig. S4B is similar to the simulation result shown in Fig. 7B. I remain unconvinced that this is so, particularly with respect to the kinetics of the second peak- at least it seems to me that the differences should be acknowledged and discussed. In any case, the best thing to do would be to move Fig. S4B to the main text alongside Fig. 7B so that the readers can make the comparison more easily.

      (4) As I wrote in my first review, in the discussion of voltage-gated calcium channels, the authors refer to "spiking events", but these are not obvious in Figure S3E. Although the fluorescence intensity changes over time, these fluctuations cannot be distinguished from measurement noise. A no-light control could help clarify this.

      (5) In the lower irradiance conditions in Fig. 4A, the ThT dynamics are slower overall, and it looks like the ThT intensity is beginning to rise at the end of the measurement. The authors write that no second peak is observed below an irradiance threshold of 15.99 µW/mm2. However, could a more prominent second peak be observed in these cases if the measurement time was extended? Additionally, the end of these curves looks similar to the curve in Fig. S4B, in which the authors write that the slow rise is evidence of the presence of a second peak, in contrast to their interpretation here.

      Additional considerations:

      (1) The analysis and interpretation of the first peak, and particularly of the time-to-fire data is challenging throughout the manuscript the time resolution of the data set is quite limited. It seems that a large proportion of cells have already fired after a single acquisition frame. It would be ideal to increase the time resolution on this measurement to improve precision. This could be done by imaging more quickly, but that would perhaps necessitate more blue light exposure; an alternative is to do this experiment under lower blue light irradiance where the first spike time is increased (Figure 4A).

      (2) The authors suggest in the manuscript that "E. coli biofilms use electrical signalling to coordinate long-range responses to light stress." In addition to the technical caveats discussed above, I am missing a discussion about what these responses might be. What constitutes a long-range response to light stress, and are there known examples of such responses in bacteria?

      (3) The presence of long-range blue light responses can also be interrogated experimentally, for example, by repeating the Live/Dead experiment in planktonic culture or the single-cell condition. If the protection from blue light specifically emerges due to coordinated activity of the biofilm, the ∆kch mutant would not be expected to show a change in Live/Dead staining in non-biofilm conditions. The CFU experiment I mentioned above could also implicate coordinated long-range responses specifically, if biofilms and liquid culture experiments can be compared (although I know that recovering cells from biofilms is challenging.)

      4. At the end of the results section, the authors suggest a critical biofilm size of only 4 μm for wavefront propagation (not much larger than a single cell!) The authors show responses for various biofilm sizes in Fig. 2C, but these are all substantially larger (and this figure also does not contain wavefront information.) Are there data for cell clusters above and below this size that could support this claim more directly?

      (5) In Fig. 4C, the overall trajectories of extracellular potassium are indeed similar, but the kinetics of the second peak of potassium are different than those observed by ThT (it rises minutes earlier)- is this consistent with the idea that Kch is responsible for that peak? Additionally, the potassium dynamics also include the first ThT peak- is this surprising given that the Kch channel has no effect on this peak according to the model?

      Detailed comments:

      Why are Fig. 2A and Video S2 called a microcluster, whereas Video S3, which is smaller, is called a biofilm?

      "We observed a spontaneous rapid rise in spikes within cells in the center of the biofilm" (Line 140): What does "spontaneous" mean here?

      "This demonstrates that the ion-channel mediated membrane potential dynamics is a light stress relief process.", "E. coli cells employ ion-channel mediated dynamics to manage ROS-induced stress linked to light irradiation." (Line 268 and the second sentence of the Fig. 4F legend): This claim is not well-supported. There are several possible interpretations of the catalase experiment (which should be discussed); this experiment perhaps suggests that ROS impacts membrane potential but does not indicate that these membrane potential fluctuations help the cells respond to blue light stress. The loss of viability in the ∆kch mutant might indicate a link between these membrane potential experiments and viability, but it is hard to interpret without the no light controls I mention above.

      "The model also predicts... the external light stress" (Lines 338-341): Please clarify this section. Where does this prediction arise from in the modeling work? Second, I am not sure what is meant by "modulates the light stress" or "keeps the cell dynamics robust to the intensity of external light stress" (especially since the dynamics clearly vary with irradiance, as seen in Figure 4A).

      "We hypothesized that E. coli not only modulates the light-induced stress but also handles the increase of the ROS by adjusting the profile of the membrane potential dynamics" (Line 347): I am not sure what "handles the ROS by adjusting the profile of the membrane potential dynamics" means. What is meant by "handling" ROS? Is the hypothesis that membrane potential dynamics themselves are protective against ROS, or that they induce a ROS-protective response downstream, or something else? Later the authors write that changes in the response to ROS in the model agree with the hypothesis, but just showing that ROS impacts the membrane potential does not seem to demonstrate that this has a protective effect against ROS.

      "Mechanosensitive ion channels (MS) are vital for the first hyperpolarization event in E. coli." (Line 391): This is misleading- mechanosensitive ion channels totally ablate membrane potential dynamics, they don't have a specific effect on the first hyperpolarization event. The claim that mechanonsensitive ion channels are specifically involved in the first event also appears in the abstract.

      Also, the apparent membrane potential is much lower even at the start of the experiment in these mutants (Fig. 6C-D)- is this expected? This seems to imply that these ion channels also have a blue light-independent effect.

      Throughout the paper, there are claims that the initial ThT spike is involved in "registering the presence of the light stress" and similar. What is the evidence for this claim?

      "We have presented much better quantitative agreement of our model with the propagating wavefronts in E. coli biofilms..." (Line 619): It is not evident to me that the agreement between model and prediction is "much better" in this work than in the cited work (reference 57, Hennes et al. 2023). The model in Figure 4 of ref. 57 seems to capture the key features of their data.

      In methods, "Only cells that are hyperpolarized were counted in the experiment as live" (Line 745): what percentage of cells did not hyperpolarize in these experiments?

      Some indication of standard deviation (error bars or shading) should be added to all figures where mean traces are plotted.

      Video S8 is very confusing- why does the video play first forwards and then backwards? It is easy to misinterpret this as a rise in the intensity at the end of the experiment.

    1. Reviewer #3 (Public review):

      Summary:

      The manuscript shows the mechanism of action of quinofumelin, a novel fungicide, against the fungus Fusarium graminearum. Through omics analysis, phenotypic analysis, and in silico approaches, the role of quinofumelin in targeting DHODH is uncovered.

      Strengths:

      The phenotypic analysis and mutant generation are nice data and add to the role of metabolites in bypassing pyrimidine biosynthesis.

      Weaknesses:

      The role of DHODH in this class of fungicides has been known and this data does not add any further significance to the field. The work of Higashimura et al is not appreciated well enough as they already showed the role of quinofumelin upon DHODH II.

      There is no mention of the other fungicide within this class ipflufenoquin, as there is ample data on this molecule.

    1. Reviewer #3 (Public review):

      The manuscript by Pooja Popli and co-authors tested importance of Atg14 in female reproductive tract by conditionally deleting Atg14 use PrCre and also Foxj1cre. The authors showed that loss of Atg14 leads to infertility due to retention of embryos within the oviduct. The authors further concluded that the retention of embryos within the oviduct is due to pyroptosis in oviduct cells leading to defective cellular integrity. This revised version of the manuscript has addressed the remaining concerns that were raised earlier. The manuscript is now a convincing one.

    1. Reviewer #3 (Public review):

      Summary:

      The authors address the role of ORC in DNA replication and that this protein complex is not essential for DNA replication in hepatocytes. They provide evidence that ORC subunit levels are substantially reduced in cells that have been induced to delete multiple exons of the corresponding ORC gene(s) in hepatocytes. They evaluate replication both in purified isolated hepatocytes and in mice after hepatectomy. In both cases, there is clear evidence that DNA replication does not decrease at a level that corresponds with the decrease in detectable ORC subunit and that endoreduplication is the primary type of replication observed. It remains possible that small amounts of residual ORC are responsible for the replication observed, although the authors provide arguments against this possibility. The mechanisms responsible for the DNA replication observed in the absence of ORC are not examined, including why such replication would primarily be due to endoreduplication.

      Strengths:

      The authors clearly show that there are dramatic reductions in the amount of the targeted ORC subunits in the cells that have been targeted for deletion. They also provide clear evidence that there is replication in a subset of these cells and that it is likely due to endoreduplication. Although there is no replication in MEFs derived from cells with the deletion, there is clearly DNA replication occurring in hepatocytes (both isolated in culture and in the context of the liver). Interestingly, the cells undergoing replication exhibit enlarged cell sizes and elevated ploidy indicating endoreduplication of the genome. These findings raise the interesting possibility that endoreduplication does not require ORC while normal replication does.

      Weaknesses:

      There remain two significant weaknesses in this manuscript. The first is that although there is clearly robust reduction of the targeted ORC subunit, the authors cannot confirm that it is deleted in all cells. For example, the analysis in Fig. 4B would suggest that a substantial number of cells have not lost the targeted region of ORC2. In their response, the authors suggest that this is due to contaminating non-hepatocyte cells but do not provide evidence that this is the case. Although the western blots show stronger effects, this type of analysis is notorious for non-linear response curves and no standards are not provided. The second weakness is that there is no evaluation of the molecular nature of the replication observed. In response to the initial review the authors point out that a previous publication mapped Mcm2-7 loading in the absence of ORC1, ORC2 and ORC5 and saw no deficit or altered location. Unfortunately, this is not done for the mutants discussed here and this previous data supports a model that limiting residual ORC is responsible for the replication observed rather than some novel mechanism (which would be expected to alter location or amounts of loading). The manuscript provides no exploration of why "ORC-independent" replication would drive endoreduplicaiton (which is the strongest evidence for an alternative mechanism of initiation but is unique to this experiment and not the previously mutants analyzed for Mcm2-7 loading). Most importantly, it remains true that after numerous papers from this lab and others claiming that ORC is not required for eukaryotic DNA replication, we still have no information about an alternative pathway that could explain Mcm2-7 loading in the absence of ORC. Without some insights in this area, studies such as these will remain controversial.

    1. Reviewer #3 (Public review):

      Summary:

      This study examines the impact of CTRP10/C1QL2 absence on obesity and metabolic health in mice. Female mice lacking CTRP10 tend to develop obesity, particularly on a high-fat diet. Surprisingly, they do not display the typical metabolic traits associated with obesity, like fatty liver or glucose intolerance. This indicates a disconnection between weight gain and metabolic issues in these female mice. The research underscores the need to understand sex-specific factors in how obesity influences metabolic health.

      Strengths:

      The study provides compelling evidence regarding Ctrp10's role in female-specific metabolic regulation in mice, shedding light on its potential significance in metabolically healthy obese (MHO) individuals.

      Weaknesses:

      -The analysis and description of sex-specific human data require more details to highlight the relevance of Ctrp10 mouse data and the analysis of differentially expressed genes in humans.<br /> -There's a lack of analysis regarding secreted Ctrp10 under various dietary conditions.

    1. Reviewer #3 (Public review):

      Summary:

      The authors of this study provides evidence that Drosophila immune cells show upregulated SAM transmethylation pathway and adenosine recycling upon wasp infection. Blocking this pathway compromises the lamellocyte formation, developmental delay and the host survival, suggesting its physiological relevance.

      Strengths:

      Snapshot quantification of the metabolite pool does not provide evidence that the metabolic pathway is active or not. The authors use an ex vivo isotope labelling to precisely monitor the SAM and adenosine metabolism. During infection, the methionine metabolism and adenosine recycling are upregulated, which is necessary to support the immune reaction. By combining the genetic experiment, they successfully show that the pathway is activated in immune cells.

      Weaknesses:

      The authors knocked down Ahcy to prove the importance of SAM methylation pathway. However, Ahcy-RNAi produces massive accumulation of SAH, in addition to block adenosine production. To further validate the phenotypic causality, it is important to manipulate other enzymes in the pathway, such as Sam-S, Cbs, SamDC, etc. The authors do not demonstrate how infection stimulates the metabolic pathway given the gene expression of metabolic enzymes is not upregulated by infection stimulus.

    1. Reviewer #3 (Public review):

      Summary:

      This study examines the roles of Rab10 and Rab4 proteins in structural long-term potentiation (sLTP) and AMPA receptor (AMPAR) trafficking in hippocampal dendritic spines using various different methods and organotypic slice cultures as the biological model.<br /> The paper shows that Rab10 inactivation enhances AMPAR insertion and dendritic spine head volume increase during sLTP, while Rab4 supports the initial stages of these processes. The key contribution of this study is identifying Rab10 inactivation as a previously unknown facilitator of AMPAR insertion and spine growth, acting as a brake on sLTP when active. Rab4 and Rab10 seems to be playing opposing roles, suggesting a somewhat coordinated mechanism that precisely controls synaptic potentiation, with Rab4 facilitating early changes and Rab10 restricting the extent and timing of synaptic strengthening.

      Strengths:

      The study combines multiple techniques such as FRET/FLIM imaging, pharmacology, genetic manipulations and electrophysiology to dissect the roles of Rab10 and Rab4 in sLTP. The authors developed highly sensitive FRET/FLIM-based sensors to monitor Rab protein activity in single dendritic spines. This allowed them to study the spatiotemporal dynamics of Rab10 and Rab4 activity during glutamate uncaging induced sLTP. They also developed various controls to ensure the specificity of their observations. For example, they used a false acceptor sensor to verify the specificity of the Rab10 sensor response.

      This study reveals previously unknown roles for Rab10 and Rab4 in synaptic plasticity, showing their opposing functions in regulating AMPAR trafficking and spine structural plasticity during LTP.

      Weaknesses:

      In the first round of revision I raised these points:

      (1) In sLTP, the initial volume of stimulated spines is an important determinant of induced plasticity. To address changes in initial volume and those induced by uncaging, the authors present Extended Data Figure 2. In my view, the methods of fitting, sample selection, or both may pose significant limitations for interpreting the overall results. While the initial spine size distribution for Rab10 experiments spans ~0.1-0.4 fL (with an unusually large single spine at the upper end), Rab4 spine distribution spans a broader range of ~0.1-0.9 fL. If the authors applied initial size-matched data selection or used polynomial rather than linear fitting, panels a, b, e, f, and g might display a different pattern. In that case, clustering analysis based on initial size may be necessary to enable a fair comparison between groups-not only for this figure but also for main Figures 2 and 3.

      - The authors responded to this point as follows: For sensor uncaging experiments, we usually uncaged glutamate at large mushroom spines because we need to have a good signal-to-noise ratio. We just happen to choose these spines with different initial sizes for Rab4 sensor and Rab10 sensor uncaging experiments.

      Even if they happen to choose these spine sizes, it is possible to compare only those that match in size. This does not require any additional experiments. Because of this, I do not find this response satisfactory.

      (2) Another limitation is the absence of in vivo validation, as the experiments were performed in organotypic hippocampal slices, which may not fully replicate the complexity of synaptic plasticity in an intact brain, where excitatory and inhibitory processes occur concurrently. High concentrations of MNI-glutamate (4 mM in this study) are known to block GABAergic responses due to its antagonistic effect on GABA-A receptors, thereby precluding the study of inhibitory network activity or connectivity, which is already known to be altered in organotypic slice cultures.

      - I found the Authors following response reasonable and useful:

      We appreciate the reviewer's comments and would like to clarify that we have conducted experiments in acute slices for LTP using conditional Rab10 knockout (Fig. 4k, 4l), and we obtained similar results. Additionally, we have recently published findings on the behavioral deficits observed in heterozygous Rab10 knockout mice (PubMed 37156612). These studies further support our conclusions and provide additional context for our findings.

    1. Reviewer #3 (Public review):

      Brickwedde et al. attempt to clarify the role of alpha in sensory gain modulation by exploring the relationship between attention-related changes in alpha and attention-related changes in sensory-evoked responses, which surprisingly few studies have examined given the prevalence of the alpha inhibition hypothesis. The authors use robust methods and provide novel evidence that alpha likely exhibits inhibitory control over later processing, as opposed to early sensory processing, by providing source-localization data in a cross-modal attention task.

      This paper seems very strong, particularly given that the follow-up MEG study both (a) clarifies the task design and separates the effect of distractor stimuli into other experimental blocks, and (b) provides source-localization data to more concretely address whether alpha inhibition is occurring at or after the level of sensory processing, and (c) replicates most of the EEG study's key findings.

      There are some points that would be helpful to address to bolster the paper. First, the introduction would benefit from a somewhat deeper review of the literature, not just reviewing when the effects of alpha seem to occur, but also addressing how the effect can change depending on task and stimulus design (see review by Morrow, Elias & Samaha (2023). Additionally, the discussion could benefit from more cautionary language around the revision of the alpha inhibition account. For example, it would be helpful to address some of the possible discrepancies between alpha and SSEP measures in terms of temporal specificity, SNR, etc. (see Peylo, Hilla, & Sauseng, 2021). The authors do a good job speculating as to why they found differing results from previous cross-modal attention studies, but I'm also curious whether the authors think that alpha inhibition/modulation of sensory signals would have been different had the distractors been within the same modality or whether the cues indicated target location, rather than just modality, as has been the case in so much prior work?

      Overall, the analyses and discussion are quite comprehensive, and I believe this paper to be an excellent contribution to the alpha-inhibition literature.

    1. Reviewer #3 (Public review):

      Summary:

      Zafirova et al. investigated the interaction of head and body orientation in the macaque superior temporal sulcus (STS). Combining fMRI and electrophysiology, they recorded responses of visual neurons to a monkey avatar with varying head and body orientations. They found that STS neurons integrate head and body information in a nonlinear way, showing selectivity for specific combinations of head-body orientations. Head-body configuration angles can be reliably decoded, particularly for neurons in the anterior STS. Furthermore, body inversion resulted in reduced decoding of head-body configuration angles. Compared to previous work that examined face or body alone, this study demonstrates how head and body information are integrated to compute a socially meaningful signal.

      Strengths:

      This work presents an elegant design of visual stimuli, with a monkey avatar of varying head and body orientations, making the analysis and interpretation straightforward. Together with several control experiments, the authors systematically investigated different aspects of head-body integration in the macaque STS. The results and analyses of the paper are mostly convincing.

      Weaknesses:

      (1) Using ANOVA, the authors demonstrate the existence of nonlinear interactions between head and body orientations. While this is a conventional way of identifying nonlinear interactions, it does not specify the exact type of the interaction. Although the computation of the head-body configuration angle requires some nonlinearity, it's unclear whether these interactions actually contribute. Figure 3 shows some example neurons, but a more detailed analysis is needed to reveal the diversity of the interactions. One suggestion would be to examine the relationship between the presence of an interaction and the neural encoding of the configuration angle.

      (2) Figure 4 of the paper shows a better decoding of the configuration angle in the anterior STS than in the middle STS. This is an interesting result, suggesting a transformation in the neural representation between these two areas. However, some control analyses are needed to further elucidate the nature of this transformation. For example, what about the decoding of head and body orientations - dose absolute orientation information decrease along the hierarchy, accompanying the increase in configuration information?

      (3) While this work has characterized the neural integration of head and body information in detail, it's unclear how the neural representation relates to the animal's perception. Behavioural experiments using the same set of stimuli could help address this question, but I agree that these additional experiments may be beyond the scope of the current paper. I think the authors should at least discuss the potential outcomes of such experiments, which can be tested in future studies.

    1. Reviewer #3 (Public review):

      Summary:

      Nucleotide modifications are important regulators of biological function, however, until recently, their study has been limited by the availability of appropriate analytical methods. Oxford Nanopore direct RNA sequencing preserves nucleotide modifications, permitting their study, however, many different nucleotide modifications lack an available base-caller to accurately identify them. Furthermore, existing tools are computationally intensive, and their results can be difficult to interpret.

      Cheng et al. present SegPore, a method designed to improve the segmentation of direct RNA sequencing data and boost the accuracy of modified base detection.

      Strengths:

      This method is well-described and has been benchmarked against a range of publicly available base callers that have been designed to detect modified nucleotides.

      Weaknesses:

      However, the manuscript has a significant drawback in its current version. The most recent nanopore RNA base callers can distinguish between different ribonucleotide modifications, however, SegPore has not been benchmarked against these models.

      I recommend that re-submission of the manuscript that includes benchmarking against the rna004_130bps_hac@v5.1.0 and rna004_130bps_sup@v5.1.0 dorado models, which are reported to detect m5C, m6A_DRACH, inosine_m6A and PseU.

      A clear demonstration that SegPore also outperforms the newer RNA base caller models will confirm the utility of this method.

    1. Reviewer #3 (Public review):

      Summary:

      In this paper, Rethemeier et al capitalize on their previous observation that the beetle central complex develops heterochronically compared to the fly and try to identify the developmental origin of this difference. For this reason, they use a fez enhancer trap line that they generated to study the neuronal stem cells (INPs) that give rise to the central complex. Using this line and staining against Drosophila type-II neuroblast markers, they elegantly dissect the number of developmental progression of the beetle type II neuroblasts. They show that the NBs, INPs, and GMCs have a conserved marker progression by comparing to Drosophila marker genes, although the expression of some of the lineage markers (otd, six3, and six4) is slightly different. Finally, they show that the beetle type II neuroblasts lineages are likely longer than the equivalent ones in Drosophila and argue that this might be the underlying reason for the observed heterochrony.

      Strengths:

      - Very interesting study system that compares a conserved structure that, however, develops in a heterochronic manner.<br /> - Identification of a conserved molecular signature of type-II neuroblasts between beetles and flies. At the same time, identification of transcription factors expression differences in the neuroblasts, as well as identification of an extra neuroblast.<br /> - Nice detailed experiments to describe the expression of conserved and divergent marker genes, including some lineaging looking into co-expression of progenitor (fez) and neuronal (skh) markers.

      Weaknesses:

      - The link between size and number of neuroblast lineages and the earlier central complex development in beetles is not examined.

    1. Reviewer #3 (Public review):

      The authors aim to understand how gene pleiotropy affects parallel evolutionary changes among independent replicates of adaptation to a new hot environment of a set of experimental lines of Drosophila simulans using experimental evolution. The flies were RNAsequenced after more than 100 generations of lab adaptation and the changes in average gene expression were obtained relative to ancestral expression levels from reconstructed ancestral lines. Parallelism of gene expression change among lines is evaluated as variance in differential gene expression among lines relative to error variance. Similarly, the authors ask how the standing variation in gene expression estimated from a handful of flies from a reconstructed outbred line affects parallelism. The main findings are that parallelism in gene expression responses is positively associated with pleiotropy and negatively associated with expression variation. Those results are in contradiction with theoretical predictions and empirical findings. To explain those seemingly contradictory results the authors invoke the role of synergistic pleiotropy and correlated selection, although they do not attempt to measure either.

      Strengths:

      The study uses highly replicated outbred laboratory lines of Drosophila simulans evolved in the lab under constant hot regime for over 100 generations. This allows for robust comparisons of evolutionary responses among lines.

      The manuscript is well written and the hypotheses are clearly delineated at the onset.

      The authors have run a causal analysis to understand the causal dependencies between pleiotropy and expression variation on parallelism.

      The use of whole-body RNA extraction to study gene expression variation is well justified.

      Weaknesses:

      The accuracy of the estimate of ancestral phenotypic variation in gene expression is likely low because estimated from a small sample of 20 males from a reconstructed outbred line. It might not constitute a robust estimate of the genetic variation of the evolved lines under study.

      There are no estimates of the standing genetic variation of expression levels of the genes under study, only estimates of their phenotypic variation. I wished the authors had been clear about that limitation and had refrained from equating phenotypic variation in expression level with standing genetic variation.

      Moreover, since the phenotype studied is gene expression, its genetic basis extends beyond expressed sequences. The phenotypic variation of a gene's expression may thus likely misrepresent the genetic variation available for its evolution. The authors do not present evidence that sequence variation correlates with expression variation.

      The authors have not attempted to estimate synergistic pleiotropy among genes, nor how selection acts on gene expression modules. It makes their conclusion regarding the role of synergistic pleiotropy rather speculative.

    1. Reviewer #3 (Public review):

      The authors apply multivoxel decoding analyses from fMRI during reward feedback about the cues previously chosen that led to that feedback. They compare two versions of the task - one in which the feedback is provided about the current trial, and one in which the feedback is provided about the previous trial. Reward probability changes slowly over time, so subjects need to identify which cues are leading to reward at a given time. They find that evidence for recall of the cue in lateral orbitofrontal cortex (lOFC) and hippocampus (HC). They also find that in the second condition, where feedback is for the one-back trial, this representation is mediated by the lateral frontal pole (FPl).

      Overall, the analyses are clean and elegant and seem to be complete. I have only a few comments, all of which can be public.

      (1) They do find (not surprisingly) that the one-back task is harder. It would be good to ensure that the reason that they had more trouble detecting direct HC & lOFC effects on the harder task was not because the task is harder and thus that there are more learning failures on the harder one-back task. (I suspect their explanation that it is mediated by FPl is likely to be correct. But it would be nice to do some subsampling of the zero-back task [matched to the success rate of the one-back task] to ensure that they still see the direct HC and lOFC there.)

      (2) The evidence that they present in the main text (Figure 3) that the HC and lOFC are mediated by FPl is a correlation. I found the evidence presented in Supplemental Figure 7 to be much more convincing. As I understand it, what they are showing in SF7 is that when FPl decodes the cue, then (and only then) HC and lOFC decode the cue. If my understanding is correct, then this is a much cleaner explanation for what is going on than the secondary correlation analysis. If my understanding here is incorrect, then they should provide a better explanation of what is going on so as to not confuse the reader.

      (3) I like the idea of "credit spreading" across trials (Figure 1E). I think that credit spreading in each direction (into the past [lower left] and into the future [upper right]) is not equivalent. This can be seen in Figure 1D, where the two tasks show credit spreading differently. I think a lot more could be studied here. Does credit spreading in each of these directions decode in interesting ways in different places in the brain?

      Comments on revisions:

      After revision, I have no additional comments.

    1. Reviewer #3 (Public review):

      Summary:

      The authors applied an innovative approach (CO-Detection by indEXing - CODEX) together with sophisticated computational analyses to image pancreas tissues from rare organ donors with type 1 diabetes. They aimed to assess key features of inflammation in both islet and extra-islet tissue areas; they report that the extra-islet space of lobules with extensive islet infiltration differs from the extra-islet space of less infiltrated areas within the same tissue section. The study also identifies four sub-states of inflamed islets characterized by the activation profiles of CD8+T cells enriched in islets relative to the surrounding tissue. Lymphoid structures are identified in the pancreas tissue away from islets, and these were enriched in CD45RA+ T cells - a population also enriched in one of the inflamed islet sub-states. Together, these data help define the coordination between islets and the extra-islet pancreas in the pathogenesis of human T1D.

      Strengths:

      The analysis of tissue from well-characterized organ donors, provided by the Network for the Pancreatic Organ Donor with Diabetes, adds strength to the validity of the findings.

      By using their innovative imaging/computation approaches, key known features of islet autoimmunity were confirmed, providing validation of the methodology.

      The detection of IDO+ vasculature in inflamed islets - but not in normal islets or islets that have lost insulin-expression links this expression to the islet inflammation, and it is a novel observation. IDO expression in the vasculature may be induced by inflammation and may lost as disease progresses, and it may provide a potential therapeutic avenue.

      The high-dimensional spatial phenotyping of CD8+T cells in T1D islets confirmed that most T cells were antigen experienced. Some additional subsets were noted: a small population of T cells expressing CD45RA and CD69, possibly naive or TEMRA cells, and cells expressing Lag-3, Granzyme-B, and ICOS.

      While much attention has been devoted to the study of the insulitis lesion in T1D, our current knowledge is quite limited; the description of four sub-clusters characterized by the<br /> activation profile of the islet-infiltrating CD8+T cells is novel. Their presence in all T1D donors, indicates that the disease process is asynchronous and is not at the same stage across all islets. Although this concept is not novel, this appears to be the most advanced characterization of insulitis stages.

      When examining together both the exocrine and islet areas, which is rarely done, authors report that pancreatic lobules affected by insulitis are characterized by distinct tissue markers. Their data support the concept that disease progression may require crosstalk between cells in the islet and extra-islet compartments. Lobules enriched in β-cell-depleted islets were also enriched in nerves, vasculature, and Granzyme-B+/CD3- cells, which may be natural killer cells.

      Lastly, authors report that immature tertiary lymphoid structures (TLS) exist both near and away from islets, where CD45RA+ CD8+T cells aggregate, and also observed an inflamed islet-subcluster characterized by an abundance of CD45RA+/CD8+ T cells. These TLS may represent a point of entry for T cells and this study further supports their role in islet autoimmunity.

      Weaknesses:

      As the author themselves acknowledge, the major limitation is that the number of donors examined is limited as those satisfying study criteria are rare. Thus, it is not possible to examine disease heterogeneity, and the impact of age at diagnosis. Of 8 T1D donors examined, 4 would be considered newly diagnosed (less than 3 months from onset) and 4 had longer disease durations (2, 2, 5 and 6 years). It was unclear if disease duration impacted the results in this small cohort. In the introduction, the authors discuss that most of the pancreata from nPOD donors with T1D lack insulitis. This is correct, yet it is a function of time from diagnosis. Donors with shorter duration will be more likely to have insulitis. A related point is that the proportion of islets with insulitis is low even near diagnosis, Finally, only one donor was examined that while not diagnosed with T1D, was likely in the preclinical disease stage and had autoantibodies and insulitis. This is a critically important disease stage where the methodology developed by the investigators could be applied in future efforts.

      While this was not the focus of this investigation, it appears that the approach was very much immune-focused and there could be value in examining islet cells in greater depth using the methodology the authors developed.

      Additional comments

      Overall, the authors were able to study pancreas tissues from T1D donors and perform sophisticated imaging and computational analysis that reproduce and importantly extend our understanding of inflammation in T1D. Despite the limitations associated with the small sample size, the results appear robust, and the claims are well supported.

      The study expands the conceptual framework of inflammation and islet autoimmunity, especially by the definition of different clusters (stages) of insulitis and by the characterization of immune cells in and outside the islets.

      Comments on revisions:

      I have not felt the need to update the initial review.

      However, I note that the paragraph describing the nPOD repository (lines 154-158) can be misinterpreted that insulitis is infrequent in T1D (17 of 200 donors had it) without the clarification that insulitis is present around the time of diagnosis in most patients and it subsides over time. Thus, authors are urged to clarify that the presence of insulitis and its severity are impacted by the disease stage and disease duration.

      The last sentence of this paragraph, lines 164-165, although linked to the previous sentence about the cause of death in the donors, may be misconstrued in the context of this paragraph, and it is unclear what data support this statement. Please delete this sentence.

    1. Reviewer #3 (Public review):

      Summary:

      Ruan and colleagues consider a branching process model (in their terminology the "Haldane model") and the most basic Wright-Fisher model. They convincingly show that offspring distributions are usually non-Poissonian (as opposed to what's assumed in the Wright-Fisher model), and can depend on short-term ecological dynamics (e.g., variance in offspring number may be smaller during exponential growth). The authors discuss branching processes and the Wright-Fisher model in the context of 3 "paradoxes" --- 1) how Ne depends on N might depend on population dynamics; 2) how Ne is different on the X chromosome, the Y chromosome, and the autosomes, and these differences do match the expectations base on simple counts of the number of chromosomes in the populations; 3) how genetic drift interacts with selection. The authors provide some theoretical explanations for the role of variance in the offspring distribution in each of these three paradoxes. They also perform some experiments to directly measure the variance in offspring number, as well as perform some analyses of published data.

      Strengths:

      - The theoretical results are well-described and easy to follow.<br /> - The analyses of different variances in offspring number (both experimentally and analyzing public data) are convincing that non-Poissonian offspring distributions are the norm.<br /> - The point that this variance can change as the population size (or population dynamics) change is also very interesting and important to keep in mind.<br /> - I enjoyed the Density-Dependent Haldane model. It was a nice example of the decoupling of census size and effective size.<br /> - Equation (10) is a nice result

      Comments on revisions:

      I appreciate the effort that the authors have put into the revision, but I still find the framing to be a bit confusing -- these apparent paradoxes only appear in the most basic version of Wright-Fisher models, and so framing the paper as the solution to these paradoxes overlooks much previous work. Saying that existing work discussing exactly these phenomena is "beyond the scope of this study", without citing or interacting in any way with that work is unscholarly. I agree with the authors that the apparent paradoxes that they consider and interesting, and by thinking about branching processes, the apparent paradoxes appear to be less paradoxical, but without contextualizing this work in the substantial Wright-Fisher literature (e.g., Cannings Exchangeable Models and the work of Möhle) it misrepresents the state of the field and the contributions of this paper.

    1. Reviewer #3 (Public review):

      Summary:

      Notch is active in HCC, but generally not mutated. The authors use a JAG1-selective blocking antibody in a large panel of liver cancer patient-derived xenograft models. They find JAG-dependent HCCs, and these are aggressive and proliferative. Notch inhibition induces cycle arrest and promotes hepatocyte differentiation, through upregulation of CEBPA expression and activation of existing HNF4A, mimicking normal developmental programs.

      The authors use aJ1.b70, a potent and selective therapeutic antibody that inhibits JAG1 against PDX models. They tested over 40 PDX models and found a handful of super-responders to single-agent inhibition. In LIV78 and Li1035 cancer cells, NOTCH2 was expressed and required, in contrast to NOTCH1. RNA-seq showed that the responsive HCCs resembled the S2 transcriptional class of HCCs, which were enriched for Notch-dependent models. They conclude that these dependent tumors have transcriptomes that resemble a hybrid progenitor cell expressing FGF9 and GAS7. Inhibition was able to induce hepatocyte differentiation away from a NOTCH-driven progenitor program. scRNA-seq analysis showed a large population of NOTCH-JAG expressing cells but also showed that there are cells that did not. Not surprisingly, NOTCH2 inhibition leads to increased CEBPA and HNF4A transcriptional activity, which are standard TFs in hepatocytes.

      Strengths:

      The paper provides useful information about the frequency of HCCs and CCA that respond to NOTCH inhibition and could allow us to anticipate the super-responder rate if these antibodies were actually used in the clinic. The inhibitor tools are highly specific, and provide useful information about NOTCH activities in liver cancers. The large number of PDXs and the careful transcriptomic analyses were positives about the study.

      Weaknesses:

      The paper is mostly descriptive.

    1. Reviewer #3 (Public review):

      In this study, Cao et al. explore the neural mechanisms by which chronic heat exposure induces negative valence and hyperarousal in mice, focusing on the role of the posterior paraventricular nucleus (pPVT) neurons that receive projections from the preoptic area (POA). The authors show that chronic heat exposure leads to heightened activity of the POA projection-receiving pPVT neurons, potentially contributing to behavioral changes such as increased anxiety level and reduced sociability, along with heightened startle responses. In addition, using electrophysiological methods, the authors suggest that increased membrane excitability of pPVT neurons may underlie these behavioral changes. The use of a variety of behavioral assays enhances the robustness of their claim. Moreover, while previous research on thermoregulation has predominantly focused on physiological responses to thermal stress, this study adds a unique and valuable perspective by exploring how thermal stress impacts affective states and behaviors, thereby broadening the field of thermoregulation.

      While the manuscript has been revised and some efforts have been made to address the reviewers' concerns, the majority of the issues raised remain insufficiently resolved. Therefore, the reviewer has highlighted key major points that the authors should address to strengthen the manuscript's conclusions.

      Major points<br /> The manuscript highlights the increased activity in pPVT neurons receiving projections from the POA (Figure 3) and shows that these neurons are necessary for heat-induced behavioral changes (Figures 4N-W). However, it remains unclear whether the POA-to-pPVT projection itself plays a critical role. Since pPVT recipient neurons can receive inputs from various brain regions, the role of the POA input in driving these effects needs to be validated more explicitly.<br /> (1) To establish this, the authors should conduct experiments directly inhibiting the POA-to-pPVT projection and demonstrate whether the increased activity in pPVT neurons due to chronic heat exposure is abolished when the POA is blocked.<br /> (2) Alternatively, the authors could use anterograde labeling from the POA and specifically target recipient neurons in the pPVT to confirm that the observed excitatory inputs originate from the POA (related to Figure 6).<br /> (3) If these experiments are not feasible, the authors should consider toning down the emphasis on the POA's role throughout the manuscript and discussing this limitation explicitly. The term "POA recipient pPVT neurons" should be used consistently to avoid misleading implications that the POA-to-pPVT excitatory projection is definitively established as the key pathway.<br /> a) For example, in lines 368-369, the phrase "The increase in presynaptic excitability of the POA to pPVT excitatory pathway" represents a logical jump, as the data only support the "differential increase in presynaptic excitability of the excitatory pathway" (as described in lines 358-359) without specifically confirming the POA-to-pPVT pathway.<br /> b) Similarly, in lines 442-446, the statement "the role of excitatory projections from POA to pPVT in chronic heat exposure-induced emotional changes" should be revised to "the role of excitatory projection recipient pPVT in chronic heat~," as the data do not provide direct evidence that heat-responsive POA neurons projecting to pPVT mediate these effects. Such revisions would improve clarity and ensure that the conclusions remain aligned with the presented data.

    1. Reviewer #3 (Public review):

      Summary:

      The authors used cTBS TMS, magnetic resonance spectroscopy (MRS), and functional magnetic resonance imaging (fMRI) as the main methods of investigation. Their data show that cTBS modulates GABA concentration and task-dependent BOLD in the ATL, whereby greater GABA increase following ATL cTBS showed greater reductions in BOLD changes in ATL. This effect was also reflected in the performance of the behavioural task response times, which did not subsume to practice effects after AL cTBS as opposed to the associated control site and control task. This is in line with their first hypothesis. The data further indicates that regional GABA concentrations in the ATL play a crucial role in semantic memory because individuals with higher (but not excessive) GABA concentrations in the ATLs performed better on the semantic task. This is in line with their second prediction. Finally, the authors conducted additional analyses to explore the mechanistic link between ATL inhibitory GABAergic action and semantic task performance. They show that this link is best captured by an inverted U-shaped function as a result of a quadratic linear regression model. Fitting this model to their data indicates that increasing GABA levels led to better task performance as long as they were not excessively low or excessively high. This was first tested as a relationship between GABA levels in the ATL and semantic task performance; then the same analyses were performed on the pre and post-cTBS TMS stimulation data, showing the same pattern. These results are in line with the conclusions of the authors.

      Comments on revisions:

      The authors have comprehensively addressed my comments from the first round of review, and I consider most of their answers and the steps they have taken satisfactorily. Their insights prompted me to reflect further on my own knowledge and thinking regarding the ATL function.

      I do, however, have an additional and hopefully constructive comment regarding the point made about the study focusing on the left instead of bilateral ATL. I appreciate the methodological complexities and the pragmatic reasons underlying this decision. Nevertheless, briefly incorporating the justification for this decision into the manuscript would have been beneficial for clarity and completeness. The presented argument follows an interesting logic; however, despite strong previous evidence supporting it, the approach remains based on an assumption. Given that the authors now provide the group-level fMRI results captured more comprehensively in Supplementary Figure 2, where the bilateral pattern of fMRI activation can be observed in the current data, the authors could have strengthened their argument by asserting that the activation related to the given semantic association task in this data was bilateral. This would imply that the TMS effects and associated changes in GABA should be similar for both sites. Furthermore, it is worth noting the approach taken by Pobric et al. (2007, PNAS), who stimulated a site located 10 mm posterior to the tip of the left temporal pole along the middle temporal gyrus (MTG) and not the bilateral ATL.

    1. Reviewer #3 (Public review):

      A bias in how people infer the amount of control they have over their environment is widely believed to be a key component of several mental illnesses including depression, anxiety, and addiction. Accordingly, this bias has been a major focus in computational models of those disorders. However, all of these models treat control as a unidimensional property, roughly, how strongly outcomes depend on action. This paper proposes---correctly, I think---that the intuitive notion of "control" captures multiple dimensions in the relationship between action and outcome is multi-dimensional. In particular, the authors propose that the degree to which outcome depends on how much *effort* we exert, calling this dimension the "elasticity of control". They additionally propose that this dimension (rather than the more holistic notion of controllability) may be specifically impaired in certain types of psychopathology. This idea thus has the potential to change how we think about mental disorders in a substantial way, and could even help us better understand how healthy people navigate challenging decision-making problems.

      Unfortunately, my view is that neither the theoretical nor empirical aspects of the paper really deliver on that promise. In particular, most (perhaps all) of the interesting claims in the paper have weak empirical support.

      Starting with theory, the elasticity idea does not truly "extend" the standard control model in the way the authors suggest. The reason is that effort is simply one dimension of action. Thus, the proposed model ultimately grounds out in how strongly our outcomes depend on our actions (as in the standard model). Contrary to the authors' claims, the elasticity of control is still a fixed property of the environment. Consistent with this, the computational model proposed here is a learning model of this fixed environmental property. The idea is still valuable, however, because it identifies a key dimension of action (namely, effort) that is particularly relevant to the notion of perceived control. Expressing the elasticity idea in this way might support a more general theoretical formulation of the idea that could be applied in other contexts. See Huys & Dayan (2009), Zorowitz, Momennejad, & Daw (2018), and Gagne & Dayan (2022) for examples of generalizable formulations of perceived control.

      Turning to experiment, the authors make two key claims: (1) people infer the elasticity of control, and (2) individual differences in how people make this inference are importantly related to psychopathology.

      Starting with claim 1, there are three sub-claims here; implicitly, the authors make all three. (1A) People's behavior is sensitive to differences in elasticity, (1B) people actually represent/track something like elasticity, and (1C) people do so naturally as they go about their daily lives. The results clearly support 1A. However, 1B and 1C are not supported.

      Starting with 1B, the experiment cannot support the claim that people represent or track elasticity because the effort is the only dimension over which participants can engage in any meaningful decision-making (the other dimension, selecting which destination to visit, simply amounts to selecting the location where you were just told the treasure lies). Thus, any adaptive behavior will necessarily come out in a sensitivity to how outcomes depend on effort. More concretely, any model that captures the fact that you are more likely to succeed in two attempts than one will produce the observed behavior. The null models do not make this basic assumption and thus do not provide a useful comparison.

      For 1C, the claim that people infer elasticity outside of the experimental task cannot be supported because the authors explicitly tell people about the two notions of control as part of the training phase: "To reinforce participants' understanding of how elasticity and controllability were manifested in each planet, [participants] were informed of the planet type they had visited after every 15 trips." (line 384).

      Finally, I turn to claim 2, that individual differences in how people infer elasticity are importantly related to psychopathology. There is much to say about the decision to treat psychopathology as a unidimensional construct. However, I will keep it concrete and simply note that CCA (by design) obscures the relationship between any two variables. Thus, as suggestive as Figure 6B is, we cannot conclude that there is a strong relationship between Sense of Agency and the elasticity bias---this result is consistent with any possible relationship (even a negative one). The fact that the direct relationship between these two variables is not shown or reported leads me to infer that they do not have a significant or strong relationship in the data.

      There is also a feature of the task that limits our ability to draw strong conclusions about individual differences in elasticity inference. As the authors clearly acknowledge, the task was designed "to be especially sensitive to overestimation of elasticity" (line 287). A straightforward consequence of this is that the resulting *empirical* estimate of estimation bias (i.e., the gamma_elasticity parameter) is itself biased. This immediately undermines any claim that references the directionality of the elasticity bias (e.g. in the abstract). Concretely, an undirected deficit such as slower learning of elasticity would appear as a directed overestimation bias.

      When we further consider that elasticity inference is the only meaningful learning/decision-making problem in the task (argued above), the situation becomes much worse. Many general deficits in learning or decision-making would be captured by the elasticity bias parameter. Thus, a conservative interpretation of the results is simply that psychopathology is associated with impaired learning and decision-making.

      Minor comments:

      Showing that a model parameter correlates with the data it was fit to does not provide any new information, and cannot support claims like "a prior assumption that control is likely available was reflected in a futile investment of resources in uncontrollable environments." To make that claim, one must collect independent measures of the assumption and the investment.

      Did participants always make two attempts when purchasing tickets? This seems to violate the intuitive model, in which you would sometimes succeed on the first jump. If so, why was this choice made? Relatedly, it is not clear to me after a close reading how the outcome of each trial was actually determined.

      It should be noted that the model is heuristically defined and does not reflect Bayesian updating. In particular, it overestimates control by not using losses with less than 3 tickets (intuitively, the inference here depends on your beliefs about elasticity). I wonder if the forced three-ticket trials in the task might be historically related to this modeling choice.

    1. Reviewer #3 (Public review):

      Summary:

      This is a retrospective analysis of 53 individuals over 26 features (12 clinical phenotypes, 12 CGM features, and 2 autocorrelation features) to examine which features were most informative in predicting percent necrotic core (%NC) as a parameter for coronary plaque vulnerability. Multiple regression analysis demonstrated a better ability to predict %NC from 3 selected CGM-derived features than 3 selected clinical phenotypes. LASSO regularization and partial least squares (PLS) with VIP scores were used to identify 4 CGM features that most contribute to the precision of %NC. Using factor analysis they identify 3 components that have CGM-related features: value (relating to the value of blood glucose), variability (relating to glucose variability), and autocorrelation (composed of the two autocorrelation features). These three groupings appeared in the 3 validation cohorts and when performing hierarchical clustering. To demonstrate how these three features change, a simulation was created to allow the user to examine these features under different conditions.

      Review:

      The goal of this study was to identify CGM features that relate to %NC. Through multiple feature selection methods, they arrive at 3 components: value, variability, and autocorrelation. While the feature list is highly correlated, the authors take steps to ensure feature selection is robust. There is a lack of clarity of what each component (value, variability, and autocorrelation) includes as while similar CGM indices fall within each component, there appear to be some indices that appear as relevant to value in one dataset and to variability in the validation. We are sceptical about statements of significance without documentation of p-values. While hesitations remain, the ability of these authors to find groupings of these many CGM metrics in relation to %NC is of interest. The believability of the associations is impeded by an obtuse presentation of the results with core data (i.e. correlation plots between CGM metrics and %NC) buried in the supplement while main figures contain plots of numerical estimates from models which would be more usefully presented in supplementary tables. Given the small sample size in the primary analysis, there is a lot of modeling done with parameters estimated where simpler measures would serve and be more convincing as they require less data manipulation. A major example of this is that the pairwise correlation/covariance between CGM_mean, CGM_std, and AC_var is not shown and would be much more compelling in the claim that these are independent factors. Lack of methodological detail is another challenge. For example, the time period of CGM metrics or CGM placement in the primary study in relation to the IVUS-derived measurements of coronary plaques is unclear. Are they temporally distant or proximal/ concurrent with the PCI? A patient undergoing PCI for coronary intervention would be expected to have physiological and iatrogenic glycemic disturbances that do not reflect their baseline state. This is not considered or discussed. The attempts at validation in external cohorts, Japanese, American, and Chinese are very poorly detailed. We could only find even an attempt to examine cardiovascular parameters in the Chinese data set but the outcome variables are unspecified with regard to what macrovascular events are included, their temporal relation to the CGM metrics, etc. Notably macrovascular event diagnoses are very different from the coronary plaque necrosis quantification. This could be a source of strength in the findings if carefully investigated and detailed but due to the lack of detail seems like an apples-to-oranges comparison. Finally, the simulations at the end are not relevant to the main claims of the paper and we would recommend removing them for the coherence of this manuscript.

    1. Reviewer #3 (Public review):

      Summary:

      Ribosomes are generally considered homogeneous complexes with no inherent role in regulating translation. However, recent studies have found heterogeneity in the composition of ribosome accessory factors, proteins, and ribosomal RNA. Moreover, there is evidence that district ribosomal isoforms are produced at different developmental stages in Xenopus, Drosophila, and zebrafish. In Drosophila, germline-derived ribosomes have a different protein composition to those produced by somatic cell types. In zebrafish, germline vs. somatic ribosomes have been shown to incorporate distinct rRNA isoforms. However, the functional significance of ribosome heterogeneity is not known.

      The manuscript by Shah et al., uses the power of the zebrafish to test the hypothesis that maternal ribosome isoforms have a distinct function relative to ribosome isoforms produced by somatic cells after the maternal-to-zygotic transition (MTZ). They confirm previous findings that all maternal rRNA are derived from the maternal-specific rRNA locus on Chromosome 4. Additionally, proteomic analysis showed that maternal and somatic ribosomes also differ in protein composition. Using ribosome tagging experiments they showed that maternally derived subunits can form functional heteroduplexes (hybrids) with somatic-derived subunits. Finally, they show that maternal-derived ribosomes continue to be expressed in germ cells where they preferentially associate with the maternally derived and germline localized nanos3 mRNA. This suggests a possible role of maternal ribosomes in germ cell-specific translational regulation.

      Strengths:

      The authors use the experimental power of zebrafish to test the hypothesis that maternal and somatic-derived ribosomes have distinct functions. They use state-of-the art proteomics, molecular modeling, and transgenesis techniques. For the most part, the data presented is clear and supports their conclusions.

      Weaknesses:

      Using pulldown experiments they show that maternal ribosomes associate with the PGC-enriched nanos3 RNA, suggesting a role for the maternal isoform in germline-specific translation. However, they acknowledge that the level of enrichment is similar to the level of maternal vs. somatic isoforms that localize to PGCs. The nanos3 mRNA is unique in that it is actively degraded in somatic cells shortly after MTZ so is never present in cells that express the somatic isoforms. Therefore, the association of nanos3 with maternal ribosomes shows that these ribosomes can associate with germline-specific RNAs, but does not provide compelling evidence for a maternal isoform-specific role in translational regulation.

    1. Reviewer #3 (Public review):

      Summary:

      Dong et al. described a deep learning-based framework of antimicrobial (AMP) generator and regressor to design and rank de novo antimicrobial peptides (AMPs). For generated AMPs, they predicted their minimum inhibitory concentration (MIC) using a model that combines the Morgan fingerprint, contact map and ESM language model. For their selected AMPs based on predicted MIC, they also use a combination of antiviral peptide (AVP) prediction models to select AMPs with potential antiviral activity. They experimentally validated 3 candidates for antimicrobial activity against S. aureus, A. baumannii, E. coli, and P. aeruginosa, and their toxicity on mouse blood and three human cell lines. The authors select their most promising AMP (P076) for in vivo experiments in A. baumannii-infected mice. They finally test the antiviral activity of their 3 AMPs against viruses.

      Strengths:

      - The development of de novo antimicrobial peptides (AMPs) with the novelty of being bifunctional (antimicrobial and antiviral activity).

      - Novel, combined approach to AMP activity prediction from their amino acid sequence.

      Weaknesses:

      - I missed the justification for combined antiviral and antibacterial activities. As the authors responded, less than 10% of the training data has antiviral activity. Therefore, I do not understand how the high percentage of antiviral activities was achieved. Especially reading that the antiviral filtering did not have an influence on the number of antiviral peptides obtained.

      - I had difficulty in reading the story because of the use of acronyms without referring to their full name for the first time, and incomplete information annotation in figures and captions.

  3. Feb 2025
    1. Reviewer #3 (Public review):

      Summary:

      In this study, Li et al. identified CAD96CA and FGF1 among 20 receptor tyrosine kinase receptors as mediators of JH signaling. By performing a screen in HaEpi cells with overactivated JH signaling, the authors pinpointed two main RTKs that contribute to the transduction of JH. Using the CRISPR/Cas9 system to generate mutants, the authors confirmed that these RTKs are required for normal JH activation, as precocious pupariation was observed in their absence. Additionally, the authors demonstrated that both CAD96CA and FGF1 exhibit a high affinity for JH, and their activation is necessary for the proper phosphorylation of Tai and Met, transcription factors that promote the transcriptional response. Finally, the authors provided evidence suggesting that the function of CAD96CA and FGF1 as JH receptors is conserved across insects.

      Strengths:

      The data provided by the authors are convincing and support the main conclusions of the study, providing ample evidence to demonstrate that phosphorylation of the transducers Met and Tai mainly depends on the activity of two RTKs. Additionally, the binding assays conducted by the authors support the function of CAD96CA and FGF1 as membrane receptors of JH. The study's results validate, at least in H. amigera, the predicted existence of membrane receptors for JH.

      Weaknesses:

      The authors have provided evidences that the Cad96Ca and FGF1 RTK receptors contribute to JH signaling through CRISPR/Cas9, inducing precocious metamorphosis, although not to the same extent as absence of JH. Therefore, it still remains unclear whether these RTKs are completely required for pathway activation or only necessary for high activation levels during the last larval stage.

      While the authors have included some additional data, the mechanism by which different RTKs function in transducing JH signaling in a tissue specific manner is still unclear. As the authors note in the discussion, it is possible that other RTKs may also play a role in facilitating the transduction of JH signaling.

      Lastly, the study does not yet explain how RTKs with known ligands could also bind JH and contribute to JH signaling activation. Although receptor promiscuity has been suggested as a possible mechanism, future studies could explore whether activation of RTK pathways by their known ligands induces certain levels of JH transducer phosphorylation, which, in the presence of JH, could contribute to full pathway activation without the need for direct JH-RTK binding.

    1. Reviewer #3 (Public review):

      In this manuscript, Fang et al. describe a new oncogenic function of the STAMBPL1 protein in triple-negative breast cancer (TNBC). STAMBPL1 is a deubiquitinase that has been poorly studied in cancer. Previous reports identify it as a promoter of epithelial to mesenchymal transition or an inhibitor of cisplatin-induced cell death, but its participation to other cancer phenotypes has not been investigated. Fang et al. find that in cell line models of TNBC, STAMBPL1 promotes expression of the transcription factor HIF-1a and its downstream target VEGF, with the consequence of stimulating neo-angiogenesis in vitro and in vivo. Mechanistically, the authors find that this occurs via a non-enzymatic and indirect mechanism, that is by promoting the expression of GRHL3, a transcription factor that in turn binds to the HIF-1a promoter to stimulate its transcription. Interestingly, the way by which STAMPB1 promotes GRHL3 expression is by facilitating the transcriptional activity of FOXO1, a known regulator of GRHL3. Because the authors find that STAMBPL1 and FOXO1 interact, they suggest that STAMBPL1 may promote the formation of an active transcriptional complex containing FOXO1, perhaps by facilitating the recruitment of transcriptional coactivators.

      In conclusion, these data position for the first time the STAMBPL1 deubiquitinase in a FOXO-GRHL3 regulatory axis for the control of VEGF expression and tumor angiogenesis.

      The main weaknesses of this work are that the relevance of this molecular axis to the pathogenesis of TNBC is not clear, and it is not clearly established whether this is a regulatory pathway that occurs in hypoxic conditions or independently of oxygen levels.

      Major criticisms:

      (1) Both FOXO1 and GRHL3 have been previously described as tumor suppressors, with reports of FOXO1 inhibiting tumor angiogenesis. Therefore, this work describes an apparently contradictory function of these proteins in TNBC. While it is not surprising that the same genes perform divergent functions in different tumor contexts, a stronger evidence in support of the oncogenic function of these two genes should be provided to make the data more convincing.<br /> To strengthen the notion that STAMBPL1, FOXO and GRHL3 are overexpressed in TNBC, the authors have utilized the BCIP tool to analyze their expression in the Metabric database. According to this analysis, the levels of STAMBPL1and GRHL3 are not higher in breast cancer than in adjacent tissues, and the levels of FOXO1 are lower. Nonetheless, the authors observe that their expression levels are significantly (yet not dramatically) higher in TNBC compared to non-TNBC (Fig.S6A-C). However, these new data do not provide convincing evidence of the relevant tumor suppressive function of these genes in TNBC, as neither is more expressed in tumors compared to adjacent normal tissues.

      (2) Because STAMBPL1 overexpression in normoxic conditions is sufficient to cause HIF-1a protein accumulation, it is not clear why the authors then use hypoxic conditions to analyze the effect of STAMBPL1 on HIF-1a transcription Avoiding HIF1-a protein degradation should not have any effect on its transcription. At the same time, it is not clear nor is being explained why different hypoxic conditions are sometimes used, resulting in different mRNA levels of HIF-1a and its downstream targets and quite significant fluctuations within the same cell line from one experimental setting to the next. In conclusion, it is not clear what is the relevance of the new HIF-1a regulatory axis described in this paper in normoxic or hypoxic conditions.

      (3) Another critical point is that necessary experimental controls are sometimes missing, and this is reducing the strength of some of the conclusions enunciated by the authors. As an example, experiments where overexpression of STAMBPL1 is coupled to silencing of FOXO1 to demonstrate dependency lack FOXO1silencing the absence of STAMBPL1 overexpression. Because diminishing FOXO1 expression affects HIF-1a/VEGF transcription even in the absence of STAMBPL1 (shown in Figure 7C, D), it is not clear if the data presented in Figure 7G are significant. The difference between HIF-1a expression upon FOXO1 silencing should be compared in the presence or absence of STAMBPL1 overexpression to understand if FOXO1 impacts HIF-1a transcription dependently or independently of STAMBPL1.

      In addition, some minor comments to improve the quality of this manuscript are provided.

      (1) In Figures 2A and D, where endogenous versus STAMBPL1 expression is shown, it is not clear what is the molecular weight of these proteins as they both appear to be of 55 KDa, even though according to the authors the exogenous protein is bigger than the endogenous and the lower band in Figure 2D is reported to be the endogenous STAMBPL1.

      (2) In Figure 2, the effect of STAMBPL1 overexpression on HIF-1a mRNA is minor. At the same time, it seems that the protein levels of HIF-1a are quite high (or at least visible by WB) in normoxic cells even in the absence of STAMBPL1 overexpression. This raises questions about the type of regulation that HIF-1a is subjected to in these cells.

      In general, because only two cell lines are used in this study and the data in patients do not appear to strongly support an oncogenic function of STAMBPL1 in TNBC (via its overexpression), data should be more solid and additional experiments should be provided to substantiate the oncogenic function of this pathway in TNCB.

    1. Reviewer #3 (Public review):

      Summary:

      Rapamycin is a macrolide of immunologic therapeutic importance, proposed as a ligand of mTOR. It is also employed as in essays to probe protein-protein interactions.<br /> The authors serendipitously found that the drug rapamycin and some related compounds, potently activate the cationic channel TRPM8, which is the main mediator of cold sensation in mammals. The authors show that rapamycin might bind to a novel binding site that is different from the binding site for menthol, the prototypical activator of TRPM8. These convincing results are important to a wide audience, since rapamycin is a widely used drug and is also employed in essays to probe protein-protein interactions, which could be affected by potential specific interactions of rapamycin with other membrane proteins, as illustrated herein.

      Strengths:

      The authors employ several experimental approaches to convincingly show that rapamycin activates directly the TRPM8 cation channel and not an accessory protein or the surrounding membrane. In general, the electrophysiological, mutational and fluorescence imaging experiments are adequately carried out and cautiously interpreted, presenting a clear picture of the direct interaction with TRPM8. In particular, the authors convincingly show that the interactions of rapamycin with TRPM8 are distinct from interactions of menthol with the same ion channel.

      Weaknesses:

      The main weakness of the manuscript was the NMR method employed to show that rapamycin binds to TRPM8. The authors developed and deployed a novel signal processing approach based on subtraction of several independent NMR spectra to show that rapamycin binds to the TRPM8 protein and not to the surrounding membrane or other proteins. In this revised version the authors have strengthened the evidence that the method gives solid results and have improved the clarity of the presentation.

      Comments on revisions:

      The authors have greatly improved the quality of the presentation of the NMR data and have answered my concerns regarding the new methodology. The manuscript is improved and represents an important contribution.

    1. Reviewer #3 (Public review):

      Summary:

      In this study, the authors address the paradox of how tyrosine can act as a stronger sticker for phase separation than phenylalanine, despite phenylalanine being higher on the hydrophobicity scale and exhibiting more prominent pairwise contact statistics in folded protein structures compared to tyrosine.

      Strengths:

      This is a fascinating problem for the protein science community with special relevance for the biophysical condensate community. Using atomistic simulations of simple model peptides and condensates as well as quantum calculations, the authors provide an explanation that relies on the dielectric constant of the medium and the hydration level that either tyrosine or phenylalanine can achieve in highly hydrophobic vs. hydrophilic media. The authors find that as the dielectric constant decreases, phenylalanine becomes a stronger sticker than tyrosine. The conclusions of the paper seem to be solid, it is well-written and it also recognises the limitations of the study. Overall, the paper represents an important contribution to the field.

      Weaknesses:

      How can the authors ensure that a condensate of GSY or GSF peptides is a representative environment of a protein condensate? First, the composition in terms of amino acids is highly limited, second the effect of peptide/protein length compared to real protein sequences is also an issue, and third, the water concentration within these condensates is really low as compared to real experimental condensates. Hence, how can we rely on the extracted conclusions from these condensates to be representative for real protein sequences with a much more complex composition and structural behaviour?

    1. Reviewer #3 (Public review):

      Summary:

      The authors performed snRNA-seq in the pre-optic area (POA), a heterogeneous brain region implicated in multiple innate behaviors, comparing two species of Peromyscus mice that possess strikingly different parenting behaviors. P. polionotus show high levels of parental care from both sexes of parent, and P. maniculatus show lower levels of care, predominantly displayed by dams rather than sires. The overall goal of understanding the genomic basis of behavioral variation is significant and of broad interest and comparative studies in POA in these two species is an excellent approach to tackle this question. The authors correctly point out that existing studies largely compare species that are highly divergent, such as mice and humans, which confounds the association of specific neuronal populations or gene expression patterns with distinct behaviors. They identify neuronal populations with differential abundance between species and sexes, and additionally report sex and species differences in gene expression within each transcriptomic cell type. Their cell type classification is aided by mapping their Peromyscus cells onto a previously existing POA single cell dataset generated in lab mice. The detection and validation of previously observed sex differences in the Gal/Moxd1 cell type, and species differences in Avp expression provides additional support that their data are robust. Importantly, the authors demonstrate reduced sexual dimorphism in the POA of P. polionotus, compared to P. maniculatus, and prior knowledge in rats and mice. This finding suggests a potential neural substrate for the increased parental behavior in P. polionotus.

      Strengths:

      This is a pioneering comparative snRNA-seq study that provides a roadmap for similar approaches in non-traditional model organisms.

      The authors have identified populations that may underlie sex- and species- differences in parenting behavior in rodents.

      A significant strength of the manuscript is the histological validation of their most robust marker genes.

      Weaknesses:

      My primary concern is that the dataset is limited: 52,121 neuronal nuclei across 24 samples, which does not provide many cells per cluster to analyze comparatively across sex and species, particularly given the heterogeneity of the large region dissected, which contains adjacent regions such as the PVN and SCN.

      There is no explanation for the finding that there is a female-bias in gene expression across all cell types in P. polionotus.

    1. Reviewer #3 (Public review):

      Summary:

      In this study by Kawadkar et al, the authors investigate the developmental role of Nup107, a nucleoporin, in regulating the larval-to-pupal transition in Drosophila through RNAi knockdown and CRISPR-Cas9-mediated gene editing. They demonstrate that Nup107, an essential component of the nuclear pore complex (NPC), is crucial for regulating ecdysone signaling during developmental transitions. The authors show that the depletion of Nup107 disrupts these processes, offering valuable insights into its role in development.

      Specifically, they find that:

      (1) Nup107 depletion impairs pupariation during the larval-to-pupal transition.<br /> (2) RNAi knockdown of Nup107 results in defects in EcR nuclear translocation, a key regulator of ecdysone signaling.<br /> (3) Exogenous 20-hydroxyecdysone (20E) rescues pupariation blocks, but rescued pupae fail to close.<br /> (4) Nup107 RNAi-induced defects can be rescued by activation of the MAP kinase pathway.

      Strengths:

      The manuscript provides strong evidence that Nup107, a component of the nuclear pore complex (NPC), plays a crucial role in regulating the larval-to-pupal transition in Drosophila, particularly in ecdysone signaling.

      The authors employ a combination of RNAi knockdown, CRISPR-Cas9 gene editing, and rescue experiments, offering a comprehensive approach to studying Nup107's developmental function.

      The study effectively connects Nup107 to ecdysone signaling, a key regulator of developmental transitions, offering novel insights into the molecular mechanisms controlling metamorphosis.

      The use of exogenous 20-hydroxyecdysone (20E) and activation of the MAP kinase pathway provides a strong mechanistic perspective, suggesting that Nup107 may influence EcR signaling and ecdysone biosynthesis.

      Weaknesses:

      The authors do not sufficiently address the potential off-target effects of RNAi, which could impact the validity of their findings. Alternative approaches, such as heterozygous or clonal studies, could help confirm the specificity of the observed phenotypes.

      NPC Complex Specificity: While the authors focus on Nup107, it remains unclear whether the observed defects are specific to this nucleoporin or if other NPC components also contribute to similar defects. Demonstrating similar results with other NPC components would strengthen their claims.

      Although the authors show that Nup107 depletion disrupts EcR signaling, the precise molecular mechanism by which Nup107 influences this process is not fully explored. Further investigation into how Nup107 regulates EcR nuclear translocation or ecdysone biosynthesis would improve the clarity of the findings.

      There are some typographical errors and overly strong phrases, such as "unequivocally demonstrate," which could be softened. Additionally, the presentation of redundant data in different tissues could be streamlined to enhance clarity and flow.

    1. Reviewer #3 (Public review):

      Neural activity in the visual cortex has primarily been studied in terms of responses to external visual stimuli. While the noisiness of inputs to a visual area is known to also influence visual responses, the contribution of this noisy component to overall visual responses has not been well characterized.

      In this study, the authors reanalyze two previously published datasets - a Ca++ imaging study from mouse V1 and a large-scale electrophysiological study from monkey V1-V4. Using regression models, they examine how neural activity in one layer (in mice) or one cortical area (in monkeys) predicts activity in another layer or area. Their main finding is that significant predictions are possible even in the absence of visual input, highlighting the influence of non-stimulus-related downstream activity on neural responses. These findings can inform future modeling work of neural responses in the visual cortex to account for such non-visual influences.

      A major weakness of the study is that the analysis includes data from only a single monkey. This makes it hard to interpret the data as the results could be due to experimental conditions specific to this monkey, such as the relative placement of electrode arrays in V1 and V4. The authors perform a thorough analysis comparing regression-based predictions for a wide variety of combinations of stimulus conditions and directions of influence. However, the comparison of stimulus types (Figure 4) raises a potential concern. It is not clear if the differences reported reflect an actual change in predictive influence across the two conditions or if they stem from fundamental differences in the responses of the predictor population, which could in turn affect the ability to measure predictive relationships. The authors do control for some potential confounds such as the number of neurons and self-consistency of the predictor population. However, the predictability seems to closely track the responsiveness of neurons to a particular stimulus. For instance, in the monkey data, the V1 neuronal population will likely be more responsive to checkerboards than to single bars. Moreover, neurons that don't have the bars in their RFs may remain largely silent. Could the difference in predictability be just due to this? Controlling for overall neuronal responsiveness across the two conditions would make this comparison more interpretable.

    1. Reviewer #3 (Public review):

      Summary:

      In their report, Tsutsumi et al., use single nucleus transcriptional and chromatin accessibility analyses of mouse achilles tendon in an attempt to uncover new markers of tendon stem/progenitor cells. They propose CD55 and CD248 as novel markers of tendon stem/progenitor cells.

      Strengths:

      This is an interesting and important research area. The paper is overall well written.

      Weaknesses:

      Major problems:

      (1) It is not clear what tissue exactly is being analyzed. The authors build a story on tendons, but there is little description of the dissection. The authors claim to detect MTJ and cartilage cells, but not bone or muscle cells. The tendon sheath is known to express CD55, so the population of "progenitors" may not be of tendon origin.

      (2) Cluster annotations are seemingly done with a single gene. Names are given to cells without functional or spatial validation. For example, MTJ cells are annotated based on Postn, but it is never shown that Postn is only expressed at the MTJ, and not in other anatomical locations in the tendon.

      (3) The authors compare their data to public data based on interrogating single genes in their dataset. It is now standard practice to integrate datasets (eg, using harmony), or at a minimum using gene signatures built into Seurat (eg AddModuleScore).

      (4) Progenitor populations (SP1, SP2). The authors claim these are progenitors but show very clearly that they express macrophage genes. What are they, macrophages or fibroblasts?

      (5) All omics analysis is done on single data points (from many mice pooled). The authors make many claims on n=1 per group for readouts dependent on sample number (eg frequency of clusters).

      (6) The scRNAseq atlas in Figure 1 is made by analyzing 2W and 6W tendons at the same time. The snRNAseq and ATACseq atlas are built first on 2W data, after which the 6W data is compared. Why use the 2W data as a reference? Why not analyze the two-time points together as done with the scRNAseq?

      (7) Figure 5: The authors should show the gating strategy for FACS. Were non-fibroblasts excluded (eg, immune cells, endothelia...etc). Was a dead cell marker used? If not, it is not surprising that fibroblasts form colonies and express fibroblast genes when compared to CD55-CD248- immune cells, dead cells, or debris. Can control genes such as Ptprc or Pecam1 be tested to rule out contamination with other cell types?

      Minor problems:

      (1) Report the important tissue processing details: type of collagenase used. Viability before loading into 10x machine.

    1. Reviewer #3 (Public review):

      The manuscript of Fuchsberger et al. investigates the cellular mechanisms underlying dopamine-dependent long-term potentiation (DA-LTP) in mouse hippocampal CA1 neurons. The authors conducted a series of experiments to measure the effect of dopamine on the protein synthesis rate in hippocampal neurons and its role in enabling DA-LTP. The key results indicate that protein synthesis is increased in response to dopamine and neuronal activity in the pyramidal neurons of the CA1 hippocampal area, mediated via the activation of adenylate cyclases subtypes 1 and 8 (AC1/8) and the cAMP-dependent protein kinase (PKA) pathway. Additionally, the authors show that postsynaptic DA-induced increases in protein synthesis are required to express DA-LTP, while not required for conventional t-LTP.

      The increased expression of the newly synthesized GluA1 receptor subunit in response to DA supports the formation of homomeric calcium-permeable AMPA receptors (CP-AMPARs). This evidence aligns well with data showing that DA-LTP expression requires the GluA1 AMPA subunit and CP-AMPARs, as DA-LTP is absent in the hippocampus of a GluA1 genetic knock-out mouse model.

      Comments on revisions:

      The authors addressed adequately all my comments.

    1. Reviewer #3 (Public review):

      Strengths:

      The paper describes a new perspective on friction perception, with the hypothesis that humans are sensitive to the instabilities of the surface rather than the coefficient of friction. The paper is very well written and with a comprehensive literature survey.

      One of the central tools used by the author to characterize the frictional behavior is the frictional instabilities maps. With these maps, it becomes clear that two different surfaces can have both similar and different behavior depending on the normal force and the speed of exploration. It puts forward that friction is a complicated phenomenon, especially for soft materials.

      The psychophysics study is centered around an odd-one-out protocol, which has the advantage of avoiding any external reference to what would mean friction or texture for example. The comparisons are made only based on the texture being similar or not.

      The results show a significant relationship between the distance between frictional maps and the success rate in discriminating two kinds of surface.

      Weaknesses:

      The main weakness of the paper comes from the fact that the frictional maps and the extensive psychophysics study are not made at the same time, nor with the same finger. The frictional maps are produced with an artificial finger made out of PDMS which is a poor substitute for the complex tribological properties of skin.

      The evidence would have been much stronger if the measurement of the interaction was done during the psychophysical experiment. In addition, because of the protocol, the correlation is based on aggregates rather than on individual interactions.

      The authors compensate with a third experiment where they used a 2AFC protocol and an online force measurement. But the results of this third study, fail to convince the relation.

      No map of the real finger interaction is shown, bringing doubt to the validity of the frictional map for something as variable as human fingers.

    1. Reviewer #3 (Public review):

      Summary:

      In this manuscript, the investigators identified LMOD1 as one of a subset of cytoskeletal proteins whose levels increase in the early stages of myogenic differentiation. Lmod1 is understudied in striated muscle and in particular in myogenic differentiation. Thus, this is an important study. It is also a very thorough study - with perhaps even too much data presented. Importantly, the investigators observed that LMOD1 appears to be important for skeletal regeneration, and myogenic differentiation and that it interacts with SIRT1. Both primary myoblast differentiation and skeletal muscle regeneration were studied. Rescue experiments confirmed these observations: SIRT1 can rescue perturbations of myogenic differentiation as a result of LMOD1 knockdown.

      Strengths:

      Particular strengths include: important topic, the use of primary skeletal cultures, the use of both cell culture and in vivo approaches, careful biomarker analysis of primary mouse myoblast differentiation, the use of two methods to probe the function of the Lmod1/SIRT1 pathway via using depletion approaches and inhibitors, and generation of six independent myoblast cultures. Results support their conclusions.

      Weaknesses:

      (1) Figure 1. Images of cells in Figure 1A are too small to be meaningful (especially in comparison to the other data presented in this figure). Perhaps the authors could make graphs smaller?

      (2) Line 148 "We found LMOD2 to be the most abundant Lmod in whole skeletal muscle." This is confusing since most if not all prior studies have shown that Lmod3 is the predominant isoform in skeletal muscle. The two papers that are cited are incorrectly cited. Clarification to resolve this discrepancy is needed.

      (3) Figure 2. Immunoflorescence (IF) panels are too small to be meaningful. Perhaps the graphs could be made smaller and more space allocated for the IF panels? This issue is apparent for just about all IF panels - they are simply too small to be meaningful. Additionally, in many of the immunofluorescence figures, the colors that were used make it difficult to discern the stained cellular structures. For example in Figure S1, orange and purple are used - they do not stand out as well as other colors that are more commonly used.

      (4) There is huge variability in many experiments presented - as such, more samples appear to be required to allow for meaningful data to be obtained. For example, Figure S2. Many experimental groups, only have 3 samples - this is highly problematic - I would estimate that 5-6 would be the minimum.

      (5) Ponceau S staining is often used as a loading control in this manuscript for western blots. The area/molecular weight range actually used should be specified. Not clear why in some experiments GAPDH staining is used, in other experiments Ponceau S staining is used, and in some, both are used. In some experiments, the variability of total protein loaded from lane to lane is disconcerting. For example, in Figure S4C there appears to be more than normal variability. Can the protein assay be redone and samples run again?

      (6) Figure S3 - Lmod3 is included in the figure but no mention of it occurs in the title of the figure and/or legend.

      (7) Abstract, line 25. "overexpression accelerates and improves the formation of myotubes". This is a confusing sentence. How is it improving the formation? A little more information about how they are different than developing myotubes in normal/healthy muscles would be helpful.

      (8) It is impossible from the IF figures presented to determine where Lmod1 localizes in the myocytes. Information on its subcellular localization is important. Does it localize with Lmod2 and Lmod3 at thin filament pointed ends?

    1. Reviewer #3 (Public review):

      Summary:

      Chen and Phillips present intriguing work that extends our view on the C. elegans small RNA network significantly. While the precise findings are rather C. elegans specific there are also messages for the broader field, most notably the switching of small RNA populations bound to an argonaute, and RNA granules behavior depending on developmental stage. The work also starts to shed more light on the still poorly understood role of the CSR-1 argonaute protein and supports its role in the decay of maternal transcripts. Overall, the work is of excellent quality, and the messages have a significant impact.

      Strengths:

      Compelling evidence for major shift in activities of an argonaute protein during development, and implications for how small RNAs affect early development. Very balanced and thoughtful discussion.

      Weaknesses:

      The switch between maternal and zygotic NRDE-3 remains unaddressed

    1. Reviewer #3 (Public review):

      Summary:

      Xiang et al. investigated the role of ubiquitin E3 ligase ITCH in SARS-CoV-2 replication. First, they described the role of ITCH on the structural proteins. Here, the ubiquitination of E and M (but not S) leads to an enhanced interaction and presumably virion assembly. In addition, E and M ubiquitination seems to be necessary for p62-guided sequestration into autophagosomes for secretion. Furthermore, ITCH regulates S proteolytic cleavage by changing furin localization and inhibiting CTSL protease maturation. In addition, SARS-CoV-2 infection upregulates ITCH phosphorylation, whereas knockout of ITCH reduces SARS-CoV-2 replication.

      Strengths:

      The proposed study is of interest to the virology community because it aims to elucidate the role of ubiquitination by ITCH in SARS-CoV-2 proteins. Understanding these mechanisms will address broadly applicable questions about coronavirus biology and enhance our knowledge of ubiquitination's diverse functions in cell biology.

      Weakness:

      The involvement of ubiquitin ligases in SARS-CoV-2 replication is not entirely new (see E3 Ubiquitin Ligase RNF5; Yuan et al., 2022; Li et al., 2023). While the data generally support the conclusions, additional work is needed to confirm the role of ITCH in SARS-CoV-2 replication in a biologically relevant context. The vast majority of data is based on transient overexpression experiments of ITCH, which ultimately leads to massive ubiquitination of several viral and host cell factors, including potentially low-affinity substrates not typically recognized under physiological conditions. In addition to that, nearly all experiments were done in cells co-overexpressing ITCH and the viral structural proteins (or cellular proteases) in HEK293T cells. Therefore, a proteomic analysis of protein ubiquitination in a) SARS-CoV-2-infected cells (ideally several cell types) and b) SARS-CoV-2-infected v2T-ITCH-KO cells would verify the ITCH-related ubiquitination of e.g., E and M and would strengthen the whole manuscript. In addition, the few key experiments using SARS-CoV-2 infected cells were performed in VeroE6 cells, which are neither human nor lung-derived. Only in one experiment were lung-derived Calu3 cells included.<br /> Moreover, the manuscript names ITCH as a central regulator of SARS-CoV-2 replication. If ITCH is beneficial for E and M interaction and thereby aids virion assembly, showing its effect on VLP production would be desirable. Clarifications regarding data acquisition and data analysis could strengthen the manuscript and its conclusions.

    1. Reviewer #3 (Public review):

      NCXs are key Ca2+ transporters located on the plasma membrane, essential for maintaining cellular Ca2+ homeostasis and signaling. The activities of NCX are tightly regulated in response to cellular conditions, ensuring precise control of intracellular Ca2+ levels, with profound physiological implications. Building upon their recent breakthrough in determining the structure of human NCX1, the authors obtained cryo-EM structures of NCX1 in complex with its modulators, including the cellular activator PIP2 and the small molecule inhibitor SEA0400. Structural analyses revealed mechanistically informative conformational changes induced by PIP2 and elucidated the molecular basis of inhibition by SEA0400. These findings underscore the critical role of the interface between the transmembrane and cytosolic domains in NCX regulation and small molecule modulation. Overall, the results provide key insights into NCX regulation, with important implications for cellular Ca2+ homeostasis.

    1. Reviewer #3 (Public review):

      Summary:

      The authors develop automated methods to visually identify micronuclei (MN) and MN-containing cells. The authors then use these methods to isolate MN-containing RPE-1 cells post-photoactivation and analyze transcriptional changes in cells with and without micronuclei. The authors find that RPE-1 cells with MN have similar transcriptomic changes as aneuploid cells and that MN rupture does not lead to vast changes in the transcriptome.

      Strengths:

      The authors develop a method that allows for automating measurements and analysis of micronuclei. This has been something that the field has been missing for a long time. Using such a method has the potential to greatly enhance the field's ability to analyze micronuclei and understand the downstream consequences. The authors also develop a method to identify cells with micronuclei in real-time, mark them using photoconversion, and then isolate them via cell sorting, which could change the way we isolate and study MN-containing cells, and the scale at which we do it. The authors use this method to look at the transcriptome. This method is very powerful as it can allow for the separation of a heterogenous population and subsequent analysis with a much higher sample number than previously possible.

      Weaknesses:

      The major weakness of this paper is the transcriptomic analysis of MN. There is in general large variance between replicates in experiments looking at cells with ruptured versus intact micronuclei. This limits our ability to assess if lack of changes are due to truly not having changes between these populations or experimental limitations. More transcriptomic analysis will be necessary to fully understand the downstream consequences of MN rupture.

    1. Reviewer #3 (Public review):

      Summary:

      Type VI secretion systems (T6SS) are employed by bacteria to inject competitor cells with numerous effector proteins. These effectors can kill injected cells via an array of enzymatic activities. A common class of T6SS effector are peptidoglycan (PG) lysing enzymes. In this manuscript, the authors characterize a PG-lysing effector-TseP-from the pathogen Aeromonas dhakensis. While the C-terminal domain of TseP was known to have lysozyme activity, the N-terminal domain was uncharacterized. Here, the authors functionally characterize TsePN as a zinc-dependent amidase. This discovery is somewhat novel because it is rare for PG-lysing effectors to have amidase and lysozyme activity. In the second half of the manuscript, the authors utilize a crystal structure of the lysozyme TsePC domain to inform the engineering of this domain to lyse gram-positive peptidoglycan.

      Strengths:

      The two halves of the manuscript considered together provide a nice characterization of a unique T6SS effector and reveal potentially general principles for lysozyme engineering.

      Weaknesses:

      The advantage of fusing amidase and lysozyme domains in a single effector is not discussed but would appear to be a pertinent question.

      Comments on revisions:

      The authors have adequately addressed my previous comments. The authors did not conduct any additional experiments to address the comments made by other reviewers. However, in most cases it seems that paring down the strength of claims made in the text or adding data to the supplement is sufficient to address these concerns.

    1. Reviewer #3 (Public review):

      Summary:

      This manuscript introduces a differentiable variant of the Gillespie algorithm (DGA) that allows gradient calculation using backpropagation. The most significant contribution of this work is the development of the DGA itself, a novel approach to making stochastic simulations differentiable. This is achieved by replacing discontinuous operations in the traditional Gillespie algorithm with smooth, differentiable approximations using sigmoid and Gaussian functions. This conceptual advance opens up new avenues for applying powerful gradient-based optimization techniques, prevalent in machine learning, to studying stochastic biological systems.

      The method was tested on a simple two-state promoter model of gene expression. The authors found that the DGA accurately captured the moments of the steady-state distribution and other major qualitative features. However, it was less accurate at capturing information about the distribution's tails, potentially because rare events result from frequent low-probability reaction events where the approximations made by the DGA have a greater impact. The authors also used the DGA to design a four-state promoter model of gene regulation that exhibited a desired input-output relationship. The DGA could learn parameters that produced a sharper response curve, which was achieved by consuming more energy.

      The authors conclude that the DGA is a powerful tool for analyzing and designing stochastic systems. The discussion lays several open questions in the field and constructively addresses shortcomings of the proposed method as well as potential ways forward.

      Strengths:

      The DGA allows gradient-based optimization techniques to estimate parameters and design networks with desired properties.

      The DGA efficacy in estimating kinetic parameters from both synthetic and experimental data. This capability highlights the DGA's potential to extract meaningful biophysical parameters from noisy biological data.

      The DGA's ability to design a four-state promoter architecture exhibits a desired input-output relationship. This success indicates the potential of the DGA as a valuable tool for synthetic biology, enabling researchers to engineer biological circuits with predefined behaviours.

      Weaknesses:

      The study primarily focuses on analysing the steady-state properties of stochastic systems.

      Comments on revisions:

      Thank you for addressing all the points raised. I am looking forward to seeing the next steps in DGAs development and performance!

    1. Reviewer #3 (Public review):

      Ito et al. investigate the role of synaptic plasticity in the medial preoptic area (MPOA) pathway of male mice and its involvement in transitions from infanticidal aggression to parental behavior. Using optogenetics, whole-cell patch-clamp recordings, and behavioral assays, they demonstrate that inhibitory synaptic transmission from the posterior-dorsal medial amygdala (MePD) to the central MPOA (cMPOA) decreases following mating and cohabitation with pregnant females. This synaptic disinhibition is correlated with a reduction in aggressive behavior toward pups. They further show that paternal experience induces enhanced inhibitory transmission in the rhomboid nucleus of the bed nucleus of the stria terminalis (BSTrh), downstream of the MPOA, through postsynaptic mechanisms. These findings suggest a circuit-based model where social experiences and mating induce synaptic changes in the Me-cMPOA-BSTrh pathway, mediating the transition to parental behavior.

      The conclusions of this paper are largely supported by the data, but several methodological and conceptual aspects require clarification or additional experiments.

      (1) When evaluating the Me Cartpt-expressing neuron projection to the cMPOA, the authors compared excitatory postsynaptic currents (EPSCs) and inhibitory postsynaptic currents (IPSCs). However, the standard procedure for isolating these currents is to hold the membrane potential at the reversal potential for inhibitory or excitatory currents, respectively. The authors appear not to have followed this procedure, making it unclear how EPSCs and IPSCs were calculated. This requires clarification to ensure the validity of their reported E/I balance changes.

      (2) The authors chose to assess parental behavior over four consecutive days. It is unclear why this specific timeframe was selected. A justification for this choice would strengthen the interpretation of the behavioral data.

      (3) The experimental design in Figure 5, where the authors lesioned the entire cMPOA to assess its role in BSTrh inhibition, presents several limitations: First, the effects on BSTrh activity could result from indirect circuit alterations rather than direct cMPOA projections. The current lesion approach cannot disentangle these possibilities. Second, the cMPOA is a heterogeneous region containing diverse neuronal subtypes. Full lesions prevent the differentiation of the roles played by distinct populations within this region. Third, lesion specificity is questionable, as some lesions extended beyond the cMPOA boundaries (Figure S5). This overextension complicates the interpretation of the results and requires tighter control.

      (4) In Figure 3, the authors show that optogenetic inhibition of Me projections to the cMPOA modifies the frequency of spontaneous inhibitory postsynaptic currents (sIPSCs). However, the proposed mechanism that this modulation reflects inter-neuronal network activity within the cMPOA lacks sufficient experimental validation. Additional experiments assessing circuit-level interactions could substantiate these claims.

      (5) While the paper highlights synaptic changes in the cMPOA, it does not establish a direct relationship between these changes and the social experience. How do mating and cohabitation with females impact this pathway and modulate synaptic strength? The discussion could benefit from integrating these factors into their proposed model.

      Overall, the paper offers valuable insights into the neural circuitry underlying male parental behavior, particularly the synaptic dynamics of the Me-cMPOA-BSTrh pathway. However, addressing these methodological and conceptual limitations would significantly enhance the clarity and impact of the work.

    1. Reviewer #3 (Public review):

      Summary:

      This study indicates that connections across human cortical pyramidal cells have identical latencies despite a larger mean dendritic and axonal length between somas in human cortex. A precise demonstration combining detailed electrophysiology and modeling, indicates that this property is due to faster propagation of signals in proximal human dendrites. This faster propagation is itself due to a slightly thicker dendrite, to a larger capacitive load, and to stronger hyperpolarizing currents. Hence, the biophysical properties of human pyramidal cells are adapted such that they do not compromise information transfer speed.

      Strengths:

      The manuscript is clear and very detailed. The authors have experimentally verified a large number of aspects that could affect propagation speed and have pinpointed the most important one. This paper provides an excellent comparision of biophysical properties between rat and human pyramidal cells. Thanks to this approach a comprehensive description of the mechanisms underlying the acceleration of propagation in human dendrite is provided.

      Weaknesses:

      The weaknesses I had identified have been addressed by the authors.

    1. Reviewer #3 (Public review):

      Summary:

      Li et al propose to better understand the mechanisms of drug resistance in nematode parasites by studying mutants of the model roundworm C. elegans that are resistant to the deworming drug ivermectin. They provide compelling evidence that loss-of-function mutations in the E3 ubiquitin ligase encoded by the UBR-1 gene make worms resistant to the effects of ivermectin (and related compounds) on viability, body size, pharyngeal pumping rate, and locomotion and that these mutant phenotypes are rescued by a UBR-1 transgene. They propose that the mechanism is resistance is indirect, via the effects of UBR-1 on glutamate production. They show mutations (vesicular glutamate transporter eat-4, glutamate synthase got-1) and drugs (glutamate, glutamate uptake enhancer ceftriaxone) affecting glutamate metabolism/transport modulate sensitivity to ivermectin in wild type and ubr-1 mutants. The data are generally consistent with greater glutamate tone equating to ivermectin resistance. Finally, they show that manipulations that are expected to increase glutamate tone appear to reduce expression of the targets of ivermectin, the glutamate-gated chloride channels, which is known to increase resistance.

      There is a need for genetic markers of ivermectin resistance in livestock parasites that can be used to better track resistance and to tailor drug treatment. The discovery of UBR-1 as a resistance gene in C. elegans will provide a candidate marker that can be followed up in parasites. The data suggest Ceftriaxone would be a candidate compound to reverse resistance.

      Strengths:

      The strength of the study is the thoroughness of the analysis and the quality of the data. There can be little doubt that ubr-1 mutations do indeed confer ivermectin resistance. The use of both rescue constructs and RNAi to validate mutant phenotypes is notable. Further, the variety of manipulations they use to affect glutamate metabolism/transport makes a compelling argument for some kind of role for glutamate in resistance.

      Weaknesses:

      The use of single ivermectin dose assays can be misleading. A response change at a single dose shows that the dose-response curve has shifted, but the response is not linear with dose, so the degree of that shift may be difficult to discern and may result from a change in slope but not EC50.

    1. Reviewer #3 (Public review):

      Summary:

      The authors have done a good job at creating a "resource" paper for the study of gut regeneration in sea cucumbers. They present a single-cell RNAseq atlas for the reconstitution of Holothuria glaberrima gut following self-evisceration in response to a potassium chloride injection. The authors provide data characterizing cellular populations and precursors of the regenerating anlage at 9 days post evisceration. As a "Tools and Resources" contribution to eLife, this work, with some revisions, could be appropriate. It will be impactful in the fields of regeneration, particularly in invertebrates, but also in comparative studies in other species, including evolutionary studies. Some of these comparative studies could extend to vertebrates and could therefore impact regenerative medicine in the future.

      Strengths:

      • Novel and useful information for a model organism and question for which this type of data has not yet been reported<br /> • Single-cell gene expression data will be valuable for developing testable hypotheses in the future<br /> • Marker genes for cell types provided to the field<br /> • Interesting predictions about possible lineage relationships between cells during sea cucumber gut regeneration<br /> • Authors have done a good job in the revision of making sure not to overstate the lineage claims in absence of definitive lineage-tracing experiments<br /> • Authors have improved the figures and the overall readability of the figures and text

      Specific questions:

      - Is there any way to systematically compare these cells to evolutionarily-diverged cells in distant relatives to sea cucumbers? Or even on a case-by-case basis? For example, is there evidence for any of these transitory cell types to have correlate(s) in vertebrate gut regeneration?

      • Authors acknowledged this would be interesting and important, but they say in the response document this is outside the scope of the current manuscript and more data would be needed to do this well.

      - Line 808: The authors may make a more accurate conclusion by saying that the characteristics are similar to blastemas or behaves like a blastema rather than it is blastema. There is ambiguity about the meaning of this term in the field, but most researchers seem to currently have in mind that the "blastema" definitions includes a discrete spatial organization of cells, and here these cells are much more spread out. This could be a good opportunity for the authors to engage in this dialogue, perhaps parsing out the nuances of what a "blastema" is, what the term has traditionally referred to, and how we might consider updating this term or at least re-framing the terminology to be inclusive of functions that "blastemas" have traditionally had in the literature and how they may be dispersed over geographical space in an organism more so than the more rigid, geographically-restricted definition many researchers have in mind. However, if the authors choose to elaborate on these issues, those elaborations do belong in the discussion, and the more provisional terminology we mention here could be used throughout the paper until that element of the revised discussion is presented. We would welcome the authors to do this as a way to point the field in this direction as this is also how we view the matter. For example, some of the genes whose expression has been observed to be enriched following removal of brain tissue in axolotls (such as kazald2, Lust et al.), are also upregulated in traditional blastemas, for instance, in the limb, but we appreciate that the expression domain may not be as localized as in a limb blastema. Additionally, since there is now evidence that some aspects of progenitor cell activation even in limb regeneration extend far beyond the local site of amputation injury (Johnson et al., Payzin-Dogru et al.), there is an opportunity to connect the dots and make the claim that there could be more dispersion of "blastema function" than previously appreciated in the field. Diving a bit more into these nuances may also enable a better conceptual framework of how blastema function may evolve across vast evolutionary time and between different injury contexts in super-regenerative organisms.

      • Authors addressed this comment and agree it is interesting, but given how much territory they had to cover and space limitations, they will save this type of discussion and comparative theoretical work for the future.

      Overall, the manuscript is much improved.

    1. Reviewer #3 (Public review):

      Background:

      Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) is a chloride channel whose dysfunction underlies cystic fibrosis, a life-limiting condition caused by thick, sticky mucus buildup in the lungs and other organs. Despite multiple high-resolution structures of CFTR, these snapshots have all captured the channel in a non-conducting or "closed" conformation - even when the protein was prepared under conditions that should favor channel opening. This discrepancy has posed a key challenge: how can a channel be experimentally observed as closed while physiological tests demonstrate it conducts chloride ions?

      Key Findings:

      (1) Stable Open Conformation

      Through repeated molecular dynamics (MD) simulations of human CFTR in lipid bilayers, researchers observed a reproducible, stable open state. Unlike previous transient openings seen in single-run or short simulations, this conformation remains consistently permeable over extended timescales.

      (2) Penta-Helical Arrangement

      The authors highlight a "penta-helical" pore-lining arrangement in which five transmembrane helices symmetrically organize to create a clear ion-conduction pathway. This novel configuration resolves the previously puzzling hydrophobic bottleneck found in cryo-EM structures.

      (3) Conductance Close to Experimental Values

      By analyzing chloride ion flow under near-physiological voltages, they calculate a channel conductance aligning well with electrophysiological measurements. This alignment provides strong support that the observed structure is functionally relevant.

      (4) Roles of Key Residues

      Several positively charged (cationic) residues in the pore appear crucial for guiding and stabilizing chloride ions. Simultaneously, small kinks in certain helices may act as structural "hinges," allowing or blocking chloride passage.

      How to Interpret These Results:

      (1) Bridging a Major Gap: The study tackles the mismatch between static "closed" CFTR structures and their known open-channel function. Successfully capturing a stable open state in MD simulations is a significant step toward reconciling what cryo-EM data shows versus what physiological experiments have long told us.

      (2) Strength in Multiple Replicas: Running many simulation repeats (rather than relying on a single trajectory) lends credibility. Only if a phenomenon is reproducible across multiple runs can it be considered robust.

      (3) Consistency with Mutational Data: Observing that known functional hotspots (e.g., specific charged residues) play a key role in the new pore model further validates these findings.

      Important Caveats and Limitations:

      (1) Simulation Timescales vs. Biology<br /> Even extended MD (on the microsecond scale) is still much faster, simpler, and more controlled than real cellular processes.

      (2) Physiological existence of the penta-helical pore<br /> Although the simulations and results are highly compelling, several factors leave open the possibility of a physiological open conformation differing from the observed penta-helical pore. These factors include ATP hydrolysis, interactions with physiological binding partners, the native membrane environment, and regions not modeled in the CFTR structures, such as the R domain. Most importantly, the transmembrane voltage is very high (500mV).

      Bottom Line:

      This work delivers a long-awaited, near-physiological view of CFTR's open conformation. It provides a foundational structure against which future experimental and computational studies can be compared. By demonstrating reliable chloride conduction and matching established biophysical data, these simulations bring us closer to understanding - and potentially targeting - CFTR's gating mechanism in health and disease. Readers should applaud the breakthroughs while recognizing that further exploration (including more complex in vitro and in vivo experiments) will still be necessary to capture the full dynamism of CFTR in the living cell environment.

    1. Reviewer #3 (Public review):

      Summary:

      The paper presents an in-depth analysis of the original colour of a fossil feather from the crest of a 125-million-year-old enantiornithine bird. From its shape and location, it would be predicted that such a feather might well have shown some striking colour and pattern. The authors apply sophisticated microscopic and numerical methods to determine that the feather was iridescent and brightly coloured and possibly indicates this was a male bird that used its crest in sexual displays.

      Strengths:

      The 3D micro-thin-sectioning techniques and the numerical analyses of light transmission are novel and state-of-the-art. The example chosen is a good one, as a crest feather is likely to have carried complex and vivid colours as a warning or for use in sexual display. The authors correctly warn that without such 3D study feather colours might be given simply as black from regular 2D analysis, and the alignment evidence for iridescence could be missed.

      Weaknesses: Trivial.

    1. Reviewer #3 (Public review):

      Summary:

      Kamal L. Nahas et al. demonstrated that pUL16, pUL21, pUL34, VP16, and pUS3 are involved in the egress of the capsids from the nucleous, since mutant viruses ΔpUL16, ΔpUL21, ΔUL34, ΔVP16, and ΔUS3 HSV-1 show nuclear egress attenuation determined by measuring the nuclear:cytoplasmic ratio of the capsids, the dfParental, or the mutants. Then, they showed that gM-mCherry+ endomembrane association and capsid clustering were different in pUL11, pUL51, gE, gK, and VP16 mutants. Furthermore, the 3D view of cytoplasmic budding events suggests an envelopment mechanism where capsid budding into spherical/ellipsoidal vesicles drives the envelopment.

      Strengths:

      The authors employed both structured illumination microscopy and cellular ultrastructure analysis to examine the same infected cells, using cryo-soft-X-ray tomography to capture images. This combination, set here for the first time, enabled the authors to obtain holistic data regarding a biological process, as a viral assembly. Using this approach, the researchers studied various stages of HSV-1 assembly. For this, they constructed a dual-fluorescently labelled recombinant virus, consisting of eYFP-tagged capsids and mCherry-tagged envelopes, allowing for the independent identification of both unenveloped and enveloped particles. They then constructed nine mutants, each targeting a single viral protein known to be involved in nuclear egress and envelopment in the cytoplasm, using this dual-fluorescent as the parental one. The experimental setting, both the microscopic and the virological, is robust and well-controlled. The manuscript is well-written, and the data generated is robust and consistent with previous observations made in the field.

      Weaknesses:

      It would be helpful to find out what role the targeted proteins play in nuclear egress or envelopment acquisition in a different orthoherpesvirus, like HSV-2. This would confirm the suitability of the technical approach set and would also act as a way to validate their mechanism at least in one additional herpesvirus beyond HSV-1. So, using the current manuscript as a starting point and for future studies, it would be advisable to focus on the protein functions of other viruses and compare them.

    1. Reviewer #3 (Public review):

      Summary:

      This study identifies confirmational fingerprints of amylodogenic light chains, that set them apart from the non-amylodogenic ones.

      Strengths:

      The research employs a comprehensive combination of structural and dynamic analysis techniques, providing evidence that conformational dynamics at VL-CL interface and structural expansion are distinguished features of amylodogenic LCs.

      Weaknesses:

      The sample size is limited, which may affect the generalizability of the findings. Additionally, the study could benefit from deeper analysis of specific mutations driving this unique conformation to further strengthen therapeutic relevance.

      Furthermore. p-value (statistical significance) of Rg difference should be computer. Finally, significance of mutations (SHM?) at the interface, such as A40G should be compared with previous observations. (Garofalo et al., 2021)

    2. Reviewer #3 (Public review):

      Summary:

      This study identifies confirmational fingerprints of amylodogenic light chains, that set them apart from the non-amylodogenic ones.

      Strengths:

      The research employs a comprehensive combination of structural and dynamic analysis techniques, providing evidence that conformational dynamics at VL-CL interface and structural expansion are distinguished features of amylodogenic LCs.

      Weaknesses:

      The sample size is limited, which may affect the generalizability of the findings. Additionally, the study could benefit from deeper analysis of specific mutations driving this unique conformation to further strengthen therapeutic relevance.

      Furthermore. p-value (statistical significance) of Rg difference should be computer. Finally, significance of mutations (SHM?) at the interface, such as A40G should be compared with previous observations. (Garofalo et al., 2021)

    1. Reviewer #3 (Public review):

      Summary:

      The manuscript entitled "Shc1 cooperates with Frs2 and Shp2 to recruit Grb2 in FGF-induced lens development" by Wang et al., investigates the molecular mechanism used by FGFR signaling to support lens development. The lens has long been known to depend on FGFR-signaling for proper development. Previous investigations have demonstrated the FGFR signaling is required for embryonic lens cell survival and for lens fiber cell differentiation. The requirement of FGFR signaling for lens induction has remained more controversial as deletion of both Fgfr1 and Fgfr2 during lens placode formation does not prevent the induction of definitive lens markers such as FOXE3 or αA-crystallin. Here the authors have used the Le-Cre driver to delete all four FGFR genes from the developing lens placode demonstrating a definitive failure of lens induction in the absence of FGFR-signaling. The authors focused on FGFR1 and FGFR2, the two primary FGFRs present during early lens development and demonstrated that lens development could be significantly rescued in lenses lacking both FGFR1 and FGFR2 by expressing a constitutively active allele of KRAS. They also showed that the removal of pro-apoptotic genes Bax and Bak could also lead to a substantial rescue of lens development in lenses lacking both FGFR1 and FGFR2. In both cases, the lens rescue included both increased lens size and the expression of genes characteristic of lens cells.

      Significantly the authors concentrated on the juxtamembrane domain, a portion of the FGFRs associated with FRS2. Previous investigations have demonstrated the importance of FRS2 activation for mediating a sustained level of ERK activation. FRS2 is known to associate both with GRB2 and SHP2 to activate RAS. The authors utilized a mutant allele of Fgfr1, lacking the entire juxtamembrane domain (Fgfr1ΔFrs) and an allele of Fgfr2 containing two-point mutations essential for Frs2 binding (Fgfr2LR). When combining three floxed alleles and leaving only one functional allele (Fgfr1ΔFrs or Fgfr2LR) the authors got strikingly different phenotypes. When only the Fgfr1ΔFrs allele was retained, the lens phenotype matched that of deleting both Fgfr1 and Fgfr2. However, when only the Fgfr2LR allele was retained the phenotype was significantly milder, primarily affecting lens fiber cell differentiation, suggesting that something other than FRS2 might be interacting with the juxtamembrane domain to support FGFR signaling in the lens. The authors also deleted Grb2 in the lens and showed that the phenotype was similar to that of the lenses only retaining the Fgfr2LR allele, resulting a failure of lens fiber cell differentiation and decreased lens cell survival. However, mutating the major tyrosine phosphorylation site of GRB2 did not affect lens development. The authors additionally investigated the role of SHP2 in lens development by either deleting SHP2 or by making mutations in the SHP2 catalytic domain. The deletion of the SHP2 phosphatase activity did not affect lens development as severely as total loss of SHP2 protein, suggesting a function for SHP2 outside of its catalytic activity. Although the loss of Shc1 alone has only a slight effect on lens size and pERK activation in the lens, the authors showed that the loss of Shc1 exacerbated the lens phenotype in lenses lacking both Frs2 and Shp2. The authors suggest that SHC1 binds to the FGFR juxtamembrane domain allowing for the recruitment of GRB2 in independently of FRS2.

      Strengths:

      (1) The authors used a variety of genetic tools to carefully dissect the essential signals downstream of FGFR signaling during lens development.

      (2) The authors made a convincing case that something other than FRS2 binding mediates FGFR signaling in the juxtamembrane domain.

      (3) The authors demonstrated that despite the requirement of both the adaptor function and phosphatase activity of SHP2 are required for embryonic survival, neither of these activities is absolutely required for lens development.

      (4) The authors provide more information as to why FGFR loss has a phenotype much more severe than the loss of FRS2 alone during lens development.

      (5) The authors followed up their work analyzing various signaling molecules in the context of lens development with biochemical analyses of FGF-induced phosphorylation in murine embryonic fibroblasts (MEFs).

      (6) In general, this manuscript represents a Herculean effort to dissect FGFR signaling in vivo with biochemical backing with cell culture experiments in vitro.

      Weaknesses:

      (1) The authors demonstrate that the loss of FGFR1 and FGFR2 can be compensated by a constitutive active KRAS allele in the lens and suggest that FGFRs largely support lens development only by driving ERK activation. However, the authors also saw that lens development was substantially rescued by preventing apoptosis through the deletion of BAK and BAX. To my knowledge, the deletion of BAK and BAX should not independently activate ERK. The authors do not show whether ERK activation is restored in the BAK/BAX deficient lenses. Do the authors suggest the FGFR3 and/or FGFR4 provide sufficient RAS and ERK activation for lens development when apoptosis is suppressed? Alternatively, is it the survival function of FGFR-signaling as much as a direct effect on lens differentiation?

      (2) Do the authors suggest that GRB2 is required for RAS activation and ultimately ERK activation? If so, do the authors suggest that ERK activation is not required for FGFR-signaling to mediate lens induction? This would follow considering that the GRB2 deficient lenses lack a problem with lens induction.

      (3) The increase in p-Shc is only slightly higher in the Cre FGFR1f/f FGFR2r/LR than in the FGFR1f/Δfrs FGFR2f/f. Can the authors provide quantification?

      (4) The authors have not shown directly that Shc1 binds to the juxtamembrane region of either Fgfr1 or Fgfr2.

    1. Reviewer #3 (Public review):

      Summary:

      In this manuscript, the group of Glickman expands on their previous studies on the function of chalkophores during the growth of and infection by Mycobacterium tuberculosis. Previously, the group had shown that chalkophores, which are metallophores specific for the scavenging of copper, are induced by M. tuberculosis under copper deprivation conditions. Here, they show that chalkophores, under copper limiting conditions, are essential for the uptake of copper and maturation of a terminal oxidase, the heme-copper oxidase, cytochrome bcc:aa3. As M. tuberculosis has two redundant terminal oxidases, growth of and infection by M. tuberculosis is only moderated if both the chalkophores and the second terminal oxidase, cytochrome bd, are inhibited.

      Strengths:

      A strength of this work is that the lab-culture experiments are expanded upon with mice infection models, providing strong indications that host-inflicted copper deprivation is a condition that M. tuberculosis has adapted to for virulence.

      Weaknesses:

      Because the phenotype of M. tuberculosis lacking chalkophores is similar, if not identical, to using Q203, an inhibitor of cytochrome bcc:aa3, the authors propose that the copper-containing cytochrome bcc:aa3 is the only recipient of copper-uptake by chalkophores. A minor weakness of the work is that this latter conclusion is not verified under infection conditions and other copper-enzymes might still be functionally required during one or more stages of infection.

    1. Reviewer #3 (Public review):

      Summary:

      This manuscript studies intracellular changes and immune processes during early HIV-1 infection with an additional focus on the small CD4+ T cell subsets. The authors used single-cell omics to achieve high resolution of transcriptomic and epigenomic data on the infected cells which were verified by viral RNA expression. The results add to understanding of transcriptional regulation which may allow progression or HIV latency later in infected cells. The biosamples were derived from early HIV infection cases, providing particularly valuable data for the HIV research field.

      Strengths:

      The authors examined the heterogeneity of infected cells within CD4 T cell populations, identified a significant and unexpected difference between naive and effector CD4 T cells, and highlighted the differences in Th2 and Th17 cells. Multiple methods were used to show the role of the increased KLF2 factor in infected cells. This is a valuable finding of a new role for the major transcription factor in further disease progression and/or persistence.

      The methods employed by the authors are robust. Single-cell RNA-Seq from PBMC samples was followed by a comprehensive annotation of immune cell subsets, 16 in total. This manuscript presents to the scientific community a valuable multi-omics dataset of good quality, which could be further analyzed in the context of larger studies.

      Weaknesses:

      Methods and Supplementary materials<br /> Some technical aspects could be described in more detail. For example, it is unclear how the authors filtered out cells that did not pass quality control, such as doublets and cells with low transcript/UMI content. Next, in cell annotation, what is the variability in cell types between donors? This information is important to include in the supplementary materials, especially with such a small sample size. Without this, it is difficult to determine, whether the differences between subsets on transcriptomic level, viral RNA expression level, and chromatin assessment are observed due to cell type variations or individual patient-specific variations. For the DEG analysis, did the authors exclude the most variable genes?

      The annotation of 16 cell types from PBMC samples is impressive and of good quality, however, not all cell types get attention for further analysis. It's natural to focus primarily on the CD4 T cells according to the research objectives. The authors also study potential interactions between CD4 and CD8 T cells by cell communication inference. It would be interesting to ask additional questions for other underexplored immune cell subsets, such as: 1) Could viral RNA be detected in monocytes or macrophages during early infection? 2) What are the inferred interactions between NK cells and infected CD4 T cells, are interactions similar to CD4-CD8 results? 3) What are the inferred interactions between monocytes or macrophages and infected CD4 T cells?

      Discussion<br /> It would be interesting to see more discussion of the observation of how naïve T cells produce more viral RNA compared to effector T cells. It seems counterintuitive according to general levels of transcriptional and translational activity in subsets.<br /> Another discussion block could be added regarding the results and conclusion comparison with Ashokkumar et al. paper published earlier in 2024 (10.1093/gpbjnl/qzae003). This earlier publication used both a cell line-based HIV infection model and primary infected CD4 T cells and identified certain transcription factors correlated with viral RNA expression.

    1. Reviewer #3 (Public review):

      Summary:

      This study provides significant insights into how host metabolism, specifically of lipids, influences the pathogenesis of Mycobacterium tuberculosis (Mtb). It builds on existing knowledge about Mtb's reliance on host lipids and emphasizes the potential of targeting fatty acid metabolism for therapeutic intervention.

      Strengths:

      To generate the data, the authors use CRISPR technology to precisely disrupt the genes involved in lipid import (CD36, FATP1), lipid droplet formation (PLIN2) and fatty acid oxidation (CPT1A, CPT2) in mouse primary macrophages. The Mtb Erdman strain is used to infect the macrophage mutants. The study, revealsspecific roles of different lipid-related genes. Importantly, results challenge previous assumptions about lipid droplet formation and show that macrophage responses to lipid metabolism impairments are complex and multifaceted. The experiments are well-controlled and the data is convincing.

      Overall, this well-written paper makes a meaningful contribution to the field of tuberculosis research, particularly in the context of host-directed therapies (HDTs). It suggests that manipulating macrophage metabolism could be an effective strategy to limit Mtb growth.

      Weaknesses:

      None noted. The manuscript provides important new knowledge that will lead mpvel to host-directed therapies to control Mtb infections.

      Comments on revisions: The authors have addressed the concerns of the reviewers.

    1. Reviewer #3 (Public review):

      Summary:

      Bone morphogenetic protein (BMP) signaling instructs multiple processes during development including cell proliferation and differentiation. The authors set out to understand the role of PRDM16 in these various functions of BMP signaling. They find that PRDM16 and BMP co-operate to repress stem cell proliferation by regulating the genomic distribution of BMP pathway transcription factors. They additionally show that PRDM16 impacts choroid plexus epithelial cell specification. The authors provide evidence for a regulatory circuit (constituting of BMP, PRDM16, and Wnt) that influences stem cell proliferation/differentiation.

      Strengths:

      I find the topics studied by the authors in this study of general interest to the field, the experiments well-controlled and the analysis in the paper sound.

      Weaknesses:

      I have no major scientific concerns. I have some minor recommendations that will help improve the paper (regarding the discussion).

    1. Reviewer #3 (Public review):

      This manuscript examines the role of pdgfrb-positive pericytes in the establishment and maintenance of the blood-brain barrier (BBB) in the zebrafish. Previous studies in PDGFB- or PDGFRB-deficient mice have suggested that loss of pericytes results in disruption of the BBB. The authors show that zebrafish pdgfrb mutant larvae have an intact BBB and that pdgfrb mutant adult fish show large vessel defects and hemorrhage but do not exhibit substantial leakage from brain capillaries, suggesting loss of pericytes is not sufficient to "open" the BBB. The authors use beautiful and compelling images and rigorous quantification to back up most of their conclusions. The imaging of the adult brain is particularly nice. The authors rigorously document the lack of BBB leakage in pdgfrbuq30bh mutant larvae and large vessel phenotypes (eg, enlargement and rupture) in pdgfrbuq30bh mutant adults. A few points would help the authors to further strengthen their findings contradicting the current dogma from rodent models.

      Major point:

      The authors document pericyte loss using a single TgBAC(pdgfrb:egfp)ncv22 transgenic line driven by the promoter of the same gene mutated in their pdgfrbuq30bh mutants. Given their findings on the consequences of pericyte loss directly contradict current dogma from rodent studies, it would be useful to further validate the absence of brain pericytes in these mutants using one of several other transgenic lines marking pericytes currently available in the zebrafish. This could be done using pdgfrb crispants, which the authors show nicely phenocopy the germline mutants, at least in larvae. This would help nail down the absence of any currently identifiable pericyte population or sub-population in the loss of pdgfrb animals and substantially strengthen the authors' conclusions.

      Other issues:

      The authors should provide more information about the pdgfrbuq30bh mutant and how it was generated (including a diagram in a supplemental figure would be useful).

      It would be helpful to show some data on whether mutants show morphological phenotypes or developmental delay at 7 and 14 dpf, to provide some context to better assess the reduced branching and vessel length vascular phenotypes (see Figures 1c-e).

      If available, it would be helpful to have a positive control for the tracer leakage experiments - a genetic manipulation that does cause disruption of the BBB and leakage at 2 hours post-tracer injection (see Figures 1f and g).

      Quantification of the findings in Figure 4c,d would be useful, as would the use of germline fish for these experiments if these are now available. If this is not possible, it would be helpful to document that the crispants used in these experiments lack pdgfrb:egfp pericytes at adult stages (this is only shown for 5 dpf larvae, in Extended Data Figure 4b).

      Adult mutants clearly show less dye leakage in the more superficial capillary regions than WT siblings, but dextran intensity is a bit higher, although this could well be diffusion from more central brain regions where overt hemorrhage is occurring. Along similar lines though, the authors' TEM data in Extended Data Figure 4d hints that there may be more caveolae in mutant brain capillaries, although the N number was lower here than for the measurements from TEM of larger central vessels (Figure 4g). It would be useful to carry out additional measurements to increase the N number in Figure 4d to see whether the difference between wild-type sibling and mutant capillary caveolae numbers remains as not significant.

      It might be helpful to include some orienting labels and/or additional descriptions in the figure legends to help readers who are not used to looking at zebrafish brain vessels have an easier time figuring out what they are looking at and where it is in the brain.

    1. Reviewer #3 (Public review):

      Summary:

      This manuscript describes an extensive application of the Yeast (SATAY) transposon mutagenesis and sequencing method to explore loss- and gain-of-function mutations conferring resistance to 20 different antifungal compounds. Impressively, the authors demonstrate that SATAY can be used to identify mutations that lead to antifungal resistance, including promoter mutations that include the direct targets of antifungal compounds and drug efflux pumps. Because SATAY is not tied to a specific genetic background, the sensitivity of an S. cerevisiae strain, AD1-8, that specifically displays Chitosan susceptibility was examined in detail, and the results suggest that Chitosan acts through interactions with the fungal cell wall. Through a series of experiments that expand upon SATAY analysis, the novel antifungal ATI-2307, the authors clearly show that the transporter Hol1 concentrates this compound within yeast.

      General Comments:

      This is a very impressive application of SATAY, highlighting many different strategies for exploring the mechanism of action of various antifungal compounds. It's clear from the findings presented that SATAY is a powerful and potentially highly productive approach for chemical-genetic analysis.

    1. Reviewer #3 (Public review):

      Summary:

      This study examines prediction errors, information gain (Kullback-Leibler [KL] divergence), and uncertainty (entropy) from an information-theory perspective using two experimental tasks and pupillometry. The authors aim to test a theoretical proposal by Zénon (2019) that the pupil response reflects information gain (KL divergence). In particular, the study defines the prediction error in terms of KL divergence and speculates that changes in pupil size associated with KL divergence depend on entropy. Moreover, the authors examine the temporal characteristics of pupil correlates of prediction errors, which differed considerably across previous studies that employed different experimental paradigms. In my opinion, the study does not achieve these aims due to several methodological and theoretical issues.

      Strengths:

      (1) Use of an established Bayesian model to compute KL divergence and entropy.

      (2) Pupillometry data preprocessing, including deconvolution.

      Weaknesses:

      (1) Definition of the prediction error in terms of KL divergence:

      I'm concerned about the authors' theoretical assumption that the prediction error is defined in terms of KL divergence. The authors primarily refer to a review article by Zénon (2019): "Eye pupil signals information gain". It is my understanding that Zénon argues that KL divergence quantifies the update of a belief, not the prediction error: "In short, updates of the brain's internal model, quantified formally as the Kullback-Leibler (KL) divergence between prior and posterior beliefs, would be the common denominator to all these instances of pupillary dilation to cognition." (Zénon, 2019).

      From my perspective, the update differs from the prediction error. Prediction error refers to the difference between outcome and expectation, while update refers to the difference between the prior and the posterior. The prediction error can drive the update, but the update is typically smaller, for example, because the prediction error is weighted by the learning rate to compute the update. My interpretation of Zénon (2019) is that they explicitly argue that KL divergence defines the update in terms of the described difference between prior and posterior, not the prediction error.

      The authors also cite a few other papers, including Friston (2010), where I also could not find a definition of the prediction error in terms of KL divergence. For example [KL divergence:] "A non-commutative measure of the non-negative difference between two probability distributions." Similarly, Friston (2010) states: Bayesian Surprise - "A measure of salience based on the Kullback-Leibler divergence between the recognition density (which encodes posterior beliefs) and the prior density. It measures the information that can be recognized in the data." Finally, also in O'Reilly (2013), KL divergence is used to define the update of the internal model, not the prediction error.

      The authors seem to mix up this common definition of the model update in terms of KL divergence and their definition of prediction error along the same lines. For example, on page 4: "KL divergence is a measure of the difference between two probability distributions. In the context of predictive processing, KL divergence can be used to quantify the mismatch between the probability distributions corresponding to the brain's expectations about incoming sensory input and the actual sensory input received, in other words, the prediction error (Friston, 2010; Spratling, 2017)."

      Similarly (page 23): "In the current study, we investigated whether the pupil's response to decision outcome (i.e., feedback) in the context of associative learning reflects a prediction error as defined by KL divergence."

      This is problematic because the results might actually have limited implications for the authors' main perspective (i.e., that the pupil encodes prediction errors) and could be better interpreted in terms of model updating. In my opinion, there are two potential ways to deal with this issue:

      a) Cite work that unambiguously supports the perspective that it is reasonable to define the prediction error in terms of KL divergence and that this has a link to pupillometry. In this case, it would be necessary to clearly explain the definition of the prediction error in terms of KL divergence and dissociate it from the definition in terms of model updating.

      b) If there is no prior work supporting the authors' current perspective on the prediction error, it might be necessary to revise the entire paper substantially and focus on the definition in terms of model updating.

      (2) Operationalization of prediction errors based on frequency, accuracy, and their interaction:

      The authors also rely on a more model-agnostic definition of the prediction error in terms of stimulus frequency ("unsigned prediction error"), accuracy, and their interaction ("signed prediction error"). While I see the point here, I would argue that this approach offers a simple approximation to the prediction error, but it is possible that factors like difficulty and effort can influence the pupil signal at the same time, which the current approach does not take into account. I recommend computing prediction errors (defined in terms of the difference between outcome and expectation) based on a simple reinforcement-learning model and analyzing the data using a pupillometry regression model in which nuisance regressors are controlled, and results are corrected for multiple comparisons.

      (3) The link between model-based (KL divergence) and model-agnostic (frequency- and accuracy-based) prediction errors:

      I was expecting a validation analysis showing that KL divergence and model-agnostic prediction errors are correlated (in the behavioral data). This would be useful to validate the theoretical assumptions empirically.

      (4) Model-based analyses of pupil data:

      I'm concerned about the authors' model-based analyses of the pupil data. The current approach is to simply compute a correlation for each model term separately (i.e., KL divergence, surprise, entropy). While the authors do show low correlations between these terms, single correlational analyses do not allow them to control for additional variables like outcome valence, prediction error (defined in terms of the difference between outcome and expectation), and additional nuisance variables like reaction time, as well as x and y coordinates of gaze.

      Moreover, including entropy and KL divergence in the same regression model could, at least within each task, provide some insights into whether the pupil response to KL divergence depends on entropy. This could be achieved by including an interaction term between KL divergence and entropy in the model.

      (5) Major differences between experimental tasks:

      More generally, I'm not convinced that the authors' conclusion that the pupil response to KL divergence depends on entropy is sufficiently supported by the current design. The two tasks differ on different levels (stimuli, contingencies, when learning takes place), not just in terms of entropy. In my opinion, it would be necessary to rely on a common task with two conditions that differ primarily in terms of entropy while controlling for other potentially confounding factors. I'm afraid that seemingly minor task details can dramatically change pupil responses. The positive/negative difference in the correlation with KL divergence that the authors interpret to be driven by entropy may depend on another potentially confounding factor currently not controlled.

      (6) Model validation:

      My impression is that the ideal learner model should work well in this case. However, the authors don't directly compare model behavior to participant behavior ("posterior predictive checks") to validate the model. Therefore, it is currently unclear if the model-derived terms like KL divergence and entropy provide reasonable estimates for the participant data.

      (7) Discussion:

      The authors interpret the directional effect of the pupil response w.r.t. KL divergence in terms of differences in entropy. However, I did not find a normative/computational explanation supporting this interpretation. Why should the pupil (or the central arousal system) respond differently to KL divergence depending on differences in entropy?

      The current suggestion (page 24) that might go in this direction is that pupil responses are driven by uncertainty (entropy) rather than learning (quoting O'Reilly et al. (2013)). However, this might be inconsistent with the authors' overarching perspective based on Zénon (2019) stating that pupil responses reflect updating, which seems to imply learning, in my opinion. To go beyond the suggestion that the relationship between KL divergence and pupil size "needs more context" than previously assumed, I would recommend a deeper discussion of the computational underpinnings of the result.

    1. Reviewer #3 (Public review):

      Summary:

      This work aims to investigate how perceptual and attentional processes affect conscious access in humans. By using multivariate decoding analysis of electroencephalography (EEG) data, the authors explored the neural temporal dynamics of visual processing across different levels of complexity (local contrast, collinearity, and illusory perception). This is achieved by comparing the decidability of an illusory percept in matched conditions of perceptual (i.e., degrading the strength of sensory input using visual masking) and attentional impairment (i.e., impairing top-down attention using attentional blink, AB). The decoding results reveal three distinct temporal responses associated with the three levels of visual processing. Interestingly, the early stage of local contrast processing remains unaffected by both masking and AB. However, the later stage of collinearity and illusory percept processing are impaired by the perceptual manipulation but remained unaffected by the attentional manipulation. These findings contribute to the understanding of the unique neural dynamics of perceptual and attentional functions and how they interact with the different stages of conscious access.

      Strengths:

      The study investigates perceptual and attentional impairments across multiple levels of visual processing in a single experiment. Local contrast, collinearity, and illusory perception were manipulated using different configurations of the same visual stimuli. This clever design allows for the investigation of different levels of visual processing under similar low-level conditions.

      Moreover, behavioural performance was matched between perceptual and attentional manipulations. One of the main problems when comparing perceptual and attentional manipulations on conscious access is that they tend to impact performance at different levels, with perceptual manipulations like masking producing larger effects. The study utilizes a staircasing procedure to find the optimal contrast of the mask stimuli to produce a performance impairment to the illusory perception comparable to the attentional condition, both in terms of perceptual performance (i.e., indicating whether the target contained the Kanizsa illusion) and metacognition (i.e., confidence in the response).

      The results show a clear dissociation between the three levels of visual processing in terms of temporal dynamics. Local contrast was represented at an early stage (~80 ms), while collinearity and illusory perception were associated with later stages (~200-250 ms). Furthermore, the results provide clear evidence in support of a dissociation between the effects of perceptual and attentional processes on conscious access: while the former affected both neuronal correlates of collinearity and illusory perception, the latter did not have any effect on the processing of the more complex visual features involved in the illusion perception.

      Weaknesses:

      The design of the study and the results presented are very similar to those in Fahrenfort et al. (2017), reducing its novelty. Similar to the current study, Fahrenfort et al. (2017) tested the idea that if both masking and AB impact perceptual integration, they should affect the neural markers of perceptual integration in a similar way. They found that behavioural performance (hit/false alarm rate) was affected by both masking and AB, even though only the latter was significant in the unmasked condition. In contrast, an early classification peak was exclusively affected by masking. A later classification peak mirrored the behavioural findings, with classification performance impacted by both masking and AB.

      The interpretation of the results primarily relies on the recurrent processing theory of consciousness (Lamme, 2020), which lead to the assumption that local contrast and illusory perception reflect feedforward and (lateral and feedback) recurrent connections, respectively. It should be mentioned, however, that this theoretical prediction is not directly tested in the study. Moreover, the evidence for the dissociation between illusion and collinearity in terms of lateral and feedback connections seems at least limited. For instance, Kok et al. (2016) found that, whereas bottom-up stimulation activated all cortical layers, feedback activity induced by illusory figures led to a selective activation of the deep layers. Lee & Nguyen (2001), instead, found that V1 neurons respond to illusory contours of the Kanizsa figures, particularly in the superficial layers. Although both studies reference feedback connections, neither provides clear evidence for the involvement of lateral connections.

      The evidence in favour of primarily lateral connections driving collinearity seems mixed as well. On one hand, Liang et al. (2017) showed that feedback and lateral connections closely interact to mediate image grouping and segmentation. On the other hand, Stettler et al. (2002) showed that, whereas the intrinsic connections link similarly oriented domains in V1, V2 to V1 feedback displays no such specificity. Additionally, the other studies cited in the manuscript focused solely on lateral connections without examining feedback pathways, making it challenging to draw definitive conclusions.

      Comments on revisions:

      The authors have thoroughly addressed all my comments and provided comprehensive responses to each point raised.

    1. Reviewer #3 (Public review):

      The current manuscript investigates the effect of 2-oxoglutarate (2OG) as modulator of glutamine synthetase (GS). To do this, the authors rely of mass photometry, specific activity measurements and single particle cryo-EM data.<br /> From the results, the authors conclude that the GS from Methanosarcina mazei shifts from a dimeric, non-active state under low concentrations of 2OG, to a dodecameric and fully active complex at saturating concentrations of 2OG.

      GS is a crucial enzyme in all domains of life. The dodecameric fold of GS is recurrent amongst prokaryotic and archaea organisms but the enzyme activity can be regulated in distinct ways. This is a very interesting work combining protein biochemistry with structural biology.

      A novel role for 2OG is presented for this mesophilic methanoarchaeon, as a crucial effector for the enzyme oligomerization and full reactivity.

      The conclusions of this paper are mostly well supported by data, but some aspects of this GS regulation and interaction with known partners like Glnk1 and sp26 need to be clarified and extended.

    1. Reviewer #3 (Public review):

      Summary:

      Wang et al., examined the brain activity patterns during sleep, especially when locked to those canonical sleep rhythms such as SO, spindle, and their coupling. Analyzing data from a large sample, the authors found significant coupling between spindles and SOs, particularly during the upstate of the SO. Moreover, the authors examined the patterns of whole-brain activity locked to these sleep rhythms. To understand the functional significance of these brain activities, the authors further conducted open-ended cognitive state decoding and found a variety of cognitive processing may be involved during SO-spindle coupling and during other sleep events. The authors next investigated the functional connectivity analyses and found enhanced connectivity between the hippocampus, the thalamus, and the medial PFC. These results reinforced the theoretical model of sleep-dependent memory consolidation, such that SO-spindle coupling is conducive to systems-level memory reactivation and consolidation.

      Strengths:

      There are obvious strengths in this work, including the large sample size, state-of-the-art neuroimaging and neural oscillation analyses, and the richness of results.

      Weaknesses:

      Despite these strengths and the insights gained, there are weaknesses in the design, the analyses, and inferences.

      A repeating statement in the manuscript is that brain activity could indicate memory reactivation and thus consolidation. This is indeed a highly relevant question that could be informed by the current data/results. However, an inherent weakness of the design is that there is no memory task before and after sleep. Thus, it is difficult (if not impossible) to make a strong argument linking SO/spindle/coupling-locked brain activity with memory reactivation or consolidation.

      Relatedly, to understand the functional implications of the sleep rhythm-locked brain activity, the authors employed the "open-ended cognitive state decoding" method. While this method is interesting, it is rather indirect given that there were no behavioral indices in the manuscript. Thus, discussions based on these analyses are speculative at best. Please either tone down the language or find additional evidence to support these claims.

      Moreover, the results from this method are difficult to understand. Figure 3e showed that for all three types of sleep events (SO, spindle, SO-spindle), the same mental states (e.g., working memory, episodic memory, declarative memory) showed opposite directions of activation (left and right panels showed negative and positive activation, respectively). How to interpret these conflicting results? This ambiguity is also reflected by the term used: declarative memory and episodic memories are both indexed in the results. Yet these two processes can be largely overlapped. So which specific memory processes do these brain activity patterns reflect? The Discussion shall discuss these results and the limitations of this method.

      The coupling strength is somehow inconsistent with prior results (Hahn et al., 2020, eLife, Helfrich et al., 2018, Neuron). Specifically, Helfrich et al. showed that among young adults, the spindle is coupled to the peak of the SO. Here, the authors reported that the spindles were coupled to down-to-up transitions of SO and before the SO peak. It is possible that participants' age may influence the coupling (see Helfrich et al., 2018). Please discuss the findings in the context of previous research on SO-spindle coupling.

      The discussion is rather superficial with only two pages, without delving into many important arguments regarding the possible functional significance of these results. For example, the author wrote, "This internal processing contrasts with the brain patterns associated with external tasks, such as working memory." Without any references to working memory, and without delineating why WM is considered as an external task even working memory operations can be internal. Similarly, for the interesting results on SO and reduced DMN activity, the authors wrote "The DMN is typically active during wakeful rest and is associated with self-referential processes like mind-wandering, daydreaming, and task representation (Yeshurun, Nguyen, & Hasson, 2021). Its reduced activity during SOs may signal a shift towards endogenous processes such as memory consolidation." This argument is flawed. DMN is active during self-referential processing and mind-wandering, i.e., when the brain shifts from external stimuli processing to internal mental processing. During sleep, endogenous memory reactivation and consolidation are also part of the internal mental processing given the lack of external environmental stimulation. So why during SO or during memory consolidation, the DMN activity would be reduced? Were there differences in DMN activity between SO and SO-spindle coupling events?

    1. Reviewer #3 (Public review):

      Summary:

      The authors used powerful and novel reagents to carefully assess the roles of the voltage gated sodium channel (NaV) isoforms in regulating the neural excitability of principal neurons of the cerebral cortex. Using this approach, they were able to confirm that two different isoforms, NaV1.2 and NaV1.6 have distinct roles in electrogenesis of neocortical pyramidal neurons.

      Strengths:

      Development of very powerful transgenic mice in which NaV1.2 and/or NaV1.6 were modified to be insensitive to ASCs, a particular class of NaV blocker. This allowed them to test for roles of the two isoforms in an acute setting, without concerns of genetic or functional compensation that might result from a NaV channel knockout.

      Careful biophysical analysis of ASC effects on different NaV isoforms.

      Extensive and rigorous analysis of electrogenesis - action potential production - under conditions of blockade of either NaV1.2 or NaV1 or both.

      Weaknesses:

      Some results are overstated in that the representative example records provided do not directly support the conclusions.

      Results from a computational model are provided to make predictions of outcomes, but the computational approach is highly underdeveloped.

    1. Reviewer #3 (Public review):

      Summary:

      Shiqiang Xu and colleagues have examined the importance of ICAM-1 and ALCAM internalization and retrograde transport in cancer cells on the formation of a polarized immunological synapse with cytotoxic CD8+ T cells. They find that internalization is mediated by Endophilin A3 (EndoA3) while retrograde transport to the Golgi apparatus is mediated by the retromer complex. The paper is building on previous findings from corresponding author Henri-François Renard showing that ALCAM is an EndoA3-dependent cargo in clathrin-independent endocytosis.

      Strengths:

      The work is interesting as it describes a novel mechanism by which cancer cells might influence CD8+ T cell activation and immunological synapse formation, and the authors have used a variety of cell biology and immunology methods to study this. However, there are some aspects of the paper that should be addressed more thoroughly to substantiate the conclusions made by the authors.

      Weaknesses:

      In Figure 2A-B, the authors show micrographs from live TIRF movies of HeLa and LB33-MEL cells stably expressing EndoA3-GFP and transiently expressing ICAM-1-mScarlet. The ICAM-1 signal appears diffuse across the plasma membrane while the EndoA3 signal is partially punctate and partially lining the edge of membrane patches. Previous studies of EndoA3-mediated endocytosis have indicated that this can be observed as transient cargo-enriched puncta on the cell surface. In the present study, there is only one example of such an ICAM-1 and EndoA3 positive punctate event. Other examples of overlapping signals between ICAM-1 and EndoA3 are shown, but these either show retracting ICAM-1 positive membrane protrusions or large membrane patches encircled by EndoA3. While these might represent different modes of EndoA3-mediated ICAM-1 internalization, any conclusion on this would require further investigation.

      Moreover, in Figure 2C-E, uptake of the previously established EndoA3 endocytic cargo ALCAM is analyzed by quantifying total internal fluorescence in LB33-MEL cells of antibody labelled ALCAM following both overexpression and siRNA-mediated knockdown of EndoA3, showing increased and decreased uptake respectively. Why has not the same quantification been done for the proposed novel EndoA3 endocytic cargo ICAM-1? Furthermore, if endocytosis of ICAM-1 and ALCAM is diminished following EndoA3 knockdown, the expression level on the cell surface would presumably increase accordingly. This has been shown for ALCAM previously and should also be quantified for ICAM-1.

      In Figure 4A the authors show micrographs from a live-cell Airyscan movie (Movie S6) of a CD8+ T cell incubated with HeLa cells stably expressing HLA-A*68012 and transiently expressing ICAM1-EGFP. From the movie, it seems that some ICAM-1 positive vesicles in one of the HeLa cells are moving towards the T cell. However, it does not appear like the T cell has formed a stable immunological synapse but rather perhaps a motile kinapse. Furthermore, to conclude that the ICAM-1 positive vesicles are transported toward the T cell in a polarized manner, vesicles from multiple cells should be tracked and their overall directionality should be analyzed. It would also strengthen the paper if the authors could show additional evidence for polarization of the cancer cells in response to T-cell interaction.

      Finally, in Figures 4D-G, the authors show that the contact area between CD8+ T cells and LB33-MEL cells is increased in response to siRNA-mediated knockdown of EndoA3 and VPS26A. While this could be caused by reduced polarized delivery of ICAM-1 and ALCAM to the interface between the cells, it could also be caused by other factors such as increased cell surface expression of these proteins due to diminished endocytosis, and/or morphological changes in the cancer cells resulting from disrupted membrane traffic. More experimental evidence is needed to support the working model in Figure 4H.

    1. Reviewer #3 (Public review):

      Summary:

      In the manuscript by Lapao et al., the authors uncover a role for the RAB27A effector protein SYTL5 in regulating mitochondrial function and turnover. The authors find that SYTL5 localizes to mitochondria in a RAB27A-dependent way and that loss of SYTL5 (or RAB27A) impairs lysosomal turnover of an inner mitochondrial membrane mitophagy reporter but not a matrix-based one. As the authors see no co-localization of GFP/mScarlet tagged versions of SYTL5 or RAB27A with LC3 or p62, they propose that lysosomal turnover is independent of the conventional autophagy machinery. Finally, the authors go on to show that loss of SYTL5 impacts mitochondrial respiration and ECAR and as such may influence the Warburg effect and tumorigenesis. Of relevance here, the authors go on to show that SYTL5 expression is reduced in adrenocortical carcinomas and this correlates with reduced survival rates.

      Strengths:

      There are clearly interesting and new findings here that will be relevant to those following mitochondrial function, the endocytic pathway, and cancer metabolism.

      Weaknesses:

      The data feel somewhat preliminary in that the conclusions rely on exogenously expressed proteins and reporters, which do not always align.

      As the authors note there are no commercially available antibodies that recognize endogenous SYTL5, hence they have had to stably express GFP-tagged versions. However, it appears that the level of expression dictates co-localization from the examples the authors give (though it is hard to tell as there is a lack of any kind of quantitation for all the fluorescent figures). Therefore, the authors may wish to generate an antibody themselves or tag the endogenous protein using CRISPR.

      In relation to quantitation, the authors found that SYTL5 localizes to multiple compartments or potentially a few compartments that are positive for multiple markers. Some quantitation here would be very useful as it might inform on function.

      The authors find that upon hypoxia/hypoxia-like conditions that punctate structures of SYTL5 and RAB27A form that are positive for Mitotracker, and that a very specific mitophagy assay based on pSu9-Halo system is impaired by siRNA of SYTL5/RAB27A, but another, distinct mitophagy assay (Matrix EGFP-mCherry) shows no change. I think this work would strongly benefit from some measurements with endogenous mitochondrial proteins, both via immunofluorescence and western blot-based flux assays.

      A really interesting aspect is the apparent independence of this mitophagy pathway on the conventional autophagy machinery. However, this is only based on a lack of co-localization between p62 or LC3 with LAMP1 and GFP/mScarlet tagged SYTL5/RAB27A. However, I would not expect them to greatly colocalize in lysosomes as both the p62 and LC3 will become rapidly degraded, while the eGFP and mScarlet tags are relatively resistant to lysosomal hydrolysis. -/+ a lysosome inhibitor might help here and ideally, the functional mitophagy assays should be repeated in autophagy KOs.

      The link to tumorigenesis and cancer survival is very interesting but it is not clear if this is due to the mitochondrially-related aspects of SYTL5 and RAB27A. For example, increased ECAR is seen in the SYTL5 KO cells but not in the RAB27A KO cells (Fig.5D), implying that mitochondrial localization of SYTL5 is not required for the ECAR effect. More work to strengthen the link between the two sections in the paper would help with future directions and impact with respect to future cancer treatment avenues to explore.

    1. Reviewer #3 (Public review):

      Summary:

      The authors have studied the mechanics of bolalipid and archaeal mixed-lipid membranes via comprehensive molecular dynamics simulations. The Cooke-Deserno 3-bead-per-lipid model is extended to bolalipids with 6 beads. Phase diagrams, bending rigidity, mechanical stability of curved membranes, and cargo uptake are studied. Effects such as the formation of U-shaped bolalipids, pore formation in highly curved regions, and changes in membrane rigidity are studied and discussed. The main aim has been to show how the mixture of bolalipids and regular bilayer lipids in archaeal membrane models enhances the fluidity and stability of these membranes.

      Strengths:

      The authors have presented a wide range of simulation results for different membrane conditions and conformations. For the most part, the analyses and their results are presented clearly and concisely. Figures, supplementary information, and movies very well present what has been studied. The manuscript is well-written and is easy to follow.

      Major issues:

      The Cooke-Deserno model, while very powerful for biophysical analysis of membranes at the mesoscale, is very much void of chemical information. It is parameterized such that it is good in producing fluid membranes and predicting values for bending rigidity, compressibility, and even thermal expansion coefficient falling in the accepted range of values for bilayer membranes. But it still represents a generic membrane. Now, the authors have suggested a similar model for the archaeal bolalipids, which have chemically different lipids (the presence of cyclopentane rings for one), and there is no good justification for using the same pairwise interactions between their representative beads in the coarse-grained model. This does not necessarily diminish the worth of all the authors' analyses. What is at risk here is the confusion between "what we observe this model of bolalipid- or mixed-membranes do" and "how real bolalipid-containing archaeal membranes behave at these mechanical and thermal conditions.".

      Another more specific, major issue has to do with using the Hamm-Kozlov model for fitting the power spectrum of thermal undulations. The 1/q^2 term can very well be attributed to membrane tension. While a barostat is indeed used, have the authors made absolutely sure that the deviation from 1/q^4 behavior does not correspond to lateral tension? I got more worried when I noticed in the SI that the simulations had been done with combined "fix langevin" and "fix nph" LAMMPS commands. This combination does not result in a proper isothermal-isobaric ensemble. The importance of tilt terms for bolalipids is indeed very interesting, but I believe more care is needed to establish that.

      This issue is reinforced when considering Figure 3B. These results suggest that increasing the fraction of regular lipids increases the tilt modulus, with the maximum value achieved for a normal Cooke-Deserno bilayer void of bolalipids. But this is contradictory. For these bilayers, we don't need the tilt modulus in the first place.

      Also, from the SI, I gathered that the authors have neglected the longest wavelength mode because it is not equilibrated. If this is indeed the case, it is a dangerous thing to do, because with a small membrane patch, this mode can very well change the general trend of the power spectrum. As a lot of other analyses in the manuscript rely on these measurements, I believe more elaboration is in order.

      The authors have found that "there is a strong dependency of the bending rigidity on the membrane mean curvature of stiffer bolalipids." The effect is negative, with the membrane becoming less stiff at higher mean curvatures. Why is that? I would assume that with more flexible bolalipids, the possibility of reorganization into U-shaped chains should affect the bending rigidity more (as Figure 2E suggests). While for a stiff bolalipid, not much would change if you increase the mean curvature. This should be either a tilt effect, or have to do with asymmetry between the leaflets. But on the other hand, the tilt modulus is shown to decrease with increasing bolalipid rigidity. The authors get back to this issue only on page 10, when they consider U-shaped lipids in the inner and outer leaflets and write, "this suggested that an additional membrane-curving mechanism must be involved." But then again, in the Discussion, the authors write, "It is striking that membranes made from stiffer bolalipids showed a curvature-dependent bending modulus, which is a clear signature that bolalipid membranes exhibit plastic behavior during membrane reshaping," adding to the confusion.

      This issue is repeated when the authors study nanoparticle uptake. They write: "to reconcile these seemingly conflicting observations we reason that the bending rigidity, similar to Figure 2F, is not constant but softens upon increasing membrane curvature, due to dynamic change in the ratio between bolalipids in straight and U-shaped conformation. Hence, bolalipid membranes show stroking plastic behavior as they soften during reshaping." But the softening effect that they refer to, as shown in Figure 4B, occurs for very stiff bolalipids, for which not much switching to U-shaped conformation should occur.

      Another major issue is with what the authors refer to as the "effective temperature". While plotting phase diagrams for kT/eps value is absolutely valid, I'm not a fan of calling this effective temperature. It is a dimensionless quantity that scales linearly with temperature, but is not a temperature. It is usually called a "reduced temperature". Then the authors refer to their findings as studying the stability of archaeal membranes at high temperatures. I have to disagree because eps is not the only potential parameter in the simulations (there are at least space exclusion and angle-bending stiffnesses) so one cannot identify changing eps with changing the global simulation temperature. This only works when you have one potential parameter, like an LJ gas.

      Minor issues:

      As the authors have noted, the fact that the membrane curvature can change the ratio of U-shaped to straight bolalipids would render the curvature elasticity non-linear (though the term "plastic" should not be used, as this is still structurally reversible when the stress is removed. Technically, it is hypoelastic behavior, possibly with hysteresis.) With this in mind, when the authors use essentially linear elastic models for fluctuation analysis, they should make a comparison of maximum curvatures occurring in simulations with a range that causes significant changes in bolalipid conformational ratios.

      The Introduction section of the manuscript is written with a biochemical approach, with very minor attention to the simulation works on this system. Some molecular dynamics works are only cited as existing previous work, without mentioning what has already been studied in archaeal membranes. While some information, like the binding of ESCRT proteins to archaeal membranes, though interesting, helps little to place the study within the discipline. The Introduction should be revised to show what has already been studied with simulations (as the authors mention in the Discussion) and how the presented research complements it.

      The authors have been a bit loose with using the term "stability". I'd like to see the distinction in each case, as in "chemical/thermal/mechanical/conformational stability".

      In the original Cooke-Deserno model, a so-called "poorman's angle-bending term" is used, which is essentially a bond-stretching term between the first and third particle. However, I notice the authors using the full harmonic angle-bending potential. This should be mentioned.

      The analysis of energy of U-shaped lipids with the linear model E=c_0 + c_1 * k_bola is indeed very interesting. I am curious, can this also be corroborated with mean energy measurements? The minor issue is calling the source of the favorability of U-shaped lipids "entropic", while clearly an energetic contribution is found. The two conformations, for example, might differ in the interactions with the neighboring lipids.

      The authors write in the Discussion, "In any case, our results indicate that membrane remodelling, such as membrane fission during membrane traffic, is much more difficult in bolalipid membranes [34]." Firstly, I'm not sure if studying the dependence of budding behavior on adhesion energy with nanoparticles is enough to make claims about membrane fission. Secondly, why is the 2015 paper by Markus Deserno cited here?

      In the SI, where the measurement of the diffusion coefficient is discussed, the expression for D is missing the power 2 of displacement.

      Where cargo uptake is discussed, the term "adsorption energy" is used. I think the more appropriate term would be "adhesion energy".

      Typos:<br /> Page 1, paragraph 2: Adaption → Adaptation.<br /> Page 10, paragraph 1: Stroking → Striking.

    1. Reviewer #3 (Public review):

      Summary:

      The manuscript by Squiers and colleagues uncovers a Commander-independent function for COMMD3 in endosomal recycling. The authors identified COMMD3 as a regulator of endosomal recycling for GLUT4-SPR through unbiased genetic screens. Subsequently, the authors performed COMMD3 knockout experiments to assess endosomal morphology and trafficking, demonstrating that COMMD3 regulates endosomal trafficking in a Commander-independent manner. Furthermore, the authors identified and confirmed that the N-terminal domain (NTD) of COMMD3 interacts with the GTPase Arf1. Using structure-guided mutations, they demonstrated that the COMMD3-Arf1 interaction is critical for the Commander-independent function of COMMD3.

      Overall, the manuscript presents compelling evidence for a Commander-independent role of COMMD3, and I agree with the author's interpretations. The manuscript uses a combination of genetic screening, microscopy, and structural and biochemical approaches to examine and support the conclusions. This is an excellent and intriguing study and I have only a few comments and suggestions to improve the manuscript further.

    1. Reviewer #2 (Public review):

      This manuscript addresses an important question which has not yet been solved in the field, what is the contribution of different gamma oscillatory inputs to the development of "theta sequences" in the hippocampal CA1 region. Theta sequences have received much attention due to their proposed roles in encoding short-term behavioral predictions, mediating synaptic plasticity, and guiding flexible decision making. Gamma oscillations in CA1 offer a readout of different inputs to this region and have been proposed to synchronize neuronal assemblies and modulate spike timing and temporal coding. However, the interactions between these two important phenomena have not been sufficiently investigated. The authors conducted place cell and local field potential (LFP) recordings in the CA1 region of rats running on a circular track. They then analyzed the phase locking of place cell spikes to slow and fast gamma rhythms, the evolution of theta sequences during behavior and the interaction between these two phenomena. They found that place cell with the strongest modulation by fast gamma oscillations were the most important contributors to the early development of theta sequences and that they also displayed a faster form of phase precession within slow gamma cycles nested with theta. The results reported are interesting and support the main conclusions of the authors. However, the manuscript needs significant improvement in several aspects regarding data analysis, description of both experimental and analytical methods and alternative interpretations, as I detail below.

      • The experimental paradigm and recordings should be explained at the beginning of the Results section. Right now, there is no description whatsoever which makes it harder to understand the design of the study.<br /> • An important issue that needs to be addressed is the very small fraction of CA1 cells phased-locked to slow gamma rhythms (3.7%). This fraction is much lower than in many previous studies, that typically report it in the range of 20-50 %. However, this discrepancy is not discussed by the authors. This needs to be explained and additional analysis considered. One analysis that I would suggest, although there are also other valid approaches, is to, instead of just analyze the phase locking in two discrete frequency bands, to compute the phase locking will all LFP frequencies from 25-100 Hz. This will offer a more comprehensive and unbiased view of the gamma modulation of place cell firing. Alternative metrics to mean vector length that are less sensitive to firing rates, such as pairwise phase consistency index (Vinck et a., Neuroimage, 2010), could be implemented. This may reveal whether the low fraction of phase locked cells could be due to a low number of spikes entering the analysis.<br /> • From the methods, it is not clear to me whether the reference LFP channel was consistently selected to be a different one that where the spikes analyzed were taken. This is the better practice to reduce the contribution of spike leakage that could substantially inflate the coupling with faster gamma frequencies. These analyses need to be described in more detail.<br /> • The initial framework of the authors of classifying cells into fast gamma and not fast gamma modulated implies a bimodality that may be artificial. The authors should discuss the nuances and limitations of this framework. For example, several previous work has shown that the same place cell can couple to different gamma oscillations (e.g., Lastoczni et al., Neuron, 2016; Fernandez-Ruiz et al., Neuron, 2017; Sharif et al., Neuron,2021).<br /> • It would be useful to provide a more through characterization of the physiological properties of FG and NFG cells, as this distinction is the basis of the paper. Only very little characterization of some place cell properties is provided in Figure 5. Important characteristics that should be very feasible to compare include average firing rate, burstiness, estimated location within the layer (i.e., deep vs superficial sublayers) and along the transverse axis (i.e., proximal vs distal), theta oscillation frequency, phase precession metrics (given their fundamental relationship with theta sequences), etc.<br /> • It is not clear to me how the analysis in Figure 6 was performed. In Fig. 6B I would think that the grey line should connect with the bottom white dot in the third panel, which would the interpretation of the results.

      Comments on revisions:

      The authors have conducted new analysis to address the issues I and the other reviewers raised in our original revision. As a result, the revised manuscript has been substantially improved.

    1. Reviewer #3 (Public review):

      Summary:

      The authors describe a new method for measuring DNA torsion in cells using the photoactivatable intrastrand cross-linker trimethyl psoralen (TMP). However, their method differs from previous TMP-based torsion mapping methods by comparing formaldehyde cross-linked and torsionally trapped chromatin to torsion-relieved (zero-torsion) chromatin in parallel. Comparison between the two datasets reveals a very slight difference, but enough to provide extremely high resolution genome-wide maps of torsion in the yeast genome. This direct comparison of the two maps confirms that blockage of TMP binding by nucleosomes and some DNA-binding proteins from TMP intercalation is a major complication of previous methods, and analysis of the data provides a glimpse of chromatin-based processes from within the DNA gyre.

      Strengths:

      In addition to providing direct evidence for the twin-supercoiled domain model and for torsional effects at transcription start (TSS) and end (TES) sites, the authors' analyses reveal some novel features of yeast higher-order structure. These include the cohesin-dependent anchoring of DNA loops at sites of positive supercoiling and the insulation of torsion between closely spaced divergent genes by general transcription factors, which implies that these factors resist free rotation. The fact that method should be generalizable to complex eukaryotic cells with large genomes, and the implications for understanding how torsion impacts transcription and gene regulation will be of substantial interest to a broad community.

      Weaknesses:

      No serious weaknesses.

    1. Reviewer #3 (Public review):

      Summary:

      This intriguing paper addresses a special case of a fundamental statistical question: how to distinguish between stochastic point processes that derive from a single "state" (or single process) and more than one state/process. In the language of the paper, a "state" (perhaps more intuitively called a strategy/process) refers to a set of rules that determine the temporal statistics of the system. The rules give rise to probability distributions (here, the probability for turning events). The difficulty arises when the sampling time is finite, and hence, the empirical data is finite, and affected by the sampling of the underlying distribution(s). The specific problem being tackled is the foraging behavior of C. elegans nematodes, removed from food. Such foraging has been studied for decades, and described by a transition over time from 'local'/'area-restricted' search'(roughly in the initial 10-30 minutes of the experiments, in which animals execute frequent turns) to 'dispersion', or 'global search' (characterized by a low frequency of turns). The authors propose an alternative to this two-state description - a potentially more parsimonious single 'state' with time-changing parameters, which they claim can account for the full-time course of these observations.

      Figure 1a shows the mean rate of turning events as a function of time (averaged across the population). Here, we see a rapid transient, followed by a gradual 4-5 fold decay in the rate, and then levels off. This picture seems consistent with the two-state description. However, the authors demonstrate that individual animals exhibit different "transition" statistics (Figure 1e) and wish to explain this. They do so by fitting this mean with a single function (Equations 1-3).

      Strengths:

      As a qualitative exercise, the paper might have some merit. It demonstrates that apparently discrete states can sometimes be artifacts of sampling from smoothly time-changing dynamics. However, as a generic point, this is not novel, and so without the grounding in C. elegans data, is less interesting.

      Weaknesses:

      (1) The authors claim that only about half the animals tested exhibit discontinuity in turning rates. Can they automatically separate the empirical and model population into these two subpopulations (with the same method), and compare the results?

      (2) The equations consider an exponentially decaying rate of turning events. If so, Figure 2b should be shown on a semi-logarithmic scale.

      (3) The variables in Equations 1-3 and the methods for simulating them are not well defined, making the method difficult to follow. Assuming my reading is correct, Omega should be defined as the cumulative number of turning events over time (Omega(t)), not as a "turn" or "reorientation", which has no derivative. The relevant entity in Figure 1a is apparently , i.e. the mean number of events across a population which can be modelled by an expectation value. The time derivative would then give the expected rate of turning events as a function of time.

      (4) Equations 1-3 are cryptic. The authors need to spell out up front that they are using a pair of coupled stochastic processes, sampling a hidden state M (to model the dynamic turning rate) and the actual turn events, Omega(t), separately, as described in Figure 2a. In this case, the model no longer appears more parsimonious than the original 2-state model. What then is its benefit or explanatory power (especially since the process involving M is not observable experimentally)?

      (5) Further, as currently stated in the paper, Equations 1-3 are only for the mean rate of events. However, the expectation value is not a complete description of a stochastic system. Instead, the authors need to formulate the equations for the probability of events, from which they can extract any moment (they write something in Figure 2a, but the notation there is unclear, and this needs to be incorporated here).

      (6) Equations 1-3 have three constants (alpha and gamma which were fit to the data, and M0 which was presumably set to 1000). How does the choice of M0 affect the results?

      (7) M decays to near 0 over 40 minutes, abolishing omega turns by the end of the simulations. Are omega turns entirely abolished in worms after 30-40 minutes off food? How do the authors reconcile this decay with the leveling of the turning rate in Figure 1a?

      (8) The fit given in Figure 2b does not look convincing. No statistical test was used to compare the two functions (empirical and fit). No error bars were given (to either). These should be added. In the discussion, the authors explain the discrepancy away as experimental limitations. This is not unreasonable, but on the flip side, makes the argument inconclusive. If the authors could model and simulate these limitations, and show that they account for the discrepancies with the data, the model would be much more compelling. To do this, I would imagine that the authors would need to take the output of their model (lists of turning times) and convert them into simulated trajectories over time. These trajectories could be used to detect boundary events (for a given size of arena), collisions between individuals, etc. in their simulations and to see their effects on the turn statistics.

      (9) The other figures similarly lack any statistical tests and by eye, they do not look convincing. The exception is the 6 anecdotal examples in Figure 2e. Those anecdotal examples match remarkably closely, almost suspiciously so. I'm not sure I understood this though - the caption refers to "different" models of M decay (and at least one of the 6 examples clearly shows a much shallower exponential). If different M models are allowed for each animal, this is no longer parsimonious. Are the results in Figure 2d for a single M model? Can Figure 2e explain the data with a single (stochastic) M model?

      (10) The left axes of Figure 2e should be reverted to cumulative counts (without the normalization).

      (11) The authors give an alternative model of a Levy flight, but do not give the obvious alternative models:<br /> a) the 1-state model in which P(t) = alpha exp (-gamma t) dt (i.e. a single stochastic process, without a hidden M, collapsing equations 1-3 into a single equation).<br /> b) the originally proposed 2-state model (with 3 parameters, a high turn rate, a low turn rate, and the local-to-global search transition time, which can be taken from the data, or sampled from the empirical probability distributions). Why not? The former seems necessary to justify the more complicated 2-process model, and the latter seems necessary since it's the model they are trying to replace. Including these two controls would allow them to compare the number of free parameters as well as the model results. I am also surprised by the Levy model since Levy is a family of models. How were the parameters of the Levy walk chosen?

      (12) One point that is entirely missing in the discussion is the individuality of worms. It is by now well known that individual animals have individual behaviors. Some are slow/fast, and similarly, their turn rates vary. This makes this problem even harder. Combined with the tiny number of events concerned (typically 20-40 per experiment), it seems daunting to determine the underlying model from behavioral statistics alone.

      (13) That said, it's well-known which neurons underpin the suppression of turning events (starting already with Gray et al 2005, which, strangely, was not cited here). Some discussion of the neuronal predictions for each of the two (or more) models would be appropriate.

      (14) An additional point is the reliance entirely on simulations. A rigorous formulation (of the probability distribution rather than just the mean) should be analytically tractable (at least for the first moment, and possibly higher moments). If higher moments are not obtainable analytically, then the equations should be numerically integrable. It seems strange not to do this.

      In summary, while sample simulations do nicely match the examples in the data (of discontinuous vs continuous turning rates), this is not sufficient to demonstrate that the transition from ARS to dispersion in C. elegans is, in fact, likely to be a single 'state', or this (eq 1-3) single state. Of course, the model can be made more complicated to better match the data, but the approach of the authors, seeking an elegant and parsimonious model, is in principle valid, i.e. avoiding a many-parameter model-fitting exercise.

      As a qualitative exercise, the paper might have some merit. It demonstrates that apparently discrete states can sometimes be artifacts of sampling from smoothly time-changing dynamics. However, as a generic point, this is not novel, and so without the grounding in C. elegans data, is less interesting.

    1. Reviewer #3 (Public review):

      Summary:

      In this set of experiments, the authors describe a novel research tool for studying complex cognitive tasks in mice, the HABITS automated training apparatus, and a novel "machine teaching" approach they use to accelerate training by algorithmically providing trials to animals that provide the most information about the current rule state for a given task.

      Strengths:

      There is much to be celebrated in an inexpensively constructed, replicable training environment that can be used with mice, which have rapidly become the model species of choice for understanding the roles of distinct circuits and genetic factors in cognition. Lingering challenges in developing and testing cognitive tasks in mice remain, however, and these are often chalked up to cognitive limitations in the species. The authors' findings, however, suggest that instead, we may need to work creatively to meet mice where they live. In some cases, it may be that mice may require durations of training far longer than laboratories are able to invest with manual training (up to over 100k trials, over months of daily testing) but the tasks are achievable. The "machine teaching" approach further suggests that this duration could be substantially reduced by algorithmically optimizing each trial presented during training to maximize learning.

      Weaknesses:

      Cognitive training and testing in rodent models fill a number of roles. Sometimes, investigators are interested in within-subjects questions - querying a specific circuit, genetically defined neuron population, or molecule/drug candidate, by interrogating or manipulating its function in a highly trained animal. In this scenario, a cohort of highly trained animals that have been trained via a method that aims to make their behavior as similar as possible is a strength.

      However, often investigators are interested in between-subjects questions - querying a source of individual differences that can have long-term and/or developmental impacts, such as sex differences or gene variants. This is likely to often be the case in mouse models especially, because of their genetic tractability. In scenarios where investigators have examined cognitive processes between subjects in mice who vary across these sources of individual difference, the process of learning a task has been repeatedly shown to be different. The authors do not appear to have considered individual differences except perhaps as an obstacle to be overcome.

      The authors have perhaps shown that their main focus is highly-controlled within-subjects questions, as their dataset is almost exclusively made up of several hundred young adult male mice, with the exception of 6 females in a supplemental figure. It is notable that these female mice do appear to learn the two-alternative forced-choice task somewhat more rapidly than the males in their cohort.

      Considering the implications for mice modeling relevant genetic variants, it is unclear to what extent the training protocols and especially the algorithmic machine teaching approach would be able to inform investigators about the differences between their groups during training. For investigators examining genetic models, it is unclear whether this extensive training experience would mitigate the ability to observe cognitive differences, or select the animals best able to overcome them - eliminating the animals of interest. Likewise, the algorithmic approach aims to mitigate features of training such as side biases, but it is worth noting that the strategic uses of side biases in mice, as in primates, can benefit learning, rather than side biases solely being a problem. However, the investigators may be able to highlight variables selected by the algorithm that are associated with individual strategies in performing their tasks, and this would be a significant contribution.

      A final, intriguing finding in this manuscript is that animal self-paced training led to much slower learning than "manual" training, by having the experimenter introduce the animal to the apparatus for a few hours each day. Manual training resulted in significantly faster learning, in almost half the number of trials on average, and with significantly fewer omitted trials. This finding does not necessarily argue that manual training is universally a better choice because it leads to more limited water consumption. However, it suggests that there is a distinct contribution of experimenter interactions and/or switching contexts in cognitive training, for example by activating an "occasion setting" process to accelerate learning for a distinct period of time. Limiting experimenter interactions with mice may be a labor-saving intervention, but may not necessarily improve performance. This could be an interesting topic of future investigation, of relevance to understanding how animals of all species learn.

    1. Reviewer #3 (Public review):

      Summary

      In this work, the authors asked how mating experience impacts reward perception and processing. For this, they employ fruit flies as a model, with a combination of behavioral, immunostaining, and live calcium imaging approaches.

      Their study allowed them to demonstrate that courtship failure decreases the fraction of flies motivated to eat sweet compounds, revealing a link between reproductive stress and reward-related behaviors. This effect is mediated by a small group of dopaminergic neurons projecting to the SEZ. After courtship failure, these dopaminergic neurons exhibit reduced activity, leading to decreased Gr5a+ neuron activity via Dop1R1 and Dop2R signaling, and leading to reduced sweet sensitivity. The authors therefore showed how mating failure influences broader behavioral outputs through suppression of the dopamine-mediated reward system and underscores the interactions between reproductive and reward pathways.

      Concern

      My main concern regarding this study lies in the way the authors chose to present their results. If I understood correctly, they provided evidence that mating failure induces a decrease in the fraction of flies exhibiting PER. However, they also showed that food consumption was not affected (Fig. 1, supplement), suggesting that individuals who did eat consumed more. This raises questions about the analysis and interpretation of the results. Should we consider the group as a whole, with a reduced sensitivity to sweetness, or should we focus on individuals, with each one eating more? I am also concerned about how this could influence the results obtained using live imaging approaches, as the flies being imaged might or might not have been motivated to eat during the feeding assays. I would like the authors to clarify their choice of analysis and discuss this critical point, as the interpretation of the results could potentially be the opposite of what is presented in the manuscript.

    1. Reviewer #3 (Public review):

      Summary:

      Krishnan et al. present a novel contextual fear conditioning (CFC) paradigm using a virtual reality (VR) apparatus to evaluate whether conditioned context-induced freezing can be elicited in head-fixed mice. By combining this approach with two-photon imaging, the authors aim to provide high-resolution insights into the neural mechanisms underlying learning, memory, and fear. Their experiments demonstrate that head-fixed mice can discriminate between threat and non-threat contexts, exhibit fear-related behavior in VR, and show context-dependent variability during extinction. Supplemental analyses further explore alternative behaviors and the influence of experimental parameters, while hippocampal neuron remapping is tracked throughout the experiments, showcasing the paradigm's potential for studying memory formation and extinction processes.

      Strengths:

      Methodological Innovation: The integration of a VR-based CFC paradigm with real-time two-photon imaging offers a powerful, high-resolution tool for investigating the neural circuits underlying fear, learning, and memory.

      Versatility and Utility: The paradigm provides a controlled and reproducible environment for studying contextual fear learning, addressing challenges associated with freely moving paradigms.

      Potential for Broader Applications: By demonstrating hippocampal neuron remapping during fear learning and extinction, the study highlights the paradigm's utility for exploring memory dynamics, providing a strong foundation for future studies in behavioral neuroscience.

      Comprehensive Data Presentation: The inclusion of supplemental figures and behavioral analyses (e.g., licking behaviors and variability in extinction) strengthens the manuscript by addressing additional dimensions of the experimental outcomes.

      Weaknesses:

      Characterization of Freezing Behavior: The evidence supporting freezing behavior as the primary defensive response in VR is unclear. Supplementary videos suggest the observed behaviors may include avoidance-like actions (e.g., backing away or stopping locomotion) rather than true freezing. Additional physiological measurements, such as EMG or heart rate, are necessary to substantiate the claim that freezing is elicited in the paradigm.

      Analysis of Extinction: Extinction dynamics are only analyzed through between-group comparisons within each Recall day, without addressing within-group changes in behavior across days. Statistical comparisons within groups would provide a more robust demonstration of extinction processes.

      Low Sample Sizes: Paradigm 1 includes conditions with very low sample sizes (N=1-3), limiting the reliability of statistical comparisons regarding the effects of shock number and intensity. Increasing sample sizes or excluding data from mice that do not match the conditions used in Paradigms 2 and 3 would improve the rigor of the analysis.

      Potential Confound of Water Reward: The authors critique the use of reward in conjunction with fear conditioning in prior studies but do not fully address the potential confound introduced by using water reward during the training phase in their own paradigm.

    1. Reviewer #3 (Public review):

      Summary:

      This paper by Esmaeili and co-authors presents a connectome prediction study to predict episodic memory and relate prediction errors to other phonotypic variables.

      Strengths:

      (1) A primary and external validation dataset.

      (2) Novel use of prediction errors (i.e., brain-cognitive gap).

      (3) A wide range of data was investigated.

      Weaknesses:

      (1) Lack of comparisons to other methods for prediction.

      (2) Several different points are being investigated that don't allow any particular one to shine through.

      (3) Some choices of analysis are not well-motivated.

      (4) How do the n-back connectomes perform for prediction if the authors do not regress task activations from the n-back task?

      (5) I am a little concerned about overfitting with the convolutional neural net. For example, the drop-off in prediction performance in the external sample is stark. How does the deep learning approach used here compare to something simpler, like a connectome-based predictive model or ridge regression?

      (6) It may be nice to try the other models in the validation dataset. This would also provide a sense of the overfitting that may be going on with overfitting.

      (7) While predictive models increase the power over association studies, they still require large samples to prevent overfitting. Do the authors have a sense of the power their main and external validation sample sizes provide?

      (8) I am not sure that the Mann-Whitney is the correct test for comparing the distributions of prediction performances. The distributions are dependent on each other as they are each predicting the same outcomes. Using the typical degrees of freedom formula would overestimate the degrees of freedom.

      (9) The brain cognition gap is interesting. It is very similar conceptually to the brain age gap. When associating the brain age gap with other phenotypes, typically age is regressed from the brain age gap and the other phenotype. In other words, age is typically associated with a brain age gap as individuals at the tail ages often show the largest gaps. Is the brain cognition gap correlated with episodic memory and do the group differences hold if episodic memory is controlled for?

      (10) I have the same question for the dopamine results. Particularly, in the correlations that are divided by brain cognition gap sign. I could see these types of patterns arise due to a correlation with a third variable.

    1. Reviewer #3 (Public review):

      Summary:

      This manuscript by Guo and colleagues features the documentation and interpretation of three successions of continental to marginal marine deposits spanning the P/T transition and their respective ichnofaunas. Based on these new data inferences concerning end-Permian mass extinction and Triassic recovery in the tropical realm are discussed.

      Strengths:

      The manuscript is well-written and organized and includes a large amount of new lithological and ichnological data that illuminate ecosystem evolution in a time of large-scale transition. The lithological documentations, facies interpretations, and ichnotaxonomic assignments look okay (with a few exceptions).

      Weaknesses:

      Some interpretations in Table 1 could be questioned: For facies association FA2 the interpretation as „terrestrial facies with periodical flooding" should be put into the right column and, given the fossil content, other interpretations, such as "marine facies" or "lagoonal environment" with some plant debris and (terrestrial) animal remains washed in, could also be possible. For FA3 the statement "bioturbation is absent" is in conflict with the next statement "strata are moderately reworked". For FA5 the observation of a "monospecific ichnoassemblage" contradicts the listing of several ichnotaxa.

      Concerning the structure of the manuscript, certain hypotheses related to the end-Permian mass extinction and the process of the P/T extinction and recovery, namely the existence of a long-persisting "tropic dead zone" are introduced as a foregone conclusion to which the new data seemingly shall be fit as corroborating evidence. Some of the data - e.g. the presence of a supposedly Smithian-age ichnofauna are interpreted as a fast recovery shortening the duration of the "tropic dead zone" episode - but these interpretations could also be interpreted as contradicting the idea of a "dead zone" sensu stricto in favour of a "normal" post-extinction environment with low diversity and occurrence of typical disaster taxa. Due to their large error bars the early Triassic radiometric ages did not put much of a constraint on the age determination of the earliest post-extinction ichnofaunas discussed here.

      Considering the somewhat equivocal evidence and controversial ideas about the P/T transition, the introduction could be improved by describing how the idea of a "tropic dead zone" arose against the background of earlier ideas, alternative views, and conflicting data. In the discussion section, alternative interpretations of the extensive data presented here - e.g. proximal-distal shifts in lithofacies with respect to the sediment source, sea level changes, preservation bias, the local occurrence of hostile environments instead of a regional scale, etc. should be discussed, also to avoid the impression that the author's conclusion was driven by confirmation bias.

      Contrary to the authors' claim, Figures S7 and S8 suggest that burrow size does not vary much within the studied sections. Size decreases and increases in the Shichuanhe and Liulin sections do not contemporaneously, are usually within the error-bar range, and might be driven by ichnotaxa composition, i.e. the presence or absence of larger ichnotaxa, rather than by size changes in the same ichnotaxon (and producer group). Here the measurement data would be needed as well to check the basis of the authors' interpretations.

      Some arthropod tracks assigned here to Kouphichnium might not represent limulid traces but other (non-marine) arthropod taxa in accordance with their occurrence in terrestrial facies/non-marine units of the succession. More generally, the ichnotaxonomy of arthropod trackways is not yet well reserved - beyond Kouphichnium and Diplichnites various similar-looking types may occur that can have a variety of distinct insect, crustacean, millipede, etc. producers (including larval stages).

    1. Reviewer #3 (Public review):

      In this manuscript, the authors use HiC to study the 3D genome of CD14+ CD16+ monocytes from the blood of healthy and those from patients with Alcohol-associated Hepatitis.

      Overall, the authors perform a cursory analysis of the HiC data and conclude that there are a large number of changes in 3D genome architecture between healthy and AH patient monocytes. They highlight some specific examples that are linked to changes in gene expression. The analysis is of such a preliminary nature that I would usually expect to see the data from all figures in just one or two figures.

      In addition, I have a number of concerns regarding the experimental design and the depth of the analyses performed that I think must be addressed.

      (1) There is a myriad of literature that describes the existence of cell type-specific 3D genome architecture. In this manuscript, there is an assumption by the authors that the CD14+ CD16+ monocytes represent the same population from both healthy and diseased patients. Therefore, the authors conclude that the differences they see in the HiC data are due to disease-related changes in the equivalent cell types. However, I am concerned that the AH patient monocytes may have differentiated due to their environment so that they are in fact akin to a different cell type and the 3D genome changes they describe reflect this. This is supported by published articles for example: Dhanda et al., Intermediate Monocytes in Acute Alcoholic Hepatitis Are Functionally Activated and Induce IL-17 Expression in CD4+ T Cells. J Immunol (2019) 203 (12): 3190-3198, in which they show an increased frequency of CD14+ CD16+ intermediate monocytes in AH patients that are functionally distinct.

      I suggest that if the authors would like to study the specific effects of AH on 3D genome architecture then they should carefully FACsort the equivalent monocyte populations from the healthy and AH patients.

      (2) The analysis of the HiC data is quite preliminary. In the 3D genome field, it is usual to report the different scales of genome architecture, for example, compartments, topologically associated domains (TADs), and loops. I think that reporting this information and how it changes in AH patients in the appropriate cell types would be of great interest to the field.

    1. Reviewer #3 (Public review):

      Summary:

      The study highlights how the initiation, reversal, and cessation of movements are linked to changes in beta synchronization within the basal ganglia-cortex loops. It was observed that different movement phases, such as starting, stopping briefly, and stopping completely, affect beta oscillations in the motor system.

      It was found that unpredictable cues lead to stronger changes in STN-cortex beta coherence. Additionally, specific patterns of beta and gamma oscillations related to different movement actions and contexts were observed. Stopping movements was associated with a lack of the expected beta rebound during brief pauses within a movement sequence.

      Overall, the results underline the complex and context-dependent nature of motor control and emphasize the role of beta oscillations in managing movement according to changing external cues.

      Strengths:

      The paper is very well written, clear and appears methodologically sound.

      Although the use of continuous movement (turning) with reversals is more naturalistic than many previous button push paradigms.

      Weaknesses:

      The generalizability of the findings are somewhat curtailed by the fact that this was performed peri-operatively during the period of the microlesion effect. Given the availability of sensing enabled DBS devices now and HD-EEG, does MEG offer a significant enough gain in spatial localizability to offset the fact that it has to be done shortly postoperatively with externalized leads, with attendant stun effect? Specifically, for paradigms that are not asking very spatially localized questions as a primary hypothesis?

      Further investigation of the gamma signal seems warranted, even though it has a slightly lower proportional change in amplitude in beta. Given that the changes in gamma here are relatively wide band, this could represent a marker of neural firing that could be interestingly contrasted against the rhythm account presented.

      Comments on revisions: I congratulate the authors on their paper and their revisions and I have no further comments. I look forward to seeing the continuous analyses in the future. Good luck!

    1. Reviewer #3 (Public review):

      The authors tested whether: 1. The number of stimulus-stimulus pairings alters whether preconditioned fear depends on online integration during formation of the stimulus-outcome memory or during the probe test/mobilization phase, when the original stimulus, which was never paired with aversive events, elicits fear via chaining of stimulus-stimulus and stimulus-outcome memories. They found that sensory preconditioning was successful with either 8 or 32 stimulus-stimulus pairings. Perirhinal cortex NMDA receptor blockade during stimulus-outcome learning impaired preconditioning following 8 but not 32 pairings during preconditioning. Therefore, perirhinal cortex NMDA activity is required for online integration or mediated learning. Perirhinal-basolateral amygdala had nearly identical effects with the same interpretation: these areas communicate during stimulus-outcome learning, and this online communication is required for later expressing preconditioned fear. Disconnection prior to the probe test, when chaining might occur, had different effects: it impaired the expression of preconditioned fear in rats that received 32, but not 8, pairings during preconditioning. The study has several strengths and provides a thoughtful discussion of future experiments. The study is highly impactful and significant; the authors were successful in describing the behavioral and neurobiological mechanisms of mediated learning versus chaining in sensory preconditioning, which is often debated in the learning field. Therefore this study will have a significant impact on the behavioral neurobiology and learning fields.

      Strengths:

      Careful, rigorous experimental design and statistics

      The discussion leaves open questions that are very much worth exploring. For example - why did perirhinal-amygdala disconnection prior to the probe have no effect in the 8-pairing group, when bilateral perirhinal inactivation did (in Wong et al, 2019)? The authors propose that perirhinal cortex outputs bypass the amygdala during the probe test, which is an excellent hypothesis to test.

      The experiments are very explicitly hypothesis-driven, and the authors provide evidence of how and why mediated learning and chaining occur during sensory-sensory learning.

    1. Reviewer #3 (Public review):

      Summary:

      Ishii et al used molecular genetics, behavioral analyses, in vivo neural activity imaging, and neural activity manipulations in mice to study the functional role of a subset of medial preoptic area (MPOA) neurons in the regulation of female sexual drive. They first employed a self-paced mating assay during which a female could control the amount of interaction time with a male to assess female sexual drive after completion of mating. The authors observed that after mating completion (i.e., male ejaculation) females spend significantly less time interacting with males, indicating that their sexual drive is reduced. Next, the authors performed a brain-wide analysis of neurons activated following male ejaculation and identified the MPOA as a strong candidate region. One caveat is that the activity labeling was not exclusive to neurons activated following male ejaculation but included all neurons activated before, during, and after the mating encounter. However, in this revised version of the manuscript, the authors have included a key control group that labels all neurons activated up to but not including male ejaculation. Comparison of the number of activated neurons in these two groups revealed a significant additional set of neurons in the female MPOA following ejaculation. Importantly, the authors also provided in vivo calcium imaging data showing that a subset of MPOA neurons responds significantly and specifically to male ejaculation and not other behaviors during the social encounter. The authors performed these studies in both excitatory and inhibitory populations of the MPOA. Their analysis identified a subpopulation of inhibitory neurons that exhibit sustained increased activity for 90 sec following male ejaculation. Finally, the authors used chemogenetics to activate MPOA neurons during home cage mating, condition place preference, pup retrieval, and the self-paced mating assay. They found that activation of female MPOA neurons that were previously activated following male ejaculation significantly reduces mating behaviors and time spent interacting with a male during the self-paced mating assay. Whereas, activation of female MPOA neurons that were previously activated during consummatory behaviors but not male ejaculation does not alter mating behaviors and time spent interacting with a male. Therefore, MPOA neurons activated following ejaculation are sufficient to suppress female sexual motivation.

      The authors' experimental execution is rigorous and well performed. Their data identify inhibitory neurons in the female MPOA as a neural locus that is activated following male ejaculation and whose prolonged activity plays a key role in the regulation of female sexual motivation. The addition of some key control groups to this revised version of the manuscript greatly strengthens the interpretation of the authors' findings.

      Strengths:

      (1) The use of the self-paced mating assay in combination with neural imaging and manipulation to assess female sexual drive is innovative. The authors correctly assert that relatively little is known about how male ejaculation affects sexual motivation in females as compared to males. Therefore, the data collected from these studies is important and valuable.

      (2) The authors provide convincing histological data and analyses to verify and validate their brain-wide activity labeling, neural imaging, and chemogenetic studies.

      (3) The single cell in vivo calcium imaging data are well performed and analyzed. They provide key insights into the activity profiles of both excitatory and inhibitory neurons in the female MPOA during mating encounters. The authors identification of an inhibitory subpopulation of female MPOA neurons that is selectively activated following completion of mating is fundamental for future experiments which could potentially find a molecular marker for this population and specifically manipulate these neurons to understand their role in female sexual motivation in greater detail.

      (4) The authors provide convincing evidence that activation of female MPOA neurons activated following male ejaculation is sufficient to suppress female sexual motivation. Importantly, the authors addition of the consummatory-hM3Dq group demonstrates that activation of female MPOA neurons activated during mating behaviors prior to male ejaculation is not sufficient to suppress female sexual motivation.

      Weaknesses:

      In this revised version of the manuscript, the authors have added important controls as well as additional clarifying text that adequately address the weaknesses that were present in the original version of the manuscript.

    1. Reviewer #3 (Public review):

      This manuscript presents a number of interesting findings that have the potential to increase our understanding of the mechanism underlying homeostatic synaptic plasticity (HSP). The data broadly support that Rab3A plays a role in HSP, although the site and mechanism of action remain uncertain.

      The authors clearly demonstrate that Rab3A plays a role in HSP at excitatory synapses, with substantially less plasticity occurring in the Rab3A KO neurons. There is also no apparent HSP in the Earlybird Rab3A mutation, although baseline synaptic strength is already elevated. In this context, it is unclear if the plasticity is absent, already induced by this mutation, or just occluded by a ceiling effect due to the synapses already being strengthened. Occlusion may also occur in the mixed cultures when Rab3A is missing from neurons but not astrocytes. The authors do appropriately discuss these options. The authors have solid data showing that Rab3A is unlikely to be active in astrocytes, Finally, they attempt to study the linkage between changes in synaptic strength and AMPA receptor trafficking during HSP, and conclude that trafficking may not be solely responsible for the changes in synaptic strength during HSP.

      Strengths:

      This work adds another player into the mechanisms underlying an important form of synaptic plasticity. The plasticity is likely only reduced, suggesting Rab3A is only partially required and perhaps multiple mechanisms contribute. The authors speculate about some possible novel mechanisms, including whether Rab3A is active pre-synaptically to regulate quantal amplitude.

      As Rab3A is primarily known as a pre-synaptic molecule, this possibility is intriguing. However, it is based on the partial dissociation of AMPAR trafficking and synaptic response and lacks strong support. On average, they saw a similar magnitude of change in mEPSC amplitude and GluA2 cluster area and integral, but the GluA2 data was not significant due to higher variability. It is difficult to determine if this is due to biology or methodology - the imaging method involves assessing puncta pairs (GluA2/VGlut1) clearly associated with a MAP2 labeled dendrite. This is a small subset of synapses, with usually less than 20 synapses per neuron analyzed, which would be expected to be more variable than mEPSC recordings averaged across several hundred events. However, when they reduce the mEPSC number of events to similar numbers as the imaging, the mESPC amplitudes are still less variable than the imaging data. The reason for this remains unclear. The pool of sampled synapses is still different between the methods and recent data has shown that synapses have variable responses during HSP. Further, there could be variability in the subunit composition of newly inserted AMPARs, and only assessing GluA2 could mask this (see below). It is intriguing that pre-synaptic changes might contribute to HSP, especially given the likely localization of Rab3A. But it remains difficult to distinguish if the apparent difference in imaging and electrophysiology is a methodological issue rather than a biological one. Stronger data, especially positive data on changes in release, will be necessary to conclude that pre-synaptic factors are required for HSP, beyond the established changes in post-synaptic receptor trafficking.

      Other questions arise from the NASPM experiments, used to justify looking at GluA2 (and not GluA1) in the immunostaining. First, there is a strong frequency effect that is unclear in origin. One would expect NASPM to merely block some fraction of the post-synaptic current, and not affect pre-synaptic release or block whole synapses. But the change in frequency seems to argue (as the authors do) that some synapses only have CP-AMPARs, while the rest of the synapses have few or none. Another possibility is that there are pre-synaptic NASPM-sensitive receptors that influence release probability. Further, the amplitude data show a strong trend towards smaller amplitude following NASPM treatment (Fig 3B). The p value for both control and TTX neurons was 0.08 - it is very difficult to argue that there is no effect. The decrease on average is larger in the TTX neurons, and some cells show a strong effect. It is possible there is some heterogeneity between neurons on whether GluA1/A2 heteromers or GluA1 homomers are added during HSP. This would impact the conclusions about the GluA2 imaging as compared to the mEPSC amplitude data.

      To understand the role of Rab3A in HSP will require addressing two main issues:

      (1) Is Rab3A acting pre-synaptically, post-synaptically or both? The authors provide good evidence that Rab3A is acting within neurons and not astrocytes. But where it is acting (pre or post) would aid substantially in understanding its role. The general view in the field has been that HSP is regulated post-synaptically via regulation of AMPAR trafficking, and considerable evidence supports this view. More concrete support for the authors' suggestion of a pre-synaptic site of control would be helpful.

      (2) Rab3A is also found at inhibitory synapses. It would be very informative to know if HSP at inhibitory synapses is similarly affected. This is particularly relevant as at inhibitory synapses, one expects a removal of GABARs or a decrease in GABA release (ie the opposite of whatever is happening at excitatory synapses). If both processes are regulated by Rab3A, this might suggest a role for this protein more upstream in the signaling; an effect only at excitatory synapses would argue for a more specific role just at those synapses.