Reviewer #1 (Public Review):

Summary:<br /> In this manuscript, Abe and colleagues employ in vivo 2-photon calcium imaging of dopaminergic axons in the mPFC. The study reveals that these axons primarily respond to unconditioned aversive stimuli (US) and enhance their responses to initially-neutral stimuli after classical association learning. The manuscript is well-structured and presents results clearly. The utilization of a refined prism-based imaging technique, though not entirely novel, is well-implemented. The study's significance lies in its contribution to the existing literature by offering single-axon resolution functional insights, supplementing prior bulk measurements of calcium or dopamine release. Given the current focus on neuromodulator neuron heterogeneity, the work aligns well with current research trends and will greatly interest researchers in the field.

However, I would like to highlight that the authors could further enhance their manuscript by addressing study limitations more comprehensively and by providing essential details to ensure the reproducibility of their research. In light of this, I have a number of comments and suggestions that, if incorporated, would significantly contribute to the manuscript's value to the field.

Strengths:<br /> -Descriptive.<br /> -Utilization of a well-optimized prism-based imaging method.<br /> -Provides valuable single-axon resolution functional observations, filling a gap in existing literature.<br /> -Timely contribution to the study of neuromodulator neuron heterogeneity.

Weaknesses:<br /> 1. It's important to fully discuss the fact that the measurements were carried out only on superficial layers (30-100um), while major dopamine projections target deep layers of the mPFC as discussed in the cited literature (Vander Weele et al., 2018) and as illustrated in FigS1B,C. This limitation should be explicitly acknowledged and discussed in the manuscript, especially given the potential functional heterogeneity among dopamine neurons in different layers. This potential across-layer heterogeneity could also be the cause of discrepancy among past recording studies with different measurement modalities. Also, mentioning technical limitations would be informative. For example: how deep the authors can perform 2p-imaging through the prism? was the "30-100um" maximum depth the authors could get?

2. In the introduction, it seems that the authors intended to refer to Poulin et al. 2018 regarding molecular/anatomical heterogeneity of dopamine neurons, but they inadvertently cited Poulin et al. 2016 (a general review on scRNAseq). Additionally, the statement that "dopamine neurons that project to the PFC show unique genetic profiles (line 85)" requires clarification, as Poulin et al. 2018 did not specifically establish this point. Instead, they found at least the Vglut2/Cck+ population projects into mPFC, and they did not reject the possibility of other subclasses projecting to mPFC. Rather, they observed denser innervation with DAT-cre, suggesting that non-Vglut2/Cck populations would also project to mPFC. Discuss the potential molecular heterogeneity among mPFC dopamine axons in light of the sampling limitation mentioned earlier.

3. I find the data presented in Figure 2 to be odd. Firstly, the latency of shock responses in the representative axons (right panels of G, H) is consistently very long - nearly 500ms. It raises a query whether this is a biological phenomenon or if it stems from a potential technical artifact, possibly arising from an issue in synchronization between the 2-photon imaging and stimulus presentation. My reservations are compounded by the notable absence of comprehensive information concerning the synchronization of the experimental system in the method section. Secondly, there appear to be irregularities in Panel J. While the authors indicate that "Significant axons were classified as either reward-preferring (cyan) or aversive-preferring (magenta), based on whether the axons are above or below the unity line of the reward/aversive scatter plot (Line 566)," a cyan dot slightly but clearly deviates above the unity line (around coordinates (x, y) = (20, 21)). This needs clarification. Lastly, when categorizing axons for analysis of conditioning data in Fig3 (not Fig2), the authors stated "The color-coded classification (cyan/magenta) was based on k-means clustering, using the responses before classical conditioning (Figure 2J)". I do not understand why the authors used different classification methods for two almost identical datasets.

4. In connection with Point 3, conducting separate statistical analyses for aversive and rewarding stimuli would offer a fairer approach. This could potentially reveal a subset of axons that display responses to both aversive and appetitive stimuli, aligning more accurately with the true underlying dynamics. Moreover, the characterization of Figure 2J as a bimodal distribution while disregarding the presence of axons responsive to both aversive and appetitive cues seems somewhat arbitrary and circular logic. A more inclusive consideration of this dual-responsive population could contribute to a more comprehensive interpretation.

5. The contrast in initialization to novel cues between aversive and appetitive axons mirrors findings in other areas, such as the tail-of-striatum (TS) and ventral striatum (VS) projecting dopamine neurons (Menegas et al., 2017, not 2018). You might consider citing this very relevant study and discussing potential collateral projections between mPFC and TS or VS.

6. The use of correlation values (here >0.65) to group ROIs into axons is common but should be justified based on axon density in the FOV and imaging quality. It's important to present the distribution of correlation values and demonstrate the consistency of results with varying cut-off values. Also, provide insights into the reliability of aversive/appetitive classifications for individual ROIs with high correlations. Importantly, if you do the statistical testing and aversive/appetitive classifications for individual ROIs with above-threshold high correlation (to be grouped into the same axon), do they always fall into the same category? How many false positives/false negatives are observed?
<br /> "Our results remained similar for different correlation threshold values (Line 556)" (data not shown) is obsolete.

Joint Public Review:

Neuropeptide signaling is an important component of nervous systems, where neuropeptides typically act via G-protein coupled receptors (GPCRs) to regulate many physiological and behavioral processes. Neuropeptides and their cognate GPCRs have been extensively characterized in bilaterian animals, revealing that a core set of neuropeptide signaling systems originated in common ancestors of extant Bilateria. Neuropeptides have also been identified in cnidarians, which are a sister group to the Bilateria. However, the GPCRs that mediate the effects of neuropeptides in cnidarians have not been identified.

In this paper the authors perform a phylogenetic analysis of GPCRs in metazoans and report that the orthologs of bilaterian neuropeptide receptors are not found in cnidarians. This indicates that neuropeptide signaling systems have largely evolved independently in cnidarians and bilaterians. To accomplish this, they generated a library of putative and known neuropeptides computationally identified in the genome of the cnidarian sea anemone Nematostella vectensis. These peptides were systematically screened for their ability to activate any of the 161 putative Nematostella GPCRs.

This work identified 31 validated GPCRs. These, together with GPCRs that cluster with them, were then used to demonstrate the independent expansion of GPCRs in cnidarian and bilaterian lineages. The authors then mapped validated receptors and ligands to the Nematostella single cell data to provide an overview of the cell types expressing these signaling genes. In addition, the authors have begun to analyze neuropeptide signaling networks in N. vectensis by showing potential signaling connections between cell types expressing neuropeptides and cell types expressing cognate receptors.

This work is the most extensive pharmacological characterization of neuropeptide GPCRs in a cnidarian to date and thus represents an important accomplishment, and is one that will improve our understanding of how peptidergic signaling evolved in animals and its impact on evolution of nervous systems."

The reviewers did not detect any weaknesses in the work but ask that the authors comment on the following points:<br /> 1- It was not clear why the phylogenetic analysis included non-validated GPCRs that clustered with the validated peptidergic receptors. Would restricting the phylogenetic analyses only to confirmed peptidergic GPCRs alter the topology of the tree and subsequent conclusions of independent expansion?<br /> 2- Clearly, other neuropeptide signaling systems in cnidarians remain to be discovered but this paper represents a huge step forward.<br /> 3- There are limitations in what can be interpreted from single cell transcriptomic data but the data nevertheless provide the foundations for future studies involving i). detailed anatomical analysis of neuropeptide and neuropeptide receptor expression in N. vectensis using mRNA in situ hybridization and/or immunohistochemical methods and ii). functional analysis of the physiological/behavioral roles of neuropeptide signaling systems in N. vectensis

Reviewer #1 (Public Review):

Summary:

This research study utilizes a realistic motoneuron model to explore the potential to trace back the appropriate levels of excitation, inhibition, and neuromodulation in the firing patterns of motoneurons observed in in-vitro and in-vivo experiments in mammals. The research employs high-performance computing power to achieve its objectives. The work introduces a new framework that enhances understanding of the neural inputs to motoneuron pools, thereby opening up new avenues for hypothesis testing research.

Strengths:<br /> The significance of the study holds relevance for all neuroscientists. Motoneurons are a unique class of neurons with known distribution of outputs for a wide range of voluntary and involuntary motor commands, and their physiological function is precisely understood. More importantly, they can be recorded in-vivo using minimally invasive methods, and they are directly impacted by many neurodegenerative diseases at the spinal cord level.<br /> The computational framework developed in this research offers the potential to reverse engineer the synaptic input distribution when assessing motor unit activity in humans, which holds particular importance.<br /> Overall, the strength of the findings focuses on providing a novel framework for studying and understanding the inputs that govern motoneuron behavior, with broad applications in neuroscience and potential implications for understanding neurodegenerative diseases. It highlights the significance of the study for various research domains, making it valuable to the scientific community.

Weaknesses: The exact levels of inhibition, excitation, and neuromodulatory inputs to neural networks are unknown. Therefore the work is based on fine-tuned measures that are indirectly based on experimental results. However, obtaining such physiological information is challenging and currently impossible. From a computational perspective it is a challenge that in theory can be solved. Thus, although we have no ground-truth evidence, this framework can provide compelling evidence for all hypothesis testing research and potentially solve this physiological problem with the use of computers.

Reviewer #1 (Public Review):

Summary:<br /> I read the paper by Parrotta et al with great interest. The authors are asking an interesting and important question regarding pain perception, which is derived from predictive processing accounts of brain function. They ask: If the brain indeed integrates information coming from within the body (interoceptive information) to comprise predictions about the expected incoming input and how to respond to it, could we provide false interoceptive information to modulate its predictions, and subsequently alter the perception of such input? To test this question, they use pain as the input and the sounds of heartbeats (falsified or accurate) as the interoceptive signal.

Strengths:<br /> I found the question well-established, interesting, and important, with important implications and contributions for several fields, including neuroscience of prediction-perception, pain research, placebo research, and health psychology. The paper is well-written, the methods are adequate, and the findings largely support the hypothesis of the authors. The authors carried out a control experiment to rule out an alternative explanation of their finding, which was important.

Weaknesses:<br /> I will list here one theoretical weakness or concern I had, and several methodological weaknesses.

The theoretical concern regards what I see as a misalignment between a hypothesis and a result, which could influence our understanding of the manipulation of heartbeats, and its meaning: The authors indicate from prior literature and find in their own findings, that when preparing for an aversive incoming stimulus, heartbeats *decrease*. However, in their findings, manipulating the heartbeats that participants hear to be slower than their own prior to receiving a painful stimulus had *no effect* on participants' actual heartbeats, nor on their pain perceptions. What authors did find is that when listening to heartbeats that are *increased* in frequency - that was when their own heartbeats decreased (meaning they expected an aversive stimulus) and their pain perceptions increased.

This is quite complex - but here is my concern: If the assumption is that the brain is collecting evidence from both outside and inside the body to prepare for an upcoming stimulus, and we know that *slowing down* of heartbeats predicts an aversive stimulus, why is it that participants responded in a change in pain perception and physiological response when listened to *increased heartbeats* and not decreased? My interpretation is that the manipulation did not fool the interoceptive signals that the brain collects, but rather the more conscious experience of participants, which may then have been translated to fear/preparation for the incoming stimulus. As the authors indicate in the discussion (lines 704-705), participants do not *know* that decreased heartbeats indicate upcoming aversive stimulus, and I would even argue the opposite - the common knowledge or intuitive response is to increase alertness when we hear increased heartbeats, like in horror films or similar scenarios. Therefore, the unfortunate conclusion is that what the authors assume is a manipulation of interoception - to me seems like a manipulation of participants' alertness or conscious experience of possible danger. I hope the (important) distinction between the two is clear enough because I find this issue of utmost importance for the point the paper is trying to make. If to summarize in one sentence - if it is decreased heartbeats that lead the brain to predict an approaching aversive input, and we assume the manipulation is altering the brain's interoceptive data collection, why isn't it responding to the decreased signal? --> My conclusion is, that this is not in fact a manipulation of interoception, unfortunately.

I will add that the control experiment - with an exteroceptive signal (knocking of wood) manipulated in a similar manner - could be seen as evidence of the fact that heartbeats are regarded as an interoceptive signal, and it is an important control experiment, however, to me it seems that what it is showing is the importance of human-relevant signals to pain prediction/perception, and not directly proves that it is considered interoceptive. For example, it could be experienced as a social cue of human anxiety/fear etc, and induce alertness.

Several additional, more methodological weaknesses include the very small number of trials per condition - the methods mention 18 test trials per participant for the 3 conditions, with varying pain intensities, which are later averaged (and whether this is appropriate is a different issue). This means 6 trials per condition, and only 2 trials per condition and pain intensity. I thought that this number could be increased, though it is not a huge concern of the paper. It is, however, needed to show some statistics about the distribution of responses, given the very small trial number (see recommendations for authors). The sample size is also rather small, on the verge of "just right" to meet the required sample size according to the authors' calculations. Finally, and just as important, the data exists to analyze participants' physiological responses (ECG) after receiving the painful stimulus - this could support the authors' claims about the change in both subjective and objective responses to pain. It could also strengthen the physiological evidence, which is rather weak in terms of its effect. Nevertheless, this is missing from the paper.

I have several additional recommendations regarding data analysis (using an ANOVA rather than multiple t-tests, using raw normalized data rather than change scores, questioning the averaging across 3 pain intensities) - which I will detail in the "recommendations for authors" section.

Conclusion:<br /> To conclude, the authors have shown in their findings that predictions about an upcoming aversive (pain) stimulus - and its subsequent subjective perception - can be altered not only by external expectations, or manipulating the pain cue, as was done in studies so far, but also by manipulating a cue that has fundamental importance to human physiological status, namely heartbeats. Whether this is a manipulation of actual interoception as sensed by the brain is - in my view - left to be proven.<br /> Still, the paper has important implications in several fields of science ranging from neuroscience prediction-perception research, to pain and placebo research, and may have implications for clinical disorders, as the authors propose. Furthermore, it may lead - either the authors or someone else - to further test this interesting question of manipulation of interoception in a different or more controlled manner.

I salute the authors for coming up with this interesting question and encourage them to continue and explore ways to study it and related follow-up questions.

Reviewer #1 (Public Review):

Summary:<br /> The question at hand is whether astrocytes contribute to the mechanism of long-term synaptic potentiation (LTP) at synaptic contacts between excitatory glutamatergic neurons and inhibitory neurons (E-I synapses). This is a legitimate query considering the immense body of work that has now established synaptic plasticity (LTP, LTD and spike-timing dependent plasticity) as an astrocyte-dependent process at excitatory synapses and, by contrast, the lack of knowledge on whether and how astrocytes control IN activity. Taking direct inspiration from that same body of work, authors recapitulate a number of experiments and approaches from prior seminal studies and provide evidence that E-I synapses in the stratum radiatum of the hippocampus display NMDAR-dependent plasticity, which can be suppressed by pharmacologically hindering astrocytes physiology, preventing astrocyte Ca2+ transients or blocking endocannabinoid CB1 receptors. Under any of these conditions, LTP can still be rescued by exogenously applying D-serine, a naturally occurring co-agonist of NMDARs primarily released by astrocytes. Coincidently, authors show that the conditions used to elicit LTP also cause a transient increase in NMDAR co-agonist site occupancy. Lastly, based on some evidence that gamma-CaMKII is predominantly expressed in INs rather than excitatory neurons, authors conducted AAV-mediated IN-specific gamma-CaMKII shRNA experiments and found that this is sufficient to suppress LTP at E-I synapses. They found that this approach also impairs contextual fear learning in behaving mice. Authors conclude that astrocytes gate LTP at E-I synapses via a mechanism wherein neuronal depolarization during LTP induction elicits endocannabinoid release which drives CB1-dependent astrocyte Ca2+ activity, causing the release of the NMDAR co-agonist D-serine (required for NMDAR activation).

Strengths:<br /> This is an important question and the experimental work seems to have been conducted at high standards. The electrophysiology traces are impeccable, the experiments are well powered, including the behavioral testing, and multiple controls and validations are provided throughout. The figures are clear and easy to understand. Overall, the conclusions from the study are consistent, or partially consistent, by the findings.

Main Weaknesses:<br /> 1- A major point of concern is the lack of proper acknowledgment of the seminal studies that were mimicked in this manuscript, notably Henneberger et al, Nature 2010, Adamsky et al, Cell 2018; and Robin et al., Neuron 2017. The entire study design is a replica of these landmark studies: it isn't built upon or inspired from them, it exactly repeats the experiments and methods performed in them, coming dangerously close to being simply a hidden attempt to plagiarize published work. The resemblance goes as far as using an identical figure display (see Fig4.D vs Fig 2D of Ref#4). The issue is that authors frame the problem, scientist logic, reasoning, technical tricks, approaches, and interpretations as their own whereas, in reality, they were taken verbatim out of previous work and applied to a (shockingly) similar problem. The probity of the present study is thus in question. Authors need to clearly acknowledge, in all relevant instances, that the work presented here recapitulates the approach, reasoning and methodology used in past seminal studies that tackled the mechanisms of astrocyte regulation of LTP.

2-Relatedly, in past work, field recordings were used to monitor LTP in hippocampal slices (refs 4, 26 and others). This method captures indiscriminately all excitatory synapses where glutamate is released to cause AMPAR-dependent (and NMDAR) transmembrane flux of cations in the postsynaptic element, including E-I synapses and not just E-E synapse like the authors claim. Therefore, a strong argument can be made that there is no actual ground to differentiate the present results from past ones.

3-There is a general lack of excitement about this study. One reason is that it replicates almost identically past work, as mentioned above. Another is that the scientific question and importance of the findings are not framed appropriately. The work is presented as an astrocyte-focused investigation, but it has very limited value to the astrocyte field. The findings are, in all accounts, identical to those unveiled by previous work especially because E-I synapses are, in fact, excitatory synapses. Where this study does bring value, however, is to the field of interneurons, but it would need to be reframed to shift the emphasis from astrocytes to E-I connections. Authors would need to elevate the text by framing their work around relevant considerations, such as IN diversity, mechanisms of LTP in IN subtypes, role of E-I connections in hippocampal circuit function, information processing, behavior, spatial learning, navigation, or grid cells activity etc...

4-A clear weakness of the study is that it fails to consider the molecular and functional diversity of interneurons in the stratum radiatum and provides no insights or considerations related to it. Authors provide no information on what type of IN were patched, or the location of their cell body in the s.r., effectively treating all patched IN as a homogeneous ensemble of cells - which they are not. Relatedly, the study is extremely evasive on the importance of the results in the context of inhibitory interneurons. This renders the significance of the insights highly uncertain and dampens both the impact of the study and the excitement it generates. Hippocampal interneurons are very diverse in molecular identity, sub-anatomical location, morphology, projections, connectivity and functional importance. Some experts go as far as recognizing 29 subtypes in the CA1, including 9 in the stratum radiatum alone (based on the location of their soma). However, this is neither addressed nor acknowledged by the authors, with the exception of a statement (line 659) where they claim to have "focused on a subpopulation of interneurons in the stratum radiatum" without providing any precision or evidence to corroborate this assertion. This diversity, alone, could explain why not all cells showed LTP, or why the mechanisms authors describe in the radiatum do not seem to be at play in the oriens. Hence, carefully considering the diversity of INs in the present work is necessary. It would refine and augment the conclusions of the paper. Instead of a sub-region specificity, the study might fuel the notion of an IN subtype specificity of LTP mechanisms, which is more useful to the field.

5-Authors take several shortcuts. Some of the conclusions are a leap from the experiments and are only acceptable due to the close analogy with very similar investigations conducted in the past that provided identical results. For instance, the present study provides no evidence of any sort that D-serine is involved - rather, it provides evidence that the pathway at hand contributes to increasing the occupancy of the co-agonist binding site of NMDARs. Considering the absence of work demonstrating that D-serine is the endogenous co-agonist of NMDARs at E-I synapses, most of the authors claims on D-serine are unfounded. This would necessitate using tools such as the canonical D-serine scavengers DAAS or DsDA, serine racemase KO mice etc. Similarly, authors provide no compelling evidence that endocannabinoid CB1 receptors involved in this pathway are located on astrocytes

6-An important caveat in this study is the protocol employed to induce LTP, which includes steps of sustained depolarization of the patched IN to -10mV. Neuronal depolarization is known to induce endocannabinoids production. In several instances, this was shown to 'activate' astrocytes and elicit the release of astrocyte-derived transmitters at nearby synapses. This implies that the endocannabinoid-dependent pathway described in the study is, most likely, artificially engaged by the protocol itself. Hence, the present work only provides evidence that an astrocyte-dependent, CB1-D-serine-pathway can be artificially called upon with this specific LTP protocol, but does not convincingly demonstrate that it is naturally occurring or necessary for plasticity at E-I synapses. Authors would need to thoroughly address this caveat by replicating some of their key findings (AM251, calcium-clamp, D-serine and CaMKII shRNA) using a protocol that does not entail the artificial depolarization of the patched interneuron.

7-Reading and understanding are hindered by a rather vast array of issues with the text itself. It needs thorough editing for typos, misnomers, meaning-altering errors in syntax, and a number of issues with English.

Reviewer #1 (Public Review):

This paper presents a set of experiments designed to test whether gravity in people's intuitive physics engine is implemented as a simple deterministic representation of gravity or as a Gaussian distribution. The work shows experimentally that the probabilistic representation of gravity does a better job at capturing both human judgments, including biases in stability inferences. The work further shows that Gaussian representations of gravity can evolve in a simple agent-environment reinforcement learning problem setup.

Strengths:<br /> The paper approaches the problem from three different angles in an impressive way. The first is through a direct comparison of human judgments against model predictions. The second is through an analysis of whether the model correctly predicts cognitive illusions. The third is through a computational exploration of how these representations emerge in a reinforcement-learning setup. The idea of approaching the same problem from multiple independent angles, and seeking confirming evidence is laudable.

Weaknesses:<br /> There are two differences between the "natural gravity" account and the "mental gravity" account. The first difference lies in the implementation of gravity. The second, however, is simply that the mental gravity model is integrating more uncertainty into the simulator. In my understanding, adding small amounts of noise to computational models will often increase their fit to human judgments (with softmaxing perhaps being the most common example of this). While counter-intuitive, this is because 'noiseless' models have perfect representations of the stimuli, which is an unrealistic assumption. In the case of intuitive physics, people might have noisy perceptual representations of exactly how flat the table is, the exact location of each block, what small disturbances might be happening in the environment, and so on. The absence of these sources of uncertainty in deterministic models can make them perform in a non-human-like manner.

While all the data presented in the paper is consistent with the possibility that people have a stochastic representation of gravity. It is possible that people have uncertainty over what unobservable forces a block tower might be under (e.g., wind, bumps to the table, etc). Therefore, even if you have a firm belief that gravity goes down, you may want to add noise in your simulations to account for the fact that, in the real world, gravity is almost never the only force acting on an object that has started to move. While the paper acknowledges that such an account would be mathematically equivalent, it does not acknowledge that this raises the question of whether people actually have stochastic representations of gravity.

This alternative account could be particularly important because I believe it might be a more accurate representation of what people believe. I may be wrong, but I believe that it is common to emphasize the probabilistic nature of the models and the importance of implementing forces as distributions (e.g., the concept of 'noisy newtons').

Reviewer #1 (Public Review):

Summary:<br /> The authors made significant updates to Hippacampome.org including 50 new cell types.

Strengths:<br /> The authors have been thorough in basing their views on peer-reviewed literature. They have made the data highly accessible and the user has the ability to control what is included.

Weaknesses:<br /> There are many inconsistencies in the literature regarding cell types and how these are incorporated into hippocampome.org is not clear.

Properties are often a result of modeling and not biological data, and caveats to this approach, and other assumptions are unclear.

Several interneuron subtypes in the dentate gyrus do not appear to be listed, such as neurogliaform cells.

The nomenclature HIPROM should be distinguished or made synonymous with HIPP. Same for MOCAP and MOPP/HICAP.

Dorsal ventral and sex differences are not mentioned.

Joint Public Review:

Summary: This study follows up on previous work showing a female-specific enhancer region of PAX1 is associated with adolescent idiopathic scoliosis (AIS). This new analysis combines human GWAS analysis from multiple countries to identify a new AIS-associated coding variant in the COL11A1 gene. Two nonsynonymous variants were found to be significantly associated with AIS: MMP14 p.Asp273Asn and COL11A1 p.Pro1335Leu, the latter of which had the more robust association and remained significant when females were tested independent of males. Using a Pax1 knockout mouse they go on to find that PAX1 and Collagen XI protein are expressed in the intervertebral discs (IVDs) and robustly in the growth plate, showing that COL11A1 expression is reduced in Pax1 mutant growth plate. Moreover, other AIS-associated genes, Gpr126 and Sox6, were also reduced in Pax1 mutant mice, suggesting a common pathway is involved in AIS. The proposed implication of a Pax1-Col11a1-Mmp3 signaling axis modulated by estrogen signaling suggests a potential mechanism by which young women have more severe scoliosis than young men, as is observed in humans.

Strengths: This work integrates a large cohort of human genetic data from AIS patients and controls from diverse ethnic backgrounds, across the globe. This work attempts to functionally test their findings in vivo and by use of cell culture. The authors propose an interesting model which warrants in depth investigation.

Weaknesses: There are concerns regarding the candidacy of COL11A1 p.Pro1335Leu that need to be addressed and clarified. Many of the main functional work was done in cell culture and not in vivo. Moreover, the evidence linking COL11A1 p.Pro1153Leu to AIS is indirect, making unclear whether impaired COL11A1 function can cause scoliosis in the mouse model, thus diminishing the strength of the conclusions regarding the proposed pathogenicity of COL11A1 p.Pro1335Leu.

Reviewer #1 (Public Review):

Summary:<br /> In this manuscript, Seba et al., investigate the mechanism of chromosome organization by the MukBEF complex in E. coli. They use a combination of Hi-C and ChIP analysis to understand the steps of MukBEF regulation: its unloading from DNA (how MukBEF activity is prevented in the terminus regions of the chromosome by MatP), and its loading onto DNA (how DNA replication influences MukBEF association with the chromosome). Seba et al., induce chromosomal rearrangements to flip the sections of the ter region, thus perturbing matS site numbers and position. They find that MukBEF activity is prevented around matS sites, and that higher matS density has greater effect on MukBEF. Separately, using replication mutants and inducible MukBEF expression, they find that MukBEF can associate with the chromosome even in the absence of replication (as seen by the emergence of long-range contacts). However, ChIP data suggests that MukBEF binding to DNA is enriched on newly replicated DNA.

Strengths:<br /> Altogether, this work provides a valuable and comprehensive view of MukBEF-mediated chromosome organization, with insights on the mechanism of the exclusion of MukBEF from the terminus region of the chromosome. The use of the programmed genetic rearrangements is powerful, and allows the authors to provide clear and convincing evidence for MukBEF exclusion from ter by matS sites. It is particularly striking to see that MukBEF can promote long-range contacts even in chromosomal regions between two matS, but the complex is excluded from the matS 'zones'. Experiments using cells blocked for replication show that MukBEF can influence chromosome organization in the absence of replication as well. While previous studies have reported some evidence in support of both of the above conclusions, the experiments described here offer clear and direct demonstration of the same.

Limitations:<br /> A few control experiments are required to strengthen conclusions. Additionally, the discussion section is lacking many references and key papers have not been cited (paragraph 1 of discussion for example has no references). The possibility that SMC-ScpAB and MukBEF can act independent of replication has been suggested previously, but are not cited or discussed. Similarly, there is some evidence for SMC-ScpAB association with newly replicated DNA (PMID 21923769).

Reviewer #1 (Public Review):

Summary:<br /> The authors set out to determine how chemical variation on kinase inhibitors determines the selection of Erk2 conformations and how inhibitor binding affects ERk2 structure and dynamics.

Strengths:<br /> The study is beautifully presented both verbally and visually. The NMR experiments and the HDX experiments complement each other for the study of Erk2 solution dynamics. X-ray crystallography of Erk2 complexes with inhibitors shows small but distinct structural changes that support the proposed model for the impact of inhibitor binding.

Weaknesses:<br /> A discussion of compound residence time for the different compounds and kinase constructs and how it could affect the very slow HDX rates might be helpful. For example, could any of the observed effects in Figure 4 be due to slow compound dissociation rather than slowed down kinase dynamics? What would be the implications?

Reviewer #1 (Public Review):

The authors investigate the role of chirping in a species of weakly electric fish. They subject the fish to various scenarios and correlate the production of chirps with many different factors. They find major correlations between the background beat signals (continuously present during any social interactions) or some aspects of social and environmental conditions with the propensity to produce different types of chirps. By analyzing more specifically different aspects of these correlations they conclude that chirping patterns are related to navigation purposes and the need to localize the source of the beat signal (i.e. the location of the conspecific).

The study provides a wealth of interesting observation of behavior and much of this data constitute a useful dataset to document the patterns of social interactions in these fish. Some data, in particular the high propensity to chirp in cluttered environments, raises interesting questions. Their main hypothesis is a useful addition to the debate on the function of these chirps and is worth being considered and explored further. However, the data they provide does not support strong conclusion statements arguing that these chirps are used for localization purposes and is even less convincing at rejecting previously established hypotheses on the communication purpose of the chirps. I would suggest thoroughly revising the manuscript to provide a neutral description of the results and leaving any speculations and interpretations for the discussion where the authors should be careful to separate strongly supported hypotheses from more preliminary speculations. I detail below several instances where the argumentation and/or the analysis are flawed.

- They analyze chirp patterning and show that, most likely, a chirp by an individual is followed by a chirp in the same individual. They argue that it is rare that a chirp elicits a "response" in the other fish. Even if there are clearly stronger correlations between chirps in the same individual, they provide no statistical analysis that discards the existence of occasional "response" patterns. The fact that these are rare, and that the authors don't do an appropriate analysis of probabilities, leads to this unsupported conclusion.<br /> - One of the main pieces of evidence that chirps can be used to enhance conspecific localization is based on their "interference" measure. The measure is based on an analysis of "inter-peak-intervales". This in itself is a questionable choice. The nervous system encodes all parts of the stimulus, not just the peak, and disruption occurring at other phases of the beat might be as relevant. The interference will be mostly affected by the summed duration of intervals between peaks in the chirp AM. They do not explain why this varies with beat frequency. It is likely that the changes they see are simply an artifact of the simplistic measure. A clear demonstration that this measure is not adequate comes from the observation in Fig7E-H. They show that the interference value changes as the signal is weaker. This measure should be independent of the strength of the signal. The method is based on detecting peaks and quantifying the time between peaks. The only reason this measure could be affected by signal strength is if noisy recordings affect how the peak detection occurs. There is no way to argue that this phenomenon would happen the same way in the nervous system. Furthermore, they qualitatively argue that patterns of chirp production follow patterns of interference strength. No statistical demonstration is done. Even the qualitative appraisal is questionable. For example, they argue that there are relatively few chirps being produced for DFs of 60 or -60 Hz. But these are DF where they have only a very small sample size. The single pair of fish that they recorded at some of these frequencies might not have chirped by chance and a rigorous statistical analysis is necessary. Similarly, in Fig 5C they argue that the position of the chirps fall on areas of the graph where the interferences are strongest (darker blue) but this is far from obvious and, again, not proven.<br /> - They relate the angle at which one fish produces chirps relative to the orientation of the mesh enclosing. They argue that this is related to the orientation of electric field lines by doing a qualitative comparison with a simplified estimate of field lines. To be convincing this analysis should include a quantitative comparison using the exact same body position of the two fish when the chirps are emitted.<br /> -They show that the very vast majority of chirps in Fig 6 occur when the fish are within a few centimeters (e.g. very large first bin in Fig6E-Type2). This is a situation when the other fish signal will be strongest and localization will be the easiest. It is hard to understand why the fish would need a mechanism to enhance localization in these conditions (this is the opposite of difficult conditions e.g. the "cluttered" environment).<br /> - The argumentation aimed at rejecting the well-established role of chirp in communication is weak at best. First, they ignored some existing data when they argue that there is no correlation between chirping and behavioral interactions. Particularly, Hupe and Lewis (2008) showed a clear temporal correlation between chirps and a decrease in bites during aggressive encounters. It could be argued that this is "causal evidence" (to reuse their wording) that chirps cause a decrease in attacks by the receiver fish (see Fig 8B of the Hupe paper and associated significant statistics). Also, Oboti et al. argue that social interactions involve "higher levels of locomotion" which would explain the use of chirps since they are used to localize. But chirps are frequent in "chirp chamber" paradigms where no movement is involved. They also point out that social context covaries with beat frequency and thus that it is hard to distinguish which one is linked to chirping propensity and then say that it is hard to disentangle this from "biophysical features of EOD fields affecting detection and localization of conspecific fish". But they don't provide any proof that beat frequency affects detection and localization so their argument is not clear. Last, they argue that tests in one species shouldn't be extrapolated to other species. But many of the studies arguing for the role of chirps in communication was done on brown ghost. In conclusion of this point, they do not provide any strong argument that rejects the role of chirps as a communication signal. A perspective that would be better supported by their data and consistent with past research would be to argue that, in addition to a role in communication, chirps could sometimes be used to help localize conspecifics.<br /> -The discussion they provide on the possible mechanism by which chirps could help with localization of the conspecific is problematic. They imply that chirps cause a stronger response in the receptors. For most chirps considered here, this is not true. For a large portion of the beat frequencies shown in this paper, chirps will cause a de-synchronization of the receptors with no increase in firing rate. They cannot argue that this represents an enhanced response. They also discuss a role for having a broader frequency spectrum -during the chirp- in localization by making a parallel with pulse fish. There is no evidence that a similar mechanism could even work in wave-type fish.<br /> -They write the whole paper as if males and females had been identified in their experiments. Although EOD frequency can provide some guess of the sex the method is unreliable. We can expect a non-negligible percentage of error in assigning sex.

Reviewer #1 (Public Review):

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

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

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

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

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

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

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

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

There has been discussion in the review process about whether a monomeric nucleus is consistent with established properties of huntingtin aggregation. I do not see a problem with an energetically unfavorable conformational state preceding a concentration-dependent growth step. The authors make the case for this sequence using a schematic free energy landscape (Fig 6) that has many similarities to a free energy landscape derived from models of polyQ nucleation (Phan et al. 2022, see Fig. 6). The theory does not consider molecules large enough to form the conformational state described by Kandola et al., but the transition state is otherwise very similar.

Reviewer #1 (Public Review):

The current manuscript provides a timely contribution to the ongoing discussion about the mechanism of the apical sodium/bile acid transporter (ASBT) transporters. Recent structures of the mammalian ASBT transporters exhibited a substrate binding mode with few interactions with the core domain (classically associated with substrate binding), prompting an unusual proposal for the transport mechanism. Early structures of ASBT homologues from bacteria also exhibit unusual substrate binding in which the core substrate binding domain is less engaged than expected. Due to the ongoing questions of how substrate binding and mechanism are linked in these transporters, the authors set out to deepen our understanding of a model ABST homolog from bacteria N. meningitidis (ABST-NM).

The premise of the current paper is that the bacterial ASBT homologs are probably not physiological bile acid transporters, and that structural elucidation of a natively transported substrate might provide better mechanistic information. In the current manuscript, the authors revisit the first BASS homologue to be structurally characterized, ABST-NM. Based on bacteriological assays in the literature, the authors identify the coenzyme A precursor pantoate as a more likely substrate for ABST-NM than taurocholate, the substrate in the original structure. A structure of ASBT-NM with pantoate exhibits interesting differences in structure. The structures are complemented with MD simulations, and the authors propose that the structures are consistent with a classical elevator transport mechanism.

The structural experiments are convincing. The binding and molecular dynamics experiments provide intriguing insights into the transporter's conformational changes. However, it is nonetheless a soft spot in the story that a transport assay is not readily available for this substrate. Mechanistic proposals, like the proposed role of T112 in unlocking the transporter, would be better supported by transport data.

Reviewer #1 (Public Review):

Summary:<br /> The manuscript proposes an alternative method by SDS-PAGE calibration of Halo-Myo10 signals to quantify myosin molecules at specific subcellular locations, in this specific case filopodia, in epifluorescence datasets compared to the more laborious and troublesome single molecule approaches. Based on these preliminary estimates, the authors developed further their analysis and discussed different scenarios regarding myosin 10 working models to explain intracellular diffusion and targeting to filopodia.

Strengths:<br /> Overall, the paper is elegantly written and the data analysis is appropriately presented.

Weaknesses:<br /> While the methodology is intriguing in its descriptive potential and could be the beginning of an interesting story, a good portion of the paper is dedicated to the discussion of hypothetical working mechanisms to explain myosin diffusion, localization, and decoration of filopodial actin that is not accompanied by the mandatory gain/loss of function studies required to sustain these claims.

Reviewer #1 (Public Review):

Summary: Bloodstream stages of the parasitic protist, Trypanosoma brucei, exhibit very high rates of constitutive endocytosis, which is needed to recycle the surface coat of Variant Surface Glycoproteins (VSGs) and remove surface immune complexes. While many studies have shown that the endo-lysosomal systems of T. brucei BF stages contain canonical domains, as defined by classical Rab markers, it has remained unclear whether these protists have evolved additional adaptations/mechanisms for sustaining these very high rates of membrane transport and protein sorting. The authors have addressed this question by reconstructing the 3D ultrastructure and functional domains of the T. brucei BF endosome membrane system using advanced electron tomography and super-resolution microscopy approaches. Their studies reveal that, unusually, the BF endosome network comprises a continuous system of cisternae and tubules that contain overlapping functional subdomains. It is proposed that a continuous membrane system allows higher rates of protein cargo segregation, sorting and recycling than can otherwise occur when transport between compartments is mediated by membrane vesicles or other fusion events.

Strengths: The study is a technical tour-de-force using a combination of electron tomography, super-resolution/expansion microscopy, immune-EM of cryo-sections to define the 3D structures and connectivity of different endocytic compartments. The images are very clear and generally support the central conclusion that functionally distinct endocytic domains occur within a dynamic and continuous endosome network in BF stages.

Weaknesses: The authors suggest that this dynamic endocytic network may also fulfil many of the functions of the Golgi TGN and that the latter may be absent in these stages. Although plausible, this comment needs further experimental support. For example, have the authors attempted to localize canonical makers of the TGN (e.g. GRIP proteins) in T. brucei BF and/or shown that exocytic carriers bud directly from the endosomes?

Reviewer #1 (Public Review):

Summary: Planar cell polarity core proteins Frizzled (Fz)/Dishevelled (Dvl) and Van Gogh-like (Vangl)/Prickle (Pk) are localized on opposite sides of the cell and engage in reciprocal repression to modulate cellular polarity within the plane of static epithelium. In this interesting manuscript, the authors explore how the anterior core proteins (Vangl/Pk) inhibit the posterior core protein (Dvl). The authors propose that Pk assists Vangl2 in sequestering both Dvl2 and Ror2, while Ror2 is essential for Dvl to transition from Vangl to Fz in response to non-canonical Wnt signaling. There are several points that affect the strength of the author's conclusions.

Strengths: The strengths of the manuscript are in the very interesting and new concept for a model of how non-canonical Wnt induces Dvl to transition from Vangl to Fz. Prickle and Vangl2 are proposed to play an opposing role to suppress Dvl activity during convergent extension movements, whereas Ror antagonizes Vangl and may be required for the transition.

Weaknesses: The weaknesses are in the clarity and resolution of the data that forms the basis of the model. In addition to whole embryo morphology that is used as evidence for convergent extension (CE) defects, two forms of data are presented, co-expression and IP, as well as a strong reliance on IF of exogenously expressed proteins. Thus, it is critical that both forms of evidence be very strong and clear, and this is where there are deficiencies; 1) For vast majority of experiments general morphology and LWR was used as evidence of effects on convergent extension movements rather than Keller explants or actual cell movements in the embryo. 2) The study would benefit from high or super resolution microscopy, since in many cases the differences in protein localization are not very pronounced. 3) The IP and Western analysis data often show subtle differences, and not apparent in some cases. 4) It is not clear how many biological repeats were performed or how and whether statistical analyses were performed.

Joint Public Review:

This paper's strengths are the interesting analysis of TLR signaling in hair follicle stem cell activation and the striking phenotype of the TLR2 cKO mice (but note below). The functional interrogation parts using HFSC-specific TLR2 genetic deletion are solid, and an endogenous regulator, CEP, is identified. The experiments reported in this manuscript are well-designed and presented. The authors provided extensive evidence supporting the roles of TLR2 signaling in regulating hair follicle stem cell functions. Importantly, the findings from this paper may have sustained impacts on our understanding of the roles of innate immunity in regulating tissue regeneration in the absence of inflammation.

The main evidence for the mechanistic analysis is based on fluorescence using immunohistochemistry, and here the expression analysis is not convincing. In addition, additional assays beyond immunolandscaping are needed to confirm the findings. The reviewers felt that your data substantiating the mechanism of interaction between TLR2 and BMP pathway needs bolstering.

Reviewer #1 (Public Review):

Authors performed a meta-analysis of GC concentrations and metabolic rates in birds and mammals. They found close associations for all studies showing a positive association between these two traits. As GCs have been viewed with close links to "stress," authors suggest that this overlooks the importance of metabolism and perhaps GC variation does not relate to "stress" per se but an increase in metabolism instead.

This is an important meta-analysis, as most researchers acknowledge the link between GCs and metabolism, metabolism is often overlooked in studies. The field of conservation physiology is especially focused on GCs being a "stress" hormone, which overlooks the importance of GCs in mediating energy balance, i.e., an animal that has high GC concentrations may not be doing that poorly compared to an animal with low GC concentrations, it might just be expending more energy, e.g., caring for young. The results, with overwhelming directionality and strong effect sizes, support the link for a positive association with these two variables.

My main concern lies in that most of the studies come from a few labs, therefore there may be limited data to test this relationship. I would include lab as a random effect to see how strong this effect might be. Furthermore, I would like to see a test of the directionality of the two variables. Authors suggest that changes in metabolism affect GC levels but likely changes in GC levels would affect metabolism. Why not look into studies that have altered GC levels experimentally and see the effect on metabolism? Based on the close link, authors suggest that GCs may not play a role outside of "stress" beyond the stressor's effect on metabolic rate. However, if they were to investigate manipulations of GCs on metabolic rate, the link may or may not be there, which would be interesting to look at. I firmly believe that GCs are tightly linked to metabolism; however, I also think that GCs have a range of effects outside of metabolism as well, depending on the course and strength of the stressor.

This work helps in the thinking that GCs are not the same as a "stress" hormone or labelling hormones with only one function. As hormones are naturally pleiotropic, the view of any one hormone being X is overly simplistic.

Reviewer #1 (Public Review):

Summary: This work by Zhang et al. provides new strategies to improve the efficiency of precise Prime Editing (PE) in zebrafish embryos. The authors test how two simple changes impact PE efficiency: first, by refolding the pegRNA before complexing with Cas9 nickase-reverse transcriptase PE2, and second, by introducing mutations to the pegRNA intended to reduce its autoinhibitory activity by disrupting complementarity between the 5' spacer sequence and the 3' PBS-RTT (Primer Binding Site-Reverse Transcriptase Template).

Strengths: The authors tested multiple loci in the zebrafish genome to determine how pegRNA refolding and point mutations in the RTT would impact overall mutagenesis efficiency and precise PE at the target sites. The impact on efficiency was tested with three types of pegRNAs designed to introduce base substitutions, insertions or deletions. Next-generation sequencing of amplicons from pooled, injected embryos provided robust measurement of mutagenesis and editing. Insertion and deletion pegRNAs were overall more efficient than substitution pegRNAs, which may be useful information in considering experimental design strategy for introducing a specific variant. There is potential for further improvement by combining the authors' methods with previously published strategies to improve pegRNAs through design and chemical modification.

Weaknesses: The observed increases in the frequency of precise PE were relatively minor and inconsistent across the multiple pegRNAs tested. The substitution pegRNAs showed very low precise PE, at levels less than 1 percent, therefore the fold changes reported were still representative of 10 percent or less of overall edits. Overall mutagenesis frequency, as measured by indel formation, increased along with increased precise PE. The approach produces highly genetically mosaic embryos, therefore the utility for transient studies in injected zebrafish embryos is unclear. Data on improved germline transmission frequency of precise PE alleles would strengthen the study and be of wide interest in the zebrafish community.

Reviewer #1 (Public Review):

Summary:<br /> The preprint by Laganowsky and co-workers describes the use of mutant cycles to dissect the thermodynamic profile of specific lipid recognition by the ABC transporter MsbA. The authors use native mass spectrometry with a variable temperature source to monitor lipid binding to the native protein dimer solubilized in detergent. Analysis of the peak intensities (that is, relative abundance) of 1-3 bound lipids as a function of solution temperature and lipid concentration yields temperature-dependent Kds. The authors use these to then generate van't Hoff plots, from which they calculate the enthalpy and entropy contributions to binding of one, two, and in some cases, three lipids to MsbA.<br /> The authors then employ mutant cycles, in which basic residues involved in headgroup binding are mutated to alanine. By comparing the thermodynamic signatures of single and double (and in one instance triple) mutants, they aim to identify cooperativity between the different positions. They furthermore use inward and outward locking conditions which should control access to the different binding sites determined previously.<br /> The main conclusion is that lipid binding to MsbA is driven mainly by energetically favorable entropy increase upon binding, which stems from the release of ordered water molecules that normally coordinate the basic residues, which helps to overcome the enthalpic barrier of lipid binding. The authors also report an increase in lipid binding at higher temperatures which they attribute to a non-uniform heat capacity of the protein. Although they find that most residue pairs display some degree of cooperativity, particularly between the inner and outer lipid binding sites, they do not provide a structural interpretation of these results.

Strengths:<br /> The use of double mutant cycles and mass spectrometry to dissect lipid binding is novel and interesting. For example, the observation that mutating a basic residue in the inner and one in the outer binding site abolishes lipid binding to a greater extent than the individual mutations is highly informative even without having to break it down into thermodynamic terms (see "weaknesses" section). In this sense, the method and data reported here opens new avenues for the structure/activity relationship of MsbA. The "mutant cycle" approach is in principle widely applicable to other membrane proteins with complex lipid interactions.

Weaknesses:<br /> The use of double mutant cycles to dissect binding energies is well-established, and has, as the authors point out, been employed in combination with mass spectrometry to study protein-protein interactions. Its application to extract thermodynamic parameters is robust in cases where a single binding event is monitored, e.g. the formation of a complex with well-defined stoichiometry, where dissociation constants can be determined with high confidence. It is, however, complicated significantly by the fact that for MsbA-lipid interactions, we are not looking at a single binding event, but a stochastic distribution of lipids across different sites. Even if the protein is locked in a specific conformation, the observation of a single lipid adduct does not guarantee that the one lipid is always bound to a specific site. In some of the complexes detected by MS, the lipid is likely bound somewhere else. Lipid binding Kds from mass spectrometry, although helpful in some instances as a proxy for global binding affinities, should therefore be taken with a grain of salt.

The authors analyze the difference in binding upon mutating binding sites (ddG etc). Here, another complicating factor comes into play, the fact that mutation of a binding site (which the authors show reduces lipid binding) may instead allow the lipid to bind to a lower-affinity site elsewhere. Unfortunately, the authors do not specify the protein concentration, but assuming it is in the single-digit micromolar range, as common for native MS experiments, lipid and protein concentrations are almost equal for most of the data points, resulting in competition between binding sites for free lipids. As a rule of thumb, for Kd measurements, the concentration of the constant component, the protein, should be far below the Kd, to avoid working in the "titration" regime rather than the "binding" regime (see Jarmoskaite et al, eLife 2020). I cannot determine whether this is the case here. The way I understand the double mutant cycle approach, reliable Kd measurements are required to accurately determine dH and TdS, so I would encourage the authors to confirm their Kd values using complementary methods before in-depth interpretations of the thermodynamic components.

It is somewhat counterintuitive that for many double mutants, and the triple mutant, the entropic component becomes more favorable compared to the WT protein. If the increase in entropy upon lipid binding comes from the release of ordered water molecules around the basic residues (a reasonable assumption) why does this apply even more in proteins where several basic residues have been changed to alanine, which coordinate far fewer water molecules?

The authors could devote more attention to the fact that they use detergent micelles as a vehicle for lipid binding studies. To a limited extent, detergents compete with lipids for binding, and are present in extreme excess over the lipid. The micelle likely changes its behavior in response to temperature changes. For example, the packing around the protein loosens up upon heating, which may increase the chance for lipids to bind. In this case, the increase in binding at higher temperatures may not be related to a change in heat capacity. This question could be addressed by MD simulations, if it's not already in the literature.

Reviewer #1 (Public Review):

Summary:<br /> The biogenesis of outer membrane proteins (OMPs) into the outer membranes of Gram-negative bacteria is still not fully understood, particularly substrate recognition and insertion by beta-assembly machinery (BAM). In the studies, the authors present their studies that in addition to recognition by the last strand of an OMP, sometimes referred to as the beta-signal, an additional signal upstream of the last strand is also important for OMP biogenesis.

Strengths:<br /> 1. Overall the manuscript is well organized and written, and addresses an important question in the field. The idea that BAM recognizes multiple signals on OMPs has been presented previously, however, it was not fully tested.

2. The authors here re-address this idea and propose that it is a more general mechanism used by BAM for OMP biogenesis.

3. The notion that additional signals assist in biogenesis is an important concept that indeed needs fully tested in OMP biogenesis.

4. A significant study was performed with extensive experiments reported in an attempt to address this important question in the field.

5. The identification of important crosslinks and regions of substrates and Bam proteins that interact during biogenesis is an important contribution that gives clues to the path substrates take en route to the membrane.

Weaknesses:

Major critiques (in no particular order):

1. The title indicates 'simultaneous recognition', however no experiments were presented that test the order of interactions during OMP biogenesis.

2. Aspects of the study focus on the peptides that appear to inhibit OmpC assembly, but should also include an analysis of the peptides that do not to determine this the motif(s) present still or not.

3. The b-signal is known to form a b-strand, therefore it is unclear why the authors did not choose to chop OmpC up according to its strands, rather than by a fixed peptide size. What was the rationale for how the peptide lengths were chosen since many of them partially overlap known strands, and only partially (2 residues) overlap each other? It may not be too surprising that most of the inhibitory peptides consist of full strands (#4, 10, 21, 23).

4. It would be good to have an idea of the propensity of the chosen peptides to form b-stands and participate in b-augmentation. We know from previous studies with darobactin and other peptides that they can inhibit OMP assembly by competing with substrates.

5. The recognition motifs that the authors present span up to 9 residues which would suggest a relatively large binding surface, however, the structures of these regions are not large enough to accommodate these large peptides.

6. The authors highlight that the sequence motifs are common among the inhibiting peptides, but do not test if this is a necessary motif to mediate the interactions. It would have been good to see if a library of non-OMP related peptides that match this motif could also inhibit or not.

7. In the studies that disrupt the motifs by mutagenesis, an effect was observed and attributed to disruption of the interaction of the 'internal signal'. However, the literature is filled with point mutations in OMPs that disrupt biogenesis, particular those within the membrane region. F280, Y286, V359, and Y365 are all residues that are in the membrane region that point into the membrane. Therefore, more work is needed to confirm that these mutations are in parts of a recognition motif rather than on the residues that are disrupting stability/assembly into the membrane.

8. The title of Figure 3 indicates that disrupting the internal signal motif disrupts OMP assembly, however, the point mutations did not seem to have any effect. Only when both 280 and 286 were mutated was an effect observed. And even then, the trimer appeared to form just fine, albeit at reduced levels, indicating assembly is just fine, rather the rate of biogenesis is being affected.

9. In Figure 4, the authors attempt to quantify their blots. However, this seems to be a difficult task given the lack of quality of the blots and the spread of the intended signals, particularly of the 'int' bands. However, the more disturbing trend is the obvious reduction in signal from the post-urea treatment, even for the WT samples. The authors are using urea washes to indicate removal of only stalled substrates. However a reduction of signal is also observed for the WT. The authors should quantify this blot as well, but it is clear visually that both WT and the mutant have obvious reductions in the observable signals. Further, this data seems to conflict with Fig 3D where no noticeable difference in OmpC assembly was observed between WT and Y286A, why is this the case?

10. The pull down assays with BamA and BamD should include a no protein control at the least to confirm there is no non-specific binding to the resin. Also, no detergent was mentioned as part of the pull downs that contained BamA or OmpC, nor was it detailed if OmpC was urea solubilized.

11. The neutron reflectometry experiments are not convincing primarily due to the lack controls to confirm a consistent uniform bilayer is being formed and even if so, uniform orientations of the BamA molecules across the surface. Further, no controls were performed with BamD alone, or with OmpC alone, and it is hard to understand how the method can discriminate between an actual BamA/BamD complex versus BamA and BamD individually being located at the membrane surface without forming an actual complex. Previous studies have reported difficulty in preparing a complex with BamA and BamD from purified components. Additionally, little signal differences were observed for the addition of OmpC. However, an elongated unfolded polypeptide that is nearly 400 residues long would be expected to produce a large distinct signal given that only the C-terminal portion is supposedly anchored to BAM, while the rest would be extended out above the surface. The depiction in Figure 5D is quite misleading when viewing the full structures on the same scales with one another.

12. In the crosslinking studies, the authors show 17 crosslinking sites (43% of all tested) on BamD crosslinked with OmpC. Given that the authors are presenting specific interactions between the two proteins, this is worrisome as the crosslinks were found across the entire surface of BamD. How do the authors explain this? Are all these specific or non-specific?

13. The study in Figure 6 focuses on defined regions within the OmpC sequence, but a more broad range is necessary to demonstrate specificity to these regions vs binding to other regions of the sequence as well. If the authors wish to demonstrate a specific interaction to this motif, they need to show no binding to other regions.

14. The levels of the crosslinks are barely detectable via western blot analysis. If the interactions between the two surfaces are required, why are the levels for most of the blots so low?

15. Figure 7 indicates that two regions of BamD promote OMP orientation and assembly, however, none of the experiments appears to measure OMP orientation? Also, one common observation from panel F was that not only was the trimer reduced, but also the monomer. But even then, still a percentage of the trimer is formed, not a complete loss.

16. The experiment in Fig 7B would be more conclusive if it was repeated with both the Y62A and R197A mutants and a double mutant. These controls would also help resolve any effect from crowding that may also promote the crosslinks. Further, the mutation of R197 is an odd choice given that this residue has been studied previously and was found to mediate a salt bridge with BamA. How was this resolved by the authors in choosing this site since it was not one of the original crosslinking sites?

17. As demonstrated by the authors in Fig 8, the mutations in BamD lead to reduction in OMP levels for more than just OmpC and issues with the membrane are clearly observable with Y62A, although not with R197A in the presence of VCN. The authors should also test with rifampicin which is smaller and would monitor even more subtle issues with the membrane. Oddly, no growth was observed for the Vec control in the lower concentration of VCN, but was near WT levels for 3 times VCN, how is this explained?

18. While Fig 8I indeed shows diminished levels for FY as stated, little difference was observed for the trimer for the other mutants compared to WT, although differences were observed for the dimer. Interestingly, the VY mutant has nearly WT levels of dimer. What do the authors postulate is going on here with the dimer to trimer transition? How do the levels of monomer compare, which is not shown?

19. In the discussion, the authors indicate they have '...defined an internal signal for OMP assembly', however, their study is limited and only investigates a specific region of OmpC. More is needed to definitively say this for even OmpC, and even more so to indicate this is a general feature for all OMPs.

20. In the proposed model in Fig 9, it is hard to conceive how 5 strands will form along BamD given the limited surface area and tight space beneath BAM. More concerning is that the two proposal interaction sites on BamD, Y62 and R197, are on opposite sides of the BamD structure, not along the same interface, which makes this model even more unlikely. As evidence against this model, in Figure 9E, the two indicates sites of BamD are not even in close proximity of the modeled substrate strands.

Reviewer #1 (Public Review):

Summary:<br /> The authors utilize fluid-structure interaction analyses to simulation fluid flow within and around the Cambrian cnidarian Quadrapyrgites to reconstruct feeding/respiration dynamics. Based on vorticity and velocity flow patterns, the authors suggest that the polyp expansion and contraction ultimately develop vortices around the organism that are like what modern jellyfish employ for movement and feeding. Lastly, the authors suggest that this behavior is likely a prerequisite transitional form to swimming medusae.

Strengths:<br /> While fluid-structure-interaction analyses are common in engineering, physics, and biomedical fields, they are underutilized in the biological and paleobiological sciences. Zhang et al. provide a strong approach to integrating active feeding dynamics into fluid flow simulations of ancient life. Based on their data, it is entirely likely the described vortices would have been produced by benthic cnidarians feeding/respiring under similar mechanisms. However, some of the broader conclusions require additional justification.

Weaknesses:

1. The claim that olivooid-type feeding was most likely a prerequisite transitional form to jet-propelled swimming needs much more support or needs to be tailored to olivooids. This suggests that such behavior is absent (or must be convergent) before olivooids, which is at odds with the increasing quantities of pelagic life (whose modes of swimming are admittedly unconstrained) documented from Cambrian and Neoproterozoic deposits. Even among just medusozoans, ancestral state reconstruction suggests that they would have been swimming during the Neoproterozoic (Kayal et al., 2018; BMC Evolutionary Biology) with no knowledge of the mechanics due to absent preservation.<br /> 2. While the lack of ambient flow made these simulations computationally easier, these organisms likely did not live in stagnant waters even within the benthic boundary layer. The absence of ambient unidirectional laminar current or oscillating current (such as would be found naturally) biases the results.<br /> 3. There is no explanation for how this work could be a breakthrough in simulation gregarious feeding as is stated in the manuscript.

Despite these weaknesses the authors dynamic fluid simulations convincingly reconstruct the feeding/respiration dynamics of the Cambrian Quadrapyrgites, though the large claims of transitionary stages for this behavior are not adequately justified. Regardless, the approach the authors use will be informative for future studies attempting to simulate similar feeding and respiration dynamics.

Reviewer #1 (Public Review):

Precision guided sterile insect technology (pgSIT) is a means of mosquito vector control that aims to simultaneously kill females while generating sterile males for field release. These sterile males are expected to mate with 'wild' females resulting in very few eggs being laid or low hatching rates. Repeated releases are expected to result in the suppression of the mosquito population. This method avoids cumbersome sex-sorting while generating the sterile males. Importantly, until release, the two genetic elements that bring about female lethality and male sterility - the Cas9 and the gRNA carrying mosquitoes - are maintained as separate lines. They are crossed only prior to release, and therefore, this approach is considered to be more safe than gene drives.

The authors had made a version of this pgSIT in their 2021 paper where they targeted *β-Tubulin 85D*, which is only expressed in the male testes and its loss-of-function results in male sterility. In that pgSIT, they did not have female lethality, but generated flightless females by simultaneously targeted *myosin heavy chain,* which is expressed only in the female wings. Here the authors argue, that the survival of females is not ideal, and so modify their 2021 approach to achieve female lethality/sterility.

To do this, they target two genes - the female specific isoform of Dsx and intersex. They use multiple gRNAs against these genes and validate their ability to cause female lethality/sterility. Having verified that these do indeed affect female fertility, they combine gRNAs against Dsx and ix to generate female lethality/sterility and use *β-Tubulin 85D* to generate male sterility (previously validated). When these gRNA mosquitoes are crossed to Cas9 and the progeny crossed to WT (the set-up for pgSIT), they find that very few eggs are laid, larval death is high, and what emerges are males or intersex progeny that are sterile.

As this is the requirement for pgSIT, the authors then test if it is able to induce population suppression. To do this, they conduct cage trials and find that only when they use 20:1 or 40:1 ratio of pgSIT:WT cages, does the population crash in 4-5 generations. They model this pgSIT's ability to suppress a population in the wild. Unfortunately, I was not able to assess what parameters from their pgSIT were used in the model and therefore the predicted efficacy of their pgSIT, (though the range of 0-.1 is not great, given that the assessment is between 0-0.15).

Finally, they also develop a SENSR with a rapid fluorescence read-out for detecting the transgene in the field. They show that this sensor is specific and sensitive, detecting low copy numbers of the transgene. This would be important for monitoring any release.

Overall, the data are clear and well presented. The manuscript is well written (albeit likely dense for the uninitiated!). I had concerns about the efficacy of generating the pgSIT animals - the overall number of eggs hatched from the gRNA (X) Cas9 cross appears to be low, therefore, very large numbers of parental animals would have to be reared and crossed to obtain enough sterile males for the SIT. In addition to this, I was concerned about the intersex progeny that can blood-feed. These could potentially contribute to the population and it would be useful to see the data that suggest that these numbers are low and the animals will not be competent in the field.

Reviewer #1 (Public Review):

Despite durable viral suppression by antiretroviral therapy (ART), HIV-1 persists in cellular reservoirs in vivo. The viral reservoir in circulating memory T cells has been well characterized, in part due to the ability to safely obtain blood via peripheral phlebotomy from people living with HIV-1 infection (PWH). Tissue reservoirs in PWH are more difficult to sample and are less well understood. In this small (n=3) autopsy study, Sun and colleagues use an advanced genetic sequencing technique to characterize HIV-1 that persists in human tissues despite antiretroviral therapy. The authors describe isolation and genetic characterization of HIV-1 reservoirs from a variety of tissues including the central nervous system (CNS) obtained from three recently deceased individuals at autopsy. They identified clonally expanded proviruses in the CNS in all three individuals.

Strengths of the work include the study of human tissues that are under-studied and difficult to access, and the sophisticated near-full length sequencing technique that allows for inferences about genetic intactness and clonality of proviruses. The small sample size (n=3) is a drawback. Furthermore, two individuals were on ART for just one year at the time of autopsy and had T cells compatible with AIDS, and one of these individuals had a low-level detectable viral load (Figure S1). This makes generalizability of these results to PWH who have been on ART for years or decades and have achieved durable viral suppression and immune reconstitution difficult.

While anatomic tissue compartment and CNS region accompany these PCR results, it is unclear which cell types these viruses persist in. As the authors point out, it is possible that these reservoir cells might have been infiltrating T cells from blood present at the time of autopsy tissue sampling. Cell type identification would greatly enhance the impact of this work. Overall, this small, thoughtful study contributes to our understanding of the tissue distribution of persistent HIV-1, and informs the ongoing search for viral eradication.

Joint Public Review:

In this manuscript, Xue and colleagues investigate the fundamental aspects of cellular fate decisions and differentiation, focusing on the dynamic behaviour of gene regulatory networks. It explores the debate between static (noise-driven) and dynamic (signal-driven) perspectives within Waddington's epigenetic landscape, highlighting the essential role of gene regulatory networks in this process. The authors propose an integrated analysis of fate-decision modes and gene regulatory networks, using the Cross-Inhibition with Self-activation (CIS) network as a model. Through mathematical modelling, they differentiate two logic modes and their effect on cell fate decisions: requires both the presence of an activator and absence of a repressor (AA configuration) with one where transcription occurs as long the repressor is not the only species on the promoter (OO configuration).

The authors establish a relationship between noise profiles, logic-motifs, and fate-decision modes, showing that defining any two of these properties allows the inference of the third. They also identify, under the signal-driven mode, two fundamental patterns of cell fate decisions: either prioritising progression or accuracy in the differentiation process. The authors apply this analysis to available high-throughput datasets of cell fate decisions in hematopoiesis and embryogenesis, proposing the underlying driving force in each case and utilising the observed noise patterns to nominate key regulators.

The paper makes a substantial contribution by rigorously evaluating assumptions in gene regulatory network modelling. Notably, it extensively compares two model configurations based on different integration logic, illuminating the consequences of these assumptions in a clear, understandable manner. The practical simulation results effectively bridge theoretical models with real biological systems, adding relevance to the study's insights. With its potential to enhance our understanding of gene regulatory networks across biological processes, the paper holds promise. Its implications extend practically to synthetic circuit design, impacting biotechnology. The conclusions stand out, addressing cell fate decisions and noise's role in gene networks, contributing significantly to our understanding. Moreover, the adaptable approach proposed offers versatility for broader applications in diverse scenarios, solidifying its relevance beyond its current scope.

However, the manuscript in its current form also has some important weaknesses, including the lack of clarity in the text and the questionable generality of specific observations. For instance, even when focusing on the CIS network, the effect of alternative model implementations is not discussed. Notably, the input signals are only considered as an additive effect over the differential equations, while signals can potentially affect each of the individual processes. The proposed model allows for a continuum of interactions/competition between transcription factors, yet only very restrictive scenarios are explored (strict AND/OR logic operations). Moreover, how the model parameters are chosen throughout the paper is not clear. Similarly, the concentration and time units are not clearly specified, making their comparison to experimental data troublesome.

Regarding clarity, how the general model (equations 1-2) transforms into the specific cases evaluated in the paper is not clearly stated in the main text, nor are the positive and negative effects of individual transcription factors adequately explained. Similarly, in the main text and Figure 2, the authors refer to a Boolean model. However, they do not clearly explain how this relates to the differential equation model, nor its relevance to understanding the paper. Additionally, the term "noise levels" is generally used to refer to noise introduced in the "noise-driven" analysis (i.e., as an input or parameter in the models). Nonetheless, it is later claimed to be evaluated as an intrinsic property of the network (likely referring to expression level variability measured by the coefficient of variation). Finally, some jargon is introduced without sufficient context about its meaning (e.g., "temporal fully-connected stage").

Additionally, proper discussion of previous work is also missing. For instance, the dynamics of the CIS network investigated by the authors have been extensively characterised (see e.g., Huang et al., Dev Biol, 2007), and how the author's results compare to this previous work should be discussed. In particular, the central assumptions behind the derivation of the model proposed in the manuscript must be assessed in the context of previous work.

Reviewer #1 (Public Review):

Gating of Kv10 channels is unique because it involves coupling between non-domain swapped voltage-sensing domains, a domain-swapped cytoplasmic ring assembly formed by the N- and C-termini, and the pore domain. Recent structural data suggests that activation of the voltage sensing domain relieves a steric hindrance to pore opening, but the contribution of the cytoplasmic domain to gating is still not well understood. This aspect is of particular importance because proteins like Calmodulin interact with the cytoplasmic domain to regulate channel activity. The effects of Calmodulin (CaM) in WT and mutant channels with disrupted cytoplasmic gating ring assemblies are contradictory, resulting in inhibition or activation, respectively. The underlying mechanism for these discrepancies is not understood. In the present manuscript, Reham Abdelaziz and collaborators use electrophysiology, biochemistry, and mathematical modeling to explore the mechanistic effects on gating of various mutations and deletions that disrupt inter-subunit interactions at the cytoplasmic gating ring assembly and the consequences for channel modulation by CaM. From the beginning, it becomes challenging for non-experts to grasp the structural basis of the perturbations that are introduced (ΔPASCap and E600R), because no structural data or schematic cartoons are provided to illustrate the rationale for those deletions or their potential mechanistic effects. In addition, the lack of additional structural information or illustrations, and a somewhat confusing discussion of the structural data, make it challenging for a reader to reconcile the experimental data and mathematical model with a particular structural mechanism for gating, limiting the impact of the work.

By expressing mutants in oocytes and recording currents using Two Electrode Voltage-Clamp (TEV), it is found that both ΔPASCap and E600R mutants have biphasic voltage-activation curves, with two clear components contributing to activation and deactivation kinetics. Notably, the first component involving activation occurs at voltages where WT channels are mostly closed. Larger deletions at the N-terminus that further disrupt the cytoplasmic gating ring assembly accentuate the first component by heavily disfavoring the second one. The data can be well described by three components involving a closed state and two open states O1 and O2, in which the second component O2 is the one affected by the mutations and deletions. Based on the structural data, the first component is hypothesized to be associated with voltage sensor activation, whereas the second component is associated with conformational changes at the cytoplasmic ring. Consistent with this interpretation, a deletion construct where the covalent link between the voltage sensor and pore has been severed is shown to primarily affect that first component. Also consistent with the first component involving voltage-sensor activation, it is found that divalent cations that are known to stabilize the voltage sensor in its most deactivated conformations, shift the occupancy of the first component to more depolarizing potentials. Activation towards and closure from the first component is slow, whereas channels close rapidly from O2. A rapid alternating pulse protocol is used to take advantage of the difference in activation and deactivation kinetics between the two open components in the mutants and thus drive an increasing number of channels toward state O1. Currents activated by the alternating protocol reached larger amplitudes than those elicited by a long depolarization to the same voltage. This finding is interpreted as an indication that the first component (O1) has a larger conductance than the second (O2). It is shown that conditioning pulses to very negative voltages results in currents that are larger and activate more slowly than those elicited at the same voltage but starting from less negative conditioning pulses. In voltage-activated curves, the component corresponding to state O1 is shown to be favored by increasingly negative conditioning voltages as compared to less negative ones. This is interpreted as indicating that the first open component O1 is primarily accessed from so-called 'deeply closed' states in which voltage sensors are in their most deactivated position(s). Consistently, a mutation that destabilizes these deactivated states is shown to largely suppress the first component in voltage-activation curves for both ΔPASCap and E600R channels. It is also shown that stimulating calcium entry into the oocytes with ionomycin and thapsigargin, which is assumed to enhance CaM-dependent modulation, results in preferential potentiation of the first component in ΔPASCap and E600R, and this potentiation is attenuated by including an additional mutation that disfavors deeply closed states where voltage sensors are (mostly) deactivated. Together, these results are interpreted as an indication that calcium-CaM preferentially stabilizes O1 in mutant channels, thus favoring activation, whereas in WT channels lacking occupancy of O1, CaM stabilizes closed states and is therefore inhibitory. Moreover, it is found that the potentiation of ΔPASCap and E600R by CaM is more strongly attenuated by mutations in the channel that disrupt interaction with the C-terminal lobe of CaM than mutations affecting interaction with the N-terminal lobe. Finally, a mathematical model is proposed consisting of two layers involving two activation steps for the voltage sensor, and one conformational change in the cytoplasmic gating ring - completion of both sets of conformational changes is required to access state O2, but accessing state O1 only requires completion of the first voltage-sensor activation step in the four subunits. The model qualitatively reproduces most major findings on the mutants.

There are several concerns associated with the analysis and interpretations that are provided. First, the conductance-voltage (G-V) relations for the mutants do not seem to saturate, and the absolute open probability is not quantified for any mutant under any condition. This makes it impossible to quantitatively compare the relative amplitudes of the two components because the amplitude of the second component remains undetermined. This makes it challenging to interpret results involving perturbations that affect the relative occupancy of O1 and O2, such as those in Figures 2, 6, and 7, and also raises concerns about the extent to which model parameters can be constrained. This issue is made even more serious by the observation that the currents in both key mutants (ΔPASCap and E600R) are extremely slow and do not appear to reach steady-state over the intervals that are studied. This reduces confidence in the parameters associated with G-V relations, as the shape and position of both components might change significantly if longer pulses were used. This is not addressed or acknowledged in the manuscript. Further, because the mutant channel currents do not saturate at the most positive potentials and time intervals examined, the kinetic characterization based on reaching 80% of the maximum seems inappropriate, because the 100% mark is arbitrary. Further, the kinetics for some of the other examined mutants (e.g. those in Fig. 2A) are not shown, making it difficult to assess the extent to which the data could be affected by having been measured before full equilibration. There are additional aspects associated with gating kinetics that are not appropriately explored. For example, I would expect that the enhanced current amplitudes from Figure 5 are only transient, ultimately reaching a smaller steady-state current magnitude that depends only on the stimulation voltage and is independent of the pre-pulse. The entire time course including the rise-time and decay is not examined experimentally. This raises concern on whether occupancy of state O1 might be overestimated under some experimental conditions if a fraction of the occupancy is only transient. The mathematical model is not utilized to examine some of these slower relaxations - this may be because the model does not reproduce these slow processes, which would represent a serious shortcoming given that the slow kinetics appear to be intrinsic to transitions around state O1. The significance of the results with the Δ2-10.L341Split is unclear. First, structural as well as functional data has established that the coupling of the voltage sensor and pore does not entirely rely on the S4-S5 linker, and thus the Split construct could still retain coupling through other mechanisms, which is consistent with the prominent voltage dependence that is observed. If both state O1 and O2 require voltage sensor activation, it is unclear why the Split construct would affect state O1 primarily, as suggested in the manuscript, as opposed to decreasing occupancy of both open states.

The figure legends and text do not describe which solutions exactly were utilized for each experiment, and the rationale for choosing some solutions over others is not properly explained. The reversal potential for solutions used to measure voltage-activation curves falls right at the spot where occupancy of the first component peaks (e.g. see Figure 1B). Because no zero-current levels are shown on the current traces, it becomes very hard to determine which voltages correspond to each of the currents (see Fig. 1A). It is unclear whether any artifacts could have been introduced to the mutant activation curves at voltages close to the reversal potential. One key assumption that is not well-supported by the data pertains to the difference in single-channel conductance between states O1 and O2 - no analysis or discussion is provided on whether the data could also be well described by an alternative model in which O1 and O2 have the same conductance. No additional experimental evidence is provided related to the difference in conductance, which represents a key aspect of the mathematical model utilized to interpret the data. The CaM experiments are potentially very interesting and could have wide physiological relevance. However, the approach utilized to activate CaM is indirect and could result in additional non-specific effects on the oocytes that could affect the results.

The description of the mathematical model that is provided is difficult to follow, and some key aspects are left unclear, such as the precise states from which state O1 can be accessed, and whether there is any direct connectivity between states O1 and O2 - different portions of the text appear to give contradictory information regarding these points. Several rate constants other than those explicitly mentioned to represent voltage sensor activation are also assigned a voltage dependence - the mechanistic basis of that voltage dependence is unclear. Finally, a clear mechanistic explanation for the full range of effects that the ΔPASCap and E600R mutants have on channel function is lacking, as well as a detailed description of how those newly uncovered transitions would influence the activity of the WT channel; this latter point is important when considering whether the findings in the manuscript advance our understanding of the gating mechanism of Kv10 channels in general, or are specific to the particular mutants that are studied. It is unclear, for example, how both the mutation or the deletion at the cytoplasmic gating ring enable conduction by state O1, especially when considering the hypothesis put forward in this study that transition to O1 exclusively involves transitions by the voltage sensor and not the cytoplasmic gating ring. It is also not clearly described whether a non-conducting state with the equivalent state-connectivity as O1 can be accessed in WT channels, or if a state like O1 can only be accessed in the mutant channels. Importantly, if a non-conducting state with the same connectivity to O1 were to be accessed in WT channels, it would be expected that an alternating pulse protocol as in Fig. 4 would result in progressively decreasing currents as the occupancy of the non-conducting state equivalent to O1 is increased. Because this is not the case, it means that mutation and deletion cause additional perturbations on the gating energetics relative to WT, which are not clearly fleshed out.

Reviewer #1 (Public Review):

Summary:<br /> Human Abeta42 inhibits gamma-secretase activity in biochemical assays.

Strengths:<br /> Determination of inhibitory concentration human Abeta42 on gamma-secretase activity in biochemical assays.

Weaknesses:<br /> Human Abeta42 may concentrate up to microM order in endosomes. If so, production of Abeta42 would be attenuated then lead to less Abeta deposition in the brain. The authors finding is interesting but does not fit the physiological condition in the brain.<br /> It is not clear whether the FRET-based assay in living cells really reflect gamma-secretase activity.<br /> Processing of APP-CTF in living cells is not only the cleavage by gamma-secretase.

https://www.dropbox.com/s/5f4aimdsn1a3y1p/miller%20-%201996%20-%20Modal%20Jazz%20Composition%20%26%20Harmony%20Vol.%201.pdf?dl=0

MODAL JAZZ COMPOSlTlON & HARMONY Miller, R 1996

Reviewer #1 (Public Review):

In this manuscript, Tian et al. describe a novel modified version of the pro-drug triptolide, CK21, and provide evidence for its improved pharmacokinetics and its safety and efficacy in multiple xenograft models of pancreatic cancer. The authors performed transcriptomic analysis upon CK21 treatment which revealed that downregulation of NF-kB and mitochondrial dysfunction induce apoptosis and therefore lead to tumor regression. Downregulation of NF-kB and induction of apoptosis was then validated in vitro and in vivo. These findings have potential clinical significance as the efficacy of CK21 in preclinical PDAC models is compelling. However, there are also some limitations to their experiments and more validation studies are necessary to strengthen their findings regarding the mechanism of action of the drug. Specifically, the authors suggest that mitochondrial dysfunction is responsible for the observed apoptosis; however, this is not demonstrated. Additionally, side-by-side comparisons to other clinical triptolide analogs to show CK21 is at least as efficacious as other analogs in vivo would be valuable, especially since other analogs have been shown to synergize with conventional chemotherapy in PDAC mouse models, whereas CK21 does not appear to. Moreover, assessing whether CK21 is efficacious in syngeneic orthotopic PDAC models is critical, especially since CK21 was shown to have an impact on NF-KB which plays a major role in the immune compartment and triptolide has been shown to be immunosuppressive.

Reviewer #1 (Public Review):

Ruesseler and colleagues combine careful paradigm design, psychophysical and EEG analyses to determine whether information leakage during decision formation is strategically adjusted to meet changing task demands. Participants made motion direction judgments that required monitoring a continuous stream of dot motion for 'response periods' characterised by a sustained period of coherent motion in a leftward or rightward direction. Coherence was modulated on a frame-to-frame basis throughout the task furnishing a parametric regressor that could be used to interrogate the longevity of sensory samples in the decision process and their influence on corresponding EEG signals. Participants completed the task under varying conditions of response period length and frequency. Psychophysical kernel analyses suggest that sensory samples had a more short-lived impact on the participants' choices when response periods were rare, suggestive of greater information leakage. When the stimulus perturbations were regressed against the EEG data, it highlighted a centro-parietal component that showed increased responsiveness to large shifts in evidence when those shifts were more rare, suggestive of a role in representing surprise. An additional triphasic component was found to correlate with the time constant of integration as estimated from the kernel analyses.

This is a very timely paper that addresses an important and difficult-to-address question in the decision-making field - the degree to which information leakage can be strategically adapted to optimise decisions in a task-dependent fashion. The authors apply a sophisticated suite of analyses that are appropriate and yield a range of very interesting observations. The paper centres on analyses of one possible model that hinges on certain assumptions about the nature of the decision process for this task which raises questions about whether leak adjustments are the only possible explanation for the current data. I think the conclusions would be greatly strengthened if they were supported by the application and/or simulation of alternative model structures.

The behavioural trends when comparing blocks with frequent versus rare response periods seem difficult to tally with a change in the leak. The greater leak should result in a reduction in the rate of false alarms yet no significant differences were observed between these two conditions. Meanwhile, false alarms did vary as a function of short/long target durations which did not show any leak effect in the psychophysical kernel analyses. Are there other models that could reproduce such effects? For example, could a model in which the drift rate varies between Rare and Frequent trials do a similar or better job of explaining the data? This ties in to a related query about the nature of the task employed by the authors. Due to the very significant volatility of the stimulus, it seems likely that the participants are not solely making judgments about the presence/absence of coherent motion but also making judgments about its duration (because strong coherent motion frequently occurs in the inter-target intervals). If that is so, then could the Rare condition equate to less evidence because there is an increased probability that an extended period of coherent motion could be an outlier generated from the noise distribution? Note that a drift rate reduction would also be expected to result in fewer hits and slower reaction times, as observed.

Some adjustment of the language used when discussing FAs seems merited. If I have understood correctly, the sensory samples encountered by the participants during the inter-response intervals can at times favour a particular alternative just as strongly (or more strongly) than that encountered during the response interval itself. In that sense, the responses are not necessarily real false alarms because the physical evidence itself does not distinguish the target from the non-target. I don't think this invalidates the authors' approach but I think it should be acknowledged and considered in light of the comment above regarding the nature of the decision process employed on this task.

The authors report that preparatory motor activity over central electrodes reached a larger decision threshold for RARE vs. FREQUENT response periods. It is not clear what identifies this signal as reflecting motor preparation. Did the authors consider using other effector-selective EEG signatures of motor preparation such as beta-band activity which has been used elsewhere to make inferences about decision bounds? Assuming that this central ERP signal does reflect the decision bounds, the observation that it has a larger amplitude at the response on Rare trials appears to directly contradict the kernel analyses which suggest no difference in the cumulative evidence required to trigger commitment.

P11, the "absolute sensory evidence" regressor elicited a triphasic potential over centroparietal electrodes. The first two phases of this component look to have an occipital focus. The third phase has a more centroparietal focus but appears markedly more posterior than the change in evidence component. This raises the question of whether it is safe to assume that they reflect the same process.

Reviewer #1 (Public Review):

The paper first demonstrates that heat-killed bacteria show little DAF-16 activation compared to live food. Of note, daf-16 survival is longer than WT when fed HK bacteria, giving important insights into the lethality of these mutants. Leakiness of the gut is assessed, which is induced by age and exacerbated by daf-16 mutation. The authors then go on to identify indole as the causal bacterial compound to drive daf-16 nuclear localization. The indole effect is fully daf-16 dependent. In searching for the indole sensor in the worm, TRPA-1 is identified and the authors argue that indole is sensed in neurons to modulate gut DAF-16. Closing the circle, lys genes are identified whose expression is upregulated by daf-16 and indole, and which are required to control bacterial growth in the gut with aging.

Reviewer #1 (Public Review):

The strongest aspect of the study is the identification of the probable Ric-8A/NCS-1 interface through the crystal structures of NCS-1 complexed with candidate peptide mimetics from Ric-8A. However, since the structures involve peptides, it is critical to validate this interface with mutational analysis of the full-length or truncated Ric-8A. Furthermore, the evidence for the complex structure based on cryo-EM reconstruction is weak. The low resolution does not allow for reliable modeling of the complex. Two analyses may support the authors' main conclusions: a) validation of the interface with mutational analysis of Ric-8A, and b) new optimized sample/grid preparation for cryo-EM data collection.

Reviewer #1 (Public Review):

In this study, the authors characterize regulatory control of embryonic genome activation in the allotetraploid, Xenopus laevis. By characterizing transcription from its L and S subgenomes, they determine that homeologous genes are differentially activated in the early embryo. It has recently been appreciated that homeologs may be differentially expressed in later embryonic development (Session and Rokhsar, Nature 2016). However, an unanswered question is whether vertebrate tetraploid genomes undergo differential induction at the onset of the major wave of zygotic genome activation (ZGA). This is a fertile area for research, that enables the study of gene regulatory network adaptations to changes in ploidy, limited by the constraints of gene dosage and an essential early developmental transition. Xenopus laevis, which recently underwent a tetraploidization event, approximately 18 million years ago, provides a very useful model embryonic system for the study of homeologous gene activation during vertebrate ZGA.

To characterize differential subgenome activation the authors focused on the ~ 2600 maternally-regulated genes expressed in the first wave of widespread ZGA. They treated embryos with cycloheximide at Stage 8 to prevent the translation of zygotic factors that would further alter the transcriptome. They found a majority of these maternally-regulated genes have asymmetric expression between the two homeologs, with transcription often occurring from the L or S copy alone. This is a fascinating result from which to dig deeper into gene regulatory mechanisms. To understand whether cis-regulatory networks dictate the biased L/S homeolog expression in the late blastula, the authors performed CUT&RUN to map active chromatin marks, H3K4me3 and H3K27ac. However, they found no differences in promoter sequences of homeologs that would implicate differential recruitment of specific transcription factors. Instead, they focused on distal enhancers and additionally performed ATAC-seq on Stage 8 and 9 animal cap explants. Approximately 70% of enhancers for homeolog pairs exhibited differential H3K27ac enrichment and chromatin accessibility. The authors then searched for transcription factor binding motifs that distinguished active enhancers from their inactive homeolog. They found binding sequences for OCT4 and SOX2/3 were enriched in active L enhancers and active S enhancers. To assess the role of these pluripotency factors, they used antisense morpholinos to block their translation in the early embryo. MOs were complementary to both the L and S homeologs of pou5f3.3 and sox3, but not to their paralogs that are primarily expressed zygotically; pou5f3.1 and pou5f3.2. MO knockdown of both Pou5f3.3 and Sox3 was inhibited leading to significant downregulation of 62% of activated genes compared to embryos injected with a control morpholino. They also analyzed binding to the genome of V5-tagged, injected versions of these 2 transcription factors and found some evidence for differential binding around TSS of homeolog pairs and a correlation between binding and the overall level of transcription at ZGA. Finally, they compare enhancer marks and accessibility in tetraploid X.laevis subgenomes to homologous enhancers in the diploid X.tropicalis. They conclude conservation of active enhancers with X.tropicalis and even zebrafish when considering the combined data from X.laevis L and S subgenome.

There are many strengths of this manuscript. In this interesting study, the authors identify what appears to be an evolutionary divergence of enhancers in a vertebrate tetraploid, that may underlie the differential expression of homeologs during the first major wave of ZGA. They generate CUT&RUN datasets of active chromatin marks during the early and late blastula. Additionally, they provide binding data for pluripotency factors OCT4 and SOX2/3 and demonstrate that their MO knockdown leads to reduced expression at ZGA. Their analyses identify correlations between differential homeolog expression and active or accessible chromatin. Further, they identify that active enhancers are enriched in OCT4 and SOX2/3. Enthusiasm is somewhat dampened by a lack of direct perturbation to differential subgenome activation or an understanding of the functional impacts of differential homeolog expression on subsequent development.

Reviewer #1 (Public Review):

The study by Akter et al demonstrates that astrocyte-derived L-lactate plays a key role in schema memory formation and promotes mitochondrial biogenesis in the Anterior Cingulate Cortex (ACC).

The main tool used by the authors is the DREADD technology that allows to pharmacologically activate receptors in a cell-specific manner. In the study, the authors used the DREADD technique to activate appropriately transfected astrocytes, a subtype of muscarinic receptor that is not normally present in cells. This receptor being coupled to a Gi-mediated signal transduction pathway inhibiting cAMP formation, the authors could demonstrate cell-(astrocyte) specific decreases in cAMP levels that result in decreased L-lactate production by astrocytes.

Behaviorally this pharmacological manipulation results in impairments of schema memory formation and retrieval in the ACC in flavor-place paired associate paradigms. Such impairments are prevented by co-administration of L-lactate.

The authors also show that activation of Gi signaling resulting in L-lactate decreased release by astrocytes impairs mitochondrial biogenesis in neurons in an L-lactate reversible manner.

By using MCT 2 inhibitors and an NMDAR antagonist the authors conclude that the molecular mechanisms underlying the observed effects are mediated by L-lactate entering neurons through MCT2 transporters and involve NMDAR.

Overall, the article's conclusions are warranted by the experimental evidence, but some weak points could be addressed which would make the conclusions even stronger.

The number of animals in some of the experiments is on the low side (4 to 6).<br /> The use of CIN to inhibit MCT2 is not optimal. Authors may want to decrease MCT2 expression by using antisense oligonucleotides.<br /> The experiment using AVP to block NMDAR only partially supports the conclusions. Indeed, blocking NMDAR will knock down any response that involves these receptors, whether L-lactate is necessary or not.<br /> Is inhibition of glycogenolysis involved in the observed effects mediated by Gi signaling? Indeed, L-lactate is formed both by glycolysis and glycogenolysis. The authors could test whether the glycogen metabolism-inhibiting drug DAB would mimic the effects of Gi activation.

Reviewer #1 (Public Review):

Zou et al. employ single-cell RNA sequencing of healthy skin, actinic keratosis (AK), squamous cell carcinoma in situ (SCCIS), and cutaneous squamous cell carcinoma (cSCC) to unravel the molecular events driving the progression of AK into cSCC (n=13 samples from 6 patients), thereby filling a gap of knowledge in skin cancer research. The authors identified several previously unreported candidate genes (including ALDH3A1, IGFBP2, MAGEA4, ITGA6, and LGALS1) involved in different stages of malignant progression, the expression of which was validated in situ in a large cohort. Functional in vitro experiments confirm a possible role for these genes in the transformation from benign to malignant skin lesions.

Moreover, the authors identified epidermal cell subpopulations that may play an important role in the development from AK to cSCC, including an "early malignant cell" subpopulation within SCCIS basal cells with higher mutational load according to CNV analysis, which they characterized in more detail. For example, they found MAGEA4 strongly expressed in basal cells of (most) SCCIS and cSCC, as well as ITGA6. Functional assays in HaCaT and cSCC cell lines revealed that the knock-down of MAGEA4 and ITGA6 reduced proliferation, migration, and invasion but increased apoptosis in the cSCC cell lines.

Finally, they describe the tumor microenvironment of a poorly differentiated cSCC sample, and scATAC sequencing of this poorly differentiated cSCC revealed that the majority of differentially accessible chromatin regions (DARs) were located in basal epidermal cells.

Altogether, the authors provide a comprehensive transcriptional analysis of premalignant (AK, SCCIS) and malignant stages of cSCC. They suggest some key driver genes for each stage, the role of which are addressed in vitro and in situ in a large cohort. Thus, this study may provide novel biomarkers for tumor staging and diagnosis as well as potential targets for the prevention and treatment of cSCC.

Reviewer #1 (Public Review):

Zhao et al. investigated the molecular nature of the binding site for carbohydrates within the UDP-sugars known to activate the P2Y14 receptor. In order to do so, they built a molecular model of the hP2Y14, docked the corresponding agonists, and performed MD simulation on the resulting complexes. The modeling was used to identify the key molecular interactions with a cluster of charged residues in the extracellular side of the TM region of the receptor, which they show are conserved within the P2Y receptors. The binding site of the UDP region was, not surprisingly, overlapping with the analogous ADP binding site experimentally observed for the P2Y12 receptor, and consequently, the region that recognizes the sugars could be anticipated. Nevertheless, the detailed modeling and simulation work shows the consistency of this hypothesis and provides a quantification of the particular interactions involved, pinpointing specifically the residues candidate to be involved in the recognition of sugars.

It follows the characterization, by functional assays, of the effect of single-point mutations of these residues in the efficacy of the different UDP-sugars. Here the results show a tendency to correlate with the molecular models, however some of the data has very low statistical significance and consequently the interpretation and conclusions extracted from this data should be taken with caution. This pertains to the particular role of the identified residues in the binding of the different sugars, which in some cases should be taken as a suggestion rather than a proof, though the general conclusion of the identification of the binding region for the sugar, its conservation among P2Y receptors and the role of some specific residues in sugar recognition seems convincing and the data are conveniently presented.

Finally, the design of ADP-sugars that activate the P2Y12 receptor, based on the transferability of the observations with the UDP-sugars for the P2Y14 receptor, is a first indication that such a recognition is possible and should happen in an analogous binding region. However, the low potencies exhibited by the ATP-sugars, in the micromolar range, are too far from the ATP agonist and the relevance of this mechanism remains to be proved. The difference between P2Y12 and P2T14, with the last one showing much higher potencies for UDP-sugar derivatives than P2Y12 for the corresponding ADP-sugars, remains an interesting question not explored in this manuscript.

Reviewer #1 (Public Review):

Identifying compounds that can selectively inhibit protein kinases is of significant importance. Here, the authors describe a computational method to use existing kinome-wide profiling data to identify sets of compounds that, when combined, are more selective than any of the compounds on their own.

The authors explain the methodology well and the methodology is well-supported. The outcome of the methodology is assessed using an assay orthogonal to the original profiling assays. It is hard to assess whether the methodology works when a different assay is used.

The discussion of using this method for polypharmacology is naively discussed and under-supported.

Joint Public Review

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

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

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

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

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

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

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

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

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

Reviewer #1 (Public Review):

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

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

The experiments are clearly described and interpreted.

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

Reviewer #1 (Public Review):

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

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

Reviewer #1 (Public Review):

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

Major Concerns:

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

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

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

Reviewer #1 (Public Review):

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

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

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

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

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

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

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

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

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

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

Reviewer #1 (Public Review):

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

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

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

Reviewer #1 (Public Review):

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

Reviewer #1 (Public Review):

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

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

Reviewer #1 (Public Review):

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

Reviewer #1 (Public Review):

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

Reviewer #1 (Public Review):

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

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

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

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

Joint Public Review:

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

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

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

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

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

Reviewer #1 (Public Review):

Summary:

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

Strengths:

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

Weaknesses:

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

Reviewer #1 (Public Review):

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

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

Joint Public Review:

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

Reviewer #1 (Public Review):

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

Joint Public Review:

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

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

Reviewer #1 (Public Review):

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

Joint Public Review:

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

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

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

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

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

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

Reviewer #1 (Public Review):

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

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

Reviewer #1 (Public Review):

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

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

Other comments:

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

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

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

Reviewer #1 (Public Review):

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

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

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

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

Reviewer #1 (Public Review):

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

Joint Public Review:

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

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

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

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

Reviewer #1 (Public Review):

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

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

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

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

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

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

Reviewer #1 (Public Review):

Summary:

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

Strengths:

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

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

Weaknesses:

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

Reviewer #1 (Public Review):

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

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

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

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

Reviewer #1 (Public Review):

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

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

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

Reviewer #1 (Public Review):

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

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

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

Reviewer #1 (Public Review):

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

Reviewer #1 (Public Review):

Summary:

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

Strengths:

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

Weaknesses:

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

Reviewer #1 (Public Review):

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

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

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

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

Reviewer #1 (Public Review):

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Reviewer #1 (Public Review):

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

Reviewer #1 (Public Review):

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

Comments on current version:

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

Reviewer #1 (Public Review):

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

Reviewer #1 (Public Review):

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

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

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

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

Reviewer #1 (Public Review):

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

Reviewer #1 (Public Review):

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

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

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

Reviewer #1 (Public Review):

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

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

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

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

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

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

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

Reviewer #1 (Public Review):

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

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

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

Reviewer #1 (Public Review):

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

I have two main comments:

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

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

Reviewer #1 (Public Review):

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

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

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

DOI: 10.7554/eLife.86670

Resource: (ZFIN Cat# ZDB-ALT-090324-1,RRID:ZFIN_ZDB-ALT-090324-1)

Curator: @evieth

SciCrunch record: RRID:ZFIN_ZDB-ALT-090324-1

What is this?

DOI: 10.7554/eLife.86670

Resource: (ZFIN Cat# ZDB-ALT-090324-1,RRID:ZFIN_ZDB-ALT-090324-1)

Curator: @evieth

SciCrunch record: RRID:ZFIN_ZDB-ALT-090324-1

What is this?

DOI: 10.7554/eLife.86670

Resource: (ZFIN Cat# ZDB-ALT-100402-1,RRID:ZFIN_ZDB-ALT-100402-1)

Curator: @evieth

SciCrunch record: RRID:ZFIN_ZDB-ALT-100402-1

What is this?

...as long as one disregards the body of the unborn human being. 🙄

"Whether to murder your own defenseless offspring"

Reviewer #1 (Public Review):

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

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

Reviewer #1 (Public Review):

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

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

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

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

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

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

Reviewer #1 (Public Review):

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

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

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

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

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

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

Reviewer #1 (Public Review):

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

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

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

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

Reviewer #1 (Public Review):

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

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

Reviewer #1 (Public Review):

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

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

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

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

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

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

Reviewer #1 (Public Review):

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

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

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

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

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

Reviewer #1 (Public Review):

This is a clear account of some interesting work. The experiments and analyses seem well done and the data are useful. It is nice to see that VSDI results square well with those from prior extracellular recordings. But the work may be less original than the authors propose, and their overall framing strikes me as odd. Some additional clarifications could make the contribution more clear.

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

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

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

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

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

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

Reviewer #1 (Public Review):

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

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

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

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

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

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

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

Reviewer #1 (Public Review):

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

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

Reviewer #1 (Public Review):

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

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

Reviewer #1 (Public Review):

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

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

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

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

Reviewer #1 (Public Review):

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

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

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

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

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

Reviewer #1 (Public Review):

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

Reviewer #1 (Public Review):

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

Reviewer #1 (Public Review):

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

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

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

Reviewer #1 (Public Review):

Summary:

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

Strengths:

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

Weaknesses:

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

Hmm this seems strange. Can you explain how this was calculated?

Reviewer #1 (Public Review):

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

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

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

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

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

Reviewer #1 (Public Review):

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

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

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

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

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

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

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

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

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

Reviewer #1 (Public Review):

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

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

The following points should be addressed:

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

Reviewer #1 (Public Review):

Summary:

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

Strengths:

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

Weaknesses:

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

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

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

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

Reviewer #1 (Public Review):

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

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

Comments on latest version:

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

Reviewer #1 (Public Review):

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

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

Comments on the latest version:

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

Reviewer #1 (Public Review):

Summary:

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

Strengths:

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

Weaknesses:

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

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

Reviewer #1 (Public Review):

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

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

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