Reviewer #2 (Public review):

The goal of HiJee Kang et al. in this study is to explore the interaction between assemblies of neurons with similar pure-tone selectivity in mouse auditory cortex. Using holographic optogenetic stimulation in a small subset of target cells selective for a given pure tone (PTsel), while optically monitoring calcium activity in surrounding non-target cells, they discovered a subtle rebalancing process: co-tuned neurons that are not optogenetically stimulated tend to reduce their activity. The cortical network reacts as if an increased response to PTsel in some tuned assemblies is immediately offset by a reduction in activity in the rest of the PTsel-tuned assemblies, leaving the overall response to PTsel unchanged. The authors show that this rebalancing process affects only the responses of neurons to PTsel, not to other pure tones. They also show that assemblies of neurons that are not selective for PTsel don't participate in the rebalancing process. They conclude that assemblies of neurons with similar pure-tone selectivity must interact in some way to organize this rebalancing process, and they suggest that mechanisms based on homeostatic signaling may play a role.

The authors have successfully controlled for potential artefacts resulting from their optogenetic stimulation. This study is therefore pioneering in the field of the auditory cortex (AC), as it is the first to use single-cell optogenetic stimulation to explore the functional organization of AC circuits in vivo. The conclusions of this paper are very interesting. They raise new questions about the mechanisms that could underlie such a rebalancing process.

(1) This study uses an all-optical approach to excite a restricted group of neurons chosen for their functional characteristics (their frequency tuning), and simultaneously record from the entire network observable in the FOV. As stated by the authors, this approach is applied for the first time to the auditory cortex, which is a tour de force. However, such approach is complex and requires precise controls to be convincing. The authors provide important controls to demonstrate the precise ability of their optogenetic methods. In particular, holographic patterns used to excite 5 cells simultaneously may be associated with out-of-focus laser hot spots. Cells located outside of the FOV could be activated, therefore engaging other cells than the targeted ones in the stimulation. This would be problematic in this study as their tuning may be unrelated to the tuning of the targeted cells. To control for such effect, the authors have decoupled the imaging and the excitation planes, and checked for the absence of out-of-focus unwanted excitation (Suppl Fig1).

(2) In the auditory cortex, assemblies of cells with similar pure-tone selectivity are linked together not only by their ability to respond to the same sound, but also by other factors. This study clearly shows that such assemblies are structured in a way that maintains a stable global response through a rebalancing process. If a group of cells within an assembly increases its response, the rest of the assembly must be inhibited to maintain the total response.<br /> One surprising result is the clear boundary between assemblies: a rebalancing process occurring in one assembly does not affect the response in another assembly comprising cells tuned to a different frequency. However, this is slightly challenged by the data shown in Figure 3.

Figure 3B-left, for example, shows that, compared to controls, non-target 16 kHz-preferring neurons only decrease their response to a 16 kHz pure tone when the cells targeted by the opto stimulation also prefer 16 kHz, but not when the targeted cells prefer 54 kHz. However, the inverse is not entirely true. Again compared to controls, Figure 3B (right) shows that non-target 54 kHz-preferring neurons decrease their response to a 54 kHz pure tone when the targeted cells also prefer 54 kHz; however, they also tend to be inhibited when the targeted cells prefer 16 kHz.

The authors suggest this may be due to the partial activation of 54 kHz-preferring cells by 16 kHz tones and propose examining the response of highly selective neurons. The results are shown in Figure 3F. It would have been more logical to show the same results as in Figure 3B, but with the left part restricted to highly 16 kHz-selective cells and the right part to highly 54 kHz-selective cells. However, the authors chose to pool all responses to 16 kHz and 54 kHz tones in every triplet of conditions (control, opto stimulation on 16 kHz-preferring cells and opto stimulation on 54 kHz-preferring cells), which blurs the result of the analysis.

Reviewer #3 (Public review):

Summary:

Context - this is the 2nd review, of a manuscript that has already undergone some revisions.<br /> The manuscript explores ways to make self-amplifying RNA (saRNA) more silent through the inclusion of genes to inhibit the innate immune response. The readouts are predominantly expression and cell viability. They take a layered approach, adding multiple genes, as well as altering the capping of the anti-immune genes.

Strengths:

As described by the other reviewers, the authors take a stepwise approach to demonstrate that they can lead to sustained expression of the transgene.

Weaknesses:

The following weaknesses need some consideration

(1) The data show sustained expression, but do not directly show amplification. The amount of RFP is constantly decreasing over the time course. There is some evidence for the srIκBα-Smad7-SOCS1 construct. But measuring the RNA itself would be beneficial<br /> (2) The end construct is very large - it has 12 genes, this may have manufacturing considerations, affecting the translatability.

Reviewer #2 (Public review):

Summary:

The authors developed a cell-type specific fluorescence-tagging approach using a CRISPR/Cas9 induced spilt-GFP reconstitution system to visualize endogenous Bruchpilot (BRP) clusters as presynaptic active zones (AZ) in specific cell types of the mushroom body (MB) in the adult Drosophila brain. This AZ profiling approach was implemented in a high-throughput quantification process, allowing for the comparison of synapse profiles within single cells, cell types, MB compartments, and between different individuals. The aim is to analyse in more detail neuronal connectivity and circuits in this centre of associative learning. These are notoriously difficult to investigate due to the density of cells and structures within a cell. The authors detect and characterize cell-type-specific differences in BRP-dependent profiling of presynapses in different compartments of the MB, while intracellular AZ distribution was found to be stereotyped. Next to the descriptive part characterizing various AZ profiles in the MB, the authors apply an associative learning assay and detect consequent AZ re-organisation.

Strengths:

The strength of this study lies in the outstanding resolution of synapse profiling in the extremely dense compartments of the MB. This detailed analysis will be the entry point for many future analyses of synapse diversity in connection with functional specificity to uncover the molecular mechanisms underlying learning and memory formation and neuronal network logics. Therefore, this approach is of high importance for the scientific community and a valuable tool to investigate and correlate AZ architecture and synapse function in the CNS.

Weaknesses:

The results and conclusions presented in this study are, in many aspects, well-supported by the data presented. To further support the key findings of the manuscript, additional controls, comments, and possibly broader functional analysis would be helpful. In particular:

(1) All experiments in the study are based on spilt-GFP lines (BRP:GFP11 and UAS-GFP1-10). The Materials and Methods section does not contain any cloning strategy (gRNA, primer, PCR/sequencing validation, exact position of tag insertion, etc.) and only refers to a bioRxiv publication. It might be helpful to add a Materials and Methods section (at least for the BRP:GFP11 line). Additionally, as this is an on locus insertion the in BRP-ORF, it needs a general validation of this line, including controls (Western Blot and correlative antibody staining against BRP) showing that overall BRP expression is not compromised due to the GFP insertion and localizes as BRP in wild type flies, that flies are viable, have no defects in locomotion and learning and memory formation and MB morphology is not affected compared to wild type animals.

(2) Several aspects of image acquisition and high-throughput quantification data analysis would benefit from a more detailed clarification.

a) For BRP cluster segmentation it is stated in the Materials and Methods state, that intensity threshold and noise tolerance were "set" - this setting has a large effect on the quantification, and it should be specified and setting criteria named and justified (if set manually (how and why) or automatically (to what)). Additionally, if Pyhton was used for "Nearest Neigbor" analysis, the code should be made available within this manuscript; otherwise, it is difficult to judge the quality of this quantification step.

b) To better evaluate the quality of both the imaging analysis and image presentation, it would be important to state, if presented and analysed images are deconvolved and if so, at least one proof of principle example of a comparison of original and deconvoluted file should be shown and quantified to show the impact of deconvolution on the output quality as this is central to this study.

(3) The major part of this study focuses on the description and comparison of the divergent synapse parameters across cell-types in MB compartments, which is highly relevant and interesting. Yet it would be very interesting to connect this new method with functional aspects of the heterogeneous synapses. This is done in Figure 7 with an associative learning approach, which is, in part, not trivial to follow for the reader and would profit from a more comprehensive analysis.

a) It would be important for the understanding and validation of the learning induced changes, if not (only) a ratio (of AZ density/local intensity) would be presented, but both values on their own, especially to allow a comparison to the quoted, previous AZ remodelling analysis quantifying BRP intensities (ref. 17, 18). It should be elucidated in more detail why only the ratio was presented here.

b) The reason why a single instead of a dual odour conditioning was performed could be clarified and discussed (would that have the same effects?).

c) Additionally, "controls" for the unpaired values - that is, in flies receiving neither shock nor odour - it would help to evaluate the unpaired control values in the different MB compartments.

d) The temporal resolution of the effect is very interesting (Figure 7D), and at more time points, especially between 90 and 270 min, this might raise interesting results.

e) Additionally, it would be very interesting and rewarding to have at least one additional assay, relating structure and function, e.g. on a molecular level by a correlative analysis of BRP and synaptic vesicles (by staining or co-expression of SV-protein markers) or calcium activity imaging or on a functional level by additional learning assays

Reviewer #2 (Public review):

Summary:

This is an important study that examines the relationship between a Parkinson's 's-associated mutation in LRRK2 kinase and increased ERM phosphorylation in astrocytes, altered excitatory and inhibitory synapse density and function, and a reduction in astrocyte size. The scope is impressively large and includes human and mouse samples, and employs immunolabeling, whole cell patch clamp recording techniques, molecular manipulation in vivo, and BioID. Experiments have appropriate controls, and the outcomes are mostly convincing. The chief weakness is that the study emphasizes scope over depth, such that it falls short of a unifying model of LRRK2-ERM interactions and leave many outcomes difficult to interpret.

The main idea is that the G2019S Parkinson's mutation in LRRK2 increases its kinase activity and that this either directly or indirectly increases ERM phosphorylation. This excessive ERM phosphorylation is expected to occur within perisynaptic astrocytic processes, reduce astrocyte complexity, and reduce excitatory synapse density and function in ACC. Overexpression of a dominant negative ezrin (phospho-dead) in astrocytes restores their morphology and excitatory synapse density in ACC. This pathway is well supported if taken on its own. But several datapoints presented do not fit this model. The reasoning driving selectivity to ACC and not M1 is not discussed or pursued (is it relevant that pERM levels appear lower in M1 at P21? Do astrocytes in S1 from G2019S mice also show reduced territories?); the differential effects on excitatory versus inhibitory synapses does not fit the model (or is this effect also expected to lie downstream of astrocytes?). Importantly, the effects of ezrin manipulation in wildtype samples (see below) are not integrated into the model, perhaps because the data run counter to expectation.

Specific Concerns and Questions:

(1) Effects in wildtype mice are not fully incorporated into the model. Overexpressing (OE) WT ezrin appears to reduce pERM levels by about half (Figure 1i vs 4B). OE-phospho-dead ezrin also appears to reduce pERM integrated density compared to control levels (same figures). This is not discussed (see also item 2). OE phospho-dead ezrin decreases synapse density and maybe function compared to OE WT ezrin in wildtype mice (4C, 4F), but it is not clear whether or not these data differ from unmanipulated wildtype sections/slices (Figures 2 and 3) because the data are normalized. These synaptic findings in wildtype should also be joined to the morphology findings in wildtype astrocytes, where OE-phospho-dead ezrin reduces astrocyte territory similar to LRRK2-G2019S. The shared morphological outcome is discussed as a potential defect in ERM phospho/dephospho balance, but it was hard to see if this could be similarly related to changes in synapse density.

(2) Labeling for pERMs shown in wildtype mouse and control human is not convincing, but is convincing in the G2019S samples (e.g., Figure 1/S1, Figure 2) (although concentration in perisynaptic astrocytes is not clear). The data presented seem to better support the idea that the mutation confers a pathological gain of ERM phosphorylation (rather than hyperphosphorylation). If the faint labeling in wildtype and control samples is genuine, one would anticipate that pERM labeling would be different in shControl vs. shLrrk2 astrocytes.

(3) Given the data presented, it would seem that overexpressing the BirA2 ezrin construct, like wildtype ezrin, could impact astrocyte biology. If overexpressing a wildtype ezrin reduces pERM levels, then perhaps the BirA2 construct expression already favors a closed conformation. This is not so much a critique of the approach as a request for clarification and to include, if possible, whether there are reasons to believe or data to support that the BirA2 construct adopts both open and closed conformations.

Reviewer #2 (Public review):

Summary:

Park et al. have made a tool for spatiotemporally restricted knockout of the astrocytic GABA transporter GAT3, leveraging CRISPR/Cas9 and viral transduction in adult mice, and evaluated the effects of GAT3 on neural encoding of visual stimulation.

Strengths:

This concise manuscript leverages state-of-the-art gene CRISPR/Cas9 technology for knocking out astrocytic genes. This has only to a small degree been performed previously in astrocytes, and it represents an important development in the field. Moreover, the authors utilize in vivo two-photon imaging of neural responses to visual stimuli as a readout of neural activity, in addition to validating their data with ex vivo electrophysiology. Lastly, they use advanced statistical modeling to analyze the impact of GAT3 knockout. Overall, the study comes across as rigorous and convincing.

Weaknesses:

Adding the following experiments would potentially have strengthened the conclusions and helped with interpreting the findings:

(1) Neural activity is quite profoundly influenced by GAT3 knockout. Corroborating these relatively large changes to neural activity with in vivo electrophysiology of some sort as an additional readout would have strengthened the conclusions.

(2) Given the quite large effects on neural coding in visual cortex assessed på jRGECO imaging, it would have been interesting if the mouse groups could have been subjected to behavioral testing, assessing the visual system.

Reviewer #2 (Public review):

Summary:

Infants' auditory brain responses reveal processing of music (clearly different from shuffled music patterns) from the age of 3 months; however, they do not show a related increase in spontaneous movement activity to music until the age of 12 months.

Strengths:

This is a nice paper, well designed, with sophisticated analyses and presenting clear results that make a lot of sense to this reviewer. The additions of EEG recordings in response to music presentations at 3 different infant ages are interesting, and the manipulation of the music stimuli into shuffled, high, and low pitch to capture differences in brain response and spontaneous movements is good. I really enjoyed reading this work and the well-written manuscript.

Weaknesses:

I only have two comments. The first is a change to the title. Maybe the title should refer to the first "postnatal" year, rather than the first year of life. There are controversies about when life really starts; it could be in the womb, so using postnatal to refer to the period after birth resolves that debate.

The other comment relates to the 10 Principal Movements (PMs) identified. I was wondering about the rationale for identifying these different PMs and to what extent many PMs entered in the analyses may hinder more general pattern differences. Infants' spontaneous movements are very variable and poorly differentiated in early development. Maybe, instead of starting with 10 distinct PMs, a first analysis could be run using the combined Quantity of Movements (QoM) without PM distinctions to capture an overall motor response to music. Maybe only 2 PMs could be entered in the analysis, for the arms and for the legs, regardless of the patterns generated. Maybe the authors have done such an analysis already, but describing an overall motor response, before going into specific patterns of motor activation, could be useful to describe the level of motor response. Again, infants provide extremely variable patterns of response, and such variability may potentially hinder an overall effect if the QoM were treated as a cumulated measure rather than one with differentiated patterns.

Reviewer #2 (Public review):

This study explores the underlying causes of the generalized movement slowness observed in astronauts in weightlessness compared to their performance on Earth. The authors argue that this movement slowness stems from an underestimation of mass rather than a deliberate reduction in speed for enhanced stability and safety.

Overall, this is a fascinating and well-written work. The kinematic analysis is thorough and comprehensive. The design of the study is solid, the collected dataset is rare, and the model tends to add confidence to the proposed conclusions. That being said, I have several comments that could be addressed to consolidate interpretations and improve clarity.

Main comments:

(1) Mass underestimation

a) While this interpretation is supported by data and analyses, it is not clear whether this gives a complete picture of the underlying phenomena. The two hypotheses (i.e., mass underestimation vs deliberate speed reduction) can only be distinguished in terms of velocity/acceleration patterns, which should display specific changes during the flight with a mass underestimation. The experimental data generally shows the expected changes but for the 45{degree sign} condition, no changes are observed during flight compared to the pre- and post-phases (Figure 4). In Figure 5E, only a change in the primary submovement peak velocity is observed for 45{degree sign}, but this finding relies on a more involved decomposition procedure. It suggests that there is something specific about 45{degree sign} (beyond its low effective mass). In such planar movements, 45{degree sign} often corresponds to a movement which is close to single-joint, whereas 90{degree sign} and 135{degree sign} involve multi-joint movements. If so, the increased proportion of submovements in 90{degree sign} and 135{degree sign} could indicate that participants had more difficulties in coordinating multi-joint movements during flight. Besides inertia, Coriolis and centripetal effects may be non-negligible in such fast planar reaching (Hollerbach & Flash, Biol Cyber, 1982) and, interestingly, they would also be affected by a mass underestimation (thus, this is not necessarily incompatible with the author's view; yet predicting the effects of a mass underestimation on Coriolis/centripetal torques would require a two-link arm model). Overall, I found the discrepancy between the 45{degree sign} direction and the other directions under-exploited in the current version of the article. In sum, could the corrective submovements be due to a misestimation of Coriolis/centripetal torques in the multi-joint dynamics (caused specifically -or not- by a mass underestimation)?

b) Additionally, since the taikonauts are tested after 2 or 3 weeks in flight, one could also assume that neuromuscular deconditioning explains (at least in part) the general decrease in movement speed. Can the authors explain how to rule out this alternative interpretation? For instance, weaker muscles could account for slower movements within a classical time-effort trade-off (as more neural effort would be needed to generate a similar amount of muscle force, thereby suggesting a purposive slowing down of movement). Therefore, could the observed results (slowing down + more submovements) be explained by some neuromuscular deconditioning combined with a difficulty in coordinating multi-joint movements in weightlessness (due to a misestimation or Coriolis/centripetal torques) provide an alternative explanation for the results?

(2) Modelling

a) The model description should be improved as it is currently a mix of discrete time and continuous time formulations. Moreover, an infinite-horizon cost function is used, but I thought the authors used a finite-horizon formulation with the prefixed duration provided by the movement utility maximization framework of Shadmehr et al. (Curr Biol, 2016). Furthermore, was the mass underestimation reflected both in the utility model and the optimal control model? If so, did the authors really compute the feedback control gain with the underestimated mass but simulate the system with the real mass? This is important because the mass appears both in the utility framework and in the LQ framework. Given the current interpretations, the feedforward command is assumed to be erroneous, and the feedback command would allow for motor corrections. Therefore, it could be clarified whether the feedback command also misestimates the mass or not, which may affect its efficiency. For instance, if both feedforward and feedback motor commands are based on wrong internal models (e.g., due to the mass underestimation), one may wonder how the astronauts would execute accurate goal-directed movements.

b) The model seems to be deterministic in its current form (no motor and sensory noise). Since the framework developed by Todorov (2005) is used, sensorimotor noise could have been readily considered. One could also assume that motor and sensory noise increase in microgravity, and the model could inform on how microgravity affects the number of submovements or endpoint variance due to sensorimotor noise changes, for instance.

c) Finally, how does the model distinguish the feedforward and feedback components of the motor command that are discussed in the paper, given that the model only yields a feedback control law? Does 'feedforward' refer to the motor plan here (i.e., the prefixed duration and arguably the precomputed feedback gain)?

(3) Brevity of movements and speed-accuracy trade-off

The tested movements are much faster (average duration approx. 350 ms) than similar self-paced movements that have been studied in other works (e.g., Wang et al., J Neurophysiology, 2016; Berret et al., PLOS Comp Biol, 2021, where movements can last about 900-1000 ms). This is consistent with the instructions to reach quickly and accurately, in line with a speed-accuracy trade-off. Was this instruction given to highlight the inertial effects related to the arm's anisotropy? One may however, wonder if the same results would hold for slower self-paced movements (are they also with reduced speed compared to Earth performance?). Moreover, a few other important questions might need to be addressed for completeness: how to ensure that astronauts did remember this instruction during the flight? (could the control group move faster because they better remembered the instruction?). Did the taikonauts perform the experiment on their own during the flight, or did one taikonaut assume the role of the experimenter?

(4) No learning effect

This is a surprising effect, as mentioned by the authors. Other studies conducted in microgravity have indeed revealed an optimal adaptation of motor patterns in a few dozen trials (e.g., Gaveau et al., eLife, 2016). Perhaps the difference is again related to single-joint versus multi-joint movements. This should be better discussed given the impact of this claim. Typically, why would a "sensory bias of bodily property" persist in microgravity and be a "fundamental constraint of the sensorimotor system"?

Reviewer #2 (Public review):

Summary:

Chronic methamphetamine (METH) abuse leads to significant structural and functional deficits in the cortical and hippocampal regions in humans. However, the specific mechanisms underlying chronic METH-induced neurotoxicity in the hippocampus and its contribution to cognitive deficits remain poorly understood. The authors aim to address this knowledge gap using a single-cell transcriptomic atlas of the hippocampus under chronic METH exposure in mice. They present analyses of differential gene expression, cell-cell communication, pseudotemporal trajectories, and transcription factor regulation to characterize the cellular-level impact of METH abuse. However, the overall quality of the manuscript is currently very poor due to a lack of basic quality control, overly descriptive content, and unclear conclusions.

Strengths:

The major strength of this study is that it may represent the first report on the impact of METH on the hippocampus in mice. However, the authors should clarify whether similar studies have been previously conducted, as this point remains uncertain.

Weaknesses:

Despite this potential novelty, the study has numerous weaknesses. Notably, single-cell RNA sequencing was unable to capture an adequate number of neuronal populations. Neurons accounted for only approximately 0.6% of the total nuclei, representing a significant underrepresentation compared to their actual physiological proportion. Given that the behavioral effects of METH are likely mediated by neuronal dysfunction, readers would reasonably expect to see transcriptional changes in neurons. The authors should explain why they were unable to capture a sufficient number of neurons and justify how this incomplete dataset can still provide meaningful scientific insights for researchers studying METH-induced hippocampal damage and behavioral alterations.

Another significant weakness of this study is the lack of a cohesive hypothesis or overarching conclusion regarding how METH impacts neural populations. The authors provide a largely descriptive account of transcriptional alterations across various cell types, but the manuscript lacks clear, biologically meaningful conclusions. This descriptive approach makes it difficult for readers to identify the key findings or take-home messages. To improve clarity and impact, the authors should focus on developing and presenting a few plausible hypotheses or mechanistic scenarios regarding METH-induced neurotoxicity, grounded in their scRNA-seq data. Including schematic figures to illustrate these hypotheses would also help readers better understand and interpret the study.

The final major weakness of this study is its poor readability. It appears that the authors did not adequately proofread the manuscript, as there are numerous typographical errors (e.g., line 333: trisulting; line 756: essencial), unsupported scientific claims lacking citations (e.g., lines 485, 503, 749-753), and grammatically incorrect sentences (e.g., lines 470-472, 540-543, 749-753). In addition, many paragraphs are unorganized and overly descriptive, which further hinders clarity. Some figures are also problematic - too small in size and overcrowded with text in fonts that are difficult to read. It is recommended that the authors carry out quality control. There are too many typographical and grammatical errors to list individually; the authors should carefully review and revise the entire manuscript to address all of these issues.

Overall, this study could have offered some incremental new insights into neurotoxicity following chronic METH exposure, despite the poor capture of neuronal populations. However, the current manuscript feels more like a data dump than a thoughtfully constructed scientific narrative. I encourage the authors to extract and highlight meaningful biological insights from their dataset and clearly articulate these in the conclusion, ideally supported by an additional schematic figure. Furthermore, I strongly urge the authors to substantially improve the basic quality of the manuscript through careful proofreading and by seeking feedback from colleagues or other readers.

Reviewer #2 (Public review):

Summary:

This study uncovers an inhibitory pathway from the anterior cingulate cortex (ACC) to pyramidal cells in the superficial sublayer of hippocampal area CA1 (CA1sup). As ACC neuron spiking tends to precede hippocampal ripples, this presents the intriguing possibility that ACC inputs are selectively inhibiting particular CA1sup neurons, which could play a role in the reactivation of task-related ensembles known to take place during hippocampal ripples. Indeed, through a generalized linear model (GLM) analysis, the authors demonstrate that the ACC activity within the 200ms immediately preceding the ripple is predictive of the ripple content.

Strengths:

The biggest strength of the work is the optogenetic manipulation experiments, which convincingly demonstrate that stimulation of ACC pyramidal neurons activates an interneuron population with symmetric spike waveforms, and inhibits parvalbumin interneurons and pyramidal cells in CA1sup but not CA1deep sublayer.

An additional strength in the GLM analysis which consistently shows that ACC activity preceding the ripple is predictive of hippocampal activity during the ripple considerably more than in shuffled data for all cells and periods tested.

Weaknesses:

The major weakness of this work is that the link with learning and memory is not very well supported.

The only evidence of rebalancing and reorganization appears to be a single statistical test (the test in Figure 1f, p=0.013) demonstrating a decrease of the GLM prediction gain from pre-task sleep to post-task sleep; the same test is repeated for subsets of the data in the rest of the figures. As the idea of rebalancing and reorganization is central to the paper as currently written, exploring it through another measure, independent of the GLM prediction gain, should be expected. The notion that this pathway is suppressed in sleep following learning can be supported by demonstrating a decrease in any of the following measures: ACC spike-triggered average CA1sup responses, cross-covariances (Wierzynski et al 2009) between ACC and CA1sup cells in post-task sleep, or ripple-triggered cross-correlations (Sirota et al. 2009).

The differences between task-active and task-inactive neurons are not convincing. The separation between task-active and task-inactive neurons is to divide a distribution that is far from bimodal into what appears to be two arbitrary groups. Similarly, the authors divide cells relative to their prediction gain ("Top PG" and "Bottom PG" in Figure 2c), which fails to select for the population of significantly predicted cells (relative to the shuffle). Within CA1sup cells, after learning, there is a significant decrease in the prediction gain for "task-inactive" cells but not "task-active" cells, but it is important to keep in mind that the "task-active" group contains only 24 neurons, and there was no difference between the two groups of cells ("task-active" vs "task-inactive") when directly compared.

Finally, it is not clear whether the identity of the pathway-responsive CA1sup neurons is fixed or whether it may change with learning. A deeper analysis into the cell pair cross-correlations or the weights of the GLM analysis may reveal whether there is a reorganization of CA1sup responses (some cells that were inhibited are no longer inhibited, and vice versa) or a dampening (the same CA1sup cells are inhibited in both cases, but the inhibition is less-pronounced in post-task sleep). The possibility of a rigid circuit dampened immediately following fear conditioning, is not discussed by the authors.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors reported two studies where they investigated the context effect of hyperaltruistic tendency in moral decision-making. They replicated the hyperaltruistic moral preference in the gain domain, where participants inflicted electric shocks to themselves or another person in exchange for monetary profits for themselves. In the loss domain, such hyperaltruistic tendency abolished. Interestingly, oxytocin administration reinstated the hyperaltruistic tendency in the loss domain. The authors also examined the correlation between individual differences in utilitarian psychology and the context effect of hyperaltruistic tendency.

Strengths:

(1) The research question - the boundary condition of hyperaltruistic tendency in moral decision-making and its neural basis - is theoretically important.<br /> (2) Manipulating the brain via pharmacological means offers causal understanding of the neurobiological basis of the psychological phenomenon in question.<br /> (3) Individual difference analysis reveals interesting moderators of the behavioral tendency.

Weaknesses:

(1) The theoretical hypothesis needs to be better justified. There are studies addressing the neurobiological mechanism of hyperaltruistic tendency, which the authors unfortunately skipped entirely.<br /> (2) There are some important inconsistencies between the preregistration and the actual data collection/analysis, which the authors did not justify.<br /> (3) Some of the exploratory analysis seems underpowered (e.g., large multiple regression models with only about 40 participants).<br /> (4) Inaccurate conceptualization of utilitarian psychology and the questionnaire used to measure it.

Comments on revisions:

The authors have addressed the weakness in the second round of revision

Reviewer #2 (Public review):

Summary:

The authors aimed to find out how and how well adult and adolescent mice discriminate tones of different frequencies and whether there are differences in processing at the level of the auditory cortex that might explain differences in behavior between the two groups. Adolescent mice were found to be worse at sound frequency discrimination than adult mice. The performance difference between the groups was most pronounced when the sounds are close in frequency and thus difficult to distinguish and could, at least in part, be attributed to the younger mice' inability to withhold licking in no-go trials. By recording the activity of individual neurons in the auditory cortex when mice performed the task or were passively listening as well as in untrained mice the authors identified differences in the way that the adult and adolescent brains encode sounds and the animals' choice that could potentially contribute to the differences in behavior.

Strengths:

The study combines behavioural testing in freely-moving and head-fixed mice, optogenetic manipulation and high density electrophysiological recordings in behaving mice to address important open questions about age differences in sound-guided behavior and sound representation in the auditory cortex.

Weaknesses:

For some of the analyses that the authors conducted it is unclear what the rationale behind them is and, consequently, what conclusion we can draw from them.

Reviewer #2 (Public review):

Summary:

The study wanted to functionally identify individual DANs that mediate larval olfactory learning. Then search for DAN-specific driver strains that mark single dopaminergic neurons, which subsequently can be used to target genetic manipulations of those neurons. 56 GAL4 drivers identifying dopaminergic neurons were found (Table 1) and three of them drive the expression of GFP to a single dopaminergic neuron in the third-instar larval brain hemisphere. The DAN driver R76F02-AD;R55C10-DBD appears to drive the expression to a dopaminergic neuron innervating the lower peduncle (LP), which would be DAN-c1.

Split-GFP reconstitution across synaptic partners (GRASP) technique was used to investigate the "direct" synaptic connections from DANs to the mushroom body. Potential synaptic contact between DAN-c1 and MB neurons (at the lower peduncle) were detected.

Then single odor associative learning was performed and thermogenetic tools were used (Shi-ts1 and TrpA1). When trained at 34{degree sign}C, the complete inactivation of dopamine release from DAN-c1 with Shibirets1 impaired aversive learning (Figure 2h), while Shibirets1 did not affect learning when trained at room temperature (22 {degree sign}C). When paired with a gustatory stimulus (QUI or SUC), activation of DAN-c1 during training impairs both aversive and appetitive learning (Figure 2k).<br /> Then examined the expression pattern of D2R in fly brains and were found in dopaminergic neurons and the mushroom body (Figure 3). To inspect whether the pattern of GFP signals indeed reflected the expression of D2R, three D2R enhancer driver strains (R72C04, R72C08, and R72D03-GAL4) were crossed with the GFP-tagged D2R strain.

D2R knockdown (UAS-RNAi) in dopaminergic neurons driven by TH-GAL4 impaired larval aversive learning. Using a microRNA strain (UAS-D2R-miR), a similar deficit was observed. Crossing the GFP-tagged D2R strain with a DAN-c1-mCherry strain demonstrated the expression of D2R in DAN-c1 (Figure 4a). Knockdown of D2R in DAN-c1 impaired aversive learning with the odorant pentyl acetate, while appetitive learning was unaffected (Figure 4e). Sensory and motor functions appear not affected by D2R suppression.

To exclude possible chronic effects of D2R knockdown during development, optogenetics was applied at distinct stages of the learning protocol. ChR2 was expressed in DAN-c1, and blue light was applied at distinct stages of the learning protocol. Optogenetic activation of DAN-c1 during training impaired aversive learning, not appetitive learning (Figure 5b-d).

Knockdown of D2Rs in MB neurons by D2R-miR impaired both appetitive and aversive learning (Figure 6a). Activation of MBNs during training impairs both larval aversive and appetitive learning.

Finally, based on the data the authors propose a model where the effective learning requires a balanced level of activity between D1R and D2R (Figure 7).

Strengths:

The work is well written, clear, and concise. They use well documented strategies to examine GAL4 drivers with expression in a single DAN, behavioral performance in larvae with distinct genetic tools including those to do thermo and optogenetics in behaving flies. Altogether, the study was able to expand our understanding of the role of D2R in DAN-c1 and MB neurons in the larva brain.

The study successfully examined the role of D2R in DAN-c1 and MB neurons in olfactory conditioning. The conclusions are well supported by the data and the model of adequate levels of cAMP (Figure 7b) appears to be able to explain a poor memory after insufficient or excessive cAMP signaling. The study provides insight into the role of D2R in associative learning expanding our understanding and might be a reference similarly to previous key findings (Qi and Lee, 2014, https://doi.org/10.3390/biology3040831).

Reviewer #2 (Public review):

Summary:

In this study the authors described a previously developed set of VHH-based PET tracers to track transplants (cancer cells, embryo's) in a murine immune-competent environment.

Strengths:

Unique set of PET tracer and mouse strain to track transplanted cells in vivo without genetic modification of the transplanted cells. This is a unique asset and a first-in-kind.

Weaknesses:

None

Reviewer #2 (Public review):

This work by Pal et al. studied the relationship between protein expression noise and translational efficiency. They proposed a model based on ribosome demand to explain the positive correlation between them, which is new as far as I realize. Nevertheless, I found the evidence of the main idea that it is the ribosome demand generating this correlation is weak. Below are my major and minor comments.

Major comments:

(1) Besides a hypothetical numerical model, I did not find any direct experimental evidence supporting the ribosome demand model. Therefore, I think the main conclusions of this work are a bit overstated.

(2) I found that the enhancement of protein noise due to high translational efficiency is quite mild, as shown in Figure 6A-B, which makes the biological significance of this effect unclear.

(3) The captions for most of the figures are short and do not provide much explanation, making the figures difficult to read.

(4) It would be helpful if the authors could define the meanings of noise (e.g., coefficient of variation?) and translational efficiency in the very beginning to avoid any confusion. It is also unclear to me whether the noise from the experimental data is defined according to protein numbers or concentrations, which is presumably important since budding yeasts are growing cells.

(5) The conclusions from Figure 1D and 1E are not new. For example, the constant protein noise as a function of mean protein expression is a known result of the two-state model of gene expression, e.g., see Eq. (4) in Paulsson, Physics of Life Reviews 2005.

(6) In Figure 4C-D, it is unclear to me how the authors changed the mean protein expression if the translation initiation rate is a function of variation in mRNA number and other random variables.

(7) If I understand correctly, the authors somehow changed the translation initiation rate to change the mean protein expression in Figure 4C-D. However, the authors changed the protein sequences in the experimental data of Figure 6. I am not sure if the comparison between simulations and experimental data is appropriate.

Comments on revisions:

Updated Review: The authors have satisfactorily answered all of my questions and comments. The current manuscript is much clearer and stronger than the previous one. I do not have any other questions.

Reviewer #2 (Public review):

In this manuscript by Floeder et al., the authors report a correlation between ITI duration and the strength of a dopamine ramp occurring in the time between a predictive conditioned stimulus and a subsequent reward. They found this relationship occurring within two different tasks with mice, during both a Pavlovian task as well as an instrumental virtual visual navigation task. Additionally, they observed this relationship only in conditions when using a dynamic predictive stimulus. The authors relate this finding to their previously published model ANCCR in which the time constant of the eligibility trace is proportionate to the reward rate within the task.

The relationship between ITI duration and the extent of a dopamine ramp which the authors have reported is very intriguing and certainly provides an important constraint for models for dopamine function. As such, these findings are potentially highly impactful to the field.

Reviewer #2 (Public review):

Basson et al. present compelling evidence supporting a gender disparity in article submission to "elite" journals. Most notably, they found that women were more likely to avoid submitting to one of these journals based on advice from a colleague/mentor. Overall, this work is an important addition to the study of gender disparities in the publishing process.

I thank the authors for addressing my concerns.

Reviewer #2 (Public review):

Summary:

The manuscript employs serial block‐face electron microscopy (SBEM) and cryofixation to obtain high‐resolution, three‐dimensional reconstructions of Drosophila antennal sensilla containing olfactory receptor neurons (ORNs) that detect CO2. This method has been used previously by the same lab in Gonzales et. al, 2021. (https://elifesciences.org/articles/69896), and Zhang et. al, 2019 Nature Communications. The previous study by Zhang also correlated morphometric measurements from SBEM with asymmetric ephaptic activity for paired neurons using electrophysiology across multiple olfactory sensilla. This manuscript applies the same SBEM method to now characterize the ab1 sensillum which houses the ab1C, CO2 detecting neuron, but stops short of integration neuronal activity with structural variability.

The SBEM-based morphometric studies do however significantly advance preliminary observations from older two-dimensional TEM-based reports. Previous images of the putative CO2 neuron in Drosophila (Shanbhag et al., 1999) and in mosquitoes (McIver and Siemicki, 1975; Lu et al, 2007) reported that the dendritic architecture of the CO2 neuron was somewhat different (circular and flattened, lamellated) from other olfactory neurons in the antenna of insects. In this study, the authors confirm this different morphology but also classify it into distinct subtypes (loosely curled, fully curled, split, and mixed).

Strengths:

The study makes a convincing case that ab1C neurons exhibit a unique, dendritic morphology unlike the canonical cylindrical dendrites found in ab1D neurons. This observation extends previous qualitative TEM findings by not only confirming the presence of flattened lamellae in CO₂ neurons but also quantifying key morphometrics such as dendritic length, surface area, and volume, and calculating surface area-to-volume ratios. The enhanced ratios observed in the flattened segments are speculated to be linked to potential advantages in receptor distribution (e.g., Gr21a/Gr63a) and efficient signal propagation.

Weaknesses:

Although this quantitative approach is very robust compared to earlier reports, interpretations are somewhat limited by the absence of direct electrophysiological data to confirm whether ultrastructural differences translate into altered neuronal function. The biggest question remains unanswered: whether structural variation observed in the ab1C dendrites by SBEM have an electrophysiological functional relevance?

Surveys of ab1 sensillum with single-sensillum recordings (even a few from multiple Drosophila antenna) as they have done for ab2s and others in the past, would have measured spontaneous activity, spike amplitude, and response to CO2. This could have allowed for comparison of frequency of functional variation, if any, to structural variation and a discussion would therefore have strengthened the overall characterization. In the case of ab2 sensilla the authors find very little variance, could the ab1 also be the same? In the absence of this data, it becomes hard to speculate whether structural variation observed in the ab1C dendrites by SBEM have any functional relevance or whether they are simply random variations in dendrite development.

Additionally, artifacts could be a consideration, even though Cryofixation is superior to chemical fixation. Although this is hard to address, all types of fixations in TEMs cause some artifacts, as does serial sectioning. An understanding of the error rates for the SBEM method would have increased the confidence in the conclusions drawn. For example, what is the structural variation of SBEMs in the ab2 population, which shows very little electrophysiological variation? Can a comparison be done?

Reviewer #2 (Public Review):

Summary:

Millet et al. show that C. elegans systematically prefers easy-to-eat bacteria but will switch its choice when harder-to-eat bacteria are offered at higher densities, producing indifference points that fit standard economic discounting models. Detailed kinetic analysis reveals that this bias arises from unchanged patch-entry rates but significantly elevated exit rates on effortful food, and dop-3 mutants lose the preference altogether, implicating dopamine in effort sensitivity. These findings extend effort-discounting behavior to a simple nematode, pushing the phylogenetic boundary of economic cost-benefit decision-making.

Strengths:

(1) Extends the well-characterized concept of effort discounting into _C. elegans_, setting a new phylogenetic boundary and opening invertebrate genetics to economic-behavior studies.

(2) Elegant use of cephalexin-elongated bacteria to manipulate "effort" without altering nutritional or olfactory cues, yielding clear preference reversals and reproducible indifference points.

(3) Application of standard discounting models to predict novel indifference points is both rigorous and quantitatively satisfying, reinforcing the interpretation of worm behavior in economic terms.

(4) The three-state patch-model cleanly separates entry and exit dynamics, showing that increased leaving rates-rather than altered re-entry-drive choice biases.

(5) Investigates the role of dopamine in this behavior to try to establish shared mechanisms with vertebrates.

(6) Demonstration of discounting in wild strain (solid evidence).

Weaknesses:

(1) The kinetic model omits rich trajectory details-such as turning angles or hazard functions-that could distinguish a bona fide roaming transition from other exit behaviors.

(2) Only _dop-3_ shows an effect, and the statistical validity of this result is questionable. It is not clear if the authors corrected for multiple comparisons, and the effect size is quite small and noisy, given the large number of worms tested. Other mutants do not show effects. Given these two concerns, the role of dopamine in c. elegans effort discounting was unconvincing.

(3) With only five wild isolates tested (and variable data quality), it's hard to conclude that effort discounting isn't a lab-strain artifact or how broadly it varies in natural populations.

(4) Detailed analysis of behavior beyond preference indices would strengthen the dopamine link and the claim of effort discounting in wild strains.

(5) A few mechanistic statements (e.g., tying satiety exclusively to nutrient signals) would benefit from explicit citations or brief clarifications for non-worm specialists.

Reviewer #2 (Public review):

Summary:

This study reexamined the idea that action potential broadening serves as a homeostatic mechanism to compensate for changes in network activity. The key finding was that, while action potential broadening does occur in certain neurons - such as CA3 pyramidal cells-it is far from a universal response. This is important because it helps resolve longstanding discrepancies in the field, thereby contributing to a better understanding of network dynamics. The replication of these findings across multiple laboratories further strengthened the study's rigor.

Strengths:

Mechanisms of network homeostasis are essential to understand network dynamics.

Weaknesses:

No weaknesses were noted by this reviewer.

Reviewer #2 (Public review):

Summary:

This manuscript investigates age-related differences in cooperative behavior by comparing adolescents and adults in a repeated Prisoner's Dilemma Game (rPDG). The authors find that adolescents exhibit lower levels of cooperation than adults. Specifically, adolescents reciprocate partners' cooperation to a lesser degree than adults do. Through computational modeling, they show that this relatively low cooperation rate is not due to impaired expectations or mentalizing deficits, but rather a diminished intrinsic reward for reciprocity. A social reinforcement learning model with asymmetric learning rate best captured these dynamics, revealing age-related differences in how positive and negative outcomes drive behavioral updates. These findings contribute to understanding the developmental trajectory of cooperation and highlight adolescence as a period marked by heightened sensitivity to immediate rewards at the expense of long-term prosocial gains.

Strengths:

(1) Rigid model comparison and parameter recovery procedure.

(2) Conceptually comprehensive model space.

(3) Well-powered samples.

Weaknesses:

(1) A key conceptual distinction between learning from non-human agents (e.g., bandit machines) and human partners is that the latter are typically assumed to possess stable behavioral dispositions or moral traits. When a non-human source abruptly shifts behavior (e.g., from 80% to 20% reward), learners may simply update their expectations. In contrast, a sudden behavioral shift by a previously cooperative human partner can prompt higher-order inferences about the partner's trustworthiness or the integrity of the experimental setup (e.g., whether the partner is truly interactive or human). The authors may consider whether their modeling framework captures such higher-order social inferences. Specifically, trait-based models-such as those explored in Hackel et al. (2015, Nature Neuroscience)-suggest that learners form enduring beliefs about others' moral dispositions, which then modulate trial-by-trial learning. A learner who believes their partner is inherently cooperative may update less in response to a surprising defection, effectively showing a trait-based dampening of learning rate.

(2) This asymmetry in belief updating has been observed in prior work (e.g., Siegel et al., 2018, Nature Human Behaviour) and could be captured using a dynamic or belief-weighted learning rate. Models incorporating such mechanisms (e.g., dynamic learning rate models as in Jian Li et al., 2011, Nature Neuroscience) could better account for flexible adjustments in response to surprising behavior, particularly in the social domain.

(3) Second, the developmental interpretation of the observed effects would be strengthened by considering possible non-linear relationships between age and model parameters. For instance, certain cognitive or affective traits relevant to social learning-such as sensitivity to reciprocity or reward updating-may follow non-monotonic trajectories, peaking in late adolescence or early adulthood. Fitting age as a continuous variable, possibly with quadratic or spline terms, may yield more nuanced developmental insights.

(4) Finally, the two age groups compared - adolescents (high school students) and adults (university students) - differ not only in age but also in sociocultural and economic backgrounds. High school students are likely more homogenous in regional background (e.g., Beijing locals), while university students may be drawn from a broader geographic and socioeconomic pool. Additionally, differences in financial independence, family structure (e.g., single-child status), and social network complexity may systematically affect cooperative behavior and valuation of rewards. Although these factors are difficult to control fully, the authors should more explicitly address the extent to which their findings reflect biological development versus social and contextual influences.

Reviewer #2 (Public review):

Summary:

This work sought to explore antibody responses in the context of hemorrhagic fever with renal syndrome (HFRS) - a severe disease caused by Hantaan virus infection. Little is known about the characteristics or functional relevance of IgG Fc glycosylation in HFRS. To address this gap, the authors analyzed samples from 65 patients with HFRS spanning the acute and convalescent phases of disease via IgG Fc glycan analysis, scRNAseq, and flow cytometry. The authors observed changes in Fc glycosylation (increased fucosylation and decreased bisection) coinciding with a 4-fold or greater increase in Haantan virus-specific antibody titer. They suggest that these shifts contribute to disease recovery. The study also includes exploratory analyses linking IgG glycan profiles to glycosylation-related gene expression in distinct B cell subsets, using single-cell transcriptomics. Overall, this is an interesting study that combines serological profiling with transcriptomic data to shed light on humoral immune responses in an underexplored infectious disease. The integration of Fc glycosylation data with single-cell transcriptomic data is a strength. However, some improvements could be made in the clarity of both the Results and Materials and Methods sections, and some conclusions would benefit from greater caution, particularly in avoiding overinterpretation of correlative findings.

Comments:

(1) While it is great to reference prior publications in the Materials and Methods section, the current level of detail is insufficient to clearly understand the study design and experimental procedures performed. Readers should not be expected to consult multiple previous papers to grasp the core methodological aspects of the present paper. For instance, the categorization of HFRS patients into different clinical subtypes/courses, and the methods for measuring Fc glycosylation should be explicitly described in the Materials and Methods section of this manuscript.

(2) The authors should explain the nature of their cohort in a bit more detail. While it appears that HFRS cases were identified based on IgM ELISA and/or PCR, these are indicators of the Haantan virus infection. My understanding is that not all Haantan virus infections progress to HFRS. Thus, it is unclear whether all patients in the HFRS group actually had hemorrhagic fever. This distinction is critical for interpreting how the results observed relate to disease severity.

(3) The authors state that: "A 4-fold or greater increase in HTNV-NP-specific antibody titers usually indicates a protective humoral immune response during the acute phase", but they do not cite any references or provide any context that supports this claim. Given that in their own words, one of the most significant findings in the study is changes in glycosylation coinciding with this 4-fold increase, it is important to ground this claim in evidence. Without this, the use of a 4-fold threshold appears arbitrary and weakens the rationale for using this immune state as a proxy for protective immunity.

(4) The authors also claim that changes in Fc glycosylation influence recovery from HFRS - a point even emphasized in the manuscript title. However, this conclusion is not well supported by the data for two main reasons. First, the authors appear to measure bulk IgG Fc glycans, not Fc glycans of Hantaan virus-specific antibodies. While reasonable, this is something that should be communicated in the manuscript. Hantaan virus-specific antibodies are likely a very small fraction of total circulating IgG antibodies (perhaps ~1%), even during acute infection. As a result, changes in bulk Fc glycosylation may (or may not) accurately reflect the glycosylation state of Hantaan virus-specific antibodies. Second, even if the bulk Fc glycan shifts do mirror those of Hantaan virus-specific antibodies, it remains unclear whether these changes causally drive recovery or are merely a consequence of the infection being resolved. Thus, while the differences in Fc glycosylation observed are interesting - and it is tempting to speculate on their functional significance - the manuscript treats the observed correlations as causal mechanistic insight without sufficient data or justification.

(5) Fc glycosylation is known to be influenced by covariates such as age and sex. While it is helpful that the authors stratified the patients by age group and looked for significant differences in glycosylation across them, a more robust approach would be to directly control for these covariates in the statistical analysis - such as by using a linear mixed effects model, in which disease state (e.g., acute vs. convalescent), age, and sex are treated as fixed effects, and subject ID is included as a random effect to account for repeated measures. This would allow the authors to assess whether observed differences in Fc glycosylation remain significant after accounting for potential confounders. This could be important given that some of the reported differences are quite small, for example, 94.29% vs. 94.89% fucosylation.

(6) The manuscript states that there are limited studies on antibody glycosylation in the context of HFRS, but does not cite any relevant literature. If prior work exists, it should be cited to contextualize the current study. If no prior studies have been conducted/reported, to the author's knowledge, that should be stated explicitly to show the novelty of the work.

Reviewer #2 (Public review):

The manuscript by Çevrim et al. presents a live-imaging workflow that captures the complete leg regeneration process in the crustacean Parhyale hawaiensis, at a resolution suitable for cell tracking and gene expression analysis. Building on earlier work describing selective stages of leg regeneration (Alwes et al., 2016), the authors recorded 22 confocal time-lapse movies, starting from amputation to full regeneration. They defined three distinct phases of regeneration (wound closure, cell proliferation and morphogenesis, and differentiation) based on cellular and morphological features.

One movie was used to assess how imaging parameters (z-spacing, time intervals, and image quality) influence tracking reliability and the time required for manual proofreading, with an effort to minimize phototoxicity. Tracking was performed in the upper tissue layers using an improved version of the Mastodon plugin Elephant in Fiji. The same sample was fixed post-imaging for in situ hybridization using an HCR protocol adapted for adult legs, targeting the gene spineless. This enabled the alignment of gene expression with specific cell lineages and the identification of progenitor cells present at the time of amputation.

In summary, the study provides a proof-of-principle for combining long-term live imaging, cell tracking, and gene expression analysis during regeneration. Given the labor-intensive nature of tracking over a 5-10 day time-lapse movie, the use of a single movie for this study is well justified. The workflow, from imaging to lineage reconstruction and molecular annotation, is successfully demonstrated and well documented with this dataset.

Although the biological insights from the cell lineage and molecular mapping are still limited, the methodology offers significant potential in regenerative biology to uncover the cellular and molecular contributions to tissue and cell type re-formation.

Confocal microscopy was used for live imaging, which restricted imaging to the upper 30 µm tissue layer. Light-sheet microscopy could have provided gentler imaging and enabled imaging from multiple angles to image the whole leg. While the authors acknowledge this possibility in the manuscript, they discarded it due to incompatibility between their mounting strategy and available light-sheet microscopes. As a future direction, optimizing the mounting approach for compatibility with light-sheet microscopes could enable more comprehensive tissue imaging.

Reviewer #2 (Public review):

Summary:

This is the first study to show how a L-R bias in the relationship between numerical magnitude and space depends on brain lateralisation, and moreover, how this is modulated by in ovo conditions.

Strengths:

Novel methodology for investigating the innateness and neural basis of a L-R bias in the relationship between number and space.

Weaknesses:

I would query the way the experiment was contextualised. They ask whether culture or innate pre-wiring determines the 'left-to-right orientation of the MNL [mental number line]'.<br /> The term, 'Mental Number Line' is an inference from experimental tasks. One of the first experimental demonstrations of a preference or bias for small numbers in the left of space and larger numbers in the right of space, was more carefully described as the spatial-numerical association of response codes - the SNARC effect (Dehaene, S., Bossini, S., & Giraux, P. (1993). The mental representation of parity and numerical magnitude. Journal of Experimental Psychology: General, 122, 371-396).<br /> This has meant that the background to the study is confusing. First, they note correctly that many other creatures, including insects can show this bias, though in none of these has neural lateralisation been shown to be a cause. Second, their clever experiment shows that an experimental manipulation creates the bias. If it were innate and common to other species, the experimental manipulation shouldn't matter. There would always be a L-R bias. Third, they seem to be asserting that humans have a left-to-right (L-R) MNL. This is highly contentious, and in some studies, reading direction affects it, as the original study by Dehaene et al showed; and in others, task affects direction (e.g. Bachtold, D., Baumüller, M., & Brugger, P. (1998). Stimulus-response compatibility in representational space. Neuropsychologia, 36, 731-735, not cited). Moreover, a very careful study of adult humans, found no L-R bias (Karolis, V., Iuculano, T., & Butterworth, B. (2011), not cited). Mapping numerical magnitudes along the right lines: Differentiating between scale and bias. Journal of Experimental Psychology: General, 140(4), 693-706). Indeed, Rugani et al claim, incorrectly, that the L-R bias was first reported by Galton in 1880. There are two errors here: first, Galton was reporting what he called 'visualised numerals' and are typically referred to now as 'number forms' - spontaneous and habitual conscious visual representations - not an inference from a number line task. Second, Galton reported right-to-left, circular, and vertical visualised numerals, and no simple left-to-right examples (Galton, F. (1880). Visualised numerals. Nature, 21, 252-256.). So in fact did Bertillon, J. (1880). De la vision des nombres. La Nature, 378, 196-198, and more recently Seron, X., Pesenti, M., Noël, M.-P., Deloche, G., & Cornet, J.-A. (1992). Images of numbers, or "When 98 is upper left and 6 sky blue". Cognition, 44, 159-196, and Tang, J., Ward, J., & Butterworth, B. (2008). Number forms in the brain. Journal of Cognitive Neuroscience, 20(9), 1547-1556.

If the authors are committed to chicks' MN Line they should test a series of numbers showing that the bias to left is greater for 2 and 3 than for 4 etc.

What does all this mean? I think that the experiment should absolutely be published in eLife, but the paper should be shorn of its misleading contextualisation, including the term 'Mental Number Line'. The authors also speculate, usefully, on why chicks and other species might have a L-R bias. I don't think the speculations are convincing, but at least if there is an evolutionary basis for the bias, it should at least be discussed.

In fact, I think it would make a very interesting special issue to bring up to date how and why the L-R bias exists, and where and why it does not.

Karolis, V., Iuculano, T., & Butterworth, B. (2011). Mapping numerical magnitudes along the right lines: Differentiating between scale and bias. Journal of Experimental Psychology: General, 140(4), 693-706. doi:10.1037/a0024255

Review of the revised version:

The background and terminology in the text have been significantly altered and clarified: Spatial Numerical Association (SNA) instead of Mental Number Line (MNL) in the text, but with a discussion about how SNA might be the basis of MNL. This entails a link from SNA - a bias - to mental representation of a sequence of numerical magnitudes, which will need to be spelt out in subsequent work with a sequence of numbers rather than a single number, in this case 4. Could the effect be generalised to much larger numbers?

Although the relationship between number and space seems fundamental, the key question is why the L-R SNA bias should exist at all. The authors take on this challenge and make important arguments for the evolutionary advantage of the bias is (see lines 138ff, 375ff, 444ff), though this is likely still to be controversial.

Subsequent work may clarify its interaction of brain lateralisation with culture, notably reading and writing direction (e.g. Dehaene, S., Bossini, S., & Giraux, P. (1993). The mental representation of parity and numerical magnitude. Journal of Experimental Psychology: General, 122, 371-396), though this relationship has exceptions and challenges (e.g. Karolis, V., Iuculano, T., & Butterworth, B. (2011). Mapping numerical magnitudes along the right lines: Differentiating between scale and bias. Journal of Experimental Psychology: General, 140(4), 693-706).

For example, would humans with more lateralised brains show a stronger bias? Would humans with reverse lateralisation show a R-L SNA?

Reviewer #2 (Public review):

Summary:

This study presents an integrated experimental and computational pipeline for high-resolution, quantitative imaging and analysis of gastruloids. The experimental module employs dual-view two-photon spectral imaging combined with optimized clearing and mounting techniques to image whole-mount immunostained gastruloids. This approach enables the acquisition of comprehensive 3D images that capture both tissue-scale and single-cell level information.

The computational module encompasses both pre-processing of acquired images and downstream analysis, providing quantitative insights into the structural and molecular characteristics of gastruloids. The pre-processing pipeline, tailored for dual-view two-photon microscopy, includes spectral unmixing of fluorescence signals using depth-dependent spectral profiles, as well as image fusion via rigid 3D transformation based on content-based block-matching algorithms. Nuclei segmentation was performed using a custom-trained StarDist3D model, validated against 2D manual annotations, and achieving an F1 score of 85+/-3% at a 50% intersection-over-union (IoU) threshold. Another custom-trained StarDist3D model enabled accurate detection of proliferating cells and the generation of 3D spatial maps of nuclear density and proliferation probability. Moreover, the pipeline facilitates detailed morphometric analysis of cell density and nuclear deformation, revealing pronounced spatial heterogeneities during early gastruloid morphogenesis.

All computational tools developed in this study are released as open-source, Python-based software.

Strengths:

The authors applied two-photon microscopy to whole-mount deep imaging of gastruloids, achieving in toto visualization at single-cell resolution. By combining spectral imaging with an unmixing algorithm, they successfully separated four fluorescent signals, enabling spatial analysis of gene expression patterns.

The entire computational workflow, from image pre-processing to segmentation with a custom-trained StarDist3D model and subsequent quantitative analysis, is made available as open-source software. In addition, user-friendly interfaces are provided through the open-source, community-driven Napari platform, facilitating interactive exploration and analysis.

Weaknesses:

The computational module appears promising. However, the analysis pipeline has not been validated on datasets beyond those generated by the authors, making it difficult to assess its general applicability.<br /> Besides, the nuclei segmentation component lacks benchmarking against existing methods.

Appraisal:

The authors set out to establish a quantitative imaging and analysis pipeline for gastruloids using dual-view two-photon microscopy, spectral unmixing, and a custom computational framework for 3D segmentation and gene expression analysis. This aim is largely achieved. The integration of experimental and computational modules enables high-resolution in toto imaging and robust quantitative analysis at the single-cell level. The data presented support the authors' conclusions regarding the ability to capture spatial patterns of gene expression and cellular morphology across developmental stages.

Impact and utility:

This work presents a compelling and broadly applicable methodological advance. The approach is particularly impactful for the developmental biology community, as it allows researchers to extract quantitative information from high-resolution images to better understand morphogenetic processes. The data are publicly available on Zenodo, and the software is released on GitHub, making them highly valuable resources for the community.

Reviewer #2 (Public review):

Summary:

The study employs a specific set of transcription factors to promote lineage conversion of pluripotent stem cells into fetal hair cells. In pluripotent stem cells, an inducible expression system containing SIX1, ATOH1, POU4F3, and GFI1 (SAPG) was inserted into a safe harbor site. The stable cell line allows for doxycycline-inducible expression of transcription factors to generate induced hair cells (iHCs). These changes were observed in gene expression and electrophysiological properties. Comparing the transcriptome with iHCs derived from fibroblasts or primary human inner ear tissue suggested that it is similar to human hair cells. Although the iHCs did not have hair bundles - a key morphological feature of hair cells - the cellular system has immense potential for the field. The defined transcription factors allow for the dissection of gene regulatory networks and provide a molecular handle for the lineage conversion process. The results also suggest that the pluripotent stem cells were not directly converted into iHCs. Instead, there are several transitional cell states. These observations indicate that lineage conversion may still be hampered by yet undefined molecular obstacles and may help identify and overcome these in future work. The stable cell line allows for repeatable and large-scale screening studies, which is not feasible using primary human cells.

Strengths:

The cellular system is well-designed, with clearly described expression of the defined factors. Transient expression of the exogenous transcription factors SIX1, ATOH1, POU4F3, and GFI1 (SAPG) upon doxycycline induction is well-documented. Increased expression of endogenous SAPG factors suggests activation of self-regulatory feedback pathways during conversion. The stable iPS cell line provides a tool for the field to study lineage conversion or generate large numbers of iHCs.

Single-nuclear RNA-seq distinguishes distinct cell clusters and cellular transition states, validating the system's utility. A comparison of previously published data from iHCs and human fetal hair cells also suggested that iHCs are similar to developing human hair cells at the transcriptome level. Whole-cell patch clamp recordings show the generation of excitable cells with heterogeneous ion channel properties, which suggests a change in the cell type.

Weaknesses:

The interpretation of the snRNA-seq results could be strengthened by explaining the three distinct clusters for uninduced cells and how they transition into the iHC trajectory.

Although the analysis focuses on the cell cluster that represents iHCs (R5), a short discussion on what clusters R1-R4 (Figure 3B) represent would be useful. These cells do not express high levels of the SAPG factors even after 21 days of continuous doxycycline induction and may provide insight into hurdles that hamper lineage conversion.

RNA velocity analysis on single-nuclear RNA-seq is impressive but requires clarification on inferring the pseudotime trajectory. Some rationale and explanation on how the ratio of unspliced to spliced mRNA in the nucleus can be used to infer the differentiation trajectory would strengthen the discussion.

Reviewer #2 (Public review):

Summary:

This paper by Wang et al. uses rich brain, behaviour, and genetics data from the ABCD cohort to ask how well cognitive abilities can be predicted from mental health related measures, and how brain and genetics influence that prediction. They obtain an out of sample correlation of 0.4, with neuroimaging (in particular task fMRI) proving the key mediator. Polygenic scores contributed less.

Strengths:

This paper is characterized by the intelligent use of a superb sample (ABCD) alongside strong statistical learning methods and a clear set of questions. The outcome - the moderate level of prediction between brain, cognition, genetics and mental health - is interesting, and particularly important is the dissection of which features best mediate that prediction and how developmental and lifestyle factors play a role.

Weaknesses:

There are relatively few weaknesses to this paper. It has already undergone review at a different journal, and the authors clearly took the original set of comments into account in revising their paper. Overall, while the ABCD sample is superb for the questions asked, it would have been highly informative to extend the analyses to datasets containing more participants with neurological/psychiatric diagnoses (e.g. HBN, POND) or extending it into adolescent/early adult onset psychopathology cohorts. But it is fair enough that the authors want to leave that for future work.

Reviewer #3 (Public review):

Summary:

Perlee et al. present a method for generating cell-type restricted knockouts in zebrafish, focusing on melanocytes. For this method, the authors knock-in a Cas9 encoding sequence into the mitfa locus. This mitfaCas9 line has restricted Cas9 expression, allowing the authors to generate melanocyte-specific knockouts rapidly by follow-up injection of sgRNA expressing transposon vectors.

The paper presents some interesting vignettes to illustrate the utility of their approach. These include 1) a derivation of albino mutant fish as a demonstration of the method's efficiency, 2) an interrogation and novel description of tuba1a/tuba1c as a potential non-autonomous contributor to melanosome dispersion, and 3) the generation of sox10 deficient melanoma tumors that show "escape" of sox10 loss through upregulation of sox9. The latter two examples highlight the usefulness of cell-type targeted knockouts (Body-wide sox10 and tuba1a loss elicit developmental defects). Additionally, the tumor models involve highly multiplexed sgRNAs for tumor initiation which is nicely facilitated by the stable Cas9.

Strengths:

The approach is clever and could prove very useful for studying melanocytes and other cell types. As the authors hint at in their discussion, this approach would become even more powerful with the generation of other Cas9-restricted lineages so a single sgRNA construct can be screened across many lineages rapidly (or many sgRNA and fish lines screened combinatorially).

The biological findings used to demonstrate the power of the approach are interesting in their own right. The non-autonomous effect of tuba1a/tuba1c loss on melanosome dispersion are striking and demonstrates very nicely how one could use Perlee et al.'s approach to search for similar mechanisms systematically. The dual targeting nature of the tuba1a/tuba1c sgRNA also suggests similar approaches might be explored for knocking out paralogs. The observation of the sox9 escape mechanism with sox10 loss is a beautiful demonstration of the relevance of SOX10/SOX9's reciprocal regulation in vivo. This system would be a very nice model for further interrogating mechanisms/interventions surrounding Sox10 in melanoma.

Finally, the figure presentation is very nice. This work involves complex genetic approaches, including multiple fish generations and multiplexed construct injections. The vector diagrams and breeding schemes in the paper make everything very clear/"grok-able," and the paper was enjoyable to read.

Weaknesses:

The authors' claims are grounded and tested rigorously. The major weaknesses that we raised in the first round of reviews were either addressed experimentally or are now detailed as limitations in the text. Congrats on the beautiful paper!

Reviewer #2 (Public review):

Garbelli et. al. set out to elucidate the function of two glutamate transporters, EAAT5b and EAAT7, in the functional and behavioral responses to different wavelengths of light. The question is an interesting one because these transporters are well-positioned to affect responses to light, and their distribution in the retina suggests that they could play differential roles in visual behaviors. However, the resolution of the functional and behavioral data presented here means that the conclusions are necessarily a bit vague.

In Figure 1, the authors show that the double KO has a decreased ERG response to UV/blue and red wavelengths. However, the individual mutations both only affect the response to red light, suggesting that they might affect behaviors such as OMR that typically rely on this part of the visual spectrum. However, there was no significant change in the response to UV/blue light of any intensity, making it unclear whether the mutations could individually play roles in detection of UV prey. Based on the later behavioral data, it seems likely that at least the EAAT7 KO should affect retinal responses to UV light, but it may be that the ERG does not have the spatial or temporal resolution to detect the difference, or that the presence of blue light overwhelmed any effect of the individual knockouts on the response to UV light.

In Figures 5 and 6, the authors compare the two knockouts to wild-type fish in terms of their sensitivity to UV prey in a hunting assay. The EAAT5b KO showed no significant impairment in UV sensitivity, while the EAAT7 KO fish actually had an increased hunting response to UV prey. However, there is no comparison of the KO and WT responses to different UV intensities, only in bulk, so we cannot conclude that the EAAT7 KO is allowing the fish to detect weaker prey-like stimuli.

In Figure 7, the EAAT5b KO seems to cause a decrease in OMR behavior to red grating stimuli, but only one stimulus is tested, so it is unclear whether this is due to a change in visual sensitivity or resolution.

The conclusions made in the manuscript are appropriately conservative; the abstract states that these transporters somehow influence prey detection and motion sensing, and this is likely true.

In terms of impact on the field, this work highlights the potential importance of these two transporters to visual processing, but further studies will be required to say how important they are and exactly what they are doing.

Reviewer #2 (Public review):

Summary:

In this study, the authors have devised a novel assay to measure relative social rank in mice that is aimed at incorporating multiple aspects of social competition while minimizing direct contact between animals. Forming a hierarchy often involves complex social dynamics related to competitive drives for different fundamental resources, including access to food, water, territory and sexual mates. This makes the study of social dominance and its neural underpinnings hard, warranting the development of new tools and methods that can help understand both social function as well as dysfunction.

Strengths:

This study showcases an assay called the Food Pellet Competition Test, where cagemate mice compete for food, without direct contact, by pushing a block in a tube from opposite directions. This task ran with stranger mice leads to more variable outcomes, suggesting co-housing helps stabilize outcomes. The authors have attempted to quantify motivation to obtain the food independent of other factors by running the assay under two conditions: one where the food is accessible and one where it isn't. This assay results in high outcome consistency across days for females and males paired housed and for male groups of three. Further, the determined social ranks correlate strongly with two common assays: the tube test and the warm spot test.

Weaknesses:

This new assay has limited ethological validity since mice do not compete for food without touching each other with a block in the middle. In addition, the assay may only be valid for a single trial per day, making its utility for recording neural recordings and manipulations limited to a single sample per mouse. The authors claim, as currently stated in results, for the new control experiment in 1H-J is not warranted given that 6/8 mice had majority winning or losing across all strangers.

Reviewer #3 (Public review):

Summary:

In this study, Wang et al utilized the available GTEx data to compile a comprehensive analysis that attempt to reveal aging-related sex-dimorphic gene expression as well as alternative splicing changes in human. The key conclusions based upon their analysis are that 1) extensive sex-dimorphisms during aging with distinct patterns of change in gene expression and alternative splicing (AS), and 2) the male-biased age-associated AS events have a stronger association with Alzheimer's disease, and 3) the females-biased events are often regulated by several sex-biased splicing factors that may be controlled by estrogen receptors. They further performed break-point analysis and reveal in males there are two main breakpoints around ages 35 and 50, while in female only one breakpoint at 45.

Strengths:

This study sets an ambitious goal, leveraging the extensive GTEx dataset to investigate aging-related, sex-dimorphic gene expression and alternative splicing changes in humans. The research addresses a significant question, as our understanding of sex-dimorphic gene expression in the context of human aging is still in its early stages. Advancing our knowledge of these molecular changes is vital for identifying therapeutic targets for age-related diseases and extending human healthspan. The study is highly comprehensive, and the authors are commendable for their attempted thorough analysis of both gene expression and alternative splicing-an area often overlooked in similar studies.

Reviewer #2 (Public review):

Summary:

The authors set out to visualize the molecular architecture of the adult forebrain glutamatergic synapses in a near-native state. To this end, they use a rapid workflow to extract and plunge-freeze mouse synapses for cryo-electron tomography. In addition, the authors use knockin mice expression PSD95-GFP in order to perform correlated light and electron microscopy to clearly identify pre- and synaptic membranes. By thorough quantification of tomograms from plunge- and high-pressure frozen samples, the authors show that the previously reported 'post-synaptic density' does not occur at high frequency and therefore not a defining feature of a glutamatergic synapse.

Subsequently, the authors are able to reproduce the frequency of post-synaptic density when preparing conventional electron microscopy samples, thus indicating that density prevalence is an artifact of sample preparation. The authors go on to describe the arrangement of cytoskeletal components, membraneous compartments, and ionotropic receptor clusters across synapses.

Demonstrating that the frequency of the post-synaptic density in prior work is likely an artifact and not a defining feature of glutamatergic synapses is significant. The descriptions of distributions and morphologies of proteins and membranes in this work may serve as a basis for the future of investigation for readers interested in these features.

Strengths:

The authors perform a rigorous quantification of the molecular density profiles across synapses to determine the frequency of the post-synaptic density. They prepare samples using two cryogenic electron microscopy sample preparation methods, as well as one set of samples using conventional electron microscopy methods. The authors can reproduce previous reports of the frequency of the post-synaptic density by conventional sample preparation, but not by either of the cryogenic methods, thus strongly supporting their claim.

Reviewer #2 (Public review):

Summary:

The manuscript by Majnik and colleagues introduces "Track2p", a new tool designed to track neurons across imaging sessions of two-photon calcium imaging in developing mice. The method addresses the challenge of tracking cells in the growing brain of developing mice. The authors showed that "Track2p" successfully tracks hundreds of neurons in the barrel cortex across multiple days during the second postnatal week. This enabled the identification of the emergence of behavioral state modulation and desynchronization of spontaneous network activity around postnatal day 11.

Strengths:

The manuscript is well written, and the analysis pipeline is clearly described. Moreover, the dataset used for validation is of high quality, considering the technical challenges associated with longitudinal two-photon recordings in mouse pups. The authors provide a convincing comparison of both manual annotation and "CellReg" to demonstrate the tracking performance of "Track2p". Applying this tracking algorithm, Majnik and colleagues characterized hallmark developmental changes in spontaneous network activity, highlighting the impact of longitudinal imaging approaches in developmental neuroscience. Additionally, the code is available on GitHub, along with helpful documentation, which will facilitate accessibility and usability by other researchers.

Weaknesses:

(1) The main critique of the "Track2p" package is that, in its current implementation, it is dependent on the outputs of "Suite2p". This limits adoption by researchers who use alternative pipelines or custom code. One potential solution would be to generalize the accepted inputs beyond the fixed format of "Suite2p", for instance, by accepting NumPy arrays (e.g., ROIs, deltaF/F traces, images, etc.) from files generated by other software. Otherwise, the tool may remain more of a useful add-on to "Suite2p" (see https://github.com/MouseLand/suite2p/issues/933) rather than a fully standalone tool.

(2) Further benchmarking would strengthen the validation of "Track2p", particularly against "CaIMaN" (Giovannucci et al., eLife, 2019), which is widely used in the field and implements a distinct registration approach.

(3) The authors might also consider evaluating performance using non-consecutive recordings (e.g., alternate days or only three time points across the week) to demonstrate utility in other experimental designs.

Reviewer #2 (Public review):

Summary:

Human histone H3K36 methyltransferase Setd2 has been previously shown to be a tumor suppressor in lung and pancreatic cancer. In this manuscript by Mack et al., the authors first use a mouse KRASG12D-driven lung cancer model to confirm in vivo that Setd2 depletion exacerbates tumorigenesis. They then investigate the enzymatic regulation of the Setd2 SET domain in vitro, demonstrating that H2A, H3, or H4 acetylation stimulates Setd2-SET activity, with specific enhancement by mono-acetylation at H3K14ac or H3K27ac. In contrast, histone ubiquitination has no effect. The authors propose that H3K27ac may regulate Setd2-SET activity by facilitating its binding to nucleosomes. This work provides insight into how cross-talk between histone modifications regulates Setd2 function. However, the manuscript lacks a clear discussion on how Setd2's in vivo tumor suppressor role and the in vitro mechanistic regulation findings are connected. Additionally, some experiments require more controls and better data quality for proper interpretation.

Specific comments:

(1) As for Figure 2F, Setd2-SET activity on WT rNuc (H3) appears to be significantly lower compared to what is extensively reported in the literature. This is particularly puzzling given that Figure 2B suggests that using 3H-SAM, H3-nuc are much better substrates than K36me1, whereas in Figure 3F, rH3 is weaker than K36me1. It is recommended for the authors to perform additional experimental repeats and include a quantitative analysis to ensure the consistency and reliability of these findings.

(2) The additional bands observed in Figure 4B, which appear to be H4, should be accompanied by quantification of the intensity of the H3 bands to better assess K36me3 activity. Additionally, the quantification presented in Figure 4C for SAH does not seem accurate as it potentially includes non-specific methylation activity, likely from H4. This needs to be addressed for clarity and accuracy.

(3) In Figure 4E, the differences between bound and unbound substrates are not sufficiently pronounced. Given the modest differences observed, authors might want to consider repeating the assay with sufficient replicates to ensure the results are statistically robust.

(4) Regarding labeling, there are multiple issues that need correction: In the depiction of Epicypher's dNuc, it is crucial to clearly mark H2B as the upper band, rather than ambiguously labeling H2A/H2B together when two distinct bands are evident. In Figure 3B and D, the histones appear to be mislabeled, and the band corresponding to H4 has been cut off. It would be beneficial to refer to Figure 3E for correct labeling to maintain consistency and accuracy across figures.

(5) There are issues with the image quality in some blots; for instance, Figure 2EF and Figure 2D exhibit excessive contrast and pixelation, respectively. These issues could potentially obscure or misrepresent the data, and thus, adjustments in image processing are recommended to provide clearer, more accurate representations.

(6) The authors are recommended to provide detailed descriptions of the materials used, including catalog numbers and specific products, to allow for reproducibility and verification of experimental conditions.

(7) The identification of Setd2 as a tumor suppressor in KrasG12C-driven LUAD is a significant finding. However, the discussion on how this discovery could inspire future therapeutic approaches needs to be more balanced. The current discussion (Page 10) around the potential use of inhibitors is somewhat confusing and could benefit from a clearer explanation of how Setd2's role could be targeted therapeutically. It would be beneficial for the authors to explore both current and potential future strategies in a more structured manner, perhaps by delineating between direct inhibitors, pathway modulators, and other therapeutic modalities.

Reviewer #2 (Public review):

Summary:

The authors have used single-particle cryoEM imaging to determine how small-molecule regulators of the SK channel interact with it and modulate their function.

Strengths:

The reconstructions are of high quality, and the structural details are well described.

Weaknesses:

The electrophysiological data are poorly described. Several details of the structural observations require a mechanistic context, perhaps better relating them to what is known about SK channels or other K channel gating dynamics.

The most pressing point I have to make, which could help improve the manuscript, relates to the selectivity filter (SF) conformation. Whether the two ion-bound state of SK2-4 (Figure 4A) represents a non-selective, conductive SF occluded by F243 or represents a C-type inactivated SF, further occluded by F243, is unclear. It would be important to discuss this. Reconstructions of Kv1.3 channels also feature a similar configuration, which has been correlated to its accelerated C-type inactivation.

Furthermore, binding of a toxin derivative to Kv1.3 restores the SF into a conductive form, though occluded by the toxin. It appears that apamin binding to SK2-4 might be doing something similar. Although I am not sure whether SK channels undergo C-type inactivation like gating, classical MTS accessibility studies have suggested that dynamics of the SF might play a role in the gating of SK channels. It would be really useful (if not essential) to discuss the SF dynamics observed in the study and relate them better to aspects of gating reported in the literature.

The SF of K channels, in conductive states, are usually stabilized by an H-bond network involving water molecules bridged to residues behind the SF (D363 in the down-flipped conformation and Y361). Considering the high quality of the reconstructions, I would suspect that the authors might observe speckles of density (possibly in their sharpened map) at these sites, which overlap with water molecules identified in high-resolution X-ray structures of KcsA, MthK, NaK, NaK2K, etc. It could be useful to inspect this region of the density map.

Reviewer #2 (Public Review):

Summary:

Peptidoglycan remodeling, particularly that carried out by enzymes known as amidases, is essential for the later stages of cell division including cell separation. In E. coli, amidases are generally activated by the periplasmic proteins EnvC (AmiA and AmiB) and NlpD (AmiC). The ABC family member, FtsEX, in turn, has been implicated as a modulator of amidase activity through interactions with EnvC. Specifically, how FtsEX regulates EnvC activity in the context of cell division remains unclear.

Strengths:

Li et al. make two primary contributions to the study of FtsEX. The first, the finding that ATP binding stabilizes FtsEX in vitro, enables the second, structural resolution of full-length FtsEX both alone (Figure 2) and in combination with EnvC (Figure 3). Leveraging these findings, the authors demonstrate that EnvC binding stimulates FtsEX-mediated ATP hydrolysis approximately two-fold. The authors present structural data suggesting EnvC binding leads to a conformational change in the complex. Biochemical reconstitution experiments (Figure 5) provide compelling support for this idea.

Weaknesses:

The potential impact of the study is curtailed by the lack of experiments testing the biochemical or physiological relevance of the model which is derived almost entirely from structural data.

Altogether the data support a model in which interaction with EnvC, results in a conformational change stimulating ATP hydrolysis by FtsEX and EnvC-mediated activation of the amidases, AmiA and AmiB. However, the study is limited in both approach and scope. The importance of interactions revealed in the structures to the function of FtsEX and its role in EnvC activation are not tested. Adding biochemical and/or in vivo experiments to fill in this gap would allow the authors to test the veracity of the model and increase the appeal of the study beyond the small number of researchers specifically interested in FtsEX.

Comments after revision:

Although I appreciate the authors' desire to save future biochemical experiments for a separate publication, the lack of in vitro data verifying their model makes it challenging to reconcile with published studies from other groups. The other reviewer's point about EnvC activating FtsEX ATPase activity resulting in a futile cycle since both are recruited to the septum well before constriction, is a good example of the disconnect between the model presented here and in vivo data.

Reviewer #2 (Public review):

Summary:

Mitochondrial DNA (mtDNA) is exclusively maternally transmitted in almost all species. Paternal mitochondria, with their mtDNA, must be rapidly degraded after fertilisation to prevent their transmission to progeny, which could lead to subsequent detrimental mito-nuclear incompatibilities. Multiple layers of mechanisms contribute to blocking the transmission of paternal mitochondria and their mtDNA to progeny. Endonuclease activity and mitophagy form a part of these strategies. However, other key regulatory mechanisms remain to be elucidated, as inactivating endonuclease and mitophagy activity only delays the clearance of paternal mitochondria. In this study, the authors mainly focused on genes involved in endonuclease function (csp-6) and autophagy (allo-1) in C. elegans, demonstrating a synergic genetic interaction that potentialize their activity. They also revealed a contribution by pink-1/pink1, in the absence of allo-1.

Strengths:

The majority of data relies on confocal microscopy images and corresponding image analysis and quantification. Images are clear, and quantifications are supported by several biological replicates of >10 n and standard statistical tests. Mutants used were obtained from the Caenorhabditis Genetics Center (CGC) and were previously validated and confirmed by the C. elegans community. The scientific approach is solid and rigorous and in line with state-of-the-art C. elegans methods. Proper controls have been performed to rule out the effect of animal viability on observed results or to confirm the staining validity of TUBES on subcellular structures surrounding paternal mitochondria. Controls validating uaDf5 PCR specificity were conducted.

Weaknesses:

However, the embryonic expression of paternally contributing genes in feminised animals cannot be completely ruled out, as RNAi was used to alter gene expression levels. An issue inherent to RNAi approaches. Also, the impact of pink-1/pink1 is significant, but there is a lack of evidence demonstrating its mitophagic function.

Goal achievements and data supportive of conclusions:

In the first part of the study, the authors strongly and clearly demonstrate the synergistic interaction between the csp-6 and allo-1 in delaying paternal mitochondria degradation and associated mtDNA in the fertilised egg. In wild-type animals, paternal mitochondria are visible (using a mitochondrial HSP-::GFP marker) until the 4-cell stage embryo. In the csp-6; allo-1 double mutant genetic background, paternal mitochondria very significantly perdures until the 2-fold embryonic stage. The uaDf5 mitochondrial deletion, detectable by PCR, that was introduced by crossing with a male, followed the same trend. In addition, loss of fncd-1/fndc1 and phb-2 did not extend the perdurance of paternal mitochondria. In the second part of the study, the authors demonstrate a contribution of the loss of pink-1/pink1, in the absence of allo-1, in delaying paternal mitochondria degradation until the 100-cell stage. Overall, the conclusions are in accordance with the data shown.

Impact on the field:

Endonuclease activity and mitophagy aren't sufficient to prevent the transmission of paternal mitochondria and associated mtDNA to progeny, but they still contribute significantly to regulating the perdurance of paternal mitochondria in early embryos. Understanding how these two functions work in concert to potentialize their activity is important, as they could potentially be manipulated/enhanced to improve paternal mitochondrial degradation in the future. Here, the authors demonstrate a detailed synergistic genetic interaction between these functions. Also, they pointed out a new potential contribution of pink-1/pink1, which may underlie a potentially more complex mitophagic protective function.

Reviewer #2 (Public review):

Summary:

The manuscript by Jia and Chen addresses the structural basis of voltage-activation of BK channels using computational approaches. Although a number of experimental studies using gating current and patch-clamp recording have analyzed voltage-activation in terms of observed charge movements and the apparent energetic coupling between voltage-sensor movement and channel opening, the structural changes that underlie this phenomenon have been unclear. The present studies use a reduced molecular system comprising the transmembrane portion of the BK channel (i.e. the cytosolic domain was deleted), embedded in a POPC membrane, with either 0 or 750 mV applied across the membrane. This system enabled acquisition of long simulations of 10 microseconds, to permit tracking of conformational changes of the channel. The authors principal findings were that the side chains of R210 and R213 rapidly moved toward the extracellular side of the membrane (by 8 - 10 Å), with greater displacements than any of the other charged transmembrane residues. These movements appeared tightly coupled to movement of the pore-lining helix, pore hydration, and ion permeation. The authors estimate that R210 and R213 contribute 0.25 and 0.19 elementary charges per residue to the gating current, which is roughly consistent with estimates based on electrophysiological measurements that used the full-length channel.

Strengths:

The methodologies used in this work are sound, and these studies certainly contribute to our understanding of voltage-gating of BK channels. An intriguing observation is the strongly coupled movement of the S4, S5, and S6 helices that appear to underlie voltage-dependent opening. Based on Fig 2a-d, the substantial movements of the R210 and R213 side chains occur nearly simultaneously to the S6 movement (between 4 - 5 usec of simulation time). This seems to provide support for a "helix-packing" mechanism of voltage gating in the so-called "non-domain-swapped" voltage-gated K channels.

Weaknesses:

The main limitation is that these studies used a truncated version of the BK channel, and there are likely to be differences in VSD-pore coupling in the context of the full-length channels that will not be resolved in the present work. Nonetheless, the authors provide a strong rationale for their use of the truncated channel, and the results presented will provide a good starting point for future computational studies of this channel.

Reviewer #2 (Public review):

Summary:

The authors developed a computational pipeline named CHROMAS to track and analyze chromatophore dynamics, which provides a wide range of biological analysis tools without requiring the user to write code.

Strengths:

(1) CHROMAS is an integrated toolbox that provides tools for different biological tasks such as: segment, classify, track and measure individual chromatophores, cluster small groups of chromatophores, analyze full-body patterns, etc.

(2) It could be used to investigate different species. The authors have already applied it to analyze the skin of the bobtail squid Euprymna berryi and the European cuttlefish Sepia officinalis.

(3) The tool is open-source and easy to install. The paper describes in detail the experiment requirements, command to complete each task and provides relevant sample figures, which are easy to follow.

Weaknesses:

(1) There are some known limitations for the current version. The users should read the "Discussion" chapter carefully before preparing their experiments and using CHROMAS.

Reviewer #2 (Public review):

Summary:

The authors have worked up a ``virtual thymus' using EPISIM, which has already been published. Attractive features of the computational model are stochasticity, cell-to-cell variability, and spatial heterogeneiety. They seek to explore the role of TECs, that release IL-7 which is important in the process of thymocyte division.

In the model, ordinary clones have IL7R levels chosen from a distribution, while `lesioned' clones have an IL7R value set to the maximum. The observation is that the lesioned clones are larger families, but the difference is not dramatic. This might be called a cell-intrinsic mechanism. One promising cell-extrinsic mechanism is mentioned: if a lesioned clone happens to be near a source of IL-7 and begins to proliferate, the progeny can crowd out cells of other clones and monopolise the IL-7 source. The effect will be more noticeable if sources are rare, so is seen when the TEC network is sparse.

Strengths:

Thymic disfunctions are of interest, not least because of T-ALL. New cells are added, one at a time, to simulate the conveyor belt of thymocytes on a background of stationary cells. They are thus able to follow cell lineages, which is interesting because one progenitor can give rise to many progeny.

There are some experimental results in Figures 4,5 and 6. For example, il7 crispant embryos have fewer thymocytes and smaller thymii; but increasing IL-7 availability produces large thymii.

Reviewer #2 (Public review):

Summary:

Based on extensive live cell assays, SEC, and NMR studies of reconstituted complexes, these authors explore the roles of clathrin and the AP2 protein in facilitating clathrin-mediated endocytosis via activated arrestin-2. NMR, SEC, proteolysis, and live cell tracking confirm a strong interaction between AP2 and activated arrestin using a phosphorylated C-terminus of CCR5. At the same time, a weak interaction between clathrin and arrestin-2 is observed, irrespective of activation.

These results contrast with previous observations of class A GPCRs and the more direct participation by clathrin. The results are discussed in terms of the importance of short and long phosphorylated bar codes in class A and class B endocytosis.

Strengths:

The 15N,1H, and 13C, methyl TROSY NMR and assignments represent a monumental amount of work on arrestin-2, clathrin, and AP2. Weak NMR interactions between arrestin-2 and clathrin are observed irrespective of the activation of arrestin. A second interface, proposed by crystallography, was suggested to be a possible crystal artifact. NMR establishes realistic information on the clathrin and AP2 affinities to activated arrestin, with both kD and description of the interfaces.

Weaknesses:

This reviewer has identified only minor weaknesses with the study.

(1) Arrestin-2 1-418 resonances all but disappear with CCR5pp6 addition. Are they recovered with Ap2Beta2 addition, and is this what is shown in Supplementary Figure 2D?

(2) I don't understand how methyl TROSY spectra of arrestin2 with phosphopeptide could look so broadened unless there are sample stability problems.

(3) At one point, the authors added an excess fully phosphorylated CCR5 phosphopeptide (CCR5pp6). Does the phosphopeptide rescue resolution of arrestin2 (NH or methyl) to the point where interaction dynamics with clathrin (CLTC NTD) are now more evident on the arrestin2 surface?

(4) Once phosphopeptide activates arrestin-2 and AP2 binds, can phosphopeptide be exchanged off? In this case, would it be possible for the activated arrestin-2 AP2 complex to re-engage a new (phosphorylated) receptor?

(5) Did the authors ever try SEC measurements of arrestin-2 + AP2beta2+CCR5pp6 with and without PIP2, and with and without clathrin (CLTC NTD? The question becomes what the active complex is and how PIP2 modulates this cascade of complexation events in class B receptors.

Reviewer #3 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

No significant weaknesses noted.

Reviewer #2 (Public review):

Li et al. describe ambisim, a tool with the goal of creating realistic synthetic single-nucleus RNA/ATAC sequencing datasets. It has become standard to pool multiple genetically distinct donors when using single-cell sequencing followed by genotype-based demultiplexing (i.e., using donor single-nucleotide variants to identify specific donor origin). A plethora of tools exist to accomplish this demultiplexing, but advanced tools to create synthetic datasets, and therefore provide definitive benchmarking, are lacking. Ambisim is a well-thought-out simulator that improves upon previous tools available by allowing for modeling of variable ambient contamination proportions and doing so in a genotype-aware fashion. This provides more realistic synthetic datasets that provide challenging scenarios for future demultiplexing tools. The authors use ambisim to benchmark a large number of available and commonly used genotype-free and -dependent demultiplexing tools. They identify the strengths and weaknesses of these tools. They also go on to define a new metric, variant consistency, to further assess demultiplexing performance across tools. Overall, this manuscript provides a useful framework to more thoroughly evaluate future demultiplexing tools, as well as provides rationale for tool selection depending on a user's experimental conditions.

The authors provide measured conclusions that are supported by their findings. There are some aspects that are unclear.

(1) Throughout the manuscript, the figure legends are difficult to understand, and this makes it difficult to interpret the graphs.

(2) Since this is both a new tool and a benchmark, it would be worthwhile in the Discussion to comment on which demultiplexing tools one may want to choose for their dataset, especially given the warning against ensemble methods. From this extensive benchmarking, one may want to choose a tool based on the number of donors one has pooled, the modalities present, and perhaps even the ambient RNA (if it has been estimated previously).

(3) What are the minimal computational requirements for running ambisim? What is the time cost?

Reviewer #2 (Public review):

Summary:

The authors perform a series of studies to follow up on their previous work, which established a role for dorsal raphe dopamine neurons (DRN) in the regulation of social-isolation-induced rebound in mice. In the present study, Lee et. al, use a combination of modern circuit tools to investigate putatively distinct roles of DRN dopamine transporting containing (DAT) projections to the bed nucleus of the stria terminalis (BNST), central amygdala (CeA), and posterior basolateral amygdala (BLP). Notably, they reveal that optogenetic stimulation of distinct pathways confers specific behavioral states, with DRNDAT-BLP driving aversion, DRNDAT-BNST regulating non-social exploratory behavior, and DRNDAT-CeA promoting socialability. A combination of electrophysiological studies and in situ hybridization studies reveal heterogenous dopamine and neuropeptide expression and different firing properties, providing further evidence of pathway-specific neural properties. Lastly, the authors combine optogenetics and calcium imaging to resolve social encoding properties in the DRNDAT-CeA pathway, which correlates observed social behavior to socially engaged neural ensembles.

Collectively, these studies provide an interesting way of dissecting out separable features of a complex multifaceted social-emotional state that accompanies social isolation and the perception of 'loneliness.' The main conclusions of the paper provide an important and interesting set of findings that increase our understanding of these distinct DRN projections and their role in a range of social (e.g., prosocial, dominance), non-social, and emotional behaviors. However, as noted below, the examination of these circuits within a homeostatic framework is limited given that a number of the datasets did not include an isolated condition. The DRNDAT-CeA pathway was investigated with respect to social homeostatic states in the present study for some of the datasets.

Strengths:

(1) The authors perform a comprehensive and elegant dissection of the anatomical, behavioral, molecular, and physiological properties of distinct DRN projections relevant to social, non-social, and emotional behavior, to address multifaceted and complex features of social state.

(2) This work builds on prior findings of isolation-induced changes in DRN neurons and provides a working framework for broader circuit elements that can be addressed across social homeostatic state.

(3) This work characterizes a broader circuit implicated in social isolation and provides a number of downstream targets to explore, setting a nice foundation for future investigation.

(4) The studies account for social rank and anxiety-like behavior in several of the datasets, which are important consideration to the interpretation of social motivation states, especially in male mice with respect to dominance behavior.

Weaknesses:

(1) The conceptual framework of the study is based on the premise of social isolation and perceived 'loneliness' under the framework of social homeostasis, analogous to hunger. In this framework, social isolation should provoke an aversive state and compensatory social contact behavior. In the authors' prior work, they demonstrate synaptic changes in DRN neurons and social rebound following acute social isolation. Thus, the prediction would be that downstream projections also would show state dependent changes as a function of social isolation state (e.g., grouped/socially engaged vs. isolated). In the current paper, a social isolation condition was included for some but not all experiments, which should be considered in the interpretation of the data, specifically within the context of dynamic isolation states.

(2) Figure 1 confirms co-laterals in the BNST and CeA via anatomical tracing studies. The goal of the optogenetic studies is to dissociate functional/behavioral roles of distinct projections. One limitation of optogenetic projection targeting is the possibility of back-propagating action potentials (stimulation of terminals in one region may back-propagate to activate cell bodies, and then afferent projections to other regions), and/or stimulation of fibers of passage. However, this is addressed in the discussion and the present data are convincing, which minimizes the concern.

(3) Sex as a biological variable should be considered in the present data, as included in the discussion.

Reviewer #2 (Public review):

Summary:

This paper investigates the neural underpinnings of an interactive speech task requiring verbal coordination with another speaker. To achieve this, the authors recorded intracranial brain activity from the left (and to a lesser extent, the right) hemisphere in a group of drug-resistant epilepsy patients while they synchronised their speech with a 'virtual partner'. Crucially, the authors were able to manipulate the degree of success of this synchronisation by programming the virtual partner to either actively synchronise or desynchronise their speech with the participant, or else to not vary its speech in response to the participant (making the synchronisation task purely one-way). Using such a paradigm, the authors identified different brain regions that were either more sensitive to the speech of the virtual partner (primary auditory cortex), or more sensitive to the degree of verbal coordination (i.e. synchronisation success) with the virtual partner (left secondary auditory cortex and bilateral IFG). Such sensitivity was measured by (1) calculating the correlation between the index of verbal coordination and mean power within a range of frequency bands across trials, and (2) calculating the phase-amplitude coupling between the behavioural and brain signals within single trials (using the power of high-frequency neural activity only). Overall, the findings help to elucidate some of the brain areas involved in interactive speaking behaviours, particularly highlighting high-frequency activity of the bilateral IFG as a potential candidate supporting verbal coordination.

Strengths:

This study provides the field with a convincing demonstration of how to investigate speaking behaviours in more complex situations that share many features with real-world speaking contexts e.g. simultaneous engagement of speech perception and production processes, the presence of an interlocutor and the need for inter-speaker coordination. The findings thus go beyond previous work that has typically studied solo speech production in isolation, and represent a significant advance in our understanding of speech as a social and communicative behaviour. It is further an impressive feat to develop a paradigm in which the degree of cooperativity of the synchronisation partner can be so tightly controlled; in this way, this study combines the benefits of using pre-recorded stimuli (namely, the high degree of experimental control) with the benefits of using a live synchronisation partner (allowing the task to be truly two-way interactive, an important criticism of other work using pre-recorded stimuli). A further key strength of the study lies in its employment of stereotactic EEG to measure brain responses with both high temporal and spatial resolution, an ideal method for studying the unfolding relationship between neural processing and this dynamic coordination behaviour.

Weaknesses:

One limitation of the current study is the relatively sparse coverage of the right hemisphere by the implanted electrodes (91 electrodes in the right compared to 145 in the left). Of course, electrode location is solely clinically motivated, and so the authors did not have control over this. In a previous version of this article, the authors therefore chose not to include data from the right hemisphere in reported analyses. However, after highlighting previous literature suggesting that the right hemisphere likely has high relevance to verbal coordination behaviours such as those under investigation here, the authors have now added analyses of the right hemisphere data to the results. These confirm an involvement of the right hemisphere in this task, largely replicating left hemisphere results. Some hemispheric differences were found in responses within the STG; however, interpretation should be tempered by an awareness of the relatively sparse coverage of the right hemisphere meaning that some regions have very few electrodes, resulting in reduced statistical power.

Reviewer #2 (Public review):

Summary:

Microbial population abundances are regularly estimated by multiplying plate counts by dilution factors, with inferences made about sample heterogeneity without taking into account heterogeneity generated through dilution and plating methods. The authors have developed REPOP, a method for disentangling methodological stochasticity from ecological heterogeneity using a Bayesian framework. They present three models: a unimodal distribution, a multimodal distribution, and a multimodal distribution that incorporates a colony count cutoff. They use a combination of simulated and experimental data to show the effectiveness of the REPOP method in resolving true microbial population distributions.

Strengths:

Overall, this paper addresses a significant issue in microbial ecology and reliably demonstrates that the REPOP method improves upon current methods of estimating microbial population heterogeneity, particularly with simulation data. The three models presented build upon each other and are discussed in a way that is fairly accessible to a broad audience. The authors also show that leveraging the information provided by non-countable plates is important. Additionally, the authors address the potential for extending this method to other sources of methodological stochasticity that may occur in microbial plating. However, it does seem that they could extend this further by discussing ways that this method could be applied to non-microbial systems, allowing this work to appeal to a broader audience.

Weaknesses:

A more thorough discussion of when and by how much estimated microbial population abundance distributions differ from the ground truth would be helpful in determining the best practices for applying this method. Not only would this allow researchers to understand the sampling effort necessary to achieve the results presented here, but it would also contextualize the experimental results presented in the paper. Particularly, there is a disconnect between the discussion of the large sample sizes necessary to achieve accurate multimodal distribution estimates and the small sample sizes used in both experiments.

Reviewer #2 (Public review):

Summary:

The study in question utilizes functional magnetic resonance imaging (fMRI) to dynamically estimate the locus and extent of covert spatial attention from visuocortical activity. The authors aim to address an important gap in our understanding of how the size of the attentional field is represented within the visual cortex. They present a novel paradigm that allows for the estimation of the spatial tuning of the attentional field and demonstrate the ability to reliably recover both the location and width of the attentional field based on BOLD responses.

Strengths:

(1) Innovative Paradigm: The development of a new approach to estimate the spatial tuning of the attentional field is a significant strength of this study. It provides a fresh perspective on how spatial attention modulates visual perception.

(2) Refined fMRI Analysis: The use of fMRI to track the spatial tuning of the attentional field across different visual regions is methodologically rigorous and provides valuable insights into the neural mechanisms underlying attentional modulation.

(3) Clear Presentation: The manuscript is well-organized, and the results are presented clearly, which aids in the reader's comprehension of the complex data and analyses involved.

Weaknesses:

(1) Lack of Neutral Cue Condition: The study does not include a neutral cue condition where the cue width spans 360{degree sign}, which could serve as a valuable baseline for assessing the BOLD response enhancements and diminishments in both attended and non-attended areas.

(2) Clarity on Task Difficulty Ratios: The explicit reasoning for the chosen letter-to-number ratios for various cue widths is not detailed. Ensuring clarity on these ratios is crucial, as it affects the task difficulty and the comparability of behavioral performance across different cue widths. It is essential that observed differences in behavior and BOLD signals are attributable solely to changes in cue width and not confounded by variations in task difficulty.

Comments on revisions:

(1) Please standardize the naming of error metrics across Figures 4-6 to improve clarity (e.g., "angular error" (Figure 4), "|angular error|" (Figure 5), and "absolute error" (Figure 6) appear to refer to the same measure). This inconsistency is also present in the main text.

(2) Consider briefly mentioning the baseline offset in Lines 179-186. It is included in Figures 4-7 and serves as a reference for interpreting attentional modulation alongside gain. Introducing it with other model parameters would improve clarity.

(3) It may be valuable to examine BOLD responses in unattended visual regions. As shown in Figure 2a, suppression patterns (e.g., the most negative responses) appear to vary in extent and distribution with attentional cue width. Analyzing these unattended regions may offer a more complete view of how attention shapes the spatial profile of cortical activity.

Reviewer #2 (Public review):

Summary:

The authors were trying to establish the role of Plasmodium falciparum surface protein 2 in merozoite biology, specifically the process of erythrocyte invasion.

Strengths:

The major strengths of the manuscript are in the Plasmodium falciparum genetic and phenotyping approaches. PfMSP2 knockouts are made in two different strains, which is important as it is known that invasion pathways can vary between strains, but is a level of comprehensiveness that is not always delivered in P. falciparum genetic studies. The knockout strains are characterised very thoroughly using multiple different assays, and the authors should be commended for publishing a good deal of negative data, where no phenotype was detected. This is not always done, but is very helpful for the field and reduces the potential for experimental redundancy, i.e., others repeating work that has already been performed but never published. The quality of the writing, referencing, and figures is also generally strong, although a few minor typos and technical comments on presentation have been communicated to the authors.

Weaknesses:

There are, however, some areas that are weaker.

(1) The section describing Laverania and avian Plasmodium MSP2 comparison is a lengthy section and could be told much more concisely for clarity in delivering the key message, i.e., that conservation in distantly related Plasmodium species could indicate an important function. The identification of MSP2-like genes in avian Plasmodium species was highlighted previously in the referenced Escalante paper, so it is not entirely novel, although this paper goes into more detailed characterisation of the extent of conservation. Overall, this section takes up much more space in the manuscript than is merited by the novelty and significance of the findings.

(2) Characterisation of the knockout strains is generally thorough, though relatively few interactions were followed by live microscopy (Figures 3E-H). A minimum of 30 merozoites were followed in each assay (although the precise number is not specified in the figure or legend), but there are intriguing trends in the data that could potentially have become significant if n was increased.

(3) The comparative RNAseq data is interesting, but is not followed up to any significant degree. Multiple transcripts are up-regulated in the absence of PfMSP2, but they are largely dismissed because they are genes of unknown function, not previously linked to invasion, or lack an obvious membrane anchor. Having gone to the lengths of exploring potentially compensatory changes in gene expression, it is disappointing not to validate or explore the hits that result.

(4) Given the abundance of PfMSP2 on the merozoite surface, it would have been interesting to see whether the knockout lines have any noticeable difference in surface composition, as viewed by electron microscopy, although, of course, this experiment relies on access to the appropriate facilities.

(5) One of the key findings is that deletion of PfMSP2 increases inhibition by some antibodies/nanobodies (some anti-CSS2, some anti-AMA1) but not others (anti-EBA/RH, anti-EBA175, anti-Rh5, anti-TRAMP, some anti-CSS2, some anti-AMA1). The data supporting these changes in inhibition are solid, but the selectivity of the effect (only a few antibodies, and generally those targeting later stages in invasion) is not really discussed in any detail. Do the authors have a hypothesis for this selectivity? The authors make attempts to explore the mechanisms for this antibody-masking (Figure 7), but the data is less solid. Surface Plasmon Resonance was non-conclusive, while an ELISA approach co-incubating MSP2 and anti-AMA1 antibodies to wells coated with AMA1 lacks appropriate controls (eg, including other merozoite proteins in similar experiments).

Overall, the claim that PfMSP2 is non-essential for in vitro growth is well justified and is an important contribution to the field. The impact of PfMSP2 deletion on antibody inhibition (which is highlighted in the title of the manuscript) and the mechanism behind it is much less definitive, but does open up an interesting area for further investigation, with more work to be done.

Reviewer #2 (Public review):

Summary:

Guo et al. benchmarked and optimized methods for detecting Identity-By-Descent (IBD) segments in Plasmodium falciparum (Pf) genomes, which are characterized by high recombination rates and low marker density. Their goal was to address the limitations of existing IBD detection tools, which were primarily developed for human genomes and do not perform well in the genomic context of highly recombinant genomes. They first analysed various existing IBD callers, such as hmmIBD, isoRelate, hap-IBD, phased-IBD, and refinedIBD. They focused on the impact of recombination on the accuracy, which was calculated based on two metrics, the false negative rate and the false positive rate. The results suggest that high recombination rates significantly reduce marker density, leading to higher false negative rates for short IBD segments. This effect compromises the reliability of IBD-based downstream analyses, such as effective population size (Ne) estimation.<br /> They showed that the best tool for IBD detection in Pf is hmmIBD, because it has relatively low FN/FP error rates and is less biased for relatedness estimates. However, this method is less computationally efficient.<br /> Their suggestion is to optimize human-oriented IBD methods and use hmmIBD only for the estimation of Ne.

Strengths:

Although I am not an expert on Plasmodium falciparum genetics, I believe the authors have developed a valuable benchmarking framework tailored to the unique genomic characteristics of this species. Their framework enables a thorough evaluation of various IBD detection tools for non-human data, such as high recombination rates and low marker density, addressing a key gap in the field.

This study provides a comparison of multiple IBD detection methods, including probabilistic approaches (hmmIBD, isoRelate) and IBS-based methods (hap-IBD, Refined IBD, phased IBD). This comprehensive analysis offers researchers valuable guidance on the strengths and limitations of each tool, allowing them to make informed choices based on specific use cases. I think this is important beyond the study of Pf.

The authors highlight how optimized IBD detection can help identify signals of positive selection, infer effective population size (Ne), and uncover population structure.

They demonstrate the critical importance of tailoring analytical tools to suit the unique characteristics of a species. Moreover, the authors provide practical recommendations, such as employing hmmIBD for quality-sensitive analyses and fine-tuning parameters for tools originally designed for non-P. falciparum datasets before applying them to malaria research.

Overall, this study represents a meaningful contribution to both computational biology and malaria genomics, with its findings and recommendations likely to have an impact on the field.

Weaknesses:

One weakness of the study is the lack of emphasis on the broader importance of studying Plasmodium falciparum as a critical malaria-causing organism. Malaria remains a significant global health challenge, causing hundreds of thousands of deaths annually.

While the study provides a thorough technical evaluation of IBD detection methods and their application to Pf, it does not adequately connect these findings to the broader implications for malaria research and control efforts. Additionally, the discussion on malaria and its global impact could have framed the study in a more accessible and compelling way, making the importance of these technical advances clearer to a broader audience, including researchers and policymakers in the fight against malaria. In the revised version, the authors have placed greater emphasis on this aspect, while still maintaining the methodological focus of the paper.

Reviewer #2 (Public review):

Gekko et al investigate the impact of perturbing mitochondrial during early embryo development, through modulation of the mitochondrial fission protein Drp1 using Trim-Away technology. They aimed to validate a role for mitochondrial dynamics in modulating chromosomal segregation, mitochondrial inheritance and embryo development and achieve this through the examination of mitochondrial and endoplasmic reticulum distribution, as well as actin filament involvement, using targeted plasmids, molecular probes and TEM in pronuclear stage embryos through the first cleavages divisions. Drp1 deletion perturbed mitochondrial distribution, leading to asymmetric partitioning of mitochondria to the 2-cell stage embryo, prevented appropriate chromosomal segregation and culminated in embryo arrest. Resultant 2-cell embryos displayed altered ATP, mtDNA and calcium levels. Microinjection of Drp1 mRNA partially rescued embryo development. A role for actin filaments in mitochondrial inheritance is described, however the actin-based motor Myo19 does not appear to contribute.

Overall, this study builds upon their previous work and provides further support for a role of mitochondrial dynamics in mediating chromosomal segregation and mitochondrial inheritance. In particular, Drp1 is required for the redistribution of mitochondria to support symmetric partitioning and ongoing development.

Strengths:

The study is well designed, the methods are appropriate and the results are clearly presented. The findings are nicely summarised in a schematic.

The addition of further quantification, including mitochondrial cluster size, elongation/aspect ratio and ROS, as requested by the reviewers, has provided further evidence for the impact of Drp1 depletion on mitochondrial morphology and function.

Understanding the role of mitochondria in binucleation and mitochondrial inheritance is of clinical relevance for patients undergoing infertility treatment, particularly those undergoing mitochondrial replacement therapy.

Weaknesses:

The only remaining weakness is that the authors have not undertaken additional experiments to clarify any role for mitochondrial transport following Drp1 depletion.

Reviewer #2 (Public review):

Summary:

The manuscript by Chuah et al. reports the experimental results that suggest the occupancy of the HbYX pockets suffices for proteasome gate opening. The authors conducted cryo-EM reconstructions of two mutant archaeal proteasomes. The work is technically sound and may be of special interest in the field of structural biology of the proteasomes.

Strengths:

Overall, the work incrementally deepens our understanding of the proteasome activation and expands the structural foundation for therapeutic intervention of proteasome function. The evidence presented appears to be well aligned with the existing literature, which adds confidence in the presentation.

Comments on revisions:

The authors have addressed all my questions.

Reviewer #2 (Public review):

This work describes the single-cell expression profiling of thousands of cells of recombinant genotypes from a model natural-variation system, a cross between two divergent yeast strains.

I appreciate the addition of lines 282-291, which now makes the authors' point about one advantage of the single-cell technique for eQTL mapping clearly: the authors don't need to normalize for culture-to-culture variation the way standard bulk methods do (e.g. in Albert et al., 2018 for the current yeast cross), and without this normalization, they can integrate analyses of expression with those of estimates of growth behaviors from the abundance of a genotype in the pool. The main question the manuscript addresses with the latter, in Figure 3, is how much variation in growth appears to have nothing to do with expression, for which the answer the authors given is 30%. I agree that this represents a novel finding. The caveats are (1) the particular point will perhaps only be interesting to a small slice of the eQTL research community; (2) the authors provide no statistical controls/error estimate or independent validation of the variance partitioning analysis in Figure 3, and (3) the authors don't seem to use the single-cell growth/fitness estimates for anything else, as Figure 4 uses loci mapped to growth from a previously published, standard culture-by-culture approach.

Reviewer #2 (Public review):

Summary:

This study investigates the role of KIF7, a ciliary kinesin involved in the Sonic Hedgehog (SHH) signaling pathway, in cortical development using Kif7 knockout mice. The researchers examined embryonic cortex development (mainly at E14.5), focusing on structural changes and neuronal migration abnormalities.

Strengths:

(1) The phenotype observed is interesting, and the findings provide neurodevelopmental insight into some of the symptoms and malformations seen in patients with KIF7 mutations.

(2) The authors assess several features of cortical development, including structural changes in layers of the developing cortex, connectivity of the cortex with thalamus, as well as migration of cINs from CGE and MGE to cortex.

Weaknesses:

(1) The Kif7 null does have phenotype differences from individual mutations seen in patients. It would be interesting to add more thoughts about how the null differs from these mutants in ciliary structure and SHH signaling via the cilium.

(2) The description of altered cortex development at E14.5 is perhaps rather descriptive. It would be useful to assess more closely the changes occurring in different cell types and stages. For this it seems very important to have a time course of cortical development and how the structural organization changes over time. This would be easy to assess with the addition of serial sections from the same mice. It might also be interesting to see how SHH signaling is altered in different cortical cell types over time with a SHH signaling reporter mouse.

(3) Abnormal neurodevelopmental phenotypes have been widely reported in the absence of other key genes affecting primary cilia function (Willaredt et al., J Neurosci 2008; Guo et al., Nat Commun 2015). It would be interesting to have more discussion of how the Kif7 null phenotype compares to some of these other mutants.

(4) The authors see alterations in cIN migration to the cortex and observe distinct differences in the pattern of expression of Cxcl12 as well as suggest cell intrinsic differences within cIN in their ability to migrate. The slice culture experiments though make it a little difficult to interpret the cell intrinsic effects on cIN of loss of Kif7, as the differences in Cxcl12 patterns still exist presumably in the slice cultures. It would be useful to assess their motility in an assay where they were isolated, as well as assess transcriptional changes in cINs in vivo lacking KIF7 for expression patterns that may affect motility or other aspects of migration.

Comments on revisions:

The authors have made significant and thoughtful responses as well as experimental additions to the authors comments. Their efforts are appreciated and the manuscript is much improved.

Reviewer #2 (Public review):

This study investigates the role of cDC1 in atherosclerosis progression using Xcr1Cre-Gfp Rosa26LSL-DTA ApoE-/- mice. The authors demonstrate that selective depletion of cDC1 reduces atherosclerotic lesions in hyperlipidemic mice. While cDC1 depletion did not alter macrophage populations, it suppressed T cell activation (both CD4+ and CD8+ subsets) within aortic plaques. Further, targeting the chemokine Xcl1 (ligand of Xcr1) effectively inhibits atherosclerosis. The manuscript is well-written, and the data are clearly presented. However, several points require clarification:

(1) In Figure 1C (upper plot), it is not clear what the Xcr1 single-positive region in the aortic root represents, or whether this is caused by unspecific staining. So I wonder whether Xcr1 single-positive staining can reliably represent cDC1. For accurate cDC1 gating in Figure 1E, Xcr1+CD11c+ co-staining should be used instead.

(2) Figure 4D suggests that cDC1 depletion does not affect CD4+/CD8+ T cells. However, only the proportion of these subsets within total T cells is shown. To fully interpret effects, the authors should provide:<br /> a) Absolute numbers of total T cells in aortas.<br /> b) Absolute counts of CD4+ and CD8+ T cells.

(3) How does T cell activation mechanistically influence atherosclerosis progression? Why was CD69 selected as the sole activation marker? Were other markers (e.g., KLRG1, ICOS, CD44) examined to confirm activation status?

(4) Figure 7B: Beyond cDC1/2 proportions within cDCs, please report absolute counts of: Total cDCs,cDC1, and cDC2 subsets. Figure 7D: In addition to CD4+/CD8+ T cell proportions, the following should be included:<br /> a) Total T cell numbers in aortas<br /> b) Absolute counts of CD4+ and CD8+ T cells.

(5) cDC1 depletion reduced CD69+CD4+ and CD69+CD8+ T cells, whereas Xcl1 depletion decreased Xcr1+ cDC1 cells without altering activated T cells. How do the authors explain these different results? This discrepancy needs explanation.

Reviewer #2 (Public review):

Summary:

Wang et al. studied the therapeutic potential of focused ultrasound noninvasively stimulating the spleen (FUS sti. spleen) to modulate the splenic immunity, with an aim to exert anti-tumor effect. They found that the treatment enhanced antitumor capability in CD8 T/ NK cells and reduced the immunosuppression, facilitating the inhibition of HCC growth in vivo.

Strengths:

They have utilized bulk RNA sequencing, single cell RNA sequencing, and flow cytometry to investigate the immune and tumor cell profiling in the mouse models upon FUS sti. spleen. Moreover, they highlighted the importance of combining FUS with spleen-targeted nanodroplets encapsulating bioavailable calcium ions (STND@Ca2+), which facilitated the calcium influx into the murine spleen and further enhanced the therapeutic efficacy of FUS.

Weaknesses:

While the study is interesting and potentially clinically impactful, the mechanism of action of the therapy is not fully elucidated. It would benefit from more rigorous approaches. With the theoretical part strengthened, this paper would be of interest to cancer cell biologists and clinician scientists working on the oncology field.

Reviewer #2 (Public review):

Summary:

Xu et al. used fMRI to examine the neural correlates associated with retrieving temporal information from an external compared to internal perspective ('mental time watching' vs. 'mental time travel'). Participants first learned a fictional religious ritual composed of 15 sequential events of varying durations. They were then scanned while they either (1) judged whether a target event happened in the same part of the day as a reference event (external condition); or (2) imagined themselves carrying out the reference event and judged whether the target event occurred in the past or will occur in the future (internal condition). Behavioural data suggested that the perspective manipulation was successful: RT was positively correlated with sequential distance in the external perspective task, while a negative correlation was observed between RT and sequential distance for the internal perspective task. Neurally, the two tasks activated different regions, with the external task associated with greater activity in the supplementary motor area and supramarginal gyrus, and the internal condition with greater activity in default mode network regions. Of particular interest, only a cluster in the posterior parietal cortex demonstrated a significant interaction between perspective and sequential distance, with increased activity in this region for longer sequential distances in the external task, but increased activity for shorter sequential distances in the internal task. Only a main effect of sequential distance was observed in the hippocampus head, with activity being positively correlated with sequential distance in both tasks. No regions exhibited a significant interaction between perspective and duration, although there was a main effect of duration in the hippocampus body with greater activity for longer durations, which appeared to be driven by the internal perspective condition. On the basis of these findings, the authors suggest that the hippocampus may represent event sequences allocentrically, whereas the posterior parietal cortex may process event sequences egocentrically.

Strengths:

The topic of egocentric vs. allocentric processing has been relatively under-investigated with respect to time, having traditionally been studied in the domain of space. As such, the current study is timely and has the potential to be important for our understanding of how time is represented in the brain in the service of memory. The study is well thought out, and the behavioural paradigm is, in my opinion, a creative approach to tackling the authors' research question. A particular strength is the implementation of an imagination phase for the participants while learning the fictional religious ritual. This moves the paradigm beyond semantic/schema learning and is probably the best approach besides asking the participants to arduously enact and learn the different events with their exact timings in person. Importantly, the behavioural data point towards successful manipulation of internal vs. external perspective in participants, which is critical for the interpretation of the fMRI data. The use of syllable length as a sanity check for RT analyses, as well as neuroimaging analyses, is also much appreciated.

Weaknesses/Suggestions:

Although the design and analysis choices are generally solid, there are a few finer details/nuances that merit further clarification or consideration in order to strengthen the readers' confidence in the authors' interpretation of their data.

(1) Given the known behavioural and neural effects of boundaries in sequence memory, I was wondering whether the number of traversed context boundaries (i.e., between morning-afternoon, and afternoon-evening) was controlled for across sequential length in the internal perspective condition? Or, was it the case that reference-target event pairs with higher sequential numbers were more likely to span across two parts of the day compared to lower sequential numbers? Similarly, did the authors examine any potential differences, whether behaviourally or neurally, for day part same vs. day part different external task trials?

(2) I would appreciate further insight into the authors' decision to model their task trials as stick functions with duration 0 in their GLMs, as opposed to boxcar functions with varying durations, given the potential benefits of the latter (e.g., Grinband et al., 2008). I concur that in certain paradigms, RT is considered a potential confound and is taken into account as a nuisance covariate (as the authors have done here). However, given that RTs appear to be critical to the authors' interpretation of participant behavioural performance, it would imply that variations in RT actually reflect variations in cognitive processes of interest, and hence, it may be worth modelling trials as boxcar functions with varying durations.

(3) The activity pattern across tasks and sequential distance in the posterior parietal cortex appears to parallel the RT data. Have the authors examined potential relationships between the two (e.g., individual participant slopes for RT across sequential distance vs. activity betas in the posterior parietal cortex)?

(4) There were a few places in the manuscript where the writing/discussion of the wider literature could perhaps be tightened or expanded. For instance:

i) On page 16, the authors state 'The negative correlation between the activation level in the right PPC and sequential distance has already been observed in a previous fMRI study (Gauthier & van Wassenhove, 2016b). The authors found a similar region (the reported MNI coordinate of the peak voxel was 42, -70, 40, and the MNI coordinate of the peak voxel in the present study was 39, -70, 35), of which the activation level went up when the target event got closer to the self-positioned event. This finding aligns with the evidence suggesting that the posterior parietal cortex implements egocentric representations.' Without providing a little more detail here about the Gauthier & van Wassenhove study and what participants were required to do (i.e., mentally position themselves at a temporal location and make 'occurred before' vs. 'occurred after' judgements of a target event), it could be a little tricky for readers to follow why this convergence in finding supports a role for the posterior parietal cortex in egocentric representations.

ii) Although the authors discuss the Lee et al. (2020) review and related studies with respect to retrospective memory, it is critical to note that this work has also often used prospective paradigms, pointing towards sequential processing being the critical determinant of hippocampal involvement, rather than the distinction between retrospective vs. prospective processing.

iii) The authors make an interesting suggestion with respect to hippocampal longitudinal differences in the representation of event sequences, and may wish to relate this to Montagrin et al. (2024), who make an argument for the representation of distant goals in the anterior hippocampus and immediate goals in the posterior hippocampus.

Reviewer #2 (Public review):

Summary:

In this paper, the authors present a detailed computational model and experimental data concerning overground locomotion in rats before and after recovery from spinal cord injury. They are able to manually tune the parameters of this physiologically based, detailed model to reproduce many aspects of the observed animals' locomotion in the naive case and in two distinct injury cases.

Strengths:

The strengths are that the model is driven to closely match clean experimental data, and the model itself has detailed correspondence to proposed anatomical reality. As such, this makes the model more readily applicable to future experimental work. It can make useful suggestions. The model reproduces a large number of conditions across frequencies, and with the model structure changed by injury and recovery. The model is extensive and is driven by known structures, with links to genetic identities, and has been extensively validated across multiple experiments and manipulations over the years. It models a system of critical importance to the field, and the tight coupling to experimental data is a real strength.

Weaknesses:

A downside is that, scientifically, here, the only question tackled is one of sufficiency. By manually tuning parameters in a manner that aligns with the field's understanding from experimental work, the detailed model can accurately reproduce the experimental findings. One of the benefits of computational models is that the counterfactual can be tested to provide evidence against alternative hypotheses. That isn't really done here. I'm fairly certain that there are competing theories regarding what happens during recovery from a hemi-section injury and a contusion injury. The model could be used to make predictions for some alternative hypotheses, supporting or rejecting theories of recovery. This may be part of future plans. Here, the focus is on showing that the model is capable of reproducing the experimental results at all, for any set of parameters, however tuned.

Reviewer #2 (Public review):

Significance:

TREM2 is an immunomodulatory receptor expressed on myeloid cells and microglia in the brain. TREM2 consists of a single immunoglobular (Ig) domain that leads into a flexible stalk, transmembrane helix, and short cytoplasmic tail. Extracellular proteases can cleave TREM2 in its stalk and produce a soluble TREM2 (sTREM2). TREM2 is genetically linked to Alzheimer's disease (AD), with the strongest association coming from an R47H variant in the Ig domain. Despite intense interest, the full TREM2 ligand repertoire remains elusive, and it is unclear what function sTREM2 may play in the brain. The central goal of this paper is to assess the ligand-binding role of the flexible stalk that is generated during the shedding of TREM2. To do this, the authors simulate the behavior of constructs with and without stalk. However, it is not clear why the authors chose to use the isolated Ig domain as a surrogate for full-length TREM2. Additionally, experimental binding evidence that is misrepresented by the authors contradicts the proposed role of the stalk.

Summary and strengths:

The authors carry out MD simulations of WT and R47H TREM2 with and without the flexible stalk. Simulations are carried out for apo TREM2 and for TREM2 in complex with various lipids. They compare results using just the Ig domain to results including the flexible stalk that is retained following cleavage to generate sTREM2. The computational methods are well-described and should be reproducible. The long simulations are a strength, as exemplified in Figure 2A where a CDR2 transition happens at ~400-600 ns. The stalk has not been resolved in structural studies, but the simulations suggest the intriguing and readily testable hypothesis that the stalk interacts with the Ig domain and thereby contributes to the stability of the Ig domain and to ligand binding. I suspect biochemists interested in TREM2 will make testing this hypothesis a high priority.

Comments on latest version:

The authors have addressed my critiques and carried out additional simulations, as requested. I would upgrade my assessment of the evidence to "solid."

Reviewer #3 (Public review):

Summary:

Using flies, Kazama et al. combined behavioral analysis, electrophysiological recordings, and calcium imaging experiments to elucidate how odors activate gustatory receptor neurons (GRNs) and elicit a proboscis extension response, which is interpreted as a feeding response.

The authors used DeepLabCut v2.0 to estimate the extension of the proboscis, which represents an unbiased and more precise method for describing this behavior compared to manual scoring.

They demonstrated that the probability of eliciting a proboscis extension increases with higher odor concentrations. The most robust response occurs at a 0.5 v/v concentration, which, despite being diluted in the air stream, remains a relatively high concentration. Although the probability of response is not particularly high it is higher than control stimuli. Notably, flies respond with a proboscis extension to both odors that are considered positive and those regarded as negative.

The authors used various transgenic lines to show that the response is mediated by GRNs. Specifically, inhibiting Gr5a reduces the response, while inhibiting Gr66a increases it in fed flies. Additionally, they find that odors induce a strong positive response in both types of GRNs, which is abolished when the labella of the proboscis are covered. This response was also confirmed through electrophysiological tip recordings.

Finally, the authors demonstrated that the response increases when two stimuli of different modalities, such as sucrose and odors, are presented together, suggesting clear multimodal integration

Strengths:

The integration of various techniques, which collectively supports the robustness of the results.<br /> The assessment of electrophysiological recordings in intact animals, preserving natural physiological conditions.

Weaknesses:

Only highly concentrated odours are capable of evoking positive responses and, even then, the proportion remains relatively low.

The authors have incorporated my suggestions.

Reviewer #3 (Public review):

Summary:

A long noncoding RNA, lnc-FANCI-2, was reported to be regulated by HPV E7 oncoprotein and a cell transcription factor, YY1 by this group. The current study focuses on the function of lnc-FANCI-2 in HPV-16 positive cervical cancer is to intrinsically regulate RAS signaling, thereby facilitating our further understanding additional cellular alterations during HPV oncogenesis. Authors used the advanced technical approaches such as KO, transcriptome and (IRPCRP) and LC- MS/MS analyses in the current study and concluded that KO Inc-FANCI-2 significantly increase RAS signaling, especially phosphorylation of Akt and Erk1/2.

Strengths:

(1) HPV E6E7 are required for full immortalization and maintenance of malignant phenotype of cervical cancer, but they are NOT sufficient for full transformation and tumorigenesis. This study helps further the understanding of other cellular alterations in HPV oncogenesis.<br /> (2) lnc-FANCI-2 is upregulated in cervical lesion progression from CIN1, CIN2-3 to cervical cancer, cancer cell lines and HPV transduced cell lines.<br /> (3) Viral E7 of high-risk HPVs and host transcription factor YY1 are two major factors promoting lnc-FANCI-2 expression.<br /> (4) Proteomic profiling of cytosolic and secreted proteins showed inhibition of MCAM, PODXL2 and ECM1 and increased levels of ADAM8 and TIMP2 in KO cells.<br /> (5) RNA-seq analyses revealed that KO cells exhibited significantly increased RAS signaling but decreased IFN pathways.<br /> (6) Increased phosphorylated Akt and Erk1/2, IGFBP3, MCAM, VIM, and CCND2 (cyclin D2) and decreased RAC3 were observed in KO cells.

Comments on revisions:

The revised manuscript has been significantly improved. The authors addressed all my concerns.

Reviewer #2 (Public review):

The paper deals with the important question of gene epistasis, focusing on asking what is the correct null model for which we should declare no epistasis.

In the first part, they use the Synthetic Genetic Array dataset to claim that the effects of a double mutation on growth rate is well predicted by the product of the individual effects (much more than e.g. the additive model). The second (main) part shows this is also the prediction of two simple, coarse-grained models for cell growth.

I find the topic interesting, the paper well written, and the approach innovative.

Comments on revisions:

The authors have adequately addressed the comments raised in the review below, and I find that the paper has improved.

Reviewer #2 (Public review):

Summary:

The authors have tried to determine the regulatory role of Phosphoglycerate mutate (PGAM), an enzyme involved in converting 3-phosphoglycerate to 2-phosphoglycerate in glycolysis, in differentiation and suppressive function of regulatory CD4 T cells through de novo serine synthesis. This is done by contributing one carbon metabolism and eventually epigenetic regulation of Treg differentiation.

Strengths:

The authors have rigorously used inhibitors and antisense RNA to verify the contribution of these pathways in Treg differentiation in-vitro. This has also been verified in an in-vivo murine model of autoimmune colitis. This has further clinical implications in autoimmune disorders and cancer.

[Editors' note: The authors addressed important comments by the reviewers.]

Reviewer #2 (Public review):

Summary:

The authors set out to characterise the GPCR family in choanoflagellates (and other unicellular holozoans). GPCRs are the most abundant gene family in many animal genomes, playing crucial roles in a wide range of physiological processes. Although they are known to evolve rapidly, GPCRs are an ancient feature of eukaryotic biology. Identifying conserved elements across the animal-protist boundary is therefore a valuable goal, and the increasing availability of genomes from non-animal holozoans provides new opportunities to explore evolutionary patterns that were previously obscured by limited taxon sampling. This study presents a comprehensive re-examination of GPCRs in choanoflagellates, uncovering examples of differential gene retention and revealing the dynamic nature of the GPCR repertoire in this group. As GPCRs are typically involved in environmental sensing, understanding how these systems evolved may shed light on how our unicellular ancestors adapted their signalling networks in the transition to complex multicellularity.

Strengths:

The paper combines a broad taxonomic scope with the use of both established and recently developed tools (e.g., Foldseek, AlphaFold), enabling a deep and systematic exploration of GPCR diversity. Each family is carefully described, and the manuscript also functions as an up-to-date review of GPCR classification and evolution. Although similar attempts to understand GPCR evolution were made over the last decade, the authors build on this foundation by identifying new families and applying improved computational methods to better predict structure and function. Notably, the presence of Rhodopsin-like GPCRs in some choanoflagellates and ichthyosporeans is intriguing, even though they do not fall within known animal subfamilies. The computational framework presented here is broadly applicable, offering a blueprint for surveying GPCR diversity in other non-model eukaryotes (and even in animal lineages), potentially revealing novel families relevant to drug discovery or helping revise our understanding of GPCR evolution beyond model systems.

Weaknesses:

While the study contributes several interesting observations, it does not radically revise the evolutionary history of the GPCR family. However, in an era increasingly concerned with the reproducibility of scientific findings, this is arguably a strength rather than a weakness. It is encouraging to see that previously established patterns largely hold, and that with expanded sampling and improved methods, new insights can be gained, especially at the level of specific GPCR subfamilies. Then, no functional follow-ups are provided in the model system Salpingoeca rosetta, but I am sure functional work on GPCRs in choanoflagellates is set to reveal very interesting molecular adaptations in the future.

Reviewer #2 (Public review):

Summary:

This important theoretical and computational study by Burger and Gerland attempts to set environmental, compositional, kinetic, and thermodynamic constraints on the proposed virtual circular genome (VCG) model for the early non-enzymatic replication of RNA. The authors create a solid kinetic model using published kinetic and thermodynamic parameters for non-enzymatic RNA ligation and (de)hybridization, which allows them to test a variety of hypotheses about the VCG. Prominently, the authors find that the length (longer is better) and concentration (intermediate is better) of the VCG oligos have an outsized impact on the fidelity and yield of VCG production with important implications for future VCG design. They also identify that activation of only RNA monomers, which can be achieved using environmental separation of the activation and replication, can relax the constraints on the concentration of long VCG component oligos by avoiding the error-prone oligo-oligo ligation. Finally, in a complex scenario with multiple VCG oligo lengths, the authors demonstrate a clear bias for the extension of shorter oligos compared to the longer ones. This effect has been observed experimentally (Ding et al., JACS 2023) but was unexplained rigorously until now. Overall, this manuscript will be of interest to scientists studying the origin of life and the behavior of complex nucleic acid systems.

Strengths:

- The kinetic model is carefully and realistically created, enabling the authors to probe the VCG thoroughly.<br /> - Fig. 6 outlines important constraints for scientists studying the origin of life. It supports the claim that the separation of activation and replication chemistry is required for efficient non-enzymatic replication. One could easily imagine a scenario where activation of molecules occurs, followed by their diffusion into another environment containing protocells that encapsulate a VCG. The selective diffusion of activated monomers across protocell membranes would then result in only activated monomers being available to the VCG, which is the constraint outlined in this work. The proposed exclusive replication by monomers also mirrors the modern biological systems, which nearly exclusively replicate by monomer extension.<br /> - Another strength of the work is that it explains why shorter oligos extend better compared to the long ones in complex VCG mixtures. This point is independent of the activation chemistry used (it simply depends on the kinetics and thermodynamics of RNA base-pairing) so it should be very generalizable.

Reviewer #2 (Public review):

Summary:

The research identifies two main SiNET subtypes (epithelial-like and neuronal-like) and reveals heterogeneity in non-neuroendocrine cells within the tumor microenvironment. The study validates findings using external datasets and explores unexpected proliferation patterns. While it contributes to understanding SiNET oncogenic processes, the limited sample size and depth of analysis present challenges to the robustness of the conclusions.

Strengths:

The studies effectively identified two subtypes of SiNET based on epithelial and neuronal markers. Key findings include the low proliferation rates of neuroendocrine (NE) cells and the role of the tumor microenvironment (TME), such as the impact of Macrophage Migration Inhibitory Factor (MIF).

Weaknesses:

However, the analysis faces challenges such as a small sample size and lack of clear biological interpretation in some analyses.

Reviewer #2 (Public review):

Summary:

This paper investigates the evolution of pesticide resistance in the two-spotted spider mite following the introduction of an SDHI acaricide, cyatpyrafen, in China. The authors make use of cyatpyrafen-naive populations collected before that pesticide was first used, as well as more recent populations (both sensitive and resistant) to conduct comparative population genomics. They report 15 different mutations in the insecticide target site from resistant populations, many reported here for the first time, and look at the mutation and selection processes underlying the evolution of resistance, through GWAS, haplotype mapping, and testing for loss of diversity indicating selective sweeps. None of the target site mutations found in resistant populations was found in pre-exposure populations, suggesting that the mutations may have arisen de novo rather than being present as standing variation, unless initially present at very low frequencies; a de novo origin is also supported by evidence of selective sweeps in some resistant populations. Furthermore, there is no significant evidence of migration of resistant genotypes between the sampled field populations indicating multiple origins of common mutations. Overall, this indicates a very high mutation rate and a wide range of mutational pathways to resistance for this target site in this pest species. The series of population genomic analyses carried out here, in addition to the evolutionary processes that appear to underly resistance development in this case, could have implications for the study of resistance evolution more widely.

Strengths:

This paper combines phenotypic characterisation with extensive comparative population genomics, made possible by the availability of multiple population samples (each with hundreds of individuals) collected before as well as after then introduction of the pesticide cyatpyrafen, as well as lab-evolved lines. This resuts in findings of mutation and selection processes that can be related back to the pesticide resistance trait of concern. Large numbers of mites were tested phenotypically to show the levels of resistance present, and the authors also made near-isogenic lines to confirm the phenotypic effects of key mutations. The population genomic analyses consider a range of alternative hypotheses, including mutations arising by de novo mutation or selection from standing genetic variation; and mutations in different populations arising independently or arriving by migration. The claim that mutations most likley arose by multiple repeated de novo mutations is therefore supported by multiple lines of evidence: the direct evidence of none of the mutations being found in over 2000 individuals from naive populations, and the indirect evidence from population genomics showing evidence of selective sweeps but not of significant migration between the sampled populations.

Weaknesses:

As acknowledged within the discussion, whilst evidence supports a de novo origin of the resistance associated mutations, this cannot be proven definitively as mutations may have been present at a very low frequency and therefore not found within the tested pesticide-naive population samples.

Near-isofemale lines were made to confirm the resistance levels associated with five of the 15 mutations, but otherwise the genotype-phenotype associations are correlative as confirmation by functional genetics was beyond the scope of this study.

Comments on revisions:

My recommendations have all been addressed in the revised version.

Reviewer #2 (Public review):

In this study, the authors identified CG14545 (named it sakura), as a key gene essential for Drosophila oogenesis. Genetic analyses revealed that Sakura is vital for both oogenesis progression and ultimate female fertility, playing a central role in the renewal and differentiation of germ stem cells (GSC).

The absence of Sakura disrupts the Dpp/BMP signaling pathway, resulting in abnormal bam gene expression, which impairs GSC differentiation and leads to GSC loss. Additionally, Sakura is critical for maintaining normal levels of piRNAs. Also, the authors convincingly demonstrate that Sakura physically interacts with Otu, identifying the specific domains necessary for this interaction, suggesting a cooperative role in germline regulation. Importantly, the loss of otu produces similar defects to those observed in sakura mutants, highlighting their functional collaboration.

The authors provide compelling evidence that Sakura is a critical regulator of germ cell fate, maintenance, and differentiation in Drosophila. This regulatory role is mediated through modulation of pMad and Bam expression. However, the phenotypes observed in the germarium appear to stem from reduced pMad levels, which subsequently trigger premature and ectopic expression of Bam. This aberrant Bam expression could lead to increased CycA levels and altered transcriptional regulation, impacting piRNA expression. In this revised manuscript, the authors further investigated whether Sakura affects the function of Orb, a binding partner they identified, in deubiquitinase activity when Orb interacts with Bam.

This elaborate study will be embraced by both germline-focused scientists and the developmental biology community.

Latest comments:

The authors answered all my persistent concerns and made changes according to the recommendations I incorporated for the revised version of the manuscript.

Reviewer #2 (Public review):

Summary:

The aim of the study was to understand how cells of the skin communicate across dermal layers. The research group has previously demonstrated that cellular connections called airinemes contribute to this communication. The current work builds upon this knowledge by showing that differentiated keratinocytes also use cytonemes, specialized signaling filopodia, to communicate with undifferentiated keratinocytes. They show that cytonemes are the more abundant type of cellular extension used for communication between the differentiated keratinocyte layer and the undifferentiated keratinocytes. Disruption of cytoneme formation led to expansion of the undifferentiated keratinocytes into the periderm, mimicking skin diseases like psoriasis. The authors go on to show that disruption of cytonemes results in perturbations in Notch signaling between the differentiated keratinocytes of the periderm and the underlying proliferating undifferentiated keratinocytes. Further the authors show that Interleukin-17, also known to drive psoriasis, can restrict formation of periderm cytonemes, possibly through the inhibition of Cdc42 expression. This work suggests that cytoneme mediated Notch signaling plays a central role in normal epidermal regulation. The authors propose that disruption of cytoneme function may be an underlying cause of various human skin diseases.

Strengths:

The authors provide strong evidence that periderm keratinocytes cytonemes contain the notch ligand DeltaC to promote Notch activation in the underlying intermediate layer to regulate accurate epidermal maintenance.

Weaknesses:

The impact of the study would be increased if the mechanism by which Interlukin-17 and Cdc42 collaborate to regulate cytonemes was defined. Experiments measuring Cdc42 activity, rather than just measuring expression, would strengthen the conclusions.

Comments on revisions:

The authors have sufficiently addressed my critiques from the initial round of evaluation. They have included useful representative images, clarified how they scored cytonemes and provided additional controls/experimental conditions that improve the rigor of the study. The results provided now support the key conclusions of the study.

Reviewer #2 (Public review):

Summary:

The function of neural circuits relies heavily on the balance of excitatory and inhibitory inputs. Particularly, inhibitory inputs are understudied when compared to their excitatory counterparts due to the diversity of inhibitory neurons, their synaptic molecular heterogeneity, and their elusive signature. Thus, insights into these aspects of inhibitory inputs can inform us largely on the functions of neural circuits and the brain.

Endophilin A1, an endocytic protein heavily expressed in neurons, has been implicated in numerous pre- and postsynaptic functions, however largely at excitatory synapses. Thus, whether this crucial protein plays any role in inhibitory synapse, and whether this regulates functions at the synaptic, circuit, or brain level remains to be determined.

New Findings:

(1) Endophilin A1 interacts with the postsynaptic scaffolding protein gephyrin at inhibitory postsynaptic densities within excitatory neurons.

(2) Endophilin A1 promotes the organization of the inhibitory postsynaptic density and the subsequent recruitment/stabilization of GABA A receptors via Endophilin A1's membrane binding and actin polymerization activities.

(3) Loss of Endophilin A1 in CA1 mouse hippocampal pyramidal neurons weakens inhibitory input and leads to susceptibility to epilepsy.

(4) Thus the authors propose that via its role as a component of the inhibitory postsynaptic density within excitatory neurons, Endophilin A1 supports the organization, stability, and efficacy of inhibitory input to maintain the excitatory/inhibitory balance critical for brain function.

(5) The conclusion of the manuscript is well supported by the data but will be strengthened by addressing our list of concerns and experiment suggestions.

Comments on revised version:

The authors addressed the concerns adequately. The three remaining concerns are:

(1) The use of one-way ANOVA is not well justified.

(2) The use of superplots to show culture to culture variability would make it more transparent.

(3) Change EEN1 in Figure 8B to EndoA1.

Reviewer #2 (Public review):

In this manuscript, Ross and Miscik et. al described the phenotypic discrepancies between F0 zebrafish mosaic mutant ("CRISPants") and morpholino knockdown (Morphant) embryos versus a set of 5 different loss-of-function (LOF) stable mutants in one particular gene involved in hepatic stellate cells development: podxl. While transient LOF and mosaic mutants induced a decrease of hepatic stellate cells number stable LOF zebrafish did not. The authors analyzed the molecular causes of these phenotypic differences and concluded that LOF mutants are genetically compensated through the upregulation of the expression of many genes. Additionally, they ruled out other better-known and described mechanisms such as the expression of redundant genes, protein feedback loops, or transcriptional adaptation.

While the manuscript is clearly written and conclusions are, in general, properly supported, there are some aspects that need to be further clarified and studied.

(1) It would be convenient to apply a method to better quantify potential loss-of-function mutations in the CRISPants. Doing this it can be known not only percentage of mutations in those embryos but also what fraction of them are actually generating an out-of-frame mutation likely driving gene loss of function (since deletions of 3-6 nucleotides removing 1-2 aminoacid/s will likely not have an impact in protein activity, unless that this/these 1-2 aminoacid/s is/are essential for the protein activity). With this, the authors can also correlate phenotype penetrance with the level of loss-of-function when quantifying embryo phenotypes that can help to support their conclusions.

(2) It is unclear that 4.93 ng of morpholino per embryo is totally safe. The amount of morpholino causing undesired effects can differ depending on the morpholino used. I would suggest performing some sanity check experiments to demonstrate that morpholino KD is not triggering other molecular outcomes, such as upregulation of p53 or innate immune response.

(3) Although the authors made a set of controls to demonstrate the specificity of the CRISPant phenotypes, I believe that a rescue experiment could be beneficial to support their conclusions. Injecting an mRNA with podxl ORF (ideally with a tag to follow protein levels up) together with the induction of CRISPants could be a robust manner to demonstrate the specificity of the approach. A rescue experiment with morphants would also be good to have, although these are a bit more complicated, to ultimately demonstrate the specificity of the approach.

(4) In lines 314-316, the authors speculate on a correlation between decreased HSC and Podxl levels. It would be interesting to actually test this hypothesis and perform RT-qPCR upon CRISPant induction or, even better and if antibodies are available, western blot analysis.

(5) Similarly, in lines 337-338 and 342-344, the authors discuss that it could be possible that genes near to podxl locus could be upregulated in the mutants. Since they already have a transcriptomic done, this seems an easy analysis to do that can address their own hypothesis.

(6) Figures 4 and 5 would be easier to follow if panels B-F included what mutants are (beyond having them in the figure legend). Moreover, would it be more accurate and appropriate if the authors group all three WT and mutant data per panel instead of showing individual fish? Representing technical replicates does not demonstrate in vivo variability, which is actually meaningful in this context. Then, statistical analysis can be done between WT and mutant per panel and per set of primers using these three independent 3-month-old zebrafish.

Reviewer #2 (Public review):

Summary:

The authors present 3.2-3.7 Å cryo-EM structures of Trypanosoma brucei aquaglyceroporin-2 (TbAQP2) bound to glycerol, pentamidine, or melarsoprol and combine them with extensive all-atom MD simulations to explain drug recognition and resistance mutations. The work provides a persuasive structural rationale for (i) why positively selected pore substitutions enable diamidine uptake, and (ii) how clinical resistance mutations weaken the high-affinity energy minimum that drives permeation. These insights are valuable for chemotherapeutic re-engineering of diamidines and aquaglyceroporin-mediated drug delivery.

My comments are on the MD part.

Strengths:

The study

(1) Integrates complementary cryo-EM, equilibrium, applied voltage MD simulations, and umbrella-sampling PMFs, yielding a coherent molecular-level picture of drug permeation.

(2) Offers direct structural rationalisation of long-standing resistance mutations in trypanosomes, addressing an important medical problem.

Weaknesses:

Unphysiological membrane potential. A field of 0.1 V nm⁻¹ (~1 V across the bilayer) was applied to accelerate translocation. From the traces (Figure 1c), it can be seen that the translocation occurred really quickly through the channel, suggesting that the field might have introduced some large changes in the protein. The authors state that they checked visually for this, but some additional analysis, especially of the residues next to the drug, would be welcome.

Based on applied voltage simulations, the authors argue that the membrane potential would help get the drug into the cell, and that a high value of the potential was applied merely to speed up the simulation. At the same time, the barrier for translocation from PMF calculations is ~40 kJ/mol for WT. Is the physiological membrane voltage enough to overcome this barrier in a realistic time? In this context, I do not see how much value the applied voltage simulations have, as one can estimate the work needed to translocate the substrate on PMF profiles alone. The authors might want to tone down their conclusions about the role of membrane voltage in the drug translocation.

Pentamidine charge state and protonation. The ligand was modeled as +2, yet pKa values might change with the micro-environment. Some justification of this choice would be welcome.

I don't follow the RMSD calculations. The authors state that this RMSD is small for the substrate and show plots in Figure S7a, with the bottom plot being presumably done for the substrate (the legends are misleading, though), levelling off at ~0.15 nm RMSD. However, in Figure S7a, we see one trace (light blue) deviating from the initial position by more than 0.2 nm - that would surely result in an RMSD larger than 0.15, but this is somewhat not reflected in the RMSD plots.

Reviewer #2 (Public review):

Summary:

Using a genetic model of beta-pix conditional trap, the authors are able to regulate the spatio-temporal depletion of beta-pix, a gene with an established role in maintaining vascular integrity (shown elsewhere). This study provides strong in vivo evidence that glial beta-pix is essential to the development of the blood-brain barrier and maintaining vascular integrity. Using genetic and biochemical approaches, the authors show that PAK1 and Stathmins are in the same signaling axis as beta-pix, and act downstream to it, potentially regulating cytoskeletal remodeling and controlling glial migration. How exactly the glial-specific (beta-pix driven-) signaling influences angiogenesis or vascular integrity is not clear.

Strengths:

(1) Developing a conditional gene-trap genetic model which allows for tracking knockin reporter driven by endogenous promoter, plus allowing for knocking down genes. This genetic model enabled the authors to address the relevant scientific questions they were interested in, i.e., a) track expression of beta-pix gene, b) deletion of beta-pix gene in a cell-specific manner.

(2) The study reveals the glial-specific role of beta-pix, which was unknown earlier. This opens up avenues for further research. (For instance, how do such (multiple) cell-specific signaling converge onto endothelial cells which build the central artery and maintain the blood-brain barriers?)

Weaknesses:

Major:

(1) The study clearly establishes a role of beta-pix in glial cells, which regulates the length of the central artery and keeps the hemorrhages under control. Nevertheless, it is not clear how this is accomplished.<br /> a. Is this phenotype (hemorrhage) a result of the direct interaction of glial cells and the adjacent endothelial cells? If direct, is the communication established through junctions or through secreted molecules?<br /> b. The authors do not exclude the possibility that the effects observed on endothelial cells (quantified as length of central artery) could be secondary to the phenotype observed with deletion of glial beta-pix. For instance, can glial beta-pix regulate angiogenic factors secreted by peri-vascular cells, which consequently regulate the length of the central artery or vascular integrity?<br /> c. The pictorial summary of the findings (Figure 7) does not include Zfhx or Vegfa. The data do not provide clarity on how these molecules contribute (directly or indirectly) to endothelial cell integrity. Vegfaa is expressed in the central artery, but the expression of the receptor in these endothelial cells is not shown. Similarly, all other experimental analyses for Zfhx and Vegfa expression were performed in glial cells. More experimental evidence is necessary to show the regulation of angiogenesis (of endothelial cells) by glial beta-pix. Is the Vegfaa receptor present on central arteries, and how does glial depletion of beta-pix affect its expression or response of central artery endothelial cells (both pertaining to angiogenesis and vascular integrity).

(2) Microtubule stabilization via glial beta-pix, claimed in Figure 5M, is unclear. Magnified images for h-betapix OE and h-stmn-1 glial cells are absent. Is this migration regulated by beta-pix through its GEF activity for Cdc42/Rac?

(3) Hemorrhages are caused by compromised vascular integrity, which was not measured (either qualitatively or quantitatively) throughout the manuscript. The authors do measure the length of the central artery in several gene deletion models (2I, 3C. 5F/J, 6G/K), which is indicative of artery growth/ angiogenesis. How (if at all) defects in angiogenesis are an indication of hemorrhage should be explained or established. Do these angiogenic growth defects translate into junctional defects at later developmental timepoints? Formation and maintenance of endothelial cell junctions within the hemorrhaging arteries should be assessed in fish with deleted beta-pix from astrocytes.

(4) More information is required about the quality control steps for 10X sequencing (Figure 4, number of cells, reads, etc.). What steps were taken to validate the data quality? The EC groups, 1 and 2-days post-KO are not visible in 4C. One appreciates that the progenitor group is affected the most 2 days post-KO. But since the effects are expected to be on the endothelial cell group as well (which is shown in in vivo data), an extensive analysis should be done on the EC group (like markers for junctional integrity, angiogenesis, mesenchymal interaction, etc.). Are Stathmins limited to glial cells? Are there indicators for angiogenic responses in endothelial cells?

Reviewer #2 (Public review):

This study by M. Blatkiewicz et al. seeks to define the spatial gene expression pattern of the adult male mouse adrenal gland using current spatial transcriptomic techniques. They propose new zone-specific gene markers and specific intra- and inter-zonal signaling pathways based on receptor-ligand expression patterns. Their web tool is user-friendly and will be helpful for adrenal scientists. The manuscript is easy to follow, but validation of crucial results of the large dataset is missing. There are also several contradictory results/interpretations, and the opportunity to dissect the sexually dimorphic gene expression pattern and mouse-human interspecies differences is a missed opportunity.

(1) The authors used 10-week-old CD1 male mouse adrenal glands to assess the spatial transcriptomics of the adrenal gland. As they also mentioned, male mice typically lose their zone-X after puberty (around 6-8 weeks of age). However, their analysis in 10-week-old mice suggests that zone-X covers most of the adrenal cortex. As shown in Figure 3A, the dots between the zona glomerulosa and the medulla are mostly positive for zone-X, which would suggest that the zona fasciculata represents a relative minority of the overall adult adrenal cortex. Is this correct? Is the presence of zone-X in sexually mature adult male mice unique to the CD1 strain? Providing histology data in support of this conclusion, using zone-specific markers combined with RNA in situ hybridization or immunofluorescence techniques in the CD1 male adrenal gland, would help to interpret these data further. Given the relatively low resolution of their gene expression profiles, it is possible there is overlap between the zona fasciculata and the zone-X.

(2) The pseudotime trajectory analysis confirms prior reports in the literature showing zonal transdifferentiation but does not provide novel insight. It would be nice to know what gene expression patterns correlate (positively or negatively) based on an unbiased analysis.

(3) The authors suggest that they identified new zonal markers, but it would be nice to see confirmation of some of these markers (e.g., Frmpd4, Oca2, Sphkap for the ZG or Cited1, Nat8f5 for the ZF, etc. ) with in situ or immunofluorescence combined with known markers such as Dab2, Cyp11b2, or Cyp11b1.

(4) The authors mention a gradual transition between the zones. It would be interesting to know whether transition zones exist between the zona glomerulosa and the zona fasciculata or the zona fasciculata and the zone-X.

(5) The authors note using Visium cyst assist, but they do not discuss the advantages of this system compared to other systems. Explanation of the approximate resolution of their analysis (e.g., how many cells were pooled in the wells) would help readers to interpret their data. It would also be nice to compare it to other spatial transcriptomic analyses of human adrenals, given the differences between the zonation of human and mouse adrenals.

(6) Interestingly, CellChat analysis suggests possible communication between the medulla and the zona fasciculata and zona glomerulosa. How do the authors explain the transfer of these molecules from the medulla to the outer zones given centripetal blood flow in the adrenal? Also, how does the fact that Igf2 expression has been shown to be expressed in the capsule (PMID: 22266195) affect the interpretation of their data?

(7) The study misses the opportunity to dissect sexually dimorphic gene expression patterns in the mouse adrenal. For example, the authors could have focused on the role of stem cells between male and female mouse adrenals, which have been reported to differ (PMID: 31104943). In addition, the authors could have focused on the sexually dimorphic zone-X and its regulation by sex hormone signaling.

(8) The capsule is classified as a connective tissue, which may be misleading given its important role as a signaling center in the adrenal. Genes enriched in typical connective tissues do not include many of the genes that seem to define the adrenal capsule. Also, some of the capsule markers appear to be found in the zona glomerulosa. Is this a result of not being able to fully resolve the small layer of zG cells and the even smaller layer of capsular cells? Guided reclustering of the cells based on known markers and separation of capsule and connective tissue might help to present their data on adrenal zonation more clearly.

Reviewer #2 (Public review):

Summary:

The current paper consists of two parts. The first part is the rigorous feature optimization of the MEG signal to decode individual finger identity performed in a sequence (4-1-3-2-4; 1~4 corresponds to little~index fingers of the left hand). By optimizing various parameters for the MEG signal, in terms of (i) reconstructed source activity in voxel- and parcel-level resolution and their combination, (ii) frequency bands, and (iii) time window relative to press onset for each finger movement, as well as the choice of decoders, the resultant "hybrid decoder" achieved extremely high decoding accuracy (~95%).

In the second part of the paper, armed with the successful 'hybrid decoder,' the authors asked how neural representation of individual finger movement that is embedded in a sequence, changes during a very early period of skill learning and whether and how such representational change can predict skill learning. They assessed the difference in MEG feature patterns between the first and the last press 4 in sequence 41324 at each training trial and found that the pattern differentiation progressively increased over the course of early learning trials. Additionally, they found that this pattern differentiation specifically occurred during the rest period rather than during the practice trial. With a significant correlation between the trial-by-trial profile of this pattern differentiation and that for accumulation of offline learning, the authors argue that such "contextualization" of finger movement in a sequence (e.g., what-where association) underlies the early improvement of sequential skill. This is an important and timely topic for the field of motor learning and beyond.

Strengths:

The use of temporally rich neural information (MEG signal) has a significant advantage over previous studies testing sequential representations using fMRI. This allowed the authors to examine the earliest period (= the first few minutes of training) of skill learning with finer temporal resolution. Through the optimization of MEG feature extraction, the current study achieved extremely high decoding accuracy (approx. 94%) compared to previous works. The finding of the early "contextualization" of the finger movement in a sequence and its correlation to early (offline) skill improvement is interesting and important. The comparison between "online" and "offline" pattern distance is a neat idea.

Weaknesses:

One potential weakness, in terms of the generality, is that the study assessed the single sequence, the "41324" across all participants. Future confirmation test of using different sequences would be important.

Reviewer #2 (Public review):

Summary:

In this work, the investigators isolated one Lacticaseibacillus rhamnosus strain (P118), and determined this strain worked well against Salmonella Typhimurium infection. Then, further studies were performed to identify the mechanism of bacterial resistance, and a list of confirmatory assays were carried out to test the hypothesis.

Strengths:

The authors provided details regarding all assays performed in this work, and this reviewer trusted that the conclusion in this manuscript is solid. I appreciate the efforts of the authors to perform different types of in vivo and in vitro studies to confirm the hypothesis.

Reviewer #2 (Public review):

This manuscript by Walton et al. suggests that they have identified a new bacteriophage that uses the exopolysaccharide Psl from Pseudomonas aeruginosa (PA) as a receptor. As Psl is an important component in biofilms, the authors suggest that this phage (and others similarly isolated) may be able to specifically target biofilm-growing bacteria.

Comments on revised version:

The authors have generally responded well to the reviewers' comments. This has served to improve this manuscript that has identified a new bacteriophage that uses the exopolysaccharide Psl from Pseudomonas aeruginosa as a receptor.

Reviewer #2 (Public review):

Summary:

The authors attempted to investigate the pangenome of MTBC by using a selection of state-of-the-art bioinformatic tools to analyse 324 complete and 11 new genomes representing all known lineages and sublineages. The aim of their work was to describe the total diversity of the MTBC and to investigate the driving evolutionary force. By using long read and hybrid approaches for genome assembly, an important attempt was made to understand why the MTBC pangenome size was reported to vary in size by previous reports. This study provides strong evidence that the MTBC pangenome is closed and that genome reduction is the main driver of this species evolution.

Strengths:

A stand-out feature of this work is the inclusion of non-coding regions as opposed to only coding regions which was a focus of previous papers and analyses which investigated the MTBC pangenome. A unique feature of this work is that it highlights sublineage-specific regions of difference (RDs) that was previously unknown. Another major strength is the utilisation of long-read whole genomes sequences, in combination with short-read sequences when available. It is known that using only short reads for genome assembly has several pitfalls. The parallel approach of utilizing both Panaroo and Pangraph for pangenomic reconstruction illuminated limitations of both tools while highlighting genomic features identified by both. This is important for any future work and perhaps alludes to the need for more MTBC-specific tools to be developed. Lastly, ample statistical support in the form of Heaps law and genome fluidity calculations for each pangenome to demonstrate that they are indeed closed.

Weaknesses:

There are no major weaknesses in the revised version of this manuscript.

Reviewer #3 (Public review):

Summary:

The authors attempted to study connections with the inferior olive to the cerebellar cortex and analyze impacts on optokinetic reflex using optogenetics to perturb the pathway. This is a commendable effort as these methods are very challenging due to the location of the inferior olive and recording methods.

Strengths:

The authors have shown that climbing fiber activity was altered due to the optogenetic perturbation. They have added an additional figure to show that complex spikes disappear with inhibitory optogenetics and the impacts on behavior are interesting.

Weaknesses:

The images provided to show injection region are difficult to see and specific cell types are not co-labeled. The data and strength of the results would benefit from high-resolution images demonstrating selectivity and expression, in particular for Figure 2A and 3A. In addition, while the processed recording data looks very striking, including the raw data, as done in Figure 2, would again support the conclusions.

One major concern is that the viruses chosen are non-specific to the cell targets and a cre-based approach is lacking to draw conclusions on only the targeted pathway of interest. It is unclear based on the figures provided if the AAVs labeled only the pathway of interest. It would be interesting to know if typical memory acquisition returns in the same animals if inhibition stops and if animal movement was impacted by the perturbation.

Reviewer #2 (Public review):

Summary:

The study introduces new tools for measuring intracellular Ca2+ concentration gradients around retinal rod bipolar cell (rbc) synaptic ribbons. This is done by comparing the Ca2+ profiles measured with mobile Ca2+ indicator dyes versus ribbon-tethered (immobile) Ca2+ indicator dyes. The Ca2+ imaging results provide a straightforward demonstration of Ca2+ gradients around the ribbon and validate their experimental strategy. This experimental work is complemented by a coherent, open-source, computational model that successfully describes changes in Ca2+ domains as a function of Ca2+ buffering. In addition, the authors try to demonstrate that there is heterogeneity among synaptic ribbons within an individual rbc terminal.

Strengths:

The study introduces a new set of tools for estimating Ca2+ concentration gradients at ribbon AZs, and the experimental results are accompanied by an open-source, computational model that nicely describes Ca2+ buffering at the rbc synaptic ribbon. In addition, the dissociated retinal preparation remains a valuable approach for studying ribbon synapses. Lastly, excellent EM.

Comments on revisions:

Specific minor comments:

(1) Rewrite the final sentence of the Abstract. It is difficult to understand.

(2) Add a definition in the Introduction (and revisit in the Discussion) that delineates between micro- and nano-domain. A practical approach would be to round up and round down. If you round up from 0.6 um, then it is microdomain which means ~ 1 um or higher. Likewise, round down from 0.3 um to nanodomain? If you are using confocal, or even STED, the resolution for Ca imaging will be in the 100 to 300 nm range. The point of your study is that your new immobile Ca2-ribbon indicator may actually be operating on a tens of nm scale: nanophysiology. The Results are clearly written in a way that acknowledges this point but maybe make such a "definition" comment in the intro/discussion in order to: 1) demonstrate the power of the new Ca2+ indicator to resolve signals at the base of the ribbon (effectively nano), and 2) (Discussion) to acknowledge that some are achieving nanoscopic resolution (50 to 100nm?) with light microscopy (as you ref'd Neef et al., 2018 Nat Comm).

(3) Suggested reference: Grabner et al. 2022 (Sci Adv, Supp video 13, and Fig S5). Here rod Cav channels are shown to be expressed on both sides the ribbon, at its base, and they are within nanometers from other AZ proteins. This agrees with the conclusions from your imaging work.

(4) In the Discussion, add a little more context to what is known about synaptic transmission in the outer and inner retina.. First, state that the postsynaptic receptors (for example: mGluR6-OnBCs vs KARs-Off-BCs, vs. AMPAR-HCs), and possibly the synaptic cleft (ground squirrel), are known to have a significant impact on signaling in the outer retina. In the inner retina, there are many more unknowns. For example, when I think of the pioneering Palmer JPhysio study, which you sight, I think of NMDAR vs AMPAR, and uncertainty in what type postsynaptic cell was patched (GC or AC....). Once you have informed the reader that the postsynapse is known to have a significant impact on signaling, then promote your experimental work that addresses presynaptic processes: "...the new tool and results allow us to explore release heterogeneity, ribbon by ribbon in dissociated preps, which we eventually plan to use at ribbon synapses within slices......to better understand how the presynapse shapes signaling......".

Reviewer #2 (Public review):

Summary:

The authors show that co-expression of bassoon, RIBEYE, Cav1.3-alpha1, Cav-beta3, Cav-alpha2delta1, and RBP2 in a heterologus system (HEK293 cells) is sufficient to generate a protein complex resembling a presyanptic ribbon-type active zone both in morphology and in function (in clustering voltage-gated Ca channels and creating sites for localized Ca2+ entry). If the 3 separate Cav gene products are taken as a single protein (i.e. a Ca channel), the conclusion is that the core of a ribbon synapse comprises 4 proteins: bassoon holds the RIBEYE-containing ribbon to the plasma membrane, and RPB2 binds to bassoon and Ca channels, tethering the Ca channels to the presynaptic active zone.

Strengths:

(1) Good use of a heterologous system with generally appropriate controls provides convincing evidence that a presynaptic ribbon-type active zone (without the ability to support exocytosis), with the ability to support localized Ca2+ entry (a key feature of ribbon-type pre-synapses) can be assembled from a few proteins.<br /> (2) In the revised manuscript, the authors do a good job of addressing the limitations of their cultured cell-system.

Weaknesses:

(1) Relies on over-expression, which almost certainly diminishes the experimentally-measured parameters (e.g. pre-synapse clustering, localization of Ca2+ entry).<br /> (2) Are HEK cells the best model? HEK cells secrete substances and have a studied-endocytitic pathway, but they do not create neurosecretory vesicles. Initially, I asked why didn't the authors did not try to reconstitute a ribbon synapse in a cell that makes neurosecretory vesicles like a PC12 cell, and the authors addressed this question in their revision.<br /> (3) Related to 1 and 2: the Ca channel localization observed is significant but not so striking given the presence of Cav protein and measurements of Ca2+ influx distributed across the membrane. Presumably, this is the result of overexpression and an absence of pathways for pre-synaptic targeting of Ca channels. But, still, it was surprising that Ca channel localization was so diffuse. I suppose that the authors tried to reduce the effect of over-expression by using an inducible Cav1.3? Even so, the accessory subunits were constitutively over-expressed.

Reviewer #1 (Public review):

Summary:

The authors, Dalal, et. al., determined cryo-EM structures of open, closed, and desensitized states of the pentameric ligand-gated ion channel ELIC reconstituted in liposomes, and compared them to structures determined in varying nanodisc diameters. They argue that the liposomal reconstitution method is more representative of functional ELIC channels, as they were able to test and recapitulate channel kinetics through stopped-flow thallium flux liposomal assay. The authors and others have described channel interactions with membrane scaffold proteins (MSP), initially thought to be in a size-dependent manner. However, the authors reported their cryo-EM ELIC structure interacts with the large nanodisc spNW25, contrary to their original hypotheses. This suggests that the channels interactions with MSPs might alter its structure, possibly influencing the functional states of the channel. Thus, the authors describe reconstitution in liposomes are more representative of the native structure and can recapitulate all channel states.

Strengths:

Cryo-EM structural determination from proteoliposomes is promising methodology within the ion channel field due to their large surface area and lack of MSP or other membrane memetics that could alter channel structure. The authors succeeded in comparing structures determined in liposomes to those in a wide range of nanodisc diameters. This comparison gives rise to important discussions for other membrane protein structural studies when deciding the best method for individual circumstances.

Weaknesses:

As the overarching goal of the study was to determine structural differences of ELIC in detergent nanodiscs and liposomes. The authors stated they determined open, closed, and desensitized states of ELIC reconstituted in liposomes and suggest the desensitization gate is at the 9' region of the pore. However, limited functional data was provided when determining the functional states of the channel with most of the evidence deriving from structures, which only provides snapshots of channels.

Reviewer #2 (Public review):

Summary:

In this paper, the authors test whether controllability beliefs and associated actions/resource allocation are modulated by things like time, effort, and monetary costs (what they call "elastic" as opposed to "inelastic" controllability). Using a novel behavioral task and computational modeling, they find that participants do indeed modulate their resources depending on whether they are in an "elastic," "inelastic," or "low controllability" environment. The authors also find evidence that psychopathology is related to specific biases in controllability.

Strengths:

This research investigates how people might value different factors that contribute to controllability in a creative and thorough way. The authors use computational modeling to try to dissociate "elasticity" from "overall controllability," and find some differential associations with psychopathology. This was a convincing justification for using modeling above and beyond behavioral output and yielded interesting results. Notably, the authors conclude that these findings suggest that biased elasticity could distort agency beliefs via maladaptive resource allocation. Overall, this paper reveals important findings about how people consider components of controllability.

Weaknesses:

The authors have gone to great lengths to revise the manuscript to clarify their definitions of "elastic" and "inelastic" and bolster evidence for their computational model, resulting in an overall strong manuscript that is valuable for elucidating controllability dynamics and preferences. One minor weakness is that the justification for the analysis technique for the relationships between the model parameters and the psychopathology measures remains lacking given the fact that simple correlational analyses did not reveal any significant associations.

Reviewer #2 (Public review):

Summary:

In this manuscript, Meier et al. engineer a new class of light-regulated two-component systems. These systems are built using bathy-bacteriophytochromes that respond to near-infrared (NIR) light. Through a combination of genetic engineering and systematic linker optimization, the authors generate bacterial strains capable of selective and tunable gene expression in response to NIR stimulation. Overall, these results are an interesting expansion of the optogenetic toolkit into the NIR range. The cross-species functionality of the system, modularity, and orthogonality have the potential to make these tools useful for a range of applications.

Strengths:

(1) The authors introduce a novel class of near-infrared light-responsive two-component systems in bacteria, expanding the optogenetic toolbox into this spectral range.

(2) Through engineering and linker optimization, the authors achieve specific and tunable gene expression, with minimal cross-activation from red light in some cases.

(3) The authors show that the engineered systems function robustly in multiple bacterial strains, including laboratory E. coli, the probiotic E. coli Nissle 1917, and Agrobacterium tumefaciens.

(4) The combination of orthogonal two-component systems can allow for simultaneous and independent control of multiple gene expression pathways using different wavelengths of light.

(5) The authors explore the photophysical properties of the photosensors, investigating how environmental factors such as pH influence light sensitivity.

Weaknesses:

(1) The expression of multi-gene operons and fluorescent reporters could impose a metabolic burden. The authors should present data comparing optical density for growth curves of engineered strains versus the corresponding empty-vector control to provide insight into the burden and overall impact of the system on host viability and growth.

(2) The manuscript consistently presents normalized fluorescence values, but the method of normalization is not clear (Figure 2 caption describes normalizing to the maximal fluorescence, but the maximum fluorescence of what?). The authors should provide a more detailed explanation of how the raw fluorescence data were processed. In addition, or potentially in exchange for the current presentation, the authors should include the raw fluorescence values in supplementary materials to help readers assess the actual magnitude of the reported responses.

(3) Related to the prior point, it would be useful to have a positive control for fluorescence that could be used to compare results across different figure panels.

(4) Real-time gene expression data are not presented in the current manuscript, but it would be helpful to include a time-course for some of the key designs to help readers assess the speed of response to NIR light.

Reviewer #2 (Public review):

Summary:

Tsurumi et al. show that recurrent neural networks can learn state and value representations in simple reinforcement learning tasks when trained with random feedback weights. The traditional method of learning for recurrent network in such tasks (backpropogation through time) requires feedback weights which are a transposed copy of the feed-forward weights, a biologically implausible assumption. This manuscript builds on previous work regarding "random feedback alignment" and "value-RNNs", and extends them to a reinforcement learning context. The authors also demonstrate that certain non-negative constraints can enforce a "loose alignment" of feedback weights. The author's results suggest that random feedback may be a powerful tool of learning in biological networks, even in reinforcement learning tasks.

Strengths:

The authors describe well the issues regarding biologically plausible learning in recurrent networks and in reinforcement learning tasks. They take care to propose networks which might be implemented in biological systems and compare their proposed learning rules to those already existing in literature. Further, they use small networks on relatively simple tasks, which allows for easier intuition into the learning dynamics.

Weaknesses:

The principles discovered by the authors in these smaller networks are not applied to larger networks or more complicated tasks with long temporal delays (>100 timesteps), so it remains unclear to what degree these methods can scale or can be used more generally.

Comments on revisions: I would still want to see how well the network learns tasks with longer time delays (on the order of 100 or even 1000 timesteps). Previous work has shown that random feedback struggles to encode longer timescales (see Murray 2019, Figure 2), so I would be interested to see how that translates to the RL context in your model.

Reviewer #3 (Public review):

Summary:

The study uses publicly available sequences of classical and non-classical genes from a number of primate species to assess the extent and depth of TSP across the primate phylogeny. The analyses were carried out in a coherent and, in my opinion, robust inferential framework and provide evidence for ancient (even > 30 million years) TSP at several classical class I and class II genes. The authors also characterise evolutionary rates at individual codons, map these rates onto MHC protein structures, and find that the fastest evolving codons are extremely enriched for autoimmune and infectious disease associations.

Strengths:

The study is comprehensive, relying on a large data set, state-of-the-art phylogenetic analyses and elegant tests of TSP. The results are not entirely novel, but a synthesis and re-analysis of previous findings is extremely valuable and timely.

Weaknesses:

Following the revision by the Authors I see mostly one weakness - Older literature on the subject is duly cited, but the discussion of the findings the context of this literature is limited.

Comments on revisions:

Lines 441-452 - In this section, you discuss an apparent paradox between long-lived balancing selection and strong directional selection, referencing elevated substitution rates. However, this issue is more nuanced and may not be best framed in terms of substitution rates. That terminology is common in phylogenetic analyses, where differences between sequences-or changes along phylogenetic branches-are often interpreted as true substitutions in the population genetic sense. In the case of MHC trees and the rates you're discussing here, the focus is more accurately on the rate at which new mutations become established within particular allelic lineages. So while this still concerns evolutionary rates at specific codons, equating them directly with substitution rates may be misleading. A more precise term or framing might be warranted in this context.

Reviewer #2 (Public review):

Summary:

In their manuscript, Gouirand et al. report on the role of Layilin expression for the motility and suppressive capacity of regulatory T cells (Tregs). In previous studies, the authors had already demonstrated that Layilin is expressed on Tregs, that it acts as a negative regulator of their suppressive capacity, that it functions to anchor Tregs in non-lymphoid tissues, and that it enhances the adhesive properties of Layilin-expressing cells by co-localization with the integrin αLβ2 (LFA-1). Building on these published data, the authors now show that Layilin is highly expressed on a subset of clonally expanded effector Tregs in both healthy and psoriatic skin and that deletion of Layilin in Tregs in vivo resulted in significantly attenuated skin inflammation. Furthermore, the authors addressed the molecular mechanism by which Layilin affects the suppressive capacity of Tregs and showed that Layilin increased Treg adhesion via modulation of LFA-1, resulting in distinct cytoskeletal changes.

Strengths:

Certainly, the strength of this study lies in the combination of data from mouse and human models.

Weaknesses:

Some of the conclusions drawn by the authors must be treated with caution, as the experimental conditions were not always appropriate, leading to a risk of misinterpretation.

Reviewer #2 (Public review):

Summary:

Microglia have been implicated in brain development, homeostasis, and diseases. "Microglia replacement" has gain tractions in recent years, using primary microglia, bone marrow or blood-derived myeloid cells, or human iPSC-induced microglia. Here, the authors extended their previous work in the area and provide evidence to support: (1) Estrogen-regulated (ER) homeobox B8 (Hoxb8) conditionally immortalized macrophages from bone marrow can serve as stable, genetically manipulated cell lines. These cells are highly comparable to primary bone marrow-derived (BMD) macrophages in vitro, and, when transplanted into a microglia-free brain, engraft the parenchyma and differentiate into microglia-like cells (MLCs). Taking advantage of this model system, the authors created stable, Adar1-mutated ER-Hoxb8 lines using CRISPR-Cas9 to study the intrinsic contribution of macrophages to Aicardi-Goutières Syndrome (AGS) disease mechanism.

Strengths:

The studies are carefully designed and well-conducted. The imaging data and gene expression analysis are carried out at a high level of technical competences and the studies provide strong evidence that ER-Hoxb8 immortalized macrophages from bone marrow are a reasonable source for "microglia replacement" exercise. The findings are clearly presented, and the main message will be of general interest to the neuroscience and microglia communities.

Reviewer #2 (Public review):

The authors aimed to develop an animal model of temporal lobe epilepsy (TLE) that will generate "on-demand" seizures and an improved platform to advance our ability to find new anti-seizure drugs (ASDs) for drug-resistant epilepsy (DRE). Unlike some of the work in this field, the authors are studying actual seizures, and hopefully events that are similar to actual epileptic seizures. To develop an optimized screening tool, however, one also needs high-throughput systems with actual seizures as a quantitative, rigorous, and reproducible outcome measures. The authors aim to provide such a model; however, this approach may be over-stated here and seems unlikely to address the critical issue of drug resistance, which is their most important claim.

Strengths:

- The authors have generated an animal model of "on demand" seizures, which could be used to screen new ASDs and potentially other therapies. The authors and their model make a good-faith effort to emulate the epileptic condition and to use seizure susceptibility or probability as a quantitative output measure.

- The events considered to be seizures appear to be actual seizures, with some evidence that the seizures are different from seizures in the naïve brain. Their effort to determine how different ASDs raise seizure probability or threshold to an optogenetic stimulus to the CA1 area of the rodent hippocampus is focused on an important problem, as many if not most ASD screening uses surrogate measures that may not be as well linked to actual epileptic seizures.

- Another concern is their stimulation of dorsal hippocampus, while ventral hippocampus would seem more appropriate.

- Use of optogenetic techniques allows specific stimulation of the targeted CA1 pyramidal cells, and it appears that this approach is reproducible and reliable with quantitative rigor.

- The authors have taken on a critically important problem, and have made a good-faith effort to address many of the technical concerns raised in the reviews, but the underlying problem of DRE remains.

Weaknesses:

- Although the model has potential advantages, it also has disadvantages. As stated by the authors, the pre-test work-load to prepare the model may not be worth the apparent advantages. And most important, the paper frequently mentions DRE but does not directly address it, and yet drug resistance is the critical issue in this field.

- Although the paper shows examples of actual seizures, there remains some concern that some of the events might not be seizures - or a homogeneous population of seizures. More quantitative assessment of the electrical properties (e.g., duration) of the seizures and their probability is likely to be more useful than the proposed quantification in the future of the behavioral seizure stages, because the former could be both more objective and automated, while the behavioral analysis of the seizures will likely be more subjective and less reliable (and also fraught with subjectivity and analytical problems). Nonetheless, the authors point that the presence of "Racine 3 or above" behavioral seizures (in addition to their electrical data) is a good argument that many (if not all) of the "seizures" are actual epileptic seizures.

- Optogenetic stimulation of CA1 provides cell-specificity for the stimulation, but it is not clear that this method would actually be better than electrical stimulation of a kindled rodent with superimposed hippocampal injury. The reader is unfortunately left with the concern of whether this model would be easier and more efficacious than kindling.

- Although the authors have taken on a critically important problem, and have combined a variety of technologies, this approach may facilitate more rapid screening of ASDs against actual seizures (beneficial), but it does not really address the fundamentally critical yet difficult problem of DRE. A critical issue for DRE that is not well-addressed relates to adverse effects, which is often why many ASDs are not well tolerated by many patients (e.g., LEV). Thus, we are left with: how does this address anti-seizure DRE?

- The focus of this paper seems to be more on seizures more than on epilepsy. In the absence of seizure spontaneity, the work seems to primarily address the issues of seizure spread and duration. Although this is useful, it does not seem to be addressing the question of what trips the system to generate a seizure.

An appraisal of whether the authors achieved their aims, and whether the results support their conclusions:

- The authors seem to have developed a new and useful model; however, it is not clear how this will address that core problem of DRE, which was their stated aim.

- A discussion of the likely impact of the work on the field, and the utility of the methods and data to the community.

- As stated before in the original review, the potential impact would primarily be aimed at the ETSP or a drug-testing CRO; however, much more work will be required to convince the epilepsy community that this approach will actually identify new ASDs for DRE. The approach is potentially time-consuming with a steep and potentially difficult optimization curve, and thus may not be readily adaptable to the typical epilepsy-models neuroscience laboratory.

Any additional context you think would help readers interpret or understand the significance of the work:

- The problem of DRE is much more complicated than described by the authors here; however, the paper could end up being more useful than is currently apparent. Although this work could be seen as technically - and maybe conceptually - elegant and a technical tour de force, will it "deliver on the promise"? Is it better than kindling for DRE? In attempting to improve the discovery process, how will the model move us to another level? Will this model really be any better than others, such as kindling?

Reviewer #2 (Public review):

The manifestation and progression of neurodegenerative disorders is poorly understood. Many of the neuronal disorders start by presenting subtle changes in neuronal circuit and quantification and measurement of these subtle behavior responses could help one delineate the mechanisms involved. The present study very nicely uses the flies' behavioral response to predator-mimicking passing shadows to measure subtle changes in their behavior. The data from various fly genetic models of Parkinson's disease supports their claim. This single trial method is useful to capture the individual animal's response to the threatening stimuli but stops short of capturing the fine ambulatory responses which could provide further information on an individual's behavioral response. By capturing the fine features, the authors could get detailed observations, such as posture, gait or wing positioning for a better understanding the behavioral response to the passing shadow.

Reviewer #2 (Public review):

Summary:

This is a well written manuscript describing studies directed at identifying the cell type responsible for pacemaking in murine collecting lymphatics. Using state of the art approaches, the authors identified a number of different cell types in the wall of these lymphatics and then using targeted expression of Channel Rhodopsin and GCaMP, the authors convincingly demonstrate that only activation of lymphatic muscle cells produces coordinated lymphatic contraction and that only lymphatic muscle cells display pressure-dependent Ca2+ transients as would be expected of a pacemaker in these lymphatics.

Strengths:

The use of targeted expression of channel rhodopsin and GCaMP to test the hypothesis that lymphatic muscle cells serve as the pacemakers in musing lymphatic collecting vessels.

Weaknesses:

The only significant weakness was the lack of quantitative analysis of most of the imaging data shown in Figures 1-11. In particular the colonization analysis should be extended to show cells not expected to demonstrate colocalization as a negative control for the colocalization analysis that the authors present. These weaknesses have been resolved by revision and addition of new and novel RNAseq data, additional colocalization data and membrane potential measurements.

Comments on revisions: No additional concerns.

Reviewer #3 (Public review):

This communication from Sukhina et al argues that a period of malnutrition (modeled by caloric restriction) causes lasting immune deficiencies (myelopoesis) not rescued by re-feeding. This is a potentially important paper exploring the effects of malnutrition on immunity, which is a clinically important topic. The revised study adds some details with respect to kinetics of immune compartment and body weight changes, but most aspects raised by the referees were deferred experimentally. Several textual changes have been made to avoid over-interpreting their data. My overall assessment of this revised study is similar to my impression before, which is that while the observations are interesting, there is both a lack of mechanistic understanding of the phenomena and a lack of resolution/detail about the phenomena itself.

Reviewer #2 (Public review):

The manuscript by Desingu et al., explores the role of SIRT2 in regulating Japanese Encephalitis Virus (JEV) replication and disease progression in rodent models. Using both an in vitro and an in vivo approach, the authors demonstrate that JEV infection leads to decreased SIRT2 expression, which they hypothesize is exploited by JEV for viral replication. To test this hypothesis, the authors utilize SIRT2 inhibition (via AGK2 or genetic knockout) and demonstrate that it leads to increased viral load and worsens clinical outcomes in JEV-infected mice. Conversely, SIRT2 overexpression via an AAV delivery system reduces viral replication and improves survival among infected mice. The study proposes a mechanism in which SIRT2 suppresses JEV-induced autophagy and inflammation by deacetylating NF-κB, thereby reducing Beclin-1 expression (an NF-κB-dependent gene) and autophagy, which the authors consider a pathway that JEV exploits for replication. Transcriptomic analysis further supports that SIRT2 deficiency leads to NF-κB-driven cytokine hyperactivation. Additionally, pharmacological inhibition of NF-κB using Bay 11 (an IKK inhibitor) results in reduced viral load and improved clinical pathology in WT and SIRT2 KO mice. Overall, the findings from Desingu et al. are generally supported by the data and suggest that targeting SIRT2 may serve as a promising therapeutic approach for JEV infection and potentially other RNA viruses that SIRT2 helps control. However, the paper does fall short in some areas. Please see below for our comments to help improve the paper.

Reviewer #2 (Public review):

Summary:

An intensification study with a double dose of 2nd generation integrase inhibitor with a background of nucleoside analog inhibitors of the HIV retrotranscriptase in 2, and inflammation is associated with the development of co-morbidities in 20 individuals randomized with controls, with an impact on the levels of viral reservoirs and inflammation markers. Viral reservoirs in HIV are the main impediment to an HIV cure, and inflammation is associated with co-morbidities.

Strengths:

The intervention that leads to a decrease of viral reservoirs and inflammation is quite straightforward forward as a doubling of the INSTI is used in some individuals with INSTI resistance, with good tolerability.

This is a very well documented study, both in blood and tissues, which is a great achievement due to the difficulty of body sampling in well-controlled individuals on antiretroviral therapy. The laboratory assays are performed by specialists in the field with state-of-the art quantification assays. Both the introduction and the discussion are remarkably well presented and documented.

The findings also have a potential impact on the management of chronic HIV infection.

Weaknesses:

I do not think that the size of the study can be considered a weakness, nor the fact that it is open-label either.

Reviewer #2 (Public review):

Summary and strengths:

In this manuscript, Karjee and colleagues used coalescent-based effective population size reconstruction (PSMC) from single genomes to understand past population trends in island birds and related this to life history traits and glacial patterns. This concept is fairly new, as there are still relatively few multiple PSMC synthesis studies. I also thought that the focus on island endemics was unique and adds value to this paper. I enjoyed seeing a paper focused on South East Asia and think that this could help contribute to our knowledge of the important biodiversity within this region.

Major weaknesses:

My biggest concern with this paper is that the analyses are limited to 20-30 species, and significant taxonomic bias is present (there are multiple species of passerine but only 1-2 representatives of other groups). While this is not an issue alone, many of the life history traits or geographical traits are conflated with phylogenetic diversity (e.g., there are no large-bodied passerines). Thus, it is my opinion that the impact of these drivers of past population size is conflated and cannot be disentangled with the current data. The authors themselves state that the core hypothesis surrounding Ne and habitat availability is not supported by their entire dataset (only seen in Passerines). This was not clear enough in the abstract, and conclusions cannot be drawn here as the impact of taxonomy cannot be separated from data richness, traits, etc. The PSMC analysis was done according to the most recent recommendations, and this part of the manuscript is fairly robust. However, in several places, it is incorrectly stated that the PSMC measures or can infer genetic diversity; PSMC only infers past effective population size. It cannot measure genetic diversity in the past. I cannot review the habitat reconstruction modelling as I am a conservation genomics specialist.

Appraisal:

I am not convinced about the findings within the paper. I do not think that the results are sufficiently supported at this time, largely due to the conflation of taxonomy with other variables. As this type of comparison is new, I do think that there is a chance for reasonable impact on the field of genomics and island biogeography if the manuscript's constraints are addressed. I do not see scope for impact on conservation at this time and find the conclusions in the abstract regarding conservation relevance to be unfounded.

Reviewer #2 (Public review):

In the manuscript "Cancer cells differentially modulate mitochondrial respiration to alter redox state and enable biomass synthesis in nutrient-limited environments", Chang et al investigate how cancer cells respond to the limitation of certain environmental nutrients by regulating the cellular NAD+/NADH ratio. They focus on serine and lipid metabolism, pathways known to be controlled by the NAD+/NADH ratio, and propose that changes in mitochondrial respiration in response to deprivation of these nutrients can influence the NAD+/NADH ratio, thereby impacting biomass synthesis.

While the study is descriptive in nature and does not investigate specific molecular mechanisms that explain the crosstalk between nutrient availability and mitochondrial redox changes, the experimental component is robust, and the conclusions are well supported by the results. Some suggestions could further refine the conclusions and enhance the quality of the manuscript.

Main critiques:

(1) Throughout the manuscript, the authors utilise the number of cell doublings per day as an endpoint readout of cell proliferation. It would be advisable to include a quantification of the cell number and to display the proliferation rate over time. This would provide valuable insights into the timeline of cellular responses and avoid potential confounding effects associated with the use of Sulforhodamine B dye, an indirect measure of cell proliferation based on protein content, which may be influenced by some of the interventions. Furthermore, it will help determine whether specific treatments reduce cellular doublings resulting from cell death. This concern is particularly evident in treatments with rotenone, e.g., Fig. 1G, where the increase in doublings could be attributed to cell death.

(2) The authors propose a model in which the deprivation of extracellular nutrients impacts mitochondrial respiration, which in turn increases the NAD+/NADH ratio and ultimately affects metabolic biosynthetic pathways that occur in the cytosol, such as serine biosynthesis. The mechanism by which nutrient availability is sensed and transmitted across different cellular compartments to regulate mitochondrial redox status remains unclear. This concern is particularly relevant for serine metabolism, as its synthesis occurs in the cytosol, but the authors connect it to mitochondrial respiration. Compartment-specific measurements of NAD+/NADH ratio would help to understand to what extent the redox state is affected by nutrients in the mitochondria and in the cytoplasm (see also minor critiques point 2). Moreover, the use of the genetic tool LbNox could be employed to manipulate the NAD+/NADH ratio in a compartment-specific manner, while also avoiding the toxicity of certain compounds, such as rotenone. This set of experiments would add depth to the investigation, which might otherwise appear too descriptive.

Reviewer #2 (Public review):

Summary:

The authors set out to dissect the mechanistic basis of their previously published finding that encountering cutaneous antigen augments the persistence of CD8+ memory T cells that enter skin (TRM) (Hirai et al., 2021, Immunity). Here they use the same murine model to study the fate of CD8+ T cells after antigen-priming in the lymph nodes, (1) those that re-encounter antigen in the skin via vaccinia virus (VV) versus (2) those that do not encounter antigen in skin but rather are recruited via topical dinitrofluorobenzene (DNFB) (so-called "bystander TRM"). The authors' previous publication establishes that this first group of CD8+ TRM has a persistence advantage over bystander TRM under TGFb-limiting conditions. The current paper advances this finding by elucidating the role of TGFBR3 in regulating CD8+ TRM skin persistence upon topical antigen exposure. Key novelty of the work lies in the generation and use of the CD8+ T cell-specific TGFBR3 knockout model, which allows them to demonstrate the role of TGFBR3 in fine-tuning the degree of CD8+ T cell skin persistence and that TGFBR3 expression is promoted by CD8+ TRM encountering their cognate antigen upon initial skin entry. Future work directly measuring active TGFb in the skin under different conditions would help identify physiologic scenarios that yield active TGFb-limiting conditions, thus establishing physiologic relevance.

Strengths:

Technical strengths of the paper include (1) complementary imaging and flow cytometry analyses, (2) integration of their scRNA-seq data with the existing CD8+ TRM literature via pathway analysis, and (3) use of orthogonal models where possible. Using a vaccina virus (VV) model, with and without ovalbumin (OVA), the authors investigate how topical antigen exposure and TCR strength regulate CD8+ TRM skin recruitment and retention. The authors use both FTY720 and a Thy1.1 depleting antibody to demonstrate that skin CD8+ TRM expand locally following both a primary and secondary recall response to topical OVA application.

A conceptual strength of the paper is the authors' observation that TCR signal strength upon initial TRM tissue entry helps regulate the extent of their local re-expansion on subsequent antigen re-exposure. They achieved this by applying peptides of varying affinity for the OT-I TCR on the DNFB-exposed flank in tandem with initial VV-OVA + DNFB treatment. They then measured TRM expansion after OVA peptide rechallenge, revealing that encountering a higher-affinity peptide upon skin entry leads to greater subsequent re-expansion. Additionally, by generating an OT-I Thy1.1+ E8i-creERT2 huNGFR Tgfbr3fl/fl (Tgfbr3∆CD8) mouse, the authors were able to elucidate a unique role for TGFBR3 in CD8+TRM persistence when active TGFb in skin is limited.

Weaknesses:

Overall, the authors' conclusions are well supported, although there are some instances where additional controls, experiments, or clarifications would add rigor. The conclusions regarding skin-localized TCR signaling leading to increased skin CD8+ TRM proliferation in-situ and increased TGFBR3 expression would be strengthened by assessing skin CD8+ TRM proliferation and TGFBR3 expression in models of high versus low avidity topical OVA-peptide exposure. The authors could further increase the novelty of the paper by exploring whether TGFBR3 is regulated at the RNA or protein level. To this end, they could perform analysis of their single-cell RNA sequencing data (Figure 1), comparing Tgfbr3 mRNA in DNFB versus VV-treated skin.

For clarity, when discussing antigen exposure throughout the paper, it would be helpful for the authors to be more precise that they are referring to the antigen in the skin rather than in the draining lymph node. A more explicit summary of some of the lab's previous work focused on CD8+ TRM and the role of TGFb would also help readers better contextualize this work within the existing literature on which it builds.

For rigor, it would be helpful where possible to pair flow cytometry quantification with the existing imaging data. Additional controls, namely enumerating TRM in the opposite, untreated flank skin of VV-only-treated mice and the treated flank skin of DNFB-only treated mice, would help contextualize the results seen in dually-treated mice in Figure 1. In figure legends, we suggest clearly reporting unpaired T tests comparing relevant metrics within VV or DNFB-treated groups (for example, VV-OVA PBS vs VV-OVA FTY720 in Figure 3F). Finally, quantifying right and left skin draining lymph node CD8+ T cell numbers would clarify the skin specificity and cell trafficking dynamics of the authors' model.

Reviewer #2 (Public review):

This paper introduces a framework for modeling individual differences in decision-making by learning a low-dimensional representation (the "individuality index") from one task and using it to predict behaviour in a different task. The approach is evaluated on two types of tasks: a sequential value-based decision-making task and a perceptual decision task (MNIST). The model shows improved prediction accuracy when incorporating this learned representation compared to baseline models.

The motivation is solid, and the modelling approach is interesting, especially the use of individual embeddings to enable cross-task generalization. That said, several aspects of the evaluation and analysis could be strengthened.

(1) The MNIST SX baseline appears weak. RTNet isn't directly comparable in structure or training. A stronger baseline would involve training the GRU directly on the task without using the individuality index-e.g., by fixing the decoder head. This would provide a clearer picture of what the index contributes.

(2) Although the focus is on prediction, the framework could offer more insight into how behaviour in one task generalizes to another. For example, simulating predicted behaviours while varying the individuality index might help reveal what behavioural traits it encodes.

(3) It's not clear whether the model can reproduce human behaviour when acting on-policy. Simulating behaviour using the trained task solver and comparing it with actual participant data would help assess how well the model captures individual decision tendencies.

(4) Figures 3 and S1 aim to show that individuality indices from the same participant are closer together than those from different participants. However, this isn't fully convincing from the visualizations alone. Including a quantitative presentation would help support the claim.

(5) The transfer scenarios are often between very similar task conditions (e.g., different versions of MNIST or two-step vs three-step MDP). This limits the strength of the generalization claims. In particular, the effects in the MNIST experiment appear relatively modest, and the transfer is between experimental conditions within the same perceptual task. To better support the idea of generalizing behavioural traits across tasks, it would be valuable to include transfers across more structurally distinct tasks.

(6) For both experiments, it would help to show basic summaries of participants' behavioural performance. For example, in the MDP task, first-stage choice proportions based on transition types are commonly reported. These kinds of benchmarks provide useful context.

(7) For the MDP task, consider reporting the number or proportion of correct choices in addition to negative log-likelihood. This would make the results more interpretable.

(8) In Figure 5, what is the difference between the "% correct" and "% match to behaviour"? If so, it would help to clarify the distinction in the text or figure captions.

(9) For the cognitive model, it would be useful to report the fitted parameters (e.g., learning rate, inverse temperature) per individual. This can offer insight into what kinds of behavioural variability the individuality index might be capturing.

(10) A few of the terms and labels in the paper could be made more intuitive. For example, the name "individuality index" might give the impression of a scalar value rather than a latent vector, and the labels "SX" and "SY" are somewhat arbitrary. You might consider whether clearer or more descriptive alternatives would help readers follow the paper more easily.

(11) Please consider including training and validation curves for your models. These would help readers assess convergence, overfitting, and general training stability, especially given the complexity of the encoder-decoder architecture.

Reviewer #2 (Public review):

Summary:

The paper is a methodological contribution to multivariate pattern analysis and, in particular, the analysis of representational geometry via pairwise representational distances, sometimes called representational dissimilarity analysis (RDA). The authors investigate through theoretical analysis and simulations how true representational distances (defined on the neural level) give rise to representational distances estimated from neurophysiological data, including fMRI and cell recordings. They demonstrate that, due to the way measurements sample neural activity, the activity common to all sampled neurons can be amplified in the representational geometry derived from these measurements, and therefore, an empirical representational geometry may deviate substantially from the true representational geometry. The authors propose to modify the obtained representational structure by removing the dimension corresponding to that common activity, and argue that such a removal of a single dimension does not relevantly affect the representational structure, again underpinned by mathematical analysis and simulation.

Importance:

The paper may at first sight be tackling a specific problem within a specific subfield of cognitive neuroscience methods. However, understanding the structure of representations is a fundamental goal of cognitive psychology and cognitive neuroscience, and the fact that methods of representational geometry are not yet routinely used by the wider community may at least partially be due to uncertainty regarding the reliability of these methods. This paper is an important step towards clarifying and improving reliability, and therefore towards more widespread adoption of representational geometry methods.

Strengths:

The paper makes its argument generally well, relying on previous work by the authors as well as others to support assumptions about neural sampling by neurophysiological measurements. Their main points are underpinned by both detailed mathematical analysis and simulations, and the latter also produces intuitively accessible illustrations of the authors' argument. The authors discuss in detail under which exact circumstances common neural activity distorts the representational geometry, and therefore, when exactly the removal of the common dimension is necessary to minimize that distortion.

Weaknesses:

(1) The argument around the Johnson-Lindenstrauss lemma on pages 5 & 6 is somewhat confused, and also not really convincing.

First, the correct reference for the lemma seems to be not [20] = Johnson et al. (1986), but Johnson & Lindenstrauss (1984). Moreover, as far as I can tell, Johnson et al. (1986) do not discuss random projections, and while they play a role in Johnson & Lindenstrauss (1984), that is only as a proof device. The paper text suggests that the lemma itself is probabilistic, while actually it is a statement of existence.

Second, the authors correctly state that the lemma implies that "the number of measurement channels required for a good approximation does not depend on the number of neurons and grows only logarithmically with the number of stimuli", but it is not clear what the relevance of this statement for this paper is, considering that distances between N points can be exactly preserved within an N − 1 dimensional subspace, irrespective of the number of dimensions of the original space, and since in cognitive neuroscience the number of measurement channels is usually (much) larger than the number of experimental stimuli.

The actually centrally important statement is not the Johnson-Lindenstrauss lemma, but one about the metric-preserving properties of random projections with zero-mean weights. It is this statement that needs to be backed up by the correct references, which, as far as I can tell, are neither the cited Johnson et al. (1986) nor even Johnson & Lindenstrauss (1984) for the lemma.

(2) The detailed mathematical analyses and simulations focus on the effect of non-zero-mean sampling weights, and that is justified by the result that such sampling leads to a distorted representational geometry. However, there is another assumption which seems to be used almost everywhere in both mathematical analyses and simulations, and which I suspect may have a relevant effect on the observed representational geometry: statistical independence between weights. In particular, in fMRI, the existence of a naturally limited spatial resolution (due to MRI technology or vasculature) makes it unlikely that the weights with which a given neuron affects different voxels are independent.

Reviewer #2 (Public review):

This paper by Kaller and colleagues combines an interesting replication of findings on the importance of maternal behavior on brain development in the offspring with a state-of-the-art MRI analysis and a novel comparison between such perinatal and early postnatal enrichment via the activity of the mother and a classical enriched environment in the adult. In general, the observations are as one would have expected. Early postnatal enrichment and adult enrichment have differential effects, which is plausible because, as the source of these changes is environmental, and environmental means very different things at these different stages. The three data sets presented are really interesting, and while the comparison between them might not always be as straightforward as it seems, the cross-sectional phenotyping with MRI already provides very important material and allows for interesting insight. Most interesting is possibly the massive effect of housing conditions at P7.

In particular, the role of individual behavior differs. The authors highlight this role of the interaction with the environment, rather than the environment alone. Maternal care is a process that involves the pup.

Importantly, the study shows that being born into an enriched environment predates certain changes that are still available after exposure at a later stage, but that there are also important differences. Detailed interpretation of these effects is not easy, however.

Notably, the study does not include a condition of enrichment from birth into adulthood, and no analysis of the perinatal enrichment effects at an adult age. The timeline can be guessed from Figure 1b, but the authors might in places be more explicit about the fact that, indirectly and sometimes directly, animals of different ages (young adult versus adult) are compared. There is obviously no experience of maternal care in adulthood and no active exploration, etc in childhood. In part, this is what this paper is about, but it requires some thought for the reader to separate the more trivial from the more profound conclusions. Some more guidance would probably be welcome here. In general, Figure 4 is a great idea (and visually very appealing), but the content is not quite clear. "Adults born in EE vs. switched to EE in adulthood": this has, as far as I can tell, not been studied. What is compared are EE effects at two different time-points with two supposedly different mechanisms.

From such a more mechanistic side, the authors might, for example, want to relate the observed patterns to what is known about the developmental (and plastic) dynamics in the respective brain regions at the given time. But age is a confounder here.

There is another interesting point that the authors might discuss more prominently. The inter-individual differences in Z-score are dramatic within essentially all groups. So while the mean effects might still be statistically different, a large proportion of animals are within a range of values that could be found in either experimental group. The same is also true for the effects of maternal care, as depicted in Figure 3. While there is, for this ROI, a clear trend that overall relative volume decreases with maternal contact time at each time point, there is a large range of values for each maternal contact time bin. Consequently, neither genetics nor maternal care per se can be the driver of this variation. Part of it will be technical, but the trend in the data indicates that certainly not all of this is noise and technical error.

This study has some open ends but also provides a very important and interesting direction for future study, corroborating the idea that behavior, maternal and own, does matter.

Reviewer #2 (Public review):

Summary:

In this study, the authors aimed to investigate how humans learn and adapt their behavior in dynamic environments characterized by two distinct types of uncertainty: volatility (systematic changes in outcomes) and noise (random variability in outcomes). Specifically, they sought to understand how participants adjust their learning rates in response to changes in these forms of uncertainty.

To achieve this, the authors employed a two-step approach:

Reinforcement Learning (RL) Model:<br /> They first used an RL model to fit participants' behavior, revealing that the learning rate was context-dependent-it varied based on the levels of volatility and noise. However, the RL model showed that participants misattributed noise as volatility, leading to higher learning rates in noisy conditions, where the optimal strategy would be to be less sensitive to random fluctuations.

Bayesian Observer Model (BOM):<br /> To better account for this context dependency, they introduced a Bayesian Observer Model (BOM), which models how an ideal Bayesian learner would update their beliefs about environmental uncertainty. They found that a degraded version of the BOM, where the agent had a coarser representation of noise compared to volatility, best fit the participants' behavior. This suggested that participants were not fully distinguishing between noise and volatility, instead treating noise as volatility and adjusting their learning rates accordingly.

The authors also aimed to use pupillometry data (measuring pupil dilation) as a physiological marker to arbitrate between models and understand how participants' internal representations of uncertainty influenced both their behavior and physiological responses. Their objective was to explore whether the BOM could explain not just behavioral choices but also these physiological responses, thereby providing stronger evidence for the model's validity.

Overall, the study sought to reconcile approximate rationality in human learning by showing that participants still follow a Bayesian-like learning process, but with simplified internal models that lead to suboptimal decisions in noisy environments.

Strengths:

The generative model presented in the study is both innovative and insightful. The authors first employ a Reinforcement Learning (RL) model to fit participants' behavior, revealing that the learning rate is context-dependent-specifically, it varies based on the levels of volatility and noise in the task. They then introduce a Bayesian Observer Model (BOM) to account for this context dependency, ultimately finding that a degraded BOM-in which the agent has a coarser representation of noise compared to volatility-provides the best fit to the participants' behavior. This suggests that participants are not fully distinguishing between noise and volatility, leading to misattribution of noise as volatility. Consequently, participants adopt higher learning rates even in noisy contexts, where an optimal strategy would involve being less sensitive to new information (i.e., using lower learning rates). This finding highlights a rational but approximate learning process, as described in the paper.

Weaknesses:

While the RL and Bayesian models both successfully predict behavior, it remains unclear how to fully reconcile the two approaches. The RL model captures behavior in terms of a fixed or context-dependent learning rate, while the BOM provides a more nuanced account with dynamic updates based on volatility and noise. Both models can predict actions when fit appropriately, but the pupillometry data offers a promising avenue to arbitrate between the models. However, the current study does not provide a direct comparison between the RL framework and the Bayesian model in terms of how well they explain the pupillometry data. It would be valuable to see whether the RL model can also account for physiological markers of learning, such as pupil responses, or if the BOM offers a unique advantage in this regard. A comparison of the two models using pupillometry data could strengthen the argument for the BOM's superiority, as currently, the possibility that RL models could explain the physiological data remains unexplored.

The model comparison between the Bayesian Observer Model and the self-defined degraded internal model could be further enhanced. Since different assumptions about the internal model's structure lead to varying levels of model complexity, using a formal criterion such as Bayesian Information Criterion (BIC) or Akaike Information Criterion (AIC) would allow for a more rigorous comparison of model fit. Including such comparisons would ensure that the degraded BOM is not simply favored due to its flexibility or higher complexity, but rather because it genuinely captures the participants' behavioral and physiological data better than alternative models. This would also help address concerns about overfitting and provide a clearer justification for using the degraded BOM over other potential models.

Comments on revisions:

The authors have addressed all my questions. Congratulations on the impressive work accomplished by the authors!

Reviewer #2 (Public review):

Summary:

This work reports the discovery of a new rhodopsin from reef-building corals that is characterized experimentally, spectroscopically, and by simulation. This rhodopsin lacks a carboxylate-based counterion, which is typical for this family of proteins. Instead, the authors find that a chloride ion stabilizes the protonated Schiff base and thus serves as a counterion.

Strengths:

This work focuses on the rhodopsin Antho2a, which absorbs in the visible spectrum with a maximum at 503 nm. Spectroscopic studies under different pH conditions, including the mutant E292A and different chloride concentrations, indicate that chloride acts as a counterion in the dark. In the photoproduct, however, the counterion is identified as E292.

These results lead to a computational model of Antho2a in which the chloride is modeled in addition to the Schiff base. This model is improved using the hybrid QM/MM simulations. As a validation, the absorption maximum is calculated using the QM/MM approach for the protonated and deprotonated E292 residue as well as the E292A mutant. The results are in good agreement with the experiment. However, there is a larger deviation for ADC(2) than for sTD-DFT. Nevertheless, the trend is robust since the wt and E292A mutant models have similar excitation energies. The calculations are performed at a high level of theory that includes a large QM region.

Reviewer #2 (Public review):

The manuscript by Eggan et al. investigates the energetics of conformational transitions in the cyclic nucleotide-gated (CNG) channel SthK. This lab pioneered transition metal FRET (tmFRET), which has previously provided detailed insights into ion channel conformational changes. Here, the authors analyze tmFRET fluorescence lifetime measurements in the time domain, yielding detailed insights into conformational transitions within the cyclic nucleotide binding domains (CNBDs) of the channel. The integration of tmFRET with time-correlated single-photon counting (TCSPC) represents an advancement of this technique.

Reviewer #2 (Public review):

Summary:

The authors provide an important summary of ten years of Brain Initiative funding including a description of the historical development of the initiative, the specific funding mechanisms utilized, and examples of grants funded and work produced. The authors also conduct analyses of the impact on overall funding in Systems and Computational Neuroscience, the raw and field normalized bibliographic impact of the work, the social media impact of the funded work, and the popularity of some tools developed.

The authors have improved the presentation by integrating the weaker of the two manuscripts with the stronger, by clarifying terminology and by performing additional analyses.

Reviewer #2 (Public review):

Summary:

Nishi et al, investigate the well-known and previously described phenomenon of age-associated myeloid-biased hematopoiesis. Using a previously established HoxB5mCherry mouse model, they used HoxB5+ and HoxB5- HSCs to discriminate cells with long-term (LT-HSCs) and short-term (ST-HSCs) reconstitution potential and compared these populations to immunophenotypically defined 'bulk HSCs' that consists of a mixture of LT-HSC and ST-HSCs. They then isolated these HSC populations from young and aged mice to test their function and myeloid bias in non-competitive and competitive transplants into young and aged recipients. Based on quantification of hematopoietic cell frequencies in the bone marrow, peripheral blood, and in some experiments the spleen and thymus, the authors argue against the currently held belief that myeloid-biased HSCs expand with age.

While aspects of their work are fascinating and might have merit, several issues weaken the overall strength of the arguments and interpretation. Multiple experiments were done with a very low number of recipient mice, showed very large standard deviations, and had no statistically detectable difference between experimental groups. While the authors conclude that these experimental groups are not different, the displayed results seem too variable to conclude anything with certainty. The sensitivity of the performed experiments (e.g. Fig 3; Fig 6C, D) is too low to detect even reasonably strong differences between experimental groups and is thus inadequate to support the author's claims. This weakness of the study is not acknowledged in the text and is also not discussed. To support their conclusions the authors need to provide higher n-numbers and provide a detailed power analysis of the transplants in the methods section.

As the authors attempt to challenge the current model of the age-associated expansion of myeloid-biased HSCs (which has been observed and reproduced by many different groups), ideally additional strong evidence in the form of single-cell transplants is provided.<br /> It is also unclear why the authors believe that the observed reduction of ST-HSCs relative to LT-HSCs explains the myeloid-biased phenotype observed in the peripheral blood. This point seems counterintuitive and requires further explanation.

Based on my understanding of the presented data, the authors argue that myeloid-biased HSCs do not exist, as:<br /> a) they detect no difference between young/aged HSCs after transplant (mind low n-numbers and large std);<br /> b) myeloid progenitors downstream of HSCs only show minor or no changes in frequency and c) aged LT-HSCs do not outperform young LT-HSC in myeloid output LT-HScs in competitive transplants (mind low n-numbers and large std!!!).<br /> However, given the low n-numbers and high variance of the results, the argument seems weak and the presented data does not support the claims sufficiently. That the number of downstream progenitors does not change could be explained by other mechanisms, for instance, the frequently reported differentiation short-cuts of HSCs and/or changes in the microenvironment.

Strengths:

The authors present an interesting observation and offer an alternative explanation of the origins of aged-associated myeloid-biased hematopoiesis. Their data regarding the role of the microenvironment in the spleen and thymus appears to be convincing.

Weaknesses:

"Then, we found that the myeloid lineage proportions from young and aged LT-HSCs were nearly comparable during the observation period after transplantation (Fig. 3, B and C)."<br /> [Comment to the authors]: Given the large standard deviation and low n-numbers, the power of the analysis to detect differences between experimental groups is very low. Experimental groups with too large standard deviations (as displayed here) are difficult to interpret and might be inconclusive. The absence of clearly detectable differences between young and aged transplanted HSCs could thus simply be a false-negative result. The shown experimental results hence do not provide strong evidence for the author's interpretation of the data. The authors should add additional transplants and include a detailed power analysis to be able to detect differences between experimental groups with reasonable sensitivity.

Line 293: "Based on these findings, we concluded that myeloid-biased hematopoiesis observed following transplantation of aged HSCs was caused by a relative decrease in ST-HSC in the bulk-HSC compartment in aged mice rather than the selective expansion of myeloid-biased HSC clones."

[Comment to the authors]: Couldn't that also be explained by an increase in myeloid-biased HSCs, as repeatedly reported and seen in the expansion of CD150+ HSCs? It is not intuitively clear why a reduction of ST-HSCs clones would lead to a myeloid bias. The author should try to explain more clearly where they believe the increased number of myeloid cells comes from. What is the source of myeloid cells if the authors believe they are not derived from the expanded population of myeloid-biased HSCs?

New comment for the authors:

While the authors provide new evidence, clarify the text, and adjust their interpretation, the presented data remain weak and do not convincingly challenge the current paradigm. As myeloid-biased HSC expansion with age has been observed and published by many different groups, the authors need to provide much stronger evidence to challenge the observations of others. Key experiments that might support their claims had been suggested, but as indicated, the authors plan to provide these much more rigorous experiments in future studies. As it stands, the overall conclusions of this manuscript thus remain weak and preliminary.

In an attempt to quantify the absolute cell number of HSPC subpopulations, the authors use a usual readout and quantify "Number of cells per minute of analysis time". This appears to be a quick and dirty reanalysis of already existing flow cytometry data. Unfortunately, this quantification cannot count the absolute number of cells reliably, as the number of cells per minute recorded is heavily influenced by the abundance of other cell populations. Instead, the author should have counted the absolute number of HSCs, MPPs, GMPs, etc. per femur, which is typically done to address this question.

At this point, as authors are seemingly not willing to provide additional hard evidence to support their claims in this study and are instead in the process of preparing additional data for a future manuscript, I believe this study, as it stands (although weak), suggests an interesting alternative model. Despite being highly controversial, this alternative model warrants future investigations and discussions in the field. As always, it will also be important to reproduce these findings independently in other labs. As my concerns and the concerns of the other reviewers are documented and available to read by others, I believe the manuscript should be published in its current form to stimulate critical discussion and future investigations of the current model.

Reviewer #2 (Public review):

Summary:

Mutations in the prolyl hydroxylase, PHD2, cause erythrocytosis and, in some cases, can result in tumorigenesis. Taber and colleagues test the structural and functional consequences of seven patient-derived missense mutations in PHD2 using cell-based reporter and stability assays, and multiple biophysical assays, and find that most mutations are destabilizing. Interestingly, they discover a PHD2 mutant that can hydroxylate the C-terminal ODD, but not the N-terminal ODD, which suggests the importance of N-terminal ODD for biology. A major strength of the manuscript is the multidisciplinary approach used by the authors to characterize the functional and structural consequences of the mutations. However, the manuscript had several major weaknesses, such as an incomplete description of how the NMR was performed, a justification for using neighboring residues as a surrogate for looking at prolyl hydroxylation directly, or a reference to the clinical case studies describing the phenotypes of patient mutations. Additionally, the experimental descriptions for several experiments are missing descriptions of controls or validation, which limits their strength in supporting the claims of the authors.

Strengths:

(1) This manuscript is well-written and clear.

(2) The authors use multiple assays to look at the effects of several disease-associated mutations, which support the claims.

(3) The identification of P317R as a mutant that loses activity specifically against NODD, which could be a useful tool for further studies in cells.

Weaknesses:

Major:

(1) The source data for the patient mutations (Figure 1) in PHD2 is not referenced, and it's not clear where this data came from or if it's publicly available. There is no section describing this in the methods.

(2) The NMR hydroxylation assay.

A. The description of these experiments is really confusing. The authors have published a recent paper describing a method using 13C-NMR to directly detect proly-hydroxylation over time, and they refer to this manuscript multiple times as the method used for the studies under review. However, it appears the current study is using 15N-HSQC-based experiments to track the CSP of neighboring residues to the target prolines, so not the target prolines themselves. The authors should make this clear in the text, especially on page 9, 5th line, where they describe proline cross-peaks and refer to the 15N-HSQC data in Figure 5B.<br /> B. The authors are using neighboring residues as reporters for proline hydroxylation, without validating this approach. How well do CSPs of A403 and I566 track with proline hydroxylation? Have the authors confirmed this using their 13C-NMR data or mass spec?<br /> C. Peak intensities. In some cases, the peak intensities of the end point residue look weaker than the peak intensities of the starting residue (5B, PHD2 WT I566, 6 ct lines vs. 4 ct lines). Is this because of sample dilution (i.e., should happen globally)? Can the authors comment on this?

(3) Data validating the CRISPR KO HEK293A cells is missing.

(4) The interpretation of the SEC data for the PHD2 mutants is a little problematic. Subtle alterations in the elution profiles may hint at different hydrodynamic radii, but as the samples were not loaded at equal concentrations or volumes, these data seem more anecdotal, rather than definitive. Repeating this multiple times, using matched samples, followed by comparison with standards loaded under identical buffer conditions, would significantly strengthen the conclusions one could make from the data.

Minor:

(1) Justification for picking the seven residues is not clearly articulated. The authors say they picked 7 mutants with "distinct residue changes", but no further rationale is provided.

(2) A major finding of the paper is that a disease-associated mutation, P317R, can differentially affect HIF1 prolyhydroxylation, however, additional follow-up studies have not been performed to test this in cells or to validate the mutant in another method. Is it the position of the proline within the catalytic core, or the identity of the mutation that accounts for the selectivity?

Reviewer #2 (Public review):

In the present manuscript, Li et al. use biochemical fractionation of "RNA granules" from P5 wildtype and FMR1 knock-out mouse brains to analyze their protein/RNA content, determine a single particle cryo-EM structure of contained ribosomes, and perform ribo-seq analysis of ribosome-protected RNA fragments (RPFs). The authors conclude from these that neither the composition of the ribosome granules, nor the state of their contained ribosomes, nor the mRNA positions with high ribosome occupancy change significantly. Besides minor changes in mRNA occupancy, the one change the authors identified is a decrease in puromycylated punctae in distal neurites of cultured primary neurons of the same mice, and their enhanced resistance to different pharmacological treatments. These results directly build on their earlier work (Anadolu et al., 2023) using analogous preparations of rat brains; the authors now perform a very similar study using WT and FMR1-KO mouse brains. This is an important topic, aiming to identify the molecular underpinnings of the FMRP protein, which is the basis of a major neurological disease. Unfortunately, several limitations of this study prevent it from being more convincing in its present form.

In order to improve this study, our main suggestions are as follows:

(1) The authors equate their biochemically purified "RG" fraction with their imaging-based detection of puromycin-positive punctae. They claim essentially no differences in RGs, but detect differences in the latter (mostly their abundance and sensitivity to DHPG/HHT/Aniso). In the discussion the authors acknowledge the inconsistency between these two modalities: "An inconsistency in our findings is the loss of distal RPM puncta coupled with an increase in the immunoreactivity for S6 in the RG." and "Thus, it may be that the RG is not simply made up of ribosomes from the large liquid-liquid phase RNA granules."

How can the authors be sure that they are analysing the same entities in both modalities? A more parsimonious explanation of their results would be that, while there might be some overlap, two different entities are analyzed. Much of the main message rests on this equivalence, and I believe the authors should show its validity.

(2) The authors show that increased nuclease digestion (and magnesium concentration) led to a reduction of their RPF sizes down to levels also seen by other researchers. Analyzing these now properly digested RPFs, the authors state that the CDS coverage and periodicity drastically improved, and that spurious enrichments of secretory mRNAs, which made up one of the major fractions in their previous work, are now reduced. In my opinion, this would be more appropriately communicated as a correction to their previous work, not as a main Figure in another manuscript.

(3) The fold changes reported in Figure 7 (ranging between log2(-0.2) and log2(+0.25)) are all extremely small and in my opinion should not be used to derive claims such as "The loss of FMRP significantly affected the abundance and occupancy of FMRP-Clipped mRNAs in WT and FMR1-KO RG (Fig 7A, 7B), but not their enrichment between RG and RCs".

(4) Figure 8 / S8-1 - The authors show that ~2/3 of their reads stem from PCR duplicates, but that even after removing those, the majority of peaks remain unaltered. At the same time, Figure S8-1 shows the total number of peaks to be 615 compared with 1392 before duplicate removal. Can the authors comment on this discrepancy? In addition, the dataset with properly removed artefacts should be used for their main display item instead of the current Figure 8.

(5) Figure 9 / S9-1, the density of punctae in both WT and FMR1-KO actually increases after treatment of HHT or Anisomycin (Figure S9-1 B-C). Even if a large fraction would now be "resistant to run-off", there should not be an increase. While this effect is deemed not significant, a much smaller effect in Figure 9C is deemed significant. Can the authors explain this? Given how vastly different the sample sizes are (ranging from 23 neurites in Figures S9-1 to 5,171 neurites in Figure 9), the authors should (randomly) sample to the same size and repeat their statistical analysis again, to improve their credibility.