Reviewer #3 (Public review):

Summary:

The authors presented evidence that spatial cognition in this population is under sexual selection, with extra-pair males, primarily chosen by the females, having better spatial cognition than males they cuckolded and males with better spatial cognition having more extra-pair young.

Strengths:

This cognitive ecology study was conducted on a well-known long-term study population of free-ranging mountain chickadees. This strong base, alongside a thorough study design and extensive statistical analyses, enabled the authors to address research questions that few other labs can address, making this a potentially powerful study of broad general interest.

Weaknesses:

Throughout the manuscript, there is a focus on the "mean number of location errors per trial over the first 20 trials". Performance changes across trials, so why weren't learning vs peak performance analyzed separately? Similarly, authors also describe results in the context of the entire task, but sometimes in the context of the first 20 trials - why is one prioritised over the other, and why is the emphasis not always consistent? Are the results across the two generally the same? A more thorough explanation addressing all these points is necessary.

Lines 429-432: Why was a categorical (i.e., chi-square test) and not a numerical comparison implemented? A numerical statistical test would capture more of the variation (i.e., the number of years separating the social and EPY males).

Reviewer #3 (Public review):

Summary:

The manuscript by Raiola and colleagues entitled "Quantitative computerized analysis demonstrates strongly compartmentalized tissue deformation patterns underlying mammalian heart tube formation" takes a highly quantitative approach to interrogating the earliest stages of cardiogenesis (12 hours, from early cardiac crescent to early heart tube) in a new and innovative way. The paper presents a new computational framework to help identify both regional and temporal patterns of tissue deformation at cellular resolution. The method is applied to live embryo imaging data (newly generated and from the group's previous pioneering work). In the initial setup, the new model was applied directly to raw time-lapse data, and the results were compared to actual cell tracks identified manually, showing close correlations of the model with the manual tracking. Next, they integrated spatial and temporal information from different embryos to generate a new model for tissue movement, driven by parameters such as tissue growth and anisotropy. Key findings from their model suggest that there are distinct compartments of tissue deformation patterns as the bilateral cardiac crescent develops into the linear heart tube, and that the ventricular chamber forms by a defined expansion pattern, as a 'hemi-barrel shape', with the arterial and venous poles (IFT and OFT) acting as the harnessing belts constraining the expansion of the chamber further. Lastly, the model is tested for its ability to predict future residence of cardiac crescent cells in the heart tube, which it seems to be able to do successfully based on fate tracking validation experiments.

The manuscript provides an exceptionally careful analysis of a critical stage during heart development - that of the earliest stages of morphogenesis, when the heart forms its first tube and chamber structures. While numerous studies have interrogated this stage of heart development, few studies have performed time-lapse imaging, and, to my knowledge, no other report has performed such in in-depth quantitative analysis and modeling of this complex process. The computational model applied to normal heart development of the myocardium (labelled by Nkx2-5) has revealed multiple new and interesting concepts, such as the distinct compartments of tissue deformation patterns and the growth trajectories of the emerging ventricle. The fact that the model operates at cellular resolution and over a nearly continuous time period of approximately 12 hours allows for unprecedented depth of the analysis in a largely unbiased manner. Going forward, one can imagine such models revealing additional information on these processes, performing analyses of subpopulations that form the heart, and maybe most importantly, applying the model to various perturbation models (genetic or otherwise). The manuscript is very well written, and the data display is accessible and transparent.

No major weaknesses are noted with the study. It would have been very exciting to see the model applied to any kind of perturbation, for example, a left-right defect model, or a model with compromised cardiac progenitor populations. However, the amount of live imaging required for such analyses renders this out of scope for the current study.

Reviewer #3 (Public review):

Summary:

Liu, He, et al. present results suggesting hippocampal ripples support short-term working memory. The basic finding that hippocampal ripples increase during a 7s working memory maintenance period is intriguing and previously not shown as far as I know, but a lack of control analyses within the task, across brain regions, or as compared to alternative oscillatory signals makes the overall evidence weak. The author needs to more thoroughly evidence this signal via several analyses (suggested below) to strengthen their finding. The paper moves on to a hippocampal-cortical ripple coupling analysis that needs further methodological details and corrected statistics to make a meaningful contribution. As is, the ripple coupling results don't seem to necessarily relate to the hippocampal ripples found in the maintenance period, making the manuscript somewhat incoherent and of low impact in its current form.

Major issues:

(1) The framing sets up "visual short term memory" (VSTM) and "long term memory" (LTM) as two different things. A long line of research with humans possessing MTL/hippocampus damage shows the hippocampal memory system contributes to working memory only when the task is difficult enough to warrant its recruitment (see Hannula et al. 2006 J. of Neuroscience, Pertzov et al. 2013 Brain, or particularly Jeneson et al. 2012 Learning & Memory and J. of Neuroscience). This theory therefore, suggests that the hippocampus contributes to working memory via LTM mechanisms, as opposed to it possessing two different roles (VSTM and LTM). While the authors might disagree with this framing, at a minimum, they should describe this line of work. As is, it's difficult to know how their task fits into this literature since it's a cross between a pattern separation probe (identify repeats from lures), working memory (7 s delays), and subsequent cued associate recognition. Addressing why they used this combination of task features would help frame its place in the literature.

(2) The basic idea of looking for hippocampal ripples as a marker for working memory maintenance is new, with no prior literature (that I know of in rodents or in the handful of human intracranial ripple papers) to build on. That said, I suspect hippocampal ripples act as a proxy for hippocampal activation, providing a possible explanation for the hippocampal ripple increase shown during the Maintenance period. The effect they show is well supported by the mixed effects modeling (MEM), making it a potentially meaningful finding, but considering the novelty, it's rather important that control analyses rule out alternative possibilities. I suggest two important ones and a third related to the lack of parametric manipulations in the next paragraph. First, the authors frame the paper by suggesting hippocampal ripples share features with beta/gamma burst theories of working memory maintenance. In that case, the obvious question is why use a ripple detector instead of measuring gamma (or beta) activity as in this previous work? Some work has suggested hippocampal ripples act differently than high-frequency activity (see Sakon et al. 2024 J. of Neuroscience), so an analysis contrasting ripples and gamma seems rather important. Second, and relatedly, the authors only compare the hippocampus and lateral temporal cortex (LTC), likely because these tend to be sites with strong coverage in epilepsy cases. That's ok, but typically there is also reasonable coverage in other MTL areas like entorhinal cortex and amygdala, which would serve as important controls to show what they're measuring likely relates to sharp-wave ripples (a hippocampal phenomenon) and not something more generic like gamma or HFA (as shown in Sakon et al. 2024, Howard et al. 2003 Cerebral Cortex, Axmacher et al. 2007 reference 26, Meltzer et al. 2008 Cerebral Cortex, etc.).

(3) Related to the last point, since there are no parametric manipulations (e.g., different delay durations, different set sizes, varying lure difficulties) there's no way to assess increased hippocampal ripples with stronger loads, which would be important for determining the hippocampal dependence of their task in the first place. Do the authors have any justification for this task as an assessment of hippocampal working memory? I could imagine using a top vs. bottom tercile of lure discrimination difficulty (as assessed across all participants or control non-patients) to compare hippocampal activity. But only after the first trial, each pair is used since only then would the patient have awareness of the difficulty of the upcoming comparison. Or maybe something could be done by comparing VSTM performance by splitting patients based on how they performed at the LTM test.

(4) Also related to the VSTM vs. LTM framing, the authors use an "LTM" cued category recognition task--presumably done at the end of the repeat/lure recognition task--as a way to argue that the hippocampal ripple effects they see relate to VSTM and not LTM. The LTM task is disappointingly underdescribed, where even in the methods (lines 588-592) I cannot figure out when this task was probed, how many trials were done in comparison to the VSTM task, etc. Considering they use the LTM task to support their VSTM interpretation, it's rather crucial to understand precisely what they did. As is, the comparison they do present relies on a statistical error, where they compare p-values (n.b. https://www.nature.com/articles/nn.2886) instead of performing a direct interaction test (lines 177-180). Specifically, if they want to say their signal relates more to VSTM subsequent memory rather than LTM subsequent memory, they need to run a model of the form: ripple_rates ~ remembered + test_type + remembered*test_type (where test_type is either their VSTM or LTM task).

(5) As noted, the increase in hippocampal ripples during maintenance seems substantial, and the MEM confirms a significant increase over time. That said, the presentation of the data is atypical, with an example raster from one channel followed by average time courses of ALL participants below it. Why not show full raster plots for all participants? Ripples are so sparse that all the data in the task can be visualized in a single raster easily. A swarm plot indicating inter-patient variability in the maintenance signal also seems crucial. As is, there is no way to assess how much of the signal depends on a small subset of channels or patients.

(6) To compare ripple rates across task phases, they average over the bounds of each phase (lines 657-660) and input these into their MEMs. This approach makes sense for quantifying what we see in the ripple plots (Figure 2), except for Encoding, where they average over the entire 3 s window, even though there is clear tuning only from ~0-1 s. Using the tuned region and not the entire window is standard and would be more appropriate for the comparisons to maintenance, retrieval, etc (e.g., line 147-148 doesn't check out when looking at the figure), otherwise you are averaging over a seeming ripple inhibition from 1-2 s. They perform a cluster-based permutation test as is, so that a window or something a bit wider would be appropriate.

(7) The authors pivot to a hippocampal-cortical ripple coupling analysis to build the argument that the hippocampal ripples shown in Figure 2 support memory maintenance in the cortex. They use a window of -500 to 500 ms from hippocampal ripples to assess coupling. This is quite wide, since it doesn't seem plausible that a cortical ripple 500 ms from a hippocampal ripple means they synchronize. They cite two papers to justify the analysis, both of which use {plus minus}500 ms windows, but for spindle-ripple coupling, not ripple-ripple, so are miscited. Later in the paper, they switch to {plus minus}50 ms for another coupling analysis, raising the question of why they used {plus minus}500 ms in the previous analysis to begin with. If they want to claim cortical ripples are tuned by hippocampal ripples all the way up to 500 ms away, they should show the rasters (as in Figure 4a) and timecourse ripple rates, but going beyond {plus minus}500 ms to show that ripples in the {plus minus}50-500 ms range are above, say 500-1000 ms to justify their window selection. I will point out that there IS previous work that used {plus minus}500 ms to measure cortical-cortical ripple coupling (Dickey et al 2022 PNAS, which should be cited regardless, as I believe the first hippocampal-cortical ripple paper showing memory effects), although the figures in that paper suggest anything beyond {plus minus}250 ms returns to baseline (see Figure 2A-B).

(8) Lines 239 to 243 comparing p-values instead of an interaction test.

(9) I don't understand what "Further analysis based on the identified cluster" means (line 271). I see in Figure 5c that their broadband classifier identified a window of optimal decoding, but did they use only activity in this cluster to train the subsequent classifier (Figure 5d)? If so, this is not described in the methods. And if it is done that way, I don't think the logic makes sense. As mentioned in comment 6, the ripples during encoding tune to 0-1s after image presentation. So it doesn't make sense to use a 1.85-2.25 s window for ripple-locked decoding-they should just be using the 0-1 s window (or whatever their cluster-based permutation test shows in Figure 2b). Otherwise, it would appear they are studying two different phenomena.

(10) As is, the results in Figure 5d need to be redone. First, the results described on lines 271-275 once again suffer from comparing p-values. They need to run an interaction model if they want to claim Maintenance shows stronger ripple-locked decoding than Encoding (it almost certainly will not, since Encoding appears to show some evidence of decoding (p=0.118)). Second, even if they do change the framing to say Encoding and Maintenance show significant decoding, is it meaningful if Retrieval fails to? If you cannot decode the same information at the time of retrieval as is theoretically being held in working memory during the delay, the coupled ripple reactivation story wouldn't appear to make sense. They do show significant Retrieval decoding in Figure 5a-b, but since I don't really understand how they settled on the "identified cluster" in Figure 5c, I'm not sure what to make of the difference between these decoders.

(11) Finally, as mentioned in the summary, the analyses in Figures 2-3 seem disjointed from those in Figures 4-5. Part of this has to do with the switch to a broadband classifier, then a switch back to coupled ripples, and then, as I already mentioned, decoding results with time windows that don't align with the hippocampal ripple effects they showed earlier. Further, since the main point of Figures 2-3 is to establish a ramp in hippocampal ripples across maintenance, shouldn't they be trying to show how the decoding changes over the course of the Maintenance period? It would also help the interpretation of Figure 5 to see how the coupled ripples change over time in Figure 4 (as they showed them in Figure 2).

Minor issues:

(1) Instead of citing a software package like Emmeans, the statistical test being performed should be explained.

(2) Decoding % accuracy in the heatmaps in Figure 5 and supplementary would be more intuitive, particularly since Figure 5b uses accuracy anyway.

(3) Figure 2b is misleading with an unnecessary change in the y-axis for retrieval.

(4) In Figure 2d, a significant cluster is mentioned, but not drawn onto the figure as in Figure 2b.

Reviewer #3 (Public review):

Summary.

Carricarte and colleagues use 0.9mm 7T fMRI in EVC and LOC, fused with previously collected EEG using the same stimulus set, in order to dissect feedforward and feedback contributions to human object processing through their layer-specific termination patterns. They report a feedforward signal in middle layers of EVC (~100ms) and LOC (~160ms), and a later signal in superficial LOC (~400ms) that they interpret as interareal feedback. Using commonality analysis with a Vision Transformer, they argue that this late signal carries higher-complexity features than the earlier signal, and conclude that feedback actively increases representational complexity in LOC.

Strengths.

The empirical work is methodologically ambitious. Sub-millimeter 7T coverage of both EVC and LOC, combined with layer-resolved EEG-fMRI fusion, represents a substantial technical achievement. The authors first reproduce established macroscale EEG-fMRI fusion patterns at 7T before extending the approach to the layer level. The figures throughout are beautifully designed and convey complex analyses with clarity. The empirical core of the paper - that LOC contains layer-distinct dynamics at distinct times, with the late signal carrying representational structure that differs in some way from the early signal - is supported by the data, though with caveats imposed by the LOC noise ceiling.

Weaknesses.

The authors' interpretation of these data (interareal feedback that reflects feature-complexity, related to the functional role of these signals) is not adequately supported and requires either reframing or substantial additional evidence.

Feedback vs. recurrence. The late superficial-LOC signal is interpreted as interareal feedback, but the data are equally consistent with within-area recurrence, lateral connections, or sustained feedforward dynamics. A reader expecting evidence of higher-area signals returning to early-time middle layers - a signature of interareal feedback - finds none in either region.

"Functional role" overclaim. The paper repeatedly claims to characterize the "functional role" of feedforward and feedback, but contains no behavioral linkage, no perturbation, and no analysis relating signals to perceptual outcomes; the fMRI task is explicitly orthogonal to object processing. What is demonstrated is spatiotemporal dynamics and representational format - both valuable, neither equivalent to functional role.

DNN analysis. The DNN analyses use several non-standard modeling choices that introduce more uncertainty than clarity. In the main analyses, the authors only use four sampling points from a single model (DeiT-small): transformer blocks 1, 7, and 12, plus the classification head. Then, the authors make their headline claims about complexity by comparing block 12 and the classification head; within the model, this is a distinction between an embedding layer and a supervised category readout, not a feature-complexity gradient. As such, the author's interpretation conflates semantic layers with representational "complexity." A more convincing use of this modeling strategy would be to demonstrate these effects in multiple models that might disentangle these factors-e.g., supervised (ResNet/ViT), self-supervised (DINOv2), and vision-language (CLIP) models-then to visualize these brain-model relationships across all layers. Alternatively, there are many suitable model-free analyses that could demonstrate the unique representational information within LOC without introducing any model-related concerns.

Reliability of LOC layer-resolved RDMs. The lower-bound noise ceiling for LOC mesoscale RDMs is approximately 0.05 across layers, with deep-LOC reliability essentially at zero. The central layer-resolved dissociation rests on RDMs that individual subjects barely reproduce; consequently, the deep LOC layer is dropped from the commonality analysis (Figure 4C shows only middle/superficial layers, while Figure 4B shows all three for EVC) because the data cannot support it. This is not damning, but it is consequential, and not sufficiently addressed in the manuscript.

Reviewer #3 (Public review):

Summary:

This article by Scheib et al. investigates how layer 5 extratelencephalic (ET) neurons in the frontal cortex encode sensorimotor information during motor learning, focusing on differences between their apical tuft dendrites and somas. The authors alternated recordings among these ET neuronal compartments in the mouse anterior lateral motor cortex (ALM) during a cued directional licking task with a target port shift. They found that while tuft dendrites predominantly encode sensory cues, with a subset selectively active during corrective actions, somatic activity was more strongly associated with action timing. Additionally, learning induced divergent plasticity: tuft dendrites increased their selectivity but decreased response gain, maintaining stable net selectivity, whereas somas showed increased net selectivity early in learning. Together, these findings reveal distinct sensorimotor representations and learning-related plasticity in dendritic and somatic compartments, providing insight into how compartment-specific activity in the frontal cortex may contribute to motor skill acquisition.

Strengths:

The authors developed an innovative imaging approach and a comprehensive data analysis pipeline to address a knowledge gap in the literature. By alternating imaging of dendritic tufts and somas in the same animals, they compare compartment-specific activity during motor learning and identify distinct encoding of task variables and learning-related plasticity across these compartments. Interestingly, a subset of dendritic tufts shows activity associated with corrective actions. The findings are discussed in the context of current theories of dendritic computation, credit assignment, and motor learning, providing a useful foundation for future mechanistic studies.

Weaknesses:

No major weaknesses were identified.

Reviewer #3 (Public review):

Summary:

In this study, the authors aim to address two questions. First, do people avoid cooperation primarily because of betrayal aversion beyond loss aversion? Second, can the effects of betrayal aversion and loss aversion be dissociated at the behavioral and neural levels? To address these questions, the authors compared individuals' choices of taking risks in a nonsocial risk task with those in a social cooperation task, with the two tasks matched in success probability and principal amount. They fitted computational models that include betrayal-aversion and loss-aversion terms and related the model parameters to ERP measures. Based on these analyses, the authors concluded that betrayal aversion has a stronger effect on cooperation than loss aversion and that betrayal is encoded earlier than loss in the brain. This is an important research question, and the attempt to combine computational modeling with ERP analysis is valuable. However, the current data analyses may not be able to support all the conclusions the authors made. For instance, the claims concerning the dissociation between betrayal aversion and loss aversion are not yet sufficiently supported by the evidence.

Strengths:

(1) The research question is theoretically important. Distinguishing betrayal aversion from loss aversion is important for research on trust, cooperation, and risky decision-making.

(2) The approach of integrating behavioral measures, self-report ratings, computational modeling, and ERP data is valuable and gives the study significance.

(3) The behavioral findings are broadly consistent. Participants reported stronger emotional responses in the cooperation task and were less willing to accept risk in the cooperation condition. These findings are generally in line with previous work on betrayal aversion and provide a reasonable manipulation check for the contrast between social and nonsocial risk.

Weaknesses:

(1) The manuscript states that the two tasks are matched in probability and principal amount, but the cooperation task additionally introduces partner outcomes, betrayal, and prosocial components. The Methods section states that, in the cooperation task, if both players cooperate, the principal is doubled and then split equally; if the partner betrays, half of the participant's principal is transferred to the partner. The model also includes an expected-other-reward term, namely, V_other=ω[p⋅2X+(1-p)⋅1.5X]. This raises an interpretive concern: if the two tasks differ not only in whether the source of uncertainty is social, but also in partner outcome, intentionality, and potential inequity structure, then the fitted "betrayal aversion" parameter may in fact reflect multiple motives rather than betrayal aversion alone. In the current experimental design, the "betrayal aversion" parameter may not be uniquely interpretable as a pure betrayal-specific construct, and the current evidence is insufficient to support such a specific interpretation.

(2) Participants were informed that the cooperation probabilities were derived from previous real participants, whereas in fact these probabilities were randomly generated. In addition, six participants explicitly expressed doubts about the authenticity of the social interaction, yet the authors retained these participants with only the brief statement that this "did not affect the results." For such a critical manipulation, this explanation is too brief. I recommend that the authors report robustness analyses excluding skeptical participants. Since six participants reportedly doubted the authenticity of the social interaction, and some participants also performed poorly on the catch trials, it would be important to show whether the main behavioral, modeling, and ERP findings remain after excluding these participants. This is especially important because the manuscript's central interpretation depends on the assumption that the cooperation task was genuinely experienced as social.

(3) The descriptions of the sample size are inconsistent across sections. The Participants section states that, after excluding one participant for misunderstanding the instructions, the final sample consisted of 49 participants; however, the behavioral results section later states that only 42 participants were included in the final analyses due to recording problems. This discrepancy is important because readers need to know clearly which sample was used for the behavioral analyses, which for the model fitting, and which for the ERP analyses; whether these analyses were conducted on the same participants; and whether the exclusion criteria were consistent across analyses. The manuscript needs a more transparent description of sample size and exclusion criteria.

(4) The authors need to do more thorough analyses to validate their models. In addition to AIC and parameter recovery, I would encourage the authors to include other model comparison metrics where possible, such as BIC and exceedance probability, as well as model-recovery analyses. The authors should also do model-based simulation analyses to show that the winning model can capture the contextual effects observed in real data.

(5) The authors should explain the rationales for the choice of ERP time windows and component selection in more detail. The current ERP analyses are time-locked to principal onset, and P3/LPP are extracted from fixed time windows. The authors should explain why this is the most appropriate time-locking point for examining betrayal- and loss-related computations, and why alternative time-locking points, such as probability-cue onset or other key task events, were not used. More importantly, the time windows of P3 and LPP are defined arbitrarily in the current analyses. The authors need to apply a more principled approach to define ERP components. It looks like the P3 and LPP are from the same ERP component in Figure 3.

(6) The manuscript has several internal inconsistencies in terminology, figure references, and result descriptions. These issues weaken the clarity of the arguments and reduce the readability of the manuscript.

(7) The authors partially achieved their aims. The study does provide evidence that social risk and nonsocial risk are not treated equivalently, and it also offers a computational framework that is informative for the field. This is an important topic, and the overall approach is promising.

via u/BlindAssassin111 at https://www.reddit.com/r/typewriters/comments/1u19nbi/1960_optima_super/

https://www.reddit.com/r/typewriters/comments/1u03qli/hermes_3000_2nd_gen_made_new_knobs_3d_printed_but/

Reviewer #3 (Public review):

The manuscript by Bai et al presents a study of the effect of trapping on the efficiency of chemotactic spreading. While the overall impression of the study is positive, there are multiple drawbacks that accumulate and together make the statement of the paper not fully justifiable. Below, I provide some detailed comments in chronological order, and indicate those of particular importance.

(1) On the first page of the Introduction, the authors use the following wording: "...how bacteria optimise their intrinsic motility parameters to maximise navigation efficiency". However, it is not shown or known whether they do. In the experiments, the authors fetch the bacteria at the far front and artificially select the ones with shorter run times. The ones at the front could be the effect of heterogeneity of the population rather than an adaptation. Moreover, the authors claim that the selective pressure is via trapping. But this can be due to a multitude of other factors that change with agar concentration, availability of nutrients, osmotic properties of water, etc.

(2) At the beginning of the results section, the authors claim that for both agar concentrations, they observe a progressive increase in chemotactic navigation. I do not see how the data for 0.2 % agar would correspond to that. Migration speed remains flat.

(3) (Important). The authors claim that the mean run speed remained constant. But this is definitely not true, as seen in the plots. The speed of modernity is increasing for both agar conditions. And here it is important to note that the chemotactic drift velocity is proportional to the square of run speed (which is not the case for the formulas in this paper, see comment below). Thus, even smaller changes in v_0 can result in a significant increase in the drift velocity.

(4) (Important). Tumble bias is also significantly increasing in 0.3 agar concentration. While it is not clear from the paper what exactly the tumble bias is, if it is related to the persistence of the turning angle, this also has a linear effect on the chemotactic drift velocity.

(5) (Important). When performing aTc dependence testing, the authors didn't report how other observables of swimming behaviour are changing.

(6) (Very important). I'm not sure that by interfering with Che-Z expression, one does not affect the whole chemotactic circuit, for example, by changing G (in terms of the model) and thus the optimality occurs not due to the agar concentration/traps but due to the perturbations in the circuit. Also, the effect of different % seems to be much more minor compared to the overall induced changes in spreading speed.

(7) (Very important). I was very confused by the statement of the authors about only 3% of traps being exited due to tumble. I don't think this is possible (in a way consistent with the suggested model). Mean free run times (Figure 1C) go down to 0.4 s. Duration of tumbles is 0.3s (Figure S2c), but the duration of traps is longer than tumbles (and a bit shorter than runs). So how can it be that a running cell gets into a trap and only in 3% cases it experiences a tumble? What would be the distribution of run durations if one combines pre-trap+trap_time+post_trap run time - would they still have a mean below 1s?? It really looks like the authors are not able to detect tumbles when bacteria are trapped. Or is there an active mechanism suppressing tumbles when in the trap?

(8) It is not clear what it means that post-tumble angles were uniformly distributed. Does this refer to only trap-associated tumbles? It is known that in the freely swimming e.coli the tumbling angles are not isotropic but have a preference for the forward direction. Is it different in agar conditions?

(9) (Very important) The authors assume an oversimplified model for the chemotactic drift based on biased random walks. As a result, the answer for chemotactic drift velocity has a wrong scaling with run speed. In the linear theory of chemotaxis by de Gennes, the scaling is v_0^2, while the authors use a linear relationship. Thus, the assumption of the simplified model is incorrect. The exact effect of the traps (where no tumbling is happening, and the directional memory is conserved) needs to be properly calculated, for example, in the same de Gennes framework. And I can't say what the result would be from the top of my head because the calculation is, in fact, not too trivial. Thus, the model used is oversimplified, and thus the fact that it shows a non-monotonous relationship with tau_f is of little predictive power.

Taken together, you see that all the key points that are used in the chain of the argument about the optimality are not rock solid and allow for alternative explanations. I think all those either need to be tested explicitly or at least clearly discussed, and the respective conclusions of the paper need to be rephrased. In my view, this work needs major revision.

Reviewer #3 (Public review):

Summary:

The authors argue that establishing the expression pattern and sub-cellular localisation of an animal's proteome will highlight hypotheses for further study. This claim is probably accepted by many in the community. This manuscript seeks to confirm the feasibility of establishing such a resource, by using current transgenic methods to knock in DNA encoding different colored fluorescent tags into C. elegans genes.

Strengths:

The authors make the points above. For example, they provide evidence that the C. elegans germline harbors two populations of mitochondria that differ qualitatively in the proteins they express. They also confirm that labelling the whole proteome is an achievable goal with relatively limited resources and time.

Weaknesses:

The work is somewhat incremental in that it uses existing transgenic technology. Cell biology in C. elegans is challenging because of the small size of many of its cells, notably neurons. This can make establishing the sub-cellular localisation of a fluorescently tagged protein, or co-localizing it with another protein, tricky. The authors point out in their introduction that advances in light microscopy such as diSPIM, STED and ISM (a close relative of SIM), have increased the resolution of light microscopy. They also point out that recent advances in expansion microscopy can similarly help overcome the resolution limit. However, they do not use these technologies to characterize their transgenic strains.

Reviewer #3 (Public review):

The SET1C/COMPASS complex is the histone H3K4 methyltransferase in Saccharomyces cerevisiae, where it plays pivotal roles in transcriptional regulation, DNA repair, and chromatin dynamics. While its canonical function in histone methylation is well-established, its full interactome remains poorly defined. Moreover, whether SET1C methylates non-histone substrates has been an open question.

In this study, Luciano et al. employ systematic yeast two-hybrid (Y2H) screening to uncover novel interactors and functions of SET1C. Their findings reveal potential functional connections to RNA biogenesis, chromatin remodeling, and non-histone methylation.

The authors performed multiple Y2H screens using Set1 (full-length, N-terminal, and C-terminal fragments) and each of its seven subunits as baits. They identified high-confidence interactors that link SET1C to diverse cellular processes, including chromatin regulation (e.g., the SWI/SNF complex via Snf2), DNA replication (e.g., Mcm2, Orc6), RNA biogenesis (e.g., spliceosome components Prp8 and Prp22; polyadenylation factors Pta1 and Ref2), tRNA processing (e.g., Trm1, Trm732), and nuclear import/export (e.g., importins Kap104 and Kap123). Some of these interactions were further validated by immunoprecipitation or in vitro assays.

Given the interaction of Set1 with Slx5 and Wss1-proteins involved in SUMO-dependent processes-the authors investigated and convincingly demonstrated that Set1 is sumoylated. This modification may influence the function and regulation of the SET1C complex.

Finally, the authors provide evidence that SET1C methylates Snf2, the catalytic subunit of the SWI/SNF chromatin remodeling complex.

One of the interactors, Nrm1, contains a domain resembling the H3K4-methylated sequence, which is also present in other proteins. Whether this H3K4-like domain is required for methylation remains to be demonstrated

Strengths:

This study offers valuable insights into the interactome of SET1C, suggesting potential links between the complex and a wide range of cellular processes. It also provides information on the possible regulation of Set1 by sumoylation. Finally, the finding that Snf2 is methylated in a Set1-dependent manner could significantly expand the known targets and functions of SET1C.

Weaknesses:

Many of the Y2H interactions remain to be validated and have to be considered as a starting point for further studies. Their functional significance remains to be explored. Several conclusions based on these 2HY data are speculative.

Reviewer #3 (Public review):

Summary:

This study investigates how the activity of hypothalamic paraventricular oxytocin (PVNOT) neurons relates to physiological states in female mice, with a particular focus on behavioral states and thermogenic sympathetic activity. To address this question, the authors combined automated video-based behavioral classification with calcium imaging of PVNOT neuron activity. Sympathetic thermogenesis was inferred from surface temperature changes measured by infrared thermography, and the authors have made their custom analysis scripts available. The authors report that strong, pulsatile activation of PVNOT neurons was "occasionally" observed immediately before transitions from resting to active states. This observation suggests that PVNOT neuronal activity may facilitate the transition from rest to activity. This phenomenon was observed in both pair-housed and individually housed animals. Taken together, these findings raise the possibility that the oxytocinergic system contributes to naturalistic behavior transitions even in the absence of social interactions. However, concerns regarding the selectivity of GCaMP expression in oxytocin-expressing neurons call into question the validity of the recorded PVNOT neuronal activity.

Strengths:

The oxytocinergic neural system is believed to subserve a wide range of physiological functions. Elucidating these roles requires monitoring PVNOT neuronal activity under diverse behavioral contexts, as well as manipulating this activity to establish causal relationships. In this study, the authors present a technically sound experimental framework that integrates behavioral tracking in both individually and group-housed mice with the monitoring and manipulation of PVNOT neuron activity. This setup represents a valuable methodological resource for researchers investigating the physiological functions of oxytocin.

Weaknesses:

(1) Immunohistochemical validation of selective GCaMP expression in oxytocin-expressing neurons showed that only 24-51% of GCaMP-positive neurons expressed oxytocin. As an alternative approach, the authors demonstrate that GCaMP-expressing PVN neurons in virgin females exhibit calcium peaks during rest-wake transitions with kinetics similar to those observed in PVNOT neurons during early lactation. However, this comparison is based solely on population-level peak profiles and does not provide direct evidence for cell-type specificity of GCaMP expression in oxytocin neurons. This limitation substantially undermines the validity of the optical calcium imaging data. In situ hybridization targeting oxytocin mRNA, rather than immunohistochemistry, may provide a more reliable assessment of expression specificity.

(2) Although the authors' interpretation is generally consistent with the data presented, their main conclusions rely heavily on observational findings. Moreover, optogenetic stimulation of PVNOT neurons failed to robustly recapitulate behavioral state transitions (Figs. 6D and S5B). Further interventional experiments will be necessary to more rigorously test the authors' interpretation and to establish mechanistic insight into the causal relationship between PVNOT activity and rest-to-active transitions. In particular, loss-of-function approaches targeting the PVNOT system, such as OXTR antagonism, inhibitory DREADDs, or cell-type-specific ablation, will be essential to determine whether perturbation of this system alters behavioral state transitions These points should be addressed in future studies.

Reviewer #3 (Public review):

Summary:

This manuscript by Mukherjee and colleagues extended earlier studies on the coordination of the SidC and SidE effector families on the generation of a unique ubiquitin layer on the surface of the vacuoles containing the bacterial pathogen Legionella pneumophila (LCV).

Strengths:

The main strength of the manuscript is the identification of the small GTPase Rab5 as a major "carrier" of these differently modified ubiquitin and ubiquitin chains, which was nicely quantified.

Weaknesses:

The results are mostly descriptive, based on mechanistic studies from earlier works.

Reviewer #3 (Public review):

Summary:

The authors record from the ACC during a task in which animals must switch contexts to avoid shock as instructed by a cue. As expected, they find neurons that encode context, with some encoding of actions prior to the context, and encoding of neurons post-action. The primary novelty is dynamic encoding of action-outcome in a discrimination-avoidance domain, while this is traditionally done using operant methods.

Comments on revised version:

I appreciate subsequent responses to my comments and other reviewers. My comments are addressed, and at this point, I think readers can judge the work appropriately in context.

Reviewer #3 (Public review):

Summary:

In this unusual paper, Hodapp and Meyniel relate the spatial topography of activity maps for confidence and surprise (from four learning tasks) to the spatial topography of receptor density maps from atlas data. They find that the brain maps for confidence and surprise are largely consistent across four studies using different stimuli/ task demands. They then use a general linear model to predict the spatial pattern of confidence/surprise-related activity from the spatial distribution of receptors (receptor types) for several neuromodulators. Further analyses test which neuromodulators are most important for predicting the functional maps.

Strengths:

The study gives an interesting new perspective on the brain networks for surprise and confidence, indicating that one reason for the involvement of different networks with these computational parameters is the neurochemical sensitivity of tissue within those networks.

Weaknesses:

I felt the paper was light on context.

To what extent are the distributions of receptor types correlated with each other?

What does the spatial topography of receptor density look like for the identified receptors (NET, MOR, 5HT1b)? Could these be displayed alongside the functional networks? I realise these are atlas data, but for me to interpret the result, I'd need to see the map, and I don't want to download the atlas.

To what extent are the correlations with receptor maps network-wide, vs being driven by one big patch of activity in a single region with high receptor density? To me, this would be important - does this study demonstrate that distant regions united in a functional purpose by shared receptor profile (which would in my opinion be more intersting that the alternative, that there is a single region within each network driving the effect).

Finally, I wasn't convinced by the spin test in this particular application. To my mind, permutation tests are valid when the permuted points are interchangeable under the null. The spin test, as used, preserves the distribution and spatial pattern of activity, but assumes that it could equally plausibly be relocated to any angle on the 3D surface (under the null). However, the brain has a lot of structure that is non-uniform across its surface (connectivity patterns and histological boundaries being important ones). The observed data probably follow this structure, but the 'spun' or permuted datasets probably overlay randomly on the connectivity structure (for example), so that one blob of activity has uniform connectivity in the real data, but overlaps the projections of multiple white matter tracts in the permuted data. But then the permuted data would likely be more heterogeneous in terms of both function and histology than the original data. Since connectivity, histology (layer structure) and receptor density are likely correlated, I think it must be impossible to find verticies that differ in one modality whilst being interchangeable in all others, therefore it may not be possible to use permutation logic to make a claim about (say) receptor density independently of connectivity and histology.

I should add I'm not sure how one would carry out a permutation test that respects the underlying brain anatomy here, or whether this is even possible; that is a difficult question.

I would add that I think the observation that the functional networks have different receptor profiles is interesting, even as a qualitative observation, but not convinced the statistical approach can be justified.

Reviewer #3 (Public review):

Summary:

This study investigates the neural mechanisms underlying sensory-perceptual differences in autism through a naturalistic movie-viewing fMRI paradigm. By employing encoding models, the authors demonstrate that autistic children and adolescents exhibit a specific alteration in visual feature weighting, characterized by a shift toward low-level visual feature encoding in higher-order association regions, particularly the posterior Superior Temporal Sulcus (pSTS). This shift is linked to social symptom severity, providing empirical support for Weak Central Coherence accounts.

Strengths:

The study's primary strengths lie in its methodological rigor and innovative approach. The use of a pre-registered analysis plan ensures transparency and enhances the credibility of the findings, while the encoding models allow for a fine-grained dissociation of low-level versus high-level feature representations across the cortex. Overall, the writing is clear, the logic is sound, and the results offer a significant contribution to the field by refining our understanding of how sensory processing is differentially organized in autism.

Weaknesses:

While the study presents compelling findings regarding visual feature encoding in autism, several methodological and interpretive limitations warrant consideration. First, the Discussion focuses primarily on WCC and EPF theories, failing to explicitly address how the results intersect with other prominent frameworks mentioned in the Introduction, such as Bayesian predictive coding or E/I imbalance hypotheses. Second, the demographic characteristics and specific sample sizes of the ASD-ADHD and ASD+ADHD subgroups are not reported, limiting the interpretability of the stratified analyses; furthermore, the counterintuitive finding that the ASD+ADHD group resembles controls is not sufficiently discussed. Third, given the significant group difference in IQ and the known relationship between cognitive ability and neural processing, the potential confounding influence of IQ on the neuroimaging results requires more explicit acknowledgment, particularly since IQ was not included as a covariate in the primary models.

Reviewer #3 (Public review):

Summary:

This study makes clever use of generative AI to create stimuli that are pixel-for-pixel identical but which have radically different meanings depending on their orientation, to investigate the perception of animacy while retaining control over low-level image features (so-called 'anagram' stimuli).

The authors present seven elegantly designed experiments in a commendably compact format.

Experiments 1 and 2 involved a working memory paradigm in which participants had to spot which of five objects in an array changed after a pause. Importantly, the changed object was an anagram stimulus that in one orientation matched the animacy/inanimacy of the changed object, and in the other orientation was the opposite (e.g., a rabbit is replaced by either a dog or a boot, where the dog and boot stimuli are actually identical, just rotated by 90 degrees). They found a difference in accuracy depending on whether the animacy of the objects matched.

Experiments 3 and 4 used a visual search task in which the participants had to localize the target, and the distractors were anagrams that either matched the target in terms of animacy or did not. There was a significant cost in terms of response time when the animacy of the target was the same as that of the distractors. Experiments 5 and 6 also used a similar visual search design, except that the task was to determine if the target was present or absent from the display, and the distractors again either matched or differed from the target in terms of animacy. Again, the authors found slower responses when the distractor arrays matched the animacy of the target than when they differed.

An obvious potential concern about the studies is addressed by Experiment 7. It is unclear if the observed effects are related to the specific orientations of the target and distractor stimuli selected in each condition. For example, it could be that all the animate versions of the anagrams involved tall and skinny shapes, while all the inanimate versions involved wide and short objects, due to the 90-degree rotational difference between the two versions of the stimuli. To control for this, the authors repeated the visual search experiment but with convex-hull silhouettes of each of the stimuli. In other words, all targets and distractors from each trial were replaced by a black splotch with approximately the same overall outline (envelope) as the corresponding stimulus. Importantly, in contrast to the anagram stimuli, the silhouettes had had no meaningful semantic interpretation, and their animacy did not change depending on their orientation.

Strengths:

The main strength is the elegant use of stimuli that control almost perfectly for low-level image features.

Weaknesses:

My only real concern about the study is whether the findings truly provide evidence for a high-level visual representation of animacy independent of the low-level stimulus characteristics, or whether, instead, the effects are essentially semantic priming, which is independent of visual processing per se. For example, if all the stimuli in the experiments were replaced with the verbal names of the depicted objects instead of pictures, would we expect different results? Words can also access semantic representations of the animacy of objects, and also don't suffer from low-level visual confounds. It would be helpful to add a discussion of this possibility to the article.

Reviewer #3 (Public review):

The manuscript by Ono et al describes application of prime editors to introduce precise genetic changes in the zebrafish model system. Probably the most important observation is that compared to the "standard" PE2, prime editor with full nuclease activity appears to be more efficient at introducing insertions into the genome. Although many laboratories around the world have successfully used oligonucleotide-mediated HDR to insert short exogenous sequences such as epitope tags or loxP sites into the zebrafish genome, the method suffers from high frequency of indels at the edit site. Thus, additional tools are badly needed, making this manuscript very important.

Comments on revised version.

Thank you for thoroughly addressing my minor concerns.

Reviewer #3 (Public review):

This article demonstrates a comparative study on two funding mechanisms adopted by the National Institutes of Health (NIH). The authors adopted a quantitative approach and introduced five metrics to compare the output of intramural and extramural grants. These findings reveal the impacts of intramural and extramural grants on the scientific community, providing funders with insights into the future decisions of funding mechanisms they should take.

Strengths:

The authors clearly presented their methods for processing the NIH project data and classifying projects into either intramural or extramural categories. The limitations of the study are also well-addressed.

Reviewer #3 (Public review):

Summary:

The American beefalo cattle breed was developed as a mixture of 5/8 domestic cattle and 3/8 (or 37.5%) bison ancestry. The authors sequenced 50 genomes from bison and hybrids (historical and present-day). They found that most animals did not carry any detectable bison ancestry, with only a few between 2-18%, while other beefalo had taurine/zebu cattle ancestry, which may explain morphological traits. Breeding design was likely each time to a parental instead of to other admixtures.

The authors utilize whole genome sequence data to explore the ancestry of beefalo with respect to expected and possible contributions from cattle lineages. Using molecular and analytical methods central to questions exploring genomic ancestry and identity, the authors very nicely show evidence that calls into question ability of ancestry to be deduced from breed club documentation without considering reproductive challenges that are known in hybridization between cattle lineages.

Comments on revised version:

The authors have addressed all my comments to help improve presentation of specific details, results, and readability. Thank you!

Reviewer #3 (Public review):

Summary:

In this manuscript, Javorski and colleagues investigate how CO2 valence is processed in the Drosophila olfactory system. Although CO2 is classically associated with an aversive labeled‑line pathway, its behavioral significance can be modulated by environmental context, such as the presence of food‑related cues. The circuit‑level mechanisms underlying this flexibility remain incompletely understood. The authors address this gap by examining how CO2 sensory information diverges at early stages of olfactory processing and how distinct neural pathways contribute to opposing behavioral outcomes. By identifying the local interneuron LN23 as a relay for CO2‑induced aversion, the study suggests that CO2 valence processing may begin to diverge at the level of the antennal lobe, prior to synaptic integration in higher‑order brain regions such as the lateral horn.

Strengths:

A major strength of this study is its comprehensive, multi-level experimental design that effectively links neuronal identity, synaptic organization, and behavior. The authors combine calcium‑based anatomical mapping, activity‑dependent reporters, optogenetic and thermogenetic manipulations, and connectomic analyses with behavioral readouts under genetically defined neuronal activation or silencing conditions. Specifically, the identification of LN23 as a component of the CO2 avoidance pathway is supported by anatomical, genetic, and behavioral evidence. Both silencing and activation experiments indicate that LN23 plays an important role in mediating CO2‑induced aversive responses. In contrast, manipulation of the projection neurons (PNv bi and PNv uni) produces more modest behavioral effects, suggesting a degree of specificity for LN23‑associated circuitry within the avoidance pathway. Moreover, the use of previous reported connectome to identify downstream third‑order neurons strengthens the proposed circuit model and provides anatomical support for early divergence of CO2 valence processing.

Weaknesses:

While the study provides a strong mechanistic framework for CO2 aversion, some aspects of context‑dependent valence modulation are less directly addressed and may benefit from further experimental exploration.

Reviewer #3 (Public review):

Summary:

Several recent findings indicate that forces perpendicular to the microtubule accelerate kinesin unbinding, where perpendicular and axial forces were analyzed using the geometry in a single-bead optical trapping assay (Khataee and Howard, 2019), comparison between single-bead and dumbbell assay measurements (Pyrpassopoulos et al., 2020), and comparison of single-bead optical trap measurements with and without a DNA tether (Hensley and Yildiz, 2025).

Here, the authors devise an assay to exert forces along the microtubule axis by tethering kinesin to the microtubule via a dsDNA tether. They compared the behavior of kinesin-1, -2, and -3 when pulling against the DNA tether. In line with previous optical trapping measurements, kinesin unbinding is less sensitive forces when the forces are aligned with the microtubule axis. Surprisingly, the authors find that both kinesin-1 and -2 detach from the microtubule more slowly when stalled against the DNA tether than in unloaded conditions, indicating that these motors act as catch bonds in response to axial loads. Axial loads accelerate kinesin-3 detachment. However, kinesin-3 reattaches quickly to maintain forces. For all three kinesins, the authors observe weakly-attached states where the motor briefly slips along the microtubule before continuing a processive run.

Strengths:

These observations suggest that the conventional view that kinesins act as slip bonds under load, as concluded from single-bead optical trapping measurements where perpendicular loads are present due to the force being exerted on the centroid of a large (relative to the kinesin) bead, need to be reconsidered. Understanding the effect of force on the association kinetics of kinesin has important implications for intracellular transport, where the force-dependent detachment governs how kinesins interact with other kinesins and opposing dynein motors (Muller et al., 2008; Kunwar et al., 2011; Ohashi et al., 2018; Gicking et al., 2022) on vesicular cargoes.

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Reviewer #3 (Public review):

Summary:

This manuscript examines how phosphate limitation primes E. coli and Salmonella for defense against polymyxin antibiotics. Other environmental signals, such as altered levels of extracellular Mg or Fe, were previously shown to induce polymyxin resistance in Enterobacteriaceae, and phosphate limitation was known to augment polymyxin resistance in other organisms such as A. baumannii and P. aeruginosa; however, whether phosphate limitation boosted polymyxin resistance in Enterobacteriaceae was not known. This study shows that this indeed occurs, and the mechanism is distinct from that in A. baumannii and P. aeruginosa. The model proposed is: (1) low phosphate causes bacteria to jettison Mg to balance cellular P/Mg ratio, (2) extracellular Fe3+ associates with the cell envelope to replace Mg as LPS-bridging cation, and (3) envelope Fe3+ activates PmrAB, which mediates a transcriptional response leading to L-Ara4N modification of lipid A and protection from polymyxin B. Flooding with Mg or chelating the surface Fe3+ blocks the protective response to low phosphate in E. coli and Salmonella but not in P. aeruginosa despite Fe still mobilizing in the latter. The differential response between Enterobacteriaceae and P. aeruginosa is connected to the presence/absence of Fe-sensing motifs in the PmrB periplasmic domain.

Strengths:

The strengths of the study are the wide array of approaches used and the thorough characterization of a novel stress-response mechanism involving metal mobilization. Combined with the analysis of multiple bacterial families, the results clarify how different strategies have evolved to defend against polymyxins during phosphate starvation.

Weaknesses:

Controls are needed in some of the genetic experiments, namely complementation, to verify linkage of defective survival phenotypes to the genes mutated and to rule out protein stability defects for the PmrB variants tested. In addition, the generalizability of the metal mobilization feature of the model would be strengthened by examining media with differing metal composition. Claims about antibiotic resistance would be strengthened by data examining bacterial growth in the presence of an antibiotic.

Reviewer #3 (Public review):

Summary:

This study evaluates the contributions of the mammalian PG-binding protein PGLYRP1 to Bordetella infection. The authors find potential roles for PGLYRP1 in both bacterial killing (canonical) and regulation of inflammation (non-canonical). While these are interesting findings and the idea that PG fragment release has differential impacts on infection depending on fragment structure, the study is ultimately limited by the lack of connection between the in vivo and in vitro experiments and determining the precise mechanism of how PGLYRP1 regulates host responses and bacterial fitness during infection requires further study.

Strengths:

(1) The combination of scRNAseq with in vitro and in vivo assays provides complementary views of PGLYRP1 function during infection.

(2) The use of TCT-deficient B. pertussis provides a useful control and perturbation in the in vitro assays.

Weaknesses/Areas for future study:

(1) The study does not ultimately resolve the initial early versus late phenotype divergence. While the in vitro assays suggest explanations for their in vivo observations, further mechanistic links are lacking and necessary for the author's conclusions throughout. To state one example, what is the early and late infection phenotype of TCT- Bp in mice lacking PGLYRP1? RNAseq data is reported from these mice but there are no burden or pathology studies. Furthermore, what are the neutrophil phenotypes (NOD-1/TREM-1 activation) in vivo? And are they dependent on PGLYRP1 and/or TCT? This will be an important topic of future study, as noted by the authors in their response.

(2) It is unclear whether or how the NOD1 and TREM-1 pathways interact.

(3) Many of the study's conclusions rely on the use of HEK293 reporter lines in the absence of bacterial infection, which may not be physiologically representative.

Comments on revised version.

The authors have responded adequately to my comments.

Reviewer #3 (Public review):

Summary:

This multi-omics study by Zhou et al elucidates the context-dependent roles of the Janus kinase-signal transducer and activator of transcription (JAK-STAT) pathway (JSP) across different cellular compartments in the breast cancer tumor microenvironment. While bulk JSP activity is associated with a favorable prognosis, single-cell analysis reveals a paradoxical landscape: high JSP in T cells drives anti-tumor cytotoxicity and reduces exhaustion, whereas high activity in tumor epithelial cells promotes malignancy and immunosuppression via the MIF-CD74 signaling axis. The JSP score (immune-related) serves as a robust predictive biomarker for response to anti-PD-1 immunotherapy, particularly in triple-negative breast cancer (TNBC). Furthermore, the study identifies the STAT4/SLC47A1 axis as a critical mechanism through which tumor cells resist ferroptosis, facilitating disease progression. These findings suggest that broad JAK-STAT inhibition may be counterproductive in cancer therapeutics; instead, therapeutic success depends on precise modulation and carefully timed interventions to preserve its T-cell-associated functions. This study may inspire future studies to explore specific factors that selectively modulate JAK-STAT activity in immune cells to achieve favorable therapeutic outcomes.

Strengths:

Significant therapeutics implications

Weaknesses:

Limited molecular mechanisms

Comments on revised version:

The authors have addressed my comments

Reviewer #3 (Public review):

Summary:

The study "PIK3CA-related overgrowth spectrum (PROS) zebrafish models reveal pan-lineage developmental dysregulation" presents important findings that extend significantly beyond a single subfield, bridging developmental biology, vascular medicine, and cancer-related PI3K signalling. By developing mosaic zebrafish models of PROS and combining live imaging with single-cell transcriptomics, the authors provide compelling evidence for a non-cell-autonomous mechanism of tissue overgrowth, a conceptual shift with meaningful therapeutic implications.

Strengths:

The evidence is overall convincing, with methodology appropriate and well-validated relative to the current state of the art; the integration of multiple approaches (in vivo modelling, scRNA-seq, ligand-receptor inference) strengthens the central claims. However, some aspects of the proposed non-cell-autonomous signalling mechanisms remain partly correlative, and direct functional validation of the rewired ligand-receptor interactions would further consolidate the conclusions.

Weaknesses:

The transgenic overexpression approach chosen by the authors represents a well-established and effective strategy for generating mosaic models in zebrafish. However, this approach introduces notable limitations: the lack of control over transgene dosage and unknown integration sites may generate non-physiological effects, potentially confounding the interpretation of key findings.

The authors are certainly aware that alternative approaches (though technically more demanding) could be considered in future studies to further strengthen the model. For instance, a CRISPR/Cas9-mediated knock-in of the pik3ca-PROS allele at the endogenous locus (retaining upstream native regulatory elements with only a minimal promoter in the construct, co-expressed with a fluorescent reporter via P2A) could allow even more physiological, lineage-restricted expression while enabling direct visualisation of mutant cells. Mesodermal specificity could potentially be further refined by driving mosaic Cas9 expression under a pan-mesodermal tbx promoter, restricting editing to the relevant lineage while simultaneously marking mutant cells fluorescently, thus even more closely mimicking the post-zygotic mutational events characteristic of PROS. As a complementary strategy, blastula transplantation experiments using pik3ca-PROS donor cells (ideally co-expressing a distinct fluorescent marker such as mCherry) into fli1:GFP transgenic hosts could provide a powerful and technically consolidated approach to directly visualise and quantify non-cell-autonomous effects on host vasculature, with precise control over mutant cell burden. This combinatorial framework, separating donor mutant cells from host tissue in a two-colour imaging setup, could be particularly compelling for validating the ligand-receptor rewiring predicted by single-cell transcriptomics in future investigations.

These reflections are offered in the spirit of prospective methodological development and do not diminish the value of the current work, which opens a valuable new avenue for therapeutic investigation, suggesting that targeting indirect overgrowth-propagating signals, alongside PI3K inhibition, deserves serious consideration.

Reviewer #3 (Public review):

Summary:

Triandafillou and colleagues report a single-cell resolved spatial atlas of gene expression of 26 gastruloids. While previous work had analyzed either single-cell gene expression or spatially coarse-grained patterns of gene expression (van den Brink et al, 2020), the authors here use multiplexed sequential RNA FISH (seqFISH) to create the first gastruloid atlas, which is simultaneously spatially and cellularly resolved. This atlas adds to a growing list of resources cataloging gastruloid development (see also Suppinger et al 2023).

To analyze this dataset, the authors also describe a novel analytical framework. Their analysis centers around the 'L-metric', which measures the degree to which pairs of genes are either coexpressed or mutually exclusive. While this metric is similar to calculating correlations in gene expressions, it has important differences (including that it can, in principle, be asymmetric; although the authors symmetrize much of their analysis). In addition to the gene-centric L-metric analysis, the authors also analyze cells in their dataset according to the cell type entropy (an information-theoretical measure of confidence in cell type assignment) and the 'exposure index' (a measure of the similarity of nearest cellular neighbors).

Using this framework, the authors focus their analysis on two major features of development. The first is the differentiation of the bipotent neuromesodermal progenitor (NMP) cells in the posterior of the gastruloid into either presomitic mesoderm (PSM) or spinal cord SC lineages. They use L-metric analysis to compare overlap in marker genes used to separate NMP, PSM, and SC fates. They highlight that L-metric analysis can recover spatial patterns of gene expression (without explicit spatial information) and discern subtle features of marker genes beyond simple binning of cell types (e.g., that Epha5 expression in anterior NMPs may predict future SC differentiation).

The second is the formation of endothelial (spatial) clusters within the gastruloid. The authors highlight two subtypes of endothelial clusters: (1) smaller clusters within the somitic anterior region, and (2) larger clusters associated with endoderm. While the authors discern some subtle differences in gene expression between these two clusters, their different spatial patterns suggest a potential physiological difference that would not be captured in traditional droplet microfluidic-based scRNAseq pipelines.

Overall, this manuscript is a sophisticated and technically sound study that will provide a valuable beachhead for future studies of developmental patterning in gastruloids and organoids.

Strengths:

The major strengths of this study are the overall technical sophistication of the data set and analysis, as well as its potential generalizability to other developmental systems (both in vitro and in vivo). The data are extensively analyzed and reasonably interpreted, and this atlas makes good use of the variability in gastruloid development to extract the statistical structure of developmental processes. The L-metric offers a parameter-free tool to analyze transcriptomic datasets that could overcome the pitfalls of other approaches.

Weaknesses:

The major limitations of this study are the depth and novelty of the developmental processes studied. The authors provide very convincing proof-of-concept that their data set can recover known features of gastruloid development, including NMP differentiation and endothelial development. However, further analysis and/or investigation would be required to discover new principles of gastruloid development and patterning.

Reviewer #3 (Public review):

This paper aims to classify, from an evolutionary perspective, the multigene family PIR found in malaria parasites infecting rodents and Old World monkeys, and to link this classification to functional diversification. The authors also hypothesize that PIR members conserved across species play important roles in parasite survival, and seek to clarify their functions.

To achieve these aims, the authors comprehensively analyze the evolution of PIR genes using genomic and transcriptomic information from many malaria parasite species. They focus on PIRC1, a member conserved across species, and attempt to clarify its function in rodent and simian malaria parasites by examining the phenotypes of parasites in which the corresponding genetic locus has been disrupted. They also attempt to determine its localization using PIRC1 tagged with an epitope sequence. However, although the locus-disrupted parasites appear to show an approximately 50% reduction in growth rate, this effect seems to be overestimated. Another weakness is that the cause of the reduced growth rate has not been clarified. The localization analysis also remains insufficiently conclusive.

Therefore, I consider that the first half of the paper, consisting of the bioinformatics analyses, achieves the objective of comprehensively summarizing PIR and may become a reference paper for discussing the evolution and function of the PIR gene family. On the other hand, regarding the function of PIRC1, no clear conclusion can be drawn from the results presented, and several additional experiments are necessary.

My major comments are as follows.

(1) The claim that the failure of eight disruption attempts indicates that pirC1 is essential is too strong.

Lines 319-321: The authors argue that a total of eight failed attempts to disrupt the pirC1 locus using two different construct designs suggest that pirC1 is essential in P. berghei. However, the failure of these attempts could also reflect technical issues with the construct design itself, such as the length of the homologous regions used for recombination, which are approximately 650 bp. Therefore, it is an overstatement to conclude that "pirC1 is essential for P. berghei blood-stage growth." Given that parasites with disruption of the corresponding locus could be obtained in both P. chabaudi and P. knowlesi, a more appropriate statement would be that "pirC1 is important for P. berghei blood-stage growth."

(2) The data on the mCherry-expressing P. berghei line shown in Supplementary Figure 11 are insufficient.

(a) Panel C: Southern blot analysis<br /> To conclusively identify the lower band in panel C as chromosome 1, additional probes specific to genes located on chromosomes 1 and 2 would be required. In addition, a parental parasite control should also be included. The Southern blot image of the parental parasite should show only a single band at the higher position, with no band at the lower position. Probes specific to chromosomes 1 and 2 would help demonstrate that the lower band corresponds to chromosome 1, rather than chromosome 2.

To this end, the authors could describe the result as follows:<br /> "In the parental parasite, only a single band corresponding to chromosome 7 was detected, indicating that the smaller chromosome was genetically modified. The size of the lower band detected with the dhfr probe was identical to that of the band detected with the control chromosome 1 probe, but distinct from that detected with the chromosome 2 probe, indicating that chromosome 1 was modified."

That said, this chromosome-level Southern blot analysis is not sufficient to demonstrate that the target PBANKA_0100500 locus was specifically modified. The authors should provide more direct evidence showing that the PBANKA_0100500 locus, rather than another genomic locus, was modified. For example, Southern blot analysis after restriction enzyme digestion would provide more definitive evidence. Diagnostic PCR may also provide more specific evidence.

(b) Panel D: Flow cytometry analysis

To allow a more accurate interpretation of the percentage of mCherry-positive cells, flow cytometry data for the parental parasite line should also be presented.

(3) There are unclear points in the PCR results shown in Supplementary Figure 12.

Supplementary Figure 12: In panel B, a PCR product should also be amplified from dPCHAS_0101200 using the P1-P3 primer pair. Why is this band absent? The authors should provide the uncropped electrophoresis image so that the larger band can be seen. In addition, if labels 1 and 2 indicate independent clones, this should be stated in the figure legend.

(4) The growth rates of P. chabaudi and P. knowlesi parasites with disruption of the PIRC1 gene locus should be quantitatively analyzed.

The growth rates of P. chabaudi and P. knowlesi are described only qualitatively, but they should be evaluated quantitatively. In Figure 4A, the parasitemia of wild-type P. chabaudi increases from approximately 6.1% on day 6 to approximately 15.6% on day 8, corresponding to a 3.8-fold increase. However, because parasite growth may already be affected by immune-mediated suppression at this stage, this value should be regarded as a minimum estimate. In contrast, the mutant increases from approximately 3.2% on day 8 to approximately 6.8% on day 10, corresponding to a 2.1-fold increase. Based on these values, the daily growth rate of the mutant appears to be reduced to at least approximately 56% of that of the wild type. Similarly, from the growth curve of P. knowlesi in Fig. 5A, the DMSO-treated group appears to increase approximately two-fold per day, whereas the rapamycin-treated group increases only approximately one-fold per day. Thus, P. knowlesi also appears to show an approximately 50% reduction in growth rate. Taken together, both P. chabaudi and P. knowlesi appear to reproducibly show an approximately 50% reduction in growth capacity. A reduction of this magnitude is difficult to describe as a "severe growth defect"; a more appropriate wording would be simply that the parasites "showed a growth defect." In addition, the terms "a severe growth defect" and "essential" appear to be overstated throughout the manuscript, and the wording should be toned down. Finally, I recommend presenting Figure 4A and Figure 5A on a logarithmic scale so that the trend in growth rates can be more intuitively appreciated from the graphs.

(5) The evidence that disruption of the PIRC1 gene locus in P. knowlesi does not affect erythrocyte invasion is weak.

The authors describe that "the developmental cycle of the parasites lacking PIRCl is slightly longer than that of parasites that produce PIRCl (line 383-384)," and appear to support this interpretation with data showing that "mutant parasites are significantly smaller than wild-type parasites (line 414)" and that "the DNA content in ML10-arrested parasites lacking PIRCl is lower than that of DMSO-treated parasites (line 417-418)" at 24 hours after invasion. However, a slightly longer developmental cycle alone does not seem sufficient to explain a 50% growth reduction.

I think the erythrocyte invasion capacity has not been quantitatively evaluated, and therefore, the evidence supporting the conclusion that the phenotype of P. knowlesi parasites with disruption of the PIRC1 gene locus is unrelated to erythrocyte invasion is weak. The authors should assess invasion efficiency using purified merozoites. For P. chabaudi, it should also be possible to apply an in vitro or in vivo erythrocyte invasion assay similar to that used for other rodent malaria parasites, and this should be evaluated as well.

(6) The authors should examine whether disruption of the PIRC1 gene locus results in a phenotype characterized by a reduced number of merozoites.

Alternatively, the reduced DNA content in ML10-arrested parasites lacking PIRC1 (lines 416-417) could suggest that the number of merozoites formed per schizont may be reduced. To clarify this point, the authors should assess whether the number of merozoites per schizont is altered in P. knowlesi (and P. chabaudi parasites lacking PIRC1).

(7) The authors propose the possibility that PIRC1 expressed in merozoites is released after invasion; however, the evidence that PIRC1 localizes to intracellular organelles is weak.

Line 333: "a peripheral pattern around the parasite" is indicative of parasite plasma membrane, PV, or PVM. ", indicative of a parasitophorous vacuole (PV) or parasitophorous vacuole membrane (PVM) location" should be amended to ", indicative of parasite plasma membrane, a parasitophorous vacuole (PV) or parasitophorous vacuole membrane (PVM) location". In the Figure S14 image, red signals are uniformly detected from the merozoites formed in the schizont stage parasite (not really microorganelle patterns), but not from the PVM surrounding the schizont, suggesting parasite plasma membrane localization, not PVM. I agree that the signal is detected from the compartments extending into the iRBC cytosol, which may be difficult to explain if it is located on the parasite plasma membrane, but how frequently were such images seen?

Figure 4D. In the images of liver-stage schizonts, AMA1 does not appear to localize to the micronemes in mature merozoites, suggesting this image is an immature schizont. Although PIRC1 appears to be expressed in liver-stage schizonts, it is difficult to clearly determine whether it localizes to intracellular organelles or to the parasite plasma membrane.

To clarify the above points, the authors should examine whether PIRC1 is detected in intracellular organelles or around the merozoites by analyzing its localization in purified merozoites.

Reviewer #3 (Public review):

Summary:

In this manuscript, Miyachi and Ichihashi investigate whether the arrangement of the genetic code affects mutational robustness. Using an in vitro minimal genetic code with vacant codons, they constructed 10 non-standard genetic codes by reassigning Ala, Ser, and Leu, generating codes with replacement costs that were generally higher than those of the standard genetic code across several amino acid property measures. They then tested how random mutations affected the activity of reporter proteins translated under these altered codes. Although error minimization theory predicts that higher-cost codes should make mutations more harmful, the authors report that protein function declined to a similar extent across all codes examined, suggesting that mutational robustness remains largely unchanged within the range of genetic code alterations tested here.

Strengths:

This is an interesting study that investigates one of the most fundamental and intriguing questions in molecular evolution: the emergence of the genetic code, which is nearly universal across nature. The in vitro approach is a powerful aspect of the work and provides an opportunity to examine this phenomenon experimentally at a depth that has previously been inaccessible.

Reviewer #3 (Public review):

Summary:

The manuscript presents an elegant and cost-effective approach for generating a tunable Bessel beam on a conventional two-photon microscope. The authors assemble a compact optical module comprising three axicons and a series of lenses that permits rapid adjustment of both lateral resolution and axial extent without modifying the focal plane. This flexibility enables the system to be readily adapted to a variety of biological preparations. As a proof of concept, the authors employ the device to record blood flow velocities in cortical microcapillaries, arterioles, and venules, thereby directly visualizing vasodilatation and vasoconstriction dynamics and permitting quantitative analysis of neurovascular coupling across cortical layers in awake mice.

The authors demonstrate that the tunability of the Bessel beam can be exploited to match the numerical aperture to the vessel type: a high NA configuration, albeit slower scan, is optimal for resolving flow in capillaries, whereas a low NA setting provides faster acquisition suitable for arterioles and venules. By implementing a one-dimensional line scan with the Bessel beam, they achieve an imaging speed that is twentyfold faster than conventional frame-by-frame scanning, which proves sufficient to capture hemodynamic transients before and after an induced ischemic stroke.

In addition to pure observation, the authors integrate a co-propagating Gaussian line to the system, allowing simultaneous imaging and photostimulation within the same focal plane. This capability addresses a common limitation of other Bessel beam implementations, in which the observation and perturbation planes often become misaligned when the Bessel beam is altered. The manuscript also emphasizes the advantage of Bessel beam excitation for calcium imaging after a perturbation, because it captures neuronal activity in planes both above and below the nominal focal plane, signals that would be missed with a standard Gaussian focus. Finally, the authors apply the technique to investigate the neuroimmune response following targeted microglial ablation; they report that adjacent microglia extend processes toward the injury site while retracting processes in the opposite direction.

Overall, the work offers a technically straightforward yet powerful extension to existing two-photon platforms, providing high-speed, volumetric imaging and stimulation capabilities that are well-suited to a broad range of neurovascular and neuroimmune studies. The experimental validation is quite thorough, and the presented data convincingly illustrates the benefits of the approach.

Strengths:

The authors present a truly clever and inexpensive optical module that can be integrated into almost any two-photon microscope, providing a tunable Bessel beam with a minimal modification of the existing system. The experimental data and accompanying quantitative analysis convincingly demonstrate that the system can reveal physiological events, such as capillary flow, calcium transients across multiple axial planes, and microglial process dynamics, that are difficult or impossible to capture with a conventional Gaussian beam. The breadth of experiments chosen for the manuscript illustrates the practical utility of the device and supports the authors' conclusions that it extends the functional repertoire of standard two-photon microscopy.

Weaknesses:

The manuscript would benefit from a more detailed contextualisation of the claimed speed advantage. Although the authors mention other techniques in the introduction, they do not provide any direct comparison with other state-of-the-art high-speed two-photon approaches such as light beads microscopy (Demas et al., Nat. Methods 2021), temporal multiplexing schemes (Weisenburger et al., Cell 2019), or random access microscopy (Villette et al., Cell 2019). A brief comparison of imaging speed, spatial resolution, and instrumental complexity would enable readers to assess the relative merits of the present method.

A second limitation that warrants discussion is the inherent trade off between volumetric coverage and image specificity. Because the Bessel beam excites fluorescence throughout an extended axial range, the detector inevitably integrates signal from a three dimensional volume into a two dimensional image. In densely labelled tissue, this can lead to significant signal crosstalk, reducing contrast and complicating quantitative interpretation. A brief analysis of how labeling density affects the fidelity of flow or calcium measurements, or suggestions for mitigating crosstalk (e.g., computational deconvolution, adaptive excitation shaping, or combinatorial sparse labeling), would broaden the applicability of the technique.

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Reviewer #3 (Public review):

Summary:

Somatic programmed DNA elimination (PDE), also known as chromatin diminution, has primarily been studied in parasitic nematodes, such as Ascaris species, in which it was discovered almost 140 years ago. Recently, PDE has also been reported in three non-parasitic nematode species. In this manuscript, Launay et al present the results of a large-scale cytological and evolutionary study of PDE across 29 free-living nematode species belonging to the Rhabditidae family, for which they established a phylogeny based on 18S and 28S ribosomal RNA sequences. By combining DNA staining and telomere DNA FISH labeling in developing embryos, they convincingly document the formation of lagging fragments and/or the loss of long germline telomeres in 17 species, during one particular division of somatic precursor cells.

Strengths:

(1) The whole study is well executed, and the results are convincing.

(2) The authors present compelling evidence that PDE is an ancestral feature of Rhabditidae nematodes.

(3) This study provides a valuable resource of lab-tractable species for future PDE studies.

Weaknesses:

(1) Some clarifications are necessary to make the figures more reader-friendly.

(2) Important references to ciliates are missing.

Reviewer #3 (Public review):

Summary:

The primary objective of this study was to establish a practical and functional framework for the propagation of stable transgenic cell lines of Blastocystis, a common animal gut microeukaryote. Although the work focused on Blastocystis ST7-B, a subtype with relatively low prevalence in humans, this choice is justified by its association with more frequent negative health effects. Beyond their relevance to the medical field, the methodological advances described here have the potential to also expand cell biology studies of this anaerobic organism, including its unusual mitochondria and redox metabolism.

Strengths:

Prior to this work, genetic tools for Blastocystis were very limited, relying on a single strong promoter-terminator combination. The authors successfully expanded the available promoter set across a range of expression strengths by testing two dozen variants in luciferase-based assays. Critically, they developed an integrated workflow from a modular transgenic construct design, to an expanded inventory of molecular components (promoters, reporters), optimized DNA delivery, stepwise antibiotic resistance-mediated clonal selection and propagation, and to reporter validation. The evaluation of several anaerobiosis-compatible labeling strategies for live (and fixed) cell optical imaging will be particularly useful, with the SNAP-tag system appearing especially promising for Blastocystis.

Weaknesses:

The presented data generally provide solid support for the conclusions that the work reached, but clarification of reasoning and several inconsistencies, as well as amendments to the visual presentation of the data, would be highly beneficial, as detailed below.

(1) Episomal persistence of the construct:<br /> The manuscript repeatedly assumes, including in its title, that constructs persist in Blastocystis in their episomal form, but no direct evidence is provided. Although this interpretation is plausible, it should be identified more clearly as provisional. Nuclear genomic integration (e.g., via NHEJ) remains a possible explanation unless supporting evidence or rationale is provided to exclude it. Testing whether the phenotype persists without drug-mediated selection in the generated transgenic cell lines would help strengthen the case for episomal maintenance.

(2) Promoters and terminators:<br /> 2.1) There is a discrepancy between the claimed number of loci (14), from which promoters used to drive luciferase expression were derived, and those detailed as having been actually generated in Table 1 (11). This inconsistency should be corrected or explained, as it creates uncertainty around the accuracy of the dataset.<br /> 2.2) Based on the presented evidence, constructs benchmarked in bioluminescence assays differed only in their promoter composition. Although terminator selection is mentioned in the Methods section, no additional details are provided; for instance, Table 1 and Figure 2 only list 23 promoters in total. Figure 2A likewise shows only promoter-dependent variation. If the terminator was held constant (LeguP1?), this should be stated explicitly. The authors may then consider revising the wording of having tested "23 promoter-terminator pairs" to better reflect that only promoters varied.<br /> 2.3) Promoter benchmarking was done with a plasmid lacking a selection marker, so it is unclear how the maintenance of the luciferase construct was ensured. Without selection, the observed reporter intensity could reflect differential or stochastic plasmid retention rather than promoter strength alone. The luminescence assay was performed 16-18 hours after transfection, but the rationale for this particular timeframe should be explained. In this context, the authors should explicitly state whether the experiments shown in Fig.2A represent biological triplicates or technical triplicates from a single transfection.

(3) Figure 2:<br /> 3.1) Several aspects of the current design may lead to ambiguity for the reader. The boxplots are colour-coded, but it is unclear whether the colours carry meaning or are purely decorative. Because the data are already spatially separated into bins, additional random colouring is redundant and may suggest distinctions that are not intended. In addition, part A of Figure 2 is split into two panels, with the scale for the left panel shown in the right panel and some of the boxplot colours falling in the range of the scale, but not in line with their counterparts in the left panel. Because the colour use is not consistent, it is difficult to tell whether the same scale should be applied to both panels or how it should be interpreted.<br /> 3.2) The left panel of part A uses a diverging blue-white-red colour scheme, which is most appropriate when the midpoint represents a meaningful central value such as zero. Because the values shown in this graph are only positive, a non-diverging 2-colour scale or a colour palette such as 'viridis' would make the plot easier to interpret.<br /> 3.3) A black background should be avoided: 'B' and 'C' labels are invisible, and it draws attention to a distracting design feature rather than the data themselves.

(4) Figure 3:<br /> 4.1) Individual snapshots should be separated more clearly, either by using a white background or by adding visible borders to make the overall composition clearer. As currently displayed, some boundaries between fluorescent channels resemble image artifacts rather than intentional panel divisions.<br /> 4.2) In parts B-D, the legend should explain more clearly what each image shows, and the figure itself would benefit from annotations. There seem to be three sub-panels in each 'condition' of part B (as well as C and D): while the middle and rightmost panel can be easily inferred to represent the fluorescent protein and bright-field image, what the leftmost panels represent is not specified. If DAPI was used to dye DNA, an explanation why mostly multiple labelled regions are visible should be provided.<br /> 4.3) Cell morphology and appearance differ markedly between UnaG/smURFP and SNAP-tag images, which should be explained. A microscope issue is mentioned in the main text, but if that was the cause, the authors should consider replacing the images, as the current distortions complicate interpretation.

Reviewer #3 (Public review):

Summary:

Chow-Wing-Bom et al. introduce an innovative wide-field visual stimulation setup for 3T experiments that enables stimulation up to a diameter of 40{degree sign} visual angle while allowing continuous gaze tracking. Using this setup, the authors systematically investigate contrast sensitivity across the visual field by presenting subjects with sinusoidal gratings varying in contrast and spatial frequency. Their findings confirm the expected organization of contrast sensitivity, demonstrating a preference for high spatial frequencies in the central field and lower frequencies in the periphery. They also extend these measurements to eccentricities up to 20{degree sign}, which exceeds previous fMRI-based reports. Moreover, the study explores the potential of using contrast sensitivity calculations as a method for detecting visual field defects, demonstrated in a healthy subject with simulated ring-shaped and upper-right-quadrant scotomas, and in a patient with LHON. The revised version additionally characterises the robustness of the approach to varying degrees of fixation instability.

Strengths:

- The manuscript is well written and provides comprehensive methodological details, ensuring high transparency and reproducibility.

- The visual stimulation setup represents a significant technical advance by enabling wide-field stimulation with continuous eye tracking, which is crucial for both research and potential clinical applications.

- The study confirms established findings regarding the organization of contrast sensitivity while extending them to a larger eccentricity range.

- The efforts to establish a measure for visual field losses aligns with current efforts to develop objective alternatives to conventional perimetry.

- The revised manuscript includes an empirical assessment of how varying levels of eye movement affect cortical contrast sensitivity estimates, providing useful guidance on the tolerance of the approach to fixation instability.

Weaknesses:

- The original version left certain methodological aspects unclear, particularly the correction of eccentricity values from the Benson atlas and the V1 masks used in each analysis branch. The authors have added a dedicated figure illustrating the eccentricity correction procedure and now explicitly state that a manually delineated V1 mask was used for the pRF-based analyses while the Benson V1 label was used for the atlas-based analyses, together with a discussion of how this difference may influence the comparison.

- Minor inconsistencies in reporting, such as the introduction of a second session in the Results section, have been corrected.

The conclusion that high-contrast patterns as in pRF mapping are not optimal to test for subtle but potentially clinically relevant changes in the visual field coverage are very valid. The suggested use of contrast sensitivity can therefore be a potentially well-suited parameter for estimating visual field losses. The presented work is an interesting starting point, and the proposed method of using contrast sensitivity as measure for partial vision loss should be further explored.

Comments on revisions:

The authors have thoroughly addressed all points raised in my original review, and I have no further concerns.

Reviewer #3 (Public review):

Summary:

The paper investigates neural fluctuations underlying arousal using a combination of resting state/naturalistic movie watching fMRI and eye tracking data. The authors have used several data driven approaches, including time varying sliding window analyses and clustering methods, to characterize large scale brain organization and hemispheric asymmetries associated with arousal fluctuations. This is an interesting study framing arousal as a dynamic, continuously varying process rather than a discrete state. Overall, the manuscript is well written and the authors have provided sufficient details about the methodological choices, their impact on the results, along with the limitations of the study.

Strengths:

This is an interesting study framing arousal as a dynamic, continuously varying process rather than a discrete state. Overall, the manuscript is well written and provides sufficient methodological and analytical details to evaluate the results.

Weakness:

While the study provides new insights regarding neural processes underlying arousal, future studies may be needed to further examine the implications of identified cluster and patterns.

Reviewer #3 (Public review):

Summary:

This manuscript characterized the splicing regulation of two long non-coding RNAs relevant to cancer, starting with a focus on PURPL and ending with insights into MALAT1. A CRISPR screen for the regulators of PURPL intron retention revealed a role for the U2AF heterodimer in inducing this retention, with U2AF2 as the actual hit. This is surprising, because the canonical function of U2AF is to recognize the polypyrimidine tract (PPT) and 3' splice site junction to induce splicing at the site. The brief mechanistic characterization of this phenomenon showed that this intron retention accounts for the nuclear localization and instability of the PURPL transcript, and seems to confer the enhanced cell proliferation feature. U2AF2 also induces retention of two introns in MALAT1, and one of them is essential for its nuclear speckle localization and enhanced cell migration.

Strengths:

These findings about PURPL and MALAT1 are clear and interesting.

Weaknesses:

The results are not sufficiently connected to each other, because one regulation is nuclear-speckle dependent but not the other.

Here are my specific comments:

Major comments:

The main issue is the lack of focus because of the distinct and incomplete analysis pertaining to the two long noncoding RNAs, PURPL and MALAT1. The paper starts with a very good genetic screen on the former, and immunofluorescence and functional analysis on the latter, with U2AF2 as the main link to induce intron retention. The first one does not show clear localization while the second docks to nuclear speckles, apparently because of the retained intron. Hence the two mechanisms are related yet distinct. Here are some suggestions to enhance the characterization and connection between the two cases:

(1) As the MALAT1 intron 2 retention contributes to its speckle localization but not the retained PURPL intron, the retained introns or their 3' splice site sequences should be swapped to see if they determine the localization.

(2) Figure 3, the rescue of the PURPL knockout by the intron-retained RNA to induce proliferation is a powerful experiment, that is lacking the rescue with the RNA without the intron as a control. This must be done and shown.

(3) The weakness of the PPT of PURPL intron 2 appears as a clear feature of its retention dependent on U2AF2, which appears direct, as backed by CLIP data. It would be good to show direct binding by EMSA or equivalent techniques. Furthermore, the data is also consistent with other determinants. The exon and upstream intronic sequences, including the branch point, could also be involved, so mutations in these are also required.

(4) In brief, what are the commonalities and differences between PURPL and MALAT1 with regard to their U2AF2-dependent intron retention?

Reviewer #3 (Public review):

Summary:

The authors aim to characterize the molecular interaction network inside phase-separated condensates formed by the MUT-16 foci-forming region (FFR), using atomistic simulations combined with residue-resolved analyses of contact frequencies, contact lifetimes, specific non-covalent interactions, ions, and water.

Strengths:

The work addresses an interesting and biologically relevant system, and the combination of large-scale atomistic simulations with an extensive contact analysis has clear potential value for the broader condensate field.

Weaknesses:

In its current form, several technical issues need to be addressed before the main conclusions can be considered robust. Most importantly, the simulated sequence is 172 residues long, while the atomistic slab has box dimensions of only 12 nm in two directions. This length scale is comparable to the expected end-to-end distances of a disordered 172-residue chain. It is therefore not clear whether individual protein chains interact with their own periodic images, which could substantially affect overall chain dynamics and subsequently bias contact lifetimes, residue-residue interaction statistics, and the inferred condensate dynamics. The authors should check, for each chain, histograms of end-to-end distances. For chains for which more than ~2-3% of the end-to-end distances exceed ~11 nm, the authors should explicitly check for self-image interactions (for example, using "gmx mindist -pi") and report whether such interactions occur and for what fraction of the trajectory. Without this control, at least in the Supporting Information, I do not think the simulation-derived contact dynamics are sufficiently trustworthy.

A second major concern is the treatment of ions. The manuscript makes important conclusions about Na⁺ association and Na⁺-mediated bridging, but the atomistic ion model is not explicitly stated. This is a reproducibility problem and also affects interpretation - for example, standard Amber ions are known to bind too strongly to the oppositely charged residues. In their results, one acidic residue appears to interact on average with roughly two Na⁺ ions, which is not obviously expected from charge balance alone. The authors should state the exact Na⁺/Cl⁻ parameters used, justify their compatibility with TIP4P-D and the protein force field, and explicitly interpret why such a strong Na⁺ association with acidic residues is observed.

More generally, because the manuscript is centered on contact lifetimes, the choice of the atomistic force field needs stronger justification. Salt bridges, cation-pi contacts, pi-pi stacking, ion coordination, and water-mediated interactions are all force-field-sensitive. Since there is no direct experimental observable used here to validate the simulations, the authors should discuss the expected limitations of the chosen force field (while I do acknowledge that testing different force fields would be computationally too demanding).

I also find the sequence-comparison section somewhat confusing. The authors compare one specific IDR, MUT-16 FFR, with the average properties of human IDRs and then frame it as more representative than FUS LCD. It is not clear how informative this is because IDR behavior depends strongly on sequence-specific patterning, molecular connectivity, and the particular interaction network of each protein. Averages over human IDRs may provide a broad context, but they do not necessarily define what is physically or biologically representative for phase separation. In addition, FUS LCD is not intended to be a representative human IDR; it is an unusually low-complexity, phase-separating domain. Therefore, the "more representative than FUS" framing should be toned down. At most, this analysis shows that MUT-16 FFR is compositionally less extreme than FUS LCD.

The ion- and water-bridging analyses are also potentially overinterpreted. A distance-based simultaneous contact with two residues does not by itself establish functional mediation or regulation of condensate dynamics. The authors should either add appropriate controls, such as local-density-normalized baselines or randomized-contact expectations, or soften the language to describe these as geometrically defined co-contact events rather than mechanistic bridging interactions.

Finally, the independence of the atomistic replicas is unclear. The manuscript should state whether all ten all-atom simulations were initiated from the same coarse-grained condensate configuration or from distinct CG frames. If the starting structures came from one CG trajectory, the authors should report how far apart those frames were in simulation time and provide evidence that the initial atomistic configurations are structurally independent. If only velocities differ, the simulations should not be described as fully independent structural replicas.

Reviewer #3 (Public review):

This important study investigates the impact of nutrient stress in the tumor microenvironment (TME), focusing on lipid metabolism in pancreatic ductal adenocarcinoma (PDAC). Understanding TME composition is crucial, as it highlights cancer vulnerabilities independent of intracellular mutations, particularly because PDAC tumors are often exposed to limited nutrient availability due to reduced perfusion.<br /> By utilizing a medium that mimics the nutrient conditions of PDAC tumors, the authors convincingly show that TME nutrient stress suppresses SREBP1, leading to reduced lipid synthesis, with low arginine levels identified as a key driver of this suppression. Importantly, mice with arginine-starved pancreatic tumors respond to polyunsaturated fatty acid-rich diet. This discovery uncovers a synthetic lethal interaction in the tumor microenvironment that could be leveraged through dietary interventions.

Comments on revised version:

The authors have satisfactorily resolved all previously raised concerns through the inclusion of additional data and clarifications in the discussion.

Reviewer #3 (Public review):

Summary

This paper analyzes human single-neuron activity recorded with Behnke-Fried electrodes during naturalistic listening and reading. The authors demonstrate a double dissociation between superior temporal gyrus neurons (responsive during listening but not reading) and fusiform gyrus neurons (responsive during reading but not listening), and report that these two classes of neurons show selectivity to specific phonological and orthographic features of the stimulus, respectively. Across the language network, the authors also report neurons whose responses are amodal (active during both listening and reading), which they organize into a modal-to-amodal processing hierarchy. A separate thread of analyses tracks the relationship between single-neuron spiking, micro-wire, and macro-wire signals across these regions. The authors interpret their findings as evidence for hierarchical processing across the language network and for a "compositional code" for orthography in reading.

Strengths

The dataset is rare and valuable. Simultaneous single-neuron, micro-wire, and macro-wire recordings during naturalistic reading and listening in the same patients are difficult to obtain, and the experimental design reflects substantial care. The cross-modality comparison at single-neuron resolution is a novel measurement, and the paper presents these results while also situating them against prior neuroimaging and intracranial work. The simultaneous availability of signals at three spatial scales within the human language network is an unusual and potentially important resource for the field.

Weaknesses

(1) Framing and novelty

The paper appropriately situates its modality-selectivity findings against prior neuroimaging and intracranial work (citing Buchweitz et al. 2009 among others) and frames its novel contribution as bringing single-neuron resolution to a question that has previously been examined at population scales. This framing is fair as far as it goes. However, two issues remain. First, the paper does not engage with neuroimaging evidence that complicates its clean modality-selectivity story - most notably Wilson, Bautista, & McCarron (2018), who found that the dorsal superior temporal sulcus is activated by both intelligible and unintelligible inputs in both modalities. Several reconciliations of single-neuron modality selectivity with population-level cross-modal activation are possible (sparse coding, BOLD-vs-spiking dissociations, etc.), and the paper should engage with these possibilities. Second, the paper's discussion extends well beyond the modality-selectivity result that is its headline contribution, into broader claims about a "compositional code" for orthography and "hierarchical processing" across the language network. These broader claims are not supported by the analyses presented (see Weakness 3), and their inclusion distracts from and weakens the core finding rather than building on it. The paper would be stronger if these claims were either subjected to the population-level analyses they require or scaled back to exploratory observations.

These framing issues are compounded by writing problems that obscure what the paper is claiming. Some passages, such as the assertion that the dataset "suggests an unprecedented examination of linguistic features across various brain regions at various resolutions," are not interpretable as written and should be rewritten.

(2) Methodological concerns about the TRF analyses

The selectivity findings in Figures 3 and 5 rest on temporal response function / temporal receptive field (TRF) analyses with several core issues.

2.1) First, the construction of the TRF feature stream for the reading condition is not specified in the methods. Reading stimuli are presented in RSVP, with all letters of a word appearing simultaneously. How letter or letter-position features are mapped to a time-varying regressor reflects a substantive hypothesis about the psychological mechanisms of reading, with statistical consequences for what the TRF can recover and how reading and listening analyses can be compared.

2.2) Second, the stimulus distribution limits which effects can be reliably estimated. While the design appears balanced for some features (e.g., subject gender and number), the features that drive the TRF analyses - particularly letter identity and position in the orthographic TRF - are unlikely to be well covered in a small stimulus set. This raises a concern about high-variance feature importance estimates.

2.3) Third, the TRF feature set includes syntactic, semantic, and discourse predictors alongside phonological and orthographic features. The paper does not justify this choice in fitting single-neuron responses in STG and FSG, and the consequences for the unique-variance analyses are not discussed. Because syntactic features are correlated with phonological and orthographic features in natural stimuli (function words are short, have characteristic phoneme distributions, and so on), the unique variance attributed to each feature set depends on what is being controlled for. Including syntactic predictors when fitting STG or FSG neurons also risks inflating overall TRF fit by chance, particularly in the absence of cross-neuron correction.

2.4) Fourth, there seems to be no correction for multiple comparisons across the neuron × feature grid. The within-neuron feature-importance procedure briefly described in the Figure 3 caption may help combat overestimates of feature importance within a single fit, but does not address the question of how many of the "selective" neurons reported across the paper would survive correction at the population level. With many neurons, many features, and a limited stimulus set, some neurons will appear selective to some features by chance alone, and these are likely to be the ones that appear as example panels in figures.

Together, these issues mean the per-feature selectivity results cannot be interpreted as the paper currently interprets them. This is consequential because the per-feature selectivity findings underpin the paper's broader claims about a compositional code for orthography and about hierarchical processing across feature levels.

(3) Claims that outrun the evidence

Several of the paper's broader claims are not supported by the analyses presented.

3.1) The authors claim a "compositional code" for orthography, in which single neurons code for the combination of letter identity and position. This claim is illustrated with two example neurons. A claim about a coding scheme is a population-level claim and requires a population-level analysis. A natural test would be a per-neuron model comparison between a TRF with letter identity alone and a TRF including letter identity × position interactions, controlled for model complexity, asking how many neurons show improved prediction with the interaction features. As noted above in {section sign}2.2, this analysis would also need to grapple with which letters and positions the data can support estimating. There is a potential connection to the data sparsity worries here: the n=2 example neurons may have the only selectivity profiles for which the relevant interactions could be estimated at all.

3.2) The "hierarchical processing" claim is motivated by neurons selective to features at multiple levels - graphemes and sub-graphemes in reading, single phonemes and diphthongs in listening. This claim is not specified mechanistically. The paper does not state what kind of structural linguistic hierarchy is intended (segmental phonology to syllabic structure?), what kind of hierarchical neurocomputational mechanism is being proposed, or why selectivity at multiple levels of a feature hierarchy is evidence for that mechanism rather than for any other mechanism (e.g., parallel feature detectors). As written, the claim is too underspecified to evaluate.

3.3) The "forked letters" finding (selectivity to k, v, w, y, z) is potentially confounded with letter frequency and co-occurrence structure. These letters are low-frequency, with some exhibiting strong positional asymmetries, and they infrequently co-occur with other letters. Under the unique-variance analysis, decorrelation from other features inflates apparent unique variance even in the absence of genuine selectivity.

3.4) The word-length effect in Figure 4 is established by PCA on the top five fusiform neurons, with no analysis showing the effect is qualitatively similar across a broader selection. Beyond establishing that something varies with word length, the paper makes no substantive claim about what the neural code represents - for instance, whether it reflects letter- or word-specific processing or a more general visual response to stimulus extent. Prior intracranial work has reported word-length effects in regions posterior to the VWFA but not within it (Thesen et al. 2012), raising the question of whether the effect reported here reflects letter-specific processing or a more general visual response that happens to correlate with stimulus extent.

(4) Missed opportunities

Several aspects of the paper are not so much wrong as underdeveloped, in ways that the authors are well-positioned to address.

4.1) The cross-scale comparison between single-neuron, micro-wire, and macro-wire signals is presented descriptively, without articulating what conclusion these analyses support about the relationship between scales of measurement. Given the rarity of simultaneous recordings at these scales, this is a substantial missed opportunity. The rasters in Figure 2 visually suggest a tight relationship between spiking and micro-population activity that is not evident in the summary in Figure 2g. This discrepancy is not explained. Characterizing the functional and temporal relationship linking spike rates to micro- and macro-HGA is a substantive scientific question, and the paper is well-positioned to address it.

4.2) The stimuli include controlled grammatical manipulations, but these manipulations are used as nuisance regressors in the TRF analyses rather than as the object of structured analysis. A design with controlled comparisons is being treated as if it were unconstrained naturalistic stimulation, which underuses the experimental structure the authors built.

4.3) Finally, the paper foregrounds the dataset as a contribution but does not describe data sharing plans. Given that several of this review's recommendations call for analyses the authors have not yet done, the long-term value of the dataset to the community will depend substantially on what is shared and how.

​​Buchweitz, A., Mason, R. A., Tomitch, L. M., & Just, M. A. (2009). Brain activation for reading and listening comprehension: An fMRI study of modality effects and individual differences in language comprehension. Psychology & neuroscience, 2(2), 111-123.

Jobard, G., Vigneau, M., Mazoyer, B., & Tzourio-Mazoyer, N. (2007). Impact of modality and linguistic complexity during reading and listening tasks. Neuroimage, 34(2), 784-800.<br /> Thesen, T., McDonald, C. R., Carlson, C., Doyle, W., Cash, S., Sherfey, J., Felsovalyi, O., Girard, H., Barr, W., Devinsky, O., Kuzniecky, R., & Halgren, E. (2012). Sequential then interactive processing of letters and words in the left fusiform gyrus. Nature communications, 3, 1284.

Wilson, S. M., Bautista, A., & McCarron, A. (2018). Convergence of spoken and written language processing in the superior temporal sulcus. Neuroimage, 171, 62-74.

Reviewer #3 (Public review):

Summary:

Histone variant H2A.Z is evolutionarily conserved among various species. The selective incorporation and removal of histone variants on the genome play crucial roles in regulating nuclear events, including transcription. Shih et al. aimed to address antagonistic mechanisms between histone variant H2A.Z deposition and DNA methylation. To this end, the authors reconstituted H2A.Z nucleosomes in vitro using methylated or unmethylated human satellite II DNA sequence and examined how DNA methylation affects H2A.Z nucleosome structure and dynamics. The cryo-EM analysis revealed that DNA methylation induces a more open conformation in H2A.Z nucleosomes. Consistent with this, their biochemical assays showed that DNA methylation subtly increases restriction enzyme accessibility in H2A.Z nucleosomes compared with canonical H2A nucleosomes. The authors identified genome-wide profiles of H2A.Z and DNA methylation using genomic assays and found their unique distribution between Xenopus sperm pronuclei and fibroblast cells. Using Xenopus egg extract systems, the authors showed SRCAP complex, the chromatin remodelers for H2A.Z deposition, preferentially bind to unmethylated DNA to deposit H2A.Z.

Strengths:

The experiments are rigorously performed, and interpretations are clear. The study presents a high-resolution cryo-EM structure of human H2A.Z nucleosome with methylated DNA. Although the effect of DNA methylation on the physical stability of the H2A.Z nucleosome is subtle, this would be important finding that warrants further functional investigation. The discovery that the SRCAP complex senses DNA methylation is novel and provides important mechanistic insight into the antagonism between H2A.Z and DNA methylation.

Weaknesses:

The authors have satisfactorily addressed my concerns.

Reviewer #3 (Public review):

Summary:

ARHGEF6 is a RAC1/CDC42 guanine nucleotide exchange factor that has been proposed to be associated with X-linked intellectual disability, but its relevance to the pathology is not well established. ARHGEF6 has been assigned a role in spine density and plasticity of hippocampal pyramidal neurons, but nothing is known about its role in interneuron development. Here, the authors show that ARHGEF6 is expressed early in development in the inhibitory lineage during the peak of interneuron generation and migration. The aim of the study is therefore to investigate whether, in addition to its role in pyramidal neurons, ARHGEF6 could play a role in inhibitory neuron development. Using both ARHGEF6-KO mice and organoids from ARHGEF6-KO hiPSCs, the authors show that ARHGEF6 plays a critical role in interneuron development and function

Strengths:

The major strength of the paper is the very detailed analysis of the role of ARHGEF6 using two different systems: ARHGEF6-KO mice and deletion of ARHGEF6 in human iPSC-derived organoids. Strikingly, deletion of ARHGEF6 in both systems induces similar defects such as an increase in apoptosis, reduced neuronal output, impaired neuronal morphology, and disrupted migratory dynamics. This compelling evidence demonstrates that ARHGEF6, in addition to its already well-described role in spine formation and plasticity, is playing a crucial role during embryonic development through its function in interneurons.

Weaknesses:

(1) In Figure 1, the authors show that ARHGEF6 is expressed in different regions of the brain, including the interneuron lineage, and that depletion of ARHGEF6 reduces the number of GABAergic neurons in the adult cortex and hippocampus. To try to better characterize this defect, the authors in Figure 2 investigate whether deletion of ARHGEF6 affects interneuron migration and survival during embryonic development. To do so, ARHGEF6 ko mice were crossed with the GAD67-eGFP reporter line to follow the inhibitory lineage. The authors analyse apoptosis using TUNEL staining, and show that it is significantly increased in the ganglion eminence of ARHGEF6-KO E14.5 embryos. The authors claim that this is not the case in the cortex. However, the image shown in Figure 2A really suggests that staining is increased. Which part of the neocortex is analysed for quantification? This should be clarified.

(2) In Figure 2F-J, the authors investigate the migration of interneurons by analysing the GAD67-eGFP staining, and clearly show that the migratory abilities of the depleted neurons are reduced. However, the authors do not discuss the fact that, because depletion of ARHGEF6 increases apoptosis, there are fewer neurons available for migration. This is important for the interpretation of the data. This point should be clarified.

(3) In Supplementary Figure S2, the authors describe the establishment of the ARHGEF6-KO human iPSC line and test the ability of these cells to undergo correct development, especially for the generation of neural progenitor cells. I was wondering why the authors do not present the data of both control and ARHGEF6-KO cells.

(4) At the molecular level, how ARHGEF6 depletion could affect neuronal survival is missing. In addition, as ARHGEF6 is a GEF for RAC1 and Cdc42 amongst other GEFs, I would have expected that the authors test how RAC1 activity (and Cdc42) is affected in ARHGEF6-depleted brains and in ARHGEF6-KO organoids. The measure of phalloidin staining and the anisotropy index are not really meaningful.

(5) The authors show that ARHGEF6-KO forebrain organoids were markedly smaller compared to their isogenic controls, and their study suggests that ARHGEF6 expression impacts progenitor maintenance and neurogenesis. Despite representing only a minority of the total neuronal population, I was wondering whether ARHGEF6-KO mice present brain morphology defects such as microcephaly.

Reviewer #3 (Public review):

Summary:

The authors sought to determine the individual and combined effects of exercise and low-fat diet consumption on regional brain volume and cognitive function in triple-transgenic Alzheimer's disease mice and wild-type controls.

Strengths:

(1) A strength of this study is its longitudinal design, which captures regional changes in brain volume across the interventions tested.

(2) Its comprehensive design includes 10 groups and is well-powered to isolate genotype-, sex-, diet- and exercise-related effects (and interactions).

(3) The analyses of volumetric and voxel-based measures are comprehensive.

Weaknesses:

(1) Use of automated tracking for NOR data reduces confidence in the behavioural data.

(2) No measures of Ab or tau pathology appear to be performed.

(3) Mice from the critical 'combined' intervention groups are not included in the PLS regression model that integrates behavioural and brain data.

(4) Analyses of behavioural data include a large number of variables without adequate justification.

Reviewer #3 (Public review):

Summary:

This manuscript describes the engineering, production and validation of an MR1 variant with enhanced suitability for screening of ligands and biophysical and structural analysis. The authors utilize a previous advance from their laboratory on a classical MHC (HLA-A2) whereby the alpha 3 and b2m domains are replaced by a helical stabilizing domain.

Strengths:

This variant has a smaller molecular weight than the native MR1, can be produced easily through refolding and is thus much more suitable for NMR analysis. The authors provide data demonstrating that many of the parameters typically evaluated in protein biochemistry/biophysics are similar to reported values between this engineered variant and the wild-type protein. Overall, this is a significant advance to the MR1 field and more broadly to MR1 relevance in immunology and cancer biology, as this will accelerate high-throughput screening and discovery of disease-relevant ligands for MR1, which have been overshadowed by the misguided fixation on 5-OP-RU.

Weaknesses:

Minor concerns about the lack of comparison with the native MR1 extracellular domain construct in the validation of this engineered construct.

Reviewer #3 (Public review):

Summary:

Over the past 3 or 4 decades, our understanding of the molecular mechanism underlying the circadian clock has increased substantially. This is in large part due to successful forward and reverse genetics approaches applied to a broad range of genetic model systems, notably Drosophila, Neurospora, mouse, Arabidopsis and cyanobacteria. Although the clock components in these species are diverse, the basic operating principles are highly conserved, allowing us to build a general view of clock mechanisms. Looking forward, there are still many unanswered questions regarding how clocks are organized at the systems level and, in turn, how they are coupled to key aspects of physiology. Each model species has its own set of advantages and disadvantages for tackling particular questions. As this timely review aims to illustrate, the zebrafish has become a particularly valuable model for exploring circadian clock biology. This is in part due to its technical advantages, accessibility of early developmental stages and its directly light-entrainable peripheral clocks. This provides unparalleled opportunities for studying the circadian clock hierarchy and its links with physiology.

Strengths:

This review does a good job of integrating the many lines of circadian clock research where the zebrafish has been used as a model and provides an overview of many future challenges it is well-suited to tackle.

Weaknesses:

There are citation errors, as well as inaccurate and misleading statements that must be remedied in a revised version.

Reviewer #3 (Public review):

Summary:

The most important weakness is that the authors have avoided the direct structural comparison of experimentally determined x-ray structures of AAC and CysZ. Instead, the comparisons are made through predicted membrane topologies and predicted structural models of protein homologs, which give rise to misleading results. Direct comparison of the X-ray structures of the ADP/ATP carrier and CysZ clearly shows that these proteins have very different folds. Therefore, flaws in the methods produce results that lead to the wrong conclusions, and the authors have not achieved their aims.

Weaknesses:

(1) Figure 2. There is something very strange about how the tree is drawn, given that S. cerevisiae AAC1, AAC2 and AAC3 share about 76-83% sequence identity but appear to be very diversified in the tree. The phylogenetic trees are only based on the sequences of three species. The authors should explain in much more detail how they made the phylogenetic trees to support their statement that all mitochondrial carriers have come from an ancient AAC.

(2) There are at least three and seven X-ray structures of CysZ (with about 43% sequence identity to the E. coli homolog) and AAC, respectively, deposited in the Protein Data Bank. Therefore, there is no need for the approach using predicted structures as described in the manuscript. It is clear from direct comparison of the CysZ and AAC structures that they have very different folds, i.e. lengths of the transmembrane helices, their orientation and packing. CysZ has been suggested to form dimers or trimers of dimers (eLife 2018;7:e27829), with each protomer formed by two long transmembrane helices and four short helices that do not cross the membrane totally. Thus, CysZ has a different membrane topology and oligomeric state than AAC (monomer with six transmembrane helices). CysZ is therefore rightfully classified in a separate 3D domain fold from mitochondrial carriers in various protein family and domain databases.

(3) In the 3D structures of CysZ, the conserved QYXDYPXDNHK motif is involved in a network of hydrogen bonds and salt bridges thought to hold the helical bundle together (eLife 2018;7:e27829). This motif is similar to PX[DE]XX[KR], a part of the signature motif, typical of mitochondrial carriers, which is repeated three times in the sequences and forms a three-fold pseudo-symmetrical salt bridge network of the so-called matrix gate that opens and closes during the transport cycle. Therefore, although this single motif in CysZ is similar to those of mitochondrial carriers, it is not found in a similar structural context to those in AAC structures.

(4) It appears odd that the sulfate transporter CysZ should be more similar to nucleotide-transporting AAC than any of the other mitochondrial carriers, of which some transport sulfate.

(5) The alphafold model of YihY is not very similar to either the crystal structures of CysZ or AAC.

(6) The authors are relying too much on the TM-score results. The values of 0.5-0.6 between AAC and CysZ or YihY probably reflect that they contain six main helices. However, as noted in point 2, they have very different folds.

Reviewer #3 (Public review):

Summary:

This study uses high-resolution videography and a custom computer-vision pipeline to dissect the motor control of cephalopod chromatophores in Euprymna berryi and Sepia officinalis. By quantifying anisotropic chromatophore deformations and applying dimensionality reduction methods, the authors infer that individual chromatophores can be a part of multiple motor units. Clustering analyses reveal putative motor units that often span multiple chromatophores, with diverse and overlapping geometries. Chromatophore expansion dynamics are faster and more stereotyped than relaxation, consistent with active neural contraction followed by passive recoil. Together, the results show that chromatophores function not as uniform pixels but as fractionated, coordinately controlled elements that enable flexible pattern generation

Strengths:

The authors present compelling, direct evidence that a). chromatophore deformations are anisotropic, and indirect evidence that b). individual chromatophores can be split across multiple putative motor units. This evidence is provided through data collected over large spatial scales, but also at a sub-chromatophore resolution. This combination of scale and resolution is not possible using traditional neuroanatomical and physiological approaches alone.

The authors also develop a new non-invasive, image analysis approach to extract information about chromatophore deformation across large spatial scales on the organism's body. In principle this approach is applicable across species and may allow for further comparative characterization of chromatophore motor control. It is therefore a promising new tool and useful resource for the community.

Weaknesses:

An important weakness of the work is that the methods the authors develop can only be applied during resting, spontaneous 'flickering' activity of chromatophores to yield interpretable results at the motor unit level. This is because common presynaptic input would confound the identification of individual motor units. Thus, there remains a large difficulty in linking insights about single motor unit organization to the circuit and behavioral levels.

Another weakness of this paper is the rather limited electrophysiological validation of the computational findings. The authors present only one electrophysiology experiment in E. berryi, the species that they used only for 'methodological development' and not for detailed characterization. A complementary electrophysiological experiment in S. officinalis, or some visualization of neuron morphology confirming that motor neurons do indeed project to multiple chromatophores would strengthen the generalizability of their computational analysis. This would be particularly pertinent to validate the author's claim that some motor units contain chromatophores that are quite distant from one another on the animal.

Overall, the authors' technical contributions and method development are an important advance. This work serves as an excellent proof of concept that their method can extract useful information about chromatophore motor control. Further validation of their method is needed to fully trust the fine-scale conclusions drawn about the distribution and composition of multi-innervated chromatophores. Furthermore, the authors raise many interesting ideas about developmental constraints on circuit wiring and potential adaptive significance of multi-innervated chromatophores for certain features of camouflage patterning. Their method may be able to help resolve some of these questions in the future if it is refined and applied across developmental stages, regions on the animal, and across species

Comments on revisions:

Thank you for clarifying my major point of confusion regarding how one might connect these results to behaviorally relevant camouflage. I now have a better understanding of the author's rationale in studying resting activity of motor units and believe that the clarifications added to the manuscript will help other readers who encounter similar confusion.

Reviewer #3 (Public review):

Summary:

These findings suggest that PGPD-SAK1 yeast show a subpopulation with lowered TOM70-GFP expression in high bud scar staining aged cells. Deletion of CAT2 or MLS1 reduces this effect. A PGPD-SAK1 acc1S1157A double mutant (called "A2A" here) shows an even larger effect of lowered tom70 expression in high bud scar staining aged cells. Utilization of various additional mutants involved in acetyl-CoA transport, carnitine shuttle, respiration, etc., leads the authors to conclude that these shifts in TOM70-GFP in aged cells are linked to the AMPK-fatty acid metabolic regulatory system.

Strengths:

These extensive and clearly described experiments reveal interesting changes in TOM70-GFP intensity in subsets of aged yeast in several mutants eventually identified as linked to the AMPK-fatty acid metabolic regulatory system.

Weaknesses:

(1) 3 biological replicates for mRNASeq is low.

(2) While "Traditional conceptions of ageing implicate a progressive accumulation of damage leading to systemic degradation in performance until death, with evolutionary pressures acting to maximise early life fitness and fecundity at the expense of ageing health." is tangential perhaps to the data and conclusions of the study, both claims of this sentence are at best controversial, and the manuscript is no weaker for their omission.

(3) The statement that "Here, we determine the basis of senescence and fitness loss in replicatively ageing yeast" is a bit strong as a summary of the present careful work presented here. If the authors had created yeast mutants that retained fitness indefinitely, this would be a more appropriate strength of claim to summarize the work.

Reviewer #3 (Public review):

Summary:

Metabolons are multisubunit complexes that promote the physical association of sequential enzymes within a metabolic pathway. Such complexes are proposed to increase metabolic flux and efficiency by channeling reaction intermediates between enzymes. The TCA cycle enzymes malate dehydrogenase (MDH1) and citrate synthase (CIT1) have been linked to metabolon formation, yet the conditions under which these enzymes interact, and whether such interactions are dynamic in response to metabolic cues, remains unclear, particularly in the native cellular context. This study uses a nanoBIT protein-protein interaction assay to map the dynamic behavior of the MDH1-CIT1 interaction in response to multiple metabolic stimuli and challenges in yeast. Beyond mapping these interactions in real time, the authors also performed GC-MS metabolomics to map whole cell metabolite alterations across experimental conditions. Finally, the authors use microscale thermophoresis to determine components that alter the MDH1-CIT1 interaction in vitro. Collectively, the authors synthesize their collected data into a model in which the MDH1-CIT1 metabolon dissociates in conditions of low respiratory flux, and is stimulated during conditions of high respiratory flux. While their data largely support these models, some key exceptions are found that suggest this model is likely oversimplified and will require further work to understand the complexities associated with MDH1-CIT1 interaction dynamics. Nonetheless, the authors put forth an interesting and timely toolkit to begin to understand the interaction kinetics and dynamics of key metabolic enzymes that should serve as a platform to begin disentangling these important yet understudied aspects of metabolic regulation.

Strengths:

- The authors address an important question: how do metabolon-associated protein protein interactions change across altered metabolic conditions?

- The development and validation of the MDH1-CIT1 nanoBIT assay provides an important tool to allow the quantification of this protein-protein interaction in vivo. Importantly, the authors demonstrate that the assay allows kinetic and real time assessment of these protein interactions, which reveal interesting and dynamic behavior across conditions.

- The use of classic biochemical techniques to confirm that pH and various metabolites can alter the MDH1-CIT1 interaction in vitro is rigorous and supports the model put forth by the authors.

Weaknesses:

The authors have addressed identified weaknesses within the revision of their manuscript.

Reviewer #3 (Public review):

Summary:

The authors build on a recent computational model of planning, the "value-guided construal" framework by Ho et al. (2022), which proposes that people plan by constructing simple models of a task, such as by attending to a subset of obstacles in a maze. They analyze both published experimental data and new experimental data from a task in which participants report attention to objects in mazes. The authors find that attention to objects is affected by spatial proximity to other objects (i.e., attentional overspill) as well as whether relevant objects are lateralized to the same hemifield. To account for these results, the authors propose a "spotlight-VGC" model, in which, after calculating attention scores based on the original VGC model, attention to objects is enhanced based on distance. They find that this model better explains participant responses when objects are lateralized to different hemifields. These results demonstrate complex interactions between filtering of task-relevant information and more classical signatures of attentional selection.

Strengths:

(1) The paper builds on existing modeling work in a novel manner and integrates classic results on attention into the computational framework.

(2) The authors report new and extensive analyses of existing data that shed light on additional sources of systematic variability in responses related to attentional spillover effects

(3) They collect new data using new stimuli in the original paradigm that directly test predictions related to the lateralization of task-relevant information, including eye tracking data that allows them to control for possible confounds.

(4) The extended model (spotlight-VGC) provides a formal account of these new results.

Comments on revised version:

I also agree that the authors addressed our comments and the manuscript is much stronger now.

Reviewer #3 (Public review):

Summary:

The authors build on a recent computational model of planning, the "value-guided construal" framework by Ho et al. (2022), which proposes that people plan by constructing simple models of a task, such as by attending to a subset of obstacles in a maze. They analyze both published experimental data and new experimental data from a task in which participants report attention to objects in mazes. The authors find that attention to objects is affected by spatial proximity to other objects (i.e., attentional overspill) as well as whether relevant objects are lateralized to the same hemifield. To account for these results, the authors propose a "spotlight-VGC" model, in which, after calculating attention scores based on the original VGC model, attention to objects is enhanced based on distance. They find that this model better explains participant responses when objects are lateralized to different hemifields. These results demonstrate complex interactions between filtering of task-relevant information and more classical signatures of attentional selection.

Strengths:

(1) The paper builds on existing modeling work in a novel manner and integrates classic results on attention into the computational framework.

(2) The authors report new and extensive analyses of existing data that shed light on additional sources of systematic variability in responses related to attentional spillover effects

(3) They collect new data using new stimuli in the original paradigm that directly test predictions related to the lateralization of task-relevant information, including eye tracking data that allows them to control for possible confounds.

(4) The extended model (spotlight-VGC) provides a formal account of these new results.

Weaknesses:

(1) The spotlight-VGC model has a free parameter - the "width" of the attentional spotlight. This seems to have been fixed to be 3 squares. It would be good if the authors could describe a more principled procedure for selecting the width so that others can use the model in other contexts.

(2) Have the authors considered other ways in which factors such as attentional spillover and lateralization could be incorporated into the model? The spotlight-VGC model, as presented, involves first computing VGC predictions and only afterwards computing spillover. This seems psychologically implausible, since it supposes that the "optimal" representation is first formed and then it gets corrupted. Is there a way to integrate these biases directly into the VGC framework, perhaps as a prior on construals? The authors gesture towards this when they talk about "inductive biases", but this is not formalized.

(3) Can the authors rule out that the lateralization effects are the result of memory biases since the main measure used is a self-report of attention?

Reviewer #3 (Public review):

Hobbs et al. use live-cell single-molecule tracking (SMT) of HaloTag- and SNAP-tagged GATA2 combined with CUT&Tag chromatin profiling to examine how GATA2 chromatin engagement evolves during erythroid differentiation. Across three complementary systems, G1E-ER4 cells, HPC7 cells, and primary bone marrow progenitors from a new Gata2-SNAP knock-in mouse, they report a transient strengthening of long-lived GATA2 chromatin binding at the "Early" (2 h) erythroid stage, manifested either as increased residence time (G1E-ER4) or expansion of the long-lived bound fraction (HPC7, primary cells). CUT&Tag identifies 1,167 Early-restricted GATA2 peaks partitioning into GATA2-only (promoter-proximal, GATA/RUNX motifs) and GATA2+GATA1 co-bound (distal, GATA/E-box motifs) subclasses. The authors propose that this kinetic phase represents a previously unappreciated dimension of the GATA switch.

This is a strong study with a genuinely novel finding-the non-monotonic kinetic behavior of GATA2 during erythroid priming, supported by complementary measurements in three biological systems. The issues below are largely clarifications, additional analyses of existing data, and modest refinements to the discussion. With these addressed, the manuscript will make a valuable contribution. I recommend a minor revision.

Specific points:

(1) Clarify the photobleaching correction and report per-cell bleach lifetimes.

The long-lived residence time claim in G1E-ER4 cells depends on careful accounting for photobleaching, which the Methods indicate was done via a right-censoring model. For reviewer and reader confidence, the authors should report the per-stage (or per-cell distribution of) photobleaching lifetimes and the photobleach-corrected residence time values alongside the apparent values in Figure 2D. If feasible, including a brief supplementary analysis with an H2B-Halo or similar long-lived control under matched conditions would further solidify the quantitative claims. This is an analysis of existing data and should not require new imaging.

(2) Unify or explicitly discuss the mechanistic differences across systems.

The three systems show qualitatively different signatures: residence time change in G1E-ER4, bound fraction expansion in HPC7, and primary cells. The authors currently group these under "enhanced engagement," but these signatures imply different underlying mechanisms (koff decrease vs. increased kon or increased specific-binding-competent pool). The Discussion partially addresses this by noting engineered vs. native differences, but a more explicit framing in both Results and Discussion would help readers. Specifically, reporting an on-rate proxy (for example, binding events per unit time normalized to detectable molecule number) alongside koff would let readers see how the mechanistic pieces fit together. I do not think this changes the central message; it sharpens it.

(3) Per-cell GATA2 concentration would strengthen the "uncoupling" claim.

A central claim of the Figure 6 model is that chromatin engagement is uncoupled from protein abundance. The ectopic Shield-1 stabilization system is a reasonable design choice, but quantifying total nuclear GATA2-Halo signal (for example, from the pre-bleach frame or a brief high-power acquisition) on a per-cell basis across stages would directly support the interpretation. For the primary cells, where the biological claim is strongest, a western blot or quantitative immunofluorescence on the flow-sorted populations would make the uncoupling argument much more defensible. I recognize this may be one additional experiment, but it is a high-value one.

(4) Additional single-cell distribution analysis.

Figure 1E and Figures 2 to 4 show substantial cell-to-cell heterogeneity, and the Early populations in particular look potentially bimodal. Given that the authors cite Wheat et al. and Palii et al. on probabilistic hematopoietic transitions, a brief supplementary analysis using distribution-based statistics (K-S test, or mixture model) rather than, or alongside, mean-based ANOVA would align the analysis with this conceptual framing and may reveal whether the Early state represents a subpopulation transition rather than a uniform shift. This is purely an analysis of existing data.

(5) Quantitative integration of CUT&Tag with SMT.

The manuscript presents SMT and CUT&Tag as complementary but does not attempt to quantitatively connect them. A back-of-the-envelope calculation of whether a 21% increase in residence time (G1E-ER4), or the fraction expansion in other systems, is consistent with the acquisition of the 1,167 Early-restricted sites, given plausible site affinities, would substantially strengthen integration. Even if the calculation is approximate, framing it explicitly would help readers appreciate that the two datasets reinforce each other.

(6) Short-lived kinetic interpretation and tracking parameters.

The 1.5 s gap allowance in tracking is long relative to the 0.55 to 0.73 s short-lived residence times reported in primary cells (Figure Supplement 1F), which could affect the interpretation of the "slowing of target search" claim. A brief sensitivity analysis with tighter gap parameters in the supplement would reassure readers that this effect is robust. Additionally, please clarify how the inferred slowing of search, which should reduce kon, is reconciled with the increased number of binding events per cell at the Early stage.

(7) CUT&Tag peak definition.

The Early-restricted peak set is defined by presence and absence at q less than 0.01, which can be sensitive to near-threshold peaks. Please report either (a) the CUT&Tag signal intensity distribution at the 1,167 sites across all three stages as a quantitative scatter or density plot, beyond the heatmap in Figure 5C, or (b) the result of a differential binding analysis (for example, DESeq2 on read counts in a union peak set) as a supplementary confirmation. Please also state the number of CUT&Tag replicates per stage and the overlap of Early-restricted sets across replicates.

(8) Knock-in mouse validation.

The Gata2-SNAP allele is a valuable new tool, and it would benefit from slightly more quantitative validation in the supplement. A brief characterization of basic hematopoietic parameters in homozygotes (CBC, LSK/HSPC frequencies, or colony assays) would confirm that the tagged allele is truly physiological and would serve the community that will want to use this mouse going forward. If this has been done, please include it; if not, a statement about what was checked would suffice.

Reviewer #3 (Public review):

Summary:

The work has the potential to identify the topographical organization of the auditory cortex, which remains controversial with current unnaturalistic sound stimulation, using an elegant approach developed in the visual domain with population receptive field mapping to study the organization of the visual system with naturalistic stimulation conditions.

Strengths:

This work presents an analysis of the topographic study of auditory cortical organization, using a substantial Human Connectome Project 7-Tesla functional imaging dataset in which 174 participants viewed naturalistic movies.

Weaknesses:

The key issue for the paper is that even the authors seem undecided on what the topographical results are and whether these results are consistent with, refute, or expand our notion of human auditory cortical field organization using this massive dataset obtained under movie-watching conditions. Short of this clarity, and much of the discussion of the issues surrounding topographic mapping is buried in the Supplementary materials section, it is not clear what the authors think the advance of the current work is beyond the large datasets.

On the flip side, there is little consideration of the challenges of mapping the auditory cortex using naturalistic stimuli that prevent dissociating visual from auditory stimulation conditions, contributing to this clarity or lack thereof in tonotopic mapping.

As such, the current manuscript struggles to achieve its full potential.

Reviewer #3 (Public review):

Summary:

In this elegant study, Tsuji et al. identify a relationship in Drosophila between cardiodynamics and threatening stimuli where mild air puffs elicit a brief bradycardia that coincides with locomotion increases. They then take advantage of the arsenal of genetic tools available in the fruit fly to reveal the indispensability of dopamine, through the action of Dop1R2, in this phenomenon. Further, they pinpoint the source of this dopamine to two specific pairs of neurons - DA-WED that are threat-activated. They then test and find a potential role for cardiac interoception from the heart in linking behavior and cardiodynamics.

Strengths:

This is an interesting and timely story that brings together the tools of fruit fly systems neuroscience and links it with physiology. The experiments are well done and tell a very nice story. In particular, the primary message of the paper - that the authors have identified specific dopaminergic neurons that regulate cardiac activity - is sound.

Weaknesses:

There are no important problems with the scientific approach. Rather, there are some interpretive changes I would consider.

(1) The changes in heart rate are small (10% or so), and, as far as I can tell, are evident for a beat or two. So the data may be better interpreted not as a change in rate but as a lengthening of diastole for a beat or two. That may seem a petty difference, but it might point to particular stretch-activated systems or changes in blood flow as the determinant.

Heart rate must be averaged over time, and so might be blurring the effects. It may be useful to produce figures centered on beat count and duration rather than time. Because the effect may even be just on a single beat, we suggest the authors try plotting the average beat duration for each beat that follows the air puff. If it's really just the first beat, using a quantification of the change of this duration relative to the average that precedes the puff may produce more striking figures.

(2) The author's model that cardiac deceleration leads to walking data is only partially supported by their data. In the first figure, the relationship between cardiac deceleration and walking probability seems to be inverted relative to their model (weak stimulus -> strong cardiac effect and weak locomotor effect; strong stimulus-> weak cardiac effect and strong locomotor effect). It is possible that this discrepancy may disappear when the authors look at beat duration rather than heart rate (for instance, if following the strong stimulus, there is a very long beat that is followed by tachycardia, thus weakening their observed HR change). It would also be easier to relate this data in Figure 1 to their interoceptive model if some data were shown that illustrated the relative timing of the cardiac change and the locomotor start.

(3) Also, since the locomotor and cardiac changes are probabilistic, it would be very useful to see how their respective probabilities change when conditioned on the other. According to their interoceptive model, locomotion should preferentially increase on trials where cardiac deceleration occurs. The authors should discuss this incongruity and also potential alternative interpretations of their cardiac manipulation experiments. Perhaps the bradycardia makes them more sensitive to threats - as suggested in the introduction? Control flies show a mild increase in locomotion following green light (Figure 5j), so perhaps by slowing the heart, they are more sensitive and thus respond more strongly to this stimulus?

(4) Looking at the example shapes of the beats in Figure 5g versus Figure 1c, the optogenetically induced diastole has a very different shape from the naturally occurring long beat. Thus, the exact cardiac stimulus may be unnatural. If this is true across trials and animals, it may be worth considering that the funny beat (like an anxiogenic atrial fibrillation in mammals) is the source of the fear and, in turn, locomotor behavior (also interesting!) rather than being a true replication of the cardiac events seen following the puff stimulus.

Reviewer #3 (Public review):

Summary:

The authors argue that establishing the expression pattern and sub-cellular localisation of an animal's proteome will highlight hypotheses for further study. This claim is probably accepted by many in the community. This manuscript seeks to confirm the feasibility of establishing such a resource, by using current transgenic methods to knock in DNA encoding different colored fluorescent tags into C. elegans genes.

Strengths:

The authors make the points above. For example, they provide evidence that the C. elegans germline harbors two populations of mitochondria that differ qualitatively in the proteins they express. They also confirm that labelling the whole proteome is an achievable goal with relatively limited resources and time.

Weaknesses:

The work is somewhat incremental in that it uses existing transgenic technology. Cell biology in C. elegans is challenging because of the small size of many of its cells, notably neurons. This can make establishing the sub-cellular localisation of a fluorescently tagged protein, or co-localizing it with another protein, tricky. The authors point out in their introduction that advances in light microscopy such as diSPIM, STED and ISM (a close relative of SIM), have increased the resolution of light microscopy. They also point out that recent advances in expansion microscopy can similarly help overcome the resolution limit. However, they do not use these technologies to characterize their transgenic strains.

Reviewer #3 (Public review):

In this paper, the authors revealed that Molidustat can induce a dose-dependent increase in Caspase-3/7 activity in the HT29 cell line, which is an APC-mutant colorectal cancer cell line. More importantly, they found that targeting PHD2 alone cannot cause cell death. By using thermal proteome profiling (TPP) and orthogonal chemical proteomic competition assays, they determined GTSP1 as a previously undiscovered off-target of Molidustat. They also revealed that combined PHD2 and GSTP1 loss leads to an increase in intracellular ROS and apoptosis. Moreover, they evaluated the effects of Molidustat in colonic organoids and showed that Molidustat has a high selectivity for colonic organoids with activated WNT signaling and/or KRAS pathway alterations, and this effect is not reproduced by hydroxylase inhibition alone, providing a new potential approach to targeting both PHD2 and GTSP1 for the treatment of APC-mutant CRC.

Reviewer #3 (Public review):

Summary:

In the present study, the authors examined pupillary responses to uncolored stimuli (number graphemes) among number-color synesthetes and non-synesthetes. After seeing a digit, the synesthetes and active control participants were asked to indicate which color they perceived using three dimensions of hue, saturation, and lightness. The lightness values were the primary independent variable for follow-up analyses. To see how the pupil responded to psychologically "bright" and "dark" digits, the authors split the reported lightness values at the median and plotted them. The synesthetes showed a pupillary constriction to digits they perceived as bright and dilation to digits they perceived as dark. Active control participants did not show that effect. In a subsequent block, only the synesthetes were shown the colors they reported perceiving as colored discs. Their pupillary responses were similar. The authors also found that the differences in pupillary responses between light and dark perceptions (with digits) were only slightly delayed in their onset to the perception of a colored disc, and therefore the color perception accompanying a digit is unlikely to be effortful or a retrieved association, but occurs rather automatically.

Strengths:

The authors employed a well-controlled and designed quasi-experiment comparing color-grapheme synesthetes to non-synesthetes and showed convincingly that the color perceptions accompanying graphemes alter the physical perception of brightness. They also made a reasoned attempt to ruled out the possibility that color associations are occurring effortful via retrieved associations.

The follow are questions which I had asked in a first round of reviews, and which were answered adequately by the authors:

(1) Are the pupillary responses among synesthetes, which objectively do not seem to match the degree of physical stimulation entering the retina, in any way maladaptive for eye functioning? I understand the constriction/dilation of the pupil to not only benefit visual acuity but also to protect the retina from damage. Are synesthetes at any risk of retinal damage due to over-dilation of the pupil to brighter stimuli? Or are these effects of a magnitude that is too small to matter? As reported in arbitrary units, it was hard to know how large these effects were in terms of measurable changes in dilation (e.g., millimeters).

(2) Likewise, is the automatic synesthetic merging of two percepts something that could be learned such that natural synesthetes and "artificial" synesthetes would look similar? For example, if a group of non-synesthetic participants were to learn a color-grapheme association to automaticity, would you expect their pupillary responses to the graphemes look similar to the synesthetes? If so (or if not), what would this tell us anything about the phenomenology of synesthesia?

(3) Do the synesthetic perceptions of digit graphemes merge in a sensible way? For example, if a synesthete sees a particular color with the digit 1, and a different color with the digit 9, what do they perceive when they see 19? or 1-9, or 1 9? Is there color blending, or an altogether different color perception?

Reviewer #3 (Public review):

Franziscus et al. describe an elegant approach for spatially specific proteome analysis. To achieve this, they expand fixed cells and subsequently use a laser to micro-dissect a region of interest, which is then analyzed by mass spectrometry.

They demonstrate the effectiveness of their approach by analyzing the nucleus, nucleolus, and the Golgi, and benchmark their hits against previous datasets for these organelles.

The manuscript is very well written and nicely guides the reader through the applied methods. The presented data is convincing, and I do not see the need for additional experimental verification of the protocol. The only minor concern is the novelty of the method and the presentation. A combination of expansion, laser microdissection, and proteomics has been applied in the past (PMID: 36450705, PMID: 39477916). In the manuscript, one of these studies is cited, though it does not become clear that this approach is already described. However, Franziscus et al. describe the approach better and make it more accessible to the reader, especially since the other studies described this methodology in combination with tissue expansion and not in combination with single cell expansion as it is done here. I would ask the authors to be clearer in the introduction about what others have already done and what their contribution is here. In general, I am convinced that the community will benefit from the presented protocol to analyze organelle proteomics in detail.

Reviewer #3 (Public review):

Summary:

This manuscript investigates a theoretically important question in cognitive science: whether higher-level physical reasoning is an abstract, modular process or is grounded in real-time body-environment interactions. To address this question, the authors combine galvanic vestibular stimulation (GVS) with the Virtual Tools task to test whether perturbing vestibular gravity signals affects performance in physical reasoning. The study is conceptually innovative and has the potential to bridge embodied sensory processing and higher-level cognition. However, in its current form, the evidence only partially supports the main claims, and several aspects of the analysis and interpretation limit the strength of the conclusions.

Strengths:

A major strength of the manuscript is the originality of the experimental paradigm. The combination of galvanic vestibular stimulation (GVS), which perturbs gravity-related vestibular signals, with computerized game-based tasks that require physical reasoning provides a novel way to test whether ongoing bodily experience influences higher-level cognition. Conceptually, the study is highly original and meaningfully bridges two domains that are often studied separately: sensorimotor processing and higher-level cognition.

Weaknesses:

The main weakness of the manuscript is that its central conclusion is not strongly supported by the data. The key finding depends on a marginally significant cross-study comparison, whereas direct GVS-versus-Sham differences in Study 2 are minimal across aggregate measures. In addition, many game-level analyses involve a large number of uncorrected multiple comparisons, raising the possibility that some of the reported effects may reflect chance findings. The manuscript's most important metric, the Gravity-Weighted Index, was not preregistered and is exploratory in nature, yet it is treated as a primary basis for confirmatory conclusions. The cross-study comparison is also difficult to interpret because the two studies differ in participant samples, number of games, and partially in the stimulus set. Finally, the mechanistic claims in the Discussion-particularly those invoking predictive coding, stochastic resonance, or updating of internal gravity models-go well beyond what can be directly inferred from the present behavioral data. Overall, the study provides intriguing but limited evidence that vestibular signals may influence some physical reasoning tasks under specific conditions, rather than strong evidence for a broad account of physical reasoning as grounded in online vestibular processing

https://www.facebook.com/groups/705152958470148/posts/1274730854845686/

A curious Series 3 Smith-Corona in crinkle tan possibly made for the war effort?

Reviewer #3 (Public review):

Summary:

In this manuscript, Max Schwarze and colleagues examined the coupling distance between presynaptic Ca²⁺ channels and the vesicular release sensor at neocortical synapses in mice. They propose that Ca²⁺ channel-release sensor coupling differs across cortical areas, with relatively loose (microdomain) coupling in prefrontal cortex (PFC) and tighter (nanodomain) coupling in primary somatosensory cortex (S1) for comparable pyramidal-neuron synapse types. To test this, they combine paired recordings and minimal stimulation with chelator manipulations (EGTA/BAPTA), mean-variance/MPFA-style analyses, presynaptic Ca²⁺ imaging, and computational modeling. They conclude that presynaptic coupling organization is area-specific in the mature cortex and contributes to regional differences in synaptic timing, reliability, and short-term plasticity.

Strengths:

This study tackles an important question and is strengthened by a cohesive body of evidence assembled from multiple complementary approaches. A major asset is the inclusion of high-value datasets, particularly the paired recordings between L5 pyramidal neurons and the systematic assessment of EGTA sensitivity, which provide a solid functional foundation for the authors' central claims. The work is further distinguished by its genuinely multimodal design: combining electrophysiology with presynaptic calcium imaging (and integrating these observations with quantitative analyses and modeling) offers a more mechanistic view of neurotransmitter release than any single method could provide. Overall, the direct, within-framework comparison of presynaptic release-control mechanisms across cortical areas for comparable synapse types is compelling and gives the conclusions a level of robustness and interpretability that is often difficult to achieve in studies of cortical synaptic diversity.

Weaknesses:

Several aspects would benefit from clearer explanation, stronger integration with the existing literature, and a more explicit discussion of limitations and potential confounds. Without these additions, some conclusions remain speculative. Throughout the manuscript, the authors also often imply that different measurements reflect the same underlying synapse population. This is unlikely to be strictly true across all experiments and makes it difficult to integrate results from the various approaches into a single, unified set of functional synaptic properties. In addition, some statements-particularly those linking coupling mode to "higher-order neocortical functions"-appear broader than what is directly supported by the experiments and should be tempered or more precisely scoped.

Below, I list several topics that could help better frame the main findings of the present study and clarify how it relates to previously published work.

(1) The authors use EGTA sensitivity of EPSCs (together with additional metrics) to argue that S1 and PFC synapses differ in Ca²⁺ channel-release sensor coupling. While this is a plausible interpretation, EGTA effects are not uniquely determined by coupling distance and can also reflect differences in Ca²⁺ entry kinetics, action potential waveform, endogenous buffering/extrusion, or release-sensor/vesicle state. The authors use a constrained modeling approach, but the rationale for the different constraint sets is not fully clear from the current description. It would be helpful to expand and clarify the Methods section to explain how these constraints were defined, justified, and applied (and how alternative constraint choices would affect the results). In this context, the Abstract's broader claim that the study "reveals microdomain coupling as a presynaptic structure-function correlate of higher-order neocortical functions" appears overstated. Given the well-known diversity of cortical synapses even within a single region (e.g., synapses onto different interneuron subclasses or different PN cell types, extracortical sources like thalamus), the authors should clarify the intended scope: is the conclusion meant to apply broadly across synapse classes in S1 and PFC, or only to the specific connection type(s) examined here?

(2) The chelator logic is sound in principle, but the Discussion should more explicitly acknowledge standard caveats and alternative explanations. The authors partly address this by including presynaptic Ca²⁺ imaging and modeling, yet it would help to explain more clearly how the combination of (i) chelator sensitivity, (ii) presynaptic Ca²⁺ signals, and (iii) model constraints rules out-or substantially reduces the likelihood of-changes in AP waveform, Ca²⁺ influx kinetics, buffering/extrusion, or sensor/vesicle state as the primary drivers. In addition, recent hypotheses emphasizing vesicle priming and/or release-site occupancy as contributors to apparent EGTA sensitivity should be discussed as a complementary or alternative interpretation.

(3) A substantial portion of the S1 comparison appears to rely on previously published datasets. This should be made unambiguous in the Results and Methods, and it would be helpful to summarize this clearly (e.g., in a table indicating which figures/analyses use new data versus reanalysis of published data). If this information is already present, it should be highlighted more prominently.

(4) The modeling is informative, but the choice of a specific VGCC-release-site geometry and channel arrangement is not sufficiently justified. The manuscript adopts a particular spatial configuration, yet the rationale for selecting this geometry, rather than other plausible architectures discussed in the literature, is not clearly explained, nor is it meaningfully revisited in the Discussion. The authors should justify why the same organization is assumed across two distinct cortical areas and, ideally, include (or at a minimum discuss) a sensitivity analysis showing how key inferences (e.g., coupling distance and channel number) depend on the assumed geometry.

(5) The calcium imaging data are valuable, but given the diversity of synapses within each cortical layer, it is not clear that imaged boutons can be confidently assigned to the specific connection types being interrogated electrophysiologically. A substantial fraction of boutons likely corresponds to different postsynaptic targets (including interneurons and distinct pyramidal-cell classes), and this heterogeneity could complicate interpretation. This limitation should be discussed explicitly

(6) In unitary connections, the authors assess EGTA effects alongside other functional parameters (strength, delay, short-term plasticity), which is a major strength. However, for L2/3 to L5 connections, it appears that EGTA sensitivity was tested primarily using extracellular stimulation. Given anatomical and circuit differences between PFC and S1, extracellular stimulation may recruit different synapse populations across regions, potentially confounding regional comparisons of EGTA sensitivity. This limitation should be acknowledged explicitly. While I am not requesting technically demanding L2/3↔L5 paired recordings in S1, the possibility that different synapse identities are being sampled should be treated as a meaningful source of uncertainty. The Discussion would also benefit from placing the magnitude of EGTA effects in the context of prior "loose coupling" literature, where comparatively large EGTA effects have been reported in some systems. In addition, the reported difference between adult PFC EGTA effects and S1 inhibition appears small (on the order of <10%) and should be interpreted cautiously, especially given that PFC and S1 mature on different timelines and P21-P26 is unlikely to reflect a mature PFC circuit state. The adult cohort (P90-P100) is therefore important, but the age mismatch complicates PFC-S1 comparisons; ideally, S1 should be assessed at matched ages, or this limitation should be discussed explicitly. Finally, for statistical robustness, in panel D of Figure 2, were the comparisons corrected for multiple testing to control Type I error?

(7) Alterations in initial release probability are often associated with changes in short-term plasticity. In the present manuscript, the authors report similar initial release probability at PFC and S1 synapses, yet observe differences in short-term plasticity profiles. The mechanistic basis for this apparent dissociation is not addressed and should be discussed explicitly, including potential explanations.

(8) There are multiple instances where the text appears to cite non-existent or misnumbered figure panels (e.g., references to "Figure 4G-I / 4J" when the relevant material appears elsewhere). These should be corrected throughout, as they currently reduce readability and confidence.

(9) The Methods describe P21-P26 animals, whereas the Results include older cohorts (e.g., P90-P100) and additional regions (e.g., mPFC). The Methods should be updated so that all cohorts and regions analyzed in the Results are fully described.

Reviewer #3 (Public review):

This work provides a novel statistical model to identify imported malaria cases, which are an important challenge for elimination, particularly in low-transmission areas. This tool was applied in Plasmodium falciparum populations in Mozambique and determined differences in importation rates in two low-transmission districts in the South.

Strengths:

The study has several strengths, particularly the development of a novel Bayesian model integrating genomic, epidemiological, and travel data to estimate importation probabilities. The findings provided important insights into malaria transmission dynamics, including the identification of importation sources and regional differences in importation rates across Mozambique. These results highlight the potential value of targeted interventions among traveler populations to support malaria elimination efforts. Moreover, this approach could be adapted to other epidemiological settings.

Weaknesses:

The study has some limitations, including uneven sample representation across provinces, incomplete metadata for risk factor analysis and a proxy for transmission intensity. Future work will include a new sample collection effort and the incorporation of monthly malaria incidence estimates.

Reviewer #3 (Public review):

Summary:

Ding et al. investigate the roles of TIE1 and TEK (Tie2) in mouse cardiac development, with a particular focus on atrial trabeculation. The authors employ multiple genetic models, including Tie1ICDflox/flox (with Cdh5-CreERT2), a knockout-first allele (EUCOMM, Tie1 tm1a/tm1a), and a Tek deletion model.

Based on the dataset from Feng et al. 2022 Nat Commun, the authors report increased expression of Tie1 and Tek transcripts in atrial endocardial cells compared to ventricular cells at embryonic day (E) 14.5. Loss of Tie1 leads to early atrial trabeculation defects detectable at E12.5, whereas ventricular defects appear later and are less pronounced at E14.5. Chamber-specific RNA sequencing reveals stronger transcriptional changes in atrial tissue.

Conditional deletion of Tek results in a similar phenotype, with more pronounced atrial defects. Combined deletion of Tie1 and Tek (Tie1 ΔICD/ΔICD; Tek+/-) leads to earlier and more severe defects in both atrial and ventricular trabeculation and results in embryonic lethality around E12.5, suggesting a synergistic interaction between the two genes.

Conditional endothelial deletion of Tie1 combined with heterozygous global Tek at later embryonic stages allows analysis at later time points and again shows more severe defects in atrial trabeculation. Postnatal analysis of this model reveals reduced heart-to-body weight ratios and potential mild atrial abnormalities.

Strengths:

(1) The authors address chamber-specific signaling mechanisms underlying atrial versus ventricular trabeculation, an area of high developmental and clinical relevance.

(2) The study provides a comprehensive temporal analysis across multiple embryonic stages.

(3) The use of multiple genetic models strengthens the overall conclusions and allows comparative interpretation.

(4) While focusing on trabeculation, the authors also include observations on coronary vessel development, increasing the broader relevance of the work. The findings are therefore of interest to the wider cardiovascular research community.

Weaknesses:

(1) Timing of recombination vs. trabeculation onset

Ventricular trabeculation begins earlier than atrial trabeculation. Since tamoxifen (in contrast to 4-hydroxytamoxifen) requires metabolic activation, Cre-mediated recombination will occur with a delay. This suggests that atrial trabeculation may be targeted before its onset, whereas ventricular trabeculation may already be underway for 2-3 days at the time of effective gene deletion.

How do the authors account for this discrepancy in their interpretation?

Have earlier induction time points been tested to better capture the onset of ventricular trabeculation? This limitation should be explicitly discussed.

(2) Clarity of genetic models and experimental design

The study employs several genetic constructs. It would improve clarity if, for each experiment, the specific genetic model and tamoxifen regimen were clearly described before presenting the results.

(3) Tie1 tm1a/tm1a phenotype vs. known global knockout

Previous studies (PMID: 8846781, 7596437) show that complete Tie1 loss leads to severe edema, vascular rupture, and embryonic lethality around E13.5-E14.5.

How does the Tie1 tm1a/tm1a allele differ, given that animals appear to survive longer? Is this allele hypomorphic rather than a full knockout?

This point requires clarification.

(4) Limited mechanistic insight

While the authors aim to investigate underlying mechanisms, the current study is largely descriptive and based on mRNA expression and genetic interaction analyses (Tie1/Tek co-deletion). Direct mechanistic insights into signaling pathways remain limited. However, the dataset provides a valuable foundation for future mechanistic studies, which should be more clearly acknowledged in the discussion.

Reviewer #3 (Public review):

Summary:

This narrative review provides a clear, well-structured, and comprehensive synthesis of intracerebral recording work on the neural correlates of consciousness. It is written in an accessible manner that will be useful to a broad community of researchers, from those new to iEEG to specialists in the field.

Strengths:

The manuscript successfully integrates methodological and theoretical perspectives and offers a balanced overview of current sometimes contradicting evidence. As such, the manuscript is important as call for a concernted better exploration of NCCs using iEEG in the future.

Weaknesses:

The manuscript discusses extensively the use of "report" as a criterion for identifying conscious perception and its limitations for separating between correlates of consciousness and post consciousness processes, yet the term is not defined at the outset. The authors should specify what they mean by "report" (e.g., verbal report, nonverbal self-report, or any meta-cognitive indication of experience). Importantly, this definition should be explicitly linked to the theoretical landscape: whether the authors adopt an access-consciousness perspective in which (self) reportability is central, or whether the review also aims to address phenomenal consciousness. Making this conceptual grounding explicit at the beginning will help readers interpret the empirical work surveyed throughout the review.

In addition, the review would benefit from an earlier introduction of the distinction between states and contents of consciousness. This distinction becomes important in the later section on anesthesia, sleep, and epileptic seizures, where the focus shifts from content-specific NCCs to alterations in global states. Presenting these definitions upfront, and briefly explaining how states and contents interact, would strengthen the coherence of the manuscript.

Overall, this is an excellent and timely review. With clearer initial theoretical definitions of consciousness, the manuscript will offer an even stronger conceptual framework for interpreting intracerebral studies of consciousness.

Comments on revised version:

The current version of the manuscript is clear and complete. Kudos to the authors for their thorough revisions.

My only remaining point concerns the definition of "report": "We define a report as any explicit behavioral response (whether verbal, manual, or otherwise) that communicates a participant's subjective state."

It would be helpful to clarify whether this definition is intended to exclude purely internal, explicit self-reports that are not externally expressed. As currently formulated, the definition appears to require overt behavioral communication. However, this raises a conceptual issue in relation to the no-report paradigm literature, where the distinction between report, metacognitive access, and overt motor/verbal expression is precisely at stake.

Could the authors specify whether "report" is meant to (i) be restricted to externally observable, behaviorally expressed reports, or (ii) extend to internally generated, explicit metacognitive judgments even when they are not communicated? Clarifying this point would help situate the manuscript more precisely within ongoing debates on the role of report in identifying neural correlates of consciousness.

Reviewer #3 (Public review):

Summary:

This narrative review provides a clear, well-structured, and comprehensive synthesis of intracerebral recording work on the neural correlates of consciousness. It is written in an accessible manner that will be useful to a broad community of researchers, from those new to iEEG to specialists in the field.

Strengths:

The manuscript successfully integrates methodological and theoretical perspectives and offers a balanced overview of current, sometimes contradicting evidence. As such, the manuscript is important as it calls for a concerted and better exploration of NCCs using iEEG in the future.

Weaknesses:

The manuscript extensively discusses the use of "report" as a criterion for identifying conscious perception and its limitations for separating between correlates of consciousness and post-consciousness processes, yet the term is not defined at the outset. The authors should specify what they mean by "report" (e.g., verbal report, nonverbal self-report, or any meta-cognitive indication of experience). Importantly, this definition should be explicitly linked to the theoretical landscape: whether the authors adopt an access-consciousness perspective in which (self) reportability is central, or whether the review also aims to address phenomenal consciousness. Making this conceptual grounding explicit at the beginning will help readers interpret the empirical work surveyed throughout the review.

In addition, the review would benefit from an earlier introduction of the distinction between states and contents of consciousness. This distinction becomes important in the later section on anaesthesia, sleep, and epileptic seizures, where the focus shifts from content-specific NCCs to alterations in global states. Presenting these definitions upfront and briefly explaining how states and contents interact would strengthen the coherence of the manuscript.

Overall, this is an excellent and timely review. With clearer initial theoretical definitions of consciousness, the manuscript will offer an even stronger conceptual framework for interpreting intracerebral studies of consciousness.

Reviewer #3 (Public review):

Summary:

The authors tackle an important problem- that is defining the topological changes that occur during tumorigenesis. To study this, they use an established stepwise cell model of breast cancer. A strength of their study is a careful, robust differential analysis of topological features across each cell state that is presented clearly and rigorously. They define changes in compartmentalization, TAD structure and chromatin looping. Intriguingly, when the authors integrate differential gene expression with chromatin looping, they see that most differentially regulated genes are not involved in loop changes, suggesting that changes in promoter or enhancer chromatin marks may play a bigger role in regulating transcription than differential loops. The differential topology analysis and its integration with transcription is very well done- one of the best versions of this I have read in the 3D genome field! However, the paper is framed largely as a cancer biology study and it teaches us much less about this. I am worried that some of the trends for each topologic feature are not going to be consistent across the pre-malignant-malignant-metastatic spectrum and would like the authors to soften some of their claims a bit regarding how this clarifies our understanding of cancer evolution.

Updated comments on revision:

There are still some issues with this paper. First, it reads descriptively. It is a series of comparisons with limited biologic insight as changes are always seen in genomics and in this case, they're often not tied back to transcription or gene regulation in cancer. Cell lines do not represent cancer faithfully and in this case should not be argued to represent malignant transformation broadly. The authors did not really soften their language as much as I think required. I would caution the authors to further qualify their results in the context of a single, clonal cell line that has undergone stepwise transformation. This is not a patient cohort analysis or frank progression. This matters because there is likely to be much more noise, not pertinent to transformation, in a cell line model. It doesn't negate the validity of the study, but this language should be adjusted appropriately. It was nice to see the authors compare gene expression data from their model to the primary tumor data, however the limited overlap is concerning that at the least patterns of transcriptional regulation in their model are not faithful to primary tumors. If this is the case, it raises concern that the topological changes are also not generalizable to cancer.

The authors declined a number of functional assays to validate their observations (which are purely correlative). And while I see that the burden of extra experiments may be beyond the scope of this study, they must soften their language to justify the observed relationships.

Reviewer #3 (Public review):

This manuscript presents an engineered 3-step circuit in E. coli that combines toggle-switch-based symmetry breaking with quorum-sensing interactions to generate colony-scale spatial patterns. The work is interesting as a synthetic circuit integration study and as a demonstration of self-organized patterning across physically separated colonies. The authors provided a compelling demonstration of the characterization/tuning of parts to guide the overall system engineering. A notable strength is the demonstration that a single circuit can generate a range of self-organized spatial patterns across separate colonies.

However, I think the paper needs to tone down the extent to which the system demonstrates multi-step differentiation or morphogenesis, which is not critical for making the paper valuable. Only the first step of their circuit design (Figure 1), the toggle switch, generates stable alternative states. The latter steps are mainly signal-dependent reporter activation states layered on top of the blue receiver state, rather than true fate transitions. The authors explicitly state that red expression is added without replacing the blue identity, and they also acknowledge that red cells lose their identity upon restreaking unless they remain near sender cells. That substantially weakens the differentiation analogy and makes the Waddington framing too strong.

A related concern is that the 3rd step does not introduce a new spatial organizing rule. The authors show that the second signal remains confined to cells already receiving the first signal, and explicitly conclude that it functions only as an autocrine cue rather than a second paracrine layer. As a result, the 3-step system seems more like an added local readout or maturation layer. Overall, the main 2-step outcome is sparse green sender colonies surrounded by red-expressing blue receivers, with distant receivers remaining blue. That is a valid engineered pattern, but it is still a local, threshold-response circuit architecture.

The autonomy claim should be toned down and stated more precisely. The plate patterning occurs without externally imposed spatial gradients, which is a strength. However, by design, the overall system behavior depends strongly on pre-culture inducer conditions that set the sender:receiver ratio, and this externally imposed history is central to the final pattern. This property is tied to how the circuit is designed where steps 2 and 3 largely respond to symmetry breaking introduced in step 1, which is dependent on both history and initialization on the plate. In particular, currently the pattern formation process is quite variable (e.g. figure 5), depending on how different colonies flip the toggle switch, and consequently, how many become senders and how many become receivers. It would have been fascinating if they could also demonstrate the differentiation within individual colonies, leading to intra-colony patterns. This aspect should at least be discussed.

The mathematical model is useful in guiding both the characterization of parts, modules and the overall system. However, the claims around its quantitative predictive power should also be made narrower. The simulations are built from multiple fitted and partly hand-tuned components, including toggle-switch response curves, colony-growth rules, diffusion, reporter-response functions, and activity decline. This supports a calibrated qualitative reconstruction of the observed patterns, but not a strong predictive or mechanistic validation.

Other specific points:

(1) Given the topic of the work, the authors should cite closely relevant studies in programming pattern formation, including:<br /> Cao et al, Cell 2016 Collective space-sensing coordinates pattern scaling in engineered bacteria<br /> Rajasekaran et al, Cell 2024 A programmable reaction-diffusion system for spatiotemporal cell signaling circuit design<br /> Lu et al, BioRxiv 2024 Discovery of interpretable patterning rules by integrating mechanistic modeling and deep learning

(2) The model assumes identical diffusion coefficients for C6-HSL and C14-HSL despite their substantially different molecular sizes and hydrophobicities. This assumption could distort kinetic lag with differential diffusion in explaining the autocrine confinement of the third step. Its impact should at least be explored in the simulations.

(3) The mCherry response parameters change significantly between the 2-step and 3-step systems. The authors acknowledged this change but did not provide a clear explanation.

(4) The 3-step system is evaluated at only a single condition with no simulation comparison, in contrast to the systematic 11-condition validation of the 2-step system.

Reviewer #3 (Public review):

Summary :

This study investigates the metabolic profiles of hemocytes across multiple stage/conditions and suggests that hemocytes act as regulators of metabolism rather than merely receivers of metabolic cues. The authors show that hemocytes rely primarily on mitochondrial respiration, which is further enhanced during proliferation in development or upon genetic manipulation of plasmatocytes, but not crystal cells.

Metabolic respiration is also activated in lamellocytes, and this activation correlates with changes in mitochondrial morphology. The authors further attempt to identify mechanisms underlying this activation, proposing that mitochondrial fission may contribute to the ability of lamellocytes to encapsulate wasp eggs.

Strengths:

This work provides detailed and valuable insights into the metabolic phenotypes of hemocyte populations at different developmental stages and under both physiological and pathological conditions. The authors perform a longitudinal assessment of hemocyte metabolism and compare metabolic states across contexts.

Importantly, they provide evidence that hemocytes regulate metabolism to perform essential immunological functions, such as wasp egg encapsulation. This reinforces the view that hemocytes are key regulators and communicators that adapt their metabolic programs according to developmental and environmental demands.

Weaknesses:

The results presented are insightful, although several controls and validations could strengthen the conclusions. It would be preferable to also include responder transgenes alone as a control for leakiness, and the scRNA-seq findings would benefit from in vivo validation.

Some conclusions appear inconsistent or insufficiently supported. For instance, although mitochondrial respiration in plasmatocytes peaks at 96 h AEL, this increase is not accompanied by detectable mitochondrial rearrangement, which remains constant between 96 h AEL and 120 h AEL.

In general, the authors should temper some statements or provide further data.

Reviewer #3 (Public review):

Summary:

The author showed expression of the viral proteases 2Apro and 3Cpro of EV-D68, which cleaved specific components of the nuclear pore complex (Nup98 and POM121 by 2Apro), and 2A but not 3C expression altered nuclear import and export. Similar nucleocytoplasmic transport deficits are observed in EV-D68-infected RD cells and iPSC-derived motor neurons (diMNs). 2A inhibitor telaprevir partially rescued the nucleocytoplasmic transport deficits and suppressed neuronal cell death after infection. While it's clear that 2A can cleave NPC proteins and affect nuclear transport, the link to neurotoxicity after EV-D68 infection is less convincing.

This study opens up a very intriguing hypothesis: that EV-D68 2Apro could be directly responsible for motor neuron cell death, mediated by POM121 and possibly Nup98 cleavage, that ultimately results in paralysis known as acute flaccid myelitis. This hypothesis notably does run counter to other published data showing that human neuronal organoids derived from iPSCs can support productive EV-D68 infection for weeks without cell death and that EV-D68-infected mice can have paralysis prevented by depletion of CD8 T cells, still with EV-D68 infection of the spinal cord. However, even if 2Apro is not ultimately responsible for motor neurons dying in human infections, that does not exclude the possibility that cleavage of nups could still disrupt motor neuron function. Notably, most children with AFM have some amount of motor function return after their acute period of paralysis, but most still have some residual paralysis for years to life. It is possible that 2A pro could mediate the acute onset of weakness, while T cells killing neurons could determine the amount of long-term, residual paralysis.

Strengths:

The characterization of nuclear pore complex components that appear to be targets of both poliovirus and EV-D68 proteases is quite thorough and expansive, so this data set alone will be useful for reference to the field. And the process by which the authors narrowed their focus to EV-D68 2Apro reducing Nup98 and POM121 as consequential to both import and export of nuclear cargo but not RNA was technically impressive, thorough, and convincing. As will be detailed below, when the authors move from studying over-expressed proteases in transformed cell lines to studying actual virus infection in both transformed cell lines and iPSC-derived neurons, some of the data only indirectly support their conclusions; however, the quality of the experiments performed is still high. So even if the claim that 2Apro causes neurotoxicity is circumstantial, the data certainly are intriguing and certainly justify further study of the effects of EV-D68 2Apro on the NPC and how this impacts pathogenesis. This is a convincing start to an intriguing line of inquiry.

Comments on revisions:

The authors have returned a stronger revised manuscript, being responsive to most of the combined reviewers' comments. It was especially important to add the clarity and specificity that the data in this manuscript did not establish a direct link for 2Apro causing AFM. The authors have clarified this language adequately, such that it is appropriate to remove the "incomplete" portion of the short assessment as they have requested. Adding in experiments with EV-D68 virus infection to complement their work with recombinant proteases also strengthened their conclusions.

There are still some areas where discrepancies remain, although these are minor and can mostly be acknowledged as limitations of their approach rather than needing more experiments, unless the authors choose to do the additional experiments. To try to make this understandable, I have copied from the rebuttal letter (*) original comment, (**) author's rebuttal, and (***) a reply to the rebuttal:

(*)(2) Telaprevir was able to rescue nucleocytoplasmic transport in RD cells at low concentrations (Figure 4A). It is not shown if this correlates with its antiviral effect in RD cells, or could this correlate with inhibition of 2A cleavage of Nup98 or POM121, which is never measured.

(**) In the aforementioned new experiment in Figure 4A, we have also included a dose-response curve for telaprevir showing its inhibition of POM121 and Nup98 cleavage.

(***) Fig.4A is in diMN not RD cells. The EC50 of telaprevir could be very different in RD cell vs diMNs. This question remains unanswered.

(*) (3) Building off of the prior point, the authors' claim that the neuroprotective effect of telaprevir is independent of its antiviral effect is not well-founded. Figure 4E (neuroprotection) was done with MOI 5, and Figure 4G (virus growth) was MOI 0.5. Telaprevir neuroprotection is not shown at MOI 0.5, nor is the neuroprotective effect correlated with inhibition of 2A cleavage of Nup98 or POM121.

(**) The selection of MOIs for these two experiments was limited by technical considerations. If the viral growth curve were to be performed at MOI 5, it would be confounded by cell death. Further, a low MOI is required in order to allow multiple rounds of infection, and is therefore more sensitive for assaying the effect of telaprevir on viral replication. On the other hand, at MOI 0.5 diMN death is very gradual, and the neuroprotection assay we would have lacked the statistical power to determine whether a rescue of this small magnitude of toxicity is significant. The EC50 of telaprevir is not expected to vary at different MOIs.

(***) This should be discussed in the Discussion as a limitation of the experiment.

(**) We have also now correlated the inhibition of 2Apro cleavage of Nup98 and POM121 with the neuroprotective effect at comparable concentrations of telaprevir, as described above.

(***) Unless you quantify this, my eye disagrees with you. In Fig.4A, cleavage of NUP98 is rescued by 3uM telaprevir, but that does not seem to be the case for POM121.

Additionally, in Fig. 4D, why is only NLS but not NES is impaired in diMN? This should be discussed.

Reviewer #3 (Public review):

Summary:

This study uses large-scale all-atom molecular dynamics simulations to examine the conformational plasticity of the HIV-1 envelope glycoprotein glycoprotein (Env) in a membrane context, with particular emphasis on how the transmembrane domain (TMD), cytoplasmic tail (CT), protomer cleavage, and membrane environment influence ectodomain orientation and antibody epitope exposure. By comparing Env constructs with and without the CT, explicitly modeling glycosylation, and embedding Env in an asymmetric lipid bilayer, the authors aim to provide an integrated view of how membrane-proximal regions and lipid interactions shape Env antigenicity, including epitopes targeted by MPER-directed antibodies.

Strengths:

The authors have made a genuine effort to address the concerns raised in the first round of review, and the revised manuscript is substantively improved. The addition of dynamical cross-correlation maps, expanded citation of prior computational work, clarification of the membrane composition rationale, data deposition to Zenodo, and the new discussion contextualizing the independence of ectodomain and TMD motions are all welcome. Several scientifically interesting aspects of the work merit highlighting before the remaining concerns are addressed.

A key strength of this work remains the scope, scale, and realism of the simulation systems. The authors construct a very large, nearly complete-Env-scale model that includes a glycosylated Env trimer embedded in an asymmetric bilayer, enabling analysis of membrane-protein interactions that are difficult to capture experimentally. The inclusion of specific glycans at reported sites, and the focus on constructs with and without the CT or cleavage, are well motivated by existing biological and structural data.

The observation that R696 orientation and its interacting partners give rise to asymmetric protomer conformations and distinct TMD tilts is a notable finding. The statement that interactions between R696 and lipid headgroups or CT residues can be strong enough to introduce a kink into the TMD is well-supported by representative snapshots and consistent with prior isolated-TMD simulations. The use of two initialization depths ("high" and "low") to probe R696 leaflet preference is methodologically interesting and the authors' interpretation - that there is a slight bias toward cytoplasmic leaflet interactions, but that these contacts could be highly dynamic over the course of viral entry - is appropriately cautious. It would be valuable to explicitly frame this as a hypothesis with testable predictions that future experimental or enhanced-sampling work could address. Similarly, the equilibration-driven kinking of the TMD core, consistent with prior isolated-TMD studies, represents a useful validation that extends those earlier observations to the intact trimeric context.

The simulations reveal substantial tilting motions of the ectodomain relative to the membrane, with angles spanning roughly 0-30{degree sign} (and up to ~40{degree sign} in some analyses), while the ectodomain itself remains relatively rigid. This framing, that much of Env's conformational variability arises from rigid-body tilting rather than large internal rearrangements, is an important conceptual contribution. The authors also provide interesting observations regarding asymmetric bilayer deformations, including localized thinning and altered lipid headgroup interactions near the TMD and CT, which suggest a reciprocal coupling between Env and the surrounding membrane.

The analysis of antibody-relevant epitopes across the prefusion state, including the V1/V2 and V3 loops, the CD4 binding site, and the MPER, is another strength. The study makes effective use of existing experimental knowledge in this context, for example by focusing on specific glycans known to occlude antibody binding, to motivate and interpret the simulations.

Finally, the revised discussion provides more context that situates the study's findings and discrepancies within the broader literature, strengthening the manuscript's clarity and interpretability.

Weaknesses:

The revised work is much improved, but still includes substantive issues with writing including organization, such as paragraph run-ons, and citation issues. Improving these would help readers make the most of this important study.

The revised Introduction now includes a paragraph summarizing prior MD work, which is an improvement. However, the paragraph remains structured around the limitations and setup of previous studies (e.g., "early studies were constrained by limited computational resources", short trajectory lengths, isolated constructs) rather than their findings. Readers benefit most from understanding what those studies showed - and where the present work confirms, extends, or diverges from those results. The current framing inadvertently positions prior work as deficient scaffolding rather than as independent data points converging on shared conclusions. The Introduction could be revised to briefly summarize the key biological conclusions from prior MD studies alongside their technical context, which could then be revisited in their appropriate place alongside key results.

The authors have verified that PDB entries are cited at first mention, and this is noted. However, a recurring issue remains: key literature-supported conclusions appear in the Results and Discussion sections without accompanying citations at each point of use. Passages that summarize experimental or computational findings - particularly those used to validate or contextualize the authors' own results - require citation at every point of claim, not only at first introduction of a reference. This is not a minor stylistic preference. Downstream readers, systematic reviewers, and automated tools that map literature to claims (e.g., scite) rely on co-occurrence of claims and citations within the same passage. A citation appearing several paragraphs earlier does not carry attribution forward. As a practical example: the statement that "MPER-targeting antibodies bind effectively only after the gp120-gp41 trimer undergoes major conformational rearrangements toward a fusion-intermediate or post-fusion state (Frey et al., 2008; Alam et al., 2009; Chen et al., 2014; Lee et al., 2016)", which is appropriate. That same standard of inline attribution should be applied throughout - including in Results and Discussion subsections where prior experimental findings are mentioned without citation.

Additionally, cited literature should be framed to highlight convergence with the authors' conclusions, not primarily to limitations of previous studies. Where prior studies independently support a finding, this should be stated explicitly. Independent replication across methods and systems is one of the strongest arguments for ground truth; treating it as such would improve the manuscript's scientific standing.

Finally, the dynamical cross-correlation maps assess ectodomain-TMD coupling, and the authors appropriately acknowledge that microsecond simulations capture only the closed ground state. However, the revised manuscript does not address the question raised in the first review regarding CT-TMD and CT-ectodomain correlations. The Results section states that "very weak correlations between the ectodomain and the TMD" were found, but it is not clear whether the CT was included in this analysis or whether analogous correlation maps for CT-TMD and CT-ectodomain pairs were computed for the full-length systems. Additional analyses of the authors' deposited MD trajectories-such as probing for exposure of cryptic epitopes and potential allosteric coupling-could serve as valuable extensions of this work.

Reviewer #3 (Public review):

Summary:

In this manuscript, Yang et al reported distinct functions of the protein-coding sequence (CDS) and the 3' untranslated region (UTR) in the Nanog mRNA in pluripotent stem cells. They first observed different localization patterns for the CDS and 3' UTR in embryonic stem cells and in blastocyst embryos, and this pattern correlates with cell populations in different pluripotent states based on single-cell sequencing data. To characterize the potentially distinct functions of these regions, the authors generated knockout (KO) cell lines in which either the CDS or the 3' UTR was genetically ablated. These deletions led to different phenotypes in multiple assays. These results provided evidence that the CDS and 3' UTR of an mRNA could have distinct functions. Although these results are potentially interesting, several questions need to be addressed before the validity of their conclusion can be confirmed.

Strengths:

This study provides evidence for distinct functions of the protein-coding sequence and 3' untranslated region of an mRNA in pluripotent stem cells. The concept could be more broadly applied.

Weaknesses:

The initial observation (distinct localization of CDS and 3' UTRs) and the causal relationship between the KO and phenotype need further validation.

Major points:

(1) The authors showed distinct localization patterns of the CDS and 3' UTRs in human and mouse ESCs and blastocysts, and the overlap between their signals was minimal (Figure 1). Does this mean that the CDS and 3' UTR RNAs exist separately? For example, in cells that only showed signals for 3' UTRs, do these RNAs only contain 3' UTRs and lack CDS? Was this confirmed by RNA-seq experiments? If so, how are they generated (i.e., by transcription from a novel promoter or partial degradation of the full-length mRNAs)? This is a key question. Without a clear characterization of these RNAs, the rest of the study cannot be substantiated.

(2) To confirm that the phenotypes of CDS or 3' UTR KO cells were caused by the deleted regions instead of other artifacts, rescue experiments should be performed.

(3) As over-expression of the 3' UTR showed a phenotype, important regions within it should be identified, and also the possibility that the 3' UTR contains open reading frame(s) and is translated should be tested.

Reviewer #3 (Public review):

This computational modeling study introduces the methodology of replacing bursting neurons in a model circuit with a simplified piecewise-linear model with an "active" and a "quiet" state representing, respectively, the burst of spikes and the inter-burst interval. The shape of the active state loosely represents the intra-burst firing rate. Because (piecewise) linear systems are explicitly solvable, the transitions from quiet to active and vice versa can be calculated explicitly to match exactly what a biophysically realistic model or a biological neuron does in different conditions. The base piecewise-linear model is built to represent a 2D biophysical neuron with a cubic v-nullcline. The simplicity of the model allows for matching the kinetics of more complex models with a tractable simplified set of equations, as exemplified by approximations of burst duration and amplitude, phase-response curves, entrainment, and, finally, mimicking the activities of two CPG circuit models using this simplified representation.

Major comments

(1) The use of piecewise linear approximations to explicitly estimate properties of biophysical neurons is a well-known and common technique. This study adds nothing to the technique in terms of novelty.

(2) Although the model explicitly matches active and inactive durations of a circuit neuron, the dynamics are explicitly "clamped" by the user because the reduced model parameters explicitly depend on the input. There are cases where this is useful, for example, when we are interested in the dynamics of _other_ neurons (B, C, D, ...) within the context of activity, and we "clamp" the dynamics of neuron A. One should note that this is no better than having a look-up table. Effectively, to give a comparison, it is like using a sine wave to represent a pacemaker neuron and explicitly define its frequency at different input levels so that it responds "dynamically". However, the neuron is restricted to what the user puts in, and therefore, calling it a dynamical system is entirely wrong. I am afraid that the use of this crude tool is not described well enough in the manuscript to warn a naïve user not to fall for this trap.

(3) The phase resetting curves are used incorrectly. PRCs are useful when the perturbation is weak (soft), which would demonstrate the nature of the vector field near the limit cycle and therefore inform us of the nature of its stability or instability. A hard PRC would always reset the cycle to the fixed offset from the perturbation phase and is therefore uninformative in understanding dynamics. (It is, however, useful experimentally in identifying which neurons are part of the CPG.) The authors clearly know that the dynamics of the system away from the limit cycle do not conserve those of a biophysical neuron. So what is the point?

(4) I work on the STG, one of the systems exemplified here. Even in the small and relatively regular CPGs of the STG, the definition of the active and quiet parts of a burst is often less clear than what the authors suggest. Bursting neurons often do multiple bursts in a cycle, and therefore, substituting the burst envelope is a subjective matter. This is even more problematic in bursting neurons in the brain, where there is often no quiet period. This should be discussed.

Reviewer #3 (Public review):

Summary:

The paper by Li et al explored the role of Estrogen receptor 1 (Esr1) expressing neurons in the pontine micturition center (PMC), a brainstem region also known as Barrington's nucleus (Hou wt al 2016, Keller et al 2018). First the author conducted bulk Ca2+ imaging/unit recording from PMCESR1 to investigate the correlations of PMCESR1 neural activity to voiding behavior in conscious mice and bladder pressure/external urethral muscle activity in urethane anesthetized mice. Next the authors conducted optogenetics inactivation/activation of PMCESR1 to confirm the contribution to the voiding behavior also conducted peripheral nerve transection together with optogenetics activation to confirm the independent control of bladder pressure and urethral sphincter muscle.

Comments on revised version:

No concerns. All my major questions were addressed.

Reviewer #3 (Public review):

Summary:

The authors present analyses of different fitness measures derived from empirical data from yeast knock-out mutants and the long-term evolution experiment (LTEE) with Escherichia coli to explore discrepancies and identify preferred methods to estimate relative fitness in high-throughput experiments. Their work has three components. They first discuss the different "encodings" of relative abundance data and conclude that logit-transformations are preferred, because they transform nonlinear abundance trajectories into linear trajectories with greater predictive power. Next, they compare per-generation with per-growth cycle relative fitness estimates inferred from simulations of pairwise competitions based on published growth traits for the yeast strains and on published pairwise competition measurements for the LTEE data. Both data sets show quantitative and qualitative (i.e. rank order) discrepancies of estimates across different time scales, which are highlighted by considering possible underlying causes (i.e. trade-offs between growth traits) and consequences (i.e. epistasis among mutations affecting different growth traits). Finally, the authors compare simulated pairwise and bulk (i.e. where many mutants compete during a growth cycle in a single environment) competition assays based on the yeast knock-out mutants and demonstrate an optimal ratio of collective mutants to wild-type strains that minimizes both sampling error and overestimation of fitness estimates when compared with pairwise competitions.

Strengths:

The study deals with a highly relevant topic. Fitness is central to general evolutionary theory, but also poorly defined and implies different traits for different organisms and conditions. For microbes, which are often used in evolution experiments, high-throughput experiments may yield different measures to quantify abundance over time, from individual growth traits to bulk competition experiments. Hence, it is relevant to consider discrepancies among those measures and identify preferred measures with respect to predicting population dynamic and evolutionary processes. The present study contributes to this aim by (i) making readers aware of differences among commonly used fitness estimates, (ii) showing that simulated (yeast) and calculated (E. coli) competitive fitness may differ across time scales, and (iii) showing that bulk competitions may yield relative fitness estimates that are systematically higher than pairwise competitions. The study is rather thorough on the theory side, with extensive derivations and analyses of various fitness measures using their resource competition model in the Supplementary Information. The study ends with a few practical recommendations for preferred methods to infer relative fitness estimates, that may be useful for experimentalists and stimulate further investigations.

Weaknesses:

The study has a few limitations. Perhaps the most apparent limitation is the lack of a clear answer to the question which fitness measure is best "in the light of first principles". The authors show clear discrepancies between fitness estimates across different time scales or using different reference genotypes in bulk competition and provide useful recommendations based on practical considerations (e.g. using pairwise competitions as "golden standard"), but it remains unclear whether these measures provide the greatest value for the questions researchers may want to answer with them (e.g. predict shifts in genotype frequencies). -- The authors have convinced me in their response that their recommendations were fundamentally related to the resource competition model, and the changes in introduction and discussion help to appreciate the choice of fitness measure in relation to the research question.

A second limitation is that the authors analyse fitness differences arising solely from resource competition, whereas microbes often interact via other mechanisms, e.g. the production of anticompetitor toxins, cross-feeding of metabolites or lack of growth to enhance their persistence in stress conditions. Without simulations of these processes, understanding discrepancies among fitness measures is necessarily limited. In addition, the analysis of trade-offs between growth traits causing these discrepancies during resource competition seems confounded by biases in measurement error or parameter estimation, at least for growth rate and lag time (Fig. 2B), where the replicate estimates for the wildtype show a similar negative correlation. -- The motivation to use a resource competition model for fitness inference is generally well motivated now. I accept their argument that resource competitive differences are most important for microbial strains with small genetic differences (e.g. from mutant libraries or from the same evolution experiment). However, it is relevant to note that this ignores situations that are rather common, where the wild-type strain produces an anticompetitor toxin or causes growth inhibition through metabolite products that lower the pH (and derived strains will likely contain resistant mutations).

Third, the study does not validate relative fitness predictions from growth traits (as is done for the yeast mutants) with measured relative fitness estimates using competition assays, while such data are available, e.g. for the LTEE. This would strengthen their inferences about preferred fitness measures. -- In their response, the authors explain that their aim was different, i.e. the provide "proof of principle" that the choices of fitness measure can produce discrepancies even when they follow the same growth model.

Fourth, the analysis of epistasis between mutations affecting different growth traits (shown in Fig. 3) based on the LTEE data could be better introduced and analysed more comprehensively. Now, the examples given in panels C-F seem rather idiosyncratic and readers may wonder how general these consequences of using fitness estimates based on different time scales are. -- The authors have made extensive improvements to address how different growth parameters, especially lag and growth rate, differently affect apparent epistasis based on measures at different time scale (per generation vs per cycle). These provide a more comprehensive analysis of down-stream consequences for epistasis detection.

Finally, the study is generally less accessible to experimentalists due to the extensive and principled treatment of specific population dynamic models and fitness inferences. This may distract from the overarching aim to identify fitness measures that are most accurate and useful for predictions of population dynamic and evolutionary processes. In this light, the motivation for the initial discussion of the importance of how to best encode relative abundance (Fig. 1) is unclear. Also, the conclusion, that logit encoding is preferred, because it linearizes logistic growth dynamics and "improves the quality of predictions", is not further motivated. Experimentalists using non-linear models to infer fitness from growth curves or competition assays may miss the relevance of this discussion. -- Thanks for this explanation (indeed, I confused "logistic dynamics" with "logistic growth model"); the additional explanations and text reductions have improved accessibility for experimentalists.

Comments on revisions:

I appreciate the thorough and effective response to all recommendations and have no further comments.

Reviewer #3 (Public review):

Summary:

In this manuscript, the authors investigated TBRS etiology by using new human pluripotent stem cell models, modeling varying levels of TBRS-associated loss of DNMT3A function. They identified increased lineage-specific proliferation of precursors in TBRS ventral MGE-like progenitors, which they propose was related to increased signaling through the PIK3/AKT/mTOR pathway. Furthermore, they show that reduced DNA methylation during MGE-like progenitor differentiation into GABAergic interneurons can cause a premature expression of neuronal and synaptic genes, triggering precocious neuronal maturation. In conclusion, they propose that TBRS-derived GABAergic neurons exhibit hyperactivity that can alters the development and structure of neuronal networks.

Strengths:

Overall, the data presented is convincing, from an early developmental point of view, given that the iPSC-derived 2D cultures or organoids used do not get to reach a mature state. Nonetheless, the data clearly show the effects that deleterious mutations in TBRS can cause during the period of neurogenesis, which was missing in the field.

Weaknesses:

(1) Li et al., 2022 (referred to in the manuscript) seems to already show the interplay between H3K27me3 and Dnmt3a discussed in this study i.e., that in the absence of DNA methylation, there is an expansion of polycomb-like repression. These data should be better acknowledged in the paragraph 'Repressive H3K27me3 compensates for severe loss of DNA methylation' (page 9), given it supports the data presented in this manuscript and suggests this as a common mechanism in the interplay between these two repressive marks, as it is well established in the literature.

(2) The authors should acknowledge that the omics data come from a mixed population of cells.

(3) The authors are encouraged to further discuss whether the overgrowth observed in ventral GABAergic cultures or organoids compares to the overgrowth observed in diseased patients. One expects MRIs to have been performed in patients and that these could be harnessed to discern if overgrowth occurs in the cortex or ventral regions of the brain.

Reviewer #3 (Public review):

Summary:

The authors noted a steep increase in the rate of growth with the onset of more frequent peristaltic-like movements and hypothesized that peristaltic activity rearranges the orientation of cell growth from circumferential to longitudinal. This study sought to alter peristalsis and then (1) carefully examine the growth of the chick cecum relative to the frequency of peristaltic-like movements and (2) examine the orientation of cells relative to the circumferential and longitudinal axes to determine whether peristalsis is required for cecum lengthening. To alter peristaltic-like movements, contraction was inhibited through treatment with nifedipine (a calcium channel blocker that acts to relax smooth muscle) or Ani9 (inhibits Ca-activated chloride channels), and contractions were induced through activation of a blue light-activatable channel rhodopsin 2 (introduced through electroporation).

Strengths:

(1) Use of multiple methods to alter peristalsis in initial studies.

(2) Live imaging.

(3) Careful measurements.

(4) Nicely presented figures.

Weaknesses:

(1) Only Nifedipine inhibition was examined for cell positional changes.

(2) Ki67 was not carefully analysed, and apoptosis was not shown at all.

(3) The results shown are suggestive of a role for peristalsis in the lengthening of the cecum. Demonstration that increased peristalsis could further increase lengthening would be helpful.

(4) The novelty of this work is incremental for the field in that the reagents used and the model of smooth muscle driving gut lengthening in mouse and chick small intestines have both previously been published. This manuscript does suggest that the role of smooth muscle in longitudinal growth may extend to other tubular organs (chick cecum).

Reviewer #3 (Public review):

This manuscript focuses on the presence/origin of directional memory during epithelial cell migration. It starts by analyzing single cells and then moves to more complex systems (confluent layers and scratch assays). The paper first demonstrates that the migration in all of these systems is well-described by persistent random walks, which likely emerge from fractional Brownian motion. This is an important demonstration, as it implies orientation memory in the systems. Then the paper proceeds to attempt to discern the origin of this memory and claims to establish key roles for adherens junctions and vinculin dimerization. While for the most part the manuscript is well-written, there are some significant overinterpretations in experimental results. The largest issue is demonstrating the role of vinculin dimerization, which is not a well-studied phenomenon inside living cells, as all data is reliant on a single point mutation (Y1065E). Additionally, the authors seem to be over-interpreting several of the assays; the statistical analysis does not seem to encompass all comparisons made, and the molecular model proposed does not clearly explain the observed results. The discussion could also be strengthened by considering other aspects of vinculin behavior (e.g., vinculin catch bonding) as well as discussing some other recent similar papers.

(1) Likely the most significant issue with the manuscript is the interpretation of the vinculin Y1065E variant and the assumption that the only defect the mutations cause is a lack of dimerization. Vinculin dimerization is mediated by a conformational change in the vinculin tail domain induced by F-actin binding (Thompson, FEBS Letters, 2013). Dimerization of the vinculin tail domain has been clearly demonstrated in in vitro systems involving purified proteins, as the authors point out in the manuscript. However, the dimerization of full-length vinculin has not been well characterised in living cells. There are several reasons to suspect dimerization is potentially not prevalent in cells. For instance, in the presence of other actin-binding proteins, there may not be sufficient binding sites available on neighboring actin filaments to facilitate dimerization. Additionally, pY1065 vinculin and vinculin Y1065E have been associated with increased vinculin activation (Huang, JBC, 2014), so other effects seem possible. While the Y1065E variant clearly has an effect on the tension sensor readout and vinculin dynamics, further experimental evidence is needed to show that these effects are due to a lack of dimerization in living cells. To justify the definitive claims made in the manuscript, the authors likely need to develop, or employ, an assay for detecting vinculin dimerization in living cells. The authors could choose between intermolecular FRET, proximity labeling assays (i.e., antibodies with DNA for signal amplification), bimolecular fluorescent complementation (i.e., split GFP) based approaches, or some other approach. It should be noted that working with full-length vinculin, not just Vt, and designing an assay that can incorporate vinculin Y1065 variants (Y1065E and potentially Y1065A/F) would strengthen results. Also, the authors should be aware that the observation of strong dimerization may invalidate the use of FRET-based tension sensors in this system or at least necessitate intermolecular FRET control experiments.

(2) The authors have seemed to assume that FRAP and adhesion stability are interchangeable. To this reviewer's knowledge, this is not the standard in the field. FRAP informs about molecular dynamics. Stability assays, which probe the spatial position of an entire focal adhesion over time (Zaidel-Bar, JCS, 2007, although other approaches are equally suitable), are typically used for assessing adhesion stability. If the authors wish to make strong claims about the stability of the adhesions, non-FRAP-based assays should be employed. Alternatively, the authors could interpret the FRAP data simply in terms of vinculin dynamics.

(3) A major conclusion in the manuscript is that in response to overexpression of a specific vinculin construct, focal adhesions behave the same in single cells, confluent cells, and collectively migrating cells for all the mutants but Y1065E. However, outside of the FRET measurements, there is not much evidence to support this claim. The authors should perform a greater comparison of the focal adhesions between the systems used in the manuscript (single cell, confluent cells, collectively migrating cells). Key measurements would include focal adhesion number per cell, focal adhesion size, focal adhesion orientation, vinculin dynamics (e.g., FRAP), focal adhesion stability, and some indicators of focal adhesion composition. For the last aspect, focusing on focal adhesion components that also have roles in adherens junctions, such as VASP, seems appropriate. Without such characterization, it is an overinterpretation to assume that focal adhesions are the same in each system and, therefore, effects are due to vinculin behavior in the adherens junctions.

(4) What is shown in Figure 3G is not clear. How are P/Po and alpha shown on different areas of the same plot?

(5) It seems that an insufficient statistical test was used in many experiments. There are comparisons being made between systems (cell migration speed, FRET index...) that are not directly compared in a statistical test. Statistical tests are limited to differences from control (over-expression of full-length vinculin), and consistent increases or decreases (not quantitative values) are taken as evidence of similarity across systems. It seems that a more rigorous and standard approach would be to use an ANOVA/MANOVA with a suitable post-hoc test to perform all of these.

(6) It is unclear how a lack of vinculin dimerization at adherences junctions perturbs epithelial migration, but the complete lack of vinculin tail, which can also not dimerize, does not. In other words, how can TL "have no other role in cell migration at confluence than those at FAs as in single cells." Notably, the authors do not include the tailless variation in the schematic model figures. These results should be included and explained.

Reviewer #3 (Public review):

Solyga, Zelechowski, and Keller present a concise report of an innovative study demonstrating clear visuomotor mismatch responses in ambulating humans, using a mobile EEG setup and virtual reality. Human subjects walked around a virtual corridor while EEGs were recorded. Occasionally, motion and visual flow were uncoupled, and this evoked a mismatch response that was strongest in occipitally placed electrodes and had a considerable signal to noise ratio. It was robust across participants and could not be explained by the visual stimulus alone.

This is an important extension of their prior work in mice, and represents an elegant translation of those previous findings to humans, where future work can inform theories of e.g. psychiatric diseases that are believed to involve disordered predictive processing. For the most part, the authors are appropriately circumspect in their interpretations and discussions of the implications. The paper in its current form represents an important addition to the literature.

The authors have included analyses of the auditory mismatch using temporal electrodes, referenced to Cz (and therefore should exhibit a mismatch positivity). This added data clearly and convincingly shows that the sensorimotor mismatch is, indeed, stronger than the passive auditory MMN.

- The reference electrode placed at Cz makes it is difficult to interpret relative differences between frontal and occipital electrode responses, as the occipital electrodes are placed farther away from the Cz reference than the frontal electrodes. Similarly, signal occuring cortically near the Cz reference might only appear as though it is occipitally distributed in this montage. It is common in EEG research to re-montage the data to an averaged common reference in order to better interpret the scalp distributions. As the electrode coverage was sparse for some subjects, this could be challenging, and this reviewer does not feel that it is necessary to do this analysis step, or even to drastically rewrite the body of the paper. We only request that some discussion, however brief, is included in the discussion section or the methods that recommend more dense electrode coverage in the future to better interpret scalp distributions and potential meso-scale sources.

- This is just a suggestion. The authors are encouraged to analyse (and report) time-frequency power and phase locking for these mismatch responses, as is common in much of the literature (see Roach et al 2008 Schizophrenia Bulletin). This is not to say that doing so will yield insights into oscillations per se, but converting the data to the time-frequency domain provides another perspective that has some advantages. fosters translations to rodent models, as ERP peaks do not map well between species, but e.g. delta-theta power does (see Lee et al 2018 Neuropsychopharmacology; Javitt et all 2018 Schizophrenia research; Gallimore et al 2023 Cereb Ctx). Further, ERP peaks can be influenced by the actual neuroanatomy of an individual (especially for quantifying V1 responses). Time frequency analyses may aid in interpreting the "early negative deflection with a peak latency of 48 ms " finding as well. As it stands, the report is complete, and it would be acceptable if the authors chose to save this type of analysis for a future publication.

Reviewer #3 (Public review):

Summary:

This valuable study presents a tool that uses brain anatomy to predict the layout and size of early visual maps, and it is strengthened by testing across a large and diverse collection of scans. The work will be useful for researchers who want to estimate likely visual map layout from standard anatomical scans and to relate anatomical differences to differences in visual organization across groups. The evidence is solid for the general usefulness of the approach, but incomplete for broader claims about prediction accuracy and use across datasets, particularly for estimates of map size and for showing that the model improves on repeated functional measurements.

Strengths:

The paper addresses a useful and important problem: estimating early visual map organization from anatomical measurements alone. Tools that predict these types of functional data from anatomical measurements were introduced more than a decade ago by Benson and colleagues, and the present authors have significantly extended that work. That is a real strength of the manuscript, because there is genuine value in having a practical tool that can estimate likely visual organization from standard anatomical scans.

Another major strength is the rigorous cross-dataset benchmarking and the accumulation of multiple datasets. The authors assembled a large and diverse set of scans and assessed model performance across different scanners, field strengths, and visual stimuli, which gives the reader a much better sense of how broadly the approach may apply. The retrospective analysis of more than 11,000 scans is especially notable and creates an unusual opportunity to ask how anatomical variation may relate to population differences in visual organization.

I also think the paper does a good job of showing why such a tool could matter in practice. A complete tool could be used in several ways. First, it could help users identify the locations of activations measured in other experiments with respect to the typical V1-V3 maps. Second, maps measured from an individual subject or patient could be compared with the predictions from the tool to ask whether they differ meaningfully from a standard anatomy-based map. Third, the tool can be used, as the authors have done here, to examine differences in anatomy across populations and interpret these differences with respect to retinotopic maps. Of these uses, the first already seems well supported by the current presentation.

Weaknesses:

(1) Quantification of the Analysis

My main concern is that the analysis relies heavily on global summary measures such as correlation and Dice score. Those measures are useful, but the paper would be more informative if it also quantified boundary differences in millimeters, especially for comparisons such as the V1/V2 boundary in Figure 2. That kind of analysis would help readers understand how large the errors are in physically meaningful terms.

(2) Model fitting methods

I also think the discussion of prediction failures for pRF size should be more explicit. The mismatch is likely influenced by the fact that the training data and several evaluation datasets were fit with different models and different analysis software. In particular, the network was trained on non-linear size estimates from the HCP data, while the comparison datasets were derived using other packages and, in some cases, different model assumptions. That likely contributes to the spread in Figure 3b and should be discussed more directly. It is important to discuss that the pRF parameters were derived using different software tools.

- HCP dataset (training data): analyzePRF (Compressive Spatial Summation model)

- NYU dataset: vistasoft

- Stanford dataset: vistasoft

- New Zealand dataset: SamSrf

- CHN dataset: Custom MATLAB software

(3) Clarifying Model Accuracy

If deepRetinotopy generates a true "noise-removed" representation of functional mapping based on anatomy, then fitting it to one fMRI measurement should predict a second, independent fMRI run better than the noisy data from the first run does.

The authors possess the exact data for this test. For the HCP dataset, the empirical fMRI data were explicitly separated into two halves: "fit 2" (the first half of the fMRI runs) and "fit 3" (the second half). They correlated these two halves to establish a "noise ceiling," the maximum possible reliability of the data. Looking at their results in Figure 2b, the correlation of the deepRetinotopy predictions falls below this noise ceiling. This means that the noisy functional Half 1 actually predicts functional Half 2 better than the anatomical model does.

The authors should state this explicitly. A side-by-side plot of Half 1 predicting Half 2 versus deepRetinotopy predicting Half 2 would show that the anatomical model regularizes map location well, but misses reliable subject-specific variation that anatomy alone cannot capture.

(4) The Hemodynamic Response Function

The assumptions used to generate the original empirical maps are permanently baked into the deep learning model. However, the authors explicitly mention the hemodynamic response function (HRF) only once, noting in the Methods that the modeled time series was "convolved with a canonical hemodynamic response function."

Beyond this single mention, there is no direct discussion of how the assumption of a single canonical HRF across all 161 HCP training subjects might have systematically impacted or biased the network's predictions. The authors address cross-dataset differences broadly under the umbrella of "experimental design" and "fMRI preprocessing pipeline" biases, but the HRF is a core biological property that mediates the connection between the anatomy and the data. The authors should explicitly discuss how this canonical assumption limits or biases the resulting deepRetinotopy network.

(5) Scoping the Input Data and Normative Use

The authors use FreeSurfer to generate a mean curvature map for the entire midthickness cortical surface. This full-hemisphere curvature map is resampled to a standard template surface space (32k_fs_LR), acting as the data frame that feeds input features into the neural network. However, while the network receives the full geometric structure of the hemisphere, it is explicitly trained to predict retinotopic parameters only within a restricted posterior ROI, based on the Wang et al. atlas and containing roughly 3,200 vertices per hemisphere.

A useful experiment to try, and perhaps the authors have already considered this, would be to restrict the input features exclusively to the posterior vertices. Including all anterior vertices may make it harder for the network to fit the localized visual data. A brief commentary on why the full hemisphere was retained as input could be highly informative for researchers adapting this geometric deep learning pipeline.

Reviewer #3 (Public review):

Summary:

This study examines how synaptic endocytic zones are positioned using a combination of cultured neurons and the Drosophila neuromuscular junction. The authors test whether neuronal activity, active zone assembly, or liprin-α function is required to localize endocytic zone markers, including Dynamin, Amphiphysin, Nervous Wreck, PIPK1γ, and AP-180. None of the manipulations tested caused a coordinated disruption in the localization or abundance of these markers, leading to the conclusion that endocytic zones form independently of synaptic activity and active zone scaffolds.

Strengths:

The work is systematic and carefully executed, using multiple manipulations and two complementary model systems. The authors consistently examine multiple molecular markers, strengthening the interpretation that endocytic zone positioning is robust to changes in activity and structural assembly.

Weaknesses:

The main limitation is that the study does not test whether the methods used are sensitive enough to detect subtle functional disruption, and no condition tested produces clear disorganization of the endocytic zone. As a result, the conclusion that these zones assemble independently is supported by negative data, without a strong positive control for disassembly or mislocalization.

This paper addresses a longstanding question in synaptic biology and provides a well-supported boundary on the types of mechanisms that are likely to govern endocytic zone localization. The conclusions are well justified by the data, though additional evidence would be needed to define the assembly mechanism itself.

Comments on revisions:

The authors responded to the initial review with care. They both revised the manuscript and conducted new experiments to address each reviewer's concern. The responses to the review were effective, and I think that the revised manuscript provides significant new insights. In my view, it does not require additional revisions.

Reviewer #3 (Public review):

Strengths:

The core strength of this study lies in its innovative demonstration that an engineered sACE2-Fc fusion redirects virus-decoy complexes to Fc-mediated phagocytosis and lysosomal clearance in macrophages, revealing a distinct antiviral mechanism beyond traditional neutralization. Its complete prophylactic protection in animal models and precise targeting of airway phagocytes establish a novel therapeutic paradigm against SARS-CoV-2 variants and future respiratory viruses.

Weaknesses:

The study attributes the complete antiviral protection to Fc-mediated phagocytic clearance, a central claim that requires more rigorous experimental validation. The observation that abrogating Fc functions compromises protection could be confounded by potential alterations in the protein's stability, half-life, or overall structure. To firmly establish this mechanism, it is crucial to include a control molecule with a mutated Fc region that lacks FcγR binding while preserving the Fc structure itself. Without this critical control, the conclusion that phagocytic clearance is the primary mechanism remains inadequately supported. The strategy of deliberately targeting virus-decoy complexes to phagocytes via Fc receptors inherently raises the question of Antibody-Dependent Enhancement (ADE) of disease. While the authors demonstrate a lack of productive infection in macrophages, this only addresses one facet of ADE. The risk of Fc-mediated exacerbation of inflammation (ADE) remains a critical concern. The manuscript would be significantly strengthened by a direct discussion of this risk and by including data, such as cytokine profiling from treated macrophages, to more comprehensively address the safety profile of this approach. The exclusive use of the K18-hACE2 mouse model, which exhibits severe disease, limits the generalizability of the findings. The "complete protection" observed may not translate to models with more robust and naturalistic immune responses or to human physiology. Furthermore, the lack of data against circulating SARS-CoV-2 variants of concern. The concept of sACE2-Fc fusion proteins as decoy receptors is not novel, and numerous similar constructs have been previously reported. The manuscript would benefit from a clearer demonstration of how the optimized B5-D3 mutant represents a significant advance over existing sACE2-Fc designs. A direct comparative analysis with previously published benchmarks, particularly in terms of neutralizing potency, Fc effector function strength, and in vivo efficacy, is necessary to establish the incremental value and novelty of this specific agent.

Comments on revised version:

The author has successfully addressed the raised issue.

Reviewer #3 (Public review):

Summary:

This is a clearly written paper that describes the reanalysis of data from a BXD study of the locomotor response to morphine and naloxone. The authors detect significant loci and an epistatic interaction between two of those loci. Single-cell data from outbred rats is used to investigate the interaction. The authors also use network methods and incorporate human data into their analysis.

Strengths:

One major strength of this work is the use of granular time-series data, enabling the identification of time-point-specific QTL. This allowed for the identification of an additional, distinct QTL (the Fgf12 locus) in this work compared to previously published analysis of these data, as well as the identification of an epistatic effect between Oprm1 (driving early stages of locomotor activation) and Fgf12 (driving later stages).

Reviewer #3 (Public review):

Summary:

This paper presents Recurrent Predictive Learning (RPL), a self-supervised model conceptually similar to Joint-Embedding Predictive Architecture (JEPA) models. RPL sequentially observes dynamic scenes to predict subsequent observations. A central claim of the work is that the model's trained representations are simultaneously invariant and equivariant to transformations, such as movement properties that emerge without explicit supervision. These representational qualities are demonstrated through three experiments utilizing two simulated datasets and one naturalistic dataset. Furthermore, the latent embeddings are qualitatively compared with neural data, showing that the model reproduces the successor representation observed in human V1 and the local/global oddball effect in the monkey Prefrontal Cortex.

Strengths:

(1) The paper addresses a fundamental question relevant to both computational neuroscience and machine vision: how the brain learns representations that are simultaneously invariant and equivariant to transformations. The manuscript is well-written, easy to follow, and supported by clear visualizations.

(2) While JEPA-style models have recently gained significant traction in the artificial intelligence community, this paper nicely bridges the gap to neuroscience. By framing these architectures as a theory for visual learning in the brain, the authors provide valuable insights into how predictive frameworks can explain cortical processing.

(3) The qualitative alignment with V1 and PFC data is a particularly strong contribution, as it offers a potential mechanistic explanation for observed neural phenomena through the lens of self-supervised learning.

Weaknesses:

(1) The central claim, that both invariance and equivariance emerge spontaneously, requires further scrutiny (see Ghaemi et al., NeurIPS, 2025; Garrido et al., arXive, 2024). In particular, the synthetic "moving animal" dataset used in this paper may be too simple to fully support this claim. In latent space prediction, a model must predict both the scene content and the dynamics of movement. Because movement (whether ego-motion or external) is often highly uncertain (or multi-modal), predictive models in naturalistic settings often "collapse" toward learning purely invariant representations, ignoring the hard-to-predict dynamics. In the provided simulations, the movements are extremely predictable. In more complex scenarios, the model would likely prioritize content (invariance) over dynamics (equivariance) unless aided by action-conditioning or explicit factor estimation (Zhang et al., ICLR, 2026). The authors' results in Figure 5 using naturalistic video seem to reflect this limitation, given the lower performance on the naturalistic videos compared to the synthetic datasets.

(2) The framing of the RPL model as an entirely new theory of representation learning is slightly overstated. The focus on prediction in representation space rather than input space is the defining characteristic of JEPA and various other Self-Supervised Learning (SSL) models, even sequential prediction. While this paper clarifies the connection between these AI frameworks and cortical circuits, the work would be strengthened by more explicitly positioning RPL within the context of existing JEPA-style models and prior SSL theories of the visual system.

(3) A significant challenge in latent-space SSL is avoiding "representational collapse" (where the model provides a trivial constant output). While the paper alludes to JEPA-like solutions, it lacks a detailed explanation (in both the text and the architectural schematics) of the specific technique used to prevent collapse. Consequently, it is difficult to evaluate the authors' claim of "biological plausibility," as the biological equivalents of common machine learning techniques (such as stop gradient) are not discussed.

(4) Recent work has shown that the capacity (size) of the predictor significantly influences the learned representations in a JEPA-type world model (Gorrido et al., 2024). In simpler scenarios, a large enough predictor can allow a model to "memorize" dynamics rather than learning generalized equivariant features. It would be beneficial to see how the ratio of predictor size to encoder size affects the emergence of these features.

Methodological Clarifications:

(1) The authors mention a contrastive learning comparison but provide few details. Since contrastive learning is primarily a technique to avoid collapse, it would be a more rigorous baseline if implemented within the same architecture as RPL to isolate the effect of the predictive objective.

(2) In the PFC data comparison (Figure 7f), there appears to be a discrepancy where the local and global conditions show nearly identical results in PFC, while different dynamics in the model. It is unclear if this is a visualization error or a genuine model deviation.

(3) The criteria for selecting specific model variables for comparison with V1 versus PFC are not explicitly defined. Clarification is needed on whether the same latent variables were used for both brain regions or if different layers were selected.

Reviewer #3 (Public review):

Summary:

Normandin et al. explore the coding of stimuli predicting an aversive event in the prelimbic cortex. Stimuli could either be explicitly paired, explicitly unpaired, or novel but with an inferred association with the aversive event (generalization). Long-term tracking of GCaMP-positive neurons allowed them to examine how coding evolves out to a month following training. In general, they found two types of ensemble codes. One was ensembles coding for each stimulus independently, but with enhanced responding to the one eliciting a freezing response. The other was ensembles that responded to all stimuli in proportion to their similarity to the stimulus paired with the aversive event, either increasing or decreasing their activation with the degree of freezing elicited by a stimulus. Importantly, this second set of ensembles was more stable across days, potentially providing a memory trace.

Strengths:

(1) The authors track ensembles in prelimbic cortex over long time scales, providing valuable information on the consolidation of neural codes.

(2) Neural coding of generalization is examined, which is under-examined in the field.

Weaknesses:

(1) Difficult to determine if responses treated as encoding stimulus valence are driven instead by the behavior that the stimulus elicits, freezing.

(2) The study implies that the identified ensembles are causally related to valence memory, but no experimental interventions are performed to justify this.

Reviewer #3 (Public review):

Summary:

In this manuscript, Fujita/Jo/Stewart/Osorno et al. investigate the contribution of Nav1.7 in regulating the excitability and firing properties of human dorsal root ganglion (hDRG) neurons in vitro. The authors characterize the effects of a previously reported Nav1.7-selective blocker AM-2099 in cultured hDRG neurons from postmortem organ donors. The authors observed modest changes in many of the properties expected by inhibiting Nav channels, including decreased action potential upstroke rate and amplitude, while increasing the voltage and current thresholds for spike generation. However, AM-2099 did not change the maximum number of APs in response to suprathreshold stimulation, leading the authors to conclude that Nav1.7 inhibition alone has limited efficacy in reducing the firing properties of hDRG neurons and that Nav1.7 blockers may have limited efficacy as analgesics. This is surprising, given that patients with loss-of-function mutations in Nav1.7 suffer from congenital insensitivity to pain. While it may indeed be true that pharmacological inhibition of Nav1.7 is unlikely to produce analgesia, the present study was limited to a single concentration of AM-2099. The manuscript would be significantly strengthened by a more careful and thorough pharmacological characterization of this compound, which has not been widely used or validated in native human DRG neurons.

Strengths:

Experiments are well-designed and executed, and the results presented are convincing. The focus on voltage-gated sodium channels in native human DRG neurons is highly relevant to recent efforts to develop safer analgesic options for chronic pain in people.

Weaknesses:

Only a single concentration of AM-2099 was used for all experiments. This compound was reported to be selective for cloned human Nav1.7 channels in heterologous systems, but has not been validated in other studies after the original publication in 2016. Since the original study reported a substantial state-dependent block of recombinant Nav1.7 channels, more detailed pharmacological characterization of AM-2099 is needed in human DRG neurons to fully support these claims. This study would be significantly strengthened by the inclusion of dose-response curves to assess how much of the sodium current is inhibited at this concentration, confirming selectivity in hDRG, and whether maximal inhibition of Nav1.7 still has limited efficacy in reducing the firing of native human sensory neurons.

Reviewer #3 (Public review):

Summary:

Human and animal trypanosomiasis are fatal illnesses caused by African trypanosomes transmitted by tsetse flies during a bloodmeal. Thus, tsetse fly feeding is the key physical step in disease transmission to mammals. Tsetse fly feeding is not a new story, but it is revisited here through the application of sophisticated imaging techniques and novel biomechanical methods of analysis. The authors aim to provide a high-resolution picture of the structures and forces involved in feeding to provide mechanistic insights into the process of feeding, from attachment, penetration, drinking and retraction of the feeding parts.

Largely, the authors have achieved their aims. They (i) examine the structures and forces involved in attachment; (ii) they provide detailed multi image analysis of the proboscis providing insights into its probing ability and physical mechanism of penetration; (iii) they conduct a controlled analysis of the physical forces involved in penetration and report that they are in the low nM range, not especially strong but much higher that the mosquito bite and finally they provide a first analysis of blood uptake during feeding.

Strengths:

The study images the tsetse fly feeding structures in unprecedented detail, with resolution to the uM scale, in 3-D, and during feeding. The resulting images are dramatic and insightful (and beautiful and frightening!), so researchers interested in trypanosomes, tsetse flies, or blood feeding by flies in general will want to see.

They conclude that flies attach strongly to smooth surfaces because of interactions possible via the array of acanthae of the pulvillus pad at the ends of the tarsi. The estimated attachment forces are similar in male & female flies, in the low mM range (they look impressively strong in video 1). They provide a very striking analysis of the proboscis and labellum and associated tooth structures (Figures 4 & 5). I recall many years ago observing that tsetse flies are messy feeders, and these structures, especially the rasping teeth structures on the reverse folded labial tips, explain why! This seems more like a chainsaw than a jigsaw in action, but the authors are probably correct that these structures and the probing/retraction mechanism explain many features of tsetse fly feeding and their ability to feed on a wide range of hosts with very different skin types.

The impressive aspect of this paper is the range of imaging techniques (CLSM, SEM, uCT, FIB SEM), the quality of the images, which attests to the obvious care taken with sample preparation. The biomechanical analysis, especially the penetration analysis, is impressive. Finally, the paper is clearly written and presented; it was a very easy read and, overall, a very engaging study.

Weaknesses:

I suppose it could be said that the paper is a descriptive study; it doesn't really test a hypothesis, but that is not a prerequisite for sharing it. Perhaps the least convincing parts are the imaging of the flexible versus rigid parts of the structures, which is based on the amount of resilin (flexible) and chitin-protein (stiff), based on their autofluorescence. It seems odd that the joints would be less blue (stiffer) in Figure 1i, or what the blue structures correspond to in Figure 6B-D.

Reviewer #3 (Public review):

Summary:

In this manuscript, Miyachi and Ichihashi investigate whether the arrangement of the genetic code affects mutational robustness. Using an in vitro minimal genetic code with vacant codons, they constructed 10 non-standard genetic codes by reassigning Ala, Ser, and Leu, generating codes with replacement costs that were generally higher than those of the standard genetic code across several amino acid property measures. They then tested how random mutations affected the activity of reporter proteins translated under these altered codes. Although error minimization theory predicts that higher-cost codes should make mutations more harmful, the authors report that protein function declined to a similar extent across all codes examined, suggesting that mutational robustness remains largely unchanged within the range of genetic code alterations tested here.

Strengths:

This is an interesting study that investigates one of the most fundamental and intriguing questions in molecular evolution: the emergence of the genetic code, which is nearly universal across nature. The in vitro approach is a powerful aspect of the work and provides an opportunity to examine this phenomenon experimentally at a depth that has previously been inaccessible.

Weaknesses:

However, the authors' use of random mutation libraries has certain limitations that prevent the study from realizing its full potential to uncover the mechanisms governing the molecular evolution of the genetic code.

Major points:

(1) Statistical analyses are missing for several of the manuscript's main claims. This issue applies throughout the paper, including, but not limited to, Figures 1D, 2B, 4B-D, and 5B.

(2) In Figure 2A, the authors modify the NanoLuc gene by reassigning Ala, Leu, or Ser to new codons and elegantly show that the in vitro availability of the corresponding tRNAs is important for protein function. However, the functional importance of the specific modified positions within NanoLuc is not clear. As a result, it is difficult to determine what the expected consequences of these codon changes should be, which in turn limits the interpretation of the observed changes in protein activity. To improve the interpretability of this experiment, the authors should report exactly how many codons were modified in each variant and, ideally, examine the effect of progressively increasing the number of reassigned codons.

(3) The calculations presented in Figure 3 raise an interesting conceptual question: why does the near-standard genetic code not exhibit the lowest cost? One possible explanation is that the standard genetic code evolved under multiple competing constraints and is therefore not expected to be optimal for any single cost metric, while still achieving strong overall performance. In this context, it would be informative if the authors combined the three cost measures into a single integrated index and examined whether the near-SGC performs more favorably when all three dimensions are considered together. Such an analysis could add important depth to the study.

(4) It is difficult to assess the consequences of the random mutations presented in Figure 4 on reporter gene function based solely on the reported "error rate/base" parameter. In particular, the x-axis in Figure 4B should be converted into the estimated number of mutations per gene. This would make the results more intuitive and would allow the reader to better evaluate the expected degree of disruption to protein function.

(5) A central limitation of the random mutagenesis libraries used in Figure 5, which also underlie one of the manuscript's main claims, is that the exact mutations and their distribution across the reporter genes are not reported. In addition, protein activity is measured only at the level of the entire library, without directly linking individual mutations to their functional consequences. This substantially limits mechanistic interpretation. In my view, this issue can only be addressed convincingly if the authors test a set of defined variants carrying specific mutations and directly evaluate their functional effects.

(6) Related to the previous point, in Figures 5C, 5E, and 5G, the authors present the ratio between low-mutation-rate and high-mutation-rate libraries. However, because each library contains a different collection of mutations, it is unclear what can be inferred from these comparisons. To overcome this limitation, the authors should assess the effects of altered genetic codes on specific, defined mutations rather than on heterogeneous mutation pools alone.

(7) Along the same lines, in Figures 5C, 5E, and 5G, it is unclear why the effects of random mutations would be expected to correlate with the three calculated cost metrics, given that the positions, identities, and functional relevance of the mutations within the genes are not known. Without this information, the biological meaning of these correlations remains difficult to evaluate.

(8) For each mutagenesis library, the number of variants, the average number of mutations per variant, and the distribution of mutation positions should be reported clearly and transparently. These details are important for evaluating the strength of the conclusions.

(9) Because only three amino acids were manipulated in the non-standard genetic codes, it remains unclear whether these particular amino acids occupy positions in the reporter proteins that are especially important for function and therefore likely to generate strong phenotypic effects. More broadly, it is not clear whether the assay is sufficiently sensitive to detect the effects of only a subset of deleterious variants within a pooled library. This point should be addressed more explicitly.

Reviewer #3 (Public review):

In this manuscript, Zatulovskiy and colleagues elaborate on their previous work describing cell size-dependent changes in the proteome by investigating whether these changes can be correlated in differences in cell physiology. Using a cleverly-designed high throughput screen, they searched for compounds that differently-sized cells display differential sensitivity towards. Their primary hit, Era2, is involved in the ferroptosis pathway and serves as the starting point for a detailed study of how excess cell size protects cells from ferroptosis-induced cell death via: 1) lower concentrations of ACSL4 (which produces peroxidation-prone PUFAs), 2) increased ferritin concentrations, and 3) increased GSH concentrations.

Overall, the experiments in this manuscript are well-designed and interpreted. It is an extremely well-written manuscript with a clear trajectory of logic.

Comments on the revised version:

The authors have addressed my original concerns adequately. I do not need to see it again, if there are further revisions.

Reviewer #3 (Public review):

Summary:

Eukaryotic gene transcription requires a large assemblage of protein complexes that govern the molecular events required for RNA Polymerase II to produce mRNAs. One of these complexes, TFIIH, comprises two modules, one of which promotes DNA unwinding at promoters, while the other contains a kinase (Kin28 in yeast) that phosphorylates the repeated motif at the C-terminal domain (CTD) of the largest subunit of Pol II. Kin28 phosphorylation of Ser5 in the YSPTSPS motif of the CTD is normally highly localized at promoter regions, and marks the beginning of a cycle of phosphorylation events and accompanying protein association with the CTD during the transition from initiation to elongation.

The two modules of TFIIH are linked by Tfb3. Tfb3 consists of two globular regions, an N-terminal domain that contacts the Core module of TFIIH and a C-terminal domain that contacts the kinase module, connected by a linker. In this paper, Giordano et al. test the role of Tfb3 as a connector between the two modules of TFIIH in yeast. They show that while no or very slow growth occurs if only the C-terminal or N-terminal region of Tfb3 is present, near normal growth is observed when the two unlinked regions are expressed. Consistent with this result, the separate domains are shown to interact with the two distinct TFIIH modules. ChIP experiments show that the Core module of TFIIH maintains its localization at gene promoters when the Tfb3 domains are separated, while localization of the kinase module, and of Ser5 phosphorylation on the CTD of Pol II, is disrupted. Finally, the authors examine the effect of separating the Tfb3 domains on another function of TFIIH, namely nucleotide excision repair, and find little or no effect when only the N-terminal region of Tfb3 or the two unlinked domains are present.

Strengths:

Experiments involving expression of Tfb3 domains in yeast are well-controlled and the data regarding viability, interaction of the separate Tfb3 domains with TFIIH modules, genome-wide localization of the TFIIH modules and of phosphorylated Ser5 CTDs, and of effects on NER, are convincing. The experiments are consistent with current models of TFIIH structure and function and support a model in which Tfb3 tethers the kinase module of TFIIH close to initiation sites to prevent its promiscuous action on elongating Pol II.

Reviewer #3 (Public review):

Summary:

In this study, authors Simone Rencken and co-authors present and investigate the genome of the common cuttlefish Sepia officinalis.

Strengths:

The authors explain in a detailed yet concise manner the main steps for a genome assembly, with very robust methods for validation, and according to current best practices. In addition to the chromosomal assembly, the authors confirmed the presence of 47 chromosomes using Hi-C data and multiple species synteny. They also generated a comprehensive gene annotation, with assessments of gene completeness, providing a useful resource for the community of researchers interested in cuttlefish biology and comparative genomics.

Reviewer #3 (Public review):

Summary:

Alonso-Caraballo et al. use behavioral testing and ex vivo patch-clamp electrophysiology combined with circuit-specific optogenetic stimulation of PVT terminals to examine how oxycodone self-administration and abstinence duration shape cue-induced relapse and PVT-NAcSh synaptic transmission in male and female rats. In the revision, the authors reanalyzed intrinsic excitability using nested hierarchical GLMMs, acknowledged the low power in the male prolonged-abstinence group, and expanded the discussion of relevant PVT-NAc literature. These changes improve the manuscript. That said, most of the revisions are textual and the main experimental gap remains. Both sexes show increased oxycodone seeking compared to saline at 14 days, but only females show a time-dependent incubation from 1 to 14 days, and the PVT-NAcSh synaptic strengthening is the same in both sexes. Nothing in the revision brings those two observations closer together. The excitability data also come from NAcSh MSNs with no confirmation of PVT connectivity, which limits what circuit-specific conclusions can be drawn. The study is a solid characterization of abstinence-related synaptic changes in this pathway, but some of the conclusions still go further than the data allow.

Strengths:

The behavioral characterization is thorough and well-executed, covering self-administration, somatic withdrawal, and cue-induced relapse across two abstinence durations in both sexes. The sex-specific escalation in oxycodone seeking from 1 to 14 days in females but not males is a clear and compelling finding. The use of circuit-specific ex vivo optogenetics to isolate PVT terminal inputs onto NAcSh neurons is a genuine methodological strength, and the demonstration of feedforward inhibitory recruitment through local GABAergic interneurons adds meaningful novelty to the circuit characterization. The reanalysis of intrinsic excitability using nested hierarchical GLMMs appropriately accounts for the non-independence of cells recorded within the same animal and is a real improvement over the original approach. The expanded discussion of prior PVT-NAc work, particularly the more accurate treatment of Keyes et al. (2020) and Paniccia et al. (2024), better situates the findings within the existing literature.

Weaknesses:

The core limitation of the study remains unchanged after revision. The PVT-NAcSh synaptic strengthening after prolonged abstinence is statistically indistinguishable between sexes, while females but not males show a time-dependent escalation in oxycodone seeking from 1 to 14 days of abstinence. The Discussion proposes hormonal modulation or differences in upstream inputs as possible explanations, but none of these are tested and the gap is left unresolved. The intrinsic excitability recordings come from NAcSh MSNs with no confirmation that those neurons receive direct PVT input, which was raised in the original review, acknowledged in the revision, and not experimentally addressed. The male prolonged-abstinence excitability trend has approximately 20% statistical power and is non-significant, yet the Discussion interprets it as a potential neuroadaptation that could facilitate signal flow through the PVT-NAcSh circuit and contribute to relapse, which goes well beyond what the data support. The failure to distinguish between D1 and D2 MSNs remains a significant limitation given that cell-type-specific plasticity at PVT-NAc synapses has been shown to be directly relevant to opioid seeking in prior work. Finally, the Conclusion builds a mechanistic framework around D2 MSNs, PV interneurons, and D1 MSNs that is drawn from studies using different drugs or experimental designs, and none of these cell-type-specific mechanisms are tested in the present experiments.

Reviewer #3 (Public review):

Summary:

In this manuscript, the authors investigate the role of the KH and RING domain-containing protein Mex3a in the differentiation and maturation of olfactory sensory neurons. Using conditional knockout of Mex3a in immature neurons, they show that mature olfactory sensory neurons display defects in membrane protein trafficking, including olfactory receptors and Adcy3, together with abnormalities in ciliary radial organization and planar cell polarity. Through single-cell RNA sequencing and quantitative proteomics, the authors further show that Mex3a-deficient neurons fail to properly resolve the unfolded protein response and exhibit transcriptomic features suggestive of lineage mixing with sustentacular cells. The study also introduces a methodological advance by adapting HyperTRIBE for use in transgenic mice, which enables the identification of in vivo Mex3a RNA targets, including components of Wnt signaling that appear to be under translational repression by Mex3a. The authors then pursue one of these targets to further explore the role of Mex3a in translational repression.

Strengths:

First, it addresses an important biological and conceptual question. Mex3a is a multifunctional protein with the potential to couple RNA regulation, protein homeostasis, and key cellular processes, yet its in vivo role in neuronal differentiation remains poorly understood. By focusing on Mex3a in olfactory sensory neurons, the manuscript asks a timely and important question of how post-transcriptional regulation contributes to the maturation of highly specialized neurons, including the establishment of ciliary architecture, membrane protein trafficking, and cell polarity. Second, the generation and validation of an inducible in vivo mouse HyperTRIBE system represents a technical advance. By incorporating the Adar deaminase domain into a transgenic mouse model, the authors establish a rigorous and useful approach for identifying Mex3a RNA targets in vivo, which is likely to be valuable to the wider RNA biology community. Third, the study integrates the Mex3a knockout model with single-cell RNA sequencing, quantitative mass spectrometry-based proteomics, ubiquitin profiling, and ribosome-related analyses, providing a broad and multilayered view of the Mex3a knockout phenotype. Finally, the imaging analyses revealing altered ciliary content and organization in olfactory sensory neurons identify an interesting and potentially important link between Mex3a, cilia biology, and vesicular trafficking. More broadly, the manuscript reflects a very substantial experimental effort, and each individual dataset has the potential to be useful for the field.

Weaknesses:

A main weakness of the manuscript is that the mechanistic links between the major findings remain somewhat correlative, and the biological narrative is not fully sustained through the later figures. The study documents defects in membrane trafficking, ciliary radial organization, and planar cell polarity, and it identifies candidate targets with clear relevance to these processes, including factors linked to vesicle trafficking. However, the manuscript then shifts its mechanistic focus toward translational regulators such as Serbp1 and Rps7, without adequately connecting these later analyses back to the core phenotypes established earlier. As a result, there is a noticeable disconnect between the phenotypic emphasis of the study and the mechanistic validation that follows.

A second weakness is that, given the breadth and potential importance of the datasets generated, validation remains limited for several of the major conclusions. This reduces confidence in the interpretation of the single-cell, proteomic, ubiquitin-related, and ribosome-associated analyses, and also limits the future value of these datasets as a resource for the field. Because the manuscript aims to address several major questions at once, stronger validation and clearer integration across the different experimental arms are needed for the conclusions to feel fully supported.

Finally, the HEK293T overexpression experiments are less solid than the in vivo analyses and do not provide equally strong support for the proposed mechanisms. In this context, some of the observed effects on cytoskeletal organization, membrane-less granule formation, and ribosome profiles may be indirect, which makes it difficult to weigh these findings alongside the much stronger in vivo phenotypes.

Reviewer #3 (Public review):

Summary:

This manuscript describes a web-based tool that allows researchers to compare large numbers of representative ("plausible") conformations of proteins. It also includes energetic analysis from multiple widely used structure-prediction methods.

Strengths:

This tool will likely be useful for students who want to learn more about the ensemble properties of proteins. The resource is well organized and it represents a large amount of computing resources.

Weaknesses:

It is not entirely clear how the database may be utilized by other groups to advance research. It could be helpful if the authors add a short section that provides example use cases that illustrate how this database can support new strategies for studying protein dynamics.

Reviewer #3 (Public review):

Summary:

The authors address the possibility that platelet (PLT) derived EVs are important mediators of acute liver injury. Furthermore, KCs are important mediators of inflammation and are noted to need to undergo metabolic reprogramming to achieve their effects during injury. They use an APAP-induced liver injury model (AILI). They show that PLTs are recruited and that they interact with KCs in this model system. RNA-seq of KCs showed upregulation of glycolysis and gluconeogenesis. PLT depletion led to reduced liver injury. RNA-seq of KCs showed downregulation of glycolysis. In vitro co-culture of KCs and pets recapitulated the glycolysis findings. In vivo, 2DG inhibited liver injury, but not in the setting of KC depletion. They went on to show that PLT-derived EVs mediate this effect on KCs using a mix of in vitro and in vivo assays, although control EVs were lacking. After doing mass spec on EVs, they find that ALDOA is the critical payload of the PEVs that mediates the pro-glycolytic effect in vivo. They both delete ALDOA from PLTs, and they use an ALDOA inhibitor to show that injury in AILI requires ALDOA.

Strengths:

This is generally an interesting series of observations with an elegant mechanism. Many of the experiments are done in vivo with highly rigorous KO models. However, in many of the EV experiments, there are concerns about a lack of appropriate controls that might limit the rigor of those aspects of the study. 

Weaknesses:

(1) There is strong variability in the gene expression between mice in Figure 1B. I worry that the signals may not be statistically significant. The authors should assess the statistical significance.

(2) In Figure 2B, the necrosis areas that are circled in the image do not seem to resemble the quantitation on the right. For example, I don't see 60% necrosis in the APAP PBS group. Also, I don't see 5-10% necrosis in the CLDN APAP group. More images that are clearer are needed, and circled necrosis areas should be shown.

(3) In Figure 2D, a higher N should be shown. The number of mice (3) is different from the other experiments, so the exclusion of those mice should be explained.

(4) In general, control EVs from a non-PLT source should be used for all EV-related experiments. EVs derived from AML12 hepatocytes would seem to be a reasonable control for some of the experiments. Otherwise, it is hard to know if this is a general EV effect or one that is specific to PLT-derived EVs. In Figure 3B, EVs from non-PLTs should be used as a control. Since it is possible that all EVs express some level of TSG101 or CD63. In addition, control EVs should be used to test effects on KC metabolism, since the claim is that the effects are specific to PLT-derived EVs. Similarly, Figure 4 needs some kind of EV control that is not from PLTs.

(5) Figure 5B should include an EV control in the blot. Most of the blots need controls from AML12 EVs or from another in vivo source.

(6) It is a little difficult to imagine how enough ALDOA protein could be transmitted from PEVs to influence KC glycolysis on the gene expression level. It is possible that ALDOA is required for PLT-induced activation of KCs, or that EVs from PLTs can induce a metabolic shift in KCs. However, it has not been definitively shown that ALDOA from PEVs is directly causing the KC activation. Ultimately, it would be good to obtain PEVs from ALDOA WT and KO mice, then provide these PEVs to AILI mice without PLTs to see if they have differential effects on the AILI model. This would really demonstrate that the ALDOA in the PEVs is mediating the glycolytic, injurious effect.

Reviewer #3 (Public review):

Summary:

This manuscript by Kim and Parsons presents an overview of the nitroreductase/metronidazole (NTR/MTZ) cell ablation system.

Strengths:

This manuscript nicely places the NTR/MTZ system in context of other cell ablation methods, with a discussion of their respective advantages and disadvantages. This review is particularly useful for highlighting the many ways the NTR/MTZ system has been applied to study regeneration of multiple cell types and to model different degenerative human diseases. The review concludes with a discussion on recent improvements made to the system and practical considerations and "best practices" for NTR-based experiments. This review could be a helpful resource, especially for researchers new to regeneration or cell ablation studies.

Comments on revised version:

I thank the reviewers for revising the manuscript to expand their discussion of using the prodrug/NTR system in other model organisms while also revising the abstract to make it clear this review will be zebrafish focused. With these revisions, this review provides an informative overview of how the prodrug/NTR system has not only been an important tool for regeneration studies and but also for elevating the zebrafish as a regeneration model. That said, including other model organisms could have been a nice addition to the last section on experimental considerations, especially in the context of discussing potential barriers to wider adoption of the NTR system. However, given that the vast majority of studies using the NTR system are in zebrafish, the current scope of this review is understandable.

Reviewer #3 (Public review):

Summary:

The authors proposed to use 5-layer systems level analysis (genomics, transcriptomics, proteomics / protein degradation, metabolomics, phosphoproteomics) to uncover how post-transcriptional mechanisms regulate stage differentiation in Leishmania donovani.<br /> This enabled the identification of several potential regulatory networks, including the regulation of stage-specific gene clusters by RNA stabilisation or decay, proteasomal degradation and protein phosphorylation.

In the new version of this manuscript, the authors have addressed all questions raised by the reviewers.

Strengths:

Although some observations in this study have already been described in the literature, the integrated analysis applied here provides a novel view on how different levels of post-transcriptional networks regulate Leishmania differentiation. This "5-layer system" represents the first analysis of this depth in kinetoplastid parasites.<br /> The revised version with an increased sample number for the RNA-seq now made the authors assumptions adequate to their obtained data.<br /> The use of a proteasomal inhibitor adds an interesting insight in how protein degradation is involved in the parasite differentiation, confirming previous observations in the literature, and help to explain the discrepancies between mRNA and protein expression in the different stages.

Weaknesses:

While this work provides an impressive and foundational dataset, it opens the door for future research to rigorously validate these initial findings and conclusions.

Significance and Impact in the field.

The different datasets generated in this study will be of great interest to the parasitology community, either to be used for hypothesis generation, to validate data from other sources, etc.

The multi-layered analysis performed here identified a series of potential feedback loops and regulatory networks to be further explored in organisms that lack transcriptional control.

Reviewer #3 (Public review):

Summary:

MICOS is a conserved mitochondrial protein complex responsible for organising the mitochondrial inner membrane and the maintenance of cristae junctions. This study sheds first light on the role of two MICOS subunits (Mic60 and the newly annotated Mic19) in the malaria parasite Plasmodium falciparum, which forms cristae de novo during sexual development, as demonstrated by EM of thin section and electron tomography. By generating knockout lines (including a double knockout), the authors demonstrate that knockout of both MICOS subunits leads to defects in cristae morphology and a partial loss of cristae junctions. With a formidable set of parasitological assays, the authors show that despite the metabolically important role of mitochondria for gametocytes, the knockout lines can progress through the life stages and form sporozoites, albeit with diminished infection efficiency.

Major comments (from the previous round of review):

(1) The authors should improve to present their findings in the right context, in particular by:

(i) giving a clearer description in the introduction of what is already known about the role of MICOS. This starts in the introduction, where one main finding is missing: loss of MICOS leads to loss of cristae junctions and the detachment of cristae membranes, which are nevertheless formed, but become membrane vesicles. This needs to be clearly stated in the introduction to allow the reader to understand the consistency of the authors' findings in P. falciparum with previous reports in the literature.

(ii) at the end to the introduction, the motivating hypothesis is formulated ad hoc "conclusive evidence about its involvement in the initial formation of cristae is still lacking" (line 83). If there is evidence in the literature that MICOS is strictly required for cristae formation in any organism, then this should be explained, because the bona fide role of MICOS is maintenance of cristae junctions (the hypothesis is still plausible and its testing important).

(2) Line 96-97: "Interestingly, PfMIC60 is much larger than the human MICOS counterpart, with a large, poorly predicted N-terminal extension." This statement is lacking a reference and presumably refers to annotated ORFs. The authors should clarify if the true N-terminus is definitely known - a 120kDa size is shown for the P. falciparum, but this is not compared to the expected length or the size in S. cerevisiae.

(3) lines 244-245: "Furthermore, our data indicates the effect size increases with simultaneous ablation of both proteins?". The authors should explain which data they are referring to, as some of the data in Figs 3 and 4 look similar and all significance tests relate to the wild type, not between the different mutants, so it is not clear if any overserved differences are significant. The authors repeat this claim in the discussion in lines 368-369 without referring to a specific significance test. This needs to be clarified.

(4) lines 304-306: "Though well established as the cristae organizing system, the role of MICOS in initial formation of cristae remains hidden in model organisms that constitutively display cristae.". This sentence is misleading since even in organisms that display numerous cristae throughout their life cycle, new cristae are being formed as the cells proliferate. Thus, failure to produce cristae in MICOS knockout lines would have been observable but has apparently not been reported in the literature. Thus, the concerted process in P. falciparum makes it a great model organism, but not fundamentally different to what has been studied before in other organisms.

(5) lines 373-378. "where ablation of just MIC60 is sufficient to deplete functionality of the entire MICOS (11, 15),". The authors' claim appears to be contrary to what is actually stated in ref 15, which they cite:

"MICOS subunits have non-redundant functions as the absence of both MICOS subcomplexes results in more severe morphological and respiratory growth defects than deletion of single MICOS subunits or subcomplexes."

This seems in line with what the authors show, rather than "different".

(6) lines 380-385: "... thus suggesting that membrane invaginations still arise but are not properly arranged in these knockout lines. This suggests that MICOS either isn't fully depleted,...". These conclusions are incompatible with findings from ref. 15, which the authors cite. In that study, the authors generated a ∆MICOS line which still forms membrane invaginations, showing that MICOS is not required at all for this process in yeast. Hence the authors' implication that MICOS needs to be fully depleted before membrane invaginations cease to occur is not supported by the literature.

(7) The authors should consider if the first part of their title could be seen as misleading: It suggests that MICOS is "the architect" in cristae formation, but this is not consistent with the literature nor their own findings.

Significance:

The main strength of the study is that it provides the first characterisation of the MICOS complex in P. falciparum, a human parasite in which the mitochondrion has been shown to be a drug target. Mic60 and the newly annotated Mic19 are confirmed to be essential for proper cristae formation and morphology, as well as overall mitochondrial morphology. Furthermore, the mutant lines are characterised for their ability to complete the parasite life cycle and defects in infection effectivity are observed. This work is an important first step for deciphering the role of MICOS in the malaria parasite and the composition and function of this complex in this organism.

The limitation of the study stems from what is already known about MICOS and its subunits in other organisms. MICOS subunit knockouts have been characterised in great detail in yeast and humans with similar findings regarding loss of cristae and cristae defects. The findings of this study do not provide dramatic new insight on MICOS function or go substantially beyond the vast existing literature in terms of the extent of the study, which focuses on parasitological assays and morphological analysis.

Exploring the role of MICOS in an early-divergent organism and human parasite is however important given the divergence found in mitochondrial biology and P. falciparum is a uniquely suited model system. One aspect that would increase the impact of the paper would be if the authors could mechanistically link the observed morphological defects to the decreased infection efficiency, e.g. by probing effects on mitochondrial function. This will likely be challenging as the morphological defects are diverse and the fitness defects appear moderate/mild.

The advance presented in this study is to pioneer the study of MICOS in P. falciparum, thus widening our understanding of the role of this complex to different model organism. This study will likely be mainly of interest for specialised audiences such as basic research parasitologists and mitochondrial biologists. My own field of expertise is mitochondrial biology and structural biology.

Comments on revised version:

The authors have addressed my all of my previous comments in the updated manuscript version.

Reviewer #4 (Public review):

Summary and background:

This report entitled "The insulin/IGF axis is critically important (for) controlling gene transcription in the podocyte" from Hurcombe et al is based on a mouse double knockdown of the IR and IGF1R and a parallel cultured mouse podocyte model. Insulin/IGF signaling system in mammals evolved as three gene reduplicated peptides (insulin, IGF-1, and IGF-2) and their two receptors IR and IGF1R that cross-react to variable extents with the peptides, are ubiquitously expressed, and signal through parallel pathways. The major downstream effect of insulin is to regulate glucose uptake and metabolism, while that of the IGF pathways is to regulate growth and cell cycling in part through mTORC1. The GH-IGF-1-IGF1R pathway regulates post-natal growth. IGF-2 signaling is thought to play a major role in regulating intrauterine growth and development, although IGF-2 is also present at high levels in post-natal life. Thus, one would anticipate that reducing IR/IGF1R signaling in any cell would slow growth and cell cycling by reducing growth factor and metabolic mTORC1-mediated and other processes including the splicing of RNA for protein synthesis.

Comments on revised version:

The second sentence of the Summary reads "This study sought to elucidate the compound role of the insulin/IGF1 axis in podocytes using transgenic mice and cell culture models deficient in both receptors." The study design and rationale for the proteosome analysis described is predicated on the finding that podocyte-specific knockdown of the IR/IGF-1R in mice is associated with development of proteinuria and reduced eGFR by 20months of life. Since the IR/IGF-1R are critically required for normal development and growth of all cells and organs, the obvious explanation for the observation would be that the model system results in defective podocyte development and deployment (caused by reduced IR/IGF-1) that, in turn, causes subsequent development of proteinuria and glomerulosclerosis (that may be much less dependent on a normal level of IR/IGF-1R expression). Thus, the experimental design does not allow a distinction between podocyte development and steady state function which are different biologic processes. The data provided does not examine podocyte status immediately after birth to confirm that podocyte number and size and structure is normal in mice that subsequently develop proteinuria and glomerulosclerosis. The response to the reviewer suggests that since this would require additional mice it has not been undertaken in order to reduce animal usage. This is not a valid argument, particularly when the investigators have not even used state-of-the-art methods to measure podocyte number, size and density in adult mice, key parameters that would be required to interpret their data. Counting podocyte nuclear number in glomerular cross-sections is simply an inadequate method, even if it is used and reported in other journals, and particularly where the examples given to justify its use can hardly be viewed as representing first rate science.

If the absence of studies that would answer the above questions, the investigators should add a sentence to the Discussion dealing with study limitations as follows. "The study design does not allow us to determine whether the primary effect of reduced IR/IGF-1R expression on the phenotype is during in utero and post-natal podocyte development and deployment, during periods of rapid growth when IGF-1 levels are highest, in steady state adult podocytes, or under all of the above conditions".

Reviewer #3 (Public review):

Summary:

This study looked at slow changes in neuronal activity (on the order of minutes to hours) in the superior colliculus (SC) and prefrontal cortex (PFC) of two monkeys. They found that SC activity shows slow drift in neuronal activity like in the cortex. They then computed a motor index in SC neurons. By definition, this index is low if the neuron has stronger visual responses than motor response, and it is high if the neuron has weaker visual responses and stronger motor responses. The authors found that the slow drift in neuronal activity was more prevalent in the low motor index SC neurons and less prevalent in the high motor index neurons. In addition, the authors measured pupil diameter and found it to correlate with slow drifts in neuronal activity, but only in the neurons with lower motor index of the SC. They concluded that arousal signals affecting slow drifts in neuronal modulations are brain-wide. They also concluded that these signals are not present in the deepest SC layers, and they interpreted this to mean that this minimizes the impact of arousal on unwanted eye movements.

Strengths:

The paper is clear and well-written.

Showing slow drifts in the SC activity is important to demonstrate that cortical slow drifts could be brain-wide.

Weaknesses:

The authors find that the SC cells with the low motor index are modulated by pupil diameter. However, this could be independent of an "arousal signal". These cells have substantial visual sensitivity. If the pupil diameter changes, then their activity should be influenced since the monkey is watching a luminous display. So, in this regard, the fact that they do not see "an arousal signal" in the most motor neurons (through the pupil diameter analyses) is not evidence that the arousal signal is filtered out from the motor neurons. It could simply be that these neurons simply do not get affected by the pupil diameter because they do not have visual sensitivity.

Comments on revisions:

The authors have given due consideration to the possibility that SC signaling of arousal could be at least in part due to changes in pupil size related responses to ambient light. Discussion of this point in the most recent revision helps to mitigate this concern.

Reviewer #3 (Public review):

Summary:

This paper explores how spatial attention affects foveal information processing across different spatial frequencies. The results indicate that exogenously directed attention enhances contrast sensitivity for low- to mid-range spatial frequencies (4-8 CPD), with no significant benefits for higher spatial frequencies (12-20 CPD). However, asymptotic performance increased as a result of spatial attention independently of spatial frequency.

Strengths:

The strengths of this article lie in its methodological approach, which combines a psychophysical experiment with precise control over the information presented in the foveola.

Weaknesses:

The authors acknowledge that they used the standard approach of analyzing observer-averaged data, but recognize that this method has limitations: it ignores the uncertainty associated with parameter estimates and the relationships between different parameters of the psychometric model. This may affect the interpretation of attentional effects. In the future, mixed-effects models at the trial level could overcome these limitations.

Reviewer #3 (Public review):

Summary:

The authors report that tracheal terminal cells (TTCs) in Drosophila do not activate innate immunity following bacterial infection, and attribute this to the absence of PGRP-LCx expression in these cells. Forced activation of the Imd pathway in TTCs leads to JNK-mediated cell death and reduced tracheal branching. The authors propose that this immune-privileged status preserves Foxo-dependent structural plasticity, which is essential for TTCs to respond to changing environmental conditions such as hypoxia.

Strengths:

The revised manuscript represents a meaningful improvement over the initial submission. The addition of multiple antimicrobial peptide reporters substantially strengthens the key observation that TTCs do not mount a humoral immune response upon infection, moving beyond reliance on the Drs-GFP reporter alone. The mechanistic dissection of the cell death pathway - demonstrating roles for JNK, AP-1, and Foxo downstream of ectopic PGRP-LCx activation - is well-executed and provides solid mechanistic insight. The inclusion of a second, independent UAS-PGRP-LCx line with a milder phenotype adds useful calibration. The hypoxia sensitivity assays provide physiological context, and the discussion of the gradient hypothesis, while based on qualitative observation, is logically reasoned and addresses a legitimate alternative interpretation.

Weaknesses:

The primary remaining concern is that the absence of PGRP-LCx expression in TTCs is supported by a single GAL4 enhancer trap line, without independent validation by complementary methods such as in situ hybridization, antibody staining, or reanalysis of publicly available single-cell transcriptomic data. The authors acknowledge this limitation transparently. While the convergent evidence from infection experiments - in which neither the Drs-GFP reporter nor the PGRP-LCx-Gal4 line shows TTC activation - lends indirect support, orthogonal confirmation would more definitively establish this mechanistic claim.

Additionally, the finding that Dcp-1 cleavage occurs in non-TTC tracheal cells as well suggests that Imd-mediated apoptotic signaling is not uniquely restricted to TTCs, and the Discussion could more explicitly address what distinguishes the TTC response in terms of degree or cellular context.

Reviewer #5 (Public review):

Summary:

The authors have extensively characterized the response of the leucine and pantothenate auxotroph Mtb strain H37Rv mc26 206 to an FDA-approved compound library and identified semapimod that is, at best, bacteriostatic in its action against the pathogen. The authors have used transcriptional profiling, metabolite quantification and a screening of genetically-resistant mutants to identify changes in leucine uptake under semapimod exposure. Based on these data, the authors attribute changes in antibiotic susceptibility to differences in environmental leucine availability and bacterial PDIM architecture. While the work presents an interesting avenue of investigation of metabolite uptake and utilization in a comparative fashion between fully virulent and auxotroph Mtb strains, it lacks clear and direct evidence to link the observations with a mechanistic explanation.

Strengths:

The authors used a well-designed screening strategy for FDA-approved compounds against a metabolically defined strain and follow up characterization of semapimod exposure through RNA-seq and pathway analysis, metabolomics and time-course analysis of drug effects. The data has been interestingly interpreted to identify a phenotypic connection between PDIM and altered drug susceptibility.

Weaknesses:

The major gap in the study is the speculative nature of the mechanism underpinning the connection between PDIM architecture and changes in leucine uptake under various bacterial growth conditions.

(1) Despite claims of identifying a "novel leucine uptake mechanism", the authors only provide endpoint metabolite measurements rather than kinetic leucine transport studies.

(2) A clear explanation for the differences in susceptibility between auxotroph and fully virulent Mtb strains through changes in "PDIM architecture" is not supported by any direct evidence such as structural analysis, lipidomics, or direct measurement of PDIM architectural changes.

(3) The figures 1D (lines 110-112, "kills bacteria") and 7c (lines 283-285) are used to infer a bactericidal role of semapimod, which maybe a mischaracterization of drug activity. The trend in CFUs in both cases seems of no bacterial growth rather than a CFU reduction- therefore interpreted as "bacteriostatic" at best. These observations would in fact align with the general antibiotic/stress response signature identified by RNA-seq, where leucine transport related genes only happen to be a small subset of many dysregulated genes. How do the authors disentangle these generic signatures from the leucine transport evidence, other than endpoint metabolite quantification?

(4) Furthermore, the studies with supplementation of leuCD (and not panCD) in rescuing from semapimod susceptibility are not supported by a clear mechanistic link. The complementation of leuCD does not completely rescue growth- does this indicate differences in uptake and metabolism? The authors should test this by monitroing the growth of the strains in minimal medium in presence and absence of exogenous leucine.

(5) It remains unclear if the authors attribute leucine uptake differences to a loss of PDIM or changes in PDIM amount and architecture. No direct evidence is provided for differences in PDIM production in the WT H37Rv strain and the auxotroph mc2 6206 strains used in this study. Mulholland et al (2024) report similar PDIM levels for WT and auxotrophic Mtb (mc2 6206) in their stocks passaged to maintain PDIM. This could change for stocks maintained differently. Since the presence of PDIM has classically been used to explain a penetration barrier for small molecules and the schematic provided by the authors at the end of the manuscript (figure 8c) suggest free leucine penetration in the absence of PDIM, how do the authors explain the increased leucine uptake and sensitivity of a PDIM positive auxotroph to semapimod through direct experimental evidence? Further on the point of PDIM production, the WT auxotroph strain seems to produce limited amounts of PDIM as evidenced by the TLC data in Figure 6b. To solidify this point, the authors should test other point mutants for PDIM production (not attenuated for growth) through TLC and quantify these differences. These data should be compared with PDIM production in the WT Mtb H37Rv strain (used by the authors) under in vitro growth conditions. A comparative lipidomics of cell envelope components might be insightful in explaining these differences. I believe answering this query is crucial and within the scope of the work whose central claim is the identification of a novel leucine uptake mechanism. It would be interesting, in fact, to identify a novel transporter associated with the PDIM layer on the cell envelope.

Reviewer #3 (Public review):

This paper extends the authors' 2022 studies of how the synthesis of membrane sphingolipids is regulated in budding yeast. Here, they hypothesized that overexpression of a protein involved in sphingolipid (SL) biosynthesis would confer resistance of lip1-1 cells, which are Dox-inducibly defective in expression of a ceramide synthase regulatory subunit, to myriocin (Myr), a serine palmitoyltransferase inhibitor that inhibits SL synthesis. To test this idea, they transformed lip1-1 cells with a multi-copy genomic library, selecting for Myr resistance. Apart from LIP1 itself and YPK1, a protein kinase downstream of TORC2, COM2, which encodes the Com2 C2H2-type zinc finger transcription factor, was the most frequent hit in the screen. They went on to show that com2Δ cells exhibited Myr sensitivity, and that Com2 protein expression was induced under conditions that reduced complex sphingolipid synthesis, such as Myr-treatment. Using ypk1-as ypk2Δ cells and the 3-MB-PP1 Ypk1as a selective Ypk1as kinase inhibitor, they showed that Com2 phosphorylation was independent of Ypk1 activity, suggesting that Ypk1 lies downstream of Com2. Consistently, Myr treatment, which reduces SL synthesis, resulted in an increase in both Com2 and Ypk1 proteins. By generating a Ptet-off-GFP-COM2 strain they showed that when Dox was removed to induce GFP-Com2 overexpression, Myr resistance was increased. They went on to show that Com2 binds to a Com2 response element in the YPK1 promoter and drives expression of Ypk1. This was confirmed by showing that expression of a YPK1-driven lacZ reporter gene was also elevated when GFP-Com2 overexpression was induced. CRISPR deletion of the putative Com2-binding site (CBS) from the endogenous YPK1 promoter was used to generate PYPK1-ΔCBS cells, which showed a significant reduction in Ypk1 expression and exhibited intermediate Myr sensitivity, suggesting that Com2 is important for but not the only regulator of Ypk1 expression. Analysis of SL levels showed that they largely paralleled the levels of Ypk1 protein and active pT662 Ypk1. Using deletion analysis of the COM2 gene, they showed that residues 2-190 and the C-terminal DNA binding domain of Com2 were essential for Com2 function in the SL synthesis pathway. Deletion of {greater than or equal to}40 amino acids from the N-terminus increased expression of Com2 protein irrespective of Myr treatment, suggesting that Com2 protein levels are regulated by protein stability. Consistently, they found the high level of Com2 protein induced by Myr was rapidly reversed by treatment with phytosphingosine (PHS), a ceramide precursor that bypasses the Myr-blocked step and restores SL synthesis. The reduction in Com2 protein plus PHS was prevented by MG132 proteasome inhibitor treatment and led to the accumulation of polyUb-Com2 species, consistent with Com2 being negatively regulated by SL-induced UPS-mediated degradation. Based on the use of selective inhibitors of different steps in SL synthesis, they showed that SL biosynthesis up to the level of MIPC (mannnosyldiinositol phosphorylceramide) is required for the SL-mediated degradation response. Based on individual and combined K to R mutagenesis of the three Lys in Com2 1-49, they showed that K23, K35 and K51 in combination are needed for PHS-induced Com2 degradation, and therefore are likely to be the main Com2 Ub sites. Finally, they observed that PHS induced an increase in K3R Com2 phosphorylation, finding that an S/T10A mutant was only weakly phosphorylated and was resistant to PHS-induced degradation, suggesting that phosphorylation of Com2 is required for PHS-dependent degradation.

The paper is clearly written, and the data in Figures 1-6 show convincingly that the Com2 zinc finger protein, by inducing the expression of a set of genes, including YPK1 and LCB1, plays an important role in sphingolipid (SL) homeostasis in yeast under conditions when sphingolipid levels are low. However, the data in Figures 7 and 8, where the authors provide evidence that the Com2 protein was rapidly degraded in a proteasome-dependent manner in response to phytosphingosine (PHS) treatment, dependent on the N-terminal 40 residues of Com2 and a combination of three Lys residues in this region, are intriguing but incomplete. There are a number of issues, including the identity of the Com2 ubiquitylation sites. They showed that the K23/35/51R Com2 mutant was stabilized, but did they provide direct evidence that these three Lys are in fact ubiquitylated (e.g. GG-K peptide enrichment based MS analysis of Ub-Com2 from PHS-treated, MG132-treated cells). They showed that PHS treatment increased Myc13-tagged Com2 ubiquitylation in the presence of MG132, but did not show that the K3R Com2 mutant (or the S/T10A phosphorylation site Com2 mutant) failed to be ubiquitylated. They also found that the WT Com2 and particularly the K3R Com2 mutant protein exhibited hyperphosphorylation in response to PHS treatment, and that mutation of 10 potential pSer sites to Ala abolished this effect, and stabilized the Com2 protein. However, it is unclear whether the K3R mutation led to increased Com2 hyperphosphorylation per se following PHS treatment, or whether this is because there is more K3R protein, as they suggest might be the case. It is also not clear what protein kinase is responsible or how it might be activated when SL levels are high. In addition, the E3 Ub ligase needed for Com2 degradation was not identified, and it is not clear whether Com2 phosphorylation is directly involved in its recognition by a phosphodependent E3 Ub ligase, as they propose in the model shown in Figure 9. Finally, and perhaps most importantly. It is unclear how elevated levels of phytosphingosine or any sphingolipid are sensed by the Com2 pathway in order to switch on the degradation response as a negative feedback event. The model depicted in Figure 9 exposes all of these unknowns. The paper would be significantly strengthened by additional experiments defining how complex SL levels are sensed, how Com2 is phosphorylated in response to SL sensor signals, and how (phospho)Com1 is recognized for ubiquitylation and degradation.

In summary, the finding that the Com2 zinc finger transcription factor is an upstream regulator of the sphingolipid biosynthesis pathway in budding yeast, acting as part of an SL sensor system to maintain sphingolipid homeostasis, is new and potentially important. However, more mechanistic work needs to be done to address the unanswered questions raised by the data in Figures 7 and 8.