Reviewer #1 (Public review):

Summary:

This study explores how heterozygosity for specific neurodevelopmental disorder-associated Trio variants affects mouse behavior, brain structure, and synaptic function, revealing distinct impacts on motor, social, and cognitive behaviors linked to clinical phenotypes. Findings demonstrate that Trio variants yield unique changes in synaptic plasticity and glutamate release, highlighting Trio's critical role in presynaptic function and the importance of examining variant heterozygosity in vivo.

Strengths:

This study generated multiple mouse lines to model each Trio variant, reflecting point mutations observed in human patients with developmental disorders. The authors employed various approaches to evaluate the resulting behavioral, neuronal morphology, synaptic function, and proteomic phenotypes.

Reviewer #2 (Public review):

Summary:

This manuscript is about using different analytical approaches to allow ancestry adjustments to GWAS analyses amongst admixed populations. This work is a follow-on from the recently published ITHGC multi-population GWAS (https://doi.org/10.7554/eLife.84394), with the focus on the admixed South African populations. Ancestry adjustment models detected a peak of SNPs in the class II HLA DPB1, distinct from the class II HLA DQA1 loci signficant in the ITHGC analysis.

Strengths:

Excellent demonstration of GWAS analytical pipelines in highly admixed populations. Particularly the utility of ancestry adjustment to improve study power to detect novel associations. Further confirmation of the importance of the HLA class II locus in genetic susceptibility to TB.

Weaknesses:

Limited novelty compared to the group's previous existing publications and the body of work linking HLA class II alleles with TB susceptibility in South Africa or other African populations. This work includes only ~100 new cases and controls from what has already been published. High resolution HLA typing has detected significant signals in both the DQA1 and DPB1 regions identified by the larger ITHGC and in this GWAS analysis respectively (Chihab L et al. HLA. 2023 Feb; 101(2): 124-137).<br /> Despite the availability of strong methods for imputing HLA from GWAS data (Karnes J et Plos One 2017), the authors did not confirm with HLA typing the importance of their SNP peak in the class II region. This would have supported the importance of this ancestry adjustment versus prior ITHGC analysis.

The populations consider active TB and healthy controls (from high-burden presumed exposed communities) and do not provide QFT or other data to identify latent TB infection.

Important methodological points for clarification and for readers to be aware of when reading this paper:

(1) One of the reasons cited for the lack of African ancestry-specific associations or suggestive peaks in the ITHGC study was the small African sample size. The current association test includes a larger African cohort and yields a near-genome-wide significant threshold in the HLA-DPB1 gene originating from the KhoeSan ancestry. Investigation is needed as to whether the increase in power is due to increased African samples and not necessarily the use of the LAAA model as stated on lines 295 and 296?

Authors response - The Manhattan plot in Figure 3 includes the results for all four models: the traditional GWAS model (GAO), the admixture mapping model (LAO), the ancestry plus allelic (APA) model and the LAAA model. In this figure, it is evident that only the LAAA model identified the association peak on chromosome 6, which lends support the argument that the increase in power is due to the use of the LAAA model and not solely due to the increase in sample size.<br /> Reviewer comment - This data supports the authors conclusions that increase power is related to the LAAA model application rather than simply increase sample size.

(2) In line 256, the number of SNPs included in the LAAA analysis was 784,557 autosomal markers; the number of SNPs after quality control of the imputed dataset was 7,510,051 SNPs (line 142). It is not clear how or why ~90% of the SNPs were removed. This needs clarification.

Authors response:<br /> In our manuscript (line 194), we mention that "...variants with minor allele frequency (MAF) < 1% were removed to improve the stability of the association tests." A large proportion of imputed variants fell below this MAF threshold and were subsequently excluded from this analysis.

Reviewers additional comment: The authors should specify the number of SNPs in the dataset before imputation and indicate what proportion of the 784,557 remaining SNPs were imputed. Providing this information might help the reader better understand the rationale behind the imputation process.

(3) The authors have used the significance threshold estimated by the STEAM p-value < 2.5x10-6 in the LAAA analysis. Grinde et al. (2019 implemented their significance threshold estimation approach tailored to admixture mapping (local ancestry (LA) model), where there is a reduction in testing burden. The authors should justify why this threshold would apply to the LAAA model (a joint genotype and ancestry approach).

Authors response: We describe in the methods (line 189 onwards) that the LAAA model is an extension of the APA model. Since the APA model itself simultaneously performs the null global ancestry only model and the local ancestry model (utilised in admixture mapping), we thus considered the use of a threshold tailored to admixture mapping appropriate for the LAAA model.

Reviewers additional comment: While the LAAA model is an extension of the APA model, the authors describe the LAAA test as 'models the combination of the minor allele and the ancestry of the minor allele at a specific locus, along with the effect of this interaction,' thus a joint allele and ancestry effects model. Grinde et al. (2019) proposed the significance threshold estimation approach, STEAM, specifically for the LA approach, which tests for ancestry effects alone and benefits from the reduced testing burden. However, it remains unclear why the authors found it appropriate to apply STEAM to the LAAA model, a joint test for both allele and ancestry effects, which does not benefit from the same reduction in testing burden.

(4) Batch effect screening and correction (line 174) is a quality control check. This section is discussed after global and local ancestry inferences in the methods. Was this QC step conducted after the inferencing? If so, the authors should justify how the removed SNPs due to the batch effect did not affect the global and local ancestry inferences or should order the methods section correctly to avoid confusion.

Authors response: The batch effect correction method utilised a pseudo-case-control comparison which included global ancestry proportions. Thus, batch effect correction was conducted after ancestry inference. We excluded 36 627 SNPs that were believed to have been affected by the batch effect. We have amended line 186 to include the exact number of SNPs excluded due to batch effect.<br /> The ancestry inference by RFMix utilised the entire merged dataset of 7 510 051 SNPs. Thus, the SNPs removed due to the batch effect make up a very small proportion of the SNPs used to conduct global and local ancestry inferences (less than 0.5%). As a result, we do not believe that the removed SNPs would have significantly affected the global and local ancestry inferences. However, we did conduct global ancestry inference with RFMix on each separate dataset as a sanity check. In the tables below, we show the average global ancestry proportions inferred for each separate dataset, the average global ancestry proportions across all datasets and the average global ancestry proportions inferred using the merged dataset. The SAC and Xhosa cohorts are shown in two separate tables due to the different number of contributing ancestral populations to each cohort. The differences between the combined average global ancestry proportions across the separate cohorts does not differ significantly to the global ancestry proportions inferred using the merged dataset.

This is an excellent response and should remain accessible to readers for clarifying this issue.

Comments on revisions:

Thank you for addressing my other recommendations to authors. These have all been satisfactorily addressed.

Reviewer #1 (Public review):

Summary:

This study reveals that TRPV1 signaling plays a key role in tympanic membrane (TM) healing by promoting macrophage recruitment and angiogenesis. Using a mouse TM perforation model, researchers found that blood-derived macrophages accumulated near the wound, driving angiogenesis and repair. TRPV1-expressing nerve fibers triggered neuroinflammatory responses, facilitating macrophage recruitment. Genetic Trpv1 mutation reduced macrophage infiltration, angiogenesis, and delayed healing. These findings suggest that targeting TRPV1 or stimulating sensory nerve fibers could enhance TM repair, improve blood flow, and prevent infections. This offers new therapeutic strategies for TM perforations and otitis media in clinical settings. This is an excellent and high-quality study that provides valuable insights into the mechanisms underlying TM wound healing.

Strengths:

The work is particularly important for elucidating the cellular and molecular processes involved in TM repair. However, there are several concerns about the current version.

Weaknesses:

Major concerns

(1) The method of administration will be a critical factor when considering potential therapeutic strategies to promote TM healing. It would be beneficial if the authors could discuss possible delivery methods, such as topical application, transtympanic injection, or systemic administration, and their respective advantages and limitations for targeting TRPV1 signaling. For example, Dr. Kanemaru and his colleagues have proposed the use of Trafermin and Spongel to regenerate the eardrum.

(2) The authors appear to have used surface imaging techniques to observe the TM. However, the TM consists of three distinct layers: the epithelial layer, the fibrous middle layer, and the inner mucosal layer. The authors should clarify whether the proposed mechanism involving TRPV1-mediated macrophage recruitment and angiogenesis is limited to the epithelial layer or if it extends to the deeper layers of the TM.

Minor concerns

In Figure 8, the schematic illustration presents a coronal section of the TM. However, based on the data provided in the manuscript, it is unclear whether the authors directly obtained coronal images in their study. To enhance the clarity and impact of the schematic, it would be helpful to include representative images of coronal sections showing macrophage infiltration, angiogenesis, and nerve fiber distribution in the TM.

Reviewer #1 (Public review):

Summary:

This paper presents results from four independent experiments, each of which tests for rhythmicity in auditory perception. The authors report rhythmic fluctuations in discrimination performance at frequencies between 2 and 6 Hz. The exact frequency depends on the ear and experimental paradigm, although some frequencies seem to be more common than others.

Strengths:

The first sentence in the abstract describes the state of the art perfectly: "Numerous studies advocate for a rhythmic mode of perception; however, the evidence in the context of auditory perception remains inconsistent". This is precisely why the data from the present study is so valuable. This is probably the study with the highest sample size (total of > 100 in 4 experiments) in the field. The analysis is very thorough and transparent, due to the comparison of several statistical approaches and simulations of their sensitivity. Each of the experiments differs from the others in a clearly defined experimental parameter, and the authors test how this impacts auditory rhythmicity, measured in pitch discrimination performance (accuracy, sensitivity, bias) of a target presented at various delays after noise onset.

Weaknesses:

(1) The authors find that the frequency of auditory perception changes between experiments. I think they could exploit differences between experiments better to interpret and understand the obtained results. These differences are very well described in the Introduction, but don't seem to be used for the interpretation of results. For instance, what does it mean if perceptual frequency changes from between- to within-trial pitch discrimination? Why did the authors choose this experimental manipulation? Based on differences between experiments, is there any systematic pattern in the results that allows conclusions about the roles of different frequencies? I think the Discussion would benefit from an extension to cover this aspect.

(2) The Results give the impression of clear-cut differences in relevant frequencies between experiments (e.g., 2 Hz in Experiment 1, 6 Hz in Exp 2, etc), but they might not be so different. For instance, a 6 Hz effect is also visible in Experiment 1, but it just does not reach conventional significance. The average across the three experiments is therefore very useful, and also seems to suggest that differences between experiments are not very pronounced (otherwise the average would not produce clear peaks in the spectrum). I suggest making this point clearer in the text.

(3) I struggle to understand the hypothesis that rhythmic sampling differs between ears. In most everyday scenarios, the same sounds arrive at both ears, and the time difference between the two is too small to play a role for the frequencies tested. If both ears operate at different frequencies, the effects of the rhythm on overall perception would then often cancel out. But if this is the case, why would the two ears have different rhythms to begin with? This could be described in more detail.

Reviewer #1 (Public review):

Summary:

The study by Cao et al. provides a compelling investigation into the role of mutational input in the rapid evolution of pesticide resistance, focusing on the two-spotted spider mite's response to the recent introduction of the acaricide cyetpyrafen. This well-documented introduction of the pesticide - and thus a clearly defined history of selection - offers a powerful framework for studying the temporal dynamics of rapid adaptation. The authors combine resistance phenotyping across multiple populations, extensive resequencing to track the frequency of resistance alleles, and genomic analyses of selection in both contemporary and historical samples. These approaches are further complemented by laboratory-based experimental evolution, which serves as a baseline for understanding the genetic architecture of resistance across mite populations in China. Their analyses identify two key resistance-associated genes, sdhB and sdhD, within which they detect 15 mutations in wild-collected samples. Protein modeling reveals that these mutations cluster around the pesticide's binding site, suggesting a direct functional role in resistance. The authors further examine signatures of selective sweeps and their distribution across populations to infer the mechanisms - such as de novo mutation or gene flow-driving the spread of resistance, a crucial consideration for predicting evolutionary responses to extreme selection pressure. Overall, this is a well-rounded, thoughtfully designed, and well-written manuscript. It shows significant novelty, as it is relatively rare to integrate broad-scale evolutionary inference from natural populations with experimentally informed bioassays, however, some aspects of the methods and discussion have an opportunity to be clarified and strengthened.

Strengths:

One of the most compelling aspects of this study is its integration of genomic time-series data in natural populations with controlled experimental evolution. By coupling genome sequencing of resistant field populations with laboratory selection experiments, the authors tease apart the individual effects of resistance alleles along with regions of the genome where selection is expected to occur, and compare that to the observed frequency in the wild populations over space and time. Their temporal data clearly demonstrates the pace at which evolution can occur in response to extreme selection. This type of approach is a powerful roadmap for the rest of the field of rapid adaptation.

The study effectively links specific genetic changes to resistance phenotypes. The identification of sdhB and sdhD mutations as major drivers of cyetpyrafen resistance is well-supported by allele frequency shifts in both field and experimental populations. The scope of their sampling clearly facilitated the remarkable number of observed mutations within these target genes, and the authors provide a careful discussion of the likelihood of these mutations from de novo or standing variation. Furthermore, the discovered cross-resistance that these mutations confer to other mitochondrial complex II inhibitors highlights the potential for broader resistance management and evolution.

Weaknesses:

(1) Experimental Evolution:

- Additional information about the lab experimental evolution would be useful in the main text. Specifically, the dose of cyetpyrafen used should be clarified, especially with respect to the LD50 values. How does it compare to recommended field doses? This is expected to influence the architecture of resistance evolution. What was the sample size? This will help readers contextualize how the experimental design could influence the role of standing variation.

- The finding that lab-evolved strains show cross-resistance is interesting, but potentially complicates the story. It would help to know more about the other mitochondrial complex II inhibitors used across China and their impact on adaptive dynamics at these loci, particularly regarding pre-existing resistance alleles. For example, a comparison of usage data from 2013, 2017, and 2019 could help explain whether cyetpyrafen was the main driver of resistance or if previous pesticides played a role. What happened in 2020 that caused such rapid evolution 3 years after launch?

(2) Evolutionary history of resistance alleles:

- It would be beneficial to examine the population structure of the sampled populations, especially regarding the role of migration. Though resistance evolution appears to have had minimal impact on genome-wide diversity (as shown in Supplementary Figure 2), could admixture be influencing the results? An explicit multivariate regression framework could help to understand factors influencing diversity across populations, as right now much is left to the readers' visual acuity.

- It is unclear why lab populations were included in the migration/treemix analysis. We might suggest redoing the analysis without including the laboratory populations to reveal biologically plausible patterns of resistance evolution.

- Can the authors explore isolation by distance (IBD) in the frequency of resistance alleles?

- Given the claim regarding the novelty of the number of pesticide resistance mutations, it is important to acknowledge the evolution of resistance to all pesticides (antibiotics, herbicides, etc.). ALS-inhibiting herbicides have driven remarkable repeatability across species based on numerous SNPs within the target gene.

- Figure 5 A-B. Why not run a multivariate regression with status at each resistance mutation encoded as a separate predictor? It is interesting that focusing on the predominant mutation gives the strongest r2, but it is somewhat unintuitive and masks some interesting variation among populations.

(3) Haplotype Reconstruction (Line 271-):

- We are a bit sceptical of the methods taken to reconstruct these haplotypes. It seems as though the authors did so with Sanger sequencing (this should be mentioned in the text), focusing only on homozygous SNPs. How many such SNPs were used to reconstruct haplotypes, along what length of sequence? For how many individuals were haplotypes reconstructed? Nonetheless, I appreciated that the authors looked into the extent to which the reconstructed haplotypes could be driven by recombination. Can the authors elaborate on the calculations in line 296? Is that the census population size estimate or effective?

(4) Single Mutations and Their Effect (line 312-):

- It's not entirely clear how the breeding scheme resulted in near-isogenic lines. Could the authors provide a clearer explanation of the process and its biological implications?

- If they are indeed isogenic, it's interesting that individual resistance mutations have effects on resistance that vary considerably among lines. Could the authors run a multivariate analysis including all potential resistance SNPs to account for interactions between them? Given the variable effects of the D116G substitution (ranging from 4-25%), could polygenic or epistatic factors be influencing the evolution of resistance?

- Why are there some populations that segregate for resistance mutations but have no survival to pesticides (i.e., the green points in Figure 5)? Some discussion of this heterogeneity seems required in the absence of validation of the effects of these particular mutations. Could it be dominance playing a role, or do the authors have some other explanation?

- The authors mention that all resistance mutations co-localized to the Q-site. Is this where the pesticide binds? This seems like an important point to follow their argument for these being resistance-related.

(5) Statistical Considerations for Allele Frequency Changes (Figure 3):

- It might be helpful to use a logistic regression model to assess the rate of allele frequency changes and determine the strength of selection acting on these alleles (e.g., Kreiner et al. 2022; Patel et al. 2024). This approach could refine the interpretation of selection dynamics over time.

Reviewer #1 (Public review):

Summary:

Felipe and colleagues try to answer an important question in Sarbecovirus Orf9b-mediated interferon signaling suppression, given that this small viral protein adopts two distinct conformations, a dimeric β-sheet-rich fold and a helix-rich monomeric fold when bound by Tom70 protein. Two Orf9b structures determined by X-ray crystallography and Cryo-EM suggest an equilibrium between the two Orf9b conformations, and it is important to understand how this equilibrium relates to its functions. To answer these questions, the authors developed a series of ordinary differential equations (ODE) describing the Orf9b conformation equilibrium between homodimers and monomers binding to Tom70. They used SPR and a fluorescent polarization (FP) peptide displacement assay to identify parameters for the equilibrium and create a theoretical model. They then used the model to characterize the effect of lipid-binding and the effects of Orf9b mutations in homodimer stability, lipid binding, and dimer-monomer equilibrium. They used their model to further analyze dimerization, lipid binding, and Orf9b-Tom70 interactions for truncated Orf9b, Orf9b fusion mutant S53E (blocking Tom70 binding), and Orf9b from a set of Sars-CoV-2 VOCs. They evaluated the ability of different Orf9b variants for binding Tom70 using Co-IP experiments and assessed their activity in suppressing IFN signaling in cells.

Overall, this work is well designed, the results are of high quality and well-presented; the results support their conclusions.

Strengths:

(1) They developed a working biophysical model for analyzing Orf9b monomer-dimer equilibrium and Tom70 binding based on SPR and FP experiments; this is an important tool for future investigation.

(2) They prepared lipid-free Orf9b homodimer and determined its crystal structure.

(3) They designed and purified obligate Orf9b monomer, fused-dimer, etc., a very important Orf9b variant for further investigations.

(4) They identified the lipid bound by Orf9b homodimer using mass spectra data.

(5) They proposed a working model of Orf9b-Tom70 equilibrium.

Weaknesses:

(1) It is difficult to understand why the obligate Orf9b dimer has similar IFN inhibition activity as the WT protein and obligate Orf9b monomer truncations.

(2) The role of Orf9b homodimer and the role of Orf9b-bound lipid in virus infection, remains unknown.

Reviewer #1 (Public review):

Summary:

In this study, Meunier et al. investigated the functional role of IL-10 in avian mucosal immunity. While the anti-inflammatory role of IL-10 is well established in mammals, and several confirmatory knockout models are available in mice, IL-10's role in avian mucosal immunity is so far correlative. In this study, the authors generated two different models of IL-10 ablation in Chickens. A whole body knock-out model and an enhancer KO model leading to reduced IL10 expression. The authors first performed in vitro LPS stimulation-based experiments, and then in vivo two different infection models employing C. jejuni and E. tenella, to demonstrate that complete ablation of IL10 leads to enhanced inflammation-related pathology and gene expression, and enhanced pathogen clearance. At a steady-state level, however, IL-10 ablation did not lead to spontaneous colitis.

Strengths:

Overall, the study is well executed and establishes an anti-inflammatory role of IL-10 in birds. While the results are expected and not surprising, this appears to be the first report to conclusively demonstrate IL-10's anti-inflammatory role upon its genetic ablation in the avian model. Provided this information is applicable in combating pathogen infection in livestock species in sustainable industries like poultry, the study will be of interest to the field.

Weaknesses:

The study is primarily a confirmation of the already established anti-inflammatory role of IL-10.

Reviewer #1 (Public review):

Summary:

By applying a laser scanning photostimulation (LSPS) approach to a novel slice preparation, the authors aimed to study the degree of convergence and divergence of cortical inputs to individual striatal projection neurons (SPNs).

Strengths:

The experiments were well-designed and conducted, and data analysis was thorough. The manuscript was well written, and related work in the literature was properly discussed. This work has the potential to advance our understanding of how sensory inputs are integrated into the striatal circuits.

Weaknesses:

This work focuses on the connection strength of the corticostriatal projections, without considering the involvement of synaptic plasticity in sensory integration.

Joint Public Review:

Following up on their previous work, the authors investigated whether HIV-1 cell-to-cell transmission activates the CARD8 inflammasome in macrophages, a key question given that inflammasome activation in myeloid cells triggers proinflammatory cytokine release. Co-cultures of HIV-infected T cells with macrophages led to viral spreading, resulting in IL1β release and cell death, with CARD8 playing a crucial role in this inflammasome response, triggered by HIV protease. The authors also found that HIV isolates resistant to protease inhibitors showed differences in CARD8 activation and IL1β production, highlighting the clinical relevance of their findings. Overall, this well-written study provides strong evidence for the role of CARD8 in protease-dependent sensing of viral spread, with implications for understanding chronic inflammation in HIV infections and its potential contribution to systemic immune activation, especially under ART. The authors have addressed initial weaknesses and verified effects in cocultures of primary T cells and macrophages. They now also provide evidence that CARD8 is activated by protease from incoming viral particles. Further studies are needed to clarify how much this mechanism contributes to systemic immune activation in untreated infections and whether this mechanism drives chronic inflammation under ART.

Reviewer #1 (Public review):

Summary:

Gruskin and colleagues use twin data from a movie-watching fMRI paradigm to show how genetic control of cortical function intersects with the processing of naturalistic audiovisual stimuli. They use hyperalignment to dissect heritability into the components that can be explained by local differences in cortical-functional topography and those that cannot. They show that heritability is strongest at slower-evolving neural time scales and is more evident in functional connectivity estimates than in response time series.

Strengths:

This is a very thorough paper that tackles this question from several different angles. I very much appreciate the use of hyperalignment to factor out topographic differences, and I found the relationship between heritability and neural time scales very interesting. The writing is clear, and the results are compelling.

Weaknesses:

The only "weaknesses" I identified were some points where I think the methods, interpretation, or visualization could be clarified.

(1) On page 16, the authors compare heritability in functional connectivity (FC) and response time series, and find that the heritability effect is larger in FC. In general, I agree with your diagnosis that this is in large part due to the fact that FC captures the covariance structure across parcels, whereas response time series only diverge in terms of univariate time-point-by-time-point differences. Another important factor here is that (within-subject) FC can be driven by intrinsic fluctuations that occur with idiosyncratic timing across subjects and are unrelated to the stimulus (whereas time-locked metrics like ISC and time-series differences cannot, by definition). This makes me wonder how this connectivity result would change if the authors used intersubject functional connectivity (ISFC) analysis to specifically isolate the stimulus-driven components of functional connectivity (Simony et al., 2016). This, to me, would provide a closer comparison to the ISC and response time series results, and could allow the authors to quantify how much of the heritability in FC is intrinsic versus stimulus-driven. I'm not asking that the authors actually perform this analysis, as I don't think it's critical for the message of the manuscript, but it could be an interesting future direction. As the authors discuss on page 17, I also suspect there's something fundamentally shared between response time series and connectivity as they relate to functional topography (Busch et al., 2021) that drives part of the heritability effect.

(2) The observation that regions with intermediate ISC have the largest differences between MZ, DZ, and UR is very interesting, but it's kind of hard to see in Figure 1B. Is there any other way to plot this that might make the effect more obvious? For example, I could imagine three scatter plots where the x- and y-axes are, e.g., MZ ISC and UR ISC, and each data point is a parcel. In this kind of plot, I would expect to see the middle values lifted visibly off the diagonal/unity line toward MZ. The authors could even color the data points according to networks, like in Figure 3C. (They also might not need to scale the ISC axis all the way to r = 1, which would make the differences more visible.)

(3) On page 9, if I understand correctly, the authors regress the vector of ISC values across parcels out of the vector of heritability values across parcels, and then plot the residual heritability values. Do they center the heritability values (or include some kind of intercept) in the process? I'm trying to understand why the heritability values go from all positive (Figure 2A) to roughly balanced between positive and negative (Figure 2B). Important question for me: How should we interpret negative values in this plot? Can the authors explain this explicitly in the text? (I also wonder if there's a more intuitive way to control for ISC. For example, instead of regressing out ISC at the parcel/map level, could they go into a single parcel and then regress the subject-level pairwise ISC values out when computing the heritability score?).

(4) On page 4 (line 155), the authors say "we shuffled dyad labels"- is this equivalent to shuffling rows and columns of the pairwise subject-by-subject matrix combined across groups? I'm trying to make sure their approach here is consistent with recommendations by Chen et al., 2016. Is this the same kind of shuffling used for the kinship matrix mentioned in line 189?

(5) I found panel A in Figure 4 to be a little bit misleading because their parcel-wise approach to hyperalignment won't actually resolve topographic idiosyncrasies across a large cortical distance like what's depicted in the illustration (at the scale of the parcels they are performing hyperalignment within). Maybe just move the green and purple brain areas a bit closer to each other so they could feasibly be "aligned" within a large parcel. Worth keeping in mind when writing that hyperalignment is also not actually going to yield a one-to-one mapping of functionally homologous voxels across individuals: it's effectively going to model any given voxel time series as a linear combination of time series across other voxels in the parcel.

(6) I believe the subjects watched all different movies across the two days, however, for a moment I was wondering "are Day 1 and Day 2 repetitions of the same movies?" Given that Day 1 and Day 2 are an organizational feature of several figures, it might be worth making this very explicit in the Methods and reminding the reader in the Results section.

References:

Busch, E. L., Slipski, L., Feilong, M., Guntupalli, J. S., di Oleggio Castello, M. V., Huckins, J. F., Nastase, S. A., Gobbini, M. I., Wager, T. D., & Haxby, J. V. (2021). Hybrid hyperalignment: a single high-dimensional model of shared information embedded in cortical patterns of response and functional connectivity. NeuroImage, 233, 117975. https://doi.org/10.1016/j.neuroimage.2021.117975

Chen, G., Shin, Y. W., Taylor, P. A., Glen, D. R., Reynolds, R. C., Israel, R. B., & Cox, R. W. (2016). Untangling the relatedness among correlations, part I: nonparametric approaches to inter-subject correlation analysis at the group level. NeuroImage, 142, 248-259. https://doi.org/10.1016/j.neuroimage.2016.05.023

Simony, E., Honey, C. J., Chen, J., Lositsky, O., Yeshurun, Y., Wiesel, A., & Hasson, U. (2016). Dynamic reconfiguration of the default mode network during narrative comprehension. Nature Communications, 7, 12141. https://doi.org/10.1038/ncomms12141

for - stats - natural language acquisition - 1 to 2 year old is age of fastest and best learning

comment - ALG philosophy - replicate the experiences that 1 to 2 year olds have

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors report that activation of excitatory DREADDs in the mid-cervical spinal cord can increase inspiratory activity in mice and rats. This is an important first step toward an ultimate goal of using this, or similar, technology to drive breathing in disorders associated with decreased respiratory motor output, such as spinal injury or neurodegenerative disease. Strengths to this study include a comparison of non-specific DREADD expression in the mid-cervical spinal cord versus specific targeting to ChAT-positive neurons, and the measurement of multiple respiratory-related outcomes, including phrenic inspiratory output, diaphragm EMG activity and ventilation. The data show convincingly that DREADDs can be used to drive phrenic inspiratory activity, which in turn increases diaphragm EMG activity and ventilation.

Comments on revisions: All of my prior comments have been sufficiently addressed.

Reviewer #1 (Public review):

Summary:

This study provides an in-depth analysis of syncytiotrophoblast (STB) gene expression at the single-nucleus (SN) and single-cell (SC) levels, using both primary human placental tissues and two trophoblast organoid (TO) models. The authors compare the older TO model, where STB forms internally (STBin), with a newer model where STB forms externally (STBout). Through a series of comparative analyses, the study highlights the necessity of using both SN and SC techniques to fully understand placental biology. The findings demonstrate that the STBout model shows more differentiated STBs with higher expression of canonical markers and hormones compared to STBin. Additionally, the study identifies both conserved and distinct gene expression profiles between the TO models and human placenta, offering valuable insights for researchers using TOs to study STB and CTB differentiation.

Strengths:

The study offers a comprehensive SC- and SN-based characterization of trophoblast organoid models, providing a thorough validation of these models against human placental tissues. By comparing the older STBin and newer STBout models, the authors effectively demonstrate the improvements in the latter, particularly in the differentiation and gene expression profiles of STBs. This work serves as a critical resource for researchers, offering a clear delineation of the similarities and differences between TO-derived and primary STBs. The use of multiple advanced techniques, such as high-resolution sequencing and trajectory analysis, further enhances the study's contribution to the field.

Weaknesses were addressed during the revision.

The authors effectively addressed my critiques in the rebuttal letter and made corresponding changes in the manuscript. Specifically, they: 1) emphasized the importance of TO orientation in influencing STB nuclear subtype differentiation by adding text to the introduction; 2) clarified the differences in cluster numbers and names between primary tissue and TO data, explaining that each dataset was analyzed independently with separate clustering algorithms and adding clarifying text to the results section; 3) included additional rationale for using SN over SC sequencing, particularly for studying the multinucleated STB; 4) acknowledged that their original evidence was insufficient to definitively determine STBout nuclei differentiation status and removed language suggesting STB-3 as a terminally differentiated subtype, presenting alternative hypotheses in the discussion; and 5) incorporated new figures and clarifications, including RNA-FISH experiments, to validate subtype-specific marker gene expression. Overall, the authors' revisions strengthened the manuscript and aligned well with my critiques.

Reviewer #1 (Public review):

Summary:

The study characterises an RNA polymerase (Pol) I mutant (RPA135-F301S) named SuperPol. This mutant was previously shown to increase yeast ribosomal RNA (rRNA) production by Transcription Run-On (TRO). In this work, the authors confirm this mutation increases rRNA transcription using a slight variation of the TRO method, Transcriptional Monitoring Assay (TMA), which also allows the analysis of partially degraded RNA molecules. The authors show a reduction of abortive rRNA transcription in cells expressing the SuperPol mutant and a modest occupancy decrease at the 5' region of the rRNA genes compared to WT Pol I. These results suggest that the SuperPol mutant displays a lower frequency of premature termination. Using in vitro assays, the authors found that the mutation induces an enhanced elongation speed and a lower cleavage activity on mismatched nucleotides at the 3' end of the RNA. Finally, SuperPol mutant was found to be less sensitive to BMH-21, a DNA intercalating agent that blocks Pol I transcription and triggers the degradation of the Pol I subunit, Rpa190. Compared to WT Pol I, short BMH-21 treatment has little effect on SuperPol transcription activity, and consequently, SuperPol mutation decreases cell sensitivity to BMH-21.

I'd suggest the following points to be taken into consideration:

Major comments:

(1) The differences in the transcriptionally engaged WT Pol I and SuperPol profiles (Figure 2) are very modest, without any statistical analyses. What is the correlation between CRAC replicates? Are they separated in PCA analyses? Please, include more quality control information. In my opinion, these results are not very convincing. Similarly, the effect of BMH-21 on WT Pol I activity (Figure 7) is also very subtle and doesn't match the effect observed in a previous study [1]. Could the author comment on the reasons for these differences? These discrepancies raise concerns about the methodology. In addition, according to the laboratory's previous work [2], Pol I ChIP signal at rDNA is not significantly different in cells expressing WT Pol I and SuperPol. How can these two observations be reconciled? I would suggest using an independent methodology to analyse Pol I transcription, for example, GRO-seq or TT-seq.

(2) While the experiments clearly show SuperPol mutant increases nascent transcription and decreases the production of abortive promoter-proximal transcripts compared to WT Pol I. RPA135-F301S mutation has a minor impact on total rRNA levels, at least those shown in Figure 3B. Are steady-state rRNA levels higher in cells expressing SuperPol mutant? It would be interesting to know if SuperPol mutant produces more functional rRNAs.

Significance:

The work further characterises a single amino acid mutation of one of the largest yeast Pol I subunits (RPA135-F301S). While this mutation was previously shown to increase rRNA synthesis, the current work expands the SuperPol mutant characterisation, providing details of how RPA135-F301S modifies the enzymatic properties of yeast Pol I. In addition, their findings suggest that yeast Pol I transcription can be subjected to premature termination in vivo. The molecular basis and potential regulatory functions of this phenomenon could be explored in additional studies.

Our understanding of rRNA transcription is limited, and the findings of this work may be interesting to the transcription community. Moreover, targeting Pol I activity is an open strategy for cancer treatment. Thus, the resistance of SuperPol mutant to BMH-21 might also be of interest to a broader community, although these findings are yet to be confirmed in human Pol I and with more specific Pol I inhibitors in future.

Joint public review:

Summary:

This study investigates the hypoxia rescue mechanisms of neurons by non-neuronal cells in the brain from the perspective of exosomal communication between brain cells. Through multi-omics combined analysis, the authors revealed this phenomenon and logically validated this intercellular rescue mechanism under hypoxic conditions through experiments. The study proposed a novel finding that hemoglobin maintains mitochondrial function, expanding the conventional understanding of hemoglobin. This research is highly innovative, providing new insights for the treatment of hypoxic encephalopathy.

Overall, the manuscript is well organized and written, however, the authors have only partially answered the reviewers comments.

Reviewer #1 (Public review):

In this study, the authors introduced an essential role of AARS2 in maintaining cardiac function. They also investigated the underlying mechanism that through regulating alanine and PKM2 translation are regulated by AARS2. Accordingly, a therapeutic strategy for cardiomyopathy and MI was provided.

Comments on revised version:

The authors have completely addressed my concerns.

Reviewer #1 (Public review):

Summary:

In this paper, Manley and Vaziri investigate whole-brain neural activity underlying behavioural variability in zebrafish larvae. They combine whole brain (single cell level) calcium imaging during the presentation of visual stimuli, triggering either approach or avoidance, and carry out whole brain population analyses to identify whole brain population patterns responsible for behavioural variability. They show that similar visual inputs can trigger large variability in behavioural responses. Though visual neurons are also variable across trials, they demonstrate that this neural variability does not degrade population stimulus decodability. Instead, they find that the neural variability across trials is in orthogonal population dimensions to stimulus encoding and is correlated with motor output (e.g. tail vigor). They then show that behavioural variability across trials is largely captured by a brain-wide population state prior to the trial beginning, which biases choice - especially on ambiguous stimulus trials. This study suggests that parts of stimulus-driven behaviour can be captured by brain-wide population states that bias choice, independently of stimulus encoding.

Comments on revisions:

The authors have revised their manuscript and provided novel analyses and figures, as well as additions to the text based on our reviewer comments.

As stated in my first review, the strength of the paper principally resides in the whole brain cellular level imaging - using a novel fourier light field microscopy (Flfm) method - in a well-known but variable behaviour.

Many of the authors' answers have provided additional support for their interpretations of results, but the new analysis in Figure 3g - further exploring the orthogonality of e1 and wopt - puts into question the interpretation of a key result: that e1 and wopt are orthogonal in a non-arbitrary way. This needs to be addressed. I have made suggestions below to address this:

Reviewer 3 had correctly highlighted the issue that in high-dimensional data, there is an increasingly high chance of two vectors being orthogonal. The authors address this by shuffling the stimulus labels. They then state (and provide a new panel g in Fig. 3) that the shuffled distribution is wider than the actual distribution, and state that a wilcoxon rank-sum test shows this is significant. Given the centrality of this claim, I would like the authors to clarify what exactly is being done here, as it is not clear to me how this conclusion can be drawn from this analysis:

In lines 449:453 the authors state:<br /> 'While it is possible to observe shuffled vectors which are nearly orthogonal to e1, the shuffled distribution spans a significantly greater range of angles than the observed data (p<0.05, Wilcoxon rank- sum test), demonstrating that this orthogonality is not simply a consequence of analyzing multi-dimensional activity patterns. '<br /> I don't understand how the authors arrive at the p-value using a rank-sum test here. (a) What is the n in this test? Is n the number of shuffles? If so, this violates the assumptions of the test (as n must be the number of independent samples and not the arbitrary number of shuffles). (b) If the shuffling was done once for each animal and compared with actual data with a rank-sum test, how likely is that shuffling result to happen in 10000 shuffle comparisons?<br /> I am highlighting this, as it looks from Figure 3g that the shuffled distribution is substantially overlapping with the actual data (i.e., not outside of the 95 percentile of the shuffled distribution), which would suggest that the angle found between e1 and wept could happen by chance.

I would also suggest the authors instead test whether e1 is consistently aligned with itself when calculated on separate held out data-sets (for example by bootstrapping 50-50 splits of the data). If they can show that there is a close alignment between independently calculated e1's across separate data sets (and do the same for wopt), and then show e1 and wopt are orthogonal, then that supports their statement that e1 and wopt are orthogonal in a meaningful way. Given that e1 captures tail vigor variability (and Wopt appears to not) then I would think this could be the case. But the current answer the authors have given is not supporting their statement.

Reviewer #1 (Public review):

Summary:

In this manuscript, Jin et. al., describe SMARTTR, an image analysis strategy optimized for analysis of dual-activity ensemble tagging mouse reporter lines. The pipeline performs cell segmentation, then registers the location of these cells into an anatomical atlas, and finally, calculates the degree of co-expression of the reporters in cells across brain regions. The authors demonstrate the utility of the method by labeling two ensemble populations during two related experiences: inescapable shock and subsequent escapable shock as part of learned helplessness.

Strengths:

- We appreciated that the authors provided all documentation necessary to use their method, and that the scripts in their publicly available repository are well commented. Submission of the package to CRAN will, as the other reviewer pointed out, ensure that the package and its dependencies can be easily installed using few lines of code in the future. Additionally, we particularly appreciate the recently added documentation website and vignettes, which provide guidance on package installation and use cases.<br /> - The manuscript was well-written and very clear, and the methods were generally highly detailed.<br /> - The authors have addressed our previous concerns, and we appreciate their revised manuscript.

Reviewer #1 (Public review):

Summary:

This study provides new insights into the role of miR-19b, an oncogenic microRNA, in the developing chicken pallium. Dynamic expression pattern of miR-19b is associated with its role in regulating cell cycle progression in neural progenitor cells. Furthermore, miR-19b is involved in determining neuronal subtypes by regulating Fezf2 expression during pallial development. These findings suggest an important role for miR-19b in the coordinated spatio-temporal regulation of neural progenitor cell dynamics and its evolutionary conservation across vertebrate species.

Strengths:

The authors identified conserved roles of miR-19 in the regulation of neural progenitor maintenance between mouse and chick, and the latter is mediated by the repression of E2f8 and NeuroD1. Furthermore, the authors found that miR-19b-dependent cell cycle regulation is tightly associated with specification of Fezf1 or Mef2c-positive neurons, in spatio-temporal manners during chicken pallial development. These findings uncovered molecular mechanisms underlying microRNA-mediated neurogenic controls.

Weaknesses:

Although the authors in this study claimed striking similarities of miR-19a/b in neurogenesis between mouse and chick pallium, a previous study by Bian et al. revealed that miR-19a contributes the expansion of radial glial cells by suppressing PTEN expression in the developing mouse neocortex, while miR-19b maintains apical progenitors via inhibiting E2f2 and NeuroD1 in chicken pallium. Thus, it is still unclear whether the orthologous microRNAs regulate common or species-specific target genes.

The spatiotemporal expression patterns of miR-19b and several genes are not convincing. For example, the authors claim that NeuroD1 is initially expressed uniformly in the subventricular zone (SVZ) but disappears in the DVR region by HH29 and becomes detectable by HH35 (Figure 1). However, the in situ hybridization data revealed that NeuroD1 is highly expressed in the SVZ of the DVR at HH29 (Figure 4F). Thus, perhaps due to the problem of immunohistochemistry, the authors have not been able to detect NeuroD1 expression in Figure 1D, and the interpretation of the data may require significant modification.

It seems that miR-19b is also expressed in neurons (Figure 1), suggesting the role of miR19-b must be different in progenitors and differentiated neurons. The data on the gain- and loss-of-function analysis of miR-19b on the expression of Mef2c should be carefully considered, as it is possible that these experiments disturb the neuronal functions of miR19b rather than in the progenitors.

The regions of chicken pallium were not consistent among figures: in Figure 1, they showed caudal parts of the pallium (HH29 and 35), while the data in Figure 4 corresponded to the rostral part of the pallium (Figure 4B).

The neurons expressing Fezf2 and Mef2 in the chicken pallium are not homologous neuronal subtypes to mammalian deep and superficial cortical neurons. The authors must understand that chicken pallial development proceeds in an outside-in manner. Thus, Mef2c-postive neurons in a superficial part are early-born neurons, while FezF2-positive neurons residing in deep areas are later-born neurons. It should be noted that the expression of a single marker gene does not support cell type homology, and the authors' description "the possibility of primitive pallial lamina formation in common ancestors of birds and mammals" is misleading.

Overexpression of CDKN1A or Sponge-19b induced ectopic expression of Fezf2 in the ventricular zone (Figure 3C, E). Do these cells maintain progenitor statement or prematurely differentiate to neurons? In addition, the authors must explain that the induction of Fezf2 is also detected in GFP-negative cells.

Reviewer #1 (Public review):

Summary:

In this study, the authors aim to understand the neural basis of implicit causal inference, specifically how people infer causes of illness. They use fMRI to explore whether these inferences rely on content-specific semantic networks or broader, domain-general neurocognitive mechanisms. The study explores two key hypotheses: first, that causal inferences about illness rely on semantic networks specific to living things, such as the 'animacy network,' given that illnesses affect only animate beings; and second, that there might be a common brain network supporting causal inferences across various domains, including illness, mental states, and mechanical failures. By examining these hypotheses, the authors aim to determine whether causal inferences are supported by specialized or generalized neural systems.

The authors observed that inferring illness causes selectively engaged a portion of the precuneus (PC) associated with the semantic representation of animate entities, such as people and animals. They found no cortical areas that responded to causal inferences across different domains, including illness and mechanical failures. Based on these findings, the authors concluded that implicit causal inferences are supported by content-specific semantic networks, rather than a domain-general neural system, indicating that the neural basis of causal inference is closely tied to the semantic representation of the specific content involved.

Strengths:

- The inclusion of the four conditions in the design is well thought out, allowing for the examination of the unique contribution of causal inference of illness compared to either a different type of causal inference (mechanical) or non-causal conditions. This design also has the potential to identify regions involved in a shared representation of inference across general domains.

- The presence of the three localizers for language, logic, and mentalizing, along with the selection of specific regions of interest (ROIs), such as the precuneus and anterior ventral occipitotemporal cortex (antVOTC), is a strong feature that supports a hypothesis-driven approach (although see below for a critical point related to the ROI selection).

- The univariate analysis pipeline is solid and well developed.

- The statistical analyses are a particularly strong aspect of the paper.

Weaknesses:

After carefully considering the authors' response, I believe that my primary concern has not been fully addressed. My main point remains unresolved:

The authors attempt to test for the presence of a shared network by performing only the Causal vs. Non-causal analysis. However, this approach is not sufficiently informative because it includes all conditions mixed together and does not clarify whether both the illness-causal and mechanical-causal conditions contribute to the observed results.

To address this limitation, I originally suggested an additional step: using as ROIs the different regions that emerged in the Causal vs. Non-causal decoding analysis and conducting four separate decoding analyses within these specific clusters:<br /> (1) Illness-Causal vs. Non-causal - Illness First<br /> (2) Illness-Causal vs. Non-causal - Mechanical First<br /> (3) Mechanical-Causal vs. Non-causal - Illness First<br /> (4) Mechanical-Causal vs. Non-causal - Mechanical First

This approach would allow the authors to determine whether any of these ROIs can decode both the illness-causal and mechanical-causal conditions against at least one non-causal condition. However, the authors did not conduct these analyses, citing an independence issue. I disagree with this reasoning because these analyses would serve to clarify their initial general analysis, in which multiple conditions were mixed together. As the results currently stand, it remains unclear which specific condition is driving the effects.

My suggestion was to select the ROIs from their general analysis (Causal vs. Non-causal) and then examine in more detail which conditions were driving these results. This is not a case of double-dipping from my perspective, but rather a necessary step to unpack the general findings. Moreover, using ROIs would actually reduce the number of multiple comparisons that need to be controlled for.

If the authors believe that this approach is methodologically incorrect, then they should instead conduct all possible analyses at the whole-brain level to examine the effects of the specific conditions independently.

Reviewer #1 (Public review):

Summary:

The paper addresses the knowledge gap between the representation of goal direction in the central complex and how motor systems stabilize movement toward that goal. The authors focused on two descending neurons, DNa01 and 02, and showed that they play different roles in steering the fly toward a goal. They also explored the connectome data to propose a model to explain how these DNs could mediate response to lateralized sensory inputs. They finally used lateralized optogenetic activation/inactivation experiments to test the roles of these neurons in mediating turnings in freely walking flies.

Strengths:

The experiments are well-designed and controlled. The experiment in Figure 4 is elegant, and the authors put a lot of effort into ensuring that ATP puffs do not accidentally activate the DNs. They also have explained complex experiments well. I only have minor comments for the authors.

Comments on revisions:

I am happy with the revised manuscript and authors' response to our concerns. The addition of Figure S8, makes it more transparent and the revised text is now more accessible to the non-experts.

Reviewer #3 (Public review):

Summary:

The hippocampal CA3 region is generally considered to be the primary site of initiation of sharp wave ripples-highly synchronous population events involved in learning and memory-although the precise mechanism remains elusive. A recent study revealed that CA3 comprises two distinct pyramidal cell populations: thorny cells that receive mossy fiber input from the dentate gyrus, and athorny cells that do not. That study also showed that it is athorny cells in particular which play a key role in sharp wave initiation. In the present work, Sammons, Masserini and colleagues expand on this by examining the connectivity probabilities among and between thorny and athorny cells. Using whole-cell patch clamp recordings, they find an asymmetrical connectivity pattern, with athorny cells receiving the most synaptic connections from both athorny and thorny cells, and thorny cells receiving fewer.

The authors then use a spiking network model to show how this assymmetrical connectivity is consistent with a preferential role of athorny cells in sharp wave initiation. Essentially, thorny and athorny cells are put into a winner-takes-all scenario in which athorny cells always win initially. Thorny cells can only become active after athorny cells decrease their firing rate due to adaptation, leading to a delay between the activation of athorny and thorny cells. As far as I understand, the initial victory of athorny cells in the winner-takes-all is doubly determined: it is both due to their intrinsic properties (lower rheobase and steeper f-I curve), and due to the bias in connectivity towards them. It appears to me that either of these two mechanisms (i.e., different intrinsic properties and symmetrical self- and cross-connections, or the same intrinsic properties and asymmetrical connectivity) would suffice to explain the sequential activation of the two cell types. From a theoretician's perspective, this overdetermination is not very elegant, but biology often isn't...

Strengths:

The authors provide independent validation of some of the findings by Hunt et al. (2018) concerning the distinction between thorny and athorny pyramidal cells in CA3 and advance our understanding of their differential integration in CA3 microcircuits. The properties of excitatory connections among and between thorny and athorny cells described by the authors will be key in understanding CA3 functions including, but not limited to, sharp wave initiation.

As stated in the paper, the modeling results lend support to the idea that the increased excitatory connectivity towards athorny cells plays an important role in causing them to fire before thorny cells in sharp waves. More generally, the model adds to an expanding pool of models of sharp wave ripples which should prove useful in guiding and interpreting experimental research.

Reviewer #1 (Public review):

Summary:

This study utilises fNIRS to investigate the effects of undernutrition on functional connectivity patterns in infants from a rural population in Gambia. fNIRS resting-state data recording spanned ages 5 to 24 months, while growth measures were collected from birth to 24 months. Additionally, executive functioning tasks were administered at 3 or 5 years of age. The results show an increase in left and right frontal-middle and right frontal-posterior connections with age and, contrary to previous findings in high-income countries, a decrease in frontal interhemispheric connectivity. Restricted growth during the first months of life was associated with stronger frontal interhemispheric connectivity and weaker right frontal-posterior connectivity at 24 months of age. Additionally, the study describes some connectivity patterns, including stronger frontal interhemispheric connectivity, which is associated with better cognitive flexibility at preschool age.

Strengths:

- The study analyses longitudinal data from a large cohort (n = 204) of infants living in a rural area of Gambia. This already represents a large sample for most infant studies, and it is impressive, considering it was collected outside the lab in a population that is underrepresented in the literature. The research question regarding the effect of early nutritional deficiency on brain development is highly relevant and may highlight the importance of early interventions. The study may also encourage further research on different underrepresented infant populations (i.e., infants not residing in Western high-income countries) or in settings where fMRI is not feasible.

- The preprocessing and analysis steps are carefully described, which is very welcome in the fNIRS field, where well-defined standards for preprocessing and analysis are still lacking.

Weaknesses:

- While the study provides a solid description of the functional connectivity changes in the first two years of life at the group level and investigates how restricted growth influences connectivity patterns at 24 months, it does not explore the links between adverse situations and developmental trajectories for functional connectivity. Considering the longitudinal nature of the dataset, it would have been interesting to apply more sophisticated analytical tools to link undernutrition to specific developmental trajectories in functional connectivity. The authors mention that they lack the statistical power to separate infants into groups according to their growing profiles. However, I wonder if this aspect could not have been better explored using other modelling strategies and dimensional reduction techniques. I can think about methods such as partial least squares correlation, with age included as a numerical variable and measures of undernutrition.

- Connectivity was asses in 6 big ROIs. While the authors justify this choice to reduce variability due to head size and optode placement, this also implies a significant reduction in spatial resolution. Individual digitalisation and co-registration of the optodes to the head model, followed by image reconstruction, could have provided better spatial resolution. This is not a weakness specific to this study but rather a limitation common to most fNIRS studies, which typically analyse data at the channel level since digitalisation and co-registration can be challenging, especially in complex setups like this. However, the BRIGHT project has demonstrated that it is possible and that differences in placement affect activation patterns, which become more localised when data is co-registered at the subject level (Collins-Jones et al., 2021). Could the co-registration of individual data have increased sensitivity, particularly given that longitudinal effects are being investigated?

- I believe that a further discussion in the manuscript on the application of global signal regression and its effects could have been beneficial for future research and for readers to better understand the negative correlations described in the results. Since systemic physiological changes affect HbO/HbR concentrations, resulting in an overestimation of functional connectivity, regressing the global signal before connectivity computation is a common strategy in fNIRS and fMRI studies. However, the recommendation for this step remains controversial, likely depending on the case (Murphy & Fox, 2017). I understand that different reasons justify its application in the current study. In addition to systemic physiological changes originating from brain tissue, fNIRS recordings are contaminated by changes occurring in superficial layers (i.e., the scalp and skull). While having short-distance channels could have helped to quantify extracerebral changes, challenges exist in using them in infant populations, especially in a longitudinal study such as the one presented here. The optimal source-detector distance that minimises sensitivity to changes originating from the brain would increase with head size, and very young participants would require significantly shorter source-detector distances (Brigadoi & Cooper, 2015). Thus, having them would have been challenging. Under these circumstances (i.e., lack of short channels and external physiological measures), and considering that the amount the signal is affected by physiological noise (either coming from the brain or superficial tissue) might change through development, the choice of applying global signal regression is justified. Nevertheless, since the method introduces negative correlations in the data by forcing connectivity to average to zero, I believe a further discussion of these points would have enriched the interpretation of the results.

Reviewer #1 (Public review):

Summary:

Building on previous in vitro synaptic circuit work (Yamawaki et al., eLife 10, 2021), Piña Novo et al. utilize an in vivo optogenetic-electrophysiological approach to characterize sensory-evoked spiking activity in the mouse's forelimb primary somatosensory (S1) and motor (M1) areas. Using a combination of a novel "phototactile" somatosensory stimuli to the mouse's hand and simultaneous high-density linear array recordings in both S1 and M1, the authors report evoked activity in S1 was biased to middle layers, whereas it was biased to upper layers in M1. They report that M1 responses are delayed and attenuated relative to S1. Further analysis revealed a 20-fold difference in subcortical versus corticocortical propagation speeds. They also find that PV interneurons in S1 are strongly recruited by hand stimulation, and their selective activation can produce a suppression and rebound response similar to "phototactile" stimuli. Silencing S1 through local PV cells was sufficient to reduce M1 response to hand stimulation, suggesting S1 may directly drive M1 responses.

Strengths:

The study was technically well done, with convincing results. The data presented are appropriately analyzed. The author's findings build on a growing body of both in vitro and in vivo work examining the synaptic circuits underlying the interactions between S1 and M1. The paper is well-written and illustrated. Overall, the study will be valuable to those interested in forelimb S1-M1 interactions.

Weaknesses:

The authors have addressed my concerns

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors discovered MYL3 of marine medaka (Oryzias melastigma) as a novel NNV entry receptor, elucidating its facilitation of RGNNV entry into host cells through macropinocytosis, mediated by the IGF1R-Rac1/Cdc42 pathway.

Strengths:

In this manuscript, the authors have performed in vitro and in vivo experiments to prove that MnMYL3 may serve as a receptor for NNV via macropinocytosis pathway. These experiments with different methods include Co-IP, RNAi, pulldown, SPR, flow cytometry, immunofluorescence assays and so on. In general, the results are clearly presented in the manuscript.

Weaknesses:

For the writing in the introduction and discussion sections, the author Yao et al mainly focus on the viral pathogens and fish in Aquaculture, the meaning and novelty of results provided in this manuscript are limited, not broad in biology. The authors should improve the likely impact of their work on the viral infection field, maybe also in the evolutionary field with fish model.

Additionally, detailed comments are as follows:

(1) Myosin is a big family, why did authors choose MYL3 as a candidate receptor for NNV?

(2) What's the relationship between MmMYL3 and MmHSP90ab1 and other known NNV receptors? Why dose NNV have so many receptors? Which one is supposed to serve as the key entry receptor?

(3) In vivo knockout of MYL3 using CRISPR-Cas9 should be conducted to verify whether the absence of MYL3 really inhibits NNV infection. Although it might be difficult to do it in marine medaka as stated by authors, the introduce of zebrafish is highly recommended, since it has already been reported that zebrafish could be served as a vertebrate model to study NNV (doi: 10.3389/fimmu.2022.863096).

(4) The results shown in Figure 6 are not enough to support the conclusion that "RGNNV triggers macropinocytosis mediated by MmMYL3". Additional electron microscopy of macropinosomes (sizes, morphological characteristics, etc.) will be a more direct evidence.

(5) MYL3 is "predominantly found in muscle tissues, particularly the heart and skeletal muscles". However, NNV is a virus mainly causes necrosis of nervous tissues (brain and retina). If MYL3 really acts as a receptor for NNV, how does it balance this difference so that nervous tissues, rather than muscle tissues, have the highest viral titers?

Comments on revisions:

The authors have addressed most of my concerns in the revised manuscript, but still one question need to further improve to strengthen the study's rationale and conclusions.

Specificity of MYL3 Selection:<br /> My previous question focused on why MYL3 was prioritized over other myosin family members. While the response broadly implicates myosins in viral entry, it does not justify why MYL3 was specifically chosen. For clarity, the "Introduction sections" should explicitly state the unique features of MYL3 (e.g., domain structure, binding affinity, or prior evidence linking it to NNV) that distinguish it from other myosins.

Reviewer #1 (Public review):

Summary:

Diarrheal diseases represent an important public health issue. Among the many pathogens that contribute to this problem, Salmonella enterica serovar Typhimurium is an important one. Due to the rise in antimicrobial resistance and the problems associated with widespread antibiotic use, the discovery and development of new strategies to combat bacterial infections is urgently needed. The microbiome field is constantly providing us with various health-related properties elicited by the commensals that inhabit their mammalian hosts. Harnessing the potential of these commensals for knowledge about host-microbe interactions as well as useful properties with therapeutic implications will likely to remain a fruitful field for decades to come. In this manuscript, Wang et al use various methods, encompassing classic microbiology, genomics, chemical biology, and immunology, to identify a potent probiotic strain that protects nematode and murine hosts from S. enterica infection. Additionally, authors identify gut metabolites that are correlated with protection, and show that a single metabolite can recapitulate the effects of probiotic administration.

Strengths:

The utilization of varied methods by the authors, together with the impressive amount of data generated, to support the claims and conclusions made in the manuscript is a major strength of the work. Also, the ability the move beyond simple identification of the active probiotic, also identifying compounds that are at least partially responsible for the protective effects, is commendable.

Weaknesses:

No major weaknesses noted.

Reviewer #1 (Public review):

Shin et al. conduct extensive electrophysiological and behavioral experiments to study the mechanisms of short-term synaptic plasticity at excitatory synapses in layer 2/3 of the rat medial prefrontal cortex. The authors interestingly find that short-term facilitation is driven by progressive overfilling of the readily releasable pool, and that this process is mediated by phospholipase C/diacylglycerol signaling and synaptotagmin-7 (Syt7). Specifically, knockdown of Syt7 not only abolishes the refilling rate of vesicles with high fusion probability, but it also impairs the acquisition of trace fear memory.

Overall, the authors offer novel insight to the field of synaptic plasticity through well-designed experiments that incorporate a range of techniques.

Comments on revisions:

The authors have adequately addressed my earlier comments and questions.

Reviewer #1 (Public review):

Summary:

This study provides comprehensive instructions for using the chromatophore tracking software, Chromas, to track and analyse the dynamics of large numbers of cephalopod chromatophores across various spatiotemporal scales. This software addresses a long-standing challenge faced by many researchers who study these soft-bodied creatures, known for their remarkable ability to change colour rapidly. The updated software features a user-friendly interface that can be applied to a wide range of applications, making it an essential tool for biologists focused on animal dynamic signalling. It will also be of interest to professionals in the fields of computer vision and image analysis.

Strengths:

This work provides detailed instructions for this toolkit along with examples for potential users to try. The Gitlab inventory hosts the software package, installation documentation, and tutorials, further helping potential users with a less steep learning curve.

Weaknesses:

The evidence supporting the authors' claims is solid, particularly demonstrated through the use of cuttlefish and squid. However, it may not be applicable to all coleoid cephalopods yet, such as octopuses, which have an incredibly versatile ability to change their body forms.

Reviewer #1 (Public review):

This paper presents a set of tools that will pave the way for a comprehensive understanding of the circuits that control wing motion in flies during flight or courtship. These tools are mainly focused on wing motor neurons and interneurons, as well as a few motor neurons of the haltere. This paper and the library of driver lines described within it will serve as a crucial resource in the pursuit of understanding how neural circuits give rise to behavior. Overall, I found the paper well-written, the figures are quite nice, and the data from the functional experiments convincing. I do not have many major concerns, but a few suggestions that I think will make the paper easier to understand.

I think the introduction could use some reorganization, as right now I found it quite difficult to follow. For example, lines 85-88 seem to fit more naturally at the end of the next paragraph, compared to the current location of those sentences, which feels rather disjointed. I would suggest introducing the organization of the wing motor system (paragraphs 3 and 4) and then discussing the VNC (paragraph 2) before moving on to describe the neurons within the VNC that may control wing motion. Additionally, lines 141-144, which describe the broad subdivisions of the VNC, can be moved up to where the VNC is first introduced.

One of my major takeaways from the paper is the call to examine the premotor circuits that govern wing motion. For that reason, I was surprised that there was little mention of the role of sensory input to these circuits. As the authors point out in the discussion, the haltere, for example, provides important input to the wing steering system. I recognize that creating driver lines for the sensory neurons that innervate the VNC is well beyond the scope of this project. I would just like some clarification in the text of the role these inputs play in structuring wing motion, especially as some act at rapid timescales that possibly forgo processing by the very circuits detailed here. This brings up a related issue: if the roles of the interneurons that are presynaptic to the wing motor neurons are "largely unexplored," with how much confidence can we say that they are the key for controlling behavior? To be sure, this has been demonstrated quite nicely in the case of courtship, but in flight, I think the evidence supporting this argument is less clear. I suggest the authors rephrase their language here.

Reviewer #1 (Public review):

Summary:

The authors validate the contribution of RAP2A to GB progression. RAp2A participates in asymmetric cell division, and the localization of several cell polarity markers, including cno and Numb.

Strengths:

The use of human data, Drosophila models, and cell culture or neurospheres is a good scenario to validate the hypothesis using complementary systems.

Moreover, the mechanisms that determine GB progression, and in particular glioma stem cells biology, are relevant for the knowledge on glioblastoma and opens new possibilities to future clinical strategies.

Weaknesses:

While the manuscript presents a well-supported investigation into RAP2A's role in GBM, several methodological aspects require further validation. The major concern is the reliance on a single GB cell line (GB5), which limits the generalizability of the findings. Including multiple GBM lines, particularly primary patient-derived 3D cultures with known stem-like properties, would significantly enhance the study's relevance.

Additionally, key mechanistic aspects remain underexplored. Further investigation into the conservation of the Rap2l-Cno/aPKC pathway in human cells through rescue experiments or protein interaction assays would be beneficial. Similarly, live imaging or lineage tracing would provide more direct evidence of ACD frequency, complementing the current indirect metrics (odd/even cell clusters, Numb asymmetry).

Several specific points raised in previous reviews still require attention:

(1) The specificity of Rap2l RNAi needs further confirmation. Is Rap2l expressed in neuroblasts or intermediate neural progenitors? Can alternative validation methods be employed?

(2) Quantification of phenotypic penetrance and survival rates in Rap2l mutants would help determine the consistency of ACD defects.

(3) The observations on neurosphere size and Ki-67 expression require normalization (e.g., Ki-67+ cells per total cell number or per neurosphere size). Additionally, apoptosis should be assessed using Annexin V or TUNEL assays.

(4) The discrepancy in Figures 6A and 6B requires further discussion.

(5) Live imaging of ACD events would provide more direct evidence.

(6) Clarification of terminology and statistical markers (e.g., p-values) in Figure 1A would improve clarity.

(7) Given the group's expertise, an alternative to mouse xenografts could be a Drosophila genetic model of glioblastoma, which would provide an in vivo validation system aligned with their research approach.

Reviewer #1 (Public review):

Summary:

Cording et al. investigated how deletion of CNTNAP2, a gene associated with autism spectrum disorder, alters corticostriatal engagement and behavior. Specifically, the authors present slice electrophysiology data showing that striatal projection neurons (SPNs) are more readily driven to fire action potentials in response to stimulation of corticostriatal afferents, and this is due to increases in SPN intrinsic excitability rather than changes in excitatory or inhibitory synaptic inputs. Specifically, these changes seem to be due to preferential reduction of Kv1.2 in dSPNs. The authors separately show that CNTNAP2 mice display repetitive behaviors, enhanced motor learning and cognitive inflexibility. Overall, the authors' conclusions are supported by their data, but a few claims could use some more evidence to be convincing.

Strengths:

The use of multiple behavioral techniques, both traditional and cutting-edge machine learning-based analyses, provides a powerful means of assessing repetitive behaviors and behavioral transitions/rigidity. Characterization of both excitatory and inhibitory synaptic responses in slice electrophysiology experiments offers a broad survey of the synaptic alterations that may lead to increased corticostriatal engagement of SPNs.

Weaknesses:

As it stands, the reported changes in dorsolateral striatum SPN excitability are only correlative with reported changes in repetitive behaviors, motor learning and cognitive flexibility. The authors do broach this in the text (particularly in "Limitations and future directions").

Reviewer #1 (Public review):

I was glad to see that the other reviewer and I had similar takeaways on the subjects of historical literature and paedomorphism. While the authors have adequately considered a more historical body of literature, they have not addressed the concerns we had with statements about paedomorphism. I'm inclined to agree with the other reviewer that the discussion on paedomorphism should be cut entirely. My comments below are to seek clarity and make sure you are saying what you intend to say.

Strengths:

Table 1 is the beginning of a useful glossary and possible character definitions with character states that can be coded for phylogenetic analyses. This is particularly important because the goal of the paper is to define terms for chondrichthyan skeletal features in order to unify research questions in the field, and add novel data on how these features might be distributed among chondrichthyan clades, starting with ratfish and little skate.

Opportunities:

Table 1 should be translated into a format reflecting 0s and 1s etc that can be coded and referred back to the matrix that is in Figure 7 (or a standalone matrix as an appendix). Right now, they do not correspond and thus it is challenging to follow and interpret the mapped characters on the tree. You are presuming reversals when you could just list the state and let the data show you the possibility of character transitions.

Figure 1 essentially shows two datapoints Holocephali and Elasmobranchi where holocephali have low TMD and Elasmobranchi have high TMD, therefore nothing directional from an ancestral to derived state. Also, because you drop the catshark from later figures/analysis, you are treating the ratfish and the little skate as sister taxa so you cannot determine which is paedomorphic and which is peramorphic. Unfortunately, the position of where the characters were mapped on Figure 7 is not able to help you determine ancestral states and therefore actually test for paedomorphism. Two sister taxa with two different conditions and no outgroup doesn't explain the TMD in Ratfishes is statistically different from that of little skates. But there is no direction. So you need to be able to reconstruct that state.

Paedomorphosis implies juvenile ancestral organization in actual existing adult stages of modern descendants. You haven't shown that yet. Only that there might be different rates of mineralization in little skates. I suggested that you datamine the literature for other stages if you think you can fill in gaps.

In the response to reviewers, the authors stated that: "... we had reported that the TMD of centra from little skate did significantly increase between stage 32 and 33. Supporting our argument that ratfish had features of little skate embryos, TMD of adult ratfish centra was significantly lower than TMD of adult skate centra (Fig 1). Also, it was significantly higher than stage 33 skate centra, but it was statistically indistinguishable from that of stage 33 and juvenile stages of skate centra. While we do agree that more samples from these and additional groups would bolster these data, we feel they are sufficiently powered to support our conclusions for this current paper."

I will respond to that. In Figure 6L, yes, A little skate stage 33 is significantly different than stage 32, though the SD bars for ratfish appear to overlap with the range for little skate 32. Also, ratfish values are not significantly different than state 33 or juvenile ratfish. You can add the adult little skate data from figures 1 to 6L and then state, "centra of adult ratfish have a TDM within the range of juvenile LS33 little skates." As per conversation earlier, it still doesn't account for paedomorphism, however, it does indicate different amounts of mineralization, and could indicate you hypothesize about rates of mineralization. I think you have a different discussion waiting to replace this one.

Joint Public Review:

Carabalona and colleagues investigated the role of the membrane-deforming cytoskeletal regulator protein Abba (MTSS1L/MTSS2) in cortical development to better understand the mechanisms of abnormal neural stem cell mitosis. The authors used short hairpin RNA targeting Abba20 with a fluorescent reporter coupled with in utero electroporation of E14 mice to show changes to neural progenitors. They performed flow cytometry for in-depth cell cycle analysis of Abba-shRNA impact to neural progenitors and determined an accumulation in S phase. Using culture rat glioma cells and live imaging from cortical organotypic slides from mice in utero electroporated with Abba-shRNA, the authors found Abba played a prominent role in cytokinesis. They then used a yeast-two-hybrid screen to identify three high confidence interactors: Beta-Trcp2, Nedd9, and Otx2. They used immunoprecipitation experiments from E18 cortical tissue coupled with C6 cells to show Abba requirement for Nedd9 localization to the cleavage furrow/cytokinetic bridge. The authors performed an shRNA knockdown of Nedd9 by in utero electroporation of E14 mice and observed similar results as with the Abba-shRNA. They tested a human variant of Abba using in utero electroporation of cDNA and found disorganized radial glial fibers and misplaced, multipolar neurons, but lacked the impact of cell division seen in the shRNA-Abba model.

[Editors' note: the authors have responded to two sets of reviews, which can be found here, https://doi.org/10.7554/eLife.92748.2, and here, https://doi.org/10.7554/eLife.92748.1]

Reviewer #1 (Public review):

Summary:

Qi and colleagues investigated the role of Kallistatin pathway in increasing hippocampal amyloid-β plaques accumulation and tau hyperpholphorylation in Alzheimer's disease, linking the increased Kallistatin level in diabetic patients with a higher risk of Alzheimer's disease development. A Kallistatin overexpressing animal model was utilized, and memory impairment was assessed using Morris water maze and Y-maze. Kallistatin-related pathway protein levels were measured in the hippocampus, and phenotypes were rescued using fenofibrate and rosiglitazone. The current study provides evidence of a novel molecular mechanism linking diabetes and Alzheimer's disease, and suggests the potential use of fenofibrate to alleviate memory impairment. However, several issues need to be addressed before further consideration.

Strengths:

The finding of this study is novel. The finding will have great impacts on diabetes and AD research. The studies were well conducted, and results convincing.

Weaknesses:

(1) The mechanism by which fenofibrate rescues memory loss in Kallistatin-transgenic mice is unclear. As a PPARα agonist, does fenofibrate target the Kallistatin pathway directly or indirectly? Please provide discussion based on literature supporting either possibility.<br /> (2) The current study exclusively investigated hippocampus. What about other cognitive memory-related regions, such as prefrontal cortex? Including data from these regions or discussing the possibility of their involvement could provide a more comprehensive understanding of the role of Kallistatin in memory impairment.<br /> (3) Fenofibrate rescued phenotypes in Kallistatin-transgenic mice while rosiglitazone, a PPARα agonist, did not. This result contradicts the manuscript's emphasis on a PPARα-associated mechanism. Please address this inconsistency.<br /> (4) Most of the immunohistochemistry images are unclear. Inserts have similar magnification to the original representative images, making judgments difficult. Please provide larger inserts with higher resolution.<br /> (5) The immunohistochemistry images in different figures were taken from different hippocampal subregions with different magnifications. Please maintain consistency, or explain why CA1, CA3 or DG was analyzed in each experiment.<br /> (6) Figure 5B is missing a title. Please add a title to maintain consistency with other graphs.<br /> (7) Please list statistical methods used in the figure legends, such as t-test or One way ANOVA with post-hoc tests.

Comments on revisions:

The authors have addressed the issues raised from the review. The manuscript has been revised accordingly.

Reviewer #1 (Public review):

The authors investigated the role of the C. elegans Flower protein, FLWR-1, in synaptic transmission, vesicle recycling, and neuronal excitability. They confirmed that FLWR-1 localizes to synaptic vesicles and the plasma membrane and facilitates synaptic vesicle recycling at neuromuscular junctions. They observed that hyperstimulation results in endosome accumulation in flwr-1 mutant synapses, suggesting that FLWR-1 facilitates the breakdown of endocytic endosomes. Using tissue-specific rescue experiments, the authors showed that expressing FLWR-1 in GABAergic neurons restored the aldicarb-resistant phenotype of flwr-1 mutants to wild-type levels. By contrast, cholinergic neuron expression did not rescue aldicarb sensitivity at all. They also showed that FLWR-1 removal leads to increased Ca2+ signaling in motor neurons upon photo-stimulation. From these findings, the authors conclude that FLWR-1 helps maintain the balance between excitation and inhibition (E/I) by preferentially regulating GABAergic neuronal excitability in a cell-autonomous manner.

Overall, the work presents solid data and interesting findings, however the proposed cell-autonomous model of GABAergic FLWR-1 function may be overly simplified in my opinion.

Most of my previous comments have been addressed; however, two issues remain.

(1) I appreciate the authors' efforts conducting additional aldicarb sensitivity assays that combine muscle-specific rescue with either cholinergic or GABergic neuron-specific expression of FLWR-1. In the revised manuscript, they conclude, "This did not show any additive effects to the pure neuronal rescues, thus FLWR-1 effects on muscle cell responses to cholinergic agonists must be cell-autonomous." However, I find this interpretation confusing for the reasons outlined below.

Figure 1 - Figure Supplement 3B shows that muscle-specific FLWR-1 expression in flwr-1 mutants significantly restores aldicarb sensitivity. However, when FLWR-1 is co-expressed in both cholinergic neurons and muscle, the worms behave like flwr-1 mutants and no rescue is observed. Similarly, cholinergic FLWR-1 alone fails to restore aldicarb sensitivity (shown in the previous manuscript). These observations indicate a non-cell-autonomous interaction between cholinergic neurons and muscle, rather than a strictly muscle cell-autonomous mechanism. In other words, FLWR-1 expressed in cholinergic neurons appears to negate or block the rescue effect of muscle-expressed FLWR-1. Therefore, FLWR-1 could play a more complex role in coordinating physiology across different tissues. This complexity may affect interpretations of Ca2+ dynamics and/or functional data, particularly in relation to E/I balance, and thus warrants careful discussion or further investigation.

[Editor's note: The authors edited the text of the manuscript to acknowledge potential complexities in the interpretations of these results.]

(2) The revised manuscript includes new GCaMP analyses restricted to synaptic puncta. The authors mention that "we compared Ca2+ signals in synaptic puncta versus axon shafts, and did not find any differences," concluding that "FLWR-1's impact is local, in synaptic boutons." This is puzzling: the similarity of Ca2+ signals in synaptic regions and axon shafts seems to indicate a more global effect on Ca2+ dynamics or may simply reflect limited temporal resolution in distinguishing local from global signals due to rapid Ca2+ diffusion. The authors should clarify how they reached the conclusion that FLWR-1 has a localized impact at synaptic boutons, given that synaptic and axonal signals appear similar. Based on the presented data, the evidence supporting a local effect of FLWR-1 on Ca2+ dynamics appears limited.

[Editor's note: The authors acknowledged that some wording in the previous version was misleading and inaccurate. In the revised version, the authors have withdrawn the conclusion that FLWR-1 function is local in synaptic boutons.]

Reviewer #1 (Public review):

Summary:

In this study, Xiao et al. conducted a comprehensive analysis of retroperitoneal liposarcoma (RPLS) by classifying patients into two distinct molecular subgroups based on whole transcriptome sequencing data from 88 cases. The G1 subgroup demonstrated a metabolic activation signature, whereas the G2 subgroup was characterized by enhanced cell cycle regulation and DNA damage repair pathways. Notably, the G2 subgroup exhibited more aggressive molecular profiles and poorer clinical prognosis compared to the G1 subgroup. Through the application of machine learning algorithms, the authors established a streamlined classification system, identifying LEP and PTTG1 as pivotal molecular biomarkers for differentiating between these two RPLS subgroups. The manuscript presents a well-structured and methodologically sound study, with particular significance attributed to its substantial sample size and the development of a clinically applicable classification framework. This innovative model holds considerable promise for advancing personalized treatment strategies and improving clinical outcomes for RPLS patients.

Comments on revisions:

The authors have adequately addressed all my concerns, and I have no further comments.

Reviewer #1 (Public review):

Summary:

In this manuscript, Dong et al. study the directed cell migration of tracheal stem cells in Drosophila pupae. The migration of these cells which are found in two nearby groups of cells normally happens unidirectionally along the dorsal trunk towards the posterior. Here, the authors study how this directionality is regulated. They show that inter-organ communication between the tracheal stem cells and the nearby fat body plays a role. They provide compelling evidence that Upd2 production in the fat body and JAK/STAT activation in the tracheal stem cells plays a role. Moreover, they show that JAK/STAT signalling might induce the expression of apicobasal and planar cell polarity genes in the tracheal stem cells which appear to be needed to ensure unidirectional migration. Finally, the authors suggest that trafficking and vesicular transport of Upd2 from the fat body towards the tracheal cells might be important.

Strengths:

The manuscript is well written. This novel work demonstrates a likely link between Upd2-JAK/STAT signalling in the fat body and tracheal stem cells and the control of unidirectional cell migration of tracheal stem cells. The authors show that hid+rpr or Upd2RNAi expression in a fat body or Dome RNAi, Hop RNAi, or STAT92E RNAi expression in tracheal stem cells results in aberrant migration of some of the tracheal stem cells towards the anterior. Using ChIP-seq as well as analysis of GFP-protein trap lines of planar cell polarity genes in combination with RNAi experiments, the authors show that STAT92E likely regulates the transcription of planar cell polarity genes and some apicobasal cell polarity genes in tracheal stem cells which appear to be needed for unidirectional migration. Moreover, the authors hypothesise and provide some supporting evidence that extracellular vesicle transport of Upd2 might be involved in this Upd2-JAK/STAT signalling in the fat body and tracheal stem cells, which is quite interesting. Overall, the work presented here provides some novel insights into the mechanism that ensures unidirectional migration of tracheal stem cells that prevents bidirectional migration. This might have important implications for other types of directed cell migration in invertebrates or vertebrates including cancer cell migration.

Weaknesses:

It remains somewhat unclear how Upd2 transported in extracellular vesicles would bind to the Dome receptor found on the surface of the tracheal cells? How Upd2 would be released from vesicles to bind Dome extracellularly and activate the JAK-STAT pathway?

Reviewer #1 (Public review):

Summary:

In their manuscript, Li and colleagues introduce a pioneering investigation into the molecular and epigenetic foundations of neuroendocrine transdifferentiation in prostate cancer. By employing a genetically engineered cellular reprogramming approach, they elucidate the pivotal roles of ASCL1 and NeuroD1 as pioneer transcription factors that suppress AR signaling and orchestrate lineage plasticity toward NEPC. Their integrative multi-omics methodology delineates dynamic transcriptional and chromatin reorganization processes, offering profound insights into mechanisms of therapeutic resistance.

Strengths:

(1) The development of a reproducible in vitro reprogramming platform to transition ARPC cells into NEPC represents a significant technical achievement. This model enables high-resolution temporal analysis of NEtD, addressing constraints inherent in traditional PDX systems.

(2) The authors reveal that ASCL1 and NeuroD1 suppress AR signaling through chromatin structural modifications at somatically amplified AR enhancers, a significant discovery that clarifies the longstanding ambiguity surrounding AR pathway inactivation during lineage plasticity.

(3) The integration of RNA sequencing, CUT&RUN, and single-cell multiomic profiling delivers a holistic perspective on dynamic epigenetic and transcriptional reprogramming during NEtD. Their observation that AR suppression precedes NE marker activation provides chronological insights into this process.

(4) By delineating the distinct roles of ASCL1/NeuroD1-driven NE lineage programs versus REST inactivation, the study critiques the excessive dependence on limited immunohistochemical indicators for NEPC classification, directly informing improvements in molecular diagnostics.

(5) The association of ASCL1/NeuroD1 with MHC class I suppression mediated by PRC2 unveils opportunities for combining agents targeting epigenetic modifiers with immune-based therapies to counteract immune evasion in NEPC.

Weaknesses:

While the study is methodologically robust, a modest limitation lies in its primary reliance on established cell lines for mechanistic exploration. Although key observations are corroborated with clinical samples, additional validation in PDX models or organoid systems could enhance translational applicability. Furthermore, while the role of ASCL1/NeuroD1 in AR enhancer silencing is convincingly demonstrated, the upstream regulatory mechanisms governing ASCL1/NeuroD1 induction under therapeutic stress remain unaddressed, a compelling avenue for future research.

Reviewer #1 (Public review):

Summary:

This is an interesting manuscript by Kirk and colleagues describing a highly valuable knock-down system that leverages CRISPRi in order to further elucidate the role of the Kruppel-Like Factor (KLF) transcription factor family in regulating the maturation of postnatal cortical projection neurons. The authors firstly use RNA-Seq and ATAC-Seq data in order to identify the KLF TF family as a potential regulator of cortical neuron maturation in the postnatal brain and subsequently knock down four KLF family members; KLF9, KL13, KLF6 and KLF7, in order to ascertain the functions of specific KLF genes in the developing cortex. The described CRISPRi knock down strategy is highly robust and penetrant as evidenced by a KD efficiency > 95% (assessed by both qPCR and single molecule FISH) and demonstrates that KLF6 and KLF7 play an activating role in driving the expression of target genes relating to axonal growth whereas KLF9 and 13 play a repressive role that inhibits the expression of overlapping gene targets. Together, the authors propose a model where the KLF TF family acts as a regulatory "switch" from activation to repression in the postnatal cortex as a mechanism to control a shift in projection neuron function from axonal growth to circuit refinement. The findings and conclusions of the manuscript offer a valuable contribution to the field of postnatal cortical development and further our understanding of the regulatory mechanisms that govern neuron maturation.

The conclusions of this manuscript are generally supported by the data, but some aspects of the data collection and analysis require some further clarification. Specifically:

(1) The authors comprehensively assess the molecular effects of KLF TF knock-down, however, the authors do not deeply address the cellular effects of these knock-downs. The authors conclude that knockdown of KLF6/7 and KLF9/13 cause downregulation and upregulation, respectively, of a common set of genes involved in cytoskeletal or axon regulation such as Tubb2 and Dpysl3. How is the morphology of the cells affected by these knockdowns? For example, does KLF9/13 knockdown cause neurite/axonal outgrowth? The authors should perform some basic experiments to assess changes in cell morphology following KLF TF KD. This is the one key point that needs addressing, in my opinion.

(2) The authors identify 374 DEGs in P10 Klf6/7 KD neurons and 115 DEGs at P20 (figure 6B). Have the authors looked to see what proportion of these DEGs are upregulated in the KLF9/13 KDs in order to get a more global understanding of the degree of overlap in the genes regulated by the KLF family members? Along similar lines, the authors later indicate that there are 144 shared targets between the KLF activator and repressor pairs (Figure 7C). What percentage does this represent of the total number of DEGs between the KLF pairs. This could further illustrate the degree to which the KLF pairs regulate the same set of genes. If it is already indicated in the manuscript, it should be made a bit more clear to the reader.

(3) Figures 5B and 6D2 are very interesting as they relate the changes in gene expression over time in neurons from P2 to P30 to the functions of KLF9/13 and KLF6/7, respectively. I would be curious to see how these two forms of analyses overlap with one another. For example, in Figure 6D2, where would the KLF9/13 upregulated genes fall on the plot shown in Figure 6D2? And would those overlapping genes fit a similar correlation?

(4) Figure 7E shows expression levels of shared KLF TF targets in control or KD conditions. Interestingly, the expression of Tubb2b, shows higher expression in ScrGFP P10 when compared to KLF9/13 P20, suggesting that derepression of KLF9/13 does not fully restore the expression level of Tubb2b seen at P10. This may suggest that other repressive regulators may be involved in the downregulation of Tubb2b from P10 to P20. Can the authors further comment on this, perhaps in the discussion, and speculate if there are other regulatory factors at play that may be controlling some of the shared targets by KLF6/7 and KLF9/13?

Reviewer #1 (Public review):

It is well established that many potivirids (viruses in the Potiviridae family), particularly potyviruses (viruses in the Potyvirus genus), recruit (selectively) either eIF4E or eIF(iso)4E, while some others can use both of them to ensure a successful infection. CBSD caused by two potyvirids, i.e., ipomoviruses CBSV and UCBSV, severely impedes cassava production in West Africa. In a previous study (PBI, 2019), Gomez and Lin (co-first authors), et al. reported that cassava encodes five eIF4E proteins, including eIF4E, eIF(iso)4E-1, eIF(iso)4E-2, nCBP-1 and nCBP-2, and CBSV VPg interacts with all of them (Co-IP data). Simultaneous CRISPR/Cas9-mediated editing of nCBp-1 and -2 in cassava significantly mitigates CBSD symptoms and incidence. In this study, Lin et al further generated all five eIF4E family single mutants as well as both eIF(iso)4E-1/-2 and nCBP-1/-2 double mutants in a farmer-preferred casava cultivar. They found that both eIF(iso)4E and nCBP double mutants show reduced symptom severity, and the latter is of better performance. Analysis of mutant sequences revealed one important point mutation, L51F of nCBP-,2 that may be essential for the interaction with VPg. The authors suggest that the introduction of the L51F mutation into all five eIF4E family proteins may lead to strong resistance. Overall I believe this is an important study enriching knowledge about eIF4E as a host factor/susceptibility factor of potyvirids and proposing new information for the development of high CBSD resistance in cassava. I suggest the following two major comments for authors to consider for improvement:

(1) As eIF(iso)4e-1/-2 or nCBP-1/-2 double mutants show resistance, why not try to generate a quadruple mutant? I believe it is technically possible through conventional breeding.

(2) I agree that L51F mutation may be important. But more evidence is needed to support this idea. For example, the authors may conduct a quantitative Y2H assay on the binding of VPg to each of the eIF4E (L51F) mutants. Such data may add as additional evidence to support your claim.

Reviewer #1 (Public review):

Summary:

In this manuscript the authors test the hypothesis that gonadal steroid signaling influences the transcriptional development of specific neurons in the mPOA during adolescence, and that such adolescent development of the mPOA is necessary for mating behaviors.

Strengths:

The authors establish a role GABAergic-Esr1 neurons in mating behaviors of both male and female mice. Differentially expressed genes are compared across adolescent development and between sexes. Single-cell sequencing is used to resolve clusters of cells based on transcript levels, and in situ hybridization is used to visualize anatomical expression patterns. The research presented is thorough and rigorous and contributes new insight into hormone-sensitive transcriptional profiles within genetically defined neuron clusters in the mPOA during adolescence.

Weaknesses: Two minor comments

(1) Fig 4 (hormone treatment): In this experiment, testosterone is given to males, yet in Sup Fig 6 it is argued that Esr1 is more influential in driving transcriptional changes compared to AR. Does DHT treatment have the same outcome as testosterone? Or, does estrogen treatment in males have the same outcome as testosterone?

(2) Fig 3i: There appears to be an age-dependent transcriptional change in male Vgat HR-low cells. Can the authors comment on age-dependent (hormone-independent) transcriptional changes in males versus females.

Reviewer #1 (Public review):

Summary:

This study presents a valuable contribution of NO signaling in zebrafish retinal regeneration in larval animals. The data on NO signaling are solid; however, the link to cxcl118b is inadequate. There are significant concerns that the RNA-seq studies largely repeat the work of a previous study done in adult animals, which is a more relevant biological variable for translational insights.

Strengths:

New data on NO signaling are valuable to the field, but may be limited to larval "regeneration".

Weaknesses:

(1) The authors state that more is known about glial reactivation than cell-cycle re-entry. They are confusing many points here. More gene networks that require cell-cycle re-entry are known. Some of the genes listed for "reactivation" are, in fact, required for cell cycle re-entry/proliferation. And the authors confuse gliosis vs glial reactivation.

(2) A major weakness of the approach is testing cone ablation and regeneration in early larval animals. For example, cones are ablated starting the day that they are born. MG that are responding are also very young, less than 48 hrs old. It is also unclear whether the immune response of microglia is a mature response. All of these assays would be of higher significance if they were performed in the context of a mature, fully differentiated, adult retina. All analysis in the paper is negatively affected by this biological variable.

(3) Related to the above point, the clonal analysis of cxcl18b+ MG is complicated by the fact that new MG are still being born in the CMZ (as are new cones for that matter).

(4) A near identical study was already done by Hoang et al., 2020, in adult zebrafish, a more relevant biological timepoint. Did the authors check this published RNA-seq database for their gene(s) of interest?

(5) KD of cxcl18b did not affect MG proliferation or any other defined outcome. And yet the authors continually state such phrases as "microglia-mediated inflammation is critical for activating the cxcl18b-defined transitional states that drive MG proliferation." This is false. Cxcl18b does not drive MG proliferation at all.

(6) A technical concern is that intravitreal injections are not routinely performed in larval fish.

Reviewer #1 (Public review):

Summary:

In this paper, the authors developed a chemical labeling reagent for P2X7 receptors, called X7-uP. This labeling reagent selectively labels endogenous P2X7 receptors with biotin based on ligand-directed NASA chemistry (Ref. 41). After labeling the endogenous P2X7 receptor with biotin, the receptor can be fluorescently labeled with streptavidin-AlexaFluor647. The authors carefully examined the binding properties and labeling selectivity of X7-uP to P2X7, characterized the labeling site of P2X7 receptors, and demonstrated fluorescence imaging of P2X7 receptors. The data obtained by SDS-PAGE, Western blot, and fluorescence microscopy clearly show that X7-uP labels the P2X7 receptor. Finally, the authors fluorescently labeled the endogenous P2X7 in BV2 cells, which are a murine microglia model, and used dSTORM to reveal a nanoscale P2X7 redistribution mechanism under inflammatory conditions at high resolution.

Strengths:

X7-uP selectively labels endogenous P2X7 receptors with biotin. Streptavidin-AlexaFluor647 binds to the biotin labeled to the P2X7 receptor, allowing visualization of endogenous P2X7 receptors.

Weaknesses:

Weaknesses & Comments<br /> (1) The P2X7 receptor exists in a trimeric form. If it is not a monomer under the conditions of the pull-down assay in Figure 2C, the quantitative values may not be accurate.<br /> (2) In Figure 3, GFP fluorescence was observed in the cell. Are all types of P2X receptors really expressed on the cell surface ?<br /> (3) The reviewer was not convinced of the advantages of the approach taken in this paper, because the endogenous receptor labeling in this study could also be done using conventional antibody-based labeling methods.<br /> (4) Although P2X7 was successfully labeled in this paper, it is not new as a chemistry. There is a need for more attractive functional evaluation such as live trafficking analysis of endogenous P2X7.<br /> (5) The reviewer has concerns that the use of the large-size streptavidin to label the P2X7 receptor may perturbate the dynamics of the receptor.<br /> (6) It is better to directly label Alexa647 to the P2X7 receptor to avoid functional perturbation of P2X7.<br /> (7) In all imaging experiments, the addition of streptavidin, which acts as a cross-linking agent, may induce P2X7 receptor clustering. This concern would be dispelled if the receptors were labeled with a fluorescent dye instead of biotin and observed.<br /> (8) There are several mentions of microglia in this paper, even though they are not used. This can lead to misunderstanding for the reader. The author conducted functional analysis of the P2X7 receptor in BV-2 cells, which are a model cell line but not microglia themselves. The text should be reviewed again and corrected to remove the misleading parts that could lead to misunderstanding.<br /> e.g. P8. lines 361-364. First, it combines N-cyanomethyl NASA chemistry with the high-affinity AZ10606120 ligand, enabling rapid labeling in microglia (within 10 min)<br /> P8. lines 372-373. Our results not only confirm P2X7 expression in microglia, as previously reported (6, 26-33), but also reveal its nanoscale localization at the cell surface using dSTORM.

Reviewer #1 (Public review):

Although the use of antimony has been discontinued in India, the observation that Leishmania parasites resistant to antimony are in circulation has been cited as evidence that these resistant parasites are now a distinct strain with properties that ensure their transmission and persistence. It is of interest to determine the properties that favor the retention of their drug resistance phenotype even in the absence of the selective pressure that the drug would otherwise exert. The hypothesis that these authors set out to test is that these parasites have developed a new capacity to acquire and utilize lipids, especially cholesterol, which enables them to grow robustly in infected hosts. The authors present compelling evidence that supports their hypothesis. However, the genetic basis for the parasite's gluttony for lipids remains unresolved.

An issue raised in the initial review was the insufficient detail in the discussion of experiments in which parasitophorous vacuoles were isolated from infected cells and their molecular content was investigated. In this new version, the authors have provided more details of those experiments, including the relative enrichment of the preparations.

A puzzling observation for which they provide compelling evidence is the capacity of LD-R parasites to undergo logarithmic growth between 4 and 24 hours in infected cells. Interestingly, after logarithmic growth within the macrophages at those early times, parasite growth slows down inexplicably after 24 hours. One is left to imagine what the consequences of such growth within an infected host will be.

They made the novel observation that Lamp1 expression increases as early as 4 hours after infection with LD-R and by 12 hours after infection with both LD-S and LD-R. Interestingly, transcription analysis did not provide evidence for increased Lamp1 transcripts, leaving open the possibility that parasite infection may exert control over host cell biology at the translational level. How this might be achieved and what genes would be targets for such controls are open questions.

The dynamic changes in lipid biosynthesis pathways, in comparison to lipid uptake and the formation of lipid droplets in infected cells, are tracked. The basis for the beneficial effect of aspirin to stifle parasite resistance to antimony is explored.

Reviewer #2 (Public review):

Summary:

Idiopathic scoliosis (IS) is a common spinal deformity. Various studies have linked genes to IS, but underlying mechanisms are unclear such that we still lack understanding of the causes of IS. The current manuscript analyzes IS patient populations and identified EPHA4 as a novel associated gene, finding three rare variants in EPHA4 from three patients (one disrupting splicing and two missense variants) as well as a large deletion (encompassing EPHA4) in a Waardenburg syndrome patient with scoliosis. EPHA4 is a member of the Eph receptor family. Drawing on data from zebrafish experiments, the authors argue that EPHA4 loss of function disrupts central pattern generator (CPG) function necessary for motor coordination.

Strengths:

The main strength of this manuscript is the human genetic data, which provide convincing evidence linking EPHA4 variants to IS. The loss of function experiments in zebrafish strongly support the conclusion that EPHA4 variants that reduce function lead to IS.

Weaknesses:

The conclusion that disruption of CPG function causes spinal curves in the zebrafish model is not fully supported. The authors' final model is that a disrupted CPG leads to asymmetric mechanical loading on the spine and, over time, the development of curves. This is a reasonable idea, but currently not strongly backed up by data in the manuscript. Potentially, the impaired larval movements simply coincide with, but do not cause, juvenile-onset scoliosis. Support for the authors' conclusion would require independent methods of disrupting CPG function and determining if this is accompanied by spine curvature. Nevertheless, the data showing correlations between spine curvature and abnormal neural patterning, neuronal firing, and swimming in eph4a loss-of-function mutant larvae are sound.

Comments on revisions:

I think the authors misunderstood my point about genetic nomenclature for the zebrafish alleles. The nomenclature guidelines are described at ZFIN, and ZFIN will ask for appropriate allele designations.

Reviewer #1 (Public review):

Public Review

The authors investigated the role of the C. elegans Flower protein, FLWR-1, in synaptic transmission, vesicle recycling, and neuronal excitability. They confirmed that FLWR-1 localizes to synaptic vesicles and the plasma membrane and facilitates synaptic vesicle recycling at neuromuscular junctions. They observed that hyperstimulation results in endosome accumulation in flwr-1 mutant synapses, suggesting that FLWR-1 facilitates the breakdown of endocytic endosomes. Using tissue-specific rescue experiments, the authors showed that expressing FLWR-1 in GABAergic neurons restored the aldicarb-resistant phenotype of flwr-1 mutants to wild-type levels. By contrast, cholinergic neuron expression did not rescue aldicarb sensitivity at all. They also showed that FLWR-1 removal leads to increased Ca2+ signaling in motor neurons upon photo-stimulation. From these findings, the authors conclude that FLWR-1 helps maintain the balance between excitation and inhibition (E/I) by preferentially regulating GABAergic neuronal excitability in a cell-autonomous manner.

Overall, the work presents solid data and interesting findings, however the proposed cell-autonomous model of GABAergic FLWR-1 function may be overly simplified in my opinion.

Most of my previous comments have been addressed; however, two issues remain.

(1) I appreciate the authors' efforts conducting additional aldicarb sensitivity assays that combine muscle-specific rescue with either cholinergic or GABergic neuron-specific expression of FLWR-1. In the revised manuscript, they conclude, "This did not show any additive effects to the pure neuronal rescues, thus FLWR-1 effects on muscle cell responses to cholinergic agonists must be cell-autonomous." However, I find this interpretation confusing for the reasons outlined below.

Figure 1 - Figure Supplement 3B shows that muscle-specific FLWR-1 expression in flwr-1 mutants significantly restores aldicarb sensitivity. However, when FLWR-1 is co-expressed in both cholinergic neurons and muscle, the worms behave like flwr-1 mutants and no rescue is observed. Similarly, cholinergic FLWR-1 alone fails to restore aldicarb sensitivity (shown in the previous manuscript). These observations indicate a non-cell-autonomous interaction between cholinergic neurons and muscle, rather than a strictly muscle cell-autonomous mechanism. In other words, FLWR-1 expressed in cholinergic neurons appears to negate or block the rescue effect of muscle-expressed FLWR-1. Therefore, FLWR-1 could play a more complex role in coordinating physiology across different tissues. This complexity may affect interpretations of Ca2+ dynamics and/or functional data, particularly in relation to E/I balance, and thus warrants careful discussion or further investigation.

(2) The revised manuscript includes new GCaMP analyses restricted to synaptic puncta. The authors mention that "we compared Ca2+ signals in synaptic puncta versus axon shafts, and did not find any differences," concluding that "FLWR-1's impact is local, in synaptic boutons." This is puzzling: the similarity of Ca2+ signals in synaptic regions and axon shafts seems to indicate a more global effect on Ca2+ dynamics or may simply reflect limited temporal resolution in distinguishing local from global signals due to rapid Ca2+ diffusion. The authors should clarify how they reached the conclusion that FLWR-1 has a localized impact at synaptic boutons, given that synaptic and axonal signals appear similar. Based on the presented data, the evidence supporting a local effect of FLWR-1 on Ca2+ dynamics appears limited.

Reviewer #1 (Public review):

Summary:

In this study from Belato, Knight and co-workers, the authors investigated the Rec domain of a thermophilic Cas9 from Geobacillus stearothermophilus (GeoCas9). The authors investigated three constructs, two individual subdomains of Rec (Rec1 and Rec2) and the full Rec domain. This domain is involved in binding to the guide RNA of Cas9, as well as the RNA-DNA duplex that is formed upon target binding. The authors performed RNA binding and relaxation experiments using NMR for the wild-type domain as well as two-point mutants. They observed differences in RNA binding activities as well as the flexibility of the domain. The authors also performed molecular dynamics and functional experiments on full-length GeoCas9 to determine whether these biophysical differences affect the RNA binding or cleavage activity. Although the authors observed some changes in the thermal stability of the mutant GeoCas9-gRNA complex, they did not observe substantial differences in the guide RNA binding or cleavage activities of the mutant GeoCas9 variants.

Overall, this manuscript provides a detailed biophysical analysis of the GeoCas9 Rec domain. The NMR assignments for this construct should prove very useful, and can serve as the basis for future similar studies of GeoCas9 Rec domain mutants. While the two mutants tested in the study did not produce significant differences from wild-type GeoCas9, the study rules out the possibility that analogous mutations can be translated between type II-A and II-C Cas9 orthologs. Together, these findings may provide the grounds for future engineering of higher fidelity variants of GeoCas9

Reviewer #1 (Public review):

Summary.

The authors goal was to map the neural circuitry underlying cold sensitive contraction in Drosophila. The circuitry underlying most sensory modalities has been characterized but noxious cold sensory circuitry has not been well studied. Importantly, they analyze all downstream partner neurons connected to the Class III sensory neurons. The authors achieve their goal and map out sensory and post-sensory neurons involved in this behavior.

Strengths.

The manuscript provides compelling evidence for sensory and post sensory neurons involved in noxious cold sensitive behavior. They use both connectivity data and functional data to identify these neurons. This work is a clear advance in our understanding of noxious cold behavior. The experiments are done with a high degree of experimental rigor.

Weaknesses.

I find no major weaknesses in this work. It is a massive amount of data that clearly shows the role of the Class III neurons in cold-induced larval body contraction.

Reviewer #1 (Public review):

Summary:

In this study, Nakagawa and colleagues report the observation that YAP is differentially localized, and thus differentially transcriptionally active, in spheroid cultures versus monolayer cultures. YAP is known to play a critical role in the survival of drug-tolerant cancer cells, and as such, the higher levels of basally activated YAP in monolayer cultures lead to higher fractions of surviving drug-tolerant cells relative to spheroid culture (or in vivo culture). The findings of this study, revealed through convincing experiments, are elegantly simple and straightforward, yet they add significantly to the literature in this field by revealing that monolayer cultures may actually be a preferential system for studying residual cell biology simply because the abundance of residual cells in this format is much greater than in spheroid or xenograft models. The potential linkage between matrix density and stiffness and YAP activation, while only speculated upon in this manuscript, is intriguing and a rich starting point for future studies.

Although this work, like any important study, inspires many interesting follow-on questions, I am limiting my questions to only a few minor ones, which may potentially be explored either in the context of the current study or in separate, follow-on studies.

Strengths:

The major strengths of the work are described above.

Weaknesses:

Rather than considering the following points as weaknesses, I instead prefer to think of them as areas for future study:

(1) Given the field's intense interest in the biology and therapeutic vulnerabilities of residual disease cells, I suspect that one major practical implication of this work could be that it inspires scientists interested in working in the residual disease space to model it in monolayer culture. However, this relies upon the assumption that drug-tolerant cells isolated in monolayer culture are at least reasonably similar in nature to drug-tolerant cells isolated from spheroid or xenograft systems. Is this true? An intriguing experiment that could help answer this question would be to perform gene expression profiling on a cell line model in the following conditions: monolayer growth, drug tolerant cells isolated from monolayer growth conditions, spheroid growth, drug tolerant cells isolated from spheroid growth conditions, xenograft tumors, and drug tolerant cells isolated from xenograft tumors. What are the genes and programs shared between drug-tolerant cells cultured in the three conditions above? Which genes and programs differ between these conditions? Data from this exercise could help provide additional, useful context with which to understand the benefits and pitfalls of modeling residual tumor cell growth in monolayer culture.

(2) In relation to the point above, there is an interesting and established connection between mesenchymal gene expression and YAP/TAZ signaling. For example, analyses of gene expression data from human tumors and cell lines demonstrate an extremely strong correlation between these two gene expression programs. Further, residual persister cancer cells have often been characterized as having undergone an EMT-like transition. From the analysis above, is there evidence that residual tumor cells with increased YAP signaling also exhibit increased mesenchymal gene expression?

Reviewer #1 (Public review):

Summary

Olfactory sensory neurons (OSNs) in the olfactory epithelium detect myriads of environmental odors that signal essential cues for survival. OSNs are born throughout life and thus represent one of the few neurons that undergo life-long neurogenesis. Until recently, it was assumed that OSN neurogenesis is strictly stochastic with respect to subtype (i.e. the receptor the OSN chooses to express). However, a recent study showed that olfactory deprivation via naris occlusion selectively reduced birthrates of only a fraction of OSN subtypes and indicated that these subtypes appear to have a special capacity to undergo changes in birthrates in accordance with the level of olfactory stimulation. These previous findings raised the interesting question of what type of stimulation influences neurogenesis, since naris occlusion does not only reduce the exposure to potentially thousands of odors, but also to more generalized mechanical stimuli via preventing airflow.

In this study, the authors set out to identify the stimuli that are required to promote the neurogenesis of specific OSN subtypes. Specifically, they aim to test the hypothesis if discrete odorants selectively stimulate the same OSN subtypes whose birthrates are affected. This would imply a highly specific mechanism in which exposure to certain odors can "amplify" OSN subtypes responsive to those odors suggesting that OE neurogenesis serves, in part, an adaptive function.

To address this question, the authors focused on a family of OSN subtypes that had previously been identified to respond to musk-related odors and that exhibit higher transcript levels in the olfactory epithelium of mice exposed to males compared to mice isolated from males. First, the authors confirm via a previously established cell birth dating assay in unilateral naris occluded mice that this increase in transcript levels actually reflects a stimulus-dependent birthrate acceleration of this OSN subtype family. In a series of experiments (in unilateral occluded and non-occluded mice) using the same birth dating assay, they show that several subtypes of this OSN family, but not other "control" subtypes exhibit increased birthrates in response to adolescent male exposure, but not to female exposure.

In the core experiment of the study, they expose unilaterally naris occluded and non-occluded mice to two musk-related odors and two "control" odors (that do not activate musk-responsive OSN subtypes) to test if these odors specifically accelerate the birth rates of OSN types that are responsive to these odors. This experiment reveals that (for the tested odors and OSN subtypes) indeed birthrates are only affected by discrete odorants that stimulate these OSN subtypes (with a complex relationship between birth rate acceleration and odor concentrations) suggesting that OE neurogenesis may serve, in part, as an adaptive function

Strength:

The scientific question is valid and opens an interesting direction. The previously established cell birth dating assay in naris occluded and non-occluded mice is well performed and accompanied by several control experiments addressing potential other interpretations of the data.

In this revised version, the authors added several new experiments addressing the previous concern that only the effect of one specific odor (muscone) on musk-responsive OSN subtypes had been tested to make the general claim that discrete odors specifically accelerate the birth rate of OSN subtypes they stimulate. Now the authors demonstrate that another musk-related odor (ambretone) also induces this effect and that other non-musk odors do not. In addition, they show that two other OSN subtypes that do not respond to musk-related odors are not affected. These experiments further substantiate the above claim.

Weakness:

(1) The main research question of this study was to test if discrete odors specifically accelerate the birth rate of OSN subtypes they stimulate, i.e. does muscone only accelerate the birth rate of OSNs that express muscone-responsive ORs, or vice versa is the birthrate of muscone-responsive OSNs only accelerated by odors they respond to?<br /> As mentioned under "strength" the authors added several experiments to further substantiate their claim. While these controls are very important to show that the observed effect is indeed specific for musk-related odors on musk-responsive OSN subtypes, these experiments still only focus on one closely related family of musk-responsive OSN subtypes. To understand if this phenomenon is a more generalized mechanism and plays a role for other OSN subtypes beyond this small family of related receptors, further experiments showing this effect for other OSN subtypes are critical.

(2) Previous concerns (#2, #4, #5 and #6) about a lack of increase in UNO effect size for olfr1440 under any muscone concentrations, strong fluctuations of newborn neurons on the closed side as well as a seemingly contradicting statement that overstimulation possibly reflects reduced survival have been addressed by adding potential explanations to the text.

In addition, the previous remark (#3) that certain phrases gave the misleading impression that musk-related odors are indeed excreted into male mouse urine at certain concentrations was addressed not only by re-phrasing, but by performing additional experiments. Although these did not deliver clear results (because of technical difficulties), interesting possibilities are discussed.

Reviewer #1 (Public review):

Summary:

In this study, Le et al.. aimed to explore whether AAV-mediated overexpression of Oct4 could induce neurogenic competence in adult murine Müller glia, a cell type that, unlike its counterparts in cold-blooded vertebrates, lacks regenerative potential in mammals. The primary goal was to determine whether Oct4 alone, or in combination with Notch signaling inhibition, could drive Müller glia to transdifferentiate into bipolar neurons, offering a potential strategy for retinal regeneration.

The authors demonstrated that Oct4 overexpression alone resulted in the conversion of 5.1% of Müller glia into Otx2+ bipolar-like neurons by five weeks post-injury, compared to 1.1% at two weeks. To further enhance the efficiency of this conversion, they investigated the synergistic effect of Notch signaling inhibition by genetically disrupting Rbpj, a key Notch effector. Under these conditions, the percentage of Müller glia-derived bipolar cells increased significantly to 24.3%, compared to 4.5% in Rbpj-deficient controls without Oct4 overexpression. Similarly, in Notch1/2 double-knockout Müller glia, Oct4 overexpression increased the proportion of GFP+ bipolar cells from 6.6% to 15.8%.

To elucidate the molecular mechanisms driving this reprogramming, the authors performed single-cell RNA sequencing (scRNA-seq) and ATAC-seq, revealing that Oct4 overexpression significantly altered gene regulatory networks. They identified Rfx4, Sox2, and Klf4 as potential mediators of Oct4-induced neurogenic competence, suggesting that Oct4 cooperates with endogenously expressed neurogenic factors to reshape Müller glia identity.

Overall, this study aimed to establish Oct4 overexpression as a novel and efficient strategy to reprogram mammalian Müller glia into retinal neurons, demonstrating both its independent and synergistic effects with Notch pathway inhibition. The findings have important implications for regenerative therapies as they suggest that manipulating pluripotency factors in vivo could unlock the neurogenic potential of Müller glia for treating retinal degenerative diseases.

Strengths:

(1) Novelty: The study provides compelling evidence that Oct4 overexpression alone can induce Müller glia-to-bipolar neuron conversion, challenging the conventional view that mammalian Müller glia lacks neurogenic potential.<br /> (2) Technological Advances: The combination of Muller glia-specific labeling and modifying mouse line, AAV-GFAP promoter-mediated gene expression, single-cell RNA-seq, and ATAC-seq provides a comprehensive mechanistic dissection of glial reprogramming.<br /> (3) Synergistic Effects: The finding that Oct4 overexpression enhances neurogenesis in the absence of Notch signaling introduces a new avenue for retinal repair strategies.

Weaknesses:

(1) In this study, the authors did not perform a comprehensive functional assessment of the bipolar cells derived from Müller glia to confirm their neuronal identity and functionality.<br /> (2) Demonstrating visual recovery in a bipolar cell-deficiency disease model would significantly enhance the translational impact of this work and further validate its therapeutic potential.

Comments on revisions:

The author answered all my questions and corrected the minor comments, so I have no more comments on the manuscript.

Reviewer #2 (Public review):

This study by Yu and coworkers investigates the potential role of Secretory leukocyte protease inhibitor (SLPI) in Lyme arthritis. They show that, after needle inoculation of the Lyme disease agent, B. burgdorferi, compared to wild type mice, a SLPI-deficient mouse suffers elevated bacterial burden, joint swelling and inflammation, pro-inflammatory cytokines in the joint, and levels of serum neutrophil elastase (NE). They suggest that SLPI levels of Lyme disease patients are diminished relative to healthy controls. Finally, using a powerful screen of secreted mammalian proteins, they find that SLPI interacts directly B. burgdorferi.

The known role of SLPI in dampening inflammation and inflammatory damage by inhibition of NE makes the enhanced inflammation in the joint of B. burgdorferi-infected mice a predicted result but it has not previously been demonstrated and could spur further study. A limitation that is unaddressed experimentally is potential contribution of the greater bacterial burden to the enhanced inflammation, leaving open the question of whether greater immunologic stimulus or a defect in the regulation of inflammation is responsible for the observed enhanced disease. Answering this question would better justify the statement in the abstract that "These data demonstrate the importance of SLPI in suppressing periarticular joint inflammation in Lyme disease."

Although the finding of SLPI binding to bacteria is potentially quite interesting the biological relevance of this interaction is not addressed. Readers of only the abstract, which describes the direct interaction of SLPI with bacteria, may mistakenly conclude that the authors demonstrate that recruitment of this immunoregulatory factor to the bacterial surface enhances inflammation of infected tissues. This attractive possibility has not been demonstrated in this study; such assertion would require comparison of bacteria that either bind or do not bind SLPI in a mouse infection model.

Finally, the investigators take advantage of clinical samples to ask if serum SLPI levels a diminished in Lyme disease patients relative to healthy controls. The assessment of human samples is interesting and generally to be lauded, but here the comparison is limited by: (a) a small sample number, with only 5 healthy control samples (which should not be difficult to obtain); and (b) the inclusion of samples from 4 patients with erythema migrans rather than Lyme arthritis, which was the manifestation tracked in the mouse studies. Moreover, of the 3 Lyme arthritis patients, serum samples from multiple blood draws were included, resulting in 5 data points; similarly, of the 4 erythema migrans patients, 13 separate samples were included. The multiple samplings from some but not all subjects could result in differential "weighting" of samples. Therefore, although the investigators provide a statistical analysis of these data, it is difficult to evaluate the validity of this apparent difference.

In summary, this is an interesting study that provides new information regarding infection in a host deficient in SLPI and, using a state-of-the-art screen of the mammalian secretome to show that B. burgdorferi binds SLPI, raising the attractive possibility that this pathogen utilizes a host immune regulator to enhance inflammation. The conclusions that SLPI enhances inflammation directly due to its immunoregulatory activity and that SLPI levels are diminished in human Lyme disease patients, as well as the implication that SLPI binding by the bacterium has pathogenic significance, each require further study.

Reviewer #1 (Public review):

The paper proposes an interesting perspective on the spatio-temporal relationship between FC in fMRI and electrophysiology. The study found that while similar networks configurations are found in both modalities, there is a tendency for the networks to spatially converge more commonly at synchronous than asynchronous timepoints.

My confidence in the findings and their interpretation has been improved by the addition of some basic simulations. It helps give confidence in the measure being used to distinguish between scenarios.

Of course, there may be other scenarios that are problematic that are not covered by the current simulations - this highlights the difficulty of making a claim based on a heuristic measure.

That said, with the simulations included and if the caveat above is acknowledged, then I think the paper is in good shape.

Instructions on how to add the facilitator as an editor/commenter might help.

Reviewer #1 (Public review):

Summary:

Huntington's disease (HD) is characterized by the expansion of polyglutamine repeats in huntingtin protein (HTT), leading to the formation of aggresomes composed of mutant huntingtin (mHTT). This study investigates the potential therapeutic strategy of enhancing autophagy to clear mHTT. The authors' evaluation of the autophagic-lysosomal pathway (ALP) in human HD brains shows that, in early stages, there is upregulated lysosomal biogenesis and relatively normal autophagy flux, while late-stage brains exhibit impaired autolysosome clearance, suggesting that early intervention may be beneficial. The authors cross the Q175 HD knock-in model with the TRGL autophagy reporter mouse to investigate ALP dynamics in vivo. In these models, mHTT is detected in autophagic vacuoles and colocalizes with autophagy receptors p62/SQSTM1 and ubiquitin. Although ALP alterations in the Q175 model are milder and later onset compared to human HD, they do show lysosome depletion and impaired autophagic flux. Treatment with an mTOR inhibitor in 6-month-old TRGL/Q175 mice normalized lysosome numbers, alleviated aggresome pathology, and reduced mHTT, p62, and ubiquitin levels. These findings suggest that autophagy modulation during the early stages of disease progression may offer potential therapeutic interventions for HD pathology.

Strengths:

Provide supportive animal evidence for mTOR inhibition in enhancing autophagy and reducing toxicity in HD animal models.

Weaknesses:

Lacks animal behavior and survival rate data, particularly regarding whether the extent of motor dysfunction in TRGL/Q175 mice is comparable to that in Q175 mice and whether the administration of mTORi INK improves these symptoms.

Reviewer #1 (Public review):

This report addresses a compelling topic. However, I have significant concerns, which necessitate a reassessment of the report's overall value.

Anatomical Specificity and Stimulation Site:<br /> While the authors clarify that the ventral MGB (MGv) was the intended stimulation target, the electrode track (Fig. 1A) and viral spread (Fig. 2E) suggest possible involvement of the dorsal MGB (MGd) and broader area. Given that MGv-AI and MGd-AC pathways have distinct-and sometimes opposing-effects on plasticity, the reported LTP values (with unusually small standard deviations) raise concerns about the specificity of the findings. Additional anatomical verification would help resolve this issue.

Statistical Rigor and Data Variability:<br /> The remarkably low standard deviations in LTP measurements are unexpected based on established variability in thalamocortical plasticity. The authors' response confirms these values are accurate, but further justification, such as methodological controls or replication-would bolster confidence in these results. Additionally, the comparison of in vivo vs. in vitro LTP variability requires more substantive support.

Viral Targeting and Specificity:<br /> The manuscript does not clearly address whether cortical neurons were inadvertently infected by AAV9. Given the potential for off-target effects, explicit confirmation (e.g., microphotograph of stimulation site) would strengthen the study's conclusions.

Integration of Prior Literature:<br /> The discussion of existing work is adequate but could be more comprehensive. A deeper engagement with contrasting findings would provide better context for the study's contributions.

Therapeutic Implications:<br /> The authors' discussion of therapeutic potential is now appropriately cautious and well-reasoned.

Conclusion:<br /> While the study presents intriguing findings, the concerns outlined above must be addressed to fully establish the validity and impact of the results. I appreciate the authors' efforts thus far and hope they can provide additional data or clarification to resolve these issues. With these revisions, the manuscript could make a valuable contribution to the field.

Reviewer #1 (Public review):

Summary:

The manuscript provides a novel method for the automated detection of scent marks from urine and feces in rodents. Given the importance of scent communication in these animals and their role as model organisms, this is a welcome tool.

Strengths:

The method uses a single video stream to allow for the distinction between urine and feces. It is automated.

Weaknesses:

The accuracy is decent but not perfect and may be too low to detect some effects that are biologically real but subtle (e.g. less than 10% differences). For many assays, however, this tools will be useful.

Reviewer #1 (Public review):

About R squared in the plots:<br /> The authors have used a z-scored R squared in the main ridge regression plots. While this may be interpretable, it seems non-standard and overly complicated. The authors could use a simple Pearson r to be most direct and informative (and in line with similar work, including Goldstein et al. 2022 which they mentioned). This way the sign of the relationships is preserved.

About the new TRF analysis:<br /> The new TRF analysis is a necessary addition and much appreciated. However, it is missing the results for the acoustic regressors, which should be there analogous to the HM-LSTM ridge analysis. The authors should also specify which software they have utilized to conduct the new TRF analysis. It also seems that the linguistic predictors/regressors have been newly constructed in a way more consistent with previous literature (instead of using the HM-LSTM features); these specifics should also be included in the manuscript (did it come from Montreal Forced Aligner, etc.?). Now that the original HM-LSTM can be compared to a more standard TRF analysis, it is apparent that the results are similar.

The authors' wording about this suggests that these new regressors have a nonzero sample at each linguistic event's offset, not onset. This should also be clarified. As the authors know, the onset would be more standard, and using the offset has implications for understanding the timing of the TRFs, as a phoneme has a different duration than a word, which has a different duration from a sentence, etc.

About offsets:<br /> TRFs can still be interpretable using the offset timings though; however, the main original analysis seems to be utilizing the offset times in a different, more confusing way. The authors still seem to be saying that only the peri-offset time of the EEG was analyzed at all, meaning the vast majority of the EEG trial durations do not factor into the main HM-LSTM response results whatsoever. The way the authors describe this does not seem to be present in any other literature, including the papers that they cite. Therefore, much more clarification on this issue is needed. If the authors mean that the regressors are simply time-locked to the EEG by aligning their offsets (rather than their onsets, because they have varying onsets or some such experimental design complexity), then this would be fine. But it does not seem to be what the authors want to say. This may be a miscommunication about the methods, or the authors may have actually only analyzed a small portion of the data. Either way, this should be clarified to be able to be interpretable.

Reviewer #1 (Public review):

I want to reiterate my comment from the first round of reviews: that I am insufficiently familiar with the intricacies of Maxwell's equations to assess the validity of the assumptions and the equations being used by WETCOW. The work ideally needs assessing by someone more versed in that area, especially given the potential impact of this method if valid.

Effort has been made in these revisions to improve explanations of the proposed approach (a lot of new text has been added) and to add new simulations.

However, the authors have still not compared their method on real data with existing standard approaches for reconstructing data from sensor to physical space. Refusing to do so because existing approaches are deemed inappropriate (i.e. they "are solving a different problem") is illogical.

Similarly, refusing to compare their method with existing standard approaches for spatio-temporally describing brain activity, just because existing approaches are deemed inappropriate, is illogical.

For example, the authors say that "it's not even clear what one would compare [between the new method and standard approaches]". How about:

(1) Qualitatively: compare EEG activation maps. I.e. compare what you would report to a researcher about the brain activity found in a standard experimental task dataset (e.g. their gambling task). People simply want to be able to judge, at least qualitatively on the same data, what the most equivalent output would be from the two approaches. Note, both approaches do not need to be done at the same spatial resolution if there are constraints on this for the comparison to be useful.

and

(2) Quantitatively: compare the correlation scores between EEG activation maps and fMRI activation maps

The abstract claims that there is a "direct comparison with standard state-of-the-art EEG analysis in a well-established attention paradigm", but no actual comparison appears to have been completed in the paper.

Reviewer #2 (Public review):

Summary:

In this present Mendelian randomization-phenome-wide association study, the authors found BMI to be positively associated with many health-related conditions, such as heart disease, heart failure, and hypertensive heart disease. They also found sex differences in some traits, such as cancer, psychological disorders, and ApoB.

Strengths:

The use of the UK-biobank study with detailed phenotype and genotype information.

Comments on revisions:

I believe the authors have presented convincing arguments for the novelty and interpretation of their study. I have no additional comments.

DOI: 10.1038/s41556-025-01658-1

Resource: bcl2fastq (RRID:SCR_015058)

Curator: @dhovakimyan1

SciCrunch record: RRID:SCR_015058

What is this?

DOI: 10.1038/s41467-025-58821-3

Resource: None

Curator: @dhovakimyan1

SciCrunch record: RRID:ZFIN_ZDB-ALT-131212-1

What is this?

DOI: 10.1038/s41467-025-58821-3

Resource: (ZFIN Cat# ZDB-ALT-150904-1,RRID:ZFIN_ZDB-ALT-150904-1)

Curator: @scibot

SciCrunch record: RRID:ZFIN_ZDB-ALT-150904-1

What is this?

Reviewer #1 (Public review):

Summary:

The study identifies two types of activation: one that is cue-triggered and non-specific to motion directions, and another that is specific to the exposed motion directions but occurs in a reversed manner. The finding that activity in the medial temporal lobe (MTL) preceded that in the visual cortex suggests that the visual cortex may serve as a platform for the manifestation of replay events, which potentially enhance visual sequence learning.

Evaluations:

Identifying the two types of activation after exposure to a sequence of motion directions is very interesting. The experimental design, procedures and analyses are solid. The findings are interesting and novel.

In the original submission, it was not immediately clear to me why the second type of activation was suggested to occur spontaneously. The procedural differences in the analyses that distinguished between the two types of activation need to be a little better clarified. However, this concern has been satisfactorily addressed in the revision.

Reviewer #1 (Public review):

Summary:

The submitted article reports the development of an unsupervised learning method that enables quantification of behaviour and poses of C. elegans from 15 minute long videos and presents a spatial map of both. The entire pipeline is a two part process, with the first part based on contrastive learning that represents spatial poses onto an embedded space, while the second part uses a transformer encoder to enable estimation of masked parts in a spatiotemporal sequence.

Strengths:

This analysis approach will prove to be useful for the C. elegans community. The application of the method on various age-related videos on various strains presents a good use-case for the approach. The manuscript is well written and presented.

Specific comments:

(1) One of the main motivations as mentioned in the introduction as well as emphasized in the discussion section is that this approach does not require key-point estimation for skeletonization and is also not dependent on the eigenworm approach for pose estimation. However, the eigenworm data has been estimated using the Tierpsy tracker in videos used in this work and stored as metadata. This is subsequently used for interpretation. It is not clear at this point, how else the spatial embedded map may be interpreted without using this kind of pose estimates obtained from other approaches. Please elaborate and comment.

(2) As per the manuscript, the second part of the pipeline is used to estimate the masked sequences of the spatiotemporal behavioral feature. However, it is not clear what the numbers listed in Fig. 2.3 represent?

(3) It is not clear how motion speed is linked to individual poses as mentioned in Figs. 4 (b) and (c).

Reviewer #1 (Public review):

Summary:

Using a combination of EEG and behavioural measurements, the authors investigate the degree to which processing of spatially-overlapping targets (coherent motion) and distractors (affective images) are sampled rhythmically and how this affects behaviour. They found that both target processing (via measurement of amplitude modulations of SSVEP amplitude to target frequency) and distractor processing (via MVPA decoding accuracy of bandpassed EEG relative to distractor SSVEP frequency) displayed a pronounced rhythm at ~1Hz, time-locked to stimulus onset. Furthermore, the relative phase of this target/distractor sampling predicted the accuracy of coherent motion detection across participants.

Strengths:

(1) The authors are addressing a very interesting question with respect to sampling of targets and distractors, using neurophysiological measurements to their advantage in order to parse out target and distractor processing.

(2) The general EEG analysis pipeline is sensible and well-described.

(3) The main result of rhythmic sampling of targets and distractors is striking and very clear even on a participant level.

(4) The authors have gone to quite a lot of effort to ensure the validity of their analyses, especially in the Supplementary Material.

(5) It is incredibly striking how the phases of both target and distractor processing are so aligned across trials for a given participant. I would have thought that any endogenous fluctuation in attention or stimulus processing like that would not be so phase aligned. I know there is literature on phase resetting in this context, the results seem very strong here and it is worth noting. The authors have performed many analyses to rule out signal processing artifacts, e.g., the sideband and beating frequency analyses.

Weaknesses:

(1) In general, the representation of target and distractor processing is a bit of a reach. Target processing is represented by SSVEP amplitude, which is most likely going to be related to the contrast of the dots, as opposed to representing coherent motion energy, which is the actual target. These may well be linked (e.g., greater attention to the coherent motion task might increase SSVEP amplitude), but I would call it a limitation of the interpretation. Decoding accuracy of emotional content makes sense as a measure of distractor processing, and the supplementary analysis comparing target SSVEP amplitude to distractor decoding accuracy is duly noted.

(2) Comparing SSVEP amplitude to emotional category decoding accuracy feels a bit like comparing apples with oranges. They have different units and scales and probably reflect different neural processes. Is the result the authors find not a little surprising in this context? This relationship does predict performance and is thus intriguing, but I think this methodological aspect needs to be discussed further. For example, is the phase relationship with behaviour a result of a complex interaction between different levels of processing (fundamental contrast vs higher order emotional processing)?

Reviewer #1 (Public review):

Summary:

Some years ago, Brookshire proposed a method to identify oscillations in behavioural data that controls for effects of aperiodic trends. Such trends can produce false positive results if not controlled for. Although this method successfully controlled for this issue, it was also relatively insensitive to true effects, and it remained unclear whether it was unable to replicate published evidence for behavioural oscillations because they were false positives or the method could not detect them. In simulated data, Harris & Beale show that their revised version of the method proposed by Brookshire is more sensitive to effects and equally unsusceptible to false positives. When applied to available data, this new version indeed revealed evidence for behavioural oscillations. This paper is therefore an important piece in the puzzle of the ongoing debate on behavioural oscillations.

Strengths:

(1) The paper is well written and compact.

(2) The new method proposed is tested thoroughly, and its application in simulated data shows its properties.

(3) It is very important that the code is made publicly available.

(4) The fact that this new version identifies behavioural oscillations in available datasets can resolve the current debate on the existence of such oscillations.

Weaknesses:

I see the following weaknesses as minor.

(1) I wonder whether the frequency-dependent results (e.g., Figures 7 and 8) need to be seen in light of the sampling rate used in the simulations. For example, a lower sampling rate might be sufficient if only low frequencies are of interest in the data and lead to higher sensitivity as the number of trials (per time point) can be increased. Conversely, a higher sampling rate might lead to a higher sensitivity for the detection of effects at higher frequencies.

(2) The behavioural oscillations from individual participants do not need to have common phases for this analysis to reveal an effect. However, this also means that in a scenario where they do have common phases, this similarity remains "unused" by the analysis (e.g., due to similar phases, the oscillation could be easier to identify on the group level as signals that are not phase locked are averaged out). In such a scenario, it remains unclear whether the analysis proposed is the most sensitive one.

Reviewer #1 (Public review):

The authors note that very premature infants experience the visual world early and, as a consequence, sustain lasting deficits including compromised motion processing. Here they investigate the effects of early eye opening in ferret, choosing a time point after birth when both retinal waves and light traveling through closed lids drive sensory responses. The laboratory has long experience in quantitative studies of visual response properties across development and this study reflects their expertise.

The investigators find little or no difference in mean orientation and direction selectivity, or in spatial frequency tuning, as a result of early eye opening but marked differences in temporal frequency tuning. These changes are especially interesting as they relate to deficits seen in prematurely delivered children. Temporal frequency bandwidth for responses evoked from early-opened contralateral eyes were broader than for controls; this is the case for animals in which either one or both eyes were opened prematurely. Further, when only one eye was opened early, responses to low temporal frequencies were relatively stronger.

The investigators also found changes in firing rate and signs of response to visual stimuli. Premature eye-opening increased spontaneous rates in all test configurations. When only one eye was opened early, firing rates recorded from the ipsilateral cortex were strongly suppressed, with more modest effects in other test cases.

As the authors' discussion notes, these observations are just a starting point for studies underlying mechanism. The experiments are so difficult to perform and so carefully described that the results will be foundational for future studies of how premature birth influences cortical development.

Reviewer #1 (Public review):

Summary:

This computational modeling study builds on multiple previous lines of experimental and theoretical research to investigate how a single neuron can solve a nonlinear pattern classification task. The authors construct a detailed biophysical and morphological model of a single striatal medium spiny neuron, and endow excitatory and inhibitory synapses with dynamic synaptic plasticity mechanisms that are sensitive to (1) the presence or absence of a dopamine reward signal, and (2) spatiotemporal coincidence of synaptic activity in single dendritic branches. The latter coincidence is detected by voltage-dependent NMDA-type glutamate receptors, which can generate a type of dendritic spike referred to as a "plateau potential." In the absence of inhibitory plasticity, the proposed mechanisms result in good performance on a nonlinear classification task when specific input features are segregated and clustered onto individual branches, but reduced performance when input features are randomly distributed across branches. Interestingly, adding inhibitory plasticity improves classification performance even when input features are randomly distributed.

Strengths:

The integrative aspect of this study is its major strength. It is challenging to relate low-level details such as electrical spine compartmentalization, extrasynaptic neurotransmitter concentrations, dendritic nonlinearities, spatial clustering of correlated inputs, and plasticity of excitatory and inhibitory synapses to high-level computations such as nonlinear feature classification. Due to high simulation costs, it is rare to see highly biophysical and morphological models used for learning studies that require repeated stimulus presentations over the course of a training procedure. The study aspires to prove the principle that experimentally-supported biological mechanisms can explain complex learning.

Weaknesses:

The high level of complexity of each component of the model makes it difficult to gain an intuition for which aspects of the model are essential for its performance, or responsible for its poor performance under certain conditions. Stripping down some of the biophysical detail and comparing it to a simpler model may help better understand each component in isolation.

Reviewer #1 (Public review):

Summary:

In this study, Jeong and Choi examine neural correlates of behavior during a naturalistic foraging task in which rats must dynamically balance resource acquisition (foraging) with the risk of threat. Rats first learn to forage for sucrose reward from a spout, and when a threat is introduced (an attack-like movement from a "LobsterBot"), they adjust their behavior to continue foraging while balancing exposure to the threat, adopting anticipatory withdraw behaviors to avoid encounter with the LobsterBot. Using electrode recordings targeting the medial prefrontal cortex (PFC), they identify heterogenous encoding of task variables across prelimbic and infralimbic cortex neurons, including correlates of distance to the reward/threat zone and correlates of both anticipatory and reactionary avoidance behavior. Based on analysis of population responses, they show that prefrontal cortex switches between different regimes of population activity to process spatial information or behavioral responses to threat in a context-dependent manner. Characterization of the heterogenous coding scheme by which frontal cortex represents information in different goal states is an important contribution to our understanding of brain mechanisms underlying flexible behavior in ecological settings.

Strengths:

As many behavioral neuroscience studies employ highly controlled task designs, relatively less is generally known about how the brain organizes navigation and behavioral selection in naturalistic settings, where environment states and goals are more fluid. Here, the authors take advantage of a natural challenge faced by many animals - how to forage for resources in an unpredictable environment - to investigate neural correlates of behavior when goal states are dynamic. Related to his, they also investigate prefrontal cortex (PFC) activity is structured to support different functional "modes" (here, between a navigational mode and a threat-sensitive foraging mode) for flexible behavior. Overall, an important strength and real value of this study is the design of the behavioral experiment, which is trial-structured, permitting strong statistical methods for neural data analysis, yet still rich enough to encourage natural behavior structured by the animal's volitional goals. The experiment is also phased to measure behavioral changes as animals first encounter a threat, and then learn to adapt their foraging strategy to its presence. Characterization of this adaptation process is itself quite interesting and sets a foundation for further study of threat learning and risk management in the foraging context. Finally, the characterization of single-neuron and population dynamics in PFC in this naturalistic setting with fluid goal states is an important contribution to the field. Previous studies have identified neural correlates of spatial and behavioral variables in frontal cortex, but how these representations are structured, or how they are dynamically adjusted when animals shift their goals, has been less clear. The authors synthesize their main conclusions into a conceptual model for how PFC activity can support mode switching, which can be tested in future studies with other task designed and functional manipulations.

Weaknesses:

While the task design in this study is intentionally stimulus-rich and places minimal constraint on the animal to preserve naturalistic behavior, this also introduces confounds that limit interpretability of the neural analysis. For example, some variables which are the target of neural correlation analysis, such as spatial/proximity coding and coding of threat and threat-related behaviors, are naturally entwined. To their credit, the authors have included careful analyses and control conditions to disambiguate these variables and significantly improve clarity.

The authors also claim that the heterogenous coding of spatial and behavioral variables in PFC is structured in a particular way that depends on the animal's goals or context. As the authors themselves discuss, the different "zones" contain distinct behaviors and stimuli, and since some neurons are modulated by these events (e.g., licking sucrose water, withdrawing from the LobsterBot, etc.), differences in population activity may to some extent reflect behavior/event coding. The authors have included a control analysis, removing timepoints corresponding to salient events, to substantiate the claim that PFC neurons switch between different coding "modes." While this significantly strengthens evidence for their conclusion, this analysis still depends on relatively coarse labeling of only very salient events. Future experiment designs, which intentionally separate task contexts (e.g. navigation vs. foraging), could serve to further clarify the structure of coding across contexts and/or goal states.

Finally, while the study includes many careful, in-depth neural and behavioral analyses to support the notion that modal coding of task variables in PFC may play a role in organizing flexible, dynamic behavior, the study still lacks functional manipulations to establish any form of causality. This limitation is acknowledged in the text, and the report is careful not to over interpret suggestions of causal contribution, instead setting a foundation for future investigations.

Joint Public Review:

Editors’ note: This is the third version of this article, and it addresses the points made during the peer review of the second version by performing additional analyses and clarifying some of the limitations of the study.

Comments made during the peer review of the first version, along with author's responses to these comments, are available with previous versions of the article.

The following summary of the article is taken from comments made by Reviewer #1 about version 2 of the article:

In this manuscript, the authors use a large dataset of neuroscience publications to elucidate the nature of self-citation within the neuroscience literature. The authors initially present descriptive measures of self-citation across time and author characteristics; they then produce an inclusive model to tease apart the potential role of various article and author features in shaping self-citation behavior. This is a valuable area of study, and the authors approach it with a rich dataset and solid methodology.

Reviewer #1 (Public review):

Summary:

This study seeks to investigate the role of the transcription factor Bcl11b/Ctip2 in regulating subcerebral projection neuron (SCPN) axon development through both cell-autonomous and non-cell-autonomous mechanisms. The authors demonstrate that Bcl11b is required within SCPNs for axonal outgrowth and proper entry into the internal capsule, while its expression in medium spiny neurons (MSNs) influences SCPN axon fasciculation and pathfinding in a non-cell-autonomous manner. Notably, through transcriptomic analysis, immunocytochemistry, and in vivo growth cone purification, the study identifies Cdh13 as a downstream mediator of Bcl11b function, localizing along axons and at growth cone surfaces to regulate SCPN axonal outgrowth.

Strengths:

To me the most interesting aspect of this study is how common transcriptional programs across neuronal cell types cooperate to facilitate axon pathfinding, this is a very interesting concept.

Overall, it could be of interest to the brain development field.

Weaknesses:

My main concern is that, as presented in the figures, many phenotypes are too subtle to be convincing and would require quantitative analyses to corroborate the claims of the study.

I also think that the growth cones transcription data needs additional validation to be incorporated into the manuscript. In fact, I am not even sure that it really brings anything to the story.

I also think that the CRISPR in utero electroporation experiments lack appropriate controls.

Reviewer #1 (Public review):

Summary:

Nysten et al. use in vivo 2-photon calcium imaging in behaving mice learning a visual associative memory task to understand how neural dynamics in the postrhinal cortex and medial entorhinal cortex evolve over task learning and through reversal learning. Using a combination of analyses to measure trial-averaged neural responses, regression models, and population decoding methods, the authors argue that both POR and MEC dynamics evolve over learning, with relatively more neurons in MEC becoming responsive. The impact of this study comes from comparing neural dynamics across multiple medial temporal lobe circuits to show how different aspects of task structure are differentially encoded. Below, I have listed several major concerns that need to be addressed to ensure the findings are robust.

Strengths:

(1) The study employs a well-controlled behavioral paradigm alongside powerful cellular-resolution two-photon imaging, enabling high-throughput recordings of hundreds of neurons simultaneously in deep brain structures.

(2) The simplicity of the task allows for a detailed examination of learning dynamics across multiple stages, including early and late learning in the main task, as well as during reversal learning.

(3) The use of sophisticated analysis methods to compare and contrast learning dynamics in large neuronal populations strengthens the study, though additional steps are needed to ensure their robustness (detailed below).

(4) Two-photon imaging enables the investigation of functional topography, further supporting previous findings of functional clustering in MEC across different task and behavioral domains.

Weaknesses:

(1) GLM Robustness & Behavioral Attribution: The current GLM design may misattribute neural activity by lacking appropriate time lags for velocity and not accounting for distinct neural states (e.g., rest vs. run). Given MEC's known speed-invariant coding, the observed decrease in speed-modulated neurons may be an artifact rather than a true learning effect. Additionally, gradual behavioral stabilization over training could influence neural dynamics in ways not fully accounted for.

(2) Licking vs. Movement Encoding: The increase in lick-modulated neurons raises questions about whether these neurons encode reward anticipation or motor execution. Without a detailed analysis of error trials and the timing of licking vs. movement adjustments, it remains unclear whether MEC activity reflects predictive coding of reward or simply motor feedback.

(3) Clustering Interpretation Issues: The functional clustering approach does not control for correlations between behavioral features, making it difficult to determine whether speed modulation plays a role in cluster assignments. The anatomical analysis in Figure 6 relies heavily on clusters that may be predominantly defined by a single regressor, requiring further clarification.

(4) Data Presentation & Statistical Support: Some key claims, particularly the increase in task-modulated neurons with learning (Figure 3), lack statistical quantification.

Reviewer #1 (Public review):

Summary:

The manuscript reports that expression of the E. coli operon topAI/yjhQ/yjhP is controlled by the translation status of a small open reading frame, that authors have discovered and named toiL, located in the leader region upstream of the operon. Authors propose the following model for topAI activation: Under normal conditions, toiL is translated but topAI is not expressed because of Rho-dependent transcription termination within the topAI ORF and because its ribosome binding site and start codon are trapped in an mRNA hairpin. Ribosome stalling at various codons of the toiL ORF, prompted in this work by some ribosome-targeting antibiotics, triggers an mRNA conformational switch which allows translation of topAI and, in addition, activation of the operon's transcription because presence of translating ribosomes at the topAI ORF blocks Rho from terminating transcription. The model is appealing and several of the experimental data mainly support it. However, it remains unanswered what is the true trigger of the translation arrest at toiL and what is the physiological role of the induced expression of the topAI/yjhQ/yjhP operon.

Reviewer #1 (Public review):

The manuscript consists of two separate but interlinked investigations: genomic epidemiology and virulence assessment of Salmonella Dublin. ST10 dominates the epidemiological landscape of S. Dublin, while ST74 was uncommonly isolated. Detailed genomic epidemiology of ST10 unfolded the evolutionary history of this common genotype, highlighting clonal expansions linked to each distinct geography. Notably, North American ST10 was associated with more antimicrobial resistance compared to others. The authors also performed long read sequencing on a subset of isolates (ST10 and ST74), and uncovered a novel recombinant virulence plasmid in ST10 (IncX1/IncFII/IncN). Separately, the authors performed cell invasion and cytotoxicity assays on the two S. Dublin genotypes, showing differential responses between the two STs. ST74 replicates better intracellularly in macrophage compared to ST10, but both STs induced comparable cytotoxicity levels. Comparative genomic analyses between the two genotypes showed certain genetic content unique to each genotype, but no further analyses were conducted to investigate which genetic factors likely associated with the observed differences. The study provides a comprehensive and novel understanding on the evolution and adaptation of two S. Dublin genotypes, which can inform public health measures. The methodology included in both approaches were sound and written in sufficient detail, and data analysis were performed with rigour. Source data were fully presented and accessible to readers.

Comments on revised version:

The authors have addressed all the points raised by the reviewer. The manuscript is now much enhanced in clarity and accuracy. The rewritten Discussion is more relevant and brings in comparison with other invasive Salmonella serotypes.

Reviewer #1 (Public review):

Summary:

This work uses a novel, ethologically relevant behavioral task to explore decision-making paradigms in C. elegans foraging behavior. By rigorously quantifying multiple features of animal behavior as they navigate in a patch food environment, the authors provide strong evidence that worms exhibit one of three qualitatively distinct behavioral responses upon encountering a patch: (1) "search", in which the encountered patch is below the detection threshold; (2) "sample", in which animals detect a patch encounter and reduce their motor speed, but do not stay to exploit the resource and are therefore considered to have "rejected" it; and (3) "exploit", in which animals "accept" the patch and exploit the resource for tens of minutes. Interestingly, the probability of these outcomes varies with the density of the patch as well as the prior experience of the animal. Together, these experiments provide an interesting new framework for understanding the ability of the C. elegans nervous system to use sensory information and internal state to implement behavioral state decisions.

Strengths:

-The work uses a novel, neuroethologically-inspired approach to studying foraging behavior<br /> -The studies are carried out with an exceptional level of quantitative rigor and attention to detail<br /> -Powerful quantitative modeling approaches including GLMs are used to study the behavioral states that worms enter upon encountering food, and the parameters that govern the decision about which state to enter<br /> -The work provides strong evidence that C. elegans can make 'accept-reject' decisions upon encountering a food resource<br /> -Accept-reject decisions depend on the quality of the food resource encountered as well as on internally represented features that provide measurements of multiple dimensions of internal state, including feeding status and time

Reviewer #1 (Public review):

Summary:

The use of a multi-omics approach to elucidate the regulatory mechanism underlying parturition and myometrial quiescence adds novelty to the study. The identification of myometrial cis-acting elements and their association with gene expression, particularly the regulation of the PLCL2 gene by PGR opens the door to further investigate the impact of PGR and other regulators.

Strengths:

(1) Multi-Omic Approach: The paper employs a comprehensive multi-omic approach, combining ChIP-Seq, RNA-Seq, and CRISPRa-based Perturb-Seq assays, which allow for a thorough investigation of the regulatory mechanisms underlying myometrial gene expression.<br /> (2) Clinical Relevance: Investigating human myometrial specimens provides direct clinical relevance, as understanding the molecular mechanisms governing parturition and myometrial quiescence can have significant implications for the management of pregnancy-related disorders.<br /> (3) Functional work: For functional screening, They have used CRISPRa-based screening of PLCL2 gene regulation using immortalized human cell-line hTERT-HM and T-hESC to add more dimension to the work which strengthens their finding of PGR-dependent regulation of the PLCL2 gene in the human myometrial cells.

Weaknesses:

(1) Variability in epigenomic mapping: The significant variations in the number and location of H3K27ac-positive intervals across different samples and studies suggest potential challenges in accurately mapping the myometrial epigenome. This variability may introduce uncertainty and complicate the interpretation of results.<br /> (2) Sample specificity: The study focuses on term pregnant nonlabor myometrial specimens, limiting the generalizability of the findings to other stages of pregnancy or labor.<br /> (3) Limited Understanding of Regulatory Mechanisms: While the study identifies potential regulatory programs within super-enhancers, the exact mechanisms by which these enhancers regulate gene expression and cellular functions in the myometrium remain unclear. Further mechanistic studies are needed to elucidate these processes.<br /> (4) Discordant analysis: Why regular enhancers are being understood in terms of motif enrichment of transcription factors and super-enhancers in terms of pathways enriched for active genes? This needs a clear reason.

Reviewer #2 (Public review):

Summary:

This study investigates the molecular function of the N-glycan-dependent endoplasmic reticulum protein quality control system (ERQC) in Cryptococcus neoformans and correlates this pathway with key features of C. neoformans virulence, especially those mediated by extracellular vesicle transport. The findings provide valuable insights into the connection between this pathway and the biogenesis of C. neoformans extracellular vesicles.

Strengths:

The strength of this study lies primarily in the careful selection of appropriate and current methodologies, which provide a solid foundation for the authors' results and conclusions across all presented data. All experiments are supported by well-designed and established controls in the study of C. neoformans, further strengthening the validity of the results and conclusions drawn from them. The study presents novel data on this important pathway in C. neoformans, establishing its connection with C. neoformans virulence. Interestingly, the findings led the authors to understand the relationship between this pathway and the transport of key fungal virulence factors via extracellular vesicles. This was demonstrated in the study, paving the way for a deeper understanding of extracellular vesicle biogenesis-a field still filled with gaps but one that this study contributes to with solid data, helping to clarify aspects of this process.

Reviewer #1 (Public review):

Summary:

This manuscript aims to explain the emergence of grid-like spatial firing patterns. Rather than taking the existence of grid cells as a given and asking what does their properties say about their function, the authors reverse the approach: they begin with a proposed computational function that the brain may need to perform-coding of 2D spatial trajectories using sequences of neural activity-and ask what type of neural code would optimally support this function. They show that, under a set of formal assumptions, such a code leads to the emergence of spatial periodicity and a hexagonal grid pattern. The aim is to provide a normative explanation for the existence of grid cells grounded in functional constraints.

Strengths:

The manuscript presents a mathematically well-defined framework that is internally consistent. The derivation is structured and leads to a hexagonal lattice as the most efficient solution for representing directional trajectories. The authors provide comparisons to experimental observations and extend the model to explain several findings in the grid cell literature. In the revised version, the discussion of foundational assumptions is expanded, and the manuscript better situates itself in relation to prior theoretical work. Overall, this work adds a very interesting view to the broader conversation about the role and origin of grid cells by offering a theoretical alternative grounded in trajectory coding.

Weaknesses:

The model depends on assumptions that, while plausible, should be treated as chosen assumptions. These include the premise that (1) grid function is trajectory coding, (2) that trajectory coding is implemented through sequences of neural activity, and (3) that such sequences are largely independent of spatial position. In the revised manuscript, the authors provide more literature to support these assumptions.

Joint Public Review:

Summary:

In this study, Daniel et al. used three cognitive tasks to investigate behavioural signatures of cerebellar degeneration. In the first two tasks, the authors found that if an equation was incorrect, reaction times slowed significantly more for cerebellar patients than for healthy controls. In comparison, the slowing in the reaction times when the task required more operations was comparable to normal controls. In the third task, the authors show increased errors in cerebellar patients when they had to judge whether a letter string corresponded to an artificial grammar.

Strengths:

Overall, the work is methodologically sound and the manuscript well written. The data do show some evidence for specific cognitive deficits in cerebellar degeneration patients.

Weaknesses:

The current version has some weaknesses in the visual presentation of results. Overall, the study lacks a more precise discussion on how the patterns of deficits relate to the hypothesized cerebellar function.

The reviewers and the editor agreed that the data are interesting and point to a specific cognitive deficit in cerebellar patients. However, in the discussion, we were somewhat confused about the interpretation of the result:

If the cerebellum (as proposed in the introduction) is involved in forming expectations in a cognitive task, should they not show problems both in the expected (1+3 =4) and unexpected (1+3=2) conditions? Without having formed the correct expectation, how can you correctly say "yes" in the expected condition? No increase in error rate is observed - just slowing in the unexpected condition. But this increase in error rate was not observed. If the patients make up for the lack of prediction by using some other strategy, why are they only slowing in the unexpected case?

If the cerebellum is NOT involved in making the prediction, but only involved in detecting the mismatch between predicted and real outcome, why would the patients not show specifically more errors in the unexpected condition?

Reviewer #1 (Public review):

Summary:

This study builds upon a major theoretical account of value-based choice, the 'attentional drift diffusion model' (aDDM), and examines whether and how this might be implemented in the human brain using functional magnetic resonance imaging (fMRI). The aDDM states that the process of internal evidence accumulation across time should be weighted by the decision maker's gaze, with more weight being assigned to the currently fixated item. The present study aims to test whether there are (a) regions of the brain where signals related to the currently presented value are affected by the participant's gaze; (b) regions of the brain where previously accumulated information is weighted by gaze.

To examine this, the authors developed a novel paradigm that allowed them to dissociate currently and previously presented evidence, at a timescale amenable to measuring neural responses with fMRI. They asked participants to choose between bundles or 'lotteries' of food times, which they revealed sequentially and slowly to the participant across time. This allowed modelling of the haemodynamic response to each new observation in the lottery, separately for previously accumulated and currently presented evidence.

Using this approach, they find that regions of the brain supporting valuation (vmPFC and ventral striatum) have responses reflecting gaze-weighted valuation of the currently presented item, whereas regions previously associated with evidence accumulation (preSMA and IPS) have responses reflecting gaze-weighted modulation of previously accumulated evidence.

Strengths:

A major strength of the current paper is the design of the task, nicely allowing the researchers to examine evidence accumulation across time despite using a technique with poor temporal resolution. The dissociation between currently presented and previously accumulated evidence in different brain regions in GLM1 (before gaze-weighting), as presented in Figure 5, is already compelling. The result that regions such as preSMA respond positively to |AV| (absolute difference in accumulated value) is particularly interesting, as it would seem that the 'decision conflict' account of this region's activity might predict the exact opposite result. Additionally, the behaviour has been well modelled at the end of the paper when examining temporal weighting functions across the multiple samples.

Weaknesses:

The results relating to gaze-weighting in the fMRI signal could do with some further explication to become more complete. A major concern with GLM2, which looks at the same effects as GLM1 but now with gaze-weighting, is that these gaze-weighted regressors may be (at least partially) correlated with their non-gaze-weighted counterparts (e.g., SVgaze will correlate with SV). But the non-gaze-weighted regressors have been excluded from this model. In other words, the authors are not testing for effects of gaze-weighting of value signals *over and above* the base effects of value in this model. In my mind, this means that the GLM2 results could simply be a replication of the findings from GLM1 at present. GLM3 is potentially a stronger test, as it includes the value signals and the interaction with gaze in the same model. But here, while the link to the currently attended item is quite clear (and a replication of Lim et al, 2011), the link to previously accumulated evidence is a bit contorted, depending upon the interpretation of a behavioural regression to interpret the fMRI evidence. The results from GLM3 are also, by the authors' own admission, marginal in places.

Reviewer #1 (Public review):

Summary:

This study builds on previous work demonstrating that several beta connexins (Cx26, Cx30, and Cx32) have a carbamylation motif which renders them sensitive to CO2. In response to CO2, hemichannels composed of these connexins open, enabling diffusion of small molecules (such as ATP) between the cytosol and extracellular environment. Here, the authors have identified that an alpha connexin, Cx43, also contains a carbamylation motif, and they demonstrate that CO2 opens Cx43 hemichannels. Most of the study involves using transfected cells expressing wild-type and mutant Cx43 to define amino acids required for CO2 sensitivity. Hippocampal tissue slices in culture were used to show that CO2-induced synaptic transmission was affected by Cx43 hemichannels, providing a physiological context. The authors point out that the Cx43 gene significantly diverges from the beta connexins that are CO2 sensitive, suggesting that the conserved carbamylation motif was present before the alpha and beta connexin genes diverged.

Strengths:

(1) The molecular analysis defining the amino acids that contribute to the CO2 sensitivity of Cx43 is a major strength of the study. The rigor of analysis was strengthened by using three independent assays for hemichannel opening: dye uptake, patch clamp channel measurements, and ATP secretion. The resulting analysis identified key lysines in Cx43 that were required for CO2-mediated hemichannel opening. A double K to E Cx43 mutant produced a construct that produced hemichannels that were constitutively open, which further strengthened the analysis.

(2) Using hippocampal tissue sections to demonstrate that CO2 can influence field excitatory postsynaptic potentials (fEPSPs) provides a native context for CO2 regulation of Cx43 hemichannels. Cx43 mutations associated with Oculodentodigital Dysplasia (ODDD) inhibited CO2-induced hemichannel opening, although the mechanism by which this occurs was not elucidated.

Weaknesses:

(1) Cx43 channels are sensitive to cytosolic pH, which will be affected by CO2. Cytosolic pH was not measured, and how this affects CO2-induced Cx43 hemichannel activity was not addressed.

(2) Cultured cells are typically grown in incubators containing 5% CO2, which is ~40 mmHg. It is unclear how cells would be viable if Cx43 hemichannels are open at this PCO2.

(3) Experiments using Gap26 to inhibit Cx43 hemichannels in fEPSP measurements used a scrambled peptide as a control. Analysis should also include Gap peptides specifically targeting Cx26, Cx30, and Cx32 as additional controls.

(4) The mechanism by which ODDD mutations impair CO2-mediated hemichannel opening was not addressed. Also, the potential roles for inhibiting Cx43 hemichannels in the pathology of ODDD are unclear.

(5) CO2 has no effect on Cx43-mediated gap junctional communication as opposed to Cx26 gap junctions, which are inhibited by CO2. The molecular basis for this difference was not determined.

(6) Whether there are other non-beta connexins that have a putative carbamylation motif was not addressed. Additional discussion/analysis of how the evolutionary trajectory for Cx43 maintaining a carbamylation motif is unique for non-beta connexins would strengthen the study.

Reviewer #1 (Public review):

Summary:

In this manuscript, Lau et al reported that KDM5 inhibition in luminal breast cancer cells results in R-loop-mediated DNA damage, reduced cell fitness and an increase in ISG and AP signatures as well as cell surface Major Histocompatibility Complex (MHC) class I, mediated by RNA:DNA hybrid activation of the CGAS/STING pathway.

Strengths:

More importantly, they have shown that KDM5 inhibition does not result in DNA damage or activation of the CGAS/STING pathway in normal breast epithelial cells. This suggests that KDM5 inhibitors may enable a wide therapeutic window in this setting, as compared to STING agonists or Type I Interferons. Their findings provide new insights into the interplay between epigenetic regulation of genomic repeats, R-loop formation, innate immunity, and cell fitness in the context of cancer evolution and therapeutic vulnerability.

Weaknesses:

More thorough analyses would be appreciated.

Reviewer #1 (Public review):

Summary:

In this study, the authors set out to define how arginine availability regulates lipid metabolism and to explore the implications of this relationship in pancreatic ductal adenocarcinoma (PDAC), a tumor type known to exist in an arginine-poor microenvironment. Using a combination of rigorous genetic and metabolomic approaches, they uncover a previously underappreciated role for arginine in maintaining lipid homeostasis. Importantly, they demonstrate that arginine deprivation sensitizes PDAC cells to ferroptosis through lipidome perturbations, which can be exploited therapeutically via co-treatment with aESA and ferroptosis inducers (FINs). These findings have meaningful implications for the field. They not only shed light on the metabolic vulnerabilities created by nutrient restriction in PDAC, but also suggest a practical avenue for combination therapies that exploit ferroptosis sensitivity. This is particularly relevant in the context of pancreatic cancer, which is notoriously resistant to conventional treatments. The methods employed are broadly applicable to other nutrient-stress contexts and may inspire similar investigations in other solid tumor types.

Strengths:

One of the major strengths of the study is the use of complementary and well-controlled approaches-including metabolomic profiling, genetic perturbations, and in vivo models-to support the central hypothesis. The experiments are thoughtfully designed and clearly presented, and the conclusions are, for the most part, well supported by the data. The findings provide mechanistic insight into nutrient-lipid crosstalk and identify a potential therapeutic strategy for targeting arginine-deprived tumors.

Weaknesses:

A key weakness of the study lies in the mechanistic connection between arginine levels and SREBP1 activation. While the authors show that arginine restriction leads to reduced SREBP1 expression, the magnitude of this effect appears modest relative to the substantial changes observed in the lipidome. The study would benefit from a deeper analysis of SREBP1 regulation-particularly whether nuclear translocation or activation is affected. This could be addressed by examining the nuclear pool of SREBP1, using either subcellular fractionation or improved immunofluorescence imaging in both cell lines and tissue samples.

Another area where additional context would strengthen the manuscript is in the transcriptomic profiling of PDAC cells cultured in a tumor interstitial fluid mimic (TIFM). While the study emphasizes lipid-related pathways, highlighting the most significantly upregulated and downregulated pathways in Figure 1B would give readers a broader perspective on how arginine restriction reprograms the PDAC transcriptome. For instance, because polyamines are downstream of arginine and are known to influence lipid metabolism, it would be worth discussing whether these metabolites contribute to the phenotypes observed. Similarly, an evaluation of whether Dgat1/2 expression is altered could help delineate the full scope of lipid metabolic rewiring.

Finally, it is worth noting that the KPC mouse model used in this study is based on conditional deletion of p53, which leads to faster-growing tumors and a distinct tumor microenvironment compared to models harboring the p53^R172H point mutation. Including a brief discussion of this distinction would help readers contextualize the translational relevance of the findings.

Reviewer #1 (Public review):

Summary:

The manuscript uses state-of-the-art analysis technology to document the spatio-temporal dynamics of brain activity during the processing of threats. The authors offer convincing evidence that complex spatio-temporal aspects of brain dynamics are essential to describe brain operations during threat processing.

Strengths:

Rigorous complex analyses well suited to the data.

Weaknesses:

Lack of a simple take-home message about discovery of a new brain operation.

Comments on revisions:

The authors have improved the presentation of the work. The overstatements about existing models of brain functions ignoring exogenous components remains largely unaddressed. The clarifications and improvements provided in revision confirm my assessment of the paper.

Reviewer #1 (Public review):

Summary:

A cortico-centric view is dominant in the study for the neural mechanisms of consciousness. This investigation represents the growing interest to understand how subcortical regions are involved in conscious perception. To achieve this, the authors engaged an ambitious and rare procedure in humans of directly recording from neurons in the subthalamic nucleus and thalamus. While participants were in surgery for the placement of deep brain stimulation devices for the treatment of essential tremor and Parkinson's disease, they were awakened and completed a perceptual-threshold tactile detection task. The authors identified individual neurons and analyzed single-unit activity corresponding with the task phases and tactile detection/perception. Among the neurons that were perception-responsive, the authors report changes in firing rate beginning ~150 milliseconds from the onset of the tactile stimulation. Curiously, the majority of the perception-responsive neurons had a higher firing rate for missed/not perceived trials. In summary, this investigation is a valuable addition to the growing literature on the role of subcortical regions in conscious perception.

Strengths:

The authors achieve the challenging task of recording human single-unit activity while participants performed a tactile perception task. The methods and statistics are clearly explained and rigorous, particularly for managing false positives and non-normal distributions. The results offer new detail at the level of individual neurons in the emerging recognition for the role of subcortical regions in conscious perception. Also, this study highlights the timing of neural activity linked to conscious perception (approximately 150 millisecond).

Weaknesses:

Due to constraints of testing with this patient population, a standard report-based detection task was administered. This type of task cannot fully exclude motor preparatory and post-perceptual processing as a factor that contributes to distinguishing between perceived versus not perceived stimuli. The authors show sensitivity to this issue by identifying task-selective neurons and their discussion of the results that refers to the confound of post-perceptual processing. Despite this limitation, the results are valuable for contributing to a growing body of literature on the subcortical neural mechanisms of consciousness.

Reviewer #1 (Public review):

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

Reviewer #1 (Public review):

In this study, Tiang et al. explore the role of ubiquitination of non-structural protein 16 (nsp16) in the SARS-CoV-2 life cycle. nsp16, in conjunction with nsp10, performs the final step of viral mRNA capping through its 2'-O-methylase activity. This modification allows the virus to evade host immune responses and protects its mRNA from degradation. The authors demonstrate that nsp16 undergoes ubiquitination and subsequent degradation by the host E3 ubiquitin ligases UBR5 and MARCHF7 via the ubiquitin-proteasome system (UPS). Specifically, UBR5 and MARCHF7 mediate nsp16 degradation through K48- and K27-linked ubiquitination, respectively. Notably, degradation of nsp16 by either UBR5 or MARCHF7 operates independently, with both mechanisms effectively inhibiting SARS-CoV-2 replication in vitro and in vivo. Furthermore, UBR5 and MARCHF7 exhibit broad-spectrum antiviral activity by targeting nsp16 variants from various SARS-CoV-2 strains. This research advances our understanding of how nsp16 ubiquitination impacts viral replication and highlights potential targets for developing broadly effective antiviral therapies.

Strengths:

The proposed study is of significant interest to the virology community because it aims to elucidate the biological role of ubiquitination in coronavirus proteins and its impact on the viral life cycle. Understanding these mechanisms will address broadly applicable questions about coronavirus biology and enhance our overall knowledge of ubiquitination's diverse functions in cell biology. Employing in vivo studies is a strength.

Weaknesses:

Minor comments:<br /> Figure 5A- The authors should ensure that the figure is properly labeled to clearly distinguish between the IP (Immunoprecipitation) panel and the input panel.

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors investigated the effect of chronic activation of dopamine neurons using chemogenetics. Using Gq-DREADDs, the authors chronically activated midbrain dopamine neurons and observed that these neurons, particularly their axons, exhibit increased vulnerability and degeneration, resembling the pathological symptoms of Parkinson's disease. Baseline calcium levels in midbrain dopamine neurons were also significantly elevated following the chronic activation. Lastly, to identify cellular and circuit-level changes in response to dopaminergic neuronal degeneration caused by chronic activation, the authors employed spatial genomics (Visium) and revealed comprehensive changes in gene expression in the mouse model subjected to chronic activation. In conclusion, this study presents novel data on the consequences of chronic hyperactivation of midbrain dopamine neurons.

Strengths:

This study provides direct evidence that the chronic activation of dopamine neurons is toxic and gives rise to neurodegeneration. In addition, the authors achieved the chronic activation of dopamine neurons using water application of clozapine-N-oxide (CNO), a method not commonly employed by researchers. This approach may offer new insights into pathophysiological alterations of dopamine neurons in Parkinson's disease. The authors also utilized state-of-the-art spatial gene expression analysis, which can provide valuable information for other researchers studying dopamine neurons. They also presented a substantial number of intriguing ideas in their discussion, which are worth further investigation.

Weaknesses:

Although not fully supported by data, the authors provided a well-explained rationale and proposed possible mechanisms for dopamine neuron degeneration due to chronic activation in their results and discussion.

Comments on revised version:

The authors have adequately addressed most of my comments, and I have no further concerns.

Reviewer #1 (Public Review):

Summary:

In this manuscript, the authors investigated the effect of chronic activation of dopamine neurons using chemogenetics. Using Gq-DREADDs, the authors chronically activated midbrain dopamine neurons and observed that these neurons, particularly their axons, exhibit increased vulnerability and degeneration, resembling the pathological symptoms of Parkinson's disease. Baseline calcium levels in midbrain dopamine neurons were also significantly elevated following the chronic activation. Lastly, to identify cellular and circuit-level changes in response to dopaminergic neuronal degeneration caused by chronic activation, the authors employed spatial genomics (Visium) and revealed comprehensive changes in gene expression in the mouse model subjected to chronic activation. In conclusion, this study presents novel data on the consequences of chronic hyperactivation of midbrain dopamine neurons.

Strengths:

This study provides direct evidence that the chronic activation of dopamine neurons is toxic and gives rise to neurodegeneration. In addition, the authors achieved the chronic activation of dopamine neurons using water application of clozapine-N-oxide (CNO), a method not commonly employed by researchers. This approach may offer new insights into pathophysiological alterations of dopamine neurons in Parkinson's disease. The authors also utilized state-of-the-art spatial gene expression analysis, which can provide valuable information for other researchers studying dopamine neurons. Although the authors did not elucidate the mechanisms underlying dopaminergic neuronal and axonal death, they presented a substantial number of intriguing ideas in their discussion, which are worth further investigation.

Weaknesses:

Many claims raised in this paper are only partially supported by the experimental results. So, additional data are necessary to strengthen the claims. The effects of chronic activation of dopamine neurons are intriguing; however, this paper does not go beyond reporting phenomena. It lacks a comprehensive explanation for the degeneration of dopamine neurons and their axons. While the authors proposed possible mechanisms for the degeneration in their discussion, such as differentially expressed genes, these remain experimentally unexplored.

Reviewer #2 (Public review):

The aim of the investigation was to find out more about the mechanism(s) by which the structural protein vimentin can facilitate the epithelial-mesenchymal transition in breast cancer cells.

The authors focused on a key amino acid of vimentin, C238, its role in the interaction between vimentin and actin microfilaments, and the downstream molecular and cellular consequences. They model the binding between vimentin and actin in silico to demonstrate the potential involvement of C238, due to its location in a rod domain known to bind beta-actin. The phenotype of a non-metastatic breast cancer cell line MCF7, which doesn't express vimentin, could be changed to a metastatic phenotype when mutant C238S vimentin, but not wild-type vimentin, was expressed in the cells. Expression of vimentin was confirmed at the level of mRNA, protein and microscopically. Patterns of expression of vimentin and actin reflected the distinct morphology of the two cell lines. Phenotypic changes were assessed through assay of cell adhesion, proliferation, migration and morphology and were consistent with greater metastatic potential in the C238S MCF7 cells. Changes in the transcriptome of MCF7 cells expressing wild-type and C238S vimentins were compared and expression of Xist long ncRNA was found to be the transcript most markedly increased in the metastatic cells expressing C238S vimentin. Moreover changes in expression of many other genes in the C238S cells are consistent with an epithelial mesenchymal transition. Tumourigenic potential of MCF7 cells carrying C238S but not wild-type, vimentin was confirmed by inoculation of cells into nude mice. This assay is a measure of stem-cell quality of the cells and not a measure of metastasis. It does demonstrate phenotypic changes that could be linked to metastasis.

shRNA was used to down-regulate vimentin or Xist in the MCF7 C238S cells. The description of the data is limited in parts and data sets require careful scrutiny to understand the full picture. Down-regulation of vimentin reversed the morphological changes to some degree, but down-regulation of Xist didn't. Conversely down-regulation of Xist inhibited cell growth, a sign of reversing metastatic potential, but down-regulation of vimentin had no effect on growth. Down-regulation of either did inhibit cell migration, another sign of metastatic reversal. Most of these findings are consistent with previous work based on ectopic expression of wild-type vimentin in MCF7 cells, but the mechanism of inhibition of cell migration by downregulation of Xist remains speculative. More complete knockdown of vimentin or Xist by CRISPR technology may be helpful.

Overall the study describes an intriguing model of metastasis that is worthy of further investigation, especially at the molecular level to unravel the connection between vimentin and metastasis. The identification of a potential role for Xist in metastasis, beyond its normal role in female cells to inactivate one of the X chromosomes, corroborates the work of others demonstrating increased levels in a variety of tumours in women and even in some tumours in men. It would be of great interest to see where in metastatic cells Xist is expressed and what it binds to.

Comments on revisions:

The revised manuscript incorporates changes in presentation of the data modelling interaction between the region of vimentin including C238 and F-actin. There is also inclusion of an extra citation supporting the role for Xist in cancer stem cell differentiation.

Reviewer #1 (Public review):

Summary:

Hua et al show how targeting amino acid metabolism can overcome Trastuzumab resistance in HER2+ breast cancer.

Strengths:

The authors used metabolomics, transcriptomics and epigenomics approaches in vitro and in preclinical models to demonstrate how trastuzumab resistant cells utilize cysteine metabolism.

Weaknesses:

However, there are some key aspects that needs to be addressed.

Major:

(1) Patient Samples for Transcriptomic Analysis: It is unclear from the text whether tumor tissues or blood samples were used for the transcriptomic analysis. This distinction is crucial, as these two sample types would yield vastly different inferences. The authors should clarify the source of these samples.

(2) The study only tested one trastuzumab-resistant and one trastuzumab-sensitive cell lines. It is unclear whether these findings are applicable to other HER2-positive tumor cell lines, such as HCC1954. The authors should validate their results in additional cell lines to strengthen their conclusions.

(3) Relevance to Metastatic Disease: Trastuzumab resistance often arises in patients during disease recurrence, which is frequently associated with metastasis. However, the mouse experiments described in this paper were conducted only in the primary tumors. This article will have more impact if the authors could demonstrate that the combination of Erastin or cysteine starvation with trastuzumab can also improve outcomes in metastasis models.

Minor:

(1) The figures lack information about the specific statistical tests used. Including this information is essential to show the robustness of the results.

(2) Figure 3K Interpretation: The significance asterisks in Figure 3K do not specify the comparison being made. Are they relative to the DMSO control? This should be clarified.

Comments on revisions:

While the authors acknowledge the limitation of using only a single trastuzumab resistant/sensitive pair, simply stating that additional cell lines will be tested in future work is simply inadequate. The biological heterogeneity of HER2-positive breast cancer demands validation in at least one independent resistant model (e.g., HCC1954 or BT 474R) alongside its parental counterpart. Without demonstrating that SLC7A11 upregulation, cysteine dependency, and sensitivity to Erastin plus trastuzumab extend beyond the original cell line pair, the generalizability and translational relevance of the findings remain uncertain. The authors need to perform and report key functional results (cell viability, apoptosis, and SLC7A11 expression) in an additional resistant and sensitive HER2-positive cell line before this manuscript can be considered robust.

Reviewer #1 (Public review):

Summary:

This study provides new insight into the non-canonical voltage-gating mechanism of BK channels through prolonged (10 μs) MD simulations of the Slo1 transmembrane domain conformation and K+ conduction in response to high imposed voltages (300, 750 mV). The results support previous conclusions based on functional and structural data and MD simulations that the voltage-sensor domain (VSD) of Slo1 undergoes limited conformational changes compared to Kv channels, and predicts gating charge movement comparable in magnitude to experimental results. The gating charge calculations further indicate that R213 and R210 in S4 are the main contributors owing to their large side chain movements and the presence of a locally focused electric field, consistent with recent experimental and MD simulation results by Carrasquel-Ursulaez et al.,2022. Most interestingly, changes in pore conformation and K+ conduction driven by VSD activation are resolved, providing information regarding changes in VSD/pore interaction through S4/S5/S6 segments proposed to underly electromechanical coupling.

Strengths:

Include that the prolonged timescale and high voltage of the simulation allow apparent equilibration in the voltage-sensor domain (VSD) conformational changes and at least partial opening of the pore. The study extends the results of previous MD simulations of VSD activation by providing quantitative estimates of gating charge movement, showing how the electric field distribution across the VSD is altered in resting and activated states, and testing the hypothesis that R213 and R210 are the primary gating charges by steered MD simulations. The ability to estimate gating charge contributions of individual residues in the WT channel is useful as a comparison to experimental studies based on mutagenesis which have yielded conflicting results that could reflect perturbations in structure. Use of dynamic community analysis to identify coupling pathways and information flow for VSD-pore (electromechanical) coupling, as well as analysis of state-dependent S4/S5/S6 interactions that could mediate coupling, provides useful predictions extending beyond what has been experimentally tested.

Weaknesses:

Include that a truncated channel (lacking the C-terminal gating ring) was used for simulations, which is known to have reduced single channel conductance and reduced electromechanical coupling compared to the full-length channel. In addition, as VSD activation in BK channels is much faster than opening, the timescale of simulations was likely insufficient to achieve a fully open state, as supported by differences in the degree of pore expansion in replicate simulations, which are also smaller than observed in Ca-bound open structures of the full-length channel. Taken together, these limitations suggest that the analysis regarding coupling pathways and interactions is incomplete. In addition, while the simulations convincingly demonstrate voltage-dependent channel opening as evidenced by pore expansion, and conduction of K+ and water through the pore, single channel conductance is underestimated by at least an order of magnitude, as in previous studies of other K+ channels. These quantitative discrepancies suggest that MD simulations may not yet be sufficiently advanced to provide insight into mechanisms underlying the extraordinarily large conductance of BK channels.

Reviewer #1 (Public review):

In this work, Ligneul and coauthors implemented diffusion-weighted MRS in young rats to follow longitudinally and in vivo the microstructural changes occurring during brain development. Diffusion-weighted MRS is here instrumental in assessing microstructure in a cell-specific manner, as opposed to the claimed gold-standard (manganese-enhanced MRI) that can only probe changes in brain volume. Differential microstructure and complexification of the cerebellum and the thalamus during rat brain development were observed non-invasively. In particular, lower metabolite ADC with increasing age were measured in both brain regions, reflecting increasing cellular restriction with brain maturation. Higher sphere (representing cell bodies) fraction for neuronal metabolites (total NAA, glutamate) and total creatine and taurine in the cerebellum compared to the thalamus were estimated, reflecting the unique structure of the cerebellar granular layer with a high density of cell bodies. Decreasing sphere fraction with age was observed in the cerebellum, reflecting the development of the dendritic tree of Purkinje cells and Bergmann glia. From morphometric analyses, the authors could probe non-monotonic branching evolution in the cerebellum, matching 3D representations of Purkinje cells expansion and complexification with age. Finally, the authors highlighted taurine as a potential new marker of cerebellar development.

From a technical standpoint, this work clearly demonstrates the potential of diffusion-weighted MRS at probing microstructure changes of the developing brain non-invasively, paving the way for its application in pathological cases. Ligneul and coauthors also show that diffusion-weighted MRS acquisitions in neonates are feasible, despite the known technical challenges of such measurements, even in adult rats. They also provide all necessary resources to reproduce and build upon their work, which is highly valuable for the community.

From a biological standpoint, claims are well supported by the microstructure parameters derived from advanced biophysical modelling of the diffusion MRS data.

Specific strengths:

(1) The interpretation of dMRS data in terms of cell-specific microstructure through advanced biophysical modelling (e.g. the sphere fraction, modelling the fraction of cell bodies versus neuronal or astrocytic processes) is a strong asset of the study, going beyond the more commonly used signal representation metrics such as the apparent diffusion coefficient, which lacks specificity to biological phenomena.<br /> (2) The fairly good data quality despite the complexity of the experimental framework should be praised: diffusion-weighted MRS was acquired in two brain regions (although not in the same animals) and longitudinally, in neonates, including data at high b-values and multiple diffusion times, which altogether constitutes a large-scale dataset of high value for the diffusion-weighted MRS community.<br /> (3) The authors have shared publicly data and codes used for processing and fitting, which will allow one to reproduce or extend the scope of this work to disease populations, and which goes in line with the current effort of the MR(S) community for data sharing.

Specific weaknesses:

Ligneul and coauthors have convincingly addressed and included my comments in their revised manuscript.

I believe the following conceptual concerns, which are inherent to the nature of the study and do not require further adjustments of the manuscript, remain:

(1) Metabolite compartmentation in one cell type or the other has often been challenged and is currently impossible to validate in vivo. Here, Ligneul and coauthors did not use this assumption a priori and supported their claims also with non-MR literature (eg. for Taurine), but the interpretation of results in that direction should be made with care.

(2) Longitudinal MR studies of the developing brain make it difficult to extract parameters with an "absolute" meaning. Indirect assumptions used to derive such parameters may change with age and become confounding factors (brain structure, cell distribution, concentrations normalizing metabolites (here macromolecules), relaxation times...). While findings of the manuscript are convincing and supported with literature, the true underlying nature of such changes might be difficult to access.

(3) Diffusion MRI in addition to diffusion MRS would have been complementary and beneficial to validate some of the signal contributions, but was unfeasible in the time constraints of experiments on young animals.

Reviewer #1 (Public review):

Summary:

This study by Torok et al. takes a creative approach to studying circuit perturbations in a sensorimotor region for vocalization control, in a songbird species, the zebra finch. By expressing the light chain of tetanus toxin in neurons in a sensorimotor region HVC, the authors constrain neural firing and study the resulting degradation and then recovery of song, after a protracted (> 70-day) period. Recording data suggest a form of synaptic homeostasis emergent in both HVC and RA as a result of the profound loss of (inhibitory?) tone in HVC. The methods to analyze changes in song are particularly strong here, using dimension reduction and visualization techniques. Single-cell sequencing data showed accompanying changes in microglia abundance, as well as several other markers that were not observed in control viral injections. LFP analyses in birds during the tetanus onset phase showed clear dysregulation of typical voltage deflections and spectral power, each of which showed recovery in parallel with song recovery. Lastly, the authors present data indicating that the anterior forebrain region LMAN is not critical for the song degradation process, pointing instead to the direct relationship between HVC and RA in song plasticity in adults. The methods are generally well established, but my main concerns regard the validation of the viral construct, the lack of direct confirmation of tetanus toxin on inhibitory neurons or E/I balance in HVC, and a missed opportunity to look at song syllable sequence degradation and recovery.

Strengths:

The species under investigation is the premier model for the neural basis of vocal learning, and the telencephalic brain regions investigated are well mapped out for their control of vocal learning behavior. The methods for electrophysiology recording and analysis, song analysis, scRNAseq, and in situ hybridization pose no concern as they are well established for this group of co-authors.

Weaknesses:

The introduction lays out a case for pursuing long-term E/I imbalances, vis-à-vis transient perturbations that have shown effects on the behavior. However, the rationale is not clearly stated. Why should the reader care that "prolonged E/I imbalances" may occur? Do they occur naturally or in some disease states (as alluded to in the first paragraph)? Without this rationale, the reader is left with an impression that the experiments were done because of a technical capability rather than a conceptual thrust.

The cited works for the statement the "AAV viral vector expressing TeNT undre the human dlx promoter, which is selective for HVC inhibitory interneurons" (reference 5 Kosche et al., 2016; and reference 10 Vallentin et al 2016) do not substantiate the targeting of this dlx5 promoter for interneurons in zebra finch HVC. Neither of these cited studies used viral vectors, and so this is a misattribution of the dlx5 promoter as targeting HVC inhibitory interneurons. However, the original development of this enhancer by Gord Fishell and others did have solid expression in HVC (Dimidschstein et al., 2016, Nature Neuroscience), and the enhancer was used to successfully target inhibitory neurons in nearby nidopallium NCM (Spool et al., 2022, Curr Biol). Citing these two studies would improve the standing of this viral approach. Nevertheless, the specific construct used here is not the same as the published studies mentioned above (AAV9-dlx-TeNT). The authors therefore need to show expression of the virus using some histological confirmation to cement the idea that they are indeed targeting inhibitory interneurons with this manipulation. The methods statement "a single injection (~100 nL) in the center of HVC was sufficient to label enough cells" is not convincing in the absence of quantified photomicrographs.

The authors present no physiological confirmation of TeNT on E/I balance directly, and so we don't have a clear picture of how/whether HVC interneurons are physiologically altered by this manipulation. That said, the Npix recordings show that there was a tremendous increase in gamma power following TeNT manipulation, which subsides as the protracted song recovery unfolds. This finding is somewhat counterintuitive, given that gamma oscillations are typically driven by inhibitory neurons in many systems (including songbird pallium) while the TeNT manipulation is purported to cause *reductions* in inhibitory neurotransmitter release within HVC. Some interpretation of these incongruent results would be useful in the Discussion.

The degradation and recovery of song is based mainly on the measures of duration of syllables and inter-syllable intervals, but HVC is also a key locus for song syllable sequence coding. The supplementary figures show some changes in sequences. It would improve the interpretation of both the degradation and recovery of the song to know whether syllable sequences (iiiABCCDDEF) truly recovered or were morphed in some way (e.g., iiiCDDDBEF). The PCA analyses (that the authors conducted) for these two potential outcomes would likely be very similar, but the actual songs would differ greatly under these two scenarios in terms of syllable sequence. From the representative spectrograms, it appears that the song syllable sequence does indeed recover well in these examples (perhaps less so in Supplementary Figure 3). A simple Markov-chain analysis of the syllable sequences across birds in the study would provide important confirmation of these insights.

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors Eapen, et al. investigated the peptide inhibitors of Cdc20. They applied a rational design approach, substituting residues found in the D-box consensus sequences to better align the peptides with the Cdc20-degron interface. In the process, the authors designed and tested a series of more potent binders, including ones that contain unnatural amino acids, and verified binding modes by elucidating the Cdc-20-peptide structures. The authors further showed that these peptides can engage with Cdc20 in the cellular context, and can inhibit APC/CCdc20 ubiquitination activity. Finally, the authors demonstrated that these peptides could be used as portable degron motifs that drive the degradation of a fused fluorescent protein.

Strengths:

This manuscript is clear and straightforward to follow. The investigation of different peptide variations was comprehensive and well-executed. This work provided the groundwork for the development of peptide drug modalities to inhibit degradation or applying peptides as portable motifs to achieve targeted degradation. Both of which are impactful. The additional points provided by the authors in response to reviewers further strengthened the manuscript and enhanced its clarity.

Weaknesses:

None, the authors have addressed all my comments, and I have no additional suggestions.

Reviewer #1 (Public review):

Summary:

The study dissects distinct pools of diacylglycerol (DAG), continuing a line of research on the central concept that there is a major lipid metabolism DAG pool in cells, but also a smaller signaling DAG pool. It tests the hypothesis that the second pool is regulated by Dip2, which influences Pkc1 signaling. The group shows that stressed yeast increase specific DAG species C36:0 and 36:1, and propose this promotes Pkc1 activation via Pck1 binding 36:0. The study also examines how perturbing the lipid metabolism DAG pool via various deletions such as lro1, dga1, and pah1 deletion impacts DAG and stress signaling. Overall this is an interesting study that adds new data to how different DAG pools influence cellular signaling.

Strengths:

The study nicely combined lipidomic profiling with stress signaling biochemistry and yeast growth assays.

Weaknesses:

One suggestion to improve the study is to examine the spatial organization of Dip2 within cells, and how this impacts its ability to modulate DAG pools. Dip2 has previously been proposed to function at mitochondria-vacuole contacts (Mondal 2022). Examining how Dip2 localization is impacted when different DAG pools are manipulated such as by deletion Pah1 (also suggested to work at yeast contact sites such as the nucleus-vacuole junction), or with Lro1 or Dga1 deletion would broaden the scope of the study.

Comments on revisions:

The revision addresses several of the concerns raised previously. Most importantly, it softens several conclusions that more clearly delineates limitations of the study. The study has yet to address how Dip2 and Pkc1 crosstalk, but new text addresses this limitation. There is also more analysis of Dip2 localization in other conditions where cell DAG pools are elevated (ie a LRO1 and DGA1 double KO, as well as PAH1 KO). Loss of these proteins elevates ER DAG, but Dip2 remains mitochondrially associated. This may imply DAG specificity, or that changes to DAG pools globally does not impact Dip2 import into mitochondria.

Reviewer #1 (Public review):

Summary:

This manuscript addresses the challenge of understanding and capturing the similarity among large numbers of visual images. The authors show that an automated approach using artificial neural networks that focuses upon the embedding of similarity through behaviorally relevant dimensions can predict human similarity data up to a certain level of granularity.

Strengths:

The manuscript starts with a very useful introduction that sets the stage with an insightful Figure 1. The methods are state of the art and well thought off, and the data are compelling. The authors demonstrate the added value of their approach in several directions, resulting in a manuscript that is highly relevant for different domains. The authors also explore its limitations (e.g., granularity).

Weaknesses:

Although this manuscript and the work it describes are already of high quality, I see several ways in which it could be further improved. Below I rank these suggestions tentatively in order of importance.

Predictions obtain correlations above 0.80, often close to correlations of 0.90. The performance of DimPred is not trivial, given how much better it performs relative to classic RSA and feature reweighting. Yet, the ceiling is not sufficiently characterized. What is the noise ceiling in the main and additional similarity sets that are used? If the noise ceiling is higher than the prediction correlations, then can the authors try to find the stimulus pairs for which the approach systematically fails to capture similarity? Or is the mismatch very distributed across the full stimulus set?

Also in the section on p. 8-p.9, it is crucial to provide information on the noise ceiling of the various datasets.

This consideration of noise ceiling brings me to another consideration. Arguments have been made that a focus on overall prediction accuracy might mask important differences in underlying processes that can be demonstrated in more specific, experimental situations (Bowers et al., 2023). Can the authors exclude the possibility that their automatic approach would fail dramatically in specifically engineered situations? Some examples can be found in the 2024 challenge of the BrainScore platform. How can future users of this approach know whether they are in such a situation or not?

The authors demonstrated one limitation of the DimPred approach to capture fine-grained similarity among highly similar stimuli. The implications of this finding were not clear to me from the Abstract etc, because it is not sufficiently highlighted in the summaries that in this case DimPred performs even worse, and much worse, than more simple approaches like feature reweighting and even than classic RSA. I would discuss this outcome more in detail. With hindsight, this problem might not be so surprising given that DimPred relies upon the embedding with a few tens dimensions that mostly capture between-category differences. To me, this seems like a more fundamental limitation than a mere problem of granularity or lack of data, as suggested in the abstract.

The DimPred approach is based on the dimensions of a similarity embedding derived from human behavior. What is important here is (i) that DimPred is based upon an approach that tries to capture latent dimensions; or (ii) that these dimensions are behaviorally relevant? There are a lot of dimension-focused approaches. Generic ones are PCA, MDS, etc. More domain-specific approaches in cogneuro include the following: (i) for two-dimensional shape representations, good results have been obtained with image-computable dimensions of various levels of complexity (Morgenstern et al., 2021, PLOS Comput. Biol.); (ii) another dimension-focused approach has focused upon identifying dimensions that are universal across networks & human representations (Chen & Bonner, 2024, arXiv). Would such generic or more specific approaches work as well as DimPred?

Joint Public Reviews:

In this study, the authors suggest that DuoHexaBody-CD37, a biparatopic CD37-targeting antibody, can induce direct cytotoxicity in diffuse large B-cell lymphoma (DLBCL) cells through antibody clustering and SHP-1 activation, independent of complement. They further propose that DuoHexaBody-CD37 inhibits cytokine-mediated pro-survival signalling, suggesting a broader role for CD37-directed therapy in disrupting tumour supportive signalling networks.

A strength of the study is the systematic in vitro characterisation of signalling responses to DuoHexaBody-CD37 across both malignant and normal B-cells. The inclusion of phosphoproteomic profiling and mutant constructs provides mechanistic detail, and the findings may be of interest to researchers working on antibody therapeutics in lymphoma.

However, the evidence supporting key mechanistic processes - particularly the role of SHP-1 in mediating cytotoxicity and the requirement for Fc receptor crosslinking - is incomplete and would benefit from further functional validation. While CD37 has been explored previously as a therapeutic target, this study does add mechanistic insight into direct cytotoxicity and cytokine modulation. Nevertheless, the exclusive reliance on in vitro systems makes the translational relevance unclear.

Overall, the study provides valuable insight into CD37-mediated signalling in lymphoma cells, but the evidence remains incomplete to support broader conclusions about therapeutic impact.

Reviewer #1 (Public review):

Summary:

The authors analyze transcription in single cells before and after 4000 rads of ionizing radiation. They use Seuratv5 for their analyses, which allows them to show that most of the genes cluster along the proximal-distal axis. Due to the high heterogeneity in the transcripts, they use the Herfindahl-Hirschman index (HHI) from Economics, which measures market concentration. Using the HHI, they find that genes involved in several processes (like cell death, response to ROS, DNA damage response (DDR)) are relatively similar across clusters. However, ligands activating the JAK/STAT, Pvr, and JNK pathways and transcription factors Ets21C and dysf are upregulated regionally. The JAK/STAT ligands Upd1,2,3 require p53 for their upregulation after irradiation, but the normal expression of Upd1 in unirradiated discs is p53-independent. This analysis also identified a cluster of cells that expressed tribbles, encoding a factor that downregulates mitosis-promoting String and Twine, that appears to be G2/M arrested and expressed numerous genes involved in apoptosis, DDR, the aforementioned ligands, and TFs. As such, the tribbles-high cluster contains much of the heterogeneity.

Strengths:

(1) The authors have used robust methods for rearing Drosophila larvae, irradiating wing discs, and analyzing the data with Seurat v5 and HHI.

(2) These data will be informative for the field.

(3) Most of the data is well-presented.

(4) The literature is appropriately cited.

Weaknesses:

(1) The data in Figure 1 are single-image representations. I assume that counting the number of nuclei that are positive for these markers is difficult, but it would be good to get a sense of how representative these images are and how many discs were analyzed for each condition in B-M.

(2) Some of the figures are unclear.

Reviewer #1 (Public review):

In the manuscript, Aldridge and colleagues investigate the role of IL-27 in regulating hematopoiesis during T. gondii infection. Using loss-of-function approaches, reporter mice, and the generation of serial chimeric mice, they elegantly demonstrate that IL-27 induction plays a critical role in modulating bone marrow myelopoiesis and monocyte generation to the infection site. The study is well-designed, with clear experimental approaches that effectively address the mechanisms by which IL-27 regulates bone marrow myelopoiesis and prevents HSC exhaustion.

Reviewer #1 (Public review):

Summary:

This study addresses the encoding of forelimb movement parameters using a reach-to-grasp task in mice. The authors use a modified version of the water-reaching paradigm developed by Galinanes and Huber. Two-photon calcium imaging was then performed with GCaMP6f to measure activity across both the contralateral caudal forelimb area (CFA) and the forelimb portion of primary somatosensory cortex (fS1) as mice perform the reaching behavior. Established methods were used to extract the activity of imaged neurons in layer 2/3, including methods for deconvolving the calcium indicator's response function from fluorescence time series. Video-based limb tracking was performed to track the positions of several sites on the forelimb during reaching and extract numerous low-level (joint angle) and high-level (reach direction) parameters. The authors find substantial encoding of parameters for both the proximal and distal parts of the limb across both CFA and fS1, with individual neurons showing heterogeneous parameter encoding. Limb movement can be decoded similarly well from both CFA and fS1, though CFA activity enables decoding of reach direction earlier and for a more extended duration than fS1 activity. Collectively, these results indicate involvement of a broadly distributed sensorimotor region in mouse cortex in determining low-level features of limb movement during reach-to-grasp.

Strengths:

The technical approach is of very high quality. In particular, the decoding methods are well designed and rigorous. The use of partial correlations to distinguish correlation between cortical activity and either proximal or distal limb parameters or either low- or high-level movement parameters was very nice. The limb tracking was also of extremely high quality, and critical here to revealing the richness of distal limb movement during task performance.

The task itself also reflects an important extension of the original work by Galinanes and Huber. The demonstration of a clear, trackable grasp component in a paradigm where mice will perform hundreds of trials per day expands the experimental opportunities for the field. This is an exciting development.

The findings here are important and the support for them is solid. The work represents an important step forward toward understanding the cortical origins of limb control signals. One can imagine numerous extensions of this work to address basic questions that have not been reachable in other model systems.

Collectively, these strengths made this manuscript a pleasure to read and review.

Weaknesses:

In the last section of the results, the authors purport to examine the representation of "higher-level target-related signals," using the decoding of reach direction. While I think the authors are careful in their phrasing here, I think they should be more explicit about what these signals could be reflecting. The "signals" here that are used to decode direction could relate to anything - low-level signals related to limb or postural muscles, or true high-level commands that dictate only what movement downstream motor centers should execute, rather than the muscle commands that dictate how. One could imagine using a partial correlation-type approach again here to extract a signal uncorrelated with all the measured low-level parameters, but there would still be all the unmeasured ones. Again, I think it is still ok to call these "high-level signals," but I think some explicit discussion of what these signals could reflect is necessary.

Related to this, I think the manuscript in general does not do an adequate job of explicitly raising the important caveats in interpreting parametric correlations in motor system signals, like those raised by Todorov, 2000. The authors do an expert job of handling the correlations, using PCA to extract uncorrelated components and using the partial correlation approach. However, more clarity about the range of possible signal types the recorded activity could reflect seems necessary.

The manuscript could also do a better job of clarifying relevant similarities and differences between the rodent and primate systems, especially given the claims about the rodent being a "first-class" system for examining the cellular and circuit basis of motor control, which I certainly agree with. Interspecies similarities and differences could be better addressed both in the Introduction, where results from both rodents and primates are intermixed (second paragraph), and in the Discussion, where more clarity on how results here agree and disagree with those from primates would be helpful. For example, the ratio of corticospinal projections targeting sensory and motor divisions of the spinal cord differs substantially between rodents and primates. As another example, the relatively high physical proximity between the typical neurons in mouse M1 and S1 compared to primates seems likely to yoke their activity together to a greater extent. There is also the relatively large extent of fS1 from which forelimb movements can be elicited through intracortical microstimulation at current levels similar to those for evoking movement from M1. All of these seem relevant in the context of findings that activity in mouse M1 and S1 are similar.

In addition, there are a number of other issues related to the interpretation of findings here that are not adequately addressed. These are described in the Recommendations for improvement.

Reviewer #1 (Public review):

Summary

Lysine acetoacetylation (Kacac) is a recently discovered histone post-translational modification (PTM) connected to ketone body metabolism. This research outlines a chemo-immunological method for detecting Kacac, eliminating the requirement for creating new antibodies. The study demonstrates that acetoacetate acts as the precursor for Kacac, which is catalyzed by the acyltransferases GCN5, p300, and PCAF, and removed by the deacetylase HDAC3. Acetoacetyl-CoA synthetase (AACS) is identified as a central regulator of Kacac levels in cells. A proteomic analysis revealed 139 Kacac sites across 85 human proteins, showing the modification's extensive influence on various cellular functions. Additional bioinformatics and RNA sequencing data suggest a relationship between Kacac and other PTMs, such as lysine β-hydroxybutyrylation (Kbhb), in regulating biological pathways. The findings underscore Kacac's role in histone and non-histone protein regulation, providing a foundation for future research into the roles of ketone bodies in metabolic regulation and disease processes.

Strengths

(1) The study developed an innovative method by using a novel chemo-immunological approach to the detection of lysine acetoacetylation. This provides a reliable method for the detection of specific Kacac using commercially available antibodies.

(2) The research has done a comprehensive proteome analysis to identify unique Kacac sites on 85 human proteins by using proteomic profiling. This detailed landscape of lysine acetoacetylation provides a possible role in cellular processes.

(3) The functional characterization of enzymes explores the activity of acetoacetyltransferase of key enzymes like GCN5, p300, and PCAF. This provides a deeper understanding of their function in cellular regulation and histone modifications.

(4) The impact of acetyl-CoA and acetoacetyl-CoA on histone acetylation provides the differential regulation of acylations in mammalian cells, which contributes to the understanding of metabolic-epigenetic crosstalk.

(5) The study examined acetoacetylation levels and patterns, which involve experiments using treatment with acetohydroxamic acid or lovastatin in combination with lithium acetoacetate, providing insights into the regulation of SCOT and HMGCR activities.

Weakness

(1) There is a limitation to functional validation, related to the work on the biological relevance of identified acetoacetylation sites. Hence, the study requires certain functional validation experiments to provide robust conclusions regarding the functional implications of these modifications on cellular processes and protein function. For example, functional implications of the identified acetoacetylation sites on histone proteins would aid the interpretation of the results.

(2) The authors could have studied acetoacetylation patterns between healthy cells and disease models like cancer cells to investigate potential dysregulation of acetoacetylation in pathological conditions, which could provide insights into their PTM function in disease progression and pathogenesis.

(3) The time-course experiments could be performed following acetoacetate treatment to understand temporal dynamics, which can capture the acetoacetylation kinetic change, thereby providing a mechanistic understanding of the PTM changes and their regulatory mechanisms.

(4) Though the discussion section indeed provides critical analysis of the results in the context of existing literature, further providing insights into acetoacetylation's broader implications in histone modification. However, the study could provide a discussion on the impact of the overlap of other post-translational modifications with Kacac sites with their implications on protein functions.

Impact

The authors successfully identified novel acetoacetylation sites on proteins, expanding the understanding of this post-translational modification. The authors conducted experiments to validate the functional significance of acetoacetylation by studying its impact on histone modifications and cellular functions.

Reviewer #1 (Public review):

Summary:

In this paper, authors investigated the role of RUNT-related transcription factor 2 (RUNX2) in oral squamous carcinoma (OSCC) growth and resistance to ferroptosis. They found that RUNX2 suppresses ferroptosis through transcriptional regulation of peroxiredoxin-2. They further explored the upstream positive regulator of RUNX2, HOXA10 and found that HOXA1/RNUX2/PRDX2 axis protects OSCC from ferroptosis.

Strengths:

The study is well designed and provides a novel mechanism of HOXA1/RNUX2/PRDX2 control of ferroptosis in OSCC.

Weaknesses:

According to the data presented in (Figure 2F, Figure 3F and G, Figure 5D and Figure 6E and F), apoptosis seems to be affected in the same amount as ferroptosis by HOXA1/RNUX2/PRDX2 axis, which raises a question on the authors' specific focus on ferroptosis in this study. Reasonably, authors should adapt the title and the abstract in a way that it recapitulates the whole data, which is HOXA1/RNUX2/PRDX2 axis control of cell death, including ferroptosis and apoptosis in OSCC.

Comments on revisions:

The revised manuscript has been well improved, and I'm satisfied with the authors' response to my comments.

Reviewer #1 (Public review):

Summary:

Epiney et al. use single-nuclei RNA sequencing (snRNA-seq) to characterize the lineage of Type-2 (T2) neuroblasts (NBs) in the adult Drosophila brain. To isolate cells born from T2 NBs, the authors used a genetic tool that specifically allows the permanent labeling of T2-derived cell types, which are then FAC-sorted for snRNA-seq. This effective labeling approach also allows them to compare the isolated T2 lineage cells with T1-derived cell types by a simple exclusion method. The authors begin by describing a transcriptomic atlas for all T1 and T2-derived neuronal and glia clusters, reporting that the T2-derived lineage comprises 161 neuronal clusters, in contrast to the T1 lineage which comprises 114 of them. The authors then use the expression of VAChT, VGlut, Gad1, Tbh, Ple, SerT, and Tdc2 to show that T2 neuroblasts generate all major neuron classes of fast-acting neurotransmitters. Strikingly, they show that a subset of glia and neuronal clusters have disproportionate enrichment in males or females, suggesting that T2 neuroblasts generate sex-biased cell types. The authors then proceed to characterize neuropeptide expression across T2-derived neuronal clusters and argue that the same neuropeptide can be expressed across different cell types, while similar cell types can express distinct neuropeptides. The functional implication of both observations, however, remains to be tested. Furthermore, the authors describe combinatorial transcription factor (TF) codes that are correlated with neuropeptide expression for T2-derived neurons along with an overall TF code for all T2-derived cell types, both of which will serve as an important starting point for future investigations. Finally, the authors map well-studied neuronal types of the central complex to the clusters of their T2-derived snRNA-seq dataset. They use known marker combinations, bulk RNA-seq data and highly specific split-GAL4 driver lines to annotate their T2-derived atlas, establishing a comprehensive transcriptomic atlas that would guide future studies in this field.

Strengths:

This study provides an in-depth transcriptomic characterization of neurons and glia derived from Type-2 neuroblast lineages. The results of this manuscript offer several future directions to investigate the mechanisms of diversifying neuronal identity. The datasets of T1-derived and T2-derived cells will pave the way for studies focused on the functional analysis of combinatorial TF codes specifying cell identity, sex-based differences in neurogenesis and gliogenesis, the relationship between neuropeptide (co)expression and cell identity, and the differential contributions of distinct progenitor populations to the same cell type.

Weaknesses:

The study presents several important observations based on the characterization of Type II neuroblast-derived lineages. However, a mechanistic insight is missing for most observations. The idea that there is a sex-specific bias to certain T2-derived neurons and glial clusters is quite interesting, however, the functional significance of this observation is not tested or discussed extensively. Finally, the authors do not show whether the combinatorial TF code is indeed necessary for neuropeptide expression or if this is just a correlation due to cell identity being defined by TFs. Functional knockdown of some candidate TFs for a subset of neuropeptide-expressing cells would have been helpful in this case.

Comments on revisions:

The authors have addressed my recommendations.

Reviewer #2 (Public review):

Summary:

The authors developed a novel tool, SCellBOW, to perform cell clustering and infer survival risks on individual cancer cell clusters from the single cell RNA seq dataset. The key ideas/techniques used in the tool include transfer learning, bag of words (BOW), and phenotype algebra which is similar to word algebra from natural language processing (NLP). Comparisons with existing methods demonstrated that SCellBOW provides superior clustering results and exhibits robust performance across a wide range of datasets. Importantly, a distinguishing feature of SCellBOW compared to other tools is its ability to assign risk scores to specific cancer cell clusters. Using SCellBOW, the authors identified a new group of prostate cancer cells characterized by a highly aggressive and dedifferentiated phenotype.

Strengths:

The application of natural language processing (NLP) to single-cell RNA sequencing (scRNA-seq) datasets is both smart and insightful. Encoding gene expression levels as word frequencies is a creative way to apply text analysis techniques to biological data. When combined with transfer learning, this approach enhances our ability to describe the heterogeneity of different cells, offering a novel method for understanding the biological behavior of individual cells and surpassing the capabilities of existing cell clustering methods. Moreover, the ability of the package to predict risk, particularly within cancer datasets, significantly expands the potential applications.

Weaknesses:

Given the promising nature of this tool, it would be beneficial for the authors to test the risk-stratification functionality on other types of tumors with high heterogeneity, such as liver and pancreatic cancers, which currently lack clinically relevant and well-recognized stratification methods. Additionally, it would be worthwhile to investigate how the tool could be applied to spatial transcriptomics by analyzing cell embeddings from different layers within these tissues.