Reviewer #3 (Public review):

This paper investigates invariance to natural background noise in the auditory cortex of ferrets and humans. The authors first replicate, in ferrets, a finding from human neuroimaging showing that invariance to background noise increases along the cortical hierarchy (i.e., from primary to non-primary auditory cortex). Next, the authors ask whether this pattern of invariance could be explained by differences in tuning to low-level acoustic features across primary and non-primary regions. The authors conclude that this tuning can explain the spatial organization of background invariance in ferrets, but not in humans. The conclusions of the paper are generally well supported by the data, but additional control analyses are needed to fully substantiate the paper's claims. Finally, additional discussion and potentially analysis, are needed to reconcile these findings with similar work in the literature (particularly that of Hamersky et al. 2025 J. Neurosci.).

The paper is very straightforwardly written, with a generally clear presentation including well-designed and visually appealing figures. Not only does this paper provide an important replication in a non-human animal model commonly used in auditory neuroscience, but it also extends the original findings in three ways. First, the authors reveal a more fine-grained gradient of background invariance by showing that background invariance increases across primary, secondary, and tertiary cortical regions. Second, the authors address a potential mechanism that might underlie this pattern of invariance by considering whether differences in tuning to frequency and spectrotemporal modulations across regions could account for the observed pattern of invariance. The spectrotemporal modulation encoding model used here is a well-established approach in auditory neuroscience and seems appropriate for exploring potential mechanisms underlying invariance in auditory cortex, particularly in ferrets. However, as discussed below, the analyses based on this simple encoding model are only informative to the extent that the model accurately captures neural responses. Thus, its limitations in modeling non-primary human auditory cortex should be considered when interpreting cross-species comparisons. Third, the authors provide a more complete picture of invariance by additionally analyzing foreground invariance, a complementary measure not explored in the original study. While this analysis feels like a natural extension and its inclusion is appreciated, the interpretation of these foreground invariance findings remains somewhat unclear, as the authors offer limited discussion of their significance or relation to existing literature.

As mentioned above, interpretation of the invariance analyses using predictions from the spectrotemporal modulation encoding model hinges on the model's ability to accurately predict neural responses. Although Figure S5 suggests the encoding model was generally able to predict voxel responses accurately, the authors note in the introduction that, in human auditory cortex, this kind of tuning can explain responses in primary areas but not in non-primary areas (Norman-Haignere & McDermott, PLOS Biol. 2018). Indeed, the prediction accuracy histograms in Figure S5C suggest a slight difference in the model's ability to predict responses in primary versus non-primary voxels. Additional analyses should be done to a) determine whether the prediction accuracies are meaningfully different across regions and b) examine whether controlling for prediction accuracy across regions (i.e., sub-selecting voxels across regions with matched prediction accuracy) affects the outcomes of the invariance analyses.

A related concern is the procedure used to train the encoding model. From the methods, it appears that the model may have been fit using responses to both isolated and mixture sounds. If so, this raises questions about the interpretability of the invariance analyses. In particular, fitting the model to all stimuli, including mixtures, may inflate the apparent ability of the model to "explain" invariance, since it is effectively trained on the phenomenon it is later evaluated on. Put another way, if a voxel exhibits invariance, and the model is trained to predict the voxel's responses to all types of stimuli (both isolated sounds and mixtures), then the model must also show invariance to the extent it can accurately predict voxel responses, making the result somewhat circular. A more informative approach would be to train the encoding model only on responses to isolated sounds (or even better, a completely independent set of sounds), as this would help clarify whether any observed invariance is emergent from the model (i.e., truly a result of low-level tuning to spectrotemporal features) or simply reflects what it was trained to reproduce.

Finally, the interpretation of the foreground invariance results remains somewhat unclear. In ferrets (Figure 2I), the authors report relatively little foreground invariance, whereas in humans (Figure 5G), most participants appear to show relatively high levels of foreground invariance in primary auditory cortex (around 0.6 or greater). However, the paper does not explicitly address these apparent cross-species differences. Moreover, the findings in ferrets seem at odds with other recent work in ferrets (Hamersky et al. 2025 J. Neurosci.), which shows that background sounds tend to dominate responses to mixtures, suggesting a prevalence of foreground invariance at the neuronal level. Although this comparison comes with the caveat that the methods differ substantially from those used in the current study, given the contrast with the findings of this paper, further discussion would nonetheless be valuable to help contextualize the current findings and clarify how they relate to prior work.

Reviewer #3 (Public review):

Summary:

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

Strengths:

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

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

DOI: 10.1186/s13058-025-02028-3

Resource: (RRID:CVCL_0553)

Curator: @dhovakimyan1

SciCrunch record: RRID:CVCL_0553

What is this?

DOI: 10.1038/s41598-025-99364-3

Resource: (IMSR Cat# JAX_000664,RRID:IMSR_JAX:000664)

Curator: @dhovakimyan1

SciCrunch record: RRID:IMSR_JAX:000664

What is this?

Reviewer #3 (Public review):

Summary:

The manuscript by Guo and colleagues features the documentation and interpretation of three successions of continental to marginal marine deposits spanning the P/T transition and their respective ichnofaunas. Based on these new data inferences concerning end-Permian mass extinction and Triassic recovery in the tropical realm are discussed.

Strengths:

The manuscript is well written and organized and includes a large amount of new lithological and ichnological data that illuminate ecosystem evolution in a time of large scale transition. The lithological documentations, facies interpretations and ichnotaxonomic assignments look alright (with few exceptions).

Weaknesses: [all eliminated in revision]

Reviewer #3 (Public review):

Summary:

Papagiannakis et al. present a detailed study exploring the relationship between DNA/polysome phase separation and nucleoid segregation in Escherichia coli. Using a combination of experiments and modelling, the authors aim to link physical principles with biological processes to better understand nucleoid organisation and segregation during cell growth.

Strengths:

The authors have a conducted a large number of experiments under different growth conditions and physiological perturbations (using antibiotics) to analyse the biophysical factors underlying the spatial organisation of nucleoids within growing E. coli cells. A simple model of ribosome-nucleoid segregation has been developed to explain the observations and tested with cleverly designed perturbation experiments.

The model and explanation presented in the original version have been strengthened with additional results and consideration of new factors. In particular, the radial attachment of the nucleoid, supported by previous studies and the A22 treatment data in this study, provides a plausible mechanism that prevents ribosomes from diffusing between and around the nucleoid lobes through the radial shells surrounding the nucleoid. The revised version of the paper incorporates this effect, resulting in model predictions that align well with the drug treatment outcomes and the observed mid-cell accumulation and confinement of ribosomes.

Furthermore, experiments involving plasmid-based gene expression, designed to redirect transcription away from chromosomal loci, offer compelling validation of the model's predictions. Overall, this is a robust and insightful study that will be of significant value to the quantitative microbiology community.

Reviewer #3 (Public review):

Summary:

It has been proposed that the FOI is a method of using parasite genetics to determine changes in transmission in areas with high asymptomatic infection. The manuscript attempts to use queuing theory to convert multiplicity of infection estimates (MOI) into estimates of the force of infection (FOI), which they define as the number of genetically distinct blood-stage strains. They look to validate the method by applying them to simulated results from a previously published agent based model. They then apply these queuing theory methods to previously published and analysed genetic data from Ghana. They then compare their results to previous estimates of FOI.

Strengths:

It would be great to be able to infer FOI from cross sectional surveys which are easier and cheaper than current FOI estimates which require longitudinal studies. This work proposes a method to convert MOI to FOI for cross sectional studies. They attempt to validate this process using a previously published agent based model which helps us understand the complexity of parasite population genetics.

Weaknesses:

(1) I fear that the work could be easily over-interpreted as no true validation was done as no field estimates of FOI (I think considered true validation) were measured. You have developed a method of estimating FOI from MOI which makes a number of biological and structural assumptions. I would not call being able to recreate model results that were generated using a model that makes its own (probably similar) defined set of biological and structural assumptions acts as a validation of what is going on in the field. The authors claim this at times (for example, Line 153 ) and I feel it would be appropriate to differentiate this in the discussion.

(2) Another aspect of the paper is adding greater realism to the previous agent based model, by including assumptions on missing data and under sampling. This takes prominence in the figures and results section, but I would imagine is generally not as interesting to the less specialised reader. The apparent lack of impact of drug treatment on MOI is interesting and counterintuitive, though it is not really mentioned in the results or discussion sufficiently to allay my confusion. I would have been interested in understanding the relationship between MOI and FOI as generated by your queuing theory method and the model. It isn't clear to me why these more standard results are not presented, as I would imagine they are outputs of the model (though happy to stand corrected - it isn't entirely clear to me what the model is doing in this manuscript alone).

(3) I would suggest that outside of malaria geneticists, the force of infection is considered to be the entomological inoculation rate, not the number of genetically distinct blood-stage strains. I appreciate that FOI has been used to explain the later before by others, though the authors could avoid confusion by stating this clearly throughout the manuscript. For example, the abstract says FOI is "the number of new infections acquired by an individual host over a given time interval" which suggests the former, please consider clarifying.

(4) Line 319 says "Nevertheless, overall, our paired EIR (directly measured by the entomological team in Ghana (Tiedje et al., 2022)) and FOI values are reasonably consistent with the data points from previous studies, suggesting the robustness of our proposed methods". I would agree that the results are consistent, given that there is huge variation in Figure 4 despite the transformed scales, but I would not say this suggests a robustness of the method.

(5) The text is a little difficult to follow at times, and sometimes requires multiple reads to understand. Greater precision is needed with the language in a few situations and some of the assumptions made in the modelling process are not referenced, making it unclear whether it is a true representation of the biology.

Comments on revisions:

I think the authors gave a robust but thorough response to our reviews and made some important changes to the manuscript which certainly clarify things for me.

Reviewer #3 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

In addition to improving the written and graphical presentation of the results, there is only one point I would like to see clarified: the inclusion of additional experiments, even if they have already been performed but are not applicable due to methodological difficulties regarding the role of Procr+ cells. Negative results also help the scientific community avoid unnecessary experiments and advance understanding.

Reviewer #3 (Public review):

The authors provide convincing data to support an elegant model in which ribosome stalling by ToiL promotes downstream topAI translation and prevents premature Rho-dependent transcription termination. However, the physiological consequences of activating topAI-yjhQP expression upon exposure to various ribosome-targeting antibiotics remain unresolved. The authors have satisfactorily addressed all major concerns raised by the reviewers, particularly regarding the SHAPE-seq data. Overall, this study underscores the diversity of regulatory ribosome-stalling peptides in nature, highlighting ToiL's uniqueness in sensing multiple antibiotics and offering significant insights into bacterial gene regulation coordinated by transcription and translation.

[Editors' note: The earlier public reviews are included. No additional reviews were requested.]

Reviewer #3 (Public review):

Summary:

The authors have extended their previous research to develop TOPBP1 as a potential drug target for colorectal cancer by inhibiting its condensation. Utilizing an optogenetic approach, they identified the small molecule AZD2858, which inhibits TOPBP1 condensation and works synergistically with first-line chemotherapy to suppress colorectal cancer cell growth. The authors investigated the mechanism and discovered that disrupting TOPBP1 assembly inhibits the ATR/Chk1 signaling pathway, leading to increased DNA damage and apoptosis, even in drug-resistant colorectal cancer cell lines.

Comments on latest version:

The authors have addressed most of the concerns that I raised in the first round of revision and I have no further questions. I appreciate the authors's efforts in carrying out an preliminary in vivo work, although as the authors pointed out the compound seems to be not effective in vivo. Future work is desired to address this to clarify the significance of the work.

Reviewer #3 (Public review):

Summary:

The heat shock response (HSR) is an inducible transcriptional program that has provided paradigmatic insight into how stress cues feed information into the control of gene expression. The recent elucidation that the chaperone Hsp70 controls the DNA binding activity of the central HSR transcription factor Hsf1 by direct binding has spurred the question of how such a general chaperone obtains specificity. This study has addressed the next logical question: how J-domain proteins execute this task in budding yeast, the leading cell model for studying the HSR. While an involvement and in part overlapping function of general class A and B J-domain proteins, Ydj1 and Sis1 are indicated by the genetic analysis, a highly specific role for the class A Apj1 in displacing Hsf1 from the promoters is found, unveiling specificity in the system.

Strengths

The central strong point of the paper is the identification of class A J-domain protein Apj1 as a specific regulator of the attenuation of the HSR by removing Hsf1 from HSEs at the promoters. The genetic evidence and the ChIP data strongly support this claim. This identification of a specific role for a lowly expressed nuclear J-domain protein changes how the wiring of the HSR should be viewed. It also raises important questions regarding the model of chaperone titration, the concept that a chaperone with limited availability is involved in a tug of war involving competing interactions with misfolded protein substrates and regulatory interactions with Hsf1. Perhaps Apj1, with its low levels and interactions with misfolded and aggregated proteins in the nucleus, is the titrated Hsp70 (co)chaperone that determines the extent of the HSR? This would mean that Apj1 is at the nexus of the chaperone titration mechanism. Although Apj1 is not a highly conserved J domain protein among eukaryotes the strength of the study is that is provides a conceptual framework for what may be required for chaperone titration in other eukaryotes: One or more nuclear J-domain proteins with low nuclear levels that has an affinity for Hsf1 and that can become limiting due to interactions with misfolded Hsp70 proteins. The provides a pathway for how these may be identified using, for example, ChIP-seq.

Weaknesses

A built-in challenge when studying the mechanism of the HSR is the general role of the Hsp70 chaperone system and its J domain proteins. Indeed, a weakness of the study is that it is unclear which of the phenotypic effects have to do with directly recruiting Hsp70 to Hsf1 dependent on a J domain protein and what instead is an indirect effect of protein misfolding caused by the mutation. This interpretation problem is clearly and appropriately dealt with in the manuscript text and in experiments, but is of such fundamental nature that it cannot easily be fully ruled out. One way forward is a reconstituted biochemical system that monitors how Hsf1 DNA binding is affected by the Hsp70 system, misfolded proteins, and the various J domain proteins. Yet this approach is clearly beyond the scope of this study.

Reviewer #3 (Public review):

Summary

Kerlin et.al combined single-molecule RNA FISH with oligonucleotide-based DNA FISH to directly examine the transcriptional activities of three adjacent genes at individual alleles in MCF7 cells. Importantly, they provided quantitative methods to resolve allele-specific (cis) and cell-to-cell (trans) variation and quantified the contribution of burst co-occurrence and burst size, which may help to more accurately analyze transcription coregulation. They found that transcriptional variability is largely gene-autonomous, and by disentangling burst co-occurrence and burst size after E2 induction, they proposed two distinct mechanisms of local gene regulation.

Strengths:

(1) Innovative Research Methods: Successfully integrates single-molecule RNA FISH with oligonucleotide-based DNA FISH to directly image the transcriptional activities of three adjacent genes at individual alleles. This enables the observation of transcriptional dynamics more precisely and provides a powerful tool for studying gene regulation.

(2) Novel Data Analysis Approaches: Develops two new analysis methods to dissect the sources of gene activity (co)variation. One approach separates allele-extrinsic, allele-intrinsic, and gene-autonomous components, and the other quantifies the contributions of burst co-occurrence and burst size correlations. These methods help to more accurately analyze transcriptional correlations between genes and reveal potential regulatory mechanisms.

Weaknesses:

Biological Insights: The findings challenge the traditional view of contact insulation sites as strict regulators of gene coregulation and suggest two distinct coregulatory mechanisms influenced by local chromosome folding. However, expression activity of multiple genes is differentially correlated at the population-level or cell-level versus single-allele-level. More in-depth analysis is needed for further biological insights.

Reviewer #3 (Public review):

Summary:

The authors present a technically impressive data set showing that repeated excitation or restraint stress internalises somato dendritic α2A adrenergic autoreceptors (α2A ARs) in locus coeruleus (LC) neurons. Loss of these receptors weakens GIRK-dependent autoinhibition, raises neuronal excitability, and is accompanied by higher MAO-A, DOPEGAL, AEP, and tau N368 levels. The work combines rigorous whole-cell electrophysiology with barbadin-based trafficking assays, qPCR, Western blotting, and immunohistochemistry. The final schematic is appealing and could, in principle, explain early LC hyperactivity followed by degeneration in ageing and Alzheimer's disease.

Strengths:

(1) Multi-level approach - The study integrates electrophysiology, pharmacology, mRNA quantification, and protein-level analysis.

(2) The use of barbadin to block β-arrestin/AP-2-dependent internalisation is both technically precise and mechanistically informative.

(3) Well-executed electrophysiology.

(4) Translation relevance - converges to a model that can be discussed by peers (scientists can only discuss models - not data!).

Weaknesses:

Nevertheless, the manuscript currently reads as a sequence of discrete experiments rather than a single causal chain. Below, I outline the key points that should be addressed to make the model convincing.

Reviewer #3 (Public review):

Summary:

A subset of cancer cells attain replicative immortality by activating the ALT mechanism of telomere maintenance, which is currently the subject of intense research due to its potential for novel targeted therapies. Key questions remain in the field, such as whether ALT telomeres adhere to the same end-protection rules as telomeres in telomerase-expressing cells, or if ALT telomeres possess unique properties that could be targeted with new, less toxic cancer therapies. Both questions, along with the approaches developed by the authors to address them, are highly relevant.

Strengths:

Since chromosome ends resemble one-ended DSBs, the authors hypothesized that the previously described END-SEQ protocol could be used to accurately sequence the 5' end of telomeres on the C-rich strand. As expected, most reads corresponded to the C-rich strand and, confirming a previous observation by de Lange's group, most chromosomes end with the ATC-5' sequence, a feature that was found to be dependent on POT1 and to be conserved in both human ALT cells and mouse cells. Through a complementary method, S1-END-SEQ, the authors further explored ssDNA regions at telomeres, providing new insights into the characteristics of ALT telomeres. The study is original, the experiments were well-controlled and excellently executed.

Weaknesses:

Overall, the discussion section is lacking depth and should be expanded and a few additional experiments should be performed to clarify the results.

(1) The finding that the abundance of variant telomeric repeats (VTRs) within the final 30 nucleotides of the telomeric 5' ends is similar in both telomerase-expressing and ALT cells is intriguing, but the authors do not address this result. Could the authors provide more insight into this observation and suggest potential explanations? As the frequency of VTRs does not seem to be upregulated in POT1-depleted cells, what then drives the appearance of VTRs on the C-strand at the very end of telomeres? Is CST-Pola complex responsible?

(2) The authors also note that, in ALT cells, the frequency of VTRs in the first 30 nucleotides of the S1-END-SEQ reads is higher compared to END-SEQ, but this finding is not discussed either. Do the authors think that the presence of ssDNA regions is associated with the VTRs? Along this line, what is the frequency of VTRs in the END-SEQ analysis of TRF1-FokI-expressing ALT cells? Is it also increased? Has TRF1-FokI been applied to telomerase-expressing cells to compare VTR frequencies at internal sites between ALT and telomerase-expressing cells?

Finally, in these experiments (S1-END-SEQ or END-SEQ in TRF1-Fok1), is the frequency of VTRs the same on both the C- and the G-rich strands? It is possible that the sequences are not fully complementary in regions where G4 structures form.

(3) Based on the ratio of C-rich to G-rich reads in the S1-END-SEQ experiment, the authors estimate that ALT cells contain at least 3-5 ssDNA regions per chromosome end. While the calculation is understandable, this number could be discussed further to consider the possibility that the observed ratios (of roughly 0.5) might result from the presence of extrachromosomal DNA species, such as C-circles. The observed increase in the ratio of C-rich to G-rich reads in BLM-depleted cells supports this hypothesis, as BLM depletion suppresses C-circle formation in U2OS cells. To test this, the authors should examine the impact of POLD3 depletion on the C-rich/G-rich read ratio. Alternatively, they could separate high-molecular-weight (HMW) DNA from low-molecular-weight DNA in ALT cells and repeat the S1-END-SEQ in the HMW fraction.

(4) What is the authors' perspective on the presence of ssDNA at ALT telomeres? Do they attribute this to replication stress? It would be helpful for the authors to repeat the S1-END-SEQ in telomerase-expressing cells with very long telomeres, such as HeLa1.3 cells, to determine if ssDNA is a specific feature of ALT cells or a result of replication stress. The increased abundance of G4 structures at telomeres in HeLa1.3 cells (as shown in J. Wong's lab) may indicate that replication stress is a factor. Similar to Wong's work, it would be valuable to compare the C-rich/G-rich read ratios in HeLa1.3 cells to those in ALT cells with similar telomeric DNA content.

Minor Points:

(1) The Y-axes of Figure 4 should be relabeled to account for the G-strand reads. Additionally, statistical analyses are absent in Figure 4 and Figure S3.

(2) A careful proofreading of the manuscript is necessary.

Reviewer #3 (Public review):

This study investigates how two cortical regions which are central to the study of rodent motor control (rostral forelimb area, RFA, and caudal forelimb area, CFA) interact during directional forelimb reaching in mice. The authors investigate this interaction using (1) optogenetic manipulations in one area while recording extracellularly from the other, (2) statistical analyses of simultaneous CFA/RFA extracellular recordings, and (3) network modeling. The authors provide solid evidence that asymmetry between RFA and CFA can be observed, although such asymmetry is only observed in certain experimental and analytical contexts.

The authors find asymmetry when applying optogenetic perturbations, reporting a greater impact of RFA inactivation on CFA activity than vice-versa. The authors then investigate asymmetry in endogenous activity during forelimb movements and find asymmetry with some analytical methods but not others. Asymmetry was observed in the onset timing of movement-related deviations of local latent components with RFA leading CFA (computed with PCA) and in a relatively higher proportion and importance of cross-area latent components with RFA leading than CFA leading (computed with DLAG). However, no asymmetry was observed using several other methods that compute cross-area latent dynamics, nor with methods computed on individual neuron pairs across regions. The authors follow up this experimental work by developing a two-area model with asymmetric dependence on cross-area input. This model is used to show that differences in local connectivity can drive asymmetry between two areas with equal amounts of across-region input.

Overall, this work provides a useful demonstration that different cross-area analysis methods result in different conclusions regarding asymmetric interactions between brain areas and suggests careful consideration of methods when analyzing such networks is critical. A deeper examination of why different analytical methods result in observed asymmetry or no asymmetry, analyses that specifically examine neural dynamics informative about details of the movement, or a biological investigation of the hypothesis provided by the model would provide greater clarity regarding the interaction between RFA and CFA.

Strengths:

The authors are rigorous in their experimental and analytical methods, carefully monitoring the impact of their perturbations with simultaneous recordings and providing valid controls for their analytical methods. They cite relevant previous literature that largely agrees with the current work, highlighting the continued ambiguity regarding the extent to which there exists an asymmetry in endogenous activity between RFA and CFA.

A strength of the paper is the evidence for asymmetry provided by optogenetic manipulation. They show that RFA inactivation causes a greater absolute difference in muscle activity than CFA interaction (deviations begin 25-50 ms after laser onset, Figure 1) and that RFA inactivation causes a relatively larger decrease in CFA firing rate than CFA inactivation causes in RFA (deviations begin <25ms after laser onset, Figure 3). The timescales of these changes provide solid evidence for an asymmetry in impact of inactivating RFA/CFA on the other region that could not be driven by differences in feedback from disrupted movement (which would appear with a ~50ms delay).

The authors also utilize a range of different analytical methods, showing an interesting difference between some population-based methods (PCA, DLAG) that observe asymmetry, and single neuron pair methods (granger causality, transfer entropy, and convergent cross mapping) that do not. Moreover, the modeling work presents an interesting potential cause of "hierarchy" or "asymmetry" between brain areas: local connectivity that impacts dependence on across-region input, rather than the amount of across-region input actually present.

Weaknesses:

There is no attempt to examine neural dynamics that are specifically relevant/informative about the details of the ongoing forelimb movement (e.g., kinematics, reach direction). Thus, it may be preemptive to claim that firing patterns alone do not reflect functional influence between RFA/CFA. For example, given evidence that the largest component of motor cortical activity doesn't reflect details of ongoing movement (reach direction or path; Kaufman, et al. PMID: 27761519) and that the analytical tools the authors use likely include this component (PCA, CCA), it may not be surprising that CFA and RFA do not show asymmetry if such asymmetry is related to control of movement details. An asymmetry may still exist in the components of neural activity that encode information about movement details, and thus it may be necessary to isolate and examine the interaction of behaviorally-relevant dynamics (e.g., Sani, et al. PMID: 33169030).

The idea that local circuit dynamics play a central role in determining the asymmetry between RFA and CFA is not supported by experimental data in this paper. The plausibility of this hypothesis is supported by the model but is not explored in any analyses of the experimental data collected. Further experimental investigation is needed to separate this hypothesis from other possibilities.

Comments on revisions:

The authors have improved the manuscript by reviewing several aspects of the text and the addition of supplemental materials. I believe these revisions have clarified some important aspects of the results.

Reviewer #3 (Public review):

Summary:

The authors demonstrated MK2i could enhance the therapeutic efficacy of MTAs. With the tumour xenograft and migration assay, the author suggested that the p38-MK2 pathway may serve as a promising therapeutic target in combination with MTAs in cancer treatment.

Strengths:

The authors provided a potential treatment for breast cancer.

Comments on revisions:

A xenograft experiment should be included to evaluate the synergistic effect of MK2i and vinblastine.

Reviewer #3 (Public review):

Hawes et al. combined behavioral, optical imaging, and activity manipulation techniques to investigate the role of striatal patch SPNs in locomotion regulation. Using Sepw1-Cre transgenic mice, they found that patch SPNs encode locomotion deceleration in a light-dark box procedure through optical imaging techniques. Moreover, genetic ablation of patch SPNs increased locomotion speed, while chemogenetic activation of these neurons decreased it. The authors concluded that a subtype of patch striatonigral neurons modulates locomotion speed based on external environmental cues. Below are some major concerns:

The study concludes that patch striatonigral neurons regulate locomotion speed. However, unless I missed something, very little evidence is presented to support the idea that it is specifically striatonigral neurons, rather than striatopallidal neurons, that mediate these effects. In fact, the optogenetic experiments shown in Fig. 6 suggest otherwise. What about the behavioral effects of optogenetic stimulation of striatonigral versus striatopallidal neuron somas in Sepw1-Cre mice?

In the abstract, the authors state that patch SPNs control speed without affecting valence. This claim seems to lack sufficient data to support it. Additionally, speed, velocity, and acceleration are very distinct qualities. It is necessary to clarify precisely what patch neurons encode and control in the current study.

One of the major results relies on chemogenetic manipulation (Figure 5). It would be helpful to demonstrate through slice electrophysiology that hM3Dq and hM4Di indeed cause changes in the activity of dorsal striatal SPNs, as intended by the DREADD system. This would support both the positive (Gq) and negative (Gi) findings, where no effects on behavior were observed.

Finally, could the behavioral effects observed in the current study, resulting from various manipulations of patch SPNs, be due to alterations in nigrostriatal dopamine release within the dorsal striatum?

Reviewer #3 (Public review):

Summary:

Understanding the mechanisms whereby animals restrict the timing of their reproduction according to day length is a critical challenge given that many of the most relevant species for agriculture are strongly photoperiodic. However, the principal animal models capable of detailed genetic analysis do not respond to photoperiod so this has inevitably limited progress in this field. The fish model medaka occupies a uniquely powerful position since it's reproduction is strictly restricted to long days and it also offers a wide range of genetic tools for exploring, in depth, various molecular and cellular control mechanisms.

For these reasons, this manuscript by Tagui and colleagues is particularly valuable. It uses the medaka to explore links bridging photoperiod, feeding behaviour and reproduction. The authors demonstrate that in female, but not male medaka, photoperiod-induced reproduction is associated with an increase in feeding, presumably explained by the high metabolic cost of producing eggs on a daily basis during the reproductive period. Using RNAseq analysis of the brain, they reveal that the expression of the neuropeptides agrp and npy that have been previously implicated in the regulation of feeding behaviour in mice, are upregulated in the medaka brain during exposure to long photoperiod conditions. Unlike the situation in mouse, these two neuropeptides are not coexpressed in medaka neurons and food deprivation in medaka led to increases in agrp but also a decrease in npy expression. Furthermore, the situation in fish may be more complicated than in mouse due to the presence of multiple gene paralogs for each neuropeptide. Exposure to long day conditions increases agrp1 expression in medaka as the result of increases in the number of neurons expressing this neuropeptide, while the increase in npyb levels results from increased levels of expression in the same population of cells. Using ovariectomized medaka and in situ hybridization assays, the authors reveal that the regulation of agrp1 involves estrogen acting via the estrogen receptor esr2a. Finally, a loss of agrp1 function mutant is generated where the female mutants fail to show the characteristic increase in feeding associated with long day enhanced reproduction as well as yielding reduced numbers of eggs during spawning.

Strengths:

This manuscript provides important foundational work for future investigations aiming to elucidate the coordination of photoperiod sensing, feeding activity and reproduction function. The authors have used a combination of approaches with a genetic model that is particularly well suited to studying photoperiodic dependent physiology and behaviour. The data are clear and the results are convincing and support the main conclusions drawn. The findings are relevant not only for understanding photopriodic responses but also provide more general insight into links between reproduction and feeding behaviour control.

The manuscript has been further strengthened by the inclusion of additional information according to my advice: The analysis of ovariectomized female fish and juvenille fish has now been reported in terms of their feeding behaviour and so provide a complete view of the position of this feeding regulatory mechanism in the context of reproduction status. Furthermore, the discussion section has been expanded to speculate on the functional significance of linking feeding behaviour control with reproductive function. Modifications made in order to address technical concerns of the other 2 reviewers have also significantly strengthened the presentation of this work.

Weaknesses:

These have now been addressed in the revised version.

Reviewer #3 (Public review):

Summary:

This study presents a valuable finding on the mechanism used by WTAP to modulate the IFN-β stimulation. It describes the phase transition of WTAP driven by IFN-β-induced dephosphorylation. The evidence supporting the claims of the authors is solid.

Strength:

The key finding is the revelation that WTAP undergoes phase separation during virus infection or IFN-β treatment. The authors conducted a series of precise experiments to uncover the mechanism behind WTAP phase separation and identified the regulatory role of 5 phosphorylation sites. They also succeeded in pinpointing the phosphatase involved.

Reviewer #3 (Public review):

I thank the authors for their extensive revision of this paper, and I found some elements greatly improved.<br /> In particular, the authors do embrace a somewhat more speculative tone in the current version, which I think is fitting for this work, as the data seem (to me) to be not fully conclusive. The data set collected here is clearly valuable and unique (and I would encourage the authors to make it publicly available!), however, my overall impression is that the specific analyses reported here might not fully

Despite the revised description of methods, results and figures, I still have trouble understanding many of the results and the authors conclusive interpretation of them. These are my main reservations:

(1) Regarding "individual prediction tendency" - thank you for adding clarifying methodological details and showing the data in a new Figure (#2). Honestly, however, I still can't say that I fully understand the result. For example, why is there also a significant response in the random condition as well? And how do you interpret the interesting time-course (with a peak ~200ms prior to the stimulus, and a reduction overtime from there?<br /> Also (I may have missed this, but..) what neural data was used to train the classifier and derive the "prediction tendency" index? Was it just the broadband neural response? Is there a way to know which sensors contributed to this metric (e.g., are they predominantly auditory? Frontal?)? And is there a way to establish the statistical significance of this metric (e.g., how good the decoder actually was in predicting behavioral sensitivity?). I don't see any statistics in the results section describing the individual prediction tendency.

(2) Regarding the TRF analysis - Thanks for clarifying the approach used to obtain 2-second long "segments" of speech tracking. This is an interesting approach, however I think quite new(?) , and for me it raises a whole new set of questions, as well as additional controls and data that I would have liked to see, to be convinced that results are significant. I will elaborate:

- Do I understand correctly that you segment the real and predicted neural response into 2-second long segments and then calculate the Pearsons' correlation between them to assess the goodness of the model? This is very unclear, since in the methods section you state only that "the same" analysis was performed as for the full data - but what exactly? Clearly, values will be very different when using such short segments. I feel that additional details are still required (and perhaps data shown) to fully understand the "semantic violation" analysis of TRFs.

- I would like to reiterate my previous comment regarding the use of permutation tests to verify the validity of TRF-based measures derived. This would be especially important when using new approaches (such as the segmentation used here). The authors argue that this is not needed since this was not done in their previously published study. However, this sounds a bit like "two wrongs make a right" argument... why not just do it, and let us know that this 2-second segmentation approach allows estimating reliable speech tracking?

- Following up on my previous comment that defining "clusters" as at least two neighboring channels (Figure 3) - the fact that this is a default in Fieldtrip is by no means sufficient justification!. This seems quite liberal to me, especially given the many comparisons performed. Here too, permutations can help to determine the necessary data-driven threshold for corrections. This is of course critical for interpreting the result shown in Figures 3E&G that are critical "take home messages" of the paper - i.e., that the prediction-index from the first part of the experiment is related to speech tracking in the second part of the experiment. To my eyes, this does not look extremely convincing, but perhaps the authors can show more conclusive data to support this (e.g., scatter plots of the betas across participant?).<br /> - A similar point can be made for the effect of semantic violations (though here the scalp-level result is somewhat more clustered). The authors point out that the semantic effect is a "replication" of their result reported in Schubert et al. 2023, but if I am not mistaken the results there were somewhat different (as was the manipulation). It would be nice to explicitly discuss the similarity/difference between these effects.

(3) Regarding the ocular-TRFs -

- Maybe this is just me, but I believe that effects that are robust should be clearly visible in the data, without the need for fancy "black-box" statistical models. In the case of the ocular TRFs, it is hard for me to see how these time-courses are not just noise (and, again, a permutation test would have helped to convince me..). The inconsistent results for horizontal and vertical eye-movements vis a vis the experimental conditions (single vs. multi-speaker conditions) don't help either, despite the authors argument that these are "independent" - but why should this be the case, especially if there is nothing really to look at in this task?<br /> - I remain with this scepticism for the mediation-portion of the analysis as well... But perhaps replications from other groups or making the data public will help shed further light on this in the future.

Minor<br /> - Thanks for adding information about the creation of semantic-violation stimuli. Since the violations and lexical-controls were taken from different audio recordings, it would have been nice to verify that differences between neural responses cannot be attributed to differences in articulations (e.g., by comparing their spectro-temporal properties).

Reviewer #3 (Public review):

Kobayashi et al identify MER21C as a common promoter of GPR1-AS/Liz in Euarchontoglires, which establishes a somatic DMR that controls ZFDB2 imprinting. In mice, MER21C appears to have diverged significantly from its primate counterparts and is no longer annotated as such.

The authors used high-quality cross-species RNA-seq data to characterise GPR1-AS-like transcripts, which included generating new data in five different species. The association between MER21C/B elements and the promoter of GPR1-AS in most species is clear and convincing. The expression pattern of MER21C/B elements overall further supports their role in enabling correct temporal expression of GPR1-AS during embryonic development.

In the revised version of the manuscript the authors provided additional support for the common evolutionary origin of the GPR1-AS/Liz promoter between primates and rodents. They also showed a more extensive concordance between the presence of GPR1-AS-like transcripts and ZDBF2 imprinting.

Altogether, these findings robustly support the conclusions of the paper, shedding light into the events underlying the evolution of imprinting at the ZDBF2 locus.

Reviewer #3 (Public review):

The study of Weber et al. provides a thorough investigation of the roles of four individual dopamine neurons for aversive associative learning in the Drosophila larva. They focus on the neurons of the DL-1 cluster which already have been shown to signal aversive teaching signals. But the authors go beyond the previous publications and test whether each of these dopamine neurons responds to salt or sugar, is necessary for learning about salt, bitter, or sugar, and is sufficient to induce a memory when optogenetically activated. In addition, previously published connectomic data is used to analyze the synaptic input to each of these dopamine neurons. The authors conclude that the aversive teaching signal induced by salt is distributed across the four DL-1 dopamine neurons, with two of them, DAN-f1 and DAN-g1, being particularly important. Overall, the experiments are well designed and performed, support the authors' conclusions, and deepen our understanding of the dopaminergic punishment system.

Strengths:

(1) This study provides, at least to my knowledge, the first in vivo imaging of larval dopamine neurons in response to tastants. Although the selection of tastants is limited, the results close an important gap in our understanding of the function of these neurons.

(2) The authors performed a large number of experiments to probe for the necessity of each individual dopamine neuron, as well as combinations of neurons, for associative learning. This includes two different training regimen (1 or 3 trials), three different tastants (salt, quinine and fructose) and two different effectors, one ablating the neuron, the other one acutely silencing it. This thorough work is highly commendable, and the results prove that it was worth it. The authors find that only one neuron, DAN-g1, is partially necessary for salt learning when acutely silenced, whereas a combination of two neurons, DAN-f1 and DAN-g1, are necessary for salt learning when either being ablated or silenced.

(3) In addition, the authors probe whether any of the DL-1 neurons is sufficient for inducing an aversive memory. They found this to be the case for two of the neurons, largely confirming previous results obtained by a different learning paradigm, parameters and effector.

(4) This study also takes into account connectomic data to analyze the sensory input that each of the dopamine neurons receives. This analysis provides a welcome addition to previous studies and helps to gain a more complete understanding. The authors find large differences in inputs that each neuron receives, and little overlap in input that the dopamine neurons of the "aversive" DL-1 cluster and the "appetitive" pPAM cluster seem to receive.

(5) Finally, the authors try to link all the gathered information in order to describe an updated working model of how aversive teaching signals are carried by dopamine neurons to the larva's memory center. This includes important comparisons both between two different aversive stimuli (salt and nociception) and between the larval and adult stages.

Reviewer #3 (Public review):

Summary:

In this work, Yamada, Brandani, and Takada have developed a mesoscopic model of the interacting proteins in the postsynaptic density. They have performed simulations, based on this model and using the software ReaDDy, to study the phase separation in this system in 2D (on the membrane) and 3D (in the bulk). They have carefully investigated the reasons behind different morphologies observed in each case, and have looked at differences in valency, specific/non-specific interactions, and interfacial tension.

Strengths:

The simulation model is developed very carefully, with strong reliance on binding valency and geometry, experimentally measured affinities, and physical considerations like the hydrodynamic radii. The presented analyses are also thorough, and great effort has been put into investigating different scenarios that might explain the observed effects.

Weaknesses:

The biggest weakness of the study, in my opinion, has to do with a lack of more in-depth physical insight about phase separation. For example, the authors express surprise about similar interactions between components resulting in different phase separation in 2D and 3D. This is not surprising at all, as in 3D, higher coordination numbers and more available volume translate to lower free energy, which easily explains phase separation. The role of entropy is also significantly missing from the analyses. When interaction strengths are small, entropic effects play major roles.

In the introduction, the authors present an oversimplified view of associative and segregative phase transitions based on the attractive and repulsive interactions, and I'm afraid that this view, in which all the observed morphologies should have clear pairwise enthalpic explanations, diffuses throughout the analysis. Meanwhile, I believe the authors correctly identify some relevant effects, where they consider specific/non-specific interactions, or when they investigate the reduced valency of CaMKII in the 2D system.

Also, I sense some haste in comparing the findings with experimental observations. For example, the authors mention that "For the current four component PSD system, the product of concentrations of each molecule in the dilute phase is in good agreement with that of the experimental concentrations (Table S2)." But the data used here is the dilute phase, which is the remnant of a system prepared at very high concentrations and allowed to phase separate. The errors reported in Table S2 already cast doubt on this comparison. Or while the 2D system is prepared via confining the particles to the vicinity of the membrane, the different diffusive behavior in the membrane, in contrast to the bulk (i.e., the Saffman-Delbrück model), is not considered. This would thus make it difficult to interpret the results of a coupled 2D/3D system and compare them to the actual system.

Reviewer #3 (Public review):

Summary:

A very thorough technical report of a new standalone, open-source software for microscopy image processing and analysis (MorphoNet 2.0), with a particular emphasis on automated segmentation and its curation to obtain accurate results even with very complex 3D stacks, including timelapse experiments.

Strengths:

The authors did a good job of explaining the advantages of MorphoNet 2.0, as compared to its previous web-based version and to other software with similar capabilities. What I particularly found more useful to actually envisage these claimed advantages is the five examples used to illustrate the power of the software (based on a combination of Python scripting and the 3D game engine Unity). These examples, from published research, are very varied in both types of information and image quality, and all have their complexities, making them inherently difficult to segment. I strongly recommend the readers to carefully watch the accompanying videos, which show (although not thoroughly) how the software is actually used in these examples.

Weaknesses:

Being a technical article, the only possible comments are on how methods are presented, which is generally adequate, as mentioned above. In this regard, and in spite of the presented examples (chosen by the authors, who clearly gave them a deep thought before showing them), the only way in which the presented software will prove valuable is through its use by as many researchers as possible. This is not a weakness per se, of course, but just what is usual in this sort of report. Hence, I encourage readers to download the software and give it time to test it on their own data (which I will also do myself).

In conclusion, I believe that this report is fundamental because it will be the major way of initially promoting the use of MorphoNet 2.0 by the objective public. The software itself holds the promise of being very impactful for the microscopists' community.

Reviewer #3 (Public review):

Summary:

The authors aimed to improve cryo-TEM workflows for plant cells. The authors present details on high-pressure-freezing protocols to vitrify, ion-mill, and image certain plant cell types.

Strengths:

Clear step-by-step outline on how to preserve and image cryo samples derived from plants.

Weaknesses:

A general current weakness of cryo-TEM is the problem of vitrifying cells that are embedded in tissues. The vast majority of cells in the plant body are currently not accessible to this technology. This is not a weakness of this specific manuscript but a general problem.

The manuscript is well organized and well written, and the discussion covers practically all questions I had while reading the results section. I only have a few comments, all of which I consider minor.

Reviewer #3 (Public review):

Summary

This paper investigates how disinformation affects reward learning processes in the context of a two-armed bandit task, where feedback is provided by agents with varying reliability (with lying probability explicitly instructed). They find that people learn more from credible sources, but also deviate systematically from optimal Bayesian learning: They learned from uninformative random feedback, learned more from positive feedback, and updated too quickly from fully credible feedback (especially following low-credibility feedback). Overall, this study highlights how misinformation could distort basic reward learning processes, without appeal to higher-order social constructs like identity.

Strengths

(1) The experimental design is simple and well-controlled; in particular, it isolates basic learning processes by abstracting away from social context.

(2) Modeling and statistics meet or exceed the standards of rigor.

(3) Limitations are acknowledged where appropriate, especially those regarding external validity.

(4) The comparison model, Bayes with biased credibility estimates, is strong; deviations are much more compelling than e.g., a purely optimal model.

(5) The conclusions are interesting, in particular the finding that positivity bias is stronger when learning from less reliable feedback (although I am somewhat uncertain about the validity of this conclusion)

Weaknesses

(1) Absolute or relative positivity bias?

In my view, the biggest weakness in the paper is that the conclusion of greater positivity bias for lower credible feedback (Figure 5) hinges on the specific way in which positivity bias is defined. Specifically, we only see the effect when normalizing the difference in sensitivity to positive vs. negative feedback by the sum. I appreciate that the authors present both and add the caveat whenever they mention the conclusion (with the crucial exception of the abstract). However, what we really need here is an argument that the relative definition is the *right* way to define asymmetry....

Unfortunately, my intuition is that the absolute difference is a better measure. I understand that the relative version is common in the RL literature; however previous studies have used standard TD models, whereas the current model updates based on the raw reward. The role of the CA parameter is thus importantly different from a traditional learning rate - in particular, it's more like a logistic regression coefficient (as described below) because it scales the feedback but *not* the decay. Under this interpretation, a difference in positivity bias across credibility conditions corresponds to a three-way interaction between the exponentially weighted sum of previous feedback of a given type (e.g., positive from the 75% credible agent), feedback positivity, and condition (dummy coded). This interaction corresponds to the non-normalized, absolute difference.

Importantly, I'm not terribly confident in this argument, but it does suggest that we need a compelling argument for the relative definition.

(2) Positivity bias or perseveration?

A key challenge in interpreting many of the results is dissociating perseveration from other learning biases. In particular, a positivity bias (Figure 5) and perseveration will both predict a stronger correlation between positive feedback and future choice. Crucially, the authors do include a perseveration term, so one would hope that perseveration effects have been controlled for and that the CA parameters reflect true positivity biases. However, with finite data, we cannot be sure that the variance will be correctly allocated to each parameter (c.f. collinearity in regressions). The fact that CA- is fit to be negative for many participants (a pattern shown more strongly in the discovery study) is suggestive that this might be happening. A priori, the idea that you would ever increase your value estimate after negative feedback is highly implausible, which suggests that the parameter might be capturing variance besides that it is intended to capture.

The best way to resolve this uncertainty would involve running a new study in which feedback was sometimes provided in the absence of a choice - this would isolate positivity bias. Short of that, perhaps one could fit a version of the Bayesian model that also includes perseveration. If the authors can show that this model cannot capture the pattern in Figure 5, that would be fairly convincing.

(3) Veracity detection or positivity bias?

The "True feedback elicits greater learning" effect (Figure 6) may be simply a re-description of the positivity bias shown in Figure 5. This figure shows that people have higher CA for trials where the feedback was in fact accurate. But, assuming that people tend to choose more rewarding options, true-feedback cases will tend to also be positive-feedback cases. Accordingly, a positivity bias would yield this effect, even if people are not at all sensitive to trial-level feedback veracity. Of course, the reverse logic also applies, such that the "positivity bias" could actually reflect discounting of feedback that is less likely to be true. This idea has been proposed before as an explanation for confirmation bias (see Pilgrim et al, 2024 https://doi.org/10.1016/j.cognition.2023.105693 and much previous work cited therein). The authors should discuss the ambiguity between the "positivity bias" and "true feedback" effects within the context of this literature....

The authors get close to this in the discussion, but they characterize their results as differing from the predictions of rational models, the opposite of my intuition. They write:

Alternative "informational" (motivation-independent) accounts of positivity and confirmation bias predict a contrasting trend (i.e., reduced bias in low- and medium credibility conditions) because in these contexts it is more ambiguous whether feedback confirms one's choice or outcome expectations, as compared to a full-credibility condition.

I don't follow the reasoning here at all. It seems to me that the possibility for bias will increase with ambiguity (or perhaps will be maximal at intermediate levels). In the extreme case, when feedback is fully reliable, it is impossible to rationally discount it (illustrated in Figure 6A). The authors should clarify their argument or revise their conclusion here.

(4) Disinformation or less information?

Zooming out, from a computational/functional perspective, the reliability of feedback is very similar to reward stochasticity (the difference is that reward stochasticity decreases the importance/value of learning in addition to its difficulty). I imagine that many of the effects reported here would be reproduced in that setting. To my surprise, I couldn't quickly find a study asking that precise question, but if the authors know of such work, it would be very useful to draw comparisons. To put a finer point on it, this study does not isolate which (if any) of these effects are specific to *disinformation*, rather than simply _less information._ I don't think the authors need to rigorously address this in the current study, but it would be a helpful discussion point.

(5) Over-reliance on analyzing model parameters

Most of the results rely on interpreting model parameters, specifically, the "credit assignment" (CA) parameter. Exacerbating this, many key conclusions rest on a comparison of the CA parameters fit to human data vs. those fit to simulations from a Bayesian model. I've never seen anything like this, and the authors don't justify or even motivate this analysis choice. As a general rule, analyses of model parameters are less convincing than behavioral results because they inevitably depend on arbitrary modeling assumptions that cannot be fully supported. I imagine that most or even all of the results presented here would have behavioral analogues. The paper would benefit greatly from the inclusion of such results. It would also be helpful to provide a description of the model in the main text that makes it very clear what exactly the CA parameter is capturing (see next point).

(6) RL or regression?

I was initially very confused by the "RL" model because it doesn't update based on the TD error. Consequently, the "Q values" can go beyond the range of possible reward (SI Figure 5). These values are therefore *not* Q values, which are defined as expectations of future reward ("action values"). Instead, they reflect choice propensities, which are sometimes notated $h$ in the RL literature. This misuse of notation is unfortunately quite common in psychology, so I won't ask the authors to change the variable. However, they should clarify when introducing the model that the Q values are not action values in the technical sense. If there is precedent for this update rule, it should be cited.

Although the change is subtle, it suggests a very different interpretation of the model.

Specifically, I think the "RL model" is better understood as a sophisticated logistic regression, rather than a model of value learning. Ignoring the decay term, the CA term is simply the change in log odds of repeating the just-taken action in future trials (the change is negated for negative feedback). The PERS term is the same, but ignoring feedback. The decay captures that the effect of each trial on future choices diminishes with time. Importantly, however, we can re-parameterize the model such that the choice at each trial is a logistic regression where the independent variables are an exponentially decaying sum of feedback of each type (e.g., positive-cred50, positive-cred75, ... negative-cred100). The CA parameters are simply coefficients in this logistic regression.

Critically, this is not meant to "deflate" the model. Instead, it clarifies that the CA parameter is actually not such an assumption-laden model estimate. It is really quite similar to a regression coefficient, something that is usually considered "model agnostic". It also recasts the non-standard "cross-fitting" approach as a very standard comparison of regression coefficients for model simulations vs. human data. Finally, using different CA parameters for true vs false feedback is no longer a strange and implausible model assumption; it's just another (perfectly valid) regression. This may be a personal thing, but after adopting this view, I found all the results much easier to understand.

Reviewer #3 (Public review):

(1) The authors described "the excitatory glutamatergic SFL axons and cholinergic SAM inputs". However, the evidence of their transmitter specificity has not been provided. Compelling evidence was neither provided nor discussed in the context of the study.

(2) Specific interference for inhibitory or excitatory synapses based on EM or other studies must be detailed and elaborated

(3) Different local microcircuits (submodules) referred to in the text should be better described and more specifically defined.

(4) I would recommend incorporating a more detailed description of synapses and, especially, synaptic vesicles, clarifying their diversity and similarity across cell subtypes. Are there any differences between cholinergic and glutamatergic synaptic vesicles, postsynaptic densities, or other features...? It would be good, if possible, to explicitly clarify: how many vesicles per different types of synapses? How many synapses per neuron of different types? How many inputs and outputs per a given neuron?

(5) Authors discuss retrograde messengers like NO? Is there any identifiable morphological type of neuron(s) or synapses that might be nitrergic?

(6) It would be good to provide separate illustrations showing the detailed organization of any glial cell or different types of glial cells they identified in this study. Authors mainly discuss glial processes but refer to "recognized glial types, such as radial glia and astrocyte-like glia" without specific illustrations, which can be deciphered from their EM data. What are vesicular organizations within different types of glial cells?

(7) The authors also discuss "supervising inputs of inhibitory (pain) and neuromodulatory (supervising) signals", without any details. It would be important to provide these details in the discussion. Specifically, I suggest incorporating comments about differences/similarities of transmitters and morphology between pain and modulatory pathways/signaling/circuits.

for - definition - coniunctio (3 types) - Carl Jung

Reviewer #3 (Public review):

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

The new mouse lines generated in this study will enhance the precision of genetic manipulation in distinct cell types and greatly facilitate future work in numerous laboratories. The authors expertly eradicated weaknesses from initial submissions. Remaining open questions regarding potential toxicity of expressing multiple recombinases and fluorescence reports were convincingly answered.

Reviewer #3 (Public review):

Protein Phosphatase 1 (PP1), a vital member of the PPP superfamily, drives most cellular serine/threonine dephosphorylation. Despite PP1's low intrinsic sequence preference, its substrate specificity is finely tuned by over 200 PP1-interacting proteins (PIPs), which employ short linear motifs (SLIMs) to bind specific PP1 surface regions. By targeting PP1 to cellular sites, modifying substrate grooves, or altering surface electrostatics, PIPs influence substrate specificity. Although many PIP-PP1-substrate interactions remain uncharacterized, the Phactr family of PIPs uniquely imposes sequence specificity at dephosphorylation sites through a conserved "RVxF-ΦΦ-R-W" motif. In Phactr1-PP1, this motif forms a hydrophobic pocket that favors substrates with hydrophobic residues at +4/+5 in acidic contexts (the "LLD motif"), a specificity that endures even in PP1-Phactr1 fusions. Neurabin/Spinophilin remodel PP1's hydrophobic groove in distinct ways, creating unique holoenzyme surfaces, though the impact on substrate specificity remains underexplored. This study investigates Neurabin/Spinophilin specificity via PDZ domain-driven interactions, showing that Neurabin/PP1 specificity is governed more by PDZ domain interactions than by substrate sequence, unlike Phactr1/PP1.

A significant strength of this work is the use of PP1-PIP fusion proteins to effectively model intact PP1•PIP holoenzymes by replicating the interactions that remodel the PP1 interface and confer site-specific substrate specificity. When combined with proteomic analyses to assess phospho-site depletion in mammalian cells, these fusions offer critical insights into holoenzyme specificity, revealing new candidate substrates for Neurabin and Spinophilin. The studies present compelling evidence that the PDZ domain of PP1-Neurabin directs its specificity, with the remodeled PP1 hydrophobic groove interactions having minimal impact. This mechanism is supported by structural analysis of the PP1-4E-BP1 substrate fusion bound to a Neurabin construct, highlighting the 4E-BP1/PDZ interaction. This work delivers crucial insights into PP1-PIP holoenzyme function, combining biochemical, proteomic, and structural approaches. It validates the PP1-PIP fusion protein model as a powerful tool, suggesting it may extend to studying additional holoenzymes. While an extremely useful model, it must be considered unlikely the PP1-PIP fusions fully recapitulate the specificity and regulation of the holoenzyme.

Reviewer #3 (Public review):

Summary:

In this manuscript, the authors discuss epithelial tissue fluidity from a theoretical perspective. They focus on the description of topological transitions whereby cells change neighbors (T1 transitions). They explain how such transitions can be described by following the fate of hexatic defects. They first focus on a single T1 transition and the surrounding cells using a hydrodynamic model of active hexatics. They show that successful T1 intercalations, which promote tissue fluidity, require a sufficiently large extensile hexatic activity in the neighborhood of the cells attempting a T1 transition. If such activity is contractile or not sufficiently extensile, the T1 is reversed, hexatic defects annihilate, and the epithelial network configuration is unchanged. They then describe a large epithelium, using a phase field model to describe cells. They show a correlation between T1 events and hexatic defects unbinding, and identify two populations of T1 cells: one performing T1 cycles (failed T1), and not contributing to tissue migration, and one performing T1 intercalation (successful T1) and leading to the collective cell migration.

Strengths:

The manuscript is scientifically sound, and the variety of numerical and analytical tools they use is impressive. The approach and results are very interesting and highlight the relevance of hexatic order parameters and their defects in describing tissue dynamics.

Weaknesses:

(1) Goal and message of the paper.

a) In my opinion, the article is mainly theoretical and should be presented as such. For instance, their conclusions and the consequences of their analysis in terms of biology are not extremely convincing, although they would be sufficient for a theory paper oriented to physicists or biophysicists. The choice of journal and potential readership should be considered, and I am wondering whether the paper structure should be re-organized, in order to have side-by-side the methods and the results, for instance (see also below).

b) Currently, the two main results sections are somewhat disconnected, because they use different numerical models, and because the second section only marginally uses the results from the first section to identify/distinguish T1 (see also below).

(2) Quite surprisingly, the authors use a cell-based model to describe the macroscopic tissue-scale behavior, and a hydrodynamic model to describe the cell-based events. In particular, their hydrodynamic description (the active hexatic model) is supposed to be a coarse-grained description, valid to capture the mesoscopic physics, and yet, they use it to describe cell-scale events (T1 transitions). For instance, what is the meaning of the velocity field they are discussing in Figure 2? This makes me question the validity of the results of their first part.

(3) The quality of the numerical results presented in the second part (phase field model) could be improved.

a) In terms of analysis of the defects. It seems that they have all the tools to compare their cell-resolved simulations and their predictions about how a T1 event translates into defects unbinding. However, their analysis in Figure 3e is relatively minimal: it shows a correlation between T1 cells and defects. But it says nothing about the structure and evolution of the defects, which, according to their first section, should be quite precise. I believe it should be possible to identify and quantify more precisely the unbinding or annihilation of the defects and hence to characterize more precisely the T1 events.

b) In terms of clarity of the presentation. For instance, in Figure 3f, they plot the mean-square displacement as a function of a defect density. I thought that MSD was a time-dependent quantity: they must therefore consider MSD at a given time, or averaged over time (in that case, what they are showing is rather an effective diffusivity). They should, in any case, be explicit about what their definition of this quantity is.

c) In terms of statistics. For instance, Figure 3g is used to study the role of rotational diffusion on the average time between T1s. The error bars in this figure are huge and make their claims hardly supported. It is, for instance, hard to believe that the dynamics of T1 cycles are unaffected by D_r. In the limit where D_r vanishes, for instance, there should be no T1 and the period of a T1 cycle should diverge, which is not observed. Their claim of a "monotonic decay" of the average time between intercalations is also not fully supported given their statistics.

Reviewer #3 (Public review):

Summary:

In this manuscript, "Neocortical Layer-5 tLTD Relies on Non-Ionotropic Presynaptic NMDA Receptor Signaling", Thomazeau et al. seek to determine the role of presynaptic NMDA receptors and the mechanism by which they mediate expression of frequency-independent timing-dependent long-term depression (tLTD) between layer-5 (L5) pyramidal cells (PCs) in the developing mouse visual cortex. By utilizing sophisticated methods, including sparse Cre-dependent deletion of GluN1 subunit via neonatal iCre-encoding viral injection, in vitro quadruple patch clamp recordings, and pharmacological interventions, the authors elegantly show that L5 PC->PC tLTD is (1) dependent on presynaptic NMDA receptors, (2) mediated by non-ionotropic NMDA receptor signaling, and (3) is reliant on JNK2/Syntaxin-1a (STX1a) interaction (but not RIM1αβ) in the presynaptic neuron. The study elegantly and pointedly addresses a long-standing conundrum regarding the lack of frequency dependence of tLTD.

Strengths:

The authors did a commendable job presenting a very polished piece of work with high-quality data that this Reviewer feels enthusiastic about. The manuscript has several notable strengths. Firstly, the methodological approach used in the study is highly sophisticated and technically challenging and successfully produced high-quality data that were easily accessible to a broader audience. Secondly, the pharmacological interventions used in the study targeted specific players and their mechanistic roles, unveiling the mechanism in question step-by-step. Lastly, the manuscript is written in a well-organized manner that is easy to follow. Overall, the study provides a series of compelling evidence that leads to a clear illustration of mechanistic understanding.

I have a couple of small items below, which the authors can address in a minor revision if they so wish.

Minor comments:

(1) For the broad readership, a brief description of JNK2-mediated signaling cascade underlying tLTD, including its intersection with CB1 receptor signaling may be desired.

(2) The authors used juvenile mice, P11 to P18 of age. It is a typical age range used for plasticity experiments, but it is also true that this age range spans before and after eye-opening in mice (~P13) and is a few days before the onset of the classical critical period for ocular dominance plasticity in the visual cortex. Given the mechanistic novelty reported in the study, can authors comment on whether this signaling pathway may be age-dependent?

Reviewer #3 (Public review):

Summary:

The authors set out to determine how SUMO2 impairs endothelial function through direct modification of the protein p66Shc. p66Shc is known to promote reactive oxygen species production, and here the authors demonstrate that SUMO2 modifies p66Shc at lysine-81, resulting in increased phosphorylation, mitochondrial translocation. These are prosed to mediate the detrimental effects of SUMO2 in a mouse model of hyperlipidemia.

Strengths:

A major strength of this work is the multi-pronged approach combining biochemical assays, proteomic analyses, and a genetically modified mouse model expressing a SUMOylation resistant mutant of p66Shc. These experiments comprehensively illustrate that lysine-81 SUMOylation of p66Shc is necessary for the observed endothelial dysfunction in hyperlipidemic conditions.

Weaknesses:

One notable weakness is that the link between the observed cellular changes and the ultimate in vivo phenotype remains only partially explored. While the authors successfully show that p66ShcK81R knockin mice are protected from endothelial dysfunction in a hyperlipidemic context, additional experiments characterizing the broader tissue-specific roles, or examining further endothelial assays in vivo, would strengthen the mechanistic conclusions. It would also be beneficial to see more direct evaluations of p66Shc subcellular localization in the protective knockin mice to complement the proteomic findings.

Despite these gaps, the data broadly support the authors' main conclusions. The authors lay out a plausible mechanistic pathway for how hyperlipidemia and increased global SUMOylation can converge on the oxidative stress pathway to provoke vascular dysfunction.

The likely impact of this work on the field is noteworthy. Beyond clarifying how a single post-translational modification event can influence the pathophysiology of endothelial cells, the study provides a model for investigating broader roles of SUMO2 in other cardiovascular conditions and highlights the importance of identifying additional SUMOylation sites and their downstream impact.

In conclusion, by demonstrating the direct SUMOylation of p66Shc at lysine-81 and linking that modification to endothelial dysfunction in a hyperlipidemic mouse model, this paper offers valuable insights into how broadly acting post-translational modifiers can evoke specific pathological effects.

Reviewer #3 (Public review):

Summary:

This paper described a new tool called "Image Correlation Spectroscopy; ICS) to detect clustering fluorescence signals such as foci in the nucleus (or any other cellular structures). The authors compared ICS DA (degree of aggregation) data with Imaris Spots data (and ImageJ Find Maxima data) and found a comparable result between the two analyses and that the ICS sometimes produced a better quantification than the Imaris software. Moreover, the authors extended the application of ICS to detect cell-cycle stages by analyzing the DAPI image of cells. This is a useful tool without the subjective bias of researchers and provides novel quantitative values in cell biology.

Strengths:

The authors developed a new tool to detect and quantify the aggregates of immuno-fluorescent signals, which is a center of modern cell biology, such as the fields of DNA damage responses (DDR), including DNA repair. This new method could detect the "invisible" signal in cells without pre-extraction, which could prevent the effect of extracted materials on the pre-assembled ensembles, a target for the detection. This would be an alternative method for the quantification of fluorescent signals relative to conventional methods.

Comments on revisions:

The authors addressed previous comments properly.

Reviewer #3 (Public review):

Summary:

The study explores the extent to which the biomineralization process in the calcitic sponge Sycon ciliatum resembles aragonitic skeleton formation in stony corals. To investigate this, the authors performed transcriptomic, genomic, and proteomic analyses on S. ciliatum and examined the expression patterns of biomineralization-related genes using in situ hybridization. Among the 829 differentially expressed genes identified in sponge regions associated with spicule formation, the authors focused on calcarin genes, which encode matrix proteins analogous to coral galaxins. The expression patterns of calcarins were found to be diverse but specific to particular spicule types. Notably, these patterns resemble those of galaxins in stony corals. Moreover, the genomic organization of calcarine genes in S. ciliatum closely mirrors that of galaxin genes in corals, suggesting a case of parallel evolution in carbonate biomineralization between calcitic sponges and aragonitic corals.

Strengths:

The manuscript is well written, and the figures are of high quality. The study design and methodologies are clearly described and well-suited to addressing the central research question. Particularly noteworthy is the authors´ integration of various omics approaches with molecular and cell biology techniques. Their results support the intriguing conclusion that there is a case of parallel evolution in skeleton-building gene sets between calcitic sponges and aragonitic corals. The conclusions are well supported by the data and analyses presented.

Weaknesses:

The manuscript is strong, and I have not identified any significant weaknesses in its current form.

Reviewer #3 (Public review):

Summary:

Drosophila neuroblasts (NBs) serve as a well-established model for studying neural stem cell biology. The intrinsic genetic programs that control their mitotic potential throughout development have been described in remarkable detail, highlighting a series of sequentially expressed transcription factors and RNA-binding proteins that together constitute the temporal patterning system.

However, the mechanisms that limit the number of NB divisions remain largely unknown in a specific subset of NBs known as mushroom body neuroblasts (MB NBs). Unlike other NBs, which terminate proliferation before or shortly after the onset of metamorphosis, MB NBs continue dividing until the end of metamorphosis, ceasing only just before adulthood.<br /> In this study, the authors identify the transcription factor Krüppel (Kr), a member of the conserved Krüppel-like family, as temporally regulated in MB NBs. They demonstrate that Kr knockdown during pupal stages maintains expression of the RNA-binding protein Imp and results in prolonged MB NB proliferation into adulthood. Their data suggest that Kr contributes to the timely silencing of Imp during metamorphosis. The authors further identify Kr-h1, a related transcription factor, as a potential antagonist. While Kr-h1 appears dispensable for the timely termination of MB NBs under normal conditions, its overexpression leads to their continued proliferation and tumor-like expansion in adults.

This work provides the first evidence for a transcription factor-driven temporal regulation mechanism in MB NBs, offering new insight into the control of neural stem cell self-renewal. Given the evolutionary conservation of Krüppel-like factors, this study may have broader implications for the neural stem cell field.

Strengths:

(1) The study possibly identifies a new series of temporal transcription factors that are specific for mushroom body neuroblasts.

(2) The mechanism could be conserved in vertebrates.

Weaknesses:

Some proposed regulatory interactions, particularly between Kr, Kr-h1, and other temporal factors like Imp, Chinmo, and E93, have not been thoroughly investigated, which weakens the support for the proposed model. Additional experimental validation is needed to confirm these relationships and strengthen the mechanistic framework.

Reviewer #3 (Public review):

Summary:

The response to lysosomal damage is a fast-moving and timely field. Besides repair and degradation pathways, increasing interest has been focusing on damaged-induced signaling. The authors conducted both transcriptomics and proteomics to characterize the cellular response to lysosomal damage. They identify a signaling pathway leading to activation of NFkappaB. Based on this and supported by Western blot and microscopy data, the authors nicely show that TAB2/3 and TAK1 are activated at damaged lysosomes and kick off the pathway to alter gene expression, which induces cytokines and protect from cell death. TAB2/3 activation is proposed to occur through K63 ubiquitin chain formation. Generally, this is a careful and well conducted study that nicely delineates the pathway under lysosomal stress. The "omics" data serves as a valuable resource for the field. More work should be invested into how TAB2/3 are activated at the damaged lysosomes, also to increase novelty in light of previous reports.

Strengths:

Generally, this is a careful and well-conducted study that nicely delineates the pathway under lysosomal stress. The "omics" data serves as a valuable resource for the field.

Weaknesses:

More work should be invested into how TAB2/3 are activated at the damaged lysosomes, also to increase novelty in light of previous reports. Moreover, different damage types should be tested to probe relevance for different pathophysiological conditions.

Suggestions:

(1) A recent paper claims that NFkappaB is activated by Otulin/M1 chains upon lysosome damage through TBK1 (PMID: 39744815). In contrast, Endo et al. nicely show that ubiquitylation is needed (shown by TAK-243) for NFkB activation but only have correlative data to link it specifically to K63 chains. On page 15, line 11, the authors even argue a "potential" involvement of K63. This point should be better dealt with. Can the authors specifically block K63 formation? K63R overexpression or swapping would be one way. Is the K63 ligase ITCH involved (PMID: 38503285) or any other NEDD4-like ligase? This could be compared to LUBAC inhibition. Also, the point needs to be dealt with more controversially in the discussion as these are alternative claims (M1 vs K63, TAB vs TBK1).

(2) It would be interesting to know what the trigger is that induces the pathway. Lipid perturbation by LLOMe is a good model, but does activation also occur with GPN (osmotic swelling) or lipid peroxidation (oxidative stress) that may be more broadly relevant in a pathophysiological way? Moreover, what damage threshold is needed? Does loss of protons suffice? Can activation be induced with a Ca2+ agonist in the absence of damage?

(3) The authors nicely define JNK and p38 activation. This should be emphasized more, possibly also in the abstract, as it may contribute to the claim of increased survival fitness.

Reviewer #3 (Public review):

Summary:

The authors aimed to develop Channelrhodopsins (ChRs), light-gated ion channels, with high potency and blue action spectra for use in multicolor (multiplex) optogenetics applications. To achieve this, they performed a bioinformatics analysis to identify ChR homologues in several protist species, focusing on ChRs from ancyromonads, which exhibited the highest photocurrents and the most blue-shifted action spectra among the tested candidates. Within the ancyromonad clade, the authors identified two new anion-conducting ChRs and one cation-conducting ChR. These were characterized in detail using a combination of manual and automated patch-clamp electrophysiology, absorption spectroscopy, and flash photolysis. The authors also explored sequence features that may explain the blue-shifted action spectra and differences in ion selectivity among closely related ChRs.

Strengths:

A key strength of this study is the high-quality experimental data, which were obtained using well-established techniques such as manual patch-clamp and absorption spectroscopy, complemented by modern automated patch-clamp approaches. These data convincingly support most of the claims. The newly characterized ChRs expand the optogenetics toolkit and will be of significant interest to researchers working with microbial rhodopsins, those developing new optogenetic tools, as well as neuro- and cardioscientists employing optogenetic methods.

Weaknesses:

This study does not exhibit major methodological weaknesses. The primary limitation of the study is that it includes only a limited number of comparisons to known ChRs, which makes it difficult to assess whether these newly discovered tools offer significant advantages over currently available options. Additionally, although the study aims to present ChRs suitable for multiplex optogenetics, the new ChRs were not tested in combination with other tools. A key requirement for multiplexed applications is not just spectral separation of the blue-shifted ChR from the red-shifted tool of interest but also sufficient sensitivity and potency under low blue-light conditions to avoid cross-activation of the respective red-shifted tool. Future work directly comparing these new ChRs with existing tools in optogenetic applications and further evaluating their multiplexing potential would help clarify their impact.

Reviewer #3 (Public review):

Summary:

Lmx1a is an orthologue of apterous in flies, which is important for dorsal-ventral border formation in the wing disc. Previously, this research group has described the importance of the chicken Lmx1b in establishing the boundary between sensory and non-sensory domains in the chicken inner ear. Here, the authors described a series of cellular changes during border formation in the chicken inner ear, including alignment of cells at the apical border and concomitant constriction basally. The authors extended these observations to the mouse inner ear and showed that these morphological changes occurred at the border of Lmx1a positive and negative regions, and these changes failed to develop in Lmx1a mutants. Furthermore, the authors demonstrated that the ROCK-dependent actomyosin contractility is important for this border formation and blocking ROCK function affected epithelial basal constriction and border formation in both in vitro and in vivo systems.

Strengths:

The morphological changes described during border formation in the developing inner ear are interesting. Linking these changes to the function of Lmx1a and ROCK dependent actomyosin contractile function are provocative.

Weaknesses:

There are several outstanding issues that need to be clarified before one could pin the morphological changes observed being causal to border formation and that Lmx1a and ROCK are involved.

Reviewer #3 (Public review):

Summary:

This is a lucidly written manuscript describing the use of transition-metal FRET to assess distance changes during functional conformational changes in a CNG channel. The experiments were performed on an isolated C-terminal nucleotide binding domain (CNBD) and on a purified full-length channel, with FRET partners placed at two positions in the CNBD.

Strengths:

The data and quantitative analysis are exemplary, and they provide a roadmap for use of this powerful approach in other proteins.

Weaknesses/Comments:

A ~3x lower Kd for nucleotide is seen for the detergent-solubilized full-length channel, compared to electrophysiological experiments. This is worth a comment in the Discussion, particularly in the context of the effect of the pore domain on the CNBD energetics.

Reviewer #3 (Public review):

Summary:

The authors describe important new biochemical elements in the synthesis of a class of critical developmental signaling molecules, BMP4. They also present a highly detailed description of developmental anomalies in mice bearing known human mutations at these specific elements.

Strengths:

This paper presents exceptionally detailed descriptions of pathologies occurring in BMP4 mutant mice. Novel findings are shown regarding the interaction of propeptide phosphorylation and convertase cleavage, both of which will move the field forward. Lastly, a provocative hypothesis regarding furin access to cleavage sites is presented, supported by Alphafold predictions.

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Reviewer #3 (Public review):

Summary:

The manuscript by Chatterjee et al., examines the role of the mirror locus in patterning butterfly wings. The authors examine the pattern of mirror expression in the common buckeye butterfly, Junonia coenia and then employ CRISPR mutagenesis to generate mosaic butterflies carrying clones of mirror mutant cells. They find that mirror is expressed in a well-defined posterior sector of final-instar wing discs from both hindwings and forewings and that CRISPR-injected larvae display a loss of adult wing structures presumably derived from the mirror expressing region of hindwing primordium (the case for forewings is a bit less clear since the mirror domain is narrower than in the hindwing, but there also do seem to be some anomalies in posterior regions of forewings in adults derived from CRISPR injected larvae). The authors conclude that wings of these butterflies have at least three different fundamental wing compartments, the mirror domain, a posterior domain defined by engrailed expression, and an anterior domain expressing neither mirror or engrailed. They speculate that this most posterior compartment has been reduced to a rudiment in Drosophila and thus has not been adequately recognized as a such a primary regional specialization.

Critique: This is a very straight-forward study and the experimental results presented support the key claims that mirror is expressed in a restricted posterior section of the wing primordium and that mosaic wings from CRISPR injected larvae display loss of adult wing structures presumably derived from cells expressing mirror (or at least nearby). The major issue I have with this paper is the strong interpretation of these findings that lead the authors to conclude that mirror is acting as a high level gene akin to engrailed in defining a separate extreme posterior wing compartment. To place this claim in context, it is important in my view to consider what is known about engrailed, for which there is ample evidence to support the claim that this gene does play a very ancestral and conserved function in a defining posterior compartments of all body segments (including the wing) across arthropods.

(A) engrailed is expressed in a broad posterior domain with a sharp anterior border in all segments of virtually all arthropods examined (broad use of a very good pan-species anti-En antibody makes this case very strong).

(B) In Drosophila, marked clones of wing cells (generated during larval stages) strictly obey a straight anterior-posterior border indicating that cells in these two domains do not normally intermix, thus, supporting the claim that a clear A/P lineage compartment exists.

In my opinion, mirror does not seem to be in the same category of regulator as engrailed for the following reasons:

(1) There is no evidence that I am aware of, either from the current experiments, or others that the mirror expression domain corresponds to a clonal lineage compartment. It is also unclear from the data shown in this study whether engrailed is co-expressed with mirror in posterior most cells of J. coenia wing discs? If so, it does not seem justified to infer that mirror acts as an independent determinant of the region of the wing where it is expressed.

(2) The mirror is not only expressed in a posterior region of the wing in flies but also in the ventral region of the eye. In Drosophila, mirror mutants not only lack the alula (derived approximately from cells where mirror is expressed), but also lacks tissue derived from the ventral region of the eye disc (although this ventral tissue loss phenotype may extend beyond the cells expressing mirror).

In summary, it seems most reasonable to me to think of mirror as a transcription factor that provides important development information for a diverse set of cells in which it can be expressed (posterior wing cells and ventral eye cells) but not that it acts as a high level regulator as engrailed.

Recommendation:

While the data provided in this succinct study are solid and interesting, it is not clear to me that these findings support the major claim that mirror defines an extreme posterior compartment akin to that specified by engrailed. Minimally, the authors should address the points outlined above in their discussion section and greatly tone down their conclusion regarding mirror being a conserved selector-like gene dedicated to establishing posterior-most fates of the wing. They also should cite and discuss the original study in Drosophila describing the mirror expression pattern in the embryo and eye and the corresponding eye phenotype of mirror mutants: McNeill et al., Genes & Dev. 1997. 11: 1073-1082; doi:10.1101/gad.11.8.1073.

Reviewer #3 (Public review):

Summary:

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

Strengths:

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

Weakness:

While this work has characterized the neural integration of head and body information in detail, it's unclear how the neural representation relates to the animal's perception. Behavioural experiments using the same set of stimuli could help address this question, but I agree that these additional experiments may be beyond the scope of the current paper.

Reviewer #3 (Public review):

Summary:

At the abandoned replication fork, loading of DnaB helicase requires assistance from PriABC, repA, and other protein partners, but it does not require replication initiator protein, DnaA. In contrast, nucleotide-dependent DnaA binding at the specific functional elements is fundamental for helicase loading, leading to the DUE region's opening. However, the authors questioned in this study that in case of impeding replication at the bacterial chromosomal origins, oriC, a strategy similar to an abandoned replication fork for loading DnaB via bypassing the DnaA interaction step could be functional. The study by Yoshida et al. suggests that PriC could promote DnaB helicase loading on the chromosomal oriC ssDNA without interacting with the DnaA protein. The conclusions drawn supported by the evidence provided are compelling.

Strengths:

Understanding the mechanism of how DNA replication restarts via reloading the replisomes onto abandoned DNA replication forks is crucial. Notably, this knowledge becomes crucial to understanding how bacterial cells maintain DNA replication from a stalled replication fork when challenging or non-permissive conditions prevail. This critical study combines experiments to address a fundamental question of how DnaB helicase loading could occur when replication initiation impedes at the chromosomal origin, leading to replication restart.

Reviewer #3 (Public review):

Summary:

Here, Guo et al. (2025) propose that the IFN-induced GTPase GVIN1 forms a coat on cytosolic Burkholderia thailandensis, blocking actin tail formation through a mechanism analogous to GBP1-mediated restriction of Shigella motility.

Their study was prompted by the intriguing observation that IFNγ priming and GBP1 coat formation fail to inhibit B. thailandensis actin-based motility in HeLa cells, yet IFNγ restricts the motility of Burkholderia in T24 cells. Further investigation revealed that IFNγ restricts B. thailandensis motility in T24 cells via both GBP1-dependent and -independent mechanisms, suggesting that HeLa cells lack a critical GBP1 co-factor required to inhibit actin tail formation.

To identify the GBP1-independent mechanism, the authors performed an siRNA screen of interferon-stimulated genes (ISGs) and identified GVIN1, a large IFN-induced GTPase, as essential for restricting B. thailandensis motility. To identify the GBP1-independent mechanism, perform a knock-down screen for ISGs and find that the loss of GVIN, a very large IFN-induced GTPase, results in higher actin tail-positive B. thailandensis in T24 cells. They further demonstrate that GVIN forms coats on the surface of B. thailandensis, which prevent the polar localization of BimA and thus actin tail formation. In summary, the data reveal two independent IFNγ-induced pathways that restrict bacterial motility: one GBP1-dependent and the other GVIN1-dependent, each relying on distinct host co-factors.

Global assessment:

This is a well-executed study that convincingly demonstrates how GVIN1 restricts the actin-based motility of B. thailandensis through the assembly of coatomers. The results are clearly described, the manuscript is easy to follow, and the data are overall compelling and well presented. I have only a few suggestions on how the manuscript could be further improved.

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Reviewer #3 (Public review):

In this manuscript, Wirz et al use neuroimaging (fMRI) to show that counterconditioning produces a longer lasting reduction in fear conditioning relative to extinction and appears to rely on the nucleus accumbens rather than the ventromedial prefrontal cortex. These important findings are supported by convincing evidence and will be of interest to researchers across multiple subfields, including neuroscientists, cognitive theory researchers, and clinicians.

In large part, the authors achieved their aims of giving a qualitative assessment of the behavioural mechanisms of counterconditioning versus extinction, as well as investigating the brain mechanisms. The results support their conclusions and give interesting insights into the psychological and neurobiological mechanisms of the processes that underlie the unlearning, or counteracting, of threat conditioning.

Strengths:

* Clearly written with interesting psychological insights<br /> * Excellent behavioural design, well-controlled and tests for a number of different psychological phenomena (e.g. extinction, recovery, reinstatement, etc).<br /> * Very interesting results regarding the neural mechanisms of each process.<br /> * Good acknowledgement of the limitations of the study.

Weaknesses:

* I am not sure that the memories tested were truly episodic<br /> * Twice as many female participants than males

Comments on revisions: I have no remaining concerns

Reviewer #3 (Public review):

Summary:

The finding of rhythmic activity in the brain has, for a long time, engendered the theory of rhythmic modes of perception, that humans might oscillate between improved and worse perception depending on states of our internal systems. However, experiments looking for such modes have resulted in conflicting findings, particularly in those where the stimulus itself is not rhythmic. This paper seeks to take a comprehensive look at the effect and various experimental parameters which might generate these competing findings: in particular, the presentation of the stimulus to one ear or the other, the relevance of motor involvement, attentional demands, and memory: each of which are revealed to effect the consistency of this rhythmicity.

The need the paper attempts to resolve is a critical one for the field. However, as presented, I remain unconvinced that the data would not be better interpreted as showing no consistent rhythmic mode effect. It lacks a conceptual framework to understand why effects might be consistent in each ear but at different frequencies and only for some tasks with slight variants, some affecting sensitivity and some affecting bias.

Strengths:

The paper is strong in its experimental protocol and its comprehensive analysis, which seeks to compare effects across several analysis types and slight experiment changes to investigate which parameters could affect the presence or absence of an effect of rhythmicity. The prescribed nature of its hypotheses and its manner of setting out to test them is very clear, which allows for a straightforward assessment of its results

Weaknesses:

There is a weakness throughout the paper in terms of establishing a conceptual framework both for the source of "rhythmic modes" and for the interpretation of the results. Before understanding the data on this matter, it would be useful to discuss why one would posit such a theory to begin with. From a perceptual side, rhythmic modes of processing in the absence of rhythmic stimuli would not appear to provide any benefit to processing. From a biological or homeostatic argument, it's unclear why we would expect such fluctuations to occur in such a narrow-band way when neither the stimulus nor the neurobiological circuits require it.

Secondly, for the analysis to detect a "rhythmic mode", it must assume that the phase of fluctuations across an experiment (i.e., whether fluctuations are in an up-state or down-state at onset) is constant at stimulus onset, whereas most oscillations do not have such a total phase-reset as a result of input. Therefore, some theoretical positing of what kind of mechanism could generate this fluctuation is critical toward understanding whether the analysis is well-suited to the studied mechanism.

Thirdly, an interpretation of why we should expect left and right ears to have distinct frequency ranges of fluctuations is required. There are a large number of statistical tests in this paper, and it's not clear how multiple comparisons are controlled for, apart from experiment 4 (which specifies B&H false discovery rate). As such, one critical method to identify whether the results are not the result of noise or sample-specific biases is the plausibility of the finding. On its face, maintaining distinct frequencies of perception in each ear does not fit an obvious conceptual framework.

Reviewer #3 (Public review):

Summary:

The authors explored how individual dorsolateral striatum (DLS) spiny projection neurons (SPNs) receive functional input from whisker-related cortical columns. The authors developed and validated a novel slice preparation and method to which they applied rigorous functional mapping and thorough analysis. They found that individual SPNs were driven by sparse, scattered cortical clusters. Interestingly, while the cortical input fields of nearby SPNs had some degree of overlap, connectivity per SPN was largely distinct. Despite sparse, heterogeneous connectivity, topographical organization was identified. The authors lastly compared direct (D1) vs. indirect (D2) pathway cells, concluding that overall connectivity patterns were the same, but D1 cells received stronger input from L6 and D2 cells from L2/3. The paper thoughtfully addresses the question of whether barrel cortex broadly or selectively innervates SPNs. Their results indicate selective input that is loosely topographic. Their work deepens the understanding of how whisker-related somatosensory signals can drive striatal neurons.

Strengths:

Overall, this is a carefully conducted study, and the major claims are well-supported. The use of a novel ex vivo slice prep that keeps relevant corticostriatal projections intact allows for careful mapping of the barrel cortex to dorsolateral striatum SPNs. Careful reporting of both columnar and layer position, as well as postsynaptic SPN type (D1 or D2), allows the authors to uncover novel details about how the dorsolateral striatum represents whisker-related sensory information.

Weaknesses:

(1) Several factors may contribute to an underestimation of barrel cortex inputs to SPNs (and thus an overestimate of the input heterogeneity among SPNs). First, by virtue of the experiments being performed in an acute slice prep, it is probable that portions of recorded SPN dendritic trees have been dissected (in an operationally consistent anatomical orientation). If afferents happen to systematically target the rostral/caudal projections of SPN dendritic fields, these inputs could be missed. Similarly, the dendritic locations of presynaptic cortical inputs remain unknown (e.g., do some inputs preferentially target distal vs proximal dendritic positions?). As synaptic connectivity was inferred from somatic recordings, it's likely that inputs targeting the proximal dendritic arbor are the ones most efficiently detected. Mapping the dendritic organization of synapses is beyond the scope of this work, but these points could be broached in the text.

(2) In general, how specific (or generalizable) is the observed SPN-specific convergence of cortical barrel cortex projections in the dorsolateral striatum? In other words, does a similar cortical stimulation protocol targeted to a non-barrel sensory (or motor) cortex region produce similar SPN-specific innervation patterns in the dorsolateral striatum?

(3) In general, some of the figure legends are extremely brief, making many details difficult to infer. Similarly, some statistical analyses were either not carried out or not consistently reported.

Reviewer #3 (Public review):

Strengths:

It's sort of novel to study the heritability of movie-watching fMRI data. The methodology the authors used in the paper is also supportive of their findings. Figures are nicely organized and plotted. They finally found that sensory processing in the human brain is under genetic control over stable aspects of brain function (here referring to neural timescale and resting state connectivity).

Weaknesses:

What I am worried about most is the sample size and interpretation of heritability.

(1) Figure 1. I assumed that the authors just calculated the ISC within each group (MZ, DZ, and UR). Of course, you can get different variations between each group. Therefore, there is heritability. Why not calculate ISC across the whole sample, then separate MZ, DZ, and UR?

(2) Heritability scores in the paper are sort of small. If the sample size is small, please consider p-values, which will tell more about the trustworthiness of your heritability.

(3) I don't understand the high-frequency signals in fMRI data. It's always regarded as noise, the band 1 here in particular.

(4) The statement "we show that the heritability of brain activity patterns can be partially explained by the heritability of the neural timescale" should come from Figure 5. However, after controlling for NT, the heritability decreased max. 0.025 in temporal areas. I am not sure this change supports the statement. If the visual cortex is outlined, and combining ISC changes in the visual cortex, I think this would somehow be answered. Instead of delta h2, adding a new model h2 would be obvious to the readers.

(5) Figures 7 and 8, when getting the difference of heritability, please also consider the standard errors of the heritability estimates. Then you can compare across networks/regions.

(6) I think movie VS resting state is a really important result in this paper. However, there is almost no discussion. Discussing this part would be more beneficial for understanding the genetic control over the neuron arousal and excitation circuits.

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Reviewer #3 (Public review):

In this report, Keenen et al. present a thoroughly characterized platform for identifying potential molecular mechanisms regulating syncytiotrophoblast cell functions in placental biology. Application of single cell assessments to identify developmental trajectories of this lineage have been challenging due to the complex, multinucleated structure of the syncytium. The authors provide a comprehensive comparative assessment of term placental tissue and three independent trophoblast organoid models. They use single cell and single nucleus RNA sequencing followed by differential gene expression and pseudotime analyses to identify subpopulations and differentiation trajectories. They further compare the datasets generated in this study to publicly available datasets from first trimester placental tissue. The work is timely as optimization of trophoblast organoids is an evolving topic in placental research. And careful characterization of in vitro models has been noted as essential for model selection and result interpretation in the field.

The study elucidates syncytiotrophoblast nucleus subtypes and proportions in three different organoid models and compares subtypes and gene expression signatures to placental tissues. This work advances the field by demonstrating the utility of different trophoblast organoids to model syncytiotrophoblast differentiation. The in-depth characterization of cell types comprising the different organoid models and how they compare to placental tissue will help to inform model selection for future experimentation in the field. Defining cell composition and cell differentiation trajectories will also aid in data interpretation for data generated by these tissue and model sources. Overall, the conclusions presented in the manuscript are well supported by the data. The figures, as presented, are informative and striking.

The authors present outstanding progress toward their overall aim of identifying, "the underlying control of the syncytiotrophoblast". They identify the chromatin remodeler, RYBP, as well as other regulatory networks that they propose are critical to syncytiotrophoblast development.

The initial study was limited in fully addressing the aim, however, as functional evidence for the contributions of the factors/pathways to syncytiotrophoblast cell development was absent. In a revised version of the manuscript, the authors report the first application of CRISPR-mediated gene silencing in a TO model. They use CRISPR-Cas9-mediated gene targeting to generate RYBP and AFF1 knockout models. Deletion of either RYBP or AFF1 increased STB-2 marker gene expression, as determined using bulk RNA-seq. Future experimentation will assess the distribution of STB nuclear subtypes in the RYBP and AFF1 knockout models and explore the essentiality of RYBP, AFF1, and other identified factors to syncyiotrophoblast development and function.

Localization and validation of the identified factors within tissue and at the protein level will also provide further contextual evidence to address the hypotheses generated. In a revised version of the manuscript, the authors localize STB markers PAPPA2 and ADAMTS6 in TOs using RNA-FISH. Future work will aim to further validate the markers and hypotheses generated from this study.

Reviewer #3 (Public review):

Summary:

In the manuscript "Ribosomal RNA synthesis by RNA polymerase I is regulated by premature termination of transcription", Azouzi and co-authors investigate the regulatory mechanisms of ribosomal RNA (rRNA) transcription by RNA Polymerase I (RNAPI) in the budding yeast S. cerevisiae. They follow up on exploring the molecular basis of a mutant allele of the second largest subunit of RNAPI, RPA135-F301S, also dubbed SuperPol, that they had previously reported (Darrière et al, 2019), and which was shown to rescue Rpa49-linked growth defects, possibly by increasing rRNA production.

Through a combination of genomic and in vitro approaches, the authors test the hypothesis that RNAPI activity could be subjected to a Premature Transcription Termination (PPT) mechanism, akin to what is observed for RNA Polymerase II (RNAPII), and which is suggested to be an important step for the quality control of rRNA transcripts. SuperPol is proposed to lack such a regulatory mechanism, due to an increased processivity. In agreement, SuperPol is shown to be resistant to BMH-21, a drug previously shown to impair RNAPI elongation.<br /> Overall, the experiments are performed with rigor and include the appropriate controls and statistical analysis. Both the figures and the text present the data clearly. The Material and Methods section is detailed enough. The reported results are interesting; however, I am not fully convinced of the existence of PPT of RNAPI, and even less of its utmost importance.

The existence of PPT of RNAPI would entail an intended regulatory mechanism. The authors propose that PPT could serve as quality control step for the UTP-A complex loading on the rRNA 5'-end. While this hypothesis is enticing and cautiously phrased by the authors, the lack of evidence showing a specific regulatory function (such as UTP-A loading checkpoint or else) limits these termination events to possibly abortive actions of unclear significance.

The authors may want to consider comparisons to other processive alleles, such as the rpb1-E1103G mutant of the RNAPII subunit (Malagon et al, 2006) or the G1136S allele of E. coli RNAP (Bar-Nahum et al., 2005). While clearly mechanistically distinct, these mutations result in similarly processive enzymes that achieve more robust transcription, possibly at the cost of decreased fidelity. Indeed, an alternative possibility explaining these transcripts could be that they originate from unsuccessful resumption of transcription after misincorporation (see below).

I suggest reconsidering the study's main conclusions by limiting claims about the regulatory function of these termination events (the title of the manuscript should be changed accordingly). Alternatively, the authors should provide additional investigation on their regulatory potential, for example by assessing if indeed this quality control is linked to the correct assembly of the UTP-A complex. The expectation would be that SuperPol should rescue at least to some extent the defects observed in the absence of UTP-A components.

Moreover, the results using the clv3 substrate suggest the possibility that SuperPol might simply be more able to tolerate mismatches, thus be more processive in transcribing, because not subjected to proof-reading mechanisms, similarly to what observed in Schwank et al., 2022. This could explain many of the observations, and I think it is worth exploring by assessing the fidelity of the enzyme, especially in the frame of suggesting a regulatory function for these termination events.

Significance:

Azouzi and co-authors' work builds on their previous study (Darrière et al, 2019) of RPA135-F301S (SuperPol), a mutant allele of the second largest RNAPI subunit, which was shown to compensate for Rpa49 loss, potentially by increasing rRNA production. The work advances the mechanistic understanding of the the SuperPol allele, demonstrating the increased processivity of this enzyme compared to its wild-type counterpart. Such increased processivity "desensitizes" RNAPI from abortive transcription cycles, the existence of which is clearly shown, though the biological significance of this phenomenon remains unclear. The lack of evidence for a regulatory mechanism behind these early termination events is, in my opinion, a limitation of this study, as it does not allow for differentiation between an intended regulatory process and a byproduct of an imperfect system.

This work is of interest for researchers studying transcription regulation, particularly those interested in understanding RNAPI's role and fidelity. Demonstrating PPT as a regulatory quality control for RNAPI could point to common strategies in between RNAPI and RNAPII regulation, where premature termination has been extensively documented. However, without evidence of a specific regulatory function, these findings may currently be limited to descriptive insights.

Reviewer #3 (Public review):

Summary:

This is a timely article that focuses on the molecular machinery in charge of the proliferation of pallial neural stem cells in chicks, and aims to compare them to what is known in mammals. miR19b is related to controlling the expression of E2f8 and NeuroD1, and this leads to a proper balance of division/differentiation, required for the generation of the right number of neurons and their subtype proportions. In my opinion, many experiments do reflect an interaction between all these genes and transcription factors, which likely supports the role of miR19b in participating in the proliferation/differentiation balance.

Strengths:

Most of the methodologies employed are suitable for the research question, and present data to support their conclusions.

The authors were creative in their experimental design, in order to assess several aspects of pallial development.

Weaknesses:

However, there are several important issues that I think need to be addressed or clarified in order to provide a clearer main message for the article, as well as to clarify the tools employed. I consider it utterly important to review and reinterpret most of the anatomical concepts presented here. The way the are currently used is confusing and may mislead readers towards an understanding of the bird pallium that is no longer accepted by the community.

Major Concerns:

(1) Inaccurate use of neuroanatomy throughout the entire article. There are several aspects to it, that I will try to explain in the following paragraphs:

a) Figure 1 shows a dynamic and variable expression pattern of miR19b and its relation to NeuroD1. Regardless of the terms used in this figure, it shows that miR19b may be acting differently in various parts of the pallium and developmental stages. However, all the rest of the experiments in the article (except a few cases) abolish these anatomical differences. It is not clear, but it is very important, where in the pallium the experiments are performed. I refer here, at least, to Figures 2C, E, F, H, I; 3D, E; 4C, D, G, I. Regarding time, all experiments were done at HH22, and the article does not show the native expression at this stage. The sacrifice timing is variable, and this variability is not always justified. But more importantly, we don't know where those images were taken, or what part of the pallium is represented in the images. Is it always the same? Do results reflect differences between DVR and Wulst gene expression modifications? The authors should include low magnification images of the regions where experiments were performed. And they should consider the variable expression of all genes when interpreting results.

b) SVZ is not a postmitotic zone (as stated in line 123, and wrongly assigned throughout the text and figures). On the contrary, the SVZ is a secondary proliferative zone, organized in a layer, located in a basal position to the VZ. Both (VZ and SVZ) are germinative zones, containing mostly progenitors. The only postmitotic neurons in VZ and SVZ occupy them transiently when moving to the mantle zone, which is closer to the meninges and is the postmitotic territory. Please refer to the original Boulder committee articles to revise the SVZ definition. The authors, however, misinterpret this concept, and label the whole mantle zone as it this would be the SVZ. Indeed, the term "mantle zone" does not appear in the article. Please, revise and change the whole text and figures, as SVZ statements and photographs are nearly always misinterpreted. Indeed, SVZ is only labelled well in Figure 4F.

The two articles mentioning the expression of NeuroD1 in the SVZ (line 118) are research in Xenopus. Is there a proliferative SVZ in Xenopus?

For the actual existence of the SVZ in the chick pallium, please refer to the recent Rueda-Alaña et al., 2025 article that presents PH3 stainings at different timepoints and pallial areas.

c) What is the Wulst, according to the authors of the article? In many figures, the Wulst includes the medial pallium and hippocampus, whereas sometimes it is used as a synonym of the hyperpallium (which excludes the medial pallium and hippocampus). Please make it clear, as the addition or not of the hippocampus definitely changes some interpretations.

d) The authors compare the entirety of the chick pallium - including the hippocampus (see above), hyperpallium, mesopallium, nidopallium - to only the neocortex of mammals. This view - as shown in Suzuki et al., 2012 - forgets the specificity of pallial areas of the pallium and compares it to cortical cells. This is conceptually wrong, and leads to incorrect interpretations (please refer to Luis Puelles' commentaries on Suzuki et al results); there are incorrect conclusions about the existence of upper-layer-like and deep-layer-like neurons in the pallium of birds. The view is not only wrong according to the misinterpreted anatomical comparisons, but also according to novel scRNAseq data (Rueda-Alaña et al., 2025; Zaremba et al., 2025; Hecker et al., 2025). These articles show that many avian glutamatergic neurons of the pallium have highly diversified, and are not comparable to mammalian cortical cells. The authors should therefore avoid this incorrect use of terminology. There are not such upper-layer-like and deep-layer-like neurons in the pallium of birds.

(2) From introduction to discussion, the article uses misleading terms and outdated concepts of cell type homology and similarity between chick and pallial territories and cells. The authors must avoid this confusing terminology, as non-expert readers will come to evolutionary conclusions which are not supported by the data in this article; indeed, the article does not deal with those concepts.

a) Recent articles published in Science (Rueda-Alaña et al., 2025; Zaremba et al., 2025; Hecker et al., 2025) directly contradict some views presented in this article. These articles should be presented in the introduction as they are utterly important for the subject of this article and their results should be discussed in the light of the new findings of this article. Accordingly, the authors should avoid claiming any homology that is not currently supported. The expression of a single gene is not enough anymore to claim the homology of neuronal populations.

b) Auditory cortex is not an appropriate term, as there is no cortex in the pallium of birds. Cortical areas require the existence of neuronal arrangements in laminae that appear parallel to the ventricular surface. It is not the case of either hyperpallium or auditory DVR. The accepted term, according to the Avian Nomenclature forum, is Field L.

c) Forebrain, a term overused in the article, is very unspecific. It includes vast areas of the brain, from the pretectum and thalamus to the olfactory bulb. However the authors are not researching most of the forebrain here. They should be more specific throughout the text and title.

(3) In the last part of the results, the authors claim miR19b has a role in patterning the avian pallium. What they see is that modifying its expression induces changes in gene expression in certain neurons. Accordingly, the altered neurons would differentiate into other subtypes, not similar to the wild type example. In this sense, miR19b may have a role in cell specification or neuronal differentiation. However, patterning is a different developmental event, which refers to the determination of broad genetic areas and territories. I don't think miR19b has a role in patterning.

(4) Please add a scheme of the molecules described in this article and the suggested interaction between them.

(5) The methods section is way too brief to allow for repeatability of the procedures. This may be due to an editorial policy but if possible, please extend the details of the experimental procedures.

Reviewer #3 (Public review):

Summary:

This study employed an implicit task, showing vignettes to participants while bold signal was acquired. The aim was to capture automatic causal inferences that emerge during language processing and comprehension. In particular, the authors compared causal inferences about illness with two control conditions, causal inferences about mechanical failures and non-causal phrases related to illnesses. All phrases that where employed described contexts with people, to avoid animacy/inanimate confound in the results. The authors had a specific hypothesis concerning the role of the precuneus (PC) being sensitive to causal inferences about illnesses (that was preregistered).<br /> Findings indicate that implicit causal inferences are facilitated by semantic networks specialized for encoding causal knowledge.

Strengths:

The major strength of the study is the clever design of the stimuli (which are nicely matched for a number of features) which can tease apart the role of the type of causal inference (illness-causal or mechanical-causal) and the use of two localizers (logic/language and mentalizing) to investigate the hypothesis that the language and/or logical reasoning networks preferentially respond to causal inference regardless of the content domain being tested (illnesses or mechanical).

I think that authors' revisions of the original manuscript have strengthened the study. Overall, the paper provides an interesting contribution to the (rather new) field of study concerning the neural basis of implicit causal inference.

I see two weaknesses concerning the visualization of the data (which could be improved)

(1) Measures of dispersion are now provided for the average PSC in the critical window. It would be more appropriate to show the variance of the data also for the percentage signal changes (PSC) figures (e.g., 1A by using shaded lines providing SE around the means or boxplots at each timepoint).

(2) The authors could consider showing in Figure 2 the data of supplementary Figure 3. It is not clear why the authors report in the main manuscript the results of a subsample of participants (and only for this figure).

Reviewer #3 (Public review):

Summary:

Rayshubskiy et al. performed whole-cell recordings from descending neurons (DNs) of fruit-flies to characterize their role in steering. Two DNs implicated in "walking control" and "steering control" by previous studies (Namiki et al., 2018, Cande et al., 2018, Chen et al., 2018) were chosen by the authors for further characterization. In-vivo whole-cell recordings from DNa01 and DNa02 showed that their activity predicts spontaneous ipsilateral turning events. The recordings also showed that while DNa02 predicts transient turns DNa01 predicts slow sustained turns. However, optogenetic activation or inactivation showed relatively subtle phenotypes for both neurons (consistent with data in other recent preprints, Yang et al 2023 and Feng et al 2024). The authors also further characterized DNa02 with respect to its inputs and show functional connection with olfactory and thermosensory inputs as well as with the head-direction system. DNa01 is not characterized to this extent.

Strengths:

(1). In-vivo recordings and especially dual recordings are extremely challenging in Drosophila and provide a much higher resolution DN characterization than other recent studies which have relied on behavior or calcium imaging. Especially impressive are the simultaneous recordings from bilateral DNs (Fig. 3). These bilateral recordings show clearly that DNa02 cells not only fire more during ipsilateral turning events but that they get inhibited during contralateral turns. In-line with this observation, the difference between left and right DNa02 neuronal activity is a much better predictor of turning events compared to individual DNa02 activity.

(2). Another technical feat in this work is driving local excitation in the head-direction neuronal ensemble (PEN-1 neurons), while simultaneously imaging its activity and performing whole-cell recordings from DNa02 (Fig. 4). This impressive approach provided a way to causally relate changes in the head-direction system to DNa02 activity. Indeed, DNa02 activity could predict the rate at which an artificially triggered bump in the PEN-1 ring-attractor returns to its previous stable point.

(3). The authors also support the above observations with connectomics analysis and provide circuit motifs that can explain how head direction system (as well as external olfactory/thermal stimuli) communicated with DNa02. All these results unequivocally put DNa02 as an essential DN in steering control, both during exploratory navigation as well as stimulus directed turns.

Weaknesses:

While this study makes a compelling case for the importance of DNa02 in steering control, the role of DNa01 on the other hand seems unclear based on physiology, optogenetics perturbations as well as connectome analysis. DNa01 still remains a bit mysterious regarding both its role in controlling steering maneuvers as well as what in behavioral context it would be relevant.

Reviewer #3 (Public review):

Summary

This study aimed to investigate whether the development of functional connectivity (FC) is modulated by early physical growth, and whether these might impact cognitive development in childhood. This question was investigated by studying a large group of infants (N=204) assessed in Gambia with fNIRS at 5 visits between 5 and 24 months of age. Given the complexity of data acquisition at these ages and following data processing, data could be analyzed for 53 to 97 infants per age group. FC was analyzed considering 6 ensembles of brain regions and thus 21 types of connections. Results suggested that: i) compared to previously studied groups, this group of Gambian infants have different FC trajectory, in particular with a change in frontal inter-hemispheric FC with age from positive to null values; ii) early physical growth, measured through weight-for-length z-scores from birth on, is associated with FC at 24 months. Some relationships were further observed between FC during the first two years and cognitive flexibility, in different ways between 4- and 5-year-old preschoolers, but results did not survive corrections for multiple comparisons.

Strengths

The question investigated in this article is important for understanding the role of early growth and undernutrition on brain and behavioral development in infants and children. The longitudinal approach considered is highly relevant to investigate neurodevelopmental trajectories. Furthermore, this study targets a little studied population from a low-/middle-income country, which was made possible by the use of fNIRS outside the lab environment. The collected dataset is thus impressive and it opens up a wide range of analytical possibilities.

Weaknesses

- Data analyses were constrained by the limited number of children with longitudinal data on NIRS functional connectivity. Nevertheless, considering more advanced statistical modeling approaches would be relevant to further explore neurodevelopmental trajectories as well as relationships with early growth and later cognitive development.<br /> - The abstract and end of the discussion should make it clearer that the associations between FC and cognitive flexibility are results that need to be confirmed, insofar as they did not survive correction for multiple comparisons.

Reviewer #3 (Public review):

Summary:

This is a solid study of stimulus-evoked neural activity dynamics in the feedforward pathway from mouse hand/forelimb mechanoreceptor afferents to S1 and M1 cortex. The conclusions are generally well supported and match expectations from previous studies of hand/forelimb circuits by this same group (Yamawaki et al., 2021), from the well-studied whisker tactile pathway to whisker S1 and M1, and from the corresponding pathway in primates. The study uses the novel approach of optogenetic stimulation of PV afferents in the periphery, which provides an impulse-like volley of peripheral spikes, which is useful for studying feedforward circuit dynamics. These are primarily proprioceptors, so results could differ for specific mechanoreceptor populations, but this is a reasonable tool to probe basic circuit activation. Mice are awake but not engaged in a somatosensory task, which is sufficient for the study goals.

The main results are: 1) brief peripheral activation drives brief sensory-evoked responses at ~ 15 ms latency in S1 and ~25 ms latency in M1, which is consistent with classical fast propagation on the subcortical pathway to S1, followed by slow propagation on the polysynaptic, non-myelinated pathway from S1 to M1; 2) each peripheral impulse evokes a triphasic activation-suppression-rebound response in both S1 and M1; 3) PV interneurons carry the major component of spike modulation for each of these phases; 4) activation of PV neurons in each area (M1 or S1) drives suppression and rebound both in the local area and in the other downstream area; 5) peripheral-evoked neural activity in M1 is at least partially dependent on transmission through S1.

All conclusions are well-supported and reasonably interpreted. There are no major new findings that were not expected from standard models of somatosensory pathways or from prior work in the whisker system.

Strengths:

This is a well-conducted and analyzed study in which the findings are clearly presented. The optogenetic sensory afferent stimulation method is novel and is well-suited for studying feedforward circuit dynamics. This study provides important baseline knowledge from which studies of more complex sensorimotor processing can build.

There are no further recommendations for the authors.

Reviewer #3 (Public review):

Summary:

The manuscript presents a detailed study on the role of MmMYL3 in the viral entry of NNV, focusing on its function as a receptor that mediates viral internalization through the macropinocytosis pathway. The use of both in vitro assays (e.g., Co-IP, SPR, and GST pull-down) and in vivo experiments (such as infection assays in marine medaka) adds robustness to the evidence for MmMYL3 as a novel receptor for RGNNV. The findings have important implications for understanding NNV infection mechanisms, which could pave the way for new antiviral strategies in aquaculture.

Strengths:

The authors show that MmMYL3 directly binds the viral capsid protein, facilitates NNV entry via the IGF1R-Rac1/Cdc42 pathway, and can render otherwise resistant cells susceptible to infection. This multifaceted approach effectively demonstrates the central role of MmMYL3 in NNV entry.

Comments on revisions:

The implemented revisions have remarkably improved the manuscript's conceptual clarity, scientific depth, and methodological rigor. Through comprehensive addressing of issue with meticulous attention to detail, the authors have produced a substantially strengthened manuscript that demonstrates enhanced experimental validity and theoretical coherence. No additional revisions appear necessary at this stage.

Reviewer #3 (Public review):

The results are consistent with the main claim that facilitation is caused by overfilling a readily releasable pool, but alternative interpretations continue to seem more likely, especially when the current results are taken together with previous studies. Key doubts could be resolved with a single straightforward experiment (see below).

The central issue is the interpretation of paired pulse depression that occurs when the interval between action potentials is 25 ms, but not when 50. To summarize: a similar phenomenon was observed at Schaffer collateral synapses (Dobrunz and Stevens, 1997), but was interpreted as evidence for a decrease in pv. Ca2+-channel inactivation was proposed as the mechanism, but this was not proven. The key point for evaluating the current study is that Dobrunz and Stevens specifically ruled out the kind of decrease in pocc that is the keystone premise of the current study because the depression occurred independently of whether or not the first action potential elicited exocytosis. Of course, the mechanism might be different at layer 2/3 cortical synapses. But, it seems reasonable to hope that the older hypothesis would be ruled out for the cortical synapses before concluding that the new hypothesis must be correct.

The old and new hypotheses could be distinguished from each other cleanly with a straightforward experiment. Most/maybe all central synapses strengthen a great amount when extracellular Ca2+ is increased from 1.3 to 2 mM, even when intracellular Ca2+ is buffered with EGTA. According to the authors' model, this is only possible when pv is low, and so could not occur at synapses between layer 2/3 neurons. Because of this, confirmation that increasing extracellular Ca2+ does not change synaptic strength would support the hypothesis that baseline pv is high, as the authors claim, and the support would be impressive because large changes have been seen at every other type of synapse where this has been studied (to my knowledge at least). In contrast, the Ca2+ imaging experiment that has been added to the new version of the manuscript does not address the central issue because a wide range of mechanisms could, in principle, decrease release without involving prior exocytosis or altering bulk Ca2+ signals, including: a small decrease in nano-domain Ca2+, which wouldn't be detected because nano-domains contribute a minuscule amount to the bulk signal during Ca2+-imaging; or even very fast activity-dependent undocking of synaptic vesicles, which was reported in the same Kusick et al, 2020 study that is central to the LS/TS terminology adopted by the authors.

Additional points:

(1) A new section in the Discussion (lines 458-475) suggests that previous techniques employed to show that augmentation and facilitation are caused by increases in pv did not have the resolution to distinguish between pv and pocc, but this is misleading. The confusion might be because the terminology has changed, but this is all the more reason to clarify this section. The previous evidence for increases in pv - and against increases in pocc - is as follows: The residual Ca2+ that drives augmentation decreases the latency between the onset of hypertonic solution and onset of the postsynaptic response by about 150 ms, which is large compared to the rise time of the response. The decrease indicates that the residual Ca2+ drives a decrease in the energy barrier that must be overcome before readily releasable vesicles can undergo exocytosis, which is precisely the type of mechanism that would enhance pv. In contrast, an increase in pocc could change the rise time, but not the latency. There is a small change in the rise time, but this could be caused by changes in either pv or pocc, and one of the studies (Garcia-Perez and Wesseling, 2008) showed that augmentation occluded facilitation, even at times when pocc was reduced by a factor of 3, which would seem to argue against parallel increases in both pv and pocc.

(2) Similar evidence from hypertonic stimulation indicates that Phorbol esters increase pv, but I am not aware of evidence ruling out a parallel increase in pocc.

Comments on revisions:

There are at least two straightforward ways to address the main concern.

The first would be experiments analogous to those in Dobrunz and Stevens that show that - unlike at Schaffer collateral synapses - paired pulse depression at L2/3 synapses requires neurotransmitter release. I proposed this in the first round, but realized since that a simpler and more powerful strategy would be to test directly that pv is/is-not near 1.0 in 1.2 mM Ca2+ simply by increasing to 2 mM Ca2+ (and showing that synaptic strength does-not/does change). This would be powerful because the increase in Ca2+ greatly increases synaptic strength at Schaffer collaterals by about 2.5-fold. Concerns about a confounding elevation in the basal intracellular Ca2+ concentration could be easily neutralized by pre-treating with EGTA-AM, which the authors have already done for other experiments.

Reviewer #3 (Public review):

Summary:

This paper provides a catalogue of 195 well-documented Drosophila strains with sparse and cell-type-specific GAL-4 expression in the adult ventral nerve cord (VNC). The focus is on motor neurons, interneurons, and modulatory unpaired neurons in the dorsal VNC neuropils that drive motor control of the wings. Intersegmental sensory and interneurons are not included. The expression patterns of all 195 fly strains are exceptionally well-characterized and catalogized. Compelling links to hemi-lineages and connectomics data are well documented, and some solid functional data demonstrate the applicability of the GAL4 strains in genetic silencing and optogenetic activation experiments. In sum, this catalogue provides a fantastic toolkit for future functional analyses of motor control centers in the dorsal VNC.

Strengths:

Particularly noteworthy is that the authors did a tremendous job in identifying and catalogizing the correspondences between the neurons in their catalogue and the MANC connectomics dataset, as well as with the respective hemi-lineages. The catalogue has been generated with exquisite care and is impressive.

Weaknesses:

There are no significant weaknesses. I have only minor recommendations on definitions and naming of neuron types, the text on the optogenetic experiments, and the comparison to other insects.

https://www.reddit.com/r/typewriters/comments/1kbp3bb/corona_3_with_case_key/

Corona 3 cases had very straightforward keys with a simple 1-2mm numb at the far end.

Reviewer #3 (Public review):

Summary:

The authors analyzed Cntnap2 KO mice to determine whether loss of the ASD risk gene CNTNAP2 alters the dorsal striatum's function.

Strengths:

The results demonstrate that loss of Cntnap2 results in increased excitability of striatal projection neurons (SPNs) and altered striatal-dependent behaviors, such as repetitive, inflexible behaviors. Unlike other brain areas and cell types, synaptic inputs onto SPNs were normal in Cntnap2 KO mice. The experiments are well-designed, and the results support the authors' conclusions.

Weaknesses:

The mechanism underlying SPN hyperexcitability was not explored, and it is unclear whether this cellular phenotype alone can account for the behavioral alterations in Cntnap2 KO mice. No clear explanation emerges for the variable phenotype in different brain areas and cell types.

Comments on revisions:

The authors have appropriately addressed all my comments. In my opinion, no further changes are required.

Reviewer #3 (Public review):

Summary:

The authors investigated the role of kallistatin in metabolic abnormalities associated with AD. They found that Kallistatin promotes Aβ production by binding to the Notch1 receptor and upregulating BACE1 expression. They identified that Kallistatin is a key player that mediates Aβ accumulation and tau hyperphosphorylation in AD.

Strengths:

This manuscript not only provides novel insights into the pathogenesis of AD, but also indicates that the hypolipidemic drug fenofibrate attenuates AD-like pathology in Kallistatin transgenic mice.

Weaknesses:

The authors did not illustrate whether the protective effect of fenofibrate against AD depends on kallistatin.

The conclusions are supported by the results.

Reviewer #3 (Public review):

Summary:

This study investigates the molecular mechanisms underlying the transdifferentiation of androgen receptor-active prostate cancer (ARPC) to neuroendocrine prostate cancer (NEPC) in prostate cancer (PC). Using a cellular reprogramming strategy, the research team successfully converted ARPC cell lines into NEPC cell lines and explored key molecular mechanisms driving this transformation. The work demonstrates the pivotal role of neurogenic pioneer transcription factors ASCL1 and NeuroD1 in NEPC transdifferentiation, which silence AR expression and signaling by remodeling chromatin architecture while inducing NEPC-associated gene programs. Additionally, the study reveals dynamic transcriptomic and epigenomic changes during NEPC transformation, as well as downregulation of the MHC class I antigen processing and presentation pathway in NEPC cell lines.

Strengths:

(1) The study introduces a novel genetically defined cellular reprogramming strategy to directly convert ARPC to NEPC. This approach circumvents previous limitations by starting from AR-active cells, thereby addressing a critical gap in the field.<br /> (2) The study provides a comprehensive characterization of the dynamic changes in the transcriptomic and epigenomic landscapes during the NEPC transdifferentiation process.

Weaknesses:

(1) What was the rationale for selecting these specific candidate factors (e.g., ASCL1, NeuroD1) to drive neuroendocrine transdifferentiation (NEtD)? Was a comprehensive screening process conducted to identify additional potential drivers of this phenotypic shift?

(‌2) The AR bypass assay employed an AR response element-driven FKBP-Casp8 fusion protein for negative selection. How was the specificity and efficiency of this system validated? Are there additional validation experiments (e.g., orthogonal AR activity assays) to confirm the complete bypass of AR signaling?

(3‌) While extensive omics data (RNA-seq, ATAC-seq, CUT&RUN) are presented, have these datasets been deposited in public repositories (e.g., GEO, SRA) to enable validation and reuse by the scientific community?

(‌4) What criteria guided the selection of time points for analyzing dynamic changes during NEtD? Would denser time-point sampling (e.g., intermediate time courses) enhance resolution of critical transitional events?

(5‌) Were multiple hypothesis testing corrections (e.g., Benjamini-Hochberg) applied during differential expression and pathway enrichment analyses? How was the statistical significance of chromatin accessibility changes and super-enhancer reconfiguration rigorously validated?

Reviewer #3 (Public review):

Summary:

In their manuscript "Multiplexed CRISPRi Reveals a Transcriptional Switch Between KLF Activators and Repressors in the Maturing Neocortex", Kirk and colleagues seek to dissect the developmentally regulated pan-neuronal gene programs that control the postnatal maturation of cortical neurons. For this, the authors analyzed newly generated and existing RNA-seq and ATAC-seq of Layer 4 and Layer 6 cortical pyramidal neurons at postnatal day 2 (P2) and day 30 (P30), and identified thousands of shared developmentally regulated genes and genomic (promoter) regions, including genes involved in axon growth (tend to be downregulated) and synaptic function (tend to be upregulated). Motif enrichment analysis of promoters of differentially regulated genes revealed a strong presence of KLF/Sp family binding motifs, pointing to Krüppel-Like Factors (KLFs) as key transcriptional regulators of cortical maturation. Expression profiling showed a developmental switch from activating KLFs (Klf6, Klf7) expressed neonatally to repressive KLFs (Klf9, Klf13) upregulated during maturation. Using an elegant in vivo multiplexed CRISPR interference (CRISPRi) system, the authors achieved efficient, cell-type-specific knockdown of these TFs and showed that Klf9 and Klf13 repress a set of genes that includes cytoskeletal regulators such as Tubb2b, Dpysl3, and Rac3. Conversely, Klf6 and Klf7 promoted the expression of these same genes in the early postnatal period, and their knockdown led to reduced expression of these genes, particularly at P10 when their activating influence is strongest. Since promoters of shared KLF targets were enriched for KLF/Sp motifs but showed little change in chromatin accessibility, the authors propose a model in which distinct KLF family members function either as transcriptional repressors and activators that compete at constitutively accessible promoters and thereby act as a developmental transcriptional switch that coordinates the downregulation of axon growth programs and upregulation of synaptic maturation genes during cortical development.

Strengths:

The study addresses an interesting question and advances our understanding of the transcriptional regulation underlying postnatal cortical development. A major strength of the study lies in the innovative use of in vivo multiplexed CRISPR interference (CRISPRi), which allows for cell-type-specific, combinatorial knockdown of redundant TFs - this an elegant solution to a long-standing challenge in transcription factor research, and should be useful also for other neuroscience studies that require local and cell-type-specific gene loss-of-function. Also, the integration of RNA-seq and ATAC-seq across developmental time points provides a robust foundation for identifying direct targets of the KLF family, and the findings are reinforced by cross-species conservation and the identification of targets with clear neurodevelopmental relevance.

Weaknesses:

The major weakness of the study lies in its relatively narrow scope: the study focuses primarily on transcriptional mechanisms and largely lacks functional validation of the neuronal phenotypes that are predicted by the gene expression data (e.g. axonal morphology). For example, the authors analyzed the effects of KLF9/13 KD on the neurons' excitability and excitatory inputs, but did not assess the effects on inhibitory inputs and E/I-ratio or morphological parameters such as axonal length and axonal target fields - the manuscript would be strengthened considerably by such analyses (axonal projections could be analyzed e.g. via local injections of the gRNA AAVs and subsequent immunolabeling of brain sections). Similarly, the chromatin-based mechanisms underlying KLF activity remain relatively speculative, and the transcriptional mechanisms upstream of the KLFs remain unexplored (this could be addressed by analyzing existing datasets; see "Additional Point 1" below). Finally, the manuscript is too long (e.g., nearly five pages in the Discussion section are devoted to discussing various misregulated genes) and would benefit from presenting the Results and Discussion sections more concisely. However, despite these limitations, the paper offers an interesting model for a transcriptional switch during neuronal maturation in the cortex and establishes a powerful methodological framework for dissecting redundant gene networks in vivo.

Reviewer #3 (Public review):

In the manuscript, the authors generated several mutant plants defective in the eIF4E family proteins and detected cassava brown streak viruses (CBSVs) infection in these mutant plants. They found that CBSVs induced significantly lower disease scores and virus accumulation in the double mutant plants. Furthermore, they identified important conserved amino acid for the interaction between eIF4E protein and the VPg of CBSVs by yeast two hybrid screening. The experiments are well designed, however, some points need to be clarified:

(1) The authors reported that the ncbp1 ncbp2 double mutant plants were less sensitive to CBSVs infection in their previous study, and all the eIF4E family proteins interact with VPg. In order to identify the redundancy function of eIF4E family proteins, they generated mutants for all eIF4E family genes, however, these mutants are defective in different eIF4E genes, they did not generate multiple mutants (such as triple, quadruple mutants or else) except several double mutant plants, it is hard to identify the redundant function eIF4E family genes.

(2) The authors identified some key amino acids for the interaction between eIF4E and VPg such as the L51, it is interesting to complement ncbp1 ncbp2 double mutant plants with L51F form of eIF4E and double check the infection by CBSVs.

Reviewer #3 (Public review):

Summary:

Hashikawa and colleagues analyze estrogen signaling in the medial preoptic area using scRNA-sequencing, RNA in situ hybridization, and specific disruption of Esr1 in glutamatergic or GABAergic neurons. They conclude that Esr1 "plays a pivotal role in the transcriptional maturation of GABAergic neurons within the MPOA during adolescence". Overall, the findings are mostly consistent with previous literature but bring additional molecular evidence and timing effects that focus on adolescence rather than the perinatal period. The most surprising results are the lack of effects of Esr1 or adolescence-associated hormone changes in glutamatergic neurons, but this seems like it could be due to limited behavioral and physiological phenotyping as well as limited transcriptomic sampling.

Strengths:

Strengths of this paper are the multiple complementary approaches and the spatially specific disruption of Esr1 in two different neuronal populations of the MPOA. These data add more molecular insights to our understanding of how this region is shaped by hormone changes during adolescence.

The idea that Esr1 regulates "transcriptional maturation" is interesting. This term should be explicitly defined (as well as "arrested adolescent transcriptional progression") and distinguished from general effects of steroid signaling. To what degree does Esr1 disruption narrowly affect genes indicative of transcriptional maturation? The paper highlights specific neuropeptide genes (e.g., Nts, Pdyn, Tac1) that might be estrogen-dependent rather than broad indicators of transcriptional maturation.

Weaknesses:

We already know that Esr1 is important within GABAergic but not glutamatergic neurons for mating behavior. However, there is not enough data to support the claim that disrupting Esr1 in glutamatergic MPOA neurons "had no observable effect." The MPOA is involved in many behaviors and physiologies that were not investigated. More assays would be required to report "no observable effect."

The small number of cells included in the transcriptional studies is a general concern, as noted by the authors. This is a particular concern for conclusions related to the role of adolescence in glutamatergic MPOA neurons. The paper reports 24,627 neurons across all treatment groups, which include 3 timepoints, 2 sexes, and GDX conditions. It seems likely that not much was detected in the glutamatergic neurons because of insufficient power.

Esr1 knockout is initiated in adolescence, not restricted to adolescence. Do we know that the effects on mating behavior are due to what is happening in adolescence vs. the function of Esr1 in adults? Are the effects different if Esr1 is knocked out in mature adults? This comparison would be important to demonstrate that adolescence is a critical time window for Esr1 function.

Reviewer #3 (Public review):

Summary:

This manuscript describes the development of a covalent labeling probe (X7-uP) that selectively targets and tags native P2X7 receptors at the plasma membrane of BV2 microglial cells. Using super-resolution imaging (dSTORM), the authors demonstrate that P2X7 receptors form nanoscale clusters upon microglial activation by lipopolysaccharide (LPS) and ATP, correlating with synergistic IL-1β release. These findings advance understanding of P2X7 reorganization during inflammation and provide a generalizable labeling strategy for monitoring endogenous P2X7 in immune cells.

Strengths:

(1) The authors designed X7-uP by coupling a high-affinity, P2X7-specific antagonist (AZ10606120) with N-cyanomethyl NASA chemistry to achieve site-directed biotinylation. This approach offers high specificity, minimal off-target reactivity, and a straightforward pull-down/imaging readout.<br /> (2) The results connect P2X7's nanoscale clustering directly with IL-1β secretion in microglia, reinforcing the role of P2X7 in inflammation. By localizing endogenous P2X7 at single-molecule resolution, the authors reveal how LPS priming and ATP stimulation synergistically reorganize the receptor.<br /> (3) The authors systematically validate their method in recombinant systems (HEK293 cells) and in BV2 cells, showing selective inhibition, mutational confirmation of the binding site, and Western blot pulldown experiments.

Weaknesses:

(1) While the data strongly indicate that P2X7 clustering contributes to IL-1β release, the manuscript would benefit from additional experiments (if feasible) or discussion on how receptor clustering interfaces with downstream inflammasome assembly. Clarification of whether the P2X7 clusters physically colocalize with known inflammasome proteins would solidify the mechanism.<br /> (2) The authors might expand on the scope of X7-uP in other native cells that endogenously express P2X7 (e.g., macrophages, dendritic cells). Although they mention the possibility, demonstrating the probe's applicability in at least one other primary immune cell type would strengthen its general utility.<br /> (3) The authors do include appropriate negative controls, yet providing additional details (e.g., average single-molecule on-time or blinking characteristics) in supplementary materials could help readers assess cluster calculations.

Reviewer #3 (Public review):

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

Strengths:

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

Weaknesses:

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

Reviewer #3 (Public review):

Summary:

The authors follow up on prior studies where they have argued for the existence of cold nociception in Drosophila larvae. In the proposed pathway, mechanosensitive Class III multidendritic neurons are the noxious cold responding sensory cells. The current study attempts to explore the potential roles of second and third order neurons, based on information of the Class III neuron synaptic outputs that has been obtained from the larval connectome.

Strengths:

The major strength of the manuscript is the detailed discussion of the second and third order neurons that are downstream of the mechanosensory Class III multidendritic neurons. These will be useful in further studies of gentle touch mechanosensation and mechanonociception both of which rely on sensory input from these cells. Calcium imaging experiments on Class III activation with optogenetics support the wiring diagram.

Weaknesses:

The scientific premise is that a full body contraction in larvae that are exposed to noxious cold is a sensorimotor behavioral pathway. This premise is, to start with, questionable. A common definition of behavior is a set of "orderly movements with recognizable and repeatable patterns of activity produced by members of a species (Baker et al., 2001)." In the case of nociception behaviors, the patterns of movement are typically thought to play a protective role and to protect from potential tissue damage.

Does noxious cold elicit a set of orderly movements with a recognizable and repeatable pattern in larvae? Can the patterns of movement that are stimulated by noxious cold allow the larvae to escape harm? Based on the available evidence, the answer to both questions is seemingly no. In response to noxious cold stimulation many, if not all, of the muscles in the larva, simultaneously contract (Turner et al., 2016) and as a result the larva becomes stationary. In response to cold, the larva is literally "frozen" in place and it is incapable of moving away. This incapacitation by cold is the antithesis of what one might expect from a behavior that protects the animals from harm.

An extensive literature has investigated the physiological responses of insects to cold (reviewed in Overgaard and MacMillan, 2017). In numerous studies of insects across many genera (excluding cold adapted insects such as snow flies), exposure to very cold temperatures quickly incapacitates the animal and induces a state that is known as a chill coma. During a chill coma the insect becomes immobilized by the cold exposure, but if the exposure to cold is very brief the insect can often be revived without apparent damage. Indeed, it is common practice for many laboratories that use adult Drosophila for studies of behavior to use a brief chilling on ice as a form of anesthesia because chilling is less disruptive to subsequent behaviors than the more commonly used carbon dioxide anesthesia. If flies were to perceive cold as a noxious nociceptive stimulus, then this "chill coma" procedure would likely be disruptive to behavioral studies, but is not. Furthermore, there is no evidence to suggest that larval sensation of "noxious cold" is aversive.

The insect chill coma literature has investigated the effects of extreme cold on the physiology of nerves and muscle and the consensus view of the field is that the paralysis that results from cold is due to complex and combined action of direct effects of cold on muscle and on nerves (Overgaard and MacMillan, 2017). Electrophysiological measurements of muscles and neurons find that they are initially depolarized by cold, and after prolonged cold exposure they are unable to maintain potassium homeostasis and this eventually inhibits the firing of action potentials (Overgaard and MacMillan, 2017). The very small thermal capacitance of a Drosophila larva means that its entire neuromuscular system will be quickly exposed to the effect of cold in the behavioral assays under consideration here. It would seem impossible to disentangle the emergent properties of a complex combination of effects on physiology (including neuronal, glial, and muscle homeostasis) on any proposed sensorimotor transformation pathway.

Nevertheless, the manuscript before us makes a courageous attempt at attempting this. A number of GAL4 drivers tested in the paper are found to affect parameters of contraction behavior (CT) in cold exposed larvae in silencing experiments. However, notably absent from all of the silencing experiments are measurements of larval mobility following cold exposure. Thus, it is not known from the study if these manipulations are truly protecting the larvae from paralysis following cold exposure, or if they are simply reducing the magnitude of the initial muscle contraction that occurs immediately following cold (ie reducing CT). The strongest effect of silencing occurs with the 19-12-GAL4 driver which targets Class III neurons (but is not completely specific to these cells).

Optogenetic experiments for Class III neurons relying on the 19-12-GAL4 driver combined with a very strong optogenetic acuator (ChETA) show the CT behavior that was reported in prior studies. It should be noted that this actuator drives very strong activation, and other studies with milder optogenetic stimulation of Class III neurons have shown that these cells produce behavioral responses that resemble gentle touch responses (Tsubouchi et al 2012 and Yan et al 2013). As well, these neurons express mechanoreceptor ion channels such as NompC and Rpk that are required for gentle touch responses.

A major weakness of the study is that none of the second or third order neurons (that are downstream of CIII neurons) are found to trigger the CT behavioral responses even when strongly activated with the ChETA actuator (Figure 2 Supplement 2). These findings raise major concerns for this and prior studies and it does not support the hypothesis that the CIII neurons drive the CT behaviors.

Later experiments in the paper that investigate strong CIII activation (with ChETA) in combination with other second and third order neurons does support the idea activating those neurons can facilitate the body-wide muscle contractions. But many of the co-activated cells in question are either repeated in each abdominal neuromere or they project to cells that are found all along the ventral nerve cord, so it is therefore unsurprising that their activation would contribute to what appears to be a non-specific body-wide activation of muscles along the AP axis. As well, if these neurons are already downstream of the CIII neurons the logic of this co-activation approach is not particular clear. A more convincing experiment would be to silence the different classes of cells in the context of the optogenetic activation of CIII neurons to test for a block of the effects, a set of experiments that is notably absent from the study.

The authors argument that the co-activation studies support "a population code" for cold nociception is a very optimistic interpretation of a brute force optogenetics approach that ultimately results in an enhancement of a relatively non-specific body-wide muscle convulsion.

Comments on revisions:

The resubmitted version of this manuscript suffers from the same weaknesses that were raised in the prior round of review. The authors claim that muscles have been removed from the electrophysiological preparations of prior studies is overstated. A small subset of muscles are removed during their recording procedures and this does not rule out the possibility that mechanical forces that are generated by the remaining muscles are being sensed by the mechanosensory neurons.

https://www.printables.com/model/1277687-underwood-portable-4-bank-typewriter-replacement-f

Found via https://www.reddit.com/r/typewriters/comments/1k8lh2v/i_designed_a_3dprintable_replacement_spool_cap/

https://www.printables.com/model/1277700-underwood-portable-typewriter-ribbon-spool-cap-thi

Found via https://www.reddit.com/r/typewriters/comments/1k8lh2v/i_designed_a_3dprintable_replacement_spool_cap/

Reviewer #3 (Public review):

Summary

Neurogenesis in the mammalian olfactory epithelium continues throughout the animal's lifespan, replacing damaged or dying olfactory sensory neurons. It has been tacitly assumed that the replacement of olfactory receptor (OR) subtypes occurs randomly. However, anecdotal evidence has suggested otherwise. In this study, Santoro and colleagues challenge this assumption by systematically exploring three key questions: Is there enrichment of specific OR subtypes during neurogenesis? Is this enrichment influenced by sensory stimuli? Does enrichment result from differential generation of OR types or differential cell death regulated by neural activity? The authors present convincing evidence that muscone stimulus selectively enhances the neurogenesis of OSNs expressing muscone receptors, suggesting that the selection of ORs in regenerating neurons is not random.

Strengths

This study is the first in formulating and systematically testing the selective promotion hypothesis. It is a comprehensive and systematic examination of multiple musk receptors under conditions of unilateral naris occlusion and various stimuli. The controls are properly done. The quality of in situ hybridization and immunofluorescent staining is high, allowing the authors to effectively estimates the number of OR types. The data convincingly demonstrate that increased expression of musk receptors in response to male odor or muscone stimulation.

Weaknesses

The revised version has addressed most initial weaknesses. However, some inconsistencies remain, raising questions about the proposed model. For instance, in the unilateral naris occlusion experiment, although average expression of non-musk receptors shows no significant change, receptors seem to fall into two groups with one subset increasing and another decreasing (Fig. 1E). This suggests naris occlusion may regulate OR expression independently of odor-induced activity, a possibility that remains unaddressed.

There is curiosity regarding receptors for the male odor SBT, olfr912, and olfr1295, which exhibit increased expression on the occluded side. The explanation that SBT exposure shortens these neurons' lifespan lacks substantiation and is inconsistent with later data. For example, Figure 3-figure supplement 3 I does not show olfr912 changes on the UNO side, and Figure 4-figure supplement 4 shows no significant decrease in olfr912 expression in SBT-exposed mice. Additionally, single-cell RNASeq experiments did not examine olfr912 and olfr1295 expression.

While the study convincingly demonstrates muscone's selective stimulation of olfr235-expressing OSNs, it lacks exploration of the mechanisms underlying this specificity. The discussion of signaling pathways remains too generic.

In summary, while the study offers significant insights into neurogenesis and OR subtype enrichment, further investigation into underlying mechanisms and addressing existing inconsistencies would strengthen its conclusions.

for - 3 types of psychological separation / othering - definition - multi-scale biotic compositional separation - individual multi-cellular human psychologically separated from individual living cells within the same human's body - definition - social separation - individual human psychologically separated from other individual humans - definition - biotic / abiotic separation - individual human psychologically separated from the environment

Reviewer #3 (Public review):

Summary:

Cholecystokinin (CCK) is highly expressed in auditory thalamocortical (MGB) neurons and CCK has been found to shape cortical plasticity dynamics. In order to understand how CCK shapes synaptic plasticity in the auditory thalamocortical pathway, they assessed the role of CCK signaling across multiple mechanisms of LTP induction with the auditory thalamocortical (MGB - layer IV Auditory Cortex) circuit in mice. In these physiology experiments that leverage multiple mechanisms of LTP induction and a rigorous manipulation of CCK and CCK-dependent signaling, they establish an essential role of auditory thalamocortical LTP on the co-release of CCK from auditory thalamic neurons. By carefully assessing the development of this plasticity over time and CCK expression, they go on to identify a window of time that CCK is produced throughout early and middle adulthood in auditory thalamocortical neurons to establish a window for plasticity from 3 weeks to 1.5 years in mice, with limited LTP occurring outside of this window. The authors go on to show that CCK signaling and its effect on LTP in the auditory cortex is also capable of modifying frequency discrimination accuracy in an auditory PPI task. In evaluating the impact of CCK on modulating PPI task performance, it also seems that in mice <1.5 years old CCK-dependent effects on cortical plasticity is almost saturated. While exogenous CCK can modestly improve discrimination of only very similar tones, exogenous focal delivery of CCK in older mice can significantly improve learning in a PPI task to bring their discrimination ability in line with those from young adult mice.

Strengths:

(1) The clarity of the results, along with the rigor multi-angled approach, provide significant support for the claim that CCK is essential for auditory thalamocortical synaptic LTP. This approach uses a combination of electrical, acoustic, and optogenetic pathway stimulation alongside conditional expression approaches, germline knockout, viral RNA downregulation and pharmacological blockade. Through the combination of these experimental configures the authors demonstrate that high-frequency stimulation-induced LTP is reliant on co-release of CCK from glutamatergic MGB terminals projecting to the auditory cortex.

(2) The careful analysis of the CCK, CCKB receptor, and LTP expression is also a strength that puts the finding into the context of mechanistic causes and potential therapies for age-dependent sensory/auditory processing changes. Similarly, not only do these data identify a fundamental biological mechanism, but they also provide support for the idea that exogenous asynchronous stimulation of the CCKBR is capable of restoring an age-dependent loss in plasticity.

(3) Although experiments to simultaneously relate LTP and behavioral change or identify a causal relationship between LTP and frequency discrimination are not made, there is still convincing evidence that CCK signaling in the auditory cortex (known to determine synaptic LTP) is important for auditory processing/frequency discrimination. These experiments are key for establishing the relevance of this mechanism.

Weaknesses:

(1) Given the magnitude of the evoked responses, one expects that pyramidal neurons in layer IV are primarily those that undergo CCK-dependent plasticity, but the degree to which PV-interneurons and pyramidal neurons participate in this process differently is unclear.

(2) While these data support an important role for CCK in synaptic LTP in the auditory thalamocortical pathway, perhaps temporal processing of acoustic stimuli is as or more important than frequency discrimination. Given the enhanced responsivity of the system, it is unclear whether this mechanism would improve or reduce the fidelity of temporal processing in this circuit. Understanding this dynamic may also require consideration of cell type as raised in weakness #1.

(3) In Figure 1, an example of increased spontaneous and evoked firing activity of single neurons after HFS is provided. Yet it is surprising that the group data are analyzed only for the fEPSP. It seems that single neuron data would also be useful at this point to provide insight into how CCK and HFS affect temporal processing and spontaneous activity/excitability, especially given the example in 1F.

(4) The circuitry that determines PPI requires multiple brain areas, including the auditory cortex. Given the complicated dynamics of this process, it may be helpful to consider what, if anything, is known specifically about how layer IV synaptic plasticity in the auditory cortex may shape this behavior.

Comments on revisions:

The manuscript is much improved and many of the issues or questions have been addressed. Ideally, evidence for the degree of transsynaptic spread for AAV9-Syn-ChrimsonR-tdTomato would also be provided in some form since in the authors' response in sounds like some was observed, as expected.

DOI: 10.1038/s41467-025-58821-3

Resource: None

Curator: @dhovakimyan1

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

What is this?

Reviewer #3 (Public review):

Summary:

In this paper, the authors present an unsupervised learning approach to represent C. elegans poses and temporal sequences of poses in low-dimensional spaces by directly using pixel values from video frames. The method does not rely on the exact identification of the worm's contour/midline, nor on the identification of the head and tail prior to analyzing behavioral parameters. In particular, using contrastive learning, the model represents worm poses in low-dimensional spaces, while a transformer encoder neural network embeds sequences of worm postures over short time scales. The study evaluates this newly developed method using a dataset of different C. elegans genetic strains and aging individuals. The authors compared the representations inferred by the unsupervised learning with features extracted by an established approach, which relies on direct identification of the worm's posture and its head-tail direction.

Strengths:

The newly developed method provides a coarse classification of C. elegans posture types in a low-dimensional space using a relatively simple approach that directly analyzes video frames. The authors demonstrate that representations of postures or movements of different genotypes, based on pixel values, can be distinguishable to some extent.

Weaknesses:

- A significant disadvantage of the presented method is that it does not include the direction of the worm's body (e.g., head/tail identification). This highly limits the detailed and comprehensive identification of the worm's behavioral repertoire (on- and off-food), which requires body directionality in order to infer behaviors (for example, classifying forward vs. reverse movements). In addition, including a mix of opposite postures as input to the new method may create significant classification artifacts in the low-dimensional representation-such that, for example, curvature at opposite parts of the body could cluster together. This concern applies both to the representation of individual postures and to the representation of sequences of postures.<br /> - The authors state that head-tail direction can be inferred during forward movement. This is true when individuals are measured off-food, where they are highly likely to move forward. However, when animals are grown on food, head-tail identification can also be based on quantifying the speed of the two ends of the worm (the head shows side-to-side movements). This does not require identifying morphological features. See, for example, Harel et al. (2024) or Yemini et al. (2013).<br /> - Another confounding parameter that cannot be distinguished using the presented method is the size of individuals. Size can differ between genotypes, as well as with aging. This can potentially lead to clustering of individuals based on their size rather than behavior.<br /> - There is no quantitative comparison between classification based on the presented method and methods that rely on identifying the skeleton.

Reviewer #3 (Public review):

Summary:

This work revises the autoregressive surrogate (AR-surrogate) method proposed in 2022 by Brookshire to estimate the oscillatory content of behavioural time series. The main issue raised by Brookshire was the inadequacy of methods used in a series of papers that rely on shuffling the time axis of the behavioural data. Brookshire argued that while this approach tests for temporal structures, it does not differentiate between 1/f activity and true oscillatory signals. The AR-surrogate, on the other hand, removes aperiodic activity and should therefore provide a more accurate representation of oscillatory behaviour.

In this well-written paper, Harris and Beale clearly describe an improvement to Brookshire's method, which has been called into question for its low sensitivity.

Strengths:

The starting point of this work is that oscillatory patterns should be tested at the individual participant level rather than at the group level. This is critical because anyone working with behavioural data will know that averaging across participants generates distorted time series. Averaging also assumes phase consistency across participants, which may not always be valid.

Once freed from this limitation, the results presented here are exciting and convincingly demonstrate a significant improvement over the original implementation.

The authors have devised a series of tests that systematically assess the effects of participant and trial number, and effect size on the accuracy of AR-surrogate results. This is particularly useful, as it may guide researchers in designing appropriate behavioural experiments.

Weaknesses:

The method proposed here is undoubtedly an improvement on the original. However, its biggest limitation is the restriction on the frequencies that can be investigated. This is acknowledged by the authors, who rightly point out that there is still room for improvement. Another issue is that modulation depths below 10-15% may be difficult to detect.

Reviewer #3 (Public review):

Summary:

This study investigates how various behavioral features are represented in the medial prefrontal cortex (mPFC) of rats engaged in a naturalistic foraging task. The authors recorded electrophysiological responses of individual neurons as animals transitioned between navigation, reward consumption, avoidance, and escape behaviors. Employing a range of computational and statistical methods, including artificial neural networks, dimensionality reduction, hierarchical clustering, and Bayesian classifiers, the authors sought to predict from neural activity distinct task variables (such as distance from the reward zone and the success or failure of avoidance behavior). The findings suggest that mPFC neurons alternate between at least two distinct functional modes, namely spatial encoding and threat evaluation, contingent on the specific location.

Strengths:

This study attempt to address an important question: understanding the role of mPFC across multiple dynamic behaviors. The authors highlight the diverse roles attributed to mPFC in previous literature and seek to explain this apparent heterogeneity. They designed an ethologically relevant foraging task that facilitated the examination of complex dynamic behavior, collecting comprehensive behavioral and neural data. The analyses conducted are both sound and rigorous.

Weaknesses:

Because the study still lacks experimental manipulation, the findings remain correlational. The authors have appropriately tempered their claims regarding the functional role of the mPFC in the task. The nature of the switch between functional modes encoding distinct task variables (i.e., distance to reward, and threat-avoidance behavior type) is not established. Moreover, the evidence presented to dissociate movement from these task variables is not fully convincing, particularly without single-session video analysis of movement. Specifically, while the new analyses in Figure 7 are informative, they may not fully account for all potential confounding variables arising from changes in context or behavior.

Reviewer #3 (Public review):

In this revised manuscript, the authors provide convincing data to support an elegant model in which ribosome stalling by ToiL promotes downstream topAI translation and prevents premature Rho-dependent transcription termination. However, the physiological consequences of activating topAI-yjhQP expression upon exposure to various ribosome-targeting antibiotics remain unresolved. The authors have satisfactorily addressed all major concerns raised by the reviewers, particularly regarding the SHAPE-seq data. Overall, this study underscores the diversity of regulatory ribosome-stalling peptides in nature, highlighting ToiL's uniqueness in sensing multiple antibiotics and offering significant insights into bacterial gene regulation coordinated by transcription and translation.

Reviewer #3 (Public review):

Summary:

In this study by Haley et al, the authors investigated explore-exploit foraging using C. elegans as a model system. Through an elegant set of patchy environment assays, the authors built a GLM based on past experience that predicts whether an animal will decide to stay on a patch to feed and exploit that resource, instead of choosing to leave and explore other patches.

Strengths:

I really enjoyed reading this paper. The experiments are simple and elegant, and address fundamental questions of foraging theory in a well-defined system. The experimental design is thoroughly vetted, and the authors provide a considerable volume of data to prove their points. My only criticisms have to do with the data interpretation, which I think are easily addressable.

Weaknesses:

History-dependence of the GLM

The logistic GLM seems like a logical way to model a binary choice, and I think the parameters you chose are certainly important. However, the framing of them seem odd to me. I do not doubt the animals are assessing the current state of the patch with an assessment of past experience; that makes perfect logical sense. However, it seems odd to reduce past experience to the categories of recently exploited patch, recently encountered patch, and time since last exploitation. This implies the animals have some way of discriminating these past patch experiences and committing them to memory. Also, it seems logical that the time on these patches, not just their density, should also matter, just as the time without food matters. Time is inherent to memory. This model also imposes a prior categorization in trying to distinguish between sensed vs. not-sensed patches, which I criticized earlier. Only "sensed" patches are used in the model, but it is questionable whether worms genuinely do not "sense" these patches.

It seems more likely that the worm simply has some memory of chemosensation and relative satiety, both of which increase on patches and decrease while off of patches. The magnitudes are likely a function of patch density. That being said, I leave it up to the reader to decide how best to interpret the data.

osm-6

The argument is that osm-6 animals can't sense food very well, so when they sense it, they enter the exploitation state by default. That is what they appear to do, but why? Clearly they are sensing the food in some other way, correct? Are ciliated neurons the only way worms can sense food? Don't they also actively pump on food, and can therefore sense the food entering their pharynx? I think you could provide further insight by commenting on this. Perhaps your decision model is dependent on comparing environmental sensing with pharyngeal sensing? Food intake certainly influences their decision, no? Perhaps food intake triggers exploitation behavior, which can be over-run by chemo/mechanosensory information?

Impact:

I think this work will have a solid impact on the field, as it provides tangible variables to test how animals assess their environment and decide to exploit resources. I think the strength of this research could be strengthened by a reassessment of their model that would both simplify it and provide testable timescales of satiety/starvation memory.

Reviewer #3 (Public review):

In this manuscript, Wu et al. investigate active H3K27ac and H3K4me1 marks in term pregnant nonlabor myometrial biopsies, linking putative enhancers and super enhancers to gene expression levels. Through their findings, they reveal the PGR-dependent regulation of the PLCL2 gene in human myometrial cells via a cis-acting element located 35-kilobases upstream of the PLCL2 gene. By targeting this region using a CRISPR activation system, they were able to increase the elevate the endogenous PLCL2 mRNA levels in immortalized human myometrial cells.

This research offers novel insights into the molecular mechanisms governing gene expression in myometrial tissues, advancing our understanding of pregnancy-related processes.

Major comments:

(1) A more comprehensive analysis of the epigenetic and transcriptomic data would have strengthened the paper, moving beyond basic association studies. Currently, it is challenging to assess the quality and significance of the data as much of the information is lacking.

Strengths:

- The combination of ChIP-Seq, RNA-Seq, and CRISPRa Perturb-Seq approaches to investigate gene regulation and expression in myometrial cells.<br /> - The use of CRISPR activation system to specifically target cis-acting elements.

Weaknesses:

- The manuscript would strongly benefit from a deeper analysis of the Omic datasets. Furthermore, expanding figures/graphs to effectively contextualize these datasets would be greatly beneficial and would add more value to this research.<br /> - Limited sample size, coupled with variability in results and overall lack of details, compromises the robustness of result interpretation.<br /> - Additional efforts are needed to dissect the proposed regulatory mechanisms.<br /> - While the discussion provided helpful context for understanding some of the experiments performed, it lacked interpretation of the results in relation to the existing literature.

Comments on revisions:

The authors have improved the manuscript by enhancing its readability and organization. Tables were added to present key information more clearly, and figures were refined for better visualization. Additionally, more details were included, particularly in the methods and bioinformatics analyses sections, ensuring a more comprehensive and precise presentation of the data.

However, in many cases, reviewers' questions and concerns were addressed in the response to reviewers rather than incorporated into the manuscript, or it was noted that these points would be explored in future studies.

Reviewer #3 (Public review):

Concerning the revised manuscript, the authors are to be commended for carefully addressing the reviewers' comments and updating the references cited.

I will differ with the authors' argument that Gardner et al's paper supports the idea of sequences, except in the most trivial sense, namely that topology implies continuity, and hence movement along the manifold will be continuous, and if one discretizes this movement, one would get a sequence.

This has very little to do with the idea that the authors propose in their manuscript. If the authors were to so choose, their idea will produce an embedded graph, and they could study the topology of this construct---but this would mean going off on a tangent.

Let us not hold up the authors to an impossible standard, namely that their theory should explain everything in the grid cell field. Not every finding under the sun needs be addressed in the discussion.

My own take on the manuscript had been that the authors' interesting idea might be fairly straightforwardly provable. The authors have decided to put another student on this particular project. That is perfectly OK. Just one final note: mathematically, the main focus ought to be on sequences of prime length (many other results will likely follow).

Reviewer #2 (Public review):

Summary:

In this paper, the authors seek to disentangle brain areas that encode the subjective value of individual stimuli/items (input regions) from those that accumulate those values into decision variables (integrators) for value-based choice. The authors used a novel task in which stimulus presentation was slowed down to ensure that such a dissociation was possible using fMRI despite its relatively low temporal resolution. In addition, the authors leveraged the fact that gaze increases item value, providing a means of distinguishing brain regions that encode decision variables from those that encode other quantities such as conflict or time-on-task. The authors adopt a region-of-interest approach based on an extensive previous literature and found that the ventral striatum and vmPFC correlated with the item values and not their accumulation, whereas the pre-SMA, IPS, and dlPFC correlated more strongly with their accumulation. Further analysis revealed that the pre-SMA was the only one of the three integrator regions to also exhibit gaze modulation.

Strengths:

The study uses a highly innovative design and addresses an important and timely topic. The manuscript is well-written and engaging, while the data analysis appears highly rigorous.

Weaknesses:

With 23 subjects, the study has relatively low statistical power for fMRI.

Reviewer #3 (Public review):

In this paper, the authors aimed to investigate carbamylation effects on the function of Cx43-based hemichannels. Such effects have previously been characterized for other connexins, e.g., for Cx26, which display increased hemichannel (HC) opening and closure of gap junction channels upon exposure to increased CO2 partial pressure (accompanied by increased bicarbonate to keep pH constant).<br /> The authors used HeLa cells transiently transfected with Cx43 to investigate CO2-dependent carbamylation effects on Cx43 HC function. In contrast to Cx43-based gap junction channels that are reported here to be insensitive to PCO2 alterations, they provide evidence that Cx43 HC opening is highly dependent on the PCO2 pressure in the bath solution, over a range of 20 up to 70 mmHg encompassing the physiologically normal resting level of around 40 mmHg. They furthermore identified several Cx43 residues involved in Cx43 HC sensitivity to PCO2: K105, K109, K144 & K234; mutation of 2 or more of these AAs is necessary to abolish CO2 sensitivity. The subject is interesting and the results indicate that a fraction of HCs is open at a physiological 40 mmHg PCO2, which differs from the situation under HEPES buffered solutions where HCs are mostly closed under resting conditions. The mechanism of HC opening with CO2 gassing is linked to carbamylation, and the authors pinpointed several Lys residues involved in this process.

Overall, the work is interesting as it shows that Cx43 HCs have a significant open probability under resting conditions of physiological levels of CO2 gassing, probably applicable to the brain, heart, and other Cx43 expressing organs. The paper gives a detailed account of various experiments performed (dye uptake, electrophysiology, ATP release to assess HC function) and results concluded from those. They further consider many candidate carbamylation sites by mutating them to negatively charged Glu residues. The paper ends with hippocampal slice work showing evidence for connexin-dependent increases of the EPSP amplitude that could be inhibited by HC inhibition with Gap26 (Figure 10). Another line of evidence comes from the Cx43-linked ODDD genetic disease, whereby L90V as well as the A44V mutations of Cx43 prevented the CO2-induced hemichannel opening response (Figure 11). Although the paper is interesting, in its present state, it suffers from (i) a problematic Figure 3, precluding interpretation of the data shown, and (ii) the poor use of hemichannel inhibitors that are necessary to strengthen the evidence in the crucial experiment of Figure 2 and others.

Reviewer #3 (Public review):

This important study investigates the impact of nutrient stress in the tumor microenvironment (TME), focusing on lipid metabolism in pancreatic ductal adenocarcinoma (PDAC).

Understanding TME composition is crucial, as it highlights cancer vulnerabilities independent of intracellular mutations, particularly because PDAC tumors are often exposed to limited nutrient availability due to reduced perfusion.

By utilizing a medium that mimics the nutrient conditions of PDAC tumors, the authors convincingly show that TME nutrient stress suppresses SREBP1, leading to reduced lipid synthesis, with low arginine levels identified as a key driver of this suppression. Importantly, mice with arginine-starved pancreatic tumors respond to a polyunsaturated fatty acid-rich diet. This discovery uncovers a synthetic lethal interaction in the tumor microenvironment that could be leveraged through dietary interventions.

The conclusions of this paper are mostly well supported by data; however, below are some aspects that could be further clarified.

This study uses PDAC cells from the LSL-Kras G12D/+ ; Trp53 ; Pdx-1-Cre PDAC model. The authors convincingly demonstrate that the cell-extrinsic stimuli of low arginine availability suppress lipid synthesis and thus exert a dominant effect over the cell-intrinsic oncogenic Ras mutation, which is known to enhance fatty acid synthesis. Could the effect of low arginine on lipid synthesis be specific for certain mutations in PDAC? It would be interesting to investigate or discuss whether different mutations show the same SREBP1 reduction caused by low arginine levels, and whether these low SREBP1 levels can be ameliorated by arginine re-supplementation. Here, Jonker et al. show that human PDAC cells cultured in TIFM have reduced SREBP1 levels (Figure 1 - Figure supplement 1C). It would be further supportive of their conclusions if the authors could show that arginine re-supplementation is sufficient to restore SREBP1 levels in human PDAC cells.

The authors demonstrate that mPDAC cells cultured in RPMI and subsequently implanted into an orthotopic mouse model exhibit reduced expression of SREBP target genes when compared to in vitro cultured mPDAC-RPMI cells. This finding is in line with the observation that culturing PDAC cells in TIFM downregulates SREBP target genes compared to PDAC cells cultured in RPMI. However, caution is needed when directly comparing mPDAC-RPMI cultured cells to those in the orthotopic model, as the latter may include non-tumor cells and additional factors that could confound the results. The authors should explicitly acknowledge this limitation in their study.

The in vivo evidence demonstrating that PUFA-rich tung oil reduces tumor size is compelling. However, the specific in vitro findings regarding its impact on doubling rates per day, particularly in the context of arginine-dependent PUFA supplementation, require further explanation. To enhance the robustness of their data and conclusions, the authors could consider conducting additional cell viability and proliferation assays. Moreover, it would be valuable to assess whether the observed effects on doubling rates per day remain significant after normalizing the data to the initial doubling time prior to PUFA supplementation. This is in particular important regarding the statement that "Addition of arginine significantly decreases sensitivity to a-ESA" as these cells already start with a higher doubling rate prior to a-ESA treatment.

Overall, this paper presents a compelling study that significantly enhances our understanding of the PDAC tumor microenvironment and its complex interactions with the tumor lipid metabolism.

Reviewer #3 (Public review):

Summary:

This important study relies on a rare dataset: intracranial recordings within the thalamus and the subthalamic nucleus in awake humans, while they were performing a tactile detection task. This procedure allowed the authors to identify a small but significant proportion of individual neurons, in both structures, whose activity correlated with the task (e.g. their firing rate changed following the audio cue signalling the start of a trial) and/or with the stimulus presentation (change in firing rate around 200 ms following tactile stimulation) and/or with participant's reported subjective perception of the stimulus (difference between hits and misses around 200 ms following tactile stimulation). Whereas most studies interested in the neural underpinnings of conscious perception focus on cortical areas, these results suggest that subcortical structures might also play a role in conscious perception, notably tactile detection.

Strengths:

There are two strongly valuable aspects in this study that make the evidence convincing and even compelling. First, these type of data are exceptional, the authors could have access to subcortical recordings in awake and behaving humans during surgery. Additionally, the methods are solid. The behavioral study meets the best standards of the domain, with a careful calibration of the stimulation levels (staircase) to maintain them around detection threshold, and additional selection of time intervals where the behavior was stable. The authors also checked that stimulus intensity was the same on average for hits and misses within these selected periods, which warrants that the effects of detection that are observed here are not confounded by stimulus intensity. The neural data analysis is also very sound and well conducted. The statistical approach complies to current best practices, although I found that, on some instances, it was not entirely clear which type of permutations had been performed, and I would advocate for more clarity in these instances. Globally, the figures are nice, clear and well presented. I appreciated the fact that the precise anatomical location of the neurons was directly shown in each figure.

Weaknesses:

The results rely on a small number of neurons; it is only the beginning of this exploration! Figure S5 is important for observing the variety of ways the neurons' activity correlated with either stimulus presence, or perception, or both. Interpretations are still very open on these different profiles.

Reviewer #3 (Public review):

Summary:

In this manuscript, Rademacher and colleagues examined the effect on the integrity of the dopamine system in mice of chronically stimulating dopamine neurons using a chemogenetic approach. They find that one to two weeks of constant exposure to the chemogenetic activator CNO leads to a decrease in the density of tyrosine hydroxylase staining in striatal brain sections and to a small reduction of the global population of tyrosine hydroxylase positive neurons in the ventral midbrain. They also report alterations in gene expression in both regions using a spatial transcriptomics approach. Globally, the work is well done and valuable and some of the conclusions are interesting. However, the conceptual advance is perhaps a bit limited in the sense that there is extensive previous work in the literature showing that excessive depolarization of multiple types of neurons associated with intracellular calcium elevations promotes neuronal degeneration. The present work adds to this by showing evidence of a similar phenomenon in dopamine neurons. In terms of the mechanisms explaining the neuronal loss observed after 2 to 4 weeks of chemogenetic activation, it would be important to consider that dopamine neurons are known from a lot of previous literature to undergo a decrease in firing through a depolarization-block mechanism when chronically depolarized. Is it possible that such a phenomenon explains much of the results observed in the present study? It would be important to consider this in the manuscript. The relevance to Parkinson's disease (PD) is also not totally clear because there is not a lot of previous solid evidence showing that the firing of dopamine neurons is increased in PD, either in human subjects or in mouse models of the disease.

Comments on revisions:

The authors have done a good job at revising the manuscript. The revised manuscript better frames the results in the context of previous literature.

Reviewer #3 (Public Review):

Summary:

In this manuscript, Rademacher and colleagues examined the effect on the integrity of the dopamine system in mice of chronically stimulating dopamine neurons using a chemogenetic approach. They find that one to two weeks of constant exposure to the chemogenetic activator CNO leads to a decrease in the density of tyrosine hydroxylase staining in striatal brain sections and to a small reduction of the global population of tyrosine hydroxylase positive neurons in the ventral midbrain. They also report alterations in gene expression in both regions using a spatial transcriptomics approach. Globally, the work is well done and valuable and some of the conclusions are interesting. However, the conceptual advance is perhaps a bit limited in the sense that there is extensive previous work in the literature showing that excessive depolarization of multiple types of neurons associated with intracellular calcium elevations promotes neuronal degeneration. The present work adds to this by showing evidence of a similar phenomenon in dopamine neurons. In terms of the mechanisms explaining the neuronal loss observed after 2 to 4 weeks of chemogenetic activation, it would be important to consider that dopamine neurons are known from a lot of previous literature to undergo a decrease in firing through a depolarization-block mechanism when chronically depolarized. Is it possible that such a phenomenon explains much of the results observed in the present study? It would be important to consider this in the manuscript. The relevance to Parkinson's disease (PD) is also not totally clear because there is not a lot of previous solid evidence showing that the firing of dopamine neurons is increased in PD, either in human subjects or in mouse models of the disease. As such, it is not clear if the present work is really modelling something that could happen in PD in humans.

Comments on the introduction:

The introduction cites a 1990 paper from the lab of Anthony Grace as support of the fact that DA neurons increase their firing rate in PD models. However, in this 1990 paper, the authors stated that: "With respect to DA cell activity, depletions of up to 96% of striatal DA did not result in substantial alterations in the proportion of DA neurons active, their mean firing rate, or their firing pattern. Increases in these parameters only occurred when striatal DA depletions exceeded 96%." Such results argue that an increase in firing rate is most likely to be a consequence of the almost complete loss of dopamine neurons rather than an initial driver of neuronal loss. The present introduction would thus benefit from being revised to clarify the overriding hypothesis and rationale in relation to PD and better represent the findings of the paper by Hollerman and Grace.

It would be good that the introduction refers to some of the literature on the links between excessive neuronal activity, calcium, and neurodegeneration. There is a large literature on this and referring to it would help frame the work and its novelty in a broader context.

Comments on the results section:

The running wheel results of Figure 1 suggest that the CNO treatment caused a brief increase in running on the first day after which there was a strong decrease during the subsequent days in the active phase. This observation is also in line with the appearance of a depolarization block.

The authors examined many basic electrophysiological parameters of recorded dopamine neurons in acute brain slices. However, it is surprising that they did not report the resting membrane potential, or the input resistance. It would be important that this be added because these two parameters provide key information on the basal excitability of the recorded neurons. They would also allow us to obtain insight into the possibility that the neurons are chronically depolarized and thus in depolarization block.

It is great that the authors quantified not only TH levels but also the levels of mCherry, co-expressed with the chemogenetic receptor. This could in principle help to distinguish between TH downregulation and true loss of dopamine neuron cell bodies. However, the approach used here has a major caveat in that the number of mCherry-positive dopamine neurons depends on the proportion of dopamine neurons that were infected and expressed the DREADD and this could very well vary between different mice. It is very unlikely that the virus injection allowed to infect 100% of the neurons in the VTA and SNc. This could for example explain in part the mismatch between the number of VTA dopamine neurons counted in panel 2G when comparing TH and mCherry counts. Also, I see that the mCherry counts were not provided at the 2-week time point. If the mCherry had been expressed genetically by crossing the DAT-Cre mice with a floxed fluorescent reported mice, the interpretation would have been simpler. In this context, I am not convinced of the benefit of the mCherry quantifications. The authors should consider either removing these results from the final manuscript or discussing this important limitation.

Although the authors conclude that there is a global decrease in the number of dopamine neurons after 4 weeks of CNO treatment, the post-hoc tests failed to confirm that the decrease in dopamine number was significant in the SNc, the region most relevant to Parkinson's. This could be due to the fact that only a small number of mice were tested. A "n" of just 4 or 5 mice is very small for a stereological counting experiment. As such, this experiment was clearly underpowered at the statistical level. Also, the choice of the image used to illustrate this in panel 2G should be reconsidered: the image suggests that a very large loss of dopamine neurons occurred in the SNc and this is not what the numbers show. A more representative image should be used.

In Figure 3, the authors attempt to compare intracellular calcium levels in dopamine neurons using GCaMP6 fluorescence. Because this calcium indicator is not quantitative (unlike ratiometric sensors such as Fura2), it is usually used to quantify relative changes in intracellular calcium. The present use of this probe to compare absolute values is unusual and the validity of this approach is unclear. This limitation needs to be discussed. The authors also need to refer in the text to the difference between panels D and E of this figure. It is surprising that the fluctuations in calcium levels were not quantified. I guess the hypothesis was that there should be more or larger fluctuations in the mice treated with CNO if the CNO treatment led to increased firing. This needs to be clarified.

Although the spatial transcriptomic results are intriguing and certainly a great way to start thinking about how the CNO treatment could lead to the loss of dopamine neurons, the presented results, the focussing of some broad classes of differentially expressed genes and on some specific examples, do not really suggest any clear mechanism of neurodegeneration. It would perhaps be useful for the authors to use the obtained data to validate that a state of chronic depolarization was indeed induced by the chronic CNO treatment. Were genes classically linked to increased activity like cfos or bdnf elevated in the SNc or VTA dopamine neurons? In the striatum, the authors report that the levels of DARP32, a gene whose levels are linked to dopamine levels, are unchanged. Does this mean that there were no major changes in dopamine levels in the striatum of these mice?

The usefulness of comparing the transcriptome of human PD SNc or VTA sections to that of the present mouse model should be better explained. In the human tissues, the transcriptome reflects the state of the tissue many years after extensive loss of dopamine neurons. It is expected that there will be few if any SNc neurons left in such sections. In comparison, the mice after 7 days of CNO treatment do not appear to have lost any dopamine neurons. As such, how can the two extremely different conditions be reasonably compared?

Comments on the discussion:

In the discussion, the authors state that their calcium photometry results support a central role of calcium in activity-induced neurodegeneration. This conclusion, although plausible because of the very broad pre-existing literature linking calcium elevation (such as in excitotoxicity) to neuronal loss, should be toned down a bit as no causal relationship was established in the experiments that were carried out in the present study.

In the discussion, the authors discuss some of the parallel changes in gene expression detected in the mouse model and in the human tissues. Because few if any dopamine neurons are expected to remain in the SNc of the human tissues used, this sort of comparison has important conceptual limitations and these need to be clearly addressed.

A major limitation of the present discussion is that it does not discuss the possibility that the observed phenotypes are caused by the induction of a chronic state of depolarization block by the chronic CNO treatment. I encourage the authors to consider and discuss this hypothesis. Also, the authors need to discuss the fact that previous work was only able to detect an increase in the firing rate of dopamine neurons after more than 95% loss of dopamine neurons. As such, the authors need to clearly discuss the relevance of the present model to PD. Are changes in firing rate a driver of neuronal loss in PD, as the authors try to make the case here, or are such changes only a secondary consequence of extensive neuronal loss (for example because a major loss of dopamine would lead to reduced D2 autoreceptor activation in the remaining neurons, and to reduced autoreceptor-mediated negative feedback on firing). This needs to be discussed.

There is a very large, multi-decade literature on calcium elevation and its effects on neuronal loss in many different types of neurons. The authors should discuss their findings in this context and refer to some of this previous work. In a nutshell, the observations of the present manuscript could be summarized by stating that the chronic membrane depolarization induced by the CNO treatment is likely to induce a chronic elevation of intracellular calcium and this is then likely to activate some of the well-known calcium-dependent cell death mechanisms. Whether such cell death is linked in any way to PD is not really demonstrated by the present results.

The authors are encouraged to perform a thorough revision of the discussion to address all of these issues, discuss the major limitations of the present model, and refer to the broad pre-existing literature linking membrane depolarization, calcium, and neuronal loss in many neuronal cell types.

Reviewer #3 (Public review):

Summary:

This manuscript investigates at behavioral and mechanistic levels the recovery of zebra finch song production after a genetically targeted insult to HVC, a vocal premotor nucleus known to generate stereotyped neural sequences that drive the correspondingly stereotyped song. This study is a close follow up to past work, published in Nature Neuroscience last year (Wang et al, 2024), in which custom lentiviruses were used to deliver a persistently active sodium channel, NacBAC or TeNT to block synaptic release, specifically to the excitatory projection neurons in HVC. In this past work, these manipulations resulted in rapid degradation of song, followed by a slow recovery that, remarkably, did not require practice. Song recovery was associated with synaptic remodeling that appeared to homeostatically bring the affected neurons back to a normal firing regime. This past paper was important because it clearly demonstrated behaviorally and mechanistically how neural plasticity can restore a learned behavior without practice, showing that dominant reinforcement learning models of birdsong are not the full story.

This past work sets the context for the current paper, which instead targets the inhibitory neuronal population in HVC for silencing via viral-mediated expression of TeNT. Again, this sophisticated targeting of HVC interneurons resulted in rapid degradation of song, followed by a much slower but seemingly full recovery.

Strengths:

Overall, this paper has several strengths. First, it provides yet another convincing example of non-canonical vocal learning in the zebra finch because LMAN (a nucleus required for trial and error song learning) is not required for song recovery. Second, its targeting of interneurons clarifies the extent to which inhibition in HVC is essential for vocal patterning (not surprising but important to show). Third, by using RNAseq of HVC at the time of peak song disruption, it zeroes in on specific genetic/cellular activations associated with a lack of inhibition (e.g., microglial activation and MHC1 expression), opening up new avenues for future study. Using in vivo electrophysiology it also characterizes some gross circuit-level abnormalities in HVC-RA transmission and during sleep.

Weaknesses:

Yet the paper also has several areas for improvement, primarily:

Main issues

(1) Narrative-level confusion, a mix of results, many hanging threads

The arc of this paper is very hard to follow, new experiments arise without a clear setup or connection to past ones. Concepts jump around unpredictably. The reading experience would be dramatically improved if there were a clear single line of logic going through the entire paper, which could be accomplished by inserting a paragraph at the end of the intro section that walks the reader step-by-step through what they are going to see. I don't recommend this for all papers - but this paper requires it, in my opinion, because we have such an unusual combination of experimental approaches, outcomes, and data formats (behavior, RNA seq, targeted tests of microglial activation in the setting of adult impairment and song development, electrophysiology during sleep. It's very difficult for me to tie this all together into a crisp narrative that sticks with me days after reading the paper. Instead, it feels like some disconnected factoids. Examples:<br /> a) Characterization of degradation and slow recovery (much slower than targeting of projection neurons form past work (Wang et al, 2024).<br /> b) Activation of microglia and MHC1 during the degraded period; microglia return to normal at recovery.<br /> c) Developmenta profile of microglia expression.<br /> e) Sleep replay in HVC is perturbed during the degraded state. Mostly returns to normal following recovery, but *some* aspects are still abnormal.<br /> f) Detailed ephys analysis of HVC excitability and RA suppression, invoking ideas that HVC drives RA inhibition.<br /> g) LMAN lesions do not block degradation or recovery.

There are at least three threads of this paper - it therefore reads like three different papers stitched together into one - united only by the method of HVC interneuron targeting. In my view, a pretty major overhaul is required, even if it means cutting out specific details and figures that distract from the paper's message (for example there is a whole sub-section analyzing HVC impact on RA that vaguely invokes ideas of HVC engagement of RA

(2) Interpretation of microglia is confusing and unresolved

Microglia activation is measured at peak song disruption, and returns to normal following recovery. To test if this phenomenon is associated with learning or degradation, the authors measure microglia during development.

"The increased inhibitory tone in HVC and the number of microglia could induce synaptic changes that contribute to degraded song production. Alternatively, the rise in microglia could be part of the recovery response to produce synaptic changes needed to regain the song following perturbation."

This is a great if/then statement on how to interpret the microglial activation at the core of the paper. But it remains unresolved. Is there a causal experiment that could distinguish these possibilities?

(3) The quantification of song dynamics during the recovery process in LMAN lesioned birds is required to support claims. Perhaps the most interesting claim of the paper - that recovery happens without LMAN, is not sufficiently supported by data analyses. This is a major problem.

The same analysis used in the LMAN-intact degradation/recovery dataset should be used for the LMAN dataset. At present, there are no quantification, only example spectrograms. Also, Supplementary Figure 4 and Supplementary Figure 5 are identical, suggesting a lack of proofreading in this part of the manuscript. For example the reader cannot even ascertain if the key aspect of song degradation - the production of exceedingly long syllables - is occurring in the LMAN lesioned animals.

Reviewer #3 (Public review):

Summary:

The authors compare how well their automatic dimension prediction approach (DimPred) can support similarity judgements and compare it to more standard RSA approaches. The authors show that the DimPred approach does better when assessing out-of-sample heterogeneous image sets, but worse for out-of-sample homogeneous image sets. DimPred also does better at predicting brain-behaviour correspondences compared to an alternative approach. The work appears to be well done, but I'm left unsure what conclusions the authors are drawing.

In the abstract, the authors write: "Together, our results demonstrate that current neural networks carry information sufficient for capturing broadly-sampled similarity scores, offering a pathway towards the automated collection of similarity scores for natural images". If that is the main claim, then they have done a reasonable job supporting this conclusion. However the importance of automating this process for broadly-sampled object categories is not made so clear.

But the authors also highlight the importance that similarity judgements have been for theories of cognition and brain, such as in the first paragraph of the paper they write: "Similarity judgments allow us to improve our understanding of a variety of cognitive processes, including object recognition, categorization, decision making, and semantic memory6-13. In addition, they offer a convenient means for relating mental representations to representations in the human brain14,15 and other domains16,17". The fact that the authors also assess how well a CLIP model using DimPred can predict brain activation suggests that their work is not just about automating similarity judgements, but highlighting how their approach reveals that ANNs are more similar to brains than previously assessed.

My main concern is with regards to the claim that DimPred is revealing better similarities between ANNs and brains (a claim that the authors may not be making, but this should be clarified). The fact that predictions are poor for homogenous images is problematic for this claim, and I expect their DimPred scores would be very poor under many conditions, such as when applied to line drawings of objects, or a variety of addition out-of-sample stimuli that are easily identified by humans. The fact that so many different models get such similar prediction scores (Fig 3) also raises questions as to the inferences you can make about ANN-brain similarity based on the results. Do the authors want to claim that CLIP models are more like brains?

With regards to the brain prediction results, why is the DimPred approach doing so much better in V1? I would not think the 49 interpretable categories are encoded in V1, and the ability to predict would likely reflect a confound rather than V1 encoding these categories (e.g., if a category was "things that are burning" then DNN might predict V1 activation based on the encoding of colour).

In addition, more information is needed on the baseline model, as it is hard to appreciate whether we should be impressed by the better performance of DimPred based on what is provided: "As a baseline, we fit a voxel encoding model of all 49 dimensions. Since dimension scores were available only for one image per category36, for the baseline model, we used the same value for each image of the same category and estimated predictive performance using cross-validation". Is it surprising that predictions are not good with one image per category? Is this a reasonable comparison?

Relatedly, what was the ability of the baseline model to predict? (I don't think that information was provided). Did the authors attempt to predict outside the visual brain areas? What would it mean if predictions were still better there?

Minor points:

The authors write: "Please note that, for simplicity, we refer to the similarity matrix derived from this embedding as "ground-truth", even though this is only a predicted similarity". Given this, it does not seem a good idea to use "ground truth" as this clarification will be lost in future work citing this article.

It would be good to have the 49 interpretable dimensions listed in the supplemental materials rather than having to go to the original paper.

Strengths:

The experiments seem well done.

Weaknesses:

It is not clear what claims are being made.

Reviewer #3 (Public review):

Summary:

Cruz and colleagues report a single-cell RNA sequencing analysis of irradiated Drosophila larval wing discs. This is a pioneering study because prior analyses used bulk RNAseq analysis, so differences at single-cell resolution were not discernible. To quantify heterogeneity in gene expression, the authors make clever use of a metric used to study market concentration, the Herfindahl-Hirschman Index. They make several important observations, including region-specific gene expression coupled with heterogeneity within each region and the identification of a cell population (high Trbl) that seems disproportionately responsible for radiation-induced gene expression.

Strengths:

Overall, the manuscript makes a compelling case for heterogeneity in gene expression changes that occur in response to uniform induction of damage by X-rays in a single-layer epithelium. This is an important finding that would be of interest to researchers in the field of DNA damage responses, regeneration, and development.

Weaknesses:

This work would be more useful to the field if the authors could provide a more comprehensive discussion of both the impact and the limitations of their findings, as explained below.

Propidium iodide staining was used as a quality control step to exclude cells with a compromised cell membrane. But this would exclude dead/dying cells that result from irradiation. What fraction of the total do these cells represent? Based on the literature, including works cited by the authors, up to 85% of cells die at 4000R, but this likely happens over a longer period than 4 hours after irradiation. Even if only half of the 85% are PI-positive by 4 hr, this still removes about 40% of the cell population from analysis. The remaining cells that manage to stay alive (excluding PI) at 4 hours and included in the analysis may or may not be representative of the whole disc. More relevant time points that anticipate apoptosis at 4 hr may be 2 hr after irradiation, at which time pro-apoptotic gene expression peaks (Wichmann 2006). Can the authors rule out the possibility that there is heterogeneity in apoptosis gene expression, but cells with higher expression are dead by 4 hours, and what is left behind (and analyzed in this study) may be the ones with more uniform, lower expression? I am not asking the authors to redo the study with a shorter time point, but to incorporate the known schedule of events into their data interpretation.

If cluster 3 is G1/S, cluster 5 is late S/G2, and cluster 4 is G2/M, what are clusters 0, 1, and 2 that collectively account for more than half of the cells in the wing disc? Are the proportions of clusters 3, 4, and 5 in agreement with prior studies that used FACS to quantify wing disc cells according to cell cycle stage?

The EdU data in Figure 1 is very interesting, especially the persistence in the hinge. The authors speculate that this may be due to cells staying in S phase or performing a higher level of repair-related DNA synthesis. If so, wouldn't you expect 'High PCNA' cells to overlap with the hinge clusters in Figures 6G-G'? Again, no new experiments are needed. Just a more thorough discussion of the data.

Trbl/G2/M cluster shows Ets21C induction, while the pattern of Ets21C induction as detected by HCR in Figures 5H-I appears in localized clusters. I thought G2/M cells are not spatially confined. Are Ets21C+ cells in Figure 5 in G2/M? Can the overlap be confirmed, for example, by co-staining for Trbl or a G2/M marker with Ets21C?

Induction of dysf in some but not all discs is interesting. What were the proportions? Any possibility of a sex-linked induction that can be addressed by separating male and female larvae?

Reviewer #3 (Public review):

Summary:

This paper presents a timely and significant contribution to the study of lysine acetoacetylation (Kacac). The authors successfully demonstrate a novel and practical chemo-immunological method using the reducing reagent NaBH4 to transform Kacac into lysine β-hydroxybutyrylation (Kbhb).

Strengths:

This innovative approach enables simultaneous investigation of Kacac and Kbhb, showcasing their potential in advancing our understanding of post-translational modifications and their roles in cellular metabolism and disease.

Weaknesses:

The paper's main weaknesses are the lack of SDS-PAGE analysis to confirm HATs purity and loading consistency, and the absence of cellular validation for the in vitro findings through knockdown experiments. These gaps weaken the evidence supporting the conclusions.

Olympia Typewriter Spacers 3D printed with TPU Filament by [[Subham Kumar]]

https://www.thingiverse.com/thing:7009800

Reviewer #3 (Public review):

Summary:

In the manuscript entitled "Convergent evolution of epigenome recruited DNA repair across the Tree of Life", Monroe et al. investigate bioinformatically how some important mechanisms of epigenome-targeted DNA repair evolved at the tree of life scale. They provide a clear example of convergent evolution of these mechanisms between animals and plants, investigating more than 4000 eukaryotic genomes, and uncovering a significant association between gain/retention of such mechanisms with genome size and high intron content, that at least partially explains the evolutionary patterns observed within major eukaryotic lineages.

Strengths:

The manuscript is well written, clear, and understandable, and has potentially broad interest. It provides a thorough analysis of the evolution of MSH6-related DNA repair mechanisms using more than 4000 eukaryotic genomes, a pretty impressive number allowing to identify both large-scale (i.e. kingdoms) as well as shorter-scale (i.e. phyla, orders) evolutionary patterns. Moreover, despite providing no experimental validation, it investigates with a sufficient degree of depth, a potential relationship between gain/retention of epigenome recruited DNA repair mediated by MSH6 and genomic, as well as life-history (population size, body mass, lifespan), traits. In particular, it provides convincing evidence for a causative effect between genome size/intron content and the presence/absence of this mechanism. Moreover, it stimulates further scientific investigation and biological questions to be addressed, such as the conservation of epigenomes across the tree of life, the existence of potential trade-offs in gain/retention vs. loss of such mechanisms, and the relationship between these processes, mutation rate heterogeneity, and evolvability.

Weaknesses:

Despite the interesting and necessary insights provided on (1) the evolution of DNA repair mechanisms, and (2) the convergent evolution of molecular mechanisms, this bioinformatic study emanates from studies in humans and Arabidopsis already showing signs of potential convergent evolution in aspects of epigenome-recruited DNA repair. For this, this study, although bioinformatically remarkably thorough, does not come as a surprise, potentially lowering its novelty.

What could have increased further its impact, interest, and novelty could have been a more comprehensive understanding of the causative processes leading to gain/retention vs. loss of MSH6-related epigenetic recruitment mechanisms. The authors provide interesting associations with life-history traits (yet not significant), and significant links with genome size and intron content only at the theoretical level. For the first aspect, the analyses could have expanded toward other life-history traits. For the second, maybe it could have been even possible to tackle experimentally some of the generated questions, functionally in some models, or deepened using specific case studies.

Reviewer #3 (Public review):

Summary:

The authors investigated the impact of an auditory stimulus on visual integration at the behavioral, electrophysiological, and mechanistic levels. Although the role of alpha brain oscillations on visual perception has been widely studied, how the brain dynamics in the visual cortices are influenced by a cross-modal stimulus remains ill-defined. The authors demonstrated that auditory stimulation systematically induced a drop in visual alpha frequency, increasing the time window for audio-visual integration, while in the unimodal condition, visual integration was modulated by small variations within the alpha frequency range. In addition, they only found a role of the phase of alpha brain oscillations on visual perception in the cross-modal condition. Based on the perceptual cycles' theory framework, the authors developed a model allowing them to describe their results according to a phase resetting induced by the auditory stimulation. These results showed that the influence of well-known brain dynamics on one modality can be disrupted by another modality. They provided insights into the importance of investigating cross-modal brain dynamics, and an interesting model that extends the perceptual cycle framework.

Strengths:

The results are supported by a combination of various, established experimental and analysis approaches (e.g., two-flash fusion task, psychometric curves, phase opposition), ensuring strong methodological bases and allowing direct comparisons with related findings in the literature.

The model the authors proposed is an extension and an improvement of the perceptual cycle's framework. Interestingly, this model could then be tested in other experimental approaches.

Weaknesses:

There is an increasing number of studies in cognitive neuroscience showing the importance of considering inter-individual variability. The individual alpha frequency (IAF) varied from 8 to 13 Hz with a huge variability across participants, and studies have shown that the IAF influenced visual perception. Investigating inter-individual variations of the IAF in the reported results would be of great interest, especially for the model.

Although the use of non-invasive brain stimulation to infer causality is a method of great interest, the use of tACS in the presented work is not optimal. Instead of inducing alpha brain oscillations in visual cortices, the use of tACS to activate the auditory cortex instead of the actual auditory stimulation would have presented more interest.

Reviewer #3 (Public review):

Summary:

The study by Schönmann et al. presents compelling analyses based on two MEG datasets, offering strong evidence that the pre-onset response observed in a highly influential study (Goldstein et al., 2022) can be attributed to stimulus dependencies, specifically, the auto-correlation in the stimuli-rather than to predictive processing in the brain. Given that both the pre-onset response and the encoding model are central to the landmark study, and that similar approaches have been adopted in several influential works, this manuscript is likely to be of high interest to the field. Overall, this study encourages more cautious interpretation of pre-onset responses in neural data, and the paper is well written and clearly structured.

Strengths:

(1) The authors provide clear and convincing evidence that inherent dependencies in word embeddings can lead to pre-activation of upcoming words, previously interpreted as neural predictive processing in many influential studies.

(2) They demonstrate that dependencies across representational domains (word embeddings and acoustic features) can explain the pre-onset response, and that these effects are not eliminated by regressing out neighboring word embeddings - an approach used in prior work.

(3) The study is based on two large MEG datasets, showing that results previously observed in ECoG data can be replicated in MEG. Moreover, the stimulus dependencies appear to be consistent across the two datasets.

Weaknesses:

(1) To allow a more direct comparison with Goldstein et al., the authors could consider using their publicly available dataset.

(2) Goldstein et al. already addressed embedding dependencies and showed that their main results hold after regressing out the embedding dependencies. This may lessen the impact of the concerns about self-dependency raised here.

(3) While this study shows that stimulus dependency can account for pre-onset responses, it remains unclear whether this fully explains them, or whether predictive processing still plays a role. The more important question is whether pre-activation remains after accounting for these confounds.

Reviewer #3 (Public review):

Summary:

This study examines semantic processing in the visual cortex of both congenitally blind and sighted individuals using fMRI and multivariate pattern analysis (MVPA). The key finding is that the visual cortex in both groups encodes the physical properties of word referents, rather than their conceptual similarities. These results suggest that the same representational mechanisms operate in both the blind and sighted brain.

Strengths:

(1) The findings contribute to a broader understanding of cortical reorganization and provide evidence for top-down processing of word referents, even in the absence of visual experience.

(2) The experiment incorporates both spoken and written word presentations (Braille for blind participants), ensuring that the results are not confounded by modality effects.

(3) The study employs a rigorous methodological approach, combining multivariate and univariate analyses to strengthen the validity of its findings.

(4) The paper is well-structured and clearly written, making it easy to follow.

Weaknesses:

(1) The word stimuli consists of only 20 nouns referring to concrete entities. However, in the behavioral experiment, participants rated the physical and conceptual similarity of only 30 word pairs, which represents just a subset of all possible word pair combinations. The average similarity ratings across subjects were then used to construct stimuli similarity matrices, which were correlated with the fMRI similarity matrices in the MVPA analysis. What is the rationale for presenting only a small subset of all possible word pair combinations to participants? Additionally, the instruction to rate the "conceptual similarity" of word pairs seems somewhat ambiguous. Would "conceptual similarity" correlate with "physical similarity"? Instead of subjective ratings, why not use cosine similarity scores from pretrained language models to construct the "conceptual similarity" matrices? This approach could provide a more objective and reproducible measure of conceptual similarity.

(2) There are only six questions each for assessing the physical and conceptual properties of the words in the fMRI experiment. Most of the physical property questions focus on shape-related attributes (e.g., round, angular, elongated, symmetrical), while the conceptual properties are limited to three pairs of antonyms (living/non-living, natural/manufactured, pleasant/unpleasant). These aspects seem insufficient to comprehensively characterize the physical and conceptual properties of the nouns. What was the rationale behind selecting only these six questions? Could this limited set of attributes introduce bias in how the neural representations in the visual cortex are interpreted?

(3) Two of the blind participants are right-handed, and two may have some form of contour vision. What was the rationale for including these participants? In addition, the sample size for blind participants is relatively small (N = 20). Does the sample size provide sufficient justification for the main conclusion that the visual cortex in both blind and sighted groups represents the physical properties of word referents? Additionally, could individual differences among blind participants impact the results, and were any analyses conducted to account for such variability?

(4) I appreciate the authors' effort to integrate both univariate and multivariate approaches in their analyses. However, the results appear somewhat contradictory: The MVPA results suggest similar neural representations of word referents in the visual cortex for both blind and sighted participants. However, the univariate analyses indicate higher activation in the visual cortex of blind participants. How can these two findings be reconciled? The authors attributed the increased activation in the visual cortex of blind participants to their "enhanced excitability", but what exactly does "excitability" mean in this context? Could this increased activation instead reflect an alternative neural strategy for processing semantic information in the blind brain? If so, how does this align with the claim that similar representational mechanisms exist in both blind and sighted individuals?

(5) The authors interpret their findings to suggest that the visual cortex can represent the physical properties of words even without visual experience, attributing this to top-down modulation from higher cognitive regions, which then backprojects to the visual cortex. However, it is unclear why only physical properties, and not conceptual properties, are backprojected. If higher cognitive regions modulate the visual cortex in a top-down manner, wouldn't both physical and conceptual attributes be expected to influence its activity? Could the authors clarify the mechanism that selectively supports physical property encoding over conceptual representation?

Reviewer #3 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

Comments on revisions:

I thank the authors for carefully addressing my suggestion to the original submission and congratulate them on their work.

Reviewer #3 (Public review):

Summary:

The authors have investigated the myelination pattern along the axons of chick avian cochlear nucleus. It has already been shown that there are regional differences in the internodal length of axons in the nucleus magnocellularis. In the tract region across the midline, internodes are longer than in the nucleus laminaris region. Here the authors suggest that the difference in internodal length is attributed to heterogeneity of oligodendrocytes. In the tract region oligodendrocytes would contribute longer myelin internodes, while oligodendrocytes in the nucleus laminaris region would synthesize shorter myelin internodes. Not only length of myelin internodes differs, but also along the same axon unmyelinated areas between two internodes may vary. This is an interesting contribution since all these differences contribute to differential conduction velocity regulating ipsilateral and contralateral innervation of coincidence detector neurons. However, the demonstration falls rather short of being convincing.

Major comments:

(1) The authors neglect the possibility that nodal cluster may be formed prior to myelin deposition. They have investigated stages E12 (no nodal clusters) and E15 (nodal cluster plus MAG+ myelin). Fig. 1D is of dubious quality. It would be important to investigate stages between E12 and E15 to observe the formation of pre-nodes, i.e., clustering of nodal components prior to myelin deposition.

(2) The claim that axonal diameter is constant along the axonal length need to be demonstrated at the EM level. This would also allow to measure possible regional differences in the thickness of the myelin sheath and number of myelin wraps.

(3) The observation that internodal length differs is explain by heterogeneity of sources of oligodendrocyte is not convincing. Oligodendrocytes a priori from the same origin remyelinate shorter internode after a demyelination event.

Significance:

The authors suggest that the difference in internodal length is attributed to heterogeneity of oligodendrocytes. In the tract region oligodendrocytes would contribute longer myelin internodes, while oligodendrocytes in the nucleus laminaris region would synthesize shorter myelin internodes. Not only length of myelin internodes differs, but also along the same axon unmyelinated areas between two internodes may vary. This is an interesting contribution since all these differences contribute to differential conduction velocity regulating ipsilateral and contralateral innervation of coincidence detector neurons.