Reviewer #2 (Public review):

The yeast double-stranded RNA endonuclease Rnt1, a homolog of bacterial RNAse III, mediates the processing of pre-rRNA, pre-snRNA, and pre-snoRNA molecules. Cells lacking Rnt1 exhibit pronounced growth defects, particularly at lower temperatures. In this manuscript, Notice-Sarpaning examines whether these growth defects can be attributed at least in part to a function of Rnt1 in mRNA degradation. To test this, the authors apply parallel analysis of RNA ends (PARE), which they developed in previous work, to identify polyA+ fragments with 5' monophosphates in RNT1 yeast that are absent in rnt1Δ cells. Because such RNAs are substrates for 5' to 3' exonucleolytic decay by Rat1 in the nucleus or Xrn1 in the cytoplasm, these analyses were performed in a rat1-ts xrn1Δ background. The data recapitulate known Rtn1 cleavage sites in rRNA, snRNAs, and snoRNAs, and identify 122 putative novel substrates, approximately half of which are mRNAs. Of these, two-thirds are predicted to contain double-stranded stem loop structures with A/UGNN tetraloops, which serve as a major determinant of Rnt1 substrate recognition. Rtn1 resides in the nucleus, and it likely cleaves mRNAs there, but cleavage products seem to be degraded after export to the cytoplasm, as analysis of published PARE data shows that some of them accumulate in xrn1Δ cells. The authors then leverage the slow growth of rnt1Δ cells for experimental evolution. Sequencing analysis of thirteen faster-growing strains identifies mutations predominantly mapping to genes encoding nuclear exosome co-factors. Some of the strains have mutations in genes encoding a larat-debranching enzyme, a ribosomal protein nuclear import factor, poly(A) polymerase 1, and the RNA-binding protein Puf4. In one of the puf4 mutant strains, a second mutation is also present in YDR514C, which the authors identify as an mRNA substrate cleaved by Rnt1. Deletion of either puf4 or ydr514C marginally improves the growth of rnt1Δ cells, which the authors interpret as evidence that mRNA cleavage by Rnt1 plays a role in maintaining cellular homeostasis by controlling mRNA turnover.

While the PARE data and their subsequent in vitro validation convincingly demonstrate Rnt1-mediated cleavage of a small subset of yeast mRNAs, the data supporting the biological significance of these cleavage events is substantially less compelling. This makes it difficult to establish whether Rnt1-mediated mRNA cleavage is biologically meaningful or simply "collateral damage" due to a coincidental presence of its target motif in these transcripts.

(1) A major argument in support of the claim that "several mRNAs rely heavily on Rnt1 for turnover" comes from comparing number of PARE reads at the transcript start site (as a proxy for fraction of decapped transcripts) and at the Rnt1 cleavage site (as a proxy for fraction of Rnt1-cleaved transcripts). The argument for this is that "the major mRNA degradation pathway is through decapping". However, polyA tail shortening usually precedes decapping, and transcripts with short polyA tails would be strongly underrepresented in PARE sequencing libraries, which were constructed after two rounds of polyA+ RNA selection. This will likely underestimate the fraction of decapped transcripts for each mRNA. There is a wide range of well-established methods that can be used to directly measure differences in the half-life of Rnt1 mRNA targets in RNT1 vs rnt1Δ cells. Because the PARE data rely on the presence of a 5' phosphate to generate sequencing reads, they also cannot be used to estimate what fraction of a given mRNA transcript is actually cleaved by Rnt1.

(2) Rnt1 is almost exclusively nuclear, and the authors make a compelling case that its concentration in the cytoplasm would likely be too low to result in mRNA cleavage. The model for Rnt1-mediated mRNA turnover would therefore require mRNAs to be cleaved prior to their nuclear export in a manner that would be difficult to control. Alternatively, the Rnt1 targets would need to re-enter prior to cleavage, followed by export of the cleaved fragments for cytoplasmic decay. These processes would need to be able to compete with canonical 5' to 3' and 3' to 5' exonucleolytic decay to influence mRNA fate in a biologically meaningful way.

(3) The experimental evolution clearly demonstrates that mutations in nuclear exosome factors are the most frequent suppressors of the growth defects caused by Rnt1 loss. This can be rationalized by stabilization of nuclear exosome substrates such as misprocessed snRNAs or snoRNAs, which are the major targets of Rnt1. The rescue mutations in other pathways linked to ribosomal proteins (splicing, ribosomal protein import, ribosomal mRNA binding) support this interpretation. By contrast, the potential suppressor mutation in YDR514C does not occur on its own but only in combination with a puf4 mutation; it is also unclear whether it is located within the Rnt1 cleavage motif or if it impacts Rnt1 cleavage at all. This can easily be tested by engineering the mutation into the endogenous YDR514C locus with CRISPR/Cas9 or expressing wild-type and mutant YDR514C from a plasmid, along with assaying for Rnt1 cleavage by northern blot. Notably, the growth defect complementation of YDR514C deletion in rnt1Δ cells is substantially less pronounced than the growth advantage afforded by nuclear exosome mutations (Figure S9, evolved strains 1 to 5). These data rather argue for a primary role of Rnt1 in promoting cell growth by ensuring efficient ribosome biogenesis through pre-snRNA/pre-snoRNA processing.

Reviewer #2 (Public review):

Summary:

This paper measures associations between RNA transcript levels and important reproductive traits in the model organism C. elegans. The authors go beyond determining which gene expression differences underlie reproductive traits, but also (1) build a model that predicts these traits based on gene expression and (2) perform experiments to confirm that some transcript levels indeed affect reproductive traits. The clever study design allows the authors to determine which transcript levels impact reproductive traits, and also which transcriptional differences are driven by stochastic vs environmental differences. In sum, this is a rather comprehensive study that highlights the power of gene expression as a driver of phenotype, and also teases apart the various factors that affect the expression levels of important genes.

Strengths:

Overall, this study has many strengths, is very clearly communicated, and has no substantial weaknesses that I can point to. One question that emerges for me is about the extent to which these findings apply broadly. In other words, I wonder whether gene expression levels are predictive of other phenotypes in other organisms. I think this question has largely been explored in microbes, where some studies (PMID: 17959824) but not others (PMID: 38895328) find that differences in gene expression are predictive of phenotypes like growth rate. Microbes are not the primary focus here, and instead, the discussion is mainly focused on using gene expression to predict health and disease phenotypes in humans. This feels a little complicated since humans have so many different tissues. Perhaps an area where this approach might be useful is in examining infectious single-cell populations (bacteria, tumors, fungi). But I suppose this idea might still work in humans, assuming the authors are thinking about targeting specific tissues for RNAseq.

In sum, this is a great paper that really got me thinking about the predictive power of gene expression and where/when it could inform about (health-related) phenotypes.

Reviewer #2 (Public review):

Summary:

In this paper, the authors used MEFs expressing the R1441G mutant of leucine-rich repeat kinase 2 (LRRK2), a mutant associated with the early onset of Parkinson's disease. They report that in these cells LAMP2 fluorescence is higher but BMP fluorescence is lower, MVE size is reduced, and that MVEs contain less ILVs. They also report that LAMP2-positive EVs are increased in mutant cells in a process sensitive to LRRK2 kinase inhibition but are further increased by glucocerebrosidase (GCase) inhibition, and that total di-22:6-BMP and total di-18:1-BMP are increased in mutant LRRK2 MEFs compared to WT cells by mass spectrometry. They also report that LRRK2 kinase inhibition partially restores cellular BMP levels, and that GCase inhibition further increases BMP levels, and that in EVs from the LRRK2 mutant, LRRK2 inhibition decreases BMP while GCase inhibition has the opposite effect. Moreover, they report that the BMP increase is not due to increased BMP synthesis, although the authors observe that CLN5 is increased in LRRK2 mutant cells. Finally, they report that GW4869 decreases EV release and exosomal BMP, while bafilomycin A1 increases EV release. They conclude that LRRK2 regulates BMP levels (in cells) and release (via EVs). They also conclude that the process is modulated by GCase in LRRK2 mutant cells, and that these studies may contribute to the use of BMP-positive EVs as a biomarker for Parkinson's disease and associated treatments.

Strengths:

This is an interesting paper, which provides novel insights into the biogenesis of exosomes with exciting biomedical potential. However, I have comments that authors need to address to clarify some aspects of their study.

Weaknesses:

(1) The intensity of LAMP2 staining is increased significantly in cells expressing the R1441G mutant of LRRK2 when compared to WT cells (Figure 1C). Yet mutant cells contain significantly smaller MVEs with fewer ILVs, and the MVE surface area is reduced (Figure 1D-F). This is quite surprising since LAMP2 is a major component of the limiting membrane of late endosomes. Are other proteins of endo-lysosomes (eg, LAMP1, CD63, RAB7) or markers (lysotracker) also decreased (see also below)?

(2) LRRK2 has been reported to interact with endolysosomal membranes. Does the R1441G mutant bind LAMP2- and/or BMP-positive membranes? Does the mutant affect endolysosomes?

(3) Immunofluorescence data indicate that BMP is decreased in mutant LRRK2-expressing cells compared to WT (Figure 1A-B), but mass spec data indicate that di-22:6-BMP and di-18:1-BMP are increased (Figure 3). Authors conclude that the BMP pool detected by mass spec in mutant cells is less antibody-accessible than that present in wt cells, or that the anti-BMP antibody is less specific and that it detects other analytes. This is an awkward conclusion, since the IF signal with the antibody is lower (not higher): why would the antibody be less specific? Could it be that the antibody does not see all BMP isoforms equally well? Moreover, the observations that mutant cells contain smaller MVEs (Figure 1D-F) with fewer ILVs are consistent with the IF data and reduced BMP amounts. This needs to be clarified.

Mass spectrometry data are only shown for two BMP species (di-22:6, di-18:1). What are the major BMP isoforms in WT cells? The authors should show the complete analysis for all BMP species if they wish to draw quantitative conclusions about the amounts of BMP in wt and mutant cells. Finally, BMP and PG are isobaric lipids. Fragmentation of BMPs or PGs results in characteristic fingerprints, but the presence of each daughter ion is not absolutely specific for either lipid. This should be clarified, e.g., were BMP and PG separated before mass spec analysis? Was PG affected? The authors should also compare the BMP data with mass spec data obtained with a control lipid, e.g., PC.

(4) It is quite surprising that the amounts of labeled BMP continue to increase for up to 24h after a short 25min pulse with heavy BMP precursors (Figure 4B).

(5) It is argued that upregulation of CLN5 may be due to an overall upregulation of lysosomal enzymes, as LAMP2 levels were also increased (Figure 2A, C, E). Again, this is not consistent with the observed decrease in MVE size and number (Figure 1D-F). As mentioned above, other independent markers of endo-lysosomes should be analyzed (eg, LAMP1, CD63, RAB7), and/or other lysosomal enzymes (e.g. cathepsin. D).

(6) The authors report that the increase in BMP is not due to an increase in BMP synthesis (Figure 4), although they observe a significant increase in CLN5 (Figure 5A) in LRRK2 mutant cells. Some clarification is needed.

(7) Authors observe that both LAMP2 and BMP are decreased in EVs by GW4869 and increased by bafilomycin (Figure 6). Given my comments above on Figure 1, it would also be nice to illustrate/quantify the effects of these compounds on cells by immunofluorescence.

Reviewer #3 (Public review):

Summary:

This study examines the metabolic regulation of progenitor proliferation and differentiation in the developing retina. The authors observe dynamic changes in glycolytic gene expression in retinal progenitors and use various strategies to test the role of glycolysis. They find that elevated glycolysis in Pten-cKO retinas results in alteration of RPC fate, while inhibition of glycolysis has converse effects. They specifically test the role of elevated glycolysis using dominant active cytoPFKB3, which demonstrates the selective effects of elevated glycolysis on progenitor proliferation and rod differentiation. They then show that elevated glycolysis modulates both pHi and Wnt signaling, and provide evidence that these pathways impact proliferation and differentiation of progenitors, particularly affecting rod photoreceptor differentiation.

Strengths:

This is a compelling and rigorous study that provides an important advance in our understanding of metabolic regulation of retina development, addressing a major gap in knowledge. A key strength is that the study utilizes multiple genetic and pharmacological approaches to address how both increased or decreased glycolytic flux affect retinal progenitor proliferation and differentiation. They discover elevated Wnt signaling pathway genes in Pten cKO retina, revealing a potential link between glycolysis and Wnt pathway activation. Altogether the study is comprehensive and adds to the growing body of evidence that regulation of glycolysis plays a key role in tissue development.

Weaknesses:

(1) Following expression of cytoPFKB3, which results in increased glycolytic flux, BrDU labeling was performed at e12.5 and increased labeled cells were detected in the outer nuclear layer. But whether these are cones or rods is not established. The rest of the analysis is focused on the precocious maturation of rhodopsin-labelled outer segments, and the major conclusions emphasize rod photoreceptor differentiation. Therefore it is unclear whether there is an effect on cone differentiation for either Pten cKO or cytoPFKB3 transgenic retina. It is also not established whether rods are born precociously. Presumably this would be best detected by BrDU labeling at later embryonic stages.

(2) The authors find that there is upregulation of multiple Wnt pathway components in Pten cKO retina. They further show that inhibiting Wnt signaling phenocopies the effects of reducing glycolysis. However, they do not test whether pharmacological inhibition of Wnt signaling reverses the effects of high glycolytic activity in Pten cKO retinas. Thus the argument that Wnt is a key downstream effector pathway regulating rod photoreceptor differentiation is weak.

(3) The use of sodium acetate to force protein acetylation is quite non-specific and will have effects beyond beta-catenin acetylation (which the authors acknowledge). Thus it is a stretch to state that "forced activation of beta-catenin acetylation" mimics the impact of Pten<br /> loss/high glycolytic activity in RPCs since the effects could be due to acetylation of other proteins.

Reviewer #2 (Public review):

Summary:

Homologous recombination (HR) is a critical pathway for repairing double-strand DNA breaks and ensuring genomic stability. At the core of HR is the RAD51-mediated strand-exchange process, in which the RAD51-ssDNA filament binds to homologous double-stranded DNA (dsDNA) to form a characteristic D-loop structure. While decades of biochemical, genetic, and single-molecule studies have elucidated many aspects of this mechanism, the atomic-level details of the strand-exchange process remained unresolved due to a lack of atomic-resolution structure of RAD51 D-loop complex.<br /> In this study, the authors achieved this by reconstituting a RAD51 mini-filament, allowing them to solve the RAD51 D-loop complex at 2.64 Å resolution using a single particle approach. The atomic resolution structure reveals how specific residues of RAD51 facilitate the strand exchange reaction. Ultimately, this work provides unprecedented structural insight into the eukaryotic HR process and deepens the understanding of RAD51 function at the atomic level, advancing the broader knowledge of DNA repair mechanisms.

Strengths:

The authors overcame the challenge of RAD51's helical symmetry by designing a minifilament system suitable for single-particle cryo-EM, enabling them to resolve the RAD51 D-loop structure at 2.64 Å without imposed symmetry. This high resolution revealed precise roles of key residues, including F279 in Loop 2, which facilitates strand separation, and basic residues on site II that capture the displaced strand. Their findings were supported by mutagenesis, strand exchange assays, and single-molecule analysis, providing strong validation of the structural insights.

Weaknesses:

Despite the detailed structural data, some structure-based mutagenesis data interpretation lacks clarity. Additionally, the proposed 3′-to-5′ polarity of strand exchange relies on assumptions from static structural features, such as stronger binding of the 5′-arm-which are not directly supported by other experiments. This makes the directional model compelling but contradicts several well-established biochemical studies that support a 5'-to-3' polarity relative to the complementary strand (e.g., Cell 1995, PMID: 7634335; JBC 1996, PMID: 8910403; Nature 2008, PMID: 18256600).

Overall:

The 2.6 Å resolution cryoEM structure of the RAD51 D-loop complex provides remarkably detailed insights into the residues involved in D-loop formation. The high-quality cryoEM density enables precise placement of each nucleotide, which is essential for interpreting the molecular interactions between RAD51 and DNA. Particularly, the structural analysis highlights specific roles for key domains, such as the N-terminal domain (NTD), in engaging the donor DNA duplex.

This structural interpretation is further substantiated by single-molecule fluorescence experiments using the KK39,40AA NTD mutant. The data clearly show a significant reduction in D-loop formation by the mutant compared to wild-type, supporting the proposed functional role of the NTD observed in the cryoEM model.

However, the strand exchange activity interpretation presented in Figure 5B could benefit from a more rigorous experimental design. The current assay measures an increase in fluorescence intensity, which depends heavily on the formation of RAD51-ssDNA filaments. As shown in Figure S6A, several mutants exhibit reduced ability to form such filaments, which could confound the interpretation of strand exchange efficiency. To address this, the assay should either: (1) normalize for equivalent levels of RAD51-ssDNA filaments across samples, or (2) compare the initial rates of fluorescence increase (i.e., the slope of the reaction curve), rather than endpoint fluorescence, to better isolate the strand exchange activity itself.

Based on the structural features of the D-loop, the authors propose that strand pairing and exchange initiate at the 3'-end of the complementary strand in the donor DNA and proceed with a 3'-to-5' polarity. This conclusion, drawn from static structural observations, contrasts with several well-established biochemical studies that support a 5'-to-3' polarity relative to the complementary strand (e.g., Cell 1995, PMID: 7634335; JBC 1996, PMID: 8910403; Nature 2008, PMID: 18256600). While the structural model is compelling and methodologically robust, this discrepancy underscores the need for further experiments.

Reviewer #2 (Public review):

Summary:

This study reports on the existence of subpopulations of isogenic E. coli and P. aeruginosa cells that are tolerant to the antimicrobial peptide tachyplesin and are characterized by accumulation of low levels of a fluorescent tachyplesin-NBD conjugate. The authors then set out to address the molecular mechanisms, providing interesting insights even though the mechanism remains incompletely defined: The work demonstrates that increased efflux may cause this phenotype, putatively together with other changes in membrane lipid composition. The authors further demonstrate that pharmacological manipulation can prevent generation of tolerance. The authors are cautious in their interpretation and the claims made are largely justified by the data.

Strengths:

Going beyond the commonly used bulk techniques for studying susceptibility to AMPs , Lee et al. used of fluorescent antibiotic conjugates in combination with flow cytometry analysis to study variability in drug accumulation at the single cell level. This powerful approach enabled the authors to expose bimodal drug accumulation pattern that were condition dependent, but conserved across a variety of E. coli clinical isolates. Using cell sorting in combination with colony-forming unit assays as well as quantitative fluorescence microscopic analysis in a microfludics-setup the authors compellingly demonstrate that low accumulators (where fluorescence signal is mostly restricted to the membrane), can survive antibiotic treatment, whereas high accumulators (with high intracellular fluorescence) were killed.

The relevance of efflux for the ´low accumulator´ phenotype and its survival is convincingly demonstrated by the following lines of evidence: i) A time-course experiment on tachyplesin-NBD pre-loaded cells revealed that all cells initially were high accumulators, before a subpopulation of cells subsequently managed to reduce signal intensity, demonstrating that the ´low accumulator´ phenotype is an induced response and not a pre-existing property. Ii) Double-mutants deficient in the delta acrA delta tolC double-KO, which showed reduced levels of low accumulators´. Interestingly, ´low accumulator´populations were nearly abrogated in bacteria deficient in the qse quorum sensing system, suggesting its centrality for the tachyplesin response. Even though this system may control acrA, the strength of the phenotype may suggest that it may control additional as-of-yet unidenitified factors relevant in the response to tachyplesin. Iii) treatment with efflux pump inhibitor sertraline and verapamil (even though some caution needs to be taken since it is not perfectly selective, see weakness) prevents generation of low accumulators. The observation that sertraline enhances tachyplesin-based killing is an important basis for developing combination therapies.

The study convincingly illustrates how susceptibility to tachyplesin adaptively changes in a heterogeneous way dependent on the growth phases and nutrient availability. This is highly relevant also beyond the presented example of tachyplesin and similar subpopulation-based adaptive changes to the susceptibility towards antimicrobial peptides or other drugs may occur during infections in vivo and they would likely be missed by standardized in vitro susceptibility testing.

Weaknesses:

Some mechanistic questions regarding tachyplesin-accumulation and survival remain. One general shortcoming of the setup of the transcriptomics experiment is that the tachyplesin-NBD probe itself has antibiotic efficacy and induces phenotypes (and eventually cell death) in the ´high accumulator´ cells. As the authors state themselves, this makes it challenging to interpret whether any differences seen between the two groups are causative for the observed accumulation pattern of if they are a consequence of differential accumulation and downstream phenotypic effects.

I have a few minor concerns regarding new data that was added during the revision:

- The statement ´ Moreover, we found that the fluorescence of low accumulators decreased over time when bacteria were treated with 20 μg mL´ is, in my opinion, not supported by the data shown in Figure S4C. That figure shows that the abundance of ´low accumulator´ cells decreases over time. Following the rationale that protease K treatment may cleave surface-associated/extracellular tachyplesin-NDB, this should lead to a shift of ´low accumulator´population to the left, indicating reduced fluorescence intensity per cell. This is not so case, but the population just disappears. However, after 120 min of treatment more cells appear in the ´high accumulator´ state. This result is somewhat puzzling.

- The authors used the metabolic dye resazurin to measure the metabolic activity of low vs. high accumulators. I am not entirely convinced that the lower fluorescence resorufin-fluorescence in tachyplesin-NBD accumulators really indicates lower metabolic activity, since a cell's fluorescence levels would also be affected by the cellular uptake and efflux. It appears plausible that the lower resorufin-fluorescence may result from reduced accumulation/increased efflux in the´low-tachyplesin NBD´ population.

Comment on revisions: All my previous comments have been satisfactorily addressed by the authors.

Reviewer #2 (Public review):

Summary:

The authors made a thorough revision of the manuscript, strengthening the message. They also considered all the comments made by the reviewers and provided appropriate and convincing arguments.

Strengths:

The revised manuscript clarifies all the major points raised by the reviewers, and the way the information is presented (in the text, figures and tables) is clear.

Weaknesses:

The authors provided an appropriate and convincing rebuttal regarding the potential weakness I pointed out in the first review of the manuscript. Therefore, I do not see any major issue in their work.

Reviewer #2 (Public review):

Summary:

The manuscript by Nosaka et al is a comprehensive study exploring the involvement of IL1beta signaling in a 2-hit model of lung injury + ventilation, with a focus on modulation by hypothermia.

Strengths:

The authors demonstrate quite convincingly that interleukin 1 beta plays a role in the development of ventilator-induced lung injury in this model, and that this role includes the regulation of neutrophil extracellular trap formation. The authors use a variety of in vivo animal-based and in vitro cell culture work, and interventions including global gene knockout, cell-targeted knockout and pharmacological inhibition, which greatly strengthen the ability to make clear biological interpretations.

Comments on revised version:

The authors have addressed my concerns/queries.

Reviewer #3 (Public review):

Summary:

In this study, Zhang et al., reported that CHMP5 restricts bone formation by controlling endolysosome-mitochondrion-mediated cell senescence. Zhang et al., report a novel role of CHMP5 on osteogenesis through affecting cell senescence. Overall, it is an interesting study and provides new insights in the field of cells senescence and bone.

Strengths:

Analyzed the bone phenotype OF CHMP5-periskeletal progenitor-CKO mouse model and found the novel role of senescent cells on osteogenesis and migration.

Weaknesses:

(1) The role and mechanism of CHMP5 gene deletion in enhancing osteogenesis via cellular senescence remain insufficiently elucidated.

(2) The use of the ADTC5 cell line as a skeletal precursor/progenitor model is suboptimal.

Overall, the results support their conclusions.

The impact of this work on the field is its proposal that cellular senescence may exert either inhibitory or promotive effects on osteogenic capacity, depending on cell type and context.

The revised manuscript has addressed most of the concerns raised during the initial review.

Reviewer #2 (Public review):

Summary:

In this study, "Forecasting protein evolution by integrating birth-death population models with structurally constrained substitution models", David Ferreiro and co-authors present a forward-in-time evolutionary simulation framework that integrates a birth-death population model with a fitness function based on protein folding stability. By incorporating structurally constrained substitution models and estimating fitness from ΔG values using homology-modeled structures, the authors aim to capture biophysically realistic evolutionary dynamics. The approach is implemented in a new version of their open-source software, ProteinEvolver2, and is applied to four viral proteins from HIV-1 and SARS-CoV-2.

Overall, the study presents a compelling rationale for using folding stability as a constraint in evolutionary simulations and offers a novel framework and software to explore such dynamics. While the results are promising, particularly for predicting biophysical properties, the current analysis provides only partial evidence for true evolutionary forecasting, especially at the sequence level. The work offers a meaningful conceptual advance and a useful simulation tool, and sets the stage for more extensive validation in future studies.

Strengths:

The results demonstrate that fitness constraints based on protein stability can prevent the emergence of unrealistic, destabilized variants - a limitation of traditional, neutral substitution models. In particular, the predicted folding stabilities of simulated protein variants closely match those observed in real variants, suggesting that the model captures relevant biophysical constraints.

Weaknesses:

The predictive scope of the method remains limited. While the model effectively preserves folding stability, its ability to forecast specific sequence content is not well supported. Only one dataset (HIV-1 MA) is evaluated for sequence-level divergence using KL divergence; this analysis is absent for the other proteins. The authors use a consensus Omicron sequence as a representative endpoint for SARS-CoV-2, which overlooks the rich longitudinal sequence data available from GISAID. The use of just one consensus from a single time point is not fully justified, given the extensive temporal and geographical sampling available. Extending the analysis to include multiple timepoints, particularly for SARS-CoV-2, would strengthen the predictive claims. Similarly, applying the model to other well-sampled viral proteins, such as those from influenza or RSV, would broaden its relevance and test its generalizability.

It would also be informative to include a retrospective analysis of the evolution of protein stability along known historical trajectories. This would allow the authors to assess whether folding stability is indeed preserved in real-world evolution, as assumed in their model.

Finally, a discussion on the impact of structural templates - and whether the fixed template remains valid across divergent sequences - would be valuable. Addressing the possibility of structural remodeling or template switching during evolution would improve confidence in the model's applicability to more divergent evolutionary scenarios.

Reviewer #2 (Public review):

This study presents an investigation of the visual and chemical properties and mating behaviour in Morpho butterflies, aimed at addressing the nature of divergence between closely related species in sympatry. The study species consists of three subspecies of Morpho helenor (bristowi, theodorus, and helenor), and the conspecific Morpho achilles achilles. The authors postulate that whereas the iridescent blue signals of all (sub)species should function as a predator reduction signal (similar to aposematism) and therefore exhibit convergence, the same signals should indicate divergence if used as a mating signal, particularly in sympatric populations. They also assess chemical profiles among the species to assess the potential utility of scent in mediating species/sex discrimination.

The authors first used reflectance spectrometry to calculate hue, brightness, and chroma, plus two measures of "iridescence" (perhaps better phrased as angular dependence) in each (sub)species. This indicated the ubiquitous presence of sexual dimorphism in brightness (males brighter), which also appears to be the case for iridescence (Figure 3A-B). Analysis of these data also indicated that whereas there is evidence for divergence among subspecies in allopatry, the same evidence is lacking for species in sympatry (P = 0.084). This was supported further by visual modelling, which showed that both conspecifics and birds should be (theoretically) capable of perceiving the colour difference among allopatric populations of M. helenor, whereas the same is not true for the sympatric species.

The authors then conducted mate choice trials, first using live individuals and second using female dummies. The live experiments indicated the presence of assortative mating among the two subspecies of M. helenor (bristowi and theodorus). The dummy presentations indicated (a) bristowi males prefer conspecific wings, whereas theodorus have no preference, (b) bristowi males prefer the con(sub)specific colour pattern, (c) theodorus prefer the con(sub)specific iridescence when the pattern is manipulated to be similar among female dummies. A fourth experiment, using sympatric M. achilles and M. helenor, indicated no preference for conspecific female dummies. Finally, chemical analysis indicated substantial differences between these two species in putative pheromone compounds, and especially so in the males.

The authors conclude that the similarity of iridescence among species in sympatry is suggestive of convergence upon a common anti-predation signal. Despite some behavioural evidence in favour of colour (iridescence)-based mate discrimination, chemical differences between Achilles and Helenor are posed as more likely to function for species isolation than visual differences.

Overall, I enjoyed reading this manuscript, which presents a valiant attempt at studying visual, chemical and behavioural divergence in this iconic group of butterflies.

Major comments

My only major comment concerns the authors' favoured explanation for aposematism (or evasive mimicry) for convergence among species, which is based upon the you-can't-catch-me hypothesis first presented by Young 1971. Although there is supporting work showing that iridescent-like stimuli are more difficult to precisely localize by a range of viewers, most of the evidence as applied to the Morpho system is circumstantial, and I'm not certain that there is widespread acceptance of this hypothesis. Given that the present study deals with closely-related (sub)species, one alternative explanation - a "null" hypothesis of sorts - is for a lack of divergence (from a common starting point) as opposed to evolutionary convergence per se. in other words, two subspecies are likely to retain ancestral character states unless there is selection that causes them to diverge. I feel that the manuscript would benefit from a discussion of this alternative, if not others. Signalling to predators could very well be involved in constraining the extent of convergence, but this seems a little premature to state as an up-front conclusion of this work. There is also the result of a *dorsal* wing manipulation by Vieira-Silva et al. 2024 (https://doi.org/10.1111/eth.13517), which seems difficult to reconcile in light of this explanation. Whereas this paper is cited by the authors, a more nuanced discussion of their experimental results would seem appropriate here.

Reviewer #2 (Public review):

The authors extend their SPLASH framework with single-cell RNA-seq in mind, in two ways. First, they introduce "compactors", which are possible paths branching out from an anchor. Second, they introduce a workflow to classify compactors according to the type of biological sequence variation represented (splicing, SNV, etc). They focus on simulated data for fusion detection, and then focus on analyzing the Tabula sapiens Smart-seq2 data, showing extensive results on alternative splicing analysis, VDJ, and repeat elements.

This is strong work with an impressive array of biological investigations and results for a methods paper. I have various concerns about terminology and comparisons, as follows (in a somewhat arbitrary order, apologies).

(1) The discussion of the weaknesses of the consensus sequence approach of SPLASH is an odd way to motivate SPLASH+ in my opinion, in that SPLASH is not yet so widely used, so the baseline for SPLASH+ is really standard alignment-based approaches. It is fine to mention consensus sequence issues briefly, but it felt belabored.

(2) Regarding compactors reducing alignment cost: the comparison should really be between compactor construction and alignment vs read alignment (and maybe vs modern contig construction algorithms and alignment).

(3) The language around "compactors" is a bit confusing, where the authors sometimes refer to the tree of possibilities from an anchor as a "compactor", and sometimes a compactor is a single branch. Presumably, ideally, compactors should be DAGs, not trees, i.e., they can connect back together. Perhaps the authors could comment on whether this matters/would be a valuable extension.

(4) The main oddness of the splicing analysis to me is not using cell-type/state in any way in the statistical testing. This need not be discrete cell types: psiX, for example, tested whether exonic PSI was variable with reference to a continuous gene expression embedding. Intuitively, such transcriptome-wide signal should be valuable for a) improving power and b) distinguishing cell-type intrinsic/"noisy" from cell-type specific splicing variation. A straightforward way of doing this would be pseudobulking cell types. Possibly a more sophisticated hierarchical model could be constructed also.

(5) A secondary weakness is that some informative reads will not be used, for example, unspliced reads aligning to an alterantive exons. This relates to the broader weakness of SPLASH that it is blind to changes in coverage that are not linked to a specific anchor (which should be acknowledged somewhere, maybe in the Discussion). In the deeply sequenced SS2 data, this is likely not an issue, but might be more limiting in sparser data. A related issue is that coverage change indicative of, e.g., alternative TSS or TES (that do not also include a change in splice junction use) will not be detected. In fairness, all these weaknesses are shared by LeafCutter. It would be valuable to have a comparison to a more "traditional" splicing analysis approach (pick your favorite of rMATS, MISO, SUPPA).

(6) "We should note that there is no difference between gene fusions and other RNA variants (e.g., RNA splicing) from a sequence assembly viewpoint". Maybe this is true in an abstract sense, but I don't think it is in reality. AS can produce hundreds of isoforms from the same gene, and be variable across individual cells. Gene fusions are generally less numerous/varied and will be shared across clonal populations, so the complexity is lower. That simplicity is balanced against the challenge that any genes could, in principle, fuse.

(7) For the fusion detection assessment, SPLASH+ is given the correct anchor for detection. This feels like cheating since this information wouldn't usually be available. Can the authors motivate this? Are the other methods given comparable information? Also, TPM>100 seems like a very high expression threshold for the assessment.

(8) Why are only 3'UTRs considered and not 5'? Is this because the analysis is asymmetric, i.e., only considering upstream anchors and downstream variation? If so, that seems like a limitation: how much additional variation would you find if including the other direction?

(9) I don't find the theoretical results very meaningful. Assuming independent reads (equivalently binomial counts) has been repeatedly shown to be a poor assumption in sequencing data, likely due to various biases, including PCR. This has motivated the use of overdispersed distributions such as the negative Binomial and beta binomial. The theory would be valuable if it could say something at a specified level of overdispersion. If not, the caveat of assuming no overdispersion should be clearly stated.

Reviewer #2 (Public review):

Tanja Nielsen et al. present a novel strategy for the identification of candidate genes in Congenital Heart Disease (CHD). Their methodology, which is based on comprehensive experiments across cell models, Drosophila and zebrafish models, represents an innovative, refreshing and very useful set of tools for the identification of disease genes, in a field which are struggling with exactly this problem. The authors have applied their methodology to investigate the pathomechanisms of Hypoplastic Left Heart Syndrome (HLHS) - a severe and rare subphenotype in the large spectrum of CHD malformations. Their data convincingly implicates ribosomal proteins (RPs) in growth and proliferation defects of cardiomyocytes, a mechanism which is suspected to be associated with HLHS.

By whole genome sequencing analysis of a small cohort of trios (25 HLHS patients and their parents), the authors investigated a possible association between RP encoding genes and HLHS. Although the possible association between defective RPs and HLHS needs to be verified, the results suggest a novel disease mechanism in HLHS, which is a potentially substantial advance in our understanding of HLHS and CHD. The conclusions of the paper are based on solid experimental evidence from appropriate high- to medium-throughput models, while additional genetic results from an independent patient cohort are needed to verify an association between RP encoding genes and HLHS in patients.

Reviewer #2 (Public review):

Summary:

This study elucidated the impact of GATA4 on aging- and injury-induced cartilage degradation and osteoarthritis (OA) progression, based on the team's finding that GATA expression is positively correlated with aging in human chondrocytes. By integrating cell culture of human chondrocytes, gene manipulation tools (siRNA, lentivirus), biological/biochemical analyses and murine models of post-traumatic OA, the team found that increasing GATA4 levels reduced anabolism and increased catabolism of chondrocytes from young donors, likely through upregulation of the BMP pathway, and that this impact is not correlated with TGF-β stimulation. Conversely, silencing GATA4 by siRNA attenuated catabolism and elevated aggrecan/collagen II biosynthesis of chondrocytes from old donors. The physiological relevance of GATA4 was further validated by the accelerated OA progression observed in lentivirus-infected mice in the DMM model.

Strengths:

This is a highly significant and innovative study that provides new molecular insights into cartilage homeostasis and pathology in the context of aging and disease. The experiments were performed in a comprehensive and rigorous manner. The data were interpreted thoroughly in the context of the current literature.

Weaknesses:

(1) While it is convincing that GATA4 expression is elevated in elderly individuals, and that it has a detrimental impact on cartilage health, the authors might want to add further discussion on the variability among individual human donors, especially given the finding that the elevation of GATA4 was not observed in chondrocytes from donor O1 (Figure 1G).

(2) It might also be worth adding additional discussion on the interplay between senescent chondrocytes and the dysfunctional ECM during aging. As noted by the authors, aging is associated with decreased sGAG content and likely degenerative changes in the collagen II network, so the microniche of chondrocytes, and thus cell-matrix crosstalk through the pericellular matrix, is also altered or impaired.

Reviewer #1 (Public review):

Summary:

This foundational study builds on prior work from this group to reveal the complexities underlying ligand-dependent RXRγ-Nur77 heterodimer formation, offering a compelling re-evaluation of their earlier conclusions. The authors examine how a library of RXR ligands influences the biophysical, structural, and functional properties of Nur77. They find that although the Nur77-RXRγ heterodimer shares notable functional similarities with the Nurr1-RXRα complex, it also exhibits unique features, notably, both dimer dissociation and classical agonist-driven activities. This work advances our understanding of the nuanced behaviors of nuclear receptor heterodimers, which have important implications for health and disease.

Strengths:

(1) Builds on previous work by providing a comprehensive analysis that examines whether Nur77-RXRγ heterodimer formation parallels that of the Nurr1-RXRα complex.

(2) Systematic evaluation of a library of RXR ligands provides a broad survey of functional outputs.

(3) Careful reanalysis of previous work sheds new light on how NR4A heterodimers function.

Weaknesses:

(1) Some conclusions appear overstated or are not well substantiated by the work presented. It's unclear how the data support a non-classical mode of agonism, for example, based on the data shown.

(2) Some assays have relatively few replicates, with only two in some cases.

Reviewer #2 (Public review):

Summary:

In this manuscript, Pavri and colleagues examine in-depth how the local transcriptional landscape affects somatic hypermutation (SHM) of variable region genes. They use the human Burkitt lymphoma Ramos cell line as a model system to examine AID-induced SHM.

The authors delete Emu and demonstrate that the epigenetic marks at the Ig loci do not correlate with their mutability. They define algorithms to map the V gene promoters and their mutational load in Ramos cells overexpressing AID and failed to find a correlation between mutation frequency and nascent transcription or transcription strength or between mutation frequency and polII stalling. Additionally, the authors show that convergent transcription may not be a major player for SHM. The authors additionally knock-in two other human V genes into the endogenous Vh gene in Ramos cells, and again failed to observe any significant correlation between PolII stalling and SHM. The authors also observe a similar lack of correlation between SHM (at the B-18 gene) and nascent transcription features in germinal center B cells. Overall, the authors conclude that mutation patterns in V genes are not linked to transcriptional features but are rather hard-wired into the sequence. The authors propose that premature transcription termination might have a role in promoting AID recruitment and activity at Ig genes.

Strengths:

The mechanisms that allow AID recruitment to Ig genes during SHM are very poorly understood. Many mechanisms have been proposed, with most invoking transcriptional features, including stalling, convergent transcription, etc. This work, demonstrating the lack of correlation with the proposed models, is of much importance to the field. The experiments are well done, and even though the results are generally "negative", they are highly relevant to our current understanding of SHM.

Weaknesses:

The authors propose premature transcription termination as a possible mechanism to determine V gene mutability, but the study does not experimentally address such possibilities.

Comments:

(1) It would be important for the authors to compare their results in Figure S1 at the B1-8 locus with those reported several years ago by Schatz and colleagues (Odegard et al, Immunity, 2005) and discuss if the results are different from what the authors report here. This is important as the first two figures essentially corroborate previous results that the Emu enhancer is important for transcription through the V genes.

(2) The authors mention that AID recruitment is facilitated by Ig enhancers. Is endogenous AID recruited to the V genes in the absence of Emu in the Ramos cells?

(3) The authors should explain how their results are different from those reported by the Schatz lab in their recent study (Wu et al, Mol Cell, 2025), demonstrating that ELOF1-mediated transcriptional pausing might promote SHM.

Reviewer #2 (Public review):

Summary:

This paper aims at understanding the effects of plasticity in shaping dynamics and structure of cortical circuits, as well as on how that depends on aspects as network structure and dendritic processing.

Strengths:

The level of biological detail included is impressive, and the numerical simulations appear to be well executed. Additionally, they have done a commendable job in open-sourcing the model.

Weaknesses (after revision):

- As noted in my initial review, the observation that network activity remains stable without an explicit homeostatic mechanism-while acknowledged by the authors as consistent with previous findings (e.g., Higgins et al., 2014)-is not clearly framed as a replication or validation step in the current manuscript. For instance, the abstract states: "In our exploratory simulations, plasticity acted sparsely and specifically, firing rates and weight distributions remained stable without additional homeostatic mechanisms," without noting that this outcome has been previously reported, albeit in models with different levels of biological detail. Furthermore, in the general response to reviewers, the authors list this as the first item in their summary of phenomena accounted for by the model, which gives the impression that it is being presented as a primary result.<br /> If this finding is instead meant to serve as a necessary validation that prior results continue to hold under the authors' extended modeling framework-including multicompartmental neurons, stochastic synaptic transmission, and a modified calcium-based plasticity rule-this should be made more explicit in both the abstract and main text. Unless there were specific reasons to suspect that these model extensions might disrupt previously observed stability, the conceptual contribution of this validation step remains unclear.<br /> I would encourage the authors to revise the manuscript to clarify the role and novelty of this result in the context of existing literature and to briefly motivate why confirming this property in their model was an important step.

- While the revised manuscript includes improvements in the discussion of the generality and specificity of the findings, it still offers limited interpretability and mechanistic insight. As it stands, the simulations provide limited understanding of the underlying principles or mechanisms at play, which constrains the broader conclusions that can be drawn from the work.

- In my first review, I suggested that the comparison with the MICrONS dataset could be made more informative-specifically by showing the same quantification of Figure 7D (7B in the previous version) in a version of the model without plasticity and clarifying the interpretation of Figure 8B, where the data appears to align closely with the model before plasticity.<br /> In their response, the authors explain that several of these features remain largely unchanged before and after plasticity. For example, they note that total $g_{\text{AMPA}}$ increases with $k$-edge indegree even in the initial model configuration. I appreciate this clarification, but it highlights a conceptual point that should be more clearly addressed in the manuscript. If the aspects of the model that align with MICrONS data are already present before plasticity, then these similarities reflect properties of the initial network architecture or baseline dynamics, rather than outcomes shaped by the plasticity process itself.<br /> If this interpretation is correct, it represents an interesting and potentially important finding. However, it is not currently articulated in the text. The manuscript places strong emphasis on the role of plasticity in shaping network structure and dynamics, yet the comparisons with MICrONS data appear to reflect features that do not depend on plasticity. Clarifying this distinction would help readers better appreciate the implications of the model-data comparison and discern which conclusions are genuinely supported by the data.

Reviewer #2 (Public review):

Summary:

This study aims the describe the single-cell transcriptomes of H pylori-associated (Hp) gastric cancers and tumour microenvironment (TME), as a starting point to understand TME diversity stratified by Hp status.<br /> RNAseq was performed for gastric cancers with current Hp+ (from N=9 people), ex-Hp+ (N=6), non-Hp (N=6), and healthy gastric tissue (N=6).<br /> The study expands on previous single-cell transcriptomic studies of gastric cancers and was motivated by previous observations about the effect of H pylori status on therapeutic outcomes. The study includes a brief review of previous work and provides valuable context for this study.

Strengths:

The observations are supported by solid RNAseq study design and analysis. The authors describe correlations between Hp status and inferred molecular characteristics including cell lineages, enrichment for cell subclusters identifed as tumour-infiltrating lyphocyte cell types, tumour-infiltrating myeloid cells and cancer-associated fibroblasts.<br /> The observed correlations between Hp status and enrichment of cell subclusters were broadly corroborated using comparisons to deconvolved bulk RNAseq from publicly available gastric cancer data, providing a convincing starting point for understanding the diversity of tumour microenvironment by Hp-status.

Weaknesses:

The authors acknowledge several limitations of this study.<br /> The correlations with HP-status are based on a small number of participants per Hp category (N=9 with current Hp+; N=6 for ex-HP+ and non-HP), and would benefit from further validation to establish reproducibility in other cohorts.<br /> The ligand-receptor cross-talk analysis and the suggestion that suppressive T cells could interact with the malignant epithelium through TIGIT-NECTIN2/PVR pairs, are preliminary findings based on transcriptomic analysis and immunostaining and will require further validation.

Reviewer #2 (Public review):

Summary:

This revised manuscript investigates the role and the mechanism by which PDE1 impacts NSCLC progression, providing solid data to demonstrate that PDE1 binds to m6A reader YTHDF2, in turn, regulating STAT3 signaling pathway through its interaction, promoting metastasis and angiogenesis. The study provides a valuable information to lung cancer field.

Strength:

The study uncovers a novel PDE1A/YTHDF2/SOCS2/STAT3 pathway in NSCLC progression and the findings provide a potential treatment strategy for NSCLC patients with metastasis.

Weakness:

Given that physical interaction of PDE1A and YTHDF2 plays a critical role in PDE1A-mediated NSCLC metastasis, the in vivo data to show that YTHDF2 mimics the effect of PDE1A in metastasis will strength the manuscript although this point was mentioned in the revised manuscript.

Reviewer #2 (Public review):

The authors investigate the phosphotransfer capacity of Ser/Thr kinase IκB kinase (IKK), a mediator of cellular inflammation signaling. Canonically, IKK activity is promoted by activation loop phosphorylation at Ser177/Ser181. Active IKK can then unleash NF-κB signaling by phosphorylating repressor IκBα at residues Ser32/Ser26. Noting the reports of other IKK phosphorylation sites, the authors explore the extent of autophosphorylation.

Semi-phosphorylated IKK purified from Sf9 cells, exhibits the capacity for further autophosphorylation. Anti-phosphotyrosine immunoblotting indicated unexpected tyrosine phosphorylation. Contaminating kinase activity was tested by generating a kinase-dead K44M variant, supporting the notion that the unexpected phosphorylation was IKK-dependent. In addition, the observed phosphotyrosine signal required phosphorylated IKK activation loop serines.

Two candidate IKK tyrosines were examined as the source of the phosphotyrosine immunoblotting signal. Activation loop residues Tyr169 and Tyr188 were each rendered non-phosphorylatable by mutation to Phe. The Tyr variants decreased both autophosphorylation and phosphotransfer to IκBα. Likewise, Y169F and Y188F IKK2 variants immunoprecipitated from TNFa-stimulated cells also exhibited reduced activity in vitro.

The authors further focus on Tyr169 phosphorylation, proposing a role as a phospho-sink capable of phosphotransfer to IκBα substrate. This model is reminiscent of the bacterial two-component signaling phosphotransfer from phosphohistidine to aspartate. Efforts are made to phosphorylate IKK2 and remove ATP to assess the capacity for phosphotransfer. Phosphorylation of IκBα is observed after ATP removal, although there are ambiguous requirements for ADP.

Strengths:

Ultimately, the authors draw together the lines of evidence for IKK2 phosphotyrosine and ATP-independent phosphotransfer to develop a novel model for IKK2-mediated phosphorylation of IκBα. The model suggests that IKK activation loop Ser phosphorylation primes the kinase for tyrosine autophosphorylation. With the assumption that IKK retains the bound ADP, the phosphotyrosine is conformationally available to relay the phosphate to IκBα substrate. The authors are clearly aware of the high burden of evidence required for this unusual proposed mechanism. Indeed, many possible artifacts (e.g., contaminating kinases or ATP) are anticipated and control experiments are included to address many of these concerns. The analysis hinges on the fidelity of pan-specific phosphotyrosine antibodies, and the authors have probed with two different anti-phosphotyrosine antibody clones. Taken together, the observations are thought-provoking, and I look forward to seeing this model tested in a cellular system.

Weaknesses:

Multiple phosphorylated tyrosines in IKK2 were apparently identified by mass spectrometric analyses. LC-MS/MS spectra are presented, but fragments supporting phospho-Y188 and Y325 are difficult to distinguish from noise. It is common to find non-physiological post-translational modifications in over-expressed proteins from recombinant sources. Are these IKK2 phosphotyrosines evident by MS in IKK2 immunoprecipitated from TNFa-stimulated cells? Identifying IKK2 phosphotyrosine sites from cells would be especially helpful in supporting the proposed model.

Reviewer #2 (Public review):

Brickwedde et al. investigate the role of alpha oscillations in allocating intermodal attention. A first EEG study is followed up with an MEG study that largely replicates the pattern of results (with small to be expected differences). They conclude that a brief increase in the amplitude of auditory and visual stimulus-driven continuous (steady-state) brain responses prior to the presentation of an auditory - but not visual - target speaks to the modulating role of alpha that leads them to revise a prevalent model of gating-by-inhibition.

Overall, this is an interesting study on a timely question, conducted with methods and analysis that are state-of-the-art. I am particularly impressed by the author's decision to replicate the earlier EEG experiment in MEG following the reviewer's comments on the original submission. Evidently, great care was taken to accommodate the reviewers suggestions.

In an earlier version, I was struggling with the report for two main reasons: It was difficult to follow the rationale of the study, due to structural issues with the narrative and missing information or justifications for design and analysis decisions, and I was not convinced that the evidence is strong, or even relevant enough for revising the mentioned alpha inhibition theory.

The authors have addressed my concerns through extensive revisions, and I find that it is now easier to follow, and makes a better case for rethinking how alpha may influence sensory processing through a clearer presentation of results and additional arguments.

Reviewer #3 (Public review):

In this study, the authors used RNAscope to explore the expression of RTN4RL2 RNA in hair cells and spiral ganglia. Through RTN4RL2 gene knockout mice, they demonstrated that the absence of RTN4RL2 leads to pre-synaptic changes of an increase in the size of presynaptic ribbons and a depolarized shift in the activation of calcium channels in inner hair cells. Additionally, they observed a post-synaptic reduction in GluA2-4 AMPA receptors and identified additional "orphan PSDs" not paired with presynaptic ribbons via immunostaining and an increased number of type I SGNs that are not connected with a ribbon synapse via serial block face imaging. These synaptic alterations ultimately resulted in an increased hearing threshold in mice, confirming that the RTN4RL2 gene is essential for normal hearing. These data are intriguing as they suggest that RTN4RL2 contributes to the proper formation and function of auditory afferent synapses and is critical for normal hearing. Most strikingly, the post-synaptic changes and hearing threshold changes are similar to recently published results by Carlton et al, 2024 on a mutation in Bai1, which is a potential binding partner for RTN4RL2. Overall this work provides some clues to the function of RTN4RL2 in the cochlea, but further studies are required to elucidate the function.

A few points would improve the manuscript and the strength of the data presented.

(1) A quantitative assessment is necessary in Figure 1 when discussing RNA scope data. It would be beneficial to show that expression levels are quantitatively reduced in KO mice compared to wild-type mice. This suggestion also applies to Figure 3D, which examines expression levels of Gria2. Data is provided for KO reduction in SGN, but not showing that hair cell labeling is specific. If slides are not available for the young ages, showing hair cell expression at P40 would be sufficient along with a loss of labeling at in the KO at P40.

(2) In Figure 2, the authors present a morphological analysis of synapses and discuss the presence of "orphan PSDs." I agree that Homer1 not juxtaposed with Ctbp2 is increased in KO mice compared to the control group. However, in quantifying this, they opted to measure the number of Ctbp2 puncta with Homer 1 juxtaposed, which indicates the percentages of orphan ribbons rather than directly quantifying the number of Homer1 not juxtaposed with Ctbp2. Quantifying the number of Homer1 not juxtaposed with Ctbp2 would more clearly represent "orphan PSDs" and provide stronger support for the discussion surrounding their presence. A measurement of these was provided in the rebuttal letter, and while this number much more clearly demonstrates the increase in the number of orphan puncta, this analysis is not provided in the manuscript. This number also suggests the number of orphan receptors may be quite high, outnumbering ribbons 2:1.

(3) In Figure 3, the authors discuss GluA2/3 puncta reduction and note that Gria2 RNA expression remains unchanged. However, the GluA2/3 labeling is done at 1-1.5 months, whereas the Gria2 RNAscope is done at P4. Additionally, there is a lack of quantification for Gria2 RNA expression due to their tissue being processed separately. RNA scope at a comparable age to the GluA2/3 would be stronger support for their statement that Gria2 expression is comparable despite a reduction in GluA2/3 puncta.

(4) In Figure 4, the authors indicate that RTN4RL2 deficiency reduces the number of type 1 SGNs connected to ribbons. Given that the number of ribbons remains unchanged (Figure 2), it is important to clearly explain the implications of this finding. It is already known that each type I SGN forms a single synaptic contact with a single IHC. The fact that the number of ribbons remains constant while additional "orphan PSDs" are present suggests that the overall number of SGNs might need to increase to account for these findings, however, the authors noted no change in the number of SGN soma. This discrepancy is important to point out.

Reviewer #2 (Public review):

Summary:

The authors had two aims: First, to decompose the attentional blink (AB) deficit into the two components of signal detection theory: sensitivity and bias. Second, the authors aimed to assess the two subcomponents of sensitivity: detection and discrimination. They observed that the AB is only expressed in sensitivity. Furthermore, detection and discrimination were doubly dissociated. Detection modulated N2p and P3 ERP amplitude, but not frontoparietal beta-band coherence, whereas this pattern was reversed for discrimination.

Strengths:

The experiment is elegantly designed, and the data -both behavioral and electrophysiological- are aptly analyzed. The outcomes, in particular the dissociation between detection and discrimination blinks, are very consistently and clearly supported by the results. The discussion of the results is also appropriately balanced.

Weaknesses:

The lack of an effect of stimulus contrast does not seem very surprising from what we know of the nature of AB already. Low-level perceptual factors are not thought to cause the AB. This is fine, as there are also other, novel findings reported. In their revision, the authors have bolstered the importance of these (null) findings by referring to AB-specific papers that would have predicted different outcomes in this regard.

The ERP analyses are extended in the revised manuscript, including those of the N1 component, which is now more appropriately analyzed at more lateral electrode sites.

Impact & Context:<br /> The results of this study will likely influence how we think about selective attention in the context of the AB phenomenon. In their revision, the authors have further extended their theoretical framing by referring to recent work on the nature of the AB deficit, showing that it can be discrete (all-or-none) and gradual.

Reviewer #2 (Public review):

Summary:

The authors aimed to explore and better understand the complex topographical organization of the human pulvinar, a brain region crucial for various high-order functions such as perception and attention. They sought to move beyond traditional histological subdivisions by investigating continuous 'gradients' of cortical connections along the dorsoventral and mediolateral axes. Using advanced imaging techniques and a comprehensive PET atlas of neurotransmitter receptors, the study aimed to identify and characterize these gradients in terms of structural connections, functional coactivation, and molecular binding patterns. Ultimately, the authors targeted to provide a more nuanced understanding of pulvinar anatomy and its implications for brain function in both healthy and diseased states.

Strengths:

A key strength of this study lies in the authors' effort to comprehensively combine multimodal data, encompassing both functional and structural connectomics, alongside the analysis of major neurotransmitter distributions. This approach enabled a more nuanced understanding of the overarching organizational principles of the pulvinar nucleus within the broader context of whole-brain connectivity. By employing cortex-wide correlation analyses of multimodal embedding patterns derived from 'gradients,' which provide spatial maps reflecting the underlying connectomic and molecular similarities across voxels, the study offers a thorough characterization of the functional neuroanatomy of the pulvinar.

Weaknesses:

Despite its strengths, the current manuscript falls short in presenting the authors' unique perspectives on integrating the diverse biological principles derived from the various neuroimaging modalities. The findings are predominantly reported as correlations between different gradient maps, without providing the in-depth interpretations that would allow for a more comprehensive understanding of the pulvinar's role as a central hub in the brain's network.

Reviewer #2 (Public review):

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

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

I also think it is not appropriate for the manuscript to avoid a comparison between the current work and Boocock et al., which reports single-cell eQTL mapping in the same yeast system. I recommend a citation and statement of the similarities and differences between the papers.

I appreciate the new statement about the single-cell technique affording better power in eQTL mapping (lines 445-453).

Reviewer #2 (Public review):

Summary:

Whole-brain network modeling is a common type of dynamical systems-based method to create individualized models of brain activity incorporating subject-specific structural connectome inferred from diffusion imaging data. This type of model has often been used to infer biophysical parameters of the individual brain that cannot be directly measured using neuroimaging but may be relevant to specific cognitive functions or diseases. Here, Ziaeemehr et al introduce a new toolkit, named "Virtual Brain Inference" (VBI), offering a new computational approach for estimating these parameters using Bayesian inference powered by artificial neural networks. The basic idea is to use simulated data, given known parameters, to train artificial neural networks to solve the inverse problem, namely, to infer the posterior distribution over the parameter space given data-derived features. The authors have demonstrated the utility of the toolkit using simulated data from several commonly used whole-brain network models in case studies.

Strengths:

(1) Model inversion is an important problem in whole-brain network modeling. The toolkit presents a significant methodological step up from common practices, with the potential to broadly impact how the community infers model parameters.

(2) Notably, the method allows the estimation of the posterior distribution of parameters instead of a point estimation, which provides information about the uncertainty of the estimation, which is generally lacking in existing methods.

(3) The case studies were able to demonstrate the detection of degeneracy in the parameters, which is important. Degeneracy is quite common in this type of model. If not handled mindfully, they may lead to spurious or stable parameter estimation. Thus, the toolkit can potentially be used to improve feature selection or to simply indicate the uncertainty.

(4) In principle, the posterior distribution can be directly computed given new data without doing any additional simulation, which could improve the efficiency of parameter inference on the artificial neural network if well-trained.

Weaknesses:

(1) While the posterior estimator was trained with a large quantity of simulated data, the testing/validation is only demonstrated with a single case study (one point in parameter space) per model. This is not sufficient to demonstrate the method's accuracy and reliability, but only its feasibility. Demonstrating the accuracy and reliability of the posterior estimation in large test sets would inspire more confidence.

(2) The authors have only demonstrated validation of the method using simulated data, but not features derived from actual EEG/MEG or fMRI data. So, it is unclear if the posterior estimator, when applied to real data, would produce results as sensible as using simulated data. Human data can often look quite different from the simulated data, which may be considered out of distribution. Thus, the authors should consider using simulated test data with out-of-distribution parameters to validate the method and using real human data to demonstrate, e.g., the reliability of the method across sessions.

(3) The z-scores used to measure prediction error are generally between 1-3, which seems quite large to me. It would give readers a better sense of the utility of the method if comparisons to simpler methods, such as k-nearest neighbor methods, are provided in terms of accuracy.

(4) A lot of simulations are required to train the posterior estimator, which seems much more than existing approaches. Inferring from Figure S1, at the required order of magnitudes of the number of simulations, the simulation time could range from days to years, depending on the hardware. Although once the estimator is well-trained, the parameter inverse given new data will be very fast, it is not clear to me how often such use cases would be encountered. Because the estimator is trained based on an individual connectome, it can only be used to do parameter inversion for the same subject. Typically, we only have one session of resting state data from each participant, while longitudinal resting state data where we can assume the structural connectome remains constant, is rare. Thus, the cost-efficiency and practical utility of training such a posterior estimator remains unclear.

Reviewer #2 (Public review):

Summary:

The cerebellum is known to be vulnerable to aging, yet specific cell type vulnerability remains understudied. This important study convincingly demonstrates that the normal aged mouse cerebellum exhibits Purkinje cell loss, and that the vulnerable PCs to age are arranged on the basis of the known zebrin stripe pattern that represents a particular subtype of the PCs. Although the patterns of PC loss were analyzed qualitatively, the phenotype is robust enough to clearly appreciate that PC loss occurs predominantly in zebrin-negative regions when combined with zebrin immunohistochemistry. Interestingly, the authors demonstrate that this phenotype appears stochastically even within the inbred C57BL/6J mouse strain examined, though the mechanisms behind this individual variability remain unexplored. In contrast to the expectation that the PC loss could account for age-related motor decline, the authors did not find any correlation between them. While the authors attempt to draw parallels with normal human aging, the human phenotypes have not been conclusively shown to match those in mice beyond the occurrence of potentially age-related PC loss. Future studies should investigate why this PC loss phenotype occurs stochastically across the population and whether these findings parallel human cerebellar aging.

Strength:

(1) Banding pattern of PC loss is very clearly demonstrated by combining immunostaining for zebrin.

(2) A critical methodological concern that a standard PC marker, calbindin, could be compromised in aging has been addressed by performing control experiments with appropriate counterstaining.

(3) Parallels with neurodegenerative phenotype would be helpful to understand the mechanisms of PC loss in the future.

Weakness:

(1) Limited strain diversity: The study exclusively uses C57BL/6J mice despite known genetic and motor differences even the closely related strains like C57BL/6N.

(2) No correlation quantified between the degree of PC loss, aging, and motor performance.

(3) It has not been demonstrated whether the neurodegenerative changes are indeed observed in zebrin-negative PCs.

(4) The mechanisms of why only a subset of mice show PC loss remain unexplored and not discussed.

(5) Linkages with normal human aging and cerebellar function are not well supported. While motor behavioral assays captured phenotypes that mimic aged people, correlation with PC loss is demonstrated to be absent in mice. It remains unclear whether this PC loss phenomenon is universal or specific to a particular individual; and whether specific to a human PC subtype.

(6) Analyses in the paraflocculus are currently not easy to understand. This lobule has heterogeneous PC subtypes, developmentally or molecularly. Zebrin-weak and Zebrin-intense PCs are known to be arranged in stripes, which resembles the pattern of developmentally defined PC subsets (Fujita et al., 2014, Plos one; Fujita et al., 2012, J Neurosci). In the data presented, it is hard to appreciate whether the viewing angle is consistent relative to the angle of the paraflocculus. This may be a limitation of the analysis of the paraflocculus in general, that the orientation of this lobule is so susceptible to fixation and dissection. Discrepancy between PC loss stripe and zebrin pattern may be an overstatement, because appropriate analyses on the paraflocculus would require a rigorously standardized analytic method.

Reviewer #2 (Public review):

Summary:

The authors were building on prior research linking cortical norepinephrine in a test of attentional set shifting. They extended prior research by assessing the effects of excitatory or inhibitory DREADDs prior to the test of attentional set shifting.

Strengths:

The use of DREADDs in the previously validated test of attentional set shifting improves temporal control of corticopetal, noradrenergic pathways during behavior. While mice typically require multiple intradimensional shifts to form an attentional set, the subjects in the current study perform a variant of the task similar to that used in humans, improving the translational validity of the work.

Weaknesses:

A critical piece of evidence needed to support the behavioral claim that mice form an attentional set is a statistically significant difference between the number of trials to reach criterion at the intradimensional vs. the extradimensional stage of the task. Based on prior literature, this could be done as a planned comparison, which would improve the power to detect differences beyond that found using an HSD test. An additional methodological ambiguity is the amount of time between the administration of CNO and the performance of the ED. As reported, it seems likely that the DREADDS were impacting performance at multiple stages of the test.

Overall, the authors seem to have achieved their aims, but have failed to provide critical statistical support for claims made.

The work is likely to be of interest to the burgeoning number of scientists investigating the role of cortical norepinephrine in cognitive flexibility.

Reviewer #2 (Public review):

Summary:

This Phase II clinical trial investigates the combination of Gamma Knife Stereotactic Body Radiation Therapy (SBRT) with Tislelizumab for the treatment of metastatic colorectal cancer (mCRC) in patients with proficient mismatch repair (pMMR). The study addresses a critical clinical challenge in the management of pMMR CRC, focusing on the selection of appropriate candidates. The results suggest that the combination of Gamma Knife SBRT and Tislelizumab provides a safe and potent treatment option for patients with pMMR/MSS/MSI-L mCRC who have become refractory to first- and second-line chemotherapy. The study design is rigorous, and the outcomes are promising.

Advantage:

The trial design was meticulously structured, and appropriate statistical methods were employed to rigorously analyze the results. Bioinformatics approaches were utilized to further elucidate alterations in the patient's tumor microenvironment and to explore the underlying factors contributing to the observed differences in treatment efficacy. The conclusions drawn from this trial offer valuable insights for managing advanced colorectal cancer in patients who have not responded to first- and second-line therapies.

Weakness:

(1) Clarity and Structure of the Abstract<br /> - Results Section: The results section should contain important data, I suggest some important sequencing data should be shown to enhance understanding.<br /> (2) As the author using the NanoString assay for transcriptome analysis, more detail should be shown such as the version of R, and the bioinformatics analysis methods.<br /> (3) It is interesting for included patients that PD-L1 increase expression after Gamma Knife Stereotactic Body Radiation Therapy (SBRT) treatment, How to explain it?<br /> (4) It would be helpful to include a brief discussion of the limitations of the study, such as sample size constraints and their impact on the generalizability of the results. This will give readers a more comprehensive understanding of the findings.<br /> (5) Language Accuracy: There are a few instances where wording could be more professional or precise.

Revision comment:

The author had responded to all questions and improved the manuscript. The author's answers and revisions are very satisfactory to me. I believe it is an important study for the immunotherapy of colorectal cancer.

Reviewer #2 (Public review):

Summary:

The study of Rollenhagen et al examines the ultrastructural features of Layer 1 of human temporal cortex. The tissue was derived from drug-resistant epileptic patients undergoing surgery, and was selected as further from the epilepsy focus, and as such considered to be non-epileptic. The analyses has included 4 patients with different age, sex, medication and onset of epilepsy. The manuscript is a follow-on study with 3 previous publications from the same authors on different layers of the temporal cortex:

Layer 4 - Yakoubi et al 2019 eLife<br /> Layer 5 - Yakoubi et al 2019 Cerebral Cortex,<br /> Layer 6 - Schmuhl-Giesen et al 2022 Cerebral Cortex

They find, the L1 synaptic boutons mainly have single active zone a very large pool of synaptic vesicles and are mostly devoid of astrocytic coverage.

Strengths:

The MS is well written easy to read. Result section gives a detailed set of figures showing many morphological parameters of synaptic boutons and surrounding glial elements. The authors provide comparative data of all the layers examined by them so far in the Discussion. Given that anatomical data in human brain are still very limited, the current MS has substantial relevance.<br /> The work appears to be generally well done, the EM and EM tomography images are of very good quality. The analyses is clear and precise.

Weaknesses:

The authors made all the corrections required and answered all of my concerns, included additional data sets, and clarified statements where needed.

Reviewer #2 (Public review):

The authors hypothesized that chemostat propagated viromes could modulate the GM and reduce NEC lesions while avoiding potential side effects, such as the earlier onset of diarrhea. This is interesting.

Major Comments:

(1) As the authors state that the aim of the research is 'We hypothesized that chemostat propagated viromes could modulate the GM and reduce NEC lesions while avoiding potential side effects, such as earlier onset of diarrhea'.<br /> a) For the efficacy, in Figure 5, there is no significance in stomach pathology and enterocolitis between groups, even between the control group and experimental groups, is it because of the low incidence of NEC? This may affect the statistical power of the conclusions. Therefore, it is unclear how one can draw the conclusion that chemostat can reduce NEC lesions?<br /> b) Convincing pathology images would be helpful.<br /> c) For the safety, such as body weight development, FVT had no statistical significance difference from control, CVT, and CVT-MO. So how can the authors draw the conclusion that chemostat can avoid potential side effects?<br /> d) There is a lack of evidence to convince the reader that there is a decrease in eukaryotic viruses. More quantitative data here would be useful.

(2) Questions regarding Figure 3F:<br /> a) How can the medium have 'the baseline viral content'?<br /> b) What is the statistical significance of the relative abundance of specific eukaryotic viruses?<br /> c) The hosts for some of the listed eukaryotic viruses are neither pigs or humans, as such, the significance of a decrease in these viruses to humans is unclear.

(3) In this study, pH 6.5 was selected as the pH value for chemostat cultivation, but considering the different adaptability of different bacteria to pH, it is recommended to further explore the effect of pH on bacteria and virus groups. In particular, it was optimized to maintain the growth of beneficial bacteria such as Lactobacillaceae and Bacteroides in order to improve the effect of chemostat cultivation.

(4) Please improve the quality of the images, charts, error bars, and statistical significance markers throughout and mark the n's. used in each experiment.

Reviewer #2 (Public review):

Trac, Huang, et al used the AZ Drug Combination Prediction DREAM challenge data to make a new random forest-based model for drug synergy. They make comparisons to the winning method and also show that their model has some predictive capacity for a completely different dataset. They highlight the ability of the model to be interpretable in terms of pathway and target interactions for synergistic effects.

In their revised manuscript and response, the authors have tried to address all points. I do not fully agree with them about the definition of overfitting still. If the objective it to identify synergies given any 2 drugs, not just those in a dataset at different doses, then the results certainly appear overfit to the training set given the performance degradation. However, at this time, I cannot add any useful suggestions to improve performance.

Reviewer #2 (Public review):

The manuscript by Liu and colleagues applied Mendelian Randomization (MR) techniques to study the causal relationship of atherosclerosis (categorized into four subtypes) and intracranial aneurysms (classified as unruptured or ruptured), as well as the potential mediation by 12 plasma matrix metalloproteinase (MMP) levels. The authors have followed rigorous MR analysis guidelines by using multiple analytical approaches, implementing strict selection criteria, and employing comprehensive sensitivity analyses. One of the strengths is the lack of overlapping samples in their two-sample MR analysis. This approach helps mitigate potential biases and increases the reliability of their causal inference. The analysis is fundamentally sound, but there are still several nuanced areas where the methodology could be strengthened. Given that most of the identified causal associations do not hold after correcting for multiple tests, the conclusions should be carefully reviewed to be fully supported by the results.

The recommendations below are meant to enhance the already robust approach.

(1) The selection of 12 MMPs lacks a clear, explicit rationale in the provided excerpt. A more detailed explanation of why these specific MMPs were chosen would strengthen the methodological rigor.

(2) Adjusting p-value for multiple testing using Bonferroni correction needs to be elucidated better.

(3) The authors should provide a more robust explanation of why they shifted from 5×10-9 to 5×10-6 to select genomic instruments.

(4) Egger's intercept may be a more robust approach for this study to test horizontal pleiotropy rather than MR-PRESSO.

Reviewer #2 (Public review):

Summary

The report by Dalas and colleagues introduces a significant novelty in the field of pentameric ligand-gated ion channels (pLGICs). Within this family of receptors, numerous structures are available, but a widely recognised problem remains in assigning structures to functional states observed in biological membranes. Here, the authors obtain both structural and functional information of a pLGIC in a liposome environment. The model receptor ELIC is captured in the resting, desensitized, and open states. Structures in large nanodiscs, possibly biased by receptor-scaffold protein interactions, are also reported. Altogether, these results set the stage for the adoption of liposomes as a proxy for the biological membranes, for cryoEM studies of pLGICs and membrane proteins in general.

Strengths

The structural data is comprehensive, with structures in liposomes in the 3 main states (and for each, both inward-facing and outward-facing), and an agonist-bound structure in the large spNW25 nanodisc (and a retreatment of previous data obtained in a smaller disc). It adds up to a series of work from the same team that constitutes a much-needed exploration of various types of environment for the transmembrane domain of pLGICs. The structural analysis is thorough.

The tone of the report is particularly pleasant, in the sense that the authors' claims are not inflated. For instance, a sentence such as "By performing structural and functional characterization under the same reconstitution conditions, we increase our confidence in the functional annotation of these structures." is exemplary.

Weaknesses

Core parts of the method are not described and/or discussed in enough detail. While I do believe that liposomes will be, in most cases, better than, say, nanodiscs, the process that leads from the protein in its membrane down to the liposome will play a big role in preserving the native structure, and should be an integral part of the report. Therefore, I strongly felt that biochemistry should be better described and discussed. The results section starts with "Optimal reconstitution of ELIC in liposomes [...] was achieved by dialysis". There is no information on why dialysis is optimal, what it was compared to, the distribution of liposome sizes using different preparation techniques, etc... Reading the title, I would have expected a couple of paragraphs and figure panels on liposome reconstitution. Similarly, potential biochemical challenges are not discussed. The methods section mentions that the sample was "dialyzed [...] over 5-7 days". In such a time window, most of the members of this protein family would aggregate, and it is therefore a protocol that can not be directly generalised. This has to be mentioned explicitly, and a discussion on why this can't be done in two days, what else the authors tested (biobeads? ... ?) would strengthen the manuscript.

To a lesser extent, the relative lack of both technical details and of a broad discussion also pertains to the cryoEM and thallium flux results. Regarding the cryoEM part, the authors focus their analysis on reconstructions from outward-facing particles on the basis of their better resolutions, yet there was little discussion about it. Is it common for liposome-based structures? Are inward-facing reconstructions worse because of the increased background due to electrons going through two membranes? Are there often impurities inside the liposomes (we see some in the figures)? The influence of the membrane mimetics on conformation could be discussed by referring to other families of proteins where it has been explored (for instance, ABC transporters, but I'm sure there are many other examples). If there are studies in other families of channels in liposomes that were inspirational, those could be mentioned. Regarding thallium flux assays, one argument is that they give access to kinetics and set the stage for time-resolved cryoEM, but if I did not miss it, no comparison of kinetics with other techniques, such as electrophysiology, nor references to eventual pioneer time-resolved studies are provided.

Altogether, in my view, an updated version would benefit from insisting on every aspect of the methodological development. I may well be wrong, but I see this paper more like a milestone on sample prep for cryoEM imaging than being about the details of the ELIC conformations.

Reviewer #2 (Public review):

Summary:

This Phase II clinical trial investigates the combination of Gamma Knife Stereotactic Body Radiation Therapy (SBRT) with Tislelizumab for the treatment of metastatic colorectal cancer (mCRC) in patients with proficient mismatch repair (pMMR). The study addresses a critical clinical challenge in the management of pMMR CRC, focusing on the selection of appropriate candidates. The results suggest that the combination of Gamma Knife SBRT and Tislelizumab provides a safe and potent treatment option for patients with pMMR/MSS/MSI-L mCRC who have become refractory to first- and second-line chemotherapy. The study design is rigorous, and the outcomes are promising.

Advantage:

The trial design was meticulously structured, and appropriate statistical methods were employed to rigorously analyze the results. Bioinformatics approaches were utilized to further elucidate alterations in the patient's tumor microenvironment and to explore the underlying factors contributing to the observed differences in treatment efficacy. The conclusions drawn from this trial offer valuable insights for managing advanced colorectal cancer in patients who have not responded to first- and second-line therapies.

Weakness:

(1) Clarity and Structure of the Abstract<br /> - Results Section: The results section should contain important data, I suggest some important sequencing data should be shown to enhance understanding.<br /> (2) As the author using the NanoString assay for transcriptome analysis, more detail should be shown such as the version of R, and the bioinformatics analysis methods.<br /> (3) It is interesting for included patients that PD-L1 increase expression after Gamma Knife Stereotactic Body Radiation Therapy (SBRT) treatment, How to explain it?<br /> (4) It would be helpful to include a brief discussion of the limitations of the study, such as sample size constraints and their impact on the generalizability of the results. This will give readers a more comprehensive understanding of the findings.<br /> (5) Language Accuracy: There are a few instances where wording could be more professional or precise.

Reviewer #2 (Public review):

Summary:

Ning and colleagues present studies supporting a role for breast carcinoma amplified sequence 2 (Bcas2) in positively regulating primitive wave hematopoiesis through amplification of beta-catenin-dependent (canonical) Wnt signaling. The authors present compelling evidence that zebrafish bcas2 is expressed at the right time and place to be involved in primitive hematopoiesis, that there are primitive hematopoietic defects in hetero- and homozygous mutant and knockdown embryos, that Bcas2 mechanistically positively regulates canonical Wnt signaling, and that Bcas2 is required for nuclear retention of B-cat through physical interaction involving armadillo repeats 9-12 of B-cat and the coiled-coil domains of Bcas2. Overall, the data and writing are clean, clear, and compelling. This study is a first rate analysis of a strong phenotype with highly supportive mechanistic data. The findings shed light on the controversial question of whether, when, and how canonical Wnt signaling may be involved in hematopoietic development.

In the revised version of their previous work, they have included responses to some of our suggestions for minor experiments and edits. We previously suggested they examine the structural compatibility of a Bcas2/beta-catenin dimer with binding to the DNA-binding protein Tcf7l1 (previously Tcf3), which would be expected for a beta-catenin nuclear-retention factor that potentiates canonical Wnt signaling responses. Although the authors did not test compatibility of Bcas2 with Tcf3 binding to beta-catenin, they show that a three-way complex with the family member Tcf4 is possible (Fig. S12), which suggests that Lef/Tcf family binding in general is plausible.

The authors' acceptance of our suggestion to evaluate cdx and hox gene expression is welcome, as these genes have previously been defined as canonical Wnt targets (Lengerke et al., 2009) that regionalize the lateral plate mesoderm (LPM) and confer pre-hematopoietic identity there (Davidson et al., 2003; Davidson and Zon, 2004). The authors' finding that cdx4 and hoxa9a are diminished in the bcas2 mutants (Fig. S7) validates this suggestion and seem to imply that the primary defect here is specification of the early hematopoietic field in the LPM, however the results are a little confusing or surprising given that scl - which is unaffected in the bcas2 mutant (Fig. 2A) - is a downstream target of Cdx4 (Davidson et al., 2003, Fig. 1b, 3d). The results in the current submission imply that early maintenance of pre-hematopoietic competence in the LPM is a canonical-Wnt-directed phenomenon separable from the earliest specification of the hematopoietic field. We believe it would be of value to further evaluate regulation of cdx1, which has been shown to cooperate with cdx4 in regulation of the LPM hematopoietic field, as well as analyze some of the putative downstream hox family targets.

We previously reviewed the article as suitable for publication and we continue to support our prior assessment. The authors have presented strong data supporting a role for Bcas2 in hematopoietic development across phyla and a mechanistic involvement in promoting canonical Wnt signaling.

Strengths:

(1) The study features clear and compelling phenotypes and results.<br /> (2) The manuscript narrative exposition and writing are clear and compelling.<br /> (3) The authors have attended to important technical nuances sometimes overlooked, for example, focusing on different pools of cytosolic or nuclear b-catenin.<br /> (4) The study sheds light on a controversial subject: regulation of hematopoietic development by canonical Wnt signaling and presents clear evidence of a role.<br /> (5) The authors present evidence of phylogenetic conservation of the pathway.

Reviewer #2 (Public review):

This paper describes an interesting observation that ER-targeted misfolded proteins are trapped within vesicles inside nucleus to facilitate quality control during cell division. This work supports the concept that transient sequestration of misfolded proteins is a fundamental mechanism of protein quality control. The authors satisfactorily addressed several points asked in the review of first submission. The manuscript is improved but still unable to fully address the mechanisms.

Strengths:

The observations in this manuscript are very interesting and open up many questions on proteostasis biology.

Weaknesses:

Despite inclusions of several protein-level experiments, the manuscript remained a microscopy-driven work and missed the opportunity to work out the mechanisms behind the observations.

Reviewer #2 (Public review):

Summary

The study is an innovative and fundamental study that clarified important aspects of brain processes for integration of information from speech and iconic gesture (i.e., gesture that depicts action, movement, and shape), based on tDCS, TMS and EEG experiments. They evaluated their speech and gesture stimuli in information-theoretic ways and calculated how informative speech is (i.e., entropy), how informative gesture is, and how much shared information speech and gesture encode. The tDCS and TMS studies found that the left IFG and pMTG, the two areas that were activated in fMRI studies on speech-gesture integration in the previous literature, are causally implicated in speech-gesture integration. The size of tDC and TMS effects are correlated with entropy of the stimuli or mutual information, which indicates that the effects stems from the modulation of information decoding/integration processes. The EEG study showed that various ERP (event-related potential, e.g., N1-P2, N400, LPC) effects that have been observed in speech-gesture integration experiments in the previous literature are modulated by the entropy of speech/gesture and mutual information. This makes it clear that these effects are related to information decoding processes. The authors propose a model of how speech-gesture integration process unfolds in time, and how IFG and pMTG interact with each other in that process.

Strengths

The key strength of this study is that the authors used information-theoretic measures of their stimuli (i.e., entropy and mutual information between speech and gesture) in all of their analyses. This made it clear that the neuro-modulation (tDCS, TMS) affected information decoding/integration and ERP effects reflect information decoding/integration. This study used tDCS and TMS methods to demonstrate that left IFG and pMTG are causally involved in speech-gesture integration. The size of tDCS and TMS effects are correlated with information-theoretic measures of the stimuli, which indicate that the effects indeed stem from disruption/facilitation of information decoding/integration process (rather than generic excitation/inhibition). The authors' results also showed correlation between information-theoretic measures of stimuli with various ERP effects. This indicates that these ERP effects reflect the information decoding/integration process.

Weakness

The "mutual information" cannot capture all types of interplay of the meaning of speech and gesture. The mutual information is calculated based on what information can be decoded from speech alone and what information can be decoded from gesture alone. However, when speech and gesture are combined, a novel meaning can emerge, which cannot be decoded from a single modality alone. When example, a person produce a gesture of writing something with a pen, while saying "He paid". The speech-gesture combination can be interpreted as "paying by signing a cheque". It is highly unlikely that this meaning is decoded when people hear speech only or see gestures only. The current study cannot address how such speech-gesture integration occur in the brain, and what ERP effects may reflect such a process. The future studies can classify different types of speech-gesture integration and investigate neural processes that underlie each type. Another important topic for future studies is to investigate how the neural processes of speech-gesture integration change when the relative timing between the speech stimulus and the gesture stimulus changes.

Comments on revisions: The authors addressed my concerns well.

Reviewer #2 (Public review):

Summary:

Luo et. al. use SHAPE-MaP to find suitable RNA targets in Porcine Epidemic Diarrhoea Virus. Results show that dynamic and transient structures are good targets for small molecules, and that exposed strand regions are adequate targets for siRNA. This work is important to segment the RNA targeting.

Strengths:

This work is well done and the data supports its findings and conclusions. When possible, more than one technique was used to confirm some of the findings.

Weaknesses:

The study uses a cell line that is not porcine (not the natural target of the virus). That being said, authors used a widely used cell line that has been used in similar studies.

Reviewer #2 (Public review):

Summary:

Noise invariance is an essential computation in sensory systems for stable perception across a wide range of contexts. In this paper, Landemard et al. perform functional ultrasound imaging across primary, secondary, and tertiary auditory cortex in ferrets to uncover the mesoscale organization of background invariance in auditory cortex. Consistent with previous work, they find that background invariance increases throughout the cortical hierarchy. Importantly, they find that background invariance is largely explained by progressive changes in spectrotemporal tuning across cortical stations, which are biased towards foreground sound features. To test if these results are broadly relevant, they then re-analyze human fMRI data and find that spectro-temporal tuning fails to explain background invariance in human auditory cortex.

Strengths:

(1) Novelty of approach: Though the authors have published on this technique previously, functional ultrasound imaging offers unprecedented temporal and spatial resolution in a species where large-scale calcium imaging is not possible and electrophysiological mapping would take weeks or months. Combining mesoscale imaging with a clever stimulus paradigm, they address a fundamental question in sensory coding.

(2) Quantification and execution: The results are generally clear and well supported by statistical quantification.

(3) Elegance of modeling: The spectrotemporal model presented here is explained clearly and, most importantly, provides a compelling framework for understanding differences in background invariance across cortical areas.

Weaknesses:

(1) Interpretation of the cerebral blood volume signal: While the results are compelling, more caution should be exercised by the authors in framing their results, given that they are measuring an indirect measure of neural activity, this is the difference between stating "CBV in area MEG was less background invariant than in higher areas" vs. saying "MEG was less background invariant than other areas". Beyond framing, the basic properties of the CBV signal should be better explored:

a) Cortical vasculature is highly structured (e.g. Kirst et al.( 2020) Cell). One potential explanation for the results is simply differences in vasculature and blood flow between primary and secondary areas of auditory cortex, even if fUS is sensitive to changes in blood flow, changes in capillary beds, etc (Mace et al., 2011) Nat. Methods.. This concern could be addressed by either analyzing spontaneous fluctuations in the CBV signal during silent periods or computing a signal-to-noise ratio of voxels across areas across all sound types. This is especially important given the complex 3D geometry of gyri and sulci in the ferret brain.

b) Figure 1 leaves the reader uncertain what exactly is being encoded by the CBV signal, as temporal responses to different stimuli look very similar in the examples shown. One possibility is that the CBV is an acoustic change signal. In that case, sounds that are farther apart in acoustic space from previous sounds would elicit larger responses, which is straightforward to test. Another possibility is that the fUS signal reflects time-varying features in the acoustic signal (e.g. the low-frequency envelope). This could be addressed by cross-correlating the stimulus envelope with fUS waveform. The third possibility, which the authors argue, is that the magnitude of the fUS signal encodes the stimulus ID. A better understanding of the justification for only looking at the fUS magnitude in a short time window (2-4.8 s re: stimulus onset) would increase my confidence in the results.

(2) Interpretation of the human data: The authors acknowledge in the discussion that there are several differences between fMRI and fUS. The results would be more compelling if they performed a control analysis where they downsampled the Ferret fUS data spatially and temporally to match the resolution of fMRI and demonstrated that their ferret results hold with lower spatiotemporal resolution.

Reviewer #2 (Public review):

It is my pleasure to review this manuscript from Stoffers, Lacin, and colleagues, in which they identify pairs of transcription factors unique to (almost) every ventral nerve cord hemilineage in Drosophila and use these pairs to create reagents to label and manipulate these cells. The advance is sold as largely technical-as a pipeline for identifying durably expressed transcription factor codes in postmitotic neurons from single cell RNAseq data, generating knock-in alleles in the relevant genes, using these to match transcriptional cell types to anatomic cell types, and then using the alleles as a genetic handle on the cells for downstream explication of their function. Yet I think the work is gorgeous in linking expression of genes that are causal for neuron-type-specific characteristics to the anatomic instantiations of those neurons. It is astounding that the authors are able to use their deep collective knowledge of hemilineage anatomy and gene expression to match 33 of 34 to transcriptional profiles. Together with other recent studies, this work drives a major course correction in developmental biology, away from empirically identified cell type "markers" (in Drosophila neuroscience, often genomic DNA fragments that contain enhancers found to be expressed in specific neurons at specific times), and towards methods in which the genes that generate neuronal type identity are actually used to study those neurons. Because the relationship between fate and form/function are built into the tools, I believe that this approach will be a trojan horse to integrate the fields of neural development and systems neuroscience.

Comments on revisions:

The authors have addressed my (minor) suggestions.

DOI: 10.1186/s12974-025-03450-2

Resource: (Thermo Fisher Scientific Cat# A-11034, RRID:AB_2576217)

Curator: @dhovakimyan1

SciCrunch record: RRID:AB_2576217

What is this?

DOI: 10.1089/zeb.2023.0052

Resource: RRID:ZFIN_ZDB-GENO-230622-2

Curator: @AleksanderDrozdz

SciCrunch record: RRID:ZFIN_ZDB-GENO-230622-2

What is this?

DOI: 10.1038/s41598-025-94549-2

Resource: (KCB Cat# KCB 200848YJ, RRID:CVCL_0546)

Curator: @dhovakimyan1

SciCrunch record: RRID:CVCL_0546

What is this?

DOI: 10.1007/978-1-0716-3012-9_10

Resource: (ZFIN Cat# ZDB-ALT-100322-2,RRID:ZFIN_ZDB-ALT-100322-2)

Curator: @AleksanderDrozdz

SciCrunch record: RRID:ZFIN_ZDB-ALT-100322-2

What is this?

Reviewer #2 (Public review):

Summary:

This is a clear and systematic study on trial history influences on the performance of monkeys in a target selection paradigm. The primary contribution of the paper is to add a twist in which the target information is revealed after, rather than before, the cue to make a foveating eye movement. This twist results in a kind of countermanding of an earlier "uninformed" saccade plan by a new one occurring right after the visual information is provided. As with countermanding tasks in general, time now plays a key factor in success in this task, and it is time that allows the authors to quantitatively assess the parametric influences of things like previous target location, previous target identity, and previous correctness rate on choice performance. The results are logical and consistent with the prior literature, but the authors also highlight novelties in the interpretation of prior-trial effects that they argue are enabled by the use of their paradigm.

Strengths:

Careful analysis of a multitude of variables influencing behavior

Weaknesses:

Results appear largely confirmatory

Comments on revisions:

The authors have addressed the previous comments.

Reviewer #2 (Public review):

Summary:

The authors made a thorough revision of the manuscript, strengthening the message. They also considered all the comments made by the reviewers and provided appropriate and convincing arguments.

Strengths:

The revised manuscript clarifies all the major points raised by the reviewers, and the way the information is presented (in the text, figures and tables) is clear.

Weaknesses:

The authors provided an appropriate and convincing rebuttal regarding the potential weakness I pointed out in the first review of the manuscript. Therefore, I do not see any major issue in their work.

Reviewer #2 (Public review):

Summary:

The authors perform a remarkably comprehensive, rigorous, and extensive investigation into the spatiotemporal dynamics between ribosomal accumulation, nucleoid segregation, and cell division. Using detailed experimental characterization and rigorous physical models, they offer a compelling argument that nucleoid segregation rates are determined at least in part by the accumulation of ribosomes in the center of the cell, exerting a steric force to drive nucleoid segregation prior to cell division. This evolutionarily ingenious mechanism means cells can rely on ribosomal biogenesis as the sole determinant for the growth rate and cell division rate, avoiding the need for two separate 'sensors,' which would require careful coupling.

Strengths:

In terms of strengths; the paper is very well written, the data are of extremely high quality, and the work is of fundamental importance to the field of cell growth and division. This is an important and innovative discovery enabled through the combination of rigorous experimental work and innovative conceptual, statistical, and physical modeling.

Weaknesses:

The authors have reasonably addressed by minor weaknesses raised in the first round of reviews, and I see no other weaknesses at this point worth raising.

for - definition - cogress - Medium article - Cogress - Part 2 - Stop Reset Go - Deep Humanity - James Gien Wong - from - Medium article - Cogress - Part 1 - Stop Reset Go - Deep Humanity - James Gien Wong - https://hyp.is/_Nyg2DF_EfCBeu_iuDroYg/medium.com/@gien_SRG/human-cogress-part-1-5159a575e1c4 - to - Stop Reset Go hypothesis annotations - progress trap - Ronald Wright - https://jonudell.info/h/facet/?max=100&expanded=true&user=stopresetgo&exactTagSearch=true&any=ronald+wright - General - https://jonudell.info/h/facet/?max=100&expanded=true&user=stopresetgo&exactTagSearch=true&any=progress+trap

Reviewer #2 (Public review):

Summary:

The regulation of kinesin is fundamental to cellular morphogenesis. Previously, it has been shown that OSM-3, a kinesin required for intraflagellar transport (IFT), is regulated by autoinhibition. However, it remains totally elusive how the autoinhibition of OSM-3 is released. In this study, the authors have shown that NEKL-3 phosphorylates OSM-3 and release its autoinhibition.

The authors found NEKL-3 directly phosphorylates OSM-3 (Figure 1). The phophorylated residue is the "elbow" of OSM-3. The authors introduced phospho-dead (PD) and phospho-mimic (PM) mutations by genome editing and found that the OSM-3(PD) protein does not form cilia, and instead, accumulates to the axonal tips. The phenotype is similar to another constitutive active mutant of OSM-3, OSM-3(G444A) (Imanishi et al., 2006; Xie et al., 2024). osm-3(PM) has shorter cilia, which resembles with loss of function mutants of osm-3 (Figure 2). The authors did structural prediction and shows that G444E and PD mutations change the conformation of OSM-3 protein (Figure 3). In the single molecule assays G444E and PD mutations exhibited increased landing rate (Figure 4). By unbiased genetic screening, the authors identified a suppressor mutant of osm-3(PD), in which A489T occurs. The result confirms the importance of this residue. Based on these results, the authors suggest that NEKL-3 induces phosphorylation of the elbow domain and inactivates OSM-3 motor when the motor is synthesized in the cell body. This regulation is essential for the proper cilia formation.

Strengths:

The finding is interesting and gives new insight into how IFT motor is regulated.

Comments on revisions: In the revised manuscript, the authors describe why they focused on NEKL-3 and detailed experimental procedures are presented.

My only minor concern is the title, which appears to be too general. Researchers in the motor protein field may firstly assume this paper focuses on kinesin-1, because the "elbow" domain was originally suggested in kinesin-1. This paper newly determines the elbow region of OSM-3 and shows its crucial role in autoinhibition. Therefore, a more specific title, "Kinesin-2 Autoinhibition Requires Elbow Phosphorylation" or "OSM-3 Autoinhibition Requires Elbow phosphorylation" may be better.

Reviewer #3 (Public review):

Salmonella is interesting due to its life within a compact compartment, which we call SCV or Salmonella containing vacuole in the field of Salmonella. SCV is a tight-fitting vacuole where the acquisition of nutrients is a key factor by Salmonella. The authors among many nutrients, focused on beta-alanine. It is also known that Salmonella requires beta-alanine from many other studies. The authors have done in vitro RAW macrophage infection assays and In vivo mouse infection assays to see the life of Salmonella in the presence of beta-alanine. They concluded by comprehending that beta-alanine modulates the expression of many genes including zinc transporters which is required for pathogenesis.

[Editors' note: The authors have appropriately addressed the previous reviewers' concerns.]

Reviewer #3 (Public review):

The dogma in the Trypanosome field is that transmission by Tsetse flies is ensured by stumpy forms. This has been recently challenged by the Engstler lab (Schuster et al. ), who showed that slender forms can also be transmitted by teneral flies. In this work, the authors aimed to test whether transmission by slender forms is possible and frequent. The authors observed that most stumpy forms infections with teneral and adult flies were successful while only 1 out of 24 slender form infections were successful.

The comparison of midgut infection in adult vs teneral flies was significant in most of the conditions. However, the critical comparison is still missing: within each type of fly (adult or teneral), was the MG infection significantly different between slender and stumpy forms?

Figure 2 convincingly demonstrates the effect of the metabolite N-acetylglucosamine on Tsetse infection. This addition helps better integrate the study with previous work. I thank the authors for their effort in performing this experiment.

It is still remains unknown why this work and Schuster et al. reached different conclusions. As a result it remains unclear in which conditions slender forms could be important for transmission. Several variables could explain differences between the two groups: the strain used, the presence or absence of glutathione, how Tsetse colonies were maintained, thorough molecular and cellular characterisation of slender and stumpy forms (to avoid using intermediate forms as slender forms), comparison to recent field parasite strains.

Reviewer #2 (Public review):

Summary:

The authors assemble 222 publicly available bone marrow single-cell RNA sequencing samples from healthy donors and primary AML, including pediatric, adolescent, and adult patients at diagnosis. Focusing on one specific subtype, t(8;21), which, despite affecting all age classes, is associated with better prognosis and drug response for younger patients, the authors investigate if this difference is reflected also in the transcriptomic signal. Specifically, they hypothesize that the pediatric and part of the young population acquires leukemic mutations in utero, which leads to a different leukemogenic transformation and ultimately to differently regulated leukemic stem cells with respect to the adult counterpart. The analysis in this work heavily relies on regulatory network inference and clustering (via SCENIC tools), which identifies regulatory modules believed to distinguish the pre-, respectively, post-natal leukemic transformation. Bulk RNA-seq and scATAC-seq datasets displaying the same signatures are subsequently used for extending the pool of putative signature-specific TFs and enhancer elements. Through gene set enrichment, ontology, and perturbation simulation, the authors aim to interpret the regulatory signatures and translate them into potential onset-specific therapeutic targets. The putative pre-natal signature is associated with increased chemosensitivity, RNA splicing, histone modification, stem-ness marker SMARCA2, and potentially maintained by EP300 and BCLAF1.

Strengths:

The main strength of this work is the compilation of a pediatric AML atlas using the efficient Cellxgene interface. Also, the idea of identifying markers for different disease onsets, interpreting them from a developmental angle, and connecting this to the different therapy and relapse observations, is interesting. The results obtained, the set of putative up-regulated TFs, are biologically coherent with the mechanisms and the conclusions drawn. I also appreciate that the analysis code was made available and is well documented.

Weaknesses:

There were fundamental flaws in how methods and samples were applied, a general lack of critical examination of both the results and the appropriateness of the methods for the data at hand, and in how results were presented. In particular:

(1) Cell type annotation:

a) The 2-phase cell type annotation process employed for the scRNA-seq sample collection raised concerns. Initially annotated cells are re-labeled after a second round with the same cell types from the initial label pool (Figure 1E). The automatic annotation tools were used without specifying the database and tissue atlases used as a reference, and no information was shown regarding the consensus across these tools.

b) Expression of the CD34 marker is only reported as a selection method for HSPCs, which is not in line with common practice. The use of only is admitted as a surface marker, while robust annotation of HSPCs should be done on the basis of expression of gene sets.

c) During several analyses, the cell types used were either not well defined or contradictory, such as in Figure 2D, where it is not clear if pySCENIC and AUC scores were computed on HSPCs alone or merged with CMPs. In other cases, different cell type populations are compared and used interchangeably: comparing the HSPC-derived regulons with bulk (probably not enriched for CD34+ cells) RNA samples could be an issue if there are no valid assumptions on the cell composition of the bulk sample.

(2) Method selection:

a) The authors should explain why they use pySCENIC and not any other approach. They should briefly explain how pySCENIC works and what they get out in the main text. In addition they should explain the AUCell algorithm and motivate its usage.

b) The obtained GRN signatures were not critically challenged on an external dataset. Therefore, the evidence that supports these signatures to be reliable and significant to the investigated setting is weak.

(3) There are some issues with the analysis & visualization of the data.

(4) Discussion:

a) What exactly is the 'regulon signature' that the authors infer? How can it be useful for insights into disease mechanisms?

b) The authors write 'Together this indicates that EP300 inhibition may be particularly effective in t(8;21) AML, and that BCLAF1 may present a new therapeutic target for t(8;21) AML, particularly in children with inferred pre-natal origin of the driver translocation.' I am missing a critical discussion of what is needed to further test the two targets. Put differently: Would the authors take the risk of a clinical study given the evidence from their analysis?

Reviewer #2 (Public review):

Summary:

This work aims to characterize the neural signaling cascade underlying the initiation of metamorphosis in Ciona larvae. Combining gene-specific functional analyses, pharmacological experiments, and live imaging approaches, the authors identify the molecular players downstream of GABA to initiate Ciona metamorphosis. The results of this study will serve as a useful framework for future research on animal metamorphosis.

Strengths:

Taking advantage of the Ciona model system, the authors meticulously conducted genetic manipulation and pharmacological experiments to test the epistatic relationships among the signaling players controlling the initiation of Ciona metamorphosis. The experiments were well designed, and the results were convincing. Based on the experimental data, the final working model proposed by the authors will server as an important foundation for further investigation on metamorphosis controls in Ciona and other marine invertebrate larvae.

Weaknesses:

In this revised manuscript, the authors have greatly improved the descriptions of their experimental results, and have clarified my previous concerns. I do not have further comments on "weaknesses".

Reviewer #2 (Public review):

Summary:

The authors combine a clever use of historical clinical data on infection duration in immunologically naive individuals and queuing theory to infer the force of infection (FOI) from measured multiplicity of infection (MOI) in a sparsely sampled setting. They conduct extensive simulations using agent based modeling to recapitulate realistic population dynamics and successfully apply their method to recover FOI from measured MOI. They then go on to apply their method to real world data from Ghana before and after an indoor residual spraying campaign.

Strengths:

- The use of historical clinical data is very clever in this context<br /> - The simulations are very sophisticated with respect to trying to capture realistic population dynamics<br /> - The mathematical approach is simple and elegant, and thus easy to understand

Weaknesses:

- The assumptions of the approach are quite strong, and the authors have made clear that applicability is constrained to individuals with immune profiles that are similar to malaria naive patients with neurosyphilis. While the historical clinical data is a unique resource and likely directionally correct, it remains somewhat dubious to use the exact estimated values as inputs to other models without extensive sensitivity analysis.

Reviewer #3 (Public review):

Cellulose is a major component of the primary cell wall of growing cells and it is made by cellulose synthases (CESAs) organized into multi-subunit complexes in the plasma membrane. Previous results have resolved the structure of secondary cell wall CESAs, which are only active in a subset of cells. Here, the authors evaluate the structure of CESAs from soybean (Glycine max, Gm) via cryo-EM and compare these structures to secondary cell wall CESAs. First, they express a select member of the GmCESA1, GmCESA3, or GmCESA6 families in insect cells, purified these proteins as both monomers and homotrimers, and demonstrated their capacity to incorporate 3H-labelled glucose into cellulase-sensitive product in a pH and divalent cation (e.g., Mg2+) -dependant fashion (Figure 2). Although CESA1, CESA3, and a CESA6-like isoforms are essential for cellulose synthesis in Arabidopsis, in this study, monomers and homotrimers both showed catalytic activity, and there was more variation between individual isoforms than between their oligomerization states (i.e., CESA3 monomers and trimers showed similar activities, which were substantially different from CESA1 monomers or trimers).

They next use cryo-EM to solve the structure of each homotrimer to ~3.0 to 3.3 A (Figure 3). They compare this with PttCESA8 and find important similarities, such as the unidentified density at a positively-charged region near Arg449, Lys452, and Arg453; and differences, such as the position and relatively low resolution (suggesting higher flexibility) of TM7, which presumably creates a large lateral lipid-exposed channel opening, rather than the transmembrane pore in PttCESA8. Like PttCESA8, an oligosaccharide in the translocation channel was co-resolved with the protein structure. Neither the N-terminal domains nor the CSRs (a plant-specific insert into the cytosolic loop between TM2 and TM3) are resolved well.

Several previous models have proposed that the cellulose synthase complexes may be composed of multiple heterotrimers, but since the authors were able to isolate beta-glucan-synthesizing homotrimers, their results challenge this model. Using the purified trimers, the authors investigated how the CESA homotrimers might assemble into higher order complexes. They detected interactions between each pair of CESA homotrimers via pull down assays (Figure 4), although these same interactions were also detected among monomers (Supplemental Figure 4). Neither catalytic activity nor these inter-homotrimer interactions required the N-terminal domain (Figure 5). When populations of homotrimers were mixed, they formed larger aggregations in vitro (Figure 6) and displayed increased activity, compared to the predicted additive activity of each enzyme alone (Figure 7). Intriguingly, this synergistic behavior is observed even when one trimer is chemically inactivated before mixing (supplemental figure 7), suggesting that the synergistic effects are due to structural interactions.

The main strength of this manuscript is its detailed characterization of the structure of multiple CESAs implicated in primary cell wall synthesis, which complements previous studies of secondary cell wall CESAs. They provide a comprehensive comparison of these new structures with previously resolved CESA structures and discuss several intriguing similarities and differences. The synergistic activity observed when different homotrimers are mixed is a particularly interesting result. These results provide fundamental in vitro support for a cellulose synthase complex comprised of a hexamer of CESA homotrimers.

The main weakness of the manuscript is that the authors' evidence that these proteins make cellulose in vitro is limited to beta-glucanase-sensitive digestion of the product. Previous reports characterizing CESA structures have used multiple independent methods: sensitivity and resistance of the product to various enzymes, linkage analysis, and importantly, TEM of the product to ensure that it makes genuine cellulose microfibrils, rather than amorphous beta-glucan.

Reviewer #2 (Public review):

Summary:

In this manuscript, Li and colleagues study the fate of endothelial cells in a mouse model of ischemic stroke. Using genetic lineage tracing approaches, they find that endothelial cells give rise to non-endothelial cells, which they term "E-pericytes." They further show that depleting these cells exacerbates blood-brain barrier leakage and worsens functional recovery. The authors also provide evidence that endothelial-to-mesenchymal transition, myeloid cell-derived TGFβ1, and endothelial TGFβRII are involved in this process. These are potentially interesting findings, however, the experimental evidence that endothelial cells undergo transdifferentiation to non-endothelial cells is weak, as is the evidence that these cells are pericytes. Addressing this foundational weakness will facilitate interpretation of the other findings.

In this revised manuscript, the authors corrected labeling errors and included negative controls for flow cytometry and immunohistochemistry data. They did not, however, substantively address the major weaknesses below related to rigorously demonstrating the cellular origin and identity of "E-pericytes."

Strengths:

(1) The authors address an important question about blood vessel function and plasticity in the context of stroke.

(2) The authors use a variety of genetic approaches to understand cell fate in the context of stroke. Particularly commendable is the use of several complementary lineage tracing strategies, including an intersectional strategy requiring both endothelial Cre activity and subsequent mural cell NG2 promoter activity.

(3) The authors address upstream cellular and molecular mechanisms, including roles for myeloid-derived TGFβ.

Weaknesses:

(1) The authors use Cdh5-CreERT2; Ai47 mice to permanently label endothelial cells and their progeny with eGFP. They then isolate eGFP+ cells from control and MCAO RP7D and RP34D brains, and use single cell RNA-seq to identify the resulting cell types. Theoretically, all eGFP+ cells should be endothelial cells or their progeny. This is a very powerful and well-conceived experiment. The authors use the presence of a pericyte cluster as evidence that endothelial to pericyte transdifferentiation occurs. However, pericytes are also present in the scRNA-seq data from sham mice, as are several other cell types such as fibroblasts and microglia. This suggests that pericytes and these other cell types might have been co-purified (e.g., as doublets) with eGFP+ endothelial cells during FACS and may not themselves be eGFP+. Pericyte-endothelial doublets are common in scRNA-seq given that these cell types are closely and tightly associated. Additionally, tight association (e.g., via peg-socket junctions) can cause fragments of endothelial cells to be retained on pericytes (and vice-versa) during dissociation. Finally, it is possible that after stroke or during the dissociation process, endothelial cells lyse and release eGFP that could be taken up by other cell types. All of these scenarios could lead to purification of cells that were not derived (transdifferentiated) from endothelial cells. Authors note that the proportion of pericytes increased in the stroke groups, but it does not appear this experiment was replicated and thus this conclusion is not supported by statistical analysis. The results of pseudotime and trajectory analyses rely on the foundation that the pericytes in this dataset are endothelial-derived, which, as discussed above, has not been rigorously demonstrated.

(2) I have the same concern regarding inadvertent purification of cells that were not derived from endothelial cells in the context of the bulk RNA-seq experiment (Fig. S4), especially given the sample-to-sample variability in gene expression in the RP34D, eGFP+ non-ECs group (e.g., only 2/5 samples are enriched for mesenchymal transcription factor Tbx18, only 1/5 samples are enriched for mural cell TF Heyl). If the sorted eGFP+ non-ECs were pericytes, I would expect a strong and consistent pericyte-like gene expression profile.

(3) Authors use immunohistochemistry to understand localization, morphology, and marker expression of eGFP+ cells in situ. The representative "E-pericytes" shown in Fig. 3A-D are not associated with blood vessels, and the authors' quantification also shows that the majority of such cells are not vessel-associated ("avascular"). By definition, pericytes are a component of blood vessels and are embedded within the vascular basement membrane. Thus, concluding that these cells are pericytes ("E-pericytes") may be erroneous.

(4) CD13 flow cytometry and immunohistochemistry are used extensively to identify pericytes. In the context of several complementary lineage tracing strategies noted in Strength #2, CD13 immunohistochemistry is the only marker used to identify putative pericytes (Fig. S3J-M). In stroke, CD13 is not specific to pericytes; dendritic cells and other monocyte-derived cells express CD13 (Anpep) in mouse brain after stroke (PMID: 38177281, https://anratherlab.shinyapps.io/strokevis/).

(5) Authors conclude that "EC-specific overexpression of the Tgfbr2 protein by a virus (Tgfbr2) decreases Evans blue leakage, promotes CBF recovery, alleviates neurological deficits and facilitates spontaneous behavioral recovery after stroke by increasing the number of E-pericytes." All data in Fig. 10, however, compare endothelial Tgfbr2 overexpression to a DsRed overexpression control. There is no group in which Tgfbr2 is overexpressed but "E-pericytes" are eliminated with DTA (this is done in Fig. 9B, but this experiment lacks the Tgfbr2 overexpression-only control). Thus, the observed functional outcomes cannot be ascribed to "E-pericytes"; it remains possible that endothelial Tgfbr2 overexpression affects EB leakage, CBF, and behavior through alternative mechanisms.

In response to this comment, authors wrote: "in Figures 9A-B, we observed no significant difference in Evans blue leakage between the Tgfbr2 overexpression group and the Tgfbr2 overexpression + DTA group (P=0.8153), this suggests that the impact of Tgfbr2 overexpression on the blood-brain barrier (BBB) is primarily attributed from the E-pericytes generated by Tgfbr2 expression."

I do not see data from a Tgfbr2 overexpression-only group in Fig. 9B. Further, I do not understand authors' logic: If the mechanism by which EC Tgfbr2 overexpression acts to reduce BBB leakage is by increasing the number of "E-pericytes," depleting "E-pericytes" with DTA in this context should increase BBB leakage.

(6) Single-cell and bulk RNA-seq data are not available in a public repository (such as GEO). Depositing these data would facilitate their independent reevaluation and reuse.

In response to this comment, authors indicated they submitted data to GEO, but did not provide an accession number.

Reviewer #2 (Public review):

Summary:

In this manuscript, Tolossa et al. analyze Inter-spike intervals from various freely available datasets from the Allen Institute and from a dataset from Steinmetz et al.. They show that they can modestly decode between gross brain regions (Visual vs. Hippocampus vs. Thalamus), and modestly separate sub areas within brain regions (DG vs. CA1 or various visual brain areas). The core result is that a multi-layer perceptron trained on the ISI distributions can modestly classify different brain areas and perhaps in a reasonably compelling way generalize across animals. The result is interesting but the exact problem formulation still feels a tad murky to me because I am worried the null is a strawman and I'm unsure if anyone has ever argued for this null hypothesis ("the impact of anatomy on a neuron's activity is either nonexistent or unremarkable"). Given the patterns of inputs to different brain areas and the existence of different developmental origin and different cell types within these areas, I am unclear why this would be a good null hypothesis. Nevertheless, the machine learning is reasonable, and the authors demonstrate that a nonlinear population based classifier can pull out reasonable information about the brain area and layer.

Strengths:

The paper is reasonably well written, and the definitions are quite well done. For example, the authors clearly explained transductive vs. inductive inference in their decoders. E.g., transductive learning allows the decoder to learn features from each animal, whereas inductive inference focuses on withheld animals and prioritizes the learning of generalizable features. The authors walk the reader through various analyses starting as simply as PCA, then finally showing a MLP trained on ISI distributions and PSTHs performs modestly well in decoding brain area. The key is ISI distributions work well in inductive settings for generalizing from one mouse to the other.

Weaknesses:

As articulated in my overall summary, I still found the null hypothesis a tad underwhelming. I am not sure this is really a valid null hypothesis ("the impact of anatomy on a neuron's activity is either nonexistent or unremarkable"), although in the statistical sense it is fine. The authors took on board some of the advice from the first review and clarified the paper but there are portions that are unnecessarily verbose (e.g., "Beyond fundamental scientific insight, our findings may be of benefit in various practical applications, such as the continued development of brain-machine interfaces and neuroprosthetics"). Also, given that ISIs cannot separate between visual areas, why is the statement that these are conserved. I still find it somewhat underwhelming that the thalamus, hippocampus , and visual cortex have different ISI distributions. Multiple researchers have reported similar things in cortex perhaps without the focus on decoding area from these ISI distributions.

All in all, it is an interesting paper with the notion that ISI distributions can modestly predict brain area and layer. It could have some potential for a tool for neuropixels, although this needs to be developed further for this use case.

Reviewer #2 (Public review):

This paper tests the hypothesis that perceptual switches during the presentation of ambiguous stimuli are accompanied by changes in neuromodulation that alter neural gain and trigger abrupt changes in brain activity. To test this hypothesis, the study combines pupillometry, artificial recurrent network (RNN) analysis and fMRI recording. In particular, the study uses methods of energy landscape analysis inspired by physics, which is particularly interesting.

Strengths<br /> - The authors should be commended for combining different methods (pupillometry, RNNs, fMRI) to test their hypothesis. This combination provides a mechanistic insight into perceptual switches in the brain and artificial neural networks.<br /> - The study combines different viewpoints and fields of scientific literature, including neuroscience, psychology, physics, dynamical systems. In order to make this combination more accessible to the reader, the different aspects are presented in a pedagogical way to be accessible to all fields.<br /> - This combination of methods and viewpoints is rarely done, so it is very useful.<br /> - The authors introduce dynamic gain modulation in their recurrent neural network, which is novel. They devote a section of the paper to studying the dynamics, fixed points and convergence of this type of network.

Weaknesses<br /> - The study may not be specific to perceptual switches. This is because the study relies on a paradigm in which participants report when they identify a switch in the item category. Therefore, it is unclear whether the effects reported in the paper are related to the perceptual switch itself, to attention, or to the detection of behaviourally relevant events. The authors are cautious and explicitly acknowledge this point in their study.<br /> - The demonstration of the causal role of gain modulation in perceptual switches is partial. This causality is clearly demonstrated in the simulation work with the RNN. However, it is not fully demonstrated in the pupil analysis and the fMRI analysis. One reason is that this work is correlative (which is already very informative).<br /> - Some effects may reflect the expectation of a perceptual switch rather than the perceptual switch itself. To mitigate this risk, the design of the fMRI task included catch trials, in which no switch occurs, to reduce the expectation of a switch. The pupil study, however, did not include such catch trials.<br /> - The paper uses RNN-based modelling to provide mechanistic insight into the role of gain modulation in perceptual switches. However, the RNN solves a task that differs from that performed by human participants, which may limit the explanatory value of the model. The RNN is provided with two inputs characterising the sensory evidence supporting the first and last image category in the sequence (e.g. plane and shark). In contrast, observers in the task don't know in advance the identity of the last image at the beginning of the sequence. The brain first receives sensory evidence about the image category (e.g. plane) with which the sequence begins, which is very easy to recognise, then it sees a sequence of morphed images and has to discover what the final image category will be. To discover the final image category, the brain considers several possibilities for the second images (it is a shark?, a frog?, a bird?, etc.), rather than comparing the likelihood of just two categories. This search process among many alternatives and the perceptual switch in the task is therefore different from the competition between only two inputs in the RNN.<br /> - Another aspect of the motivation for the RNN model remains unclear. The authors introduce dynamic gain modulation in the RNN, but it is not clear what the added value of dynamic gain modulation is. Both static (Fig. S1) and dynamic (Fig. 2F) gain modulation lead to the predicted effect: faster switching when the gain is larger.<br /> - The authors are to be commended for addressing their research questions with multiple tools and approaches. There are links between the different parts of the study. The RNN and the pupil are linked by the notion of gain modulation, the RNN and the fMRI analysis are linked by the study of the energy landscape, the fMRI study and the pupil study are indirectly linked by previous work for this group showing that the peak in LC fMRI activity precedes a flattening of the energy landscape. These links are very interesting but could have been stronger and more complete.

Comments on revisions:

I thank the authors for their responses.<br /> My review presents points that the authors themselves present as weaknesses or limitations. It also includes points that cannot be addressed in a revision (e.g. causality).<br /> Regarding the fact that the RNN only considers two categories, whereas subjects consider more categories (because they don't know the final image), I have toned down my remark (removing "markedly" different, removing the fact that the hypothesis space is vast given that participants have some priors). I also removed the qualifier "mechanistically" different, because it can be understood in different ways. The point remains that the proposed model has 2 inputs, the corresponding network in the brain has >2 inputs (because it considers more categories than the RNN), which is different, and which is the point of my remark. I think it may limit the value of the model, but I don't think it is not "sensible".

Reviewer #2 (Public review):

Summary:

Baniulyte and Wade describe how translation of an 8-codon uORF denoted toiL upstream of the topAI-yjhQP operon is responsive to different ribosome-targeting antibiotics, consequently controlling translation of the TopAI toxin as well as Rho-dependent termination with the gene.

Strengths:

The authors used multiple different approaches such as a genetic screen to identify factors such as 23S rRNA mutations that affect topA1 expression and ribosome profiling to examine the consequences of various antibiotics on toiL-mediated regulation.

Weaknesses: Future experiments will be needed to better understand the physiological role of the toiL-mediated regulation and elucidate the mechanism of specific antibiotic sensing.

The results are clearly described, and the revisions have helped to improve the presentation of the data.

Reviewer #3 (Public review):

Summary:

The authors were trying to show that a novel neuronal metallothionein of poorly defined function, GIF/MT3, is actually heavily persulfidated in both the Zn-bound and apo (metal-free) forms of the molecule as purified from a heterologous (bacterial) or native host. Evidence in support of this conclusion is strong, with both spectroscopic and mass spectrometry evidence strongly consistent with this general conclusion. The authors would appear to have achieved their aims.

Strengths:

The analytical data in support of the author's primary conclusions are strong. The authors also provide some modeling evidence that supports the contention that MT3 (and other MTs) can readily accommodate a sulfane sulfur on each of the 20 cysteines in the Zn-bound structure, with little perturbation of the overall structure. This is not the case with Cys trisulfides, which suggests that the persulfide-metallated state is clearly positioned at lower energy relative to the immediately adjacent thiolate- or trisulfidated metal coordination complexes.

Weaknesses:

The biological significance of the findings is not entirely clear. On the one hand, the analytical data are solid (albeit using a protein derived from a bacterial over-expression experiment), and yes, it's true that sulfane S can protect Cys from overoxidation, but everything shown in the summary figure (Fig. 9D) can be done with Zn release from a thiol by ROS, and subsequent reduction by the Trx/TR system. In addition, it's long been known that Zn itself can protect Cys from oxidation. I view this as a minor shortcoming that will motivate follow-up studies.

Impact:

The impact will be high since the finding is potentially disruptive to the MT field for sure. The sulfane sulfur counting experiment (the HPE-IAM electrophile trapping experiment) may well be widely adopted by the field. Those in the metals field always knew that this was a possibility, and it will interesting to see the extent to which metal binding thiolates broadly incorporate sulfane sulfur into their first coordination shells.

Comments on revisions:

The revised manuscript is only slightly changed from the original, with the inclusion of a supplementary figure (Fig. S2) and minor changes in the text. The authors did not choose to carry out the quantitative Zn binding experiment (which I really wanted to see), but given the complexities of the experiment, I'll let it go.

Reviewer #2 (Public review):

Summary:

In 2021 (PMID: 33503405) and 2024 (PMID: 38578830) Constantinou and colleagues published two elegant papers in which they demonstrated that the Topbp1 checkpoint adaptor protein could assemble into mesoscale phase-separated condensates that were essential to amplify activation of the PIKK, ATR, and its downstream effector kinase, Chk1, during DNA damage signalling. A key tool that made these studies possible was the use of a chimeric Topbp1 protein bearing a cryptochrome domain, Cry2, which triggered condensation of the chimeric Topbp1 protein, and thus activation of ATR and Chk1, in response to irradiation with blue light without the myriad complications associated with actually exposing cells to DNA damage.

In this current report Morano and co-workers utilise the same optogenetic Topbp1 system to investigate a different question, namely whether Topbp1 phase-condensation can be inhibited pharmacologically to manipulate downstream ATR-Chk1 signalling. This is of interest, as the therapeutic potential of the ATR-Chk1 pathway is an area of active investigation, albeit generally using more conventional kinase inhibitor approaches.

The starting point is a high throughput screen of 4730 existing or candidate small molecule anti-cancer drugs for compounds capable of inhibiting the condensation of the Topbp1-Cry2-mCherry reporter molecule in vivo. A surprisingly large number of putative hits (>300) were recorded, from which 131 of the most potent were selected for secondary screening using activation of Chk1 in response to DNA damage induced by SN-38, a topoisomerase inhibitor, as a surrogate marker for Topbp1 condensation. From this the 10 most potent compounds were tested for interactions with a clinically used combination of SN-38 and 5-FU (FOLFIRI) in terms of cytotoxicity in HCT116 cells. The compound that synergised most potently with FOLFIRI, the GSK3-beta inhibitor drug AZD2858, was selected for all subsequent experiments.

AZD2858 is shown to suppress the formation of Topbp1 (endogenous) condensates in cells exposed to SN-38, and to inhibit activation of Chk1 without interfering with activation of ATM or other endpoints of damage signalling such as formation of gamma-H2AX or activation of Chk2 (generally considered to be downstream of ATM). AZD2858 therefore seems to selectively inhibit the Topbp1-ATR-Chk1 pathway without interfering with parallel branches of the DNA damage signalling system, consistent with Topbp1 condensation being the primary target. Importantly, neither siRNA depletion of GSK3-beta, or other GSK3-beta inhibitors were able to recapitulate this effect, suggesting it was a specific non-canonical effect of AZD2858 and not a consequence of GSK3-beta inhibition per se.

To understand the basis for synergism between AZD2858 and SN-38 in terms of cell killing, the effect of AZD2858 on the replication checkpoint was assessed. This is a response, mediated via ATR-Chk1, that modulates replication origin firing and fork progression in S-phase cell under conditions of DNA damage or when replication is impeded. SN-38 treatment of HCT116 cells markedly suppresses DNA replication, however this was partially reversed by co-treatment with AZD2858, consistent with the failure to activate ATR-Chk1 conferring a defect in replication checkpoint function.

Figures 4 and 5 demonstrate that AZD2858 can markedly enhance the cytotoxic and cytostatic effects of SN-38 and FOLFIRI through a combination of increased apoptosis and growth arrest according to dosage and treatment conditions. Figure 6 extends this analysis to cells cultured as spheroids, sometimes considered to better represent tumor responses compared to single cell cultures.

Significance:

Liquid phase separation of protein complexes is increasingly recognised as a fundamental mechanism in signal transduction and other cellular processes. One recent and important example was that of Topbp1, whose condensation in response to DNA damage is required for efficient activation of the ATR-Chk1 pathway. The current study asks a related but distinct question; can protein condensation be targeted by drugs to manipulate signalling pathways which in the main rely on protein kinase cascades?

Here, the authors identify an inhibitor of GSK3-beta as a novel inhibitor of DNA damage-induced Topbp1 condensation and thus of ATR-Chk1 signalling.

This work will be of interest to researchers in the fields of DNA damage signalling, biophysics of protein condensation, and cancer chemotherapy.

Comments on latest version:

Morano et al. have revised their manuscript in response to the points raised by reviewer #3 as follows.

1) Fig. 2E: Correcting the previously erroneous labelling of this Fig. makes it match the textual description.

2) Figs 3A and B: The revised textual description of the flow cytometry BrdU incorporation is now precise.

3) Fig. 3E: Removing the suspect WB images is a pragmatic decision that does not significantly affect the overall conclusions of the paper.

4) Fig. 3D: Despite its puzzling appearance this data is now described accurately in the text as "DSBs remained elevated after the combined treatment" rather than "increased after the combined treatment. A more convincing increase in the presumed damaged DNA band is evident in Fig. 4D when AZD2858 is combined with a much lower concentration of SN38 (1.5nM) which could mean that the concentration used in Fig. 3D (300nM) induced maximal damage that could not be further enhanced.

Reviewer #2 (Public review):

Despite over 50 years of investigation, our understanding of how the ubiquitous heat shock response, governed by the transcription factor HSF1, was regulated was minimal. In recent years, a coordinated yet simple negative feedback circuit has been elucidated in high detail that centers on the chaperone Hsp70 as a direct-binding inhibitor of HSF1 transcriptional activation. However, roles for the obligatory Hsp70 J-domain partner co-chaperones are currently poorly understood. The present study applies several orthogonal techniques to the question and uncovers an unexpected role for the nuclear JDP Apj1 in attenuation of the heat shock response (HSR) via removal of Hsf1 from HSEs in heat shock gene promoter regions. Interestingly, Apj1 appears to play no role in initiating repression of Hsf1, as null mutants do not exhibit constitutive derepression of the HSR. This role is likely filled by the general nucleo/cytoplasmic JDP Ydj1, as previously reported. These results enhance understanding of HSR regulation and underscore the pivotal role that chaperones play in controlling pro-survival gene expression.

Overall, the work is exceptionally well done and controlled, and the results are properly and appropriately interpreted. Several of the approaches, while powerful, are somewhat indirect (i.e., following gene expression via ribosomal profiling) but ultimately provide a compelling answer to the main question being asked. However, at the end of the day, there is really only one major finding here: Apj1 regulates Hsf1 attenuation via Hsp70. That finding is strongly supported by the experimental data but lacks the one piece of mechanistic evidence found in other recent papers - differential binding of Ssa1/2 to Hsf1 at either the N- or C-terminal binding sites.

Reviewer #2 (Public review):

I would like to thank the authors for the revision and the input they invested in this study.

With the revised text of the study, my earlier criticism holds, and your arguments about the counterfactual approach are irrelevant to that. The recent rise of the counterfactual approach might likely mirror the fact that there are too many scientists behind their computers, and few go into the field to collect in situ data. Studies like the one presented here are a good intellectual exercise but the real impact is questionable. All your main conclusions are inferred from published studies on 7! bird species. In addition, spatial sampling in those seven species was not ideal in relation to your target questions. Thus, no matter how fancy your findings look, the basic fact remains that your input data were for 7 bird species only! Your conclusion, „our study provides a novel understanding of how QTP shapes migration patterns of birds, " is simply overstretching.

The way you respond to my criticism on L 81-93 is something different than what you admit in the rebuttal letter. The text of the ms is silent about the drawbacks and instead highlights your perspective. I understand you; you are trying to sell the story in a nice wrapper. In the rebuttal you state: „we assume species' responses to environments are conservative and their evolution should not discount our findings." But I do not see that clearly stated in the main text.

In your rebuttal, you respond to my criticism of "No matter how good the data eBird provides is, you do not know population-specific connections between wintering and breeding sites" when you responded: ... "we can track the movement of species every week, and capture the breeding and wintering areas for specific populations" I am having a feeling that you either play with words with me or do not understand that from eBird data nobody will be ever able to estimate population-specific teleconnections between breeding and wintering areas. It is simply impossible as you do not track individuals. eBird gives you a global picture per species but not for particular populations. You cannot resolve this critical drawback of your study. I am sorry that you invested so much energy into this study, but I see it as a very limited contribution to understanding the role of a major barrier in shaping migration.

My modest suggestion for you is: go into the field. Ideally use bird radars along the plateau to document whether the birds shift the directions when facing the barrier.

Reviewer #2 (Public review):

Summary :

The paper proposes a model to explain the learning that occurs in brain-computer interface (BCI) tasks when animals need to adapt to novel BCI decoders. The model consists of a network formulation of the "re-aiming" learning strategy, which assumes that BCI learning does not modify the underlying neural circuitry, but instead occurs through a reorganization of existing neural activity patterns.

The authors formalize this in a recurrent neural network (RNN) model, driven by upstream inputs that live in a low-dimensional space.

They show that modelling BCI learning as reorganization of these upstream inputs can explain several experimental findings, such as the difference in the ability of animals to adapt to within vs outside-manifold perturbations, biases in the decoded behaviour after within-manifold perturbations, or qualitative changes in the neural responses observed during credit assignment rotation perturbations or operant conditioning of individual neurons.

Overall, while the idea of re-aiming as a learning strategy has previously been proposed in the literature, the authors show how it can be formalized in a network model, which allows for more direct comparisons to experimental data.

Strengths:

The paper is very well written. The presentation of the model is clear, and the use of vanilla RNN dynamics driven by upstream inputs that are constant in time is consistent with the broader RNN modeling literature.

The main value of the paper lies in the fact that it proposes a network implementation for a learning strategy that had been proposed previously. The network model has a simple form, but the optimization problem is performed in the space of inputs, which requires the authors to solve a nonlinear optimization problem in that space.

While some of the results (eg the fact that the model can adapt to within but not outside-manifold perturbations) are to be expected based on the model assumptions, having a network model allows to make more direct and quantitative comparisons to experiments, to investigate analytically how much the dimension of the output is constrained by the input, and to make predictions that can be tested in data.

The authors perform such comparisons across three different experiments. The results are clearly presented, and the authors show that they hold for various RNN connectivities.

Weaknesses :

The authors mention alternative models (eg, based on synaptic plasticity in the RNN and/or input weights) that can explain the same experimental data that they do, they do not provide any direct comparisons to those models.

Thus, the main argument that the authors have in favor of their model is the fact that it is more plausible because it relies on performing the optimization in a low-dimensional space. It would be nice to see more quantitative arguments for why the re-aiming strategy may be more plausible than synaptic plasticity (either by showing that it explains data better, or explaining why it may be more optimal in the context of fast learning).

In particular, the authors model the adaptation to outside-manifold perturbations (OMPs) through a "generalized re-aiming strategy". This assumes the existence of additional command variables, which are not used in the original decoding task, but can then be exploited to adapt to these OMPs. While this model is meant to capture the fact that optimization is occurring in a low-dimensional subspace, the fact that animals take longer to adapt to OMPs suggests that WMPs and OMPs may rely on different learning mechanisms, and that synaptic plasticity may actually be a better model of adaptation to OMPs. It would be important to discuss how exactly generalized re-aiming would differ from allowing plasticity in the input weights, or in all weights in the network. Do those models make different predictions, and could they be differentiated in future experiments?

Reviewer #2 (Public review):

Summary:

I am not familiar with mathematical modeling of gene expression, so I will evaluate this manuscript solely from a biological point of view.

Kerlin et al. combined single-molecule RNA FISH and mathematical modeling approaches to quantitatively characterize changes in the transcriptional dynamics of three neighboring genes at the FOS locus in response to estradiol (E2) stimulation. They showed that the neighboring JDP2 and BATF genes, located on the same side of the TAD boundary, exhibit highly coordinated bursting dynamics. While FOS and JDP2/BATF are strongly insulated (~7:1 intra-to-inter-domain contact ratio) by the TAD boundary, correlated bursting dynamics were still observed between these gene pairs, suggesting that enhancers can bypass strong insulation sites. The authors proposed that burst co-occurrence arises from the activity of ERα-bound enhancers at the locus. They also proposed that the burst size correlation between two neighboring genes located on the same side of the TAD boundary results from local spreading of histone marks.

Strengths:

The direct visualization of coordinated transcriptional bursting across a strong insulation site is novel. This finding was carefully analyzed using the mathematical framework developed by the authors.

Weaknesses:

Several models were proposed based on single-molecule RNA FISH analysis of the FOS locus, but the generality of these findings remains uncertain. The proposed models were not directly tested through follow-up experiments, leaving the authors' conclusions largely speculative.

Reviewer #2 (Public review):

Summary:

While immune cell distribution in tuberculosis (TB) is well documented, research on its disruption in diabetes-tuberculosis (DM-TB) comorbidity remains limited. In this study, Chaudhary et al. explore immune cell perturbations in DM-TB using single-cell RNA sequencing (scRNA-seq), providing key insights into the impaired host immune response. By elucidating the molecular mechanisms underlying immune dysfunction in DM-TB, this study addresses an important knowledge gap. The study demonstrates that diabetes impairs lung immune cell infiltration and contributes to a dampened immune response against Mycobacterium tuberculosis. Reduced Th1 and M1 macrophage populations indicate a compromised ability to mount an effective pro-inflammatory response, which is essential for TB control. The observed increase in IL-16 signaling and reduction in TNF and IFN-II responses suggest a shift toward a more immunosuppressive or dysregulated inflammatory state. The interplay between chronic inflammation, hyperglycemia, and dyslipidemia in diabetes further exacerbates immune dysfunction, reinforcing the idea that metabolic disorders significantly impact TB pathogenesis.

Strengths:

This well-designed study employs robust methodology, well-executed experiments, and a well-written manuscript. The use of scRNA-seq is a notable strength, offering high-resolution analysis of immune cell heterogeneity in the lung environment. Additionally, the study corroborates its findings in a long-term infection model, demonstrating that chronic M. tuberculosis (H37Rv) infection in diabetic mice leads to increased bacterial burden and worsened tissue pathology.

Weaknesses:

(1) The study focuses on CD3⁺ and CD11c⁺ cells but does not extensively examine other key immune players that may contribute to DM-TB pathogenesis. Given that diabetes affects multiple immune compartments, a broader immune profiling approach would provide a more comprehensive understanding.

(2) While the study identifies increased IL-16 signaling and reduced TNF/IFN-II responses, the precise molecular mechanisms driving these changes remain unclear. Further investigation into metabolic-immune crosstalk (e.g., how hyperglycemia affects immune cell differentiation and cytokine secretion) would strengthen the mechanistic depth of the findings.

(3) The study suggests targeting IL-16 and Th17 cells as potential therapeutic strategies; however, no experimental validation (e.g., testing IL-16 inhibitors in DM-TB models) is provided. Validating these interventions would enhance their translational relevance.

(4) Incorporating clinical samples (e.g., PBMCs from DM-TB patients) could help bridge the gap between murine and human studies, offering more translational insights into disease mechanisms.

Overall, this study provides valuable findings, but addressing these concerns would further strengthen its impact on understanding DM-TB immunopathogenesis.

Reviewer #2 (Public review):

Summary:

Garibova et al. investigated the conservation of sperm recognition and interaction with the egg envelope in two groups of distantly related animals: mammals (mouse) and fish (zebrafish). Previous work and key physiological differences between these two animal groups strongly suggest that mouse sperm would be incapable of interaction with the zebrafish egg envelope (chorion) and its constituent proteins, though homologous to the mammalian zona pellucida (ZP). Indeed, the authors showed that mouse sperm do not bind recombinant zebrafish ZP proteins nor the intact chorion. Surprisingly, however, mouse sperm are able to locate and bind to the zebrafish micropyle, a specialized canal within the chorion that serves as the egg's entry point for sperm. This study suggests that sperm attraction to the egg might be highly conserved from fish to mammals and depends on the presence of a still unknown glycosylated protein within the micropyle. The authors further demonstrate that mouse sperm are able to enter the micropyle and accumulate within the intrachorionic space, potentially through a CatSper-dependent mechanism.

Strengths:

The authors convincingly demonstrate that mouse sperm do not bind zebrafish ZP proteins or the chorion. Furthermore, they make the interesting observation that mouse sperm are able to locate and enter the zebrafish micropyle in an MP-dependent manner, which is quite unexpected given the large evolutionary distance between these species, the many physiological differences between mouse and zebrafish gametes, and the largely different modes of both fertilization and reproduction in these species. This may indicate that the sperm chemoattractant in the egg is conserved between mammals and fish; however, whether zebrafish sperm are attracted to mouse eggs was not tested.

Weaknesses:

The key weakness of this study lies in the rationale behind the overall investigation. In mammals, the zona pellucida (ZP) has been implicated in binding sperm in a taxon-specific manner, such that human sperm are incapable of binding the mouse ZP. Indeed, work by the corresponding author showed that this specificity is mediated by the N-terminal region of the ZP protein ZP2 (Avella et al., 2014). The N-termini of human and mouse ZP2 share 48% identity, which is higher than the overall identity between mouse and zebrafish ZP2, with the latter ortholog entirely lacking the N-terminal domain that is essential for sperm binding to the ZP. Given this known specificity for mouse vs. human sperm-ZP binding, it does not follow that mouse sperm would bind ZP proteins from not only a species that is much more distantly related, but also one that is not even a mammal, the zebrafish. Furthermore, the fish chorion does not play a role in sperm binding at all, while the mammalian ZP can bind sperm at any location. On the contrary, the zebrafish chorion prevents polyspermy by limiting sperm entry to the single micropyle.

In addition, though able to provide some information regarding the broad conservation of sperm-egg interaction mechanisms, the biological relevance of these findings is difficult to describe. Fish and mammals are not only two very distinct and distantly related animal groups, but also employ opposite modes of fertilization and reproduction (external vs. internal, oviparous vs viviparous). Fish gametes interact in a very different environment compared to mammals and lack many typically mammalian features of fertilization (e.g., sperm capacitation, presence of an acrosome, interaction with the female reproductive tract), making it difficult to make any physiologically relevant claims from this study. While this study may indicate conserved mechanisms of sperm attraction to the egg, the identity of the molecular players involved is not investigated. With this knowledge, the reader is forced to question the motivation behind much of the study.

During fertilization in fish, the sperm enters the micropyle and subsequently, the egg, as it is simultaneously activated by exposure to water. During egg activation, the chorion lifts as it separates from the egg and fills with water. This mechanism prevents supernumerary sperm from entering the egg after the successfully fertilizing sperm has bound and fused. In this study, the authors show that mouse sperm enter the micropyle and accumulate in the intrachorionic space. Whether any sperm successfully entered the egg is not addressed, and the status of egg activation is not reported. In Supplementary Videos 3-4, the egg shown has been activated for some time, as evident by the separation of yolk and cytoplasm, yet the chorion is only partially expanded (likely due to mouse IVF conditions). How multiple sperm were able to enter the micropyle but presumably not the egg is not addressed, yet this suggests that the zebrafish mechanism of blocking polyspermy (fertilization by multiple sperm) is not effective for mouse sperm or is rendered ineffective due to mouse IVF conditions. The authors do not discuss these observations in the context of either species' physiological process of fertilization, highlighting the lack of biological context in interpreting the results.

The authors further show that the zebrafish micropyle does not trigger the acrosome reaction in mouse sperm. Whether the acrosome reacts is not correlated with a sperm's ability to cross the micropyle opening, as both acrosome-intact and acrosome-reacted sperm were observed within the intrachorionic space. While the acrosome reaction is a key event during mammalian fertilization and is required for sperm to fertilize the egg, zebrafish sperm do not contain an acrosome. Thus, these results are particularly difficult to interpret biologically, bringing into question whether this observation has biological relevance or is a byproduct of egg activation/chorion lifting that indirectly draws sperm into the chorion.

The final experiments regarding CatSper1's role in mediating mouse sperm entry into the micropyle/chorion are not convincing. As no molecular interactions are described or perturbed, the reader cannot be sure whether the sperm's failure to enter is due to signaling via CatSper1 or whether the overall failure to undergo hyperactivation limits sperm motility such that the mutant sperm can no longer find and enter the zebrafish micropyle. Indeed, in Figure 5E, no CatSper1 mutant sperm are visible near any part of the egg, suggesting that overall motility is impaired, and this is not a phenotype specific to interactions with the micropyle.

Reviewer #2 (Public review):

Summary:

This manuscript investigates the mechanism by which chronic stress induces locus coeruleus (LC) neuron degeneration. The authors demonstrate that chronic stress leads to internalization of α2A-adrenergic receptors (α2A-ARs) on LC-neurons, causing increased cytosolic noradrenaline (NA) accumulation and subsequent production of the neurotoxic metabolite DOPEGAL via monoamine oxidase A (MAO-A). The study suggests a mechanistic link between stress-induced α2A-AR internalization, disrupted autoinhibition, elevated NA metabolism, asparagine endopeptidase (AEP) activation, and Tau pathology relevant to Alzheimer's disease (AD). The conclusions of this paper are mostly well supported by data, but some aspects of image acquisition need to be extended.

Strengths:

This study clearly demonstrates the effects of chronic stimulation on the excitability of LC neurons using electrophysiological techniques. It also elucidates the role of α2-adrenergic receptor (α2-AR) internalization and the associated upstream and downstream signaling pathways of GIRK1 using a range of pharmacological agents, highlighting the innovative nature of the work.

Additionally, the study identifies the involvement of the MAO-A-DOPEGAL-AEP pathway in this process. The topic is timely, the proposed mechanistic pathway is compelling, and the findings have translational relevance, particularly regarding therapeutic strategies targeting α2A-AR internalization in neurodegenerative diseases.

Weaknesses:

(1) The manuscript reports that chronic stress for 5 days increases MAO-A levels in LC neurons, leading to the production of DOPEGAL, activation of AEP, and subsequent tau cleavage into the tau N368 fragment, ultimately contributing to neuronal damage. However, the authors used wild-type C57BL/6 mice, and previous literature has indicated that AEP-mediated tau cleavage in wild-type mice is minimal and generally insufficient to cause significant behavioral alterations. Please clarify and discuss this apparent discrepancy.

(2) It is recommended that the authors include additional experiments to examine the effects of different durations and intensities of stress on MAO-A expression and AEP activity. This would strengthen the understanding of stress-induced biochemical changes and their thresholds.

(3) Please clarify the rationale for the inconsistent stress durations used across Figures 3, 4, and 5. In some cases, a 3-day stress protocol is used, while in others, a 5-day protocol is applied. This discrepancy should be addressed to ensure clarity and experimental consistency.

(4) The abbreviation "vMAT2" is incorrectly formatted. It should be "VMAT2," and the full name (vesicular monoamine transporter 2) should be provided at first mention.

Reviewer #2 (Public review):

In K. Kostanjevec et.al, the authors study a possible mechanism for the formation of spiral patterns in the cornea. First the authors analyze an inferred velocity field, which is deduced from images of fixed corneas, and then determine the position-dependent spiral angle of this velocity fields. Next, the authors analysed two possible markers of cell polarity: the direction of the centrosome-nuclei and the axis of mitosis. Then the authors introduce a stochastic agent-based model of self-propelled particles with over-damped dynamics and with aligning interactions to the orientation of the nearest neighbors and to the particle's velocity. The authors claim to be able to reproduce the equal-time autocorrelation function and the velocity Fourier spectrum. Then the authors introduce the geometry of the cornea by constraining the dynamics on a spherical cap and show that their model can reproduce a typical trajectory in experiments. Finally, the authors produce a phase diagram of the states at a fixed time point as a function of the spherical cap radius and the strength of the coupling aligning constant. Finally, the authors propose an interpretation of the cell fluxes based on the equation of mass conservation.

Reviewer #2 (Public review):

This is a short yet very clear manuscript demonstrating that two methods (END-seq and S1-END-seq), previously developed in the Nussenzweig laboratory to study DSBs in the genome, can also be applied to the 5' ends of mammalian telomeres and the accumulation of telomeric single-stranded DNA.

The authors first validate the applicability of END-seq using different approaches and confirm that mammalian telomeres preferentially end with an ATC 5' end through a mechanism that requires intact POT1 (POT1a in mice). They then extend their analysis to cells that maintain telomeres through the ALT mechanism and demonstrate that, in these cells as well, telomeres frequently end in an ATC 5' sequence via a POT1-dependent mechanism. Using S1-END-seq, the authors further show that ALT telomeres contain single-stranded DNA and estimate that each telomere in ALT cells harbors at least five regions of ssDNA.

I find this work very interesting and incisive. It clearly demonstrates that END-seq can be applied with unprecedented depth and precision to the study of telomeric features such as the 5' end and ssDNA. The data are very clear and thoroughly interpreted, and the manuscript is well written. The results are carefully analyzed and effectively presented. Overall, I find this manuscript worthy of publication, as the optimized END-seq methods described here will likely be widely utilized in the telomere field.

I only have a few minor suggestions:

How can we be sure that all telomeres are equally represented? The authors seem to assume that END-seq captures all chromosome ends equally, but can we be certain of this? While I do not see an obvious way to resolve this experimentally, I recommend discussing this potential bias more extensively in the manuscript.

I believe Figures 1 and 2 should be merged.

Scale bars should be added to all microscopy figures.

Reviewer #2 (Public review):

Summary:

In this paper, the authors describe the results of a longitudinal study of pertussis infection in mother/infant dyads in Lusaka, Zambia. Unlike many past studies, the authors assessed the infection status of individuals independently of whether they were symptomatic for a respiratory infection. As a result, this work represents one of the first studies specifically designed to assess asymptomatic transmission of pertussis. Using qPCR, the authors find strong evidence for the role of asymptomatic transmission from mothers to infants and also evidence for long-term bacterial carriage. This work represents an important contribution to our understanding of the global burden of pertussis. Also, it highlights the still under-appreciated role of asymptomatic transmission across many infectious diseases (including vaccine-preventable ones).

Strengths:

Unlike many past studies, the authors assessed the infection status of individuals independently of whether they were symptomatic for a respiratory infection. As a result, this work represents one of the first studies specifically designed to assess asymptomatic transmission of pertussis. Using qPCR, the authors find strong evidence for the role of asymptomatic transmission from mothers to infants and also evidence for long-term bacterial carriage.

Weaknesses:

While I am quite enthusiastic about the work, I am concerned that a number of likely relevant confounders were not discussed and that the broader implications of their findings were not well grounded in the existing literature. For example, I could not find information on the vaccination status of the mothers in the study. Given the conclusions about asymptomatic transmission and the durability of immunity, it is important to know the vaccination status of the mothers. Moreover, did the authors have other metadata on the mother/infant dyads, e.g., household size, vaccination status of household members, etc.? Given the potential implications of more widespread asymptomatic transmission associated with pertussis infection, I believe the authors should better couch their results in the context of the broader debate around asymptomatic transmission.

Reviewer #3 (Public review):

NCXs are key Ca2+ transporters located on the plasma membrane, essential for maintaining cellular Ca2+ homeostasis and signaling. The activities of NCX are tightly regulated in response to cellular conditions, ensuring precise control of intracellular Ca2+ levels, with profound physiological implications. Building upon their recent breakthrough in determining the structure of human NCX1, the authors obtained cryo-EM structures of NCX1 in complex with its modulators, including the cellular activator PIP2 and the small molecule inhibitor SEA0400. Structural analyses revealed mechanistically informative conformational changes induced by PIP2 and elucidated the molecular basis of inhibition by SEA0400. These findings underscore the critical role of the interface between the transmembrane and cytosolic domains in NCX regulation and small molecule modulation. Overall, the results provide key insights into NCX regulation, with important implications for cellular Ca2+ homeostasis.

Comments on revisions:

The authors have adequately addressed my previous comments.

Reviewer #3 (Public review):

Summary:

The authors aim to establish that cipargamin can be used for the treatment of infection caused by Babesia organisms.

Strengths:

The study provides strong evidence that cipargamin is effective against various Babesia species. In vitro growth assays were used to establish that cipargamin is effective against Babesia bovis and Babesia gibsoni. Infection of mice with Babesia microti demonstrated that cipargamin is as effective as the combination of atovaquone plus azithromycin. Cipargamin protected mice from lethal infection with Babesia rodhaini. Mutations that confer resistance to cipargamin were identified in the gene encoding ATP4, a P-type Na ATPase that is found in other apicomplexan parasites, thereby validating ATP4 as the target of cipargamin. A 7-day treatment of cipagarmin, when combined with a single dose of tafenoquine, was sufficient to eradicate Babesia microti in a mouse model of severe babesiosis caused by a lack of adaptive immunity.

Weaknesses:

Cipargamin was tested in vivo at a single dose administered daily for 7 days. Despite the prospect of using cipargamin for the treatment of human babesiosis, there was no attempt to identify the lowest dose of cipagarmin that protects mice from Babesia microti infection.

Comments on revisions:

The authors have edited the manuscript and, in doing so, have addressed all queries pertaining to experimental design. The authors have decided to keep the discussion unchanged, but have replied to this reviewer regarding comments on interpretation of some data. The reader could have benefited from the authors' explanation. Nonetheless, the manuscript in its present form describes a valuable and significant body of work.

Reviewer #2 (Public review):

Summary:

While technical advances have enabled large-scale, multi-site neural recordings, characterizing inter-regional communication and its behavioral relevance remains challenging due to intrinsic properties of the brain such as shared inputs, network complexity, and external noise. This work by Saiki-Ishkawa et al. examines the functional hierarchy between premotor (PM) and primary motor (M1) cortices in mice during a directional reaching task. The authors find some evidence consistent with an asymmetric reciprocal influence between the regions, but overall, activity patterns were highly similar and equally predictive of one another. These results suggest that motor cortical hierarchy, though present, is not fully reflected in firing patterns alone.

Strengths:

Inferring functional hierarchies between brain regions, given the complexity of reciprocal and local connectivity, dynamic interactions, and the influence of both shared and independent external inputs, is a challenging task. It requires careful analysis of simultaneous recording data, combined with cross-validation across multiple metrics, to accurately assess the functional relationships between regions. The authors have generated a valuable dataset simultaneously recording from both regions at scale from mice performing a cortex-dependent directional reaching task.

Using electrophysiological and silencing data, the authors found evidence supporting the traditionally assumed asymmetric influence from PM to M1. While earlier studies inferred a functional hierarchy based on partial temporal relationships in firing patterns, the authors applied a series of complementary analyses to rigorously test this hierarchy at both individual neuron and population levels, with robust statistical validation of significance.

In addition, recording combined with brief optogenetic silencing of the other region allowed authors to infer the asymmetric functional influence in a more causal manner. This experiment is well designed to focus on the effect of inactivation manifesting through oligosynaptic connections to support the existence of a premotor to primary motor functional hierarchy.

Subsequent analyses revealed a more complex picture. CCA, PLS, and three measures of predictivity (Granger causality, transfer entropy, and convergent cross mapping) emphasized similarities in firing patterns and cross-region predictability. However, DLAG suggested an imbalance, with RFA capturing CFA variance at a negative time lag, indicating that RFA 'leads' CFA. Taken together these results provide useful insights for current studies of functional hierarchy about potential limitations in inferring hierarchy solely based on firing rates.

While I would detail some questions and issues on specifics of data analyses and modeling below, I appreciate the authors' effort in training RNNs that match some behavioral and recorded neural activity patterns including the inactivation result. The authors point out two components that can determine the across-region influence - 1) the amount of inputs received and 2) the dependence on across-region input, i.e., relative importance of local dynamics, providing useful insights in inferring functional relationships across regions.

Weaknesses:

(1) Trial-averaging was applied in CCA and PLS analyses. While trial-averaging can be appropriate in certain cases, it leads to the loss of trial-to-trial variance, potentially inflating the perceived similarities between the activity in the two regions (Figure 4). Do authors observe comparable degrees of similarity, e.g., variance explained by canonical variables? Also, the authors report conflicting findings regarding the temporal relationship between RFA and CFA when using CCA/PLS versus DLAG. Could this discrepancy be due to the use of trial-averaging in former analyses but not in the latter?

(2) A key strength of the current study is the precise tracking of forelimb muscle activity during a complex motor task involving reaching for four different targets. This rich behavioral data is rarely collected in mice and offers a valuable opportunity to investigate the behavioral relevance of the PM-M1 functional interaction, yet little has been done to explore this aspect in depth. For example, single-trial time courses of inter-regional latent variables acquired from DLAG analysis can be correlated with single-trial muscle activity and/or reach trajectories to examine the behavioral relevance of inter-regional dynamics. Namely, can trial-by-trial change in inter-regional dynamics explain behavioral variability across trials and/or targets? Does the inter-areal interaction change in error trials? Furthermore, the authors could quantify the relative contribution of across-area versus within area dynamics to behavioral variability. It would also be interesting to assess the degree to which across-area and within-area dynamics are correlated. Specifically, can across-area dynamics vary independently from within-area dynamics across trials, potentially operating through a distinct communication subspace?

(3) While network modeling of RFA and CFA activity captured some aspects of behavioral and neural data, I wonder if certain findings such as the connection weight distribution (Figure 7C), across-region input (Figure 7F), and the within-region weights (Figure 7G), primarily resulted from fitting the different overall firing rates between the two regions with CFA exhibiting higher average firing rates. Did the authors account for this firing rate disparity when training the RNNs?

(4) Another way to assess the functional hierarchy is by comparing the time courses of movement representation between the two regions. For example, a linear decoder could be used to compare the amount of information about muscle activity and/or target location as well as time courses thereof between the two regions. This approach is advantageous because it incorporates behavior rather than focusing solely on neural activity. Since one of the main claims of this study is the limitation of inferring functional hierarchy from firing rate data alone, the authors should use the behavior as a lens for examining inter-areal interactions.

Comments on revisions:

I appreciate the authors' thoughtful revisions in response to prior reviews, which I believe have substantially improved the manuscript. In particular, I found the addition of the new section "Manifestations of hierarchy in firing patterns" to be valuable, as it begins to address some of the more complex and potentially conflicting observations

Reviewer #2 (Public review):

Summary:

This study explores the potential of inhibiting the p38-MK2 signaling pathway to enhance the efficacy of microtubule-targeting agents (MTAs) in breast cancer treatment using a dual-target inhibitor.

Strengths:

The study identifies the p38-MK2 pathway as a promising target to enhance the efficacy of microtubule-targeting agents (MTAs), offering a novel therapeutic strategy for breast cancer treatment. The study also employs a wide range of techniques, especially live-cell imaging, to assess the microtubule dynamics in TNBC cells. The revised manuscript added new in vitro and in vivo evidence that furtherly supported the conclusions.

Comments on revisions:

The authors have appropriately addressed all of my comments and concerns. Specifically, they performed additional in vitro experiments using MCF10A cells and p53 knockout cells to determine the IC50 of CMPD1. They also repeated the in vivo treatment experiment and evaluated the toxicity of the drug treatment in the CAL-51 model. Furthermore, they provided genetic evidence for the combination treatment. I'm satisfied with the revision and have no further major comments. Minor comment: make sure the name of the chemo drug shown in Fig. 3 is consistent.

Reviewer #2 (Public review):

Summary:

The author of this manuscript aimed to uncover the mechanisms behind miRNA retention within cells. They identified PCBP2 as a crucial factor in this process, revealing a novel role for RNA-binding proteins. Additionally, the study discovered that SYNCRIP is essential for PCBP2's function, demonstrating the cooperative interaction between these two proteins. This research not only sheds light on the intricate dynamics of miRNA retention but also emphasizes the importance of protein interactions in regulating miRNA behavior within cells.

Strengths:

This paper makes important progress in understanding how miRNAs are kept inside cells. It identifies PCBP2 as a key player in this process, showing a new role for proteins that bind RNA. The study also finds that SYNCRIP is needed for PCBP2 to work, highlighting how these proteins work together. These discoveries not only improve our knowledge of miRNA behavior but also suggest new ways to develop treatments by controlling miRNA locations to influence cell communication in diseases. The use of liver cell models and thorough experiments ensures the results are reliable and show their potential for RNA-based therapies

Weaknesses:

The manuscript is well-structured and presents compelling data, but I noticed a few minor corrections that could further enhance its clarity:

Figure References: In the response to Reviewer 1, the comment states, "It's not Panel C, it's Panel A of Figure 1"-this should be cross-checked for consistency.<br /> Supplementary Figure 2 is labeled as "Panel A"-please verify if additional panels (B, C, etc.) are intended.

Western Blot Quality: The Alix WB shows some background noise. A repeat with optimized conditions (or inclusion of a cleaner replicate) would strengthen the data. Adding statistical analysis for all WBs would also reinforce robustness.

These are relatively small refinements, and the manuscript is already in excellent shape. With these adjustments, it will be even stronger.

Reviewer #2 (Public review):

Hawes et al. investigated the role of striatal neurons in the patch compartment of the dorsal striatum. Using Sepw1-Cre line, the authors combined a modified version of the light/dark transition box test that allows them to examine locomotor activity in different environmental valence with a variety of approaches, including cell-type-specific ablation, miniscope calcium imaging, fiber photometry, and opto-/chemogenetics. First, they found ablation of patchy striatal neurons resulted in an increase in movement vigor when mice stayed in a safe area or when they moved back from more anxiogenic to safe environments. The following miniscope imaging experiment revealed that a larger fraction of striatal patchy neurons was negatively correlated with movement speed, particularly in an anxiogenic area. Next, the authors investigated differential activity patterns of patchy neurons' axon terminals, focusing on those in GPe, GPi, and SNr, showing that the patchy axons in SNr reflect movement speed/vigor. Chemogenetic and optogenetic activation of these patchy striatal neurons suppressed the locomotor vigor, thus demonstrating their causal role in the modulation of locomotor vigor when exposed to valence differentials. Unlike the activation of striatal patches, such a suppressive effect on locomotion was absent when optogenetically activating matrix neurons by using the Calb1-Cre line, indicating distinctive roles in the control of locomotor vigor by striatal patch and matrix neurons. Together, they have concluded that nigrostriatal neurons within striatal patches negatively regulate movement vigor, dependent on behavioral contexts where motivational valence differs.

In my view, this study will add to the important literature by demonstrating how patch (striosomal) neurons in the striatum control movement vigor. This study has applied multiple approaches to investigate their functionality in locomotor behavior, and the obtained data largely support their conclusions. Nevertheless I have some suggestions for improvements in the manuscript and figures regarding their data interpretation, accuracy, and efficacy of data presentation.

(1) The authors found that the activation of the striatonigral pathway in the patch compartment suppresses locomotor speed, which contradicts with canonical roles of the direct pathway. It would be great if the authors could provide mechanistic explanations in the Discussion section. One possibility is that striatal D1R patch neurons directly inhibit dopaminergic cells that regulate movement vigor (Nadal et al., Sci. Rep., 2021; Okunomiya et al., J Neurosci., 2025). Providing plausible explanations will help readers infer possible physiological processes and give them ideas for future follow-up studies.

(2) On page 14, Line 301, the authors stated that "Cre-dependent mCheery signals were colocalized with the patch marker (MOR1) in the dorsal striatum (Fig. 1B)". But I could not find any mCherry on that panel, so please modify it.

(3) From data shown in Figure 1, I've got the impression that mice ablated with striatal patch neurons were generally hyperactive, but this is probably not the case, as two separate experiments using LLbox and DDbox showed no difference in locomotor vigor between control and ablated mice. For the sake of better interpretation, it may be good to add a statement in Lines 365-366 that these experiments suggest the absence of hyperactive locomotion in general by ablating these specific neurons.

(4) In Line 536, where Figure 5A was cited, the author mentioned that they used inhibitory DREADDs (AAV-DIO-hM4Di-mCherrry), but I could not find associated data on Figure 5. Please cite Figure S3, accordingly.

(5) Personally, the Figure panel labels of "Hi" and "ii" were confusing at first glance. It would be better to have alternatives.

(6) There is a typo on Figure 4A: tdTomata → tdTomato

Reviewer #2 (Public review):

Summary:

The authors investigated the mechanisms behind breeding season-dependent feeding behavior using medaka, a well-known photoperiodic species, as a model. Through a combination of molecular, cellular, and behavioral analyses, including tests with mutants, they concluded that AgRP1 plays a central role in feeding behavior, mediated by ovarian estrogenic signals.

Strengths:

This study offers valuable insights into the neuroendocrine mechanisms that govern breeding season-dependent feeding behavior in medaka. The multidisciplinary approach, which includes molecular and physiological analyses, enhances the scientific contribution of the research.

Comments on revised version:

My concerns from the first review have been addressed. The manuscript's key points are clearly presented, and the conclusions are readily comprehensible

Reviewer #2 (Public review):

Summary:

This paper formulates an individual-based model to understand the evolution of division of labor in vertebrates. A main conclusion of the paper is that direct fitness benefits are the primary factor causing the evolution of vertebrate division of labor, rather than indirect fitness benefits.

Strengths:

The paper formulates an individual-based model that is inspired by vertebrate life history. The model incorporates numerous biologically realistic details, including the possibility to evolve age polytheism where individuals switch from work to defence tasks as they age or vice versa, as well as the possibility of comparing the action of group augmentation alone with that of kin selection alone.

Weaknesses:

The model makes assumptions that restrict the possibility that kin selection leads to the evolution of helping. In particular, the model assumes that in the absence of group augmentation, subordinates can only help breeders but cannot help non-breeders or increase the survival of breeders, whereas with group augmentation, subordinates can help both breeders and non-breeders and increase the survival of breeders. This is unrealistic as subordinates in real organisms can help other subordinates and increase the survival of non-breeders, even in the absence of group augmentation, for instance, with targeted helping to dominants or allies. This restriction artificially limits the ability of kin selection alone to lead to the evolution of helping, and potentially to division of labor. Hence, the conclusion that group augmentation is the primary driving factor driving vertebrate division of labor appears forced by the imposed restrictions on kin selection. The model used is also quite particular, and so the claimed generality across vertebrates is not warranted.

I describe some suggestions for improving the paper below, more or less in the paper's order.

First, the introduction goes to great lengths trying to convince the reader that this model is the first in this or another way, particularly in being only for vertebrates, as illustrated in the abstract where it is stated that "we lack a theoretical framework to explore the conditions under which division of labor is likely to evolve" (line 13). However, this is a risky and unnecessary motivation. There are many models of division of labor and some of them are likely to be abstract enough to apply to vertebrates even if they are not tailored to vertebrates, so the claims for being first are not only likely to be wrong but will put many readers in an antagonistic position right from the start, which will make it harder to communicate the results. Instead of claiming to be the first or that there is a lack of theoretical frameworks for vertebrate division of labor, I think it is enough and sufficiently interesting to say that the paper formulates an individual-based model motivated by the life history of vertebrates to understand the evolution of vertebrate division of labor. You could then describe the life history properties that the model incorporates (subordinates can become reproductive, low relatedness, age polyethism, etc.) without saying this has never been done or that it is exclusive to vertebrates; indeed, the paper states that these features do not occur in eusocial insects, which is surprising as some "primitively" eusocial insects show them. So, in short, I think the introduction should be extensively revised to avoid claims of being the first and to make it focused on the question being addressed and how it is addressed. I think this could be done in 2-3 paragraphs without the rather extensive review of the literature in the current introduction.

Second, the description of the model and results should be clarified substantially. I will give specific suggestions later, but for now, I will just say that it is unclear what the figures show. First, it is unclear what the axes in Figure 2 show, particularly for the vertical one. According to the text in the figure axis, it presumably refers to T, but T is a function of age t, so it is unclear what is being plotted. The legend explaining the triangle and circle symbols is unintelligible (lines 227-230), so again it is unclear what is being plotted; part of the reason for this unintelligibility is that the procedure that presumably underlies it (section starting on line 493) is poorly explained and not understandable (I detail why below). Second, the axes in Figure 3 are similarly unclear. The text in the vertical axis in panel A suggests this is T, however, T is a function of t and gamma_t, so something else must be being done to plot this. Similarly, in panel B, the horizontal axis is presumably R, but R is a function of t and of the helping genotype, so again some explanation is lacking. In all figures, the symbol of what is being plotted should be included.

Third, the conclusions sound stronger than the results are. A main conclusion of the paper is that "kin selection alone is unlikely to select for the evolution of defensive tasks and division of labor in vertebrates" (lines 194-195). This conclusion is drawn from the left column in Figure 2, where only kin selection is at play, and the helping that evolves only involves work rather than defense tasks. This conclusion follows because the model assumes that without group augmentation (i.e., xn=0, the kin selection scenario), subordinates can only help breeders to reproduce but cannot help breeders or other subordinates to survive, so the only form of help that evolves is the least costly, not the most beneficial as there is no difference in the benefits given among forms of helping. This assumption is unrealistic, particularly for vertebrates where subordinates can help other group members survive even in the absence of group augmentation (e.g., with targeted help to certain group members, because of dominance hierarchies where the helping would go to the breeder, or because of alliances where the helping would go to other subordinates). I go into further details below, but in short, the model forces a narrow scope for the kin selection scenario, and then the paper concludes that kin selection alone is unlikely to be of relevance for the evolution of vertebrate division of labor. This conclusion is particular to the model used, and it is misleading to suggest that this is a general feature of such a particular model.

Overall, I think the paper should be revised extensively to clarify its aims, model, results, and scope of its conclusions.

Reviewer #2 (Public review):

In this study, Cai and colleagues investigate how one component of the m6A methyltransferase complex, the WTAP protein, responds to IFNb stimulation. They find that viral infection or IFNb stimulation induces the transition of WTAP from aggregates to liquid droplets through dephosphorylation by PPP4. This process affects the m6A modification levels of ISG mRNAs and modulates their stability. In addition, the WTAP droplets interact with the transcription factor STAT1 to recruit the methyltransferase complex to ISG promoters and enhance m6A modification during transcription. The investigation dives into a previously unexplored area of how viral infection or IFNb stimulation affects m6A modification on ISGs. The observation that WTAP undergoes a phase transition is significant in our understanding of the mechanisms underlying m6A's function in immunity. However, there are still key gaps that should be addressed to fully accept the model presented.

Major points:<br /> (1) More detailed analyses on the effects of WTAPsgRNA on the m6A modification of ISGs:<br /> a. A comprehensive summary of the ISGs, including the percentage of ISGs that are m6A-modified,<br /> b. The distribution of m6A modification across the ISGs, and<br /> c. A comparison of the m6A modification distribution in ISGs with non-ISGs.<br /> In addition, since the authors propose a novel mechanism where the interaction between phosphorylated STAT1 and WTAP direct the MTC to the promoter regions of ISGs to facilitate co-transcriptional m6A modification, it is critical to analyze whether the m6A modification distribution holds true in the data.

(2) Since a key part of the model includes the cytosol-localized STAT1 protein undergoing phosphorylation to translocate to the nucleus to mediate gene expression, the authors should focus on the interaction between phosphorylated STAT1 and WTAP in Figure 4, rather than the unphosphorylated STAT1. Only phosphorylated STAT1 localizes to the nucleus, so the presence of pSTAT1 in the immunoprecipitate is critical for establishing a functional link between STAT1 activation and its interaction with WTAP.

(3) The authors should include pSTAT1 ChIP-seq and WTAP ChIP-seq on IFNb-treated samples in Figure 5 to allow for a comprehensive and unbiased genomic analysis for comparing the overlaps of peaks from both ChIP-seq datasets. These results should further support for their hypothesis that WTAP interacts with pSTAT1 to enhance m6A modifications on ISGs.

Minor points:<br /> (1) Since IFNb is primarily known for modulating biological processes through gene transcription, it would be informative if the authors discussed the mechanism of how IFNb would induce the interaction between WTAP and PPP4.

(2) The authors should include mCherry alone controls in Figure 1D to demonstrate that mCherry does not contribute to the phase separation of WTAP. Does mCherry have or lack a PLD?

(3) The authors should clarify the immunoprecipitation assays in the methods. For example, the labeling in Fig. 2A suggests that antibodies against WTAP and pan-p were used for two immunoprecipitations. Is that accurate?

(4) The authors should include overall m6A modification levels quantified of GFPsgRNA and WTAPsgRNA cells, either by mass spectrometry (preferably) or dot blot.

Comments on revisions:

The authors thoroughly addressed the aforementioned points during the review process.

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

Reviewer #2 (Public review):

uORFs, short open reading frames located in the 5' UTR, are pervasive in genomes. However, their roles in maintaining protein abundance are not clear. In this study, the authors propose that uORFs act as "molecular dam", limiting the fluctuation of the translation of downstream coding sequences. First, they performed in silico simulations using an improved ICIER model, and demonstrated that uORF translation reduces CDS translational variability, with buffering capacity increasing in proportion to uORF efficiency, length, and number. Next, they analysed the translatome between two related Drosophila species, revealing that genes with uORFs exhibit smaller fluctuations in translation between the two species and across different developmental stages within the same species. Moreover, they identified that bicoid, a critical gene for Drosophila development, contains a uORF with substantial changes in translation efficiency. Deleting this uORF in Drosophila melanogaster significantly affected its gene expression, hatching rates, and survival under stress conditions. Lastly, by leveraging public Ribo-seq data, the authors showed that the buffering effect of uORFs is also evident between primates and within human populations. Collectively, the study significantly advances our understanding of how uORFs regulate the translation of downstream coding sequences at the genome-wide scale, as well as during development and evolution. It would be particularly interesting to explore whether similar buffering functions are conserved in other organisms, and whether their regulatory effects could be harnessed for practical applications, such as improving crop traits or benefiting human health.

Comments on revisions:

The authors have fully addressed all of my concerns, and the revisions have substantially improved the manuscript. I have no further comments.

Reviewer #2 (Public review):

Summary

Schubert et al. recorded MEG and eye tracking activity while participants were listening to stories in single-speaker or multi-speaker speech. In a separate task, MEG was recorded while the same participants were listening to four types of pure tones in either structured (75% predictable) or random (25%) sequences. The MEG data from this task was used to quantify individual 'prediction tendency': the amount by which the neural signal is modulated by whether or not a repeated tone was (un)predictable, given the context. In a replication of earlier work, this prediction tendency was found to correlate with 'neural speech tracking' during the main task. Neural speech tracking is quantified as the multivariate relationship between MEG activity and speech amplitude envelope. Prediction tendency did not correlate with 'ocular speech tracking' during the main task. Neural speech tracking was further modulated by local semantic violations in the speech material and by whether or not a distracting speaker was present. The authors suggest that part of the neural speech tracking is mediated by ocular speech tracking. Story comprehension was negatively related with ocular speech tracking.

Strengths

This is an ambitious study, and the authors' attempt to integrate the many reported findings related to prediction and attention in one framework is laudable. The data acquisition and analyses appear to be done with great attention to methodological detail. Furthermore, the experimental paradigm used is more naturalistic than was previously done in similar setups (i.e.: stories instead of sentences).

Weaknesses

While the analysis pipeline is outlined in much detail, some analysis choices appear ad-hoc and could have been more uniform and/or better motivated (other than: this is what was done before).

Reviewer #2 (Public review):

Summary:

This work concerns the evolution of ZDBF2 imprinting in mammalian species via initiation of GPR1 antisense (AS) transcription from a lineage-specific long-terminal repeat (LTR) retrotransposon. It extends previous work describing the mechanism of ZDBF2 imprinting in mice and humans by demonstrating conservation of GPR1-AS transcripts in rabbits and non-human primates. By identifying the origin of GPR1-AS transcription as the LTR MER21C, the authors claim to account for how imprinting evolved in these species but not in those lacking the MER21C insertion. This illustrates the principle of LTR co-option as a means of evolving new gene regulatory mechanisms, specifically to achieve parent-of-origin allele specific expression (imprinting). Examples of this phenomenon have been described previously, but usually involve initiation of transcription during gametogenesis rather than post-fertilization, as in this work. The findings of this paper are therefore relevant to biologists studying imprinted genes or interested more generally in the evolution of gene regulatory mechanisms.

Strengths:

(1) The authors convincingly demonstrate the existence of GPR1-AS orthologs in specific mammalian lineages using high quality RNA-seq libraries collected from diverse mammalian species.

(2) The authors demonstrate imprinting of the ZDBF2 locus in rabbits and Rhesus macaques using allele-specific expression analysis. The transcription of GPR1-AS orthologs therefore correlates with imprinting of the ZDBF2 locus.

Weaknesses:

(1) Experimental evidence directly linking GPR1-AS transcription to ZDBF2 imprinting in rabbits and non-human primates is lacking. Consideration should be given to the challenges associated with studying non-model species and manipulating repeat sequences. Further, this mechanism is established in humans and mice, so the authors' model is arguably sufficiently supported merely by the existence of GPR1-AS orthologs in other mammalian lineages.

Reviewer #2 (Public Review):

In this manuscript, Glaser et al. describe a new selective plane illumination microscope designed to image a large field of view that is optimized for expanded and cleared tissue samples. For the most part, the microscope design follows a standard formula that is common among many systems (e.g. Keller PJ et al Science 2008, Pitrone PG et al. Nature Methods 2013, Dean KM et al. Biophys J 2015, and Voigt FF et al. Nature Methods 2019). The primary conceptual and technical novelty is to use a detection objective from the metrology industry that has a large field of view and a large area camera. The authors characterize the system resolution, field curvature, and chromatic focal shift by measuring fluorescent beads in a hydrogel and then show example images of expanded samples from mouse, macaque, and human brain tissue.

Glaser et al. have responded to the reviewer comments by removing some of the overstated claims from the prior manuscript and editing portions of the manuscript text to enhance the clarity. Although the manuscript would be stronger if the authors had been able to provide data that justified the original high-impact claims from the initial publication (e.g. that the images could be used for robust and automated neuronal tracing across large volumes), the amended manuscript text now more closely matches the supporting data. As with the initial submission, I believe that the microscope design and characterization is a useful contribution to the field and the data are quite stunning.

Reviewer #2 (Public review):

Summary:

In this work the authors show that dopaminergic neurons (DANs) from the DL1 cluster in Drosophila larvae are required for the formation of aversive memories. DL1 DANs complement pPAM cluster neurons which are required for the formation of attractive memories. This shows the compartmentalized network organization of how an insect learning center (the mushroom body) encodes memory by integrating olfactory stimuli with aversive or attractive teaching signals. Interestingly, the authors found that the 4 main dopaminergic DL1 neurons act partially redundant, and that single cell ablation did not result in aversive memory defects. However, ablation or silencing of a specific DL1 subset (DAN-f1,g1) resulted in reduced salt aversion learning, which was specific to salt but no other aversive teaching stimuli tested. Importantly, activation of these DANs using an optogenetic approach was also sufficient to induce aversive learning in the presence of high salt. Together with the functional imaging of salt and fructose responses of the individual DANs and the implemented connectome analysis of sensory (and other) inputs to DL1/pPAM DANs this represents a very comprehensive study linking the structural, functional and behavioral role of DL1 DANs. This provides fundamental insight into the function of a simple yet efficiently organized learning center which displays highly conserved features of integrating teaching signals with other sensory cues via dopaminergic signaling.

Strengths:

This is a very careful, precise and meticulous study identifying the main larval DANs involved in aversive learning using high salt as a teaching signal. This is highly interesting because it allows to define the cellular substrates and pathways of aversive learning down to the single cell level in a system without much redundancy. It therefore sets the basis to conduct even more sophisticated experiments and together with the neat connectome analysis opens the possibility to unravel different sensory processing pathways within the DL1 cluster and integration with the higher order circuit elements (Kenyon cells and MBONs). The authors' claims are well substantiated by the data and balanced, putting their data in the appropriate context. The authors also implemented neat pathway analyses using the larval connectome data to its full advantage, thus providing network pathways that contribute towards explaining the obtained results.

Weaknesses:

Previous comments were fully addressed by the authors.

Reviewer #2 (Public review):

The study by Setogawa et al. aims to understand the role that different striatal subregions belonging to parallel brain circuits have in associative learning and discrimination learning (S-O-R and S-R tasks). Strengths of the study are the use of multiple methodologies to measure and manipulate brain activity in rats, from microPET imaging to excitotoxic lesions and multielectrode recordings across anterior dorsolateral (aDLS), posterior ventral lateral (pVLS)and dorsomedial (DMS) striatum.

The main conclusions are that the aDLS promotes stimulus-response association and suppresses response-outcome associations. The pVLS is engaged in the formation and maintenance of the stimulus-response association. There is a lot of work done and some interesting findings however, the manuscript can be improved by clarifying the presentation and reasoning. The inclusion of important controls will enhance the rigor of the data interpretation and conclusions.

Comments on revisions:

The authors have made important revisions to the manuscript and it has improved in clarity. They also added several figures in the rebuttal letter to answer questions by the reviewers. I would ask that these figures are also made public as part of the authors' response or if not, included in the manuscript.

Reviewer #2 (Public review):

This is potentially interesting work, but the analyses are attempted in a rather scattergun way, with little evident critical thought. The structure of the work (Results before Methods) can work in some manuscripts, but it is not ideal here. The authors discuss results before we know anything about the underlying data that the results come from. It gives the impression that the authors regard data as a resource to be exploited, without really caring where the data comes from. The methods can provide meaningful insights if correctly used, but while I don't have reasons to doubt that the analyses were conducted correctly, findings are presented with little discussion or interpretation. No follow-up analyses are performed.

In summary, there are likely some gems here, but the whole manuscript is essentially the output from an analytic pipeline.

Taking the researchers aims in turn:

(1) Meta-GWAS - while combining two datasets together can provide additional insights, the contribution of this analysis above existing GWAS is not clear. The PRACTICAL consortium has already reported the GWAS of 70% of these data. What additional value does this analysis provide? (Likely some, but it's not clear from the text.) Also, the presentation of results is unclear - authors state that only 5 gene regions contained variants at p<5x10-8, but Figure 1 shows dozens of hits above 5x10-8. Also, the red line in Figure 1 (supposedly at 5x10-8) is misplaced.

(2) Cross-phenotype analysis. It is not really clear what this analysis is, or why it is done. What is the iCPAGdb? A database? A statistical method? Why would we want to know cross-phenotype associations? What even are these? It seems that the authors have taken data from an online resource and have written a paragraph based on this existing data with little added value.

(3) PW-MR. I can see the value of this work, but many details are unclear. Was this a two-sample MR using PRACTICAL + FinnGen data for the outcome? How many variants were used in key analyses? Again, the description of results is sparse and gives little added value.

(4) Colocalization - seems clear to me.

(5) Additional post-GWAS analyses (pathway + druggability) - again, the analyses seem to be performed appropriately, although little additional insight other than the reporting of output from the methods.

Minor points:

(6) The stated motivation for this work is "early detection". But causality isn't necessary for early detection. If the authors are interested in early detection, other analysis approaches are more appropriate.

(7) The authors state "193 proteins were associated with PCa risk", but they are looking at MR results - these analyses test for disease associations of genetically-predicted levels of proteins, not proteins themselves.

Strengths:

The data and methods used are state-of-the-art.

Weaknesses:

The reader will have to provide their own translational insight.

Reviewer #2 (Public review):

Summary:

The study provides an updated literature review and meta-analysis for the 5-year survival estimates in breast cancer patients across continental Africa. The findings reveal substantial disparities between regions and other factors, highlighting the disadvantaged areas in Africa and the urgent need to address these inequities across the continent.

Strengths:

The main strengths of this study include:<br /> (1) the thorough literature search with an increasing number of included studies that enhances result reliability;<br /> (2) standard and appropriate statistical methods with clear reporting;<br /> (3) a comprehensive discussion.

Overall, the paper is well-structured, clearly presented, and provides useful insights.

Weaknesses:

However, I have a few concerns that I would like the authors to address.

(1) The conclusion "A country-wise comparison with 2018 estimates suggests a declining survival tendency, with WHO AFRO countries reporting the poorest estimates among other WHO regions." appears to have been drawn from the comparisons across both different regions and different time periods, which is incorrect! As shown in Figure 8, survival in Africa has increased from below 30% (WHO AFRO 2017) to around 50% (AFRICA 2024, presumably the current study). Section 3.5 is confusing and headed in the wrong direction. The key message in Figure 8 is that the current survival estimate in Africa is still lower than that of other WHO regions from a few years ago, highlighting the urgent need to improve survival in Africa.

(2) The previous review by Ssentongo et al. classified countries into North Africa and sub-Saharan Africa (SSA), regions divided by the Sahara Desert. This classification is not only geographical-based, but also accounts for the significant differences in ethnicity, health system, and socioeconomic factors. North Africa (especially Egypt, Tunisia, Morocco) has better cancer registries, earlier detection, more treatment access, and therefore better survival outcomes (as shown in Figure 2). SSA tends to have worse outcomes, due to later-stage diagnosis, limited pathology, and access barriers. Given that the survival in women with breast cancer is among the lowest for several SSA countries, the study would benefit from an additional comparison between pooled estimates of North African and SSA, and comparisons with previous pooled estimates.

(3) The authors classified studies under the female group. Females constituted at least 80% of the sample population, and subgroup analysis revealed only a marginal discrepancy in survival rates between the two sexes. However, most of the breast cancer patients and related studies consist predominantly of females. Given the non-negligible differences in various aspects between females and males, sensitivity analyses restricted to studies among females (as in Figure 2-3) would be informative for future research in breast cancer patients.

(4) Stage at diagnosis and treatment are the strongest prognostic factors for breast cancer survival. Though data regarding these variables are not available for all studies, and it's complicated to compare or pool the results from different studies (as mentioned in the limitation), could the authors perform the regression analyses regarding early vs. late stages, and the percentage of treatment received? These two factors are too significant to overlook in studies on breast cancer survival.

(5) The authors reported that studies published before 2019 had a higher survival than those conducted from 2019 onwards, which could be misleading and requires further explanation. As the authors noted ─"the year of publication may not be a reliable measure of the effect in question"─ a better approach would be to use the year of inclusion, i.e., the year the studies were conducted.

(6) Northern and Western Africa both have the highest incidence of breast cancer in Africa, yet their 5-year survival estimates differ substantially. However, the authors have discussed the survival disparities without considering their similarly higher incidence rates. Could this disparity reflect different contributing factors, with the higher incidence rate in Northern Africa resulting from better screening programs (leading to more detections), while that in Western Africa stems from other epidemiological factors despite lower screening participation? Though the incidence rate is not the primary focus of this study, briefly exploring this dichotomy would enhance the discussion and provide valuable insights for readers.

Reviewer #2 (Public review):

This is a timely and insightful study aiming to explore the general physical principles for the sub-compartmentalization--or lack thereof--in the phase separation processes underlying the assembly of postsynaptic densities (PSDs), especially the markedly different organizations in three-dimensional (3D) droplets on one hand and the two-dimensional (2D) condensates associated with a cellular membrane on the other. Simulation of a highly simplified model (one bead per protein domain) is carefully executed. Based on a thorough consideration of various control cases, the main conclusion regarding the trade-off between repulsive excluded volume interactions and attractive interactions among protein domains in determining the structures of 3D vs 2D model PSD condensates is quite convincing. The results in this manuscript are novel; however, as it stands, there is substantial room for improvement in the presentation of the background and the findings of this work. In particular, (i) conceptual connections with prior works should be better discussed, (ii) essential details of the model should be clarified, and (iii) the generality and limitations of the authors' approach should be better delineated. Specifically, the following items should be addressed (with the additional references mentioned below cited and discussed):

(1) Excluded volume effects are referred to throughout the text by various terms and descriptions such as "repulsive force according to the volume" (e.g., in the Introduction), "nonspecific volume interaction", and "volume effects" in this manuscript. This is somewhat curious and not conducive to clarity, because these terms have alternate or connotations of alternate meanings (e.g., in biomolecular modeling, repulsive interactions usually refer to those with longer spatial ranges, such as that between like charges). It will be much clearer if the authors simply refer to excluded volume interactions as excluded volume interactions (or effects).

(2) Inasmuch as the impact of excluded volume effects on subcompartmentalization of condensates ("multiple phases" in the authors' terminology), it has been demonstrated by both coarse-grained molecular dynamics and field-theoretic simulations that excluded volume is conducive to demixing of molecular species in condensates [Pal et al., Phys Rev E 103:042406 (2021); see especially Figures 4-5 of this reference]. This prior work bears directly on the authors' observation. Its relationship with the present work should be discussed.

(3) In the present model setup, activation of the CaMKII kinase affects only its binding to GluN2Bc. This approach is reasonable and leads to model predictions that are essentially consistent with the experiment. More broadly, however, do the authors expect activation of the CaMKII kinase to lead to phosphorylation of some of the molecular species involved with PSDs? This may be of interest since biomolecular condensates are known to be modulated by phosphorylation [Kim et al., Science 365:825-829 (2019); Lin et al, eLife 13:RP100284 (2025)].

(4) The forcefield for confinement of AMPAR/TARP and NMDAR/GluN2Bc to 2D should be specified in the main text. Have the authors explored the sensitivity of their 2D findings on the strength of this confinement?

(5) Some of the labels in Figure 1 are confusing. In Figure 1A, the structure labeled as AMPAR has the same shape as the structure labeled as TARP in Figure 1B, but TARP is labeled as one of the smaller structures (like small legs) in the lower part of AMPAR in Figure 1A. Does the TARP in Figure 1B correspond to the small structures in the lower part of AMPAR? If so, this should be specified (and better indicated graphically), and in that case, it would be better not to use the same structural drawing for the overall structure and a substructure. The same issue is seen for NMDAR in Figure 1A and GluN2Bc in Figure 1B.

(6) In addition to clarifying Figure 1, the authors should clarify the usage of AMPAR vs TARP and NMDAR vs GluN2Bc in other parts of the text as well.

(7) The physics of the authors' model will be much clearer if they provide an easily accessible graphical description of the relative interaction strengths between different domain-representing spheres (beads) in their model. For this purpose, a representation similar to that given by Feric et al., Cell 165:1686-1697 (2016) (especially Figure 6B in this reference) of the pairwise interactions among the beads in the authors' model should be provided as an additional main-text figure. Different interaction schemes corresponding to inactive and activated CAMKII should be given. In this way, the general principles (beyond the PSD system) governing 3D vs 2D multiple-component condensate organization can be made much more apparent.

(8) Can the authors' rationalization of the observed difference between 3D and 2D model PSD condensates be captured by an intuitive appreciation of the restriction on favorable interactions by steric hindrance and the reduction in interaction cooperativity in 2D vs 3D?

(9) In the authors' model, the propensity to form 2D condensates is quite weak. Is this prediction consistent with the experiment? Real PSDs do form 2D condensates around synapses.

(10) More theoretical context should be provided in the Introduction and/or Discussion by drawing connections to pertinent prior works on physical determinants of co-mixing and de-mixing in multiple-component condensates (e.g., amino acid sequence), such as Lin et al., New J Phys 19:115003 (2017) and Lin et al., Biochemistry 57:2499-2508 (2018).

(11) In the discussion of the physiological/neurological significance of PSD in the Introduction and/or Discussion, for general interest it is useful to point to a recently studied possible connection between the hydrostatic pressure-induced dissolution of model PSD and high-pressure neurological syndrome [Lin et al., Chem Eur J 26:11024-11031 (2020)].

(12) It is more accurate to use "perpendicular to the membrane" rather than "vertical" in the caption for Figure 3E and other such descriptions of the orientation of the CaMKII hexagonal plane in the text.

Reviewer #2 (Public review):

Summary:

This article presents Morphonet 2.0, a software designed to visualise and curate segmentations of 3D and 3D+t data. The authors demonstrate their capabilities on five published datasets, showcasing how even small segmentation errors can be automatically detected, easily assessed, and corrected by the user. This allows for more reliable ground truths, which will in turn be very much valuable for analysis and training deep learning models. Morphonet 2.0 offers intuitive 3D inspection and functionalities accessible to a non-coding audience, thereby broadening its impact.

Strengths:

The work proposed in this article is expected to be of great interest to the community by enabling easy visualisation and correction of complex 3D(+t) datasets. Moreover, the article is clear and well written, making MorphoNet more likely to be used. The goals are clearly defined, addressing an undeniable need in the bioimage analysis community. The authors use a diverse range of datasets, successfully demonstrating the versatility of the software.

We would also like to highlight the great effort that was made to clearly explain which type of computer configurations are necessary to run the different datasets and how to find the appropriate documentation according to your needs. The authors clearly carefully thought about these two important problems and came up with very satisfactory solutions.

Weaknesses:

There is still one concern: the quantification of the improvement of the segmentations in the use cases and, therefore, the quantification of the potential impact of the software. While it appears hard to quantify the quality of the correction, the proposed work would be significantly improved if such metrics could be provided.

The authors show some distributions of metrics before and after segmentations to highlight the changes. This is a great start, but there seem to be two shortcomings: first, the comparison and interpretation of the different distributions does not appear to be trivial. It is therefore difficult to judge the quality of the improvement from these. Maybe an explanation in the text of how to interpret the differences between the distributions could help. A second shortcoming is that the before/after metrics displayed are the metrics used to guide the correction, so, by design, the scores will improve, but does that accurately represent the improvement of the segmentation? It seems to be the case, but it would be nice to maybe have a better assessment of the improvement of the quality.

Reviewer #2 (Public review):

Summary:

Poge et al. present a workflow for studying plant tissue by combining high-pressure freezing, cryo-fluorescence microscopy, FIB milling, and cryo-electron tomography (cryo-ET). They tested various plant tissues, including Physcomitrium patens, Arabidopsis thaliana, and Limonium bicolor. The authors successfully produce thin lamellae suitable for cryo-ET studies. Using sub-tomogram averaging, they determined the Rubisco structure at subnanometer resolution, demonstrating the potential of this workflow for plant tissue studies.

Strengths:

This manuscript is likely the first to systematically apply FIB milling and cryo-ET to plant tissue samples. It provides a detailed methodological description, which is not only valuable for plant tissue studies but also adaptable to a broader range of biological tissue samples. The study compares the plunge freezing method with a high-pressure freezing method, demonstrating that high-pressure freezing can vitrify thick tissues while preserving their native state. Additionally, the authors explore two methods for plant tissue sample preparation, the "waffle" method and in-carrier high-pressure freezing combined with the "lift-out" approach. The "waffle" method is suitable for samples less than 25um, while the in-carrier high-pressure freezing method can process samples up to 100um.

Weaknesses:

The described workflow is very complicated and requires special expertise. The success rate of this workflow is not very high, particularly for high-pressure freezing and life-out technology. Further improvements are needed for automation and increasing throughput.

Reviewer #2 (Public review):

This valuable paper studies the problem of learning from feedback given by sources of varying credibility. The solid combination of experiment and computational modeling helps to pin down properties of learning, although some ambiguity remains in the interpretation of results.

Summary:

This paper studies the problem of learning from feedback given by sources of varying credibility. Two bandit-style experiments are conducted in which feedback is provided with uncertainty, but from known sources. Bayesian benchmarks are provided to assess normative facets of learning, and alternative credit assignment models are fit for comparison. Some aspects of normativity appear, in addition to deviations such as asymmetric updating from positive and negative outcomes.

Strengths:

The paper tackles an important topic, with a relatively clean cognitive perspective. The construction of the experiment enables the use of computational modeling. This helps to pinpoint quantitatively the properties of learning and formally evaluate their impact and importance. The analyses are generally sensible, and parameter recovery analyses help to provide some confidence in the model estimation and comparison.

Weaknesses:

(1) The approach in the paper overlaps somewhat with various papers, such as Diaconescu et al. (2014) and Schulz et al. (forthcoming), which also consider the Bayesian problem of learning and applying source credibility, in terms of theory and experiment. The authors should discuss how these papers are complementary, to better provide an integrative picture for readers.

Diaconescu, A. O., Mathys, C., Weber, L. A., Daunizeau, J., Kasper, L., Lomakina, E. I., ... & Stephan, K. E. (2014). Inferring the intentions of others by hierarchical Bayesian learning. PLoS computational biology, 10(9), e1003810.<br /> Schulz, L., Schulz, E., Bhui, R., & Dayan, P. Mechanisms of Mistrust: A Bayesian Account of Misinformation Learning. https://doi.org/10.31234/osf.io/8egxh

(2) It isn't completely clear what the "cross-fitting" procedure accomplishes. Can this be discussed further?

(3) The Credibility-CA model seems to fit the same as the free-credibility Bayesian model in the first experiment and barely better in the second experiment. Why not use a more standard model comparison metric like the Bayesian Information Criterion (BIC)? Even if there are advantages to the bootstrap method (which should be described if so), the BIC would help for comparability between papers.

(4) As suggested in the discussion, the updating based on random feedback could be due to the interleaving of trials. If one is used to learning from the source on most trials, the occasional random trial may be hard to resist updating from. The exact interleaving structure should also be clarified (I assume different sources were shown for each bandit pair). This would also relate to work on RL and working memory: Collins, A. G., & Frank, M. J. (2012). How much of reinforcement learning is working memory, not reinforcement learning? A behavioral, computational, and neurogenetic analysis. European Journal of Neuroscience, 35(7), 1024-1035.

(5) Why does the choice-repetition regression include "only trials for which the last same-pair trial featured the 3-star agent and in which the context trial featured a different bandit pair"? This could be stated more plainly.

(6) Why apply the "Truth-CA" model and not the Bayesian variant that it was motivated by?

(7) "Overall, the results from this study support the exact same conclusions (See SI section 1.2) but with one difference. In the discovery study, we found no evidence for learning based on 50%-credibility feedback when examining either the feedback effect on choice repetition or CA in the credibility-CA model (SI 1.2.3)" - this seems like a very salient difference, when the paper reports the feedback effect as a primary finding of interest, though I understand there remains a valence-based difference.

(8) "Participants were instructed that this feedback would be "a lie 50% of the time but were not explicitly told that this meant it was random and should therefore be disregarded." - I agree that this is a possible explanation for updating from the random source. It is a meaningful caveat.

(9) "Future studies should investigate conditions that enhance an ability to discard disinformation, such as providing explicit instructions to ignore misleading feedback, manipulations that increase the time available for evaluating information, or interventions that strengthen source memory." - there is work on some of this in the misinformation literature that should be cited, such as the "continued influence effect". For example: Johnson, H. M., & Seifert, C. M. (1994). Sources of the continued influence effect: When misinformation in memory affects later inferences. Journal of experimental psychology: Learning, memory, and cognition, 20(6), 1420.

(10) Are the authors arguing that choice-confirmation bias may be at play? Work on choice-confirmation bias generally includes counterfactual feedback, which is not present here.

Reviewer #2 (Public review):

Summary:

The paper examines the diversity of complex amacrine neurons in the ventral lobe of the adult octopus brain, a structure involved in learning and memory. The work builds on a recent paper by the authors that described the connectivity of the much larger population of simple amacrine (SAM) interneurons from the same pioneering EM volume.

Strengths:

While the EM volume only provides a snapshot of a tiny fraction of an adult octopus' brain, the authors can make specific conclusions and formulate precise hypotheses about neuron function, synaptic pathways, and developmental trajectories. One example is the reconstruction of a putative maturation sequence for the SAM neuronal lineage, based on the correlation of soma position and the number of synapses, uncovering a plausible developmental sequence of cell morphologies, with interesting parallels to vertebrate neurogenesis.

Weaknesses:

The weakness of the study is that it is examining a relatively small volume (260 × 390 × 27 µm), and several neurons are only incompletely reconstructed. It also remains unclear approximately how many neurons remain to be reconstructed from this volume.

To improve the presentation, the authors should consider showing videos with the volumetric reconstructions of the different types with their partners/synapses and their relation to the SFL track and SAMs. Such videos would help the reader to appreciate the morphological differences between the cell types. The authors could also consider carrying out further morphological analyses to strengthen their cell-type classification, including Sholl value, radial density of input and output synapses, the number of branch nodes, and similar measures.

Reviewer #2 (Public review):

Summary:

Building on previous models of multisensory integration (including their earlier correlation-detection framework used for non-spatial signals), the author introduces a population-level Multisensory Correlation Detector (MCD) that processes raw auditory and visual data. Crucially, it does not rely on abstracted parameters, as is common in normative Bayesian models," but rather works directly on the stimulus itself (i.e., individual pixels and audio samples). By systematically testing the model against a range of experiments spanning human, monkey, and rat data, the authors show that their MCD population approach robustly predicts perception and behavior across species with a relatively small (0-4) number of free parameters.

Strengths:

(1) Unlike prior Bayesian models that used simplified or parameterized inputs, the model here is explicitly computable from full natural stimuli. This resolves a key gap in understanding how the brain might extract "time offsets" or "disparities" from continuously changing audio-visual streams.

(2) The same population MCD architecture captures a remarkable range of multisensory phenomena, from classical illusions (McGurk, ventriloquism) and synchrony judgments, to attentional/gaze behavior driven by audio-visual salience. This generality strongly supports the idea that a single low-level computation (correlation detection) can underlie many distinct multisensory effects.

(3) By tuning model parameters to different temporal rhythms (e.g., faster in rodents, slower in humans), the MCD explains cross-species perceptual data without reconfiguring the underlying architecture.

Weaknesses:

(1) The authors show how a correlation-based model can account for the various multisensory integration effects observed in previous studies. However, a comparison of how the two accounts differ would shed light on the correlation model being an implementation of the Bayesian computations (different levels in Marr's hierarchy) or making testable predictions that can distinguish between the two frameworks. For example, how uncertainty in the cue combined estimate is also the harmonic mean of the unimodal uncertainties is a prediction from the Bayesian model. So, how the MCD framework predicts this reduced uncertainty could be one potential difference (or similarity) to the Bayesian model.

2) The authors show a good match for cue combination involving 2 cues. While Bayesian accounts provide a direction extension to more cues (also seen empirically, for eg, in Hecht et al. 2008), discussion on how the MCD model extends to more cues would benefit the readers.

Likely Impact and Usefulness:

The work offers a compelling unification of multiple multisensory tasks- temporal order judgments, illusions, Bayesian causal inference, and overt visual attention - under a single, fully stimulus-driven framework. Its success with natural stimuli should interest computational neuroscientists, systems neuroscientists, and machine learning scientists. This paper thus makes an important contribution to the field by moving beyond minimalistic lab stimuli, illustrating how raw audio and video can be integrated using elementary correlation analyses.

Reviewer #2 (Public review):

Summary:

In their study, Osorio and colleagues present 'retriever,' an innovative computational tool designed to extract disease-specific transcriptional drug response profiles from the LINCS-L1000 project. This tool has been effectively applied to TNBC, leveraging single-cell RNA sequencing data to predict drug combinations that may effectively target the disease. The public review highlights the significant integration of extensive pharmacological data with high-resolution transcriptomic information, which enhances the potential for personalized therapeutic applications.

Strengths:

A key finding of the study is the prediction and validation of the drug combination QL-XII-47 and GSK-690693 for the treatment of TNBC. The methodology employed is robust, with a clear pathway from data analysis to experimental confirmation.

Comments on revisions:

I commend the authors for their thorough and thoughtful revisions, which have significantly strengthened the manuscript. The expanded discussion on the limitations of the LINCS-L1000 dataset and the inherent challenges of imputation techniques provides critical context for interpreting the tool's predictive accuracy. The addition of clinical implications, including strategies for integrating retriever into clinical trial design and its broader applicability to other diseases, enhances the translational relevance of the work. Addressing drug resistance mechanisms in the context of combination therapy further underscores the biological rationale for the approach.

The transparency regarding computational requirements and ethical considerations-particularly data privacy, bias mitigation, and model validation-demonstrates a responsible and forward-thinking approach to computational biology. These additions not only improve the manuscript's rigor but also set a precedent for ethical practices in personalized medicine research.

With these revisions, the authors have effectively addressed prior concerns and elevated the impact of their work. The manuscript now presents a compelling case for the retriever as a valuable tool in precision oncology.

Reviewer #3 (Public review):

The authors use a generic model framework to study the emergence of habituation and its functional role from information-theoretic and energetic perspectives. Their model features a receptor, readout molecules, and a storage unit, and as such, can be applied to a wide range of biological systems. Through theoretical studies, the authors find that habituation (reduction in average activity) upon exposure to repeated stimuli should occur at intermediate degrees to achieve maximal information gain. Parameter regimes that enable these properties also result in low dissipation, suggesting that intermediate habituation is advantageous both energetically and for the purpose of retaining information about the environment.

A major strength of the work is the generality of the studied model. The presence of three units (receptor, readout, storage) operating at different time scales and executing negative feedback can be found in many domains of biology, with representative examples well discussed by the authors (e.g. Figure 1b). A key takeaway demonstrated by the authors that has wide relevance is that large information gain and large habituation cannot be attained simultaneously. When energetic considerations are accounted for, large information gain and intermediate habituation appear to be the favorable combination.

Comments on the revision:

The authors have adequately addressed the points I raised during the initial review. The text has been clarified at multiple instances, and the treatment of energy expenditure is now more rigorous. The manuscript is much improved both in terms of readability and scientific content.

https://taz.de/Mehr-russisches-Erdgas-fuer-China/!6021655/

Reviewer #2 (Public review):

This work presents new genetic tools for enhanced Cre-mediated gene deletion and genetic lineage tracing. The authors optimise and generate mouse models that convert temporally controlled CreER or DreER activity to constitutive Cre expression, coupled with the expression of tdT reporter for the visualizing and tracing of gene-deleted cells. This was achieved by inserting a stop cassette into the coding region of Cre, splitting it into N- and C-terminal segments. Removal of the stop cassette by Cre-lox or Dre-rox recombination results in the generation of modified Cre that is shown to exhibit similar activity to native Cre. The authors further demonstrate efficient gene knockout in cells marked by the reporter using these tools, including intersectional genetic targeting of pericentral hepatocytes.

The new models offer several important advantages. They enable tightly controlled and highly effective genetic deletion of even alleles that are difficult to recombine. By coupling Cre expression to reporter expression, these models reliably report Cre-expressing i.e. gene-targeted cells and circumvent false positives that can complicate analyses in genetic mutants relying on separate reporter alleles. Moreover, the combinatorial use of Dre/Cre permits intersectional genetic targeting, allowing for more precise fate mapping.

The study and the new models have also limitations. The demonstration of efficient deletion of multiple floxed alleles in a mosaic fashion, a scenario where the lines would demonstrate their full potential compared to already existing models, has not been tested in the current study. Mosaic genetics is increasingly recognized as a key methodology for assessing cell-autonomous gene functions. The challenge lies in performing such experiments, as low doses of tamoxifen needed for inducing mosaic gene deletion may not be sufficient to efficiently recombine multiple alleles in individual cells while at the same time accurately reporting gene deletion. In addition, as discussed by the authors, a limitation of this line is the constitutive expression of Cre, which is associated with toxicity in some cases.

Comments on revisions: I have no further comments.

Reviewer #2 (Public review):

Summary:

Canonical Wnt signaling has previously been shown to be responsible for correct patterning of the oral-aboral axis as well as germ layer formation in several cnidarians. The post-gastrula stage, the planula larvae is not only elongated, it has a specific swimming direction due to the decentralized cellular positioning and slanted anchoring of the cilia. This, in turn, is in most other animals the result of a Wnt-Planar-cell polarity pathway. This paper by Uveira et al investigates the role of Wnt3 signaling in serving as a local cue for the PCP pathway which then is responsible for the orientation of the cilia and elongation of the planula larva of the hydrozoan Clytia hemisphaerica. Wnt3 was shown before to activate the canonical pathway via ß-catenin and to act as an axial organizer. The authors provide compelling evidence for this somewhat unusual direct link between the pathways through the same signaling molecule, Wnt3. In conclusion, they propose a two-step model: 1) local orientation by Wnt3 secretion 2) global propagation by the PCP pathway over the whole embryo.

Strengths:

In a series of elegant and also seemingly sophisticated experiments, they show that Wnt3 activates the PCP pathway directly, as it happens in the absence of canonical Wnt signaling (e.g. through co-expression of dnTCF). Conversely, constitutive active ß-catenin was not able to rescue PCP coordination upon Wnt3 depletion, yet restored gastrulation. This uncouples the effect of Wnt3 on axis specification and morphogenetic movements from the elongation via PCP. Through transplantation of single blastomeres providing a local source of Wnt3, they also demonstrate the reorganization of cellular polarity immediately adjacent to the Wnt3 expressing cell patch. These transplantation experiments also uncover that mechanical cues can also trigger the polarization, suggesting a mechanotransduction or direct influence on subcellular structures, e.g. actin fiber orientation.

This is a beautiful and elegant study addressing an important question. The results have significant implications also for our understanding of the evolutionary origin of axis formation and the link of these two ancient pathways, which in most animals are controlled by distinct Wnt ligands and Frizzled receptors. The quality of the data is stunning and the paper is written in a clear and succinct manner. This paper has the potential to become a widely cited milestone paper.

Weaknesses:

I can not detect any major weaknesses. The work only raises a few more follow-up questions, which the authors are invited to comment on.

I acknowledge the revisions made by the authors. Some open questions remain that need to be addressed in future work, and I accept the limitations of this study, as argued by the authors. Besides the elegant and high-quality experiments, I also appreciate the thoughtful and inspiring discussion.

Reviewer #2 (Public review):

This manuscript addresses a fundamental problem of immunology - the persistence mechanisms of tissue-resident memory T cells (TRMs). It introduces a novel quantitative methodology, combining the in vivo tracing of T cell cohorts with rigorous mathematical modeling and inference. Interestingly, the authors show that immigration plays a key role for maintaining CD4+ TRM populations in both skin and lamina propria (LP), with LP TRMs being more dependent on immigration than skin TRMs. This is an original and potentially impactful manuscript.

Comments on revised version: This reviewer is satisfied with the author responses and the changes made in the manuscript.

Reviewer #2 (Public review):

Strengths:

Wang and colleagues successfully uncovered an important function of the Drosophila PRDM16/PRDM3 homolog Hamlet (Ham) - a PR domain containing transcription factor with known roles in the nervous system in Drosophila. To do so, they generated and analyzed new mutants lacking the PR domain, and also employed diverse preexisting tools. In doing so, they made a fascinating discovery: They found that PR-domain containing isoforms of ham are crucial in the intriguing development of the fly genital tract. Wang and colleagues found three distinct roles of Ham: (1) Specifying the position of the testis terminal epithelium within the testis, (2) allowing normal shaping and growth of the anlagen of the seminal vesicles and paragonia and (3) enabling the crucial epithelial fusion between the seminal vesicle and the testis terminal epithelium. The mutant blocks fusion even if the parts are positioned correctly. The last finding is especially important, as there are few models allowing one to dissect the molecular underpinnings of heterotypic epithelial fusion in development. Their data suggest that they found a master regulator of this collective cell behavior. Further, they identified some of the cell biological players downstream of Ham, like for example E-Cadherin and Crumbs. In a holistic approach, they performed RNAseq and intersected them with the CUT&TAG-method, to find a comprehensive list of downstream factors directly regulated by Ham. Their function in the fusion process was validated by a tissue-specific RNAi screen. Meticulously, Wang and colleagues performed multiplexed in situ hybridization and analyzed different mutants, to gain a first understanding of the most important downstream-pathways they characterized - which are Wnt2 and Toll.

This study pioneers a completely new system. It is a model for exploring a process crucial in morphogenesis across animal species, yet not well-understood. Wang and colleagues not only identified a crucial regulator of heterotypic epithelial fusion but took on the considerable effort of meticulously pinning down functionally important downstream effectors by using many state-of-the-art methods. This is especially impressive, as dissection of pupal genital discs before epithelial fusion is a time-consuming and difficult task. This promising work will be the foundation future studies build on, to further elucidate how this epithelial fusion works, for example on a cell biological and biomechanical level.

Weaknesses:

The developing testis-genital disc system has many moving parts. Myotube migration was previously shown to be crucial for testis shape. This means, that there is the potential of non-tissue autonomous defects upon knockdown of genes in the genital disc or the terminal epithelium, affecting myotube behavior which in turn affects epithelial fusion, as myotubes might create the first "bridge" bringing the two epithelia together. Nevertheless, this is outside the scope of this work and could be addressed in the future.

Reviewer #2 (Public review):

This manuscript explores the molecular mechanisms that are involved in substrate recognition by the PP1 phosphatase. The authors previously showed that the PP1 interacting protein (PPI), PhactrI, conferred substrate specificity by remodelling the PP1 hydrophobic substrate groove. In this work, the authors aimed to understand the key determinant of how other PIPs, Neurabin and Spinophilin, mediate substrate recognition.

The authors generated a few PP1-PIP fusion constructs, undertook TMT phosphoproteomics and validated their method using PP1-Phactr1/2/3/4 fusion constructs. Using this method, the authors identified phsophorylation sites controlled by PP1-Neurabin and focussed their work on 4E-BP1, thereby linking PP1-Neurabin to mTORC1 signalling. Upon validating that PP1-Neurabin dephosphorylates 4E-BP1, they determined that 4E-BP1 PBM binds to the PDZ domain of Neurabin with an affinity that was greater than 30 fold as compared to other substrates. PP1-Neurabin dephosphorylated 4E-BP1WT and IRSp53WT with a catalytic efficiency much greater than PP1 alone. However, PP1-Neurabin bound to 4E-BP1 and IRSp53 mutants lacking the Neurabin PDZ domain with a catalytic efficiency lesser than that observed with 4E-BP1WT. These results indicate the involvement of the PDZ domain in facilitating substrate recruitment by PP1-Neurabin. Interestingly, PP1-Phactr1 dephosphorylation of 4E-BP1 phenocopies PP1 alone, while PP1-Phactr1 dephosphorylates IRSp53 to a much higher extent than PP1 alone. These results highlights the importance of the PDZ domain and also shed light on how different PP1-PIP holoenzymes mediate substrate recognition using distinct mechanisms. The authors also show that the remodelling of the hydrophobic PP1 substrate groove which is essential for substrate recognition by PP1-Phactr1, was not required by PP1-Neurabin. Additionally, the authors also resolved the structure of a PP1-4E-BP1 fusion with the PDZ-containing C-terminal of Neurabin and observed that the Neurabin/PP1-4E-BP1 complex structure was oriented at 21{degree sign} to that in the unliganded Spinophilin/PP1 complex (resolved by Ragusa et al., 2010) owing to a slight bend in the C-terminal section that connects it to the RVxF-ΦΦ-R-W string. Since, no interaction was observed with the remodelled PP1-Neurabin hydrophobic groove, the authors utilised AlphaFold3 to further answer this. They observed a high confidence of interaction between the groove and phosphorylated substrate and a low confidence of interaction between the groove and unphosphorylated substrate, thereby suggesting that the hydrophobic groove remodelling is not involved in PP1-Neurabin recognition and dephosphorylation of 4E-BP1.

In this work, the authors provide novel insights into how Neurabin depends on the interaction between its PDZ domain and PBM domains of potential substrates to mediate its recruitment by PP1. Additionally, they uncover a novel PP1-Neurabin substrate, 4E-BP1. They systematically employ phosphoproteomics, biochemical and structural methods to investigate substrate specifity in a robust fashion. Furthermore, the authors also compares the interactions between PP1-Neurabin to 4E-BP1 and IRSp53 (PP1-Phactr1 substrate) with PP1-Phactr1, to showcase the specificity of the mode of action employed by these complexes in mediating substrate specificity. The authors do employ an innovative PP1-PIP fusion strategy previously explored by Oberoi et al., 2016 and the authors themselves in Fedoryshchak et al., 2020. This method, allows for a more controlled investigation of the interactions between PP1-PIPs and its substrates. Furthermore, the authors have substantially characterised the importance of the PDZ domain using their fusion constructs, however, I believe that a further exploration into either structural or AlphaFold3 modelling of PBM domain substrate mutants, or a Neurabin PDZ-domain mutant might further strengthen this claim. Overall, the paper makes a substantial contribution to understanding substrate recognition and specificity in PP1-PIP complexes. The study's innovative methods, biological relevance, and mechanistic insights are strengths, but whether this mechanism occurs in a physiological context is unclear.

Reviewer #2 (Public review):

Summary:

This paper studies the role of hexatic defects in the collective migration of epithelia. The authors emphasize that epithelial migration is driven by cell intercalation events and not just isolated T1 events, and analyze this through the lens of hexatic topological defects. Finally, the authors study the effect of active and passive forces on the dynamics of hexatic defects using analytical results, and numerical results in both continuum and phase-field models.

The results are very interesting and highlight new ways of studying epithelial cell migration through the analysis of the binding and unbinding of hexatic defects.

Strengths:

(1) The authors convincingly argue that intercalation events are responsible for collective cell migration, and that these events are accompanied by the formation and unbinding of hexatic topological defects.

(2) The authors clearly explain the dynamics of hexatic defects during T1 transitions, and demonstrate the importance of active and passive forces during cell migration.

(3) The paper thoroughly studies the T1 transition through the viewpoint of hexatic defects. A continuum model approach to study T1 transitions in cell layers is novel and can lead to valuable new insights.

Weaknesses:

(1) The authors could expand on the dynamics of existing hexatic defects during epithelial cell migration, in addition to how they are created during T1 transitions.

(2) The different terms in the MPF model used to study cell layer dynamics are not fully justified. In particular, it is not clear why the model includes self-propulsion and rotational diffusion in addition to nematic and hexatic stresses, and how these quantities are related to each other.

(3) The authors could provide some physical intuition on what an active extensile or contractile term in the hexatic order parameter means, and how this is related to extensility and contractility in active nematics and/or for cell layers.