Reviewer #3 (Public review):

Summary:

This important work provides a web-based tool to contextualize effect sizes in psychiatry with respect to reliability and base rates (collectively referred to as predictive utility analysis). The methods for the tool incorporate established psychometric principles that I think are of use for multiple fields in this seemingly easy-to-use tool. I agree with the critical importance of this tool and the methodological points made in this manuscript. Enthusiasm for the manuscript is weakened by a lack of clarity on the formulation of the paper and stated goals of the examples used, with the inferences and impact on clinical decision making from various parameterizations via this tool left open-ended.

Strengths:

This paper presents a well-considered and, what I think will be highly useful, web-based tool to contextualize effect sizes with respect to reliability and base rates. As the authors rightly point out, such a tool could be used in conjunction with widespread analytic power analysis tools in study planning. The paper also well contexualizes the need for such a tool in the relatively recent history of concerns of power, reliability, and inference in psychiatry specifically, and more general meta-scientific debates in psychology and neuroscience.

Weaknesses:

My primary feedback on this manuscript is the lack of clarity in what the paper itself, specifically, separate from the tool, is hoping to achieve. There is a central, but unresolved, tension in whether the reader is supposed to:

(1) focus on the specifics of the examples used and whether to reevaluate the substantive claims from the studies, (2) buy in to how various reliability and base rate parameters impact modeling outcomes, (3) receive an introduction to the tool itself.

In my estimation, the largest contribution to the field here is in (2) and (3), but currently much of the real estate of the paper is dedicated to several examples of (1). While these specific examples may be illustrative to some degree, I think given the number and brevity of such, they are unlikely to incidentally achieve points (2) and (3) above. Specific examples include the assertion of kappas for DSM diagnoses, without much nuance (e.g., see https://psycnet.apa.org/buy/2015-27500-001). Given the relatively limited space given to this example, however, it's hard to be entirely certain what the reviewer should take away.

A second point of concern is where this tool would be situated in the research pipeline. I agree with the authors that this tool could be used in ways that parallel power analysis. With that in mind, it seems the most common use of this tool for an individual investigator is likely to be in a priori study planning. In contrast, and with my point above in mind, the use of the tool for existing results is likely best done with multiple estimates of effect sizes, reliability, and base rates, as is common in meta-analysis or consensus reviews. Nevertheless, there is no real example or guidance around how this influences new study planning.

A third point is that more nuance would be useful in the introduction about the current state of psychiatry research. For example, I share many of the authors' concerns about reliability, power, reproducibility, and barriers to translation. That said, it is the case that while effect sizes should be considered considerably more, they are widely considered in psychiatry research via the common place of meta-analysis and other data pooling approaches. Another such example that the authors state in the context of reliability: "However, this [reliability] attenuation is rarely accounted for in routine analyses in psychiatry". This is true in practice, but somewhat misleading insofar as the method by which to do this remains unclear. For example, should we all report disattenuated associations, assuming there is no error and everything is perfectly reliable? This, of course, would be unrealistic to expect zero error. That we can achieve this with the new tool is clear, but the nuance of how and under what circumstances it should be done is not clear, and such nuance should be better reflected in the framing of the problem. That is, there is also a lack of clarity on what ought to be best practices and field-wide goals, rather than simply the lack of an ability to model these factors.

Minor point

For conceptual clarity, it would benefit the manuscript to at least briefly mention the role of validity in translational importance. Of course, the current psychometric issues of reliability, base rate, power, etc are critical, but it should at least be mentioned, given the potential wide audience of this manuscript, validity is important as well. For example, highly reliable measures may not be valid indicators of underlying disease etiology (e.g., fMRI head motion is a highly reliable trait-level feature, but typically not considered an important predictor or consequence of mental health worth investing translational resources in). Relatedly, confounding as a general topic would be useful to mention just briefly, to help with the spirit of considering underlying issues in translation.

Reviewer #1 (Public review):

Summary:

Here the authors attempted to test whether the function of Mettl5 in sleep regulation was conserved in Drosophila, and if so, by which molecular mechanisms. To do so they performed sleep analysis, as well as RNA-seq and ribo-seq in order to identify the downstream targets. They found that the loss of one copy of Mettl5 affects sleep, and that its catalytic activity is important for this function. Transcriptional and proteomic analyses show that multiple pathways were altered, including the clock signaling pathway and the proteasome. Based on these changes the authors propose that Mettl5 modulate sleep through regulation of the clock genes, both at the level of their production and degradation, possibly by altering the usage of Aspartate codon.

Comments on revisions:

The authors addressed all my comments satisfactorily.

Reviewer #3 (Public review):

Xiaoyu Wu and colleagues examined a potential role in sleep of a Drosophila ribosomal RNA methyltransferase, mettl5. Based on sleep defects reported in CRISPR generated mutants, the authors performed both RNA-seq and Ribo-seq analyses of head tissue from mutants and compared to control animals collected at the same time point. A major conclusion was that the mutant showed altered expression of circadian clock genes, and that the altered expression of the period gene in particular accounted for the sleep defect reported in the mettl5 mutant. In this revision, the authors have added a more thorough analysis of clock gene expression and show that PER protein levels are increased relative to wild type animals a specific times of day, indicating increased stability of the protein. Given that PER inhibits its own transcription, the per RNA is low in the mutants. The revised manuscript included efforts toward a more detailed understanding of how clock gene expression was altered in the mutants, as well as other clarification of sleep phenotypes.

Comments on revisions:

All critiques have been addressed by the authors; the manuscript is much improved from its original submission. Thank you.

Reviewer #1 (Public review):

Summary:

This study aims to clarify MATR3's function and molecular mechanism in oocyte growth and maturation, explore its association with OMA, and its potential as a diagnostic and therapeutic target using specific knockout mouse models, human OMA samples, and multi-omics technologies. And it has fully achieved preset objectives with results strongly supporting conclusions. Specifically, it addresses the gap in the synergistic mechanism of epigenetic and secretory signals regulated by RNA-binding proteins (RBPs) in oocyte growth and enriches the molecular etiological spectrum of oocyte maturation disorders. It is the first time the conservative function of MATR3 has been revealed in multiple species, providing a paradigm for cross-species research on RBPs in the field of reproductive biology. It also provides a new candidate target for OMA, a clinically refractory infertility disease, and is expected to promote the optimization of assisted reproductive technology and the development of precision medicine.

Strengths:

The strengths of this study are significant and prominent. First, the research system is comprehensive, integrating knockout mouse models, in vitro knockdown models, multi-species (mouse, porcine, and human) verification, combined with scRNA-seq, LACE-seq, CO-IP, and other multi-omics and molecular biology technologies, forming a complete and progressive evidence chain. Second, the mechanism analysis is in-depth, clarifying the dual molecular mechanisms of MATR3 regulating the transcriptional synthesis and secretion of GDF9 through "recruiting KDM3B to regulate H3K9me2 demethylation" and "directly binding to Rdx mRNA", with a clear logical closed loop. Third, the clinical correlation is close. It is the first time to find abnormal nuclear localization of MATR3 in oocytes of OMA patients, providing new clues for clinical disease mechanism research, and verifying the downstream function of GDF9 through rescue experiments, effectively enhancing the translational value of the results.

Weaknesses:

This study included only one OMA patient's oocyte sample. Without clinical screening for MATR3 mutations or abnormal expression, establishing a causal relationship between MATR3 and OMA remains difficult.

Reviewer #2 (Public review):

Summary:

This study investigates the role of MATR3 in oocyte development and folliculogenesis using conditional knockout mouse models together with in vitro follicle culture and molecular analyses. The authors aim to determine whether MATR3 regulates oocyte maturation and follicle development and to explore potential mechanisms linking MATR3 function to transcriptional and epigenetic regulation in growing oocytes.

Strengths:

A major strength of the work is the use of a conditional knockout mouse model combined with complementary in vitro follicle culture approaches, which together provide a useful framework for examining gene function during oocyte development. The study also attempts to integrate cellular phenotypes with molecular analyses of transcriptional activity and epigenetic markers.

Weaknesses:

Several weaknesses limit the strength of the conclusions. These include insufficient validation of key experimental manipulations (such as the efficiency of MATR3 knockdown in siRNA experiments), limited quantification or statistical analysis for some datasets, inconsistencies between the text and presented data in certain figures, and incomplete methodological descriptions that make it difficult to fully evaluate reproducibility.

Reviewer #3 (Public review):

Summary:

The study aims to elucidate the dual molecular mechanisms of the RNA-binding protein MATR3 in oocyte growth and maturation. The authors propose that MATR3, highly expressed in growing oocytes (GOs), regulates oocyte quality through two pathways: epigenetically, by recruiting KDM3B to remove the repressive H3K9me2 mark at the Gdf9 locus to activate transcription; and post-transcriptionally, by binding Rdx mRNA to maintain microvillus structure for GDF9 secretion. This mechanism ensures oocyte-granulosa cell communication and female fertility. The study also explores the link between MATR3 and human oocyte maturation arrest (OMA).

Strengths:

The study proposes an innovative dual-mechanism model encompassing "epigenetic transcriptional activation and cytoskeletal regulation," which not only expands the functional understanding of RNA-binding proteins in chromatin regulation but also reveals the coordination between nuclear transcription and organelle structure. By integrating scRNA-seq and LACE-seq, the authors constructed a comprehensive regulatory network for MATR3, identifying both key targets and numerous potential molecules, thereby providing rich resources for future mechanistic studies. Furthermore, the inclusion of oocyte samples from human OMA patients directly links the basic findings to clinical reproductive disorders. Despite the limited sample size, this approach demonstrates strong translational potential.

Weaknesses:

The partial phenotypic improvement achieved by exogenous GDF9 supplementation suggests that the downstream effector pathways may involve a more complex network regulation, implying that the current interpretation of GDF9's central role could be further explored. Regarding the developmental abnormalities of granulosa cells in the conditional knockout model, their pathological origins require in-depth analysis to determine whether they represent primary alterations or secondary adaptive responses resulting from the loss of oocyte signaling.

Reviewer #1 (Public review):

The manuscript by Fisher et al describes the molecular mechanism underlying how G beta gamma subunits engage with the beta 3 isoform of PLC. The paper used a combination of cryo EM, BRET assays, and biochemical assays of PLC beta activity. A key discovery is that G beta gamma is not sufficient to drive membrane binding by itself, and instead promotes G alpha activation. The work is important, but suffers slightly from some ambiguity in the actual interface that is present in their cryo EM model, as crosslinkers could stabilise a transient and non-native complex. This is somewhat abrogated by the careful mutational analysis, which shows that mutation of any of these three sites does somewhat block PLC beta G beta gamma activation. However, there could be some improvement in the presentation of this data, as well as possible mutant selection. Overall, this paper is a nice complement to the Falzone et al paper, showing the membrane-bound complex of PLCB3 on membranes, with this work building on this work, highlighting the importance this will have in our full understanding of PLC beta activation.

Major concerns:

My biggest concern is the potential that this interface is artefactual based on the crosslinking strategy utilised. Here are thoughts on how this could be better validated, presented in a more convincing way.

(1) The authors' main claim is that there is a degree of plasticity of G beta gamma binding to the PLC beta 3 isoform, with three possible binding sites. The main complication of this is, of course, the possibility that the crosslinking stabilises a non-native complex, driven by a mutated cysteine.

Because of this, any other additional details about this interface are going to be critical for the scientific audience to judge if this is accurate.

What would greatly help Figure 1 is an evolutionary conservation analysis of the novel Gbg interface in PLC, to see how well this is conserved, and compare this to the conservation of the previously annotated sites. Conservation of these sites on both the G beta gamma and PLC side would help justify this as a native complex.

This will also help orient the reader to the identity of the mutated residues assayed in Figure 3.

(2) The g beta gamma orientation is also different than what I have observed in previous g beta gamma effector structures. Is there any precedent for this as an effector interface? A supplemental figure comparing this structure to other g beta gamma interfaces from other enzymes, for example recent Tesmer structure with PI3K.

(3) The mutational analysis in Figure 2D-G seems to give some strange results, and I have some question why certain residues were chosen rather than others. Mutation of the Gbg side will be more complicated, as of course that can affect any of the three surfaces. My main question is that, from the way Figure 2A is oriented, the main salt bridge in their novel interface to me looks like R199-D228, with K183 being in the wrong orientation to E226, and D167 being far from any charged residues. Why did the authors not make the corresponding R199 to D or E mutation?

(4) To help the reader's interpretation of Figure 2A, I would recommend a supplemental figure showing the density for interfacial residues, as that also would increase confidence in the interface.

Reviewer #2 (Public review):

In this manuscript, the authors dissect how Gβγ potentiates PLCβ3 signaling in cells. Using engineered crosslinking to stabilize a Gβγ-PLCβ3 complex, single particle cryo-EM, and cell-based functional assays, they identify and map multiple putative Gβγ interaction surfaces on PLCβ3, including a previously unrecognized binding mode. Structure-guided mutagenesis supports the functional relevance of these interactions and suggests that Gβγ potentiation is not primarily mediated by PLCβ3 membrane recruitment, but instead enhances PLCβ3 activity after the lipase is already at the membrane.

Previous reconstitution work on the membrane surface (Falzone & MacKinnon, 2023) proposed a recruitment/partitioning-centric model in which Gβγ increases PLCβ3 output largely by elevating its membrane surface concentration, whereas Gαq primarily increases catalytic turnover; under those reconstitution conditions, the two inputs can combine approximately multiplicatively. In receptor-driven cellular signaling, however, PLCβ3 is robustly recruited to the plasma membrane upon Gαq activation, which raises the question of whether Gβγ contributes mainly through additional recruitment or through a post-recruitment mechanism once PLCβ3 is already at the membrane.

This manuscript helps address that gap by using membrane-anchored PLCβ3 and complementary cellular readouts to separate "getting PLCβ3 to the membrane" from "boosting activity once PLCβ3 is already there." Their results argue that, in cells, membrane recruitment is largely dominated by Gαq·GTP, while Gβγ can further potentiate PIP2 hydrolysis after membrane association, consistent with a modulatory role at the membrane rather than primary recruitment.

Overall, the work provides a structural and mechanistic framework for Gβγ-PLCβ3 cooperation and helps clarify the basis of Gq pathway amplification. The manuscript is generally strong, but some issues need to be addressed.

Major comments:

(1) BMOE/BM(PEG)2 crosslinking may enforce a non-native docking geometry, potentially compromising the physiological relevance and precision of the Gβγ-PLCβ3 interface as described. Although a >50% 1:1 crosslinked complex is formed and remains active, the solution maps show lower local resolution for Gβγ, consistent with a dynamic, potentially heterogeneous, interface. One interface is captured via a single engineered cysteine pair (PLCβ3 E60C-Gβ C271), which could potentially bias the pose. It would be helpful if the authors could provide additional orthogonal support (e.g., alternative crosslinked sites) and bolster the clarification of its uniqueness and relevance.

(2) In the crosslinked structure, the authors report that GβD228 interacts with PLCβ3 R199 and K183. In Figure 2A, R199 appears closer to Gβ D228 than K183, yet only K183 is functionally tested. Testing R199 (e.g., R199E/R199A) would strengthen the structure-guided validation of this interface.

(3) The mutagenesis strategy appears inconsistent across figures/assays, which makes it difficult to interpret phenotypes and directly link the functional data to the proposed interfaces. For example, in Figure 2E, we see R185L but R215E, while residue L40 is mutated to Gly in the IP accumulation assays but to Glu/Lys (L40E/K) in the BRET assays (Figures 3B/3D/3F). The authors should (i) clearly justify the rationale for each substitution (conservative vs charge-reversal, interface disruption, etc.) and (ii), where possible, test the same mutants across assays (or provide evidence that alternative substitutions yield consistent conclusions).

Reviewer #3 (Public review):

Summary:

PLCβ3 is activated by both Gαq and Gβγ subunits. This paper follows previous solutions and cryoEM studies of PLCβ3 / Gβγ, trying to understand the molecular details of activation using cellular BRET assays and cryoEM.

Strengths:

The authors find evidence for multiple binding sites on PLCβ3 for Gβγ and suggest that Gβγ is not bone fide activator per se but enhances Gαq activation by positioning the catalytic site towards substrate, although this is not completely convincing. Although these sites may not naturally be operative, the authors might want to develop the potential role of these sites.

The authors also find that this activation is not through recruitment of the enzyme to the membrane by Gβγ released upon G protein activation, in accord with other PLCβ enzymes, but not for PLCβ3, and again, the authors might want to develop this point further.

Weaknesses:

(1) I'm confused as to why the authors feel that their mechanism is distinct from the two-state enzyme, the synergistic activation proposed by Ross in 2011, using a primarily thermodynamic argument. As written, the authors appear to be very reliant on structural and BRET studies that do not give the details that would disprove this interpretation. The main issue is that the author's mechanism does not fully explain how Gβγ activation occurs for PLCβ2 in reconstituted systems in the absence of Gαq subunits.

(2) In a recent study, McKinnon presents a model showing that Gαq and Gβγ activate PLCβ3 by two distinct pathways and that activation by Gβγ occurs through membrane recruitment. It is not surprising that the authors find that this is not true since the pelleting method used by McKinnon is subject to error. The authors should directly address the limitations of this previous work and the changes in proteoliposomes with sedimentation that alter partition coefficients. Although the inability of Gβγ to drive membrane binding is in accord with the quantitative studies of Scarlata, showing that the affinity of PLCβ3 to Gβγ is fairly weak as compared to the intrinsic membrane partition coefficient.

(3) It was proposed many years ago that in signaling complexes Gαq - Gβγ may not have to fully dissociate when binding PLCβ, but rather shift their relative orientation when binding to PLCβ to allow activation. Is their model consistent with this? Is it possible that PLCβ3 keeps Gβγ from diffusing to enhance the rate of Gq / Gβγ re-association?

(4) The authors find that Gβγ binds multiple sites, and it is clear that the PH domain site is the primary one in accord with previous work. Could these weaker sites be an artifact of the elevated concentrations used in cryoEM and BRET assays?

(5) Although their assays infer differences in binding affinities, it would strengthen the paper if the authors could estimate the association energies of these different binding sites. This estimation would also address the concern stated above.

Reviewer #1 (Public review):

Summary:

The authors set out to understand the complex regulation of the assembly of the Type 3 Secretion System of S. typhimurium. They found that the gene synteny as well as specific mRNA stem loops were important for the translational coupling of sctS and sctT. Without this regulation, SctT self-oligomerizes, which disrupts the export of effector proteins and leads to a decreased fitness of the pathogen. The work was done using a variety of convincing methods and leads to an updated picture of how T3SS assembly occurs. Since the same genetic synteny is found in a large majority of T3SS in different bacteria, it is likely that this is a general mechanism, but one that needs to be further experimentally validated.

Strengths:

The paper uses an impressive amount of experiments, with different techniques, to describe how they identified the genetic regulation of SctT production.

Weaknesses:

Only minor weaknesses are found.

(1) Regarding the use of the complex being unique. It is not well explained what makes this a unique complex.

(2) The paper would benefit from a discussion regarding how regulation might work in the minority of bacterial strains where the T3SS gene synteny is largely different. One would expect that those bacteria would have a different way of regulating T3SS assembly, but that is not discussed at all by the authors.

Reviewer #2 (Public review):

Summary:

In this manuscript, Samuel Wagner and colleagues describe an elegant mechanism to prevent promiscuous assembly of a core virulence type III secretion system protein, SctS. Starting from a bioinformatic standpoint, they demonstrate that synteny is highly conserved, and sctT occurs immediately downstream of sctS. Secretion is greatly reduced when sctT is removed or scrambled from its genomic context, and sctT expression is accordingly reduced (sctS synteny is also important, though less so). The distance between sctS and sctT is crucial. An elegant series of genetic experiments leads the authors to pinpoint a stem loop structure that occludes the Shine-Dalgarno sequence of sctT. This property is independent of the actual gene preceding sctT. In sum, this means that SctS is already expressed before SctT is expressed, preventing SctT from forming cytotoxic homooligomers.

Strengths:

The manuscript is very well-written, easy to follow, and describes a substantial amount of genetic detective work to identify the underlying mechanism. I have only a number of textual suggestions, mainly for the Introduction text, which I believe could be revised for a flagellar and broader audience.

Weaknesses:

Major concern:

While the work is rigorous and substantial, I am unsure as to whether its findings will appeal beyond a niche audience.

Minor points:

(1) Line 117: The number here seems to be very small. RefSeq has ~200,000 genomes. My guess is that at least 100,000 of these will be bacterial. Many (most?) bacteria have flagella, and some unflagellated strains have injectisomes, meaning I would have guessed that the authors would have ~50,000 genomes with SctRSTU. This estimate is error-prone, but not by too much. Can the authors explain the discrepancy between my estimate and their figure of almost two orders of magnitude? (SctRSTU/FliPQGFlhB should also be easy to pick up by sequence searches, so I don't think this is due to false negatives).

(2) Discussion: I would appreciate some discussion of how species that do not conserve the synteny of sctS and sctT prevent problems of sctT oligomerisation? It doesn't need to be evidence-based at this stage, but I'm sure the authors have thought about this, and the Discussion is an appropriate place to share their speculations.

Reviewer #3 (Public review):

At the core of the bacterial type III secretion system (T3SS), a nanomachine used to inject effector proteins into eukaryotic cells, five highly conserved proteins, SctRSTUV, form the export apparatus, which is the actual gate for effector proteins. Not only are these proteins the most strongly conserved parts of the system, but also their gene order is conserved, which is not the case for most other components of the T3SS. Interestingly, this order does not completely recapitulate the assembly order, which is SctR5-T4-S-U-V. Looking into the reasons for the conserved synteny, the authors noted a stem-loop in the mRNA of the Salmonella SPI-1 sctS gene, which is present in many other T3SS as well (and in fact had been found in Yersinia before). They then use an array of clever gene permutations and modifications to discern the benefit of this order for the bacteria. The combination of thorough sequence analysis with different, partly quantitative, protein expression and secretion assays and growth curves, both in the native Salmonella background and in heterologous systems, provides strong evidence for the interpretation of the authors: The stem-loop in sctS prevents the premature expression of SctT, which can otherwise assemble into "futile multimers" that can lead to ion loss. The presence of stem-loops in many other sctS/T genes gives weight to this finding.

This is a very nice and thorough study addressing an important point in the assembly of type III secretion systems. I only have a few suggestions.

(1) Conserved gene orders have been shown for many complexes, and the findings presented in this manuscript might be applicable to other membrane complexes.

The conservation of gene order and the presence of the stem loop give weight to the authors' findings. However, it is only mentioned quite late in the discussion that a similar stem loop was found in Yersinia upstream sctT earlier, and was interpreted differently. The authors' current discussion is somewhat evasive on this point. Why would these similar structures be used differently? Why would temperature not play a role in Salmonella SPI-1? And wouldn't the stem-loop also couple sctS and sctT expression in Yersinia? This should be addressed, if possible, by experiments (at least, the influence of temperature on the SPI-1 mRNA structure should be testable for the authors) and by a more detailed discussion (given the redundancy of RNA thermometers in the Yersinia T3SS, the interpretation in the current paper might well be the more compelling one).

(2) A point that deserves more attention is that a similar finding in Yersinia has been interpreted differently before (as a temperature sensor rather than translational coupling) - are these systems really different? Testing the different interpretations in the respective other system (at least the influence of temperature in the Salmonella SPI-1 system used in this manuscript) would have made the interpretation even more compelling.

(3) Another point that should be discussed in more detail is why this mechanism is present when replacement of the sctT ATG by weaker start codons and the simple omission of a separate SD sequence upstream sctT would achieve the same outcome. This could be tested in one of the nice heterologous systems, as used in Figure 4.

Reviewer #1 (Public review):

Summary:

This is an interesting and well-written manuscript in which the authors set out to answer a simple, old question with a modern toolkit: where in crab evolution did sideways walking arise, how often has it been lost or regained, and is it plausibly linked to the ecological and taxonomic success of true crabs. To do this, they record locomotion from 50 live species, convert each species' movements into a quantitative index that compares forward versus sideways bouts, and then map the resulting states onto a recent crab phylogeny to infer the most likely evolutionary history of locomotor direction.

Strengths:

The strongest part of the study is the dataset itself. Comparable behavioral measurements across dozens of crab species are rare. The authors have done the field and husbandry work needed to make this possible. The overall pattern they recover, that most true crabs are strongly biased toward sideways movement (while a smaller set of lineages move predominantly forward), is interesting and likely to be useful to others. The phylogenetic mapping is also a reasonable way to address the "how many times" question (although this is peripheral to my expertise). The manuscript makes a convincing case that sideways locomotion is not simply a trivial byproduct of a crab-like body plan.

Weaknesses:

Where I am less convinced is in how strongly the authors describe the discreteness of the behavioral categories and the absence of intermediates. The manuscript states that the Forward-Sideways Index shows a clear separation between two locomotor types with little evidence for intermediates, and it cites a statistical test rejecting a single peak in the distribution. However, the histogram in Figure 3 appears structured within each labeled category, with subclusters inside both the forward and sideways groups rather than a single tight peak per group. This matters because the index is built by first placing each movement bout into "forward" versus "sideways" bins using a fixed angle boundary and then collapsing the result into a single ratio. That approach is simple and transparent enough, but it can also hide mixed strategies. For example, a species that produces substantial amounts of both forward and sideways walking can still end up with a strongly positive or negative index, and therefore be classified as a pure "type," even though the underlying behavior is mixed. In that context, rejecting a single peak in the across-species distribution does not, by itself, justify the stronger claim that intermediates are rare or absent.

Related to this, a key methodological choice is the use of 60 degrees as the cutoff between forward and sideways bouts. This boundary may be reasonable as a convention, but the paper does not explain why it is the right place to draw the line, and there is a plausible biological concern that a fixed angular cutoff does not mean the same thing across taxa.

Crabs vary in body shape and in how the legs are arranged around the body. In my own comparative work, for example, some species show an elliptical stance pattern elongated along the preferred direction of travel, while others show a more circular leg arrangement, and the latter can express more mixed forward and sideways behavior. When limb arrangement and body geometry differ across species, the same measured angle can correspond to different underlying mechanics and different functional "degree of sidewaysness." The practical implication is that the reported binary separation may partly reflect the imposed classification rule, rather than a sharp biological divide.

Another limitation that affects interpretation is the decision to use one individual per species. I understand the logistics, and for some questions, a single representative individual can be a reasonable first pass. But it is not strong support for negative claims about intermediates, especially in a group where individuals can change substantially with growth and allometry. Crabs can grow dramatically, often with pronounced allometric shifts in limb proportions that can alter the center of mass location. Size alone can alter the kinematics and choice of locomotor behaviors in crustaceans. In species where appendage proportions change with size, or where certain legs become disproportionately large (or calcified), it is plausible that locomotor direction and the distribution of movement angles shift across ontogeny. That makes it hard to treat a single individual as a complete description of a species-level strategy, particularly for species that fall closer to the boundary between categories.

In sum, this is a valuable and useful behavioral comparative study with a dataset that many in the field will appreciate. The main conclusions about the likely evolutionary placement of sideways walking are plausible, but several of the stronger claims about discrete locomotor types, the absence of intermediates, and the relationship to diversification would be more convincing if the analysis were less dependent on a fixed angular cutoff and on single individuals per species, or if the manuscript framed those points more cautiously so the conclusions track the strength of the evidence.

Reviewer #2 (Public review):

Summary:

The current work investigates the evolution of sideward locomotion in Brachyura in light of a single evolutionary origin. To this end, the authors first analysed the mode of locomotion in 50 crab species and observed mutually exclusive presence of sideways vs. forward movement. The phylogenetic analysis confirmed that there is indeed a single evolutionary origin for sideways movement, which was sometimes followed by several reversions to forward locomotion. This way, authors demonstrate how locomotor movement modes shape evolutionary diversification in animals by showing that species richness is much higher in side-ways-moving crabs than in the nearest groups. This is an interesting work that integrates behavioural analysis and phylogenetic relations, capitalising largely on crabs. I have a few suggestions and questions.

Firstly, I think the paper spends too much time on a straightforward analysis of the mode of locomotion. I was also wondering whether the phylogenetic analysis could be simply achieved by maximising an objective function in which the modes of movement are inversely coded for two putative groups, with all values calculated at all possible nodes.

Unfortunately, I find that the authors did not sufficiently discuss differences in the ecological niches of species with forward vs. sideways locomotion modes (including challenges of locomotion and substrate).

Likewise, what are the anatomic correlates of forward vs. sideways locomotion? For instance, how are the advantages assumed for sideways movement associated with a flattened body? Is it possible that the mode of motion is secondary to flattened/narrow body structure, which basically limits the distance between legs and thus makes the forward movement difficult - under this logic, the mode of movement would be a secondary phenomenon to body shape traits. How can one differentiate between this alternative and the one that puts the mode of movement in the centre of the story? On a related note, how do different modes of movement relate to the ability to fit into tight spaces - how does it relate to differences in leg joints?

Is it possible that the sideways movement maximises the scanned visual field per unit time/displacement, which may be beneficial for mostly forward-moving predators?

It is really difficult to decipher the information contained in the nodes (circles) in the printed black-and-white version of the manuscript.

Briefly, although I find the study interesting, the presented complexity may not be necessary given the endpoints; it can be achieved much more simply. Furthermore, the degree to which the conceptual analysis of different modes of locomotion was exercised was limited. The general approach may serve as a good model for the evolutionary analysis of other traits. The demonstration of traceability of the relations in question is a major contribution of the work.

Strengths:

The research question and the novel combination of different data types.

Weaknesses:

The complexity of the methods used, along with a limited discussion of the potential dynamics that may underlie the evolution of the sideways movement mode.

通过了同行评审，但独立评估发现了幻觉、伪造结果和夸大新颖性——这个细节极为重要，却经常被忽视。它揭示了一个深刻的系统性漏洞：AI 已经学会了「通过评审」，但没有学会「诚实做科学」。这两件事在人类评审员看来是同一件事，但在 AI 系统的优化目标中可能是分离的。这是 AI 安全在科学领域的具体表现。

史上第一篇完全由 AI 自主生成并通过同行评审的论文——这个里程碑的重要性不亚于 AlphaFold 折叠蛋白质。令人惊讶的是，这篇论文得分超越了 55% 的人类作者投稿（平均分 6.33，高于人类投稿平均录取线）。学术界存在了数百年的「同行评审」制度，第一次被一个 AI 系统悄悄穿越了。

【启发】「AI 天然不在意结构，除非你明确要求」——这个发现定义了人类工程师在 AI 时代最不可替代的职责：做代码结构的「守门人」。这与 Every 文章里「每个人都是管理者」的洞见形成呼应：人类的工作从「执行代码」转变为「审查代码质量并为 AI 设定标准」。对工程团队文化的启发：代码 Review 的重要性不是在下降，而是在上升——因为现在需要 Review 的代码量是以前的 10 倍。

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have submitted a second revision, largely to address a comment from Reviewer 2, which was "The failure to model the neural data with an explicit model is a missed opportunity." The authors have now included a computational model.]

This study makes a fundamental contribution to our understanding of interocular suppression, particularly continuous flash suppression (CFS). Using neuroimaging data from two macaque monkeys, the study provides compelling evidence that CFS suppresses orientation responses in neurons within V1. These findings enrich the CFS literature by demonstrating that neural activity under CFS may prevent high-level visual and cognitive processing.

Comments on previous revisions:

The authors have addressed all my previous comments.

Reviewer #2 (Public review):

Summary:

The goal of this study was to investigate the degree to which low-level stimulus features (i.e., grating orientation) are processed in V1 when stimuli are not consciously perceived under conditions of continuous flash suppression (CFS). The authors measured the activity of a population of V1 neurons at single neuron resolution in awake fixating monkeys while they viewed dichoptic stimuli that consisted of an oriented grating presented to one eye and a noise stimulus to the other eye. Under such conditions, the mask stimulus can prevent conscious perception of the grating stimulus. By measuring the activity of neurons (with Ca2+ imaging) that preferred one or the other eye, the authors tested the degree of orientation processing that occurs during CFS.

Strengths:

The greatest strength of this study is the spatial resolution of the measurement and the ability to quantify stimulus representations during CSF in populations of neurons preferring the eye stimulated by either the grating or the mask. There have been a number of prominent fMRI studies of CFS, but all of them have had the limitation of pooling responses across neurons preferring either eye, effectively measuring the summed response across ocular dominance columns. The ability to isolate separate populations offers an exciting opportunity to study the precise neural mechanisms that give rise to CFS, and potentially provide insights into nonconscious stimulus processing.

Weaknesses:

(The authors have now included a computational model in the second revision.)

Reviewer #3 (Public review):

Summary:

In this study, Tang, Yu & colleagues investigate the impact of continuous flash suppression (CFS) on the responses of V1 neurons using 2-photon calcium imaging. The report that CFS substantially suppressed V1 orientation responses. This suppression happens in a graded fashion depending on the binocular preference of the neuron: neurons preferring the eye that was presented with the marker stimuli were most suppressed, while the neurons preferring the eye to which the grating stimuli were presented were least suppressed. Binocular neuron exhibited an intermediate level of suppression.

Strengths:

The imaging techniques are cutting-edge.

Weaknesses:

The strength of CFS suppression varies across animals, but the authors attribute this to comparable heterogeneity in the human psychophysics literature.

Comments on previous revisions:

The authors have addressed my comments from the previous round of review, and I have no further comments.

Reviewer #1 (Public review):

In this paper, Stanojcic and colleagues attempt to map sites of DNA replication initiation in the genome of the African trypanosome, Trypanosoma brucei. Their approach to this mapping is to isolate 'short-nascent strands' (SNSs), a strategy adopted previously in other eukaryotes (including in the related parasite Leishmania major), which involves isolation of DNA molecules whose termini contain replication-priming RNA. By mapping the isolated and sequenced SNSs to the genome (SNS-seq), the authors suggest that they have identified origins, which they localise to intergenic (strictly, inter-CDS) regions within polycistronic transcription units and suggest display very extensive overlap with previously mapped R-loops in the same loci. Finally, having defined locations of SNS-seq mapping, they suggest they have identified G4 and nucleosome features of origins, again using previously generated data. Though there is merit in applying a new approach to understand DNA replication initiation in T. brucei, where previous work has used MFA-seq and ChIP of a subunit of the Origin Replication Complex (ORC), there are two significant deficiencies in the study that must be addressed to ensure rigour and accuracy.

(i) The suggestion that the SNS-seq data is mapping DNA replication origins that are present in inter-CDS regions of the polycistronic transcription units of T. brucei is novel and does not agree with existing data on the localisation of ORC1/CDC6, and it is very unclear if it agrees with previous mapping of DNA replication by MFA-seq due to the way the authors have presented this correlation. For these reasons, the findings essentially rely on a single experimental approach, which must be further tested to ensure SNS-seq is truly detecting origins. Indeed, in this regard, the very extensive overlap of SNS-seq signal with RNA-DNA hybrids should be tested further to rule out the possibility that the approach is mapping these structures and not origins.

(ii) The authors' presentation of their SNS-seq data is too limited and therefore potentially provides a misleading view of DNA replication in the genome of T. brucei. The work is presented through a narrow focus on SNS-seq signal in the inter-CDS regions within polycistronic transcription units, which constitute only part of the genome, ignoring both the transcription start and stop sites at the ends of the units and the large subtelomeres, which are mainly transcriptionally silent. The authors must present a fuller and more balanced view of SNS-seq mapping, across the whole genome, to ensure full understanding and clarity.

In the revised manuscript, the authors have improved the presentation and analysis of their data, expanding the description of SNS-seq mapping across the genome, and more clearly assessing to what extent there is correlation between SNS-seq signal and previous mapping approaches to predict origins (by MFA-seq and ChiP-chip of ORC1/CDC6). With regard the correlation between SNS-seq and ORC/1CDC6 ChIP-chip, it should be noted that two datasets were generated in distinct strains of T. brucei (Lister 427 and TREU927, respectively), and it is unclear if the latter dataset can be accurately mapped to the strain used here. Notwithstanding this concern, these improvements clarify a number of aspects of the SNS-seq mapping: (1) the signal is more prevalent in the transcribed core of the genome than in the largely transcriptionally silent subtelomeres; and (2) whereas previous work revealed strong correlation between ORC1/CDC6 localisation and MFA-seq peaks at the ends of multigene transcription units, neither of these data show significant overlap with SNS-seq signal, which is not seen at transcription start or stop sites ('SSRs'; supplementary Fig.8D) and shows marked depletion at predicted ORC1/CDC6 sites (supplementary Fig.8C). To the authors' credit, they acknowledge this lack of correlation in the discussion.

The authors have not provided any new data to substantiate their assertion that SNS-seq accurately detects origins in T. brucei, and therefore the work rests on a single experimental approach, without validation. As a result, the suggestion of abundant, previously undetected origins in the intergenic regions of multigene transcription remains a prediction. One key untested limitation of the work lies in the observation that the very large majority of SNS-seq signal overlaps with previously RNA-DNA hybrids; without an experimental test, the suggestion that the authors have 'disclosed for the first time a strong link between RNA:DNA hybrid formation and DNA replication initiation' remains conjecture.

Reviewer #2 (Public review):

Summary:

Stanojcic et al. investigate the origins of DNA replication in the unicellular parasite Trypanosoma brucei. They perform two experiments, stranded SNS-seq and DNA molecular combing. Further, they integrate various publicly available datasets, such as G4-seq and DRIP-seq, into their extensive analysis. Using this data, they elucidate the structure of origins of replications. In particular, they find various properties located at or around origins, such as polynucleotide stretches, G-quadruplex structures, regions of low and high nucleosome occupancy, R-loops, and that origins are mostly present in intergenic regions. Combining their population-level SNS-seq and their single-molecule DNA molecular combing data, they elucidate the total number of origins as well as the number of origins active in a single cell.

Between the initial submission and this revision, the raised major concerns have not been resolved, and no additional validation has been provided.

Strengths:

(1) A very strong part of this manuscript is that the authors integrate several other datasets and investigate a large number of properties around origins of replication. Data analysis clearly shows the enrichment of various properties at the origins, and the manuscript is concluded with a very well-presented model that clearly explains the authors' understanding and interpretation of the data.

(2) The DNA combing experiment is an excellent orthogonal approach to the SNS-seq data. The authors used the different properties of the two experiments (one giving location information, one giving single-molecule information) well to extract information and contrast the experiments.

(3) The discussion is exemplary, as the authors openly discuss the strengths and weaknesses of the approaches used. Further, the discussion serves its purpose of putting the results in both an evolutionary and a trypanosome-focused context.

Weaknesses:

I have major concerns about the origin of replication sites determined from the SNS-seq data. As a caveat, I want to state that, before reading this manuscript, SNS-seq was unknown to me; hence, some of my concerns might be misplaced.

(1) There are substantial discrepancies between the origins identified here and those reported in previous studies. Given that the other studies precede this manuscript, it is the authors' duty to investigate these differences. A conclusion should be reached on why the results are different, e.g., by orthogonally validating origins absent in the previous studies.

(2) I am concerned that up to 96% percent of all SNS-seq peaks are filtered away. If there is so much noise in the data, how can one be sure that the peaks that remain are real? Upon request, the authors have performed a control, where randomly placed peaks were run through the same filtering process. Only approximately twice as many experimental peaks passed filtering compared to random peaks. While the authors emphasize reproducibility between replicates, technical artifacts from the protocol would also be reproducible. Moreover, in other SNS-seq studies, for example, Pratto et al. Cell 2021, Fig. 1B, + and − strand peaks always appear closely paired. This pattern contrasts strongly with Fig. 2A in this manuscript.

Further, I have some minor concerns that do not affect the main conclusions of the manuscript:

- Fig 2C: The regions shown in the heatmap have different sizes, and I presume that the regions are ordered by size on the y-axis? If so, does the cone-shaped pattern, which is origin-less for genic regions and origin-enriched for intergenic regions, arise from the size of the regions? (I.e., for each genic region, the region itself is origin-less and the flanking intergenic regions contain origins.) If this is the case, then the peaks/valleys, centered exactly on the center of the regions on the mean frequency plots, arise from the different sizes of the analyzed regions, not from the fact that origins are mostly found at the center of intergenic regions. This data would be better presented with all regions stretched to the same size. This has not been addressed in the revision.

- Line 123, "and the average length of origins was found to be approximately 150 bp.": To determine origins, the authors filter away overlapping peaks and peaks that are too far from each other. Both restrict the minimal and maximal length of origins that can be observed, and this, in turn, affects the average length. This has not been addressed in the revision.

Are claims well substantiated?:<br /> The identification of origins via SNS-seq appears to be incompletely supported to me.<br /> All downstream analyses depend on the reliability of origin identification.

Impact:<br /> This study has the potential to be valuable for two fields: In research focused on T. brucei as a disease agent, where essential processes that function differently than in mammals are excellent drug targets. Further, this study would impact basic research analyzing DNA replication over the evolutionary tree, where T. brucei can be used as an early-divergent eucaryotic model organism.

Reviewer #1 (Public review):

Summary:

The manuscript "Adapting Clinical Chemistry Plasma as a Source for Liquid Biopsies" addresses a timely and practical question: whether residual plasma from heparin separator tubes can serve as a source of cfDNA for molecular profiling. This idea is attractive, since such samples are routinely generated in clinical chemistry labs and would represent a vast and accessible resource for liquid biopsy applications. The preliminary results are encouraging, and likely to benefit the research community.

Comments on revisions:

The concerns raised have been addressed. The heparin separator-based cfDNA method described in this study is likely to benefit the research community. I have no further scientific concerns.

Reviewer #2 (Public review):

Summary:

The authors propose that leftover heparin plasma can serve as a source for cfDNA extraction, which could then be used for downstream genomic analyses such as methylation profiling, CNV detection, metagenomics, and fragmentomics. While the study is potentially of interest, several major limitations reduce its impact; for example, the study does not adequately address key methodological concerns, particularly cfDNA degradation, sequencing depth limitations, statistical rigor, and the breadth of relevant applications.

Strengths:

The paper provides a cheap method to extract cfDNA, which has broad application if the method is solid.

Weaknesses:

(1) The introduction lacks a sufficient review of prior work. The authors do not adequately summarize existing studies on cfDNA extraction, particularly those comparing heparin plasma and EDTA plasma. This omission weakens the rationale for their study and overlooks important context.

(2) The evaluation of cfDNA degradation from heparin plasma is incomplete. The authors did not compare cfDNA integrity with that extracted from EDTA plasma under realistic sample handling conditions. Their analysis (lines 90-93) focuses only on immediate extraction, which is not representative of clinical workflows where delays are common. This is in direct conflict with findings from Barra et al. (2025, LabMed), who showed that cfDNA from heparin plasma is substantially more degraded than that from EDTA plasma. A systematic comparison of cfDNA yields and fragment sizes under delayed extraction conditions would be necessary to validate the feasibility of their proposed approach.

(3) The comparison of methylation profiles suffers from the same limitation. The authors do not account for cfDNA degradation and the resulting reduced input material, which in turn affects sequencing depth and data quality. As shown by Barra et al., quantifying cfDNA yield and displaying these data in a figure would strengthen the analysis. Moreover, the statistical method applied is inappropriate: the authors use Pearson correlation when Spearman correlation would be more robust to outliers and thus more suitable for methylation and other genomic comparisons.

(4) The CNV analysis also raises concerns. With low-coverage WGS (~5X) from heparin-derived cfDNA, only large CNVs (>100 kb) are reliably detectable. The authors used a 500 kb bin size for CNV calling, but they did not acknowledge this as a limitation. Evaluating CNV detection at multiple bin sizes (e.g., 1 kb, 10 kb, 50 kb, 100 kb, 250 kb) would provide a more complete picture. In addition, Figure 3 presents CNV results from only one sample, which risks bias. Similar bias would exist for illustrations of CNVs from other samples in the supplementary figures provided by the authors. Again, Spearman correlation should be applied in Figure 3c, where clear outliers are visible.

(5) It is important to point out that depth-based CNV calling is just one of the CNV calling methods. Other CNV calling software using SNVs, pair-reads, split-reads, and coverage depth for calling CNV, such as the software Conserting, would be severely affected by the low-quality WGS data. The authors need to evaluate at least two different software with specific algorithms for CNV calling based on current WGS data.

(6) The authors omit an important application of cfDNA: somatic mutation detection. Degraded cfDNA and reduced sequencing depth could substantially impact SNV calling accuracy in terms of both recall and precision. Assessing this aspect with their current dataset would provide a more comprehensive evaluation of heparin plasma-derived cfDNA for genomic analyses.

Comments on revisions:

As suggested previously, the Pearson correlation analysis tends to be overstated; please replace it with Spearman correlation in the whole manuscript. Currently, the authors include both of them in the abstract, method, results, and graphics, all of which are required to be updated to only use Spearman correlation results.

I don't have other concerns about the manuscript.

AI Scientist 研究——一个让 AI 自动化完整科研周期的系统——被 Nature 正式发表了。令人震惊的是：一篇关于「AI 能否替代科学家」的论文，本身就是通过「AI 辅助科研」的过程产生的，并通过了人类同行评审。这个自指性质让 Nature 的认可变成了一个双重背书：既是对内容的认可，也是对方法论的认可。Sakana 将这个成果作为 Marlin 的技术背书，是极为聪明的品牌叙事策略。

「预测反馈」的概念令人惊讶：AI 在报告发出前，预测各位审阅者会说什么、Twitter 会怎么反应、调查结果会是什么——研究者先在「预测反馈」中迭代，只有当预期信息增量足够高时，才真正发出去等待真实反馈。这是一种「反馈的预计算」——把等待时间转化为优化时间，本质上是把「串行等待」变成了「并行模拟」。

Reviewer #1 (Public review):

Summary:

This manuscript investigates the biological mechanism underlying the assembly and transport of the AcrAB-TolC efflux pump complex. By combining endogenous protein purification with cryo-EM analysis, the authors show that the AcrB trimer adopts three distinct conformations simultaneously and identify a previously uncharacterized lipoprotein, YbjP, as a potential additional component of the complex. The work aims to advance our understanding of the AcrAB-TolC efflux system in near-native conditions and may have broader implications for elucidating its physiological mechanism.

Strengths:

Overall, the manuscript is clearly presented, and several of the datasets are of high quality. The use of natively isolated complex is a major strength, as it minimizes artifacts associated with reconstituted systems and enables the discovery of a novel subunit. The authors also distinguish two major assemblies-the TolC-YbjP sub-complex and the complete pump-which appear to correspond to the closed and open channel states, respectively. The conceptual advance is potentially meaningful, and the findings could be of broad interest to the field.

Weaknesses:

(1) As the identification of YbjP is a key contribution of this work, a deeper comparison with functional "anchor" proteins in other efflux pumps is needed. Including an additional supplementary figure illustrating these structural comparisons would be valuable.

(2) The observation of the LTO states in the presence of TolC represents an important extension of previous findings. A more detailed discussion comparing these LTO states to those reported in earlier structural and biochemical studies would improve the clarity and significance of this point.

Comments on revisions:

In the revision, the authors have addressed the above concerns to improve this study.

Reviewer #2 (Public review):

Summary:

This manuscript reports the high-resolution cryo-EM structures of the endogenous TolC-YbjP-AcrABZ complex and a TolC-YbjP subcomplex from E. coli, identifying a novel accessory subunit. This work is an impressive effort that provides valuable structural insights into this native complex.

Strengths:

(1) The study successfully determines the structure of the complete, endogenously purified complex, marking a significant achievement.<br /> (2) The identification of a previously unknown accessory subunit is an important finding.<br /> (3) The use of cryo-EM to resolve the complex, including potential post-translational modifications such as N-palmitoyl and S-diacylglycerol, is a notable highlight.

Weaknesses:

(1) Clarity and Interpretation: Several points need clarification. Additionally, the description of the sample preparation method, which is a key strength, is currently misplaced and should be introduced earlier.<br /> (2) Data Presentation: The manuscript would benefit significantly from improved figures.<br /> (3) Supporting Evidence: The inclusion of the protein purification profile as a supplementary figure is essential. Furthermore, a discussion comparing the endogenous AcrB structure to those obtained in other systems (e.g., liposomes) and commenting on observed lipid densities would strengthen the overall analysis.

Comments on revisions:

In the revision, all my concerns have been addressed.

Reviewer #1 (Public review):

Summary:

Witte et al. examined whether canonical behavioral functions attributed to the cerebellum decline with age. To test this, they recruited younger, old, and older-old adults in a comprehensive battery of tasks previously identified as cerebellar-dependent in the literature. Remarkably, they found that cerebellar function is largely preserved across the lifespan-and in some cases even enhanced. Structural imaging confirmed that their older adult cohort was representative in terms of both cerebellar gray- and white-matter volume. Overall, this is an important study with strong theoretical implications and compelling evidence supporting the motor reserve hypothesis, demonstrating that cerebellar-dependent measures remain largely intact with aging.

Strengths:

(1) Relatively large sample size.

(2) Most comprehensive behavioral battery to date assessing cerebellar-dependent behavior.

(3) Structural MRI confirmation of age-related decline in cerebellar gray and white matter, ensuring representativeness of the sample.

Weaknesses:

The absence of a voxel-based morphometry (VBM) analysis limits the anatomical and functional specificity of the conclusions. Such an analysis would help identify which functions are truly cerebellar-dependent, rather than relying primarily on inferences drawn from prior neuropsychological literature. Notably, the authors have undertaken this analysis in a separate manuscript.

As acknowledged in the Discussion, the classification of tasks as "cerebellar-dependent" versus "general" remains somewhat ambiguous. Some measures labeled as "general" may still engage cerebellar processes. Moreover, analyses in the authors' forthcoming manuscript show weak structure-behavior correlations, casting further doubt on how clearly cerebellar-specific functions can be distinguished from more general processes.

Reviewer #2 (Public review):

Summary:

The authors are investigating cerebellar-mediated motor behaviors in a large sample of adults, including 30 individuals over the age of 80 (a great strength of this work). They employed a large battery of motor tasks that are tied to cerebellar function, in addition to a cognitive task and motor tasks that are more general. They also evaluated cerebellar structure. Across their behavioral metrics, they found that even with cerebellar degeneration, cerebellar-mediated motor behavior remained intact relative to young adults. However, this was not the case for measures not directly tied to cerebellar function. The authors suggest that these functions are preserved and speak to the resiliency and redundancy of function in the cerebellum. They also speculate that cerebellar circuits may be especially good for preserving function in the face of structural change. The tasks are described very well, and their implementation is also well-done with consideration for rigor in the data collection and processing. The inclusion of Bayesian estimates is also particularly useful, given the theoretically important lack of age differences reported. This work is methodologically rigorous with respect to the behavior, and certainly thought-provoking.

Strengths:

The methodological rigor, inclusion of Bayesian statistics, and the larger sample of individuals over the age of 80 in particular are all great strengths of this work. Further, as noted in the text, the fact that all participants completed the full testing battery is of great benefit. Please note, upon my second review the strengths remain. This is a really wonderful investigation and amazingly comprehensive from a behavioral perspective given the numerous tasks and domains that were considered.

Weaknesses:

The suggestion of cerebellar reserve, given that at the group level there is a lack of difference for cerebellar specific behavioral component,s could be more robustly tested. That is, the authors suggest that this is a reserve given that volume of cerebellar gray matter is smaller in the two older groups, though behavior is preserved. This implies volume and behavior are seemingly dissociated. However, there is seemingly a great deal of behavioral variability within each group and likewise with respect to cerebellar volume. Is poorer behavior associated with smaller volume? If so, this would suggest still that volume and behavior are linked; but, rather than being age that is critical it is volume. On the flip side, a lack of associations between behavior and volume would be quite compelling with respect to reserve. More generally, as explicated in the recommendations, there are analyses that could be conducted that, in my opinio,n would more robustly support their arguments given the data that they have available.

The authors have done wonderful work to address the comments from the initial feedback/reviews. While I may ultimately disagree with the approach of including the imaging data in another manuscript, that is at the same time, a reasonable decision. This, however, does not change the impression that the paper would be stronger with the inclusion of the volumetric imaging data. I can understand why it may be published separately - it would be a very long paper to include both. At the same time the assertions made here, which are largely nicely supported by the preprint, would ultimately strengthen this work. The behavior certainly stands on its own as an excellent and needed investigation; together, both pieces make for a truly excellent contribution to the literature.

Reviewer #1 (Public review):

This is an important article, which represents the culmination of 25 years of research on the spore coat protein, SafA. Reading this paper is not necessarily easy because it requires time, patience, and attention to detail, but it is truly rewarding. The attentive reader will certainly appreciate the description of a biochemical tour de force, providing convincing experimental evidence for every aspect of a step-by-step inner coat assembly model. It was previously known that SafA was a coat morphogenetic protein responsible for the assembly of the inner layer of the spore coat in Bacillus subtilis, and SafA was already viewed as a hub that directly or indirectly recruited several dozens of coat proteins to the spore envelope. It was also known that there were isoforms of SafA (the most important being the C30 form), and SafA was a substrate of Tgl, a transglutaminase involved in crosslinking some of the coat proteins, especially those found in the inner coat. Several studies have combined genetics and various types of microscopy approaches, including fluorescence microscopy, to decipher the mechanism of coat assembly, but the current study brings top-notch biochemistry into the picture and, therefore, is able to go much further into the molecular characterization of this important mechanism. It should be noted that spore coat assembly is a notoriously difficult process to study biochemically. It was also suspected to be a complex mechanism, because coat assembly is a protracted process involving at least 80 different proteins, whose production is controlled both temporally and spatially, but the current paper manages to connect specific chemical reactions to well-known stages of spore formation. The authors did so by generating several constructs with specific substitutions of Cys and Lys residues, interfering with the completion of disulfide bond formation and crosslinking events, thus determining the order of events and the structural consequences when one of these steps is impaired. Importantly, their conclusions are consistent with previous work. In the updated model, self-assembly of SafA is the first step, promoted by disulfide bond formation between C30 complexes. This is followed by recruitment of inner coat proteins and, finally, transglutamination to stabilize the scaffold structure (referred to as a "spotwelding activity".

The work is extremely thorough. I did not identify any weaknesses and could not think of any experiment that would have been omitted.

Reviewer #2 (Public review):

Summary:

The authors assemble a variety of information from biochemical experiments on oligomeric and higher-order assembly of the spore coat protein SafA, which functions as a hub in spore coat development. Together, the data indicate a robust process of assembly, guided initially by an organized process of disulfide bond formation and ultimately leading to cross-linking by the enzyme Tgl. Interestingly, neither process is strictly necessary for the formation of highly assembled oligomeric forms of SafA, but instead, these processes are mutually supportive in creating a strong, intercrosslinked assembly. Given this lead-up, it is somewhat disappointing to find that the cross-linking defective SafA mutants do not exhibit any obvious defects in sporulation in vivo, and one is left with the conclusion that this stage of spore coat assembly is accomplished by multiple independent co-occurring activities. The information is sufficient to support a detailed model for SafA assembly, which is significant in that it helps to explain the process of building a critically important hub-scaffold for spore coat development.

Strengths:

The main body of experiments supports a detailed model for the assembly of SafA monomers into spore coat superstructures. This is interesting because it shows how a protein can be used as both a scaffold and a hub in contributing to the assembly of a super-resilient biological material.

Weaknesses:

(1) The weak sporulation phenotype of the crosslinking mutants diminishes the significance of the mechanism that is described.

(2) The narrative flow of the originally submitted manuscript could be improved by removing some unnecessary and confusing figures on peripheral subjects and rearranging some of the latter figures to arrive at a conclusion that focuses more on SafA assembly.

(3) The original manuscript appears to have a labeling error in the supplementary figures, but a correctly labeled version of the figures would not support one of the manuscript's claims.

Reviewer #3 (Public review):

The manuscript by Amara et al. provides novel mechanistic insight into how SafA, a spore coat morphogenetic protein, self-assembles and is later crosslinked by the Tgl transglutaminase during spore coat assembly. Through rigorous, carefully executed biochemical analyses of SafA's oligomerization and crosslinking states, the authors demonstrate that SafA forms dimers that promote disulfide bond formation between two cysteine pairs found in its C30 region; this disulfide bond-mediated crosslinking promotes, but is not essential for, Tgl-mediated crosslinking of lysine residues within SafA. Specifically, one pair in its N-terminal C30 region promotes the formation of higher-order oligomers, while the second pair in its C-terminus C30 region promotes its ability to form a tetramer. Mutation of both cysteine pairs prevents higher-order SafA structures and reduces the efficiency of Tgl-mediated crosslinking via lysines in close proximity to the cysteines. They further show that disulfide bond formation promotes, but is not essential for, SafA to self-assemble into structures ~1200 kDa via SAXS analyses and kinetic analyses of Tgl-mediated crosslinking of purified SafA in vitro.

Major Comments:

(1) While the authors' detailed and thorough biochemical analyses advance our understanding of how SafA forms higher-order structures in the presence and absence of Tgl, they could broaden the significance of their findings with additional functional analyses of their mutants in B. subtilis. Figure 8 shows that loss of Tgl and SafA disulfide bond formation renders SafA more extractable (presumably leading to a less resilient spore coat), and FRAP analyses indicate that SafA in ∆tgl sporulating cells is more mobile than in its lysine crosslinked form. Some ideas that the authors could test to try and identify additional functions for the Cys and Lys residues in SafA:<br /> - Analyze the Cys mutants in the FRAP assay?<br /> - Does loss of SafA-mediated crosslinking via the Cys and/or Lys mutations affect its localization to the forespore or the recruitment of its client proteins like GerQ?<br /> - Have the authors tested higher concentrations of lysozyme? Or chloroform?

(2) While the authors show in supplementary data that the safA point mutants they generated do not affect spore germination in the single condition tested, the Rudner group previously showed that SafA plays a role in spore germination by affecting CwlJ localization to the forespore. Perhaps the authors might see a more significant phenotype on spore germination with their Cys and Lys mutants if they tried to complement a ∆safA∆sleB double mutant with mutant safA constructs? For the germination assays, it was unclear to me whether the authors used heat activation prior to inducing spore germination.

(3) Have the authors looked at whether the Cys or Lys mutations affect the sensitivity of spores to oxidative insults, especially since the Cys residues might temper the effects of oxidizing agents?

(4) Did the authors test the effect of single Cys mutations on disulfide bond formation, since intermolecular disulfide bond formation might still be possible even if one of the Cys residues has been changed?

(5) Finally, I was unsure how many times each experiment was replicated and how many experiments had been conducted in total.

Reviewer #1 (Public review):

Summary:

In this manuscript, Frangos at al. used a transcriptomic and proteomic approach to characterise changes in HER2-driven mammary tumours compared to healthy mammary tissue in mice. They observed that mitochondrial genes, including OXPHOS regulators, were among the most down-regulated genes and proteins in their datasets. Surprisingly, these were associated with higher mitochondrial respiration, in response to a variety of carbon sources. In addition, there seems to be a reduction in mitochondrial fusion and an increase in fission in tumour tissues compared to healthy tissues.

Strengths:

The data are clearly presented and described.

The author reported very similar trends in proteomic and transcriptomic data. Such approaches are essential to have a better understanding of the changes in cancer cell metabolism associated with tumorigenesis.

The authors provided a direct link between HER2 inhibition and OXPHOS, strengthening the mechanistic aspect of the work.

Weaknesses:

The manuscript would have benefited from more ex-vivo approaches to further dissect mechanistic links and resolve the contradiction of elevated respiration with reduced expression of most associated proteins (but these points are clearly articulated in the discussion).

The results presented support the authors' conclusions, and limitations are addressed in the discussion. This work will likely impact the progression of the field, and the provided data will benefit the scientific community.

Comments on revisions:

The authors addressed all my concerns.

Reviewer #2 (Public review):

Frangos et al present a set of studies aiming to determine mechanisms underlying initiation and tumour progression. Overall, this work provides some useful datasets, further establishing mitochondrial dysfunction during the cellular transformation process.

A key strength is the coordinated analysis of transcriptomics and proteomics from tumour samples derived from a Neu-dependent mouse model for breast cancer. This analysis provides rigorous datasets that show robust patterns, including down-regulation across many components of mitochondrial OXPHOS that were generally consistent at both the mRNA and protein level. Parallel analysis of corresponding tumour samples thereby clearly shows the opposite trend of increased mitochondrial function, which is unexpected. As such, this work further establishes altered mitochondrial phenotypes in tumour contexts and further illustrates that mitochondrial function is not necessarily always tightly correlated with mitochondrial gene expression patterns.

Several key weaknesses remain. It remains unclear how increased mitochondrial function is being sustained despite wide decreases in mRNA and protein levels of OXPHOS components. In terms of mechanism, the study confirmed that pharmacologic EGFR inhibition decreases OXPHOS in a EGFR-dependent breast cancer line. However, it remains unclear if the cell culture system recapitulates other key observations of the tumour model (namely decreased expression with increased function).

Therefore, the mechanistic basis of increased mitochondrial function in light of decreased mitochondrial content remains speculative, as does the role of these changes for tumour initiation or progression.

Comments on revisions:

We agree with the overall findings of the study and appreciate that the claims in text and title have been appropriately toned down.

As additional suggestions eg for presentation, many of the graphics/labels are still too small to be useful. It would be interesting to see if this cell line is similar to the tumours in terms of all the phenotypes. The lapatinib experiment was good. I wonder how quick this drug affects the mitochondria. Also it would be interesting to see if these cells have higher OXPHOS than other non-transformed breast epithelial cells.

The WB on oxphos components is good with ab110413 but this looks like many subunits are detected so this should be made clear.

Reviewer #1 (Public review):

Summary:

The study investigates the role of vascular mural cells, specifically pericytes and vascular smooth muscle cells (vSMCs), in maintaining blood-brain barrier (BBB) integrity and regulating vascular patterning. Analyzing zebrafish pdgfrb mutants that lack brain pericytes and vSMCs, the show that mural cell deficiency does not impair BBB establishment or maintenance during larval and early juvenile stages. However mural cells seem to be crucial for preventing vascular aneurysms and hemorrhage in adulthood as focal leakage, basement membrane disruption and increased caveolae formation are observed in adult zebrafish at aneurysm hotspots. The authors challenge the paradigm that mural cells are essential for BBB regulation in early development while highlighting their importance for long-term vascular stability.

Strengths:

Previous studies have established that the zebrafish BBB shares molecular and morphological homology with e.g. the mammalian BBB and therefore represents a suitable model. By examining mural cell roles across different life stages-from larval to adult zebrafish-the study provides an unprecedented comprehensive developmental analysis of brain vascular development and of how mural cells influence BBB integrity and vascular stability over time. The use of live imaging, whole-brain clearing, and electron microscopy offers high-resolution insights into cerebrovascular patterning, aneurysm development, and structural changes in endothelial cells and basement membranes. By analyzing "leakage hotspots" and their association with structural endothelial defects in adults the presented findings add novel insights into how mural cell loss may lead to vascular instability.

Reviewer #2 (Public review):

Summary:

The authors generated a zebrafish mutant of the pdgfrb gene. The presented analyses and data confirm previous studies demonstrating that Pdgfrb signaling is necessary for mural cell development in zebrafish. In addition, the data support previously published studies in zebrafish showing that mural cell deficiency leads to hemorrhages later in life. The authors presented quantified data on vessel density and branching, assessed tracer extravasation, and investigated the vasculature of adult mice using electron microscopy.

Strengths:

The strength of this article is that it provides independent confirmation of the important role of Pdgfrb signaling for the development of mural cells in the zebrafish brain. In addition, it confirms previous literature on zebrafish that provides evidence that, in the absence of pericytes/VSMC, hemorrhages appear (Wang et al, 2014, PMID: 24306108 and Ando et al 2021, PMID: 3431092)".

The Reviewing Editor has carefully reviewed the revised manuscript and is fully satisfied with the authors' revisions.

Reviewer #3 (Public review):

This manuscript provides novel insights into altered glucose metabolism and KC status during early MASLD. The authors propose that hyperactivated glycolysis drives a spatially patterned KC depletion that is more pronounced than the loss of hepatocytes or hepatic stellate cells. This concept significantly enhances our understanding of early MASLD progression and KC metabolic phenotype.

Through a combination of TUNEL staining and MS-based metabolomic analyses of KCs from HFHC-fed mice, the authors show increased KC apoptosis alongside dysregulation of glycolysis and the pentose phosphate pathway. Using in vitro culture systems and KC-specific ablation of Chil1, a regulator of glycolytic flux, they further show that elevated glycolysis can promote KC apoptosis.

However, it remains unclear whether the observed metabolic dysregulation directly causes KC death or whether secondary factors, such as low-grade inflammation or macrophage activation, also contribute significantly. Nonetheless, the results, particularly those derived from the Chil1-ablated model, point to a new potential target for the early prevention of KC death during MASLD progression.

The manuscript is clearly written and thoughtfully addresses key limitations in the field, especially the focus on glycolytic intermediates rather than fatty acid oxidation. The authors acknowledge the missing mechanistic link between increased glycolysis and KC death. A few things require clarification.

Strengths:

• The study presents the novel observation of profound metabolic dysregulation in KCs during early MASLD and identifies these cells as undergoing apoptosis. The finding that Chil1 ablation aggravates this phenotype opens new avenues for exploring therapeutic strategies to mitigate or reverse MASLD progression.

• The authors provide a comprehensive metabolic profile of KCs following HFHC diet exposure, including quantification of individual metabolites. They further delineate alterations in glycolysis and the pentose phosphate pathway in Chil1-deficient cells, substantiating enhanced glycolytic flux through 13C-glucose tracing experiments.

• The data underscore the critical importance of maintaining balanced glucose metabolism in both in vitro and in vivo contexts to prevent KC apoptosis, emphasizing the high metabolic specialization of these cells.

• The observed increase in KC death in Chil1-deficient KCs demonstrates their dependence on tightly regulated glycolysis, particularly under pathological conditions such as early MASLD.

Weaknesses:

• The TUNEL staining in the overview in Figure 2 is not convincing. Typically the signal overlaps with DAPI, which is mostly not the case in the figures shown.

• The mechanistic link between elevated glycolytic flux and KC death remains unclear.

• Figure S5: shows deltadelta CT values, not relative values. What are the housekeeping genes? There should be at least 2, and they should not have metabolically related functions such as Gapdh.

• Figure 1C: shows WT and KO gating side by side

• The following point has not been answered: "While BMDMs from Chil1 knockout mice are used to demonstrate enhanced glycolytic flux, it remains unclear whether Chil1 deficiency affects macrophage differentiation itself." Expression of certain genes that indicate function does not show whether BMDMs isolated from these KO mice are fully differentiated. Here, counting BM input/ BMDM output, flow cytometry on BMDMs, morphology etc. should be tested.

Reviewer #4 (Public review):

Summary:

In this study, He et al. investigate the mechanisms underlying Kupffer cell (KC) loss during metabolic stress. It has long been observed that embryonically derived KCs decline in obesity and liver disease, a loss that is compensated by monocyte recruitment, although the underlying mechanisms remain unclear. The authors propose that metabolic reprogramming, particularly excessive glycolysis, drives KC death. Using an original murine genetic model to modulate glycolysis, they further demonstrate that enhanced glycolytic activity exacerbates KC damage.

Strengths:

Overall, the study is extremely clearly presented, with a convincing and simple message destined to a vast audience.

Weaknesses:

This manuscript has already undergone one round of revisions in which I was not involved. The authors have tried to address several points raised by the previous reviewers, notably regarding the unexpectedly high level of TUNEL staining observed in KCs. However, I share these concerns expressed by the three reviewers that the reported levels remain difficult to reconcile with the biology. A TUNEL positivity rate of ~60% at week 16 of the HFHC diet would imply massive KC death, which should have led to a near-complete depletion of the KC population, something that is not observed. While I agree that the KC compartment is clearly affected under this dietary challenge, I would strongly encourage the authors to carefully rule out potential technical biases that could account for this implausibly high rate of cell death.

Considering the new in-vivo experiment with 2-DG, it is definitely convincing and clearly adds some value to the full study.

So the full story deserves publication.

Reviewer #1 (Public review):

In this manuscript, the authors aimed to identify the molecular target and mechanism by which α-Mangostin, a xanthone from Garcinia mangostana, produces vasorelaxation that could explain the antihypertensive effects. Building on on prior reports of vascular relaxation and ion channel modulation, the authors convincingly show that large-conductance potassium BK channels are the primary site of action. Using electrophysiological, pharmacological, and computational evidence, the authors achieved their aims and showed that BK channels are the critical molecular determinant of mangostin's vasodiltory effects, even though the vascular studies are quite preliminary in nature.

Strengths:

(1) The broad pharmacological profiling of mangostin across potassium channel families, revealing BK channels - and the vascular BK-alpha/beta1 complex - as the potently activated target in a concentration-dependent manner.

(2) Detailed gating analyses showing large negative shifts in voltage-dependence of activation and altered activation and deactivation kinetics.

(3) High-quality single-channel recordings for open probability and dwell times.

(4) Convincing activation in reconstituted BKα/β1-Caᵥ nanodomains mimicking physiological condition and functional proof-of-concept validation in mouse aortic rings.

Weaknesses are minor:

(1) Some mutagenesis data (e.g., partial loss at L312A) could benefit from complementary structural validation.

The author's rebuttal provides alphafold3 models for mutants. While there are interesting preliminary observations, the authors decided not to include these in the main manuscript, awaiting further structual validation. I concur.

(2) While Cav-BK nanodomains were reconstituted, direct measurement of calcium signals after mangostin application onto native smooth muscle could be valuable.

In their response, the authors acknowledge the importance of measuring Ca2+ sparks in smooth muscle cells to further validate their findings. However, this is not provided in the manuscript. Part of my earlier comment alludes to the possibility of α-Mangostin directly affecting Cav1.2 or ryanodine receptor activity, and therefore BK activity would go up. With the current provided evidence, these possibilities cannot be excluded and need to be acknowledged.

(3) The work has impact for ion channel physiology and pharmacology, providing a mechanistic link between a natural product and vasodilation. Datasets include electrophysiology traces, mutagenesis scans, docking analyses, and aortic tension recordings. The latter however are preliminary in nature.

The authors acknowledge that additional vascular physiology experiments would strengthen the argument they make. They are however unable to provide such evidence in the present manuscript. Therefore, I strongly suggest that the authors tune down the physiological implications of α-Mangostin that they include in the manuscript. I'd also suggest that "vasorelaxation" is removed from the manuscript title, given the preliminary nature of the findings.

Reviewer #2 (Public review):

Summary:

In the present manuscript, Cordeiro et al. show that α-mangostin, a xanthone obtained from the fruit of the Garcinia mangostana tree, behaves as an agonist of the BK channels. The authors arrive at this conclusion by examining the effects of mangostin on macroscopic and single-channel currents elicited by BK channels formed by the α subunit and α + β1 subunits, as well as αβ1 channels coexpressed with voltage-dependent Ca2+ (CaV1,2) channels. The single-channel experiments show that α-mangostin produces a robust increase in the probability of opening without affecting the single-channel conductance. The authors contend that α-mangostin activation of the BK channel is state-independent, and molecular docking and mutagenesis suggest that α-mangostin binds to a site in the internal cavity. Importantly, α-mangostin (10 μM) alleviates noradrenaline-induced contracture. Mangostin is ineffective if the contracted muscles are pretreated with the BK toxin iberiotoxin.

In this revised version of the manuscript by Cordeiro et al., the authors have adequately answered my previous concerns. However, as I stated in my comments, without determining the probability of opening across a wide range of voltages, any conclusion about the drug's mechanism of action can be questioned. For example, the statement in Discussion line 481: "The higher shift observed in 1 μM Cai 2+ may reflect the steep Cai2+-dependence of the closed-open equilibrium (Cui, Cox and Aldrich, 1997) and the allosteric coupling of voltage and Cai2+ signals (Horrigan and Aldrich, 2002; Magleby, 2003; Clay, 2017), which are effective in this concentration range, which may lead to a higher apparent activation when voltage activation is facilitated by Cai 2+ (Sun and Horrigan, 2022)." has no support in the data and is not predicted by the allosteric model. In order to have a larger shift induced by the drug in the presence of Ca2+, you need either to alter the Ca2+ binding or the allosteric coupling factor C.<br /> Please note that in the manuscript, there are several problems with the English in this sentence.

Minor

In Figure 1E, BKa should read BKalpha.

Reviewer #3 (Public review):

Summary:

This research shows that a-mangostin, a proposed nutraceutical, with cardiovascular protecting properties, could act through the activation of large conductance potassium permeable channels (BK). The authors provide convincing electrophysiological evidence that the compound binds to BK channels and induces a potent activation, increasing the magnitude of potassium currents. Since these channels are important modulators of the membrane potential of smooth muscle in vascular tissue, this activation leads to muscle relaxation, possibly explaining cardiovascular protecting effects.

Strengths:

The authors have satisfactorily answered my previous comments and present evidence based on several lines of experiments that a-mangostin is a potent activator of BK channels. The quality of the experiments and the analysis is high and represents an appropriate level of analysis. This research is timely and provides a basis to understand the physiological effects of natural compounds with proposed cardio protective effects.

Weaknesses:

The identification of the binding site continues to be the least developed point of the manuscript. The authors show that the binding site is probably located in the hydrophobic cavity of the pore and show that point mutations reduce the magnitude of the negative voltage shift of activation produces by a-mangostin. This binding site should be demonstrated in the future using structural techniques such as cryo-EM.

Reviewer #1 (Public review):

Summary:

The authors introduce ImPaqT, a modular toolkit for zebrafish transgenesis, utilizing the Golden Gate cloning approach with the rare-cutting enzyme PaqCI. The toolkit is designed to streamline the construction of transgenes with broad applications, particularly for immunological studies. By providing a versatile platform, the study aims to address limitations in generating plasmids for zebrafish transgenesis.

Strengths:

The ImPaqT toolkit offers a modular method for constructing transgenes tailored to specific research needs. By employing Golden Gate cloning, the system simplifies the assembly process, allowing seamless integration of multiple genetic elements while maintaining scalability for complex designs. The toolkit's utility is evident from its inclusion of a diverse range of promoters, genetic tools, and fluorescent markers, which cater to both immunological and general zebrafish research needs. Even small DNA fragements, such as the viral 2a sequence, can be cloned into a multi-component plasmid in one step. The components can be assembled from PCR fragments or synthesized DNA fragments, forgoing the need for "entry" vectors. Further, the authors show that the exisiting PaqCI sites can be domesticated to improve the versatility of the system. The validation provided in the manuscript is Convincing, demonstrating the successful generation of several functional transgenic lines. These examples highlight the toolkit's efficacy, particularly for immune-focused applications.

Comments on revisions:

The authors have addressed all the concerns raised in the first review. Congratulations to the authors for their effort.

Reviewer #2 (Public review):

Summary:

Hurst et al. developed a new Tol2-based transgenesis system, ImPaqT, an Immunological toolkit for PaqCl-based Golden Gate Assembly of Tol2 Transgenes, to facilitate the production of transgenic zebrafish lines. This Golden Gate assembly-based approach relies on only a short 4-base-pair overhang sequence in the final construct, and the insertion construct and backbone vector can be assembled in a single-tube reaction using PaqCl and a ligase. This approach can also be expandable by introducing new overhang sequences while maintaining compatibility with existing ImPaqT constructs, allowing users to add fragments as needed.

The generation of several transgenic zebrafish lines for immunological studies demonstrates the feasibility of the ImPaqT in vivo. Lineage tracing of macrophages via LPS injection demonstrates the approach's functionality and validates its use in vivo.

Comments on revisions:

The authors have addressed all my concerns.

Reviewer #1 (Public review):

Summary:

For each of three key transcription factor (TF) proteins in E. coli, the authors generate a large library of TF binding site (TFBS) sequences on plasmids, such that each TFBS is coupled to the expression of a fluorescence reporter. By sorting the fluorescence of individual cells and sequencing their plasmids to identify each cell's TFBS sequence (sort-seq), they are able to map the landscape of these TFBSs to the gene expression level they regulate. The authors then study the topographical features of these landscapes, especially the number and distribution of local maxima, as well as the statistical properties of evolutionary paths on these landscapes. They find the landscapes to be highly rugged, with about as many local peaks as a random landscape would have, and with those peaks distributed approximately randomly in sequence space. This is quite different from previous work on landscapes for eukaryotic TFBSs, which tend to be rather smooth. The authors find that there are a number of peaks that produce regulation stronger than that of the wild-type sequence for each TF, and that it is not too unlikely to reach one of those "high peaks" from a random starting sequence. Nevertheless, the basins of attraction for different peaks have significant overlap, which means that chance plays a major role in determining which peak a population will evolve to.

Strengths:

(1) The apparent differences in landscape topography between prokaryotic TFBSs and other molecular landscapes is a fascinating discovery to add to the field of genotype-phenotype maps. I am really excited to learn the molecular mechanisms of this in the future.

(2) The experiments and analysis of this paper are very well-executed and, by and large, very thorough. I appreciated the systematic nature of the project, both the large-scale experiments done on three TFs with replicates, and the systematic analysis of the resulting landscapes. This not only makes the paper easy to follow, but also inspires confidence in their results since there is so much data and so many different ways of analyzing it. It's a great recipe for other studies of genotype-phenotype landscapes to follow.

(3) Considering how technical the project was, I am really impressed at how easy to read I found the paper, and the authors deserve a lot of credit for making it so. They do a great job of building up the experiments and analyses step-by-step, and explaining enough of the basics of the experimental design and essence of each analysis in the main text without getting too complicated with details that can be left to the Methods or SI.

Weaknesses:

(1) Regarding the effect of measurement uncertainties, one way in which they attempt to test their effect is to simulate dynamics on noisy and noise-free versions of the landscape and measure visitation frequencies. While they show that visitation frequencies are highly correlated between these cases, I'd prefer a more direct test of epistasis or navigability (e..g, number of local peaks), since that's how they are characterizing the landscapes, and the connection between that and visitation frequency of individual states is unclear.

(2) I am still a little concerned about the fraction of sequences missing from the data due to filtering, although I appreciate the difficulties in testing the importance of this (requiring additional assumptions) and the authors' good-faith efforts to do their best with the data they have.

Reviewer #2 (Public review):

The authors aim to investigate the ability of evolution to create strong transcription factor binding sites (TFBSs) de novo in E. coli. They focus on three global transcriptional regulators: CRP, Fis, and IHF, using a massively parallel reporter assay to evaluate the regulatory effects of over 30,000 TFBS variants. By analyzing the resulting genotype-phenotype landscapes, they explore the ruggedness, accessibility, and evolutionary dynamics of regulatory landscapes, providing insights into the evolutionary feasibility of strong gene regulation. Their experiments show that de novo adaptive evolution of new gene regulation is feasible. It is also subject to a blend of chance, historical contingency, and evolutionary biases that favor some peaks and evolutionary paths.

(1) Strengths of the methods and results:

The authors successfully employed a well-designed sort-seq assay combined with high-throughput sequencing to map regulatory landscapes. The experimental design ensures reliable measurement of regulation strengths. Their system accounts for gene expression noise and normalizes measurements using appropriate controls.

Comprehensive Landscape Mapping:<br /> The study examines ~30,000 TFBS variants per transcription factor, providing statistically robust and thorough maps of the regulatory landscapes for CRP, Fis, and IHF. The landscapes are rigorously analyzed for ruggedness (e.g., number of peaks) and epistasis, revealing parallels with theoretical uncorrelated random landscapes.

Evolutionary Dynamics Simulations:<br /> Through simulations of adaptive walks under varying population dynamics, the authors demonstrate that high peaks in regulatory landscapes are accessible despite ruggedness. They identify key evolutionary phenomena, such as contingency (multiple paths to peaks) and biases toward specific evolutionary outcomes.

Biological Relevance and Novelty:<br /> The author's work is novel in focusing on global regulators, which differ from previously studied local regulators (e.g., TetR). They provide compelling evidence that rugged landscapes are navigable, facilitating de novo evolution of regulatory interactions. The comparison of landscapes for CRP, Fis, and IHF underscores shared topographical features, suggesting general principles of global transcriptional regulation in bacteria.

(2) Weaknesses of the methods and results:

Undersampling of Genotype Space:<br /> Approximately 40% of the theoretical TFBS genotype space remains uncharacterized after quality filtering. The authors now discuss this limitation more explicitly and provide analyses suggesting that undersampling does not strongly bias their conclusions at the landscape level. Nevertheless, predictive modeling approaches could further extend these landscapes in future work.

Simplified Regulatory Architecture:<br /> The study considers a minimal system consisting of a single TFBS upstream of a reporter gene. While this simplification allows clean interpretation and high-throughput measurement, natural promoters often involve combinatorial regulation and chromosomal context effects that may alter landscape topography.

Lack of Experimental Evolution Validation:<br /> The evolutionary conclusions are based on simulations rather than direct experimental evolution. The authors provide a reasonable justification for this choice and frame their conclusions at the statistical level rather than for specific trajectories, but experimental validation would be a valuable future extension.

Impact on the Field:<br /> This study advances our understanding of adaptive landscapes in gene regulation and offers a critical step toward deciphering how global regulators evolve de novo binding sites. The findings provide foundational insights for synthetic biology, evolutionary genetics, and systems biology by highlighting the evolutionary accessibility of strong regulation in bacteria.

Utility of Methods and Data:<br /> The sort-seq approach, combined with landscape analysis, provides a robust framework that can be extended to other transcription factors and systems. If made publicly available, the study's data and code would be valuable for researchers modeling transcriptional regulation or studying evolutionary dynamics.

Additional Context:<br /> The study builds on a growing body of work exploring regulatory evolution. For instance, recent studies on local regulators like TetR and AraC have revealed high ruggedness and epistasis in TFBS landscapes. This study distinguishes itself by focusing on global regulators, which are more complex biologically and more influential in bacterial gene networks. The observed evolutionary contingency aligns with findings in other biological systems, such as protein evolution and RNA folding landscapes, underscoring the generality of these evolutionary principles.

Conclusion:<br /> The authors successfully mapped the genotype-phenotype landscapes for three global regulators and simulated evolutionary dynamics to assess the feasibility of strong TFBS evolution. They convincingly demonstrate that ruggedness and epistasis, while prominent, do not preclude the evolution of strong regulation. Their results support the notion that gene regulation evolves through a blend of chance, contingency, and evolutionary biases.

This paper makes a significant contribution to the understanding of regulatory evolution in bacteria. While minor limitations exist, the authors' methods are robust, and their findings are well-supported. The work will likely be of broad interest to researchers in molecular evolution, synthetic biology, and gene regulation.

Reviewer #1 (Public review):

The work presented by Cheung et al. used a quantitative proteomics method to capture molecular changes in B cells exposed to LPS and IL-4, a combination of stimuli activating naive B cells. Amino acid transporters, cholesterol biosynthetic enzymes, ribosomal components, and other proteins involved in cell proliferation were found to increase in stimulated B cells. Experiments involving genetic loss-of-function (SLC7A5), pharmacological inhibition (HMGCR, SQLE, prenylation), and functional rescue by metabolites (mevalonate, GGPP) validated the proteomics data and revealed that amino acid uptake, cholesterol/mevalonate biosynthesis, and cholesterol uptake played a crucial role in B cell proliferation, survival, biogenesis, and immunoglobulin class switching. Experiments involving cholesterol-free medium showed that both biosynthesis and LDLR-mediated uptake catered to the cholesterol demand of LPS/IL-4-stimulated B cells. A role for protein prenylation in LDLR-mediated cholesterol uptake was postulated and backed by divergent effects of GGPP rescue in the presence and absence of cholesterol in culture medium.

Strengths:

The discovery was made by proteome-wide profiling and unbiased computational analysis. The discovered proteins were functionally validated using appropriate tools and approaches. The metabolic processes identified and prioritized from this comprehensive survey and systematic validation highly likely represent mechanisms of high importance and influence. Analysis of immune cell metabolism at the protein level is relatively compared to transcriptomic and metabolomic analysis.

The conclusions from functional validation experiments were supported by clear data and based on rational interpretations. This was enabled by well-established readouts/analytical methods used to determine cell proliferation, viability, size, cholesterol content, and transporter/enzyme function. The data generated from these experiments strongly support the conclusions.

This work reveals a complex, yet intriguing, relationship between cholesterol metabolism and protein prenylation as they serve to promote B cell activation. The effects of pharmacological inhibition and metabolite replenishment on the cholesterol content and activation of B cells were determined and logically interpreted.

Weaknesses:

The findings of this study were obtained almost exclusively from ex vivo B cell stimulation experiments. Their contribution to B cell state and B cell-mediated immune responses in vivo was not explored. Without in vivo data, the study still provides valuable mechanistic information and insights, but it remains unknown, and there is no discussion about, how the identified mechanisms may play out in B cell immunity.

The role of HMGCR, SQLE, and prenylation in B cell activation was assessed using pharmacological inhibitors. Evidence from other loss-of-function approaches, which could strengthen the conclusions, does not exist. This is a moderate weakness and somewhat offset by other data, including those obtained from the tests involving multiple distinct pharmacological inhibitors and the metabolite replenishment experiments.

Reviewer #2 (Public review):

This study uses mass spectrometry to quantify how LPS + IL-4 modify the mouse B cell proteome as naïve cells undergo blastogenesis and enter the cell cycle. This analysis revealed changes in key proteins involved in amino acid transport and cholesterol biosynthesis. Genetic and pharmacological experiments indicated important roles for these metabolic processes in B cell proliferation.

This work provides new information about the regulation of TI B cell responses by changes in cell metabolism and also a comprehensive mass spectrometry dataset which will be an important general resource for future studies. The experiments are thorough and carefully carried out. The majority of conclusions are backed up by data that is shown to be highly significant statistically. The comprehensive mass spectrometry dataset will be an important general resource for future studies.

After revision, the study now includes new data showing that the up regulation of amino acid uptake and cholesterol metabolism is not restricted to LPS + IL-4 (TLR4 + IL4R) stimulation but is also observed after stimulation of TLR7, TLR9, CD40 and the BCR. This increases the impact of this work and shows that this metabolic rewiring is a common feature of B cell activation. The inclusion of inhibitor data showing important roles for MTOR and ERK/p38a MAP kinases in the metabolic changes identified and provides preliminary insights into the mechanisms involved.

Reviewer #1 (Public review):

Summary:

Adult laboratory mice produce ultrasonic vocalizations during free social interactions, as well as lower-frequency, voiced calls (squeaks) during aversive contexts. The question of whether mice possess a more complex repertoire of vocalizations has been of great interest to scientists studying rodent vocal behavior. In the current study, the authors analyze the rates and acoustic features of vocalizations produced by pairs of mice that are allowed to interact across a barrier, which prevents direct physical interaction. In this context, they find that same-sex (but not opposite-sex) pairs of mice produce vocalizations that are lower in frequency than the typical 70 kHz ultrasonic vocalizations produced during free interactions and that are also distinct from squeaks. These lower frequency vocalizations were observed in both male-male and female-female pairs, as well as in same-sex pairs from multiple mouse strains. The authors also report that call rates and acoustic features are not affected in male-male pairs that have been treated with the anxiolytic drug buspirone, suggesting that anxiety is not a major driver of vocalization in this behavioral context.

Strengths:

(1) The observation that same-sex pairs of mice produce lower frequency (<70 kHz) vocalizations in this behavioral context is novel.

(2) The consideration of multiple types of pairs (female-female, male-male, and female-male), as well as the inclusion of multiple strains of mice and barriers with different hole diameters, are all strengths of the study.

(3) The authors include detailed analyses of vocalization acoustic features, as well as detailed tracking of mouse positions relative to the barrier.

Weaknesses:

The categorization applied to vocalizations based on their mean frequencies is poorly supported and ignores the distinction in laryngeal production mechanism between voiced and ultrasonic vocalizations. Specifically, the authors are likely lumping together voiced and ultrasonic vocalizations into their "low frequency" (< 30 kHz) category, while they reserve the term "ultrasonic" exclusively for the subset of ultrasonic vocalizations with the highest mean frequencies (> 50 kHz). This categorization scheme also does not align well with past work on lower frequency rodent vocalizations, which complicates the comparison of the present findings to that past work.

In some analyses, the authors report that different groups of mice produce different relative proportions of vocalization types (as defined by mean frequency) but then compare acoustic features of vocalizations between groups after pooling all vocalizations together. The analyses of acoustic features conducted in this way may be confounded by the different proportions of vocalization types across groups.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors examine vocal communication during same-sex dyadic interactions in mice, comparing periods of physical separation (with limited sensory access) to direct social contact. They report that separation dramatically alters the vocal repertoire, shifting it away from canonical ultrasonic vocalizations (USVs) toward low-frequency vocalizations (LFVs) and broadband "noisy" calls. While LFVs and noisy calls have been described previously, largely in aversive contexts, this study provides a detailed, systematic characterization of these vocalizations during social interactions, thereby extending prior work.

The authors explore several experimental manipulations and analyses, including divider hole size, strain and sex differences, anxiolytic drug treatment, and correlations with spatial proximity, to infer potential functions of these call types. Although the dataset is rich, the results are largely descriptive, and many conclusions remain tentative. Several experimental variables are not fully controlled, and in some cases, the interpretation exceeds what the data can clearly support. Nonetheless, with improved experimental framing, additional analyses of existing data, and a clearer discussion of limitations, this work has the potential to make a valuable contribution by broadening the field's focus beyond USVs to understand a wider vocal repertoire relevant to social context.

Strengths:

Much work on mouse vocal communication focuses almost exclusively on USVs. This manuscript convincingly demonstrates that non-USV vocalizations (LFVs and noisy calls) are prominent and systematically modulated by social context, highlighting an underappreciated dimension of mouse communication. Furthermore, the authors employ several experimental manipulations, including sensory access, strain, sex, and pharmacological treatment, to assess changes in vocalization repertoire. This provides a valuable resource for the field and reveals robust context dependence of vocalization. The discussion is thoughtful and integrative, particularly in its consideration of potential communicative roles of LFVs and noisy calls and their relationship to sensory constraints and signal propagation, although these ideas will require further experimental validation.

Weaknesses:

There are several concerns regarding experimental design and data interpretation that could be addressed to strengthen the manuscript.

(1) The terminology used for vocalization types is confusing and needs better clarification. The authors refer to Grimsley et al. (2016) multiple times, yet they use the same names for their vocalizations while applying different definitions. This makes it very difficult to compare the two papers. Since this study and Grimsley et al. use different mouse strains (FVB vs CBA), a direct comparison of absolute frequencies may also not be appropriate. Please explicitly clarify the definitions of the call types (e.g., frequency range, voiced vs. USV) and explain how they relate to those in the previous study earlier in the manuscript.

(2) In the initial experiment, mice always experience separation first (15 minutes), followed by unification (5 minutes), using novel same-sex dyads. Multiple factors besides physical contact could influence vocalization across this sequence, including habituation to the arena, reduced anxiety over time, or increasing familiarity with the partner despite physical separation. It is unclear whether the authors have tested the reverse order (unification first, followed by separation). If not, this limitation should be explicitly acknowledged. In addition, examining whether vocalizations or behaviors change over the course of the 15-minute separation period, for example, by comparing early vs late phases, could help disentangle effects of habituation from those of physical separation per se.

(3) The conclusion that separation-induced LFVs are unlikely to be anxiety-driven may overinterpret the buspirone experiment (Figure 8). Vehicle injections themselves produced large changes in call rate and call-type distribution, raising concerns about stress or arousal induced by the injection procedure. Comparisons between buspirone-treated animals and untreated animals are therefore problematic, as these groups differ in their experimental histories, including the number of exposures. The manuscript would benefit from independent measures confirming the anxiolytic efficacy of buspirone compared to vehicle injection in this paradigm, such as behavioral readouts of anxiety. In addition, the experimental design requires a clearer description. It is not always clear whether the same dyads were tested twice, or how social familiarity, contextual familiarity, and habituation to injections were handled. Male data comparing first and second exposures should also be included as supplementary figures to allow direct comparison with the excluded female dataset.

(4) The idea that noisy calls function to attract conspecific attention is intriguing. However, in Figure 5, all call types, including LFVs and USVs, are most likely to occur when mice are already in close proximity during separation, which seems inconsistent with a long-distance signaling role. Analyses of the temporal relationship between vocalizations and behavior would strengthen this claim. For example, it would be informative to test whether bouts of noisy calls precede approach behavior or a reduction in inter-animal distance. Examining whether calls occur before, during, or after orientation toward the partner could further clarify whether these vocalizations actively modulate social behavior.

(5) The effects of divider hole size on vocal repertoire are striking but difficult to interpret. Unexpectedly, small holes and no holes yield similar call distributions, whereas large holes produce a markedly different profile dominated by LFVs, which also differs from free interactions. If large holes allow greater tactile or close-range interaction, the reduction in USVs and MFV is counterintuitive. Incorporating behavioral metrics such as distance, orientation, or specific interaction types alongside call classification would greatly aid interpretation and help link vocal output to interaction quality rather than divider type alone.

(6) Throughout the study, vocalizations are pooled across both animals in the dyad. Because the arena is neutral rather than a home cage, either animal could be initiating vocalization. Assigning calls to individuals, where possible, using spatial or acoustic cues, would substantially strengthen functional interpretations. Even limited analyses, e.g., identifying which animal vocalizes first or whether calls precede approach by the partner, could provide important insight into the communicative role of different call types.

Reviewer #1 (Public review):

Summary:

The authors aimed to uncover novel therapeutic vulnerabilities in APC-mutant colorectal cancer (CRC), which constitutes the majority of CRC cases. They hypothesized that modulating oxygen-sensing pathways (via PHD inhibition) could disrupt adaptive stress responses in these tumours.

Strengths:

The study employs a powerful, two-pronged approach to identify Molidustat's targets. By using both Thermal Proteome Profiling (TPP) and an orthogonal chemical proteomic competition assay, the authors provide compelling evidence that GSTP1 is a genuine, direct off-target, effectively addressing the common limitation of indirect effects in proteomic screens.

Weaknesses:

(1) In Figure 1, the current data rely on a single guide RNA (sgRNA). To make the data solid, at least two independent sgRNAs targeting different regions of PHD2 should be used.

(2) Figure 3E: Asn205 site should be mutated to prove that whether Molidustat inhibits GSTP1 activity via Asn205 or not.

(3) Figure 5B and 5C: The metabolic imbalance phenotype observed upon dual knockout of PHD2 and GSTP1 requires rescue experiments to confirm on-target specificity.

Reviewer #2 (Public review):

Summary:

The authors aimed to determine Molidustat targets and the potential utility of these findings. They clearly demonstrate that Molidustat interferes with GSTP1 and some other proteins on top of PHD2. They also demonstrate that PHD2 deletion is not sufficient to recapitulate Molidustat effects in cells and proteomes. Finally, they demonstrate synthetic lethality in organoids for Molidustat and APC deletion.

Strengths:

The data on Molidustat proteomes, GSTP1 binding, inhibition and metabolic health of organoids is really clear. All biochemical, docking and omic data are really strong. The potential impact of these findings could be the use of Molidustat in APC null tumours and awareness of potential off-target effects.

Weaknesses:

A main but minor weakness is that Molidustat also inhibits other PHDs, although these are less expressed. PHD1 has been shown to control the cell cycle and be expressed in the colon, where it is needed for viability. Although this does not explain the lack of effect of other PHD inhibitors, it does warrant some discussion. The use of MTT is not very good to detect viability when it measures metabolism; this also needs to be discussed and perhaps supplemented with colony or cell number measurements.

Reviewer #3 (Public review):

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

Specific comments:

(1) What is the possible molecular mechanism of dual GSTP1/PHD2 loss, inducing cell death?

(2) Can the authors mutate the binding site of Molidustat on GTSP1 to verify the in silico docking results?

(3) Evidence for Molidustat inhibiting PHD2 activity or stabilising HIF-1α should be provided.

Reviewer #1 (Public review):

Summary:

The study examines human biases in a regime-change task, in which participants have to report the probability of a regime change in the face of noisy data. The behavioral results indicate that humans display systematic biases, in particular, overreaction in stable but noisy environments and underreaction in volatile settings with more certain signals. fMRI results suggest that a frontoparietal brain network is selectively involved in representing subjective sensitivity to noise, while the vmPFC selectively represents sensitivity to the rate of change.

Strengths:

- The study relies on a task that measures regime-change detection primarily based on descriptive information about the noisiness and rate of change. This distinguishes the study from prior work using reversal-learning or change-point tasks in which participants are required to learn these parameters from experiences. The authors discuss these differences comprehensively.

- The study uses a simple Bayes-optimal model combined with model fitting, which seems to describe the data well. The model is comprehensively validated.

- The authors apply model-based fMRI analyses that provide a close link to behavioral results, offering an elegant way to examine individual biases.

Weaknesses:

The authors have adequately addressed my prior concerns.

Reviewer #3 (Public review):

This study concerns how observers (human participants) detect changes in the statistics of their environment, termed regime shifts. To make this concrete, a series of 10 balls are drawn from an urn that contains mainly red or mainly blue balls. If there is a regime shift, the urn is changed over (from mainly red to mainly blue) at some point in the 10 trials. Participants report their belief that there has been a regime shift as a % probability. Their judgement should (mathematically) depend on the prior probability of a regime shift (which is set at one of three levels) and the strength of evidence (also one of three levels, operationalized as the proportion of red balls in the mostly-blue urn and vice versa). Participants are directly instructed of the prior probability of regime shift and proportion of red balls, which are presented on-screen as numerical probabilities. The task therefore differs from most previous work on this question in that probabilities are instructed rather than learned by observation, and beliefs are reported as numerical probabilities rather than being inferred from participants' choice behaviour (as in many bandit tasks, such as Behrens 2007 Nature Neurosci).

The key behavioural finding is that participants over-estimate the prior probability of regime change when it is low, and under estimate it when it is high; and participants over-estimate the strength of evidence when it is low and under-estimate it when it is high. In other words participants make much less distinction between the different generative environments than an optimal observer would. This is termed 'system neglect'. A neuroeconomic-style mathematical model is presented and fit to data.

Functional MRI results how that strength of evidence for a regime shift (roughly, the surprise associated with a blue ball from an apparently red urn) is associated with activity in the frontal-parietal orienting network. Meanwhile at time-points where the probability of a regime shift is high, there is activity in another network including vmPFC. Both networks show individual differences effects, such that people who were more sensitive to strength of evidence and prior probability show more activity in the frontal-parietal and vmPFC-linked networks respectively.

Strengths

(1) The study provides a different task for looking at change-detection and how this depends on estimates of environmental volatility and sensory evidence strength, in which participants are directly and precisely informed of the environmental volatility and sensory evidence strength rather than inferring them through observation as in most previous studies

(2) Participants directly provide belief estimates as probabilities rather than experimenters inferring them from choice behaviour as in most previous studies

(3) The results are consistent with well-established findings that surprising sensory events activate the frontal-parietal orienting network whilst updating of beliefs about the word ('regime shift') activates vmPFC.

Weaknesses

(1) The use of numerical probabilities (both to describe the environments to participants, and for participants to report their beliefs) may be problematic because people are notoriously bad at interpreting probabilities presented in this way, and show poor ability to reason with this information (see Kahneman's classic work on probabilistic reasoning, and how it can be improved by using natural frequencies). Therefore the fact that, in the present study, people do not fully use this information, or use it inaccurately, may reflect the mode of information delivery.

In the response to this comment the authors have pointed out their own previous work showing that system neglect can occur even when numerical probabilities are not used. This is reassuring but there remains a large body of classic work showing that observers do struggle with conditional probabilities of the type presented in the task,

(2) Although a very precise model of 'system neglect' is presented, many other models could fit the data.

For example, you would get similar effects due to attraction of parameter estimates towards a global mean - essentially application of a hyper-prior in which the parameters applied by each participant in each block are attracted towards the experiment-wise mean values of these parameters. For example, the prior probability of regime shift ground-truth values [0.01, 0.05, 0.10] are mapped to subjective values of [0.037, 0.052, 0.069]; this would occur if observers apply a hyper-prior that the probability of regime shift is about 0.05 (the average value over all blocks). This 'attraction to the mean' is a well-established phenomenon and cannot be ruled out with the current data (I suppose you could rule it out by comparing to another dataset in which the mean ground-truth value was different).

More generally, any model in which participants don't fully use the numerical information they were given would produce apparent 'system neglect'. Four qualitatively different example reasons are: 1. Some individual participants completely ignored the probability values given. 2. Participants did not ignore the probability values given, but combined them with a hyperprior as above. 3. Participants had a reporting bias where their reported beliefs that a regime-change had occurred tend to be shifted towards 50% (rather than reporting 'confident' values such 5% or 95%). 4. Participants underweighted probability outliers resulting in underweighting of evidence in the 'high signal diagnosticity' environment (10.1016/j.neuron.2014.01.020 )

In summary I agree that any model that fits the data would have to capture the idea that participants don't differentiate between the different environments as much as they should, but I think there are a number of qualitatively different reasons why they might do this - of which the above are only examples.

Reviewer #3 (Public review):

Summary

In this manuscript, Zhang et al. investigate the conduction and inhibition mechanisms of the Kv2.1 channel, with a particular focus on the distinct effects of TEA and RY785 on Kv2 potassium channels. Using microsecond-scale molecular dynamics simulations, the authors characterize K⁺ ion permeation and RY785-mediated inhibition within the central pore. Their results reveal an inhibition mechanism that differs from those described for other Kv channel inhibitors.

Strengths

The study identifies a distinctive inhibitory mode for RY785, which binds along the channel walls in the open-state structure while still permitting a reduced level of K⁺ conduction. In addition, the authors propose a long-range allosteric coupling between RY785 binding in the central pore and changes in the structural dynamics of Kv2.1. Overall, this is a well-organized and carefully executed study, employing robust simulation and analysis methodologies. The work provides novel mechanistic insights into voltage-gated potassium channel inhibition and may offer useful guidance for future structure-based drug design efforts.

Weaknesses:

As noted in the Discussion, this study focuses primarily on the major binding site within the central pore and was not designed to systematically assess other potential allosteric binding sites for RY785. A more comprehensive structural and biophysical evaluation of possible additional binding sites would be a valuable direction for future investigations.

Comments on revisions:

The authors have addressed my comments.

Reviewer #1 (Public review):

Summary:

In many vertebrates, the neural tube closes by folding, elevation, and fusion of bilateral neural folds. Loss of the actin-binding protein Vinculin causes failed cranial neural tube closure in mice and is associated with neural tube defects in human patients, but it was not known how Vinculin contributes to neural tube closure. Here, Prudhomme and colleagues find that neural fold elevation and the apical constriction that drives it initiate normally in Vinculin-deficient mouse embryos, but both arrest before the neural folds fuse. The time of failure coincides with increased mechanical tension within the cranial neural plate. They find that Vinculin localizes to areas of high mechanical stress in the WT neural plate, including multi-cellular junctions and dividing cells, and in the absence of Vinculin, recruitment of Myosin and Apical junction proteins is reduced at these sites. These data support a model in which Vinculin recruits junctional proteins to high-stress areas to maintain junctional integrity during neural tube closure.

Strengths:

The data presented are thorough, rigorous, and convincing. The combination of live imaging and transgenic fluorescent reporters enables direct observation of junctional behaviors within the mouse cranial neural plate and detailed analysis of how these behaviors are disrupted upon loss of Vinculin. The authors make good use of an ESC transplant approach to efficiently generate mutant and transgenic embryos for analysis.

Weaknesses:

Although the loss of junctional integrity, especially at multi-cellular junctions, is clearly and convincingly demonstrated in Vinculin-deficient embryos, it is not clear precisely how this disrupts the elevation of the neural folds to cause exencephaly.

Reviewer #2 (Public review):

Summary

Using mouse embryos early in development, this excellent paper from Prudhomme et al. shows that Vinculin's recruitment to adherens junctions during mammalian cranial neural tube closure is essential for maintaining junctional integrity in response to increased tension during this process. Previous work had shown that during neural tube elevation, planar polarity of Myosin II and mechanical forces in the tissue are increased. Additionally, mouse embryos lacking Vinculin were known to display neural tube closure failure, and mutations in human Vinculin had been associated with increased risk of neural tube defects, but the mechanism remained unclear. Here, the authors utilize a high-throughput embryonic stem cell (ESC)-based pipeline to generate Vinculin-depleted embryos, complemented by a conditional mutant lacking Vinculin in the embryonic lineages, to investigate this question. The authors show that Vinculin is not required for force generation, but Vinculin is recruited to cell-cell junctions in a tension-dependent manner and is needed to transmit actomyosin-mediated tension to junctions - particularly tricellular and higher-order multicellular junctions - so that apical constriction can happen during neural fold elevation. Furthermore, they find that Vinculin is required to maintain adhesion during high force events (e.g., rosette resolution and cell division) during neural tube closure. The research builds on previous studies about Vinculin's role in mechanotransduction at cell-cell junctions carried out in cultured epithelial cells, zebrafish cardiomyocytes, or early Xenopus embryos, and investigates how physiological forces required for mouse neural tube closure challenge junction integrity and the important role that Vinculin plays in maintenance of junction integrity and translation of mechanical forces into changes in tissue structure during this process.

Strengths:

This study stands out for its sophisticated use of laser ablation and live imaging in neurulating mouse embryos, enabling quantification of junctional tension, Vinculin recruitment to multicellular junctions, and assessment of junction integrity during neural tube elevation. The authors' use of both ESC-derived Vinculin mutant embryos complemented by a second conditional mutant of Vinculin convincingly demonstrates that their findings are specific to the loss of Vinculin. Additionally, the authors demonstrated proof-of-principle for their ESC-based pipeline with a Shroom3 mutant known to be important for neural tube closure. The Zallen lab's application of the genetically engineered ESC-derived mouse embryo pipeline to efficiently generate larger numbers of mutant mouse embryos exhibiting neural tube closure defects (compared with traditional genetic crossing strategies) that can be utilized for live imaging and mechanical perturbations like laser ablation will be valuable for future work in the field. The authors show that Vinculin depletion disrupts tricellular and multicellular junctions. Notably, over 75% of higher-order (5+) vertices in Vinculin mutant embryos display gaps, but interestingly, about one third of 5+ cell junctions in Control embryos also display gaps, indicating that transient vertex remodeling events are needed for normal neural tube closure. Overall, this is a well-written paper that places the authors' findings within the context of prior literature; their beautiful data that is robustly analyzed and clear figure presentation will make the authors' exciting findings accessible to readers.

Weaknesses:

The criteria for selection of junctions targeted by laser ablation, including specifics of location, Myosin II intensity, and initial junction length, should be more clearly described in the Methods, especially given the use of different reporter strains (MyoIIB-GFP vs. GFP-Plekha7) across figures, which may influence junction selection for laser ablation. Analysis of Myosin II in Vinculin mutant embryos would benefit from staining for active Myosin II (pMRLC), and further examination of actomyosin organization at different stages of neural fold elevation in controls vs. Vinculin mutants would be informative. Although the authors note that ZO-1 gaps are limited to a subset of vertices where adherens junction gaps are detected, the increased frequency of tight junction gaps in Vinculin mutants could have functional significance that should be noted. Finally, inclusion of schematics to detail how the adherens and tight junction gaps were defined and measured at cell vertices, as well as how cell division completion was defined, would improve transparency and strengthen readers' understanding of how the data were quantified.

Reviewer #3 (Public review):

Summary:

Prudhomme et al report a detailed analysis of the role of vinculin in maintaining neuroepithelial integrity during cranial neurulation.

Strengths:

The authors use complementary experiments involving super-resolution microscopy, laser ablation, and live imaging of conditional knockout and ESC-derived embryos to demonstrate that loss of vinculin produces wide gaps between the adherens junctions of neuroepithelial cells at later stages of cranial neural fold elevation. The data presented are of extremely high quality, logically presented in a compelling story, and represent a very substantial contribution.

Weaknesses:

The authors are invited to consider the largely minor questions recommended below.

(1) The laser ablations reported are a correlate of cell border, or 'junctional' tension. Please avoid broad statements such as 'mechanical forces are upregulated' (abstract), which invoke gene-like regulation of tissue-level forces (in Newtons). Changes in junctional tension are likely to relate to changes in force generated, but their relationship is not simple: higher tensile stress withstood by the shorter length of junctions in cells with smaller apical surfaces does not necessarily translate into greater force being produced by that cell. The junctional tension readout measured is perfectly relevant to the paper, more so than tissue-level forces would have been.

(2) What is the mechanical mechanism by which loss of vinculin prevents neural fold elevation? The authors present exciting findings about the cellular consequences of losing Vcl at the late elevation stages when the tissue is quantifiably dysmorphic. A clear argument of how Vcl loss could lead to this dysmorphology would strengthen the paper, particularly given that junctional tension defects are excluded and apical non-constriction at the late stage is only mild.

(3) Can the authors comment on the likely impacts of Vcl deletion on the basal domain of the cell? For example, they could cite live-imaging of distinct behaviours in Williams et al Dev Cell 2014, and the NTD phenotypes of some integrin/focal adhesion mutant mice.

(4) The apparent uncoupling of apical area (larger in Vcl KO) from junctional tension (equivalent) in this model is noteworthy. Can the authors speculate on its potential basis?

(5) Live imaging in Figure 7C appears to show a marked reduction in apical area before cleavage furrow formation (T0-18min), suggesting a large apical constriction event (post-mitotic?), as previously reported (e.g., Ampartzidis et al Dev Biol 2023). Do junctional gaps appear during these constrictions?

(6) The live imaging setup used is clearly sufficient to identify differences between genotypes, so this is only a minor point. The gassing conditions listed in the methods specify 5% CO2, but E8.5 embryos also need low O2 to complete cranial closure. Was the O2 level controlled? Was tissue-level shape change observed to be consistent with ongoing neurulation during live-imaging?

(7) Neither the multi-cell laser ablations in the pre-print by De La O cited here, nor the narrower junctional ablations in Bocanegra-Moreno et al., Nat Phys, (2023), identified differences in recoil between developmental stages. Why might those results be different from the findings reported here (e.g., analysis region - not specified in the latter paper)? Limitations to interpreting junctional ablations between cells with different junction lengths include more of the recoil being dissipated by retraction of the longer ablated border.

(8) Is a truncated Vcl expressed in the ESC model, which could bind catenin without an F-actin anchor? The very high-contrast western shown is cropped so it is not clear whether the catenin-binding N-terminus is present. Does the antibody used recognise the head domain (this reviewer could not readily find the information)?

Reviewer #1 (Public review):

Summary:

Using electron microscopy, the authors report discontinuities in the plasma membrane of C. elegans embryos. They associate these discontinuities with cell division and speculate that membrane rupture and subsequent resealing contribute to cytokinesis. They further discuss the proximity of these sites to vesicles and propose a role for vesicle-mediated membrane extension.

Weaknesses:

(1) The possibility that the membrane discontinuity is an artifact

Although the authors focus on discontinuities in the plasma membrane, similar discontinuities are also observed in mitochondria, the nuclear envelope, and yolk granules. This raises concerns about whether the electron micrographs presented are suitable for assessing membrane continuity.

Electron micrographs result from a lengthy sample preparation process, including high-pressure freezing, freeze substitution in acetone containing OsO4, gradual warming, uranyl acetate staining, resin embedding, and ultrathin sectioning. In general, lipids are soluble in acetone at temperatures above −30 {degree sign}C, and preservation of membrane structures relies heavily on efficient OsO4 fixation. Insufficient OsO4 treatment would be expected to reduce membrane contrast.

C. elegans embryos are encapsulated by an eggshell that forms at fertilization and gradually develops during the first few cell divisions. It is unclear how efficiently OsO4 in acetone penetrates the eggshell during freeze substitution, raising further concern about plasma membrane preservation under the conditions used.

(2) Lack of evidence linking membrane discontinuity to cell division

The reported plasma membrane discontinuities are not specific to mitotic cells. If this were a physiological process playing an important role in cytokinesis, it should occur in a temporally and spatially coordinated manner with nuclear division. However, it remains unclear at what stage of the cell cycle the membrane rupture occurs and where it is located relative to chromosomes and the mitotic spindle.

(3) Lack of evidence for extension of the separated membrane

Although the authors speculate that resealing of the ruptured membrane occurs via extension of the separated membrane, no direct evidence supporting this mechanism is presented. Proximity to vesicles alone does not demonstrate that membrane extension occurs through vesicle fusion. More direct evidence is required to support this claim.

(4) Inconsistency with published work

Numerous studies have examined cell division in developing C. elegans embryos using the GFP::PH(PLC1δ1) marker expressed from the ltIs38 transgene [pAA1; pie-1::GFP::PH(PLC1δ1) + unc-119(+)], generated by the Oegema lab (https://wormbase.org/species/c_elegans/transgene/WBTransgene00000911#01--10 ). To date, no study has reported membrane ruptures of the magnitude described here. The complexity of cell surface morphology from the 8- to 12-cell stages onward has been well documented, for example, by Fu et al. (2016) using light-sheet microscopy and 3D reconstruction (doi:10.1038/ncomms11088).

Supplementary Movies 5, 6, and 10 of this paper illustrate how single-plane images can easily produce apparent membrane discontinuities, for example, due to membrane orientations nearly parallel to the imaging plane.

The three single-plane images from only three embryos presented in Figure 6 are insufficient to support the authors' strong conclusions. Raw 3D data should be provided.

Reviewer #2 (Public review):

Summary:

Liang et al. explore an unusual observation of membrane discontinuities in dividing C. elegans embryonic cells. This report is the first to demonstrate that, instead of the classical invagination of membranes during cytokinesis, cells in the early embryos of C. elegans exhibit separation of sister membranes that extend independently. TEM images of high-pressure-frozen samples provide strong evidence for the presence of Membrane Openings (MOs) in cells at various stages of the cell cycle, predominantly during mitosis. High-resolution images (x 30,000) clearly show the wrinkled plasma membrane and smooth MOs.<br /> The electron microscopy data are supported by the live cell imaging of strains with fluorescently tagged membrane markers. This study opens up the possibility of tracking MOs at other stages of C. elegans development, and also asks if it might be a common phenomenon in other species that exhibit rapid embryonic growth and divisions.

Strengths:

(1) Thorough verification of Membrane Openings (MO) by several methods:

(a) 4 independent sample batches.

(b) Examined historical collections.

(c) Analysed embryos at different stages of development. The absence of MOs in later stages (comma) serves as a negative control and gives confidence that MOs are genuine and not technical artifacts.

(2) Live cell imaging of strain with fluorescently labelled membranes provides real-time dynamics of membrane rupture.

(3) After observing the membrane rupture, the next obvious question is - what prevents the cytosol from leaking out? The EM images showing PBL and PEL - extracellular matrix serving as barriers for the cytosol are convincing.

Weakness:

(1) The association of membrane discontinuities with cell division is not convincing, as there are 159 cells out of 425 showing MOs, but it is not mentioned clearly how many of these are undergoing cell division. Also, it's not clear whether the 20 dividing cells analysed for MOs are a part of the 159 cells or a separate dataset. A graphical representation of the number of samples and observed frequencies would be helpful to understand the data collection workflow.

(2) In Figures 3A and 3B, the resolution of the images is not enough to verify 3A as classical membrane invagination and 3B as detached sister membranes.

(3) Figure 6 lacks controls. How does the classical invagination look in this strain? Also, adding nuclear dye would be informative, in order to correlate the nuclear division with membrane rupture, as claimed.

Reviewer #3 (Public review):

Summary:

In this manuscript, the authors challenge a dogma in cell biology, namely that cells are at any time point engulfed by a continuous plasma membrane. Liang et al. find that during C elegans embryogenesis, a high number of cells are not entirely surrounded by a plasma membrane but show membrane openings (MOs). These openings are enriched at the embryo's periphery, towards the eggshell. The authors propose that plasma membrane discontinuities emerge during metaphase of mitosis and that independent extension of "sister membranes" engulfs the daughter cells.

Strengths:

On the positive side, the authors find plasma membrane discontinuities not only by electron microscopy but also by fluorescence microscopy and provide information about the dynamics of membrane openings and their emergence. While this is assuring, the authors conclude that MOs emerge during metaphase. From what the authors show, this particular information cannot be deduced, as there is no dynamic capture of a membrane scission event together with a chromatin marker that would indicate mitosis. The authors could, however, attempt to find such events in live movies, given the high incidence of MOs reported from their EM data.

Weaknesses:

In order to convincingly demonstrate the absence of any plasma membrane in the respective regions of the embryonic periphery or between cells of the embryo, the authors would have to show consecutive serial TEM sections where MOs are detected over more z-planes, beyond the mere 3D reconstructions. Although the authors state in the methods section that continuous ultrathin sections were cut for the metaphase sample (page 21, line 472), consecutive sections are never shown in TEM. While we do see the 3D reconstructions, better documentation of the underlying TEM data is missing. It would be necessary to show a membrane opening in consecutive z sections. Alternatively, the authors could seek the possibility to convincingly back up their claims with volume imaging by focused ion beam scanning EM (FIBSEM), where cellular volumes can be sectioned in almost isotropic resolution.

Another critical issue concerns the detection of the membrane discontinuities in electron micrographs, which, in my opinion, is ambiguous. How do the authors reliably discriminate in their TEM images whether there is a plasma membrane or not? The absence - or weak appearance - of the stain of the electron dense material at membranes, which seems to be their criterion for MOs, is also apparent at other, intracellular membranes, like at the NE or at the ER (for example, see Figure 1C). Also, the plasma membrane itself appears unevenly stained in regions that the authors delineate as intact (for example, Figure 1C, 2B/1).

Reviewer #1 (Public review):

[Editors' note: This version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have addressed the comments raised in the previous round of review.]

Summary:

In their paper entitled "Alpha-Band Phase Modulates Perceptual Sensitivity by Changing Internal Noise and Sensory Tuning," Pilipenko et al. investigate how pre-stimulus alpha phase influences near-threshold visual perception. The authors aim to clarify whether alpha phase primarily shifts the criterion, multiplicatively amplifies signals, or changes the effective variance and tuning of sensory evidence. Six observers completed many thousands of trials in a double-pass Gabor-in-noise detection task while an EEG was recorded. The authors combine signal detection theory, phase-resolved analyses, and reverse correlation to test mechanistic predictions. The experimental design and analysis pipeline provide a clear conceptual scaffold, with SDT-based schematic models that make the empirical results accessible even for readers who are not specialists in classification-image methods.

Strengths:

The study presents a coherent and well-executed investigation with several notable strengths. First, the main behavioral and EEG results in Figure 2 demonstrate robust pre-stimulus coupling between alpha phase and d′ across a substantial portion of the pre-stimulus interval, with little evidence that the criterion is modulated to a comparable extent. The inverse phasic relationship between hit and false-alarm rates maps clearly onto the variance-reduction account, and the response-consistency analysis offers an intuitive behavioral complement: when two identical stimuli are both presented at the participant's optimal phase, responses are more consistent than when one or both occur at suboptimal phases. The frontal-occipital phase-difference result suggests a coordinated rather than purely local phase mechanism, supporting the central claim that alpha phase is linked to changes in sensitivity that behave like changes in internal variability rather than simple gain or criterion shifts. Supplementary analyses showing that alpha power has only a limited relationship with d′ and confidence reassure readers that the main effects are genuinely phase-linked rather than a recasting of amplitude differences.

Second, the reverse-correlation results in Figure 3 extend this story in a satisfying way. The classification images and their Gaussian fits show that at the optimal phase, the weighting of stimulus energy is more sharply concentrated around target-relevant spatial frequencies and orientations, and the bootstrapped parameter distributions indicate that the suboptimal phase is best described by broader tuning and a modest change in gain rather than a pure criterion account. The authors' interpretation that optimal-phase perception reflects both reduced effective internal noise and sharpened sensory tuning is reasonable and well-supported. Overall, the data and figures largely achieve the stated aims, and the work is likely to have an impact both by clarifying the interpretation of alpha-phase effects and by illustrating a useful analytic framework that other groups can adopt.

Reviewer #2 (Public review):

Summary:

The study of Pilipenko et al evaluated the role of alpha phase in a visual perception paradigm using the framework of signal detection theory and reverse correlation. Their findings suggest that phase-related modulations in perception are mediated by a reduction in internal noise and a moderate increase in tuning to relevant features of the stimuli in specific phases of the alpha cycle. Interestingly, the alpha phase did not affect the criterion. Criterion was related to modulations in alpha power, in agreement with previous research.

Strengths:

The experiment was carefully designed, and the analytical pipeline is original and suited to answer the research question. The authors frame the research question very well and propose several models that account for the possible mechanisms by which the alpha phase can modulate perception. This study can be very valuable for the ongoing discussion about the role of alpha activity in perception.

Conclusion:

This study addresses an important and timely question and proposes an original and well-thought-out analytical framework to investigate the role of alpha phase in visual perception. While the experimental design and theoretical motivation are strong, the very limited sample size substantially constrains the strength of the conclusions that can be drawn at the group level.

Bibliography:

Button, K., Ioannidis, J., Mokrysz, C. et al. Power failure: why small sample size undermines the reliability of neuroscience. Nat Rev Neurosci 14, 365-376 (2013). https://doi.org/10.1038/nrn3475

Tamar R Makin, Jean-Jacques Orban de Xivry (2019) Science Forum: Ten common statistical mistakes to watch out for when writing or reviewing a manuscript eLife 8:e48175 https://doi.org/10.7554/eLife.48175

Reviewer #1 (Public review):

Summary:

In the manuscript "Heat Shock Factor Regulation of Antimicrobial Peptides Expression Suggests a Conserved Defense Mechanism Induced by Febrile Temperature in Arthropods," Xiao and colleagues examine the role of the shrimp Litopenaeus vannamei HSF1 ortholog (LvHSF1) in the response to viral infection. The authors provide compelling support for their conclusions that the activation of LvHSF1 limits viral load at high temperatures. Specifically, the authors convincingly show that (i) LvHSF1 mRNA and protein are induced in response to viral infection at high temperatures, (ii) increased LvHSF1 levels can directly induce the expression of the nSWD (and directly or indirectly other antibacterial peptides, AMPs), (ii) nSWD's antimicrobial activities can limit viral load, and, (iv) LvHSF1 protects survival at high temperatures following virus infection. These data thus provide a model by which an increase in HSF1 levels limits viral load through the transcription of antimicrobial peptides, and provide a rationale for the febrile response as a conserved response to viral infection.

Strengths:

The large body of careful time series experiments, tissue profiling, and validation of RNA-seq data is convincing. Several experimental methodologies are used to support the author's conclusions that nSWD is an LvHSf1 target and increased LvHSF1 alone can explain increased levels of nSWD. Similar carefully conducted experiments also conclusively implicate nSWD protein in limiting WSSV viral loads.

Weaknesses:

As with any complex biological phenomenon, several aspects remain incompletely explained. Nevertheless, in their revision, the authors provide additional analyses supporting the authors model that losing LvHSF1 is not detrimental to survival, by more directly altering viral loads. In addition, their revised manuscript clarifies the complex interactions between infection, the role of HSF1, and hormesis. These revisions increase the impact of their findings.

Comments on revisions:

The authors have addressed all comments, and the manuscript is very much improved.

Reviewer #3 (Public review):

In the manuscript titled "Heat Shock Factor Regulation of Antimicrobial Peptides Expression Suggests a Conserved Defense Mechanism Induced by Febrile Temperature in Arthropods", the authors investigate the role of heat shock factor 1 (HSF1) in regulating antimicrobial peptides (AMPs) in response to viral infections, particularly focusing on febrile temperatures. Using shrimp (Litopenaeus vannamei) and Drosophila S2 cells as models, this study shows that HSF1 induces the expression of AMPs, which in turn inhibit viral replication, offering insights into how febrile temperatures enhance immune responses. The study demonstrates that HSF1 binds to heat shock elements (HSE) in AMPs, suggesting a conserved antiviral defense mechanism in arthropods. The findings are informative for understanding innate immunity against viral infections, particularly in aquaculture. However the logical flow of the paper can be improved.

Comments on revisions:

Some aspects of the initial study design, regarding the selection of representative candidate genes and the logical flow, raised concerns. However, these issues have been addressed in the revised manuscript through additional validations and clarifications. Most of my comments and concerns were sufficiently addressed in the revised manuscript. The results support the authors' conclusion that HSF1-dependent regulation of AMP expression contributes to antiviral defense under febrile conditions.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have addressed the comments raised in the previous round of review.]

Summary:

This study provided key experimental evidence for the "Solstice-as-Phenology-Switch Hypothesis" through two temperature manipulation experiments.

Strengths:

The research is data-rich, particularly in exploring the effects of pre- and post-solstice cooling, as well as daytime versus nighttime cooling, on bud set timing, showcasing significant innovation. The article is well-written, logically clear, and is likely to attract a wide readership.

Reviewer #2 (Public review):

In 'Developmental constraints mediate the reversal of temperature effects on the autumn phenology of European beech after the summer solstice', Rebindaine and co-authors report on two experiments on Fagus sylvatica where they manipulated temperatures of saplings between day and night and at different times of year. I think the experiments are interesting, but note that the treatments are extreme compared to natural conditions. Further, given that much of the experiment happened outside, I am not sure how much we can generalize from one year for each experiment, especially when conducted on one population of one species.

Reviewer #1 (Public review):

Summary:

The authors use a gambling task with momentary mood ratings from Rutledge et al. and compare computational models of choice and mood to identify markers of decisional and affective impairments underlying risk-prone behavior in adolescents with suicidal thoughts and behaviors (STB). The results show that adolescents with STB show enhanced gambling behavior (choosing the gamble rather than the sure amount), and this is driven by a bias towards the largest possible win rather than insensitivity to possible losses. Moreover, this group shows a diminished effect of receiving a certain reward (in the non-gambling trials) on mood. The results were replicated in a general online sample where participants were divided into groups with or without STB based on their self-report of suicidal ideation on one question in the Beck Depression Inventory self-report instrument. The authors suggest, therefore, that adolescents diagnosed with depression or anxiety with decreased sensitivity to certain rewards may need to be monitored more closely for STB due to their increased propensity to take risky decisions aimed at (expected) gains (such as relief from an unbearable situation through suicide) regardless of the potential losses. However, such a result was only found in the clinical sample and cannot be generalized more broadly based on the current findings.

Strengths:

(1) The study uses a previously validated task design and replicates previously found results through well-explained model-free and model-based analyses.

(2) Sampling of adolescents at high risk can help target early preventative diagnoses and treatments for suicide.

(3) Replication of the results in an online cohort increases confidence in the findings.

(4) The models considered for comparison are thorough and well-motivated. The chosen models allow for teasing apart which decision and mood sensitivity parameters relate to risky decision-making across groups based on their hypotheses.

(5) Novel finding of mood (in)sensitivity to non-risky rewards and its relationship with risk behavior in STB.

Weaknesses:

(1) Sample size of 25 for S- group is low-powered, which is explicitly mentioned as a study limitation.

(2) Modeling in the mediation analysis focused on predicting risk behavior in this task from the model-derived bias for gains and suicidal symptom scores. Thus, the implications of this work are more relevant to a basic-science understanding of the etiology of suicidal behavior than they are useful as a predictor of suicidal behavior, and it is not clear that a psychiatrist or psychologist could use this task to potentially determine who is at higher risk of attempting suicide and must be more closely monitored. Indeed, relationships between task parameters and behavior and suicidal behavior was limited to the clinical sample with a diagnosis of depression or anxiety disorder, and did not extend to the online sample. Therefore, the claim that these findings provide "computational markers for general suicidal tendency among adolescents" is unwarranted.

Reviewer #2 (Public review):

Summary:

This article addresses a very pertinent question - what are the computational mechanisms underlying risky behaviour in patients having attempted suicide. In particular, it is impressive how the authors find a broad behavioral effect whose mechanisms they can then explain and refine through computational modeling. This work is important because currently, beyond previous suicide attempts, there has been a lack of predictive measures. This study is the first step towards that: understanding the cognition on a group level. Before then being able to include it in future predictive studies (based on the cross-sectional data, this study by itself cannot assess the predictive validity of the measure).

Strengths:

- Large sample size<br /> - Replication of their own findings<br /> - Well-controlled task with measures of behaviour and mood + precise and well-validated computational modeling

Questions, based on revised manuscript and replies to other reviewers:

(1) Replies to reviewers in general: Bayes Factors have been added, it would be good to also use common verbal terms to describe them (e.g. 'anecdotal', 'moderate' etc). For example, my reading of table S8 would be that for gambling rate there is only anecdotal evidence that it does not relate to PSWQ, BDI, and moderate evidence it does not relate to TAI.

(2) Reply to reviewer 1 Q2 (Predicting STB):<br /> For the regression predicting suicidal ideation, it seems to me that what you did was a regression STB ~ gambling behaviour + approach + mood? Could you clarify? I had expected as a test of whether the task can predict STB risk something slightly different - a cross-validation (LOO or maybe 5-fold in the large sample): STB ~ gambling behaviour + approach [parameter from model] + mood [parameter from model]; and then computing in the left out participants: predicted STB. Then checking correlation between STB and predicted STB. This would allow testing whether the diverse task measures together predict STB (with the caveat, that it's cross-validated, rather than hold-out sample, unless you could train on one sample (in lab) and test on the other (online).

(3) Reply to reviewer 2 Q1 (parameter recovery): I'm looking at S3, it seems to still show only the scatter plots and not the correlation matrices, which are now added as text notes. Can you actually show these matrices? An off-diagonal correlation of 0.63 appears quite high. I think it needs to be discussed exactly which parameters those are, and whether that impacts the interpretation of the results.

(4) Reply to reviewer 3 Q3 (mood model): I would have imagined that the response would involve changing the mood equations (equation 8 main text) to include a term for whether the participant gambled or not, independent of the gamble value.

Reviewer #3 (Public review):

This manuscript investigates computational mechanisms underlying increased risk-taking behavior in adolescent patients with suicidal thoughts and behaviors. Using a well-established gambling task that incorporates momentary mood ratings and previously established computational modeling approaches, the authors identify particular aspects of choice behavior (which they term approach bias) and mood responsivity (to certain rewards) that differ as a function of suicidality. The authors replicate their findings on both clinical and large-scale non-clinical samples.

The main problem, however, is that the results do not seem to support a specific conclusion with regard to suicidality. The S+ and S- groups differ substantially in the severity of symptoms, as can be seen by all symptom questionnaires and the baseline and mean mood, where S- is closer to HC than it is to S+. The main analyses control for illness duration and medication but not for symptom severity. The supplementary analysis in Figure S11 is insufficient as it mistakes the absence of evidence (i.e., p > 0.05) for evidence of absence. Therefore, the results do not adequately deconfound suicidality from general symptom severity.

The second main issue is that the relationship between an increased approach bias and decreased mood response to CR is conceptually unclear. In this respect, it would be natural to test whether mood responses influence subsequent gambling choices. This could be done either within the model by having mood moderate the approach bias or outside the model using model-agnostic analyses.

Additionally, there is a conceptual inconsistency between the choice and mood findings that partly results from the analytic strategy. The approach bias is implemented in choice as a categorical value-independent effect, whereas the mood responses always scale linearly with the magnitude of outcomes. One way to make the models more conceptually related would be to include a categorical value-independent mood response to choosing to gamble/not to gamble.

The manuscript requires editing to improve clarity and precision. The use of terms such as "mood" and "approach motivation" is often inaccurate or not sufficiently specific. There are also many grammatical errors throughout the text.

Claims of clinical relevance should be toned down, given that the findings are based on noisy parameter estimates whose clinical utility for the treatment of an individual patient is doubtful at best.

Comments on revisions:'

The authors adequately addressed my comments and I find the manuscript substantially strengthened.

Reviewer #1 (Public review):

Summary

From transcriptomic comparisons of adult mouse cochlear and vestibular hair cells, Xu et al. provide a broad and well-organized overview of differences across 4 established hair cell types (2 cochlear and 2 vestibular). They go on to demonstrate the power of such analyses to provide functional insights by focusing on the differentiated expression of ciliary genes, building to the hypothesis that kinociliary motility occurs in adult vestibular hair cells.

Background

Cilia are prominent in sensory receptors, including vertebrate photoreceptors, olfactory neurons and mechanosensitive hair cells of the inner ear and lateral line. Cilia can be motile or nonmotile depending on their axonemal structure: motile cilia require dynein and the inner 2 singlet microtubules of the 9+2 array. Primary cilia, present early in development, are considered to have sensory functions and to be nonmotile (Mill et al., Nature Rev Gen 2023).

In hair cells, the kinocilium anchors and polarizes the mechanosensitive hair bundle of specialized microvilli. The kinocilium matures from the primary cilium of a newborn hair cell; behind it the bundle of mechanosensory microvilli rises in a descending staircase of rows. During maturation of the mammalian cochlea, all hair cells lose the kinocilium, though not the associated basal body. The consensus for many years has been that most vertebrate kinocilia, and especially mammalian kinocilia, are nonmotile, based largely on the lack of spontaneous motility in excised mammalian vestibular organs, but also on the impression that the rare examples of spontaneous beating motility even in non-mammalian hair cells are associated with deterioration of the preparation (Rüsch & Thurm 1990).

Strengths

In comparing RNA expression across the 4 major types of mouse hair cells - 2 cochlear and 2 vestibular - Xu et al. provide rich data sets for exploration of structure-function differences between these highly specialized cell types. The revised paper significantly improves the organization, interpretation and readability of the presentation of overall findings. smFISH and immuno-staining back up key RNA data, and comparisons are made with published data.

The ciliary motility focus of the rest of the paper is creative and highly interesting. The authors curated the ciliary genes into types associated with different aspects of beating motility, and also investigated the expression of genes typical of primary cilia, which are considered to have sensory and cell signaling functions and to be nonmotile. Their data justify suggesting a role for kinociliary motility (or force generation) in adult mammalian vestibular hair cells, in opposition to a long-held assumption. The results should stimulate investigation of the implications for mechanosensitivity.

Weaknesses

Data

Functional data on kinocilia motility: The technical difficulty in making such measurements in small mouse hair bundles led the authors to work with bullfrog crista bundles. Though not extensively studied here, the ciliary motility shown is convincing. Mouse hair bundle motions are also shown but the evidence connecting the data to kinociliary motion are more suggestive than convincing. But the authors are not dogmatic about these data, and it is reasonable to show them.

Interpretation

The authors take the view that kinociliary motility is likely to be normally present but is rare in their observations because conditions are not right. But while others have described some (rare) kinociliary motility in fish organs (Rusch & Thurm 1990), they interpreted its occurrence as a sign of pathology. Indeed, in this paper, it is not clear what role kinociliary motility would play in mature hair bundles. The authors have added a discussion of this question in the revision.

An underlying rationale for the hypothesis that ciliary motility manifests in mammalian vestibular hair cells seems to rest on the presence of the necessary mRNA and its contrasting absence in cochlear hair cells. Another way to look at this difference could be that evolution acted on cochlear hair cells to shed kinocilia as one of many changes to improve mechanosensitivity at much higher sound frequencies. In vestibular hair cells, kinociliary motion might be useful to enhance mechanostimulation in the developing vestibule (as suggested in this revision) and not so active in maturity. Nevertheless, with their scholarly analysis of the expression of ciliary genes, the authors make a significant argument for further investigation of when and why hair cell kinocilia show active motility.

Reviewer #2 (Public review):

Summary:

In this study the authors compared the transcriptomes of the various different types of hair cells contained in the sensory epithelia of the cochlea and vestibular organs of the mouse inner ear. The analysis of their transcriptomic data lead to novel insights into the potential function of the kinocilium.

Strengths:

The novel findings for the kinocilium gene expression along with the demonstration that some kinocilia demonstrate rhythmic beating as would be seen for known motile cilia is fascinating. It is possible that perhaps the kinocilium known to play a very important role in the orientation of the stereocilia, may have a gene expression pattern that is more like a primary cilium early in development and later in mature hair cells more like a motile cilium. Since the kinocilium is retained in vestibular hair cells it makes sense that it is playing a different role in these mature cells than its role in the cochlea.

Another major strength of this study which cannot be overstated is that for the transcriptome analysis they are using mature mice. To date there is a lot of data from many labs for embryonic and neonatal hair cells but very little transcriptomic data on the mature hair cells. They do a nice job in presenting the differences in marker gene expression between the 4 hair cell types. This information is very useful to those labs studying regeneration or generation of hair cells from ES cell cultures. One of the biggest questions these labs confront is what type of hair cell develop in these systems. The more markers available the better. These data will also allow researchers in the field to compare developing hair cells with mature hair cell to see what genes are only required during development and not in later functioning hair cells.

Comments on revision:

I am satisfied with the revision, the authors made an effort to incorporate the changes requested.

Reviewer #1 (Public review):

This revised manuscript by Qin and colleagues delineates an important neural mechanism that suppresses the intake of sugar solution in response to internal glucose level (the "brake" mechanism for sugar consumption). They identified a three-step neuropeptidergic system that downregulates the sensitivity of sweet-sensing gustatory sensory neurons, primarily in response to elevated level of circulating glucose. First, neurons that release a neuropeptide Hugin (which is an insect homolog of vertebrate Neuromedin U (NMU)) are activated by a high concentration of hemolymph glucose, which is directly sensed by Hugin-releasing neurons in a cell-autonomous mechanism. Next, Hugin neuropeptides activate Allatostatin A (AstA)-releasing neurons via one of Hugin receptors, PK2-R1. Finally, the released AstA neuropeptide suppresses sugar response in sweet-sensing Gr5a-expressing gustatory sensory neurons through the AstA-R1 receptor. Suppression of sugar response in Gr5a-expressing neurons reduces fly's sugar intake motivation. They also found that NMU-expressing neurons in the ventromedial hypothalamus (VMH) of mice (which project to the rostal nucleus of the solitary tract (rNST)) are also activated by high concentration of circulating glucose, independent of synaptic transmission, and that injection of NMU reduces the glucose-induced activity in the downstream of NMU-expressing neurons in rNST. These data suggest that the function of Hugin neuropeptides in the fly is analogous to the function of NMU in the mouse.

The authors have provided multiple lines of compelling evidence generated through rigorous and comprehensive experiments, which spans genetic abrogation, neuronal manipulation, pharmacology, and functional imaging. The authors are also receptive to the critiques and reframed the central message, such that their conclusions are soundly supported by the presented data. Importantly, the parallel study in mice adds a unique comparative perspective that makes the paper of interest to a wide range of readers.

Reviewer #2 (Public review):

Summary:

The question of how caloric and taste information interact and consolidate remains both active and highly relevant to human health and cognition. The authors of this work sought to understand how nutrient sensing of glucose modulates sweet sensation. They found that glucose intake activates hugin signaling to AstA neurons to suppress feeding, which contributes to our mechanistic understanding of nutrient sensation. They did this by leveraging the genetic tools of Drosophila to carry out nuanced experimental manipulations, and confirmed the conservation of their main mechanism in a mammalian model. This work builds on previous studies examining sugar taste and caloric sensing, enhancing the resolution of our understanding.

Strengths:

Fully discovering neural circuits that connect body state with perception remains central to understanding homeostasis and behavior. This study expands our understanding of sugar sensing, providing mechanistic evidence for a hugin/AstA circuit that is responsive to sugar intake and suppresses feeding. In addition to effectively leveraging the genetic tools of Drosophila, this study further extends their findings into a mammalian model with the discovery that NMU neural signaling is also responsive to sugar intake.

Weaknesses:

The effect of Glut1 knockdown on PER in hugin neurons is modest in both fed and starved flies, suggesting that glucose intake through Glut1 may only be part of the mechanism. The authors address this in their discussion.

Reviewer #2 (Public review):

Summary:

The authors goals is to be develop a more accurate system that reports TDP-43 activity as a splicing regulator. Prior to this, most methods employed western blotting or QPCR based assays to determine whether targets of TDP-43 were up or down regulated. The problem with that is the sensitivity. This approach uses an ectopic delivered construct containing splicing elements from CFTR and UNC13A (two known splicing targets) fused to a GFP reporter. Not only does it report TDP-43 function well, but it operates at extremely sensitive TDP-43 levels, requiring only picomolar TDP-43 knockdown for detection. This reporter should supersede the use of current TDP-43 activity assays, its cost-effective, its rapid and reliable.

Strengths:

In general, the experiments are convincing and well designed. The rigor, number of samples and statistics, and gradient of TDP-43 knockdown were all viewed as strengths. In addition, the use of multiple assays to confirm the splicing changes were viewed as complimentary (ie PCR and GFP-fluorescence) adding additional rigor. The final major strength i'll add is the very clever approach to tether TDP-43 to the loss of function cassette such that when TDP-43 is inactive it would autoregulate and induce wild-type TDP-43. This has many implications for the use of other genes, not just TDP-43, but also other protective factors that may need to be re-established upon TDP-43 loss of function.

Weaknesses:

Admittedly, one needs to initially characterize the sensor and the use of cell lines is an obvious advantage, but it begs the question of whether this will work in neurons. Additional future experiments in primary neurons will be needed. The bulk analysis of GFP-positive cells is a bit crude. As mentioned in the manuscript, flow sorting would be an easy and obvious approach to get more accurate homogenous data. This is especially relevant since the GFP signal is quite heterogenous in the image panels, for example Figure 1C, meaning the siRNA is not fully penetrant. Therefore, stating that 1% TDP-43 knockdown achieves the desired sensor regulation might be misleading. Flow sorting would provide a much more accurate quantification of how subtle changes in TDP-43 protein levels track with GFP fluorescence.

Some panels in the manuscript would benefit from additional clarity to make the data easier to visualize. For example, Figure 2D and 2G could be presented in a more clear manner, possibly split into additional graphs since there are too many outputs. Sup Figure 2A image panels would benefit from being labeled, its difficult to tell what antibodies or fluorophores were used. Same with Figure 4B.

Figure 3 is an important addition to this manuscript and in general is convincing showing that TDP-43 loss of function mutants can alter the sensor. However, there is still wild-type endogenous TDP-43 in these cells, and its unclear whether the 5FL mutant is acting as a dominant negative to deplete the total TDP-43 pool, which is what the data would suggest. This could have been clarified. Additional treatment with stressors that inactivate TDP-43 could be tested in future studies.

Overall, the authors definitely achieved their goals by developing a very sensitive readout for TDP-43 function. The results are convincing, rigorous, and support their main conclusions. There are some minor weaknesses listed above, chief of which is the use of flow sorting to improve the data analysis. But regardless, this study will have an immediate impact for those who need a rapid, reliable, and sensitive assessment of TDP-43 activity, and it will be particularly impactful once this reporter can be used in isolated primary cells (ie neurons) and in vivo in animal models. Since TDP-43 loss of function is thought to be a dominant pathological mechanism in ALS/FTD and likely many others disorders, having these type of sensors is a major boost to field and will change our ability to see sub-threshold changes in TDP-43 function that might otherwise not be possible with current approaches.

Comments on revisions:

In the revised version, most of the reviewer's comments have been appropriately addressed with the exception of 1) the use of flow sorting to improve the data analysis and 2) testing this sensor in primary neurons. The latter is the focus of an ongoing separate study. Though flow sorting would significantly strengthen this study and help others in the field to use this sensor, it is still an impactful and innovative study without it.

Reviewer #3 (Public review):

The DNA and RNA binding protein TDP-43 has been pathologically implicated in a number of neurodegenerative diseases including ALS, FTD, and AD. Normally residing in the nucleus, in TDP-43 proteinopathies, TDP-43 mislocalizes to the cytoplasm where it is found in cytoplasmic aggregates. It is thought that both loss of nuclear function and cytoplasmic gain of toxic function are contributors to disease pathogenesis in TDP-43 proteinopathies. Recent studies have demonstrated that depletion of nuclear TDP-43 leads to loss of its nuclear function characterized by changes in gene expression and splicing of target mRNAs. However, to date, most readouts of TDP-43 loss of function events are dependent upon PCR based assays for single mRNA targets. Thus, reliable and robust assays for detection of global changes in TDP-43 splicing events are lacking. In this manuscript, Xie, Merjane, Bergmann and colleagues describe a biosensor that reports on TDP-43 splicing function in real time. Overall, this is a well-described unique resource that would be of high interest and utility to a number of researchers validated in multiple cell types as a sensitive readout of TDP-43 loss of function. Future studies validating the utility of this biosensor in models of TDP-43 loss of function (e.g. disease iPSNs) that do not rely on TDP-43 knockdown will be of further interest.

Reviewer #1 (Public review):

Summary:

Planar cell polarity core proteins Frizzled (Fz)/Dishevelled (Dvl) and Van Gogh-like (Vangl)/Prickle (Pk) are localized on opposite sides of the cell and engage in reciprocal repression to modulate cellular polarity within the plane of static epithelium. In this interesting manuscript, the authors explore how the anterior core proteins (Vangl/Pk) inhibit the posterior core protein (Dvl). The authors propose that Pk assists Vangl2 in sequestering both Dvl2 and Ror2, while Ror2 is essential for Dvl to transition from Vangl to Fz in response to non-canonical Wnt signaling.

Strengths:

The strengths of the manuscript are found in the very interesting and new concept along with supportive data for a model of how non-canonical Wnt induces Dvl to transition from Vangl to Fz with an opposing role for PK and Vangl2 to suppress Dvl during convergent extension movements. Ror is key player required for the transition and antagonizes Vangl.

Weaknesses:

In addition to general whole embryo morphology that is used as evidence for CE defects, two forms of data are presented: co-expression and IP, as well as IF of exogenously expressed proteins. The microscopy would benefit from super-resolution microscopy since in many cases the differences in protein localization are not very pronounced, and Western analysis data often show relatively subtle differences. Thus, future work will determine the strength of the interactions of the model.

Major points.

Overexpression conditions

A possible concern is that most analyses were performed with overexpression conditions. PCP core proteins (Vangl2, Pk, Dvl, and Fz receptors) are known to display polarized subcellular localization in both the neural epithelium and DMZ explants (Ref: PCP and Septins govern the polarized organization of the actin cytoskeleton during convergent extension, Current Biology, 2024). However, in this study, overexpressed PCP core proteins failed to show polarized localization. Thus, one must be careful in interpreting data.

Subtle effects

Several of the reported results show quite modest changes in imaging and immunoprecipitation analyses, which are supportive of the proposed molecular model, but future experiments will be needed to robustly test the model.

Reviewer #1 (Public review):

Summary:

This manuscript presents an end-to-end pipeline, intended to accelerate EM-based connectomics by combining low-resolution imaging for large volumes with synapse-level imaging only in selected regions of interest. In principle, this strategy can substantially reduce imaging time, computational demands, analysis time, and overall cost.

General note:

Overall, I found the manuscript interesting and valuable, particularly as a description of how one laboratory has assembled and applied a practical workflow to reconstruct and analyze the central complex across multiple insect species. In that sense, the work is compelling as an account of a real, functioning strategy for comparative connectomics, and I appreciated reading it. My main reservation is not about the relevance of the biological problem or the utility of the pipeline in the authors' own hands, but about whether the manuscript, in its current form, fully meets the expectations of a paper that is focused on tools and resources. The expectation would be that this paper would be a venue for sharing new techniques, software tools, datasets, and other resources intended to be usable by the community. Here, because much of the pipeline appears to build on existing methods and software, the key value added should be a particularly clear demonstration of how these components were adapted, integrated, validated, and documented for this specific use case in a way that others could realistically reproduce and adopt. At present, that translational and reproducibility-oriented component does not yet seem sufficiently developed, despite the clear promise of the overall approach.

Major comments:

(1) The work is valuable as a practical integration and application of multiple existing tools into a coherent pipeline, together with a new multi-resolution imaging strategy. However, the manuscript at times reads as though it introduces an entirely novel workflow. I would encourage the authors to clarify the contribution more explicitly: which components are genuinely new (for example, the acquisition strategy and the end-to-end integration/validation), and which are adaptations of already established methods or software. This would make the scope and novelty of the paper easier to assess.

(2) The most distinctive element is the multi-resolution acquisition strategy. However, as described, the selection of high-resolution regions seems to be decided a priori based on anatomy (guided by xCT localization of the CX), rather than being determined automatically from the data (i.e., ROI placement is anatomy-driven rather than data-driven). A more data-driven or machine learning-guided ROI strategy would strengthen the methodological contribution and the adaptability to new scenarios, along the lines of approaches such as SmartEM [1].

(3) The manuscript emphasizes open-source availability and reduced barriers to entry, but the current software release, as referenced, does not yet appear to support straightforward external reuse. Since much of the pipeline builds on existing methods, the main added value lies in how these technologies were adapted, combined, and validated for the present problem. A clear and complete explanation of this adaptation is therefore essential, but is currently missing. I would suggest the following concrete improvements:<br /> a) Provide a single landing page or umbrella repository that links each pipeline step in the paper to the corresponding codebase, including version tags/commits and expected inputs/outputs for each step.<br /> b) Include step-by-step tutorials for each component.<br /> c) Provide an example dataset together with a full reproduction walkthrough in a controlled environment.<br /> d) Clearly explain the required parameters and configuration for each step, including how they should be adjusted for other datasets or scenarios.<br /> e) Follow packaging and distribution best practices (for example, PyPI/conda releases, Docker containers, and version pinning).

(4) In my own attempt to set up and run parts of the released code, I encountered issues that currently limit reproducibility. For example, when creating an environment for EMalign (https://github.com/Heinze-lab/EMalign), the required Python version is not specified, and installation did not succeed under Python 3.12 due to dependency constraints. Additionally, synful_312 (https://github.com/Heinze-lab/synful_312) and SegToPCG (https://github.com/Heinze-lab/SegToPCG) appear to be empty despite being referenced in the manuscript. These are fixable issues, but addressing them is important if the paper is to deliver on its "low entry cost" claim.

(5) Table 1 reports acquisition times, which is helpful. However, the multi-resolution approach adds essential processing steps that appear due to the strategy followed (e.g., "XY alignment high-res" and "high-res to low-res alignment"). Please include registration/alignment (and other major post-processing) runtimes and resource requirements, such as storage, in a comparable table so readers can assess true end-to-end cost.

References:

[1] Meirovitch, Y., et al. "SmartEM: machine learning-guided electron microscopy." Nature Methods (2025).

Reviewer #2 (Public review):

Summary:

The paper proposes a workflow to accelerate EM connectomics by combining multi-scale imaging with image processing and analysis (image alignment, registration, neuron tracing, automated segmentation and synapse prediction, proof-reading) to derive a brain region connectome. The paper argues and (partially) demonstrates that this approach facilitates comparative connectomics.

The data acquisition pipeline uses a well-established sample preparation protocol, uCT guided acquisition, and SBEM imaging at cellular and synaptic resolution.

Data processing and analysis combine existing state-of-the-art components and focus on the alignment and complementary analysis of the two SBEM resolution levels. The paper applies the workflow to the central complex of six different insects and performs some preliminary analysis based on this (which is acceptable for a resource/tool).

Disclaimer for the rest of the review: I am an expert in image analysis and segmentation, so I have mainly focused on these aspects as I am not qualified to analyze the details of image acquisition.

Strengths:

The paper addresses an important problem and promises an acceleration and democratization of comparable connectomics. The time savings of the imaging approach are well-motivated and derived. The methods used for image alignment, segmentation, synapse detection, and proofreading are state-of-the-art.

Weaknesses:

I see two major weaknesses in the paper:

(1) The paper introduces the (approximate) equivalence of the projectome and connectome in the insect brain very prominently in the introduction and uses this as a central motivation for the multi-resolution image acquisition protocol. But - to me - it is unclear how this principle is really used in the analysis presented in the last results and if this assumption is evaluated at all. Specifically, Figure 4 a shows the anatomical neuron reconstructions (from cellular resolution SBEM), d-g show connectome-level analysis from the synaptic resolution data. The only link I can see between the two is that the neural processes in the synapse-resolution data can be mapped to the neurons from the cellular resolution data, thanks to the image alignment. This is certainly important, BUT it is only tangentially related to the projectome vs. connectome claim from the introduction. This claim implies that a tentative connectome is derived from projectome-level data (e.g. by assuming a uniform probability of synapse-formation given surface or distance between projections) that is then validated by the "true" connectome data from synaptic resolution. Instead, what is actually solved - to my understanding - is mapping the local connectome to the projectome. While related, these are different things and the current framing of the paper and the quite brief description of the section on comparative connectomics (also no corresponding Methods section) make this claim inadequately supported.

(2) Reporting on segmentation and proofreading is purely qualitative. Given that this is claimed as a core contribution of the paper (e.g. statement in line 497 and following), I would expect substantially more reporting and evaluation of this claim:<br /> a) Report the actual time needed for proofreading the segmentations in CAVE. I could not find any numbers on this.<br /> b) Report the initial segmentation quality of the model: How many errors does it make? Note: There is a brief mention of VoI-based quantification in Methods (around line 1060), but the results are not reported.

What should be done: Report the error rates (with an accurate measure such as skeleton VoI) independently for all 6 volumes. Given that the authors have the proofread versions, this is feasible. Only then can the claims be made here be evaluated. Note that the F1-score of synapse prediction is quantified. This is a good starting point, but could also be extended to further species in order to assess the actual transferability. Furthermore, none of the data from the study seems to be available. The training data of the network has to be made available. If possible, high-resolution data should be proofread too.

Further points:

(1) Why isn't reconstruction at the cellular level addressed with ML? This is surely possible and should be easier than the full connectome analysis. Similar to before, the actual times needed for tracing with CATMAID are not reported; the manuscript only states that this can be done in minutes for a neuron, but it's unclear if this is the best or average case. It would help to have quantitative numbers to assess whether automation would bring any benefits.

(2) Finally, regarding the underlying software. I did not try this myself due to time constraints, but did check the repositories. They seem to be in an ok state with some documentation in a README. However, given the central role of the software contribution, I would expect a centralized doc page that explains how to use the different parts of the software, including a full example with sample data. Without this, application by other labs - a central claim - will be difficult.

Reviewer #1 (Public review):

Summary:

The authors aimed to determine the neural networks involved in updating behaviour by training mice on a 'go / no go' odour discrimination task, and measuring their brain activity using functional MRI.

Strengths:

The use of the translationally relevant 'go / no go' task is a major strength, as this is a task that can be used as readily in humans as in animals such as mice. The use of fMRI in awake, behaving mice is also a major strength, as this allows the activation of multiple brain regions to be measured while behaviour is ongoing, and also facilitates comparison to human studies. The computational modelling approaches further support these translational aims, again being as readily applied to human data as to animal data.

Weaknesses:

The major weakness of the paper - and one that is potentially addressable - is that the key analysis of the paper, showing that the periaqueductal gray (PAG) is recruited for reversal learning, is only partially supported by the data presented in the paper as it stands. The authors have used a sophisticated way of analysing the behavioural data using 'signal detection theory', in which they collected behavioural data showing correct 'go' responses ('hits'), correct 'no go' responses ('correct rejections'), missed 'go' responses ('misses') and go responses when mice should have withheld a response ('false alarms'). The data presented showing a double dissociation in the activation of the nucleus accumbens for 'hits' but not 'correct rejections' and the PAG for 'correct rejections' but not 'hits' is very interesting; however, it is confounded by the fact that the nucleus accumbens may activate when the animal makes a response, and the PAG when the animal withholds a response. If the authors also included the analysis of nucleus accumbens and PAG activation for 'misses' and 'false alarms', this would allow them to determine whether the activation of these regions reflects the behavioural response or the expectation of reinforcement from the response.

Thus, the paper includes very interesting data and is impressive in its approach to analysing behaviour in a manner that is highly translatable between species. The additional analyses would markedly strengthen the paper and would add depth to the finding that the PAG appears to be involved in behavioural flexibility.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors test the hypothesis that whole-brain functional magnetic resonance imaging in behaving mice, coupled with reinforcement-learning modeling, can dissociate neural substrates of initial cue-reward acquisition versus contingency reversal, and potentially reveal underappreciated contributors to cognitive flexibility. Using a head-fixed go/no-go odor discrimination task with subsequent rule reversal in a subset of mice, they model trial-by-trial state-action values with a model-free Q-learning algorithm (hierarchical Bayesian fit) and use the model-derived decision variable as a parametric regressor in whole-brain analyses. They report that acquisition-related signals prominently involve ventral and dorsal striatal regions, whereas reversal learning additionally recruits the periaqueductal gray (negative correlation with the decision variable) and shows an apparent double dissociation between nucleus accumbens and periaqueductal gray responses for hit versus correct-rejection outcomes during reversal.

Strengths:

(1) The reversal manipulation is implemented without explicit punishment, targeting suppression of previously rewarded actions under reward omission - an underexplored regime for midbrain contributions beyond canonical threat/pain framing.

(2) The manuscript provides a credible MR-compatible olfactory/licking platform with synchronized sniff/lick/valve/reward timing and high-field imaging, supporting feasibility and broader utility for mesoscale systems neuroscience in rodents.

(3) Trial-by-trial value estimates from a Q-learning variant are fit via hierarchical Bayesian inference and explicitly integrated into subject-level general linear models with a mouse hemodynamic response function, which is appropriate for leveraging within-subject dynamics in small-N rodent fMRI.

(4) The decision-variable maps during acquisition recover expected basal ganglia involvement (including nucleus accumbens and dorsal striatum), providing face validity; the reversal-stage map yields an interpretable set of cortical/striatal/pallidal regions plus periaqueductal gray/hippocampus.

(5) The finite impulse response analysis stratified by behavioral outcomes (hit, false alarm, correct rejection, miss) adds interpretability beyond the model regressor alone, and the reported crossover interaction between nucleus accumbens and periaqueductal gray is potentially impactful if robust.

Weaknesses:

(1) The core claim regarding selective periaqueductal gray engagement rests on a subset of n = 6 mice for reversal. With permutation-based whole-brain inference and very small cluster sizes, the robustness of the periaqueductal gray effect to reasonable analytic perturbations is not yet convincing. I would suggest providing leave-one-animal-out analyses for the periaqueductal gray cluster/ROI effects and reporting how often the key findings survive.

(2) The authors note that due to temporal resolution and hemodynamics, they cannot separate stimulus, choice, and feedback and therefore model "whole trials." This limitation creates ambiguity about whether periaqueductal gray signals reflect value updating, action inhibition (no-lick), reward omission, autonomic arousal, or motor preparation/withholding, especially given the strong hit versus correct-rejection opponency. I would suggest adding targeted analyses that disambiguate "withholding" from "reversal-related updating".

(3) ROIs are defined from the whole-brain decision-variable maps and then interrogated by outcome types; the manuscript acknowledges non-independence. This can inflate apparent dissociations. It would be better if the authors define ROIs independently (anatomical periaqueductal gray/nucleus accumbens masks, or split-half ROI definition with held-out data) and repeat the key ROI conclusions.

(4) The reversal group is a subset of the acquisition cohort and also experiences a different task phase structure and additional sessions; the paper attempts to address exposure differences descriptively. I would suggest that the authors formally test whether periaqueductal gray effects are explained by session count, time-in-scanner, or learning rate differences (e.g., include these as covariates, or match sessions more strictly).

(5) The platform records sniffing and licking, but the imaging models described include motion, global, and ventricle regressors and do not clearly include trialwise lick/sniff covariates. Given the periaqueductal gray's known autonomic and defensive coordination roles, physiological state confounding is a major concern. Could the authors incorporate sniff and lick metrics (and their derivatives) as nuisance regressors and show whether the periaqueductal gray effects persist?

Reviewer #1 (Public review):

Summary:

In their manuscript, Zhou and colleagues present a detailed look at how the JSP functions differently in the various cells of a breast tumor. The authors have effectively shown that the JSP acts as a double-edged sword, as it helps T cells fight cancer but also allows tumor cells to grow and avoid ferroptosis. These findings are important because they identify a useful biomarker to predict how TNBC patients might respond to PD-1 inhibitors.

Strengths:

This work is important because it provides a clear explanation for the conflicting roles of the JSP in the tumor environment. The evidence is solid, as it combines data from thousands of patients with single-cell analysis and lab experiments to confirm the role of STAT4 in cancer progression and immunity.

Weaknesses:

However, there are areas for improvement in the scope of the review, the depth of analysis, and the potential for broader clinical implications. The authors are encouraged to address these issues to enhance the scientific and clinical impact of the study.

Major Issues:

(1) The authors demonstrate that STAT4 upregulates SLC47A1, but this is currently supported only by expression correlation and western blot data. To confirm a direct link, the authors are encouraged to perform ChIP-qPCR or luciferase reporter assays to show that STAT4 binds directly to the SLC47A1 promoter.

(2) The conclusion that the MIF-CD74 axis drives immunosuppression is based on computational inference. To support this, the authors could consider mining publicly available breast cancer spatial transcriptomics data to show the co-localization of MIF and CD74. Alternatively, performing simple dual-color immunofluorescence staining on a few clinical sections would effectively demonstrate the physical proximity of these cells.

(3) TNBC is highly heterogeneous and includes subtypes like mesenchymal and immunomodulatory groups. The authors should analyze whether the JSP score or STAT4 levels vary significantly between these subtypes, as this could further refine the selection of patients for JAK1 inhibitors.

(4) While the JSP score works well in the current datasets, the authors should consider validating its predictive accuracy in additional independent immunotherapy cohorts, such as the TONIC trial, to ensure the biomarker is robust across different treatment settings.

Minor Issue:

The manuscript mentions a U-shaped trajectory of JSP activity during tumor transition. A more detailed biological explanation of why the pathway activity initially drops and then rises would add depth to the discussion.

Reviewer #2 (Public review):

Summary:

The JAK-STAT pathway (JSP) exhibits cell-type-specific functional heterogeneity in breast cancer. This study investigates the JSP in breast cancer and its response to anti-PD‑1 immunotherapy. JSP displays distinct cell‑type heterogeneity: it promotes malignant phenotypes and immunosuppression in tumor cells, while enhancing cytotoxicity and reducing exhaustion in T cells. Elevated JSP expression correlates with improved immunotherapy responses, especially in triple‑negative breast cancer. These findings highlight the paradoxical roles of JSP, indicating that broad inhibition may compromise anti‑tumor immunity.

Strengths:

The major strengths of this study include the comprehensive characterization of JSP heterogeneity across epithelial, tumor, and T cells in breast cancer. The identification of JSP and STAT4 as predictive biomarkers for immunotherapy response, particularly in triple‑negative breast cancer, provides clinically relevant insights for patient stratification.

Weaknesses:

The findings rely heavily on public dataset analyses.

Reviewer #3 (Public review):

Summary:

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

Strengths:

Significant therapeutic implications.

Weaknesses:

Limited molecular mechanisms.

Reviewer #1 (Public review):

Summary:

Fields et al. investigated the heterogeneity and kinetics of human antibody secreting cell (ASC) differentiation by analyzing ex vivo tonsil samples and using in vitro differentiation modeling. They discovered that a CD30+ intermediate subset emerges in transition from B cell to ASC in both contexts, but not from germinal centers, and they identified cytokines that promote this state. They also identified an isoform of CD44, CD44v9, that is expressed on some ASCs.

Strengths:

The strengths are the novelty of the findings and the identification of two new markers that may be useful for tracking ASC heterogeneity.

Weaknesses:

However, some of this work seems preliminary and would need to be further validated. Some of the data presented was only representative, with limited controls and biological repeats, limiting the interpretation. For example, the role of Mef2c for CD30 expression was not robustly demonstrated. It was not clear if Figure 1 scRNAseq/ATACseq was from multiple donors or just one. Future studies may extend these novel findings and determine the functional relevance of these factors, CD30, and CD44v9 for ASC differentiation and physiology.

Reviewer #2 (Public review):

Summary:

Bhattacharya and colleagues here use cell culture, single-cell RNA and ATACseq sequencing of such in vitro cultures and of ex vivo isolated B-lineage cells to infer an ontogeny for extra-germinal centre B cell differentiation. The manuscript presents a useful potential ontogeny for plasma cells, wherein in vitro cultured naïve human B cells enter a CD30+ intermediate state before moving in subsequent days through a CD44v9+ state before ultimately obtaining a 'mature' antibody-secreting plasma cell phenotype. Ex vivo isolated germinal centre B cells obtain the plasma cell state without expressing CD30 in their development. Phenotype analysis of tonsillar B-lineage cells supports the same phenotype conversion in vivo, although the intermediate cell population was smaller in vivo. The link to CD44v9 expression on developing plasma cells is inferred to be for extra-GC (T-independent) responses, but the data presented leave this equivocal, and the functional importance of developing via a CD30+CD44v9+ intermediate is not investigated.

Strengths:

The article presents a solid potential ontogeny for PC development, wherein some differentiating B cells acquire a CD30+ state, transition through a CD44v9+CD30+ state, then downmodulate CD30 before obtaining canonical CD38+ 'PC' status. A strength is the integration of in vitro cultured B cell results with tonsillar B-lineage cell data sets, and careful flow cytometry of the in vitro cultures over several days to infer lineage. The data provide reasonable support for the concept. CD30+ cells are shown to develop readily from naïve B cells in culture, but uncommonly from GC B cell cultures. A nice piece of data is Figure 6B, which shows reasonably strong correlative changes in phenotype through the assumed ontogeny, and this fits with the expected trajectory of maturation.

Weaknesses:

The most important weakness throughout is the non-absolute nature of the relationship. An example is seen in that the sorted ex vivo GC B cells also give rise to the 'extra-GC' phenotype of plasma cell, suggesting that while the profile is enriched, it is not absolute. There is a further weakness, as while cultures are run for several days, division-associated shifts in PC phenotype are not mapped; such would greatly strengthen the weight of the argument, and show conditional shifts in phenotype associated with division, an uncontrolled parameter in the mix. For example, for the MEF2C A388 inhibition experiments, it would be strong evidence of the pathway/process contributing if a by-division peak increase in CD30+ population was demonstrated in the early days of culture.

There are some basic sort experiments performed (e.g. 3C-3F), which show that the CD30+ cells do give rise to PC preferentially, but what is missing is the step-wise phenotype shifts in these sorted populations, which should support the trajectory shown in Figure 3B and (the in vitro equivalent of) 6B. It would emphatically support the trajectory to show the cellular phenotypes on the PC with sorting based on CD30, CD44v9, CD27, and CD20 expression, and following outcome phenotypes 24-48 hours later, if the inferred maturation trajectory is true.

There are also specific weaknesses with the bioinformatics, in that, while the analyses are likely appropriate, unpresented data is necessarily used to shape the argument. For example, Figure 1C shows bubble plots for two plasma cell sets, yet, of archetypal PC-expressed genes, only IRF4 is demonstrated to confirm they are true PC, and the gene is not universally expressed in cells in the clusters. For this figure, it would help to expand the bubble plot to show J-CHAIN, XBP-1, CIITA and PRDM1 or other appropriate PC demarcating molecules. Similarly, in Fig 2B, more evidence of a bifurcation in state is needed than that CD44v9 distinguishes PC1 from PC2 clusters-this is the stated conclusion, but 2A depicts that 50% of PC1 relatively weakly express CD44, while <25% of PC2 express it. Demonstrating additional molecules or genes distinguishing the clusters would improve veracity. Figure 2F shows clonal lineages, but it would be helpful to see somatic hypermutation burdens and learn if they differ between the demarcated subsets. I also find the pseudotime analyses of limited value, as some of the branches follow trajectories that are unrealistic biologically, so less weight should be placed on the pathways to which they do or do not point (i.e., the notion that GC B cells do or do not give rise to particular PC subsets).

Statistically, some of the experiments are single wells from single donors, so there is a low level of confidence and no reproducibility demonstrated for some aspects of the study, which is a weakness.

Paradoxical to the argument that it is the TI response process being modelled, it is presented that CpG stimulation, plus proxy T cell help (CD40L), drives the CD30+ phenotype best with the addition of the GC-associated cytokine IL-21. This should be carefully considered and discussed.

Overall, in addition to presenting more contextual information from the bioinformatics, the best way to solidify the data set, in my vie,w would be to revisit the hypothesis with two additional experimental approaches: (1) to incorporate division tracing into the ontogeny studies and (2) to perform lineage tracing on sort-purified populations at different stages of the maturation process.

Reviewer #1 (Public review):

Summary:

Spinal projection neurons in the anterolateral tract transmit diverse somatosensory signals to the brain, including touch, temperature, itch, and pain. This group of spinal projection neurons is heterogeneous in their molecular identities, projection targets in the brain, and response properties. While most anterolateral tract projection neurons are multimodal (responding to more than one somatosensory modality), it has been shown that cold-selective projection neurons exist in lamina I of the spinal cord dorsal horn. Using a combination of anatomical and physiological approaches, the authors discovered that the cold-selective lamina I projection neurons are heavily innervated by Trpm8+ sensory neuron axons, with calb1+ spinal projection neurons primarily capturing these cold-selective lamina I projection neurons. These neurons project to specific brain targets, including the PBNrel and cPAG. This study adds to the ongoing effort in the field to identify and characterize spinal projection neuron subtypes, their physiology, and functions.

Strengths:

(1) The combination of anatomical and physiological analyses is powerful and offers a comprehensive understanding of the cold-selective lamina I projection neurons in the spinal cord dorsal horn. For example, the authors used detailed anatomical methods, including EM imaging of Trpm8+ axon terminals contacting the Phox2a+ lamina I projection neurons. Additionally, they recorded stimulus-evoked activity in Trpm8-recipient neurons, carefully selected by visual confirmation of tdTomato and GFP juxtaposition, which is technically challenging.

(2) This study identifies, for the first time, a molecular marker (calb1) that labels cold-selective lamina I projection neurons. Although calb1+ projection neurons are not entirely specific to cold-selective neurons, using an intersectional strategy combined with other genes enriched in this ALS group or cold-induced FosTRAP may further enhance specificity in the future.

(3) This study shows that cold-selective lamina I projection neurons specifically innervate certain brain targets of the anterolateral tract, including the NTS, PBNrel, and cPAG. This connectivity provides insights into the role of these neurons in cold sensation, which will be an exciting area for future research.

Weaknesses:

(1) The sample size for the ex vivo electrophysiology conducted on the calb1+ lamina I projection neurons (Figure 5) is limited to a total of six recorded neurons. Given the difficulty and complexity of the preparation, this is understandable. Notably, since approximately 87% of lamina I projection neurons heavily innervated by Trpm8+ terminals are calb1+, these six recordings of such neurons in Figure 4E could also be calb1+.

Reviewer #2 (Public review):

Summary:

In this study, the authors took advantage of a semi-intact ex vivo somatosensory preparation that includes hindlimb skin to characterize the response of projection neurons in the dorsal horn of the spinal cord to peripheral stimulation, including cold thermal stimuli. The main aim was to characterize the connectivity between peripheral afferents expressing the cold sensing receptor TRPM8 and a set of genetically tagged neurons of the anterolateral system (ALS). These ALS neurons expressed high levels of the calcium binding protein calbindin 1.

In addition, combining different viral tracing methods, the authors could identify the anatomical targets of this specific subset of projection neurons within the brainstem and diencephalon.

Strengths:

The use of a relatively new (seldom used previously) transgenic line to label TRPM8-expressing afferents, combined with the genetic characterization of a previously identified subset of projections neurons add specificity to the characterization. The transgenic line appears to capture well the subpopulation of Trpm8-expressing neurons.

In addition, the use of electron microscopy techniques makes the interpretation of the structural contacts more compelling

The writing is clear and the presentation of findings follows a logical flow.

Overall, this study provides solid, novel information about the brain circuits involved in cold thermosensation.

Weaknesses:

In the characterization of recorded neurons in close contact or in the absence of this contact with TRPM8 afferents, the number of recordedd neurons is relatively low. In addition, the strength of thermal stimuli is not very well controlled, preventing a more precise characterization of the connectivity.

The authors acknowledge that, technically, this is a very difficult preparation with very low yield as far as obtaining successful recordings. Moreover, the tissue needs to be maintained at room temperature which is obviously not ideal when characterizing cold thermoreceptors due to the unavoidable effects of low temperature on cold-activated receptors.

Reviewer #3 (Public review):

Summary:

Razlan and colleagues provide a detailed anatomical characterization of lamina I projection neurons in the mouse spinal cord that are densely innervated by primary afferents activated by cooling of the skin. The authors validate a Trpm8-Flp mouse line, show synaptic contacts between Trpm8⁺ boutons and projection neurons at the ultrastructural level, and demonstrate at the physiological level that these neurons specifically respond to cooling stimuli. Next, by taking advantage of previous transcriptomic analysis of ALS neurons, the authors identify calbindin as a marker for cold activatetd lamina I projection neurons and map their ascending projections to the rostral lateral parabrachial area, caudal periaqueductal gray, and ventral posterolateral thalamus, well-known thermosensory and thermoregulatory centers. Altogether, these findings provide strong anatomical and functional evidence for a direct line of transmission from Trpm8⁺ sensory afferents through Calb1⁺ lamina I neurons to key supraspinal centers controlling perception of cold and thermoregulatory responses.

Strengths:

The combination of mouse genetics, electron microscopy, ex-vivo physiology, optogenetics and viral tracing provides convincing evidence for a direct cold pathway. The work validates the Trpm8-Flp line by extensive anatomical and molecular characterization. Integration with previous transcriptomic and anatomical data, neatly links the cold-selective lamina I neurons to a molecularly defined cluster of ALS neurons, strengthening the bridge between molecular identity, anatomy, and physiological function.

Weaknesses:

The main limitation remains the relatively small number of neurons that could be recorded electrophysiologically. While understandable given the complexity of the preparation, this necessarily limits generalization.

Reviewer #1 (Public review):

Summary:

Spinal projection neurons in the anterolateral tract transmit diverse somatosensory signals to the brain, including touch, temperature, itch, and pain. This group of spinal projection neurons is heterogeneous in their molecular identities, projection targets in the brain, and response properties. While most anterolateral tract projection neurons are multimodal (responding to more than one somatosensory modality), it has been shown that cold-selective projection neurons exist in lamina I of the spinal cord dorsal horn. Using a combination of anatomical and physiological approaches, the authors discovered that the cold-selective lamina I projection neurons are heavily innervated by Trpm8+ sensory neuron axons, with calb1+ spinal projection neurons primarily capturing these cold-selective lamina I projection neurons. These neurons project to specific brain targets, including the PBNrel and cPAG. This study adds to the ongoing effort in the field to identify and characterize spinal projection neuron subtypes, their physiology, and functions.

Strengths:

(1) The combination of anatomical and physiological analyses is powerful and offers a comprehensive understanding of the cold-selective lamina I projection neurons in the spinal cord dorsal horn. For example, the authors used detailed anatomical methods, including EM imaging of Trpm8+ axon terminals contacting the Phox2a+ lamina I projection neurons. Additionally, they recorded stimulus-evoked activity in Trpm8-recipient neurons, carefully selected by visual confirmation of tdTomato and GFP juxtaposition, which is technically challenging.

(2) This study identifies, for the first time, a molecular marker (calb1) that labels cold-selective lamina I projection neurons. Although calb1+ projection neurons are not entirely specific to cold-selective neurons, using an intersectional strategy combined with other genes enriched in this ALS group or cold-induced FosTRAP may further enhance specificity in the future.

(3) This study shows that cold-selective lamina I projection neurons specifically innervate certain brain targets of the anterolateral tract, including the NTS, PBNrel, and cPAG. This connectivity provides insights into the role of these neurons in cold sensation, which will be an exciting area for future research.

Weaknesses:

(1) The sample size for the ex vivo electrophysiology is small. Given the difficulty and complexity of the preparation, this is understandable. However, a larger sample size would have strengthened the authors' conclusions.

(2) The authors used tdTomato expression to identify brain targets innervated by these cold-selective lamina I projection neurons. Since tdTomato is a soluble fluorescent protein that fills the entire cell, using synaptophysin reporters (e.g., synaptophysin-GFP) would have been more convincing in revealing the synaptic targets of these projection neurons.

(3) The summary cartoon shown in Figure 7 can be misleading because this study did not determine whether these cold-selective lamina I projection neurons have collateral branches to multiple brain targets or if there are anatomical subtypes that may project exclusively to specific targets. For example, a recent study (Ding et al., Neuron, 2025) demonstrated that there are PBN-projecting spinal neurons that do not project to other rostral brain areas. Furthermore, based on the authors' bulk labeling experiments, the three main brain targets are NTS, PBNrel, and cPAG. The VPL projection is very sparse and almost negligible.

Reviewer #2 (Public review):

Summary:

In this study, the authors took advantage of a semi-intact ex vivo somatosensory preparation that includes hindlimb skin to characterize the response of projection neurons in the dorsal horn of the spinal cord to peripheral stimulation, including cold thermal stimuli. The main aim was to characterize the connectivity between peripheral afferents expressing the cold-sensing receptor TRPM8 and a set of genetically tagged neurons of the anterolateral system (ALS). These ALS neurons expressed high levels of the calcium-binding protein calbindin 1.

In addition, combining different viral tracing methods, the authors could identify the anatomical targets of this specific subset of projection neurons within the brainstem and diencephalon.

Strengths:

The use of a relatively new (seldom used previously) transgenic line to label TRPM8-expressing afferents, combined with the genetic characterization of a previously identified subset of projection neurons, adds a specificity to the characterization. The transgenic line appears to capture well the subpopulation of Trpm8-expressing neurons

In addition, the use of electron microscopy techniques makes the interpretation of the structural contacts more compelling.

The writing is clear, and the presentation of findings follows a logical flow.

Overall, this study provides solid, novel information about the brain circuits involved in cold thermosensation.

Weaknesses:

In the characterization of recorded neurons in close contact or in the absence of this contact with TRPM8 afferents, the number of recorded neurons is relatively low. In addition, the strength of thermal stimuli is not very well controlled, preventing a more precise characterization of the connectivity.

The authors could provide some sense of the effort needed to record from the 6 cold-activated neurons described. How many preparations were needed, etc?

Reviewer #3 (Public review):

Summary:

Razlan and colleagues provide a detailed anatomical characterization of lamina I projection neurons in the mouse spinal cord that are densely innervated by primary afferents activated by cooling of the skin. The authors, building on their previous anatomical work, validate a Trpm8-Flp mouse line, show synaptic contacts between Trpm8⁺ boutons and projection neurons at the ultrastructural level, and demonstrate at the physiological level that these neurons specifically respond to cooling stimuli. Next, by taking advantage of their previous transcriptomic analysis of ALS neurons, they identify calbindin as a marker for cold-activated lamina I projection neurons and map their ascending projections to the rostral lateral parabrachial area, caudal periaqueductal gray, and ventral posterolateral thalamus, well-known thermosensory and thermoregulatory centers. Altogether, these findings provide strong anatomical and functional evidence for a direct line of transmission from Trpm8⁺ sensory afferents through Calb1⁺ lamina I neurons to key supraspinal centers controlling perception of cold and thermoregulatory responses.

Strengths:

The combination of mouse genetics, electron microscopy, ex vivo physiology, and viral tracing provides convincing evidence for a direct cold pathway. The work validates the Trpm8-Flp line by extensive anatomical and molecular characterization. Integration with previous transcriptomic and anatomical data neatly links the cold-selective lamina I neurons to a molecularly defined cluster of ALS neurons, strengthening the bridge between molecular identity, anatomy, and physiological function.

Weaknesses:

While anatomical evidence for direct synaptic connectivity between Trpm8+ afferents and lamina I projection neurons is compelling, a physiological demonstration of strict monosynaptic transmission is not shown. The conclusion that these inputs are exclusively monosynaptic should be toned down. Similarly, the statement that "Lamina I ALS neurons that are surrounded by Trpm8 afferents are cold-selective" should also be toned down as only a few neurons have been tested and it cannot be excluded that other neurons with similar characteristics may be polymodal.

Reviewer #1 (Public review):

Summary:

CCK is the most abundant neuropeptide in the brain, and many studies have investigated the role of CCK and inhibitory CCK interneurons in modulating neural circuits, especially in the hippocampus. The manuscript presents interesting questions regarding the role of excitatory CCK+ neurons in the hippocampus, which has been much less studied compared to the well-known roles of inhibitory CCK neurons in regulating network function. The authors adopt several methods including transgenic mice and viruses, optogenetics, chemogenetics, RNAi, and behavioral tasks to explore these less-studied roles of excitatory CCK neurons in CA3. They find that the excitatory CCK neurons are involved in hippocampal-dependent tasks such as spatial learning and memory formation, and that CCK-knockdown impairs these tasks.

However, these questions are very dependent on ensuring that the study is properly targeting excitatory CCK neurons (and thus their specific contributions to behavior).

There needs to be much more characterization of the CCK transgenic mice and viruses to confirm the targeting. Without this, it is unclear whether the study is looking at excitatory CCK neurons or a more general heterogeneous CCK neuron population.

Strengths:

This field has focused mainly on inhibitory CCK+ interneurons and their role in network function and activity, and thus this manuscript raises interesting questions regarding the role of excitatory CCK+ neurons, which have been much less studied.

Weaknesses:

(1a) This manuscript is dependent on ensuring that the study is indeed investigating the role of excitatory CCK-expressing neurons themselves and their specific contribution to behavior. There needs to be much more characterization of the CCK-expressing mice (crossed with Ai14 or transduced with various viruses) to confirm the excitatory-cell targeting. Without this, it is unclear whether the study is looking at excitatory CCK neurons or a more general heterogeneous CCK neuron population.

(2) The methods and figure legends are still extremely sparse, still leading to many questions regarding methodology and accuracy. More details would be useful in evaluating the tools and data, and the lack of proper quantification is still prevalent throughout the paper. In many places, only % values are noted, or only images are presented, and the number of cells counted is almost never reported.

Reviewer #2 (Public review):

Summary:

In this study, the authors have demonstrated, through a comprehensive approach combining electrophysiology, chemogenetics, fiber photometry, RNA interference, and multiple behavioral tasks, the necessity of projections from CCK+ CAMKIIergic neurons in the hippocampal CA3 region to the CA1 region for regulating spatial memory in mice. Specifically, authors have shown that CA3-CCK CAMKIIergic neurons are selectively activated by novel locations during a spatial memory task. Furthermore, authors have identified the CA3-CA1 pathway as crucial for this spatial working memory function, thereby suggesting a pivotal role for CA3 excitatory CCK neurons in influencing CA1 LTP. The data presented appear to be well-organized and comprehensive.

Strengths:

(1) This work combined various methods to validate the excitatory CCK neurons in the CA3 area; these data are convincing and solid.

(2) This study demonstrated that the CA3-CCK CAMKIIergic neurons are involved in the spatial memory tasks; these are interesting findings, which suggest that these neurons are important targets for manipulating the memory-related diseases.

(3) This manuscript also measured the endogenous CCK from the CA3-CCK CAMKIIergic neurons; this means that CCK can be released under certain conditions.

Weaknesses:

In summary, this work can be formally accepted after the revision. For the limitations of the revision, the distinct neural effects of cholecystokinin (CCK) receptors (CCK-1R, CCK-2R, and CCK-3R) on hippocampal function have not been fully elucidated. Recent studies indicate that CCK-2R can modulate hippocampal activity at CA3-Schaffer collateral synapses; however, the roles of CCK-1R and CCK-3R in hippocampal function remain poorly characterized, with limited experimental evidence supporting their involvement. Overall, this study provides an interesting and novel perspective on the role of excitatory CCK signaling in hippocampus-dependent navigation learning.

Reviewer #3 (Public review):

Summary:

Fengwen Huang et al. used multiple neuroscience techniques (transgenetic mouse, immunochemistry, bulk calcium recording, neural sensor, hippocampal-dependent task, optogenetics, chemogenetics, and interfer RNA technique) to elucidate the role of the excitatory cholecystokinin-positive pyramidal neurons in the hippocampus in regulating the hippocampal functions, including navigation and neuroplasticity.

Strengths:

(i) The authors provided the distribution profiles of excitatory cholecystokinin in the dorsal hippocampus via the transgenetic mice (Ai14::CCK Cre mice), immunochemistry, and retrograde AAV.

(ii) The authors used the neural sensor and light stimulation to monitor the CCK release from the CA3 area, indicating that CCK can be secreted by activation of the excitatory CCK neurons.

(iii) The authors showed that the activity of the excitatory CCK neurons in CA3 is necessary for navigation learning

(iv) The authors demonstrated that inhibition of the excitatory CCK neurons and knockdown of the CCK gene expression in CA3 impaired the navigation learning and the neuroplasticity of CA3-CA1 projections.

Weaknesses:

(i) The causal relationship between navigation learning and CCK secretion remains nebulous; answering this question will require a more sensitive CCK-BR sensor in future work.

Reviewer #1 (Public review):

Summary:

The authors test whether the frog buccal ventilatory rhythm generator behaves as a discrete, anatomically localized oscillator or as a distributed, state-dependent network. They combine reduced preparations (segment/subsegment work), systematic extracellular unit surveys over a defined grid, and local AMPA/GABA microinjections in a hemisected brainstem preparation. Based on these approaches, the authors conclude that mild global excitation (bath AMPA) broadens the distribution of rhythmically active units and renders a previously defined "buccal area" functionally non-identifiable as a unique necessary/sufficient locus.

The central idea is plausible, and the overall experimental strategy is appropriate for the question being asked. However, in its current form, the manuscript overstates the strength of inference supporting the "expansion" and "loss of necessity/sufficiency" conclusions. This is primarily due to (a) statistical treatment of unit-mapping data that does not respect clustering by preparation/animal, (b) inconsistent statistical reporting across sections, and (c) limited interpretability of focal inhibitory perturbations under a globally excited state.

Strengths:

(1) The manuscript addresses a clear mechanistic question with broader relevance: whether rhythm generation is best conceptualized as a localized kernel or as an emergent distributed property that changes with excitatory state.

(2) The authors use convergent approaches (reduced preparations, mapping, and necessity/sufficiency-style pharmacological perturbations), which is appropriate for circuit-level inference.

(3) A strong element is the within-unit analysis supporting state-dependent changes in phase coupling for a subset of units ("lung" units adopting a buccal-like pattern). The authors' offline PCA-based spike sorting (with cluster-quality selection via silhouette score) provides some reassurance that the reported pre/post injection changes are not simply driven by unit misidentification.

Weaknesses:

(1) Pseudoreplication in unit-survey statistics undermines the main mapping inference. The Methods state that "Units were pooled from multiple preparations" and that chi-squared tests were used to compare proportions across conditions (baseline vs 60 nM AMPA). The Results similarly report proportion changes (e.g., 110 units pooled from three preparations vs 137 units pooled from three additional animals) analyzed with chi-squared tests. Because many units come from the same preparation/animal, independence is unlikely to hold; therefore, inference about state-dependent reorganization at the systems level should be made at the preparation/animal level or via hierarchical models that explicitly account for clustering.

(2) Statistical methods are inconsistently described and need harmonization. In the segment dose-response "Analysis," values are described as compared to zero using a "One-sample t-test." Yet Table 1 is titled as using a "Wilcoxon One-sample Test." These discrepancies must be resolved throughout (Methods, Results, figure legends, and tables), including clear reporting of the unit of n and exact test statistics.

(3) Unit classification and operational definitions raise interpretational concerns. The unit classification scheme defines "buccal units" as those firing during buccal bursts as well as lung bursts, and explicitly notes that "no units were found which fired only during buccal bursts." This is a consequential result, and it currently reads more like a limitation of detection/classification (or state-space sampled) than a robust biological conclusion. Without additional evidence, it weakens claims about a distinct buccal rhythmogenic module and complicates the interpretation of "buccal identity" changes under excitation.

(4) Microinjection mapping: high exclusion rate and alternative explanations for 'loss of necessity' under excitation. The manuscript reports that 15 experiments were conducted, but 9 were excluded because the buccal area was not found or the preparation was "overdriven." This exclusion rate is too high to leave implicit; it raises concerns about selection bias and demands transparent accounting. Moreover, under baseline conditions, GABA (or AMPA-GABA) microinjections reliably reduce/abolish buccal bursts, but under bath 60 nM AMPA, the same injections produce no significant change in instantaneous frequency. This pattern can be interpreted as network redistribution, but it can also reflect state-dependent changes in gain, dynamic range, or local pharmacological impact (e.g., inhibition being comparatively underpowered in the globally excited state). Additional controls/analyses are required to distinguish these explanations.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors investigate the response of the amphibian respiratory rhythm generator under varying excitability conditions. They use pharmacological agents to increase and/ or decrease synaptic excitability and demonstrate the resilience of buccal rhythms under different conditions. They employ these results to formulate their primary thesis, that there is no obligatory locus of the buccal respiratory rhythm in the frog, and that their respiratory rhythmogenic mechanisms should be considered diffuse and anatomically distributed across a larger brainstem region.

Strengths:

This manuscript is well written, with a sufficiently large number of experiments, for which the authors should be congratulated.

Weaknesses:

The presented results don't support the authors' main conclusions, and the interpretation of the data is heavily biased toward their hypothesis. This impregnates an unsubstantiated narrative in the Abstract, Introduction, and Discussion of this manuscript, which must be reexamined with the following points in consideration:

(1) The authors seem to confuse degeneracy with redundancy. For instance, at line 54, they state, "These findings support the broader hypothesis that respiratory rhythm-generating circuits can switch to being diffuse and redundant, with discrete oscillators quickly drowning in a sea of excitations."

Redundancy means having the same component repeated multiple times to buffer the failure of any single component, whereas degeneracy means different functional components that compensate for one another under perturbations (Goaillard and Marder, ARN 2021)

Since the premotor-lung units get converted to buccal units under high excitability, this suggests a degenerate mechanism for respiratory rhythm generation- rather than a redundant mechanism, where there should be multiple buccal units that get recruited under different excitability conditions.

(2) Line 83, "but the essential requirement for a discrete, rudimentary buccal oscillator is also lost".

This statement is not supported by the data presented in this study. How does the expansion of the buccal unit imply that the essential requirement for discreteness is lost? Under increased excitability, does the burst/rhythm initiation zone also expand? Or does it still remain centered around the location of buccal units under physiological conditions? Increased excitability can lead to recruitment of a larger area, without a change in the location of the rhythmogenic kernel.

(3) Line 86, "... oscillators should be viewed as promiscuous flexible functional entities that expand or contract...".

Oscillators can be regarded as promiscuous only if, under physiological conditions, they switch positions. Under high excitability, only the flexibility argument holds, which has been established in mammals before (e.g., CA Del Negro, K Kam, JA Hayes, JL Feldman, The Journal of physiology 587 (6), 1217-1231; CA Del Negro, C Morgado-Valle, JL Feldman,Neuron 34 (5), 821-830; NA Baertsch, LJ Severs, TM Anderson, JM Ramirez, Proceedings of the National Academy of Sciences 116 (15), 7493-7502; NA Baertsch, HC Baertsch, JM Ramirez Nature communications 9 (1), 843).

Results:

(4) Interpretation of data in Figure 6.

How does the Buccal activity and L2 Power stroke change with 60nm AMPA (in CN5)? Does the increase in the Buccal neurons and decrease in power stroke neurons also reflect in the CN5 activity? Also see comments on Figure 9 data below.

(5) Interpretation of data in Figure 7.

Here, classifying buccal neurons solely by spiking may obscure the fact that the 'silent' neurons under baseline conditions were part of the rhythmic network but could not spike due to subthreshold inputs. 60 nM AMPA increased their firing in response to previously subthreshold synchronous inputs during the buccal burst. Intracellular recordings are required to negate this possibility and establish that the neuronal classification is robust.

(6) Interpretation of data in Figure 8.

"Lung units can transform into buccal units under excitation".<br /> CN5 buccal and lung bursts need to be compared before and after AMPA injection. From Figure 8 A-D, it is apparent that the example Unit2's activity increases during the buccal bursts, after AMPA injection. However, they are also present in buccal burst pre-AMPA, albeit with less frequency.

It is striking that the pre-AMPA epoch (panel A) is less than half of the post-AMPA epoch. This would, in itself, lead to a biased estimate of lung units that are active under the baseline condition during the buccal bursts.

Figure 8G, meta-analysis of lung units spiking during the baseline buccal bursts is warranted to interpret the main claim of this figure. Similarly, analysis of spiking per lung burst for the post-AMPA condition is essential for comparing the lung unit's contribution under high excitability.

(7) Interpretation of data in Figure 9

"Buccal area loses importance under increased excitation."

This interpretation is not fully supported by the data presented in this manuscript. Under 60 nm AMPA, does the ratio of lung burst to buccal burst change in CN5? This analysis is crucial for determining whether the lung units are indeed converted into buccal bursts at the expense of lung activity or whether their appearance during buccal bursts is incidental due to increased excitability. In the baseline, there are 4-5 buccal bursts per lung burst, whereas under high excitability, there are 2-3 buccal bursts per lung burst (Figure 9 A-B). This seems inconsistent with the conclusion that increased excitability converts lung units into buccal units (Figures 6 &7).

Could the authors comment on the connectivity between the lung and the buccal units? Results in Figure 9A-B indicate that lung units may receive an efference copy of buccal units, and under high excitability, their spikes may generate negative feedback onto the buccal units, terminating their bursts. This could explain the decrease in the buccal-to-lung burst in high-AMPA conditions. This type of circuit interaction resembles the mammalian breathing CPG, in which the parafacial/RTN (which controls the abdominal muscles) and preBötC (which controls the diaphragm) interact and cross-inhibit each other.

(8) Line 382.

"Buccal-like bursting produced from two independent slices".

The two "independent" slices have portions of the same anatomical kernel, the buccal rhythm generator. This experiment is like the sandwich slice preparation of preBötC (Del Negro Lab), in which two thinner slices exhibit rhythmic activity. Thus, the two slices are not independent; they are anatomically adjacent and functionally overlapping.

Reviewer #3 (Public review):

Summary:

This study uses isolated frog brainstem preparations to test whether inspiratory rhythm generation is confined to a narrowly defined neural center or instead reflects the activity of a distributed and adaptable network. Building on prior rodent work, the authors examine structural and functional parallels between the frog Buccal Area and the mammalian preBötzinger complex. By increasing excitatory drive, they assess whether a localized rhythmogenic region can expand into a broader network that participates in buccal rhythm generation, providing insight into how respiratory circuits are dynamically reconfigured across physiological states.

Strengths:

The work presents compelling evidence that ventilatory rhythm generation is supported by a flexible, state-dependent network rather than a fixed anatomical locus. The experimental preparation is well-suited to address these questions, and the data are generally of high quality. The demonstration that increased excitation recruits a more distributed network parallels observations in mammalian systems and strengthens the translational relevance of the findings. Overall, the analyses are thoughtful, and the interpretations are largely well supported by the results.

Weaknesses:

Some issues limit the strength of the conclusions. First, the study does not address the transition from eupnea to gasping in mammals, which could provide important physiological context for the observed AMPA-induced network reorganization. Second, the reported transformation of lung-active neurons into buccal-active neurons would benefit from additional analyses to clarify whether neurons switch identities or acquire dual activity. Finally, the necessity and sufficiency experiments in Figure 9 require further support, particularly through AMPA dose-response analyses and more comprehensive GABA manipulations, to confirm that network expansion does not obscure the continued functional importance of the core buccal region.

Reviewer #1 (Public review):

Summary:

Choucri and Treiber have reassessed their previous study on TE-gene chimeric transcripts in neural genes in response to Azad et al (2024). Azad and colleagues argued that, contrary to Choucri and Treiber's findings, chimeric TE-mRNAs are relatively infrequent, and they cautioned that further optimization of bioinformatics pipelines is needed to detect TE insertions from RNAseq accurately. In this short response, Choucri and Treiber clearly demonstrate that differences in the tools used between their study and that of Azad et al. likely account for the contrasting results, along with RT-PCR failure in designing primers that would match the chimeric transcript, and the use of different Drosophila lines. The authors emphasize the need for uniform, standardized criteria in such analysis, which would ultimately strengthen and advance the field.

Strengths:

The addition of a ratio to compute the number of splice reads specific to the chimeric transcript and compare to the exon-exon splice reads is really interesting because it opens the door to finally quantify the contribution of chimeric TEs to the overall gene expression, although this is not the scope of the present article. The clear dissection of chimeric transcripts, along with the results from Azad et al, allows us to understand the differences between the two studies confidently. Finally, the discussion on Drosophila lines is indeed essential, given that the lines and even individuals have high TE polymorphism.

Weaknesses:

I think it is necessary to add more detail to this article, for instance, the differences between TEchim and Tidal could be laid out more precisely. Regarding the roo example, one of the caveats of this family, along with others, is the presence of simple repeats. It would be important to show that the simple repeats are not interfering with the read mapping. Regarding the experiments, if we are looking for a standardized protocol, then we should have a detailed material and methods section, with every experiment, replicate, and PCR temperature clearly defined. Finally, and in my opinion, more importantly, the use of RT negative controls on the RT PCRs, along with DNA PCRs to show insertion presence, is mandatory for testing the presence of chimeric genes. Of course, water negative PCR controls are also needed, and unfortunately, absent from Figure 3.

Reviewer #2 (Public review):

Summary:

This study by Choucri and Treiber aims to directly address a recent critique regarding the role of transposable elements (TEs) in diversifying the neural transcriptome of Drosophila. The authors seek to demonstrate that TEs are not merely genomic "noise" but are frequently and reliably "exonized" into brain-specific mRNA. By introducing an upgraded computational pipeline, TEChim, and conducting precise experimental validations, the authors set out to show that TE-mediated splicing represents a genuine biological phenomenon that expands the molecular repertoire of the nervous system.

Strengths:

The study's primary strength lies in its rigorous technical "forensic" analysis of previous failed replication attempts. The authors convincingly demonstrate that the lack of signal in the opposing study stemmed from a fundamental methodological mismatch: the software used by the critics (TIDAL) is logically incapable of detecting splice sites located within TE sequences. Importantly, the authors complement this computational clarification with definitive experimental evidence through an effective "experimental rescue." By employing correctly designed primers and matching the genetic backgrounds of the fly strains, thereby accounting for genomic polymorphisms, they successfully validated all seven loci that were previously reported as undetectable. This dual-pronged strategy, addressing both algorithmic bias and experimental design, establishes a more robust technical benchmark for the detection and validation of TE-derived exons in neural tissues.

Weaknesses:

While the technical rebuttal is highly convincing, the scope of the study remains primarily defensive. As a response to a prior critique, the work focuses on establishing the existence and detectability of chimeric TE-derived transcripts rather than exploring their broader functional consequences. As a result, there is limited new insight into how these TE-modified isoforms influence neural circuit function or organismal behavior. In addition, the detection and validation of these events remain technically demanding, requiring deep sequencing and specialized bioinformatic expertise, which may limit broader adoption by laboratories without dedicated computational resources.

Reviewer #3 (Public review):

Summary:

This manuscript by Choucri and Treiber responds to a recent paper by Azad et al., which responds to a paper by Treiber and Wadell (Genome Research, 2020). The controversy relates to the detection of transcripts with transposable elements (TEs) spliced into them in the Drosophila brain.

Strengths:

The authors now argue convincingly that these transcripts exist using an improved, updated version of their pipeline. They also validate some of their findings using RT-PCR and explain why Azad et al. failed to detect these transcripts due to methodological errors. Overall, I am convinced that these transcripts exist and that the TE-derived transcripts described by Choucri and Treiber are real.

Weaknesses:

The authors should mention that combining PCR-amplified cDNA generation with short-read sequencing is suboptimal for detecting TE-fusion transcripts. Recently, direct long-read ONT RNA sequencing, which does not require amplification and spans the entire transcript, has been used to detect similar transcripts in human stem cells and the human brain (PMID: 40848716 & Garza et al, BioRxiv). Had the authors used this technology to validate their findings, there would be no question about these transcripts. If not doing such experiments, then they should at least discuss the possibility and the advantage of the approach.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have addressed the minor comments raised in the previous round of review.]

Summary:

In this manuscript, Chengjian Zhao et al. focused on the interactions between vascular, biliary, and neural networks in the liver microenvironment, addressing the critical bottleneck that the lack of high-resolution 3D visualization has hindered understanding of these interactions in liver disease.

Strengths:

This study developed a high-resolution multiplex 3D imaging method that integrates multicolor metallic compound nanoparticle (MCNP) perfusion with optimized CUBIC tissue clearing. This method enables the simultaneous 3D visualization of spatial networks of the portal vein, hepatic artery, bile ducts, and central vein in the mouse liver. The authors reported a perivascular structure termed the Periportal Lamellar Complex (PLC), which is identified along the portal vein axis. This study clarifies that the PLC comprises CD34⁺Sca-1⁺ dual-positive endothelial cells with a distinct gene expression profile, and reveals its colocalization with terminal bile duct branches and sympathetic nerve fibers under physiological conditions.

Comments on revisions:

The authors very nicely addressed all concerns from this reviewer. There are no further concerns and comments.

Reviewer #3 (Public review):

Xu, Cao and colleagues aimed to overcome the obstacles of high-resolution imaging of intact liver tissue. They report successful modification of the existing CUBIC protocol into Liver-CUBIC, a high-resolution multiplex 3D imaging method that integrates multicolor metallic compound nanoparticle (MCNP) perfusion with optimized liver tissue clearing, significantly reducing clearing time and enabling simultaneous 3D visualization of the portal vein, hepatic artery, bile ducts, and central vein spatial networks in the mouse liver. Using this novel platform, the researchers describe a previously unrecognized perivascular structure they termed Periportal Lamellar Complex (PLC), regularly distributed along the adult liver portal veins.<br /> Using available scRNAseq data, the authors assessed the CD34⁺Sca-1⁺ cells' expression profile, highlighting mRNA presence of genes linked to neurodevelopment, bile acid transport, and hematopoietic niche potential. Different aspects of this analysis were then addressed by protein staining of selected marker proteins in the mouse liver tissue. Next, the authors addressed how the PLC and biliary system react to CCL4-induced liver fibrosis, implying PLC dynamically extends, acting as a scaffold that guides the migration and expansion of terminal bile ducts and sympathetic nerve fibers into the hepatic parenchyma upon injury.

The work clearly demonstrates the usefulness of the Liver-CUBIC technique and the improvement of both resolution and complexity of the information, gained by simultaneous visualization of multiple vascular and biliary systems of the liver. The identification of PLC and the interpretation of its function represent an intriguing set of observations that will surely attract the attention of liver biologists as well as hepatologists. The importance of the CD34+/Sca1+ endothelial cell population and claims based on transcriptomic re-analysis require future assessment by functional experimental approaches to decipher the functional molecules involved in PLC formation, maintenance, and the involvement in injury response before establishing their role in biliary, arterial, and neural liver systems.

Strengths:

The authors clearly demonstrate an improved technique tailored to the visualization of the liver vasulo-biliary architecture in unprecedented resolution.<br /> This work proposes a new morphological feature of adult liver facilitating interaction between the portal vein, hepatic arteries, biliary tree, and intrahepatic innervation, centered at previously underappreciated protrusions of the portal veins - PLCs.

Weaknesses:

The importance of CD34+Sca1+ endothelial cell sub-population for PLC formation and function was not tested and warrants further validation.

Reviewer #1 (Public review):

This manuscript investigates how dentate gyrus (DG) granule cell subregions, specifically suprapyramidal (SB) and infrapyramidal (IB) blades, are differentially recruited during a high cognitive demand pattern separation task. The authors combine TRAP2 activity labeling, touchscreen-based TUNL behavior, and chemogenetic inhibition of adult-born dentate granule cells (abDGCs) or mature granule cells (mGCs) to dissect circuit contributions.

This manuscript presents an interesting and well-designed investigation into DG activity patterns under varying cognitive demands and the role of abDGCs in shaping mGC activity. The integration of TRAP2-based activity labeling, chemogenetic manipulation, and behavioral assays provides valuable insight into DG subregional organization and functional recruitment. However, several methodological and quantitative issues limit the interpretability of the findings. Addressing the concerns below will greatly strengthen the rigor and clarity of the study.

Major points:

(1) Quantification methods for TRAP+ cells are not applied consistently across panels in Figure 1, making interpretation difficult. Specifically, Figure 1F reports TRAP+ mGCs as density, whereas Figure 1G reports TRAP+ abDGCs as a percentage, hindering direct comparison. Additionally, Figure 1H presents reactivation analysis only for mGCs; a parallel analysis for abDGCs is needed for comparison across cell types.

(2) The anatomical distribution of TRAP+ cells is different between low- and high-cognitive demand conditions (Figure 2). Are these sections from dorsal or ventral DG? Is this specific to dorsal DG, as itis preferentially involved in cognitive function? What happens in ventral DG?

(3) The activity manipulation using chemogenetic inhibition of abDGCs in AsclCreER; hM4 mice was performed; however, because tamoxifen chow was administered for 4 or 7 weeks, the labeled abDGC population was not properly birth-dated. Instead, it consisted of a heterogeneous cohort of cells ranging from 0 to 5-7 weeks old. Thus, caution should be taken when interpreting these results, and the limitations of this approach should be acknowledged.

(4) There is a major issue related to the quantification of the DREADD experiments in Figure 4, Figure 5, Figure 6, and Figure 7. The hM4 mouse line used in this study should be quantified using HA, rather than mCitrine, to reliably identify cells derived from the Ascl lineage. mCitrine expression in this mouse line is not specific to adult-born neurons (off-targets), and its expression does not accurately reflect hM4 expression.

(5) Key markers needed to assess the maturation state of abDGCs are missing from the quantification. Incorporating DCX and NeuN into the analysis would provide essential information about the developmental stage of these cells.

Minor points:

(1) The labeling (Distance from the hilus) in Figure 2B is misleading. Is that the same location as the subgranular zone (SGZ)? If so, it's better to use the term SGZ to avoid confusion.

(2) Cell number information is missing from Figures 2B and 2C; please include this data.

(3) Sample DG images should clearly delineate the borders between the dentate gyrus and the hilus. In several images, this boundary is difficult to discern.

(4) In Figure 6, it is not clear how tamoxifen was administered to selectively inhibit the more mature 6-7-week-old abDGC population, nor how this paradigm differs from the chow-based approach. Please clarify the tamoxifen administration protocol and the rationale for its specificity.

Comments on revisions:

I appreciate the authors' careful and thorough revisions. They have addressed all of my previous concerns satisfactorily, and the manuscript is now significantly strengthened. I have no further concerns.

Reviewer #2 (Public review):

In this study, the authors investigate how increasing cognitive demand shapes activity patterns in the dorsal dentate gyrus (DG). Using a touchscreen-based TUNL task combined with TRAP/c-Fos tagging, birth-dating of adult-born granule cells (abDGCs), and chemogenetic inhibition, they show that higher task demand increases mature granule cell (mGC) recruitment and enhances suprapyramidal (SB) versus infrapyramidal (IB) blade bias. Functionally, mGC inhibition reduces overall activity and impairs performance without disrupting blade bias, whereas inhibition of {less than or equal to}7-week-old abDGCs increases mGC activity, abolishes blade bias, and impairs discrimination under high-demand conditions. These findings suggest that effective pattern separation depends not only on overall DG activity levels but also on the spatial organization of recruited ensembles.

The integration of touchscreen TUNL with temporally controlled activity tagging and birth-dated cohorts is technically strong. Quantification of SB-IB bias and radial/apical distributions adds anatomical precision beyond bulk activity measures. The comparison between mGC and abDGC inhibition is conceptually compelling and supports dissociable functional roles. Overall, the data convincingly demonstrate that increasing cognitive demand amplifies blade-biased DG recruitment and that mGCs and abDGCs differentially contribute to both behavioral performance and network organization.

However, how abDGCs are integrated into the mGC network under high cognitive demand remains unresolved. Additional experiments are needed to clarify how abDGCs shape spatial recruitment patterns and whether they directly inhibit or indirectly regulate mGC activity to maintain high performance.

Furthermore, the authors frame "high cognitive demand" as a multidimensional construct encompassing broad behavioral challenge. It would strengthen the work to delineate how local abDGC-mGC circuit interactions regulate specific task components in real time. This will require higher temporal resolution approaches, as TRAP and c-Fos labeling integrate activity over prolonged windows and primarily reflect sustained engagement rather than moment-to-moment computations.<br /> The central conclusion that dentate function depends on coordinated spatial recruitment rather than total activity magnitude is supported by the data, although mechanistic interpretations should be tempered given methodological limitations.<br /> Overall, this work advances models of adult neurogenesis by emphasizing a critical-period modulatory role of abDGCs in organizing DG network activity during high-demand discrimination. The combined behavioral and circuit-level framework is likely to be influential in the field.

Reviewer #3 (Public review):

This study examines the role of dentate gyrus neuronal populations, reflecting neurogenesis and anatomical location (suprapyramidal vs infrapyramidal blade), in a mnemonic discrimination task that taxes the pattern separation functions of the dentate. The authors measure dentate gyrus activity resulting from cognitive training and test whether adult neurogenesis is required for both the anatomical patterns of activity and performance in the cognitive task. The authors find that more cognitively challenging variants of the task evoked more dentate activity, but also distinct patterns of activity (more activity in the suprapyramidal blade, less in the infdrapyramidal blade). Using chemogenetic approaches they silence mature vs immature dentate gyrus neurons and find that only mature neurons (either the general population or specifically mature adult-born neurons), and not immature adult-born neurons, are required for the difficult version of the task. Inhibition of mature adult-born neurons furthermore increased overall activity in the dentate and reduced the biased pattern of activity across the blades, consistent with evidence that adult-born neurons broadly regulate dentate gyrus activity.

Comments on revisions:

I appreciate the efforts the authors have taken to revise this manuscript. I have only minor concerns with this revised version of the manuscript:

Methods state that significance is defined as P<0.05 but some results are interpreted as significant when P=0.05. Either the alpha value needs to change or the interpretation needs to change.

I believe the statistical results for group and blade effects for the ANOVAs, in Figs 2,3 & 4, appear to be switched (blade should be significant, not group).

I appreciate that sometimes there is not a perfect overlap between immunohistochemical signals, but I continue to believe that the spatially-non-overlapping TRAP and EDU signals in Fig 3 is caused by these 2 markers being in different cells. A Z-stack or orthogonal projection could verify/disprove this concern.

Reviewer #1 (Public review):

Kong et al.'s work describes a new approach that does exactly what the title states, "Correction of local beam-induced sample motion in cryo-EM images using a 3D spline model." It is, therefore, a more elaborate approach than current methods in the field for the "movie alignment" stage. Additionally, the work uses 2DTM (2D Template Matching)-related measurements to quantify the improvement of the new method compared to other methods in the field. I find both parts very compelling (the new method and the testing approach)

On a "focused" view, the strengths of the work rest on presenting a better approach for motion correction and on measuring their performance very well at the 2D level in a compelling manner

On a more "general" view, the authors introduce the important notion that even one of the most worked-out steps in the processing workflow can still be done better in a measurable way, and that this could lead to better results beyond the 2DTM metrics used for testing, reflecting in better results along the processing pipeline (although the manuscript does not explore further this notion)

On the "usability" side, the method is still CPU-based and is slower than standards in the field. This may pose significant limitations in practical work, although the authors are aware of this issue and are working on it.

Reviewer #2 (Public review):

Summary:

The authors present a new method, Unbend, for measuring motion in cryo-EM images, with a particular emphasis on more challenging in situ samples such as lamella and whole cells (that can be more prone to overall motion and/or variability in motion across a field of view). Building on their previous approach of full-frame alignment (Unblur), they now perform full-frame alignment followed by patch alignment, and then use these outputs to generate a 3D model of the motion. This model allows them to estimate a continuous, per-pixel shift field for each movie frame that aims to better describe complex motions and so ultimately generate improved motion-corrected micrographs. Performance of Unbend is evaluated using the 2D template matching (2DTM) method developed previously by the lab, and results are compared to using full-frame correction alone and to the leading local motion correction methods. Several different in situ samples are used for evaluation covering a broad range that will be of interest to the rapidly growing in situ cryo-EM community.

Strengths:

The method appears an elegant way of describing complex motions in cryo-EM samples and the authors present sound data that Unbend generally improves SNR of aligned micrographs as well as increases detection of particles matching the 60S ribosome template when compared to using full-frame correction alone and since review to the leading local motion correction methods. The authors also give interesting insights into how different areas of a lamella behave with respect to motion by using Unbend on a montage dataset collected previously by the group. There is growing interest in imaging larger areas of in situ samples at high resolution and these insights contribute valuable knowledge. Additionally, the availability of data collected in this study through the EMPIAR repository will be much appreciated by the field.

Weaknesses:

A major weakness was comparing this method to full-frame approaches only but this has since been addressed by the authors during review and Unbend is compared to MotionCor2, 3, CryoSPARC and Warp. The improvements here are smaller, generally it seems to perform on par with the above methods, but there are significant gains for certain samples (e.g. the M. pneumoniae sample). A comment from this reviewer about using an adaptive approach to decide if/when to proceed to the full Unbend pipeline, over full-frame alone, has been addressed by the authors.

Reviewer #3 (Public review):

Summary

Kong and coauthors describe and implement a method to correct local deformations due to beam induced motion in cryo-EM movie frames. This is done by fitting a 3D spline model to a stack of micrograph frames using cross-correlation-based local patch alignment to describe the deformations across the micrograph in each frame, and then computing the value of the deformed micrograph at each pixel by interpolating the undeformed micrograph at the displacement positions given by the spline model. A graphical interface in cisTEM allows the user to visualise the deformations in the sample, and the method is proved to be successful by showing improvements in 2D template matching (2DTM) results on the corrected micrographs using five in situ samples.

Impact

This method has great potential to further streamline the cryo-EM single particle analysis pipeline by shortening the required processing time as a result of obtaining higher quality particles early in the pipeline, and is applicable to both old and new datasets, therefore being relevant to all cryo-EM users.

Strengths

(1) The key idea of the paper is that local beam induced motion affects frames continuously in space (in the image plane) as well as in time (along the frame stack), so one can obtain improvements in the image quality by correcting such deformations in a continuous way (deformations vary continuously from pixel to pixel and from frame to frame) rather than based on local discrete patches only. 3D splines are used to model the deformations: they are initialised using local patch alignments and further refined using cross-correlation between individual patch frames and the average of the other frames in the same patch stack.

(2) Another strength of the paper is using 2DTM to show that correcting such deformations continuously using the proposed method does indeed lead to improvements, as evidenced by the number of particles found and the quality of the detections (measured using 2DTM SNR). This is shown using five in situ datasets, where local motion is quantified using statistics based on the estimated motions of ribosomes. The same analysis is performed using other deformation correction tools, with Unbend showing superior performance in terms of particle detected or 2DTM SNR of the detections.

Reviewer #2 (Public review):

Summary:

In this study, Bansal et al examine and characterize feeding behaviour in Anopheles stephensi mosquitoes. While sharing some similarities to the well-studied Aedes aegypti mosquito, the authors demonstrate that mated-females, but not unmated (virgin) females, exhibit suppression in their blood-feeding behaviour after imbibing an initial bloodmeal. Using brain transcriptomic analysis comparing sugar fed, blood fed and starved mosquitoes, several candidate genes potentially responsible for influencing blood-feeding behaviour were identified, including two neuropeptides (short NPF and RYamide) that are known to modulate feeding behaviour in other mosquito species. Using molecular tools including in situ hybridization, the authors map the distribution of cells producing these neuropeptides in the nervous system and in the gut. Further, by implementing systemic RNA interference (RNAi), the study suggests that both neuropeptides (particularly in the brain, but not in the abdomen since knockdown outside the brain did not affect feeding behaviour) appear to promote blood-feeding while having no impact on sugar feeding. Interestingly, when either of these two neuropeptide gene transcripts were reduced independently by RNAi, the proportion of females acquiring a blood meal was not affected, whereas simultaneous knockdown of both sNPF and RYa led to a reduction in blood feeding behaviour but did not impact sugar feeding.

Given that the expression of both neuropeptide genes was found in mostly in non-overlapping brain neurons, this suggests that these two neuropeptides may elicit at least partially complementary actions promoting blood feeding in A. stephensi. Indeed, their putative receptors appear to be colocalized within several neurons within the brain, which could explain why knockdown of both sNPF and RYa transcripts was required to affect blood feeding behaviour (although authors could not confirm if either of these neuropeptides act independently as only partial knockdown was achieved in the brain). Finally, while sNPF was mapped to brain neurons and midgut enteroendocrine cells, the authors mapped RYa only in the brain while reporting expression in the abdomen by qPCR, but that was not localized to the midgut EECs (like sNPF). Therefore, the source of RYamide in the abdomen remains unknown in this mosquito species, but could involve the abdominal ganglia where this neuropeptide has been localized in Ae. aegypti.

Strengths and/or weaknesses:

Overall, the manuscript was effectively communicated. Previous concerns and requested clarifications have been addressed in the revised manuscript. While advanced cell-specific tools are lacking in this mosquito species, one weakness here is that peptides could have been applied ectopically in attempts to rescue the deficit in blood feeding behaviour following knockdown by RNAi. Further insight in this regard may be provided in future studies by this and other research groups.

Reviewing editor comment:

Inclusion of a schematic in Supplementary Figure S9B addresses the point raised by reviewer 1 in the previous round.

Reviewer #1 (Public review):

Summary:

The authors aimed to investigate how short-term visual deprivation influences tactile processing in the primary somatosensory cortex (S1) of sighted rats. They justify the study based on previous studies that have shown that long-term blindness can enhance tactile perception, and aim to investigate the change in neural representations underlying rapid, short-term cross-modal effects. The authors recorded local field potentials from S1 as rats encountered different tactile textures (smooth and rough sandpaper) under light and dark conditions. They used deep learning techniques to decode the neural signals and assess how tactile representations changed across the four different conditions. Their goal was to uncover whether the absence of visual cues leads to a rapid reorganization of tactile encoding in the brain.

Strengths:

The study effectively integrates high-density local field potential (LFP) recordings with convolutional neural network (CNN) analysis. This combination allows for decoding high-dimensional population-level signals, revealing changes in neural representations that traditional analyses (e.g., amplitude measures) failed to detect. The custom treadmill paradigm permits independent manipulation of visual and tactile inputs under stable locomotion conditions. Gait analysis confirms that motor behavior was consistent across conditions, strengthening the conclusion that neural changes are due to sensory input rather than movement artifacts.

Weaknesses:

(1) While the study interprets the emergence of more distinct texture representations in the dark as evidence of rapid cross-modal plasticity, the claim rests on correlational data from a short-term manipulation and decoding analysis. The authors show that CNN-derived feature embeddings cluster more clearly by texture in the dark, but this does not directly demonstrate plasticity in the classical sense (e.g., synaptic or circuit-level reorganization). The authors have noted this as a limitation and have clarified that the observed changes reflect functional reorganization rather than structural plasticity.

(2) Although gait was controlled, changes in arousal or exploratory behavior in light versus dark conditions might play a role in the observed neural differences. The authors have controlled for various factors in relation to locomotion, but future studies would benefit from more direct behavioural readouts of arousal states (e.g., via pupillometry or cortical state indicators).

(3) It should be noted that the time course of the observed changes (within 10 minutes) is quite rapid, and while intriguing, the study does not include direct evidence that the underlying circuits were reorganized-only that population-level signals become more discriminable. The authors have adequately discussed this as an avenue for more mechanistic future research.

(4) The authors have adequately discussed that, while these findings are consistent with somatotopy and context-dependent dynamics, they do not provide strong independent evidence for novel spatial or temporal organization.

(5) The authors have also discussed that, while the neural data suggest enhanced tactile representations, the study does not assess whether rats' actual tactile perception improved. Future studies including an assessment of a behavioral readout (e.g., discrimination accuracy), would be insightful.

(6) The authors' discussion about the implications for sensory rehabilitation, including Braille training and haptic feedback enhancement was a bit premature, but they have amended this, and it remains an interesting translational potential to be explored in future studies.

(7) While the CNN showed good performance, more transparent models (e.g., linear classifiers or dimensionality reduction) appear to not exceed chance level. The implications of this are that there is an underlying complex structure in the LFPs that has yet to be fully uncovered, on the mechanistic level. This would be important to push the findings forward in future studies.

Therefore, while the authors raise interesting hypotheses around rapid plasticity, somatotopic dynamics, and rehabilitation, the evidence for each is indirect. Stronger claims will require future causal experiments, behavioral readouts, and mechanistic specificity beyond what the current data provides. However, the work represents an interesting starting point to a more mechanistic understanding in the future.

Reviewer #2 (Public review):

Summary:

Yamashiro et al. investigated how transient absence of visual input (i.e. darkness) impacts tactile neural encoding in the rat primary somatosensory cortex (S1). They recorded local field potentials (LFPs) using a 32-channel array implanted in forelimb and hindlimb primary somatosensory cortex while rats walked on smooth or rough textures under illuminated and dark conditions. Employing a convolutional neural network (CNN), they successfully decoded both texture and lighting conditions from the LFPs. The authors conclude that the subtle differences in LFP patterns underlie tactile representation surface roughness and become more distinct in darkness, suggesting a rapid cross-modal reorganization of the neural code for this sensory feature.

Strengths:

• The manuscript addresses a valuable question regarding how sensory cortices dynamically adapt to changes in sensory context.<br /> • The use of machine learning (CNNs) enables the analysis to go beyond conventional amplitude-based metrics, potentially uncovering subtle but meaningful effects.<br /> • The authors have substantially improved the manuscript with clearer figures, additional statistical analyses (including permutation tests and cross-validation), and greater methodological transparency.

Weaknesses:

• The new analyses (grand-average LFPs, correlation maps, wavelet decompositions, attribution-score correlations) improve transparency but do not yet clarify which specific neural features the CNN exploits, leaving the central interpretability question unresolved.<br /> • A plausible alternative explanation for the increased discriminability in darkness remains insufficiently ruled out: visually driven activity in the light condition (e.g., ambient illumination changes or self-motion-induced visual input) could contaminate S1 LFPs and account for the effect without reflecting a true neural representational change.<br /> • Behavioural and order controls have been improved but remain somewhat limited in sample size.

Overall assessment:

The revised manuscript is clearer, more transparent, and technically strengthened. However, the true nature of the signal changes underlying the observed differences in discriminability remains unclear, limiting the scientific strength of the conclusions. The possibility that visual interference contributes to the observed effects remains a plausible and untested alternative interpretation. Additional experiments or analyses quantifying visually evoked activity in S1 would be required to confirm the claim of genuine reorganization of neural representation depending on the illumination condition.

Reviewer #2 (Public review):

Summary:

An abundant literature documents molecular changes in the rodent hypothalamus that occur during the transition from prepubertal to mature reproductive physiology. Equally well documented is the role of sex steroids and their receptors during this important period of reproductive development, as well as the importance of GABAergic and glutamatergic neurons. The medial preoptic area (MPOA) is known to play a central role in expression of sexually dimorphic reproductive function and previously reported sexually dimorphic patterns of gene expression are consistent with this role. The present manuscript extends this knowledge base and reports the results of a detailed evaluation of transcriptional dynamics in the MPOA during the adolescent transition to maturity with a particular focus on the role of the estrogen receptor gene (Esr1). Both single cell RNA sequencing (scRNseq) and multiplex in situ hybridization methods were employed and the results subjected to detailed computational analyses to demonstrate that the transcriptomic structure of MPOA neurons displays both sex and cell type specific expression profiles. In addition, both hormonal and genetic manipulations of Esr1 signaling during puberty altered the transcriptional profiles of MPOA neurons, and these changes aligned with maturation of hormone-dependent reproductive function. The authors provide this evidence to illustrate Esr1-dependent control of gene regulatory networks required for normal expression of reproductive behaviors expressed during the transition from adolescence to adulthood. The results presented in this manuscript are extensive and represent the most comprehensive evaluation of transcriptomic changes during reproductive maturation to date. The methods appear strong and the results provide a rich data set that will support a good deal of future analysis.

Strengths:

(1) The major strength of this manuscript is the extensive set of images and graphs that illustrate molecular changes that occur in MPOA neurons during adolescence, although additional spatial detail as to locations of the source neurons would be welcome in order to place the changes in the proper circuitry context.

(2) Targeting Esr1 deletion to MPOA GABA neurons is a good choice, given how these cells have been implicated in sexual differentiation of reproductive behavior previously, and the lack of comparable responses in glutamatergic neurons is convincing. The AAV-frtFlex-Cre virus created by the investigators is a most useful tool for such studies. Profiling distinct transcriptomic trajectories in GABA and glutamatergic neurons during reproductive maturation is impressive and leads to some of the best supported conclusions in this paper.

(3) Cellular and molecular resolution of the transcriptomics data appears excellent, however, because the source tissue for the scRNAseq analysis was obtained by bulk dissection of the MPOA anatomical resolution is limited. This problem is addressed to some extent by careful comparison of scRNAseq results with previously published spatial transcriptomics data. The HM-HCR-FISH analysis clearly documents spatially restricted changes in gene expression, but it is hard to discern where these changes occur based on the images presented or the descriptions included in the Results. The anatomical schematic included in Figure 4 suggests that investigators are not familiar with components of the MPOA (see Allen Mouse Brain Atlas).

Weaknesses:

(1) A major conceptual flaw is that the authors do not distinguish between genetically determined sex differences in patterns of gene expression and differences caused by the fact that MPOA neurons are exposed to different endocrine environments in adolescent males and females, which can cause different transcriptional trajectories independent of genetic sex. This issue does not render their results invalid, but their terminology should address the issue in the discussion and "limitations" section. At the very least the endocrine status of "intact females" should be included.

(2) A major technical flaw is that the MPOA is treated as a functionally distinct brain region (block dissections) with uniform distribution of cell types (FISH data are not illustrated or reported with sufficient spatial detail). Thus, an enormous amount of molecular data is provided that cannot be mapped to distinct neural circuits, thereby limiting the neurobiological impact. This is also a weakness of the FISH data, which is presented with only small regions illustrated without anatomical detail. In fact, some images are compared that appear to illustrate different MPOA structures, although it is impossible to be certain of this due to the lack of morphological landmarks. The analysis of how Esr1 orchestrates regulatory gene networks is impressive and interesting, but the fact that many of the observed transcriptional events occur in neural circuits that do not overlap confounds interpretation.

(3) The locations of the AAV injections should be characterized because deleting Esr1 in multiple distinct parts of the MPOA will likely confound interpretation. This is especially problematic given the limited number of mice used for parts of the RNAscope analysis.

(4) Although the focus of these experiments on adolescence is welcome, neither the Introduction nor the Discussion do a good job of placing these studies in the context of what is already known about brain maturation during puberty. It is true that this is very much a results-focused manuscript, but the scholarship can be improved. Simply stating that your results are consistent with previous reports places an undue burden on the reader to go figure out what is new.

(5) Throughout the manuscript, the authors utilize obscure abbreviations, which often makes reading their text overly cumbersome. This is certainly justified in certain instances where complex names of analytical methods are used repeatedly, but the authors are encouraged to try and simply their use of non-standard abbreviations.

Comments on revisions:

The authors have considered issues raised during the initial review. Although there do not appear to be significant changes to analyses, figures or conclusions, the authors have added important revisions listing limitations in study design and methodology that impact interpretation.

Reviewer #3 (Public review):

The paper identifies effects of gonadal hormones within hormone-responsive GABAergic neurons in the MPOA. Although it is not surprising that hormones have effects on neurons that express hormone receptors, the current paper adds insights with higher cellular and spatial resolution than previous work and focuses on adolescence period. The paper also identifies a major role for Esr1-dependent mechanisms on behavior using an intersectional genetic strategy to ablate Esr1 in GABAergic or glutamatergic neurons in the MPOA.

The authors have thoughtfully addressed the reviews, in particular by focusing quantitative analyses on Vgat+Esr1+ clusters and adding important technical and conceptual considerations in the limitations section.

I have one remaining minor concern. I appreciate that the text now defines "transcriptional maturation". However, the term seems inappropriate when describing the "minimal transcriptional changes" in Vgat+hormone RLow clusters, which implies that they are transcriptionally immature. Do the authors mean to imply that transcriptional maturation is observed in Vgat+Esr1+ clusters but not Vgat+hormone RLow clusters? The authors also use the term "hormone-dependent transcriptional dynamics", which I think is more appropriate. For example, hormone-dependent transcriptional dynamics are observed in Vgat+Esr1+ clusters but not Vgat+hormone RLow clusters.

Reviewer #1 (Public review):

Summary:

Overall, this is an interesting and well-written manuscript on a fascinating question in a "charismatic" model system.

Strengths:

1) The Introduction is concise, though it might be helpful to the non-specialist reader to learn a bit more about what is known about the social control of somatic growth across diverse species (including humans), which would help to make this work more generally interesting.

(2) The experiment is well-designed.

(3) The data collected are comprehensive.

(4) The complementary analysis of both feeding and aggression/submission data with and without known social roles is a neat idea and compelling!

Weaknesses:

(1) I was surprised that the HPA/stress axis was not considered here at all. Wouldn't we expect that subordinates have increased stress axis activation, which in turn could inhibit their growth and aggressive behavior?

(2) To what extent are growth, food intake, agonistic behavior, and/or gene expression patterns coordinated across P1 vs P2 pairs? The lack of such an analysis seems like a missed opportunity.

(3) What was the rationale for using whole bodies for the transcriptome analysis? Given the hypotheses, the forebrain or hypothalamus and certain other organ systems (e.g., liver, gonads, skin, etc.) would have been obvious candidate tissues here. I realize that cost is always a consideration, but maybe a focus on the fore-/midbrain could have been prioritized.

(4) Given the preceding point, why was a fold-change threshold used for assessing DEGs (supplementary Figure 3)? There is no biological justification to ever use a fold-change threshold, especially in bulk RNA-seq analysis. This is particularly true here, where whole bodies were used for RNA-seq analysis, which is a bit unusual. Relatively small cell populations (such as hypothalamic neurons that regulate growth or food intake) may show substantial gene expression variation across social types, yet will be masked by the masses of other cells in the whole body sample. However, gene expression may still vary significantly, albeit the fold-difference may be small. I therefore suggest a reanalysis that omits any fold-change threshold.

(5) Why is the analysis of color (hue, saturation) buried in the supplementary materials? Based on the hypotheses that motivated the study, color seems just as relevant as food intake, growth, and agonistic behavior, so even if the results are negative, they should be presented in the main paper.

(6) The Discussion is sometimes difficult to follow. The authors may want to consider including a conceptual graphic that integrates the different aspects of growth and satiety regulation, etc., into a work-in-progress model of sorts, which would also facilitate clearer hypotheses for future research.

Reviewer #2 (Public review):

In this manuscript, the authors test growth, behavior, and gene expression in pairs of clownfish as they establish social dominance hierarchies, examining patterns of gene expression in these pairs after dominance has been established. The authors show solid evidence that emerging dominant clownfish show increased growth, aggression, and food consumption compared to their submissive or solitary counterparts, eventually adopting distinct gene expression profiles.

Major Comments:

(1) The Introduction is comprehensive, but it could be condensed. Likewise, the discussion could be condensed. There is considerable redundancy between the methods, the results, and the legend in Figure 1. The authors should consolidate and remove the redundancy.

(2) For Figure 3, the authors are showing PC2 and PC3; why is PC1 not shown? There is so much overlap between the three groups in PC2 vs PC3; it seems unlikely that researchers could conclusively identify any individual as belonging to a group based on the expression profile. The ovals shown do not capture all the points within each of the groups, and particularly the grey S oval seems misaligned with the datapoints shown.

(3) The authors indicate that the 15 replicates exhibiting the greatest size difference between P1 and P2 were selected for gene profiling. Does this mean that each of the P1 and P2 were pairs with each other? Have the authors tried examining the gene expression patterns in a paired manner? E.g., for the pairs that showed the greatest size differences, do they also show the greatest differences in gene expression? Do the P1s show the most extreme differences from P2s that also show the most extreme P2 differences? Perhaps lines on Figure 3A connecting datapoints from the P1 and P2 pairs would be informative.

(4) For the specific target pathways that are up- and downregulated in the different backgrounds, I recommend that the authors include boxplots (or heatmaps) showing the actual expression values for these targets. Figure 6 shows a heatmap for appetite-related genes, and it would be great to see a similar graph for the metabolism and glycolysis genes; it would also be informative to see similar graphs for hormonal and sexual maturation pathways as well.

(5) Particularly given that there is a relatively small number of genes enriched in the different rank conditions, I did not understand the need to do the WGCNA module analysis. I thought that an analysis of GO terms across the dataset would have been more meaningful than the GO term analysis shown in Figure 4, which considers only genes assigned to the "brown WGCNA module". This should be simplified or clarified.

(6) The authors say that they have identified coordinated changes in behaviors and the "underlying gene expression, leading to the emergence" of social roles. This is a little bit misleading, since the gene expression analysis occurred well after the behavioral and phenotypic differences emerged. Presumably, the hormonal and genetic shifts that actually caused the behavioral and phenotypic difference occurred during the weeks during which the experiment was underway, and earlier capture of the transcriptome would presumably reveal different patterns, and ones that would be considered more causative. The authors acknowledge this in 434-435, but it could be emphasized further.

(7) The authors have measured a number of differences between the different dominance classes of fish. All these differences were measured relative to the other classes, but in my view, the Solitary group was the closest to a baseline control. So I'm not sure that it is fair to say that "P2 and S individuals showed consistent downregulation of these genes and pathways" (line 401). I encourage the authors to emphasize the differences in gene expression from the "perspective" of the P1 individuals compared to the baseline of P2 and S individuals. Line 474 says that "P2 fish showed significant upregulation" of a number of pathways. It should be very clear what that is compared to (compared to P1, presumably?)

(8) Along the same lines, the authors say in line 514 that subordinates and solitaries strategically downregulate their growth. I'm not convinced that this is the case: I would consider this growth trajectory to be the default and the baseline. I would interpret that under certain social conditions, a P1 dominant pattern of growth, behavior, and gene expression is allowed to emerge.

Reviewer #3 (Public review):

Summary:

The authors tested the hypothesis that interactions among size- and age-matched rivals will lead to the emergence of social roles, accompanied by divergence in four aspects of individual phenotypes: growth, feeding behavior, fighting behaviors, and gene expression in clownfish.

Strengths:

The data on growth, feeding rate, and fighting behaviors support the authors' claims.

Weaknesses:

Gene analysis conducted in this study is not sufficient to clarify how the relevant genes actually regulate growth and behavior.

The information obtained from whole-body gene expression analysis is very limited. Various gene expression is associated with the regulation of fighting behaviors, food intake, growth, and metabolism, and these genes are regulated differently across tissues, even within a single individual. Gene expression analysis should be performed separately for each tissue.

Clownfish undergo sex change depending on social status and body size, as the authors mention in the manuscript. Numerous gene expressions are affected by sex change. It is unclear how this issue was addressed.

Reviewer #1 (Public review):

Summary:

In this study, the authors examine how a developmentally regulated cis-regulatory element controls SOX2 expression during neural differentiation of human stem cells. The results suggest that this highly conserved long-range enhancer mediates neural-specific SOX2 regulation and offer insight into the role of promoter-enhancer contacts in this process. Although the findings are interesting, several limitations need to be addressed.

Strengths:

A central question in developmental biology is how genes are regulated in a context-dependent manner. SOX2, a major pluripotency factor, is expressed in diverse tissues during development, and therefore understanding the mechanisms that control its spatiotemporal expression is critical. This study addresses this important question by examining the functional relevance of a neural-specific, developmentally regulated SOX2 enhancer and its associated promoter-enhancer contacts in driving gene expression during human neural development. Using multiple model systems and techniques, the authors test the requirement of this enhancer by analyzing SOX2 expression in mutant lines, providing evidence for its role in this process.

Weaknesses:

A key limitation of the study is the absence of data from homozygous SOX2 enhancer deletion, which leaves the analysis incomplete and tempers the conclusions that can be drawn. Furthermore, the suitability of teratomas as a model system is questionable, given their limited capacity to recapitulate the spatial patterning, regional specification, and organized developmental processes characteristic of the human forebrain. Finally, the manuscript remains largely descriptive with little mechanistic insight.

Reviewer #2 (Public review):

Summary:

The authors use a combination of genomics, genome conformation assays, and CRISPR-mediated deletion to study the transcriptional regulation of the SOX2 gene in human neural stem cells (hNSCs).

Strengths:

The authors show that two distal elements, located ~550kb downstream of the SOX2 gene, are important for SOX2 transcription in hNSC. They investigate both the deletion of these elements in established hNSCs and in hNSCs generated by differentiation of human pluripotent stem cells, suggesting these elements are important in both the establishment and maintenance of SOX2 expression in hNSCs.

Weaknesses:

Homologous elements have been studied in the mouse genome and have conserved function in mouse NSCs, yet these findings are not mentioned. Inclusion of biological replicates for the scRNA-seq and replicate CRISPR-deleted clones would strengthen the study.

Reviewer #1 (Public review):

Summary:

In this work, the authors investigate the mechanisms of low-frequency synaptic depression at cerebellar parallel fiber to interneuron synapses using unitary recordings that allow direct quantification of synaptic vesicle release. They show that sparse stimulation can induce robust synaptic depression even in the absence of substantial vesicle consumption, and that this depressed state is rapidly reversed when stimulation frequency is increased. To account for these observations, the authors propose a model in which low-frequency depression reflects a redistribution of vesicles within the readily releasable pool, in particular, a reduction in docking site occupancy due to vesicle undocking.

Strengths:

I found the experimental work to be of high quality throughout. The use of simple synapse recordings to count individual vesicle release events is particularly powerful in this context and allows questions to be addressed that are difficult to approach with more conventional approaches. The demonstration that low-frequency depression can occur independently of prior vesicle release, together with the rapid recovery observed during high-frequency stimulation, places strong constraints on possible underlying mechanisms and represents a clear strength of the study.

The modeling framework is clearly laid out and helps organize a broad set of observations across stimulation frequencies. Several of the experimental tests appear well-motivated by the model, including the recovery train experiments, the analysis of failures, and the use of doublet stimulation. Taken together, the data provide a coherent phenomenological description of low-frequency depression and its relationship to vesicle availability within the readily releasable pool.

Weaknesses:

While the experimental results are strong, the manuscript would benefit from rebalancing the strength of the mechanistic conclusions drawn from the modeling in light of its limitations. The framework is clearly useful and provides a coherent interpretation of the data, but it is not uniquely constrained by the experimental observations, and alternative models or interpretations could plausibly account for the findings. The use of different model regimes concatenated across time, with substantially different parameter values, highlights the abstract nature of the approach. For these reasons, the model seems best presented as one plausible explanatory framework rather than a definitive biological mechanism. Clarifying the distinction between data-driven observations and model-based inferences would help readers assess which conclusions are strongly supported and which remain more speculative.

The interpretation of the Ca2+-related experiments would benefit from more cautious wording. The absence of detectable changes in presynaptic Ca2+ signals does not exclude more localized or subtle Ca2+-dependent mechanisms, and conclusions regarding Ca2+ independence should therefore be framed accordingly. In addition, while low-frequency depression is still observed at reduced extracellular Ca2+, these experiments appear less diagnostic of the specific model-derived mechanism emphasized elsewhere in the manuscript - namely, a selective reduction in docking-site occupancy - and should be discussed with appropriate qualification in the text.

Major points:

(1) Clarify and qualify mechanistic claims derived from the model.

Throughout the manuscript, changes in model parameters are at times described as if they directly reflected underlying physiological mechanisms. As a result, the conceptual distinction between experimentally observed phenomena, model-derived variables, and biological interpretation is not always clear. Several conclusions in the Results and Discussion are phrased as mechanistic statements, although they rest on assumptions intrinsic to the modeling framework. The authors should systematically review the text and explicitly distinguish between (i) experimentally observed changes in synaptic responses and (ii) inferences about vesicle docking states or transitions within the model.

In particular, statements implying that vesicle undocking is the mechanism underlying low-frequency depression should be rephrased to reflect that this is an interpretation within the proposed framework rather than a uniquely demonstrated biological process. For example, statements such as "Low-frequency depression is caused by synaptic vesicle undocking" should be replaced with formulations such as "Within the framework of our model, low-frequency depression is accounted for by a redistribution of synaptic vesicles away from docking sites" or "Our results are consistent with a model in which changes in vesicle docking-state occupancy contribute to low-frequency depression."

A particularly problematic example is the statement that "these experiments further confirm that LFD only involves a decrease in δ, without accompanying changes in ρ or IP size." Here, an experimentally defined phenomenon (LFD) is directly equated with changes in model-derived variables. Such statements should be revised to make clear that δ, ρ, and IP size are inferred quantities within the model, and that the experimental data are interpreted through this framework rather than directly confirming changes in these parameters. Similarly, over-generalizing statements such as "Undocking therefore represents the key mechanism controlling short-term depression across stimulation frequencies" should be softened to reflect that this conclusion emerges from the model rather than from direct experimental evidence.

(2) Address the biological interpretation of time-dependent model regimes.

The model relies on distinct parameter regimes applied at different time points, with some transitions effectively suppressed in certain regimes. While this approach captures the data well, its biological interpretation remains unclear. The authors should either (i) expand the discussion to outline plausible biological processes that could give rise to such regime changes (for example, calcium-dependent modulation of transition rates or activity-dependent changes in vesicle state stability), or (ii) more explicitly frame this aspect of the model as a descriptive abstraction rather than a mechanistic proposal. This further underscores the need to clearly separate the descriptive role of the model from claims about underlying biological mechanisms.

(3) Reframe conclusions drawn from calcium-related experiments.

The calcium imaging data demonstrate no detectable changes in the measured presynaptic calcium signals under the tested conditions, but they do not rule out that calcium signals contribute in ways undetectable by the assay. Conclusions should therefore be revised to reflect this limitation, avoiding statements that exclude a role for calcium-dependent mechanisms. Wording such as "we did not detect evidence for..." would be more appropriate than conclusions implying the absence of an effect.

Similarly, while low-frequency depression is still observed at reduced extracellular calcium (1.5 mM Ca²⁺), the specific mechanistic signature emphasized elsewhere in the manuscript - namely a selectively reduced first response during a high-frequency recovery train - is no longer apparent. These experiments should therefore be discussed as consistent with the proposed framework, but not as providing independent support for a selective reduction in docking-site occupancy. Explicitly acknowledging this limitation would improve clarity and avoid over-interpreting these data.

(4) Soften interpretations based on non-significant comparisons.

In several places, comparisons that do not reach statistical significance are used to argue for equivalence between conditions (for example, comparisons involving failure versus non-failure trials or different LFD conditions). These conclusions should be revised to emphasize the limits of statistical power and framed as a lack of evidence for a difference rather than evidence of independence.

Reviewer #2 (Public review):

Summary:

Silva and co-workers exploit their previously established methods of analyzing release events at single parallel fiber to molecular layer interneuron synapses. They observed synaptic depression at low transmission frequencies (< 5 Hz), which rapidly recovers during high-frequency transmission. Analysis of the time course of low-frequency depression revealed an initial rapid and a slow linearly increasing time course. Strikingly, the initial depression occurred even in the absence of preceding release, arguing against vesicle depletion as the underlying mechanism.

Strengths:

The main strength of the study is the careful demonstration of an interesting synaptic phenomenon challenging the classical vesicle-centered interpretation of synaptic depression.

Weaknesses:

No major weaknesses were identified by this reviewer.

The finding of release-independent synaptic depression is important and would have widespread implications. Therefore, some more analyses to increase the confidence in these findings could be performed.

My concern is whether rundown could explain the findings. If the rate of failures in s1 increases and at the same time the amplitude decreases during the experiments, an apparent depression in s2 could arise. The Supplementary Figure 5A addresses run-down, but the figure is not easy to understand, and, as far as I understood, it does not address the question of whether the release-independent depression could be caused by a rundown. To address this, the analysis of Figure 5 could be repeated by investigating the failure rate and amplitude separately or by analyzing the 1st and 2nd half of the recordings separately.

Reviewer #3 (Public review):

Summary:

The manuscript builds on the observation that, at some synapses, low-frequency stimulation causes synaptic depression, which can be reversed by subsequent high-frequency stimulation. Such low-frequency depression (LFD) cannot be easily explained by the depletion of a single vesicle pool. Here, Silva and colleagues propose a model of activity-dependent vesicle trafficking to explain LFD at synapses between cerebellar granule cells and molecular layer interneurons.

Strengths:

Overall, LFD is interesting and worthy of examination, and the authors provide new experimental results that are of the high quality expected from this group.

Weaknesses:

The study proposes a novel model of vesicle trafficking that is not explained by known biological mechanisms, and the manuscript does not adequately compare or discuss alternative models.

I have several concerns about how the authors interpret the data. First, the manuscript's primary conceptual advance is the idea that LFD involves vesicle undocking, rather than depletion. However, most experiments were performed under conditions that promote vesicle depletion (3 mM extracellular Ca2+). When experiments were repeated in physiological Ca2+, there appeared to be little or no LFD (stats are not provided). Second, the RS/DS/DU/undocking model, though not outside the realm of possibility, is not readily explained by known mechanisms and is only loosely supported by experimental findings. Third, when simulating LFD, the authors do not compare alternative models and use inappropriate language to imply that a model fit represents the truth (e.g., "the finding of identical experimental and simulated values confirms that the undocking mechanism accounts for LFD"). Finally, the model is presented in an overly complicated manner. The sheer amount of terms and nomenclature makes the manuscript confusing and difficult to read. Overall, the manuscript would benefit from added experiments and more statistics, a better justification and evaluation of the model, and more nuanced language.

Major concerns:

(1) Most experiments were performed under conditions that exacerbate depletion

In order to attribute LFD to vesicle undocking rather than depletion, it is important to show LFD under conditions where depletion is minimal. As mentioned above, the authors only report significant LFD in elevated extracellular Ca2+. In a small number of experiments performed in more physiological Ca2+ (1.5 mM), there is no depression after a single stimulus, and it is not clear that there was statistically significant depression during a low-frequency train. Several studies cited in support of LFD share this problem:

• Abrahamsson et al., (2007) recorded from Schaffer collaterals in 4 mM Ca, 3-4X physiological Ca2+.

• Doussau et al., (2010) recorded from aplysia synapses in 3X Ca compared to seawater.

• Rudolph et al., (2011) is cited as an example of LFD. However, this study performed experiments at high release probability cerebellar climbing fibers, and reported depression that increased monotonically with

stimulation frequency, so it does not resemble the phenomenon studied in this paper. Lin et al., (2022) also largely describe monotonic depression at the calyx.

The authors note that their results differ from those of Atluri and Regehr, but do not mention that a possible reason for the difference is the increased release probability in their experiments.

The authors should provide statistics for the data obtained in 1.5 mM Ca, and discuss why LFD is increased in conditions that also elevate vesicle release probability.

(2) Lack of biological mechanisms supporting the model

The model is presented without compelling biological support. The evidence in support of vesicle undocking comes from experiments by the Watanabe lab, which showed fewer-than-expected docked vesicles under EM when cultured synapses were stimulated immediately prior to high-pressure freezing. Kusick et al were careful to note that these vesicles may have been lost to fusion.

The putative undocking Kusick describes is immediate (< 5 ms after stimulation), and was not shown to be Ca2+ sensitive. This manuscript describes "calcium-dependent undocking" that proceeds from 10 ms - 200 ms. Multiple studies from the Watanabe lab show that a single stimulus lowers the number of docked vesicles, and subsequently, there is a transient redocking of vesicles that can be blocked by EGTA or Syt7 knockout.

I also question the rationale for the authors' model that 2 vesicles are coupled in series to a single release site. Previous papers from this lab cited EM studies from frog and neuromuscular that showed filamentous connections between vesicles (do these synapses show LFD?). Here, the authors primarily cite their previous models to support their arguments. I encourage them to continue searching for ultrastructural evidence for 2-vesicle-docking-units and to cite such studies.

(3) Comparison to other vesicle models

The authors use overly assertive language to suggest that the model proves a mechanism. "Altogether, these results indicate that the slow phase of LFD ... reflects a δ decrease without significant changes in pr, in ρ or in IP size". Simulating data does not conclusively "indicate" the underlying mechanism, but the authors could state their data can be "explained by a model where..".

However, LFD does not require activity-dependent undocking. Instead, the phenomenon has been explained by high-release probability, paired with an activity-dependent increase in either docking or release probability (Chiu and Carter, 2024; Doussau et al., 2017). Does the new model do a better job of replicating some facet of the data? If multiple models can explain the same data, how can we determine which model is correct? The "Alternative Presynaptic Depression Mechanisms" should be expanded to discuss these issues.

Reviewer #1 (Public review):

Sensory hair cells of the inner ear convert mechanical sound vibrations into electrical signals through mechano-electrical transduction (MET), a process critically dependent on the specialized organization and lipid composition of their plasma membrane. Although the protein components of the MET complex are relatively well characterized, the role of the lipid environment remains poorly understood and often overlooked. Recent discoveries that core MET proteins TMC1 and TMC2 function as lipid scramblases, disrupting membrane lipid asymmetry, expose a significant gap in our understanding of how lipid homeostasis is regulated in hair cells and how membrane dynamics influence MET function.

In this study, the authors address this gap by identifying the P4-ATPase ATP8B1 and its chaperone TMEM30B as essential regulators of membrane lipid asymmetry in outer hair cells. They also generated HA-tagged knock-in mice to precisely localize the P4-ATPase ATP8B1 and its chaperone TMEM30B within outer hair cells, demonstrating their enrichment in stereocilia, and convincingly demonstrate that loss of these proteins causes phosphatidylserine externalization, hair cell degeneration, and hearing loss in mouse models, phenocopying defects observed in TMC1 mutant mice with constitutive scrambling activity. While these findings establish lipid flippase pathways as critical for hair cell survival and auditory function, they also raise important questions about the precise mechanisms linking lipid asymmetry disruption to MET dysfunction and hair cell pathology.

Overall, the data convincingly support the conclusion that ATP8B1-TMEM30B flippase activity is required to maintain stereocilia lipid asymmetry and auditory function. The study substantially advances understanding of how lipid homeostasis intersects with MET. However, several points require clarification to ensure that localization claims and mechanistic interpretations are fully supported by the presented data.

Revisions considered essential by this reviewer are:

(1) Figure 1D.<br /> The authors should clarify how the qPCR data were normalized and specify the reference (housekeeping) genes used. This information is necessary to evaluate the robustness and comparability of the gene expression data.

(2) Figure 1F.<br /> The lack of F-actin staining at the hair cell base raises the possibility that the permeabilization conditions may have limited antibody access to certain membrane regions. This is especially important given that the authors used a gentle permeabilization agent such as saponin to preserve membrane integrity. Because the authors conclude that ATP8B1 and TMEM30B are localized "almost exclusively to OHC bundles and the apical membrane, with minimal staining in the remaining plasma membrane," (line 128). Including co-labeling with a plasma membrane marker or more comprehensive F-actin visualization of lateral and basal regions would help ensure that the restricted localization is biological rather than technical. In the absence of such controls, the localization claim may be somewhat overstated and should be tempered accordingly.

(3) Figure 7B.<br /> Although quantification of ATP8B1-HA intensity at the bundle appears similar between WT and Cib2 KO samples, the representative image suggests that some bundles lack detectable labeling. To better capture phenotype variability, it would be helpful to include an additional quantification showing the fraction or number of bundles with detectable ATP8B1-HA signal in Cib2 KO mice.

(4) Lines 346-349.<br /> The manuscript suggests that IHCs lack stereocilia-enriched P4-ATPases. However, this conclusion is not directly supported by the presented data. The authors should either provide supporting localization or expression data for other P4-ATPases or soften the statement to indicate that no stereocilia-enriched P4-ATPases were detected under the conditions examined.

Recommendations:

(5) The authors convincingly demonstrate that TMEM30B loss results in ATP8B1 mislocalization. While not essential to the central conclusions, examining TMEM30B localization in ATP8B1 KO hair cells would clarify whether this interdependence is reciprocal, as described for other P4-ATPase-CDC50 complexes.

(6) Lines 359-374.<br /> The discussion of Annexin V labeling is careful and balanced. This paragraph would benefit from referencing other studies that showed minimal Annexin V labeling in healthy P6 organ of Corti, reinforcing that robust PS externalization in the present study is pathological rather than developmental.

(7) Lines 392-399.<br /> The proposed feedback model linking MET activity and ATP8B1-TMEM30B localization is compelling. The discussion could be strengthened by noting that in TMC1/2 double knockout hair cells, PS externalization is not observed, consistent with the idea that flippase activity becomes critical specifically when scrambling occurs. The mislocalization observed in Cib2 KO hair cells further supports the coupling between TMC-mediated scrambling and flippase-mediated membrane restoration.

Reviewer #2 (Public review):

Summary:

Prior work identified TMEM30B (knockout mice) as well as ATP8B1 (human genetics and mouse model), ATP8A2 (knockout mice), and ATP811A (human genetics) as relevant for hearing. The authors also reasoned that, given the recent discovery of TMC1 and TMC2's dual function as mechanotransduction channels of the inner ear and as lipid scramblases, a counterpart flippase should be in the sensory hair-cell stereocilia bundle where mechanotransduction happens. They use CRISPR/CAS to modify the endogenous mouse genes and add an HA tag at the N-terminus of the ATP8B1, ATP8A1, ATP8A2, and ATP11A proteins. Their experiments with these mice unambiguously localized ATP8B1 at the base of outer hair cell stereocilia bundles. Knockout of ATP8B1 results in loss of outer hair cells, deficient auditory function (ABR), and degeneration of outer hair cell stereocilia bundles. Similarly, hair cells from genetically modified mice with endogenous HA-tagged TMEM30B proteins show localization of this protein to outer hair cell stereocilia bundles. TMEM30B knock-out mice phenocopy the ATP8B1 knock-out model. Interestingly, the authors show that annexing V staining precedes hair cell loss in ATP8B1 and TMEM30B knockout mice and that proper localization of these proteins is lost in mice that lack CIB2, a protein essential for hair cell mechanotransduction.

Strengths:

(1) Use of knock-in HA-tagged proteins, rather than antibody staining, to unambiguously localize ATP8B1 and TMEM30B.

(2) Systematic characterization of auditory function (ABR), hair cell loss, and hair-cell stereocilia bundle morphology.

(3) Advances our understanding of the role played by lipid homeostasis in auditory function.

(4) Reports on mouse models that will be helpful to further understand the mechanistic role played by ATP8B1 and TMEM30B in normal hearing and hereditary deafness.

Weaknesses:

(1) Are the HA tags causing any functional issues? Function and localization of tagged proteins can sometimes be compromised. It would be good to know, for each knock-in model (TMEM30B, ATP8B1, ATP8A1, ATP8A2, and ATP11A ), whether the HA-tagged protein is causing any issues with the mice and particularly with hearing (ABRs). Are these mice normal? Can they hear? These data are missing.

(2) Following on the point above, is it possible that ATP8B1-HA is well localized, but localization for the other three flippases (ATP8A1-HA, ATP8A2-HA, and ATP11A-HA) is compromised by the tag? Is this potential mislocalization causing any functional phenotypes? (ABRs of point 1). I find it surprising that there are flippases only in outer hair cells, and only formed by ATP8B1. A possible explanation is that the tag is interfering with trafficking. If so, there should be a phenotype (ABRs), although this might be masked by redundancy among these flippases or caused by systemic issues (admittedly difficult to sort out). Given that this manuscript will likely become foundational, and that there is evidence that at least two of the other flippases are involved in hearing loss, it would be good to provide more information about the mice and HA-tagged proteins in the other knock-ins (ATP8A1-HA, ATP8A2-HA, and ATP11A-HA). Depending on the data available for the knock-ins, the authors may want to discuss these scenarios and soften the statement indicating that inner-hair cells may lack flippase activity altogether.

(3) Expression of ATP8B1 at P0 (Figure 1D), when there should not be protein in outer hair cells yet, seems high. Does this mean that other cells in the cochlea also express ATP8B1? Is this a concern?

(4) Fluorescence scales in Figure 6 B and D and Figure 7 B and D are very different. So are the values for WT. One would expect that the WT would be similar in all cases (at least within the same compartments), given that the methods section indicates that "All images were collected using identical acquisition parameters, including zoom and laser power, across genotypes". If WT shows such variability, how can we compare?

Reviewer #1 (Public review):

Summary:

This paper examines plasticity in early cortical (V1-V3) areas in an impressively large number of rod monochromats (individuals with achromatopia). The paper examines three things:

(1) Cortical thickness. It is now well established that early complete blindness leads to increases in cortical thickness. This paper shows increased thickness confined to the foveal projection zone within achromats. This paper replicates work by Molz (2022) and Lowndes (2021), but the detailed mapping of cortical thickness as a function of eccentricity and the inclusion of higher retinotopic areas is particularly elegant.

(2) Failure to show largescale reorganization of early visual areas using retinotopic mapping. This is a replication of a very recent study of Molz et al. but I believe, given anatomical variability, the larger n in this study, and how susceptible pRF findings are to small changes in procedure, this replication is also of interest.

(3) Connective field modelling, examining the connections between V3-V1. The paper finds changes in the pattern of connections, and smaller connective fields in individuals with achromatopsia than normally sighted controls, and suggests that these reflect compensatory plasticity, with V3 compensating for the lower resolution V1 signal in individuals with achromatopsia.

This is a carefully done study (both in terms of data collection and analysis) that is an impressive amount of work.

*Effects of eye-movements

The authors have carried out the eye-movement analyses I asked of them. Unfortunately, in 4 individuals they couldn't calibrate the eyetracker (it's impressive they managed in 10). I think this means that 4 of 13 (since a different participant was excluded from head motion) individuals weren't included in correlation analyses. Limiting the correlation analysis to individuals with better fixation has obvious issues. I'd recommend redoing (or additionally including) stats using non-parametric measures while classifying these 4 as having fixation instability of 3 (i.e. greater instability than the participant with the worst fixation who was successfully calibrated).

*Interpreting pRFs

The paper would be strengthened by a little more explicit clarity about what pRFs represent and how that affects their interpretation of their findings as plasticity vs. non-plasticity (I know the authors are aware of this, but I think it would be helpful for readers who are less experienced in pRFs). In the introduction it would be helpful to point out that pRFs represent the collective response of a large population of neurons, and as a result pRF estimates can vary depending on which population of neurons that stimulus drives.

For example, imagine for the sake of argument that rods only project to V1 neurons with larger receptive fields. If one measured pRFs in a control observer under phototopic vs. scotopic conditions one would see smaller pRFs in the photopic conditions. This wouldn't represent 'plasticity' - it would represent the fact that the firing neurons contributing to the pRF signal are a slightly different population because of a change in the stimulus content. This is of course exactly what you see in 2C. And indeed, the authors make this identical point ". In the non-selective condition, the smaller pRFs in controls are in line with the higher spatial resolution of the<br /> cone system, which is not active in the achromat group." But this point would be clearer if more of the conceptual underpinnings were made explicit in the introduction (or at this point in the paper).

Shifts in which population of neurons drive your pRFs can explain main of the more puzzling results in the paper without detracting from your main conclusions. For example, in 2D, I don't think it's differences in S/N driving your results (pRFs are at least theoretically meant to be robust to S/N). If smaller RFs 'drop out' under low luminance and these smaller RFs also tend to be more central, then one would expect the control results of 1D. And I think a similar argument might even be made for the smaller difference in the rod monochromats.

It would be possible to make the point of Figure 4B more simply if Figure 4B was replaced by additional Panels in Figure 2 simply showing V3 pRF sizes/eccentricity distributions. That would make the point that you don't see the same expansion in pRF sizes in V3 in a way that is just as clear, and is closer to the data.

*Interpreting cRFs

Similarly, I think the paper would be improved with more clarity about the underlying signal in CF modeling. Once again, I appreciate that the authors are familiar with this, but it will help the reader in interpretation. (And I do believe thinking carefully about this may alter your interpretations). CF receptive fields 'find' the region in V1 that best predict the V3 signal in a given voxel. In resting state this likely represents a combination of:

(1) visually driven signal - correlations that may or may not reflect connectivity but represent the fact that regions that represent the same region of visual space will be active at the same time.

(2) global bilaterally symmetrical signal consisting of enhanced correlations between iso-eccentric regions (Raemaekers et al., 2014), which may arise from vasculature that symmetrically stems from the posterior cerebral artery (Tong et al., 2013; Tong and Frederick, 2014).

(3) intrinsic neural fluctuations that are more strongly correlated between connected neurons. These are likely quite weak compared to the other contributions.

I think if you ignore 2, (which is not likely to differ between rod mono and controls) and model 1 and 3, you might well see shifts in CFs towards the boundary of the scotoma - essentially the CF's location will be biased towards the region of V1 that has stronger correlations - which = the region which has a visual signal.

I do find convincing the argument that you don't see the same shift in controls in the rod-selective condition. So I think the results of 4A are fine. But a little more clarity about 'what's under the hood' in CF modeling would be nice.

*Interpreting the relationship between pRFs and cRFs

So there's something here that confuses me. We are all agreed that V3 pRF sizes are similar across RM and control. V1 pRFs are larger in RM. It feels intuitive that smaller CFs would compensate but I can't make it make sense to myself when I think it through. Each pRF represents a combination of receptive field location scatter and bandwidth. You want to argue that eccentricity mapping looks pretty normal, so there's no reason to think increased rf scatter, and I can believe that (though I do think this assumption should be discussed explictly).

So far I think we agree.

But let's think about what drives a CF during visual stimulation ... Specifically lets think about 'the pRF of the CF' (the region of visual space represented by the cluster of voxels in the CF). If pRFs for individual voxels in V1 are big, then the pRF for the CF is also going to be large. But we know that pRFs for V3 are normal size. So, the V3 CF will 'find' a smaller number of voxels in V1, in order to try to find the 'correct sized' CF pRF. Note that this explanation is very similar to yours. But doesn't require ANY 'intrinsic' connectivity. It's really just assuming the whole thing is driven by the visual signal and the CF size is determined by the ratio of the pRF sizes in V3 vs. V1.

One possible solution would be to regress out the visual stimulus and redo this analysis based on the residuals.

Reviewer #3 (Public review):

Summary:

This study addresses a long-standing question in visual neuroscience concerning how the human visual system balances stability and plasticity when sensory input is altered from early in life. Using achromatopsia as a model of lifelong cone deprivation, the authors examine whether early visual cortex undergoes retinotopic reorganization to compensate for the absence of foveal cone input, or whether canonical retinotopic organization is largely preserved. By combining fMRI-based population receptive field (pRF) mapping with connective field (CF) modelling, the authors characterize changes across multiple hierarchical stages of visual processing.

The main findings indicate that primary visual cortex (V1) shows no systematic remapping of the foveal projection zone, whereas extrastriate cortex, particularly V3, exhibits altered patterns of sampling from V1. The authors interpret these results as evidence for hierarchical adaptation, whereby downstream readout mechanisms adjust to make more efficient use of degraded rod-mediated input while preserving early-stage retinotopic organization.

Strengths:

A major strength of this work is the use of silent substitution to generate rod-selective stimuli. This approach enables a principled comparison between achromats and typically sighted controls by isolating rod-driven responses in both groups. In doing so, the study overcomes a key limitation of prior work, where differences in cortical organization could often be confounded by differences in photoreceptor class rather than reflecting neural reorganization per se. The inclusion of a rod-driven baseline in controls provides an important reference for distinguishing long-term adaptation from transient or stimulus-driven effects.

Another notable strength is the integration of CF modelling alongside conventional pRF mapping. While pRF analyses alone suggest enlarged receptive fields in V1, consistent with reduced spatial resolution, the CF analysis offers a more mechanistic account by revealing changes in how V3 samples information from the V1 surface. This multi-level modelling approach moves beyond descriptive accounts of cortical map structure and provides a framework for interpreting how downstream areas may adjust their integration strategies under conditions of altered input.

Weaknesses:

Although the study is methodologically strong, the central claims regarding stability and compensatory plasticity require clearer conceptual framing and stronger empirical support. Stability is primarily defined as the absence of large-scale retinotopic remapping in V1, yet the presence of significantly enlarged V1 pRFs indicates substantial tuning-level plasticity at the input stage; distinguishing topographic stability from functional reorganization would therefore strengthen the interpretation. Moreover, the proposed compensatory mechanism raises a signal-processing concern, as reduced downstream sampling (smaller CFs in V3) cannot restore spatial information lost due to coarse upstream representations, and may instead limit integration. The mechanistic link between altered CF properties and normalization of extrastriate pRFs is not directly tested, as group differences are not shown to covary across individuals or visual field locations. Finally, the interpretation of these changes as compensatory implies functional benefit, yet no behavioral or performance measures are provided to establish that the observed reorganization preserves or enhances visual function, leaving open whether these effects reflect adaptive optimization or passive downstream consequences of altered input.

Reviewer #1 (Public review):

Summary:

The paper presents a three-layered hierarchical model for simulating Drosophila larva locomotion, navigation, and learning. The model consists of a basic locomotory layer that generates crawling and turning using a coupled-oscillator framework, incorporating intermittency in movement through alternating runs and pauses. The intermediate layer enables navigation by allowing larvae to actively sense and respond to odor gradients, facilitating chemotaxis. The adaptive learning layer integrates a spiking neural network model of the Mushroom Body, simulating associative learning where larvae modify their behavior based on past experiences. The model is validated through simulations of free exploration, chemotaxis, and odor preference learning, demonstrating close agreement with empirical behavioral data. This modular framework provides a valuable advance for modeling of larva behavior.

Strengths:

Every modeling paper requires certain assumptions and abstractions. The main strength of this paper lies in its modular and hierarchical approach to modeling behavior, making connections to influential theories of motor control in the brain. The authors also provide a convincing discussion of the experimental evidence supporting their layered behavioral architecture. This abstraction is valuable, offering researchers a useful conceptual framework and marking a significant step forward in the field. Connections to empirical larval movement are another major strength.

Weaknesses:

While the model represents a conceptual advance in the field, some of its assumptions and choices fall behind state-of-the-art approaches. One limitation is the paper's simplified representation of larval neuromechanics, in which the body is reduced to a two-segment structure with basic neural control. Another limitation is the absence of an explicit neuromuscular control system, which would better capture the role of segmental central pattern generators (CPGs) and neuronal circuits in regulating peristalsis and turning in Drosophila larvae. Many detailed neuromechanical models, as cited by the authors, have already been published. These abstractions overlook valuable experimental studies that detail segmental dynamics during crawling and the larval connectome.

The strength of the model could also be its weakness. The model follows a subsumption architecture, where low-level behaviors operate autonomously while higher layers modulate them. However, this approach may underestimate the complexity of real neural circuits, which likely exhibit more intricate feedback mechanisms between sensory input and motor execution.

Reviewer #2 (Public review):

The paper proposes a hierarchically layer approach to larval locomotion, chemotaxis and learning. The model consists of a basic locomotor layer with two coupled oscillators, one for crawls and one for turns. The intermediate layer modulates the frequency and amplitude of tunings to enables chemotaxis. The higher layer, integrates a spiking neural network model of the Mushroom Body to modify the door valence in response to experience as during learning.

The model is compared to experimental data with a good degree of agreement. This modular framework provides a valuable advance for modeling larva behavior.

Strengths:

A novel multilayer level model that reflects current thinking of the neuronal organisation of motor control. The model is very useful to investigate the neuronal architecture of central pattern generators<br /> and higher order motor control circuits that could be linked to larval connectome data.

Weaknesses:

All the limitations of the model are discussed and therefore the paper perfectly fits its purpose.

Reviewer #1 (Public review):

Summary:

The authors describe the results of a single study designed to investigate the extent to which horizontal orientation energy plays a key role in supporting view-invariant face recognition. The authors collected behavioral data from adult observers who were asked to complete an old/new face matching task by learning broad-spectrum faces (not orientation filtered) during a familiarization phase and subsequently trying to label filtered faces as previously seen or novel at test. This data revealed a clear bias favoring the use of horizontal orientation energy across viewpoint changes in the target images. The authors then compared different ideal observer models (cross-correlations between target and probe stimuli) to examine how this profile might be reflected in the image-level appearance of their filtered images. This revealed that a model looking for the best matching face within a viewpoint differed substantially from human data, exhibiting a vertical orientation bias for extreme profiles. However, a model forced to match targets to probes at different viewing angles exhibited a consistent horizontal bias in much the same manner as human observers.

Strengths:

I think the question is an important one: The horizontal orientation bias is a great example of a low-level image property being linked to high-level recognition outcomes and understanding the nature of that connection is important. I found the old/new task to be a straightforward task that was implemented ably and that has the benefit of being simple for participants to carry out and simple to analyze. I particularly appreciated that the authors chose to describe human data via a lower-dimensional model (their Gaussian fits to individual data) for further analysis. This was a nice way to express the nature of the tuning function favoring horizontal orientation bias in a way that makes key parameters explicit. Broadly speaking, I also thought that the model comparison they include between the view-selective and view-tolerant models was a great next step. This analysis has the potential to reveal some good insights into how this bias emerges and ask fine-grained questions about the parameters in their model fits to the behavioral data.

Weaknesses:

I'll start with what I think is the biggest difficulty I had with the paper. Much as I liked the model comparison analysis, I also don't quite know what to make of the view-tolerant model. As I understand the authors' description, the key feature of this model is that it does not get to compare target and probe at the same yaw angle, but must instead pick a best match from candidates that are at different yaws. While it is interesting to see that this leads to a very different orientation profile, it also isn't obvious to me why such a comparison would be reflective of what the visual system is probably doing. I can see that the view-specific model is more or less assuming something like an exemplar representation of each face: You have the opportunity to compare a new image to a whole library of viewpoints and presumably it isn't hard to start with some kind of first pass that identifies the best matching view first before trying to identify/match the individual in question. What I don't get about the view-tolerant model is that it seems almost like an anti-exemplar model: You specifically lack the best viewpoint in the library but have to make do with the other options. I sort of understand the reasoning that this enforces tolerance of viewpoint variability, but I'm not clear on whether or not this is a version of face familiarity and recognition that the authors think has an analog in human visual processing.

I do think that this model is interesting in terms of the differential tuning it exhibits, but don't find it easy to align with any theoretical perspective on face recognition. Specifically, do the authors think there is a stage of face processing in which tolerance as they've operationalized it in the model is extant? What I'm looking for is a concrete description of the circumstances that the authors are saying lead to this kind of model potentially being a meaningful analog of face recognition. For example, is the idea that one may become familiar with a face in some very limited set of viewpoints and then be presented with that face in other views?

Alternatively, if the authors prefer to say that they simply thought this was a nice exercise in terms of identifying a different model and that it may not be a meaningful proxy for face recognition. I think that's fine, to be clear! I just still don't see anything in the text that convinces me of the ecological validity of this version of view-tolerance.

Reviewer #2 (Public review):

This study investigates the visual information that is used for the recognition of faces. This is an important question in vision research and is critical for social interactions more generally. The authors ask whether our ability to recognise faces, across different viewpoints, varies as a function of the orientation information available in the image. Consistent with previous findings from this group and others, they find that horizontally filtered faces were recognised better than vertically filtered faces. Next, they probe the mechanism underlying this pattern of data by designing two model observers. The first was optimised for faces at a specific viewpoint (view-selective). The second was generalised across viewpoints (view-tolerant). In contrast to the human data, the view-specific model shows that the information that is useful for identity judgements varies according to viewpoint. For example, frontal face identities are again optimally discriminated with horizontal orientation information, but profiles are optimally discriminated with more vertical orientation information. These findings show human face recognition is biased toward horizontal orientation information, even though this may be suboptimal for the recognition of profile views of the face.

One issue in the design of this study was the lowering of the signal-to-noise ratio in the view-selective observer. This decision was taken to avoid ceiling effects. However, it is not clear how this affects the similarity with the human observers.

Another issue is the decision to normalise image energy across orientations and viewpoints. I can see the logic in wanting to control for these effects, but this does reflect natural variation in image properties. So, again, I wonder what the results would look like without this step.

Despite the bias toward horizontal orientations in human observers, there were some differences in the orientation preference at each viewpoint. For example, frontal faces were biased to horizontal (90 deg) but other viewpoints had biases that were slightly off horizontal (e.g. right profile: 80 deg, left profile: 100 deg). This does seem to show that differences in statistical information at different viewpoints (more horizontal information for frontal and more vertical information for profile) do influence human perception. It would be good to reflect on this nuance in the data.

Comments on revisions:

I am happy with the response and changes to the comments in my review. The key findings from this study are: (1) that there is bias toward the use of horizontal information across all viewpoints for face recognition in humans using an old-new recognition task. (2) In contrast, the optimal information for matching faces varies as a function of viewpoint. The view-selective model shows horizontal information is dominant for frontal views and vertical information is dominant for profile views.

The data from the view-tolerant model is less easy to interpret as it doesn't fit with any theoretically plausible model of face recognition. It might be a useful model for a face matching task in which participants had to match unfamiliar faces across viewpoints. This might be a possible extension of the current work.

Nonetheless, I still think this is an interesting contribution to the literature.

Reviewer #1 (Public review):

Summary:

This brief piece by Swartz and colleagues outlines the complexities surrounding the choice of clinical specialty for physician-scientists. It is, in general, clear and well-written, and it will be useful to research-oriented medical students choosing a path and to the mentors who are guiding them.

Strengths:

The writing is clear. The points made are not profound, but they are important and will be of use to the intended audience.

Weaknesses:

I have only minor suggestions for improvement. There are some areas of redundancy where the article could be tightened up by consolidating.

Reviewer #2 (Public review):

Summary:

This article is a useful compendium of advice for MD/PhD students (and research-focused MD students) to consider when it is time to decide on a clinical field for residency training. The authors are a distinguished group of physician-scientists and program directors who are drawing on published data and their own experience as mentors to provide advice and resources to students about to make what can be a career-defining choice. It makes an effective argument for considering important differences between clinical fields in their ability to sustain research integration, provide mentorship, meet lifestyle expectations, and foster a long-term career as a research-focused physician-scientist.

Strengths:

(1) A lot has been written about physician-scientists as an endangered species. Given the important role that physician-scientists can play if they engage in research that is informed by experience in patient care, not nearly enough has been written about the choices that students make during training that can keep them on track or throw them off.

(2) The article provides not only general advice, but specific information in the 2 tables that can help trainees to weigh their priorities and consider their options.

(3) Among the best advice is to weigh clinical demands, maintenance of procedural skills, recognition of the impact of research time on salary, and the impact of high salaries on the tension between research effort and clinical effort in clinical departments, which is where most physician-scientists in academia are employed.

Areas for potential improvement:

(1) Some of the most useful pieces of advice are scattered through the text when they might be more impactful if focused. For example, what are the 4 or 5 most essential factors that someone in an MD/PhD or an MD program should weigh when they are deciding between clinical disciplines? There are also published data on the experience of past graduates in achieving a research-focused career in each clinical discipline. How should that data be applied by trainees? What are the factors that should be weighed in deciding where to work as a research-focused physician once training has been completed?

(2) Some clinical fields at academic institutions have proved to be much more hospitable to careers as research-focused physicians than others. Published data highlight the challenges. I believe the authors have tried very hard to present a balanced perspective, but in the process, they have, I believe, missed an opportunity to guide trainees and make them aware of what they should look for to avoid making a decision that may prove incompatible with their long-term goals.

(3) An issue that hasn't been raised: Where will be the jobs for physician-scientists who have an MD {plus minus} PhD and want to do research and discovery? How many openings will there be for physician-scientists in academia 5-10 years from now? In industry? How are recent events in Washington affecting the continuation of those jobs? Unfortunately, I am not aware of labor statistics for physician-scientists, but perhaps the authors can find them.

(4) Additional questions that can be raised and addressed in the article: Should one of the "smart choices" in the article's title be where you do the residency, and not just which residency you do? How important is it to be at a successful, research-intensive medical center/university, both during and after residency and fellowship training? If being in an institution where there are numerous very successful physician-scientists and scientists improves the likelihood of being able to sustain a physician-scientist career, how should graduating students improve their chances of being at one of those institutions?

(5) In every clinical discipline, there are departments that value physician-scientists more than other departments and invest accordingly. What advice would the authors give to help graduating students identify those departments?

Reviewer #1 (Public review):

This paper investigates how different learning curricula influence the way that humans piece together directly experienced transitions into a broader cognitive map. When adjacent learning trials were grouped within rows or columns of the map, subsequent navigation through the map was weaker than when adjacent learning trials came from disjoint spaces in the map. The authors speculate that the grouped curriculum resulted in mental fragmentation that made navigation across space more difficult later on.

This is an interesting paradigm that contributes useful new findings in the domain of map learning to the growing literature on curriculum learning. The evidence for a difference between conditions is highly compelling, but, as the authors are very transparent in acknowledging in the Discussion, the evidence for their proposed mechanism - mental fragmentation under grouped learning - is somewhat weak. The study thus presents an intriguing empirical result but not an ironclad mechanistic account.

An alternative - by their account, "less interesting" - explanation is that grouped learning was easier because trials in close succession had overlapping elements, and so participants were not trying as hard or as engaged. There is a literature on spaced (as opposed to massed) learning being better for subsequent memory because it increases retrieval effort. It seems very plausible that this could be going on here, and the control experiment reported in the supplement would not help to rule this out. This literature deserves some discussion.

The Introduction focuses entirely on literature showing advantages in grouped over intermixed learning, setting that up as the most well-motivated expectation from the literature. Upon finding the opposite, the Discussion then mentions that interleaving has been found to be useful in "applied domains", but then returns to how surprising this is in light of recent findings in the category learning literature. But there is a substantial earlier literature on interleaved vs blocked curricula in category learning, very often finding advantages for interleaving. See, e.g., Carvalho & Goldstone, 2015, for a review. There is also a paper showing interleaving advantages in associative inference, Zhou et al., 2023, JEP:G, which is very relevant to several of the discussion section paragraphs. Thus, the treatment of the prior curriculum learning literature is currently sparse.

Reviewer #2 (Public review):

I think this paper is an excellent and timely contribution. It clearly shows that learning overlapping relationships in a disjoint training schedule (where the overlaps are not encountered close together in time) appears to aid the formation of an integrated associative memory structure (a cognitive map) and supports generalisation. I believe the methods are sound and the results are clear. I only have a couple of methodological questions that may not warrant any changes to the paper (or only very minor changes/additions):

(1) The mixed effects models did not include random slopes for the within-subject factors ("spatial manipulation" and "block"), and so the corresponding fixed effect inferences may be unsafe. Having said that, it is likely that including these slopes may not be warranted given their contribution to the model's fit. I recommend that the authors check this.

(2) The mixed effects models for accuracy appear to model average performance across trials rather than using a generalised linear model with a (e.g.) logit link function and the binomial distribution to characterise performance. I think this is a little sub-optimal, as the latter is often more sensitive. Nonetheless, it is not in any way wrong; the results are clear enough as is, and there may be a good reason to avoid a non-linear link function, which can alter the interpretation of effects close to the ceiling and floor.

I think the introduction and/or discussion would benefit from contrasting their results with Berens & Bird (2022, PLOS Comp Bio). In this paper, it is shown that blocking the training of discriminations in a linear hierarchy (what we call progressive training) substantially benefited transitive inference performance. This seems at odds with the author's finding that "participants struggle to integrate information across rows and columns, i.e. across groups of transitions that were trained separately in time".

I would really like to know what the authors think about this discrepancy (or, indeed, whether they think there is one at all). Is it possibly because "progressive" learning is some combination of "grouping", "blocking" and "chaining" (where there is a structured overlap between adjacently trained relationships)? Or is it something else, e.g., that there is a fundamental difference between learning associations and discriminations (personally, I lean on this explanation)?

Relevant to this, the authors note that their "findings do contradict recent reports from the category learning literature, where blocking seems to help learning and generalisation (Dekker et al., 2022; Flesch et al., 2018; Noh et al., 2016). It may be that where the goal is not to learn a complex knowledge structure - like a map - but simply to compress exemplars by mapping them onto a smaller number of labels - the benefits of blocking emerge." However, the benefit of progressive (blocked) training in my own work was observed in a task that required learning a complex/relational structure in the form of a transitive hierarchy, which theoretical accounts suggest depends on learning map-like representations (Whittington et al., 2020).

Reviewer #3 (Public review):

Summary:

This study examines how training regimes influence the formation of cognitive maps. Participants learned two relational maps over three days through pairwise transitions: one map was trained with grouped sequences that followed rows or columns, while the other was trained with disjoint transitions sampled randomly across the map. In addition, the study manipulated the temporal spacing of training blocks (blocked vs. semi-blocked) and tested whether the results generalized across two map geometries (a 5×5 grid and a 4×4 torus).

Furthermore, they run a follow-up experiment (or condition) testing rows and columns shuffled in the grouped condition.

While grouped training produced better performance during learning, the authors report that disjoint training led to superior performance at test on tasks probing the global map knowledge.

Summarising experimental design:

(1) Map geometry (between-subjects): 5×5 grid vs 4×4 torus

(2) Training block schedule (between-subjects): Blocked vs Semi-blocked

(3) Training regime/transition sampling (within-subject): Grouped or Disjoint (Day 1 and Day 2)

Strengths:

The study addresses a clear and timely theoretical question about how the training regime affects the formation of cognitive maps. A further strength is the well-controlled experimental design, allowing the authors to test their hypotheses in a systematic and informative way.

Weaknesses:

(1) If I understood correctly, participants learned one map on the first day and the other on the second day, with the training regime (grouped vs. disjoint) counterbalanced across maps. This raises the possibility that experience with one training regime on day one could influence performance on the second day. For example, it would be interesting to examine whether participants who experienced the disjoint regime first showed any differences when learning the grouped regime on the following day. While it may be difficult to fully disentangle such transfer effects from the main training regime effects, it would be informative to test whether performance on the second day depends on the regime experienced on the first day (e.g., whether prior exposure to the disjoint regime predicts performance on the subsequent grouped training, but not vice versa).

(2) The author mentions a control experiment. Did the participants in the control experiment complete only the training phase or also the testing tasks used in the main experiment? If testing was included, it would be informative to report whether performance at test was comparable to that observed in the main experiment. Given that this condition appears to involve blocked transitions while moving across both rows and columns, I would expect performance to fall somewhere between the grouped and disjoint conditions.

(3) Participants' performance did not differ between conditions in the map reconstruction task, suggesting that participants in both the grouped and disjoint regimes were ultimately able to form a cognitive map. Was this task always administered last during the testing session? I wonder whether the explicit request of the reconstruction task could have influenced participants' awareness of the map structure.

(4) The manuscript describes the study as consisting of four experiments (two groups per map shape, differing in the blocked versus semi-blocked schedule). However, based on the design described in the Methods, this appears more accurately characterized as a single experiment with two between factors: map geometry (grid vs. torus) and blocking schedule (blocked vs. semi-blocked) manipulated between participants, and training regime (grouped vs. disjoint) manipulated within participants.

(5) It is not entirely clear to me from the Results section whether performance at test differed between the two map geometries (grid and torus), or whether the reported effects of training regime were consistent across them.

Reviewer #1 (Public review):

Summary:

This work aims to elucidate the molecular mechanisms affected in hypoxic conditions causing reduced cortical interneuron migration. They use human assembloids as a migratory assay of subpallial interneurons into cortical organoids and show substantially reduced migration upon 24 hours hypoxia. Bulk and scRNA-seq shows adrenomedullin (ADM) up-regulation, as well as its receptor RAMP2 confirmed at protein level. Adding ADM to the culture medium after hypoxic conditions rescues the migration deficits, even though the subtype of interneurons affected is not examined. However, the authors demonstrate very clearly that ineffective ADM does not rescue the phenotype and blocking RAMP2 also interferes with the rescue. The authors are also applauded for using 4 different cell lines and using human fetal cortex slices as an independent method to explore the DLXi1/2GFP-labelled iPSC-derived interneuron migration in this substrate with and without ADM addition (after confirming that also in this system ADM is up-regulated). Finally, the authors demonstrate PKA - CREB signalling mediating the effect of ADM addition, and also lead to up-regulation of GABAreceptors. Taken together this is a very carefully done study on an important subject - how hypoxia affects cortical interneuron migration. In my view it would be of great interest for the readers of Elife.

Strengths:

Its strengths are the novelty and the thorough work using several culture methods and 4 independent lines.

Weaknesses:

The main weakness is that we dont know which interneuron subtypes are most affected by hypoxia and which may be rescued in their migration by ADM.

A further weakness is that the few genes confirmed to be regulated after hypoxia do not help determining which statistical cut-off can be considered reliable, given that they didn't compare strongly regulated versus weakly regulated genes.

Comments on revisions:

Unfortunately, the authors did not address my suggestions. While they show example stainings of interneuron subtypes, they do not show if Calretinin, calbinin or somatostatin+ interneurons are differentially affected by hypoxia or the rescue with ADM. I still consider this an important piece of information to add.

Reviewer #2 (Public review):

Summary:

The manuscript by Puno and colleagues investigates the impact of hypoxia on cortical interneuron migration and downstream signaling pathways. They establish two models to test hypoxia, cortical forebrain assembloids and primary human fetal brain tissue. Both of these models provide a robust assay for interneuron migration. In addition, they find that ADM signaling mediates the migration deficits and rescue using exogenous ADM. The findings are novel and very interesting to the neurodevelopmental field, revealing new insights into how cortical interneurons migrate and as well, establishing exciting models for future studies.The authors use sufficient iPSC lines including both XX and XY, so analysis is robust. In addition, the RNAseq data with re-oxygenation is a nice control to see what genes are changed specifically due to hypoxia. Further, the overall level of valiation of the sequencing data and involvement of ADM signaling is convincing, including the validation of ADM at the protein level. Overall this is a very nice manuscript. I have a few comments and suggestions for the authors.

Strengths/Weaknesses:

(1) Can they comment on the possibility of inflammatory response pathways being activated by hypoxia - has this been shown before? While not the focus of the manuscript, it would be discussed in the Discussion as an interesting finding and potential involvement of other cells in the Hypoxic response.

(2) Can they comment on the mechanism at play here with respect to ADM and binding to RAMP2 receptors - is this a potential autocrine loop, or is the source of ADM from other cell types besides inhibitory neurons? Given the scRNA-seq data, what cell-to-cell mechanisms can be at play? Since different cells express ADM, there could be different mechanisms at place in ventral vs dorsal areas.

(3) For data from Figure 6 - while the ELISA assays are informative to determine which pathways (PKA, AKT, ERK) are active, there is no positive control to indicate these assays are "working" - therefore, if possible, western blot analysis from assembloid tissue could be used (perhaps using the same lysates from Fig 3) as an alternative to validate changes at the protein level (however, this might prove difficult); further to this, is P-CREB activated at the protein level using WB?

(4) Can the authors comment further on the mechanism and what biological pathways and potential events are downstream of ADM binding to RAMP2 in inhibitory neurons? What functional impact would this have linked to the CREB pathway proposed? While the link to GABA receptors is proposed, CREB has many targets beyond this.

(5) Does hypoxia cause any changes to inhibitory neurogenesis (earlier stages than migration?) - this might always be known but was not discussed.

(6) In the Discussion section - it might be worth detailing to the readers what the functional impact of delayed/reduced migration of inhibitory neurons into the cortex might results in, in terms of functional consequences for neural circuit development

Comments on revisions:

The authors have addressed my comments thoroughly. I have no further comments or suggestions

Reviewer #3 (Public review):

Summary:

The authors aimed to test whether hypoxia disrupts the migration of human cortical interneurons, a process long suspected to underlie brain injury in preterm infants but previously inaccessible for direct study. Using human forebrain assembloids and ex vivo developing brain tissue, they visualized and quantified interneuron migration under hypoxic conditions, identified molecular components of the response, and explored the effect of pharmacological intervention (specifically ADM) on restoring the migration deficits.

Strengths:

The major strength of this study lies in its use of human forebrain assembloids and ex vivo prenatal brain tissue, which provide a direct system to study interneuron migration under hypoxic conditions. The authors combine multiple approaches: long-term live imaging to directly visualize interneuron migration, bulk and single-cell transcriptomics to identify hypoxia-induced molecular responses, pharmacological rescue experiments with ADM to establish therapeutic potential, and mechanistic assays implicating the cAMP/PKA/pCREB pathway and GABA receptor expression in mediating the effect. Together, this rigorous and multifaceted strategy convincingly demonstrates that hypoxia disrupts interneuron migration and that ADM can restore this defect through defined molecular mechanisms.

Overall, the authors achieve their stated aims, and the results strongly support their conclusions. The work has significant impact by providing the first direct evidence of hypoxia-induced interneuron migration deficits in the human context, while also nominating a candidate therapeutic avenue. Beyond the specific findings, the methodological platform-particularly the combination of assembloids and live imaging-will be broadly useful to the community for probing neurodevelopmental processes in health and disease.

Comments on revisions:

The authors have fully addressed my concerns by incorporating the relevant discussion into the manuscript, especially regarding how well the migration observed in hSO-hCO assembloids reflects in vivo condition. I have no further comments.

Reviewer #2 (Public review):

[Editors' note: This version was assessed by the editors. The authors have addressed a point raised by Reviewer #2, who thought the authors compared cells grown in low-serum and high serum conditions. This has been clarified in the latest version.]

In the manuscript Ruhling et al propose a rapid uptake pathway that is dependent on lysosomal exocytosis, lysosomal Ca2+ and acid sphingomyelinase, and further suggest that the intracellular trafficking and fate of the pathogen is dictated by the mode of entry. Overall, this is manuscript argues for an important mechanism of a 'rapid' cellular entry pathway of S.aureus that is dependent on lysosomal exocytosis and acid sphingomyelinase and links the intracellular fate of bacterium including phagosomal dynamics, cytosolic replication and host cell death to different modes of uptake.

A key strength is the nature of the idea proposed, while continued reliance on inhibitor treatment combined with lack of phenotype / conditional phenotype for genetic knock out is a major weakness.

In the previous version, the authors perform experiments with ASM KO cells to provide genetic evidence of the role for ASM in S. aureus entry through lysosomal modulation.

Reviewer #1 (Public review):

[Editors' note: The article has been improved and several points raised by the reviewers have now been addressed. The authors should ideally further improve the clarity of the figures and the description of the experimental methods. This is particularly important for an article discussing potential confounding factors.]

Summary:

This important article reveals that the Nora virus can colonize the intestinal cells of Drosophila melanogaster, where it persists with minimal immediate impact on its host. However, upon aging, infection, or exposure to toxicants, stem cell activation induces Nora virus proliferation, enabling it to colonize enterocytes. This colonization disrupts enterocyte function, leading to increased gut permeability and a significant reduction in lifespan. Results are convincing and hold significant import for the Drosophila community.

Strengths:

(1) Building on previous studies by Habayeb et al. (2009) and Hanson et al. (2023), this study highlights cryptic Nora virus infection as a crucial factor in aging and gut homeostasis in Drosophila melanogaster.

(2) Consistent with the oral route of Nora virus transmission, the study demonstrates that the virus resides in intestinal stem cells, with its replication directly linked to stem cell proliferation. This process facilitates the colonization of enterocytes, ultimately disrupting intestinal function.

(3) The study establishes a clear connection between stem cell proliferation and virus replication, suggesting that various factors - such as microbiota, aging, diet, and injury - can influence Nora virus dynamics and associated pathology.

(4) The experimental design is robust, comparing infected flies with virus-cured controls to validate findings.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors report that Nora virus, a natural Drosophila pathogen that also persistently infects many laboratory fly stocks, infects intestinal stem cells (ISCs), leading to a shorter life span and increased sensitivity to intestinal infection with the Pseudomonas bacterium. Nora virus infection was associated with an increased proliferation of ISC and disrupted gut barrier function. Genetically, the authors show that increased ISC division in Nora virus and Pseudomonas coinfected flies is driven by signaling through the JAK-STAT pathway and apoptosis.

Accordingly, blocking apoptosis and JAK-STAT signaling reduces viral load, suggesting that in this context the JAK-STAT pathway is proviral in contrast to other previous observations in systemically infected flies. This work adds to the findings of another recent paper showing that another persistent fruit fly virus, Drosophila A virus, also increases ISC proliferation and decreases gut barrier function. Intestinal viruses should therefore be considered confounders in studies of fly intestinal physiology.

Strengths:

Overall, the data are convincing and robust, starting with two wildtype fly stocks (Ore-R strain) that differ in their Nora virus infection status, followed by experiments in which cleared stocks are reinfected with a purified Nora virus stock preparation. The conclusions of the paper will be of interest to scientists working on insect physiology, virology, and immunology, but should also serve as a warning for scientists that use the fly as a model to study gut physiology.

Reviewer #3 (Public review):

Summary:

Franchet et al. sought to characterize the impact of Nora virus on host lifespan and sensitivity to a variety of infectious or stressful treatments. Through careful and rigorous analyses, they provide evidence that the Nora virus greatly impacts fly survival to infection, overall lifespan, and intestinal integrity. The authors have been thorough and rigorous, and the experimental evidence including proper isolation of the virus and Koch's Postulate reinoculation of the organism is excellent. The additional work is valuable and to the gold standard of the field, characterizing the pathology of the gut, including data showing gut leakage, the presence of the virus in the intestinal stem cells, and the importance of stem cell proliferation for virus replication and spread using elegant genetic tools to block stem cell proliferation or enterocyte death.

Strengths:

The authors have been rigorous and careful. The initial finding is presented through the lens of two related strains differing in virus infection. From there, the authors characterized the virus and isolated a purified culture, which they used to reinoculate a cleared strain to demonstrate proper Koch's Postulate satisfaction. The authors have also probed various parameters in terms of dietary importance in relevant conditions for many experiments. The additional work to characterize the pathology of the gut is compelling, using genetic tools to block or allow intestinal stem cell proliferation and enterocyte death through JAK-STAT and JNK signalling alongside the tracing of virus presence using a Nora virus antibody. JAK-STAT and JNK are previously described as regulators of these processes, making these tools appropriate and convincing. It is also interesting to see good evidence that the virus itself is damaging, rather than simply permitting coinfection by gut microbes (which does happen).

Reviewer #2 (Public review):

This paper describes an analysis of a commercially available panel for a spatial transcriptomic approach and introduces a computational tool to predict potential off-target binding sites for the type of probe used in the aforementioned panel. The performance of the prediction tool was validated by examining a dataset that profiled the same cancer tissue with multiple modalities. Finally, a detailed analysis of the potential pitfalls in a published study communicated by the company that commercialized the spatial transcriptomic platform in question is provided, along with best practice guidelines for future studies to follow.

Strengths:

- The manuscript is clearly written and easy to follow.<br /> - The authors provide clean, organized, and well-documented code in the associated GitHub repository.

Comments on revision:

My impressions from the first round of review haven't really changed. I don't think the software tool is well developed, and failing to incorporate thermodynamics or consider the impact of alignment settings is a major weakness.

I do think the topical area is relevant. The inclusion of the Xenium /Hubmap data modestly strengthens the manuscript relative to the original submission.

Reviewer #3 (Public review):

Summary:

The authors present a new computational method (OPT) for predicting off-target probe binding in the commercial 10X Xenium spatial transcriptomics platform. They identified 28 genes in the 10x xenium human breast cancer gene panel (280 genes) that are not accurately detected at the single-molecule level. They validated the predicted off-target binding using reference data from single-cell RNA-seq and 3'-sequencing-based Visium RNA-seq. This work provides a practical resource and will serve as a valuable reference for future data interpretation.

Strengths:

(1) Provides a toolbox for the community to identify off-target probes.

(2) Validates the predictions using single-cell RNA-seq and sequencing-based Visium RNA-seq datasets.

Comments on revision:

The authors state that OPT is a new software tool and have posted example code on GitHub. However, the Jupyter notebook does not display any figures or workflows that would allow the process to be replicated. Please provide documentation and code that can reproduce the results/figures presented in the paper.

Reviewer #1 (Public review):

Summary

Alpha oscillations have been previously proposed to shape the temporal resolution of visual perception, with a higher alpha frequency providing a finer resolution. This study goes beyond by investigating three additional processes that could influence joint visual temporal perception: the aperiodic neural signal, the integration of recent perceptual experience (serial dependence), and subjective confidence. To address their question, they developed a novel task where two Gabor patches oriented in opposite directions are presented in a continuous stream. This allows for testing for robust perceptual integration while avoiding bias from suboptimal perception. Behavioral analyses revealed an association between confidence and individual temporal integration thresholds, and demonstrated that serial dependence biases visual temporal integration as well as its associated confidence. EEG analyses first replicated the previous findings showing that faster IAF provides higher temporal resolution. Interestingly, the aperiodic neural signal was associated with both perceptual and temporal precision. Finally, the authors show that serial dependence is reduced in individuals with faster IAF and enhanced in participants exhibiting a stronger aperiodic component. Together, these findings highlighted that visual temporal integration arises from an interplay between alpha oscillations, the aperiodic signal, serial dependance and subjective confidence.

Strengths:

(1) The novel task proposed in the study represents a substantial improvement over the two-flash fusion task previously used to investigate the role of alpha oscillations in visual temporal perception.

(2) Serial dependence has attracted increasing interest in vision research in recent years. Testing whether recent visual inputs also influence temporal resolution is, therefore, a valuable and timely approach. In this regard, the authors provide evidence for a serial dependence effect.

(3) Although the functional role of brain oscillations has been extensively studied over the past decade, the role of the aperiodic neural signal has long been overlooked. This study revealed that the aperiodic component plays a role in perceptual precision and temporal resolution, thus providing evidence for an important role of the aperiodic neural signal.

(4) The mediation analysis demonstrates that the aperiodic and oscillatory neural components act independently, providing important insights for future studies aimed at understanding their respective role.

Weaknesses

It would have been valuable to record EEG continuously during the experiment to investigate how spontaneous alpha oscillations and aperiodic signal dynamically influence the temporal integration, serial dependance and confidence on a trial-by-trial basis.

Appraisal

The authors employed a novel and thoughtfully designed task, combined with appropriate analyses, to address their research question. Their results are convincing and provide strong support for their conclusions.

Impact

This study provides valuable insights into the role of the aperiodic neural signal in visual temporal integration. This is important because its contribution has likely been underestimated, and future research will likely uncover increasing evidence of its impact across multiple cognitive functions.

It was also very interesting to observe how alpha oscillations are associated with serial dependence and confidence, extending beyond their well-known role in visual temporal resolution. This opens intriguing avenues for future research on the functional role of alpha oscillations.

Reviewer #2 (Public review):

Summary:

This paper examines resting-state electroencephalography (EEG), the electrophysiological underpinnings of the temporal integration window in perception, and its modulation by priors (serial dependence) as measured through the perceptual fusion point of two continuous alternating stimuli. The study also includes a measure of perceptual confidence. Separating periodic from aperiodic EEG activity, the results show that the faster the individual alpha-frequency at rest and the steeper the aperiodic slope (previously linked to higher sampling/ lower noise), the lower the perceptual fusion point (corresponding to narrower integration windows), with independent contributions of the period and aperiodic activity to the integration window. The data also reveal that the point of fusion depends on prior history, and that the strength of this effect depends on individual alpha frequency and aperiodic slope: the lower the individual alpha frequency and the aperiodic slope, the stronger the serial dependence, with the two contributions being again independent. Higher alpha frequency also led to higher confidence. The results are interpreted to suggest that speed of alpha oscillations and aperiodic slope of the power spectrum (presumably reflecting rate/fidelity of visual sampling and the level of background noise) jointly shape the perceptual measure under study: high rate/ fidelity and low noise promote temporal precision in integration, while lower rate/fidelity and higher noise lead to a higher reliance on prior history. It is concluded that it is the interaction between two EEG features that shapes temporal integration and hence perceptual fusion.

Strengths:

The strength lies in the use of a continuous visual stream of two alternating stimuli whose timing shapes fusion or separation of the two stimulus precepts, avoiding some of the pitfalls of previous fusion probes through discrete (not continuous) stimulus pairs (missed detection of one stimulus of the pair may be misinterpreted as fusion). The results seem robust (based on n=83 participants), the results are interesting, and the interpretations are sound.

Weaknesses:

The main weakness lies in the reliance on resting state EEG for correlation with the behavioural measures. This captures trait-based relationships, but does miss out on the brain activity dynamics within/across trials, which could be used for a direct readout of evidence accumulation to a decision, for capturing spontaneous fluctuations of the processes under study, etc. Also, in terms of resting state EEG, both eyes-closed (EC) and eyes-open (EO) data have been recorded, but their links to perceptual fusion point/ confidence seem somewhat inconsistent across the results. This is a bit confusing. Are the EO and EC signals in any way related/ correlated, and if not, what are they supposed to represent? Would an analysis of these EEG measures during task performance (e.g., in a pre-stimulus = baseline time window) provide more consistent results? These points could be resolved by additional analyses and/or more elaborate discussions.

Reviewer #3 (Public review):

Summary:

In this study, the authors seek to explain what influences the temporal resolution of visual perception and its associated metacognitive monitoring, interindividual differences in such processes, and the neural mechanisms associated with these interindividual differences. More specifically, they investigated the factors influencing the perception of a rapid alternating stream of visual patterns as a single fused percept versus two segregated stimuli, and how these factors relate to stable features of ongoing brain activity. They introduce a novel sustained-stream temporal integration paradigm designed to address limitations of traditional two-flash tasks, and combine this with resting-state electroencephalography (EEG) to examine how individual alpha peak frequency and the aperiodic component of the power spectrum relate to temporal integration thresholds, perceptual history effects, and subjective confidence. Their overarching aim is to move beyond a purely oscillatory account of temporal sampling and to test whether periodic (alpha) and non-periodic (aperiodic) neural dynamics jointly shape perceptual decisions.

Strengths:

The study has several notable strengths. First, the experimental paradigm represents a thoughtful and innovative refinement of earlier approaches. By presenting alternating gratings within a continuous stream and varying the duration of each element rather than introducing discrete blank intervals, the authors mitigate well-known confounds of classical two-flash paradigms, particularly the possibility that "fusion" reports reflect missed detections rather than genuine temporal integration. The psychometric functions are well characterized, and the sample size is large for an individual-differences EEG study, with an a priori power analysis supporting the adequacy of the sample. Second, the use of spectral parameterization to separate oscillatory alpha peak frequency from the aperiodic component of the spectrum is methodologically rigorous and timely, as this distinction is increasingly recognized as important to avoid confounds in oscillatory activity estimation and the measurement of neural noise/excitatory-inhibitory balance (i.e., the aperiodic component of the power spectrum). The present work contributes to this emerging direction by relating both to behavioral indices within the same dataset. Third, the integration of perceptual thresholds, serial dependence, and subjective confidence within a unified framework provides a richer account of temporal perception than studies focusing on a single measure. In particular, the demonstration that resting alpha frequency predicts integration thresholds and that the aperiodic exponent relates to variability of the psychometric function is broadly consistent with the authors' central claims.

Weaknesses:

(1) At the same time, several aspects of the interpretation require caution. One conceptual issue concerns the interpretation of the psychometric slope parameter as an index of "temporal precision." The manuscript consistently equates steeper slopes with higher perceptual precision or lower internal noise. However, the slope of a binary psychometric function does not uniquely index sensory temporal resolution. It reflects the steepness of the transition between response categories and can arise from multiple sources, including variability in sensory encoding, instability of decision criteria, lapse rates, or other decisional processes. Even in the literature cited by the authors, slope is often described more generally as reflecting perceptual variability or sensory and/or decision noise rather than a pure measure of perceptual precision. An abrupt transition from "fused" to "segregated" responses, therefore, does not necessarily imply finer temporal resolution at the sensory level; it may instead reflect more consistent categorization or reduced decisional variability. The present data convincingly demonstrate relationships between spectral measures and the steepness of behavioral transitions, but they do not by themselves establish that this steepness reflects perceptual temporal precision rather than broader sources of behavioral variability.

(2) A related concern involves the causal language used to describe the relationship between neural measures and behavior. The EEG metrics are derived from resting-state recordings and therefore reflect stable, trait-like individual differences. Nonetheless, the Discussion sometimes adopts mechanistic phrasing suggesting that slower alpha rhythms or flatter spectra lead the brain to compensate by weighting prior information more heavily, or that neural noise is being "regulated." Such formulations imply within-task adaptive processes that are not directly measured. The results demonstrate robust between-participant associations, but further research is needed to establish whether individuals regulate neural noise or adjust prior weighting dynamically.

(3) Another point that merits clarification concerns the control analyses. The authors appropriately use spectral parameterization to dissociate oscillatory alpha peak frequency from the aperiodic component in the main analyses; however, their subsequent control analyses examining other frequency bands appear to rely on conventional band-power measures. Because band power can be influenced by the aperiodic background, null effects in other bands are difficult to interpret without similarly accounting for aperiodic structure.

(4) In addition, the temporal structure of the stimulus stream introduces an interpretational nuance. Varying the duration of each Gabor in a continuous alternation produces quasi-periodic stimulation rates, and several of these ISIs fall within the alpha frequency range. Rhythmic visual stimulation at alpha-range frequencies is known to produce strong stimulus-locked responses and can interact with intrinsic alpha rhythms in a frequency-dependent manner (Keitel et al., 2019; Gulbinaite et al., 2017). Although the present study does not record EEG during task performance and therefore cannot directly assess stimulus-driven steady-state responses, this aspect of the design complicates a purely intrinsic sampling interpretation. The observed relationship between resting alpha frequency and integration thresholds may reflect intrinsic sampling speed, but it could also be influenced by how closely an individual's alpha rhythm aligns with alpha-range temporal structure in the stimulus.

Conclusion:

Despite these limitations, the study achieves many of its primary aims. The sustained-stream paradigm reliably elicits graded temporal integration behavior and robust serial dependence effects. Individual alpha frequency is convincingly associated with integration thresholds, and the aperiodic exponent relates to behavioral variability measures. These findings support the broader conclusion that temporal perception reflects an interaction between rhythmic neural dynamics and the background spectral structure of ongoing activity. The work is likely to have a meaningful impact for researchers studying perceptual timing, perceptual history, individual differences in brain rhythms, and the functional role of aperiodic neural activity.

References:

Keitel, C., Keitel, A., Benwell, C. S., Daube, C., Thut, G., & Gross, J. (2019). Stimulus-driven brain rhythms within the alpha band: The attentional-modulation conundrum. Journal of Neuroscience, 39(16), 3119-3129.

Gulbinaite, R., Van Viegen, T., Wieling, M., Cohen, M. X., & VanRullen, R. (2017). Individual alpha peak frequency predicts 10 Hz flicker effects on selective attention. Journal of Neuroscience, 37(42), 10173-10184.

Reviewer #2 (Public review):

Summary:

The work presented by Zhang and coauthors in this manuscript presents the study of the neuropeptide corazonin in modulating the post-mating response of the brown planthopper, with further validation in Drosophila melanogaster. To obtain their results, the authors used several different techniques that orthogonally demonstrate the involvement of corazonin signalling in regulating the female post-mating response in these species.

They first injected synthetic corazonin peptide into female brown planthoppers, showing altered mating receptivity in virgin females and a higher number of laid eggs after mating. The role of corazonin in controlling these post-mating traits has been further validated by knocking down the expression of the corazonin gene by RNA interference and through CRISPR-Cas9 mutagenesis of the gene. Further proof of the importance of corazonin signaling in regulating the female post-mating response has been achieved by knocking down the expression or mutagenizing the gene coding for the corazonin receptor.

Similar results have been obtained in the fruit fly Drosophila melanogaster, suggesting that corazonin signaling is involved in controlling the female post-mating response in multiple insect species.

The study of the signalling pathways controlling the female post-mating response in insects other than Drosophila is scarce, and this limits the ability of biologists to draw conclusions about the evolution of the post-mating response in female insects. This is particularly relevant in the context of understanding how sexual conflict might work at the molecular and genetic levels, and how, ultimately, speciation might occur at this level. Furthermore, the study of the post-mating response could have practical implications, as it can lead to the development of control techniques, such as sterilization agents.

The study, therefore, expands the knowledge of one of the signalling pathways that control the female post-mating response, the corazonin neuropeptide. This pathway is involved in controlling the post-mating response in both Nilaparvata lugens (the brown planthopper) and Drosophila melanogaster, suggesting its involvement in multiple insect species.

The study uses multiple molecular approaches to convincingly demonstrate that corazonin controls the female post-mating response. The data supporting the main claim of the manuscript are solid and convincing.

Reviewer #1 (Public review):

Summary:

This paper leverages 7T fMRI data from the Natural Scenes Dataset to investigate whether retinotopic coding, the position-selective organization of visual response structures, spontaneous resting-state interactions between the Default Network (DN) and the Dorsal Attention Network (dATN). Using individualized network parcellations and population receptive field (pRF) modeling, the authors show that DN voxels can be split into two subpopulations based on their response to visual stimulation: those with position-specific positive BOLD responses (+pRFs) and those with position-specific negative BOLD responses (-pRFs). Critically, these subpopulations relate differently to the dATN during rest: -pRFs are anticorrelated with the dATN, +pRFs are positively correlated, and non-retinotopic DN voxels show no coupling. The anticorrelation (and positive correlation) is enhanced when DN and dATN voxels share visual field preferences. An event-triggered analysis suggests that retinotopic coding shapes both "top-down" (DN-initiated) and "bottom-up" (dATN-initiated) spontaneous activity transients, supporting the claim that the retinotopic scaffold is intrinsic to the DN. These findings challenge the prevailing view of global DN-dATN antagonism and suggest retinotopic coding as an organizing principle for cross-network communication.

Strengths:

The central finding that what looks like network-level independence between DN and dATN decomposes into structured, bivalent interactions organized by voxel-level visual field preferences is a compelling demonstration that macro-scale network descriptions can hide meaningful substructure. The logic of the analysis is clean: pRF properties are estimated from retinotopic mapping data and then used to predict resting-state coupling in completely independent scanning sessions. This cross-session, cross-modality design rules out many circularity concerns.

The use of individualized multi-session hierarchical Bayesian parcellation (Kong et al.) to define DN and dATN boundaries within each subject is the right methodological choice for this question. Network boundaries in posterior cortex, where DN and dATN interdigitate most closely, vary considerably across individuals, and group-average approaches would introduce exactly the kind of misassignment that would most confound the result.

The matched-vs-random pRF analysis is well-controlled. The authors demonstrate that cortical distance between matched and randomly-matched dATN pRFs does not differ, effectively ruling out spatial proximity on the cortical surface as a confound. tSNR controls further show that signal quality differences do not drive the effect.

The event-triggered analysis (Figure 3) is creative and adds genuine value. Showing that retinotopically-specific coupling persists during DN-initiated activity transients, not only dATN-initiated ones, is the key piece of evidence for the claim that the code is intrinsic to the DN rather than passively inherited through bottom-up visual drive.

The result is observed consistently across all individual participants, which provides strong evidence for the robustness of the qualitative pattern despite the small sample size inherent to densely-sampled designs.

Weaknesses

(1) The nature of negative pRFs requires more scrutiny

The entire interpretive framework depends on treating negative pRFs in the DN as genuine position-selective neural responses (suppression). However, negative BOLD signals are well known to arise from non-neural sources, specifically, vascular stealing (where activation in nearby tissue diverts blood from adjacent voxels) and macrovascular draining vein effects that produce spatially displaced signal inversions. These concerns are amplified at 7T, where T2*-weighted GE-EPI carries substantial macrovascular weighting. The DN and dATN interdigitate extensively in the posterior cortex, often within millimeters. A negative pRF in a DN voxel adjacent to a positive dATN voxel could, in principle, reflect the hemodynamic shadow of its neighbor rather than an independent neural response.

The spatial dispersion control (matched vs. random pRFs have similar cortical distribution) is valuable but addresses long-range confounds, not *local* hemodynamic crosstalk. The reliability of sign and center position across runs is reassuring but does not exclude a vascular origin, as vascular architecture is itself stable across sessions. I would encourage the authors to test whether the matched-vs-random effect survives exclusion of voxels near large pial vessels (identifiable from T2* contrast or the venograms available in the NSD). These analyses would not be dispositive, but they would meaningfully strengthen the neural interpretation.

(2) Amount of retinotopic mapping data and choice of pRF pipeline

The NSD includes 6 runs of retinotopic mapping (~5 minutes each; 3 bar-aperture, 3 wedge/ring). The authors use only the 3 bar-aperture runs (~15 minutes total per subject) and fit their own pRFs using AFNI's 3dNLfim procedure, rather than using the pRF estimates provided as part of the NSD release (which were fitted using the analyzePRF toolbox with all 6 runs).

Fifteen minutes of bar data is quite limited for reliable voxel-wise pRF estimation, especially in regions far from the early visual cortex, where signal-to-noise is inherently lower. Standard recommendations for robust pRF mapping in higher-order regions generally suggest substantially more data. The variance-explained threshold is close to the noise floor by design, meaning that a non-trivial number of the "retinotopic" DN voxels may be poorly estimated. Given that the core analyses depend on both the sign and the center position of these pRFs, the limited data is a significant concern.

The authors do not explain why they chose to re-fit pRFs rather than use the NSD-provided estimates. If the motivation was methodological (e.g., the NSD pRF pipeline does not readily yield signed amplitude, or the bar-only fits were judged more appropriate for detecting negative responses), this should be made explicit. If the NSD-provided pRFs can reproduce the key findings, this would substantially increase confidence in the results. If they cannot, that divergence itself would be important to understand. I would ask the authors to address this choice and, if feasible, to report whether the core results replicate using the NSD-provided pRF estimates and/or whether using all 6 runs of retinotopy data changes the findings.

(3) pRF model adequacy for the Default Network

The isotropic Gaussian pRF model was developed for and validated in early and mid-level visual cortex, where it captures the dominant spatial selectivity of neuronal populations. In DN voxels where the model explains comparatively little variance, it is less clear that the model is capturing the right quantity. Specifically, the negative pRFs could conceivably be described by a model with a dominant suppressive surround (e.g., a difference-of-Gaussians model), in which what appears as a "negative pRF" in the standard model is actually the surround component of a center-surround mechanism whose center is poorly resolved. This distinction matters: a genuine inverted code (negative center response) implies a qualitatively different computation than inherited surround suppression from nearby visual cortex.

The authors should consider discussing why the standard model is sufficient for the questions asked, or ideally, testing whether the sign distinction survives under alternative pRF model specifications.

(4) Interpreting resting-state transients as top-down vs. bottom-up

The event-triggered analysis labels high-amplitude DN pRF activations as "top-down events" and dATN activations as "bottom-up events." This is a reasonable inference given experience-sampling studies showing that rest involves alternation between internal and external attention, but it remains an inference. Without concurrent experience sampling, eye-tracking, or physiological monitoring, we cannot establish that a spontaneous DN transient reflects memory retrieval or internally-directed thought rather than a global arousal fluctuation. Similarly, dATN transients during rest could reflect covert shifts of spatial attention to remembered or imagined locations rather than bottom-up processing per se. I would ask the authors to soften this framing or to discuss what additional data would be needed to validate the top-down/bottom-up attribution.

(5) The "retinotopic code" vs. "visual field bias" distinction

The paper uses the language of a "retinotopic code" throughout and correctly distinguishes this from a "retinotopic map," noting that DN voxels do not form a continuous topographic representation on the cortical surface. This distinction deserves greater emphasis. In vision science, retinotopic maps carry computational significance through their topographic continuity and relationship to cortical wiring. A distributed collection of voxels with coarse visual field preferences but no cortical topography is a fundamentally different organizational feature. Recent reviews have drawn an explicit distinction between *retinotopic maps* and *visual field biases* (Groen, Dekker, Knapen & Silson, TiCS 2022), and the present findings may be more accurately characterized as the latter. Perhaps the authors think that the distinction is merely a signal-to-noise distinction, in which case I would invite them to clearly speak to this interpretation. In any case, this is not a criticism of the findings themselves, but clarity on this point would prevent conflation of two different organizational principles and would help position the work for both the vision and network neuroscience communities.

Reviewer #2 (Public review):

Summary:

Using a public dataset of retinotopic mapping and resting-state data, the authors find that the default mode network has voxels that respond (positively or negatively) to visual stimulation at specific retinotopic positions, and that resting-state activity in these voxels is correlated with activity in more traditional sensory voxels with the same visual-location preference. The retinotopic specificity is bidirectional, such that high activity in default mode voxels drives activity only in voxels with matching receptive fields in sensory cortex, and vice versa. These findings are at odds with traditional views of the default mode network as having abstract (non-retinotopic) representations and competing (rather than cooperating) with external sensory representations.

Strengths:

This study continues an intriguing line of research about how default mode regions interact with the sensory cortex. Demonstrating that there are structured interactions between these regions at rest, and that these interactions are in fact organized according to retinotopic location (as opposed to traditional views of representational format in the default mode network), provides a new framework for thinking about large-scale internal and external brain networks. The authors make use of a well-powered public dataset that allows for precise estimates of pRFs and individual-specific resting-state networks, and develop a number of interesting analyses that characterize the relationships between DN and dATN voxels. The findings are exciting and could have a major impact on future studies in cognitive neuroimaging.

The authors mention that these findings could shed light on internal/external interactions such as "anticipatory saccades or memory-guided attention," which is true, though I would argue that constructing DN representations of external stimuli is in fact even more fundamental than these specific cases (e.g., see Barnett and Bellana, 2025, "Situation models and the default mode network"). The "highways" identified in this study could play a vital role in real-world perceptual processes that are constantly translating external input into internal mental models.

Weaknesses:

(1) The criterion used for defining voxels as retinotopic seems very liberal. The authors show that only 5% of voxels have R^2>0.14 in a null analysis, and therefore define voxels with R^2>0.14 as retinotopic. Although all the networks in 1C show voxel distributions that differ from the null, the number of false positives above R^2>0.14 seems problematic, especially for the DN positive pRFs (red distribution) and to a lesser extent the DN negative pRFs (blue distribution). From visual inspection of the plot, the false discovery rate (fraction of voxels labeled as retinotopic that are false positives) looks like it would be greater than 50% for the DN-positive pRFs. The authors do show that the positive pRF voxels have above-chance consistency across runs, again providing evidence that there are true positive voxels in this set, but perhaps a stricter criterion (such as having consistent negative fits across runs) would provide more targeted identification of the DN voxels with true retinotopic sensitivity.

(2) The claim that "opponency at rest between the DN and dATN appears to be driven by the subset of DN voxels with negative retinotopic tuning" is not well supported. The fraction of DN voxels with negative pRFs is small: 9.42% of DN voxels have pRFs, and 58.77% are negative, so about 6% of DN voxels have negative pRFs. The fact that any DN voxels have negative pRFs is notable, but the authors do not provide evidence that these 6% are driving the overall behavior of the DN. They do show (e.g., in Figure 2B) that negative and positive pRFs have opposing influences, but the overall correlation with dATN does not look similar to the negative pRF connectivity. I'm also unsure whether "opponency" is a reasonable description for two networks that are "independent (i.e., not correlated)" in this analysis.

(3) The event-triggered analysis is effective at testing the bidirectional relationship between DN and dATN, with high activity in either network triggering a response in the other network. However, it would be helpful to show more validation that these "events" are meaningful windows of time to study. First, is 13 TRs a typical length of time that activity is elevated during one of these events? Second, the top-down and bottom-up terminology is perhaps too loaded and not well-justified; if the negative pRFs in the DN reflect a meaningful coding system, then couldn't low (rather than high) activity indicate a top-down event?

(4) The framing of this paper relative to the authors' past week, such as Steel et al. 2024 ("A retinotopic code structures the interaction between perception and memory systems"), could be improved. The existence of negative pRFs in the DN and a functional relationship between these pRFs and the sensory pRFs have already been described in prior work. My understanding of the primary novelty here is that this paper examines resting-state data, showing that there are widespread spontaneous interactions between broad internal and external networks, but this distinction is not made explicit in the Introduction.

(5) The definition of the default mode (DN) in this study aligns with past research, but the definition of the dorsal attention network (dATN) seems at odds with standard terminology. For example, the authors cite Fox et al. 2006, which depicts the dATN as including regions such as IPS, FEF, SMA, and MT+. Here, however, the "dATN" seems to be primarily lateral and ventral visual cortex (e.g., Figure S5). The exact location of these sensory pRFs is not critical to the authors' claims, but this labeling seems incorrect, and the motivation for defining/selecting the sensory network in this way is not described.

Reviewer #3 (Public review):

Summary:

This paper addresses an important question (the relationship between DN and dATN, and the role of retinotopic coding) and uses a set of novel analyses.

Strengths:

Important question, novel analytical approaches (pRF-informed functional connectivity analysis).

Weaknesses:

Some of the key claims are not fully supported by the data presented. There is also a concern about over-interpretation of the results. Key issues:

(1) The authors claim that retinotopic coding scaffolds the interaction between DMN and dATN. However, retinotopically tuned voxels account for a mere 9% of DMN voxels. So this appears to be a major overstatement. For instance, the statement that "these findings would position retinotopy as a unifying framework for brain-wide information processing" is not justified given the presented data.

(2) Given that positive pRF voxels in DMN positively correlate with dATN voxels and negative pRF voxels in DMN negatively correlate with dATN voxels, there is a concern that these results could be contributed to by imprecise brain network parcellations. E.g., could some of the positive pRF voxels in DMN be erroneously assigned to DMN and actually belong to one of the other task-positive networks? There is insufficient validation of network parcellation to put this worry to rest, especially since it depends on ICA, which has a degree of arbitrariness built in.

(3) The claim that retinotopic coding is intrinsic to the DN network is not supported by rigorous analysis and results. The analysis here has many arbitrary factors, including: the threshold of the 99th percentile of resting-state distribution; the designation of DN as "top-down" and dATN as "bottom-up"; the definition of "anti-matched" voxels instead of using randomly selected voxels; and the statistics being paired between matched and anti-matched voxels instead of using comparisons to baseline. Overall, I do not think that the result supports the conclusion that retinotopic coding in DN is intrinsic instead of being bottom-up-driven, given the very high threshold (99%) used and the fact that many other networks could also send bottom-up input to DN. Furthermore, the idea that bottom-up inputs only occur when the dATN (or any other RSN)'s spontaneous BOLD activity is above a certain threshold is a huge and unvalidated assumption.

Reviewer #1 (Public review):

Summary:

Garcia-Alcala, Kratz and Cluzel investigate to what extent our understanding of bacterial physiology in bulk experiments can be applied to single-cell observations. They find that intrinsic noise may be powerful enough to even inverse the trends found in the bulk. The authors hypothesize that the asymmetric distribution of ribosomes to daughter cells during cell division plays the dominant role in the intrinsic noise and is able to generate the observed phenomenon. They do not show it directly, but the data and its agreement with the model are sufficient to support this claim.

Strengths:

The experimental part is convincing: the positive correlation between the elongation rate and promoter activity of unnecessary protein is clear, as well as the negative correlation between the mean values while changing the promoter strength. This was demonstrated in both rich and poor media. The causality between the growth rate and the promoter activity was shown using the negative lag time of the cross-correlation function. A simple, reasonable model accounts well for the data. This paper demonstrates an interesting phenomenon and provides a plausible theory for it, advancing our understanding of bacterial physiology on the single-cell level.

Weaknesses:

(1) Mean-reversion timescales were assumed to be longer than the simulation time and much longer than the cell cycle time. It is not clear whether the results are robust in case mean-reversion timescales become of the order of the cell-cycle or smaller. If not, is there an argument for such practically infinite reversion timescales?

(2) It is not easy to understand the simulation part unless one reads Ref. [14]. k(t) is assumed Equation (1) from Reference [14]? Is it crucial that the ribosome noise appears only at the division? The ribosome noise strength \sigma_R=0.06 - is it lower or higher than the naively expected binomial division? Also, a more intuitive explanation of the Simpson paradox would help the reader.

(3) It would be useful for the reader to see the raw data and not only the filtered one to appreciate the measurement noise level.

(4) Negative lag time of the cross-correlation function is visible, but consider adding a statistical test for it.

(5) Can you make similar cross-correlation plots using the model? Can you infer by using it, whether the data agrees better with the assumption that ribosomal noise appears only at division or continuous fluctuations during the cell cycle?

Reviewer #2 (Public review):

Summary:

The manuscript by Garcia-Alcala et al. reports an interesting paradox: the cost of gene expression slows the population-average growth rate, whereas at the single-cell level, expression levels from these genes positively correlate with the growth rate. The effect is observed in the expression of flagellar genes and a gene under a synthetic promoter in E. coli. The findings are explained by the inheritance of growth factors, including ribosomes, during asymmetric division.

Strengths:

(1) The manuscript adds strength to an emerging body of literature showing that the population-level bacterial growth laws do not match correlations based on single-cell data. The evidence presented here is more striking than in previous works (such as Pavlou et al., Nat. Commun. 2025), as the trends in population-level data and single-cell data are reversed.

(2) A relatively simple model correctly explains the trends in the data.

Weaknesses:

(1) It is not clear whether flagellar proteins are expressed proportionally to the reporter signal. Furthermore, it is questionable if E. coli bacteria in the mother machine channels are flagellated. If they are, they could potentially swim out of the channels, which is not the case when they do not carry the MotA E98K mutation. The authors should provide some evidence that E. coli expresses the actual filament proteins in the channels.

(2) It is unclear what fraction of the total proteome mVenus represents in different measurements. Some quantification is needed (for example, using the Coomassie staining). Using f_U as high as 14.4% in simulations is questionable.

(3) The data from the MC4100 strain does not directly match the trends of MG1655. The justification for filtering out the low-frequency components of MC4100 is not particularly convincing. It appears unlikely that ribosomes or other growth factors partition significantly differently in the MC4100 strain than in the MG1655 strain. Further discussion and a plot similar to Figure 1 (Left) for this strain are warranted.

(4) The model needs to be described in more detail. A closed set of equations that has been simulated must be presented, along with all values of the model parameters and their sources. The authors should consider depositing their code on GitHub or another publicly accessible repository.

Reviewer #1 (Public review):

Summary:

Effective decision-making in dynamic environments requires the brain to flexibly adjust how sensory evidence is accumulated over time, a process often modeled as an adaptive "leak." McGaughey and Gold propose that this flexibility is not solely a property of downstream integrators but is also supported by stimulus-specific sensory adaptation in the middle temporal area (MT). By recording single-unit activity in rhesus macaques during a motion direction-discrimination task, the authors found that more rapidly changing environments lead to reduced sensory encoding and discriminability in MT, which they argue accounts partially for a "leakier" integration. Furthermore, the study identifies pupil-linked arousal as a parallel, independent mechanism contributing to this adaptive process.

Strengths:

The study addresses an important question in cognitive neuroscience by exploring the neural substrates of perceptual flexibility. A major strength is the novel focus on how sensory adaptation, rather than just downstream integration, contributes to behavioral changes in dynamic environments. By shifting the perspective toward the encoding stage, the authors provide a more comprehensive account of how the brain manages evidence accumulation. This conceptual advance is supported by a rigorous experimental approach that combines human-like psychophysics with large-scale single-unit recordings in the middle temporal area (MT) and pupillometry.

Weaknesses:

(1) Alternative mechanisms for performance differences

The authors assume that the difference in performance between the low-switch (LS) and high-switch (HS) frequency conditions is explained by a change in the "leakiness" of integration. However, several other mechanisms could potentially explain this effect:

(i) Temporal Uncertainty: Integration might start later in the HS condition, leading to lower performance.

(ii) Reduced Efficiency: Integration could be less efficient in the HS condition (i.e., lower signal-to-noise ratio) without a change in the leak parameter itself.

(iii)Evidence Contamination: Motion information from the adapting stimulus in the HS condition may be integrated rather than ignored, which might be the case since the transition from the adapting to the test stimulus is not externally cued.

To distinguish between these alternatives, I suggest two possible analyses. First, a formal model comparison could be performed, though I acknowledge this may be inconclusive in the absence of response-time data. Second, an analysis of motion energy kernels could be revealing; the leak hypothesis makes the specific prediction that for long test stimuli, early samples should contribute more to the choice in the LS condition than in the HS condition, relative to late samples.

(2) Independence of neural and pupil-linked signals


The authors take the lack of session-wise correlation between context-dependent contributions from neural and pupil terms as evidence that these two signals provide independent contributions to the behavioral effect. However, could this lack of correlation simply be a result of high variability or noise in these estimates? The data shown in Figure 7B suggests that measurements are very noisy, which might obscure a potential relationship.

Reviewer #2 (Public review):

McGaughey & Gold trained rhesus macaque monkeys to perform a motion-direction discrimination task in which a behaviorally irrelevant adapting stimulus with either fast or slow direction alternations preceded a variable-duration test stimulus, while simultaneously recording single-unit activity in area MT and pupil diameter. They report that adaptation to the more rapidly changing stimulus was associated with reduced behavioral sensitivity, attenuated test-evoked MT responses, and larger pupil-linked arousal signals. The authors interpret these behavioral changes as evidence for a more "leaky" evidence-accumulation process, and argue that this apparent leak is implemented in part through context-dependent sensory adaptation in MT and in part through arousal-related mechanisms. More broadly, they conclude that flexible evidence accumulation in dynamic environments arises from distributed adjustments across sensory encoding and neuromodulatory systems rather than solely from changes within a downstream accumulator. If correct, this interpretation has significant implications not only for our understanding of the neural mechanisms of perceptual decision-making but also for broader theories concerning the functional role of sensory adaptation.

The conclusions of the paper are mostly well supported by the data. Evidence for robust adaptation-induced changes in sensory encoding, behavior, and pupil dynamics is convincing, but further clarification and refinement are needed to establish a clear mechanistic link between these effects and decision-making processes.

Aspects of the behavioral analysis would benefit from a tighter connection between theoretical claims about evidence accumulation and the empirical features of the psychometric functions. For example, the rightward shifts observed across adapting conditions are interpreted as consistent with a reset of accumulation on switch trials, but similar patterns could also arise from failures to detect the test stimulus on a subset of trials, leading responses to default to the final adaptor direction. Likewise, changes in psychometric slope and asymptote are attributed to differences in evidence accumulation without explicit modelling or consideration of alternative explanations. Clarifying how specific features of the psychometric functions map onto distinct components of the decision process will strengthen the link between the theoretical framework and the behavioral data.

A slight concern is the lack of a consistent analytical approach for relating behavioral changes to neural and pupil-linked measures. Different sections of the manuscript rely on different behavioral metrics-such as differences in accuracy within a selected stimulus-duration range (e.g., Figure 5C) or psychometric slope differences (Figure 6C) - without clear justification for these choices. The analytical approach likewise varies between simple correlational analyses (Figure 5C, Figure 6C), pseudo-experimental group comparisons (Figures 5D, E), and the inclusion of neural or pupil terms in the behavioral psychometric regression model (Figure 7B). While each metric and approach may be defensible in isolation, adopting a more consistent framework will help convince readers that the reported effects are robust and not contingent on the selective choice of metric or analysis.

Reviewer #3 (Public review):

Summary:

Environments change over time; therefore, optimal decision-making ought to discount older observations of the environment in favor of newer ones in a manner consistent with the amount of temporal instability. Computational models of perceptual decision-making model this temporal discounting with a 'leak' parameter that determines the rate at which older information is discarded. In this study, McGaughey and Gold examine the neurophysiological mechanisms that could underlie adaptation to different degrees of temporal instability. They developed a novel variant of the well-established perceptual decision-making random-dot-motion paradigm, in which the stimulus being evaluated was preceded by an 'adapting' stimulus with either high or low temporal stability. When the test stimulus was preceded by the adapting stimulus with lower temporal stability, NHPs showed reduced psychometric slopes, indicative of increased temporal discounting ('leak'). While the NHPs performed this task, single-unit neural activity was recorded in area MT, along with pupillometric data. The authors use these neural and pupil datasets to investigate two potential sources of adaptive discounting under varying amounts of temporal instability: sensory adaptation (changes in instantaneous evidence encoding), and arousal-related changes in evidence accumulation. MT neurons respond differently to the test stimulus under conditions of high vs low temporal stability of the adapting stimulus - when the adapting stimulus is more stable, MT neurons have larger and more selective responses to the test stimulus. In addition, evoked pupil responses to the test stimulus were modulated by the adapting stimulus. Both the strength of the difference in MT responses across contexts and the difference in pupil diameter across contexts were correlated with context-dependent modulation of the monkeys' behavior over sessions. The paper concludes that both sources appear to independently contribute to adaptive evidence accumulation, likely operating at different processing stages in the brain.

Strengths:

(1) While computational models of perceptual decision-making have been very useful for explaining behavior and neural responses in decision-making areas, we are still in search of some of the neural mechanisms that could implement such models. Studies such as this one, which aim to identify neural correlates of simplified model parameters, are quite crucial.

(2) Analysis is generally careful and well-executed.

(3) Prompts some interesting follow-up questions that could be answered with simultaneous recordings and causal manipulations, as the authors state in the Discussion - e.g., which areas are affected by arousal-related neuromodulation correlated with evoked pupil size and how.

Weaknesses:

(1) The task design may not be optimal. While the amount of time the monkey is exposed to each motion direction during the adapting stimulus is matched, it's hard to know if the reduced MT responses to the test stimulus are truly due to the greater frequency of switches during the HSF adapting stimulus or because the monkeys have been exposed to more repetitions of the stimulus. It's increased sensory adaptation in either case, but it makes it problematic to interpret this as temporal context-dependent adaptation specifically. I think this could potentially be partially addressed by an analysis that is in the paper, but could potentially be emphasized/fleshed out more, specifically the results shown in Figure 4D that seem to show that most of the reduction in neural response for adapting units occurs between the first and second stimuli.

(2) The pupillometric analysis seems to be an indirect way of assessing whether the accumulator itself might be modulated by temporal context, but the link could be made clearer. The authors show that context-dependent behavior is related to pupil size, which is related to arousal/neuromodulation, but it would be helpful to have some idea of what neural mechanisms underlying adaptive decision-making are actually impacted by this neuromodulation. Lacking neural data to address this question (e.g., from a brain region proposed to be involved in the accumulation process), at least more discussion of this would be helpful. Essentially, I'm unsure of how to interpret the pupil results: the argument that temporal context affects instantaneous evidence encoding in MT that then drives the accumulator is very clear, but I am a bit confused about what, mechanistically, I should think about the effect of neuromodulation doing.

Reviewer #1 (Public review):

Summary: