Reviewer #3 (Public review):

This manuscript aims to investigate cell extrinsic mechanisms that regulate differentiation and distribution of interneuron types in the spinal cord. The authors demonstrate that the loss of motor neurons leads to changes in number and distribution of different interneuron types, specifically V0v, V1, and V2b (but not V2a). The authors then hypothesize that this phenotype may be controlled by the action of Onecut (OC) transcription factors in motor neurons. Conditional knockout of OC1 + OC2 in motor neurons using Olig2-Cre, however, does not lead to significant changes in numbers of V1, V2a, V2b interneurons, although there is a change in their spatial distribution. While the authors do not check V0v neurons in OC mutants, they do check V2c, which show a reduction in number and change in distribution. Why the same neurons are not checked across experiments is unclear. The authors then analyze existing RNA-seq data to identify factors that could be mediating effects of the OC factors in motor neurons. They identify Ntf3 as a candidate and confirm that it is upregulated in OC mutants. Conditional loss of function of Ntf3 (Olig2-Cre) leads to increases in V1, V2a, and V2b (but not V2c) interneurons and changes in distribution of all four interneuron types. However, the Ntf3 phenotypes do not necessarily suggest that it works in the same pathway as OC to control interneuron development. Finally, the authors demonstrate that these Ntf3 conditional mutants have major defects in motor function.

The main conclusions of the manuscript are that i) motor neurons non-cell autonomously control interneuron development, ii) that OC activity in Olig2 lineage cells non-cell autonomously controls aspects of interneuron development, and iii) that Ntf3 in motor neurons non-cell autonomously controls aspects of interneuron development. The mechanistic link between OC and Ntf3 activity is not clear. And the interneuron phenotype seen when motor neurons are depleted it not phenocopied by either loss of OC or Ntf3 from motor neurons. While the authors addressed some of my initial comments, the impact of this work on the field remains difficult to assess for the following reasons:

(1) The manuscript relies heavily on quantifying numbers and spatial distribution of interneuron populations. However, these do not seem to be consistent in control animals across experiments, making it difficult to interpret any changes observed in genetic manipulations. Specifically, in Fig. 2 and 4, the same markers are being used to quantify V1, V2a, V2b, and V2c interneurons in controls vs. OC (Fig. 2) or Ntf3 (Fig. 4) conditional knockouts, but the numbers of neurons and their distribution in control animals are variable between these two figures. For example, there seem to be a mean of >300 V1 neurons in E12.5 brachial sections of Fig. 2 controls, but this number is <150 in Fig. 4 controls. The cell distribution scoring is similarly variable between these controls without any explanation. The same is true for E14.5 controls used in Fig. S2 vs. Fig. S6.<br /> The authors explain in response to the 1st review that technical variability including different antibodies, different researchers performing experiments, and different mouse backgrounds may contribute to this variation, but do not include this explanation clearly in the manuscript where it would be useful for readers. It would have also helped, for example, if authors had labeled datapoints on bar plots based on the animal that they came from to understand inter-animal variability within experiments. Overall, the biological significance of the results remain difficult to interpret due to high technical variability.

(2) In the initial review, it was noted that there is no data to support the claim that OC1/2 mutants have altered interneuron development because of higher Ntf3 expression. In response to this, the authors note that the manuscript does not claim that OC exerts its non-cell autonomous effects through Ntf3 and add a new paragraph in the discussion which now addresses the fact that it is difficult to compare the phenotypes observed the different genetic manipulations presented in the work. While this paragraph addresses the incomplete mechanistic link between OC and Ntf3, it also decreases the mechanistic impact of the work.

(3) In Figure 3E-3G, the authors show that some V1, V2a, V2b interneurons express the Ntf3 receptor TrkC. It is not stated (apologies if I missed it) what age this expression is, and from the images, it looks like in addition to medially located newborn neurons being negative, laterally located Gata3 interneurons are also broadly negative for TrkC, and many Foxd3 and Chx10 interneurons are also negative. Separate images of each channel and/or scoring would help clarify this. If many relevant interneurons are indeed TrkC negative, how this affects the conclusions should be addressed in the manuscript.

(4) Behavioral phenotypes are not necessarily caused by Ntf3's role in premotor interneuron development.

Reviewer #3 (Public review):

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

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

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

Comments on revised version.

I had only minor issues with the manuscript, which have now been addressed.

Reviewer #3 (Public review):

Summary:

The manuscript by Jiang and co-authors presents an analysis of experimental measurements (about 400k variants) from a deep mutational scan of HIS3 enzyme. The authors assess the ability of a genotype to be "rescued" and show that this depends on mutation sites (in particular their solvent accessibility) and mutations effects (should be mild on folding stability or binding affinity). They further identify a set of super-compensatory mutations and their results suggest that these mutations flatten the fitness landscape.

Strengths:

This finding is interesting and likely of interest to a broad community. The analysis seems sound.

Comments on revised version.

The authors have satisfactorily addressed my concern. Additional robustness experiments and case studies from ProteinGym are valuable.

DOI: 10.21203/rs.3.rs-7072571

Resource: RRID:RRRC_00699

Curator: @bandrow

SciCrunch record: RRID:RRRC_00699

What is this?

DOI: 10.21203/rs.3.rs-7072571

Resource: RRID:RRRC_00699

Curator: @bandrow

SciCrunch record: RRID:RRRC_00699

What is this?

DOI: 10.21203/rs.3.rs-7072571

Resource: RRID:RRRC_00699

Curator: @bandrow

SciCrunch record: RRID:RRRC_00699

What is this?

DOI: 10.21203/rs.3.rs-7072571

Resource: RRID:RRRC_00699

Curator: @bandrow

SciCrunch record: RRID:RRRC_00699

What is this?

DOI: 10.21203/rs.3.rs-7072571

Resource: RRID:RRRC_00699

Curator: @bandrow

SciCrunch record: RRID:RRRC_00699

What is this?

DOI: 10.21203/rs.3.rs-7072571

Resource: RRID:RRRC_00699

Curator: @bandrow

SciCrunch record: RRID:RRRC_00699

What is this?

DOI: 10.21203/rs.3.rs-7072571

Resource: RRID:RRRC_00699

Curator: @bandrow

SciCrunch record: RRID:RRRC_00699

What is this?

Women in society face many challenges simply because of their gender. Regardless of their education, wealth or social status, they can still experience unfair treatment from men. Some women are forced to sacrifice their personal ambitions to satisfy family and cultural expectations. However, women deserve equal opportunities, respect and the freedom to make their own decisions.

Maiguru's actions show that women in the family are expected to take responsibility for serving men. Although she is Babamukuru's wife, her work in the kitchen is treated as normal. Nyasha's decision not to wait for her father to finish eating suggests that she does not fully accept these traditional expectations.

On Sunday evening, the day after the wedding, Babamukuru called me to the sitting-room. He sat in his armchair and Maiguru sat on the sofa. I took the same chair I had sat in on my first night at the mission, but I was not the same girl. He did not shout, which was worse than shouting. He said he had held me up to Nyasha as the daughter she should copy, and that I had shamed his trust. A beating, he said, might help me grow up faster. I counted fifteen strokes, one for every year I had lived. Afterwards Anna was sent away on leave and her chores became mine. I scrubbed and swept without complaint, and a small, strange part of me was glad of the ache. If this was the price of saying no once, then at least I had bought something that belonged to me, even if I could not yet say what it was.

What I added: • Tambu's physical and emotional experience, such as counting the strokes and his calm voice being worse than shouting. • A callback to the chair on her first night, to show how much she has changed. • A final line tying the pain to owning her decision.

What I took away: • The words "crime" and "masochistic delight". I replaced them with action, so the reader sees the pain instead of being told about it. • Most of Babamukuru's reasoning, which I shortened to two sentences.

Why: The original is flat and quick, which makes the beating of a girl seem normal and routine. I slowed it down to show the cost to Tambu and to connect it to the theme of girls being disciplined into obedience. The trade-off is that my version explains her feelings more than the original does.

PatientID: None

KindredID: 1

Case: F, 3Y0M, Ethnicity Unknown

DiseaseAssertion: VHL

FamilyInfo: Mother aged 38 was diagnosed with bilateral pheochromocytoma resected when she was the age of 18 years. She presented several relapses, the most recent one at the age of 32, when she was also diagnosed with cerebral angioma. Genetic testing revealed the presence of the VHL c 244 C>G (p. Arg 82 Gly) heterozygote mutation, while the tests for RET, SDHB, SDHC and SDHD were negative.

CasePresentingHPOs: HP:0001954; HP:0000980; HP:0001649; HP:0000822; HP:0002666; HP:0006748 (Recurrent fever, Pallor, Tachycardia, Hypertension, Pheochromocytoma, Adrenal pheochromocytoma)

CaseHPOFreeText: Several months history of febrile episodes, sweating and irritability. An abdominal ultrasound performed in a pediatric hospital revealed a right adrenal tumor mass. The clinical examination of our patient revealed: pallor, paroxysmal febrile episodes with irritability and sweating, tachycardia, hypertension. There was no palpable abdominal mass. Abdominal ultrasound showed a tumor of the right adrenal gland. MRI showed a right adrenal tumor confirmed by pathology to be a malignant pheochromocytoma. After 6 months from the complete resection of the tumor, the daughter is without any clinical symptoms, with normal blood pressure, normal ophthalmoscopy, no tumor markers and no evidence of tumor on cerebral or abdominal MRI.

CaseNotHPOs: N/A

CaseNotHPOFreeText: N/A

CasePreviousTesting: N/A

PreviouslyPublished: N/A

SupplementalData: N/A

Variant: p.R82G (c.244C>G)

LegacyVariant: N/A

CaseProblemVariantFreeText: N/A

ClinVarID: 1297059, https://www.ncbi.nlm.nih.gov/clinvar/variation/1297059/

CAID: N/A

gnomAD: N/A

VariantEvidence: N/A

MutationType: missense_variant;transversion

CivicName: R82G (c.244C>G)

MultipleGeneVariants: N/A

Reviewer #3 (Public review):

Summary:

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

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

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

Global assessment:

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

Comments on revised version.

The authors have answered all my points.

Reviewer #3 (Public review):

Summary:

This manuscript examines a key mechanism by which KMT2A regulates RNA polymerase I transcription at ribosomal DNA. The authors suggest that KMT2A facilitates the recruitment of PCAF to rDNA. This process enhances histone acetylation and supports assembly of the RNA polymerase I transcription machinery. The study addresses an intriguing question by proposing a catalytic-independent role for KMT2A in rDNA transcription, potentially linking the KMT2A-dependent pathway to histone acetylation. However, several aspects of the proposed mechanism require further experimental validation. Notably, while the current evidence demonstrates associations among KMT2A, PCAF occupancy, histone acetylation, and rRNA transcription, it does not fully support the proposed objectives.

Strengths:

This could be the first report of a lysine methyltransferase regulating an acetyltransferase in Pol I-mediated gene expression.

Weaknesses:

(1) The causal relationship between KMT2A and the recruitment of PCAF needs to be demonstrated. Simply showing reduced PCAF occupancy after depleting KMT2A does not, on its own, prove direct recruitment. The authors should investigate whether KMT2A and PCAF physically interact, and whether this interaction depends on DNA or RNA.

(2) The main prediction of the model is that restoring PCAF activity should reverse the molecular effects caused by the depletion of KMT2A. The authors should test whether PCAF restoration can mitigate the consequences of KMT2A loss. They should also assess PCAF occupancy, H3K9 acetylation levels, Pol I occupancy, and nascent rRNA synthesis.

(3) The catalytic-independent function of KMT2A should be directly investigated. The absence of a significant change in H3K4me3 levels following KMT2A depletion does not confirm that KMT2A's catalytic activity is not essential. Rescue experiments comparing wild-type KMT2A with a catalytically inactive variant would provide a much stronger assessment of the proposed non-catalytic mechanism.

(4) The manuscript highlights H3K9ac; however, various acetyltransferases and histone acetylation marks are linked to active rDNA. The authors should investigate whether KMT2A specifically regulates H3K9ac or leads to broader changes in histone acetylation at rDNA.

(5) Due to the highly repetitive nature of rDNA, the manuscript must include detailed information about the reference assembly, mapping strategy, management of multimapping reads, normalisation processes, and biological replicates. The authors should demonstrate that any observed changes in occupancy are not due to technical differences in rDNA mapping or variations in copy number.

(6) KMT2A regulates a wide range of transcriptional programs, and its depletion can affect proliferation, cell-cycle distribution, or nucleolar function. The authors should include appropriate controls to demonstrate that the rDNA phenotype is not a result of changes in cellular proliferation or a generalised response to transcriptional or nucleolar stress.

(7) The CSB and B-WICH complex have previously been linked to the recruitment of PCAF and the acetylation of H3K9 at active rDNA. The authors should investigate whether KMT2A operates independently of these factors or if KMT2A functions within an established pathway for remodeling rDNA chromatin.

(8) The distinction between active and silent rDNA should be taken into account. The authors need to determine whether KMT2A/PCAF occupancy is preferentially associated with active rDNA copies. Sequential ChIP analysis or the use of established markers for active, poised, and silent rDNA would help clarify the chromatin context in which the proposed mechanism operates.

Reviewer #3 (Public review):

The study by Kašnik et al investigates the role of Samp1, an inner nuclear membrane protein, in muscle cell differentiation. Samp1 was already known to be required for myogenic differentiation and to influence chromatin organization at the nuclear periphery, but whether these two functions were connected was unclear. The authors set out to address this by asking whether the differentiation defect caused by Samp1 depletion is accompanied by failures in genome reorganization at the nuclear periphery.

Using C2C12 mouse myoblasts with stable Samp1 knockdown, they combine RNA sequencing, immunofluorescence, FRIC analysis, and chromosome 8 DNA-FISH to track both the transcriptional and spatial consequences of Samp1 loss during differentiation. The goal is to show that Samp1 is needed not just for muscle gene activation but also for the peripheral repositioning of chromatin that normally accompanies differentiation, and that these two processes are linked.

The biggest weakness of this study is that it does not explain how Samp1 actually controls chromatin organization at the nuclear periphery. Is it acting through emerin, the LINC complex, or lamin A/C? This is never addressed. At minimum, the authors should test whether a Samp1 mutant that cannot bind emerin or SUN2 can still rescue the chromatin and differentiation defects.

Related to this, only chromosome 8 is examined for repositioning defects. This chromosome was deliberately chosen because it is known to move during myogenesis, so it is not surprising that it fails to reposition upon Samp1 depletion. A chromosome that does not normally reposition should be included to show the effect is specific, and genes that are expected to remain away from the periphery should also be examined to test whether Samp1 depletion causes indiscriminate rather than selective chromatin reorganization defects.

More broadly, the study is largely descriptive. The main finding is that knocking down Samp1 disrupts gene expression and chromatin repositioning, and that these two things correlate. But which comes first? Does the chromatin move and then genes get silenced, or the other way around? This question is central to the paper's argument and is never tested. Without some attempt to address this, the study reads more as an observation than a mechanistic advance.

PatientID: 237

KindredID: 89

Case: F, 46Y0M, Chinese

DiseaseAssertion: VHL

FamilyInfo: N/A

CasePresentingHPOs: HP:0005584 (Renal cell carcinoma)

CaseHPOFreeText: The proband presented with renal cell carcinoma at age 46.

CaseNotHPOs: HP:0010797; HP:0002666; HP:0009711; HP:0001737; HP:0001732 (Hemangioblastoma, Pheochromocytoma, Retinal capillary hemangioma, Pancreatic cysts, Abnormality of the pancreas)

CaseNotHPOFreeText: N/A

CasePreviousTesting: N/A

PreviouslyPublished: This patient was also published in a later paper by Wang et al., 2018 (PMID: 29330336).

SupplementalData: Patient and family genotype-phenotype information is listed in Supplementary Table 1.

Variant: c.642+70C>T

LegacyVariant: N/A

CaseProblemVariantFreeText: N/A

ClinVarID: 900551, https://www.ncbi.nlm.nih.gov/clinvar/variation/900551/

CAID: N/A

gnomAD: N/A

VariantEvidence: N/A

MutationType: splice_site_variant

CivicName: 3'UTR alteration (c.*70C>T)

MultipleGeneVariants: N/A

Reviewer #3 (Public review):

Summary:

DeCoeur et al. explored the conformational dynamics of the intrinsically disordered protein (IDP) p53-TAD and a cancer-associated variant by examining its conformation-dependent block of conductance through a nanopore. Using this approach, they identified a preferred conformational ensemble stabilized by the anti-cancer compound EGCG. They supplemented their experimental observations with steered molecular dynamics simulations of the IDP's conformational ensembles. Much of the work appears to recapitulate prior observations for this IDP, and as such, this work reads more like a method development paper. Although the use of nanopores to study IDPs as done here is not completely novel, these sorts of applications remain relatively few, and thus this work is still useful. However, there are several issues with the data and its interpretation that suggest only incomplete evidence for the conclusions. Namely, what appear to be very low statistics for the observed long-lived pore-blockage events on which much of the experimental conclusions seem to be based, and also conclusions from simulations that do not appear to align with the data. Until these issues are addressed, I find some of the conclusions to be only weakly supported by the data.

Strengths:

The use of nanopore current blockage to interrogate the dynamics of IDPs has the potential to be an ideal approach to investigate both mechanisms of variant pathology and drug efficacy.

Weaknesses:

The apparently small dataset may be limiting, and in several cases the authors appear to also over-interpret their results based on small effects.

Reviewer #3 (Public review):

This paper from the Villasenor lab describes the results of experiments aimed at determining the role of the interaction of β1 integrin with CD98hc on the endo- exocytic trafficking of CD98hc, and its ability to function as an amino acid transporter. The paper demonstrates the following novel and interesting observations:

(1) CD98hc is internalised via fast endophilin-mediated endocytosis (FEME).

(2) A mutant of CD98hc that has been reported to oppose its interaction with β1 integrin (CD98hc ISM) alters CD98hc endo- exocytic trafficking to favour a situation in which CD98hc adopts a more endosomal distribution (than does wild-type CD98hc) following stimulation of FEME with a β-adrenergic agonist.

(3) Driving CD98hc endocytosis with a β-adrenergic agonist reduces uptake of branched-chain amino acids (BCAAs); an effect which is more pronounced following expression of the β1 integrin binding-deficient CD98hc ISM mutant.

General comments:

The findings of this paper are, at their core, very interesting and important and most of the work is well-executed. I consider that the 3 conclusions that I have listed above are solid and interesting (although some additional controls, etc would help consolidate these findings (see below)). However, the authors have vastly overplayed their hand in attempting to use mathematical modelling approaches and (in my opinion) invoking unnecessary working hypotheses concerning endocytic noise for which they have little evidence. I feel that the paper needs to be restructured to simplify the route between the core findings and the interpretation, and to move the mathematical modelling and 'endocytic noise' analyses and hypotheses to the discussion.

Specific points (in order of appearance):

(1) I am puzzled by how the graphs in Figures 1E&F have been derived from primary data and am sceptical of their validity. The curves don't look like anything that has been derived from experimental data. I gather that the curves in Figures 1E&F were generated by the equations described in the 'modelling CD98hc internalisation kinetics..'methods section, but I really cannot see how. Specifically, how can measurements of steady-state plasma membrane (PM) and endosomal pools of CD98 possibly allow the derivation of the APM and ATE operands in the equations in the 'modelling CD98hc internalisation kinetics..' methods section? Moreover, I don't see how this could be achieved in a way that could demonstrate a statistically significant difference in the trafficking of TfnR and CD98hc. The authors cite their previous 2017 Cell Reports paper to support this figure. However, the data in this paper are clearly experimental data (therefore understandable and clear), and the analysis in Vallasenor et al. (2017) does not resemble what has been performed to generate Figures 1E&F. Can the authors please properly clarify and justify this figure?

(2) Figures 1G&H. In the assay described in Figures 1G&H, it doesn't look like the CD98hc mAb is internalised in the control. And with the siRNAs that are purported to oppose CD98 internalisation (ARF6 and endophilin), it looks like CD98 has disappeared completely, rather than accumulating at the PM as one would expect if internalisation were blocked.

(3) In Figure 1H, the authors state that knockdown of endophilin A1 and A2 reduced CD98hc endocytosis, but it doesn't really look like this to me and there are neither quants nor stats on this.

(4) In Figure S1D, the conclusion that knockdown of dynamin or endophilin A1 and A2 decreases intracellular CD98hc-positive vesicles is not apparent to me, and these data need quantification and statistical analysis.

(5) In Figure 1J, the conclusion that addition of dyngo4A reduces internalisation of anti-CD98hc is not statistically supported. Moreover, although β-adrenergic agonists are clearly boosting internalisation of CD98hc in U2OS cells (Figure S1J), this, despite the asterisks (stats), does not appear to be the case in ICE-BECs (Fig. 1J); indeed, the increase is marginal, and the inter-experimental variation is too great to support a statistically significant increase in internalised CD98hc in ICE-BECs.

(6) The authors need to display representative images from experiments leading to the data in Figure 2B.

(7) The data in Figure 2 do not 'show that CD98hc is sorted to recycling endosomes after FEME internalisation' in an integrin-dependent manner. For this, one would need to demonstrate localisation of the CD98hc-β1 integrin complex to Rab11 (or Rab14)-positive compartments and these data are missing.

(8) I cannot find any details of the coordinates or construction of the CD98hc ISM mutant in this paper. I am assuming that this has been informed by the Ingber JCS paper from 2020, but the authors need to describe the construction and the provenance of their mutant. Also, importantly, the authors need to validate that this mutation opposes co-immunoprecipitation of β1 integrin and CD98hc. Or to use some other approach, such as FRET, to show this). OK, some of this has been performed by Ingber's group, but as it this is so important to the authors' conclusions, they need to confirm this. Also, it would be nice if the authors were to use their IP/proteomic approach to compare the interactomes of WT CD98hc and CD98 ISM.

(9) I think that some of the callouts to Figures 3 A-F are not correct in the manuscript. For instance, at the top of the page of the results (no page numbers), the callout to the sentence '...expressing either mGL-CD98hc WT or ISM (Figure 3A-D)' is likely wrong, and this is confusing.

(10) The data in Figures 3A,B,D&E do show that the CD98hc ISM mutant moves from the PM to endosomes more than does WT CD98hc following β-adrenergic stimulation. This is fine. However, I don't agree that the conclusions summarised in Figure 3C&F can be justified from these data. In fact, I do not believe it is necessary or justified to attempt to extrapolate these quite basic immunofluorescence data into an involved kinetic model. It would so improve the paper if these mathematical/kinetic extrapolations were moved to the discussion and presented as discursive points rather than hard-and-fast conclusions.

(11) The data in Figure 4A do not appear to show anything further than those in Figures 3 3A,B,D&E. Indeed, in light of Figure 3 A,B,D&E one would expect the vesicular CD98hc to be increased by the ISM mutation, but I'm not convinced that the amplitude of these so-called oscillations is necessarily different between WT and ISM mutant of CD98hc. All the differences between WT and ISM in Figure 4A&B appear proportionally larger than they are because of the truncated (non-zero baseline) axes in these graphs; a linear axis such as the y-axes in Fig. 4A&B should begin at zero, surely?

(12) In Figure 4D, it doesn't look at all as if the PM localisation of CD98hc and intracellular levels of BCAAs are similar between WT and ISM mutant of CD98hc - as the authors state in their results text.

(13) Why do the authors need to invoke what appear to me to be rather far-fetched and poorly supported arguments around 'endocytic noise' when the data in Figures 3A,B,D&E seem to be sufficiently consistent with those in Figure 4E to support the assertion that altered trafficking of CD98hc influences BCAA uptake?. Surely, it would be sufficient to argue that a mutant transporter that assumes a state which is distributed more endosomally than at the PM would be less efficient in uptake of BCAAs. So why the noisy arguments? It just seems to me to undermine what is potentially quite a nice and interesting paper.

Reviewer #3 (Public review):

The authors report an interaction between KHC and KLC1 through the coiled coil 3 of KHC, and then characterise the binding of TRAK2 to KHC through coiled coil 4 of KHC. The reporting of this second interaction is novel. The authors make a number of mutants which change the affinity of TRAK2 for KHC, but it is not clear if it ultimately prevents binding. They then demonstrate through competitive binding that TRAK2 binds more tightly to CC4 than CC1 and therefore can trigger release of Kinesin-1 auto-inhibition. The authors, however, do not show directly that the kinesin is no longer inhibited. This could be tested using negative stain EM, SAXS or motility assays in the future. The experiments are performed with immunoprecipitation pulldowns coupled with western blotting in cells, and ITC with recombinantly purified proteins.

Strengths:

The data showing the binding of KLC1 to KHC and the TRAK2 binding to KHC are interesting.

The ITC data looks very good from the profiles. It seems, however, that the experiments were done once rather than replicated (at least twice, ideally three times to accommodate variation). The size-exclusion chromatography experiments showing competition between different adaptors to KHC are nicely done, and the SEC-MALS is informative in terms of determining the stoichiometry and size of the assembled complexes. The work is performed with recombinant proteins and therefore removes any ambiguity about the interactions in cells.

Weaknesses:

The experiments lack appropriate controls, with some experiments incomplete, and the statements claimed are not supported by the data. There are some problems with figure and data presentation and the number of replicates/lack of quantification. The validation of AlphaFold models and predictions is missing. The cell biology experiments are preliminary.

There is a concern with the cell biology experiments. All experiments are done with transfections in the presence of the endogenous proteins. It is not clear if the proteins are overexpressed and they appear cytoplasmic. Beyond this, it is not possible to claim co-localization of the transfected proteins.

The manuscript would benefit from general editing to improve understanding. The names used to describe the methods are incorrect. This has implications for the solidity of the statements and conclusions of the paper.

Reviewer #3 (Public review):

Summary:

This study uses computational modeling to examine how local synaptic activity influences astrocyte membrane potential and, in particular, whether the classical Nernstian relationship between extracellular potassium concentration and astrocyte membrane potential is maintained throughout the astrocyte. The authors focus on the possibility that local ionic changes associated with synaptic activity produce membrane potential responses in fine astrocytic processes that differ from those predicted by a global Nernstian relationship. The study addresses an important and longstanding question in astrocyte physiology and provides a potentially useful computational framework for examining how cellular morphology, membrane conductances, and local synaptic inputs shape astrocyte membrane potential. The central conclusion is that Nernstian behavior can break down during local synaptic input, particularly in fine astrocytic processes. The modeling framework could therefore be useful for understanding how the spatial organization of astrocytes influences their responses to local neuronal activity. However, the strength and generality of this conclusion depend on several biological assumptions that are not sufficiently considered in the current model or discussion.

Strengths:

This computational modeling addresses a longstanding question in astrocyte physiology dating back to the 1960s: whether astrocyte membrane potential (VM) follows the Nernstian prediction in response to changes in extracellular K+ concentration ([K+]e). Significant recent progress in astrocyte studies has provided a renewed opportunity to revisit this question. In this regard, the effort to develop a conductance-based NEURON model that incorporates understanding of astrocyte structure and physiology is highly valuable. The model has also shown the potential to simulate how changes in astrocyte membrane Na+, Ca2+, and Cl+ permeabilities, resulting from synaptic inputs, could alter the relative K+ permeability, and therefore the Nernstian behavior of astrocyte VM at different subregions of astrocytes. These questions are important to astrocyte physiology and remain technically challenging to experimentally evaluate. However, several concerns about the omission of recent studies on astrocyte structure and function from the model and the physiological interpretation of the Nernstian behavior of astrocytes need to be addressed before the conclusions can be adequately supported.

Weaknesses:

(1) The premise of the modeling:<br /> The cellular context should be clearly stated. The model is intended to simulate rodent grey matter cortical protoplasmic astrocytes, but not white matter fibrous astrocytes or other specialized astrocyte populations, which differ morphologically and, to some extent, functionally.

(2) The architecture of astrocytes:<br /> This model can be refined by incorporating recent advances in our understanding of astrocyte morphology (PMID: 35283239, PMID: 31550514). For example, (a) the branching pattern of astrocytic processes, particularly the terminal processes (or leaflets), which is a key element of the model; (b) the location of synapses within an astrocytic domain. Specifically, synapses can make contact with virtually every structural component of an astrocyte, from the soma to different levels of processes, including endfeet contacting blood vessels. This anatomical evidence is in sharp contrast to the prevailing perisynaptic astrocytic process (PAP) concept adopted in the modeling; and (c) the existence of a large quantity of reflective astrocytic processes that loop back and form gap junctional coupling at their stemming points that wrap around bundles of axons or large dendrites, forming a scaffold-like architecture (also see PMID:32312988 in your reference list). This may create regions of strong local astrocyte VM response to activity-dependent elevations of [K+]e, which could be an important feature to consider in the modeling.

(3) Astrocyte membrane potential is not an autonomous feature of individual astrocytes:<br /> If the goal is to simulate astrocyte VM, astrocyte syncytial coupling cannot be ignored. Specifically, the very low astrocyte-to-astrocyte pathway resistance (4.2 MΩ) provides strong electrical coupling that equalizes the VM of astrocytes within a syncytium to a uniform level, a property termed astrocyte syncytial isopotentiality (PMID: 26435164; PMID: 30277762). Experimental studies have demonstrated that coupling among 7-9 astrocytes is sufficient to maintain this isopotential state. Thus, the VM of an individual astrocyte is not determined solely by its own K+ conductance and transmembrane K+ gradient, but rather the result of the electrotonic spatiotemporal summation of voltage across the syncytium. A realistic model that seeks to predict astrocyte VM should incorporate syncytial coupling as a fundamental component.

(4) The historical debate about the Nernstian behavior of astrocyte VM in response to [K+]e:<br /> The authors should acknowledge the longstanding debate over the Nernstian behavior of glial VM in response to changes in [K+]e. This relationship was first described in the seminal neuroglia studies of Kuffler and colleagues in 1966, using optic nerve neuroglia, which are likely equivalent to fibrous astrocytes in rodent white matter. They reported a slope of ~58 mV per 10-fold change in [K+]e (PMID: 5966434). This interpretation was subsequently challenged by a series of in vivo studies of neuroglia VM in cortical grey matter, including Pape and Katzman (1972; PMID: 5016004), Ransom and Goldring (1973; PMID: 4805015), and Futamachi and Pedley (1976; PMID: 1276917). Importantly, the Futamachi study provided early in vivo evidence consistent with syncytial isopotentiality, although the existence of the astrocyte syncytium could not be demonstrated experimentally until the later work of Ransom and colleagues in 1981 (PMID: 7248773). This historical literature should be introduced in the Introduction to establish the significance of the present modeling work.

(5) Astrocyte syncytial isopotentiality:<br /> The authors should consider that syncytial isopotentiality is a system-wide feature of both grey and white matter astrocytes. At minimum, this means that somatic astrocyte VM recordings are not consistent with a simple Nernstian prediction of VM in response to changes in [K+]e. Therefore, a model of astrocyte VM should account for syncytial coupling rather than treating VM as a property determined by individual astrocytes.

(6) Distinguish K+ Nernstian behavior from multi-ion permeability and transporter-mediated flux:<br /> Conceptually, the high and near-exclusive K+ permeability of the resting astrocyte VM provides the basis for applying the Nernst equation to describe VM. In the present, Na+ and Ca2+ permeabilities are also introduced without a clear distinction between the conditions under which a Nernst equation remains applicable and those in which it does not. The authors should clearly define Nernstian behavior as referring specifically to K+ permeability. When the Na+ and Ca2+ permeabilities, resulting from the activation of AMPA/NMDA receptors, are involved in astrocyte across-membrane ionic activities, the VM follows the GHK prediction. Additionally, the model includes Na+-dependent transporters, which do not represent channel-mediated permeability. The authors should therefore distinguish channel-mediated ionic permeability from transport-mediated ionic flux when describing and modeling changes in astrocyte VM.

Reviewer #3 (Public review):

The study by Saqib M. et al. aimed to develop a refined murine model for the study of Down syndrome. The authors developed a Ts66Yah murine line by removing triplicated genes using CRISPR technology from the previously developed Ts65Dn. In this study, the authors provide a deep metabolic profiling of the murine model, studying highly metabolic tissues (liver, skeletal muscle and adipose depots) in both sexes.

The major strength of the study is the large variety of metabolic assessments in males and females, identifying key dimorphic features in the model. However, this could also be considered a point of weakness since this is not a hypothesis-driven study, but rather a descriptive/exploratory study.

Due to the thorough description of the model and the metabolic profile, this study will be very useful for people working on research in Down syndrome. However, there is a lack of information related to cognition, behaviour, and other key features relevant to Down syndrome that would need further study.

Reviewer #3 (Public review):

Summary:

The study reanalyzes data from a previously published cohort together with an additional cohort to investigate hippocampal activity during approach-avoidance conflict. Unlike many prior studies that isolate reward- or threat-based learning, this task requires animals to evaluate reward and threat concurrently. The central finding is that hippocampal representations differ between hesitant behaviors that lead to approach versus avoidance outcomes, with representations of the attack zone more likely during pauses preceding abort decisions. This is an important extension of prior work on hippocampal activity and deliberation, suggesting that the hippocampal content may help shape the eventual outcome.

Strengths:

All behavioral findings are replicated independently across cohorts, making the behavioral results highly convincing. The design is robust, and the task is especially valuable for studying approach-avoidance conflict. The behavioral paradigm is complex and rare, and neuronal recordings in such a paradigm are of great value.

The major strength of the study is the comparison of neural activity during hesitant behavior leading to different outcomes; namely, pauses followed by the animal aborting the approach (mid-track aborts), and pauses followed by the animal committing to the approach (mid-track continues). Hippocampal activity differed between the two pauses: the attack zone was more likely to be represented during mid-track aborts. The same effect was observed on the journey before the pause: even before the animal hesitates, hippocampal activity before a pause that led to a mid-track abort was more likely to represent the attack zone than hippocampal activity before pauses that led to continued approach. This analysis suggests that hippocampal content before and during deliberative behavior is predictive of the animal's decision.

Weaknesses:

The interpretation of the retreat-related decoding results is less clear. The study compares two sets of retreating behavior: on the one hand, retreat after being attacked, and on the other hand, retreat after hesitation in the absence of an attack (a mid-track abort). Hippocampal activity represents the attack zone more after the animal is attacked. However, these two retreating behaviors originate from different spatial locations: retreats always start past the "attack threshold", while mid-track aborts always start before this threshold. Given that hippocampal decoding is strongly location-dependent, this difference in position makes the neural decoding results difficult to interpret. The increased representation may be due to differences in physical location, rather than distinct processing of immediate threat and an anticipatory return state.

Comments on revised version.

The revised manuscript is indeed more clear, but the study is largely unchanged.

Reviewer #3 (Public review):

Summary:

In this manuscript, Liu et al. used C. elegans animals lacking functional BMP as a model to dissect the neuropeptide signaling pathways that lead to BMP-associated fat loss. First, they established the BMP mutants as a model of dyspepsia that results in chronic dietary restriction. They then used this model to identify neuropeptide genes that are upregulated and required for BMP-associated fat loss. Next, they sought to identify the receptors for these neuropeptides and to place the genes in a genetic and cellular pathway. They also showed that the same neuropeptides and receptors contribute to fat loss in diet-restricted C. elegans. They conclude that they have identified a neuropeptide signaling cascade in which impaired pharyngeal function activates sensory neurons, which then signal through interneurons to enhance triglyceride hydrolysis in the intestine.

Strengths:

In this manuscript, Liu et al. characterized the pharyngeal muscles and the intestinal bacterial context of animals lacking functional BMP. They showed a correlation between BMP-associated fat loss and pharyngeal impairments that could lead to insufficient food grinding. This finding suggests that C. elegans lacking functional BMP could serve as a model for dyspepsia and chronic dietary restriction. Moreover, the authors analyzed previously published gene expression data to identify neuropeptides that are overexpressed in animals lacking BMP. They then used mutants for these neuropeptides and their receptors to determine which of these genes contribute to BMP-associated fat loss. Finally, they showed that the same neuropeptides and receptors also contribute to fat loss in diet-restricted C. elegans.

Weaknesses:

(1) The authors use double mutants between BMP pathway mutants and neuropeptide or neuropeptide receptor mutants to argue that the reduced fat levels of BMP mutants are suppressed. However, with the exception of unc-31, the fat content of the corresponding single neuropeptide or neuropeptide receptor mutant is not shown. Without these, the double-mutant phenotype cannot be interpreted as suppression, since it could reflect an independent effect on fat storage. To show that the effects are related to BMP signaling, the authors should compare wild-type animals to neuropeptide mutants in a sma-6(+) background. Similarly, the fat content of ADL-ablated animals is not shown in an otherwise wild-type background.

(2) In several places, the authors use cell-specific expression of neuropeptides to conclude that a given neuropeptide acts in a particular cell type (e.g., Figure 4B,C; Figure 5C,D). However, because neuropeptides are secreted and can act at a distance, expression in a non-native cell type may rescue the phenotype. These experiments therefore show sufficiency but do not establish the endogenous site of action. Cell-specific knockout or knockdown, or expression from control promoters in unrelated cell types, would help address this.

(3) The authors report that expressing npr-35 from two promoters with non-overlapping expression each fully restores the low-fat phenotype of sma-6; npr-35 mutants. This is surprising for a receptor and is difficult to interpret.

(4) The authors identify neuropeptide genes co-expressed with npr-35 and follow up on flp-18. The rationale for restricting the search to co-expressed neuropeptides may bias hypothesis generation. Similarly, the authors show that flp-1 and flp-4, in addition to flp-18, contribute to BMP-associated fat loss, but only flp-18 is examined further because of its overlapping co-expression with npr-35, again creating a bias in the investigation of the role of neuropeptide signaling in BMP-associated fat loss.

(5) It is difficult to interpret the experiment in Figure 5E, where the authors conclude that npr-4 is required in flp-18-overexpressing animals. Without a demonstrated fat-loss phenotype from overexpressing flp-18, a requirement for npr-4 in those animals cannot be meaningfully assessed.

Overall, the authors convincingly identify neuropeptides and receptors that are overexpressed and that contribute to fat loss. However, several points make it difficult to fully support the proposed model and the linear pathway from the pharynx to the intestine through ADL sensory neurons and interneurons. These include the absence of phenotypic analysis of the single mutants, the challenges of interpreting cell-specific rescue experiments when studying neuropeptide function, the fact that additional neuropeptides causing BMP-associated fat loss are identified but not studied further, and results that do not necessarily point to a linear pathway (e.g., the triple mutant sma-6; nlp-10; npr-35 has a stronger phenotype than the double mutants with sma-6, the fat loss caused by overexpression of nlp-10 in a sma-6 background is not suppressed by npr-35, and the flp-18 overexpression experiment is difficult to interpret). The reviewer therefore suggests that the linearity of this pathway, and the sites of action of the neuropeptides and receptors, should be presented more cautiously or supported by additional data.

Reviewer #3 (Public review):

Summary:

The authors aimed to answer the question of whether the basal ganglia, specifically neurons in the substantia nigra pars reticulata (SNr), directly select actions. This was done by recording the activity of SNr neurons, as well as neurons in the superior colliculus (a major recipient of SNr projections), during cued and self-directed actions, specifically recording the same SNr units during clearly distinct actions.

Strengths:

As the major output nucleus of the rodent basal ganglia, the SNr is a key location to determine if single-cell activity within the basal ganglia is specific to the selection or suppression of specific actions. This choice also provides a natural transition to the activity/roles of downstream motor nuclei that receive basal ganglia output. Multiple definitions of "action" were addressed throughout this manuscript, which is essential for an ambiguous concept like "action selection." They convincingly demonstrate that a "simple action selection hypothesis" in which there is a 1:1 correspondence between SNr single-unit activity and specific actions is incompatible with their data. The manuscript was clearly written and well-organized.

Weaknesses:

While the authors systematically address multiple definitions of an "action," all of the actions in this work are variations of either licking or reaching. The similar SNr activity during different types of reaches has several potential interpretations, which the authors enumerate and present arguments for why their interpretation (SNr does not implement action selection) is the most plausible. However, the study does not quite fully eliminate these possibilities. Finally, while the authors essentially eliminate the possibility of a 1:1 correspondence between SNr units and specific actions, it remains possible that SNr selects actions through a more complex population coding scheme. Indeed, they demonstrate that they can distinguish lick and reach actions by examining population SNr activity.

Appraisal of whether authors achieved their aims/evidence supports conclusions:

The authors achieved their aims of determining whether individual SNr neurons select for specific actions. This includes multiple definitions of "actions," with some actions differentiated by muscle group and body part (licking vs reaching), target, or timing. The evidence provided largely supports the authors' claims, though the low number of subjects in the causal optogenetic experiments makes interpretation of those results more difficult.

Discussion of likely impact of the work in the field:

This work will provide a foundation for future research into more nuanced dissections of basal ganglia circuitry, specifically between the SNr and its downstream target nuclei.

Reviewer #3 (Public review):

Summary:

Female receptivity to male courtship is regulated by many factors, including development and internal status. In mature, mated females, male courtship triggers ovipositor extrusion, which prevents intromission. In immature flies, however, rejection occurs through another behavior: immature wing flicking. How this behavior is engaged and regulated is unclear. Here, Bernet & Philipsborn advanced in this matter by defining behavioral and neuronal keys related to this phenotype. The authors show that immature wing flicking depends on pheromones and acoustic cues from the males to be triggered. Additionally, the authors identify the pC1a cluster as key for this behavior.

Strengths:

(1) In contrast to the regulation of ovipositor extrusion, immature wing flicker, while observed, has not been fully characterized. This is a significant step forward in our understanding of the ethology around female receptivity.

(2) The behavioral approaches that the authors used to determine the nature and correlation of immature wing flicker with male courtship are very convincing.

Weaknesses:

While the manuscript has clear strengths, particularly in describing immature wing flicking behavior, several analyses make some conclusions difficult to assess. This is especially troublesome since some of these assertions are the main points the authors highlight as significant findings. In particular:

(1) The authors describe immature female wing flicking as resembling that produced by mature males during agonistic encounters. While I see some similarities, this assessment is subjective. In Figure 1D, the authors present comparative metrics without statistics; thus, it is difficult to assess the validity of the results. Implications, however, can be direct: do females produce acoustic waves to mimic males and deter mating partners (or vice versa)?

(2) From Figure 3F, it is difficult to conclude that the arborization pattern does not differ between mature and immature flies (here, referred to as a 5h vs 10d difference). This may be an artifact of the representative images, but the arborization at 10d appears less dense, particularly around the PI area. If this difference is consistent, this could also reflect neuronal maturation contributing to this phenotype, which is particularly relevant to what the authors discuss in lines 309-339. Differences in synaptic partners might potentially explain the contrasting action of pC1 neurons in immature vs mature females (PMCID: PMC11386958).

(3) The experiments presented do not exclude the possibility that other pC1 neurons, in addition to pC1a neurons, affect the behavior. As written (line 363), the statement indicating that pC1a is the only one affecting immature female flicking is then incorrect.

Reviewer #3 (Public review):

Summary:

This paper proposes and tests a modified reinforcement learning model that can express different decision-making strategies which spontaneously emerge when performing a task and match real animal behavior. A recurrent neural network (RNN) is trained in the style of prior work on meta reinforcement learning (e.g. Wang et al. 2016, 2018), where an initial algorithm is used to train the network and a second algorithm emerges later from the recurrent dynamics of the network. These are termed weight-RL and recurrent-RL, respectively. By making several adjustments to the meta-RL training procedure, the authors find that their version (called hybrid deep reinforcement learning, or H-DRL) shows a better match to real animal behavior and orbitofrontal cortical activity dynamics. Overall, this paper is an improvement on the prior meta-RL model, but it is unclear what neuroscientists should take away from this.

Strengths:

(1) The authors introduce a model, H-DRL, whose main strength is that it can better approximate animal behavior and neural activity on specific tasks compared to its predecessor, meta-RL. This could potentially be important for interpreting the algorithms underlying animal learning.

(2) The changes that have been made from meta-RL are not overly complex.

(3) The model is assessed using two types of decision-making tasks that are similar to many of the tasks used in rodent behavioral and systems neuroscience.

(4) In addition to behavioral data, RNN unit activity is compared directly with single unit orbitofrontal cortical activity. This makes the model appealing for neuroscience applications.

Weaknesses:

(1) In the introduction, the authors mention that other extensions of meta-RL have been tried. How does H-DRL compare with these other modifications?

(2) The authors try to convey the impact of their model in the introduction by stating that, unlike meta-RL, "it embodies a fundamentally different theoretical claim in the context of neuroscience". It is not clear what the fundamentally different theoretical claim is. While meta-RL implements weight updates over longer timescales, H-DRL implements weight updates after each trial. Is this the fundamentally different theoretical claim? If so, that does not seem like a novel concept for behavioral and systems neuroscience.

(3) It is not clear what inspired the specific changes to the meta-RL training procedure. Were they decisions based on incremental trial and error to intentionally reproduce the empirical behavioral and neural results, or were they based on prior logic?

(4) Regarding the inconsistency between OFC neurons and H-DRL in previous outcome encoding (Figure 5c), it would be helpful to speculate on why this happens because it seems to be the only place where H-DRL fails.

(5) Figure 5e seems tangential to the overall message of the paper. The paper is about H-DRL as a superior approach to modelling real behavior and neural activity compared to meta-RL. But this panel, which is the last panel in the paper, is not directly relevant because there is no comparison with the model.

Reviewer #3 (Public review):

Summary:

The authors generated a cross-species single-cell transcriptomic atlas of inner ear and lateral line organs across four species (human, mouse, chicken, zebrafish) and 11 developmental stages. By comparing mechanosensitive hair cells to surrounding supporting cells, they identified hair cell-enriched (HCE) genes, conserved transcriptional programs, and stratified developmental markers. They used these core and temporally stratified gene sets to evaluate hair cell identity and maturation state in models of avian regeneration, mouse cochlear organoids, and transcription factor-reprogrammed fibroblasts. A publicly available web-based resource (HRP Hair Cell Gene Explorer and gEAR portal) was created to facilitate field-wide data exploration.

Strengths:

(1) Comprehensive Multi-Species Benchmark:

Cross-species analysis spanning 43 hair cell populations and 11 developmental stages establishes a rigorous reference dataset for benchmarking hair cell identity across development, cell biology, and regenerative models.

(2) Biological Relevance:

The pan-HCE gene set captures 25% of all known human deafness genes, confirming its strong predictive value for hair cell-specific function and disease mechanisms.

(3) Methodological Rigor & Robust Thresholding:

The use of area under the receiver operating characteristic curve (AUC) provides a platform-independent metric. Testing four calculation strategies (combining 29 mechanosensitive vs. 23 mature populations with unweighted [ES1] vs. species-balanced [ES2] weighting) and taking their intersection ensures robust gene selection without species bias.

(4) Temporal Stratification & Application:

Categorizing pan-HCE genes into early, sustained (ES-HCE), late (L-HCE), and transiently enriched (T-HCE) sets enables tracking of maturation state across different animal and cellular models, proving effective in evaluating regenerating avian hair cells, mouse cochlear organoids (Lgr5^+ lineage), and Gfi1/Atoh1/Pou4f3/Six1-reprogrammed fibroblasts.

(5) Experimental Validation:

Key pan-HCE genes were independently validated across species using spatial transcriptomics, RNAscope, and Hybridization Chain Reaction (HCR).

(6) Community Utility:

Broad accessibility via an interactive ShinyApp and gEAR portal integration facilitates customized field-wide analysis.

Weaknesses:

Weaknesses were considered minor.

(1) Interspecies Homology Resolution:

Machine learning-based clustering (MetaNeighbor) showed that factors such as age, species, and sensory modality often override subtype identity, failing to resolve fine-grained cross-species homologies for specific subtypes (e.g., distinguishing mouse inner vs. outer hair cells relative to chicken tall vs. short hair cells).

(2) Species Imbalance & Mapping Artifacts:

Despite weighting schemes (ES2), teleost genome duplications (1-to-many ortholog mapping in zebrafish) complicate cross-species signal normalization. This remains an overarching issue in many fields when performing cross-species analysis.

(3) Different mechanisms of regeneration:

Converted fibroblasts induced only a percentage of pan-HCE genes (28.7%) and very few transient genes (9.3%). This could reflect incomplete programming towards a fully mature native hair cell state, as the authors suggest. It is also possible that direct programming via transcription factor expression or Lgr5+ cell conversion could employ mechanisms distinct from those used in normal development or in regenerative species.

Reviewer #3 (Public review):

Summary:

In this manuscript, the authors implement a complementary learning system within a pretrained LLM. Each new episode is stored in its own small adapter, a routing step selects the right adapter at recall, and a slower consolidation stage transfers the stored episodes into the base weights. The main contributions are a demonstration that this fast store retains a thousand episodes without the catastrophic forgetting seen under vanilla sequential fine-tuning, a retrieval scheme in which a stored episode is regenerated into the context window so the model can answer questions about it, and a consolidation procedure that transfers the episodes into shared weights while leaving the model's general capabilities largely intact. The authors also show that neither the adapters nor the consolidated weights support direct question answering on their own, which separates storing a memory from being able to access it.

Strengths:

The paper is technically sound and, to my knowledge, one of the first efforts to make the connection between complementary learning systems and the LLM plus adapter configuration explicit and then build it end to end. It is very clearly written and honest about negative results. The authors have built a system in which the fast and slow systems and the transfer between them are all explicit and measurable, on top of semantically rich pretrained representations, which is something memory research has underutilized in the LLM era.

Weaknesses:

My main comment is that the paper should be positioned more explicitly. The framing should be clearer if the paper is more of an ML contribution or a neuroscience contribution (it is both, but there should be an emphasis). Routed adapters/loras are already popular, and many studies have addressed continual learning in the ML literature (gated LoRA and related methods), and the authors should be upfront about this in the introduction rather than only in the discussion to help readers understand the framing earlier. Previous studies on adapters do not diminish the paper, because in my opinion its value is the neuroscience framing, and that is where I think the paper has not explored sufficiently. The classic phenomena that CLS was proposed to explain are cited but not directly tested, which I think is a missed opportunity, since most of them can be tested with materials already in the paper. Below are my main suggestions:

The original 95 CLS paper proposes a slow cortical system because integrated knowledge supports inferences/generalizations that the episodic memory system cannot, and people need time and often sleep to form such generalizations. The paper's adapter loads one episode at a time, but the consolidated model might be able to extract the core rules or schemas of the episodic memories. If consolidation can support inference/generalizations that retrieval cannot, that is the strongest possible argument for the two-system design.

Additionally, in the original CLS proposal, replay is interleaved so that new memories are transferred into cortex alongside old knowledge. Here, consolidation trains on the new episodes only, and the general capability of the LLM degrades accordingly. The effect of rehearsal or pseudo-rehearsal, and the interference with existing knowledge close to the consolidated content, are not measured.

In human memory, repeated visits to the same scenario are a core aspect of episodic memory: you visit your office many times a day with slight changes in context, and episodic memory has to keep track of these visits while knowing which differences should be memorized. In the paper's design, a repeated episode would create a second adapter with a near-identical embedding, and a slightly paraphrased episode would become a new memory. Human memory studies show memory strengthens or updates the existing trace when revisitation happens, as in reconsolidation. The current design also rules out any overlap between adapters, giving a hippocampal module that does pattern separation but not the "pattern completion" half.

Two well-established findings in the consolidation literature are worth examining: consolidated memories keep the gist and lose specific details (Winocur and Moscovitch), and new information consolidates much faster when it fits something already known (Tse et al. 2007's schema study in rodents). The paper's judge scores each character episode on separate details, and the supplement contains an example in which a question about one episode makes the consolidated model reconstruct a different episode from years earlier with the same theme, which resembles a classic "false memory". The current setup in the paper could examine these false memory structures in a much more nuanced way.

I believe experiments tied to the memory, psychology, and cognitive science literature along these lines would greatly strengthen the study, and could make this paper a "template" for how the field can study effects that have been observed in humans but have lacked a concrete and powerful enough modern modeling system.

Reviewer #3 (Public review):

Summary:

The authors seek to validate the effectiveness of an inhibitor of the Pol theta helicase-like domain ATPase activity in its ability to ablate MMEJ activity in cell line models. They then confirm the inhibitor is synthetic lethal in a variety of BRCA1/2 deficient cancer models (and one PALB2 model). Finally, they report apparent effectiveness in treatment of a single patient that failed therapy with PARPi due to 53BP1 deficiency, a hypothesized special use-case for targeting pol theta.

Strengths:

It is a clear bench-to-bedside translation of mechanistic-oriented basic science to a clinical therapy. The experiments are largely rigorously performed. The approaches employed are impressively diverse, from in vitro to cell-line model, to preclinical model, to clinical application. The interpretations made are well supported by the available data.

Weaknesses:

The addition of a few missing details would improve the usefulness to the reader. Additionally, the rationale behind some approaches could be clarified.

Reviewer #3 (Public review):

Summary:

Using realistic mathematical models, Cebrián-Lacasa et al. address the relationship between waves of activation of Cyclin B-Cdk1 that propagate through the cytoplasm of large (~1 mm) oocytes and fertilized eggs and surface contraction waves (SCWs) driven by Rho GTPase activity in the cell cortex. They present numerical simulations of the underlying reaction-diffusion equations that account in broad strokes for both the expected behavior of 'fronts' of Cdk1 activation (that propagate at constant velocity from the nucleus-the source of Cdk1 activity-to the cell cortex) and the unusual behavior of 'backs' of Cdk1 inactivation (that may propagate either away from or towards the nucleus, or exhibit simultaneous inactivation throughout the cytoplasm). They also model Rho GTPase activity in the cortex as an excitable system that propagates SCWs (target patterns, spiral waves, and more complicated patterns). When Cdk1 is activated in the cortex, it phosphorylates and inhibits the RhoGEF, Ect1, which suppresses SCWs by reducing Rho GTPase activity. As the wave-back of Cdk1 inactivation moves across the cortex, Rho GTPase activity recovers abruptly, and SCWs reappear as 'phase waves' whose speed and directionality are determined by the underlying cytoplasmic Cdk1 signal.

Strengths:

As a theoretical examination of an interesting and puzzling aspect of early embryonic development, this study shares the same strengths and weaknesses as all mathematical and computational approaches to molecular cell biology. The mathematical models are precise formulations of the underlying assumptions of the authors (which are quite reasonable in this reviewer's opinion), and the analysis and computational results are dependable consequences of the molecular mechanisms the authors have in mind. The model is expertly analyzed, and the results are both reliable and intriguing. The results are discussed in light of experimental evidence. Because the authors' methods and results suggest novel-and sometimes counterintuitive-avenues for experimental research, this paper is likely to have a significant impact on the field of Rho GTPase signaling in oocytes and early embryos, and perhaps in other cells as well.

Weaknesses:

Like all mathematical models, the underlying assumptions can be critiqued as neglecting this -or-that 'crucial' effect (e.g., mechanical coupling via cortical tension or cytoplasmic flow, as the authors acknowledge), and the highly technical methods of analysis and simulation can be unfamiliar and off-putting to experimental cell biologists. For those who take the time to understand this paper, it may change the way they think about the coupling of cell cycle control (Cdk1 activation and inactivation) and cell surface contraction waves.

Reviewer #3 (Public review):

Summary:

The authors use the advanced technique of cryo-electron tomography to understand the connections between the basal body and the mitochondrion in trypanosomes. They show that this connection is mediated by flexible and extendable filaments.

Strengths:

The authors use an array of advanced cryo-electron microscopy techniques that provide solid evidence that p197 forms the filaments between the basal body and the mitochondrion and demonstrate that these filaments are flexible and able to span a wide range of distances. This provides an important insight into how the trypanosome basal body, which has a dynamic localisation through the cell cycle, can manage its critical connection to the mitochondrion. The filaments provide the necessary flexibility to maintain the basal body - mitochondrion connections as the basal body is repositioned.

Weaknesses:

The authors were unable to directly connect the filaments to the structural models for their protein component, p197 and how the filament flexibility relates to the changes in the repeat region of the protein. In part, this is due to the flexibility of these filaments and demonstrates the limitation of cryo-EM to resolve such structures, but this in itself is an important outcome, as it will inform the community's use of this technology.

Reviewer #3 (Public review):

Summary:

This manuscript presents a resource describing the morphology and distribution of mitochondria across a large part of the central brain of Drosophila. In addition to providing a valuable resource for the community, the authors analyze their dataset in great detail. These analyses reveal interesting differences in mitochondria across cell types and brain regions with regard to morphological parameters, their spatial relationship to pre- and post-synapses, differences in mitochondrial characteristics between neurons that use different neurotransmitters, and between synapses with multiple postsynaptic partners.

Strengths:

The main strength of the paper is the large size of the dataset comprising ca. 6 million segmented mitochondria distributed across more than 20000 neurons. This dataset provides enough statistical power to detect differences in mitochondrial characteristics between brain regions and cell types. An additional strength is the easy accessibility of the data through the neuPrint web interface, enabling the community to explore the dataset and perform further analyses.

Weaknesses:

The study is primarily descriptive. While this is not necessarily a weakness, the manuscript could more clearly discuss potential applications of the dataset beyond pure characterization. Potential improvements include neurotransmitter predictions, cell type classification, or sites of gap junction coupling.

Conclusion:

Taken together, I consider this manuscript to provide a highly valuable resource and analysis that will be useful to researchers interested in mitochondria and neuronal cell biology in Drosophila. Furthermore, the dataset provides potential for researchers to link mitochondrial characteristics to neuronal physiology.

Reviewer #3 (Public review):

Summary:

Dopaminergic neurons (DANs) are known to play a role in conveying rewarding and punishing signals that influence future behaviour. This study uses optogenetic manipulation of a range of subpopulations of DANs to assess their influence in several operant learning paradigms, such that the animal's own behaviour determines the DAN activation. The results show surprisingly inconsistent effects and do not support the widespread assumption that specific DANs consistently convey either positive or negative valence. In one case, the apparent valence of the DAN activation switches over a time frame of minutes from aversive to attractive, and the relevant circuits are further dissected to show this effect is dopamine-dependent, for a specific DAN subset, and contingent on operant control of behaviour.

Strengths:

This study has two major strengths. The first is to address the relatively neglected field of operant learning in Drosophila. The detailed unpicking of learning circuits in the Drosophila brain that has been made possible by neurogenetics and other advances has almost exclusively focussed on classical conditioning paradigms, but these are often not representative of the real behavioural situations that animals face. Cross-comparison of the behavioural results of identified neuron activation in a wider range of paradigms is very welcome. The second is the use of multiple paradigms and a wide-ranging screen to survey the effects across many lines (targeting different DAN populations), including many that have been previously tested in classical conditioning. A further strength is the useful review (in the introduction and discussion) of existing research that already raises problems with the view that a single dimensional positive and negative "value" (as conceived of in standard reinforcement learning theory) can be directly mapped to the activity of two broad clusters of DANs in the brain.

Weaknesses:

The main weakness is that it is difficult from the manuscript to understand what the authors believe is the underlying mechanism by which DAN activation should affect behaviour in operant paradigms, and how this should relate to the better-known role of DAN activity in classical conditioning. For example, they refer to Heisenberg and Wolf's 1991 distinction between operant activity and operant learning. That paper proposed a mechanism involving a goal, some degree of random variation in action, comparison of sensory input to a goal, correlation of the efference copy of the action to the output of this comparison, with the strength of this correlation subsequently shaping the action probabilities. It would help to be explicit about what DAN activity is assumed to represent in this scheme - the outcome of comparison to a goal? The actual assumptions behind the work seem more simplistic: if different groups of DANs 'signal' reward or punishment, animals should persist in actions that activate the reward DANs and desist in actions that activate the punishment DANs. This might be justified by the standard way that innately rewarding/punishing stimuli are operationally defined in learning theory. But what brain circuitry is assumed to underlie the variation and choice of actions, and how is this influenced by DANs?

Perhaps what is most clearly shown is that avoidance behaviour to activation of innately punishing sensory neurons is not directly a consequence of downstream activation of specific DANs, such that DAN activation can be substituted to produce the same behavioural phenomena (at least for the DANs tested here). Indeed, this is how the core results are summarised at the start of the discussion. But should this have been expected? There are a lot of assumptions needed to connect the expected effect of a reinforcement signal in classical conditioning to its effect on operant behaviour that are not made sufficiently explicit.

Appraisal:

The authors met their aim to carry out a (fairly) comprehensive test of the effects of optogenetic activation of a variety of DAN subpopulations under several operant paradigms that differ in relevant respects (group vs. individual testing, freely moving vs. tethered). The lack of consistent results across these paradigms, and generally weak effects (with limited statistical analysis) make it difficult to interpret whether the outcome here is mostly 'noise', but perhaps this is an example where the failure to find a clear effect (as predicted) is itself informative. The paper appropriately describes the limitations (such as the mixed range and specificity of DAN subsets manipulated across the paradigms) which were probably unavoidable given the tools available.

Likely impact on the field:

This work should have an impact in countering assertions that dopamine neurons in the fly brain can be understood as (collectively) conveying a single dimension of valence, from positive to negative, across all behavioural and learning situations. It also provides strong motivation to more clearly understand the nature of operant learning and how/where it might be implemented in the insect brain.

DOI: 10.21203/rs.3.rs-7072571

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Curator: @bandrow

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DOI: 10.21203/rs.3.rs-7072571

Resource: RRID:RRRC_00699

Curator: @bandrow

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Reviewer #3 (Public review):

Summary:

Weber et al. focused on a punishment learning paradigm in Drosophila larvae using primarily high salt as an aversive stimulus. They examined the DL1-cluster of dopaminergic neurons (DANs) consisting of four neurons, mostly important for encoding such punishment. Using temporally precise optogenetic activation and inhibition during both training and testing, the authors show that particularly DAN-f1/g1 activity can bidirectionally alter memory strength and valence of high salt learning. Depending on the timing of the manipulation, artificial DAN activation could also strengthen, weaken, or abolish expression of learned behavior without altering innate preferences. By combining behavioral experiments with computational modeling, the authors developed a connectome-based circuit model in which activity of the DL1 compartment causes output neurons (MBONs) to recruit reward-like DANs via an intrinsic feedback loop. In contrast, models based on independent compartmental plasticity for reward and punishment failed to reproduce the memory valence reversals observed in behavioral experiments. Thereby, the study identified an important feature of the larval mushroom body circuit relying on intercompartmental feedback signals to process learned signals and provide appropriate behavioral outputs.

Strengths:

(1) The study benefits from temporal precision across both memory acquisition and retrieval phases using an optogenetic approach. DAN-f1/g1 function is addressed thoroughly and manipulated across several paradigms, convincingly validating that optogenetic manipulations specifically alter learning but not innate preferences.

(2) The study benefits from treating the DL1 cluster as functionally heterogeneous. By examining individual neurons during retrieval, the authors solidify a prominent role for DAN-c1 in memory retrieval and DAN-f1/g1 in aversive reinforcement.

(3) Computational modeling nicely complements the behavioral results, showing that simpler circuit architectures fail to reproduce the valence reversals observed during behavioral experiments. The success of the cross-compartmental feedback model therefore narrows the range of plausible circuit explanations and supports the authors' circuit-level rebalancing theory.

Weaknesses:

(1) The PI is calculated from the number of larvae occupying each side of the arena after a 5-minute period of free exploration. This is a reasonable summary and standard method to measure the behavioral results, but it provides limited information about how preferences and memory retrieval dynamics may develop over time. While standard in the field, trajectory-based parameters as odor approach behavior could differ between the experiments, so not all information can be retrieved.

(2) Their model argues for cross-compartment interaction in the mushroom body circuit, which is, however, not corroborated experimentally. Silencing individual DL1 neurons during the testing phase had little behavioral effect aside from DAN-c1, leaving the specific retrieval roles of DAN-f1 and DAN-g1 somewhat unresolved, particularly given that their simultaneous inhibition was shown to enhance memory recall.

(3) Another limitation concerns how neuronal dynamics are represented in computational models: whereas the four DL1-DANs are represented individually, the four-neuron pPAM cluster is modelled as a single unit. Together with the limited temporal resolution of the calcium signals, as well as the unknown output dynamics in MBONs, the current model simplifies the cellular organization and physiological dynamics underlying the proposed circuit mechanism. The response parameters of the four DL1-DANs and the pPAM cluster were fitted to previously measured calcium responses evoked by brief high-salt or fructose stimulation. Although these fits reproduce the distinct temporal profiles and stimulus sensitivities observed experimentally, it remains uncertain how faithfully such stimulus-evoked responses capture DAN dynamics.

(4) Blue light activation used in the optogenetic paradigm adds an additional (aversive) stimulus that might interfere with the behavioral outcome. While the authors included all reasonable controls and point out the benefits of being consistent with their previous work, it does add a potential confounder.

Reviewer #3 (Public review):

Summary:

This paper uses correlative FIB-SEM to reconstruct cholinergic and serotonergic axons in mouse somatosensory cortex. The authors wanted to examine how these neuromodulatory axons are organized at the ultrastructural level, specifically whether their vesicles are concentrated at synaptic structures like fast transmitters (glutamate and GABA) or distributed differently. They compare the two types against glutamate and GABA axons in the same datasets, and found that the synaptic vesicles are distributed more homogeneously in the neuromodulatory axons, supporting volume transmission.

Strengths:

The main strength is the dataset. FIB-SEM gives isotropic resolution, so vesicles can be counted and positioned accurately in 3D. The correlative light-EM approach lets them identify genetically labeled axons without using electron-dense stains that would obscure internal structures. This is a clear improvement over previous EM studies that relied on immunolabeling and only looked at varicosities.

The analysis is quantitative and systematic. They don't rely on identifying boutons or varicosities as the unit of analysis. Instead, they sample along the axon centerline at regular intervals, which avoids the bias of only looking at swellings. This is a cleaner way to ask where vesicles actually sit relative to synapses and other structures.

The comparison with glutamate and GABA axons is important. It shows that the differences are not just about neuromodulatory axons being "less synaptic" in a graded way, but qualitatively different in how vesicles are organized. Glutamate and GABA axons concentrate vesicles at synapses; ACh and 5-HT axons don't.

Weaknesses:

An intrinsic weakness of the EM approach is the missing of molecular information. The paper finds vesicles to be distributed homogeneously regardless of potential "post-synaptic" contact elements. However, protein machinaries for vesicle release might still statistically bind to certain postsynaptic elements.

PatientID: N/A

KindredID: 1

Case: M, 3Y0M, Caucasian

DiseaseAssertion: VHL

FamilyInfo: Family history was remarkable for a renal tumor in the paternal grandmother at age 65, treated by nephrectomy in 1998. Furthermore, a maternal uncle had a history of thyroid cancer, and a maternal cousin had a history of breast cancer. The patient’s parents and a 13-year-old half-brother were healthy.

CasePresentingHPOs:HP:0005584, HP:0000790 ( renal cell carcinoma, hematuria)

CaseHPOFreeText: Computed tomographic scan showed a right renal mass. The tumor was impinging on the renal sinus and extended to the renal capsule. The patient underwent a right nephrectomy. In addition, one of five hilar lymph nodes was positive for metastatic disease.

CaseNotHPOs: N/A

CaseNotHPOFreeText: N/A

CasePreviousTesting: N/A

PreviouslyPublished: N/A

SupplementalData: N/A

Variant: p. L188V (c.562C>G)

LegacyVariant: N/A

CaseProblemVariantFreeText: N/

ClinVar: 2225 https://www.ncbi.nlm.nih.gov/clinvar/variation/2225/

CAID: N/A

gnomAD: 0.00002121 https://gnomad.broadinstitute.org/variant/3-10191569-C-G

VariantEvidence: N/A

MutationType: missense_variant;transversion

CivicName: L188V (c.562C>G)

MultipleGeneVariants: t(X;1)(p11.2; p34.3)

via u/radiant_control at https://www.reddit.com/r/TypewriterRepair/comments/1xk6tkj/olympia_sg3_right_margin_stop/

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DOI: 10.21203/rs.3.rs-7072571

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DOI: 10.21203/rs.3.rs-7072571

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DOI: 10.21203/rs.3.rs-7072571

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DOI: 10.21203/rs.3.rs-7072571

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DOI: 10.21203/rs.3.rs-7072571

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DOI: 10.21203/rs.3.rs-7072571

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DOI: 10.21203/rs.3.rs-7072571

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DOI: 10.21203/rs.3.rs-7072571

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DOI: 10.21203/rs.3.rs-7072571

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DOI: 10.21203/rs.3.rs-7072571

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Reviewer #3 (Public review):

Strengths:

Mahieu and colleagues ask whether mitochondrial genetic variation helps explain differences in human telomere length. They selected seven donors from a Flow-FISH reference cohort of 491 individuals and compared their mitochondrial backgrounds in cybrids sharing the same nuclear background.

The combination of telomere and mitochondrial assays is a strength. The association between low complex I activity and telomere shortening, together with the NAC/NR rescue in Cyb2, provides useful evidence linking mitochondrial function to telomere maintenance. The correlation between donor telomere length and cybrid ROS is also interesting, although the cybrid results are more persuasive than the claims about inheritance.

Weaknesses:

(1) The authors have clarified that the seven donors include intermediate telomere lengths. Their analyses excluding donors #1, #3 and #6 are reassuring, since the correlation persists in each case. However, these results appear only in the response, and the full leave-one-out analysis is not reported. The small, selected sample still limits how broadly the correlation can be interpreted.

(2) The revised manuscript makes the distinction between the cybrid and donor findings clearer. However, CI activity shows no significant association with donor telomere length. The proposed PARP1 mechanism also remains untested: the authors acknowledge that they did not establish whether PARP1 is required for the NAC/NR rescue, but still describe its role too strongly.

(3) The authors appropriately acknowledge that the ATP6 A177T association is inconclusive (p = 0.153). Some inheritance claims remain stronger than this warrants. The family observations are too limited to separate mitochondrial from nuclear or shared environmental effects, and the cybrid experiments do not isolate ATP6 A177T from the other variants transferred with it.

Reviewer #3 (Public review):

Summary:

Current theories suggest psilocybin promotes meta-learning, modifies learned associations, and promotes flexibility, contributing to its transdiagnostic clinical relevance. However, the effects of psilocybin on neural state dynamics during learning and decision-making are unclear. Jacobs et al. use a rat model to examine how psilocybin changes prefrontal cortex encoding during a value-based probabilistic choice task. The authors found psilocybin increased high-value choices when uncertainty was low and increased choice variability when uncertainty was high, compared to baseline performance. A reinforcement learning model found psilocybin decreased side bias and increased reward learning while decreasing the unrewarded learning rate. Encoding of rewarded actions was enhanced in the mPFC while unrewarded actions were attenuated.

Strengths:

The neural correlates and computations underlying the impacts of psychedelics are poorly understood, and this study examines these through well-established decision-making approaches. These data show changes in mPFC activity during a dynamic task, allowing for analysis across different contexts and events. The data presented provide some support for leading theories on psilocybin's therapeutic use in promoting meta-learning and flexibility. The combination of techniques, including decision-making, computational modeling, and neural recordings, is appropriate, powerful, and needed to make sense of the underlying change in experience triggered by psilocybin.

Weaknesses:

An unfortunate weakness in the design that limits the interpretability of the findings is a lack of control data under saline administration, and a lack of comparison of psilocybin to saline rather than baseline. Psilocybin performance is compared to a single baseline session, which lacks the effect of an injection that would be present in a saline control. There is some evidence that mild stress can itself impact outcome encoding. Supplemental data in this manuscript suggest there is no significant difference in probability of selecting the optimal choice on low uncertainty trials between baseline and saline; however, the direction of impact of the saline injection is in the same direction as psilocybin in the main figures. This means that the mild stress of simply receiving an injection of saline may not be totally neutral with regard to these measures, and may contribute to the effects attributed to psilocybin at both a behavioral and neural level.

Reviewer #3 (Public review):

Summary:

This study investigates how task components can be learned and transferred across different task contexts. The authors designed two consecutive sequence learning tasks, in which complex image sequences were generated from the combination of two graph-based structural "building blocks". One of these components was shared between the prior and transfer task environments, allowing the authors to test compositional transfer. Behavioral analyses using generalized linear models (GLMs) assessed participants' sensitivity to the underlying structure. MEG data were recorded and analyzed using classifications and feature representational similarity analysis (RSA) to examine whether neural similarity increased for stimuli sharing the same relational structure. The paper aims to uncover the neural dynamics that support compositional transfer during learning.

Strengths and weaknesses:

I found the methods and task design of this paper difficult to follow, particularly the way stimuli were constructed and how the experimental sequences were generated from the graph structures. These aspects would be hard to replicate without some clarification. I appreciate the integration of behavioral and neuroimaging data. The overall approach, especially the use of compositional graph structures in sequence learning, is interesting and could be used and revised in further studies in compositionality and transfer learning. I appreciated the authors' careful interpretation of their findings in the discussion. However, I would have liked a similar level of caution in the abstract, which currently overstates some claims.

Comments on revised version.

No further comments. I thank the authors for their diligence in addressing my comments.

Reviewer #3 (Public review):

Summary:

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

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

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

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

Strength:

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

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

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

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

Weakness:

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

Reviewer #3 (Public review):

Summary:

The manuscript reports that Yoda1 and Yoda2 agonize PIEZO2 in a manner similar to PIEZO1, increasing open probability and stretch sensitivity, but the mechanism underlying this sensitivity is incomplete. Mutagenesis was shown exclusively in PIEZO1, with no corresponding mutagenesis in PIEZO2, so the proposed mechanism in PIEZO2 is inferred by homology rather than directly tested. All experiments use mouse PIEZO2, and the human ortholog should be used before generalizing the proposed reinterpretation of the field.

Strengths:

The pressure-clamp electrophysiology demonstrating a shift in half-activation pressure for PIEZO2 is compelling evidence in support of the central claim.

Reviewer #3 (Public review):

Summary:

While our knowledge regarding visual opsins is largely very good, a lot more uncertainty exists around the role of non-visual opsins. Using the power of the Drosophila melanogaster model system, Kirsh et al. investigate the role of the non-visual opsin Rhodopsin7 (Rh7). Expression analysis, based on Rh7-Gal4>UAS-GFP and HRC in situ staining, reveals strong expression in the optic lobes and somewhat weaker, but nevertheless extensive expression in the brain. An investigation of motor activity reveals that loss of function leads to an altered day and night rhythm, specifically decreasing activity during the dark phase. These flies were also less sensitive, but still responsive to a light-induced startle response and showed deficiencies in the optomotor response. To further investigate how Rh7 may modulate these responses, inspired by the Dark line of flies (which were kept in the dark for ~1400 generations) and which has accumulated C-terminal related losses, the authors conducted rescues with an intact and a C-terminal-deficient Rh7 and were able to pinpoint that region as an important driver of related behavioral shifts. These findings are particularly intriguing as Rh7 represents an ancient opsin with phylogenetic and mechanistic parallels to mammalian melanopsin.

Strengths:

The paper is well-written and contains high-quality data with appropriate sample sizes, and the conclusions are well supported.

Weaknesses:

No weaknesses were identified by this reviewer, but the following recommendations are made:

(1) The authors should clarify exactly what tissues were taken for the comparative qPCR. This is particularly interesting in terms of the retina. Since Rh7 appears not to be expressed within the photoreceptor cells of the retina, this raises the important question as to which cells it is expressed in. To address this important question, it would also be helpful to include an expression analysis of the retina itself (by extending the RH7-GFP expression patterns and/or adding HCR in situ of the ommatidia array). The cell types of the retina are very well classified, and some evidence already exists for Rh7 expression in support cells (e.g., Charlton-Perkins et al., (2017); PMID: 28562601). This study has a unique opportunity to investigate this further by adding these critical data for a more complete picture of Rh7.

(2) Mammalian opsins should be included in the phylogenetic analysis illustrated in Figure 2A and indicate their position on the tree. This will allow readers to better put the authors' statements regarding the intermediate position of Rh7 into perspective. In addition, note that the distinction between red and deep red is easy to miss regarding the Rh7 cluster. Perhaps the authors could use a more distinct colour scheme, for example, orange and deep red.

(3) More details should be provided on the optomotor response experiments. Specifically, specifications of the frequencies used for the optomotor response are needed. Results show a relatively large level of variation, which may be due to different angular perspectives that flies may have had while viewing the stimulus. If possible, provide videos as examples, as they will make it clearer to viewers how much flies could move around in the setup (from the methods, it seems they could move within the 2.2 of the 3 cm diameter of the arena, which would lead to substantial differences in the visual angle of the viewed grating.

Reviewer #3 (Public review):

Summary:

This manuscript presents a comprehensive and well-executed investigation into the metabolic role of D-serine in the central nervous system. The authors provide solid evidence that D-serine competitively inhibits mitochondrial L-serine transport, thereby impairing one-carbon metabolism. This stereoselective mechanism reduces glycine and formate production, suppresses cellular proliferation, and induces apoptosis in immature neural cells and glioblastoma stem cells. Developmental analyses further reveal a physiological enantiomeric shift in serine metabolism during neurogenesis, aligning with the transition from proliferation to maturation. Overall, the study bridges developmental neurobiology, cancer metabolism, and amino acid transport, uncovering a previously unrecognized metabolic function of D-serine beyond its role in neurotransmission.

Strengths:

(1) The discovery that D-serine inhibits one-carbon metabolism by competing for mitochondrial L-serine transport-rather than through enzymatic inhibition or receptor-mediated signaling-represents a significant and previously underappreciated mechanism. This finding has broad implications for understanding metabolic regulation during neurodevelopment and offers potential relevance for targeting metabolic vulnerabilities in cancer.

(2) The authors integrate metabolomics, mitochondrial transport assays, molecular dynamics simulations, genetic and pharmacologic perturbations, transcriptomics, and both in vitro and ex vivo models. The breadth of experimental approaches, combined with the coherence of the findings across systems, provides strong support for the central conclusions and enhances the overall impact of the study.

(3) The temporal shift in D-/L-serine levels during neurodevelopment is elegantly linked to the transition from proliferative to mature neuronal states. The selective vulnerability of neural progenitors and tumor cells-contrasted with the resistance of mature neurons-highlights a biologically meaningful and potentially targetable metabolic distinction.

Reviewer #3 (Public Review):

Per my training and expertise, my evaluation and feedback below are focused on the behavioral components of this study and not the modeling. The authors use heat avoidance thermotaxis behavior in adult flies as a behavioral read out of decision-making with the goal of providing a novel quantitative analysis of the navigational strategies that contribute to heat avoidance behavior. Breaking down a specific behavior (here, heat avoidance) into component behavioral motifs can provide a more detailed analysis that can contribute to deeper understanding of navigational strategies within Drosophila and potentially aid understanding of navigational strategies at a broader level. The authors describe temperature preference behaviors, as has been previously reported and examine the role(s) of thermoreceptors localized to the antennae compared to the rest of the fly. The thermotaxis behavior is then broken down into several parameters with the goal of gaining deeper insight into how and when the fly initiates and generates heat avoidance behavior. The work would be further strengthened and clarified by more completely setting the findings within the context of the field both by including relevant citations and via text that describes this within the manuscript. Additionally, while the authors discuss choosing the temperatures in the assay to allow for more "straightforward interpretation", it would be important to note that this might not be what the fly actually experiences and although it might drive a "decision" it might not be revealing the ethologically accurate behavior. Additionally, Figure 2 in particular can be revised to aid the reader in understanding and evaluating the results. For example, writing out the terms on the y-axis (or making a table a reader could easily reference) and including statistically significant findings on the figure itself would allow the reader to more easily draw their own conclusions. Finally, a more thorough discussion would help make the findings more accessible and demonstrate how these findings have the potential to be of broad interest to many disciplines. For example, placing findings in the context of navigation and quantitative behavioral analysis across species and referring to figures within the discussion section itself.

Reviewer #3 (Public review):

Summary:

The authors established an experimental system that reproduced three-dimensional triphasic epithelia, i.e., the original epithelium, its EMT, and MET. Keratinocytes (KCs), skin epithelial cells, placed on a microporous membrane migrated through 3.0-um or larger micropores. The 3.0-um-pored membrane induced an epithelial structure with three states: stratified KCs above the membrane, KCs showing EMT within the micropores, and a new stratified epithelium under the membrane. The membrane with larger micropores failed to maintain this triphasic epithelia. Live imaging revealed that KCs moved in a reciprocating manner, with actin-rich filopodia-like KC structures extending into and out of the 3.0-um micropores, while the cells migrated unidirectionally into larger micropores. KO of Piezo1 and keratin 6 increased KC entry to and exit from the 3.0-um micropores. Their results demonstrate that benign keratinocytes migrate through confined spaces in a reciprocating manner, which might help form triphasic epithelia, recapitulating wound healing processes.

Strengths:

Careful observation of the behaviour of keratinocytes on the different sized pores. CrispR-Cas9 gene editing to KO Piezo 1 and keratin 6 isoforms in HaCaT keratinocytes.

Reviewer #3 (Public review):

The authors employed the BindCraft platform to develop binders targeting the chemokine CCL25, a selective activator of the chemokine receptor CCR9. They successfully generated two classes of binders: one that inhibits all CCL25-mediated CCR9 activation, and another that permits CCR9 G protein signaling while simultaneously preventing arrestin recruitment. These tools will enable the dissection of arrestin involvement in regulating cell migration.

Reviewer #3 (Public review):

Summary:

Hossain et al. investigate the role of ITK as a central regulator of autoimmune lung injury. They used ITK-deficient mice and the pristane-induced pulmonary hemorrhage (PH) model to show that ITK deficiency confers protection against PH. The adoptive cell transfer experiment suggests a possible role for altered Treg cells in ITK-deficient mice in regulating the inflammatory response in the lungs of pristane-injected mice. This study shows that targeting the ITK axis may be beneficial by reducing systemic inflammatory injury that contributes to poor outcomes in PH.

Strengths:

This study highlights the importance of ITK in regulating pulmonary hemorrhage. The enrichment of Treg cells is known to confer protection in autoimmunity-mediated alveolar damage. However, the involvement of ITK in regulating the Treg cells' function is interesting and could be explored as a novel therapeutic approach for chronic inflammation.

Comments on revised version:

The authors have answered my comments by incorporating new results and clarification to their observation.

Proband: FA_II:1, male uknown age

FamilyDetails: heterozygous unaffected parents, parents were first cousins, VWF:Ag on low end of reference range

Labs: prolonged bleeding time (15min), reduced VWF:Ag (0.06 IU/mL), FVIII:Ag (0.18 IU/mL), FVIII:C (0.20 IU/mL), and VWF:RiCoF (0.06 IU/mL), absent multimers

Genotype: p.Arg273Trp reported as c.1067C>T (MANE transcript is 817C>T)

CAID: CA228829

Proband: FB_II:3, male age unknown

Family details: parents are unaffected heterozygotes, VWF:Ag on the low end of reference range

Labs: prolonged bleeding time (15min), reduced VWF:Ag (0.09 IU/mL), FVIII:Ag (0.33 IU/mL), FVIII:C (0.21 IU/mL), and VWF:RiCoF (0.04 IU/mL), absent multimers

Genotype: p.Arg273Trp reported as c.1067C>T (MANE transcript is 817C>T)

CAID: CA228829

Proband: FC_II:6, male age unknown

FamilyDetails: parents are unaffected hets, first cousins, fathers VWF:Ag at very low end of reference

Labs: prolonged bleeding time (>20min), reduced VWF:Ag (less than 0.01 IU/mL), FVIII:Ag (0.06 IU/mL), FVIII:C (0.09 IU/mL), and VWF:RiCoF (less than 0.01 IU/mL), absent multimers

Genotype: p.Arg273Trp reported as c.1067C>T (MANE transcript is 817C>T)

CAID: CA228829

Supplementary Table S1 & S2 Proband and Variant Information:

Case71: GT75, Female, 9 years old, French/African

DiseaseAssertion: Glanzmann thrombasthenia

FamilyInfo: N/A

ParentalGenotype: N/A

CasePresentingHPOs: HP:0031364, HP:0000421, HP:0000225

(Ecchymosis, epistaxis, gingival bleeding)

CaseHPOFreeText: Lots of deciduous teeth with bleeding, hematomas in the eye and under the clavicle

CaseNotHPOs: N/A

CaseNotHPOsFreeText: N/A

ProteinExpression: Flow cytometry showed less than 5% αIIbβ3 (See Supplementary Table 1)

PlateletAggregation: Absent platelet aggregation (See Supplementary Table 1)

CasePreviousTesting: Sanger sequencing of ITGA2B and ITGB3

Gene: ITGA2B

Variant: NM_000419.3:c.*165T>C

LegacyVariant: N/A

ClinVar: N/A

CAiD: CA915940530

gnomAD: N/A

PMID: PMID:27057166

Gene: TPM1

Disease: hypertrophic cardiomyopathy 3

MonDO: MONDO:0007267

InheritancePattern: AD

Case#: Family MI, Northern European

CasePresentingHPOs: HP:0001639

CaseHPOFreeText:

CaseNotHPOs:

CaseNotHPOFreeText:

CasePreviousTesting:

CaseMethod1:

CaseMethod2:

CaseGenotypingMethod: PCR amplification followed by Cycle Sequencing

Variant: The nucleotide variant positions here refer to those described in the initial cloning of the gene in 1988 (PMID: 3336363), but nucleotide G579A here aligns to NM_001018005.2(TPM1):c.523G>A (p.Asp175Asn).

ClinVar: 12456

CAID: CA018106

gnomAD: Grpmax FAF = 7.900e-7, SNV: 15-63060899-G-A, gnomADv4_D175N

VariantEvidence:

CaseAddInfo:

CasePMIDs: PMID:8327508

Case#: Family MZ, Northern European

CasePresentingHPOs: HP:0001639 ( Hypertrophic cardiomyopathy)

CaseHPOFreeText:

CaseNotHPOs:

CaseNotHPOFreeText:

CasePreviousTesting:

CaseMethod1:

CaseMethod2:

CaseGenotypingMethod: PCR amplification followed by Cycle Sequencing

Variant: The nucleotide variant positions here refer to those described in the initial cloning of the gene in 1988 (PMID: 3336363), but nucleotide A595G here aligns to NM_001018005.2(TPM1):c.539A>G (p.Glu180Gly).

ClinVar: 12455

CAID: CA019017

gnomAD: 15-63060915-A-G not in gnomAD v4.0.0

VariantEvidence:

CaseAddInfo:

CasePMIDs: PMID:8327508

Case#: ATM02_V-3

Demographics: Male, 18 yrs at report

CasePresentingHPOs: HP:0000752, HP:0001581

CaseNotHPOs:

CasePreviousTesting:

CaseMethod1:

CaseMethod2:

CaseGenotypingMethod:

Variant: NM_017890.4:c.6879delT

ClinVar:

CAID: CA4824093

gnomAD:

VariantEvidence: This variant has been reported in two apparently unrelated families of common ethnicity, and therefore likely founder mutation. Hence, the score is reduced from default.

CaseAddInfo:

CasePMIDs:

Reviewer #3 (Public review):

Summary

The work of Pal and colleagues considers a hierarchical and multi-population version of the "oscillatory recurrent gated neural integrator circuits" (ORGaNICs) model, showing through analytics that the model captures multiple relevant experimental results: first of all, its oscillatory dynamics produce a profile with high resemblance to experimental results, both in terms of decay of power at high frequency and in terms of shifting peak as a function of stimulus contrast. Second, inter-areal communication subspace dimensionality is lower than within-area dimensionality. The authors then proceed to further characterize the model's response properties as a function of input and feedback gain. In particular, they find that frequencies transmitted with higher strength also carry more information, that changing gain modifies the dimensionality of communication subspaces, and that these properties can be used in a three-layer model, where an upstream area can select which downstream area to communicate to, based on the strength of feedback gain.

Strengths

This work demonstrates that a single-circuit model with normalization properties can capture both the oscillatory dynamics and the inter-areal communication properties measured in cortical circuits, matching multiple experimental results. The full analytical tractability of the model is highly advantageous, allowing for easier exploration of parameters, replicability, and effective interpretations of results compared to purely numerical approaches.

The work also makes a useful conceptual link between normalization, coherence-based communication, and subspace-based communication. In particular, it shows how both phenomena can emerge from the same circuit dynamics, where normalization is a key factor.

Interestingly, the model is also extended to multiple areas, showing how attention (in the form of changes in feedback gain) can synchronize the activity of a downstream area with one of two upstream areas, thus effectively selecting which area to communicate with.

In general, this is an interesting computational framework and a useful starting point for future modeling work. A particular strength is that it connects normalization, oscillatory dynamics, coherence, and communication subspaces within one analytically tractable model, making it possible to generate mechanistic hypotheses about when inter-areal communication should be stronger, lower-dimensional, or preferentially routed through feedback.

Reviewer #3 (Public review):

Summary:

In this manuscript, the authors describe the results of a high throughput screen for small molecule activators of GCN2. Ultimately, they find 3 promising compounds. One of these three, compound 20 (C20) is of the most interest both for its potency and specificity. The major new finding is that this molecule appears to activate GCN2 independent of GCN1, which suggests that it works by a potentially novel mechanism. Biochemical analysis suggests that each bind in the ATP binding pocket of GCN2, and that at least in vitro C20 is a potent agonist. Structural modeling provides insight into how the three compounds might dock in the pocket and generates testable hypotheses as to why C20 perhaps acts through a different mechanism than other molecules.

Strengths:

Of the 3 compounds identified by the authors, C20 is of the most interest, not just for its intriguing mechanistic distinction as being GCN1-independent (shown genetically in two distinct cell lines, CHO and 293T, and in contrast to other GCN2 activators) but also for its potency. Ultimately, C20 might be a tool for providing mechanistic insight into the details of GCN2 activation and regulation and could be exploited therapeutically.

Weaknesses:

The chief limitation of this work is that the experiments exploring the effects of C20 on ISR output in cells are limited, so how useful these compounds are both experimentally and therapeutically remains to be determined.

Comments on revised version.

The authors have satisfactorily addressed my comments. A more extensive analysis of UPR signaling in cells (transcription and cell death in particular) would have further strengthened the paper, but that can be left to future work.

Case: Patient 2, F, Hungarian

DiseaseAssertion: VWD type 3

FamilyInfo: compatible with recessive inheritance

ParentalGenotype(s): n/a

CasePresentingHPOs: n/a

CaseHPOFreeRext: Bleeding score: 23, VWF:Ag (IU dL−1): < 1, VWF:CB (IU dL−1): 1, FVIII:C (IU dL−1): 10, VWF:RCo below detection limit (<10 IU dL−1), not detectable VWF on multimer gels, bleeding episode severity increased after the menarche

CaseNOTHPOs: n/a

CaseNOTHPOFreeText: no inhibitor detected, did not become refractory to factor replacement therapy

CasePreviousTesting: n/a

Gene: VWF

Variant:

delEx1‐3 (delEx1‐3), Exon 1–3

c.2435delC (p.Pro812ArgfsX31), Exon 18

Intron 40 VNTR: 18/19

Note: multimer electrophoresis, Recombinant VWF antigen concentrations and Collagen binding activity (VWF:CB) measured by ELISA, direct sequencing of the 51 exons and the exon‐intron boundaries, Breakpoint analysis and breakpoint‐specific PCR

PatientID: 4

KindredID: 4

Case: F, 16Y0M, Ethnicity Unknown

DiseaseAssertion: retinal capillary hemangioma

FamilyInfo: N/A - family history was unremarkable. The paper states however that this patient inherited the duplication from a nonsymptomatic parent.

CasePresentingHPOs: HP:0009711 (retinal capillary hemangioma)

CaseHPOFreeText: a 16- year-old girl referred to this center for VHL testing due to an isolated retinal angioma

CaseNotHPOs: N/A

CaseNotHPOFreeText: N/A

CasePreviousTesting: N/A

PreviouslyPublished: N/A

SupplementalData: N/A

Variant: c.*1149A>G

LegacyVariant: N/A

CaseProblemVariantFreeText: N/A

ClinVarID: N/A

CAID: CA2573130264 https://reg.clinicalgenome.org/redmine/projects/registry/genboree_registry/by_caid?caid=CA2573130264

gnomAD: N/A

VariantEvidence: Quantitative Southern blot/real-time quantitative PCR analyses was normal in this patient. Known polymorphic variant on the 3’UTR of the VHL gene, as well as the 5’UTR. PCR–RFLP assay approach showed that both alleles were expressed in apparently equimolar amounts (Fig. 2d) suggesting that the 11 bp duplication has no effect on expression of the affected allele.

MutationType: 3_prime_UTR_variant

CivicName: c.–65_–55dup11 AND 3' UTR alteration (c.*1149A>G)

MultipleGeneVariants: Germline, VHL, c.–65_–55dup11

Reviewer #3 (Public review):

Liu, He, et al. present results suggesting hippocampal ripples support short-term working memory possibly via coupling with lateral temporal ripples. The basic finding that hippocampal ripples increase during a 7 s working memory maintenance period is intriguing and previously not shown, although the lack of control analyses in other MTL regions limits the importance of the finding. The paper moves onto a hippocampal-lateral temporal ripple coupling analysis that shows evidence of memory reinstatement of late encoding categorical representations, although don't necessarily relate to the main hippocampal ripple results found earlier in the paper.

(1) "Thus, the lack of association between VSTM-delay ripples and later cued recall raises a possibility: ramping-up ripple dynamics during active maintenance may support online VSTM, whereas LTM formation may depend more on ripple events occurring during post-encoding time windows." The idea that ripples occur during post-encoding instead of encoding is not supported by Henin et al. (2021) Brain or Sakon et al (2024) J of Neuro. No one has replicated the post-encoding ripples in Norman et al 2019, which appear to be a statistical fluke due to the lack of ripple tuning during that window.

(2) Thank you for doing the gamma comparison-it's very important that people keep investigating ripples vs. high gamma. I also appreciate the use of a direct interaction test comparing them even though the results did not show a significant difference in slopes.

Even with 1/3 the electrodes I maintain that the AMY control would be quite important to differentiate high gamma (frequently shown in AMY) and ripples (do not occur in AMY-either in animals or humans). It's ok if the error bars are noisy and I'd even be fine with pooling AMY+ERC as a non-hippocampal MTL control. That way the field doesn't have to wholly rely on "future studies" as written in the (helpful) revised Discussion.

(3) Thanks for taking a look.

(4) This is a nice effect. Z=1.8 for a three-way interaction despite only 13 participants seems meaningful to me.

(5) I appreciate the change. I strongly recommend changing each row to channel X trial, since superimposing with rows confuses the participant-to-participant comparisons (it's not in the spirit of what a raster is meant to reveal). I also suggest shrinking the plot in the y-direction to make visualizing the ramp easier. Visualization aside, the swarm plot of participant-level ramping effects is very important and really hammers home the nice ramping effect. Congrats.

(6) I would suggest replacing Figs. 2b-e with Fig. S4. Using the entire Encoding period is misleading considering the clear tuning from 0-1 s.

(7) This makes more sense, thank you.

(8) Better, although I think the proper interaction test is between maintenance with encoding. Since the swarms show Remember < Forget for Encoding now, however, it's less of an important point.

(9) Thanks for the more detailed explanation. Based on past literature it seems unlikely it takes over one second to reinstate semantic information (see the same Encoding ripple references above...or a long line of HFA or even concept cell work), but your classifier shows what it shows. So I'm ok with the analysis and presentation even if I'm suspect of the theory.

(10) Thank you for including the interaction tests. I once again disagree with the theoretical framework since Encoding also has salient visual inputs yet shows clear tuning with decoding not significantly different from maintenance (what causes those big error bars in Fig. 5d, left??). That said, I'm satisfied with the presentation since they report this interaction between Encoding and Maintenance in Results.

(11) Thanks, I think these were important analyses to add. I'm not sure what to make of the fact that coupled ripples don't increase considering that hippocampal ripples do, so by statistical chance alone you would think they should, but it's not a major point.

Reviewer #3 (Public review):

Summary:

The authors established an experimental system that reproduced three-dimensional triphasic epithelia, i.e., the original epithelium, its EMT, and MET. Keratinocytes (KCs), skin epithelial cells, placed on a microporous membrane migrated through 3.0-um or larger micropores. The 3.0-um-pored membrane induced an epithelial structure with three states: stratified KCs above the membrane, KCs showing EMT within the micropores, and a new stratified epithelium under the membrane. The membrane with larger micropores failed to maintain this triphasic epithelia. Live imaging revealed that KCs moved in a reciprocating manner, with actin-rich filopodia-like KC structures extending into and out of the 3.0-um micropores, while the cells migrated unidirectionally into larger micropores. KO of Piezo1 and keratin 6 increased KC entry to and exit from the 3.0-um micropores. Their results demonstrate that benign keratinocytes migrate through confined spaces in a reciprocating manner, which might help form triphasic epithelia, recapitulating wound healing processes.

Strengths:

Careful observation of the behaviour of keratinocytes on the different sized pores. CrispR-Cas9 gene editing to KO Piezo 1 and keratin 6 isoforms in HaCaT keratinocytes.

Weaknesses:

The authors have improved the observed weaknesses including better statistical analysis and more detail on replicates. They have also performed staining for laminin beta3 chain.

Reviewer #3 (Public review):

In this manuscript, Negreira et al. propose a new scDNAseq method, using semi-permeable capsules (SPCs) and primary template-directed amplification (PTA). The authors optimize several metrics to improve their predictions, such as determining GC bias, Intra-Chromosomal fluctuation (ICF -metric to differentiate replicative and non-replicative cells) and Intra-chromosomal coefficient of variation (ICCV - chromosome read distribution). The coverage evenness was evaluated using the fini index and the median absolute pairwise difference between the counts of two consecutive bins. They validate the proposed method using two Leishmania donovani strains isolated from different countries, BPK081 (low genomic variability) and HU3 (high genomic variability). Then, they showed that the method outperforms WGA and has similar accuracy to the discontinued 10X-scDNA (10X Genomics), further improving on short CNV identification. The authors also show that the method can identify somy variations, insertions/deletions and SNP variations across cells. This is a timely and very relevant work that has a wide applicability in copy number variation assessment using single-cell data.

I really appreciate this work. My congratulations to the authors.

Reviewer #3 (Public review):

Summary:

Hossain et al. investigate the role of ITK as a central regulator of autoimmune lung injury. They used ITK-deficient mice and the pristane-induced pulmonary hemorrhage (PH) model to show that ITK deficiency confers protection against PH. The adoptive cell transfer experiment suggests a possible role for altered Treg cells in ITK-deficient mice in regulating the inflammatory response in the lungs of pristane-injected mice. This study shows that targeting the ITK axis may be beneficial by reducing systemic inflammatory injury that contributes to poor outcomes in PH.

Strengths:

This study highlights the importance of ITK in regulating pulmonary hemorrhage. The enrichment of Treg cells is known to confer protection in autoimmunity-mediated alveolar damage. However, the involvement of ITK in regulating the Treg cells' function is interesting and could be explored as a novel therapeutic approach for chronic inflammation.

Weakness:

The novelty of this study lies in the association between ITK-deficient Tregs and pulmonary hemorrhage in autoimmunity. One limitation of this study is that the authors performed all experiments in ITK global knockout mice, in which not only T cells but all other cell types are deficient in ITK. Therefore, further studies are required for a mechanistic rationale for targeting ITK in severe inflammatory lung disease.

Comments on revised version:

The authors have answered my comments by incorporating new results and clarification to their observation.

Proband: F4_AM, 27yo (at report) female

Phenotypes: HP:0030134, HP:0003010, HP:0030129

Family: Both parents carry the variant. All het carriers were classified type 1

Labs: FVIII 0.02 IU/mL, VWF 0.03 IU/mL (below detection threshold)

Variant: NM_000552.5:c.4975C>T

CAID: CA114141

PMID: PMID:16043485

Gene: TPM1

Disease: hypertrophic cardiomyopathy 3

MonDO: MONDO:0007267

InheritancePattern: AD

Reviewer #3 (Public review):

Summary:

This study uses bulk mRNA sequencing to profile transcriptional changes in intestinal cells during the early postnatal period in mice-a developmental window that has received relatively little attention despite its importance. This developmental stage is particularly significant because it parallels late gestation in humans, a time when premature infants are highly vulnerable to necrotizing enterocolitis (NEC). By sampling closely spaced timepoints from birth through postnatal week four, the authors generate a resource that helps define transcriptional trajectories during this phase. Although the primary focus is on murine tissue, the authors also present limited data from human fetal intestinal biopsy samples and organoids.

Strengths:

The close temporal sampling in mice offers a detailed view of dynamic transcriptional changes across the first four weeks after birth. The authors leverage these close timepoints to perform hierarchical clustering to define relationships between developmental stages. This is a useful approach, as it highlights when transcriptional states shift most dramatically and allows for functional predictions about classes of genes that vary over time. This high-level analysis provides an effective entry point into the dataset and will be useful for future investigations. The inclusion of human fetal intestinal samples, although limited, is especially notable given the scarcity of data from late fetal timepoints. The authors are generally careful in their presentation of results, acknowledging the limitations of their approach and avoiding over-interpretation. As they note, this dataset is intended as a foundation for their lab and others, with secondary approaches required to more fully explore the biological questions raised. The revised manuscript also addresses many of the issues of clarity and presentation raised in the original review.

Weaknesses:

A limitation of the study is the use of bulk mRNA sequencing on unsorted cell populations to draw conclusions about individual cell types. This is particularly challenging for intestinal epithelial cells, where few genes are exclusively expressed in single cell types. For instance, markers such as Lgr5 and Olfm4 are enriched in intestinal stem cells (ISCs), but are also expressed by other absorptive and secretory lineages. Although the authors incorporate marker-based deconvolution analyses, the epithelial signatures used here are not among the cell populations originally validated for mMCPcounter. Conclusions that specific epithelial populations increase or decrease across timepoints would benefit from more robust systematic, complementary validation.

Validation of the sequencing data in this study remains limited. The authors have added imaging/IF-based validation of mesenchymal populations; however, validation otherwise relies primarily on qPCR, which measures expression using a similar modality rather than providing orthogonal support. Many of the epithelial cell type-specific dynamics inferred from the bulk sequencing and deconvolution analyses are therefore not independently validated. Moreover, the regional differences reported in Lgr5, Olfm4, and Ascl2-appearing much higher in proximal than distal samples-were not recapitulated by qPCR validation of Olfm4. Additional orthogonal validation of these cell type-specific dynamics would be valuable in future studies.

Finally, the human fetal biopsy samples represent a potentially valuable component of the study given the scarcity of data from these developmental timepoints, but the conclusions that can currently be drawn from these samples are limited. The central figure presenting these data shows immunofluorescence for LGR5, a single stem cell marker, and the staining at day 35 is difficult to interpret. The data support localization of LGR5-positive cells to crypts as early as 26 weeks, but more extensive analysis would be needed to draw broader conclusions about human intestinal development. Thus, while inclusion of these samples adds value to the study, this component remains relatively limited in scope.

Reviewer #3 (Public review):

Summary:

This manuscript from Løberg and coworkers tests a previously suggested hypothesis for how coeliac disease is triggered. The disease is characterized by T cells responding to deamidated gluten peptides that are invariably associated with the production of IgA antibodies against the self-protein transglutaminase 2 (TG2), which is responsible for the deamidation. According to their hypothesis, intracellular TG2 is released into the gut when intestinal epithelial cells (IEC) are shed into the lumen and degraded, where it forms transient complexes with gluten while deamidating it. As complexes are taken up into gut-associated lymphoid tissues, the complexes will function as hapten-carrier antigens for B-T cell interactions, driving B cell responses against TG2 and T cell responses against deamidated gluten. They have previously created a mouse strain carrying human antibodies specific for TG2, TCR specific for deamidated gluten and HLA molecules that can efficiently present the gluten peptides. Here, they have now created a novel mouse model where they can induce expression of TG2 fused to deamidated gluten peptides in IEC. Using this together with previous mouse strains, they show that IEC lysates from induced animals contain antigens that will activate antigen-specific B and T cells in vitro, and that the fusion protein can be detected in the gut lumen between 12 hours and 3 days after induction of expression. Furthermore, when TG2- and deamidated gluten-specific B and T cells are transferred into the mice that are subsequently induced, TG2-specific IgG and IgA antibodies are produced and there is strong activation of germinal centre responses of the B cells and Tfh responses by the T cells. However, for this response to happen, the transferred T cells need to be orally primed with deamidated peptides and the strong mucosal adjuvant CT before induction of the TG2 fusion protein that will activate B cells.

Strengths:

There is a lack of animal models that mimic celiac disease, at least partly because it is a complex condition involving both classical hypersensitivity and autoimmunity. While the major T cell antigens responsible are gluten peptides that have been deamidated through the action of transglutaminase 2 (TG2) and are presented on specific HLA molecules, the disease is also invariably associated with an autoantibody response against the enzyme, TG2, that modifies the peptides, usually consisting of IgA antibodies. The antibody response is so strongly correlated with the disease that it is now used for diagnosis in the clinic. The group responsible for the current work has previously developed mouse models in efforts to study the disease, including strains expressing disease-associated human HLA, TCR and antibodies. Although they have so far not been able to fully replicate the disease in mice, these have been useful tools to study how the disease may be triggered in the gut.

Where TG2 modifies gluten peptides and where it is encountered by B cells has been a bit of a puzzle. Most agree that TG2 is primarily an intracellular protein, but that significant amounts can also be found extracellularly, attached to cell surfaces or the extracellular matrix. Gluten peptides are mainly located extracellularly or in endosomes, and for this reason extracellular TG2 in the gut have been thought to be most important for deamidation. However, where TG2 is present in the gut has not been definitively answered. In addition, an attractive model that would explain the immune responses is that extracellular TG2 bind gluten peptides, that these are taken up by TG2-specific B cells, and deamidated peptides are subsequently presented on MHCII for T cells. This would require TG2-peptide complexes to be present extracellularly where B and T cells are both present. The authors have previously hypothesized that TG2 may be produced in IEC and released into the gut lumen, where it would form complexes with gluten peptides and then be taken up by M cells positioned over gut-associated lymphoid tissues, in particular Peyer´s patches. Previously, they have demonstrated that B and T cells can be forced to interact in Peyer´s patches following an oral immunization with antibodies specifically recognizing that B cell receptor that are linked to a gluten peptide in the presence of a strong mucosal adjuvant in the form of cholera toxin.

Here, the authors now specifically address whether expression of TG2 in IEC is sufficient to trigger autoreactive B and T cells to respond. They show that induced expression of a TG2-gluten peptide fusion protein specifically in IECs is sufficient to trigger the production of IgG and IgA antibodies against TG2 when antigen-specific B and T cells are present. Following induction, they also demonstrate activation of B and T cells in Peyer´s patches, resulting in autoantibody production of IgA and IgG antibodies. The use of an inductive system to express the antigen is an important control, with transferred cells only activated when the antigen is produced. In addition, the fact that activation of cells mainly occurs in Peyer´s patches further supports that it is dependent on TG2 fusion protein secreted into the gut lumen that triggers the response, as the main function of Peyer´s patches is to initiate responses to antigen in the lumen.

Overall, the authors present convincing data that proteins primarily present intracellularly in IEC can trigger antigen-specific responses in Peyer´s patches, given that antigen-specific B and T cells are present.

Weaknesses:

This paper is still some way from establishing a mouse model that mimics celiac disease, and the authors do not make any such claims. It demonstrates a situation that could be similar to when celiac disease is first triggered in humans. However, the fact that a TG2-specific IgA antibody response can be triggered in the model does not necessarily show that it can be triggered in a more natural situation (when the antigen would need to be a TG2 - gluten peptide complex) or that it is the only way for such a response to be triggered. Hence, it does not really prove that the model describes the situation in people with coeliac disease, only that a similar response can be triggered in the mouse model.

There are also many remaining questions regarding the response that could have been further developed. Some of which should probably have been addressed already in this manuscript. First, given the importance of the expression of the antigen in IECs into the lumen and the strong responses in Peyer´s patches, the authors should have provided additional information about the expression of the TG2-fusion protein in epithelial cells in the follicular-associated epithelium covering and other epithelia surrounding the structure. Is it possible that even M cells express the antigen, and that it may not need to be in the lumen to reach the Peyer´s patches? Second, it is not addressed whether antigen-specific pre-activation of T cells using peptide and CT is strictly needed or if CT alone could have created an environment where antigen-specific responses are triggered by the TG2 fusion protein alone (i.e. using CT as an adjuvant for a response to an antigen expressed in IEC). Or even if other inflammatory gut responses, not necessarily triggered by CT but instead by virus, pathogenic bacteria or oral dextran, would have sufficed. Although T cell cross-reactivity to external antigens could play a role in humans developing disease, it would be easier to envision a situation where any gut inflammation, in the presence of antigen-specific B and T cells and a susceptible HLA environment, could trigger a response. Finally, the role of dendritic cells and/or other APCs present in the gut and/or Peyer´s patches in the priming of T cells should probably have been discussed, i.e., whether presentation of antigen by B cells is sufficient or not. If inflammation or CT alone is sufficient for T cell priming (see above), this indirectly supports that direct presentation from B cells may play an important role in T cell activation.

Other themes that could have been further developed are more general, involving the system and its correlation with celiac disease. For example, what would happen if the expression of the TG2 fusion protein is maintained over time using dox; will damage be observed to the gut mucosa that is similar to the one seen in celiac patients? What would happen when the antigen is no longer expressed? Will the mice maintain memory B and T cells that can rapidly respond upon re-expression of the antigen? Or would the constant presence of endogenous TG2 eventually lead to tolerance development? It would be particularly interesting to see if the cells are first triggered/primed by the expression of the GP2 fusion antigen in IEC, and then determine if memory cells can be activated, or active responses maintained, if gluten is given orally to the mice and its interaction with endogenous TG2 is then sufficient.

Reviewer #3 (Public review):

Summary:

This study provides structural and functional insights into the sterol recognition mechanism of ABCG5/G8.

Strengths:

The modeling of ergosterol into the density map is plausible, considering that the protein was heterologously expressed in yeast, only CHS was added during purification, and MD simulations rendered CHS binding to this site unlikely. The identified ergosterol-binding site in the central TMD cavity closely aligns with the location previously observed in a cholesterol-soaked crystal structure, strongly supporting the notion that this cavity serves as the primary substrate-transport pocket. Furthermore, mutagenesis of the key Tyr residue abolishes the ergosterol-specific enhancement of ATPase activity, providing robust functional support for the structural findings.

Weaknesses:

However, several caveats should be considered when interpreting these results:

First, while local resolution in the TMD region appears sufficient to trace side chains, the overall resolution of 3.5 Å poses challenges for precisely discerning subtle side-chain movements or rotamer changes. As the structural comparison with the apo and CRL-bound forms reveals no major helical shifts-remaining confined to side-chain rearrangements-caution is warranted when attributing mechanistic significance to these localized variations without exhaustive functional validation.

Second, a major limitation lies in the mechanistic model proposed by the authors. The manuscript suggests that the peripheral cholesterol-binding site (CRL) observed exclusively in previous crystal structures represents an intermediate state of sterol flip-flop. However, the authors provide no new experimental or computational evidence in this study to substantiate this hypothesis. Consequently, this model remains speculative and lacks sufficient empirical backing at this stage.

Reviewer #3 (Public review):

Summary:

This study integrates living neuronal circuits with a real-time reinforcement-learning framework to enable closed-loop optimization of directional firing sequences at single-spike resolution. By using the spatiotemporal structure of neuronal firing as feedback, the system adaptively searches for stimulation patterns that increase a predefined propagation reward. The work represents an exciting step toward systematic and adaptive control of living neuronal networks.

Strengths:

The study presents a cutting-edge closed-loop platform that combines neuronal cultures, high-temporal-resolution electrophysiology, and reinforcement learning with millisecond-scale latency. The ability to optimize directional activity propagation at single-spike resolution is particularly novel. More broadly, the work provides a compelling framework for interacting with biological neural networks in an adaptive rather than purely predefined manner.

Weaknesses:

Several aspects of the analysis and interpretation require further clarification. In particular, the definition and computation of directional propagation and reward are not always clear. The generalizability of the optimized stimulation patterns across cultures also remains unclear.

Reviewer #3 (Public review):

Summary:

This manuscript shows how a change in food source can lead to organismal adaptation to stress. Namely, different yeast strains impact the response of Drosophila to cold stress. An intriguing connection between food intake, gut, and neuronal signaling is described.

Strengths:

The genetic association studies suggest how pathways can be altered to provide cold tolerance in Drosophila.

Weaknesses:

[MRPL10+] is described here as a yeast prion, yet there is no solid evidence supporting this. It is unclear whether the prion exists; therefore, the primary conclusion is unclear. More biochemical analyses and additional characterization are needed to support the idea that MRPL10 is, in fact, in a prion state in the strains the authors received and utilized in this manuscript. It is unclear whether the mating scheme to produce daughter cells without the prion would actually work as described, and no follow-up work verifies the lack of the prion state. In addition, more common prions were omitted from the study, and it is unclear whether they might be present in the strains used as well. There is no [PSI+], [RNQ+], or [URE3] strain assessed, and it is possible that there is another prion in the [MRPL10+] strain.

Reviewer #3 (Public review):

Summary:

Bedford considers how the fitness of SARS-CoV-2 and influenza H3N2 variants have changed over time. The fitness of viral variants are estimated from trajectories of variant frequencies using multinomial logistic regression (MLR). The MLR approach was previously developed and is well-validated. Changes in mean population fitness (i.e. fitness flux) is then derived from changes in the fitness of circulating variants through time.

Strengths:

The manuscript makes some noteworthy observations. For one, it is reassuring to know that fitness variation well predicts the rate of fitness change in viral populations, as expected under Fisher's fundamental theorem. Similarly, it is interesting that simple counts of mutations perform as well as much more sophisticated protein language models in predicting variant fitness.

Weaknesses:

My two main concerns both relate to the interpretation of fitness flux and how confident we should be that it is quantifying changes in absolute fitness as opposed to environmentally-dependent changes in fitness through time.

(1) Interpretation of fitness flux:

I'm not entirely convinced that mean population fitness can be meaningfully compared through time, at least not as a measure of fitness change on an absolute scale. Here, mean population fitness is defined as the weighted sum of the relative fitness of each variant, so changes in mean pop fitness necessarily reflect changes in relative fitness. To obtain a fitness value of each variant that is comparable across time, a "scaffolding approach" is used to estimate window-specific effect and the global fitness (f_i) of each variant. The major assumption here is that by accounting for the window-specific effects, the global fitness of each variant becomes directly comparable. This assumption seems somewhat suspect. It seems impossible to know whether the window-specific effect is capturing the full environmentally-dependent component of fitness in a given window. There could also be a high degree of temporal autocorrelation in window-specific effects between neighboring windows due to similarities in environment that would decay over time.

To put this in another way, say we directly competed a 2020 SARS-CoV-2 variant with a 2025 variant in the distant future after all host-immunity to these strains had waned. Would we really be confident in estimating the fitness advantage of the 2025 variant over the 2020 variant? Or would this estimates of relative strain fitness still reflect the environments in which they were measured in, including the NPIs that were in effect in 2020 and the complex immune structure of the host population in 2025?

(2) Inability to separate different components of fitness:

Earlier work, like Meijers et al. for SARS-Cov-2 (Cell, 2023), decomposed overall changes in fitness into different components of fitness such as changes in intrinsic fitness (transmission potential) and immune escape. While the current model is simpler, in some ways this earlier work was more elegant and more powerful in its ability to explain what components of fitness drove the overall change in population-level fitness.

Reviewer #3 (Public review):

Summary:

The manuscript titled "Glia regulate local retinoic acid levels to specify neuronal specialisation for high-acuity vision" by Lahne et al. examines the interaction of cellular and signaling mechanisms involved in neuronal specialization. While there have been rapid increases in the discovery and cataloguing of different cell types based on transcriptional signatures that can be uncovered by single-cell approaches, there is much less known about how variations in cell morphology within a cell type are governed. The highly stereotypical specializations in photoreceptor morphology found in high acuity zones of various species are an excellent example. This study implicates retinoic acid signaling as a functional driver of these photoreceptor specializations in addition to its previously described role in establishing the spatial positioning of high acuity zones within the neural tissue. Furthermore, evidence is presented that retinoic acid does not directly signal through photoreceptors, but instead this signal is received by Müller glia to non-cell-autonomously affect the photoreceptors. Overall, this study identifies a potential mechanism that integrates the broad patterning role of retinoic acid with its local effects on specializations within a cell type and suggests that glial cells are integral to this mechanism.

Strengths:

The major strengths of this study are the well-executed experiments and clearly communicated results. The application of pharmacological agents is useful for precise timing of target inhibition and to prevent effects on other retinoic acid-mediated processes.

Weaknesses:

There are two issues with the study that weaken the conclusions that are drawn. The first is that the primary evidence that Mueller glia are the cells receiving the retinoic acid signal is that the RARE reporter is active in these cells. However, it should be considered whether this reporter is capable of responding to all retinoic acid signaling. Is it possible that the construct's binding site sequences and/or their configuration will limit the ability to detect other receptor complexes that respond to retinoic acid? For example, will complexes that contain RorBeta or RxrGamma (two established retinoic acid receptors) in complex with thyroid receptors be able to activate this reporter? If that is the case, then it could be that the Mueller glia are shaping the retinoic acid availability in the local environment of cones through their expression of the Cyp26 genes, but the cones as well as the Müller glia are directly responding to the retinoic acid signaling. If there are methods to test this, such as directly activating/repressing retinoic acid signaling in cones or MG with some cell type specificity, that would greatly strengthen the argument that it is a non-cell autonomous effect. One experiment that does argue in favor of this is that the loss of MG leads to a small outer segment, but this is where the second issue should be considered. The study uses three methods (including genetic loss of MG) that block the acuity zone-specific elongation of the photoreceptors, but one concern is that the shortening of these outer segments is a non-specific effect. In all three of the treatments (Figures 3, 5, 9), the segments look somewhat disorganized and not simply like a conversion of the Acuity zone outer segments to the Dorsal state. It would be powerful to complement these approaches with a retinoic acid-related manipulation that does the opposite - that converts Dorsal outer segments into a longer Acuity zone-like morphology. That would be strong support for the proposed hypothesis.

Reviewer #3 (Public review):

Summary

This manuscript investigates whether high-level physical reasoning is influenced by ongoing vestibular and bodily signals rather than operating as a fully abstract process. The authors combine Galvanic Vestibular Stimulation (GVS) with the Virtual Tools task to test the effects of vestibular perturbation during reasoning under terrestrial gravity in Study 1 and visually simulated altered gravity in Study 2. The experimental approach is original and provides a potentially useful bridge between research on vestibular processing, physical cognition, and embodied reasoning.

The revised manuscript is substantially improved. The authors have responded carefully to many of the methodological concerns raised in the previous review. In particular, they have removed the original arbitrarily weighted Gravity-Weighted Index, introduced mixed-effects models that account for participant-level and game-level variability, clarified the basis of the gravity-impact classification, and more clearly distinguished preregistered from exploratory analyses. The interpretation of the strategy measures and the treatment of the 0.5g and 2g conditions have also been improved. These revisions provide a substantially stronger and more transparent analytical framework for evaluating the hypotheses.

Strengths

The principal strength of the study is its conceptual and methodological originality. Combining vestibular stimulation with a relatively high-level physical problem-solving task provides an innovative approach to testing whether ongoing bodily information is associated with physical reasoning. The comparison of games that differ in their dependence on gravity is also potentially informative for distinguishing general effects of vestibular perturbation from effects more specifically associated with gravity-relevant reasoning.

The revised analyses represent another important strength. The mixed-effects models provide a more principled basis for inference than reliance on individual game-level comparisons alone, while the revised Gravity Index removes the arbitrary weighting used in the original manuscript. The clearer treatment of exploratory analyses also makes it easier to distinguish the primary evidence from complementary observations. Overall, the revision has addressed many of the methodological concerns raised previously and has made the empirical pattern considerably easier to evaluate.

Weaknesses

The main remaining concern is the correspondence between the strength of the empirical evidence and the strength of the manuscript's central claims.

In Study 1, the aggregate measures provide little evidence for an overall effect of GVS on performance or strategy. More importantly for the proposed gravity-specific account, the newly introduced mixed-effects analyses do not show significant stimulation-by-gravity-impact interactions for the principal performance or strategy measures. Some gravity-level-specific and game-level effects are present, including a difference in placement distance for high-gravity-impact games, and the exploratory spatial analyses provide additional evidence that vestibular perturbation may influence aspects of strategy. These findings are potentially informative, but the overall pattern is selective rather than a consistent and convergent demonstration that greater dependence on gravity systematically increases the detrimental effect of GVS.

The evidence in Study 2 is more limited. Aggregate differences between GVS and Sham are small across the main performance and strategy measures, and the mixed-effects analyses do not identify reliable stimulation effects across the low-, medium-, or high-gravity-impact categories. Study 2 therefore does not directly demonstrate that GVS facilitates physical reasoning under altered gravity.

The cross-study Gravity Index analyses provide some evidence that the effects may differ across gravitational contexts, but the pattern remains heterogeneous. For success rate, the high-gravity-impact contrast is in the predicted direction but remains a directional trend, with the credible interval including the point of equivalence. Other performance measures do not provide convergent support for the same pattern. The distance index shows reliable cross-study contrasts at some gravity-impact levels, but these form a crossover pattern rather than a simple reduction of the GVS effect as gravity dependence increases. The principal study-by-gravity-impact interactions are also not robust. In addition, this Gravity Index analysis was not preregistered and compares two separate participant samples. Taken together, these findings are more consistent with suggestive evidence for a context-dependent influence of vestibular perturbation than with a definitive demonstration of facilitation or rapid adaptation under altered gravity.

A second concern is the mechanistic interpretation. The experiment directly measures behavioral performance and strategy under GVS and Sham conditions. It does not directly measure the strength of a terrestrial gravity prior, prediction errors, sensory reweighting, internal-model updating, or stochastic resonance. Predictive coding and related frameworks provide plausible interpretations of the findings, but the present behavioral data cannot distinguish among these mechanisms. Statements that GVS downregulates a terrestrial gravity prior, accelerates revision of an internal model, recalibrates cognitive expectations, or provides a vestibular "teaching signal" therefore imply a level of mechanistic specificity that is not directly established by the current experiments.

Overall, the study remains innovative and potentially valuable, and the revision has substantially strengthened the analytical framework. The empirical results support a more circumscribed conclusion that vestibular perturbation can influence selected aspects of physical reasoning and strategy, with suggestive evidence that these effects may vary across gravitational contexts. The evidence is less conclusive for the broader claims that real-time embodied experience generally determines high-level physical reasoning or that vestibular perturbation facilitates rapid adaptation through specific mechanisms of gravity-prior updating.

Reviewer #3 (Public review):

Summary:

Conditioned analgesia refers to the ability of a learned fear cue to suppress pain-related behavior and neural activity. Understudied, the authors developed a novel conditioned analgesia procedure in which a cue that had been paired or unpaired with shock was played while a hot plate increased temperature. Compared to several control conditions, the authors found increased latency to a nociceptive response (paw licking). The authors identified somatostatin neurons in the periaqueductal gray as a likely mediator of the behavior. They then showed that: (1) stimulating vlPAG-SST neurons blocked nociceptive response latency increases to the CS+, (2) stimulating vlPAG-SST neurons suppressed fear retrieval freezing, (3) stimulating vs. inhibiting vlPAG-SST neurons drove opposing modulation of c-fibers and Aδ-fibers, (4) direct-projecting vlPAG SST neurons modulate freezing while RVM-projecting vlPAG SST neurons modulate conditioned analgesia.

Strengths:

These experiments have many strengths. The behavioral assay is chief among them. The assay is robust and controls for confounding factors to reveal a repeatable effect of a shock-paired cue to delay nociceptive responding. The optogenetic experiments provide the correct level of temporal precision, given the authors' time-specific interest in cued responding. Combining neuronal manipulations with spinal recordings is particularly innovative, especially in the context of more behavioral neuroscience-based assays. All-in-all, I found this to be an exceptionally strong set of experiments.

Weaknesses:

No obvious weaknesses were identified by this reviewer.

Reviewer #3 (Public review):

Summary:

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

Strengths:

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

Reviewer #3 (Public review):

Summary:

The authors report findings from a set of experiments that compare learning outcomes from two broad classes of training regimens. The first, concept discovery, emphasizes the identification of task components. The second, concept implementation, emphasizes the procedural deployment of task components. Learners tend to self-schedule the former, but task performance and performance on an immediate test are supported by the latter.

Strengths:

The authors address a novel research question with clear application value. The experiments that are reported in the manuscript are effectively designed to answer the research questions of interest. However, as I will expound on below, the authors ultimately misinterpret their findings.

Weaknesses:

This manuscript makes no mention of the distinction between learning and performance (e.g., Schmidt & Bjork, 1992; Soderstrom & Bjork, 2015). It is well-known in the human learning literature that valid tests of learning are ones that entail a separation of context from an initial acquisition phase. This separation may be temporal (i.e., a delayed test) or feature-based (i.e., a test of transfer on novel iterations of a task). In any case, contextual differentiation between test and acquisition is critical to provide an accurate assessment of learning. To the authors' credit, they do report results from both a delayed test and tests of transfer. However, they do not appropriately interpret the results of those tests, which demonstrate no impact of training schedule on learning. They instead rely on findings from immediate tests to support their claims that graduated concept implementation supports learning. In truth, concept implementation is neither preferred by learners nor beneficial to learning. These findings are accordingly quite limited in terms of generating insights for effective training conditions.

Compounding my primary concern above, I will note that the authors report fitting Bayesian multilevel models (MLMs) to their data, yet rely extensively on analyses of participant means (e.g., permutation t-tests) when a proper MLM would suffice, and in fact would be more appropriate. Bayesian MLMs are an incredibly flexible and robust analytic tool (e.g., Fiechter, 2024), and I would have liked to have seen a more comprehensive approach in this manuscript.

Reviewer #3 (Public review):

Summary:

Maigler & Lin et al present a convincing set of behavioral and electrophysiological experiments and analyses exploring how individual differences in taste preference map onto neural responses in the gustatory cortex (GC). They go on to examine how both preferences and neural responses shift following intervening taste experience. Their experiments are strengthened by examining tastes of distinct identities and palatability (sweet, sour, salty, bitter) and correspond each animal's individual preference to the palatability-related late phase of the neural response.

Strengths:

(1) They demonstrate a relationship between the behavioral expression of taste preference and palatability-related GC neural responses. The direct correlation of expression of taste preference with GC neural responses indicates that taste preference behavior may be less noisy than previously thought, reflecting actual neural activity.

(2) They address the stability of individual taste preference by comparing within and between session expression. This finding indicates that individual preference on any given trial or test session can differ from canonical palatability.

(3) The animal's preferences for various tastes are reflected in the neurophysiological recordings, despite that behavior and physiology sessions are separated by several weeks, with an intervening surgery, across multiple delivery methods (active licking vs passive delivery), and across homeostatic states (thirsty vs sated).

(4) They provide evidence that representational drift in palatability coding may arise from sensory experience rather than from the passive passage of time.<br /> The findings are novel and impactful, and the results are relatively complete.

Weaknesses:

(1) The authors state that "no differences in effects were observed between taste batteries" (Methods), but it is not clear which analyses were performed to determine this, especially considering that many of the analyses are within-animal. Without more clarity, it is difficult to evaluate whether the interaction of different tastes within the sets of stimuli bias the main conclusions.

Reviewer #3 (Public review):

Summary:

The manuscript studies a minimal model of tissue homeostasis in which stem (S), progenitor/transit-amplifying (T), and differentiated (D) cells interact through stochastic fate decisions and mechanically regulated proliferation. Combining a compartment-level analytical description with particle-based simulations, the authors show that pressure-dependent growth can stabilise cell populations and maintain tissue homeostasis over a broad parameter range. They derive homeostatic cell fractions and identify distinct regimes, including tissues maintained by rare stem cells or by long-lived progenitors. Most notably, the simulations reveal the spontaneous emergence of persistent stem-cell clusters and renewal-unit-like structures in the absence of explicit niche signals or differential adhesion. The authors further analyse spatial correlations, cluster statistics, lineage dynamics and neighbourhood compositions, and argue that stochastic fate decisions qualitatively alter the spatial organisation of mechanically regulated tissues. Based on the annotated manuscript, several of these central claims concern the emergence and stability of stem-cell clusters and their interpretation as self-organised structures.

Strengths:

The manuscript is clearly written, technically competent, and combines analytical calculations with large-scale agent-based simulations in an elegant way. The systematic analysis of spatial observables, including pair correlations, cluster-size distributions, void statistics, neighbourhood composition, and lineage tracing, provides a rich characterisation of tissue organisation. The comparison with the authors' previous work on deterministic stem-cell hierarchies is particularly interesting, as it demonstrates that altering the fate-choice scheme can qualitatively change the resulting tissue architecture from stem-cell repulsion to stem-cell clustering. The study therefore generates a number of experimentally testable predictions regarding stem-cell spatial organisation and lineage dynamics. I also found the attempt to connect microscopic fate decisions to mesoscopic tissue-level organisation valuable, as this remains a relatively underexplored area at the interface of stem-cell biology and tissue mechanics.

Weaknesses:

My main concern relates to novelty and positioning within the existing literature. The manuscript frequently presents mechanical feedback as a mechanism capable of generating tissue homeostasis and robust cell-type proportions. However, the idea that crowding- or pressure-dependent feedback can robustly stabilise renewing tissues is already well established, both in mechanical homeostasis models and in more general feedback-based theories of tissue regulation. Consequently, the homeostasis aspect of the present manuscript appears more as an application of existing principles to a particular mechanical framework than as a fundamentally new conceptual advance. The authors should position their work more clearly with respect to these studies and explain more explicitly what genuinely new biological or mathematical insights are provided beyond the existence of homeostatic steady states.

The manuscript therefore derives its novelty primarily from the spatial phenomena emerging from the coupling of stochastic fate decisions and mechanical interactions. While the observed stem-cell clustering is intriguing, the mechanistic explanation remains incomplete. The authors attribute clustering to stochastic symmetric divisions combined with mechanical control, yet it remains unclear whether the observed structures genuinely arise from a new self-organised mechanical mechanism or simply reflect local genealogical correlations generated by repeated symmetric divisions. Several of the strongest conclusions, including long-range order, renewal-unit formation, and stable niche-like organisation, require more rigorous support. In particular, the manuscript currently lacks appropriate control models that would disentangle the effects of mechanics, stochasticity, and daughter-cell placement. Furthermore, the definition of clusters via a specific distance threshold appears somewhat arbitrary and may itself influence the inferred cluster sizes and conclusions regarding finite renewal units. It would be important to demonstrate robustness with respect to this choice.

I also have concerns regarding the simulation methodology and interpretation of the spatial statistics. Large tissues are assembled from smaller pre-equilibrated patches. While this may be computationally convenient, it raises concerns about whether long-range structures can emerge naturally and whether the reported spatial organisation could be affected by the construction procedure. Given that one of the central claims concerns spatial ordering over large scales, it would be important to demonstrate explicitly that the patching procedure does not influence the results. Similarly, the manuscript interprets pair-correlation and void statistics as evidence for long-range ordering of stem-cell clusters, but does not sufficiently exclude alternative explanations arising from finite system size, patch construction, or simple genealogical clustering.

Conclusion:

Overall, I find the manuscript interesting, whilst I also believe it should have a major revision. The most valuable contribution of the study is not the demonstration that mechanical feedback can maintain homeostasis, but rather the suggestion that stochastic fate decisions can qualitatively reshape the spatial organisation produced by mechanically regulated tissues. For a broad-interest journal, however, the authors should sharpen the positioning of the work relative to prior homeostasis theory, establish more clearly the mechanistic origin of the reported stem-cell clustering, and provide additional evidence that the observed structures are genuine emergent features of the model rather than artefacts of modelling assumptions or analysis choices.

Reviewer #3 (Public review):

Recent work reported that STING binds Ap4A and proposed that elevated Ap4A levels could modulate the cGAS-STING pathway. Intracellular Ap4A levels are controlled by the hydrolase NUDT2, itself a cancer drug target, and loss of NUDT2 raises cellular Ap4A pools. Building on this, the authors set out to investigate whether and how Ap4A modulates the cGAS-STING pathway. This question was motivated by the fact that the mechanism by which STING might bind a linear dinucleotide such as Ap4A remained unclear, and by the existence of alternative routes of crosstalk between Ap4A and the pathway. These include the chemical similarity between Ap4Ns and pppGpA, the linear intermediate generated by cGAS during cGAMP synthesis, raising the possibility that Ap4A could inhibit cGAS directly, as well as a potential downstream effect on the kinase TBK1.

Using in vitro biochemistry, the authors show that STING does not, in fact, bind Ap4A, contrary to what was previously claimed, and they further examine the impact of NUDT2 loss on the cGAS-STING pathway. This clarifies for the field whether Ap4A could influence the pathway in any way, whether through binding to cGAS, STING, or TBK1.

The authors find that cGAS can bind Ap4A but cannot process it. cGAS also binds Ap4G, but processes it only inefficiently and only when supplied at very high concentrations in vitro. This argues against physiological relevance in cells, since inhibition of canonical cGAMP synthesis would require Ap4Ns to be present in excess over ATP and GTP, a condition unlikely to be met at physiological nucleotide concentrations even when NUDT2 is absent. The authors also test for effects on TBK1, showing that while it can bind Ap4A, the concentrations required for inhibition are similarly not physiological.

The authors conduct a thorough series of biochemical and biophysical experiments to clarify the underlying mechanism, systematically ruling out a plausible effect of Ap4A in cells at each step. Even where an effect on cGAS or TBK1 can be detected at very high, non-physiological concentrations, this remains confined to in vitro conditions. The experiments are sound and conducted with scientific rigor, and the results support the authors' conclusions.

This work provides clear evidence that STING does not bind Ap4Ns, and that even where binding does occur elsewhere in the pathway, there is no plausible mechanism by which Ap4Ns could modulate the cGAS-STING pathway under physiological conditions. This resolves an open question for the field: if Ap4Ns do have biological effects related to this pathway, these are unlikely to arise from a direct interaction with cGAS, STING, or TBK1, and must instead be mediated through other processes. The methods and data will be a useful reference for the community when evaluating future claims of nucleotide second-messenger crosstalk.

Prior studies have shown that NUDT2 disruption, which elevates cellular Ap4A levels, is associated with down-regulation of interferon-response pathways. This is notable in light of the current findings, which show no direct biochemical interaction between Ap4A and cGAS, STING, or TBK1. Together, this suggests that if elevated Ap4A does suppress IFN production, it likely does so indirectly, through mechanisms other than direct engagement of the cGAS-STING-TBK1 axis.

Reviewer #3 (Public review):

Summary:

The LC3 family of proteins, which includes LC3B, are ubiquitin-like proteins that are covalently linked to phosphatidylethanolamine in the expanding autophagosomal membrane during autophagy. LC3 family members bind to short sequences of amino acids that reside within dynamic regions in a wide variety of proteins. These sequences, termed LC3 Interacting Regions (LIRs), were initially thought to function primarily to link LIR containing autophagy cargo receptors to LC3 family members to help facilitate their capture during autophagy. However, the functional importance of LIRs in autophagy has broadened to include more general functions in autophagy as well. While a general consensus for LIR sequences has been described as [FWY]0-X1-X2-[LVI]3 recent work has suggested that additional sequences outside of the canonical LIR sequence can bind LC3 family members and play important roles in autophagy. In this manuscript by Kosmatka et al, the authors perform a high throughput screen using bacterial surface display coupled with fluorescence associated cell sorting to identify which human sequences can bind to LC3B. They identify a variety of peptides capable of binding LC3B including peptides from proteins that have not previously been described as LC3B binding proteins. The results from the bacterial surface display were then used to guide sequence analysis, mutational analysis and structural studies to further characterize the range of LIR sequences that are capable of binding LC3B. Taken together, this work adds to the growing knowledge of how LIR sequences interact with LC3 family members and demonstrates which amino acids both inside and outside of the LIR sequence aid in binding. This work also identifies new potential LC3 binding proteins which may play unknown roles in autophagy regulation. Lastly, this work reinforces the importance of alternative LIR sequences such as the [WFY]0-X1-X2-[WFY]3 sequence which the authors have dubbed the LIR+ sequence.

Strengths:

The manuscript uses a robust approach to identify and characterize different peptide sequences that can interact with LC3B. They validate a large number of sequences using biolayer interferometry (BLI). The large number of LC3B binding sequences and their dissociation constants adds significant new information to the field that will help others understand what sequences can bind to LC3B. The authors are also very careful to accurately report on their data and not overly interpret their findings.

Weaknesses:

After the authors identify proteins from their bacterial display assay, the remainder of the manuscript is focused on characterizing the different types of sequences that are identified in addition to validating the LC3B-LIR interactions using BLI and X-ray crystallography. However, it's not entirely clear if the screen identified novel LC3B binders that interact with LC3B in cells. While I acknowledge that the focus of the manuscript is on the characterization of LIR sequences that can bind LC3B it seems like a missed opportunity to not validate a few of the novel LC3B binders in vivo.

Reviewer #3 (Public review):

Summary:

The manuscript by Zavadska et al. presents a phylogenomic study focused on the relationships among metakinetoplastids, specifically addressing the question whether Neobodonida are monophyletic. The authors collected eleven kinetoplastid strains affiliated with five out of six neobodonid clades identified in previous studies and sequenced their transcriptomes. These data along with SRAs available from public databases were processed via assembly, annotation and decontamination. The final dataset, representing all (non-trypanosomatid) kinetoplastids with genome and/or transcriptome data available as well as selected trypanosomatids and discoban outgroups, was used for protein orthology inference and identification of single-copy orthologs present in the majority of taxa, followed by phylogenetic analysis in maximum likelihood and Bayesian frameworks.

Strengths:

I find the new data and resulting phylogenetic reconstruction valuable and interesting, particularly given the paucity of genomic/transcriptomic data from free-living kinetoplastids. The study is well-designed methodologically, and the main finding (paraphyly of Neobodonida) appears indisputable, considering the provided phylogenimic evidence. Following best practices, the authors shared their primary data, scripts, and files resulting from the conducted analyses.

Weaknesses:

Several aspects of the presentation and interpretation would benefit from revision. In particular, the composition of the neobodonid lineages central to the study is insufficiently explained, and an 18S rRNA gene-based tree showing these lineages and the placement of the newly analysed strains would substantially improve the clarity of the study. The Introduction would also benefit from a more concise and better-structured account of previous phylogenetic evidence and a clearer explanation of the broader biological significance of kinetoplastids, while the Methods could be streamlined by removing redundant information and presenting some details in tables. Finally, the rationale for including the electron microscopy images in the supplement should be clarified, as these are currently not discussed in the text and represent only a single studied strain.

Reviewer #3 (Public review):

Summary:

In this work, the authors probe the combined role of phosphorylation of an intrinsically disordered region (IDR) and domain pocket interactions with small molecules on the assembly of a multidomain protein HDAC6 using molecular simulations. Their find that IDR phosphorylation and ligand interactions with domain pockets can together reshaped in the interaction networks; thereby, expanding mechanistic understanding of multidomain protein assembly in the context of phase separation beyond an IDR centric grammar. The work is supported by extensive simulations featuring several controls and analysis of the underlying interaction networks.

Strengths:

(1) They find an important role of phosphorylation and ligand binding in shaping multidomain protein assembly.

(2) They demonstrate that even if IDR:IDR interactions are important in isolated IDR systems, folded domain-folded domain interactions can dominate in the full-length protein. Furthermore, ligands can significantly perturb the interaction landscape, e.g., by redirecting folded domain-folded domain interactions to domain pocket ones.

(3) They also show that different ligands can yield differing impact on the interaction networks by both competing with and compensating interactions to varying degrees. This is demonstrated for two ligands (Nexturastat A and HPOB).

(4) They probe both the IDRs in isolation (including both the phosphorylated and unphosphorylated versions) and condensates formed via these IDRs. They also characterize assemblies of the full length proteins (with and without phosphorylation) in presence and absence of the ligands. The combined simulations, in general, support the key conclusions of the paper.

Weaknesses:

(1) There are areas where statistical tests can improve the quantitative presentation of the work. Specifically, the difference in the IDR ensembles for the isolated chains should be assessed for statistical significance.

(2) There appears to be considerable finite-size effects in some of the slab simulations that may affect the conclusions. In particular, the chains along the long axis appear to be interacting across the periodic boundary. This can happen if the slab long axis is not long enough/if the ratio of dilute phase to dense phase is not large enough.

(3) Some decisions in the simulation conditions require further justification/explanation. More specifically, the concentrations of small molecules used, as well as the decision to conduct simulations at 295 K, should be adequately justified.

(4) Given the size of the full-length protein, it is understandable that the full dense phase is not probed for the full-length protein. However, it would be useful to comment on how the conclusions may change in the context of the full length. For instance, there is no real interface that the small molecules need to diffuse across and so discussions on the role of partitioning in the paper should be better contextualized in light of this.

Reviewer #3 (Public review):

Summary:

The manuscript by Wang et al. describes the identification of a novel mechanism by which the canonical Wnt/beta-catenin pathway could regulate endothelial permeability in the central nervous system (CNS). Specifically, they show that in circumventricular organs (CVOs), in which the blood-brain barrier (BBB) is not established in vessels and endothelial cells are highly permeable, the previously reported low levels of Wnt/beta-catenin coincide with high levels of the vascular endothelial growth factor receptor 2 (VEGFR2, Flk-1), whereas the decoy receptor VEGFR1 (flt-1) is expressed at low levels. In order to test the hypothesis in vivo that the Wnt/beta-catenin pathway controls VEGF signaling in CNS vessels by regulating VEGF receptors, the authors analyzed mosaic cerebellar vessels of mice deficient for the Wnt receptor frizzled 4 (Fzd4), showing that BBB+ (normal condition) vessels show low VEGFR2 and high VEGFR1, whereas BBB- (Fzd4ko) vessels show high VEGFR2 and low VEGFR1. Similarly, although not as conclusively due to strong background from Müller cells, these effects were also visible in the retina of these mice. Conversely, dominant genetic activation of beta-catenin signaling in endothelial cells in vivo resulted in upregulation of VEGFR1 and downregulation of VEGFR2 in vessels of the CVOs as well as of the choroid plexus.

In order to better understand the direct relevance of Wnt/beta-catenin signaling for this regulatory theme, the authors activated the pathway in HEK293 cells, stably harboring the Super-Top-FLASH reporter construct in the presence of VEGFR2 and VEGF. Moreover, by transfecting Wnt1 into HEK293 cells, the authors analysed the effect of TGFbeta, EGF, and FGF signaling. Together, these experiments showed that Wnt/beta-catenin signaling potently suppressed VEGF signaling at low concentrations of Wnt1 transfection, whereas VEGFR2 suppression was only visible at relatively high concentrations. Also, the other pathways were suppressed, although to a lower extent.

In conclusion, the authors suggest a mechanism of VEGF signaling suppression by Wnt/beta-catenin 1) at the post-receptor level of VEGF receptors and 2) at the transcriptional level of VEGFR1 and VEGFR2, independent of VEGF signaling suppression.

Strengths:

(1) The present manuscript provides interesting additional information on top of the published work on the mechanistic function of vascular permeability control by Wnt/beta-catenin, specifically by the highlighted interaction with the VEGF pathway and the opposed regulation of the two VEGF receptors VEGFR1 and VEGFR2.

(2) They have used state-of-the-art animal models, high-resolution imaging, and appropriate in vitro analysis.

(3) This finding has potentially strong implications for future therapeutic strategies, aiming at Wnt/beta-catenin activation in various diseases of the CNS in which vascular repair is desired.

Weaknesses:

A detailed analysis of the post-receptor and transcriptional mechanisms remains largely unexplored and needs to be explored in the future.

Reviewer #3 (Public Review):

Summary:

The authors show convincingly the complexity of gene up- and down-regulation at the outset of metamorphosis and identify substantial differences between the two sexes, even at this early time in development. The complexity of microRNA expression and the difference between the sexes are also nicely laid out. The functional significance of these differences, though, is harder to establish. The authors have focused on the roles of two families of developmental hormones, the ecdysteroids, and the juvenile hormones. The emergence of sex-specific differentiation of organs during metamorphosis is clearly downstream of the action of ecdysteroids and/or JH, but there is no evidence that the presence or lack of these hormones has any effect on the sexual identity of organ systems - i.e., that manipulations of JH or ecdysteroid result in either the masculinization or feminization of individuals or their organs. The precedence for the linkage of these hormones to sex determination is the 2002, Belgacem & Martin study, which describes the effects of JH on fly locomotion. These authors show that the number of stop/start bouts is sexually dimorphic, and removal of JH in males shifts their frequency into the female range while giving treated males exogenous JH moves it back. While this is referred to as a "feminization" of male behavior, this quantitative shift in frequency is not as compelling as would be a qualitative shift -- for example, the removal of JH causing males to show egg-laying behavior (a result that has never been seen). Also, these effects are in a fully mature system, rather than at the early metamorphic time examined in the present paper. In driving and coordination metamorphosis, JH and ecdysteroids are intimately involved in sexual differentiation, but I know of no compelling evidence that they play a role in sex determination.

While the summary of the effects or removal of specific microRNAs on the components of the biosynthetic pathway for the JHs and ecdysteroids (Figure 2E ,F) is quite compelling, I am concerned about the effects of the removal of mir-277 and mir-34 on the levels of both the JHs and 20E. My concern centers around the data from the control group (w[1118] animals in Figure 2D). These data are the first report of a marked sex difference in the titer of either JH or ecdysteroid at the start of metamorphosis in Drosophila. As expected, males show a 10-20 increase in levels of JH III, JHB3, and 20E between the L3 stage and the white puparium, but, surprisingly, the levels of these hormones in female L3 larvae are equal to or greater than that seen at pupariation! These data for females run counter to over 50 years of work on the effects of ecdysteroids in Drosophila!

As far as I can gather from the paper, the L3 data were obtained using wandering larvae. This stage lasts for about 12 hours and ends with pupariation. Larvae from this period need to be used with caution for hormone studies. Levels of both JH and ecdysteroid are low as larvae leave the food but rapidly rise to their peak levels at the white puparium stage 12 hours later. To deal with the rapidly changing hormonal landscape through this period, the researchers have used physiological markers to track this progression. Initially, it was the sage of "puffing" of the giant salivary gland chromosomes, but, for bulk collection of staged larvae, larvae are fed on food containing a blue dye, and progression is tracked by the loss of blue coloring from the gut. I could not find if the authors had any criteria for selecting larvae during the wandering period. Male and female larvae grow to different sizes. Might this difference in growth be biased when larvae were selected during their wandering phase?

The other hormone-related issue is the expression of Kr-h1 during larval stages and metamorphosis (Figure 1G). Kr-h1 is the main target of JH and Kr-h1 expression is often used as a proxy for the JH titer. The authors report that peak Kr-h1 expression occurs in the L3 (when the JH titer should be lowest!) and that it drops at wandering. This pattern is counter to that reported in the literature (e.g., FlyBase, ModEncode).

Reviewer #3 (Public review):

Summary:

In this study, the authors use several genome-wide approaches to find commonalities and differences between distinct dormancy models, including S. pombe spores, killifish diapause embryos, and human dormant cancer cells. As G0 states are ubiquitous in nature, yet still understudied, this study provides not only a clear demonstration of an evolutionarily-conserved component in G0 regulation, but also a rich resource of genomics datasets, that will be especially of interest to S. pombe and killifish researchers.

The main conclusions of the study are that: (1) there are commonalities in dormancy programs across eukaryotic evolution; (2) the uncoupling between transcriptome and translatome is more pronounced in non-dividing cells, particularly at ribosomal protein coding genes; and (3) dormant cells retain dynamic responses to stress, changing their cellular state and maintaining this difference.

Overall, the study is clearly written, provides large data resources for future research in the dormancy field, and the conclusions are supported by the presented evidence (although point 3 would require further experimental clarification, see below).

Major comments:

A key consideration when comparing transcriptomes of cycling and dormant cells is the overall RNA quantity in the cells; however, it is not made clear in the manuscript whether this overall level was compared and/or if RNA-seq used spike-in quantification. However, this will directly affect some conclusions; for example, there is a conceptual difference between a transcript upregulated in spores and a transcript that appears upregulated in spores but is in fact 'less repressed than average' (resulting in higher FC). While the overall transcript diversity as described will be not affected, this analysis can provide important context. For the highlighted example of ribosomal protein mRNAs, this scenario could be what resulted in an apparent mRNA increase but protein decrease (which would be interpreted as both mRNA stabilization and translation inhibition); if the total mRNA is much lower, then the mRNA levels may be similar (which would then be interpreted as no change in transcription nor mRNA stability, but highlight the importance of translation inhibition).

This point was more clearly described in a previous seminal study by the authors (Marguerat et al 2012), and so should be made clearer here as well. What is the overall RNA level in cycling cells compared to quiescent cells, and compared to spores? Likewise, what is the overall reduction in total protein levels? Was the overall reduction comparable to the previous study? These overall levels should at least be quantified, which is a straight-forward experiment. The current mention of this limitation (two sentences in the last paragraph of the conclusion) is not enough.

Accordingly, the term "induced" (in Fig 2 for example) may be misleading, and could be separated into truly "induced" genes and "relatively induced" genes, when normalized to absolute levels. Likewise, Fig S2A and S2I are misleading due to this effect (normalization will tend to show a similar number of up-regulated and down-regulated genes). These panels should be clarified by plotting next to the relative quantification (current panels) a comparison taking overall RNA level into account. This will very likely strongly increase the number of downregulated genes and decrease the number of upregulated genes, and the new lists can also be subjected to GO analysis.

The same issue would be important to discuss for the killifish experiment as well.

For spore offspring stress experiments, the estimated number of cell divisions after spore germination should be indicated. It appears over 20, which would confirm the authors' conclusion that an epigenetic state is induced and persists over multiple rounds of replication and underlie improved heat resistance, indeed hinting at transcriptional memory through chromatin modification. As the phenotype is tested at a population-level, it is unclear whether every spore is equally able to impart this phenotype, and for how long the stress resistance response persists. Moreover, it may be clearer to test heat resistance in log-phase cells, as in the current experimental setup cells are grown to stationary-phase before plating; however, stationary-phase cultures are more heterogenous and more heat-resistant.

Note also that using 3-fold serial dilutions (instead of more commonly used 10-fold) means that the differences shown in Fig 3M are mild. Plating duplicates (at log-phase) and imaging at several times of growth would be necessary to have a clearer view of the result.

Significance:

Overall, the study provides a proof-of-concept that dormancy programs across vastly different eukaryotes display commonalities. This is not an entirely new concept, but this is the first demonstration of it using S. pombe and turquoise killifish and will therefore be of interest to a wide audience of researchers interested in quiescence and dormancy in general. A key finding (albeit also not entirely new) is the transcriptome/proteome difference, which appears increased in dormant cells; this hints at the existence of key post-transcriptional regulatory mechanisms in dormant and G0 cells.

A current key limitation is that only relative quantifications are discussed, which can currently give a misleading idea of overall transcriptional activity in dormant cells. Another limitation is that differentially-regulated genes, proteins and GO processes are mentioned, but with relatively limited biological interpretation, making some sections of the manuscript lengthy and descriptive.

Advance: The authors provide a vast amount of datasets for fission yeast spores (transcriptome, proteome, differential viability of a mutant collection) and killifish, which will be a very useful resource for researchers in the field. The authors identified several genes and processes that are commonly differentially regulated in dormant cells across several systems, including autophagy and ribosomal protein genes, which were previously known to be required for G0.

Reviewer #3 (Public review):

Summary:

The study aims to explain why different HER2 isoforms produce distinct cancer-cell phenotypes, with a particular focus on the poorly understood mechanisms by which p95-HER2 promotes the invasive and metastatic behaviors of HER2-positive breast cancer. The authors propose that functional selectivity at the HER2 receptor level, particularly signaling through Y1139, preferentially engages an MRTFA-TGFB1I1 transcriptional/cytoskeletal program, thereby shifting p95-HER2-expressing cells toward individual motility, matrix degradation, invasion, and metastasis rather than simply proliferation.

Strengths:

A major strength is the multi-level experimental strategy. Rather than relying on a single invasion assay, the authors integrate phenotypic profiling, single-cell RNA-seq, imaging of MRTFA nuclear localization, protein validation, cytoskeletal analysis, matrix-degradation assays, transwell invasion, 3D spheroid/organoid assays, and orthotopic transplantation. This provides relatively coherent evidence that p95-HER2 cells occupy a distinct biological state characterized by individual motility and invasion, accompanied by a myogenic/contractile transcriptional program and increased MRTFA nuclear localization. Another strong aspect is the attempt to connect the downstream phenotype to a specific HER2 phosphorylation site. The authors identify Y1139 as a candidate determinant of the "go" phenotype and show that mutation of Y1139 to phenylalanine eliminates MRTFA translocation as well as the associated motility and invasion phenotypes

Weaknesses:

The main limitation is that the evidence for the proposed signaling mechanism is stronger for functional dependence than for direct molecular mechanism. The data establish that Y1139, MRTFA, and TGFB1I1 are required for the p95-HER2 invasive phenotype, but they do not appear to fully establish how phosphorylation at Y1139 mechanistically couples p95-HER2 to MRTFA activation. In particular, a direct biochemical link between Y1139 and the machinery controlling actin polymerization/MRTFA nuclear translocation would make the proposed pathway substantially more convincing.

A second limitation is the model system used in the study. Much of the mechanistic work relies on three particular engineered HER2 isoform-expressing cell lines, while the in vivo experiments use NOD/SCID mice. This is useful for testing tumor-cell intrinsic invasion and metastasis, but it limits conclusions about the generality of the functional regulation across different cell contexts, and also limits the understanding of how the pathway operates in the intact immune microenvironment. This is especially relevant because the manuscript itself places p95-HER2 in the broader context of immune evasion and notes that MRTFA can regulate PD-L1; however, the current models cannot adequately establish whether the proposed pathway contributes to immune-mediated metastatic progression in vivo.

Finally, the distinction between "go" and "grow" signaling is conceptually attractive, but the extent to which it represents a general property of HER2-positive human breast cancers remains less certain. The study provides strong experimental evidence for functional selectivity in the models examined, but additional validation in independent patient-derived models and clinically relevant tumors would be needed before generalizing this mechanism across HER2-positive disease.