Reviewer #2 (Public review):

Summary:

This paper describes a study that uses a combination of observational and experimental techniques to investigate the hypothesis that the zona incerta is a neural loci where sensory information is integrated to interpret the motivational value of reward-associated cues. They show that manipulation of GABAergic neurons in this region bidirectionally modulates responding during a progressive ratio test, that activating these neurons recovers motivational deficits incurred by chronic stress, and that they fire in response to reward-associated visual or auditory cues. They also showed that activity in these neurons is not necessary for incentive salience of reward-associated cues, because inactivating them did not prevent Pavlovian-instrumental transfer. However, activating them did enhance responding during the presentation of reward-associated cues in females but not in males.

Strengths:

The study has a very systematic and elegant approach to assess how this region responds first to intrinsic motivation and then to motivation-enhancing effects of reward-associated cues.

Weaknesses:

Males and females are used throughout, but sample sizes are generally too small to make a meaningful interpretation of sex differences (which is not the focus of the study, but is worth bearing in mind). In the last experiment, the lack of discrimination between CS+ and CS- conditions across training for males confounds any interpretation of sex-differences in the outcomes.

The ZI is known to be a region where there is notable convergence of neural inputs from a diverse and heterogenous range of sensory and other cortical inputs. To my knowledge, this is the first study that has directly tested whether it may serve to encode motivational/incentive properties of reward-associated cues. The outcomes are not definitive - it appears that they are sufficient but not necessary. However, this study represents an important first step - the ZI also has notable heterogeneity in the genetic identity of neurons, and properly dissecting the function of ZI microcircuits will likely require characterising function based on more than one molecular marker. This is addressed by the authors in the discussion.

In summary, this study will have a significant impact on our understanding of how motivation is calculated based on complex environmental signals.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors investigated the relationship between the Tat system and MPIase, a glycolipid that facilitates protein integration into the bacterial cell membrane. The TAT (twin-arginine translocation) system is a unique membrane transport machinery that exports fully folded proteins containing a twin-arginine signal peptide. Using both in vivo and in vitro approaches, the authors demonstrated that a sufficient amount of MPIase is required for Tat-dependent protein translocation. Furthermore, the authors successfully reconstituted the Tat transport system by combining recombinant TatA, TatB, TatC, MPIase, and FoF1-ATP synthase.

Strengths:

The reconstituted system clearly demonstrated the requirement for each component, as substrate translocation occurred only when all components were present. Based on these findings, the authors proposed a mechanistic role for MPIase in facilitating Tat-mediated membrane translocation. Previous studies have shown that MPIase is involved in Sec-dependent protein translocation and membrane protein integration, as well as YidC-dependent membrane insertion. The present study further demonstrated that MPIase also plays an essential role in the Tat translocation pathway. Overall, this work highlights the central importance of MPIase in bacterial membrane protein biogenesis and provides new insights into the molecular mechanism of Tat-dependent protein transport.

Weaknesses:

(1) To show the importance of the Tat system in bacterial cells, it would be good to describe in the introduction how many proteins are translocated via the Tat system.

(2) Figure 2B and D show that a sufficient amount of MPIase is important in SufI translocation. However, the reason why MPIase level was upregulated in the BL21 strain but not in the KS46 strain remains unexplained. The authors should address this point.

(3) In Figures 4A and B, the authors explain that MPIase first works as a receptor of TorA-GFP without recognizing the RR motif. This conclusion is based on the results of the fractionation assays, where "sup" indicates the cytoplasmic and periplasmic fractions, and "ppt" indicates the membrane fraction. In Figure 4B, under the TatABC+++, (RR), +MPIase condition, the substrate is secreted most efficiently via the Tat pathway and should therefore be recovered in the periplasm fraction (sup). However, the authors point out that efficiently processed substrate was recovered in the ppt fraction rather than the sup fraction. The authors should explain why this occurred.

Reviewer #2 (Public review):

Summary:

The work provides mechanistic insights into the establishment of the anterior-posterior axis of the mouse embryo by quantifying multiple cellular and tissular parameters from high-quality live imaging data. It shows that the direction of the axis is predetermined by the embryo geometry, that the cells whose migration defines the direction of the axis (the anterior visceral endoderm) have a ratchet-like movement probably depending on transient relaxation events of the epithelial cells lying in their way, and that the adjacent cell layer (the epiblast) moves in the opposite direction.

Strengths:

The dataset is large, with multiple embryos from relevant reporter lines integrally imaged at high resolution for long periods of time, and the analysis tools are novel, original and powerful.

Weaknesses:

Since all data are obtained from wild-type unchallenged embryos, the direct causality between events may not be fully guaranteed.

Reviewer #2 (Public review):

Overall, I think these are exciting results that make a very nice contribution to the literature. I thought the picture-tagging of sequence locations in the fMRI study was clever, and the across-sequence RSA results were especially compelling. But there are several aspects of the presentation of the results that reduced my confidence and enthusiasm.

(1) This is an unusual paper in that there is one human intracranial study and two fMRI studies. The paradigm for the intracranial study is very different than the fMRI paradigm. The key differences are that the fMRI paradigm is hierarchical, while the intracranial is flat, with no sequence learning component, and the fMRI is auditory, while the intracranial is auditory. The justification for the switch from intracranial to fMRI was that intracranial does not allow anterior-posterior axis analysis, but there are so many differences between the studies that this feels like an awkward transition and justification. Also, anterior-posterior analysis in the MTL may not be feasible in EC with intracranial data, but it can be feasible in the hippocampus, and indeed this could be very worthwhile and relevant to pursue (see point 2).

While the two independent fMRI datasets is a strength, the replications would have been much more compelling had the analysis for the second dataset been preregistered.

(2) The intracranial results are pitched as a novel "abstract coordinate representation" but there is a substantial prior literature on MTL "ordinal position codes", which I believe is the same thing in this paradigm. Most of this literature is in the hippocampus, which is, of course, very relevant given the hippocampal findings here, but there is also evidence for this kind of information in EC, e.g., https://elifesciences.org/articles/45333.

(3) Given the intracranial results in the hippocampus as well as the prior relevant literature on position coding, it was not clear why the hippocampus was not an ROI in the fMRI studies.

(4) It wasn't until reading the Methods section carefully that I understood that the results do not hold for the right EC, only the left. This deserves more acknowledgment.

(5) The use of one-sided t-tests with an alpha of .05 reduced my confidence in the robustness of the results.

Reviewer #2 (Public review):

Summary:

The authors first surveyed metazoan genomes to identify homologs of Drosophila errantiviruses and classified them into two groups, "insect" and "ancient" elements, supporting the hypothesis of an early evolutionary origin for these retrotransposons. They subsequently identified two distinct types of envelope proteins, one resembling the glycoprotein F of paramyxoviruses and the other akin to the glycoprotein B of herpesviruses. Despite differences in their primary amino acid sequences, these proteins display notable structural similarity in their predicted domain architectures. The congruence between the phylogenies of the envelope and pol genes further supports the ancient origin of the envelope genes, challenging earlier hypotheses that proposed recent recombination events with baculoviruses. Additional analysis of the Pol "bridge region" corroborated the divergence among these elements, consistent with a pattern of limited cross-species recombination. Finally, by comparing these elements with non-envelope-containing Gypsy retrotransposons, the authors concluded that errantiviruses originated from multiple elements independently.

Strengths:

The conclusions of this study are based on a comprehensive collection of errantiviruses identified across a wide range of metazoan genomes. These findings are further supported by multiple lines of evidence, including phylogenetic congruence and the diverse evolutionary origins of envelope genes. AlphaFold2-assisted protein domain structure analyses also provided key insights into the characterization of these elements. Together, these results present a compelling case that errantiviruses arose independently through multiple evolutionary events, extending well beyond previous hypotheses.

Original Weaknesses:

It would be beneficial to emphasize in the Abstract the potential impact of this work by more clearly articulating the current knowledge gap in the field. While the second paragraph of the Introduction briefly touches on this point, highlighting the broader significance in the Abstract would better capture readers' interest. Additionally, some methodological choices would benefit from clearer justification and explanation. For instance, in Figure 6, the selection of the bridge region/RNase H domain is not explicitly explained, leaving the rationale for its choice unclear.

Reviewer #2 (Public review):

Summary:

The authors aimed to develop a large-scale drug screen to identify B-lp modulators in a vertebrate whole-animal system. Using the zebrafish LipoGlo system that the authors had previously published and validated, the authors screened 2762 drug candidates to generate 49 hits and ultimately validated 19 drugs as genuine ApoB-lowering drugs. Using LipoGlo-Electrophoresis, the authors are able to obtain insights into the ApoB-lipoprotein size/subclass distribution. The authors further validate and study the mechanism of a strong hit, Enoxolone, known as also known as 18β-Glycyrrhetinic acid, which has previously been reported to modulate lipid metabolism. The authors also show that Enoxolone effects are mediated through HNF4⍺, which has been previously shown in the mouse system, but this is the first time it has been shown in the zebrafish.

Strengths:

The study was methodical and robust, using a published and well-validated zebrafish LipoGlo model. The authors validated the hits from the screen independently and considered the possibility that some drugs may have been detected as false positive results due to effects on the enzymatic activity of NanoLuciferase; only one hit, verteporfin, was shown to be a false positive. Using LipoGlo-Electrophoresis, the authors are able to obtain extra insights into the ApoB-lipoprotein size/subclass distribution. They showed that while enoxolone treatment reduces total B-lps, there are no overt changes in B-lp size distribution compared to vehicle-treated animals, other than a slight increase in the zero mobility (ZM) fraction, which contains very large particles and/or tissue aggregates. In contrast, the positive control, lomitapide, does show a change in B-lp size distribution compared to vehicle-treated animals - an increase in frequency of LDLs (low-density lipoprotein), but a decrease in VLDLs (very low-density lipoprotein). This study also assesses the LipoGlo-Electrophoresis profile of HNF4⍺ inhibitors. Work in the zebrafish larvae means that the effect on overall development and an entire vertebrate organism can also be assessed. Finally, the authors applied a thorough statistical measure to define a hit, using the Strictly Standardized Mean Difference (SSMD) method.

Reviewer #2 (Public review):

Summary:

The authors have improved clarity overall and have spoken to most of the issues raised by the reviewers. There are still two outstanding problems however, where issues raised during the review were inappropriately dismissed in the manuscript. These should be explicitly addressed as limitations to the results presented (no eye tracking), and early pilot experiments that informed the experiments as presented (pink noise) rather than brushed off as 'unnecessary' and 'would be uninformative'.

Eye tracking:<br /> It is generally accepted that experiments testing stimuli presented at specific locations in peripheral vision require eye tracking to ensure that the stimulus is presented as expected, in particular, in the correct location. As I stated in the previous round of review, while a stimulus presentation time of 200ms does help eliminate some saccades, it does not eliminate the possibility that subjects were not fixating well during stimulus onset. I am also unclear what the authors mean by 'trained observer' in this context, though the authors state that an author subject in a different portion of the paper is an 'expert observer'. Does this mean the 'trained observers' are non-expert recruited subjects? Given the conditions tested differ from previous work (Freeman & Simoncelli, 2011) *these differences are a main contribution of the paper!* which DID include eye tracking in a subset of subjects, it is entirely possible to get similar results to this work in the context of non eye-tracking controlled stimulus presentation. The reasons now in the manuscript are not reasons that make eye tracking 'considered unnecessary'.

I appreciate that the authors now state the lack of eye tracking explicitly, but believe the paper needs to at least state that this is a limitation of the results reported, and eyetracking being 'considered unnecessary' is unreasonable, nor a norm in this subfield.

N=1:<br /> The authors now state clearly the limitations of a single subject in the manuscript, and state the expertise level of this subject.

Large number of trials:<br /> The authors now address this, and include an enumeration of the large number of trials.

Simple Models / Physiology comparison:<br /> I support the choice to reduce claims regarding tight connections to physiology, and appreciate the explanation of the luminance model.

Previous Work:<br /> I appreciate the author's changes to the introduction, both in discussing previous work and citation fixes.

Blurred White, Pink Noise:<br /> While the authors now address pink noise, the explanation for such stimuli being expected to be uninformative is confusing to me. The manuscript now first states that pink noise is a natural choice, then claims it would be uninformative, while also stating in the rebuttal (not the manuscript) that they tried it and it indeed reduced the artifacts they note. The logic of the experiments indeed relies on finding the smallest critical scaling value, which is measured by subjects determining if a synthesis is similar or different to a target or second synth. A synthesis free from artifacts would surely affect the subjects' responses and the smallest critical scaling measured.

The statement that the authors experimented with pink noise early on and found this able to address the artifacts should be stated in the manuscript itself, not just in the rebuttal, and the blanket statement that this experiment would be 'uninformative' is incorrect. Surely this early pilot the authors mention in the rebuttal was informative to designing the experiments that appear in the final paper and would be an informative experiment to include.

Comments on revised version.

The authors have addressed my outstanding concerns, adding discussion about the limitations of not having eye tracking in the study, details about the subject pool, limitations of a subset of the study which contains a single subject, and experiments with pink noise seeds, and this relationship to largest vs smallest critical scaling. In addition, they have added clarity around internal noise vs metamerism in the context of this study as raised by the other reviewer.

Reviewer #2 (Public review):

In this manuscript, the authors investigate how the oncogenic fusion protein NUP98-KDM5A alters gene expression in leukemia, using a combination of cellular experiments with model and patient cell lines, as well as in vitro studies. Upon transfection of U2OS cells with mEGFP-tagged NUP98-KDM5A, the authors show that the fusion proteins form sub-micrometer puncta, whereas KDM5A alone does not. These foci are also observed at expected native expression levels (using OpenCell data). The tag has an effect here, as switching to an mCherry tag raises the apparent saturation concentration for phase separation. Finally, the authors show via super-resolution imaging that the foci correlate with H3K4me3 distribution.

In vitro, the fusion protein forms amorphous, gel-like condensates at double-digit nanomolar concentrations. Truncation analysis identifies PHD3 of KDM5A as required for maximal phase separation, consistent with the ability of the protein to bind H3K4me3 peptides. Addition of polynucleosomes increases the amount of fusion protein partitioning into the condensate in an H3K4me3-binding-dependent manner. Condensates are gel-like with slow internal dynamics in vitro; in cells, however, the dynamics depend on the position of the EGFP tag (no corresponding experiments with mCherry are shown). Reconstitution with H3K4me3- and H3K4me0-modified arrays shows colocalization with both wild-type NUP98-KDM5A and the binding mutant. Here, H3K4me3 arrays recruit ~20% more protein and yield gel-like structures in a manner dependent on the PTM and on the PHD finger.

In cells, the fusion protein colocalizes with H3K4me3-marked loci, including the HOX clusters, as confirmed by FISH. Finally, re-analysis of published expression datasets from patient cells shows that genes are predominantly upregulated and that the upregulated genes are H3K4me3-marked.

This is a well-executed mechanistic study. The data convincingly establish that NUP98-KDM5A forms sub-micrometer foci at realistic expression levels, that these foci correlate with H3K4me3-marked sites, that the PHD3-H3K4me3 interaction mediates chromatin binding while the NUP98 moiety drives phase separation in vitro, that foci in cells overlap genes heavily decorated with H3K4me3, and that H3K4me3-marked genes are those found to be upregulated in patient datasets. These are important mechanistic findings and of interest to the community.

Still, the functional/causal link is a bit more tentative, as the data is mostly correlative, since it is not directly established that there is feedback between H3K4 methylation, NUP98-KDM5A recruitment, phase separation and target gene overexpression. An experiment that could further bolster this claim would be a direct test of whether NUP98-KDM5A expression drives overexpression of bound genes, e.g. expression of the fusion protein vs PHD- and NUP98-mutant variants, followed by qPCR of target genes, such as the HOX cluster, and possibly H3K4me3 ChIP at the same loci. As all the constructs and cell lines exist, this could be feasible and would substantially strengthen the manuscript.

Reviewer #2 (Public review):

Summary:

In this manuscript, Gini et al. investigate the mechanisms by which CDK4 and CDK6 upregulation drives resistance to EGFR tyrosine kinase inhibitors (TKIs) in EGFR-mutant lung adenocarcinoma (LUAD). The study utilizes preclinical models, including cell line-derived xenografts (CDXs), patient-derived xenografts (PDXs), and primary organoids, alongside large-scale clinical genomic datasets. The authors demonstrate that CDK4 or CDK6 overexpression allows cancer cells to bypass EGFR TKI-induced G1/S arrest, leading to continuous cell cycle progression. This sustained proliferation during EGFR inhibition induces DNA replication stress, activates DNA damage response pathways (such as ATM and TPX2), and ultimately causes genomic instability. The authors also show that this leads in turn to the upregulation of tumor-promoting genes (e.g., AGR2, ASNS, STEAP1) and an epithelial-mesenchymal transition (EMT) phenotype. Moreover, the authors show that combinatorial treatment utilizing TKIs such as osimertinib alongside CDK4/6 inhibitors effectively suppresses proliferation, mitigates DNA damage, and restores TKI sensitivity in preclinical models.

Overall, this is a highly translational study that provides a strong mechanistic rationale for biomarker-driven clinical trials combining EGFR and CDK4/6 inhibitors. However, there are a few experimental and analytical areas that require clarification or additional data to fully support the authors' conclusions.

Major Comments:

(1) Reliance on overexpression models over loss-of-function

The mechanistic studies mainly rely on overexpression of CDK4 and CDK6 to simulate the amplified state. Although the authors argued that the level of overexpression mimics that observed in resistant tumors, a complementary study in which CDK4/CDK6 were suppressed in a model where CDK4/CDK6 is amplified (such as HCC827 or TH116), and replication stress and osimertinib sensitivity tested would greatly strengthen their observations. Indeed, there is mention of CDK4 constructs to perform knockdown studies in the methods, but those studies are not included in this submission.

(2) Mechanistic link between genomic instability and specific gene amplifications

The authors highlight that CDK4/6 activation leads to recurrent copy number gains and transcriptional upregulation of specific pro-tumor genes including AGR2, ASNS, and STEAP1. While the paper establishes that CDK4/6 overexpression causes general genomic instability (increased FGA), it does not mechanistically explain why these specific genes are consistently amplified. The authors should investigate or discuss whether these specific loci are inherently fragile under replication stress, if they are direct downstream targets of the E2F transcriptional program, or if this is a result of random genomic instability followed by strong positive selection under osimertinib pressure.

(3) Discrepancies in tumor mutational burden (TMB) reporting

There is a slight contradiction regarding the TMB data that needs to be clarified for readers. The manuscript states that in the clinical datasets, "EGFR-mutant LUAD harboring cell cycle gene alterations exhibited significantly elevated FGA and TMB relative to cell cycle-negative tumors" (Line 265-266). However, in the next section, the authors say, "Notably, no corresponding increase in TMB was observed with CDK4 or CDK6 CNA, similar to our findings in preclinical models" (Line 271-273). The authors should clarify or discuss why broad cell cycle alterations correlate with high TMB, while CDK4/6-specific alterations drive structural instability (FGA) without increasing TMB.

Reviewer #2 (Public review):

Summary:

Jiang et al. sought to elucidate the molecular basis of polymyxin antibiotic interaction with the renal transporter hPepT2, a transporter previously implicated in polymyxin-induced nephrotoxicity. They combined molecular dynamics simulations with transporter mutagenesis, functional uptake assays, kinetic analyses, protein expression studies, antibacterial susceptibility testing, and mouse nephrotoxicity experiments to develop a structure-interaction relationship (SIR) model and apply this model to the rational design of polymyxin analogues.

Overall, the study represents a substantial multidisciplinary effort that integrates computational and experimental approaches. The identification of transporter residues involved in polymyxin recognition and the subsequent design of analogues with reduced hPepT2-mediated uptake provide a valuable framework for developing safer polymyxin antibiotics. In particular, the identification of FADDI-795 as an analogue that retains antibacterial activity while exhibiting reduced nephrotoxicity represents an encouraging proof of concept.

Strengths:

The computational predictions are strengthened by extensive experimental validation, including site-directed mutagenesis, transport kinetics, fluorescence uptake assays, membrane expression analyses, and in vivo toxicity studies. The consistency between multiple independent experimental approaches increases confidence in many of the authors' conclusions.

Weaknesses:

Several conclusions would benefit from a more cautious interpretation. A major limitation is that several transporter mutations substantially altered total or membrane protein expression, making it difficult to distinguish effects on substrate binding from indirect effects caused by impaired transporter stability or trafficking. The authors acknowledge this limitation in the Discussion, but some mechanistic conclusions remain stronger than the available evidence supports.

Similarly, while the proposed binding model is biologically plausible and supported by mutagenesis, it remains an inferred model derived from molecular simulations rather than a direct structural determination. Statements describing the model as "validated" should therefore be moderated to indicate that the experimental data provide support rather than definitive structural confirmation.

The translational implications are promising but remain preliminary. Although FADDI-795 demonstrated reduced nephrotoxicity in the mouse model while maintaining antibacterial activity, no pharmacokinetic studies were presented to demonstrate reduced renal accumulation or altered tissue distribution, and additional efficacy studies in infection models would further strengthen the therapeutic claims.

Reviewer #2 (Public review):

The study addresses the conundrum of how the mRNAs of SARS-CoV-2 are efficiently translated since the 5' leader, which has common elements for all the viral genes, is highly structured. The authors test the hypothesis that m6A modification at position 74 is key to this translation. First, the authors show convincingly that this site is modified. Then, with extensive transfected reporter experiments using luciferase assays as well as sucrose gradient sedimentation, this modification is shown to be key for efficient translation. While the mechanism of this effect is not entirely clear (see comments/suggestions below), the authors show that it is independent of YTH "reader" proteins and likely involves altered interactions between SL3 (which contains A74) and downstream elements in the UTR. These results are important because they both offer insight into the function of m6A in gene expression and suggest how they may be important for the translation of viral mRNA in particular.

While the data on their own make the overall case that the m6A modification in the 5'UTR of the viral genes is important to their expression, there are several things worth considering that could refine the model and make it more convincing.

It is not clear whether putative uORF translation, particularly translation of the uORF that begins with a CUG codon at position 59 in the 5'UTR (as shown in Finkel et al., Nature 2020), would be impacted by this modification (as it includes the putative m6A site at position 74). It is also worth considering whether SL3 melting by translation of this uORF would alter the proposed mechanism.

It is a bit unclear why the A74T mutant was put in the longer construct while the C75G mutant was put in a shorter construct. While not essential, the mechanistic arguments would be stronger if the same construct had been used to compare the mutations.

While the authors show that "global depletion of m6A modification does not grossly alter translation efficiency" in a general sense (page 11), it would be of interest to know whether any host mRNAs with 5'UTR m6A (i.e., ACTA2 and COX8A, mentioned in this study) are affected by the mechanism here (i.e. run them in the luciferase assay).

The authors show that the YTH "reader" proteins have a very small inhibitory effect (1.6-fold) on the translation of the viral mRNA with 5'UTR m6A. However, it remains unclear how important this is or whether it is generally true for host mRNAs with this modification.

It is reassuring to see controls for changes in RNA levels in the supplemental material. The RNAs were generally stable under the experimental parameters explored, which would rule out RNA-decay-based mechanisms of m6A regulation. However, it should be noted that mRNA level experiments appear to have been done at 24 h while luciferase measurements were done at 48 h (as noted on p. 23, gene expression vs luciferase activity). It is not clear whether any RNA decay phenotypes would be apparent at 24 h.

The authors use the term "ribosome profiling" (for example, on page 10), but it would appear the experiment performed is actually "polysome profiling" or "sucrose gradient sedimentation" since it did not involve ribosome footprinting.

Reviewer #2 (Public Review):<br /> <br /> Summary:

Rademacher et al. present a paper showing that chronic chemogenetic excitation of dopaminergic neurons in the mouse midbrain results in differential degeneration of axons and somas across distinct regions (SNc vs VTA). These findings are important. This mouse model also has the advantage of showing a axon-first degeneration over an experimentally-useful time course (2-4 weeks). 2. The findings that direct excitation of dopaminergic neurons causes differential degeneration sheds light on the mechanisms of dopaminergic neuron selective vulnerability. The evidence that activation of dopaminergic neurons causes degeneration and alters mRNA expression is convincing, as the authors use both vehicle and CNO control groups, but the evidence that chronic dopaminergic activation alters circadian rhythm and motor behavior is incomplete as the authors did not run a CNO-control condition in these experiments.

Strengths:<br /> This is an exciting and important paper.<br /> The paper compares mouse transcriptomics with human patient data.<br /> It shows that selective degeneration can occur across the midbrain dopaminergic neurons even in the absence of a genetic, prion, or toxin neurodegeneration mechanism.

Weaknesses:

Major concerns:

(1) The lack of a CNO-positive, DREADD-negative control group in the behavioral experiments is the main limitation in interpreting the behavioral data. Without knowing whether CNO on its own has an impact on circadian rhythm or motor activity, the certainty that dopaminergic hyperactivity is causing these effects is lacking.

(2) One of the most exciting things about this paper is that the SNc degenerates more strongly than the VTA when both regions are, in theory, excited to the same extent. However, it is not perfectly clear that both regions respond to CNO to the same extent. The electrophysiological data showing CNO responsiveness is only conducted in the SNc. If the VTA response is significantly reduced vs the SNc response, then the selectivity of the SNc degeneration could just be because the SNc was more hyperactive than the VTA. Electrophysiology experiments comparing the VTA and SNc response to CNO could support the idea that the SNc has substantial intrinsic vulnerability factors compared to the VTA.

(3) The mice have access to a running wheel for the circadian rhythm experiments. Running has been shown to alter the dopaminergic system (Bastioli et al., 2022) and so the authors should clarify whether the histology, electrophysiology, fiber photometry, and transcriptomics data are conducted on mice that have been running or sedentary.

Reviewer #3 (Public review):

Summary:

Core conclusions are well-supported by data: co-folding outperforms docking in known ligand pose/affinity prediction (validated by RMSD and IC₅₀ correlation), struggles with false positive discrimination in virtual screens (lower AUC values), and is complementary to docking (non-correlated errors, distinct strengths in drug discovery stages).

Strengths:

Unprecedented prospective design with 557 novel Mac1-ligand complexes ensures rigorous, independent evaluation of co-folding methods, provides an unbiased and rigorous benchmark dataset, which contains structures and compounds absent from the co-folding models training sets. Comprehensive comparison of 3 co-folding tools (AlphaFold3, Chai-1, Boltz-2) with DOCK3.7 across diverse targets and metrics enables nuanced performance assessment. The revised results clarify an intriguing finding: co-folding can predict correct ligand poses even when protein formations are mispredicted. The study clearly demonstrates complementary roles of co-folding (superior pose/affinity prediction for known ligands) and docking (better hit prioritization), and addresses deep learning memorization concerns via ligand similarity analysis.

Weaknesses:

The study identifies a major limitation of co-folding-failure to capture rare protein conformational changes, which deserve future investigation. The authors include uncalibrated Boltz-2 affinity data (addressing a prior comment) but note that large-scale free energy perturbation (FEP) comparisons are beyond their capabilities.

Appraisal of Aims Achieved:

The authors successfully achieved their primary aims and the results provide strong, well-supported evidence for their core conclusions. Key conclusions are grounded in the study's unbiased, training-set independent data, ensures the conclusions are not confounded by model memorization and are broadly applicable to the field's use of these co-folding models.

Field Impact:

This study provides a critical reality check for the field: co-folding models are powerful tools for pose prediction but are not yet standalone solutions for virtual screening, a key distinction that will prevent over-reliance on these models and guide more rational tool selection.

Reviewer #2 (Public review):

Summary:

Savage et al. investigates the synchronization of retinal Ca2+ waves with developmental cell death, microglia activation, and vascular outgrowth. These developmental processes occur through a mechanism where apoptotic cells release ATP through Panx-1 channels to stimulate both Ca2+ retinal waves and microglia activation. Using scRNAseq, the authors classify autofluorescence cell clusters (ACCs) at the leading edge of vasculature outgrowth as Hmox-1+ microglia. From here they show microglia engulfment of apoptotic RGCs and the potential release of ATP may contribute to Ca2+ wave generation. The authors demonstrate these mechanisms through the use of two pharmacological to agents to either block the ATP release from Panx-1 or by blocking receptor binding to ATP. Furthermore, while previous studies have described the site of initiation of retinal Ca2+ waves as random, this study shows the initiation of Ca2+ waves are biased to the leading edge of vascular growth in the developing retina. To do this, the authors use a combination of wide-field Ca2+ imaging and multi-electrode arrays to pinpoint the sites of Ca2+ wave initiation in the developing retina.

Strengths:

Savage et al. uses a several techniques to interrogate these mechanisms, including single cell RNAseq, wide-field Ca2+ imaging, and multi-electrode arrays. With these experiments, this manuscript proposes several novel ideas, such as ATP as the Ca2+ wave initiating cue, and the localization the Ca2+ wave initiation to the leading edge of vascular growth.

Weaknesses:

The main limitation of this study is the reliance on only two pharmacological agents to test their central hypotheses. In future studies, these conclusions could be strengthened if they used genetic knockout models to perturb programmed cell death and/or ATP release (i.e. BAX-KO, Panx-1 KO).

Reviewer #2 (Public review):

The determination of macromolecular structures directly within their native cellular environment is becoming increasingly routine, making standardized data collection strategies essential. In this manuscript, Tuijtel et al. provide a timely and valuable contribution by benchmarking key acquisition parameters and establishing practical guidelines for in situ cryo-electron tomography (cryo-ET). Critically, the authors present a systematic framework for optimizing data collection to achieve the highest attainable resolution.

Using Dictyostelium cells as a model system, the authors generate multiple datasets at a constant total dose while varying the tilt increment. They demonstrate that tilt-series acquired with finer increments (1-3 degrees) yield superior alignment accuracy and improved template-matching performance, resulting in higher-quality reconstructions than those collected with coarser increments (5 degrees or above). Furthermore, the authors show that for subtomogram averaging, a 3-degree tilt increment outperforms all other conditions tested, particularly after per-particle refinement as implemented in M.

Comments on revised version.

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

Reviewer #2 (Public review):

In the manuscript entitled "Adaptive plasticity of aspartate metabolism in succinate dehydrogenase-deficient cancer cells," Sokolov et al. delineate the metabolic adaptations that succinate dehydrogenase (SDH)-deficient cancer cells undergo over time to overcome the initial aspartate limitation. To do so, the authors generated five clonal osteosarcoma SDH subunit B (SDHB) knockout cell lines using the CRISPR/Cas9 system and compared the proliferation rates of early- and late-passage cells, revealing that the latter rewired central carbon metabolism to increase aspartate levels and therefore replicate faster than their early-passage counterparts. Using a series of pharmacological and/or genetic interventions, the authors show that this rewiring can occur via two different routes: either through reduced Complex I (CI) activity, whereby glutamine is channelled towards aspartate synthesis via reductive carboxylation, or through a metabolic rewiring in which aspartate is produced from glucose via the PC-GOT2 pathway while CI activity is preserved. The CI-suppression-independent route depends on PC expression, as evidenced by an analysis of DepMap cell-line data, in which higher PC expression is associated with decreased SDH dependency. Moreover, they find that other consequences of aspartate deprivation observed in SDH-deficient cells, including impaired pyrimidine synthesis, replication stress, and DNA damage, are ameliorated in late-passage cells.

Overall, this study is interesting because it disentangles the different metabolic rewiring routes that SDH-deficient cells can undergo to reverse aspartate limitation and sheds light on previously reported, seemingly contradictory results in the field. However, the study's major premise requires further validation, and important controls are missing, diminishing the overall strength of the conclusions.

Major points:

(1) The main conclusion that two separate routes allow SDH-deficient cells to overcome aspartate limitation, defined by their CI-activity status, is not convincingly proven. Indeed, to show this dichotomous behaviour, the authors performed Western blots for two CI subunits and determined the basal oxygen consumption rate. However, these assays are insufficient to demonstrate that LP clones 2 and 3 maintain functional CI, in contrast to LP clone 1. Moreover, it is not ruled out that these clones show dysfunction in ETC complexes other than CI. To assess these points, the activities of all individual ETC complexes should be carefully measured, for instance, by Seahorse assay after permeabilization. Furthermore, given the complex nature of CI, a reduction in two subunits does not necessarily reflect a reduction in its assembly. Therefore, CI assembly should be assessed directly by BN-PAGE analysis of isolated mitochondria.

(2) It is difficult to reconcile why the authors used an NDUFA8 KO in clone 2 EP to mimic the physiological long-term CI-suppression-dependent adaptation. Indeed, this approach seems to represent an extreme scenario of Complex I loss that may induce non-physiological adaptations that override the effects of SDH KO. To assess the distinct metabolic fluxes between the two proposed routes, it would be advisable to use a more physiological model and instead compare the tracing data from LP clone 2 with those from LP clone 1, which exhibits a "natural" CI-suppressed state. Does clone 1 LP show similar metabolic changes to A8KO, including increased reductive carboxylation?

(3) It is unclear whether the loss of Complex I at late passage is an intrinsic progression of osteosarcoma cells rather than a feature specific to SDH-deficient cells. A proper comparison between SDHB-deficient cells and WT cells, both at early and late passage, should be carried out. This is essential to fully understand the adaptive trajectories of SDH-deficient cells. This comparison is essential to identify the baseline metabolic hardware of the osteosarcoma cells. Indeed, the authors state that "While wild-type 143B cells synthesize most aspartate from glutamine via oxidative TCA cycling and GOT2 activity, ..." (Page 7, third paragraph), but these data are not included in the manuscript and would represent an important control for assessing the observed metabolic changes in comparison with the wild-type context.

(4) The data showing that the PC-GOT2 pathway is mainly driven by enhanced PC activity are not fully convincing, as PC activity seems to be equally important for maintaining aspartate levels in the NDUFA8 KO compared with clone 2 LP. Moreover, the extracted expression data from DepMap suggest that increased PC expression might not be transcriptionally regulated, as only a slight association between PC mRNA levels and SDH dependency was observed. Are PC mRNA levels increased in clone 2 LP? If not, PC might be regulated post-transcriptionally. To test this, the nascent translation of PC could be assessed.

Reviewer #2 (Public review):

Summary:

Barrett et al. examine how neural activity in the mouse motor cortex varies when a movement is performed with the ipsilateral or contralateral forelimb. First, they train animals to grasp and manipulate a pellet of food with either the left forepaw, the right forepaw, or both. Next, they measure activity in the primary and secondary forelimb motor areas (fl-M1 and fl-M2) and in the classical tongue-jaw area (tj-M1 / LOM). While responses in the forelimb areas are diverse, with some neurons preferring ipsilateral or bilateral movements, a plurality of cells prefer the contralateral limb. In LOM, by contrast, little limb selectivity is observed. At the neural population level, structure is preserved across conditions in LOM, but not in the forelimb areas. Finally, paw position can be decoded from activity in all three areas, and the LOM decoder generalized across limbs.

Strengths:

While previous studies in macaques have compared motor cortical activity during movement (and perturbation) of the contralateral and ipsilateral arms, no analogous work has been undertaken in rodents. This paper closes this knowledge gap by showing, for the first time, moderate-to-strong lateralization in the forelimb motor cortical areas of mice transporting grasped food pellets to the mouth, and a relative absence of lateralization in the classical tongue-jaw area. On the whole, I think this is a solid paper that reports novel observations of interest to the motor systems community.

Weaknesses:

The central question posed is whether cortical activity depends on the effector(s) used (ipsi forelimb, contra forelimb, or both). The corresponding hypotheses (Figure 1) are somewhat coarse-grained and are not mutually exclusive. One might expect to see condition-independent, limb-selective, and uni-/bimanual-selective signals in motor cortex (though their magnitudes could differ substantially), and to find these signals intermingled at the level of single neurons. The authors may wish to consider setting up a more focused question. For example, can bimanual responses be explained as a sum of the unimanual responses from the left and right limbs?

In the area usually identified as tongue-jaw motor cortex (here referred to as LOM), unit and population activity look quite similar for ipsilateral, contralateral, and bilateral forelimb reaches. The most parsimonious explanation is that the activity is related mostly to mouth and tongue movements, rather than limb movements. Systematic mapping studies with microstimulation in the rat (Neafsy et al., Brain Res. Rev. 1986) and optogenetic stimulation in the mouse (Mayrhofer et al., Neuron 2019) tend to support the idea that tjM1/LOM is specialized for control of the tongue and mouth. Thus, I'm not entirely convinced that it "encodes ingestion-related forelimb parameters necessary for oromanual coordination." The authors could say more about this issue: what specific limb-related parameters do they think are encoded, why would these parameters be effector-independent, what evidence for this encoding is presented here, and how can limb- and mouth-related components be distinguished? The problem could potentially be addressed experimentally, as well, by delivering food pellets directly to the mouth while preventing manipulation with the paws, but this experiment isn't strictly necessary.

Because the corticospinal tract is strongly lateralized, cortical activity presumably has a smaller effect on ipsilateral than contralateral motor output. Somatosensory feedback should also be relatively lateralized for the forelimb areas. The authors could say a bit more about this issue and how it relates to their data and conclusions in the Discussion.

An important limitation of the behavioral task is that it involves only a single stereotyped movement for each limb, instead of multiple directions, speeds, or loads. This issue and its consequences for the analyses (especially those in Figures 7-10) and conclusions could be discussed.

Reviewer #2 (Public review):

Major concern 1: The manuscript does not clearly establish a bona fide GS filament state.

The authors repeatedly refer to GS "filaments," but the data presented appear to support primarily a di-decameric assembly rather than a well-defined filamentous polymer.

A two-decamer reconstruction can define a putative inter-decamer interface, but it cannot by itself demonstrate propagation of a repeating filament geometry. To establish a bona fide filament, the authors should provide evidence for a reproducible one-dimensional assembly, such as at least three consecutive repeating units or equivalent quantitative evidence that the same inter-decamer transform propagates along an assembly axis.

In the current manuscript, many of the supporting 2D classifications appear to contain at most two adjacent GS decamers. This is particularly evident in the time-resolved cryo-EM datasets shown in Supplementary Figures 9-10, where I do not see convincing 2D classes corresponding to filaments. The same concern applies to other datasets, including Supplementary Figures 2, 6, and 11, where the apparent assemblies are primarily two-decamer particles.

Moreover, many of the selected "filament" classes show only one well-resolved GS decamer, while the neighboring decamer density is blurred. This suggests substantial variability in the relative position and/or orientation of adjacent decamers. Such heterogeneity is difficult to reconcile with a stable repeating filament geometry.

Therefore, the authors should explicitly define what they mean by "filament." If their evidence supports only a di-decameric or short oligomeric assembly, the terminology should be changed accordingly throughout the manuscript.

Symmetry concern

Given the low quality and heterogeneity of the 2D classifications for the putative "filament" classes, the use of D5 symmetry requires stronger justification. The current reconstructions primarily show the result after applying D5 symmetry to a two-decamer assembly. The authors should show reconstructions of the same particle sets processed under C1, C5, and D5 symmetry, and explain why D5 symmetry is justified.

This is particularly important because the claimed interface density and ligand interpretation are sensitive to symmetry averaging. Without showing how the reconstruction behaves under less restrictive symmetry assumptions, it is difficult to determine whether the final D5 map reflects a true biological assembly or a symmetry-imposed interpretation.

Filament abundance and physiological relevance

Even under the authors' broad classification criteria, the filament-like population appears to be a minor species. In some datasets, especially Supplementary Figure 10, the apparent filament fraction is very low, approximately 2-10%. This raises a major concern: if GS filaments are rare even under high-concentration cryo-EM conditions, are they expected to form to a meaningful extent under physiological conditions?

The authors propose a concentration-dependent assembly mechanism. If so, the relevance of GS filamentation in the lower-concentration cellular environment becomes even less clear. The authors should quantify filament abundance as a function of GS concentration and glutamine concentration, ideally under conditions closer to physiological ranges.

K52/C53 interface mutations

The authors use K52 and C53 as filament-interface residues, but the mechanistic contribution of these residues to filament assembly remains insufficiently explained. Why should K52A or C53A disrupt filament formation? Is the effect due to loss of a specific side-chain contact, altered local electrostatics, reduced crosslinker accessibility/reactivity, local structural destabilization, or nonspecific disruption of the interface?

The manuscript states that the interface is "concentration dependent and driven primarily by electrostatic interactions," but the data presented before that statement do not clearly establish this. The authors should explicitly identify the interacting electrostatic partners and provide structural or biochemical evidence supporting this interpretation.

Functional linkage between filamentation and kinetics is weak.

The authors should establish the oligomeric state of GS under the actual assay conditions. In particular, what is the filament fraction during the Figure 2F / Supplementary Figure 15 kinetic assays? Is the change in KM ammonia quantitatively correlated with filament abundance?

This is currently unclear. The direct comparison between decamer and 2-decamer fractions does not robustly show a functional difference, and the later glutamine-addition assays are interpreted as filament-mediated without directly demonstrating the filament fraction under the same assay conditions.

In Figure 2F, WT, K52A, and C53A already show different ammonia-dependent kinetic parameters in the absence of added glutamine. K52A and C53A appear to have lower basal kcat/KM ammonia and higher KM ammonia than WT even without glutamine. The authors should explain why these interface mutants already alter basal ammonia kinetics. Without such an explanation, K52A and C53A cannot be treated as clean controls that selectively disrupt glutamine-stabilized filamentation.

Major concern 2: The interface density is not convincingly assigned to glutamine.

The second foundational issue is the assignment of the interface density to glutamine. At present, the evidence is not sufficient to support the conclusion that glutamine is the ligand at this interface.

The local density at the interface appears weak and likely has lower local resolution than the reported global resolution. The current density could represent a low-occupancy or symmetry-averaged amino-acid-like density rather than a confidently assigned glutamine molecule.

Ligand pose and hydrogen bonding.

The proposed glutamine pose also requires more rigorous validation. The authors state that glutamine forms hydrogen bonds with interface residues, including K52, C53, and E55. These hydrogen bonds should be shown explicitly in a figure, with distances listed.

The proposed interaction involving C53 appears unusual and should be justified chemically and geometrically.

Glutamate has not been excluded.

The largest problem is that the authors do not adequately consider glutamate as an alternative ligand. They compare the density with phosphate and ATP/ADP, but this is not sufficient. Glutamate is present at high concentration during turnover, and it is chemically and structurally very similar to glutamine. Given the limited local density and possible orientational averaging, distinguishing glutamine from glutamate from the current cryo-EM density alone is not justified.

The authors should report or estimate the concentrations of glutamate and glutamine at the vitrification time point used for the high-resolution turnover-filament reconstruction. If glutamate is present at a much higher concentration than glutamine, the authors must explain why the interface density should be assigned to glutamine rather than glutamate.

The authors should fit both glutamine and glutamate into the interface density using the same validation criteria and compare the results. Stronger support would come from direct structural experiments, such as cryo-EM structures of GS incubated separately with glutamate and glutamine under controlled conditions.

Unless stronger evidence is provided, the claim that "glutamine binds to the filament interface" cannot be made.

Specific comments

Interface assembly statement:<br /> "These data suggest that the formation of the interface is concentration dependent and driven primarily by electrostatic interactions."

What specific data support "concentration dependent" at this point in the manuscript? Which residues or chemical groups are proposed to form the electrostatic interactions? The authors should provide a more explicit explanation.

Line 149-150:<br /> "In both scenarios, any signal is likely to be averaged out and experiments with symmetry expansion and focused classification did not yield any convincing density."

Please show these analyses. Negative results are important here because they bear directly on the reliability of the interface interpretation.

"Glutamine stabilizes larger GS filaments":<br /> What does "larger" mean? Longer filaments, more decamers per filament, or larger diameter? The authors should define this quantitatively, preferably by reporting filament-length distributions or the number of decamers per assembly.

Filament classification:<br /> The criteria used to classify particles or 2D classes as "filament" are not sufficiently clear. The authors should provide the full 2D classification results for each time-resolved dataset, including selected and discarded classes, particle numbers, and objective selection criteria. Some selected and discarded classes appear visually similar, especially in Supplementary Figures 9-10.

R298A decamer:<br /> The R298A mutant is presented as a turnover-decamer structure, not a filament structure. The authors should clarify whether R298A forms filament-like particles under comparable turnover conditions. If R298A does not form filaments, this should be reported and explained. If filament-like particles were present but excluded during processing, the authors should provide their abundance and justify why only the decameric form was analyzed. This point matters because R298A is used to connect E305-loop disorder with the proposed filament-associated mechanism, although R298A is a loop-stabilization mutant rather than a filament-interface mutant.

Line 231-233:<br /> "a reaction time that should yield a high concentration of product due to the higher enzyme concentration than previous experiments"

What is the estimated product concentration at vitrification? What concentration range qualifies as "high"? The authors should provide a quantitative estimate.

Glutamine hydrogen bonds:<br /> The proposed hydrogen bonds linking glutamine to K52, C53, and E55 should be shown explicitly with atom identities and distances.

Glutamate comparison:

What is the glutamate concentration in the same sample? Given that glutamate is chemically similar to glutamine and likely present at high concentration, why is the interface density not glutamate? The authors should compare glutamine and glutamate fitting using the same validation criteria.

Line 248-253:<br /> The speculation that apo filaments may arise from high GS concentration or residual glutamine should be moved to the Discussion. In the Results, this reads as an ad hoc explanation rather than a result directly supported by data.

Actual assay-state oligomeric distribution:<br /> What is the filament fraction under the actual kinetic assay conditions? Is the KM ammonia change quantitatively correlated with filament abundance?

Figure 2F:<br /> Why do WT, K52A, and C53A differ in basal ammonia-dependent activity even without added glutamine? The authors should explain whether these mutations alter intrinsic ammonia kinetics independent of filamentation.

Supplementary Figure 15 / Figure 2F:<br /> Please clarify the relationship between Figure 2F and Supplementary Figure 15. The kinetic constants in Figure 2F appear to depend on global fitting of progress curves shown in Supplementary Figure 15. The authors should provide replicate-level raw progress curves, between-replicate variability, fitting residuals, and individual fitted parameters.

Supplementary Figure 19:<br /> Supplementary Figure 19 should be presented consistently with Supplementary Figure 18, including the corresponding 2D classification results.

In summary, although the revised manuscript improves the presentation of cryo-EM map processing, the two foundational claims remain unresolved. The current data establish, at most, a di-decameric or filament-like GS assembly, but not a rigorously defined filamentous polymer. In addition, the interface density is not convincingly assigned to glutamine, particularly because glutamate has not been excluded as the most relevant alternative ligand. Since the proposed negative-feedback mechanism depends directly on these two points, the current evidence does not support the strength of the title, abstract, or mechanistic conclusions.

Reviewer #2 (Public review):

Summary:

The authors developed a deep learning model based on a DenseNet CNN architecture to predict two cognitive functions: working memory and episodic memory, from functional connectivity matrices. These matrices were recorded under three conditions: during rest, a working memory task, and a movie, and were treated as images for the CNN algorithm. They tested their model's performance across different conditions and a separate dataset with a different age distribution (using the same MRI scanner, scanning configurations, and cognitive tests). They also calculated the "brain cognition gap" based on the model trained on resting functional connectivity to predict working memory. Extending from the commonly used index "brain age," the brain cognition gap was defined as the difference between the working memory score predicted by their model (predicted working memory) and the working memory score based on the working memory test itself (observed working memory). This brain cognition gap was found to be associated with physical activity, education, and cardiovascular risk. The authors also conducted additional mediation tests to examine whether regional functional variability mediated the relationship between PET-derived measures of dopamine and the brain cognition gap.

Strengths:

The major strength of this manuscript is the extensive effort the authors have put into creating a new 'biomarker' that links deep learning with fMRI, PET, physical activity, education, and cardiovascular risk across two studies. This effort is impressive.

Concerns from the previous round of review:

(1) The primary issue is still the lack of baseline models against which to benchmark the predictive performance of the proposed DenseNet model. This concern was raised independently by two reviewers. Without such benchmarks, it is difficult to interpret the reported results in the context of prior work on MRI-based cognition prediction.

Notably, the authors state: "While we compared our model with the connectome predictive modeling (CPM) approach and observed better performance with our deep learning framework, we did not conduct a comprehensive benchmark across all available machine learning methods, nor was this the aim of the present study."

However, I could NOT find any discussion or results related to the CPM model in the manuscript. It is therefore unclear whether the DenseNet model was actually statistically compared with CPM, and, if so, how the comparison was conducted.

Note that the statement, "While Vieira et al. show that the majority (76%) of prior studies used linear modeling approaches, including CPM and penalized regressions, these models are often vulnerable to overfitting, especially when applied to high-dimensional fMRI data," is not entirely accurate. Linear models typically have far fewer parameters than deep-learning models and are therefore often less prone to overfitting. In fact, it is well established that deep-learning models are particularly susceptible to overfitting and usually require substantially larger sample sizes to achieve stable and reliable performance. Although deep-learning models may outperform shallower models once sufficient data are available and training is well controlled, this does not justify the authors' claim as stated. I therefore disagree with the argument put forward by the authors.

The authors further justify the absence of benchmarking by stating: "In this context, deep learning was employed as a flexible framework capable of modelling high-dimensional functional connectivity patterns across cognitive states, rather than as a claim of inherent methodological superiority. Thus, our goal was not to propose a universally superior prediction model, but rather to test how brain state influences predictive utility for WM and EM using a deep learning approach." However, most shallow models can likewise be applied across different brain states and cognitive targets. This rationale does not establish deep learning as a uniquely appropriate or necessary choice. If deep learning is indeed a better approach in this context, the authors should demonstrate this empirically through appropriate benchmarking against established baseline models.

(2) Additional analysis shows that "BCG is not significantly associated with cognition itself". This is the most perplexing result. This is like saying Brain Age Gap is not related to chronological Age. It is counterintuitive since the Brain Age Gap is calculated by chronological age minus actual age, and most research has shown a strong relationship between the Brain Age Gap and age.

If the brain cognition gap is not related to cognition, is it possible that the results found are mainly due to the predictive model not fitting well with another dataset? Regardless, the lack of association between BCG and cognition deserves a discussion.

(3) I still do not fully understand the rationale of the mediation analysis. The analysis and findings are still not related to aims 1 and 2, since DA and entropy are not part of the prediction models. But I appreciate the explanation that this part is related to the authors' previous work, and that the authors attempted to link to them somehow.

[Editors' note: the authors have responded to these points.]

Reviewer #2 (Public review):

Earhart et al. investigated the role of the complement system in trained innate immunity (TII) in alveolar macrophages (AM). They used a WT and C3 knockout murine model primed with locally administered heat-killed P. aeruginosa (HKPA). Additionally, they employed ex vivo AM training models using C3 knockout mice, where reconstitution of C3 and blockade of C3R were performed. The study concluded that the C3-C3R axis is essential for inducing TII in macrophages in the ex vivo model. The manuscript is well-written and easy to follow.

Comments on revised version.

My concerns have been addressed, and the provided data is convincing supporting the manuscript's claims.

Reviewer #2 (Public review):

Summary:

This work by Waltner, et. al. provides a comprehensive single cell multiomics analysis of plasticity in gene regulatory networks present in Ewing sarcoma using single cell RNA-sequencing (scRNA-seq) and single cell assay for transposase accessible chromatin with sequencing (scATAC-seq). They find that Ewing sarcoma cell lines models have distinct patterns of chromatin accessibility compared to non-Ewing sarcoma models, and that there is significant variability across Ewing sarcoma cell lines, and sometimes within a single cell line. These differences across models are linked to 3 distinct gene regulatory modules, 2 of which are present across the range of model systems studied here. The first modules present across models is activated when the fusion is expressed and includes genes enriched for the known EWSR1::FLI1 response element, GGAA microsatellites along with other neural crest transcription factors. The other module primarily consists of genes repressed by EWSR1::FLI1, which are activated in EWSR1::FLI1-low states. Interestingly, EWSR1::FLI1-low cells have already been tied to more migratory and metastatic phenotypes and the data here suggest these cells are more responsive to external signals from TGF-β and this may be mediated through FOSL2-mediated gene regulation. This is a technically rigorous study, with a variety of different analytical techniques used to address similar questions and this approach elevates confidence in the answers provided. This is further strengthened by the diverse set of model systems used, including patient-derived cell lines, cell line xenograft models, patient-derived xenografts, mining available single cell data from patient samples, and validation of the gene modules identified in a larger set of patient microarray samples. In whole, this study provides a valuable resource for understanding heterogeneity, plasticity, and gene expression networks in Ewing sarcoma. This may be a useful resource for future studies of metastatic disease and provide a framework for similar questions in other fusion-driven sarcomas.

Comments on revised version.

The authors have addressed comments from my prior review. Thank you!

Reviewer #2 (Public review):

Summary:

This paper presented a hypothesis testing procedure for the independence of two time-series that was potentially suitable for nonlinear dependence and for small-sample cases. This should bring potential benefits for biology data.

Strengths:

The test offers good flexibility for different kinds of dependence (through adjusting \rho) and seems to have good finite sample performance compared to the literature. The justification regarding the validity of the test procedure is clear.

Reviewer #2 (Public review):

Summary:

Otgonbaatar et al. sought to investigate β-catenin/Arm protein lifetime and stabilization dynamics in vivo during embryonic development. To address this question, the authors developed an endogenous tandem fluorescent protein timer (tFP) system that enables the visualization of newly synthesized versus long-lived Arm protein in vivo. Using this approach, the authors sought to determine where stabilized Arm accumulates during development and how it contributes to dorsal closure.

Strengths:

A major strength of the study is the development and application of the endogenous Arm timer system, which provides a powerful approach for monitoring protein stabilization dynamics in living tissues. Using this system, the authors unexpectedly found that the strongest Arm stabilization occurs not in Wnt signaling regions, but at the leading edge cells during dorsal closure. The study combines quantitative live imaging, optogenetic perturbation, genetic analysis, and structure-function approaches to demonstrate that stabilized junctional Arm interacts with α-catenin and contributes to tissue mechanics required at the leading edge for dorsal closure. Particularly compelling is the combination of multiple perturbations, including optogenetic disruption of Arm or α-catenin, Axin overexpression, and Arm mutants, which produce consistent dorsal closure defects.

Some conclusions are generally supported by the presented data. The work provides strong evidence that Arm plays an important role in dorsal closure. The identification of a requirement for the Dishevelled DEP domain and JNK signaling supports a non-canonical regulatory mechanism controlling dorsal closure.

Weaknesses:

(1) Conclusions are made regarding force transmission;(however, no experimental evidence is provided to support these conclusions.

(2) The conclusion was made that Wingless does not affect dorsal closure. However, this was based solely on Wingless overexpression in the amnioserosa, and the level of Wingless expression was not quantified. One possibility is that this level was not sufficient to see an effect. Alternatively, Wingless may have a role in migrating epithelium rather than the amnioserosa. Indeed, it is known that wingless mutants display a defect in dorsal closure.

(3) The effect of JNK knockdown on Arm localization maybe is indirect, and due to a secondary consequence on disruption of epithelial morphology rather than a direct effect of JNK on Arm.

(4) Some conclusions rely on overexpression-based perturbations (e.g., Axin or Arm mutants), which may not fully recapitulate endogenous physiological regulation.

(5) The Arm timer was not able to detect Wingless-dependent Arm stabilization in stripes. This finding demonstrates that the timer is not sensitive enough to thoroughly analyze Arm dynamics.

Overall, this work provides important conceptual advances in understanding junctional β-catenin/Arm function during dorsal closure. The endogenous fluorescent timer approach will likely be broadly useful to the community for studying protein stability dynamics in vivo, and the findings expand current views of β-catenin by highlighting its mechanical and junctional functions during tissue morphogenesis.

Reviewer #3 (Public review):

Despite the abundance of RNA velocity tools, there are still major limitations, and there is strong skepticism about the results these methods lead to. In this paper, the authors try to address some limitations of current RNA velocity approaches by proposing a unified framework to jointly infer transcriptional and splicing dynamics. The method is then benchmarked on 6 real datasets against the most popular RNA velocity tools.

Comments on revised version:

The Authors addressed my 2 follow-up comments suitably.

Thanks for the time you took addressing them. I have no further comments.

Reviewer #2 (Public review):

Summary:

The authors use a postnatal mouse model of E. coli bacterial meningitis and a mouse brain endothelioma cell line combined with cell type specific gene deletion to study the function of endothelial TLR4, a cell surface receptor that recognizes gram positive bacterial wall components, in the local leptomeningeal (LPM) response with a focus on endothelial barrier breakdown mediated by TLR4. Single cell transcriptional profiling and imaging studies using wholemount preps of the LPM support that LPM endothelial, CD206+ local macrophage and LPM fibroblast and arachnoid barrier cell inflammatory response and is abrogated in endothelial specific KO of TLR4, pointing to a role for endothelial TLR4 in local LPM response. Culture studies using Bend3.1 cells (a mouse brain endothelioma cell line) support a direct role for TLR4 in the bacteria-mediated inflammatory response and in internalization of Cldn5 via the endosomal-lysosomal pathway, resulting in loss of barrier integrity

Strengths:

The local LPM cell response in meningitis and the role of specific LPM cells in inflammation and CNS barrier breakdown has not been extensively studied, despite ample evidence for primary immune response in the meninges in human patients and in animal models. The authors employ a robust, multi-model approach using both in vivo and in vitro models with cell-type specific knockout to study the function of TLR4 in brain endothelial cell response. The authors nicely combine functional barrier assays with IF for junctional localization in their experimental design and they delve into potential mechanisms of Cldn5 internalization using markers of endosomal-lysomal pathway localization. The authors also describe a new type of barrier assay using a streptavidin-coated plates upon which barrier forming cell cultures can be plated, this could be a very useful alternative or complement to other size-selective barrier assays and presumably could work for other barrier forming cell types, like epithelial cells.

Comments on revised version.

In their revision, the authors addressed prior noted weaknesses with new data and analysis. They now show that TLR4-VE-cad cKO mice have a largely similar disease progression as control mice, including increased bacterial burden in the LPM and brain. This underscores that that the reduced vascular leakage and blunted inflammatory response is due to loss of TLR4 response to bacteria on VE-cad recombined cells and not because the mice are protected from meningitis. The authors also performed additional experiments to show that Cldn5 internalization via the endosomal-lysosomal pathway is independent of NFKB signaling. The authors also added in important discussion points about how their results fit into the broader literature on TLR4 in BBB endothelial cell junctional protein localization and prior work on meningitis in global TLR4.

Reviewer #2 (Public review):

Summary:

In this manuscript, dos Santos et al seek to identify cell-specific programs that drive neuronal wiring patterns. They focus on two chemosensory and mechanosensory neurons in the Drosophila nervous system, as they both display stereotyped connectivity in the ventral nerve cord. Single-neuron RNA sequencing identified cell surface molecules that distinguish the sensory neurons and may instruct their respective wiring patterns. They functionally test several of these candidates and observe miswiring phenotypes upon knockdown experiments. Additionally, they attempt to miswire the chemosensory neurons. Overall, this manuscript addresses an important question about how neurons identify appropriate synaptic partners through precise cell surface molecular codes. However, there are significant deficiencies in the experimental logic and rigor, and the manuscript can be very difficult to digest.

Strengths:

The use of two sensory neurons with stereotyped connectivity is a significant strength, as this enables the authors to identify genes that are required for wiring. Additionally, analyzing the transcriptomes of single neurons repeatedly could potentially be a robust approach to identifying cell-specific cell-surface molecules that drive wiring.

Weaknesses:

(1) The authors perform RNAseq for single identifiable neurons, as opposed to neuronal subclasses, which has been reported before. It would be beneficial to elaborate on the significance of using single neurons for answering the scientific question. This is briefly mentioned toward the end of one of the results subsections: "Repeated RNA sequencing of an identifiable neuron seeks to address the fundamental nature of variability in connectomics, axonal branching, and cellular identity." But this should be in the Introduction.

(2) The authors chose the P14 pupal stage for one of the analyses. It is not clear why this specific stage is chosen. Does pSc and aPa connectivity occur at this stage?

(3) This reviewer is confused as to why looking at differentially expressed CSMs between pupal and adult stages of two different neurons is useful. This does not seem like an appropriate comparison. This data might be better in the supplemental material, especially given the lack of precise age synchronization across pupal samples (as reported).

(4) It is very difficult to follow the logic because the manuscript seems to jump around between different results and lacks a compelling through line.

(5) "Single cell sequencing of the same neuron reveals transcriptome precision": What are the controls here? An aPa neuron is shown in Figure 3 as an example of a different neuronal subtype, but were other factors (e.g., lack of Repo expression) checked to ensure that samples were not contaminated?

(6) "However, whether any of these exon 6 or 9 splicing specificities are biologically significant can only be determined using exon 6 and 9 isoform-specific RNAi." The authors could alternatively use CRISPR techniques to target specific isoforms that they hypothesize might be important for neural wiring, enabling them to assess isoform-specific wiring defects.

(7) In the section "The set of cell surface receptors required to wire up the pSc mechanosensory neuron": Several previous subsections of the Results use RNAseq to identify molecules expressed in pSc neurons across different stages. It's unclear why the authors did not start with the identified list of candidate cell surface receptors identified in their RNAseq experiments.

a. Were any of the genes screened the same as those identified by the authors as differentially expressed in pSc mechanosensory neurons, either across developmental stage (pupa vs. adult) or across neuronal subtype (pSc vs. Gr59d)? If so, it would be helpful to state this here. (They do mention later on that five CSMs identified were more highly expressed in pSc than aPa. However, changes in expression across developmental stages within the pSc neuron would still be helpful to comment on, especially since the authors identified greater transcriptomic differences across developmental stages than they did between different neuronal subtypes.)

b. The 39 genes not expressed in pSc neurons served as their negative control, but the average axonal targeting grade was 2.3 (between moderate and severe). This calls into question the use of this method as an appropriate measure of whether a gene expressed by pSc neurons is truly required for proper axon targeting; there seems to be a strong probability of significant off-target effects. Performing a global knockdown and cell-specific rescue could potentially complement these experiments and serve as a stronger indicator of candidate receptors' roles in pSc-specific axon targeting.

(8) It seems as though the purpose of the experiments described in the last results subsection ("Re-wiring the Gr59 chemosensory neuron") is to redirect the Gr59d neuron toward the pSc neuron's axonal targeting phenotype. However, the authors do not state whether they were able to do so effectively (i.e., whether or not there were significant differences between the rewired Gr59d neuron and the pSc neuron). This leaves the story unfinished.

(9) At the end of the discussion, the authors state that "...if a Gr59d chemosensory neuron is functionally rewired to a pSc mechanosensory circuit, activation of the Gr59d neuron using a bitter tastant molecule should elicit a grooming (mechanosensory) response...". The authors should attempt this experiment, especially given that they have developed the PXGS technique.

Reviewer #2 (Public review):

The manuscript reports protection of midlobular hepatocytes from APAP toxicity by activation of Atf4-CHOP (Ddit3)-mediated cell cycle arrest and stress response. The authors acknowledge that their finding is unexpected because CHOP typically induces cell death. Therefore, they functionally validate several aspects of the proposed Atf4-CHOP mechanism. Along these lines, the mitigation of APAP toxicity by AAV expression of Atf4 or Btg2, the latter identified as CHOP effector, is impressive. Whether Atf4 indeed acts through CHOP and whether midlobular hepatocytes are protected because of cell cycle arrest is less clear. These and other criticisms are described in the following.

Major points:

(1) Starting with the basics, one wonders why midlobular hepatocytes manage to mount a defensive response to APAP, but PC hepatocytes don't. Is this because midlobular hepatocytes express the relevant Cyps (2e1 but also 1a2 and 3a11) at lower levels, which mitigates toxicity and buys them time? This would be supported by F2A but not by F3B, at least not for the most important Cyp2e1. A moderate difference is shown for Cyp1a2 expression in F3D but is that enough to explain the different fates? Or are additional post-transcriptional effects on these Cyps at work? The difference in baseline Cyp2e1 expression between F2A and F3B remains unexplained after revision.

(2) The evidence presented in support of cell cycle arrest of midlobular hepatocytes is not fully convincing: there is no overt difference in S and G2/M gene scores in F2F; the marker genes used for S phase and G1 to S progression in F2G are unusual. Along these lines, one wonders if spatial transcriptomics confirmed the Ki67 immunostaining results in F1 also for specific zones, not only overall as shown in F2E? In contrast to the revised discussion, the abstract does not reflect that limited evidence for a cell cycle arrest in pericentral hepatocytes was found.

(3) The authors conclude in line 364 that halting of proliferation by Btg2 favors survival, which raises the question of whether Btg2 knockout causes death in midlobular hepatocytes in F6K. Data addressing this question, that is, localization and extent of tissue necrosis and ALT levels after APAP, are missing. The efficiency of knockout of Btg2 is also not given. Additional Btg2 knockout data support its proposed role in the revised manuscript.

(4) Related to the previous question, the BTG2 immunostaining in F6F is not convincing when compared to F6D. One also wonders if it is necessary to apply APAP to find induction of BTG2 by AAV-Ddit3? The BTG2 immunostaining remains weak, not only in in F6F but now also in F6D of the revised manuscript, which together with lack of high-resolution immunostaining of AAV-Ddit3-induced BTG2 in the absence of APAP results in limited support for the conclusion that APAP promotes nuclear localization of BTG2.

(5) Related to the previous question, the proposed Atf4-Ddit3 axis is challenged by the lack of midlobular induction of Atf4 in the APAP scRNA-seq data published by another group presented in S4F and G. Further analysis of AAV-Atf4 samples generated for F5 could address if it is really Atf4 that acts on Ddit3 in APAP toxicity. The extended list of transcription factors (from 30 to 50) includes Atf4 but direct evidence for an interaction with Ddit3 is missing from the revised manuscript.

(6) Related to the previous question, the ATF4 immunostaining in F5A doesn't look convincing, with many brown pigments appearing to be outside of the nucleus. The ATF4 immunostaining after APAP challenge remains weak.

(7) It is not ruled out that AAV expression of Atf4 or Btg2 reduces hepatocyte sensitivity to APAP by affecting expression of the Cyps needed for activation. In other words, does AAV-Atf4 or AAV-Btg2 change the expression of any of the Cyps relevant to APAP in the 3 weeks before APAP application (F5B)? S5A of the revised manuscript rules out loss of Cyp2e1 expression as a confounding factor.

(8) It is laudable that the authors tried to extend their findings to human by using snRNA-seq data from a published study (line 391) but it is unclear why they didn't analyze all 10 patients in that study but instead focused on 2 and stated that this small sample number prevented drawing definitive conclusions and could therefore only be mentioned in the discussion. The revised manuscript continues to focus on rare spatial transcriptomics analyses of patients with APAP toxicity although more snRNA-seq analyses of such patients are available which should also allow for analysis of hepatocyte zonation.

Comments on revised version.

After revision, the proposed role of Btg2 is substantiated but it remains unclear why midlobular hepatocytes don't proliferate after APAP challenge and whether the observed protective effects are indeed mediated by Atf4 acting directly through CHOP.

Reviewer #2 (Public review):

Summary:

In this manuscript, Hossaim and colleagues investigate the role of the ITK kinase in modulating inflammation in a pristane-induced lung hemorrhage model. Using a germline ITK KO mouse, they report that loss of ITK skews the T cell compartment toward a memory-like state, expanding Tregs, and conferring protection against alveolar hemorrhage, inflammatory monocyte recruitment, proteinuria, and systemic cytokine elevation. They further show that transfer of ITK-deficient Tregs into wild-type hosts with established disease attenuates injury and shifts the cytokine balance toward resolution, and that ITK-deficient Tregs carry a transcriptional signature enriched for OXPHOS, mTORC1, MYC, and cell-cycle programs. While these observations are interesting for the development of potential immunotherapies, there are several issues with the methodological approach that support the authors' claims, tempering my enthusiasm for this manuscript.

Strengths:

(1) The clinical motivation and potential targeted therapies are relevant.

(2) The murine phenotype seems robust.

Weaknesses:

(1) All loss-of-function experiments are from a global ITK knockout. This is a major limitation and weakness of this study. The protection observed in the intact knockout, therefore, cannot be attributed to Tregs specifically. The Treg-intrinsic claim rests almost entirely on a single adoptive-transfer experiment. In order to show that this effect is Treg-specific, the authors would need to generate a Treg-specific ITK-deficient mouse

(2) In their sufficiency experiment (adoptive Treg cell transfer), donor and/or host cells are not congenically marked, so persistence, lung trafficking, and in vivo expansion of transferred Tregs are not demonstrated.

(3) The authors claim that ITK-deficient Tregs possess enhanced metabolic fitness. This conclusion is based on transcriptional profiling of isolated splenic Tregs from unchallenged mice, yet it concerns lung protection during active disease. A disease-state and ideally lung-relevant transcriptome would more directly support the mechanistic narrative. Additional functional validation would be needed (Seahorse assay, mitochondrial mass/potential, etc). Some of these GSEA programs enriched in ITK-deficient Tregs could reflect a more general proliferative signature.

Reviewer #2 (Public review):

Summary:

This is an interesting paper from Alonso-Caraballo and colleagues that examines the influence of opioid use, acute and prolonged abstinence, and sex on cue-induced relapse and paraventricular thalamus (PVT) to nucleus accumbens shell (NAcSh) medium spiny neurons circuit physiology. The study presents a valuable finding that following prolonged, but not acute abstinence from oxycodone self-administration, female rodents exhibit higher relapse rates to drug paired cues. Additionally, the study presents the useful finding that prolonged abstinence increased PVT-NAcSh MSN synaptic strength in both sexes, an effect that is likely due to presynaptic adaptations. While the evidence to support these two findings is solid, further experiments are required to determine the functional role of the PVT-NAcSh MSN circuit in relapse following prolonged oxycodone abstinence, and the mechanism underlying the heightened relapse vulnerability in females in this model of opioid use disorder.

Strengths:

The paper is interesting, well written and presented, and the experiments are well designed and conducted. The revised analysis of spike count data that models the hierarchical structure of the data is appropriate to overcome low animal numbers and the potential for oversampling. The authors are transparent in reporting the results related to this analysis in figure 5 and acknowledge the study is underpowered to confirm the trend of increased intrinsic excitability in male MSNs following prolonged oxycodone analysis.

Impact:

The topic is of interest to the field of substance use disorders and gives solid evidence for the need to consider targeted therapeutics aimed at relapse prevention in opioid use disorder.

Reviewer #2 (Public review):

Tittelmeier et al. investigated the role of sphingolipid (SL) metabolism in the maintenance of endolysosomal vesicle integrity. They find that both impaired SL biosynthesis and degradation in C. elegans decreases the fluidity of endolysosomal membranes and promotes their rupture, while it has little effect on plasma membrane fluidity. Endolysosomal membrane fluidity is also negatively affected in human cells upon knockdown (KD) of a gene (SPHK2) involved in the SL degradation pathway. Aggregated forms of tau in both models (C. elegans and human cells) can also cause rigidification of the endolysosomal membrane, with SL homeostasis disruption having an additive effect, exacerbating endolysosomal rupture. Notably, KD of SPHK2 also increased the formation of tau foci, suggesting that compromised endolysosomal integrity may promote tau aggregation. These data provide a clearer understanding of how genetic manipulation of SL metabolism affects endolysosomal membranes and their rigidification in the context of tau aggregation. Supplementation of polyunsaturated fatty acids (PUFAs), which has a beneficial effect on Alzheimer's patients, improved membrane fluidity and reduced tau propagation in human cells and tau-associated neurotoxicity in C. elegans, suggesting a possible mechanism of action.

Comments on revised version:

The authors have:<br /> Corrected editorial errors (Points 1 and 2).

Clarified the experimental rationale, added new data to rule out alternative explanation, and improved the presentation of the C. elegans model (Point 3).

Provided experimental evidence and appropriate discussion regarding the specificity and broader physiological context of SL gene knockdown effects (Point 4).

Overall, the authors' responses are thorough, supported by new data where appropriate, and demonstrate a clear understanding of the concerns raised. All points raised have been satisfactorily resolved.

Reviewer #3 (Public review):

Summary:

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

Strengths:

Significant therapeutics implications

Weaknesses:

Limited molecular mechanisms

Comments on revised version:

The authors have addressed my comments

Reviewer #3 (Public review):

In this study, Liu and colleagues utilize TRAP-seq to profile the repertoire of actively translated mRNAs in different intestinal cell types (anterior INT1 vs. posterior INT2-9 cells) in C. elegans. A key goal of this study was to identify transcripts differentially expressed/translated between these intestinal cell subtypes in the context of animals being well fed or subjected to acute (30 minutes) or chronic (3 hours) starvation, followed by refeeding.

The authors identify a number of differentially expressed genes across all of the conditions tested. They then provide an initial survey of the landscape of translatome changes through Weighted Gene Network Correlation Analysis (WGNA), and some high-level functional surveys via Gene Ontology (GO) term analysis and protein domain analysis. The authors validate the enriched expression patterns of some of their identified candidate genes using fluorescent promoter fusion reporters, confirming INT1-specific expression. The authors further implicate the role of several other candidate genes in pathogen avoidance and in response to nutritional cues by knocking them down specifically in INT1 cells by RNAi. Finally, the authors identify pyruvate as a major nutrient signal coming from the bacterial diet that suppresses the release of a key insulin peptide (INS-7) and identify some of the genes expressed in INT1 that are required for this response.

Strengths:

(1) Good use of and justification for TRAP-seq, because scRNA-seq would be difficult under the varied conditions used (starvation, refeeding)

(2) The manuscript is generally clear to read, and the data are generally well-presented with good supporting data that includes replicates, sample sizes, error measurements, and associated statistics.

(3) The dataset will be an interesting resource to mine for future studies focusing on mechanisms of how particular intestinal cell types respond to different environmental signals.

Weaknesses:

(1) A limitation of TRAP-seq, although powerful, is that only relative comparisons can be made between genotypes/conditions to identify differentially-expressed genes, rather than assessing whether a given gene is expressed at a certain level in a cell type under a certain condition. This limitation is due to the non-specific association of sticky RNA species to the beads during the immunoprecipitation step. This is a minor point however, and the authors do a nice job of focusing their analysis on differentially expressed transcripts in the current study.

(2) Another limitation of the current study is that the experiments testing the role of candidate genes identified by their profiling experiments do not dive a bit deeper into providing a mechanistic understanding of the phenotypes being studied. At present, the results are thus viewed more as a genomics-based screen with some limited follow-up on interesting hits. However, this reviewer appreciates that when placed in context of the work presented, a presentation of the profiling data along with some validation is an excellent starting point for future mechanistic studies elaborating on these interesting candidates.

Appraisal of whether the authors achieved their aims, and whether the results support their conclusions.

The main goal of the study was to survey the dynamic responses at the level of actively translated mRNAs of the INT1 vs INT2-9 cells in response to metabolic challenge.

Overall, the authors use established methods to perform their genome-wide analysis, and the set of differentially regulated genes are enriched for expected molecular functions and form coherent networks in anticipated pathways.

The validation experiments (promoter::GFP fusion reporters, INT1-specific knockdowns of highly regulated genes) further corroborate the quality of the TRAP-seq datasets generated.

I have a few points for the authors that would further strengthen this work:

(1) The authors rightfully focus on the top differentially-regulated candidates, but it's unclear at present how far down their fold change list would lead to expression pattern validations. It would be useful to test a few more promoter::GFP fusion reporters at different enrichment/fold-change/statistical cutoffs.

(2) Although the INT1-specific RNAi provides a convenient strategy for rapidly perturbing and testing genes of interest for phenotypes, independently validating the knockdowns with genetic mutants, or alternatively (if genes are essential), degron alleles.

Likely impact of the work on the field, and the utility of the methods and data to the community.

The TRAP-seq data and list of differentially-expressed candidate genes will form an interesting set of high-priority candidates to study for their role in the reception and transduction of nutritional cues in response to food status and pathogens. This data will thus benefit the C. elegans community of researchers studying the mechanisms governing these phenomena.

Comments on revised version:

I think the authors have done a good job of addressing the suggestions from the previous round of review in this new version.

Reviewer #2 (Public review):

Summary:

The authors set out to enable large-scale measurement of fat in skull bone marrow using routine structural brain MRI scans. They present a neural-network pipeline trained largely on realistic simulated examples and show that the resulting skull marrow measure is highly repeatable in test-retest data and consistent in monozygotic twins. Applying it to ~33,000 UK Biobank participants, they report expected population patterns (including sex- and menopause-related differences) and identify genetic and health-related associations, creating an important resource that can be built upon by researchers interested in BMA, imaging, bone, metabolism, neuroscience, ageing, haematology, and other fields.

Major strengths:

A notable methodological strength is the training strategy: by using a large, simulated dataset that captures plausible variation in skull-layer thickness and MRI intensity, the authors reduce reliance on scarce expert-labelled images. The modelling choice (using 1D intensity profiles through the skull rather than analysing the full 3D volume) appears well matched to the anatomy and offers an efficient approach for thin, layered structures. Multiple validation steps (including test-retest reliability and twin concordance) support the robustness of the measurement pipeline.

On the biological and genetic side, the study demonstrates that the skull BMA estimate relates to known correlates of marrow fat (e.g., age/sex/menopause patterns/bone density) and integrates population imaging with large-scale genetic analysis to highlight loci and candidate genes with plausible relevance to skeletal and marrow biology. The inclusion of cross-ancestry analyses and integration with cell-type-resolved gene-expression resources further improves interpretability and usability for the community.

Major limitations:

The main limitation is conceptual rather than technical: the phenotype is derived from T1-weighted MRI intensity, which does not directly separate fat and water signals and can vary with scanner and sequence settings. The manuscript provides convincing evidence that the measure is reproducible and biologically meaningful, but it should still be interpreted as a semi-quantitative proxy for marrow fat rather than a direct fat-fraction measurement. Accordingly, the genetic and phenotypic associations are likely informative, but the most direct claims about "adiposity" would be stronger if anchored to established quantitative fat-measurement imaging or spectroscopy in the skull.

The genetic "replication" analysis in a smaller, ancestrally heterogeneous non-European-ancestry sample is useful as a test of transferability, but it is not equivalent to replication in an independent cohort of similar ancestry and is expected to show reduced SNP-level reproducibility because of differences in sample size and genetic background. This should be clearly framed so readers understand what level of generalisation is supported by the current evidence.

Likely impact and utility:

Overall, the work provides a practical method for extracting new biological information from widely available brain MRI scans and should be particularly useful to researchers working with large imaging biobanks and those studying connections between bone, blood, metabolism, and brain ageing. The combination of a scalable measurement approach and openly reported genetic results is likely to accelerate follow-up studies, including cross-cohort comparisons and mechanistic work on candidate pathways.

Reviewer #2 (Public review):

Summary:

This study by Suzuki et al. reports an interesting stereo-selective role of D-serine in regulating one-carbon metabolism during neurodevelopment to adapt the functional transition, probably through the competition with mitochondrial transport of L-serine. The authors provide a multi-layered set of evidence, including metabolomics, enzyme assays, mitochondrial transport competition and functional assays in immature/neural progenitor cells, to build up a conceptual integration of D-serine as both a neurotransmitter and a metabolic regulator in central neural system, which raises a broad potential interest to the neuroscience and metabolism communities.

Strengths:

This work provides a conceptual advance that D-serine is not only serves as a traditional neurotransmitter in central neural system but also critically contributes to metabolic regulation of neural cells. The authors performed solid metabolomic assays to validate the suppressive effect of D-serine on one-carbon metabolic pathway, providing some evidence that D-serine competitively inhibits mitochondrial serine transport, but not directly impairs SHMT2 enzymatic activity. All these data indicate a critical role of D-serine synthesis during neural maturation and suggest a potential translational strategy for targeting serine metabolism in neural tumors.

Comments on revised version.

My previous concerns have been appropriately addressed or discussed in this revised version of manuscript. I have to say that, at this stage, I have no further questions.

Reviewer #2 (Public review):

Summary:

This manuscript investigates the impact of plasticity mechanisms in an excitation-inhibition (EI) network model on the emergence of synchronization patterns that the authors associate with different sleep phases. The model consists of an EI Kuramoto network in which recurrent excitatory couplings evolve according to Hebbian and homeostatic adaptation rules. Through numerical simulations, the authors analyze how these plasticity mechanisms modify both the collective dynamics and the structure of the coupling matrix.

Strengths:

The topic addressed in the manuscript is timely and potentially relevant, as understanding the interplay between synaptic adaptation and collective neural dynamics remains an important challenge in theoretical neuroscience.

Weaknesses:

In its current form, the work suffers from substantial conceptual, methodological, and technical limitations that significantly weaken the conclusions.

From a biological perspective, the model is highly abstract and qualitative. The connection between the model variables and the physiological processes that the authors aim to describe remains unclear. Consequently, the manuscript does not provide sufficient evidence to support biologically meaningful conclusions regarding sleep dynamics. In my opinion, the work is more naturally positioned within the framework of theoretical or computational dynamical systems than within the scope of a biology-oriented journal.

From a mathematical and dynamical-systems perspective, the analysis is incomplete, and several important technical aspects are either missing or inadequately addressed. In particular, the characterization of the dynamical regimes is often imprecise, the numerical evidence is not sufficiently robust, and little effort is made to interpret the results within the broader context of synchronization theory, adaptive networks, or collective dynamics.

More specifically:

(1) The biological interpretation of the model variables is ambiguous throughout the manuscript. At several points, the authors suggest that individual oscillators should not be interpreted as neurons but rather as abstract biological units (lines 78-82, 86-89, 418-420). However, other parts of the manuscript refer to the coupling matrix entries, particularly $J_{ee}$, as synaptic weights (e.g., line 118). These two interpretations are not obviously compatible. If the oscillators represent coarse-grained or abstract units, the biological meaning of the adaptive couplings should be carefully justified. More generally, the manuscript lacks a clear discussion of what aspects of neural circuits are captured by the model and which aspects are intentionally neglected.

(2) More fundamentally, the manuscript inherits the well-known limitations associated with interpreting Kuramoto oscillators as neural elements. Kuramoto phase oscillators provide a minimal description of synchronization phenomena, but they do not explicitly represent membrane dynamics, firing rates, spiking activity, synaptic currents, or realistic neuronal timescales.

Under certain assumptions, Kuramoto-like models can be rigorously derived from more detailed neuronal models through phase-reduction techniques (see, for instance, Chapter 10 of Izhikevich's \textit{Dynamical Systems in Neuroscience}). However, the authors do not employ such a reduction procedure, nor do they establish a formal connection between their model variables and the dynamics of neuronal populations. As a consequence, the biological interpretation of the model remains unclear.

The authors should therefore explicitly discuss these limitations and carefully justify why the synchronization patterns observed in such a highly reduced model can be related to neural sleep states. At present, the biological interpretation appears considerably stronger than what the model itself can support, for instance, the claims in lines 321-322 or 330-337. In particular, it remains unclear whether the reported dynamical regimes should be interpreted as genuine mechanisms underlying sleep rhythms or merely as generic synchronization phenomena arising in adaptive oscillator networks.

(3) The numerical methodology raises serious concerns regarding the robustness of the reported results. According to the Methods section, simulations are performed using only $N=100$ oscillators and integration times of approximately 50 time units. Such choices may be sufficient for illustrative purposes but are generally inadequate for drawing conclusions about asymptotic collective behavior in adaptive dynamical systems. Finite-size fluctuations can strongly affect synchronization measures, and adaptive networks are well known to exhibit extremely long transients, metastability, and slow convergence processes. No systematic finite-size analysis is provided, nor is there any demonstration that the reported states persist for larger system sizes or longer integration times.

(4) The use of the term "bistable regime" to describe the dynamics shown in Figure 1C is incorrect. A bistable regime refers to a parameter region in which multiple attractors coexist and the asymptotic state depends on the initial condition. The figure instead presents a single trajectory displaying oscillatory dynamics. No evidence is provided for the coexistence of attractors, nor are multiple initial conditions explored. Furthermore, the displayed time series are too short to determine whether the observed dynamics correspond to a stable limit cycle, quasiperiodic motion, intermittent behavior, or a long transient approaching another attractor. The authors should perform a proper dynamical characterization of this regime. Similar collective oscillatory states have been extensively studied in synchronization and adaptive-network models and should be discussed in relation to the existing literature.

In particular, several time series shown in the manuscript (e.g., Figures 1C and 2F) exhibit trends that suggest the possibility of unresolved transient dynamics. The authors should demonstrate convergence of the reported regimes by substantially extending simulation times and by performing finite-size analyses. Simulations with at least one order of magnitude more units ($N\gtrsim 1000$) and integration times sufficient to establish asymptotic behavior would be expected in a study whose main claims rely on collective dynamical phenomena.

(5) The manuscript lacks several standard tools routinely employed in the analysis of nonlinear dynamical systems. The conclusions are largely based on visual inspection of time series and order parameters. However, no bifurcation analysis, stability analysis, phase-space characterization, attractor reconstruction, or systematic exploration of parameter dependence is provided. As a consequence, many of the identified "phases" or "regimes" remain only qualitatively described. A more rigorous dynamical-systems treatment would substantially strengthen the work and would help distinguish genuine asymptotic states from finite-size or transient phenomena.

(6) A substantial fraction of the results appears to extend the authors' previous work by incorporating plastic adaptation mechanisms. While incremental advances are acceptable, the manuscript would benefit from a broader theoretical context. The discussion is heavily centered on previous studies by the same authors, whereas there exists an extensive literature on synchronization, adaptive networks, neural mass models, balanced EI systems, and sleep-related oscillations that is largely absent from the discussion. The novelty and significance of the present contribution would be easier to assess if the results were more carefully compared with alternative theoretical approaches.

Reviewer #2 (Public review):

Summary:

This preprint describes a practical and useful approach for labeling and tracking NPCs in situ, using a fluorescently conjugated nanobody that binds directly to the core scaffold nucleoporin Nup84 with nanomolar affinity. Useful applications including timelapse imaging, affinity purification, and proximity labeling are envisioned.

Strengths:

Clever use of a fluorescently conjugated nanobody that binds directly to the core scaffold nucleoporin Nup84 with nanomolar affinity.

Reviewer #2 (Public review):

Summary:

In the manuscript titled "Multiple Molecular Pathways to Longevity: Opposing Gene Expression Programs Define Distinct Aging Strategies", the authors investigated diverse genetic pathways that contribute to lifespan extension in Caenorhabditis elegans and aimed to identify shared and distinct molecular mechanisms among various longevity mutants. Through comprehensive RNA sequencing of different longevity mutants representing seven distinct pathways, the authors showed that these mutants cluster into three primary groups based on their gene expression profiles. This transcriptomic analysis revealed that while some longevity genes are commonly regulated across multiple pathways, others exhibit opposing expression patterns, suggesting that distinct molecular strategies can lead to increased lifespan. Specifically, they identified a set of 196 genes that are consistently upregulated in most longevity mutants, many of which are involved in innate immunity and stress defense. By performing RNAi-based screening, the authors further validated the functional roles of several candidates, including C08F11.7, ugt-62, and K05C4.9, supporting their contributions to longevity and stress resistance. The authors conclude that longevity is mediated through multiple molecular pathways and provide a public online tool to study these complex transcriptomic landscapes.

Significance:

This study provides a systematic, side-by-side transcriptomic comparison of nine genetically distinct long-lived C. elegans mutants, revealing that lifespan extension arises from both shared and opposing gene expression programs. By identifying three distinct longevity groups and demonstrating that key pathways can be modulated in opposite directions to achieve long life, the work challenges the notion of a single universal transcriptional signature of aging. Importantly, functional validation shows that select commonly regulated genes can directly modulate lifespan and stress resistance, highlighting actionable molecular targets for promoting healthy aging.

Comments on revised version:

The authors addressed my concerns successfully.

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

Comments on revised version.

Thank you for submitting the revised manuscript. I believe the revisions have substantially improved the quality and clarity of the study, and the authors have addressed the major concerns raised during the initial review.

Reviewer #3 (Public review):

In this manuscript, the authors investigate the role of attention in foveal processing during a naturalistic task. They record neural activity from extrastriate visual areas V4 and inferotemporal cortex, as well as from the lateral prefrontal cortex, in macaques performing a free-gaze visual search task. In this task, animals searched for a face or house target among multiple complex stimuli, with no constraints on eye movements. Unlike classic studies of visual attention, which often rely on controlled fixation, this work examines neural activity in both foveal and peripheral receptive fields during naturalistic eye movements.

The main question addressed by the authors is how feature-based attention is distributed and coordinated across foveal and peripheral visual fields during active search, and how this attentional processing influences saccade behavior. The authors show that foveal units in visual areas exhibit feature-based attentional enhancement, with stronger responses when a fixated stimulus is a target compared to when the same stimulus serves as a distractor. Peripheral units in visual and prefrontal areas show both feature-based and spatial attentional modulation, consistent with prior work. Finally, the authors show that attentional modulation depends primarily on stimulus category rather than response magnitude, with neurons showing similar enhancement for all images within the target category regardless of how strongly individual images drive the cell.

There are several notable strengths of this paper including:

(1) Disentangling feature-based and spatial attention during naturalistic vision remains a central challenge. This paper tackles both simultaneously, parsing neural populations by object selectivity (face-selective, house-selective, non-selective) and RF position (foveal vs. peripheral).

(2) The unconstrained search task (Fig. 1A) moves beyond the dominant fixed-gaze, cued-attention designs (Zhou & Desimone, 2011) to study attention as it operates during natural behavior, with sequential fixations and voluntary saccades.

(3) The scale of the multi-area recordings is a major strength and is well aligned with current trends in primate and human neuroscience toward large-scale, multi-area recordings. Simultaneous recordings from visual and prefrontal areas, comprising over 4,900 foveal units and more than 1,500 peripheral units, enable meaningful cross-area latency comparisons and area-specific analyses of attentional modulation. This study builds on the authors' previous analyses of this dataset by expanding the scope to show that feature-based attention generalizes across neuronal classes and operates on categorical identity rather than response magnitude.

(4) The combination of simultaneous multi-area recordings and a rich behavioral paradigm provide a dataset that is well suited for population decoding, cross-area interaction analyses, and trial-by-trial prediction of saccade choices, which could substantially deepen mechanistic understanding beyond the largely univariate comparisons presented here.

While the data broadly support the paper's main conclusions, several issues limit the strength of the mechanistic interpretation and should be taken into consideration:

(1) Receptive field size is not explicitly quantified and may confound foveal-peripheral comparisons. Units are classified as foveal or peripheral based on responsiveness to the cue versus the search array (Methods, p. 17), but the manuscript lacks essential information about receptive field sizes, eccentricities, and the number of search stimuli falling within each receptive field and related proper controls. This is critical because receptive fields in visual area V4 at foveal eccentricities are relatively small (Gattass et al., 1988; Desimone & Schein, 1987), whereas receptive fields in inferotemporal cortex can span several degrees to tens of degrees and often include the fovea (Op de Beeck & Vogels, 2000; DiCarlo & Maunsell, 2003; Zoccolan et al., 2007). Given the 2{degree sign} × 2{degree sign} stimulus size, multiple search items could potentially fall simultaneously within peripheral receptive fields. This introduces a potential confound, as attentional modulation is known to be strongest when multiple stimuli appear within a single receptive field (Reynolds et al., 1999). Although the authors acknowledge this issue for visual area V4 (p. 17), it is neither quantified nor controlled for. Without explicit receptive field mapping relative to the search array, comparisons between foveal and peripheral units, as well as between visual areas, are difficult to interpret cleanly.

(2) Attentional modulation is difficult to dissociate from saccade planning and decision-related signals. The free-gaze paradigm enhances ecological validity but introduces a temporal confound: mean distractor fixation durations are approximately 156 ms (p. 9), while attentional effects emerge between 137 and 170 ms after fixation onset (Fig. 2). As a result, the reported attentional modulation coincides with preparation of the subsequent saccade. Neural activity measured in the primary analysis window (150-225 ms; p. 19) therefore likely reflects a mixture of visual, attentional, motor planning, target recognition, and behavioral relevance signals, all of which are known to modulate responses in visual areas at similar latencies (e.g., Chelazzi et al., 1998). Moreover, target fixations (~257 ms) and distractor fixations (~156 ms) occur on fundamentally different behavioral timescales, which may inflate apparent foveal attentional effects. While the authors suggest that these timing differences support the idea that foveal feature-based attention facilitates prolonged fixation on target stimuli, this interpretation is not fully supported by the current analyses. That said, the saccade-aligned analyses of peripheral units (Fig. S3) partially mitigate this concern by demonstrating that feature-based modulation persists through saccade execution.

(3) The "attention-out" condition for spatial attention lacks directional control. In the spatial attention analyses (Fig. 4D-F), the "attention-out" condition appears to include all fixations followed by saccades directed away from the receptive field, regardless of saccade direction. This differs from classic spatial attention designs, which typically use controlled anti-saccades or saccades to fixed locations opposite the receptive field (e.g., Moore & Armstrong, 2003; Gregoriou et al., 2009). Saccades directed toward locations adjacent to, but outside, the receptive field may still partially engage spatial attention mechanisms near the receptive field via broad attentional fields or motor preparation gradients (Bisley & Goldberg, 2010). In addition, the "attention-out" condition likely contains a heterogeneous mixture of trials in which the stimulus in the receptive field is either a target or a distractor, since feature-based attention effects are derived from this same pool of trials. As a result, spatial and feature attention effects are not fully orthogonal, and variance related to feature attention may already be embedded in the spatial attention baseline.

[Editors' note: the authors have provided responses to each of these points.]

Reviewer #3 (Public review):

Summary:

In this study, Freier et al., demonstrate that 3 distinct metabolic pathways are critical for the synthesis of 1C-THF, a metabolite that is crucial for the growth and virulence of Listeria monocytogenes. Using an elegant suppressor screen, they also demonstrate the hierarchical importance of these metabolic pathways with respect to the biosynthesis of 1C-THF.

Strengths:

This study uses elegant bacterial genetics to confirm that 3 distinct metabolic pathways are critical for 1C-THF synthesis in L. monocytogenes and lack of either one of these pathways compromises bacterial growth and virulence. The study uses a combination of in vitro growth assays, macrophage-CFU assays and murine infection models to demonstrate this.

Comments on revisions:

The revised manuscript is improved, and the additional genetic experiments provide further support for the proposed metabolic model. However, the central conclusion is not fully established without direct measurement of 1C-THF levels. While I appreciate the authors' explanation regarding the technical limitations, quantitative metabolite measurements (e.g., by mass spectrometry) would have provided much stronger evidence linking the genetic perturbations to altered 1C-THF pools.

Reviewer #2 (Public review):

Summary:

The authors attempt to address the issue of high rates of translation failure from animal studies to humans in the literature, where promising results in animal studies fail when conducting human clinical trials. Using parameters from a previous meta-analysis on prenatal amino acid supplementation and the effects it has on maternal blood pressure, the authors assessed the performance of the metrics used and whether they can quantify translation success. Performing a simulation study, the authors compared nine translation success metrics and found that no one method was uniformly optimal. The authors list several limitations of the study, such as comparability of effect sizes between animal and human studies, different goals of animal studies versus human studies, and the focus of the study on one aspect (statistics of translation) is part of a broader, more complex decision-making process before proceeding to human trials. The authors recommend using multiple metrics in combination while taking into consideration their strengths and weaknesses to assess the translation of animal studies to human outcomes. The paper achieves the aim of providing a model with several metrics to evaluate translation success from animal studies to humans.

Strengths:

(1) Utilizing 9 different translation success metrics in combination provides strong flexibility in evaluating whether results in animal studies can translate to humans. This would allow researchers to evaluate translation success using multiple different metrics according to the context of the study.

(2) The authors accommodated for the limited sample size in animal studies, which are typically underpowered, and also caution that special attention should be given to heterogeneity when interpreting translation results.

(3) Overall, this approach has the potential to be applied to other biomedical studies, provided the limitations for each of the metrics are considered. It would provide a useful tool in assessing translation from animals to humans, in addition to other factors such as safety, pharmacokinetics, etc.

Weaknesses:

While the study has several strengths, there are some limitations.

(1) Preclinical animal study sizes tend to be much smaller than human studies, which results in underpowered results. The authors adjusted for this by pooling animal study data. However, high heterogeneity in the animal studies can affect translation results.

(2) The study focuses only on evaluating the statistical component of translation, which is only one aspect of the decision-making process to move on to human trials. The study does not take into account safety and toxicological profiles, pharmacokinetics, or genetics, which are important considerations that influence the overall effect in humans.

Reviewer #2 (Public review):

The authors address a long-standing controversy regarding the functional role of neural oscillations in cortical computations and layer-specific signalling. Several studies have implicated gamma oscillations in bottom-up processing, while lower-frequency oscillations have been associated with top-down signalling. Therefore, the question the authors investigate is both timely and theoretically relevant, contributing to our understanding of feedforward and feedback communication in the brain. This paper presents a novel and complicated data acquisition technique, the application of simultaneous EEG and fMRI, to benefit from both temporal and spatial resolution. A sophisticated data analysis method was executed in order to understand the underlying neural activity during a visual oddball task. The authors defined both feature-specific and feature-unspecific contrasts, further subdivided by EEG power regressors, to examine how orientation information is signalled across cortical layers. Feature specific contrast was established via comparing trials where stimulus orientation (respectively) was left with those where the stimulus orientation was right. Further specifying it depending on EEG power regressors as congruent where stimulus orientation of EEG regressor matches voxel preference or incongruent (stimulus orientation of EEG regressor does not match voxel preference).

Figures are well-designed and appropriately represent the results, which seem to support the overall conclusions. However, some of the claims (particularly those regarding the contribution of gamma oscillations) feel somewhat overstated, as the results offer indeed some significant evidence. On the other hand, the lower-frequency findings are compelling, the functional specificity observed within the alpha frequency band is a particularly interesting result and further highlights the importance of distinguishing feature specificity in order to reveal more nuanced characteristics of neuroimaging data.

Overall, main findings are very interesting, and mainly in line with our current understanding of feedback and feedforward signalling. The paper is well-written, addresses a relevant and timely research question, introduces a novel and elegant analysis approach, and presents interesting findings.

The evidence for gamma involvement in the observed effects is selective: no significant gamma-related clusters were found for the feature-unspecific BOLD signal (Figure 5C,F), with significant effects emerging only in positively responding voxels and only for the contrast between congruent and incongruent conditions in the feature-specific BOLD response. The authors address this in the Discussion, noting that the stimulus may have elicited a weaker gamma response overall, and the contrast of EEG congruent vs. incongruent is necessary in order to achieve the largest contrast-to-noise ratio.

Authors reported negative relationship between the alpha frequency band and the feature specific BOLD signal increases (for congruent condition, Figure 5A,D). Furthermore, testing for the functional specificity between lower vs. upper alpha (Figure 5B,E), the authors included statistical test on the mixed effects model coefficients, and found significant interaction between alpha frequencies in the congruent condition. This interaction was mainly driven by the upper alpha band (which was later confirmed with simple effects analysis) and revealed stronger negative relationship of upper alpha and the BOLD signal for the subtraction of congruent over incongruent conditions. These are exciting results, which further advocate for a more active role of upper alpha band involvement (relative to lower alpha band) in processing visual features.

Expanding on this, the authors have also conducted an exploratory analysis of the relationship between the behavioural findings and underlying neural activity for non-oddball trials (Figure S12 in Supplementary Figures). This confirmed a positive relationship between task performance and alpha frequency, suggesting that high behavioural accuracy is reflected by a stronger modulation of high-frequency alpha power.

This study provides a valuable and exciting contribution to the literature on oscillatory dynamics and laminar fMRI.

Comments on revised version.

Thank you for the thorough revision and for addressing the comments so carefully. The new figures are super beautiful and make the results considerably easier to interpret, they are a real improvement to the paper.

Reviewer #2 (Public review):

Summary:

This manuscript describes a combination of species distribution mapping experimental data from common garden and physiological experiments to project the future distribution of genetic subgroups with the widespread grass Phragmites australis. Overall, the sample sizes seem appropriate for the questions being asked, and the key results regarding projected change in distribution of the focal lineages are well supported. However, at this point, it is difficult to evaluate the broader impact of the work on the field or the utility of the data for the broader community outside of those studying the focal species, P. austrina.

Strengths:

A key strength of the paper is the use of common garden and physiological experiments in conjunction with species distribution modeling. The experiments provide a mechanistic basis for the correlations between interspecific lineage and climatic data, suggesting that the distributional patterns are more likely to result from genetic differences rather than limited dispersal among regions. I would, in fact, emphasize the experimental validation of modeling efforts even more in the introduction.

Weaknesses:

I see two weaknesses with the framing of the ms and the presentation of the results. First, no data support the claims that polyploidy has any causal effect. The ploidy levels are, in fact, completely confounded with other genetic differences, so it is not possible to eliminate genetic variation, independent of ploidy, as the causative factor. As the authors note, ploidy was not manipulated in the reported experiments. Thus, the focus on polyploidy in the introduction and elsewhere distracts from the novel and informative experiments that were conducted. Second, the manuscript indicates that intraspecific variation is critical for the evolutionary potential of a species to respond to environmental change, but intraspecific variation is seldom considered in species distribution models. To me, an assessment of evolutionary potential requires estimates of heritable genetic variation and responses to selection. The sample sizes presented here are modest to estimate heritabilities, but the manuscript could be framed with this perspective in mind. However, instead, the manuscript performs species distribution modeling on a small number of sub-specific lineages, essentially treating them as homogeneous "species" - thus the analysis commits the same oversimplification that the manuscript highlights, but does so at a finer evolutionary scale than species. Not acknowledging this simplification (or better, examining phenotypic variation within the genetically defined lineages) hinders what would otherwise be a strength of the manuscript.

The title suggests that asymmetric introgression and thermal tolerance are the most important findings of the work. However, the introduction contains no explanation of the potential importance of gene flow (other than to say that asymmetric gene flow was suggested by some preliminary analyses), and the discussion offers only a limited explanation of either the potential mechanisms underlying the asymmetric gene flow or its importance for the long-term evolution of the species. Similarly, the novelty of combining experiments and species distribution modeling is scarcely mentioned, and there is no exploration of the connection between tolerance alleles and gene flow. Could introgression of heat tolerance alleles alter the spread of the hybridizing lineages, for example? A greater emphasis on these general population genetic parameters could potentially highlight the broader impact of this work.

Reviewer #2 (Public review):

Summary:

In this work, Lohse and colleagues develop a system for doing targeted photostimulation in mouse cortex. The system uses a camera image to target laser stimulation to stereotactically defined locations in mouse dorsal cortex.

Strengths:

The hardware is well designed, and the software is well documented and supported. The build guide and well-documented software package should allow for simple implementation of the technology. Without a doubt, this is a valuable community resource for the circuit neuroscience field.

Weaknesses:

No weaknesses were identified by this reviewer.

Reviewer #2 (Public review):

Summary:

Pelczyk et al. investigated the binding site of the neuropeptide Y Y4 receptor with the aim of identifying novel small-molecule agonists. The authors first assessed small cyclic peptides as tool compounds and then identified interactions between peptides and receptor residues, which were confirmed by single-point mutagenesis combined with functional assays for intracellular signalling. It is interesting that a peptide receptor can be activated by the relatively small cyclic peptides used in the study. The authors identified both common and peptide-specific interactions. The identified interactions guided ultra-large library screening, which yielded 53 compounds, 3 of which were confirmed as Y4R-specific agonists in an IP-one accumulation assay.

Strengths:

The combination of techniques (docking, mutagenesis and functional assays) strongly supports the identification and evaluation of small molecules as agonists at the neuropeptide Y Y4 receptor. Functional assays highlight residues that are important for the binding of all tested peptides, as well as residues with peptide-specific importance.

The structure-activity relationship component of the study nicely highlights which components of the peptide are important for binding to the different members of the neuropeptide Y receptor family.

Weaknesses:

It would have been great to see concentration-response curves for the three identified small-molecule agonists, as this would have stengthened the case for these agonists.

Reviewer #2 (Public review):

Summary:

The study analyzes stool metagenomes from 98 SCD patients and 46 controls, with SCD and control groups matched on age, race, sex, and ethnicity. The authors report lower Shannon diversity, lower Firmicutes/Bacteroidetes ratio, loss of health-associated taxa, increased disease-associated indicators, altered butyrate/fatty-acid metabolism pathways, and enrichment of provirus/prophage fractions in SCD. They further correlate aged-like neutrophils and prophage fractions with inflammatory cytokines. The main strength is that this is not just another 16S comparison. The use of whole-community metagenomics, immune profiling, neutrophil assays, and clinical metadata makes the study more biologically interesting than prior small SCD microbiome papers. The main weakness is that the causal and mechanistic interpretation is too strong. The data support an association between SCD status and microbiome/virome features, but they do not yet establish a clear "axis of pathophysiology." The provirus findings are intriguing, but require stronger statistical control, better validation, and more cautious interpretation.

Strengths:

The major strengths of the study include the clinically relevant disease setting, the use of whole-community sequencing, the integration of microbial, immune-cell, cytokine, and clinical measurements, and the novel attention to bacterial virus-related features. A particularly interesting aspect of the work is the analysis of virus-like elements integrated into bacterial genomes. The authors report that these elements are enriched in the gut microbial communities of patients with sickle cell disease and are associated with several inflammatory signals in blood. This observation is potentially important because it suggests that the microbial contribution to inflammation in sickle cell disease may involve not only bacteria but also bacterial virus-related genetic elements.

Weaknesses:

The evidence for this proposed immune-related mechanism is incomplete. The study is cross-sectional and largely based on associations, so it cannot determine whether these virus-like elements drive immune activation, reflect immune activation, or are linked indirectly through disease severity, treatment history, or other clinical factors. The main limitations are the single-center design, modest sample size for some immune measurements, limited ability to control for treatment and disease heterogeneity, and the need for clearer multiple-testing correction in the correlation analyses. In particular, stronger adjustment for available clinical factors such as hydroxyurea use, transfusion history, pain admissions, genotype, and other markers of disease burden would help readers judge how specific the microbial and viral findings are to sickle cell disease itself.

Overall, the authors largely achieve their descriptive aim of identifying gut microbial differences associated with sickle cell disease. The evidence is solid for the presence of broad microbial community differences, but incomplete for the stronger conclusion that virus-like elements form a pathophysiological immune axis. The work will likely be useful to researchers studying the microbiome, inflammation, and sickle cell disease, especially as a hypothesis-generating dataset. Its impact would be strengthened by more cautious interpretation, stronger control of clinical confounders, clearer statistical correction, and future longitudinal or experimental studies to test causality.

Reviewer #2 (Public review):

Summary:

Singh et al. apply MOA-seq to map transcription factor occupancy genome-wide in HUVECs across a hypoxia time course. The study provides a well-validated, high-resolution view of cistrome dynamics and identifies both HIF1A-associated and independent regulatory programs.

Major comments from the first round of review:

Methodological validation is strong. MOA-seq's ability to map protein-bound DNA at near-nucleotide resolution without factor-specific antibodies is a genuine advance, and the cross-validation against independent ChIP-seq and ENCODE datasets is convincing. As noted, future work with additional biological replicates could further strengthen confidence in the smaller kinetic clusters.

Imaging-based validation would strengthen the key biological claims. The kinetic clustering and pathway enrichments are computationally inferred. Orthogonal approaches, for example, live-cell fluorescence imaging of HIF1A nuclear translocation to confirm the proposed temporal binding waves, would provide independent experimental support.

Reviewer #2 (Public review):

Summary:

The ADP-ribosyltransferase tankyrase controls many biological processes, many of which are relevant to human disease. This includes Wnt/beta-catenin signalling, which is dysregulated in many cancers, most notably colorectal cancer. Tankyrase is a positive regulator of Wnt/beta-catenin signalling in that it counters the activity of the beta-catenin destruction complex (DC). Catalytic inhibition of tankyrase not only blocks PAR-dependent ubiquitylation and degradation of AXIN1/2, the central scaffolding protein in the DC, but also tankyrase itself. As a result, blocking tankyrase gives rise to tankyrase accumulation, which may accentuate its non-catalytic functions, which have been proposed to drive Wnt/beta-catenin signalling. Most tankyrase catalytic inhibitors have shown limited efficacy and substantial toxicity in vivo. By developing tankyrase-directed PROTACs, the authors aim to block both catalytic and non-catalytic functions of tankyrase, aspiring to achieve a more complete inhibition of Wnt/beta-catenin signalling. The successfully developed PROTAC, based on the existing catalytic inhibitor IWR1, IWR1-POMA, induces the degradation of both TNKS and TNKS2, blocks beta-catenin-dependent transcription without stabilising the DC in puncta/degradasomes, and inhibits cancer cell growth in vitro. Mechanistically, this points to a scaffolding role of tankyrase in the DC, at least under conditions of tankyrase catalytic inhibition, in line with previous proposals.

Strengths:

The study clearly illustrates the incentive for developing a tankyrase degrader, namely, to abolish both catalytic and non-catalytic functions of tankyrase. By and large, the study achieves these ambitions, and the findings support the main conclusions, although the statement that a more complete inhibition of the pathway is achieved requires corroboration. The proteomics studies are powerful. IWR1-POMA constitutes a very useful tool to re-evaluate targeting of tankyrase in oncogenic Wnt/beta-catenin signalling. The paired compounds will benefit investigations of tankyrase scaffolding functions across many different biological systems controlled by tankyrase. The findings are exciting.

Comments on revised version:

I thank the authors for responding to the queries raised in the original review, most of which have now been addressed. This further strengthens this well-conducted study and well-presented manuscript. I congratulate the authors for this interesting and insightful work.

A few minor points remain:

I appreciate the authors acknowledge that testing the physical properties of the degradasome puncta is necessary to explore whether they indeed represent condensates. The term "condensates" implies liquid-liquid phase separation (rightly or wrongly). However, this question has not yet been resolved in the case of degradasomes. I therefore suggest the term "condensates" to be avoided. A simple morphological description as "puncta" may suffice.

I thank the authors for including the additional data comparing tankyrase binding by IWR and IWR-POMA. I agree that using the BRET signal of IWR-POMA is informative. Adding the IC50 values directly to the figure panels (S3E, S3G) would help the reader to quickly assess binding. The comparison between these two panels is insightful.

Regarding the use of the terms TNKS, TNKS1 and TNKS2, if the authors would like to use the name "TNKS" to refer to both paralogues collectively, can this please be specified early in the manuscript to limit confusion with the official gene name "TNKS", which of course only refers to one paralogue?

Reviewer #2 (Public review):

Summary

openretina is a Python package for training and applying convolutional neural network-based models of retinal ganglion cell responses. The package integrates dataloading, model training, and evaluation in a unified framework built on PyTorch Lightning and Hydra, and ships with pre-trained model checkpoints and publicly available datasets (whitenoise, natural scenes) spanning multiple species (marmoset, mouse, axolotl, salamander) and recording modalities (multielectrode array recordings or 2-p calcium imaging). Beyond predictive modelling, openretina includes a suite of in silico analysis tools for probing learned representations, including maximally exciting input synthesis, discriminatory stimulus optimisation, and model weight visualisation. The broader openretina initiative aims to establish a community-driven platform for computational retina research, lowering barriers to entry and facilitating cross-dataset model benchmarking. This is a valuable contribution given the longstanding fragmentation of datasets, codebases, and analysis practices across retina laboratories.

Strengths:

The tool has several strengths. By providing a framework built on deep learning infrastructure, the package substantially lowers the barrier to entry for researchers without extensive machine learning backgrounds. The inclusion of pre-trained model checkpoints across multiple species and recording modalities will allow users to apply state-of-the-art models. The in silico toolkit - and in particular the MEI synthesis pipeline - has already demonstrated its scientific potential, with prior work using optimised stimuli to discover a previously uncharacterised RGC type confirmed experimentally, illustrating what becomes possible when these tools are made broadly accessible. The current modular Core + Readout architecture is a well-suited architecture for modeling retina responses. The HDF5-based data standard provides a sensible common format for contributing new datasets. Overall, the initiative is well-motivated, the engineering is competent, and the vision of a collaborative, community-driven platform for retina modelling is one that the retina community would benefit from.

Weaknesses:

(1) The in silico tools provided are valuable, but users should interpret their outputs in light of the performance of the underlying models. The predictive performances of current models and datasets in the package are far from performance ceilings.

(2) The authors appropriately note that optimised stimuli reveal what a neuron responds to but not how the computation is implemented. I would encourage readers to keep this distinction in mind when using the weight visualization tools as well - convolutional filters in a shared, unconstrained core do not map onto retinal circuit elements, and should be treated as model descriptors rather than circuit proxies. For example, RGCs of the same type may appear to sample inputs from two different filters, which should have been a single filter. Or a single RGC may be sampling from two filters, which under more constrained conditions could be approximated with a single filter. These are degeneracies in the CNN modeling framework that should be kept in mind when drawing circuit-level interpretations.

(3) The datasets currently distributed with the package vary in recording quality, and users should be aware that model performance may not only reflect architectural limitations but may also be limited by noise and data artifacts, including spike sorting errors.

(4) As the platform grows and community-contributed datasets are added, explicit data quality standards will be essential. I encourage the authors to develop dataset standards to ensure that their resource provides access to highly curated datasets, which I believe is an important step in having high-fidelity models whose functional interpretations can be trusted.

Reviewer #2 (Public review):

Summary:

This manuscript addresses an important and mechanistically interesting question: whether plasma membrane glutamate transporters contribute only to slow clearance of ambient glutamate or whether they can rapidly shape synaptic signaling during high-frequency auditory activity. This manuscript provides important evidence that EAAT-mediated glutamate uptake is not merely a slow background clearance mechanism but is essential for maintaining reliable synaptic transmission and linear stimulus-intensity coding in ventral cochlear nucleus T-stellate cells during sustained auditory nerve activity.

Strengths:

The finding that EAATs may be required for rapid, local control of glutamate during high-frequency auditory nerve activity is interesting and could have broad relevance to auditory processing. The electrophysiological evidence is generally strong, particularly the use of patch-clamp recordings, stimulus trains, partial versus complete EAAT blockade, and comparison with bushy cell/endbulb synapses. The comparison between T-stellate cells and bushy cells/endbulb synapses strengthens the manuscript. The authors demonstrate that EAAT blockade disrupts coding in T-stellate cells but has little effect on bushy cell spike transmission, supporting a cell-type- and synapse-specific role of glutamate uptake.

Weaknesses:

However, some mechanistic conclusions, especially the specific contribution of neuronal versus glial EAATs and the absence of glutamate crosstalk between auditory nerve inputs, rely mainly on pharmacological and indirect electrophysiological inference and would be strengthened by additional anatomical, genetic, or direct glutamate-sensing evidence.

(1) Clarification of DL-TBOA concentration.

The authors used bath application of 200 µM TBOA and 25-50 µM in the other experiments, stating that "sub-maximal concentrations (25-50 µM)". The authors should provide a clearer rationale for why different concentrations were used across experiments rather than a fixed concentration.

The reversibility of DL-TBOA effects should be demonstrated by washout experiments. In addition, potential off-target effects of DL-TBOA on postsynaptic receptors, intrinsic membrane excitability, or presynaptic release (e.g., PPR measurement) should be carefully considered. It would also be useful to test the effects of the submaximal DL-TBOA concentrations (25-50 µM) on membrane potential and inward currents, shown in Figure 1, to determine whether these concentrations depolarize the membrane potential in current-clamp mode or induce inward currents under voltage-clamp conditions.

(2) Potential contribution of altered intrinsic excitability.

In Figures 3B and 3C, DL-TBOA appears to induce additional action potentials even immediately after the first stimulation, whereas Figures 6 and 7 suggest that the first EPSC is not substantially altered. This raises the possibility that the enhanced firing may partly result from a modest depolarization caused by background glutamate accumulation or from other changes in intrinsic membrane properties after drug treatment. To address this, the authors should provide a quantitative analysis of physiological parameters under submaximal DL-TBOA conditions, including spontaneous action potential frequency, resting membrane potential, input resistance, and spike threshold.

(3) Spillover/ crosstalk between AN-fiber-synpases.

The authors should provide more explanation of how altering the number of active auditory nerve fibers demonstrates the absence of glutamate spillover/crosstalk between bouton synapses. Strong stimulation likely recruits more AN fibers, but it may also change release probability, axonal synchrony, or stimulation spread. The authors should more clearly justify the interpretation that strong stimulation recruits additional independent AN fibers rather than altering release probability or activating fibers with different intrinsic properties.

(4) Interpretation of glial versus neuronal EAAT contributions.

The authors claim that both neuronal and glial transporters contribute to rapid uptake using pharmacological approaches. The pharmacological data demonstrate that glial EAATs play a major role in glutamate clearance at T-stellate cell synapses. The strong increase in EPSC decay time and synaptic charge after UCPH-101/DHK application supports the conclusion that glial transporters contribute substantially to limiting glutamate accumulation during sustained auditory nerve activity. However, the conclusion that neuronal EAATs contribute directly should be stated with some caution. The evidence for neuronal EAAT involvement is indirect and depends on the pharmacological specificity and completeness of glial EAAT blockade. The conclusion would be strengthened by additional evidence, such as EAAT subtype expression/localization in T-stellate cells or auditory nerve terminals, transporter current recordings, immunohistochemistry, or genetic manipulation of neuronal EAATs. In addition, fitting the decay phase with a double-exponential model may help determine whether glial and neuronal EAATs contribute over distinct temporal windows.

Reviewer #2 (Public review):

The authors developed Opto-MDMi, an optogenetic system for light-controlled activation of endogenous p53. The main idea is to target the p53-MDM2/MDMX regulatory interaction using PMI inhibitory peptides. This is a nice strategy because it avoids overexpression of p53, which can have adverse effects that might confound the study of p53 activity. The authors first tested a LOVTRAP-based localization strategy, which showed some efficacy but also showed basal activation. They then developed a LOV2-PMI peptide-caging module to control the activity of the PMI peptide itself, testing for interactions first in vitro and then in vivo. Finally, they combined the two systems into a dual-lock design, where LOVTRAP controls localization and LOV2-PMI controls peptide activity. This combination led to somewhat more potent stimulation of p53 activity.

Another useful aspect of the paper is the detailed description of the development and testing of the LOV2-PMI peptide-caging module, which may aid in the design of other LOV2-based peptide-caging designs.

Strengths

Overall, the paper is novel and rigorous, and the claims are supported by the data. The optoMDMi tool seems ready for implementation, for example, to manipulate and study the role of p53 signaling dynamics. A few points of clarification would strengthen the work.

Weaknesses

The authors develop many tool variants, but there is some lack of clarity over how all of these tools compare to each other, and which ones interested users should use. The work would also be strengthened by showing modulation of endogenous p53 in more than one cell line.

Reviewer #2 (Public review):

This manuscript examines the role of autophagy receptor proteins, particularly p62/SQSTM1, in regulating intracellular Mtb survival in human macrophages. Counterintuitively, depleting p62 reduces bacterial survival rather than enhancing it, pointing to a previously unrecognised mechanism. The authors demonstrate that in the absence of p62, mitochondrial quality is maintained through enhanced TOM20⁺ mitochondria-derived vesicle (MDV) biogenesis, dependent on MIRO1/MIRO2. During Mtb infection, these MDVs are redirected to bacterial phagosomes, promoting RAB7 recruitment, overcoming phagosome maturation arrest and facilitating lysosomal targeting of Mtb. In parallel, bacteria experience increased oxidative stress, further contributing to bacterial killing.

Strengths:

The mechanistic chain is built using multiple complementary approaches, including genetic perturbation, redox biosensors, metabolic assays and microscopy. The use of primary human macrophages from multiple donors alongside established cell lines increases confidence that the phenotype is not cell-line specific. The replication clock experiment is particularly elegant and clearly demonstrates that the reduction in bacterial burden reflects enhanced killing rather than impaired bacterial replication. Overall, the study identifies an unexpected connection between mitochondrial quality control and phagosome maturation and provides a potentially important advance in our understanding of host-pathogen interactions.

Weaknesses:

The study remains entirely in vitro, and the phenotype is absent in mouse macrophages, limiting the immediate physiological and translational relevance of the findings. In addition, many of the central mechanistic conclusions rely heavily on colocalisation analyses, making it difficult to distinguish direct mechanistic relationships from associated trafficking events.

Overall, this is an interesting and technically strong study that uncovers a novel link between mitochondrial quality control and anti-mycobacterial defence. The mechanistic model is plausible and supported by substantial experimental work. However, several aspects of the proposed pathway require stronger experimental support before some of the broader conclusions can be fully justified.

Major points

(1) The central conclusion that TOM20⁺ MDVs are recruited to Mtb-containing phagosomes is based largely on microscopy and colocalisation analyses. Additional orthogonal approaches would strengthen this key aspect of the study and help establish the nature of the vesicles recruited to bacterial phagosomes.

(2) The proposed mechanism whereby TOM20⁺ MDVs facilitate RAB7 recruitment and reverse phagosome maturation arrest remains incompletely demonstrated. While the MIRO1/2 and RAB7 knockdown experiments support the model, they do not directly establish a causal link between MDV recruitment and phagosomal RAB7 acquisition. Additional experiments addressing this step would considerably strengthen the manuscript.

(3) The absence of a phenotype in mouse macrophages raises important questions regarding the conservation and physiological relevance of the proposed mechanism. The authors should discuss possible explanations for this species-specific effect and, if feasible, provide additional experimental insight into the basis of this difference.

(4) The conclusion that mitochondrial quality is maintained despite impaired p62-dependent mitochondrial turnover is based primarily on mitochondrial content, membrane potential, ROS measurements and Seahorse analysis. These are informative but relatively indirect measurements. Additional assessment of mitochondrial turnover by mitophagy would strengthen this aspect of the study.

(5) The proteins studied throughout the manuscript (p62/SQSTM1, NDP52, OPTN, TAX1BP1 and NBR1) are generally classified as selective autophagy receptors rather than adaptors. The terminology should be corrected throughout the manuscript.

Minor points:

(1) Several conclusions throughout the manuscript are based primarily on colocalisation analyses. The limitations of these approaches should be acknowledged explicitly.

(2) The discussion would benefit from a clearer consideration of how the proposed mechanism relates to established pathways regulating phagosome maturation arrest during Mtb infection.

(3) The authors may wish to comment on whether enhanced MDV biogenesis could represent a broader host defence mechanism against intracellular pathogens beyond Mtb.

Reviewer #2 (Public review):

Summary:

The authors generate a comparative single-cell transcriptomic atlas of fetal ovarian development in cattle, human, and mouse, with the goal of identifying conserved and species-specific cellular and molecular features of early ovarian differentiation. The study provides a valuable resource for the field and reveals potentially interesting species-specific characteristics, including a putative bovine steroidogenic cell population. While the dataset is substantial and the computational analyses are generally appropriate, several major conclusions rely primarily on computational inference without independent experimental validation, limiting the strength of evidence supporting some of the central claims.

Strengths:

This study provides a valuable cross-species single-cell atlas of fetal ovarian development by integrating newly generated bovine data with human and mouse datasets. The work fills an important gap in reproductive biology and offers a useful resource for investigating conserved and species-specific features of ovarian development.

The analyses are comprehensive and combine developmental trajectory reconstruction, regulatory network inference, cell-cell communication analysis, and cross-species classification. The identification of a putative bovine-specific steroidogenic cell population is particularly intriguing and may provide a basis for future studies of species-specific ovarian development.

Weaknesses:

The main limitation is that several key conclusions rely primarily on computational analyses without independent experimental validation. In particular, the proposed bovine-specific steroidogenic cell population, which represents the major novel finding of the study, is supported only by transcriptomic evidence.

In addition, many mechanistic interpretations derived from trajectory, regulatory network, and cell-cell communication analyses remain speculative. While the study succeeds as a comparative resource, the evidence supporting several of the central biological claims remains incomplete, and the biological significance of some cross-species differences is not fully explored.

Reviewer #2 (Public review):

This review addresses a highly relevant and timely topic, namely the role of sarcoplasmic reticulum-mitochondria communication and mitochondria-associated membranes (MAMs) in skeletal muscle aging. The manuscript successfully brings together literature from several interconnected fields, including calcium signaling, mitochondrial biology, excitation-contraction coupling, muscle metabolism, and sarcopenia. Given the growing interest in organelle crosstalk as a determinant of muscle health and disease, the topic is undoubtedly of considerable interest to the readership and has the potential to make a valuable contribution to the field.

However, in its current form, the manuscript devotes a substantial proportion of its content to the description of well-established concepts that are already extensively covered in the literature. Large sections are dedicated to general skeletal muscle physiology, excitation-contraction coupling, calcium handling, mitochondrial biology, and MAM structure and composition. While this background information is useful, the level of detail is often excessive for a review that aims to focus on aging-induced alterations in SR-mitochondria interactions. As a consequence, the central theme of the manuscript becomes diluted, and the review reads more like a broad overview of skeletal muscle physiology than a focused analysis of aging-related MAM remodeling.

In contrast, the sections specifically dedicated to aging and MAM dysfunction, which represent the most novel and potentially impactful aspects of the review, are comparatively brief and largely descriptive. The discussion of how aging alters MAM architecture, calcium microdomains, mitochondrial calcium signaling, and organelle communication would benefit from substantially greater depth. For example, although the manuscript highlights alterations in proteins such as MFN2, IP3R, VDAC, and MCU, the mechanistic implications of these changes for sarcopenia and age-associated muscle dysfunction are not critically developed. Similarly, the review would be strengthened by a more comprehensive discussion of the evidence linking MAM disruption to impaired muscle performance, metabolic inflexibility, denervation, and mitochondrial dysfunction during aging.

Another limitation is that much of the manuscript summarizes published findings without sufficiently evaluating the strength of the evidence or discussing existing controversies. Several statements imply causal relationships between MAM disruption and sarcopenia, whereas in many cases, the available data remain largely correlative. The authors should more clearly distinguish between established mechanisms, experimental observations, and emerging hypotheses. A more critical assessment of conflicting findings, particularly regarding the role of MFN2 and the dual consequences of altered mitochondrial calcium uptake, would considerably improve the scientific rigor of the review.

A major omission concerns the role of mitochondrial Ca²⁺ uptake in skeletal muscle physiology and aging. Throughout the manuscript, mitochondrial Ca²⁺ uptake is presented as a central determinant of muscle function and as a key mechanism linking MAM disruption to sarcopenia. However, the authors do not adequately discuss evidence that challenges this view. In particular, genetic mouse models lacking MCU exhibit surprisingly mild skeletal muscle phenotypes under basal conditions despite a near-complete abolition of rapid mitochondrial Ca²⁺ uptake. These findings have generated considerable debate regarding the physiological importance of mitochondrial Ca²⁺ uptake for muscle function and metabolic regulation. While MCU deletion clearly affects exercise adaptation and certain stress responses, the relatively modest baseline phenotype suggests the existence of compensatory pathways and raises important questions regarding the extent to which impaired mitochondrial Ca²⁺ uptake alone can explain age-associated muscle dysfunction. A balanced review should acknowledge these observations and discuss the ongoing debate regarding the relative contributions of mitochondrial Ca²⁺ deficiency versus mitochondrial Ca²⁺ overload in aging skeletal muscle.

Similarly, the discussion of MFN2 would benefit from greater nuance. The manuscript largely presents MFN2 as a structural tether linking the sarcoplasmic reticulum and mitochondria. However, MFN2 is a multifunctional protein with well-established roles in mitochondrial fusion, mitochondrial network organization, mitophagy regulation, and metabolic signaling. Consequently, many of the phenotypes associated with altered MFN2 expression cannot be unequivocally attributed to changes in MAM formation. The review does not sufficiently distinguish between the effects of MFN2 on organelle tethering and its effects on mitochondrial dynamics. This distinction is particularly important because several studies have questioned whether MFN2 acts primarily as a positive tether, a negative regulator of contacts, or whether its influence on organelle communication is secondary to its role in controlling mitochondrial morphology. As a result, attributing age-related alterations in SR-mitochondria communication solely to changes in MFN2-mediated tethering may oversimplify a considerably more complex biological scenario.

The manuscript's organization could also be improved. The sections discussing aging-related alterations, mitochondrial dysfunction, calcium dysregulation, oxidative stress, and therapeutic interventions contain significant overlap and repetition. Streamlining some background sections and reallocating space to a more detailed discussion of aging-specific mechanisms would help maintain focus and improve readability. In particular, the manuscript would benefit from expanding the sections on aging-induced MAM remodeling, age-dependent changes in MAM composition and ultrastructure, and the potential of MAM-targeted interventions as therapeutic strategies for sarcopenia.

Finally, the review would gain from a stronger future perspectives section. Several important questions remain unresolved, including whether MAM disruption is a primary driver of muscle aging or a secondary consequence of mitochondrial dysfunction, how MAM architecture differs among muscle fiber types during aging, and whether MAM-associated proteins could serve as reliable biomarkers or therapeutic targets in human sarcopenia. Highlighting these knowledge gaps would further enhance the review's impact.

Overall, the manuscript covers an important and emerging area of research and contains a valuable compilation of the relevant literature. Nevertheless, substantial revision is required to reduce the emphasis on well-established background information, deepen and critically analyze the aging-specific sections, and provide a more focused discussion of the role of MAMs in skeletal muscle aging and sarcopenia.

Reviewer #2 (Public review):

In this manuscript, the authors studied the cellular mechanism of theta-nested gamma oscillations in the medial entorhinal cortex (MEC) in vitro. The theta-nested gamma activity was induced by theta-modulated optogenetic stimulation of CaMKII+ neurons. In Figures 1 through 4, they describe the firing phase, synaptic input, and LFP-IPSC coupling of stellate cells, pyramidal cells, and interneurons. They then conducted voltage imaging, capturing the simultaneous activity of 41 cells, and found that subthreshold membrane potentials cluster in a weakly distance-dependent manner (Figure 5). The experiments and analysis are done rigorously for the most part.

However, the results described in Figures 1 to 4 are largely descriptive and highly similar to those in their recent publication, which utilized almost identical experiments. While the voltage imaging data during theta-nested gamma oscillations are novel, the authors report data from only a single experiment, leaving it unclear whether the results are reproducible. Furthermore, without a comparison to in vivo data, it remains unclear what novel insights this manuscript provides to advance our understanding of the cellular mechanisms underlying theta-nested gamma oscillations.

(1) The authors recently published another paper on the topic of theta-nested gamma oscillations in the MEC (Williams et al., eNeuro, 2026). In that study, they utilized a Thy1 promoter instead of the CaMKII promoter used here. The motivation for testing the CaMKII promoter in the current manuscript, as well as the novel insights expected from this experimental setup, remains unclear. Given that existing literature suggests inhibitory MEC cells play a critical role in theta activity (e.g., Gonzalez-Sulser et al., 2014)-implying that theta modulation should drive inhibitory rather than excitatory cells-the previous use of the Thy1 promoter appears closer to in vivo conditions than the CaMKII promoter used here.

The overall conclusion of the current manuscript is that excitatory-inhibitory (E-I) interactions dominate the generation of theta-nested gamma oscillations. However, in their previous eNeuro paper, the authors demonstrated that the interneuron network gamma (ING) mechanism can sustain gamma oscillations without excitatory synaptic transmission. It seems expected that excitatory cells would be involved when the optogenetic stimulation selectively drives excitatory cells. If CaMKII stimulation is less physiological and artificially forces the theta-nested gamma activity to rely on excitatory connections, this conclusion could be misleading. It may potentially describe a mechanism that is irrelevant to physiological processes in vivo. Please see my comment 3, which is related to this point.

In addition, Figures 1 and 2 heavily overlap with the authors' previous eNeuro publication. The differences in experimental settings and the motivation for performing almost identical experiments must be clearly articulated prior to these figures to avoid confusion. The authors must also justify why it is necessary to present such similar data, and explicitly point out the novel findings in the current paper compared to their previous work.

(2) Using voltage imaging to investigate theta-nested gamma oscillations is novel. However, the impact of the findings from this experiment appears minimal in the manuscript's current state. The most novel and interesting observation is likely presented in Figure 6, where the authors identified clustered voltage correlations. However, this appears to be an n=1 experiment, and these findings should be replicated at least in a few experiments. Furthermore, the manuscript lacks a discussion or interpretation of this observation, making it unclear whether the result is biologically meaningful. Please find specific suggestions regarding this point below.

(3) The authors' primary motivation for investigating the mechanisms underlying theta-modulated gamma oscillations is their potential role in grid cell firing. Therefore, it is critical that the mechanisms studied here in vitro accurately reflect in vivo processes. For this reason, greater effort should be made to better link this in vitro study with existing in vivo data. Numerous public in vivo datasets are available that detail the firing activity of putative principal cells and interneurons during exploratory behavior in mice. Intracellular recordings in awake animals have also been published, some of which the authors already cite. The data presented in Figures 1 and 4, for example, could be straightforwardly compared with those existing in vivo metrics. Furthermore, available in vivo silicon probe recordings could provide a reliable estimate of the spatial distribution of gamma-related spike activity. Such data should be compared with the voltage imaging results presented in this study.

This limitation connects back to the first point. In this manuscript, the authors tested a different method for inducing theta-nested gamma oscillations (via the CaMKII promoter) than in their recent eNeuro paper (via the Thy1 promoter). The outcomes of these two induction methods must be systematically compared against in vivo data to determine which approach aligns more closely with physiological conditions. Without such a comparison, the scientific justification for testing a different promoter in this study remains unclear.

Reviewer #2 (Public review):

Summary:

The manuscript by McCraken and colleagues provides a continuation of their 2023 study (Cell Reports 42:113165) characterizing calcium regulation in retinal ganglion cells (RGCs) after acute optic nerve damage (a 10s crush using an intraorbital approach). This work is principally focused on how mitochondrial calcium stores change in both RGCs that are resilient and susceptible to injury. They report that resilient RGCs typically exhibited high calcium levels, but paradoxically, manipulating mitoCa2+ levels was more protective when the stores were reduced. Overall, regardless of susceptibility, mitoCa2+ levels decreased after injury, which is opposite to other reports that mitoCa2+ increases in degenerating neurons. The manipulation of mitoCa2+ was conducted both pharmacologically (Ru265) and by overexpression or knockdown of a primary calcium uniporter MCU. The evaluation of mitoCa2+ was conducted by using a reporter (Twitch2b) that was targeted to the mitochondria.

Strengths:

Many of the experiments are elegant and well-performed.

Weaknesses:

(1) Some experiments require further controls to validate that reagents are doing what they are intended to do.

(2) Some findings can have alternate interpretations that are not considered.

(3) There is a broad generalization to the biology of all RGCs that may not be biologically relevant to different RGC subtypes.

Reviewer #2 (Public review):

Summary:

Human DS is associated with metabolic dysfunction in humans, but the precise details of this have not been studied in detail. Here, the authors use a mouse model of DS to study systemic metabolic and transcriptional responses in key metabolic tissues to provide a deep understanding of the metabolic changes associated with DS. As part of his work, the authors also aimed to help inform the selection of a mouse model that best reflects the metabolic profile of DS, through comparison with other DS model metabolic data.

The data presented in this model will be of interest to those in the field of metabolism. The immediate impact is unclear, but the breadth of data presented makes this a very useful resource.

Strengths:

(1) This work builds on other comprehensive analyses that the authors have performed in other DS mouse models.

(2) The authors note common metabolic disturbances between male and female mice (e.g., insulin resistance) alongside clearly sexually dimorphic phenotypes (e.g., body weight). Studying both sexes in this context is important.

(3) The authors have written the paper in a way that integrates a large number of observations well. There is complex data, and a high degree of sexual dimorphism. The study has generated a valuable and wide-ranging dataset comprising molecular, biochemical, and physiological data that will be useful for further, more mechanistic studies of metabolism in DS.

(4) For specific observations, like the findings of altered body temperature in male and female mice, the authors undertake follow-up hypothesis-driven analyses of BAT mitochondria and specific hormones. Although these analyses do not explain the change in temperature, they ensure the study is not purely descriptive in nature.

Reviewer #2 (Public review):

Summary:

This manuscript reports the development of a cryo super-resolution fluorescence microscopy system. The authors demonstrate that they can achieve a mechanical and thermal stability that is sufficient to perform cryo-SMLM over the course of several hours. Focus instability is compensated for by tracking a fluorescent bead for its movement in the axial direction and adjusting the sample stage accordingly during data acquisition. Lateral instabilities are corrected after data acquisition. An enclosure around the microscope allows to significantly reduce ice contamination during cryo-SMLM imaging and sample transfer. The authors show an example of correlative cryo-SMLM and cryo-ET imaging achieved with their microscope system, which depicts the distribution of FtsZ-rsEGFP2 in E. coli.

Strengths:

The authors have designed a microscopy system for SR-cryo-CLEM, which achieves high stability while reducing complexity and costs substantially when compared to vacuum-insulated systems (e.g., Hoffman et al., 2020). They also provide software for controlling the microscope and data acquisition. This lowers the barrier for other labs to implement SR-cryo-CLEM into existing cryo-ET workflows. Reduction of ice contamination helps to increase throughput, which is currently one of the biggest bottlenecks for SR-cryo-CLEM.

Weaknesses:

To correct for focus drift, the authors track a fluorescent bead in the far-red channel. This is possible for bacterial samples as used in this work, as beads can easily be introduced to surround the cells.

Recommendations:

(1) It is not discussed how this can be achieved in other samples than bacterial samples, such as lamellae in mammalian cells. Here, it would be much more difficult to introduce bright point-like markers with far-red fluorescence that would be distributed in the entire cell to capture at least one in the final lamella. Furthermore, it might be important to know for readers whether the far-red channel has to be sacrificed entirely for the focus correction.

(2) The authors show an application of SR-cryo-CLEM imaging of FtsZ-rsEGFP2 in E. coli. In the chosen correlative example (Figure 4d.f), no clear structure can be seen in the fluorescent images. The overview image (Figure 4d) shows no distinct signal in the cell, as it is shown for the non-correlative example in Figure 4a. The cryo-SMLM image (Figure 4f) does not show any ring-like features or accumulations of signals at the constriction site, as would be expected for a projecting along the optical axis. A clearer application example, which would show how increased resolution in cryo fluorescence microscopy enables resolving certain structural details or adds information not accessible in cryo electron tomography, would have strengthened the work. Particularly if taking into consideration that bacteria have a strong auto-fluorescence in the green range (Dahlberg et al., 2020), which could lead to high background or false positive localizations when using green fluorophores as labels.

(3) Access to CAD drawings (particularly for custom-made parts, such as cryostat or humidity enclosure) and a parts list is highly important for other researchers who would like to set up this SR-cryo-CLEM system in their own lab or institution. This is currently missing and, therefore, creating a hurdle for a wider adaptation of the technique.

Reviewer #2 (Public review):

Summary:

Chromatin regulates a wide range of biological processes. The nucleosome, composed of 147 bp of DNA wrapped around a histone octamer containing histones H2A, H2B, H3, and H4, is the fundamental unit of chromatin. Post-translational modifications of histone proteins regulate the dynamic properties of nucleosomes and thereby influence chromatin accessibility and gene expression. Among these modifications, lysine acetylation on histone H3 is closely associated with transcriptional activation. While the epigenetic functions of acetylation on the histone H3 N-terminal tail have been extensively studied, the molecular mechanisms by which acetylation within the histone H3 core domain, particularly at Lys56, Lys64, and Lys122, modulates nucleosome architecture to facilitate RNA polymerase II (RNAPII) transcription remain unclear.

In this study, Oishi et al. investigated the effects of histone H3 acetylation at K56, K64, and K122 on RNAPII transcription using in vitro transcription assays. Furthermore, the authors determined the three-dimensional structures of nucleosomes containing these acetylation marks by cryo-electron microscopy single-particle analysis, revealing distinct structural dynamics depending on the acetylation site. Overall, this study advances our understanding of the molecular mechanisms linking histone H3 core acetylation to transcriptional regulation.

Strengths:

(1) Site-specifically acetylated histone H3 proteins were chemically synthesized using a unique and rational peptide ligation strategy, representing a major technical strength of this study.

(2) The in vitro transcription assays demonstrated that H3K56ac and H3K122ac increase the production of run-off transcripts, whereas H3K64ac has little effect on transcription efficiency. These findings highlight the distinct functional roles of individual acetylation sites within the histone H3 core domain.

(3) The cryo-EM structures of nucleosomes containing either H3K56ac or H3K122ac revealed that H3 acetylation weakens histone-DNA interactions, providing a structural basis for the observed effects on transcription.

Weaknesses:

(1) Although the biochemical and structural data are convincing and sufficiently support the authors' conclusions, complementary cellular experiments would further strengthen the physiological relevance of the in vitro findings. While such experiments are not essential for supporting the main claims of the study, they would enhance the overall impact and biological significance of the work.

(2) Although the authors demonstrate the structural consequences of individual H3 core acetylation events, the study does not investigate potential synergistic effects among multiple acetylated lysine residues within the H3 core domain. Consequently, the relationship between combinatorial acetylation patterns and their collective impact on RNA polymerase II-mediated transcription remains unclear.

Reviewer #2 (Public review):

Summary:

The manuscript addresses an important and underexplored question: how affinity maturation alters antibody encounter-state landscapes rather than simply improving bound-state affinity. The authors combine adaptive MD, Markov State Models (MSMs), transition path theory, mutagenesis, SPR kinetics, and double-mutant cycle analysis into a coherent story.

Strengths:

This manuscript presents a compelling computational and experimental analysis of antibody affinity maturation in the HIV-1 DH270 lineage. The main finding is that somatic mutations reshape encounter-state pathways through glycan-mediated steering rather than simply stabilizing the final bound state. This is novel and potentially important for vaccine design. The combination of adaptive MD, MSMs, SPR kinetics, and double-mutant cycle analysis is a major strength.

Weaknesses:

The proposed sequence that somatic mutations cause glycan capture, which causes reorientation, which causes enhanced association, is based on correlation rather than direct causality.

The four MSM states are not convincingly explained, and the robustness of these states is unclear.

The productive collision surface area analysis needs more quantitative data.

The coupling energy values are near the uncertainty range. Some conclusions about long-range communication networks appear stronger than the data justify. The data support coupling, but they do not necessarily support detailed mechanistic networks.

The study investigates one lineage, one epitope class, and one viral system. Hence, the generalization is limited.

DOI: 10.1016/j.celrep.2026.117477

Resource: RRID:ZFIN_ZDB-ALT-151120-2

Curator: @evieth

SciCrunch record: RRID:ZFIN_ZDB-ALT-151120-2

What is this?

Reviewer #3 (Public review):

Summary:

This preprint proposes luxCDABE-based luminescence as a high-throughput alternative (or complement) to CFU time-kill assays for estimating antimicrobial rates of population change at super-MIC concentrations, by comparing luminescence- and CFU-derived rates across 20 antimicrobials (22 assays) and attributing divergences primarily to filamentation (luminescence closer to biomass/volume than cell number) and changes in culturability / carryover (CFU undercounting viable cells).

Strengths:

The authors do not merely report discrepancies; they experimentally validate the biological causes. Specifically, they successfully attribute the slower decline of luminescence in certain drugs to bacterial filamentation (maintaining biomass despite halted division) and the rapid decline of CFU in others to loss of culturability or carryover effects.

The inclusion of 20 antimicrobials spanning 11 classes provides a robust dataset that allows for broad categorization of drug-specific assay behaviors.

The study critically exposes flaws in the "gold standard" CFU method, specifically regarding antimicrobial carryover (demonstrated with pexiganan) and the potential for CFU to overestimate cell death in the presence of VBNC (viable but non-culturable) states induced by drugs like ciprofloxacin.

The use of chromosomal integration for the lux operon to minimize plasmid copy-number effects and the validation of linearity between light intensity and cell density establish a solid technical foundation.

In summary:<br /> Muetter et al. provide a compelling argument that luminescence is a reliable, high-throughput alternative to CFU for super-MIC investigations, particularly when the quantity of interest is biomass. The paper effectively warns researchers that discrepancies between CFU and luminescence are often biological (filamentation, VBNC) rather than methodological failures.

Comments on revised version:

The revised version addressed my comments well.

Reviewer #2 (Public review):

Summary

Antimalarial combination therapy is the standard of care for malaria, a disease that impacts hundreds of millions of people annually. Combination therapy is crucial for effectively treating the disease and delaying the emergence of drug resistance. Despite the importance of choosing appropriate partner antimalarials for combination therapy, drug interactions are typically evaluated late in the course of drug development. Standard in vitro assays that determine synergistic, antagonistic, or additive interactions between drug combinations rely on measuring inhibition of parasite proliferation, which is inadequate for translation to pharmacodynamic models for parasite clearance in the patient. Direct measurement of parasite viability under drug treatment has previously relied on methods that are labor and resource-intensive, limiting applications to single compounds and single concentrations. Here, Hellingman et al make use of an inducible chemiluminescence reporter to measure cell viability and apply this novel approach to quantify drug interactions. The methodology is a significant improvement upon prior methods, requiring significantly fewer resources, half the time, and substantially less handling than the standard PRRv2 assay, whilst maintaining high resolution and sensitivity.

They assess the limit of detection for the improved method and cross-reference their results for single drugs at a single concentration with the currently standard PRRv2 assay. The authors next established analytical methods to characterize the impact of drug combinations on parasite viability using the GDPI pharmacodynamic model and compared their MULT-i2 assay to the prior cPRR approach. Their refined workflow allowed them to comprehensively evaluate the known synergistic combination between atovaquone and proguanil with greater resolution than the comparable cPRR assay and identified additional interaction parameters between the fast-acting antimalarials piperaquine and pyrimethamine. Overall, the authors demonstrate that their inducible lacZ system provides significant advantages compared with prior approaches to determine parasite viability. They convincingly demonstrate the strengths of their approach by characterizing two antimalarial combinations at much greater resolution than previously possible with prior methods. The system and methods established here will be particularly useful for evaluating novel antimalarial combinations with chemical series in preclinical evaluation and to optimize future antimalarial therapies.

Strengths:

The streamlined approach relies on induction of the lacZ enzyme only after drug washout. As opposed to when stably expressed, this allows the authors to estimate parasite viability without undergoing serial dilutions to estimate viable parasite titers. This innovation vastly reduced resource and time intensity, enabling greater throughput for parasite viability estimation. The established methodology and analysis pipeline enabled the testing of 49 drug combinations for parasite viability in the MULT-i2 assay compared to only 9 in the conventional cPRR assay. This provided improved resolution in the ability to estimate drug combination parameters in a pharmacodynamic model. The ability to comprehensively characterize combination pharmacodynamic properties in vitro will have important implications for downstream modelling of in vivo combinations, and for optimizing future antimalarial combination therapies.

The authors made good use of modelling and AICc for parametric estimation and model evaluation to demonstrate the advantages of the richer dataset afforded by the MULT-i2 assay.

Weaknesses:

The authors correctly identified a range of confounding effects that lead to artefacts in their assay results when compared to the cPRR assay. For instance, the authors observed reduced signal at high parasite density during recovery due to overgrowth and likely enzyme degradation, and suggested residual signal may remain from non-proliferating sexual stage parasites surviving drug treatment that would not be detected in the cPRR assay.

Measurement of parasite viability in the MULT-i2 assay was achieved by extrapolating the chemoluminescence signal to that of a serial dilution of parasites made at the initiation of drug treatment. How did the authors account for differing levels of enzyme expression at early (e.g., ring) vs late stage parasites (trophozoite or schizonts)? Were cultures synchronized prior to initiation of assays? Could differences in life-cycle progression following drug treatment be an additional confounding factor that may account for differences with the PRRv2 assay?

The addition of an inducible element is an improvement of their earlier lacZ/β-galSENSOR (PMID: 41575867); however, the authors fail to explain why this is an improvement and how this adds additional merit over the initial system. While the authors compare their new assay to the PRRv2, they fail to compare it to their own non-inducible lacZ/β-galSENSOR system. Their non-inducible system already showed superiority to the cPRR assays, and it would be good to show how they compare and what the advantages of the new system are over the old. e.g., how is the signal-to-noise improved? How does the sensitivity compare? How quickly does the can the signal be detected after induction? They show signal after 48h, but it would be very useful to the community to look at earlier timepoints as well and compare them to the uninduced line and a line that has been induced 48h earlier to match the expression patterns throughout the lifecycle (something like 2h,4h,6h, 12h, and 24h).

Is the chemiluminescence signal for the i-lacZ induced parasites comparable to the stably expressed lacZ parasites previously characterized by the group? If so, do the authors consider this inducible iteration a complete replacement for PRR assays?

Reviewer #4 (Public review):

Summary of General Strengths & Weaknesses:

The studies here are highly informative for anatomical tracing and sympathetic nerve function in the liver in relation to glucose levels, but because they are conducted in a single species, it is challenging to translate them to humans or determine whether these neural circuits are evolutionarily conserved. Dual-labeling anatomical studies are elegant, and the addition of chemogenetic and optogenetic studies provides mechanistically informative. Denervation studies lack proper controls, and sensory innervation in the liver is overlooked.

Specific Weaknesses - Major:

(1) The species name should be included in the title.

(2) Tyrosine hydroxylase was used to mark sympathetic fibers in the liver, but this marker also labels a portion of sensory fibers that need to be ruled out in whole-mount imaging data.

(3) Chemogenetic and optogenetic data demonstrating hyperglycemia should be described in the context of prior work demonstrating liver nerve involvement in these processes. There is only a brief mention in the Discussion currently, but comparing methods and observations would be helpful.

(4) Sympathetic denervation with 6-OHDA can drive compensatory increases in tissue sensory innervation, and this should be measured in the liver denervation studies to implicate potential crosstalk, especially given the increase in LPGi cFOS that may be due to afferent nerve activity. Compensatory sympathetic drive may not be the only culprit, though that is clearly assumed. The sensory or parasympathetic/vagal innervation of the liver is altogether ignored in this paper and could be better described in general.

Comments on the revised version.

Across all reviewer comments, the revised resubmission has adequately addressed all concerns.

Reviewer #2 (Public review):

Summary:

This study investigates whether visuomotor mismatch responses can be detected in humans. By adapting paradigms from rodent studies, the authors report EEG evidence of mismatch responses during visuomotor conditions and compare them to visual-only stimulation and mismatch responses in other modalities.

Strengths:

- Authors use a creative experimental design to elicit visuomotor mismatch responses in humans.

- The study provides an initial dataset and analytical framework that could support future research on human visuomotor prediction errors.

Weaknesses:

- Methodological issues (e.g., volume conduction) make it difficult to confidently attribute the observed mismatch responses to activity in visual cortical regions. This could be alleviated by increasing the number of channels.

The authors successfully demonstrate that visuomotor mismatch paradigms can, in principle, be applied in human EEG. This approach provides a translational bridge between rodent and human work on predictive processing.

Comments on latest version.

The authors added a brief discussion paragraph which addresses my previous comment.

Reviewer #2 (Public review):

Summary:

The manuscript "Mechanical interaction enables a collective mode of protocell proliferation" addresses an interesting and potentially high-impact question about protocell proliferation in prebiotic environments. The central observation that wall-deficient B. Subtilis proliferate in dense colonies but die by membrane rupture in isolation is striking and a fundamental contribution to the field. However, the data and the mechanistic explanation offered for this observation are incomplete. The measurement and analyses used to build the mechanistic case raise methodological questions that may be difficult to fully resolve with the existing data and approach, and the authors should therefore consider whether additional independent experiments are needed to support the mechanical shearing hypothesis.

Strengths:

The central observation that wall-deficient B. Subtilis proliferate in dense colonies but die by membrane rupture in isolation is convincing and a significant contribution to the field interested in the growth of protocells. This adds an important aspect of collective growth that is different from individual dynamics.

Weaknesses:

(1) The surface-volume balance ratio η is an elegant concept and provides an intuitively reasonable framework for understanding why isolated cells lyse. However, its application here rests on treating cells as flat discs of uniform thickness, and Figure S4 makes clear that the cells are highly irregular and lobulated in ways that make this approximation questionable. The authors should clarify whether they have validated this assumption, for instance, through direct thickness measurements or sensitivity analysis. However, even with such validation, the modest quantitative differences between aggregated and isolated η trajectories, combined with the inherent difficulty of accurate perimeter measurement in these morphologically complex cells, mean that η measurements are unlikely to provide robust quantitative support for the mechanism. The authors should therefore consider whether η is better presented as a motivating conceptual framework rather than primary quantitative evidence and seek more direct experimental support for the surface-volume balance argument through independent means. For instance, osmotic pressure manipulation to test whether reducing volume expansion pressure preferentially rescues isolated cells.

(2) The comparison of circularity between colony and isolated cells is complicated by the fact that the segmentation approach is fundamentally different in the two conditions; isolated cell boundaries are detected against a clear background, while colony boundaries are detected from inter-cell fluorescence gradients. The authors should address whether this introduces systematic bias. However, this may be difficult to fully resolve given the inherent complexity of the system, and that the deformation-division correlation in Figure 3C, while suggestive, would be substantially strengthened by a more direct perturbative approach. Specifically, can cell deformation be mechanically induced in isolated cells, for instance, using micromanipulation, external flow, or confinement in fabricated microstructures, to test whether artificially deformed isolated cells gain the ability to divide? Such an experiment would provide direct evidence for the deformation-division link that the correlational analysis cannot.

(3) The interpretation of FliptR lifetime as a direct membrane tension readout is complicated in this system because cell-cell interfaces contain two apposed bilayers in proximity, potentially altering FliptR photophysics through changes in local membrane density and dielectric environment independently of tension. The authors should address whether they have considered this possibility and what controls were performed. Disambiguating tension-dependent from environment-dependent lifetime changes is technically challenging and suggests that the membrane tension argument would be more convincingly supported by an independent measurement approach. For instance, tether-pulling experiments using optical tweezers on isolated versus colony cell membranes, or testing whether membrane tension-modulating interventions such as osmotic shifts produce the predicted changes in cell fate, would provide more direct evidence. The current FLIM data should be regarded as suggestive rather than conclusive.

(4) The Cellular Potts Model reproduces the experimental observations, but since its key parameters, particularly the substrate-pinning energy, were calibrated against those same observations, this demonstrates internal consistency rather than independent validation. The η-based lysis criterion is implemented as a model input, meaning the model cannot independently confirm the η hypothesis. The authors should clarify the extent to which model parameters were fitted to data versus independently motivated and be explicit that the model is best understood as a mechanistic illustration rather than independent evidence.

Reviewer #2 (Public review):

Summary:

The authors asked how the visuomotor system can keep visual selection and saccade targeting related but not rigidly coupled-the flexibility required for tasks like anti-saccades. They recorded visual receptive fields (RFs) and saccade motor fields (MFs) from individual neurons in marmoset frontal eye fields and adjacent premotor eye fields (FEF+) using obliquely inserted Neuropixels probes that traverse horizontal segments of the smooth marmoset cortex. They reported that visual and motor vector angles each changed smoothly with occasional abrupt jumps (a mosaic, rather than retinotopic, organization), that the two maps drifted with respect to one another, and that they were best described by mosaic-map models tuned to different preferred spatial frequencies. They then proposed that the offset in spatial scale, combined with partial shared structure between the maps, produced a moiré interference pattern, in which the distribution of local visual-motor angle differences matched the data.

Strengths:

(1) Unlike in the macaque brain, where FEF is buried in the arcuate sulcus, the marmoset cerebral cortex is lissencephalic (smooth). The authors used this feature to their great advantage and sampled horizontal mesoscale structure with oblique penetrations of ultra-high-density Neuropixels probes.

(2) The mosaic framing was grounded in previous studies on direction maps in ferret V1 and MT, and the rate-of-change analysis (Supplementary Figure 2) plausibly reproduced the fracture-line phenomenon of those maps.

(3) The authors confirmed the robustness of the finding by reaching the same conclusions using two architecturally distinct generators: the Fourier-based annulus model and the Gaussian-noise model.

(4) They additionally provided an independent confirmation of the mosaic saccade-vector organization using electrical microstimulation. They reconciled the lower microstimulation spatial frequency by matching the spatial-averaging footprint (Supplementary Figure 6).

(5) The Noise Mosaic (NM) model was used thoughtfully to decouple two properties that the Annulus Mosaic (AM) model confounds - spatial-scale offset and inter-map correlation - and to show that both an intermediate correlation (ρ ≈ 0.6) and a scale offset are required. Conceptually, a structural (topographic) substrate for visuomotor flexibility is a fresh alternative to the standard account in which flexibility lives entirely in time-varying activity on a single map.

Weaknesses:

The two claims here are not of the same strength. The first claim that RF and MF angles are organized as mosaics at distinct spatial scales was well supported. The second claim that a moiré interference pattern is the substrate for visuomotor flexibility was an inference rather than a direct observation, and several features of the design contribute to how strongly it can be held.

First, the recordings were one-dimensional. Each oblique penetration yielded a line through the cortex, so the two-dimensional moiré pattern (Figure 4A) existed only in simulations; it was not reconstructed from the data. What the data provided was the marginal distribution of local angular differences, and the model was accepted when its simulated distribution was statistically indistinguishable from the empirical one. Matching a low-dimensional summary statistic is necessary but not strongly sufficient - multiple underlying architectures could produce similar 1-D difference distributions - so the moiré interpretation is best read as a plausible and parsimonious interpretation of the data rather than a confirmed mechanism.

Second, the inferential logic needs to be strengthened. The "preferred" spatial frequencies were those at which a two-sample Kolmogorov-Smirnov test fails to reject equality between model and data. Failure to reject is not confirmation, and the width of the accepted band depends on statistical power, which depends on sample size. The authors did show that most parameter combinations were rejected, so the test did discriminate. That said, a continuous goodness-of-fit landscape with confidence intervals on the preferred SF, and a direct test that the visual and saccade preferred SFs differ, would better support the "distinct spatial scales" claim than visual inspection of two overlapping troughs.

Third, the dataset was from two male marmosets, with 18 of 39 sites contributing to the core analyses, and the angular-difference distributions were pooled across penetrations and animals. This is standard for primate electrophysiology, but it means the spatial statistics were assumed stationary across the region, and individual variability in map layout was averaged over. The oblique-penetration geometry also added some uncertainty: the spatial-frequency estimates (in cycles/mm) are only as accurate as the reconstructed penetration angles (18.2{degree sign} {plus minus} 8.3{degree sign}), and angle error would propagate directly into the inferred scales.

Fourth, while the authors suggested the moiré interference pattern can serve flexible routing for behaviours such as anti-saccades, this was not directly tested. Instead, they used free viewing and natural saccades, so the paper demonstrated a candidate substrate without testing whether behaviour employs it. This does not undercut the main findings, but readers should treat the functional narrative in the introduction and discussion as a set of predictions rather than results.

Reviewer #2 (Public review):

Summary and strengths:

In this study, Bhojappa et al. investigate the roles of the septin-associated kinases Elm1, Gin4, Hsl1, and Kcc4 in septin organization and cytokinesis in budding yeast. Through quantitative analyses of kinase localization dynamics, septin organization, actomyosin ring (AMR) constriction, and cell morphology, the authors demonstrate that Elm1 and Gin4 play particularly important roles in maintaining proper septin architecture and cytokinetic progression. The work further identifies an interaction between the Gin4 KA1 domain and the Hof1 F-BAR domain and provides evidence that several cytokinesis-related functions of Gin4 are independent of its kinase activity. Artificial tethering approaches further supports that spatial organization at the bud neck is critical for the execution of septin-dependent cytokinetic processes. The authors combine live-cell imaging, quantitative analyses, biochemical interaction assays, and genetic perturbations to build a comprehensive framework for understanding how these kinases contribute to cytokinesis.

Comments on revised version:

The revised manuscript has been substantially improved. The authors have carefully addressed the concerns raised during review by providing additional experiments, analyses, quantifications, clarifications, and improved presentation of the data. The conclusions are now well supported by the experimental evidence. The study advances our understanding of the mechanisms linking septin organization to cytokinesis and will be of interest to researchers studying septins, cell division, and cytoskeletal regulation.

Overall Assessment:

This work provides valuable mechanistic insight into the coordination of septin organization and cytokinesis by septin-associated kinases. The experiments are carefully executed, the analyses are thorough, and the conclusions are supported by the data presented. The manuscript represents a useful contribution to the fields of cytokinesis and septin biology.

Reviewer #2 (Public review):

Summary:

Immunogenic Plasmodium falciparum proteins that could be targeted to prevent parasite development in the liver are of significant interest for novel anti-malarial vaccine development. In this study, McConville et al evaluate the trafficking and functional importance of LSA3, a protein expressed in the blood and liver stages and previously shown to provide protection in immunized chimpanzees. LSA3 contains a PEXEL motif but the authors have previously shown that this protein does not appear to be exported beyond the PVM in the liver stage (McConville et al PNAS 2024). However, LSA3 trafficking and functional importance have not been comprehensively evaluated across stages. In the present study, the authors find that blood-stage LSA3 undergoes PEXEL processing and a portion of the protein is exported into the erythrocyte where it localizes to punctate structures distinct from Maurer's clefts. Using a knockout mutant, LSA3 is shown to be dispensable for blood and mosquito stages but important to liver-stage development. Collectively, these results validate LSA3 as a liver-stage target and place it among several other PEXEL proteins that display differential trafficking beyond the PVM in the erythrocyte but not the hepatocyte.

Strengths:

(1) The authors present a thorough analysis of LSA3 trafficking in the blood stage. PEXEL processing by Plasmepesin 5 is clearly demonstrated through a combination of mini LSA3-GFP reporters and Plasmepsin 5 inhibitors. Importantly, an LSA3 knockout mutant is used to show that the LSA3-C anti-sera also reacts with additional, unidentified parasite proteins in the blood stage. Nonetheless, comparison between the WT and KO parasites clearly indicates that a portion of LSA3 is exported into the erythrocyte, which is further supported by protease-protection assays with fractionated iRBCs. This contrasts with the liver stage where LSA3 does not appear to traffic beyond the PVM, similar to what has been observed for other PEXEL proteins in the rodent malaria model.

(2) This study provides the first analysis of LSA3 exoerythrocytic function, showing this protein is important for liver stage development in chimeric human liver mice. Several PEXEL proteins in P. berghei have been shown to be exported into the host cell in the blood stage but do not appear to cross the PVM in the liver stage. These observations reinforce that even without detectible export into the hepatocyte, PEXEL proteins play critical roles during liver stage development.

Weaknesses:

The authors previously reported that anti-LSA3-C signal in the liver stage localizes within the parasite and at the parasite periphery but is not exported into the hepatocyte. In the present study, it is shown that anti-LSA3-C reacts with other parasite proteins beyond LSA3 in the blood stage and this may also occur in the liver stage. However, since liver-stage IFAs were only performed on samples co-infected with both WT and ∆LSA3 parasites, non-specific anti-LSA3-C reactivity at this stage could not be determined and the localization of LSA3 in the liver stage remains somewhat unclear.

Comment on revisions:

The authors thoughtfully addressed the reviewer comments.

Reviewer #2 (Public review):

The authors present an interesting study on calibrating and validating a biventricular cardiac electromechanical model. This is an important contribution, but some questions remain about the quantitative validation and verification aspects of the study.

Major comments:

(1) The title and paper stress the importance of validation on several occasions. However, the actual validation performed is limited to the section in lines 427-439. Furthermore, it is entirely qualitative, making assessing the model's quality difficult. Most of the paper is focused on sensitivity analysis, which is also interesting but unrelated to validation. Can you include a quantitative comparison with deformation biomarkers? E.g., spatially quantify strain differences between simulation and in vivo data, or overlay the current configuration of the geometry with MRI in various views, and calculate a displacement error norm.

(2) You mention the ASME V&V40 standards throughout your paper. Yet, you only address the "second V" validation, ignoring the "first V" verification. How did you ensure that your computational models are implemented correctly?

(3) All parameters discussed in this publication are physical parameters. What is the sensitivity of your model outputs concerning computational parameters?

Comments on revised version.

The authors have addressed my prior comments

Reviewer #2 (Public review):

This study applies the Logan assemblage of the Sequence Read Archive to investigate papillomavirus diversity at a large scale. The authors combine sequence similarity searches, phylogenetic analyses, protein annotation, structural comparisons, and metadata integration to identify and characterize novel papillomavirus sequences. Beyond papillomavirus sequence discovery, the study develops a framework for associating viral sequences with host, geographic, and ecological metadata through the integration of both established and recently developed large-scale public sequence repositories. This framework may provide a foundation for similar investigations across other viral taxa.

An important aspect of the work is the systematic processing and integration of metadata across a large number of sequencing libraries. The approaches developed to aggregate, curate, and interpret host and environmental information may be broadly applicable to future large-scale studies of other viral families. At the same time, interpretations based on metadata-derived ecological and host-association patterns should be considered in the context of the inherent limitations of public sequencing repositories, including uneven taxonomic representation, heterogeneous sampling strategies, laboratory-derived samples, and variable sequencing protocols. The comments below primarily address methodological details, interpretation of ecological patterns, and opportunities to further strengthen the robustness of the analyses and conclusions.

Pages 136-137: The manuscript focuses primarily on L1-containing contigs. Could the authors provide a summary of libraries containing other PV hallmark genes (e.g., E1 or E2) but lacking full-length L1 sequences? This would help assess how much additional PV diversity may remain inaccessible under an L1-centered framework. Furthermore, the manuscript does not provide a detailed discussion of technical or biological explanations for libraries with detected PV sequences but lacking L1 sequences. Could such cases represent incomplete assemblies, low-abundance infections, highly divergent PVs, or endogenous papillomavirus-derived elements? Clarifying these possibilities would help readers interpret the biological significance of these detections.

Page 141: The rationale for performing the search in two sequential Logan releases is unclear. Does Logan v1.1 fully supersede v1.0? If so, why was the initial search performed on v1.0 rather than directly on v1.1? Providing a clearer description of the differences between the two database versions and explaining how these differences motivated the two-round search strategy would improve reproducibility.

The data could have been explored at the libraries' read level. The analysis is currently limited to presence/absence and diversity patterns derived from assembled PV contigs. However, the identified PV-positive libraries provide an opportunity to explore abundance-related metrics. Read counts, coverage estimates, or other measures of sequence representation could be used to characterize PV abundance within libraries, providing additional ecological context and helping distinguish low-level incidental detections from strongly represented infections. In addition, the curated PV sequence dataset generated in this study could serve as a reference for targeted read-mapping analyses. Aligning reads from a subset of libraries classified as PV-negative may help determine whether PV sequences are present below assembly detection thresholds. Such an analysis could provide valuable insights into the sensitivity of assembly-based virus discovery approaches and help establish practical coverage or read-count thresholds for detecting low-abundance papillomaviruses. These results could have important implications for future surveillance, clinical, and environmental studies aimed at PV detection.

Pages 155-156: Clustering was performed using sequence identity, while host, geographic, and ecological annotations were assigned from representative centroids. How frequently did clusters contain sequences associated with conflicting metadata (e.g., distinct hosts or geographic regions), and how were such cases handled?

Page 160: The authors state that the 70% query coverage threshold was selected based on an observed bimodal distribution. Could this analysis be shown explicitly (e.g., in a supplementary figure), and could the authors discuss how sensitive the number of novel PV calls could have been to alternative coverage thresholds?

Pages 167-168: The rationale for clustering highly divergent sequences at 60% nucleotide identity should be explained. Is this threshold associated with established genus-level classifications in this viral family, or was it chosen empirically?

Pages 167-168: For the 45 sequences lacking nucleotide-level matches, did the authors investigate amino-acid similarity to known PV L1 proteins? Such analyses would help determine whether these sequences represent deeply divergent PVs or potentially more distant viral lineages.

Pages 181-183: The biological interpretation of host-associated PV diversity may depend on library type. Could the authors summarize the proportion of samples originating from field collections, laboratory animals, cell culture systems, or experimental infections?

Pages 243-248: Could the observed geographic and ecological patterns be influenced by laboratory-derived samples? Distinguishing field-collected samples from laboratory, captive, or experimental material would strengthen the ecological interpretations.

Pages 254-261: The biome analyses focus on PV occurrence. An analysis of host composition across biomes would be highly informative and could help disentangle whether observed patterns reflect PV ecology or underlying host distributions.

Page 294: Statements regarding structural similarity appear to rely primarily on visual comparisons. Could the authors provide quantitative structural alignment metrics (e.g., RMSD, TM-score, DALI score, Foldseek score) to support these conclusions?

Page 321-324: Given the scale and curation of the dataset, the final case-study section is limited. Broader comparative analyses of gene content, ORF architecture, and composition related to host associations, phylogenetic relationships, and/or ecological variables could provide additional evolutionary insights beyond a small number of illustrative examples.

Page 333: Given the emphasis on the feasibility of petabase-scale sequence mining, the manuscript would benefit from a more detailed description of the computational resources required. The reported ~10-hour runtime is difficult to interpret without information regarding hardware specifications, CPU-hours, memory requirements, storage footprint, and cloud infrastructure (if used). Such information is important for evaluating the reproducibility and practical applicability of the approach.

Pages 408-409: Were metadata available regarding viral enrichment procedures, particle purification, or size-selection protocols? Such information could influence the interpretation of PV detection frequencies across library types.

Pages 415-416: The differentiation between viral and endogenous viral sequences is one of the biggest challenges in viral metagenomics and large-scale data mining for viral sequences. This issue is particularly relevant because the distinction between exogenous and endogenous viral sequences may directly affect estimates of novel PV diversity and inferred host associations. The manuscript acknowledges that papillomavirus sequences recovered from DNA-based libraries may derive from integrated viral DNA. However, there is no systematic analysis addressing the potential contribution of endogenous papillomavirus elements (EVEs) to the reported diversity estimates. Given the large number of host genome sequencing projects represented in the SRA, some detected PV-like sequences may correspond to integrated or fossil viral sequences rather than exogenous viruses. The authors could discuss this possibility more explicitly and provide analyses evaluating the prevalence of integration signatures, disrupted ORFs, host-genome flanking regions, or other indicators that would help distinguish endogenous viral elements from actively circulating PVs.

Pages 532-533: The study is described as "petabase-scale"; however, the analyses were performed on a pre-assembled and compressed representation of the SRA rather than directly on petabase-scale raw sequencing data. The authors may wish to clarify this distinction and explicitly acknowledge that the computational burden is substantially reduced by the Logan framework and, from this perspective of computational power applied, this study is not in the same context as Serratus and Logan.

Perspective comment: One of the strengths of this study is the generation of a highly curated papillomavirus protein dataset spanning a broad range of known and newly identified PV diversity. Given the increasing importance of structure-based homology detection in virology, the authors may wish to discuss the potential of this resource for future structure-guided discovery efforts. Recent studies have shown that protein structure prediction and comparison can reveal extremely distant evolutionary relationships that are undetectable at the sequence level. The curated PV dataset generated here could serve as a valuable reference for searching unannotated proteins from metagenomic "dark matter" datasets for structural homologs or convergent folds related to papillomavirus proteins. Such approaches may help identify highly divergent PV lineages or previously unrecognized viral proteins that retain structural similarity despite extensive sequence divergence.

Reviewer #2 (Public review):

Tang et al. investigated the contribution of Aldh1a1+ cells, as putative stem/progenitor cells, to endometrial development, maintenance during the estrous cycle, and postpartum repair in mouse models. They employed in vitro organoid formation and in vivo lineage tracing models coupled with RNA-seq to test the stem-ness of Aldh1a1+ cells. They found that mouse endometrial cells with high ALDH activity (using the ALDEFLUOR assay) formed more and larger organoids and were enriched for stem/progenitor cell gene signatures. Similar results were shown using endometrial cells from a human patient sample. Epithelial ALDH1A1 expression was shown to be hormonally regulated, becoming more restricted to the glands, a putative epithelial stem cell niche, under estrogen stimulation. Using lineage-tracing initiated postnatally/prepubertally, Aldh1a1+ epithelial cells were shown to expand, contributing to both the luminal and glandular epithelium into adulthood, whereas adult initiation of labeling showed expansion of stromal Aldh1a1+ cells but not epithelial. Postnatal ablation of single-labeled Aldh1a1+ epithelial cells resulted in impaired gland development. Lastly, Aldh1a1-lineage traced cells (adult labeled) were present during postpartum endometrial repair as were epithelial/mesenchymal transitional cells.

Comments on revised version.

In the revised manuscript, comments have largely been addressed and the manuscript is improved. The authors have tempered their inference of the contribution of ALDH1A1+ cells to endometrial regeneration, but the conclusions are still somewhat overstated. However, the overall work provides valuable insight and strengthens the growing body of literature characterizing endometrial stem/progenitor cells and their function.

Reviewer #2 (Public review):

In the manuscript by Han et al, the authors assess binding of SARS-CoV-2 to heparan sulfate clusters via advanced light microscopy of viral particles. The authors claim that SARS-CoV-2 spike (on the context of pseudovirus and in authentic virus) engages heparan sulfate clusters on the cell surface which then promotes endocytosis and subsequent infection. The finding that HSPGs are important for SARS-CoV-2 entry in some cell types is well described but the authors here attempt to make the claim that HS represents an alternative "receptor" and that HS engagement is far more important than the field appreciates. The data itself appears of appropriate quality and would be of interest to the field, but the overly generalized conclusions lack adequate experimental support. This significantly diminishes enthusiasm for this manuscript as written. Additional controls would be of great benefit.

Further, it is this reviewers opinion that the findings do not represent a novel paradigm as claimed. HS has been well described for SARS-CoV-2 and other viruses to serve as attachment factors to promote initial virus attachment. A more balanced and nuanced view of their interesting data would be of value.

Major:

The authors need to rigorously define a "receptor." This reviewer would argue that a receptor is a host factor that is necessary and sufficient for active promotion of viral entry (genome release into the cytoplasm) while an attachment factor is a host factor that enhances initial viral attachment/endocytosis but is not necessary nor sufficient. The evidence does NOT implicate HS as a receptor under this definition. This is proven in Fig 1 (and elsewhere) in which ACE2 is absolutely required for viral entry.

The authors should genetically perturb HS biosynthesis in their key assays to demonstrate necessity. HS biosynthesis genes have been shown to be important for SARS-CoV-2 entry into some cells but not others (Huh7.5 cells PMID 33306959 but not in Vero cells PMID 33147444, Calu3 cells 35879413, A549 cells 33574281, and others 36597481. This is inconsistent with the claim that HS is broadly important (beyond the BHK cells overexpressing ACE2 that are used here).

Is targeting HS really a compelling anti-viral strategy? The data show a ~5-fold reduction. The strengths and limitations of HS targeting should be presented in a more balanced discussion. Animal data showing anti-viral activity of PIX is warranted. This would enhance this claim and also provide key evidence of a relevant role for HS in a more physiologic model.

The authors provide inadequate discussion into the fact that these studies rely exclusively on cell lines (which also happen to be TMPRSS2 deficient). The role of proteases in the role of HS should be tested in the cell lines and primary cells used as protease expression is a key determinant of the site of fusion.

An alternative method to disrupt HS (other than PIX) is needed in primary airway cells. A genetic approach would be much more convincing. The authors should also demonstrate whether entry in their primary cell assays are TMPRSS2 vs Cathepsin L dependent (using E64d and camostat for instance) as mentioned above.

Each figure legend should clearly state how many independent experiments and replicates per experiment were performed.

All bar plots should show individual dots (i.e. Fig 1G) to better reveal the variance of each dataset.

Reviewer #2 (Public review):

In this manuscript, the authors tackle an important question of why IL-17 production and TH17 responses are lower than expected during Mtb infection. The authors identify an axis of cross-regulation between TH1 and TH17 cells and provide data to support roles for Mtb virulence factors ESX1 and PDIM in promoting TH1 responses and/or suppressing TH17 responses.

Strengths:

The strengths include the significance of the work, the combination of host and Mtb genetic models to dissect the mechanistic basis for regulation of IL-17 production from T cells during infection, and the rigor of the experiments. There are a number of exciting findings from the work, including the cross talk between T cell responses and the impact of ESX1 and PDIM on these responses. It is particularly striking that that IL17a deficient mice partially rescue the attenuation of ESX-1 and PDIM mutants.

Comments on revised version.

The revised manuscript has tempered a lot of the language in the original text to more accurately state (and not overstate) interpretations of the data. The claim that the effect is independent of route of infection seems a little too large of a claim when only two routes were tested (aerosol and intranasal). And although the authors revised the results section to acknowledge the contribution of an IFNg-dependent suppression of IL-17 production from T cells, the abstract has not been updated and still claims that all effects are independent of IFNg.

Reviewer #2 (Public review):

Summary:

In terms of data, the revised manuscript is by and large the same, though the authors added new experiments examining the effects of the Open Field Test (OFT) arena size (Fig. 1 Supplement 1) and sex and mating status (Fig. 6). The authors have also provided textual revisions, partially addressing my previous major criticism about novelty over the work of Mohammad et al., 2016, Curr Biol. They argue that the main advance is the systematic inclusion of Total Walking (TOWA) data (e.g. Introduction, page 6 top in the tracked changes document). While I am still not convinced that the findings represent a huge leap forward over that previous work, the authors' systematic analysis is very nice and may prove of use to those seeking to develop Drosophila as a model for studying emotion primitives.

Strengths:

The main strength of the paper is the rigorous use of several stressful or aversive treatments and their subsequent removal to show that WAFO is a robust proxy for stress-like emotional primitives across multiple stimuli. The pharmacological, molecular, and neuronal activity manipulations, although more limited in scope, lend further credence to the authors' central claim.

Weaknesses:

The authors have addressed some of my previous points with textual revisions and in their rebuttal. As stated above, the conceptual advance over Mohammad et al. remains in my opinion limited, but I appreciate that this point is now clearly discussed in the manuscript.

Reviewer #2 (Public review):

Summary:

The authors aim to determine whether mitochondrial genotype influences telomere length. By generating cybrids harboring different mitochondrial backgrounds, the authors seek to establish a mechanistic link between mitochondrial status and telomere biology.

Strengths:

A major strength of the study is the use of cybrid technology, which provides a great approach to investigate the role of mitochondrial DNA independently of the nuclear genome. The authors also employ multiple complementary assays to assess telomere-related phenotypes associated with mitochondrial dysfunction. Together, these experiments generate an interesting dataset that will be of value to researchers interested in the intersection between mitochondrial biology, genome stability, aging, and development. These results also build on previous work supporting roles for ROS/mitochondria in driving telomere shortening.

Weaknesses:

The data support the conclusion that mitochondrial background is associated with differences in telomere length and telomere-related phenotypes. However, some of the mechanistic interpretations would benefit from additional evidence. In particular, the manuscript discusses mitochondrial influences on telomere shortening, yet telomere length in some experiments is assessed at a single time point. Consequently, the current data do not directly address the rate of telomere attrition. Differences observed between cybrid lines could potentially arise from events occurring during cybrid formation, clonal selection, or subsequent cell expansion. Longitudinal analyses across multiple passages, ideally beginning immediately after cybrid generation and controlling for population doublings, would help establish whether mitochondrial function directly affects telomere shortening dynamics. Some experimental results would also benefit from additional quantification, clarification, and some biological replicates are missing.

Overall, this study provides interesting evidence linking mitochondrial background to telomere biology. The cybrid models represent a useful resource for the field, and the work raises important questions regarding mitochondria-telomere communication.

Reviewer #2 (Public review):

The Unfolded protein response (UPR) and related integrated stress response (ISR) are critical signaling systems for cell survival in response to acute stresses. While the UPR directs critical adaptive gene expression, certain chronic stresses switch this pathway towards cell death and disease. An important question concerns the mechanisms by which the UPR switches from being adaptive to maladaptive. Prevailing models focus on the transcription factor CHOP (DDIT3 or GADD153), whose levels are enhanced via the UPR, and extended/amplified amounts of CHOP are suggested to boost death-related gene expression. However, the literature and this manuscript point out a number of observations that do not neatly fit with this model, suggesting that there are still unresolved processes by which CHOP adjusts cell outcomes via the UPR.

This manuscript features a nice hepatocyte-targeted knockout of CHOP to discern the contribution of CHOP in the transition between adaptive and maladaptive outcomes. The key ideas presented in this study are that CHOP-directed gene expression is focused on protein synthesis, metabolism, and hepatocyte identity. In the progression of the UPR, CHOP expression can lead to resumption of protein synthesis, which can assist in the translation of the UPR-directed transcriptome, which includes ATF6/XBP1-directed genes that aid the processing capacity of the endoplasmic reticulum (ER). However, enhanced nascent protein can further stress the ER. CHOP directs gene expression in both the first phase- acute and second phase-chronic in the UPR, and the pivotal decision lies in the transition between the phases.

Overall, the manuscript includes some new ideas as well as refinements of earlier ones for CHOP-determination of UPR-directed cell fate. The CHOP-hepatocyte knockout mouse model helps to delineate the different tissue functions of CHOP, which has been a problem for some earlier studies. The manuscript progression of experiments is solid, and experimental design and documentation are rigorous. The manuscript text is largely clear, but there are portions that would benefit from fuller explanations of ideas.

There are three points of concern. First, the manuscript model (Figure 7) lays out a timeline for the progression of the UPR between two phases. The study is not always clear about the times assayed, and there appears to be a single time point for measurements. Second, there is emphasis on protein synthesis changes in the model. It is true that the literature argues that resumption of protein synthesis concurrent with stress damage (i.e., GADD34-directed gene expression) is a key reason for the potentially debilitating effects of CHOP (e.g., Marciniak et al 2004, Han et al 2013). However, the manuscript does not feature protein synthesis measurements. Inclusion of bulk protein synthesis measurements in the context of this model system would strengthen the study and support for the model. Finally, for this reviewer, some of the most interesting ideas center on CHOP-directed transcription of genes that regulate hepatocyte identity. There is solid evidence for direct CHOP regulation of these genes, but the manuscript does not really develop and test the ramifications of these networks on cell fate during ER stress.

Reviewer Concerns:

(1) The abstract packs in a lot of information. The ideas would not be clear to a general reader. Furthermore, the UPR and ISR are referred to in the second-to-last sentence, but not defined earlier in the abstract.

(2) There are some typos/grammar concerns.

(3) ATF4 diminished with CHOP-depletion (Figure S2A). What is the mechanism here? Does this complicate the analysis of CHOP-directed gene expression? How does this fit with Figure 6J? The timelines for TM treatment are critical. The authors should more fully explain the time courses in the experiments.

(4) Figures 2 and 3: There is a discussion on enhanced protein synthesis with loss of CHOP (reduced GADD34 expression). What is the time point - 8 hours TM? Emphasize, explain, and justify time points of experiments here and in later panels. It would strengthen the model with direct measurements of protein synthesis. The authors could include GADD34 protein measurements in these panels. Figure 3 - panel D - some abbreviations are not standard.

(5) Figure 4: One of the most interesting in the manuscript is the transcription factors downstream of CHOP that are linked with hepatocyte differentiation and metabolism. The manuscript would be bolstered by developing some of these target genes into the Figure 7 transition model.

(6) Figure 6: The comparison of CHOP and ATF6 target genes is a highlight of the manuscript. The literature on this topic is complex, and there are some suggestions that CHOP can be downstream of ATF6. Furthermore, there were some earlier models by Walter and others about extended induction of Perk (death) vs induction of other UPR sensors (survival) (e.g. PMID: 17991856). It would be helpful in the Discussion to delineate between these models and their critical differences.

Reviewer #2 (Public review):

Summary:

This technically sophisticated study combines behavioral analysis, voltage imaging, electrophysiology, and a newly developed cell-specific optogenetic voltage clamp (cOVC) approach to investigate gap-junction (GJ)-mediated coupling in C. elegans body-wall muscle cells. The work explores the coordination of muscle cells and systems physiology and introduces a method with potential utility beyond the nematode system studied.

Strengths:

The main strength of the work is the development and application of the cOVC method. This approach enables minimally invasive in vivo assessment of cell-to-cell electrical coupling in intact animals. This technique represents a meaningful advance over traditional electrophysiological techniques that require dissection or cell isolation.

With respect to the GJ biology and function, the authors support their conclusions by integrating additional independent experimental approaches. Findings from behavioural/locomotion assays, voltage imaging, patch-clamp recordings, and cOVC measurements are generally consistent, particularly for unc-9 mutants, which show reduced synchronization of muscle cells, impaired electrical coupling, and severe locomotor defects.

The gain-of-function experiment using murine Cx36 suggests that more or less electrical coupling can disrupt (normal) locomotion.

Weaknesses:

The main issue of this otherwise excellent manuscript relates to interpretation rather than experimental quality. Throughout the manuscript, increased correlation is often interpreted as evidence of increased electrical coupling. Are correlation, synchrony, and conductance equivalent measures? If not, how would this affect these correlations? Furthermore, could broader action potentials and altered excitability also increase correlation values? This concern could be addressed through a discussion of this limitation.

Similarly, the proposed mechanism that reduced GJ coupling increases excitability through reduced leak currents is plausible but not directly demonstrated. Are alternative explanations, e.g., compensatory changes in ion-channel expression or gap-junction composition, possible? These could also be considered to improve the balance of this work.

The conclusions regarding Cx36 overexpression would also benefit from more cautious wording, as developmental or localization effects have not been excluded.

However, the experimental dataset is very strong. In my opinion, no major additional studies are needed. Direct analysis of compensatory changes in innexin expression or localization could strengthen the interpretation of the proposed mechanism. Overall, the study is of high technical quality, contains a notable methodological advance, and provides important insights into muscle synchronization and GJ biology.

Reviewer #2 (Public review):

Summary:

This study made selective lesions in motor cortical subregions and the magnocellular red nucleus in nine macaque monkeys, and evaluated reaching and grasping movements using maximum speed and trajectory variability. The results suggest that damage to the posterior old primary motor cortex (M1) was mainly associated with reduced maximum speed, whereas damage to the new M1 was mainly associated with increased trajectory variability. Damage to the anterior old M1 did not clearly add further impairment. Lesions of the magnocellular red nucleus (RNm) alone mainly reduced reaching speed, but recovery after subsequent cortical lesions was worse than after cortical lesions alone, suggesting that the rubrospinal pathway may be important for compensation after cortical damage in monkeys. Overall, this is a valuable study that examines differences among M1 subregions using selective lesions in macaques.

Strengths:

(1) This study tackles an important question. It attempts to decompose the diverse upper-limb impairments after stroke into the effects of different primary motor cortex subregions.

(2) Another strength is that the lesions and behavioral impairments were evaluated quantitatively. The use of nine macaque monkeys with different lesion patterns, together with quantitative behavioral evaluation, provides a rare and valuable dataset. The authors also followed recovery using quantitative behavioral measures such as maximum speed and trajectory variability.

(3) The inclusion of RNm lesions is also valuable, as it revisits the classic question raised by Lawrence and Kuypers (1968) of how brainstem descending pathways contribute to recovery after cortical motor damage.

Weaknesses:

(1) The main limitation is that the contribution of each cortical lesion is sometimes interpreted from largely qualitative comparisons. Because the lesion extent was not always limited to the intended region, it is difficult to fully separate the independent contribution of each subregion. Some conclusions are also based on comparisons between a small number of animals. The dataset itself is valuable, and the manuscript would be strengthened by presenting these conclusions more cautiously and explicitly acknowledging this limitation.

(2) Because the behavioral evaluation is quantitative, it would be helpful to show the relationship between lesion size and behavioral impairment more quantitatively. For example, rank correlations between the lesion size of each cortical region and behavioral measures could help readers evaluate whether the type and size of lesion are related to behavioral impairment.

(3) The discussion of area 4s could be further developed. The authors suggest that this region may have a different role, but the specific hypothesis is not fully clear. There has also been skepticism in the previous literature about area 4s, for example, Meyers et al. (1954), and this broader background could be discussed. (Meyers R, Knott JR, Skultety FM, Imler R (1954) On the Question as to the Existence of a "4s" Suppressor Mechanism. Journal of Neurosurgery 11:7-23.)

Reviewer #2 (Public review):

Summary:

In this study, Li et al. investigated the relationships among regional cortical tracer dynamics following intrathecal gadolinium administration, neural activity, and amyloid-β deposition in humans. Using serial MRI acquisitions after intrathecal gadodiamide administration in 96 participants, the authors characterized regional signal enhancement and clearance patterns across the human cortex. They integrated these imaging measures with transcriptomic data (Allen Human Brain Atlas), resting-state fMRI outcomes, and an external amyloid PET dataset. The authors report that regions with more efficient tracer clearance are enriched for genes related to synaptic organization and neuronal cell types, that tracer clearance patterns are in parts spatially coupled to spontaneous neural activity, and that regional mismatch between neural activity and tracer clearance is associated with increased amyloid burden according to the PET dataset.

Strengths:

The study addresses an important and very timely question about the interaction among neural activity, cerebrospinal fluid dynamics (waste clearance), and regional vulnerability to neurodegeneration. Integrating serial post-contrast MRI, transcriptomics, resting-state fMRI, and amyloid imaging is ambitious and conceptually very interesting. The spatial characterization of cortical tracer dynamics is potentially valuable for the field, particularly given the increasing interest in human glymphatic imaging approaches and intrathecal contrast MRI, which provides an opportunity to assess CSF tracer dynamics without confounding tracer signal from the blood. The imaging preprocessing pipeline includes normalization of regional cortical signal intensity to a reference region within each session before calculation of longitudinal percentage change, which helps reduce inter-session variability within individuals for conventional T1-weighted imaging. The transcriptomic analyses linking tracer dynamics to neuronal and synaptic gene expression patterns are also interesting. In addition, the manuscript addresses recent literature on neurovascular coupling, glymphatic function, and amyloid vulnerability.

Weaknesses:

Several issues limit the strength of the conclusions. One concern relates to the interpretation of repeated post-intrathecal contrast MRI measurements as direct indicators of glymphatic influx and clearance. The approach presented by the authors measures regional signal changes following intrathecal gadodiamide administration, but does not directly visualize paravascular flow or establish that the observed signal dynamics specifically reflect glymphatic transport mechanisms. Although it is widely accepted that CSF influx occurs primarily along periarterial spaces as part of the glymphatic system, and the terminology "glymphatic MRI" is increasingly used in the literature, the physiological processes contributing to delayed parenchymal enhancement, including CSF-interstitial exchange mediated by convective bulk flow and/or extracellular diffusion, as well as transient and, in the case of linear gadolinium agents, even long-term tracer retention remain incompletely resolved. Importantly, tracer kinetics may not directly reflect interstitial fluid kinetics, as solute transport may also be influenced by compartmental and extracellular barriers, diffusion constraints, and tissue retention effects. As currently written, several sections of the manuscript appear to overstate what can be directly inferred from the imaging data. This issue may be particularly relevant given the intrathecal use of gadodiamide (Omniscan), a linear gadolinium-based contrast agent with known long-lasting tissue retention due to lower kinetic stability compared to macrocyclic agents. Sustained signal at later imaging time points may therefore not only reflect impaired glymphatic clearance dynamics may also be influenced by tissue retention of contrast material, particularly in the context of neurological disease. In addition, the participant cohort is heterogeneous and includes individuals with neuroinflammatory and neurodegenerative diseases, peripheral neuropathy, and motor neuron disease. Although the authors argue that the spatial tracer patterns are relatively preserved across neurodegenerative groups, this heterogeneity complicates interpretation of imaging data and raises the possibility that disease-related factors and altered tracer-tissue interactions contribute to the observed effects. Thus, the rationale for interpreting a greater tracer signal at 39h as evidence of impaired glymphatic clearance should be explained more carefully, particularly given the highly heterogeneous patient population.

In addition, the analyses linking spontaneous neural activity and tracer clearance are based on a very small rs-fMRI subgroup (n = 15), limiting the generalizability. The interpretation of the "mismatch" analysis also requires caution. The mismatch index was computed from z-scored fALFF and tracer clearance and is subsequently associated with amyloid burden derived from the external PET dataset rather than from the studied participants themselves. Therefore, the observed spatial associations should be interpreted with greater caution rather than as evidence for a direct mechanistic relationship. The cross-sectional nature of the analyses also limits conclusions regarding the directionality and temporal sequence of the relationships between neural activity, tracer dynamics, and amyloid burden. Several statements in the Discussion currently imply stronger causal or biological conclusions than are directly supported by the data.

Despite these limitations, the study presents an interesting dataset and proposes a framework for understanding regional vulnerability to protein accumulation in neurodegeneration. This work hopefully motivates further investigation into the important relationships among neural activity, CSF dynamics, and neurodegeneration in humans.

Reviewer #2 (Public Review):

The authors present the OpenApePose database constituting a collection of over 70000 ape images which will be important for many applications within primatology and the behavioural sciences. The authors have also rigorously tested the utility of this database in comparison to available Pose image databases for monkeys and humans to clearly demonstrate its solid potential. However, the variation in the database with regards to individuals, background, source/setting is not clearly articulated and would be beneficial information for those wishing to make use of this resource in the future. At present, there is also a lack of clarity as to how this image database can be extrapolated to aid video data analyses which would be highly beneficial as well.

I have two major concerns with regard to the manuscript as it currently stands which I think if addressed would aid the clarity and utility of this database for readers.

(1) Human annotators are mentioned as doing the 16 landmarks manually for all images but there is no assessment of inter-observer reliability or the such. I think something to this end is currently missing, along with how many annotators there were. This will be essential for others to know who may want to use this database in the future.

Relevant to this comment, in your description of the database, a table or such could be included, providing the number of images from each source/setting per species and/or number of individuals. Something to give a brief overview of the variation beyond species. (subspecies would also be of benefit for example).

(2) You mention around line 195 that you used a specific function for splitting up the dataset into training, validation, and test but there is no information given as to whether this was simply random or if an attempt to balance across species, individuals, background/source was made. I would actually think that a balanced approach would be more appropriate/useful here so whether or not this was done, and the reasoning behind that must be justified.

This is especially relevant given that in one test you report balancing across species (for the sample size subsampling procedure).

And another perhaps major concern that I think should also be addressed somewhere is the fact that this is an image database tested on images while the abstract and manuscript mention the importance of pose estimation for video datasets, yet the current manuscript does not provide any clear test of video datasets nor engage with the practicalities associated with using this image-based database for applications to video datasets. Somewhere this needs to be added to clarify its practical utility.

Reviewer #2 (Public review):

Summary:

In this study, the authors investigate how cytosolic acetyl-CoA metabolism influences replicative aging in budding yeast. They propose that acetyl-CoA regulates aging through three major pathways: (1) mitochondrial transport to support mitochondrial function, (2) fatty acid synthesis, and (3) global protein acetylation. The data show that AMPK activation promotes mitochondrial import of acetyl-CoA and partially mitigates mitochondrial decline in a subset of aging cells. Furthermore, the engineered A2A strain, which enhances mitochondrial acetyl-CoA utilization while relieving inhibition of fatty acid synthesis, increases the proportion of cells exhibiting a "low senescence" phenotype.

Overall, this is a thoughtful and potentially impactful study that advances our understanding of metabolic control of aging. Addressing the points below, particularly by refining interpretations and, where feasible, incorporating additional analyses, will further strengthen the manuscript and its conclusions.

Strengths:

The study has several notable strengths. It addresses an important question by shifting the focus from lifespan to preservation of late-life fitness, which is highly relevant to aging biology. The work integrates metabolic, genetic, and functional analyses to link cytosolic acetyl-CoA flux with distinct aging outcomes, and the engineering of the A2A strain provides a clear and elegant demonstration of how coordinated pathway modulation can improve cellular fitness.

Comments on revised version.

I am fine with the revisions.

Reviewer #2 (Public review):

Summary:

This study by Guy and Bird and colleagues is a natural follow-up to their 2018 Human Molecular Genetics paper, further clarifying the molecular basis of C-terminal deletions (CTDs) in MECP2 and how they contribute to Rett syndrome. The authors combine human genetic data with well-designed experiments in embryonic stem cells, differentiated neurons, and knock-in mice to explain why some CTD mutations are disease-causing while others are harmless. They show that pathogenic mutations create a specific amino acid motif at the C-terminus, where +2 frameshifts produce a PPX ending that greatly reduces MeCP2 protein levels (likely due to translational stalling) whereas +1 frameshifts generating SPRTX endings are well tolerated.

Strengths:

This is a comprehensive and rigorous study that convincingly pinpoints the molecular mechanism behind CTD pathogenicity, with strong agreement between the cell-based and animal data. The authors also provide a proof of principle that modifying the PPX termination codon can restore MeCP2-CTD protein levels and rescue symptoms in mice. In addition, they demonstrate that adenine base editing can correct this defect in cultured cells and increase MeCP2-CTD protein levels. Overall, this is a well-executed study that provides important mechanistic and translational insight into a clinically important class of MECP2 mutations.

Weaknesses:

The adenine base editing to change the termination codon is shown feasible in generated cell lines, but yet to be shown in vivo in animal models.

Comments on revised version.

The authors have addressed all of my questions and comments.

Reviewer #2 (Public review):

Summary:

In this manuscript, Noirot-Gros and coworkers investigated the network of c-di-GMP associated protein complexes in Pseudomonas fluorescens. They did so by using a genome-wide yeast two-hybrid screen, and that was further probed by phenotypic screening that focused on biofilm and motility phenotypes. From this network map, they discovered that the phosphodiesterase DipA interacts with the GGDEF domains of many c-di-GMP-binding proteins.

Strengths:

(1) Broadness of screen led to identification of new interactions: The genome-wide yeast two-hybrid screening approach permitted broad investigation of c-di-GMP-associated protein-protein interactions. These interactions included some previously validated interactions as well as newly discovered interactions.

(2) Complementary experimental validation: The proposed network was experimentally validated, including by using a CRISPRi-based approach in which the expression of genes encoding proteins identified in the network was systematically suppressed, and then the impact on the biofilm and motility phenotypes was assessed.

Weaknesses:

The findings would have been strengthened by further biochemical analysis, but this is likely beyond the scope of the paper.

Reviewer #2 (Public review):

Summary:

In this manuscript, Hall et al. present a rigorous and comprehensive multi-omic comparative analysis investigating how host-adapted and non-host-adapted mycobacteria reconfigure the bovine host immune response. By utilizing RNA-seq, ATAC-seq, and ChIP-seq across four histone marks (H3K4me3, H3K4me1, H3K27ac, and H3K27me3) plus CTCF binding, the authors track the regulatory dynamics of primary bovine alveolar macrophages (bAM) challenged with Mycobacterium bovis (MBO), Mycobacterium tuberculosis (MTU), M. bovis BCG, and gamma-irradiated (killed) M. bovis (IRR).

The study highlights a profound, pathogen-driven epigenomic reprogramming that is largely unique to the host-adapted virulent pathogen (M. bovis). Crucially, the authors integrate these regulatory networks with existing Holstein-Friesian GWAS datasets to prioritize novel candidate genes (ERBB4, LRCH1, MRTFA, and RNPC3) associated with M. bovis infection susceptibility. This work represents a significant advancement in our understanding of host-pathogen interactions and animal resilience to bovine tuberculosis (bTB).

Strengths:

(1) The manuscript addresses a major socioeconomic problem in global livestock agriculture and human zoonotic health. By profiling host-adapted vs. non-host-adapted and live vs. dead bacilli, it provides fundamental insights into mycobacterial virulence mechanisms and evolutionary adaptation.

(2) The multi-omic approach is robustly executed, and the sample size (n=6 for RNA-seq, n=3 for ChIP/ATAC-seq subgroups) is highly appropriate for primary livestock cell cultures.

(3) The inclusion of live virulent, live attenuated, non-host-adapted, and killed strains allows the authors to dissect whether host responses are driven by passive PAMP recognition or active, pathogen-directed virulence factors.

(4) The parallel mapping of four distinct histone marks alongside chromatin accessibility mapping (ATAC-seq) yields a highly refined picture of enhancer and promoter dynamics.

Weaknesses:

(1) The profound transcriptional response of the gamma-irradiated (IRR) M. bovis group (3,320 DEGs vs. 2,312 for MTU) is intriguing but lacks a deep biochemical and functional explanation.

(2) While the paper provides a clear atlas of epigenetic alterations, the underlying mycobacterial effectors driving these specific chromatin alterations remain largely correlative.

Reviewer #2 (Public review):

Summary:

In this manuscript, Sun and colleagues use precision fMRI to investigate the spatial patterns of verbal versus nonverbal processing in the cortex. They first show that the left hemisphere tends to be more active for word than face processing, whereas the right hemisphere tends to be more active for face than word processing during a working memory task. They then show that this is not confined to a particular network specialized for verbal vs. nonverbal processing but is a pan-network hemispheric difference across 8/9 association networks. This was unexpected, as prior precision imaging work emphasized network specialization and the authors had hypothesized that verbal vs. nonverbal processing would show bilateral network-level effects in a single, right-lateralized network (FPN-B). They then replicated this pan-network effect in an independent dataset.

Strengths:

(1) This paper is neat, clear, and succinct. The authors convincingly show that there exists a hemispheric difference in face vs. word processing during a working memory paradigm across many association networks.

(2) They replicate this result in a fully independent dataset. They do a particularly nice job setting up a prospective replication analysis over 4 distinct association networks.

(3) They do a wonderful job framing the experiment - they provide context on how previous precision imaging findings would have suggested a specialized network for verbal vs. nonverbal processing, they replicate major findings from that work in this data (network laterality and bilateral network activation in multiple task contexts), and then show the surprising pan-network hemispheric laterality in two independent datasets.

(4) This paper adds a unique perspective to precision imaging findings. Most precision imaging has shown that different networks seem to be specialized for different cognitive tasks - individual task activations tend to follow network boundaries and networks tend to be cohesively activated. These types of findings led to the idea that previously reported broad hemispheric effects for verbal vs. nonverbal processing could instead be due to a lateralized network specialized for verbal versus nonverbal processing. However, this paper accounts for individualized network topography and yet finds a hemispheric effect that transcends individual networks. I think this result will have a strong influence on how many readers think about network specialization.

Weaknesses:

(1) The evidence for the main result comes only from a single fMRI task (n-back) with a particular set of stimuli (faces, words) in which processing demands are not matched across verbal and nonverbal conditions (word blocks use rhyming, face blocks use an exact match). While the claim made is fairly broad (hemispheric laterality in verbal vs. nonverbal processing), it isn't clear how well this finding would generalize to other types of stimuli or processing. This was mentioned in the limitations section, but the paper would be strengthened by both additional evidence for a general verbal versus nonverbal processing effect and by a discussion of how these specific stimuli (words and faces) and processing demands (differences between rhyming and exact match) might affect the results. The authors did include supplemental post-hoc analyses of scene and letter conditions that are matched in processing, but did not discuss them in the main text.

(2) While lateralization is seen in 8/9 networks, the effect is much larger in some networks (FP-A, DATN-A) versus others. Similarly, the face > word effect is much stronger in some regions of the cortex than others. For example, all the individuals shown exhibit a patch of RH mid-LPFC cortex with particularly strong face > word preference compared to anywhere else in association cortex and an analogous LH mid-LPFC region that shows a particularly strong word > face preference. While the authors are correct that lateralization is seen across many networks, there does seem to be a topography to it rather than a diffuse hemispheric difference. I wonder to what degree the general hemispheric laterality pattern could be driven by a subset of regions that happen to cross several association networks. Neither the differences between networks nor the finer-scale activation patterns are considered in this paper. The paper would be strengthened by considering them.

(3) The paper is focused on association networks and provides an interesting report on face versus word processing in those networks specifically. In the brain maps, it is possible to see face versus word preference in non-association regions as well. The authors don't discuss these patterns, but the paper would be strengthened by describing the relationship of these patterns with known face and language processing systems in the sensory cortex.

Reviewer #2 (Public review):

Summary:

Murrell and colleagues examine sex differences in mouse decision-making tasks, using the FED3 device, which allows for continuous data collection in the home-cage. Mice performed four tasks across two weeks, which provided all of their food. Across tasks, male mice were more likely to repeat a rewarded choice than females, which benefits decision accuracy in deterministic tasks. This work complements existing results for decision-making differences in males and females, affirming that this domain of cognition is particularly sensitive to sex differences. However, there are some specific features of the FED3 device, such as single housing, closed economy feeding, and 24-hour access that can uniquely influence decision-making in a (likely) sex-dependent manner that encourage considering these data as examining sex differences in a particular context, rather than as a generalized finding. At the same time, these data could offer new insights about nuances of behavior like circadian rhythms or bout analysis, uniquely enabled by the extended availability of the FED3 devices. The analyses in this paper also make an important point, encouraging researchers to use methods that allow for much larger N's to provide clearer and more robust results.

The FED3 devices are an innovative new way to approach behavior, and have allowed the authors to test many dozens of mice in a battery of tasks, over which they see similar patterns of increased win-stay behavior in male C57b6 mice (wildtypes from several knockout lines). The authors point out that there are discrepancies in prior literature across tasks and species in terms of how sex differences influence decision making, but there are some particular ways that sex differences could interact with the FED3 devices that it would be interesting and important to consider further. In particular, the fact that the animals live with the device, singly housed, may be an underrecognized contributor to sex differences. Changes in social interaction and dominance arising from long-term single housing are very likely to impact males and females differently, for example.

Continuous data collection is a fascinating way to look at learning and decision-making, but it also raises interesting questions about whether these dynamics are impacted as a function of continuous access to the device. In addition to summary metrics over the whole task, it might be valuable to look at learning across the task each day, and within circadian periods of each day. For example, it seems based on the example sessions for the 100-0 bandit task that animals take at least a few reversals to learn the task structure. How many trials does it take for a male or female mouse to reach some criteria of success? Do the sex differences exist at all time points? Does the light cycle affect the accuracy or trial counts? There are numerous such analyses that could particularly inform future use of the FEDs across laboratories, and identification of similar or distinct patterns of sex differences or behavior in other apparatuses, and would be a benefit to the field.

The authors employed several computational techniques to identify parameters or features of behavior that might explain the sex differences they observed, and this is a strength of the manuscript. However, the win-stay lose-shift agent may not be an ideal match to make conclusions about exploitation, as it is unclear how win-stay and lose-shift strategies map onto explore/exploit tradeoffs. If an animal were exploiting an option, they may win-stay *and* lose-stay, if the task is probabilistic. Indeed, the model fit is weaker for the 80-20 bandit, suggesting this model may not reflect the actual strategies mice are engaging in, potentially in both bandit tasks. This point is particularly worth considering in light of the criteria for shifts in the tasks being based not on the number of trials completed, but on the number of pellets earned. When shifts are tied to reward collection rather than trials, it can amplify differences in behavior driven by reward consumption.

Reviewer #2 (Public review):

Summary:

The authors investigate how salt gradients influence the transport of Pseudomonas putida in confined microfluidic environments. They report that salt gradients enhance directional migration, increase run persistence, and promote transport toward contaminant-rich regions. To explain these observations, the authors propose a physical steering mechanism in which differential diffusiophoretic mobilities of the cell body and flagellar bundle generate an aligning torque that reorients cells along the salt gradient.

Strengths:

The study addresses an interesting question at the interface of microbiology, complex fluids, and active matter. Their experiments suggest that salt gradients influence bacterial transport behavior and lead to more persistent, directional motion. Once confirmed, the proposed mechanism would broaden our understanding of how environmental gradients can shape microbial migration through physical interactions in addition to more traditional sensing-based pathways.

Weaknesses:

The main limitation of the current study is that the proposed steering mechanism is not directly demonstrated. The evidence for the diffusiophoretic torque is largely inferred from trajectory statistics and theoretical modeling. While the observed transport behavior is convincing, the causal link between the observed migration patterns and the proposed reorientation mechanism remains less well established. In particular, the manuscript focuses primarily on cell trajectories and transport properties, whereas the proposed mechanism fundamentally involves changes in cell orientation. Additional evidence connecting orientation dynamics to the proposed torque mechanism would strengthen the conclusions.

A related concern is whether alternative physical mechanisms associated with the imposed salt gradients have been fully excluded. For example, weak flow-mediated effects or other hydrodynamic influences could potentially contribute to the observed transport behavior. The manuscript would benefit from a more thorough discussion of such possibilities and a clearer justification for why the proposed diffusiophoretic mechanism should be regarded as the dominant explanation.

The manuscript would also benefit from a clearer positioning within the broader literature on physically induced microbial transport and swimmer reorientation. Previous studies have demonstrated directed migration arising from rheotaxis (Marcos et al., 2012, PNAS) and viscosity-gradient-induced steering (Stehnach et al., 2021, Nature Physics). While the mechanism proposed here appears distinct, a more explicit discussion of how the present work relates to these earlier studies would help readers better understand the specific conceptual advance being made.

Reviewer #2 (Public review):

This is an interesting study aiming to capture the fundamental principles of ATPase-like machines with an elementary model of rigid bars. While molecular motors have been the subject of many studies in statistical physics, taking very simplified approaches, these past studies generally abstract away from geometrical constraints and do not account for allosteric mechanisms. In turn, several simple physical models of allostery are now available, but most consider only long-range effects without reference to reactivity or the conversion of chemical to mechanical energy. The essential ingredient of the present model is a form of negative allostery that stems from geometrical constraints. These constraints impose the presence of hidden microstates and the connections between states that form a reaction network. Nontrivial tradeoffs can then be derived, e.g., on the catalytic rate.

One limitation of the approach is that energetic constraints, which are equally important, are not themselves derived from physical principles. This includes the different kinetic rates, the binding constants, and the mechanisms of reactivity, even though, in principle, they should follow from basic interaction energies in the context of thermal fluctuations. This is a legitimate choice of modeling level, handled notably by imposing a hierarchy between rates. It would be appreciated, however, if the overall logic of the derivation were clarified, presenting more clearly from the beginning what the fundamental hypotheses of the model are, which aspects are derived from these hypotheses, and which require additional assumptions. It seems indeed that the model involves both fundamental physical assumptions that are used to derive some emerging kinetic features (e.g., geometry imposes futile cycles) and global kinetic assumptions that are used to derive some microscopic features (e.g., a productive cycle imposes the relative values of the kinetic rates).

The conclusion ends with a proposal to generalize to more elaborate models. I was wondering, however, if the opposite would not be desirable. The current model is already quite involved (as the 7 pages of SI listing transitions between states testify). Wouldn't it be possible to obtain some of the main results, e.g., the trade-offs defining an optimal cleavage rate, from an even simpler model?

Reviewer #2 (Public review):

Summary:

The authors evaluate whether commonly used LLMs (ChatGPT, Claude and Gemini) can reconstruct signalling networks and predict effects of network perturbations, and propose a pipeline for benchmarking future models. Across three phenotypes (hypertrophy, fibroblast signalling, and mechanosignalling), LLMs capture upstream ligand-receptor interactions and conserved crosstalk but fail to recover downstream transcriptional programmes. Logic-based simulations show that LLM-derived networks underperform compared to manually curated models. The authors also propose that their pipeline can be used for benchmarking future models aimed at reconstructing signalling networks.

Strengths:

The authors compare the outcomes from three LLMs with three manually curated and validated models. Additionally, they have investigated gene network reconstruction in the context of three distinct phenotypes. Using logic-based modelling, the authors assessed how LLM-derived networks predict perturbation effects, providing functional validation beyond network overlap.

Weaknesses:

The authors have used legacy models for all three LLMs, and the study would benefit from testing the current versions of the LLMs (ChatGPT 5.2, Claude 4.5 and Gemini 2.5). Additional metrics such as node coverage, node invention, direction accuracy and sign accuracy would be useful to make robust comparisons across models.

Reviewer #2 (Public review):

In their manuscript entitled 'ATP-driven conformational dynamics reveal hidden intermediates in a heterodimeric ABC transporter', Pečak et al. use elegant single-molecule FRET experiments in detergent to investigate the heterodimeric ABC transporter TmrAB. By combining simulations of the transporter's accessible volume with elegant trapping strategies, the authors identify an unresolved outward-facing open state and conclude that it is usually obscured by a rapidly interconverting ATP-bound ensemble. Overall, the study demonstrates that smFRET can resolve the short-lived intermediate states of TmrAB and potentially other ABC transporters that are obscured in ensemble measurements.

It is a very interesting study that highlights the power of combining high-resolution structural information with spectroscopic approaches. I had three major concerns with the original version, all of which have been addressed by the authors in this revised version.

Reviewer #2 (Public review):

Summary:

This very ambitious project addresses one of the core questions in visual processing related to the underlying anatomical and functional architecture. Using a large sample of rare and high-quality EEG recordings in humans, the authors assess whether face-selectivity is organised along a posterior-anterior gradient, with selectivity and timing increasing from posterior to anterior regions. The evidence suggests that it is the case for selectivity, but the data are more mixed about the temporal organisation, which the authors use to conclude that the classic temporal hierarchy described in textbooks might be questioned, at least when it comes to face processing.

Strengths:

A huge amount of work went into collecting this highly valuable dataset of rare intracranial EEG recordings in humans. The work is worth publishing for the data alone, assuming they are shared in an easily accessible and documented format. Currently, the OSF repository linked in the article is empty, so no assessment of the data can be made. The topic is important and a key question in the field is addressed. The EEG methodology is strong, relying on a well-established and high SNR SSVEP method. The method is particularly well suited to clinical populations, leading to interpretable data in a few minutes of recordings. The authors have attempted to quantify the data in many different ways, and provided various estimates of selectivity and timing, with matching measures of uncertainty. Non-parametric confidence intervals and comparisons are provided, using resampling that preserve dependencies in a hierarchical manner, which is rare. Two types of analyses are also provided to support evidence in favour of the lack of practical significance for some of the comparisons. Collectively, the various analyses and rich illustrations provide convincing evidence in favour of the conclusions.

Comments on revised version:

The authors have addressed all my previous comments and the work is mostly limited by the lack of pre-registration and the exploratory nature of some of the analyses. However, with data and code available, other teams can assess the impact of researchers' degrees of freedom on the main outcomes.

Reviewer #2 (Public review):

Summary:

The authors analyzed PopART data to better characterize the age and sex specific transmission dynamics in Zambia with a goal of allocation of resources.

Strengths:

Important analysis to hone in on key driver of HIV transmission in Zambia, which hopefully can be used to tune prevention efforts to maximize effect while limiting required resources. Two analytic approaches used, and while the phylogenetic data was markedly more limited, it mirrored the simulated epidemic. The authors did a nice job reviewing the limitations of the data and the analyses and providing analyses to support their goals and hypothesis, and this work may have more impact now that resources in SSA for HIV prevention and treatment may become more scarce.

Comments on revised version.

The revised manuscript clarifies the impact and utility of this work and better allows the comparability of the two methods. Highlighting the differences (or lack thereof) between the undiagnosed and diagnosed population) simplifies the public health approach.

Reviewer #2 (Public review):

Summary:

In this manuscript, Yu et al seek to develop a Drosophila genetic tool to simultaneously co-express up to 12 transgenes. They leverage the native Dscam exon 4 alternative splicing to generate a UAS to enable cell- and temporal-specific expression of transgenes. This tool is called the poly-transgene expression system (PXGS). Previous approaches to co-express transgenes have been limited to four to five genes, so PXGS would be a significant advancement, especially when examining processes that require robust expression of many genes to confer function. The authors showed that PXGS can drive expression of multiple (1) fluorescent reporters and (2) cell surface receptors in different cell types (neurons, glia, and muscles). However, there are major proof-of-principle experiments missing to demonstrate the utility of PXGS and its potential limitations. Additionally, some of the data is just not interpretable, and experimental rigor is significantly lacking.

Strengths:

Developing a genetic tool to co-express transgenes beyond what is currently available would be significant.

Weaknesses:

(1) While the authors stated that each PXGS construct can express 12 transgenes, this was not directly tested - the largest number of genes tested was in the PXGS_fluorophores, which has 4 genes inserted in 10 alternates (and therefore it can be determined if genes from all the alternates are spliced in at a meaningful level).

a. First, the authors state that they tested the expression of the fluorophores in S2 cells using RT-PCR before generating the fly line. However, this data is not shown. Also, it is possible to test expression and localization of UAS transgenes in S2 cells with a ubiquitous GAL4, similar to what they did for GFP expression in Supplemental Figure 1.

b. In the corresponding figure for this experiment (Figure 2), there are some concerning expression patterns and potential channel bleed-through/crosstalk. The nSyb-Gal4 is a pan-neuronal driver, yet expression of three fluorophores was extremely minimal. This could potentially be explained by the deterministic vs random alternative splicing. However, it is more concerning that in the GFP, RFP, and iRFP channels, the exact same tiny cluster of neurons is observed, suggesting potential bleed-through of the channels. Appropriate controls are required, including expression of a traditional fluorescent reporter with the nSyb-Gal4 they are using. And replicates would help with the experimental rigor.

c. Additionally, it would be helpful to know if genes inserted at each alternate exon are expressed at a similar efficiency (vs. some alternate exons have higher levels of expression)

(2) PXGS expression in non-neuronal cells: The authors attempt to show that fluorophores targeted to different cellular compartments can be expressed in neurons and non-neuronal cells (glia and ubiquitously).

a. In Supplemental Figure 2A, they first use S2 cells to confirm expression, which does confirm. However, they use no markers to show that the fluorophores localize to the corresponding compartments (e.g., mitochondria and nucleus). In Supplementary Figure 2B, with that magnification and resolution, it is impossible to determine if the fluorophores localize properly.

b. In Figure 3, it is impossible to know if there is any glial expression based on those images. They state that "subcellular localization of fluorophores was observed in the flight muscle", but again, that cannot be concluded from the images. Also, the schematic of the construct is the same one used in Supplementary Figure 2. Why show it again?

(3) In the functional expression of PXGS transgenes section, while the authors used RT-PCR to show that each receptor gene is transcribed in S2 cells, it was not tested if they are correctly expressed, translated, and localized in the fly. The functional outcome observed (Figure 4 b-c) could be the result of misexpression of one or multiple genes.

a. Supp Figure 3: Why does the Sli lane have so many bands?

b. Why were these genes chosen for misexpression? Is there any evidence that they are required for the wiring of the mechanosensory neuron? Does the co-expression lead to an additive effect?

c. The RT-PCR result (Supplemental Figure 3) showed variations (e.g., kek and kir being significantly dimmer than tutl; multiple products for Sli). Is there any explanation behind this, and could this be the outcome of some alternate exons being more efficiently spliced than others?

d. Figure 4: These images seem to be taken with a widefield scope and only one plane. Is it possible that some of the pSC neurons are in a different Z plane, and they are not being captured here? There definitely is part of the axon terminal out of focus in some of the images. Also, most of the figure graph axes (e.g., 4b) are extremely difficult to read. And the figure overall is not easy to interpret.

(4) Supplemental Figure 5: This figure is quickly mentioned in the Discussion without much explanation. First, this must be in the Results section since it is an experiment. Second, this needs more context because, as is, it seems like it was just thrown into the manuscript.

(5) The authors mentioned that the size of the inserted genes could be a limitation for this technique and tested cell surface receptors of different sizes. However, there was no explicit discussion in the main text.

Reviewer #2 (Public review):

Summary:

The authors present an investigation of the relationship between the iEEG frequency bands signal and hemodynamic responses at different cortical depths. Based on this, the authors aim to uncover the layered origin of iEEG signals at different frequencies. The authors then interpret their results in terms of feedforward and feedback processing, arguing that the correlations between fMRI and iEEG signals reflect the interaction between both processes. In addition, the authors aim to infer the extent to which these processes are involved during naturalistic music processing.

Strengths:

This study combines the neural recording methodologies yielding the highest spatio-temporal precision achievable in humans, while using naturalistic auditory stimuli. This combination of recording methods and experimental design offers key insights regarding the precise origin of iEEG signals, which is necessary to improve the interpretability of future iEEG studies.

Weaknesses:

(1) The current framing of the paper leads the authors to interpret their findings in ways that are not warranted by the data. The main analysis of the paper consists of correlating the hemodynamic responses from different layers with iEEG signals from different frequency bands, which enables us to infer the relationship between the two signals. It does not, however, enable us to draw inferences regarding the extent of feedforward and feedback processing and the interaction between the two during naturalistic auditory processing. This would require comparing hemodynamic responses in different cortical layers or frequency bands activation against some baseline condition. Based on the presented analysis, statements such as "our frequency-specific results demonstrate that naturalistic music perception seamlessly integrates both feedforward and feedback processing streams" should be removed.

(2) The presentation of existing literature omits key details and findings, making it difficult to fully understand the research question the authors are trying to address. For example, the author mentions studies showing that feed-forward and feedback processing are segregated across cortical layers and that feed-forward and feedback processing have distinct time-frequency signatures (lines 47-58). However, the authors do not mention which cortical layer or which frequency band is associated with which kind of processing. As a result, it is difficult for the reader to determine what exact hypothesis the author is trying to test in the study. This might also relate to the confusion raised in (1).

(3) The method section omits key details. When describing the paradigm, the authors do not describe how the tones were presented, nor how the signals were synchronized. Similarly, there is no mention of the pipeline used for iEEG electrodes localization. In addition, the exact regressors that entered the generalized linear model of hemodynamic responses are not clearly stated: were all regressors (frequency bands + acoustic signal + HFA) entered together in a single model or in separate models? The mention of a cubic spline is also not sufficient for the reader to understand what was done and for which purpose. Finally, the exact tests used for some comparisons are omitted (in Figure 2, for example, no mention of the exact test used to compare betas between A1 and A2). The current structure of the method section is also quite difficult to follow: the authors switch back and forth between describing acquisition protocols and participant counts, for example.

(4) The lack of methodological details (as described in point 3 above) casts doubts about the validity of some of the statistical tests reported. Throughout the paper, the authors present quantitative statements and statistical tests comparing the fitted beta parameters between brain regions (A1 and A2) and cortical depths. However, the authors do not mention any normalization procedure taken to ensure that the scale of the signals being compared was equated. If the overall magnitude of the signals in A1 differs from that of A2, the mean of the beta distribution is expected to differ as well. Similarly, if the signal-to-noise ratio differs between brain regions or cortical layers, so should the variance of the beta parameters across subjects, which might break the homoscedasticity assumption of some tests, which might or might not be a problem depending on the exact test the authors used (hence the importance of reporting them).

Reviewer #2 (Public review):

Summary:

Verran et al. leverage a previously published RNAseq dataset of zebrafish cerebrospinal fluid contacting neurons (CSF-cNs) to identify potential receptors involved in chemosensory signalling in these neurons. They then validate expression of the identified receptors by hybridization chain reaction (HCR) in zebrafish larvae. This way they uncover potential roles for the somatostatin receptor Sstr2a, metabotropic glutamtate receptor Grm2a, LDL receptor Ldlrad2 and the Phosphatase receptor Ptprna, suggesting the existence of numerous chemo-sensory pathways in CSF-cNs and providing a potential entry point for further investigation.

Strengths:

This is a useful resource; the provided HCR data that demonstrates expression of these receptors in CSF-cNs is convincing, and the finding that CSF-cNs express these receptors is interesting.

Weaknesses:

The overall insight provided by this manuscript is rather limited, essentially just demonstrating the expression of 4 receptors in CSF-cNs, whose expression was predicted to be enriched in these neurons anyway by a previously published dataset.

Reviewer #2 (Public review):

Summary:

This manuscript challenges the widely used interpretation of VBIT-4 as a specific inhibitor of VDAC1 oligomerization, arguing instead that it acts primarily as a membrane-active compound. Using high-speed atomic force microscopy, electrophysiology, liposome leakage assays, Laurdan fluorescence, microscale thermophoresis, coarse-grained molecular dynamics, and cell-based assays in wild-type and VDAC1-knockout HeLa cells, the authors show that VBIT-4 partitions into lipid bilayers, induces membrane defects and leakage, and causes VDAC1-independent cytotoxicity within a concentration range commonly used to infer VDAC1-specific effects.

Strengths:

The main strength is the convergence of several independent approaches to the same conclusion. Atomic force microscopy directly visualizes VBIT-4-induced defects in lipid regions while VDAC1 assemblies remain apparently intact. Electrophysiology separates VDAC1 channel behavior from background membrane conductance and shows that VBIT-4 does not measurably alter VDAC1 conductance or voltage gating, while increasing nonspecific membrane permeability. Lipid-only membranes, lipid nanodiscs lacking VDAC1, and VDAC1-knockout cells provide important controls supporting a VDAC1-independent mechanism.

The wild-type versus VDAC1-knockout cytotoxicity comparison is a particularly strong test of VDAC1 independence. The observations that VBIT-4 is poorly soluble, aggregation-prone, and sensitive to storage conditions are also important, as they offer a plausible explanation for variability across previous studies. The revised manuscript is further strengthened by quantitative analysis of VDAC1 organization in atomic force microscopy images and by simulations including multiple VDAC1 molecules.

Weaknesses

The main limitation is that the conclusion that VBIT-4 does not affect VDAC1 oligomerization is strongest for the specific readouts used here: atomic force microscopy measurements of cluster compaction, VDAC1 channel properties, and simulated assembly behavior. These are direct and informative measurements, but they are not identical to the chemical cross-linking readouts used in much of the prior VBIT-4 literature. Readers should therefore distinguish between VDAC1 cluster organization in membranes, as measured here, and cross-linking-defined VDAC1 proximity.

A second limitation is the uncertainty around effective VBIT-4 concentration. Because VBIT-4 is poorly soluble, aggregation-prone, pH-dependent, membrane-partitioning, and storage-sensitive, nominal added concentration may differ substantially from the concentration of active compound available in each assay. This complicates comparisons across the different in vitro, simulation, cellular, and previously published assays.

The coarse-grained simulations provide a coherent mechanistic framework for membrane partitioning, aggregation, and defect formation. However, the VBIT-4 coarse-grained model is newly parameterized and is used to support a quantitative partitioning argument. The manuscript would be easier to interpret if the coarse-grained-derived partition coefficient were reported with uncertainty, convergence information, and protonation state, and compared with a matched all-atom octanol-water partition estimate from the same atomistic model used to build the coarse-grained mapping. This matters because the partitioning argument is used quantitatively to relate micromolar aqueous VBIT-4 to millimolar concentrations in the bilayer.

Finally, the cellular data strongly support VDAC1-independent cytotoxicity, but the lower-dose mitochondrial functional phenotypes were not directly compared between wild-type and VDAC1-knockout backgrounds. VDAC1 independence is therefore more directly established for cytotoxicity than for the lower-dose mitochondrial phenotypes.

Overall, this work provides a valuable and timely reassessment of VBIT-4, and its central conclusion will be useful for researchers interpreting studies that use this compound as a probe of VDAC1 function.

Reviewer #2 (Public review):

Summary:

This manuscript investigates the origins of inter-item biases in visual working memory. The authors proposed a computational model where overlapping memory signals are disentangled, inducing memory biases that depend on relative noise levels across items. The key theoretical advance is the prediction that bias direction depends not only on absolute memory noise but on the relative noise levels of target and non-target representations. Using four experiments with color mosaics whose color variability manipulates memory precision, the authors report that biases reverse as a function of relative noise in a manner predicted by the model.

Strengths:

The manuscript is clearly written and theoretically motivated. The experiments are well designed and provide converging evidence for a distinctive and non-intuitive prediction of the proposed model. I found the central result compelling: independently manipulating target and non-target noise leads to qualitatively different bias patterns, consistent with the model's prediction that relative noise is a key determinant of bias direction.

Weaknesses:

The main limitation is that the evidence establishes consistency of the data with the proposed Demixing Model, but does not demonstrate that the model provides a unique explanation of the data. Although the manuscript argues that dominant theories struggle to account for the observed reversals, no formal comparison with alternative computational frameworks is presented. In addition, model fitting results are reported only briefly, making it difficult to evaluate fit quality at the level of individual observers.

Reviewer #2 (Public review):

Summary:

The manuscript presents interesting observations regarding the exceptional longevity and improved healthspan of male daf-2 mutants. Given the comparatively limited focus on male aging in C. elegans, the study provides a potentially useful characterization of sex-specific effects associated with reduced IIS signaling.

Strengths:

The 4-fold increase in lifespan of male daf-2 mutants is a striking and unexpected observation. The altered fat metabolism between older daf-2 mutant males and hermaphrodites provides further evidence of sex-specific effects.

Weaknesses:

(1) A major limitation of the current study is that the conclusions rely primarily on a single daf-2 allele. It would strengthen the manuscript to validate at least the major observations using an independent daf-2 allele or through daf-2 RNAi. This is particularly relevant for the proposed male-specific enhancement of longevity and healthspan, as it remains unclear whether the observed effects broadly reflect reduced IIS signaling or may be influenced by allele-specific effects or background mutations.

(2) The methods for male lifespan assays require additional detail. Although the authors state that males were generated and transferred every three days, it is not clear whether males were maintained singly or in groups, how many males were placed per plate, or how many were censored by fleeing. These details are particularly important for male aging assays, as male lifespan in C. elegans is known to be influenced by social interactions. Factors such as population density can affect survival and healthspan measurements. Clarifying these procedures would improve reproducibility and interpretation of the reported male-specific lifespan effects.

(3) Because reduced IIS signaling in daf-2 mutants is known to alter metabolism, physiology, and potentially male-derived signaling, it would be interesting to determine whether the enhanced longevity of daf-2 males is influenced by altered male-male interactions or resistance to male-associated toxicity. In this context, clarification of whether lifespan assays were performed with grouped or individually maintained males would be valuable. If not already tested, lifespan analysis under isolated single-male conditions could help distinguish intrinsic longevity effects from potential contributions of population-dependent signaling or social interactions.

(4) In Figure 2D, the body-length measurements in WT males appear somewhat unexpected, particularly the apparent increase between Day 14 and Day 20. Since adult worms are not typically expected to exhibit substantial growth at advanced ages, additional clarification regarding the measurement methodology would be helpful, including confirmation that the scale bars and image scaling were applied consistently across conditions.

(5) The use of palmitic acid barriers following Beydoun et al. (2024) is appropriate; however, it would be helpful to clarify whether WT and daf-2 males exhibited comparable fleeing behavior under these assay conditions. Because male worms are highly prone to plate leaving and censoring, genotype-dependent differences in fleeing behavior could potentially influence survival analyses and the number of censored animals. In addition, as Beydoun et al. primarily characterized these barrier conditions using hermaphrodites, it would be useful to clarify whether comparable barrier effectiveness was observed in male lifespan assays.

(6) Separately, Beydoun et al. (2024) also reported that palmitic acid barrier conditions can influence body-size measurements, whereas PEG-based barriers did not show similar effects on body size. It would therefore be useful to know whether comparable body-length trends were observed under alternative barrier conditions, particularly given the unexpected increase in WT male body length at later ages.

Reviewer #2 (Public review):

Summary:

This paper addresses whether congenital aphantasia reflects an alteration of visual representations themselves, or rather of the systems that allow internally generated representations to reach conscious experience.

Strengths:

The study is novel and ambitious. The authors combine several complementary structural MRI approaches in a rare and well-characterised population, and the convergence of the findings toward frontotemporal and cingulate systems, with relative sparing of early visual cortex and major visual pathways, is particularly interesting because it could affect the way visual imagery is modelled and tested experimentally and clinically.

Weaknesses:

Overall, I found the manuscript conceptually and methodologically strong. My main concern regards the interpretation of the anatomical findings, rather than the findings per se. The authors discuss their results within a rich cognitive framework. However, the current dataset does not appear to include independent behavioural or neuropsychological measures that would allow the proposed cognitive interpretation to be tested in the same participants. As a result, the manuscript sometimes moves quite rapidly from 'these structural differences involve systems associated with higher-order control, salience, conscious access' to 'these structural differences may explain the cognitive mechanisms of aphantasia'. I agree that this is the most interesting interpretation, and probably the right one to explore. Although plausible, it remains indirect. The authors already acknowledge this point when discussing memory, affective control, and semantic processing. However, the same logic should be extended to the interpretation of the full set of findings. For example, if the salience/anterior insula findings are interpreted in relation to access to internally generated representations, it would be useful to know whether aphantasic participants also differ behaviourally on tasks tapping interoception or related aspects of internal monitoring. I appreciate that collecting additional behavioural data may not be feasible at this stage, especially given the difficulty of recruiting participants with such a specific manifestation. However, I think it should be acknowledged more explicitly in a dedicated limitation paragraph.

Reviewer #2 (Public review):

Summary:

Drosophila haematopoiesis has been shown to be governed by a number of signalling pathways such as JAK/STAT and Dpp. This important study shows a role for nutrient sensing and autophagy in determining blood cell differentiation. The authors show that General control non-derepressible 5 (Gcn5), a histone acetyltransferase affects blood cell differentiation. Gcn5 also negatively regulates autophagy through its effector TFEB which directly regulates autophagy genes. The authors also show that mTORC1 modulates Gcn5 levels and through it TFEB activity thus acting as a fine-tuning mechanism which maintains optimal levels of autophagy.

Strengths:

The main strength of the work lies in the interesting finding that cellular metabolic processes such as autophagy has a direct role in blood cell differentiation and has the potential to be of interest to those working on vertebrate haematopoiesis as well. The report has generated intriguing data, using promoters specific for sub sections of the lymph gland, that different cellular subsets of the lymph gland contribute differently towards haematopoiesis, but this is not followed up in detail and the final conclusions are derived from a combination of whole lymph gland perturbations as well as those from specific promoters.

Weakness:

(1) Gc5 seems to be expressed throughout the lymph gland but modulating it in the subsections do not have the same result. It is very striking that the knockdown of Gcn5 in the prohemocyte population does not have an effect on differentiation whereas overexpression does. And the modulations of Gcn5 in PSC also has variable effects across hemocyte subpopulations which is not explored in the manuscript. Interestingly, also the domain deletion constructs show differential effect on blood cell differentiation when altered solely in the prohemocytes which is not explained. While Gcn5 can be seen in all sections of the lymph gland in the first figure, under the HHLT-Gal4 and Hml-Gal4, Gcn5 looks cytoplasmic and almost completely excluded from the nucleus strikingly unlike Gcn5 expression under the Collier-Gal4 and Dome-Gal4. The rest of the experiments in the manuscript are done with multiple promoters, with autophagy flux measured by modulating Gcn5 with a pan hemocyte promoter, but the mTORC1-Gcn5 axis is explored using chemical modulators which affect the whole of the lymph gland (Fig7) or using two pro-hemocyte promoters (Fig8).

(2) The knockdown of Gcn5 seems to affect the gland size (A compared to B and C). Since mTORC1 is a central regulator of cell size, it is possible that some of the effects seen in these knockdowns are potentially through mTORC1 affecting size suggesting that the signalling axis between mTORC1 and Gcn5 might not be a one-way axis as suggested in Figure 9. Also, this would mean that in experiments where absolute cell counts of crystal cells or niche cells are used to assess blood cell differentiation, further analysis to consider total cell numbers in the lymph gland would strengthen the manuscript.

(3) A genetic manipulation of mTORC1 specifically in the pro hemocytes would strengthen the role of mTORC1 in the pathway rather than the chemical modulation which affects the whole of the lymph gland.

Comments on the revised manuscript:

Overall, the revisions make the narrative more coherent. The authors have also added data which substantiates their conclusions.

However, in some instances, the authors are not clearly able to explain the discrepancies in the data (Gen-5 depletions under the Hml-Gal4 in the whole larval lysates remove p62 completely) which is not ideal.

A query regarding the discrepancies in the immunofluorescence data: The authors have removed the IF data which suggested that there could be differences in the shuttling of Gcn5 between the nucleus and cytoplasm. The authors suggest that immunofluorescence issues are at the root of these variable results, but the reviewer wonders whether there could be further unexplored mechanisms re: shuttling that is unexplored here and would have been potentially novel.

Reviewer #2 (Public review):

Summary:

Zylberberg et al. reanalyze eye-tracking and behavioral data to test two predictions of the attentional Drift Diffusion Model, finding that these predictions are not met. Similarly, predictions of normative models (inspired by rational inattention) are not in line with the data, and the authors propose a post-choice model of attention. This model better accounts for the two effects but also does not account for all patterns, so the authors conclude that eye movements most likely reflect both pre- and post-decisional processes.

Strengths:

A clear strength is the systematic falsification-based approach of the paper, establishing (partially) new predictions and testing to what extent these are met by extant models and by a newly developed theory. The authors do a good job in providing intuitions behind the effects and the reasons why models such as the aDDM predict them. The paper is of substantial relevance for the field, as it shows that effects pertaining to the last fixation(s) should be interpreted with caution. Another strength is the paper's transparency as the authors clearly acknowledge that their new model does not do a perfect job either.

Weaknesses:

The paper focuses on analyzing the Krajbich 2010 data, but shows that the second effect replicates in many other datasets. A more principled approach, in which both effects are analyzed and presented for all datasets, would be more convincing. The results should then be shown together for clarity/readability.

Similarly, it would be nice to show to what extent the models' predictions depend (not depend) on using the best-fitting parameter values (are there any parameter settings under which the two effects are not predicted?)

Reviewer #2 (Public review):

McGaughey and Gold trained rhesus macaque monkeys to perform a motion-direction discrimination task in which a behaviorally irrelevant adapting stimulus with either fast or slow direction alternations preceded a variable-duration test stimulus, while simultaneously recording single-unit activity in area MT and pupil diameter. They report that adaptation to the more rapidly changing stimulus was associated with reduced behavioral sensitivity, attenuated test-evoked MT responses, and larger pupil-linked arousal signals. The authors interpret these behavioral changes as evidence for context-dependent adjustments to the temporal dynamics of decision formation and argue that these adjustments are supported by both sensory adaptation in MT and arousal-related mechanisms. More broadly, they conclude that flexible evidence accumulation in dynamic environments arises from distributed adjustments across sensory encoding and neuromodulatory systems rather than solely from changes within a downstream accumulator. If correct, this interpretation has important implications not only for our understanding of perceptual decision making, but also for broader theories concerning the functional role of sensory adaptation.

The conclusions of the paper are generally supported by the data. Evidence for adaptation-induced changes in sensory encoding, behavior, and pupil dynamics is convincing, and the revised manuscript substantially strengthens the connection between the behavioral findings and the proposed decision-making framework.

Comments on revised version.

The revised manuscript provides a clearer account of how recent stimulus history influences behavioral performance. In the original version, aspects of the psychometric functions were interpreted as evidence for a more leaky evidence-accumulation process, although some of these effects could potentially have reflected alternative mechanisms, including influences of the adapting stimulus on short-duration trials. The additional analyses and discussion included in the revision clarify that information from the adapting stimulus contributes to behavior at short viewing durations and appropriately temper claims regarding the specific computational mechanism underlying the observed behavioral effects. While the data do not uniquely identify whether these effects arise from changes in leak, other nonlinearities, or related decision processes, they provide convincing evidence that recent temporal context influences the temporal dynamics of decision formation.

My original review also noted that different sections of the manuscript relied on different behavioral metrics and analytical approaches when relating behavioral changes to neural and pupil-linked measures. The revised manuscript now provides a clearer rationale for these choices, including distinctions arising from the different trial types and time windows used in the neural and pupil analyses.

Reviewer #2 (Public review):

Okabe and colleagues build on a super-resolution-based technique they have previously developed in cultured hippocampal neurons, improving the pipeline and using it to analyze spine nanostructure differences across 8 different mouse lines with mutations in autism or schizophrenia (Sz) risk genes/pathways. It is a worthy goal to try to use multiple models to examine potential convergent (or not) phenotypes, and the authors have made a good selection of models. They identify some key differences between the autism versus the Sz risk gene models, primarily that dendritic spines are smaller in Sz models and (mostly) larger in autism risk gene models. They then focus on three models (2 Sz - 22q11.2 deletion, Setd1a; 1 ASD - Nlgn3) for timelapse imaging of spine dynamics, and together with computational modelling provide a mechanistic rationale for the smaller spines in Sz risk models. Bulk RNA sequencing of all 8 model cultures identifies several differentially expressed genes which they go on to test in cultures, finding that ecgr4 is upregulated in several Sz models and its misexpression recapitulates spine dynamics changes seen in the Sz mutants, while knockdown rescues spine dynamics changes in the Sz mutants. Overall, these have the potential to be very interesting findings and useful for the field.