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    1. Reviewer #2 (Public review):

      Summary:

      This manuscript reports the application of a combined targeted therapeutic approach to gastric cancer treatment. The RTK, FGFR2 and the phosphatase, SHP2 are targeted with existing drugs; AZD457 and SHP099, respectively. Having shown increased mRNA levels of FGFR2 and SHP2 in a patient population and highlighted the issue of resistance to single therapies the combination of inhibitors is shown to reduce cancer-related signalling in two gastric cell lines. The efficacy of the dual therapy is further demonstrated in a single patient case study and mouse xenograft models. Finally, the rationale for SHP2 inhibition is shown to be linked to immune response.

      Strengths:

      The data is generally well presented, and the study invokes a novel patient data set which could have wider value. The study provides additional evidence to support the combined therapeutic approach of RTK and phosphatase inhibition.

      Weaknesses:

      Combined therapy approaches targeting RTKs and SHP2 have been widely reported. Indeed, SHP099 in combination with FGFR inhibitors has been shown to overcome adaptive resistance in FGFR-driven cancers. Furthermore, the inhibition of SHP2 has been documented to have important implications in both targeting proliferative signalling as well as immune response. Thus, it is difficult to see novelty or a significant scientific advance in this manuscript. Although the data is generally well presented, there is inconsistency in the interpretation of the experimental outcomes from ex vivo, patient and mouse systems investigated. In addition, the study provides only minor or circumstantial understanding of the dual mechanism.

      Using data from a 161 patient cohort FGFR2 was identified as displaying amplification of FGFR2 in ~6% with concomitant elevation of mRNA of patients which correlated with PTPN11 (SHP2) mRNA expression. The broader context of this data is of value and could add a different patient demographic to other data on gastric cancer. However, there is no detail on patient stratification or prior therapeutic intervention.

      Comments on revisions: This has been attended to in the revised version

      In SNU16 and KATOIII cells the combined therapy is shown to be effective and appears to be correlated with increase apoptotic effects (i.e. not immune response).

      Fig 2E suggests that the combined therapy in SNU16 cells is little better than FGFR2-directed AZD457 inhibitor alone, particularly at the higher dose.

      The individual patient case study described via Fig 3 suggests efficacy of the combined therapy (at very high dosage), however the cell biopsies only show reduced phosphorylation of ERK, but not AKT. This is at odds with the ex vivo cell-based assays. Thus, it is not clear how relevant this study is.

      The mouse xenograft study shows a convincing reduction in tumor mass/volume and a clear reduction in pAKT, whilst pERK remains largely unaffected by the combined therapeutic approach. This is in conflict with the previous data which seems to show the opposite effect.

      Comments on revisions: The authors have clarified this point

      In all, the impact of the dual therapy is unclear with respect to the two pathways mediated by ERK and AKT.

      Finally, the authors demonstrate the impact of SHP2 on PD-1 expression and propose that the SHP099/AZD4547 combination therapy significantly induces the production of IFN-γ in CD8+ T cells. This part of the study is unconvincing and would benefit from an investigation of the tumor micro-environment to assess T cell infiltration.

    1. Reviewer #2 (Public review):

      Summary:

      In this manuscript, the authors combined coarse-grained structure-based model simulation, optical tweezer experiments, and AI-based analysis to assess the knotting behavior of the TrmD-Tm1570 protein. Interestingly, they found that while the structure-based model can fold the single knot from TrmD and Tm1570, the double-knot protein TrmD-Tm1570 cannot form a knot itself, suggesting the need for chaperone proteins to facilitate this knotting process. This study has strong potential to understand the molecular mechanism of knotted proteins, supported by many experimental and simulation evidence. However, there are a few places that appear to lack sufficient details, and more clarification in the presentation is needed.

      Strengths:

      A combination of both experimental and computational studies. The authors have addressed my questions in their revised manuscript. I appreciate their efforts.

    1. Reviewer #2 (Public review):

      Summary:

      This is a mechanistic study that provides new insights into the inhibition of SARS-CoV-2 Mpro.

      Strengths:

      The identification of dimer interface stabilization/destabilization as distinct inhibitory mechanisms and the discovery of C300 as a potential allosteric site for ebselen are important contributions to the field. The experimental approach is modern, multi-faceted, and generally well-executed.

      Weaknesses:

      The primary weaknesses relate to linking the biophysical observations more directly to functional enzymatic outcomes and providing more quantitative rigor in some analyses. While the study is overall strong, addressing its weaknesses and limitations would elevate the impact and translational relevance of the current manuscript.

      (1) Correlation with Functional Activity:

      The most significant gap is the lack of direct enzymatic activity assays under the exact conditions used for MS and HDX. While EC50 values are listed from literature, demonstrating how the observed dimer stabilization (by peptidomimetics) or dimer disruption (by ebselen) directly correlates with inhibition of proteolytic activity in the same experimental setup would solidify the functional relevance of the biophysical observations. For instance, does the fraction of monomer measured by native MS quantitatively predict the loss of activity? Also, the single inhibitor concentration used in each MS experiment needs to be specified in the main text and legends. A discussion on whether the inhibitor concentrations required to observe these dimerization effects (in native MS) or structural dynamics (in HDX-MS) align with EC50 values would be helpful for contextualizing the findings.

      (2) For the two Cys residues found to be targeted by ebselen, what are their respective modification stoichiometry related to the ebselen concentration? Especially for the covalent binding site C300, which is proposed in this study to represent a novel allosteric inhibition mechanism of ebselen, more direct experimental evidence is needed to support this major hypothesis. Does mutation or modification of C300 affect the Mpro dimerization/monomer equilibrium and alter the enzymatic activity? If ebselen acts as a covalent inhibitor linked to multiple Cys, why is its activity only in the uM range?

      (3) For the allosteric inhibitor pelitinib with low-uM activity, no significant differences in deuterium uptake of Mpro were observed. In terms of the binding affinity, what is the difference between pelitinib and ebselen? Some explanations could be provided about the different HDX-MS results between the two non-peptidomimetic inhibitors with similar activities.

      (4) Native MS Quantification:

      The analysis of monomer-dimer ratios from native MS spectra appears qualitative or semi-quantitative. A more rigorous and quantified analysis of the percentage of dimer/monomer species under each condition, with statistical replicates, would strengthen the equilibrium shift claims. For native MS analysis of each inhibitor, the representative spectrum can be shown in the main figure together with quantified dimer/monomer fractions from replicates to show significance by statistical tests.

      (5) Changes of HDX rates in certain regions seem very subtle. For example, as it states 'residues 296-304 in the C-terminal region of M pro were more flexible upon ebselen binding (Figure 4c)', the difference is barely observable. The percentage of HDX rate changes between two conditions (with p values) can be specified in the text for each fragment discussed, and any change below 5% or 10% is negligible.

    1. Reviewer #2 (Public review):

      Summary:

      The authors conducted a brain-wide survey of Avp (arginine vasopressin) and its Avpr1a gene expression in the mouse brain using RNAscope, a high-resolution in situ hybridization method. Overall, the findings are useful and important because they identify brain regions that express the Avpr1a transcript. A comprehensive overview of Avpr1a expression in the mouse brain could be highly informative and impactful. The authors used RNAscope (a proprietary in situ hybridization method) to assess transcript abundance of Avp and one of its receptors, Avpr1a. The finding of Avp-expressing cells outside the hypothalamus and the extended amygdala is novel and is nicely demonstrated by new photomicrographs in the revised manuscript. The Avpr1a data suggest expression in numerous brain regions. In the revised manuscript, reworked figures make the data easier to interpret.

      Strengths:

      A survey of Avpr1a expression in the mouse brain is an important tool for exploring vasopressin function in the mammalian brain and for developing hypotheses about cell- and circuit-level function.

      [Editors' note: The authors have substantially addressed all the reviewers' concerns and comments.]

    1. Reviewer #2 (Public review):

      This is an interesting study that shows that mRNA acetylation at synapses is dynamically regulated at synapses by spatial memory in the mouse hippocampus. The dynamic changes of ac4C-mRNAs regulated by memory were validated by methods including ac4C dot-blot and liquid 13 chromatography-tandem mass spectrometry (LC-MS/MS).

    1. Reviewer #2 (Public review):

      Summary:

      In this paper, the authors have characterized Rv2577 as a Fe3+/Zn2+ -dependent metallophosphatase and a nucleomodulin protein. The authors have also identified His348 and Asn359 as critical residues for Fe3+ coordination. The authors show that the proteins encode for two nuclease localization signals. Using C-terminal Flag expression constructs, the authors have shown that MmpE protein is secretory. The authors have prepared genetic deletion strains and show that MmpE is essential for intracellular survival of M. bovis BCG in THP-1 macrophages, RAW264.7 macrophages and mice model of infection. The authors have also performed RNA-seq analysis to compare the transcriptional profiles of macrophages infected with wild type and mmpE mutant strain. The relative levels of ~ 175 transcripts were altered in mmpE mutant infected macrophages and majority of these were associated with various immune and inflammatory signalling pathways. Using these deletion strains, the authors proposed that MmpE inhibits inflammatory gene expression by binding to the promoter region of vitamin D receptor. The authors also showed that MmpE arrests phagosome maturation by regulating the expression of several lysosome associated genes such as TFEB, LAMP1, LAMP2 etc. These findings reveal a sophisticated mechanism by which a bacterial effector protein manipulates gene transcription and promotes intracellular survival.

      Strength:

      The authors have used a combination of cell biology, microbiology and transcriptomics to elucidate the mechanisms by which Rv2577 contributes to intracellular survival.

      Weakness:

      The authors should thoroughly check the mice data and show individual replicate values in bar graphs.

      Comments on revisions:

      Thanks to the authors for addressing the concerns raised during the review of the original manuscript. The data is now presented with clarity, and discrepancies in mouse experiments have also been addressed with additional experiments.

    1. Reviewer #2 (Public review):

      Summary:

      The authors performed a genetic screen using deficiency lines and identified Uev1a as a factor that protects nurse cells from RasG12V-induced cell death. According to a previous study from the same lab, this cell death is caused by aberrant mitotic stress due to CycA upregulation (Zhang et al.). This paper further reveals that Uev1a forms a complex with APC/C to promote proteasome-mediated degradation of CycA.

      In addition to polyploid nurse cells, the authors also examined the effect of RasG12V-overexpression in diploid germline cells, where RasG12V-overexpression triggers active proliferation not cell death. Uev1a was found to suppress its overgrowth as well.

      Finally, the authors show that the overexpression of the human homolog, UBE2V1 and UBE2V2, suppresses tumor growth in human colorectal cancer xenografts and cell lines. Notably, these genes' expression correlates with the survival of colorectal cancer patients carrying Ras mutation.

      Strength:

      This paper presents a significant finding that UBE2V1/2 may serve as a potential therapy for cancers harboring Ras mutations. The authors propose a fascinating mechanism in which Uev1a forms a complex with APC/C to inhibit aberrant cell cycle progression.

      Comments on revisions:

      The authors have addressed several of the major concerns, including the addition of new data and improved figure presentation. However, some issues remain insufficiently resolved, particularly regarding control reuse (Major Comment 3) and experimental interpretation (Major Comments 5 and 8).

      Regarding Major Comment 5, the authors state that UAS copy number affects the frequency of egg chamber degradation in Fig. 2D, and thus explains the reduced phenotype in RasG12V + GFP-RNAi compared to RasG12V alone. However, this explanation is not consistent with other data in the manuscript. UAS-RasG12V combined with UAS-lacZ in Fig. 2G shows a phenotype comparable to UAS-RasV12 alone, despite also increasing the UAS copy number. This suggests that the effect is not simply due to copy number.

      I understand that the authors used UAS-RasG12V + GFP-RNAi as a control for the RNAi experiments and UAS-RasG12V + lacZ for the overexpression experiments. I suggest examining the phenotype frequency of UAS-RasG12V + UAS-GFP, to figure the reason out. Overall, these results indicate that there is a spectrum of phenotype frequencies, and therefore appropriate controls should be included for each experiment rather than reusing the same dataset across different experiments, as also noted in Major Comment 3.

    1. Reviewer #2 (Public review):

      Summary:

      The authors performed bioinformatic analyses to trace the genomic history of the clinically relevant pT181 plasmid. Specifically, they:

      (1) tracked the presence of pT181 across different S. aureus strain backgrounds through time. It was first found in one, later multiple strains, though this may reflect changes in sampling over time.

      (2) estimated the mutation rate of the chromosome and plasmid.

      (3) estimated the plasmid copy number of pT181, and found that it decreased over time. The latter was supported by two sets of statistical analyses, first showing that the number of single-copy isolates increased over time, and second, that the multicopy isolates demonstrated a lower PCN over time.

      (4) reported the different integration sites at which pT181 integrated into the genome.

      As a caveat, they mentioned that identical plasmid sequences have variable plasmid copy numbers across different genomes in their dataset.

      Strengths:

      This is a very solid, well-considered bioinformatic study on publicly available data. I greatly appreciate the thoughtful approach the authors have taken to their subject matter, neither over- nor underselling their results. It is a strength that the authors focussed on a single plasmid in a single bacterial species, as it allowed them to take into account unique knowledge about the biology of this system and really dive deep into the evolution of this specific plasmid. It makes for a compelling case study. At the same time, I think the introduction and discussion can be strengthened to demonstrate what lessons might be drawn from this case study for other plasmids.

      Weaknesses:

      The finding that the pT181 copy number declined over time is the most interesting claim of the paper to me, and not something that I have seen done before. While the authors have looked at some confounders in this analysis, I think this could be strengthened further in a revision.

      For the flow of the storyline, I also think the estimation of mutation rates (starting L181) and integration into the chromosome (starting L255) could be moved to the supplement or a later position in the main text.

      Clearly, the use of publicly available data prevents the authors from controlling the growth and sequencing conditions of the isolates. It is striking that they observe a clear signal in spite of this, but I would have loved to see more discussion of the metadata that came with the publicly available sequences and even more use of that metadata to control for confounding.

    1. Reviewer #2 (Public review):

      Summary:

      This manuscript studies the impacts of knocking out a protein known to be involved in synapse maturation in mice, measuring their ability to hunt prey items (and to discriminate simple visual patterns) under binocular and monocular viewing conditions. The main results are that the mice with this protein knocked out are impaired when performing visual tasks with binocular viewing, but are actually better when they perform monocularly. The interpretation is that the knocked-out protein has affected binocular visual integration.

      Strengths:

      Overall, the attempt to connect a protein to behavior/perception, via known mechanistic effects on synapse development and visual critical periods, is admirable.

      The use of multiple visual conditions and behavioral paradigms (binocular/monocular, cricket hunting/orientation discrimination, light/dark) strengthens and enriches the results.

      Weaknesses:

      The primary interpretation - that binocular integration is affected in the PSD-95 knockouts- is not supported by the behavioral evidence. Using behavior to isolate a particular stage in visual processing (and further, to distinguish it from elements of generating the behavioral response and/or acquiring the visual information in the first place) is notoriously difficult. Such attempts are, of course, the domain of psychophysics. In fact, the most classical and loveliest success is in the domain of binocular integration- Bela Julesz's "psychoanatomy" that used random dot stereograms to isolate stereoscopic computations.

      I mention this example because it is, in fact, directly relevant to my primary concern about the evidence used as support for the favored interpretation here. Julesz's stimuli were extremely clever in isolating binocular mechanisms (i.e., binocular mechanisms MUST be used to perform the task), and any perceptual/behavioral reports are very straightforward to interpret (i.e., a stereoscopically-defined shape can be identified, or not).

      Now compare this to the work described in this manuscript. KO (knockout) mice are worse than wild types at chasing prey items or at moving towards a rewarded orientation, but they get better when performing this task monocularly. No argument that that is an interesting bit of scientific phenomenology to characterize. However, the behaviors do not require binocular integration, the freely-moving paradigms involve a variety of gaze and body-movement strategies, and the metrics used to quantify performance are similarly high-dimensional. Bottom line, it is not possible to glean whether the KO's intriguing binocular-vs-monocular differences are due to binocular integration per se, or something better thought of as fundamentally sensorimotor in origin. The tasks do not isolate visual from sensorimotor processing, and the behaviors and associated metrics cannot definitely adjudicate between a multitude of possible specific interpretations.

      More specifically, the KO mice may have abnormal patterns of binocular coordination. Eye movements were not tracked in these studies, despite the availability of such instrumentation and their successful application in many preceding studies of mouse prey capture. If the KO mice do not coordinate their eye movements (in task-specific/task-relevant ways), they might receive binocular input that is abnormal. Under monocular conditions, that mismatched or inappropriately coordinated binocular input is absent, which would relieve them of the confusing visual information. That is rather different than having an impairment of binocular integration, as it is basically a question of whether the visual system is impaired, or whether the inputs to the visual system are abnormal due to differences in binocular coordination.

      It is also possible that the binocular deficit, as measured in behavior,r occurs in a distinct part of the sensorimotor loop. Even if the binocular eye movements are normal, and binocular visual integration is normal, PSD-95 KO mice may be confused or distracted by the larger visual field that comes from binocular viewing (quite profound in species with mostly lateralized eyes). Such a "post-sensory" interpretation related to target selection (from what could be a totally normal visual representation) is difficult to rule out as well.

      In summary, this reviewer appreciates the value of trying to connect this molecular mechanism to sensory processing and behavior. The use of naturalistic tasks and freely-moving paradigms is also something to commend. However, the sorts of visual stimuli and behavioral paradigms used here are not well-suited to supporting the rather specific interpretation that has been put forth in this manuscript.

    1. Reviewer #2 (Public review):

      Summary:

      The basic helix-loop-helix transcription factor TCF4 (also known, as ITF2, SEF2, or E2-2) is a protein involved in the development and functioning of many different cell types. TCF4 plays important roles in the nervous system, both in health and disease. Its importance in the nervous system is underlined by its association with common and rare cognitive disorders. Specifically, variants of the TCF4 gene are implicated in increased susceptibility to schizophrenia, and mutations in the TCF4 gene cause Pitt-Hopkins syndrome (PTHS) or mild to moderate non-syndromic intellectual disability.

      In this manuscript, the authors have studied whether reinstating TCF4 later in postnatal development in juvenile PTHS model mice could reverse behavioral phenotypes, thereby simulating gene therapy. Previous research by the same group has demonstrated that restoring TCF4 during embryonic or neonatal stages, corresponding to prenatal or neonatal periods in humans, improved phenotypes in a PTHS mouse model. In the current study, a conditional TCF4 reinstatement mouse model, Tcf4-lox-stop-lox (Tcf4-LSL), previously developed and characterized by their lab, where Cre-mediated recombination removes a floxed transcriptional stop cassette downstream of exon 17, leading to reinstatement of all TCF4 isoforms at appropriate levels in neurons, was used. The study showed that this later intervention failed to correct most phenotypes, suggesting that perinatal reinstatement of TCF4 holds the greatest potential to treat behavioral symptoms of PTHS. However, the study also suggests that some cognitive behaviors may still be responsive to TCF4 reinstatement later in life.

      Strengths:

      This is a very important study aimed at developing gene therapy for PTHS. The study is technically very well performed and written.

      Weaknesses:

      The only weakness is that a human disease is modelled in a mouse, which is evolutionarily not the closest mammal to humans. Hopefully, in the future, similar studies will also be performed in a nonhuman primate model, for example rhesus macaque.

    1. Reviewer #2 (Public review):

      Summary:

      The authors derived a time-specific signature of reactogenicity from mouse muscle following exposure to vaccines /TLRs for capturing the reactogenicity patterns. They tested this reactogenicity signature in mouse blood, and then they applied the reactogenicity signature to human blood from subjects having received different vaccines. They identified biomarkers in mouse muscle which are also observed in mouse and human blood and could be used as a reactogenicity signature in mice, instead of CRP.

      Strengths:

      (1) The authors used transcriptomic response following vaccination and used common genes to human and mice for defining a reactogenic signature.

      (2) As the authors used different formulations in mice, the model was trained across a broad reactogenicity spectrum, which has the advantage of being used for evaluating new vaccines/vaccine platforms.

      Weaknesses:

      (1) The muscle gene signature reflects local reactogenicity. Systemic reactogenicity is not specifically addressed, except where overlapping gene signatures are observed for both local and systemic reactogenicity.

      (2) In the same logic, could we find additional genes in the blood which are not captured in the muscle?

      (3) The peak of the reactogenicity is usually 24h; it is not certain that additional TPs have helped the findings. If they have, the authors should explain.

    1. Reviewer #2 (Public review):

      Summary

      This manuscript proposes an original and conceptually interesting model in which anti-apoptotic BCL-2 family proteins, particularly BCL-XL and MCL-1, not only sequester BIM but also act as adaptor "co-receptors" that recruit BIM to the CUL5-WSB2 ubiquitin ligase complex for degradation. The authors present a mechanistic framework supported by structure-guided mutagenesis, BH3 mimetic perturbations and co-immunoprecipitation assays performed in RPE1 cells. In parallel, the study shows that neuroblastoma cell lines are highly dependent on WSB2 for survival. These observations give the work both conceptual and translational relevance.

      Strengths

      The principal strength of the study lies in its conceptual novelty. Reframing BCL-XL and MCL-1 not only as sequestration factors but also as adaptors that facilitate substrate engagement by an E3 ligase substantially extends current models of apoptotic regulation. The mechanistic narrative developed in RPE1 cells is clear and internally consistent: the combination of AlphaFold-guided motif identification with complementary mutagenesis provides a persuasive framework for how WSB2 associates with anti-apoptotic BCL-2 family members and promotes BIM turnover. The definition of a BCL-XL/MCL-1 co-receptor mechanism for WSB2-mediated BIM degradation is therefore both intuitive and mechanistically appealing. In parallel, the authors present a distinct experimental series showing that neuroblastoma cells exhibit pronounced sensitivity to WSB2 loss, undergo apoptosis upon its depletion and display reduced competitiveness in mixed-culture assays. Although the mechanistic connection between these observations requires further clarification, the convergence of a well-defined biochemical model with a clear cancer-relevant phenotype enhances the potential biological significance of WSB2 and raises the possibility that its regulation may hold therapeutic relevance.

      Weaknesses

      There are several limitations that readers should consider when interpreting the study. The most fundamental issue is the disconnect between the mechanistic model established in RPE1 cells and the apoptotic phenotype observed in neuroblastoma. Although the manuscript convincingly demonstrates the WSB2-BCL-XL/MCL-1-BIM axis in RPE1 cells and independently shows that WSB2 loss compromises neuroblastoma viability, it does not examine whether BIM levels are elevated upon WSB2 depletion in neuroblastoma, nor whether apoptosis in these cells requires BIM. Without demonstrating WSB2-BCL-2-BIM complex formation or BIM dependence in the disease-relevant context, it remains unclear whether the co-receptor mechanism characterised in RPE1 cells explains the phenotype. This gap is compounded by the observation that PUMA, another potent pro-apoptotic factor, also increases following WSB2 loss, raising the possibility that multiple death pathways contribute to the outcome. The absence of a genetic rescue experiment, such as re-expression of an shRNA-resistant WSB2 restoring viability and suppressing apoptosis, further limits causal inference regarding WSB2's role in neuroblastoma.

      Many central claims rely on single Western blots and pulldown assays without quantification or assessment of reproducibility. This complicates the interpretation of CHX chase experiments (where initial steady-state levels differ between samples) and limits confidence in BH3 mimetic experiments, which use a single concentration and short exposure time. Without dose-response curves, time-course analyses, caspase inhibition, or orthogonal genetic perturbation of BCL-XL or MCL-1, indirect or off-target drug effects cannot be excluded. Reduced co-IP signals in these assays could therefore reflect early apoptotic events or compound instability rather than specific disruption of protein-protein interactions.

      A further limitation concerns the inference of a direct WSB2-BCL-XL interaction. The mutagenesis analyses are performed in lysates that contain endogenous or overexpressed BIM, and BH3 mimetics disrupt the WSB2 interaction only when the BCL-XL-BIM heterodimer is dismantled. The study thus cannot distinguish whether the mapped WSB2 motifs mediate direct contact with BCL-XL or whether they influence the architecture or stability of the BCL-XL-BIM complex. Because no purified protein reconstitution or biophysical binding assays are presented, the evidence for direct binding remains suggestive rather than conclusive.

      The ubiquitination data also remain incomplete. Although the WSB2 mutation reduces the ubiquitin smear on BIM, the assay does not demonstrate dependence on CUL5, RBX2 or ARIH2, leaving open which ligase components are directly responsible. MLN4924 implicates CRLs more broadly, but the ubiquitination assay itself does not assign activity to the CUL5-WSB2 module.

      Finally, several methodological details are insufficiently described, including the generation and validation of the doxycycline-inducible WSB2 and HA-WSB2 lines and the suitability of the WSB2-overexpressing control line used in immunoprecipitations.

      Collectively, these issues do not undermine the conceptual interest of the proposed co-receptor model, but they do limit the strength of the mechanistic claims and weaken the connection between the defined mechanism and the neuroblastoma phenotype.

    1. Reviewer #2 (Public review):

      Summary:

      To discover peptides that interact with autophagy-related protein LC3B and profile the key binding determinants, the authors screened a library of ~500,000 36-residue peptides derived from the human proteome using bacterial cell-surface display. Analysis of the screening data revealed exceptions to the reported LIR motif and a strong preference for negatively charged residues adjacent to the LIR.<br /> These results support a refinement of the LIR motif definition and expand the network of candidate LC3B interaction partners.

      Strengths:

      High-throughput approach.

      Weaknesses:

      Lack of in vitro data and molecular dynamics simulations.

    1. Reviewer #2 (Public review):

      Summary:

      In this elegant study, the authors employ live iGluSnFR-based imaging of glutamate release from cortical boutons to dissect the distinct roles of the Ca²⁺ sensor synaptotagmin-7 (Syt7) in synaptic transmission. Although multiple functions have been attributed to Syt7 over the years, the field remains conflicted. The authors argue that one major obstacle for resolving some of these discrepancies lies in a fundamental limitation of electrophysiological recordings, which aggregate signals across all synapses to yield averaged readouts, dominated by strong, high-release-probability synapses. By using a live glutamate imaging approach combined with sensitive detection of action potential-evoked activity across different stimulation regimes, and a dedicated analysis pipeline, the authors confirm a role for Syt7 in facilitating synchronous release and in regulating the magnitude of asynchronous release. In contrast, they find no evidence that Syt7 contributes to the facilitation of asynchronous release, do not find evidence for a role for Syt7 in synaptic vesicle replenishment during AP trains, and provide evidence suggesting that the maintenance of facilitation by Syt7 may occur independently of vesicle depletion.

      Strengths:

      This study offers a fresh perspective on a debated issue, using a new experimental approach that the authors previously explored in the context of Synaptotagmin 1 (Mendonca et al. 2022). The authors record the response to a series of pair-pulse stimulations, followed by an AP train. By carefully quantifying individual events and by sorting events based on their efficacy, the authors extract quantitative information that they assign to different properties of synaptic function. They also devised an interesting approach for monitoring aspects of facilitation, in which they isolate PPR events where the first response did not elicit detectable release (thus regarding the release in response to the second AP as facilitating), and compare them with successful events. Together, the authors provide semi-quantitative descriptions of synchronous and asynchronous release during single, paired, and AP trains, yielding a weighted estimate of Syt7's contribution to distinct features of synaptic vesicle release that are independent of postsynaptic readouts. A major strength of the study is the confirmation of two principal proposed functions of Syt7: facilitation of synchronous release and regulation of the magnitude of asynchronous release.

      Weaknesses:

      The experimental approach presented here is elegant and well-executed. However, a principal limitation lies in translating electrophysiological terminology to imaging-based measurements. For instance, interpreting signals persisting beyond 10 ms as a proxy for asynchronous release relies on assumptions that would be good to experimentally justify. Could such signals arise from iGluSnFR saturation, or be affected by desensitization?. Moreover, the quantification of asynchronous release is based on very small signals that represent only a fraction of the already small synchronous release component, raising concerns about signal-to-noise limitations. A key issue is that failures to evoke glutamate release may arise from AP failures, such that the second response in a PPR does not necessarily represent facilitation. Given that many of the findings largely confirm existing literature, the study might have benefited from a different framing, for example, as an additional validation of the correspondence between electrophysiological measures and the authors' imaging-based readouts. Another point concerns the analysis of synaptic vesicle replenishment following depletion, which would ideally be addressed using alternative stimulation protocols, such as quantifying the response/success rate to single APs at varying time points after a train. Although the authors are appropriately cautious in their conclusions (e.g., with respect to Figure 5b), this limitation remains. Finally, the use of heterogeneous cortical neuronal cultures is likely to introduce substantial variability, as the authors themselves acknowledge, which may arise from the co-expression of multiple Ca²⁺ sensors across diverse cell types.

      In summary, the authors were able to confirm previously-described changes in neurotransmission properties upon the loss of Syt7 using live imaging of glutamate release at the level of single boutons. They also present preliminary evidence for the interdependence of Syt7 function, synaptic vesicle replenishment, and the facilitation of asynchronous release, although these results will need to be substantiated in future studies using alternative stimulation protocols and complementary methodologies. Taken together with the group's prior work on synaptotagmin-1, this study illustrates that live imaging of glutamate release offers an alternative approach that recapitulates some elements detectable via electrophysiological analysis, while possibly revealing new insights into the function of synaptic proteins. As a whole, taking a live imaging approach may be a broadly accessible way forward to analyze synaptic function. The potential of studying synaptic proteins in diverse cell types that are difficult to access with patch-clamp electrophysiology is particularly compelling.

    1. Reviewer #2 (Public review):

      Summary:

      Abdelmageed et al., demonstrate POLK expression in nervous tissue and focus mainly on neurons. Here, they describe an exciting age-dependent change in POLK subcellular localization, from the nucleus in young tissue to the cytoplasm in old tissue. They argue that the cytosolic POLK associates with stress granules. They also investigate cell-type specific expression of POLK, and quantitate expression changes induced by cell autonomous (activity) and cell nonautonomous (microglia) factors.

      Comments on revisions:

      Do the authors have any explanation or reason for why they weren't able to achieve a higher knockdown of POLK using siRNA in Figure 1A2? It does not seem statistically different by eye, as all values in the KD overlap with the control. This does not seem like strong evidence that their antibody works.

    1. Reviewer #2 (Public review):

      This manuscript by Carmona, Zagotta, and Gordon is generally well-written. It presents a crude and incomplete structural analysis of the voltage-gated proton channel based on measured FRET distances. The primary experimental approach is Förster Resonance Energy Transfer (FRET), using a fluorescent probe attached to a noncanonical amino acid. This strategy is advantageous because the noncanonical amino acid likely occupies less space than conventional labels, allowing more effective incorporation into the channel structure.

      Fourteen individual positions within the channel were mutated for site-specific labeling, twelve of which yielded functional protein expression. These twelve labeling sites span discrete regions of the channel, including P1, P2, S0, S1, S2, S3, S4, and the dimer-connecting coiled-coil domain. FRET measurements are achieved using acridon-2-ylalanine (Acd) as the acceptor, with four tryptophan or four tyrosine residues per monomer serving as donors. In addition to estimating distances from FRET efficiency, the authors analyze full FRET spectra and investigate fluorescence lifetimes on the nanosecond timescale.

      Despite these strengths, the manuscript does not provide a clear explanation of how channel structure changes during gating. While a discrepancy between AlphaFold structural predictions and the experimental measurements is noted, it remains unclear whether this mismatch arises from limitations of the model or from the experimental approach. No further structural analysis is presented to resolve this issue or to clarify the conformational states of the protein.

      The manuscript successfully demonstrates that Acd can be incorporated at specific positions without abolishing channel function, and it is noteworthy that the reconstituted proteins function as voltage-activated proton channels in liposomes. The authors also report reversible zinc inhibition of the channel, suggesting that zinc induces structural changes in certain channel regions that can be reversed by EDTA chelation. However, this observation is not explored in sufficient depth to yield meaningful mechanistic insight.

      Overall, while the study introduces an interesting labeling strategy and provides valuable methodological observations, the analysis appears incomplete. Additional structural interpretation and mechanistic insight are needed.

      Major Points

      (1) Tryptophan and tyrosine exhibit similar quantum yields, but their extinction coefficients differ substantially. Is this difference accounted for in your FRET analysis? Please clarify whether this would result in a stronger weighting of tryptophan compared to tyrosine.

      (2) Is the fluorescence of acridon-2-ylalanine (Acd) pH-dependent? If so, could local pH variations within the channel environment influence the probe's photophysical properties and affect the measurements?

      (3) Several constructs (e.g., K125Tag, Y134Tag, I217Tag, and Q233Tag) display two bands on SDS-PAGE rather than a single band. Could this indicate incomplete translation or premature termination at the introduced tag site? Please clarify.

      (4) In Figure 5F, the comparison between predicted FRET values and experimentally determined ratio values appears largely uninformative. The discussion on page 9 suggests either an inaccurate structural model or insufficient quantification of protein dynamics. If the underlying cause cannot be distinguished, how do the authors propose to improve the structural model of hHV1 or better describe its conformational dynamics?

      (5) Cu²⁺, Ru²⁺, and Ni²⁺ are presented as suitable FRET acceptors for Acd. Would Zn²⁺ also be expected to function as an acceptor in this context? If so, could structural information be derived from zinc binding independently of Trp/Tyr?

      (6) The investigated structure is most likely dimeric. Previous studies report that zinc stabilizes interactions between hHV1 monomers more strongly than in the native dimeric state. Could this provide an explanation for the observed zinc-dependent effects? Additionally, do the detergent micelles used in this study predominantly contain monomers or dimers?

      (7) hHV1 normally inserts into a phospholipid bilayer, as used in the reconstitution experiments. In contrast, detergent micelles may form monolayers rather than bilayers. Could the authors clarify the nature of the micelles used and discuss whether the protein is expected to adopt the same fold in a monolayer environment as in a bilayer?

    1. Reviewer #2 (Public review):

      Summary:

      This is a very interesting study focusing on a remarkable oligomerization domain, the LisH-CTLH-CRA module. The module is found in a diverse set of proteins across evolution. The present manuscript focuses on the extraordinary elaboration of this domain in GID/CTLH RING E3 ubiquitin ligases, which assemble into a gigantic, highly ordered, oval-shaped megadalton complex with strict subunit specificity. The arrangement of LisH-CTLH-CRA modules from several distinct subunits is required to form the oval on the outside of the assembly, allowing functional entities to recruit and modify substrates in the center. Although previous structures had shown that data revealed that CTLH-CRA dimerization interfaces share a conserved helical architecture, the molecular rules that govern subunit pairing have not been explored. This was a daunting task in protein biochemistry that was achieved in the present study, which defines this "assembly specificity code" at the structural and residue-specific level.

      The authors used X-ray crystallography to solve high-resolution structures of mammalian CTLH-CRA domains, including RANBP9, RANBP10, TWA1, MAEA, and the heterodimeric complex between RANBP9 and MKLN. They further examined and characterized assemblies by quantitative methods (ITC and SEC-MALS) and qualitatively using nondenaturing gels. Some of their ITC measurements were particularly clever and involved competitive titrations and titrations of varying partners depending on protein behavior. The experiments allowed the authors to discover that affinities for interactions between partners is exceptionally tight, in the pM-nM range, and to distill the basis for specificity while also inferring that additional interactions beyond the LisH-CTLH-CRA modules likely also contribute to stability. Beyond discovering how the native pairings are achieved, the authors were able to use this new structural knowledge to reengineer interfaces to achieve different preferred partnerings.

      Strengths:

      Nearly everything about this work is exceptionally strong.

      (1) The question is interesting for the native complexes, and even beyond that, has potential implications for the design of novel molecular machines.

      (2) The experimental data and analyses are quantitative, rigorous, and thorough.

      (3) The paper is a great read - scholarly and really interesting.

      (4) The figures are exceptional in every possible way. They present very complex and intricate interactions with exquisite clarity. The authors are to be commended for outstanding use of color and color-coding throughout the study, including in cartoons to help track what was studied in what experiments. And the figures are also outstanding aesthetically.

      Weaknesses:

      There are no major weaknesses of note, but I can make a few recommendations for editing the text.

    1. Reviewer #2 (Public review):

      Summary:

      The fascinating topic of the host range of arthropods, including insects, and the detoxification of host secondary metabolites has been elucidated through studies of the host specificity of two closely related species. The discovery that key genes were acquired from fungi through horizontal gene transfer (HGT) is particularly significant.

      Strengths:

      (1) The discovery that the TkDOG15 enzyme, acquired through HGT from fungi, plays a key role in the detoxification of green tea catechins in the Kanzawa mite, revealing a new mechanism of plant-herbivore interactions, is highly encouraging.

      (2) The verification of this finding through various experiments, including behavioral, toxicological, transcriptomic, and proteomic analyses, RNAi-based gene function analysis, and recombinant enzyme activity assays, is also highly commendable.

      (3) By proposing a two-step model in which amino acid substitutions and expression regulation of a specific enzyme gene (TkDOG15) enable host adaptive evolution, this study contributes significantly to our understanding of the evolutionary mechanisms of speciation and plant defense overcoming.

      Weaknesses:

      While transcriptome/proteome analyses reported changes in the expression of other detoxification-related enzymes, including CCEs, UGTs, ABC transporters, DOG1, DOG4, and DOG7, it is regrettable that the contribution of each enzyme, including its interaction with TkDOG15 and the functional analysis of each enzyme within the overall catechin detoxification system, was not investigated.

    1. Reviewer #2 (Public review):

      The work by Spokaite et al describes the discovery of a novel Rab5 binding site present in complex II of class III PI3K using a combination of HDX and Cryo EM. Extensive mutational and sequence analysis define this as the primordial Rab5 interface. The data presented are convincing that this is indeed a biologically relevant interface, and is important in defining mechanistically how VPS34 complexes are regulated.

      This paper is a very nice expansion of their previous cryo-ET work from 2021, and is an excellent companion piece on high-resolution cryo-EM of the complex I class III complex bound to Rab1 from the Hurley lab in 2025. Overall, this work is of excellent technical quality and answers important unexplained observations on some unexpected mutational analysis from the previous work.

      They used their increased affinity VPS34 mutant to determine the 3.2 ang structure of Rab5 bound to VPS34-CII. Clear density was seen for the original Rab5 interface, but an additional site was observed. Based on this structure, they mutated out the VPS34 interface, allowing for a high-resolution structure of the Rab5 bound at the VPS15 interface.

      They extensively validated the VPS15 interface in the yeast variant of VPS34, showing that the Vp215-Rab5 (VPS21) interface identified is critical in controlling complex II VPS34 recruitment.

      The major strengths of this paper are that the experiments appear to be done carefully and rigorously, and I have very few experimental suggestions.

      Here is what I recommend based on some very minor weaknesses I observed

      (1) My main concern has to do a little bit with presentation. My main issue is how the authors use mutant description. They clearly indicate the mutant sequence in the human isoform (for example, see Figure 2A, VPS15 described as 579-SHMIT-583>DDMIE); however, when they shift to the yeast version, they shift to saying VPS15 mutant, but don't define the mutant, Figure 2G). I would recommend they just include the same sequence numbering and WT to mutant replacement every time a new mutant (or species) is described. It is always easier to interpret what is being shown when the authors are jumping between species, when the exact mutant is included. This is particularly important in this paper, where we are jumping between different subunits and different species, so a clear description in the figure/figure legends makes it much easier to read for non-specialists.

      (2) The HDX data very clearly shows that Rab5 is likely able to bind at both sites, which back ups the cryo EM data nicely. I am slightly confused by some of the HDX statements described in the methods.

      (3) The authors state, "Only statistically significant peptides showing a difference greater than 0.25 Da and greater than 5% for at least two timepoints were kept." This seems to be confusing as to why they required multiple timepoints, and before they also describe that they required a p-value of less than 0.05. It might be clearer to state that significant differences required a 0.25 Da, 5%, and p-value of <0.05 (n=3). Also, what do they mean by kept? Does this mean that they only fully processed the peptides with differences?

      (4) They show peptide traces for a selection in the supplement, but it would be ideal to include the full set of HDX data as an Excel file, including peptides with no differences, as there is a lot of additional information (deuteration levels for everything) that would be useful to share, as recommended from the Masson et al 2019 recommendations paper. This may be attached, but this reviewer could not see an example of it in the shared data dropbox folder.

    1. Reviewer #2 (Public review):

      Summary:

      The authors conducted a brain-wide survey of Avp (arginine vasopressin) and its Avpr1a gene expression in the mouse brain using RNAscope, a high-resolution in situ hybridization method. Overall, the findings are useful and important because they identify brain regions that express the Avpr1a transcript. A comprehensive overview of Avpr1a expression in the mouse brain could be highly informative and impactful. The authors used RNAscope (a proprietary in situ hybridization method) to assess transcript abundance of Avp and one of its receptors, Avpr1a. The finding of Avp-expressing cells outside the hypothalamus and the extended amygdala is novel and is nicely demonstrated by new photomicrographs in the revised manuscript. The Avpr1a data suggest expression in numerous brain regions. In the revised manuscript, reworked figures make the data easier to interpret.

      Strengths:

      A survey of Avpr1a expression in the mouse brain is an important tool for exploring vasopressin function in the mammalian brain and for developing hypotheses about cell- and circuit-level function.

      Future considerations:

      The work contained in the manuscript is substantial and informative. Some questions remain and would be addressed in the current manuscript. How many cells are impacted? Are transcripts spread across many cells or only present in a few cells? Is density evenly distributed through a brain region or compacted into a subfield?

    1. Reviewer #2 (Public review):

      Summary:

      The authors used the Drosophila heart tube to model Retinal vasculopathy with the goal of building a model that could be used to identify druggable targets and for testing chemical compounds that might target the disease. They generated flies expressing human TREX1 as well as a line expressing the V235G mutation that causes a C-terminal truncation that has been linked to the disease. In humans, this mutation is dominant. Heart tube function was monitored using OCM; the most robust change upon overexpression of wild-type or mutant TREX1was heart tube restriction, and this effect was similar for both forms of TREX1. Lifespan and climbing assays did show differential effects between wt and mutant forms when they were strongly and ubiquitously expressed by an actin-Gal4 driver. Unfortunately, these types of assays are less useful as drug screening tools. Their conclusion that the primary effect of TREX is on neuronal function is inferential and not directly supported by the data.

      Strengths:

      The authors do not show that CG3165 is normally expressed in the heart. Further fly heart tube function was similarly restricted in response to expression of either wild-type or mutant TREX1. The fact that expression of any form of human TREX1 had deleterious effects on heart function suggests that TREX1 serves different roles in flies compared to humans. Thus, in the case of this gene, it may not be a useful model to use to identify targets or use it as a drug screening tool.

      The significant effects on lifespan and climbing that did show differential effects required ubiquitous overexpression using an actin-gal4 driver that does not allow the identification of tissue-specific effects. Thus, their assertion that the results suggested a strong positive correlation between Drosophila neuromotor regulation and transgenic hTREX1 presence and a negative impact from hTREX1 V235G" is not supported by these data. Also worrisome was the inability to identify the mutant TREX1 protein by Western blot despite the enhanced expression levels suggested by qPCR analysis. Mutant TREX1 cannot exert a dominant effect on cell function if it isn't present.

      There are also some technical problems. The lifespan assays lack important controls, and the climbing assays do not appear to have been performed correctly. It is unclear what the WT genetic background is in Figure 1-3, so it is unclear if the appropriate controls have been used. Finally, the lack of information on the specific statistical analyses used for each graph makes it difficult to judge the significance of the data. Overall, the current findings establish the Retinal vasculopathy disease model platform, but with only incremental new data and without any mechanistic insights.

    1. Reviewer #2 (Public review):

      Summary:

      The authors have used a knock-in mouse model to explore late-in-life amyloid effects on sleep. This is an excellent model as the mutated genes are regulated by the endogenous promoter system. The sleep study techniques and statistical analyses are also first-rate.

      The group finds an age-dependent increase in motor activity in advanced age in the NLGF homozygous knock-in mice (NLGF), with a parallel age-dependent increase in body temperature, both effects predominate in the dark period. Interestingly, the sleep patterns do not quite follow the sleep changes. Wake time is increased in NLGF mice, and there is no progression in increased wake over time. NREMS and REM sleep are both reduced, and there is no progression. Sleep-wake effects, however, show a robust light:dark effect with larger effects in the dark period. These findings support distinct effects of this mutation on activity and temperature and on sleep. This is the first description of the temporal pattern of these effects. NLGF mice show wake stability (longer bout durations in the dark period (their active period) and fewer brief arousals from sleep. Sleep homeostasis across the lights-on period is normal. Wake power spectral density is unaffected in NLGF mice at either age. Only REM power spectra are affected, with NLGF mice showing less theta and more delta. There are interesting sex differences, with females showing no gene difference in wake bout number, while males show a gene effect. Similarly, gene effects on NREM bout number seem larger in males than in females. Although there was no difference in homeostatic response, there was normalization of sleep-wake activity after sleep deprivation.

      Strengths:

      Approach (model extent of sleep phenotyping), analysis.

      Weaknesses:

      The weaknesses are summarized below and are viewed as "addressable".

      (1) The term insomnia. Insomnia is defined as a subjective dissatisfaction with sleep, which cannot be ascertained in a mouse model. The findings across baseline sleep in NLGF mice support increased wake consolidation in the active period. The predominant sleep period (lights on) is largely unaffected, and the active period (lights off) shows increased activity and increased wake with longer bouts. There is a fantastic clue where NLGF effects are consistent with increased hypocretinergic (orexinergic) neuron activity in the dark period, and/or increased drive to hypocretin neurons from PVH.

      (2) Sleep-wake transitions are impaired: This should not be termed an impairment. It could actually be beneficial to have greater state stability, especially wake stability in the dark or active period. There is reduced sleep in the model that can be normalized by short-term sleep loss. It is fascinating that recovery sleep normalized sleep in the NLGF in the immediate lights-on and light-off period. This is a key finding.

    1. Reviewer #2 (Public review):

      This study presents an important analysis of how interactions between muscles can serve as biomarkers to quantify therapeutic responses in post-stroke patients. To do so, the authors employ an information-theoretical metric (co-information) to define muscle networks and perform cluster analysis.

      I thank the authors for improving the clarity of the Methods section; the newly added Figure 5 is very helpful.

      One minor suggestion is that the authors should avoid overloading the notation "m" for both the EEG measurement and the matrix of II values (Eq. 1.1), which I now realise was the source of some of my initial confusion. I suggest that the authors use separate notation for these two quantities.

    1. Reviewer #2 (Public review):

      Summary:

      The authors developed a cell-type-specific fluorescence-tagging approach using a CRISPR/Cas9 induced spilt-GFP reconstitution system to visualize endogenous Bruchpilot (BRP) clusters at presynaptic active zones (AZ) in specific cell types of the mushroom body (MB) in the adult Drosophila brain. This AZ profiling approach was implemented in a high-throughput quantification process allowing to compare synapse profiles within single cells, cell-types, MB compartments and between different individuals. Aim is to in more detail analyze neuronal connectivity and circuits in this center of associative learning, notoriously difficult to investigate due to the density of cells and structures within the cells. The authors detect and characterize cell-type specific differences in BRP-dependent profiling of presynapses in different compartments of the MB, while intracellular AZ distribution was found to be stereotyped. Next to the descriptive part characterizing various AZ profiles in the MB, the authors apply an associative learning assay and Rab3 knock-down and detected consequent AZ reorganization.

      Strengths:

      The strength of this study lies in the outstanding resolution of synapse profiling in the extremely dense compartments of the MB. This detailed analysis will serve as an entry point for many future studies of synapse diversity in connection with functional specificity to uncover the molecular mechanisms underlying learning and memory formation and neuronal network logic. Therefore, this approach is of high importance to the scientific community and represents a valuable tool to investigate and correlate AZ architecture and synapse function in the CNS.

      Weaknesses:

      The results and conclusions presented in this study are conclusively and well supported by the data presented and appropriate controls. As a comment that could possibly aid and strengthen the manuscript (but not required for acceptance of the manuscript): The experiments in the study are based on spilt-GFP lines (BRP:GFP11 and UAS-GFP1-10). The authors clearly validate the new on-locus construct with a genomic GFP insertion (qPCR, confocal and STED imaging of the brain with anti-BRP (Nc82), MB morphology and memory formation). It would be important to comment on the significant overall intensity decrease of anti-BRP (Nc82) in Fig. S1B (R57C10>BRP::rGFP) and possibly a Western Blot with a correlative antibody staining against BRP might help to show that BRP protein level are not affected. Additionally, it would be important to state, at least in the Materials and Methods section, that the flies are not homozygous viable (and to offer an explanation) and to state that all experiments were performed with heterozygous flies.

    1. Reviewer #2 (Public review):

      Summary:

      In this EEG study, Huang et al. investigated the relative contribution of two accounts to the process of conflict control, namely the stimulus-control association (SC), which refers to the phenomenon that the ratio of congruent vs. incongruent trials affects the overall control demands, and the stimulus-response association (SR), stating that the frequency of stimulus-response pairings can also impact the level of control. The authors extended the Stroop task with novel manipulation of item congruencies across blocks in order to test whether both types of information are encoded and related to behaviour. Using decoding and RSA they showed that the SC and SR representations were concurrently present in voltage signals and they also positively co-varied. In addition, the variability in both of their strengths was predictive of reaction time. In general, the experiment has a sold design and the analyses are appropriate for the research questions.

      Strength:

      (1) The authors used an interesting task design that extended the classic Stroop paradigm and is effective in teasing apart the relative contribution of the two different accounts regarding item-specific proportion congruency effect.

      (2) Linking the strength of RSA scores with behavioural measure is critical to demonstrating the functional significance of the task representations in question.

      Weakness:

      (1) The distinction between Phase 2 and Phase 1&3 behavioral results, specifically the opposite effect of MC/MI in congruent trials raises some concerns with regard to the effectiveness of the ISPC manipulation. Why do RTs and error rates under MC congruent condition in Phase 2 seem to be worse than MI congruent? Could there be other factors at play here, e.g. order effect? How does this potentially affect the neural analyses where trials from different phases were combined? Also, the manuscript does not mention whether there is counterbalancing for the color groups across participants, so far as I can tell.

    1. Reviewer #2 (Public review):

      Summary and overall evaluation:

      The authors assessed how visual discrimination of stimuli in the foveola changes before, during, and after small instructed eye movements (in the "micro" range). Consistent with (and advancing) related prior work, their main finding regards a pre-saccadic modulation of visual performance at the saccade target vs. the opposite location. This pre-saccadic modulation in foveal vision peaks ~70 ms prior to the instructed small saccade.

      Strengths:

      The study uses an impressive, technically advanced set-up and zooms in on peri-saccadic modulations in visual acuity at the micro scale. The findings build on related prior findings from the literature on smaller and larger eye movements and add temporal granularity over prior work from the same lab. The writing is easy to follow, and the figures are clear.

      Weaknesses:

      At the same time, the findings remain relatively empirical in nature and do not profoundly advance theoretical understanding beyond adding valuable granularity to existing knowledge. Relevant prior literature could be better introduced and acknowledged. In addition, there remain concerns regarding potential cue-driven attentional influences that may confound the reported effects (leaving the possibility that the reported effects may be related to cue-driven attention, rather than saccade planning/execution per se). There are also some issues regarding specific statistical inferences. I detail these points below.

      Major Points:

      (1) Novelty framing and introduction of relevant prior literature

      At times, this study is introduced as if no prior study explored the time course of changes in visual perception surrounding small (micro) saccades. Yet, it appears that a prior study from the same lab, using a very similar task, already showed a time course (Figure 5 in Shelchkova & Poletti, 2020). While this study is discussed in the introduction, it is not mentioned that at least some pre-saccade time course was already reported there, albeit a more crude one than the one in the current article. Moreover, the 2013 study by Hafed also specifically looked at "peri-microsaccade modulation in visual perception" and also already showed a temporal modulation that peaked ~50 ms before microsaccade onset. I appreciate how the current study differs in a number of ways (focusing on visual acuity in the foveola), but I was nevertheless surprised to see the first reference to this relevant prior finding in the discussion (and without any elaboration). Though more recent, the same could be argued for the 2025 study by Bouhnik et al. on pre-microsaccade modulations in visual processing in V1, which, like the Hafed study, is first mentioned only in the discussion. Perhaps these studies could be introduced in the paragraph starting at line 48, or in the next paragraph, to do better justice to the existing literature on this topic when motivating the study. This would likely also help to better point out the major advances provided by the current study.

      Relatedly, in Shelchkova & Poletti (PNAS, 2020), an apparently similar congruency effect on performance was reported >200 ms milliseconds before saccade onset, as evident from Fig 5 in that article. How should readers rhyme this with the current findings? Ideally, the authors would not only acknowledge that such a time course was already reported previously, but also discuss the discrepancies between these findings further: why may the performance effects appear much earlier in this prior study compared to in the current study, where the congruency effect emerges only ~100 ms prior to the instructed small saccade?

      (2) Saccade- or cue-driven? (assumption that attention is unaltered in failed saccade trials)

      Because the authors used a cue to instruct saccade direction, it remains a possibility that the reported modulations in visual performance may be driven directly by the spatial cue (cue-related attentional allocation), rather than the instructed small saccade per se. While the authors are clearly aware of this potential confound, questions remain regarding the convincingness of the presented control analyses. In my view, a more compelling control would require an additional experiment.

      The central argument against a cue-locked (purely attentional) modulation is the absence of a performance modulation in so-called "failed" saccade trials. However, a key assumption here is that putative cue-driven attention was unaltered in these trials. This is never verified and, in my opinion, highly unlikely. Rather, trials with failed microsaccades could very well be the result of failing to process the cue in the first place (indeed, if the task is to make a saccade to the cue, failure to make a saccade equates failure to perform the task). In such trials, any putative cue-driven influences over spatial attention would also be expected to be substantially reduced. Accordingly, just because failed saccade trials show little performance modulation does not rule out cue-driven attention effects, because attention may also have "failed" in these failed saccade trials. The control for potential cue-driven attention effects would be more convincing if the authors included a condition with the same cues, where participants are simply not instructed to make any saccades to the cues. Unfortunately, such an experimental condition appears not to have been included here. The author may still consider adding such a control experiment.

      Another argument against a cue-driven effect is that the authors found no interaction with time in the cue-locked data, whereas they did find such an interaction in the saccade-locked data. However, the lack of significance in the cue-locked data but significance in the saccade-locked data is not strong evidence against a cue-driven influence. Statistically, there is no direct comparison here, and more importantly, with longer delays, the cue-locked data may also start to show a dip (this could potentially be tested by the authors if they have enough trials available to extend their cue-locked analysis further in time). Indeed, exogenous attention, that may have been automatically evoked by the spatial cue, is known to be transient and to eventually even reverse after a brief initial facilitation (see e.g., Klein TiCS, 2000).

      Finally, the authors consistently refer to "endogenous" attention (starting at line 221) when addressing potential cue-driven attention confounds. However, because the cue is not predictive, but is a spatial cue that differs in a bottom-up manner between left and right cues, "exogenous" attention is a more likely confound here in my view. Specifically, the spatial cue may automatically trigger attention in the direction of the target location it points to (and such exogenous effects would be expected even for unpredictive cues).

      (3) Benefit and cost, or just cost?

      Line 151 states that no statistically significant benefit for the saccade target was found compared to the neutral baseline. Yet, the claim throughout the article is distinct, such as in line 159: "These results show that approximately 100 milliseconds before microsaccade onset, discrimination rapidly improved at the intended target location". I do not question the robustness of the congruency effect, but the authors should be more careful when inferring "improved" perception at the target location because, as far as I could tell (as well as in the authors' own writing in line 151), this is not substantiated statistically when compared to the neutral baseline.

      Related to this point, in Figure 3B, it would be informative to also see the average performance in the neutral cue condition (for example, as a straight line as in some other figures). This would help to better appreciate the relative benefits and/or costs compared to the neutral condition, also in the time-resolved data.

      (4) Statistical inference for the comparison between failed and non-failed trials

      Currently, the lack of modulation in the failed saccade trials hinges on a null effect. It would be stronger to support the claims with a significant difference in the congruency effect between failed and non-failed trials. Indeed, lack of significance in failed saccade trials does by itself not constitute valid evidence that the congruency effect is larger in saccade compared to failed saccade trials. For this, a significant interaction between saccade-trial-type (failed/non-failed) and congruency (congruent/incongruent) should be established (see e.g., Nieuwenhuis et al., Nat Neurosci, 2011).

      (5) Time window justification

      While the authors nicely depict their data across the full time axis, all statistics are currently performed on data extracted from specific time windows. How exactly were these time windows determined and justified? Likewise, how were the specific times picked for visualizing and statistically quantifying the data in e.g., Figures 3D and E? It would be reassuring to add justification for these specific time windows and/or to verify (using follow-up analyses) that the presented results are robust when different time windows are chosen.

      (6) Microsaccade definition

      Microsaccades are explicitly defined as being below half a degree. This appears rather arbitrary and rigid. Does the size of saccades not ultimately depend on the task and stimulus (e.g., Otero-Millan et al., PNAS, 2013) rather than being a fixed biological property? Perhaps this could be stated less rigidly, such as by stating how microsaccades are often observed below 0.5 degrees.

      (Relatedly, one may wonder whether the type of instructed saccades that the authors studied here involves the same type of eye movements as the type of fixational microsaccades that have been the focus of ample prior studies. However, I recognize that this specific reflection may open a debate that is beyond the scope of this article.

    1. Reviewer #2 (Public review):

      Summary:

      This study investigates the role of spinal astrocytes in mediating stress-induced pain hypersensitivity, focusing on the LC (locus coeruleus)-to-SDH (spinal dorsal horn) circuit and its mechanisms. The authors aimed to delineate how LC activity contributes to spinal astrocytic activation under stress conditions, explore the role of noradrenaline (NA) signaling in this process, and identify the downstream astrocytic mechanisms that influence pain hypersensitivity.

      The authors provide strong evidence that 1-hour restraint stress-induced pain hypersensitivity involves the LC-to-SDH circuit, where NA triggers astrocytic calcium activity via alpha1a adrenoceptors (alpha1aRs). Blockade of alpha1aRs on astrocytes-but not on Vgat-positive SDH neurons-reduced stress-induced pain hypersensitivity. These findings are rigorously supported by well-established behavioral models and advanced genetic techniques, uncovering the critical role of spinal astrocytes in modulating stress-induced pain.

      However, the study's third aim-to establish a pathway from astrocyte alpha1aRs to adenosine-mediated inhibition of SDH-Vgat neurons-is less compelling. While pharmacological and behavioral evidence is intriguing, the ex vivo findings are indirect and lack a clear connection to the stress-induced pain model. Despite these limitations, the study advances our understanding of astrocyte-neuron interactions in stress-pain contexts and provides a strong foundation for future research into glial mechanisms in pain hypersensitivity.

      Strengths:

      The study is built on a robust experimental design using a validated 1-hour restraint stress model, providing a reliable framework to investigate stress-induced pain hypersensitivity. The authors utilized advanced genetic tools, including retrograde AAVs, optogenetics, chemogenetics, and subpopulation-specific knockouts, allowing precise manipulation and interrogation of the LC-SDH circuit and astrocytic roles in pain modulation. Clear evidence demonstrates that NA triggers astrocytic calcium activity via alpha1aRs, and blocking these receptors effectively reduces stress-induced pain hypersensitivity.

      Weaknesses:

      The study offers mainly indirect evidence for astrocyte-released adenosine acting on SDH-VGAT neurons. The potential contributions of astrocyte-derived D-serine and adenosine to different spinal neuron subtypes, as well as the transient "dip" in astrocytic calcium following LC optostimulation, merit further clarification in future work once appropriate tools become available.

      Comments on revisions:

      The authors have thoroughly addressed my previous comments, resolving most of the points I raised except those noted in the "Weaknesses" section above. I understand that some of these aspects will require future tool development.

    1. Reviewer #2 (Public review):

      Summary:

      This manuscript uses single-molecule run-off experiments and TASEP/HMM models to estimate biophysical parameters, i.e., ribosomal initiation and elongation rates. Combining inferred initiation and elongation rates, the authors quantify ribosomal density. TASEP modeling was used to simulate the mechanistic dynamics of ribosomal translation, and the HMM is used to link ribosomal dynamics to microscope intensity measurements. The authors' main conclusions and findings are:

      - Ribosomal elongation rates and initiation rates are strongly coordinated.

      - Elongation rates were estimated between 1 and 4.5 aa/sec. Initiation rates were estimated between 1 and 2 ribosomes/min. These values agree with previously reported ones.

      - Ribosomal density was determined to be below 12% for all constructs and conditions.

      - eIF5A-perturbations (GC7 inhibition) resulted in non-significant changes in translational bursting and ribosome density.

      - eIF5A perturbations affected both elongation and initiation rates.

      Strengths:

      This manuscript presents an interesting scientific hypothesis to study ribosome initiation and elongation concurrently. This topic is relevant for the field. The manuscript presents a novel quantitative methodology to estimate ribosomal initiation rates from Harringtonine run-off assays. This is relevant because run-off assays have been used to estimate, exclusively, elongation rates.

      Comments on revisions:

      The authors have addressed my concerns. Specifically, they have expanded the discussion on unexpected eIF5A perturbation results, calculated CAI values for all constructs, and made code and data publicly available via GitHub and Zenodo. The mathematical notation is now consistent, and all variables are properly defined.

    1. Reviewer #2 (Public review):

      Summary:

      Neural stem cells produce a wide variety of neurons during development. The regulatory mechanisms of neural diversity are based on the spatial and temporal patterning of neural stem cells. Although the molecular basis of spatial patterning is well-understood, the temporal patterning mechanism remains unclear. In this manuscript, the authors focused on the roles of cell cycle progression and cytokinesis in temporal patterning and found that both are involved in this process.

      Strengths:

      They conducted RNAi-mediated disruption on cell cycle progression and cytokinesis. As they expected, both disruptions affected temporal patterning in NSCs.

      Weaknesses:

      Although the authors showed clear results, they needed to provide additional data to support their conclusion sufficiently.

      For example, they can examine the effects of cell cycle acceleration on the temporal patterning.

    1. Reviewer #2 (Public review):

      Summary:

      This work addresses the question whether artificial deep neural network models of the brain could be improved by incorporating top-down feedback, inspired by the architecture of neocortex.

      In line with known biological features of cortical top-down feedback, the authors model such feedback connections with both, a typical driving effect and a purely modulatory effect on the activation of units in the network.

      To asses the functional impact of these top-down connections, they compare different architectures of feedforward and feedback connections in a model that mimics the ventral visual and auditory pathways in cortex on an audiovisual integration task.

      Notably, one architecture is inspired by human anatomical data, where higher visual and auditory layers possess modulatory top-down connections to all lower-level layers of the same modality, and visual areas provide feedforward input to auditory layers, whereas auditory areas provide modulatory feedback to visual areas.

      First, the authors find that this brain-like architecture imparts the models with a light visual bias similar to what is seen in human data, which is the opposite in a reversed architecture, where auditory areas provide feedforward drive to the visual areas.

      Second, they find that, in their model, modulatory feedback should be complemented by a driving component to enable effective audiovisual integration, similar to what is observed in neural data.

      Overall, the study shows some possible functional implications when adding feedback connections in a deep artificial neural network that mimic some functional aspects of visual perception in humans.

      Strengths:

      The study contains innovative ideas, such as incorporating an anatomically inspired architecture into a deep ANN, and comparing its impact on a relevant task to alternative architectures.

      Moreover, the simplicity of the model allows it to draw conclusions on how features of the architecture and functional aspects of the top-down feedback affects performance of the network.

      This could be a helpful resource for future studies of the impact of top-down connections in deep artificial neural network models of neocortex.

      Weaknesses:

      Some claims not yet supported.

      The problem is that results are phrased quite generally in the abstract and discussion, while the actual results shown in the paper are very specific to certain implementations of top-down feedback and architectures. This could lead to misunderstanding and requires some revisions of the claims in the abstract and discussion (see below).

      "Altogether our findings demonstrate that modulatory top-down feedback is a computationally relevant feature of biological brain..."

      This claim is not supported, since no performance increase is demonstrated for modulatory feedback. So far, only the second half of the sentence is supported: "...and that incorporating it into ANNs affects their behavior and constrains the solutions it's likely to discover."

      "This bias does not impair performance on the audiovisual tasks."

      This is only true for the composite top-down feedback that combines driving and modulatory effects, whereas modulatory feedback alone can impair the performance (e.g., in the visual tasks VS1 and VS2). The fact that modulatory feedback alone is insufficient in ANNs to enable effective cross-modal integration and requires some driving component is actually very interesting, but it is not stressed enough in the abstract. This is hinted at in the following sentence, but should be made more explicitly:

      "The results further suggest that different configurations of top-down feedback make otherwise identically connected models functionally distinct from each other, and from traditional feedforward and laterally recurrent models."

      "Here we develop a deep neural network model that captures the core functional properties of top-down feedback in the neocortex" -> this is too strong, take out "the", because very likely there are other important properties that are not yet incorporated.

      "Altogether, our results demonstrate that the distinction between feedforward and feedback inputs has clear computational implications, and that ANN models of the brain should therefore consider top-down feedback as an important biological feature."

      This claim is still not substantiated by evidence provided in the paper. First, the wording is a bit imprecise, because mechanistically, it is not really the feedforward versus feedback (a purely feedforward model is not considered at all in the paper), but modulatory versus driving. Moreover, the second part of the sentence is problematic: The results imply that, computationally/functionally, driving connections are doing the job, while modulatory feedback does not really seem to improve performance (best case, it does not do any harm). It is true that it is a feature that is inspired by biology, but I don't see why the results imply that (modulatory) top-down feedback should be considered in ANN models of the brain. This would require to show that such models either improve performance, or do improve the ability to fit neural data, both which are beyond the scope of the paper.

      The same argument holds for the following sentence, which is not supported by the results of the paper:

      "More broadly, our work supports the conclusion that both the cellular neurophysiology and structure of feed-back inputs have critical functional implications that need to be considered by computational models of brain function."

      Additional supplementary material required

      Although the second version checked the influence of processing time, this was not done for the most important figure of the paper, Figure 4. A central claim in the abstract "This bias does not impair performance on the audiovisual tasks" relies on this figure, because only with composite feedback the performance is comparable between the the "drive-only" and "brain-like" models. Thus, the supplementary Figure 3 should also include the composite networks and drive only network to check the robustness of the claim with respect to process time. This robustness analysis should then also be mentioned in the text. For example, it should be mentioned whether results in these networks are robust or not with respect to process time, whether there are differences between network architectures or types of feedback in general etc.

      Moreover, the current analysis for networks with modulatory feedback is a bit confusing. Why is the performance so low for the reverse model for a process time of 3 and 10? This is a very strong effect that warrants explanation. More details should be added in the caption as well. For example, are the models separately trained for the output after 3 and 10 processing steps for the comparison, or just evaluated at these times? Not training these networks separately might explain the low performance for some networks, so ideally networks are trained for each choice of processing steps.

    1. Reviewer #2 (Public review):

      Summary:

      The authors set out to investigate how well the onset of a self-initiated movement could be predicted at different times prior to action onset. To do so, they collected EEG and MEG data across 15 human participants who watched natural landscape images on a screen. These participants performed active self-initiated movements or observed passive actions to have a new image appear. By comparing the neural activity prior to active and time-matched passive actions, the authors found that even though a build-up of neural activity is visible close to 1s prior to action, action onset could only be reliably predicted around 100ms prior to action. These results confirm what was already suggested in previous literature: the commitment to action is only clear from the late stages in the visible neural ramp-up to action onset.

      Strengths:

      (1) The paper presents a well-thought-out methodology to assess the predictive value of neural activity prior to a self-initiated movement and passively observed action, while keeping all other experimental factors identical. This methodology can be applied outside the specific scope of this paper as well, in efforts to assess the correspondence of a neural signature with an observed behavior.

      (2) The results are a strong confirmation of what was suggested less clearly in previous research (Trevena & Miller, 2010, Consciousness & Cognition; Schmidt et al., 2016, Neuroscience & Biobehavioral Reviews; Travers et al., 2020, NeuroImage).

      Weaknesses:

      (1) Although the authors conducted a solid confirmatory study, the importance of this confirmation is less clear to me. How do the current results change our interpretation of the relation between conscious intention and neural preparation for action? Do these results affect our interpretation of free will? Why does it matter at all whether we see neural preparatory activity prior to the report of a conscious intention to act, or prior to action observation? This study does not clarify the relationship between the observed neural phenomenon, the action or the experienced intention. It does not explain whether this relation is causal, correlational or something else.

      (2) Whereas Derchi et al. (2023, Scientific Reports) were able to keep the entire experimental context similar across intended and unintended conditions, Jeay-Bizot et al. have one big difference between their passive and active conditions: the presence of a movement. Therefore, the present results explain the presence or absence of a movement rather than the presence or absence of an intention to act.

    1. Reviewer #2 (Public review):

      In this article, Schmidt et al use iPSC-derived human cortical neurons to test the effects the psychedelic psilocin in different models of neuroplasticity.

      Using human iPSC-derived cortical neurons, the authors test the expression of 5-HT2A and subcellular distribution, as well as the effect of different times of exposure to psilocin on 5-HT2A expression. The authors evaluated the effect of the 5-HT2 antagonist ketanserin, as well as the inhibition of dynamin-dependent endocytic pathways with dynasore. Gene expression and plasticity (structural and functional) was also evaluated after different times of exposure to psilocin.

      In general, results are interesting since they use the iPSC to evaluate the potentially translationally relevant effects of psilocin (the active metabolite of the psychedelic psilocybin).

      Comments on revisions:

      The authors have addressed all of my previous concerns. A particular strength of the rebuttal is that the authors corroborated the lack of selectivity/specificity of the anti-5-HT2A antibody used in earlier versions of the manuscript.

    1. Reviewer #2 (Public review):

      Summary:

      The authors used experimental evolution, repeatedly subjecting Saccharomyces cerevisiae populations to rapid liquid-nitrogen freeze-thaw cycles, while tracking survival, cellular biophysics, metabolite levels, and whole-genome sequence changes. Within 25 cycles, viability rose from ~2 % to ~70 % in all independent lines, demonstrating rapid and highly convergent adaptation despite distinct starting genotypes. Evolved cells accumulated about three-fold more intracellular trehalose, adopted a quiescence-like phenotype (smaller, denser, non-budding cells), showed cytoplasmic stiffening and reduced membrane damage, and re-entered growth with shorter lags-traits that together protected them from ice-induced injury. Whole-genome indicated that multiple genetic routes can yield the same mechano-chemical survival strategy. A population model in which trehalose controls quiescence entry, growth rate, lag, and freeze-thaw survival reproduced the empirical dynamics, implicating physiological state transitions rather than specific mutations as the primary adaptive driver. The study therefore concludes that extreme-stress tolerance can evolve quickly through a convergent, trehalose-rich quiescence-like state that reinforces membrane integrity and cytoplasmic structure.

      Strengths:

      Experimental design, data presentation and interpretation, writing

      Weaknesses:

      None

      Comments on revisions:

      The revised manuscript is improved and addresses the reviews concerns adequately.

    1. Reviewer #2 (Public review):

      Summary:

      The altered metabolism of tumors enables their growth and survival. Classically, tumor metabolism often involves increased activity of a given pathway in intermediary metabolism to provide energy or substrates needed for growth. Papadopoli et al. investigate the converse - the role of mitochondrial electron transfer flavoprotein dehydrogenase (ETFDH) in cancer metabolism and growth. The authors present compelling evidence that ETFDH insufficiency, which is detrimental in non-malignant tissues, paradoxically enhances bioenergetic capacity and accelerates neoplastic growth in cancer cells in spite of the decreased metabolic fuel flexibility that this affords tumor cells. This is achieved through the retrograde activation of the mTORC1/BCL-6/4E-BP1 axis, leading to metabolic and signaling reprogramming that favors tumor progression.

      Strengths:

      This review focuses primarily on the cancer metabolism aspects of the manuscript.

      The study provides robust evidence linking ETFDH insufficiency to enhanced cancer cell bioenergetics and tumor growth.

      The use of multiple cancer cell lines and in vivo models strengthens the generalizability of the findings.

      The mechanistic insights into the mTORC1/BCL-6/4E-BP1 axis and its role in metabolic reprogramming are of general interest within and outside the immediate field of tumor metabolism.

      Conclusion:

      This manuscript provides significant insights into the role of ETFDH insufficiency in cancer metabolism and growth. The findings highlight the potential of targeting the mTORC1/BCL-6/4E-BP1 axis in ETFDH-deficient cancers. The compelling data support the conclusions presented in the manuscript, which will be valuable to the cancer metabolism community.

      [Editors' note: The authors have addressed each of the two weaknesses previously listed in the public review, providing new experimental data on nucleotides and showing that the catalytic activity is required via the suggested addback experiment.]

    1. Reviewer #2 (Public review):

      The substantially revised paper has increased in clarity and is much more accessibe and straightforward than the first version. The analyses are now clearer and support the conclusions better. There are however some remaining methodological weakness, which in my mind still renders the evidence to not be entirely convincing.

      (1) The temporal autocorrelation concern is not fully convincingly addressed. The temporal autocorrelation curves supplied in the supplements are really helpful, but linearly regressing out the temporal distance from the neural distance clearly does not work, as one can see from the right panel of supplementary Figure 1. If the method had worked correctly the line should have been flat. The analysis however shows that decision trials with a lag > 2 are basically independent - so a simple way to address this is to restrict the RSA analysis to trials with a decision lag of > 2. This analysis would strengthen the paper a lot.

      (2) In the final analysis, the authors use all the trials to make the claim that the hippocampus represents the characters in a shared social space. However, as within-character distances are still included in the analysis, this result could still be driven by the effects of within-character representations that are not shared across characters. A simple way of addressing this concern would be to only include between-character distances in this analysis, making it truly complementary to the previous within-character analysis. It would also be very interesting to compare the the within- and between-character analyses in the hippocampus directly.

      (3) Overall, the correction for multiple comparisons in the fMRI and the resulting corrected p-values are not sufficiently explained and documented in the paper. What was exactly permuted in the tests? Was correction applied in a voxel-wise or cluster-wise fashion? If cluster-wise, the cluster-wise p-values need to be reported.

    1. Reviewer #2 (Public review):

      Summary:

      This study investigates the involvement of first-order thalamic nuclei in language-related tasks using task-based fMRI in a 3 × 2 design contrasting linguistic and non-linguistic versions of reading, speech comprehension, and speech production. By focusing on the LGN, MGN, and VLN and combining activation, connectivity, lateralization, and multivariate pattern analyses, the authors aim to characterize modality-specific and language-related thalamic contributions.

      Strength:

      A major strength of the work is its hypothesis-driven and multimodal analytical approach, and the modality-specific engagement of first-order thalamic nuclei is robust and consistent with known thalamocortical organization. This is a very sound study overall.

      Weaknesses:

      However, several conceptual issues complicate the interpretation of the results as evidence for linguistic modulation per se. A central concern relates to the operationalization of the linguistic versus non-linguistic contrast. In the present design, linguistic and non-linguistic stimuli differ along multiple dimensions beyond linguistic content. For example, written words and scrambled images differ in spatial frequency structure, edge composition, contrast regularities, and familiarity, while intelligible speech and acoustically scrambled sounds differ substantially in temporal and spectral statistics. This is particularly relevant given that first-order thalamic nuclei such as the LGN are known to be highly sensitive to low-level sensory properties. As a result, observed differences in thalamic responses may reflect sensitivity to stimulus properties rather than linguistic processing per se, and this limits the specificity of claims regarding linguistic modulation.

      Relatedly, although the manuscript frequently refers to effects "depending on the linguistic nature of the stimuli," the statistical evidence for linguistic versus non-linguistic modulation is uneven across analyses. Whole-brain contrasts collapse across stimulus type and primarily test modality effects. Similarly, the primary ROI analyses of activation amplitude are collapsed across linguistic and non-linguistic conditions and convincingly demonstrate modality-specific engagement of thalamic nuclei, but do not in themselves provide evidence for linguistic modulation. Linguistic effects emerge only in later, more targeted analyses focusing on hemispheric lateralization and multivariate pattern classification, and these effects are nucleus-, modality-, and analysis-specific rather than general. Taken together, these results suggest that linguistic modulation constitutes a secondary and selective finding, whereas modality-specific task engagement represents the primary and most robust outcome of the study.

      An additional interpretational issue concerns task engagement and attention. The tasks differ substantially in cognitive demands (e.g., passive reading and listening versus overt speech production), and linguistic and non-linguistic blocks may differ systematically in salience or engagement. This is particularly important given prior evidence, cited by the authors, that LGN and MGN activity can be modulated by task demands and attention. In the absence of behavioral measures indexing task engagement or compliance, it is difficult to determine whether differences between linguistic and non-linguistic conditions reflect linguistic processing per se or are mediated by attentional factors.

      Finally, while the manuscript emphasizes the novelty of evaluating thalamic involvement in language, thalamic contributions to language have been documented previously in both lesion and functional imaging studies. The contribution of the present work, therefore, lies less in establishing thalamic involvement in language per se, and more in its focus on specific first-order nuclei, its multimodal design, and its combination of univariate, connectivity, and multivariate analyses. Moderating claims of novelty would help place the findings more clearly within the existing literature.

    1. Reviewer #2 (Public review):

      Summary:

      The manuscript reports a cryo-EM structure of TMAO demethylase from Paracoccus sp. This is an important enzyme in the metabolism of trimethylamine oxide (TMAO) and trimethylamine (TMA) in human gut microbiota, so new information about this enzyme would certainly be of interest.

      Strengths:

      The cryo-EM structure for this enzyme is new and provides new insights into the function of the different protein domains, and a channel for formaldehyde between the two domains.

      Weaknesses:

      (1) The proposed catalytic mechanism in this manuscript does not make sense. Previous mechanistic studies on the Methylocella silvestris TMAO demethylase (FEBS Journal 2016, 283, 3979-3993, reference 7) reported that, as well as a Zn2+ cofactor, there was a dependence upon non-heme Fe2+, and proposed a catalytic mechanism involving deoxygenation to form TMA and an iron(IV)-oxo species, followed by oxidative demethylation to form DMA and formaldehyde.

      In this work, the authors do not mention the previously proposed mechanism, but instead say that elemental analysis "excluded iron". This is alarming, since the previous work has a key role for non-heme iron in the mechanism. The elemental analysis here gives a Zn content of about 0.5 mol/mol protein (and no Fe), whereas the Methylocella TMAO demethylase was reported to contain 0.97 mol Zn/mol protein, and 0.35-0.38 mol Fe/mol protein. It does, therefore, appear that their enzyme is depleted in Zn, and the absence of Fe impacts the mechanism, as explained below.

      The proposed catalytic mechanism in this manuscript, I am sorry to say, does not make sense to me, for several reasons:

      (i) Demethylation to form formaldehyde is not a hydrolytic process; it is an oxidative process (normally accomplished by either cytochrome P450 or non-heme iron-dependent oxygenase). The authors propose that a zinc (II) hydroxide attacks the methyl group, which is unprecedented, and even if it were possible, would generate methanol, not formaldehyde.

      (ii) The amine oxide is then proposed to deoxygenate, with hydroxide appearing on the Zn - unfortunately, amine oxide deoxygenation is a reductive process, for which a reducing agent is needed, and Zn2+ is not a redox-active metal ion;

      (iii) The authors say "forming a tetrahedral intermediate, as described for metalloproteinase", but zinc metalloproteases attack an amide carbonyl to form an oxyanion intermediate, whereas in this mechanism, there is no carbonyl to attack, so this statement is just wrong.

      So on several counts, the proposed mechanism cannot be correct. Some redox cofactor is needed in order to carry out amine oxide deoxygenation, and Zn2+ cannot fulfil that role. Fe2+ could do, which is why the previously proposed mechanism involving an iron(IV)-oxo intermediate is feasible. But the authors claim that their enzyme has no Fe. If so, then there must be some other redox cofactor present. Therefore, the authors need to re-analyse their enzyme carefully and look either for Fe or for some other redox-active metal ion, and then provide convincing experimental evidence for a feasible catalytic mechanism. As it stands, the proposed catalytic mechanism is unacceptable.

      (2) Given the metal content reported here, it is important to be able to compare the specific activity of the enzyme reported here with earlier preparations. The authors do quote a Vmax of 16.52 µM/min/mg; however, these are incorrect units for Vmax, they should be µmol/min/mg. There is a further inconsistency between the text saying µM/min/mg and the Figure saying µM/min/µg.

      (3) The consumption of formaldehyde to form methylene-THF is potentially interesting, but the authors say "HCHO levels decreased in the presence of THF", which could potentially be due to enzyme inhibition by THF. Is there evidence that this is a time-dependent and protein-dependent reaction? Also in Figure 1C, HCHO reduction (%) is not very helpful, because we don't know what concentration of formaldehyde is formed under these conditions; it would be better to quote in units of concentration, rather than %.

      (4) Has this particular TMAO demethylase been reported before? It's not clear which Paracoccus strain the enzyme is from; the Experimental Section just says "Paracoccus sp.", which is not very precise. There has been published work on the Paracoccus PS1 enzyme; is that the strain used? Details about the strain are needed, and the accession for the protein sequence.

    1. Reviewer #2 (Public review):

      Summary:

      This study aimed to explore dynamic changes in the somatosensory representation of both the body and artificial body parts. The study investigated how proprioceptive localisation along the finger changes when participants wear, actively use, and then remove a hand augmentation device - a rigid finger-extension. By mapping perceived target locations along the biological finger and the extension across multiple stages, the authors aim to characterise how the somatosensory system updates our spatial body representation during and after interaction with body augmentation technology.

      Strengths:

      The manuscript addresses an interesting question of how augmentation devices alter proprioceptive localisation abilities. Conceptually, the work moves beyond classic tool-use paradigms by focusing on a device that is used with the hand to extend the fingers' abilities (versus a tool that is simply used by the hand), and by attempting to map perceived spatial structure across both biological and artificial segments within the same framework.

      A major strength is the multi-stage design, which samples localisation abilities at baseline, the beginning of device wear, post-training, and immediately post-removal. This provides a richer characterisation of short-term adaptation compared to a simple pre/post comparison. The dense sampling across stages and target locations generates a rich behavioural dataset that will be valuable to readers interested in somatosensory body representation. The within-subject, counterbalanced control session further strengthens interpretability, providing a useful comparison for interpreting stage-dependent effects, and to probe how functional training shapes changes in the perceptual representations. Finally, the augmentation device itself appears carefully engineered, with thoughtful design decisions regarding wearability, including comfort and customised fit. The manuscript is also communicated clearly, with transparent reporting of analyses and succinct figures that make the pattern changes across stages straightforward to evaluate.

      Weaknesses:

      There is conceptual ambiguity in how the regression outcomes are interpreted in relation to perceived length and spatial integration. The manuscript treats regression slope as a proxy for "length perception" and discards the intercept as "spatial bias," but in this localisation task translation (intercept) and scaling (slope) are coupled: changes in anchoring at the proximal baseline (intercept) or distal endpoint can generate slope differences without uniform rescaling across the mapped surface. Relatedly, the analyses do not establish whether the reported effects are global across targets or disproportionately driven by the most distal locations. This limits the strength of inferences about "partitioning" or "reallocation" of representational space across biological and artificial segments. Some interpretive statements also appear stronger than the evidence supports (e.g., describing the stage 2 bio-extension map as "geometrically accurate", despite Bayes factors that provide only anecdotal support for no difference from true length). Extensive repeated judgements to a fixed set of locations may additionally stabilise response strategies or anchoring even without feedback, complicating the separation of body-representation change from task-specific calibration.

      The manuscript would also benefit from clearer conceptual framing of what the device is and what its training probes are. The device is described variably as an "artificial finger" versus a rigid "finger extension," with different implications for perception and function. In addition, the training tasks appear to emphasise manipulation and dexterity more than scenarios requiring an extended reachable workspace (indeed, participants appear to have performed at least as well, if not better, in the control training), which brings into question whether participants explored the device's intended functionality and possible proprioceptive consequences. The control experiment is thoughtfully designed to test whether functional training contributes to the stage 3 changes, but because localisation is not performed while wearing the short device, the design does not resolve whether the stage 2 change and the post-removal aftereffect are specific to the augmentative extension versus more general consequences of wearing a device on the finger (and the following possible distorted distal cues).

      Finally, the immediate post-removal aftereffects are intriguing, but the mechanistic interpretation remains underspecified. As presented within the internal model framework, the magnitude and consistency of the aftereffect following brief exposure are difficult to reconcile with the stability expected from a lifetime biological finger model, and because the aftereffect is assessed only immediately after removal, its time course and functional significance remain unclear.

    1. Reviewer #2 (Public review):

      Summary:

      The paper by Stephens and co-workers provides important mechanistic insight into how hyaluronan synthase (HAS) coordinates alternating GlcNAc and GlcA incorporation using a single Type-I catalytic centre. Through cryo-EM structures capturing both "proofreading" and fully "inserted" binding poses of UDP-GlcA, combined with detailed biochemical analysis, the authors show how the enzyme selectively recognizes the GlcA carboxylate, stabilizes substrates through conformational gating, and requires a priming GlcNAc for productive turnover.

      These findings clarify how one active site can manage two chemically distinct donor sugars while simultaneously coupling catalysis to polymer translocation.

      The work also reports a DDM-bound, detergent-inhibited conformation that possibly illuminates features of the acceptor pocket, although this appears to be a purification artefact (it is indeed inhibitory) rather than a relevant biological state.

      Overall, the study convincingly establishes a unified catalytic mechanism for Type-I HAS enzymes and represents a significant advance in understanding HA biosynthesis at the molecular level.

      Strengths:

      There are many strengths.

      This is a multi-disciplinary study with very high-quality cryo-EM and enzyme kinetics (backed up with orthogonal methods of product analysis) to justify the conclusions discussed above.

      Comments on revisions:

      The suggestions made in the initial comments have all been responded to very well.

    1. Reviewer #2 (Public review):

      Summary:

      The manuscript by the Root laboratory and colleagues describes how the posterolateral cortical amygdala (plCoA) generates valenced behaviors. Using a suite of methods, the authors demonstrate that valence encoding is mediated by several factors, including spatial localization of neurons within the plCoA, glutamatergic markers, and projection. The manuscript shows convincingly that multiple features (spatial, genetic, and projection) contribute to overall population encoding of valence. Overall, the authors conduct many challenging experiments, each of which contains the relevant controls, and the results are interpreted within the framework of their experiments.

      Strengths:

      - The manuscript is well constructed, containing lots of data sets and clearly presented, in spite of the abundance of experimental results.

      - The authors should be commended for their rigorous anatomical characterizations and post-hoc analysis. In the field of circuit neuroscience, this is rarely done so carefully, and when it is, often new insights are gleaned as is the case in the current manuscript.

      - The combination of molecular markers, behavioral readouts and projection mapping together substantially strengthens the results.

      - The focus on this relatively understudied brain region in the context is valence is well appreciated, exciting and novel.

      Weaknesses:

      The weaknesses noted in the primary review have all been addressed adequately.

    1. Reviewer #2 (Public review):

      Summary:

      This manuscript by Rosenthal and Goldberg investigates interactions between artemisinins and its quinoline partner drugs currently used for treating uncomplicated Plasmodium falciparum malaria. The authors show that chloroquine (CQ), piperaquine, and amodiaquine antagonize dihydroartemisinin (DHA) activity, and in CQ-resistant parasites, the interaction is described as "superantagonism," linked to the pfcrt genotype. Mechanistically, application of the heme-reactive probe H-FluNox indicates that quinolines render cytosolic heme chemically inert, thereby reducing peroxide activation. The work is further extended to triple ACTs and ozonide-quinoline combinations, with implications for artemisinin-based combination therapy (ACT) design, including triple ACTs.

      Strengths:

      The manuscript is clearly written, methodologically careful, and addresses a clinically relevant question. The pulsing assay format more accurately models in vivo artemisinin exposure than conventional 72-hour assays, and the use of H-FluNox and Ac-H-FluNox probes provides mechanistic depth by distinguishing chemically active versus inert heme. These elements represent important refinements beyond prior studies, adding nuance to our understanding of artemisinin-quinoline interactions.

      Weaknesses:

      Several points warrant consideration. The novelty of the work is somewhat incremental, as antagonism between artemisinins and quinolines is well established. Multiple prior studies using standard fixed-ratio isobologram assays have shown that DHA exhibits indifferent or antagonistic interactions with chloroquine, piperaquine, and amodiaquine (e.g., Davis et al., 2006; Fivelman et al., 2007; Muangnoicharoen et al., 2009), with recent work highlighting the role of parasite genetic background, including pfcrt and pfmdr1, in modulating these interactions (Eastman et al., 2016). High-throughput drug screens likewise identify quinoline-artemisinin combinations as mostly antagonistic. The present manuscript adds refinement by applying pulsed-exposure assays and heme probes rather than establishing antagonism de novo.

      The dataset focuses on several parasite lines assayed in vitro, so claims about broad clinical implications should be tempered, and the discussion could more clearly address how in vitro antagonism may or may not translate to clinical outcomes. The conclusion that artemisinins are predominantly activated in the cytoplasm is intriguing but relies heavily on Ac-H-FluNox data, which may have limitations in accessing the digestive vacuole and should be acknowledged explicitly. The term "superantagonism" is striking but may appear rhetorical; clarifying its reproducibility across replicates and providing a mechanistic definition would strengthen the framing. Finally, some discussion points, such as questioning the clinical utility of DHA-PPQ, should be moderated to better align conclusions with the presented data while acknowledging the complexity of in vivo pharmacology and clinical outcomes.

      Despite these mild reservations, the data are interesting and of high quality and provide important new information for the field.

      Editor's Review of the Revision: The authors have provided a well-reasoned rebuttal to the comments of the three reviewers. Most of the changes were incorporated in their revised Discussion. Their data with the active heme probe H-FluNox are novel and the authors reveal interesting interactions between peroxide and 4-aminoquinoline-based antimalarials that open new avenues of research especially when considering antimalarial combinations that combine these chemical scaffolds. This study will be of broad interest to investigators studying and developing antimalarial drugs and combinations and the impact of Plasmodium falciparum resistance mechanisms. A minor recommendation would be that the authors state H-FluNox when referring to their small molecule probe in the abstract, so that it is captured in PubMed searches.

    1. Reviewer #2 (Public review):

      Summary:

      In this study, the authors identify a previously uncharacterised regulator of mitochondrial function using a genetic screen and propose a role for this protein in supporting mitochondrial protein production. They provide evidence that the protein localises to mitochondria, interacts with components of the mitochondrial translation machinery, and is required for normal heart function in an animal model.

      Strengths:

      A major strength of the work is the use of multiple independent approaches to assess mitochondrial activity and protein production, which together provide support for the central conclusions. The in vivo data linking loss of this factor to impaired heart function are particularly compelling and elevate the relevance of the study beyond a purely cell-based context.

      Weaknesses:

      Given prior reports placing this protein outside mitochondria, its mitochondrial localisation would benefit from more rigorous and quantitative validation, and the proposed mechanism of the interaction with the mitochondrial translation machinery remains only partially explored. In addition, the physiological analysis is largely limited to the heart, leaving open questions about how broadly this pathway operates across tissues.

      Major comments:

      (1) Evidence for mitochondrial localization of EOLA1<br /> EOLA1 has previously been reported as a nuclear and cytosolic protein and is not annotated in MitoCarta 3.0, making rigorous validation of its mitochondrial localization particularly important. Although the authors provide several lines of evidence, interpretation is complicated by the use of different cell lines across localization, interaction, and functional experiments. Greater consistency in the cellular models used would strengthen the conclusions. The immunofluorescence analysis of tagged EOLA1 would also benefit from quantification across more cells and the inclusion of an additional mitochondrial marker (e.g., an outer membrane marker such as TOM20), as HSP60 staining can vary with mitochondrial state.

      (2) Normalization of OCR measurements<br /> Clarification of how Seahorse oxygen consumption rate measurements were normalized (e.g., cell number or protein content) would aid interpretation, particularly given potential effects of Eola1 loss on cell growth.

      (3) Linking interaction data to functional phenotypes<br /> Loss-of-function analyses are performed in mouse cell lines, whereas localization and interactome studies are conducted in human HEK293T cells. The absence of a human EOLA1 knockout model makes it difficult to directly connect the interaction data to the observed functional phenotypes. Additional validation or discussion of species conservation would improve clarity.

      (4) Mechanistic interpretation of the EOLA1-TUFM-12S rRNA interaction<br /> The identification of TUFM and 12S mt-rRNA as EOLA1 interactors is an interesting finding; however, the basis for prioritizing TUFM among the many mitochondrial proteins identified in the interactome is not fully explained. Providing enrichment statistics and functional categorization of mitochondrial interactors would increase transparency. In addition, the proposed role of the ASCH domain in RNA binding would be strengthened by structure-informed or mutational analysis of the conserved RNA-binding motif.

      (5) Interpretation of mitochondrial translation and protein abundance data<br /> Several assays supporting impaired mitochondrial translation would benefit from additional controls and quantification. The de novo mitochondrial translation assay (Fig. 3h) is not quantified, making it difficult to assess the magnitude and reproducibility of the effect. In addition, western blots showing reduced levels of mitochondrially encoded OXPHOS subunits (Figure 3g) lack a mitochondrial loading control (e.g., TOM20 or VDAC). Since loss of EOLA1 may affect mitochondrial mass, normalization to a mitochondrial marker is necessary. Relatedly, it would be informative to assess whether steady-state levels of mitoribosomal proteins (e.g., MRPS15, MRPL37) and nuclear-encoded OXPHOS subunits are altered upon Eola1 loss, both in knockout cell lines and in the knockout mouse.

      (6) Physiological scope of the in vivo analysis<br /> The cardiac phenotype observed in the whole-body Eola1 knockout mouse is compelling, but the focus on a single tissue limits interpretation of EOLA1's broader physiological role. Examination of additional high-energy-demand tissues would help clarify whether the observed effects are heart-specific or more general. In addition, the presence of residual EOLA1 protein bands in western blots (Figure 4a) and remaining Eola1 transcripts in qRT-PCR analyses (Extended Figure 4e) from knockout tissues should be addressed. The authors should clarify whether these signals reflect incomplete knockout, alternative isoforms, antibody cross-reactivity, or technical background.

      (7) Relationship to previously reported MT2A interaction<br /> Given prior reports of EOLA1 interaction with MT2A, a brief comment on whether MT2A was detected in the authors' co-immunoprecipitation experiments and how this relates to the proposed mitochondrial role would be useful.

    1. Reviewer #2 (Public review):

      Summary:

      In this manuscript, the authors present the development and characterization of a pulsed ponderomotive phase plate for transmission electron microscopy (TEM). The primary goal is to overcome the long-standing challenge of generating stable, tunable phase contrast for weakly scattering biological specimens - a capability that has remained elusive despite decades of development. While the commercially available Volta Phase Plate offers phase enhancement, it suffers from a lack of control and stability. More recent efforts have focused on continuous-wave (CW) laser phase plates; however, these systems face significant practical hurdles, including extreme optical power requirements, thermal instability of mirrors, and the necessity for high-finesse optical cavities that act as diffraction gratings for the electron beam. The authors aim to demonstrate that a pulsed, free-space laser interaction can circumvent these limitations, offering a more robust path toward practically usable phase plates

      Strengths:

      The most significant strength of this work is the elegant use of a free-space pulsed interaction, which fundamentally simplifies the hardware requirements compared to cavity-based designs. By utilizing a high-intensity pulsed laser focus rather than a standing wave inside a resonator, the authors eliminate the need for complex locking feedback loops and avoid the thermal mirror deformation that currently limits CW systems.

      Furthermore, this approach provides a critical theoretical advantage regarding image quality. Current CW cavity-based designs must grapple with the Kapitza-Dirac effect, where the standing wave creates a diffraction grating that generates unwanted "ghost images," delocalizing the signal. Recent proposals have had to resort to complex crossed-beam geometries to mitigate these artifacts. In contrast, the traveling-wave nature of the pulsed interaction described here inherently avoids the creation of a standing wave grating, thereby eliminating ghost images entirely without requiring elaborate compensation strategies.

      The authors successfully demonstrate a proof-of-concept implementation, reporting a pronounced peak phase shift of approximately 430 radians and a stable angular deflection of the electron beam. The stability data, covering a 10-hour period, suggests that this approach is robust enough for data collection sessions typical in structural biology.

      Weaknesses:

      However, the strength of the evidence is modestly tempered by limitations in data presentation and analysis. The agreement between the experimental data and the theoretical simulation in Figure 2b is imperfect; the simulation underestimates the depth of the central signal trough. While the authors acknowledge this "muted" prediction, the discrepancy suggests that the theoretical model or the estimation of experimental parameters (such as electron beam size or laser intensity) requires refinement to fully describe the interaction.

      While the authors claim stability over many hours, the data in Figure 3c reveal a significant drift in the baseline reference signal. Although attributed to a weakening electron beam, this drift complicates the reader's ability to assess the true stability of the laser-induced phase shift. A drift-corrected analysis would have provided more compelling evidence of the "stable angular kick" described.

      Despite these specific weaknesses in data presentation, the work represents a fundamental step forward. The authors have effectively demonstrated that the trade-off between beam current and spatiotemporal resolution (driven by space-charge effects) can be managed to achieve significant phase modulation. By moving the field away from the tight constraints of optical cavities and toward free-space pulsed interactions, this work establishes a potentially more viable route for integrating laser phase plates into routine biological imaging workflows. This study will be of high value to biophysicists and microscopists seeking to push the boundaries of contrast in cryo-EM

    1. Reviewer #3 (Public review):

      Summary:

      The paper "The 1000+ mouse project: large-scale spatiotemporal parametrization and modeling of preclinical cancer immunotherapies" is focused on developing a novel methodology for automatic processing of bioluminescence imaging data. It provides quantitative and statistically robust insights on preclinical experiments that will contribute to optimizing cell-based therapies. There is an enormous demand for such methods and approaches that enable the spatiotemporal evaluation of cell monitoring in large cohorts of experimental animals.

      Strengths:

      The manuscript is generally well written, and the experiments are scientifically sound. The conclusions reflect the soundness of experimental data. This approach seems to be quite innovative and promising to improve the statistical accuracy of BLI data quantification.<br /> This methodology can be used as a universal quantification tool for BLI data for in vivo assessment of adoptively transferred cells due to the versatility of the technology.

      Comments on revisions:

      The critiques have been taken care of appropriately.

    1. Reviewer #2 (Public review):

      Using chronic intravital two-photon imaging of calcium dynamics in meningeal macrophages in Pf4Cre:TIGRE2.0-GCaMP6 mice, the study identified heterogeneous features of perivascular and non-perivascular meningeal macrophages at steady state and in response to cortical spreading depolarization (CSD). Analyses of calcium dynamics and blood vessels revealed a subpopulation of perivascular meningeal macrophages whose activity is coupled to behaviorally driven diameter fluctuations of their associated vessels. The analyses also investigated synchrony between different macrophage populations and revealed a role for CGRP/RAMP1 signaling in the CSD-induced increase, but not the decrease, in calcium transients.

      This is a timely study at both the technical and conceptual levels, examining calcium dynamics of meningeal macrophages in vivo. The conclusions are well supported by the findings and will provide an important foundation for future research on immune cell dynamics within the meninges in vivo. The paper is well written and clearly presented.

      I have only minor comments.

      (1) Please indicate the formal definition of perivascular versus non-perivascular macrophages in terms of distance from the blood vessel. This information is not provided in the main text or the Methods. In addition, please explain how the meningeal vasculature was imaged in the main text.

      (2) Similarly, the method used to induce acute CSD (pin prick) is not described in the main text and is only mentioned in the figure legends and Methods. Additional background on the neurobiology of acute CSD, as well as the resulting brain activity and neuroinflammatory responses, could be helpful.

    1. Reviewer #2 (Public review):

      In the current report, Sun and Colleagues sought to determine the liver-specific role that DHHC7, a DHHC palmitoyltransferase protein, plays in regulating whole-body energy balance and hepatic crosstalk with adipose tissues. The authors generated an inducible, liver-specific DHHC7 knockout mouse to determine how altered palmitoylation in hepatocytes alters hepatokine production/secretion, and in turn, systemic metabolism. The ablation of DHHC7 was found to alter the production of proteoglycan 4 (Prg4), a hepatokine previously linked to metabolic regulation. The authors propose that the change in Prg4 production is mediated by the loss of Gαi palmitoylation, due to DHHC7 ablation, thereby augmenting cAMP-PKA-CREB signaling in hepatocytes, which alleviates the 'brake' on Prg4 production. The authors further propose that Prg4 overexpression leads to excessive binding to GPR146 on adipocytes, which in turn suppresses PKA-mediated HSL activation, promoting impairments in lipolysis, leading to obesity. The report is interesting and generally well-written, but it appears to have some clear gaps in additional data that would aid in interpretation. The addition of confirmatory culture studies would be incredibly helpful for testing the hypotheses being explored. My comments, concerns, and/or suggestions are outlined below in no particular order.

      (1) Figures: All data should be presented in dot-boxplot format so the reader knows how many samples were analyzed for each assay and group. n=3 for some assays/experiments is incredibly low, particularly when considering the heterogeneity in responsiveness to HFD, food intake, etc....

      (2) Figure 1E-F: It is unclear when the food intake measure was performed. Mice can alter their feeding behavior based on a myriad of environmental and biological cues. It would also be interesting to show food intake data normalized to body mass over time. Mice can counterregulate anorexigenic cues by altering neuropeptide production over time. It is not clear if this is occurring in these mice, but the timing of measuring food intake is important. Additionally, the VO2 measure appears to be presented as being normalized to total body mass, when in fact, it would probably be more accurate to normalize this to lean body mass. Normalizing to total body mass provides a denominator effect due to excessive adiposity, but white fat is not as metabolically active as other high-glucose-consuming tissues. If my memory serves me right, several reports have discussed appropriate normalizations in circumstances such as this.

      (3) Figure 1J-N: It is not all that surprising that fasting glucose and/or TGs were found to be similar between groups. It is well-established that mice have an incredible ability to become hyperinsulinemic in an effort to maintain euglycemia and lipid metabolism dynamics. A few relatively easy assays can be performed to glean better insights into the metabolic status of the authors' model. First, fasting insulin concentrations will be incredibly helpful. Secondly, if the authors want to tease out which adipose depot is most adversely affected by ablation, they could take an additional set of CON and KO mice, fast them for 5-6 hours, provide a bolus injection of insulin (similar to that provided during an insulin tolerance test), and then quickly harvest the animals ~15 minutes after insulin injections; followed by evaluating AKT phosphorylation. This will really tell them if these issues have impairments in insulin signaling. The gold-standard approach would be to perform a hyperinsulinemic-euglyemic clamp in the CON and KO mice. I now see GTT and ITT data, but the aforementioned assays could help provide insight.

      (4) Figure 3A: This looks overexposed to me.

      (5) Figures 3-4: It appears that several of these assays could be complemented with culture-based models, which would almost certainly be cleaner. The conditioned media could then be used from hepatocyte cultures to treat differentiated adipocytes.

      (6) Figure 4: It is unclear how to interpret the phospho-HSL data because the fasting state can affect this readout. It needs to be made clear how the harvest was done. Moreover, insulin and glucagon were never measured, and these hormones have a significant influence over HSL activity. I suspect the KO mice have established hyperinsulinemia, which would likely affect HSL activity. This provides an example of why performing some of these experiments in a dish would make for cleaner outcomes that are easier to interpret.

  2. Feb 2026
    1. Reviewer #2 (Public review):

      Sun et al. have developed a midbrain-like organoid (MLO) model for neuronopathic Gaucher disease (nGD). The MLOs recapitulate several features of nGD molecular pathology, including reduced GCase activity, sphingolipid accumulation, and impaired dopaminergic neuron development. They also characterize the transcriptome in the MLO nGD model. CRISPR correction of one of the GBA1 mutant alleles rescues most of the nGD molecular phenotypes. The MLO model was further deployed in proof-of-principle studies of investigational nGD therapies, including SapC-DOPS nanovesicles, AAV9-mediated GBA1 gene delivery, and substrate-reduction therapy (GZ452). This patient-specific 3D model provides a new platform for studying nGD mechanisms and accelerating therapy development. Overall, only modest weaknesses are noted.

    1. Reviewer #2 (Public review):

      Summary:

      This study shows that the knockdown of the effects of TPS/TPP in Helicoverpa armigera and Spodoptera frugiperda can be rescued by trehalose treatment. This suggests that trehalose metabolism is necessary for development in the tissues that NPP and dsRNA can reach.

      Strengths:

      This study examines an important metabolic process beyond model organisms, providing a new perspective on our understanding of species-specific metabolism equilibria, whether conserved or divergent.

      Weaknesses:

      While the effects observed may be truly conserved across Lepidopterans and may be muscle-specific, the study largely relies on one species and perturbation methods that are not muscle-specific. The technical limitations arising from investigations outside model systems, where solid methods are available, limit the specificity of inferences that may be drawn from the data.

    1. Reviewer #2 (Public review):

      Summary:

      The authors sought to validate the use of genetic screening pipelines that assess phenotypes in founders (F0, referred to as "crispants") obtained from CRISPR/Cas9 gene editing in 1-cell zygotes. The application of this approach in mice has generally been avoided due to concerns that results would be confounded by genetic mosaicism, but benefits to this approach include reducing animal numbers needed to achieve goals of identifying knockout phenotypes, as well as improved efficiency in the use of time and resources. The authors targeted seven genes associated with visible recessive phenotypes and observed the expected null phenotype in up to 100% of founders for each gene. Although mosaicism was common in the crispants, the various alleles were generally all functional null alleles and, in fact, some in-frame deletions with null phenotypes revealed critical functional motifs within the gene products. The rigorous data presented support using crispants to assess knockout phenotypes when guide RNAs with strong on-target and low off-target scores are used for gene editing in 1-cell mouse embryos.

      Strengths:

      By targeting multiple genes with existing, well-characterized mutations, the authors established a robust system for validating the analysis of crispants to assess gene function.

      Cutting-edge technologies were used to carefully assess the spectrum of mutations generated.

      Weaknesses:

      There could have been some discussion regarding how this approach would be impacted if mutations are dominant or embryonic lethal (for the latter, for example, F0 can be examined as embryos).

    1. Reviewer #2 (Public review):

      Summary:

      In this manuscript, Thompson et al. investigate the impact of prior ATP exposure on later macrophage functions as a mechanism of immune training. They describe that ATP training enhances bactericidal functions which they connect to the P2x7 ATP receptor, Nlrp3 inflammasome activation, and TWIK2 K+ movement at the cell surface and subsequently at phagosomes during bacterial engulfment. This is an incremental addition to existing literature, which has previously explored how ATP alters TWIK2 and K+, and linked it to Nlrp3 activation. The novelty here is in discovering the persistence of TWIK2 change and exploring the impact this biology may have on bacterial clearance. Additional experiments could strengthen their hypothesis that the in vivo protective effect of ATP-training on bacterial clearance is mediated by alveolar macrophages.

      Strengths:

      The authors demonstrate three novel findings: 1) prolonged persistence of TWIK2 at the macrophage plasma membrane following ATP that can translocate to the phagosome during particle engulfment, 2) a persistent impact of ATP exposure on remodeling chromatin around nlrp3, and 3) administering mice intra-nasal ATP to 'train' lungs protects mice from otherwise fatal bacterial infection.

      Weaknesses:

      (1) Some methods remain unclear including the timing and method by which lung cellularity was assessed in Figure 2. It is also difficult to understand how many mice were used in experiments 1, 2 and 6 and thus how rigorous the design was. A specific number is only provided for 1D and the number of mice stated in legend and methods do not match.

      (2) The study design is not entirely ideal for the authors' in vivo question. Overall, the discussion would benefit from a clear summary of study caveats, which are primarily that that 1) in vitro studies attributing ATP training-mediated bacterial killing to persistent TWIK2 relocation, K+ influx, a glycolytic metabolic shift , and epigenetic nlrp3 reprogramming were performed in BMDM or RAW cells and not primary AMs, 2) data does not eliminate the possibility that non-AM immune or non-immune cells in the lung are "trained" and responsible for ATP-mediated protection in vivo; flow data examined total lung digest which may obscure important changes in alveolar recruitment, and 3) in vivo work shows data on acute bacterial clearance but does not explore potential risks that "training" for a more responsive inflammasome may have for the severity of lung injury during infection.

      (3) The is some lack of transparency on data and rigor of methods. Clear data is not provided regarding the RNA-sequencing results. Specific identities of DEGs is not provided, only one high-level pathway enrichment figure. It would also be ideal if controls were included for subcellular fractionating to confirm pure fractions and for dye microscopy to show negative background.

      (4) In results describing 5A, the text states that "ATP-induced macrophage training effects, as measured by augmented bactericidal activity, were diminished in macrophages treated with protease inhibitors". However, these data are not identified significant in the figure; protease dependence can be described as a trend that supports the authors' hypothesis but should not be stated as significant data in text.

      In summary, this work contains some useful data showing how ATP can train macrophages via TWIK2/Nlrp3. Revisions have significantly improved methods reporting, added some data to strengthen the conclusions, and toned down on overstatements to bring conclusions more in line with data presented. The title still overstates what the authors have actually tested, since no macrophage-specific targeting in vivo (no conditional gene deletion, macrophage depletion etc) was performed in infection studies. However, in vitro data provide clear evidence that macrophages can be trained by ATP, and through caveats remain, it is plausible that macrophage training is a key mechanism for the protection observed here in the lung.

    1. Reviewer #2 (Public review):

      Summary:

      Kumar et al. aimed to assess the role of the understudied H3K115 acetylation mark, which is located in the nucleosomal core. To this end, the authors performed ChIP-seq experiments of H3K115ac in mouse embryonic stem cells as well as during differentiation into neuronal progenitor cells. Subsequent bioinformatic analyses revealed an association of H3K115ac with fragile nucleosomes at CpG island promoters, as well as with enhancers and CTCF binding sites. This is an interesting study, which provides important novel insights into the potential function of H3K115ac. However, the study is mainly descriptive, and functional experiments are missing.

      Strengths:

      (1) The authors present the first genome-wide profiling of H3K115ac and link this poorly characterized modification to fragile nucleosomes, CpG island promoters, enhancers, and CTCF binding sites.

      (2) The study provides a valuable descriptive resource and raises intriguing hypotheses about the role of H3K115ac in chromatin regulation.

      (3) The breadth of the bioinformatic analyses adds to the value of the dataset

      Comments on revisions:

      The authors sufficiently addressed my concerns.

    1. Reviewer #2 (Public Review):

      This an exciting study investigating the role of OXT in central nervous system (CNS) regulation of different behaviors and physiological processes. The study clearly shows the expression level of Oxt and Oxtr in different brain nuclei and regions.

      Sex differences in Oxt expression are also well demonstrated.

      Extensions of OXT's function in CNS regulation are sufficiently discussed.

      Overall, this provides a good direction for further investigate OXT's role in CNS's regulation on different behaviors and physiological processes.

    1. Reviewer #2 (Public Review):

      The manuscript from Chang et al. taps on an important issue in olfactory perceptual plasticity, named the generalization of perceptual learning effect by training using odors. They employed a discrimination training/learning task with either binary odor mixture or odor enantiomers, and tested for post-training effect at several time intervals. Their results showed contrasting patterns of specificity (enantiomers) and transfer (odor mixtures), and the learning effect persisted at 2 weeks post-training. They demonstrated that the effect was independent of task difficulty, olfactory adaptation and gender.

      Overall this was a well-controlled study and shows novel results. The strength of the study includes the consideration of odor structure and perceptual (dis)similarity and the control training condition. I have two minor issues that hope the authors could address in the next version of the manuscript.

      1) The author used a binary odor mixture with a ration 7:9 or 9:11, why is this ratio chosen and used for the experiment?

      2) Over the course of training, has the valence of odor (odor mixture) changed, it would be helpful to include these results in the supplements. As the author indicated in the discussion, the potential site underlying the transfer effect is the OFC, which has been found to represent odor valence previously (Anderson, Christoff et al. 2003). It would be nice to see the author replicate the results with odor/odor mixture valence (change) controlled.

      Anderson, A. K., K. Christoff, I. Stappen, D. Panitz, D. G. Ghahremani, G. Glover, J. D. Gabrieli and N. Sobel (2003). "Dissociated neural representations of intensity and valence in human olfaction." Nat Neurosci 6(2): 196-202.

    1. Reviewer #2 (Public Review):

      Many tropical montane species live only within narrow elevational ranges. Rapid climate change has led to considerable interest in determining whether these narrow elevational ranges are the result of physiological specialization: if so, then warming temperatures will have direct fitness consequences. Thus far, studies of tropical montane ectotherms have often found patterns consistent with physiological specialization, while the few field studies of tropical montane birds (endotherms) have not. However, these few studies measured the thermal physiology of adult birds. The early life stages of birds may show physiological specialization, as eggs and nestlings function as ectotherms.

      In this paper, Ocampo and colleagues provide the first test of the hypothesis that bird eggs are physiologically specialized to the climatic conditions of certain elevational zones. They use experiments and observations to measure water vapor conductance rates and eggshell traits in a diverse set of 197 species that live from the lowland Amazon to the high Andes. Ocampo and colleagues present two principal results: (1) High-elevation eggs lose less water over time than do low-elevation eggs, high elevations tend to be less humid than low elevations and (2) Eggshell traits do not show consistent patterns along the elevational gradient. The pattern in water loss is consistent with the hypothesis that high-elevation eggs are physiologically specialized for the slightly drier environments they experience. The finding that eggshell traits did not vary with elevation, however, means that the pattern of water loss is not driven by single eggshell traits (thicker eggshells could reduce water loss rates, as could fewer or smaller eggshell pores).

      This paper represents a strong advance for two main reasons. First, it provides evidence that egg physiology varies with elevation as predicted by the hypothesis that eggs are physiologically adapted to certain climatic conditions. This means egg physiological adaptation is a factor that could influence species' elevational ranges. Second, it is a proof-of-concept study that shows it is possible to measure eggshell physiology for a large number of species in the field in order to test hypotheses. As such, it should inspire many further tests that examine adaptation in egg physiology in the context of species' distributions along environmental gradients.

      There are two caveats that readers should be aware of. First, measuring these traits is difficult, and there remain questions about the efficacy of different methods. For example, the authors note that quantifying eggshell structures is very difficult, with several unresolved questions about their method of using scanning electron microscopy images to measure eggshell pores. Similarly, the authors mention that temperature variation may partially influence their main result that high-elevation eggs lose water at slower rates than low-elevation eggs (temperatures were colder for experiments at high elevations than for low elevations). Second, I regard the analyses of eggshell traits for specific families as exploratory. There are no a priori expectations for how different families might be expected to differ in their patterns. These analyses are fruitful in that they generate additional hypotheses that future work can test. However, it does mean that the statistical significance of eggshell trait relationships with elevation for specific families should be interpreted with caution.

    1. Reviewer #2 (Public Review):

      In this manuscript, Jong et al. provide and validate a very useful resource for performing CRISPR screenings to study neutrophil differentiation and function. The major strength of the paper lies in its careful validation of many aspects of the Hoxb8-immortalized progenitor cells, including their differentiation capacity, their ability to clear bacteria, and their capacity to differentiate in vivo. The authors succeed at this, with results correctly supporting their conclusions. The major weaknesses are its presentation and writing, some of which are poorly organized. Finally, while the potential impact of this resource in the field could be very large, the CRISPR screening results appear half-baked, almost preliminary, and could be better validated, or at least presented. A few other points that warrant revision are included below:

      • The introduction should be better constructed and organized. It should be written with more connectors to present facts in a stream that flows naturally, from the broad general facts to the experimental details implemented in the manuscript. It should also discuss other similar approaches used in the literature, such as LaFleur et al. 2019, and relate in which ways these presented methods could be better.

      • The scheme in Figure 4A should more clearly indicate the timings, doublings, numbers of cells, and other aspects of the experimental design.

      • The volcano plot in Figure 4B is poorly informative and almost redundant. What does one make of it?

      • The representation (normalized reads) of each sgRNA in the library and across multiple experiments, including their correlation, should be checked and plotted, to visualize how robust these replicates are.

      • In Figure 4E, the distribution of the hit sgRNAs should be compared to all other targeting guides (instead of just to non-targeting controls). Linear density distribution plots or scatter plots of all guides are usually the best way, but there are others (for example, see Figure 4 of LaFleur et al. 2019). Ideally, each independent sgRNA for each gene in the library, as well as biological replicates, should be separately shown, with hits clearly highlighted.

      • While in vivo differentiation is shown as possible with these cell lines, it is unclear whether CRISPR screenings could be performed in vivo too. Would sgRNA representation suffice for genome-wide? At least some of the new hits could be validated by testing differentiation in vivo (i.e. WASH complex).

      • In the methods section, the RNA-seq analysis pipeline details are missing (versions, software for alignment, quantification, differential gene expression, and enrichment). Also, parameters for MAGeCK and MAGeCKFlute should be explicit and detailed.

      • The discussion is mostly a summary of the results. It is lacking in detail and thoughtful discussion regarding novelty and impact beyond the validation of the cell line. What about potential applications? What about extending screenings to test bacterial-killing, as suggested in Figure 2? What about limitations compared to other similar methods out there? There is little discussion of such important potential matters. Also, a large part of the discussion is dedicated to discussing details about Cebpe that are all well known in the literature and add little value.

      • Figure legends are typically too succinct and hard to interpret, especially for non-experts. The text should enable the figure reader to correctly interpret what is shown in each panel.

    1. Reviewer #5 (Public review):

      While the study presents an innovative and potentially impactful mRNA-based approach for addressing monogenic causes of male infertility, several significant weaknesses limit the strength of the authors' central conclusions.

      First, the functional evidence for true fertility restoration remains incomplete. Although the authors convincingly demonstrate partial recovery of sperm motility, the downstream reproductive outcomes, particularly for IVF, are weak. Importantly, these concerns are shared by all three reviewers and the former Reviewing Editor, and to my eye they are both thoughtfully articulated and well warranted. The ICSI data show modest improvement, but this rescue is difficult to interpret.

      In parallel, significant mechanistic questions persist regarding the unusually prolonged persistence of naked mRNA and reporter protein expression in germ cells, which is not fully reconciled with established mRNA and protein half-life biology and is supported largely by inference rather than by direct decay measurements.

      Finally, although the authors have conducted additional cellular analyses, concerns about the extent and specificity of germ-cell targeting versus Sertoli-cell expression remain unresolved. Together, these issues do not negate the technical novelty of the work, but they do constrain the confidence with which the current dataset can support the authors' strongest therapeutic claims.

    1. Reviewer #2 (Public Review):

      The stated goal of the authors is to establish and characterize an experimental system to study neutrophil heterogeneity in a manner that allows for functional outcomes to be probed. To do so, they start with murine GMPs that are conditionally immortalized by ER-HoxB8 expression and make single-cell clonal populations to ask whether those GMPs or neutrophils derived by differentiating such clonal GMPs harbor heterogeneity. At a conceptual level, this is an innovative approach that could shed light on mechanisms of neutrophil heterogeneity that have been described in both health and disease. They perform bulk multi-omics and functional analyses of both the clonal GMPs and neutrophil-like cells, including transcriptional and epigenetic profiling. However, the major weakness of the study is that the authors do not provide rigorous or convincing data that the cells they derive are truly mature neutrophils. To the contrary, the neutrophil-like cells lack Ly6G expression and so the authors fall back on using CD11b as the primary marker for delineating neutrophils; however, CD11b is expressed by both myeloid progenitors and some premature and mature myeloid lineages that are not neutrophils. They acknowledge this shortcoming, but they make an assumption that Ly6G expression is the only way in which the cells they derive are different from primary neutrophils without presenting any evidence indicating such. The authors use only SCF during the maturation of ER-HoxB8 GMPs into leukocytes, rather than including other cytokines such as G-CSF (or use in vivo maturation) that could have better-induced differentiation and maturation into granulocytes/neutrophils. The authors did not use their transcriptional analyses to further establish that the cells they derive from ER-HoxB8 GMPs are similar/different from primary murine neutrophils. Unfortunately, this shortcoming means that all of the analyses of neutrophil-like cells derived from clonal GMPs may or may not represent the transcriptional, epigenetic, etc. profile of a true mature neutrophil. It is also not rigorously addressed whether what they call PMNs derived from clonal GMPs are a transcriptionally uniform population or if they harbor heterogeneity within the bulk population. Overall, while conceptually intriguing and in pursuit of an experimental system that would be impactful for the field, the study as performed has critical flaws.

    1. Reviewer #2 (Public review):

      Summary:

      The manuscript entitled "Mitochondrial Protein FgDML1 Regulates DON Toxin Biosynthesis and Cyazofamid Sensitivity in Fusarium graminearum by affecting mitochondrial homeostasis" identified the regulatory effect of FgDML1 in DON toxin biosynthesis and sensitivity of Fusarium graminearum to cyazofamid. The manuscript provides a theoretical framework for understanding the regulatory mechanisms of DON toxin biosynthesis in F. graminearum and identifies potential molecular targets for Fusarium head blight control. The paper in innovative, but there are issues in the writing that need to be added and corrected.

      Comments on revisions:

      The author has addressed my questions.

    1. Reviewer #2 (Public review):

      Summary:

      In this manuscript, Farber and colleagues have performed single cell RNAseq analysis on bone marrow derived stem cells from DO Mice. By performing network analysis, they look for driver genes that are associated with bone mineral density GWAS associations. They identify two genes as potential candidates to showcase the utility of this approach.

      Strengths:

      The study is very thorough and the approach is innovative and exciting. The manuscript contains some interesting data relating to how cell differentiation is occurring and the effects of genetics on this process. The section looking for genes with eQTLs that differ across the differentiation trajectory (Figure 4) was particularly exciting.

      Weaknesses:

      The manuscript is, in parts, hard to read due to the use of acronyms and there are some questions about data analysis that still need to be addressed.

      Comments on revisions:

      Dillard et al have made several improvements to their manuscript.

      (1) We previously asked the authors to determine whether any cell types were enriched for BMD-related traits since the premise of the paper is that 'many genes impacting BMD do so by influencing osteogenic differentiation or ... adipogenic differentiation'. Given the potential for the cell culture method to skew the cell type distribution non-physiologically, it is important to establish which cell types in their assay are most closely associated with BMD traits. The new CELLECT analysis and Figure 1E address this point nicely. However, it would still be nice to see the correlations between these cell types and BMD traits in the mice as this would provide independent evidence to support their physiological importance more broadly.

      (2) Shortening the introduction.

      (3) Addressing limitations that arise from not accounting for founder genome SNPs when aligning scRNA-seq data.

      (4) The main take-away of this paper is, to us, the development of a single cell approach to studying BMD-related traits. It is encouraging that the cells post-culture appear to be representative of those pre-culture (supplemental figure 3).

      However, the authors seem to have neglected several comments made by both reviewers. While we share the authors' enthusiasm for the single cell analytical approach, we do not understand their reluctance to perform further statistical tests. We feel that the following comments have still not been addressed:

      (1) The manuscript still contains the following:

      "To provide further support that tradeSeq-identified genes are involved in differentiation, we performed a cell type-specific expression quantitative trait locus (eQTL) analysis for each mesenchymal cell type from the 80 DO mice. We identified 563 genes (eGenes) regulated by a significant cis-eQTL in specific cell types of the BMSC-OB scRNA-seq data (Supplementary Table S14). In total, 73 eGenes were also tradeSeq-identified genes in one or more cell type boundaries along their respective trajectories (Supplementary Table S9)."

      The purpose of this paragraph is to convince readers that the eGenes approach aligns with the tradeSeq approach (and that their approach can therefore be trusted). It is essential that such claims are supported by statistical reasoning. Given that it would be very simple to perform permutation/enrichment analyses to address this point, and both reviewers requested similar analyses, we do not understand the author's reluctance here. Otherwise, this section should be rewritten so that it does not imply that the identification of these genes provides support for their approach.

      (2) Given that a central purpose of this manuscript is to establish a systematic workflow for identifying candidate genes, the manuscript could still benefit from more explanation as to why the authors chose to highlight Tpx2 and Fgfrl1. Tpx2 does already have a role in bone physiology through the IMPC. The authors should comment on why they did not explore Kremen1, for instance, as this gene seems important for the transition to both OB1 and 2.

      A final minor comment is that it would be very helpful if the authors could indicate if the DDGs in Table 1 are also eGenes for the relevant cell type. This is much more meaningful than looking through GTEx.

    1. Reviewer #2 (Public review):

      Summary:

      Xu et al. used fMRI to examine the neural correlates associated with retrieving temporal information from an external compared to internal perspective ('mental time watching' vs. 'mental time travel'). Participants first learned a fictional religious ritual composed of 15 sequential events of varying durations. They were then scanned while they either (1) judged whether a target event happened in the same part of the day as a reference event (external condition); or (2) imagined themselves carrying out the reference event and judged whether the target event occurred in the past or will occur in the future (internal condition). Behavioural data suggested that the perspective manipulation was successful: RT was positively correlated with sequential distance in the external perspective task, while a negative correlation was observed between RT and sequential distance for the internal perspective task. Neurally, the two tasks activated different regions, with the external task associated with greater activity in the supplementary motor area and supramarginal gyrus, and the internal condition with greater activity in default mode network regions. Of particular interest, only a cluster in the posterior parietal cortex demonstrated a significant interaction between perspective and sequential distance, with increased activity in this region for longer sequential distances in the external task but increased activity for shorter sequential distances in the internal task. Only a main effect of sequential distance was observed in the hippocampus head, with activity being positively correlated with sequential distance in both tasks. No regions exhibited a significant interaction between perspective and duration, although there was a main effect of duration in the hippocampus body with greater activity for longer durations, which appeared to be driven by the internal perspective condition. On the basis of these findings, the authors suggest that the hippocampus may represent event sequences allocentrically, whereas the posterior parietal cortex may process event sequences egocentrically.

      Strengths:

      The topic of egocentric vs. allocentric processing has been relatively under-investigated with respect to time, having traditionally been studied in the domain of space. As such, the current study is timely and has the potential to be important for our understanding of how time is represented in the brain in the service of memory. The study is well thought out and the behavioural paradigm is, in my opinion, a creative approach to tackling the authors' research question. A particular strength is the implementation of an imagination phase for the participants while learning the fictional religious ritual. This moves the paradigm beyond semantic/schema learning and is probably the best approach besides asking the participants to arduously enact and learn the different events with their exact timings in person. Importantly, the behavioural data point towards successful manipulation of internal vs. external perspective in participants, which is critical for the interpretation of the fMRI data. The use of syllable length as a sanity check for RT analyses as well as neuroimaging analyses is also much appreciated.

      Suggestions:

      The authors have done a commendable job addressing my previous comments. In particular, the additional analyses elucidating the potential contribution of boundary effects to the behavioural data, the impact of incorporating RT into the fMRI GLMs, and the differential contributions of RT and sequential distance to neural activity (i.e., in PPC) are valuable and strengthen the authors' interpretation of their findings.

      My one remaining suggestion pertains to the potential contribution of boundary effects. While the new analyses suggest that the RT findings are driven by sequential distance and duration independent of a boundary effect (i.e., Same vs. Different factor), I'm wondering whether the same applies to the neural findings? In other words, have the authors run a GLM in which the Same vs. Different factor is incorporated alongside distance and duration?

    1. Reviewer #2 (Public review):

      The paper from Kulej et al. reports a set of tools for proteogenomic analysis of cancer proteomes. Their approach utilizes modern methods in long-read RNA sequencing to assemble a proteome database that is specific to Ewing sarcoma-derived A673 cells. To maximize proteome coverage and therefore increase the odds of detecting cancer-specific alterations at the protein level, the authors use multiple enzymes (trypsin, gluC, etc.) to digest cellular proteins and then perform multidimensional peptide fractionation. Peptide samples are then analyzed by LC-MS/MS using data-dependent and data-independent schemes on a timstof mass spectrometer. Proteogenomics is an important area of investigation for cancer research and does require new informatics tools.

      The authors describe an end-to-end workflow where they claim to have optimized four different steps:

      (1) Assembly of a sample-specific protein database using long-read transcriptomic data.

      (2) Use of 8 different proteolytic enzymes to maximize diversity of peptides.

      (3) Multiple stages of peptide fractionation using SCX and high pH rp chromatography.

      (4) Utilize acquisition methods on the timstof mass spec to provide MS/MS data from single-charged peptides and multiply-charged peptides.

      The authors published two earlier versions of ProteomeGenerator (versions 1 and 2) in the Journal of Proteome Research. In these earlier versions, 'ProteomeGenerator' was the set of software tools designed to integrate DNA and RNA sequencing to create a sample-specific protein database. To test the performance of each ProteomeGenerator version, the authors generated LC-MS/MS data using a combination of trypsin and LysC, then in the other paper, trypsin, LysC, and GluC. In both papers, they performed some levelof peptide fractionation prior to LC-MS/MS. They acquired LC-MS/MS data on a Thermo Q-Exactive in one paper and a Thermo Orbitrap mass spec in the other paper.

      In the current paper, the primary innovation is the use of long-read sequencing to potentially improve the quality of the sample specific protein database. The other three components noted above are incremental compared to the authors' previous two papers and generally accepted practices in the field of proteomics. To note one example, the authors previously digested proteins using three enzymes and now use eight. Similarly, they are now using a timstof Bruker mass spec instead of one from Thermo. The detailed descriptions around the use of many enzymes and peptide fractionation, etc., create a very technically oriented paper, similar to or more so than the authors' earlier papers in J. Proteome Research. So, while there is enthusiasm for the use of long-read sequencing across biomedical research, the impact here for proteogenomic applications is somewhat lost with all of the technical description for experimental details that are not particularly innovative. In this respect, the report is not well matched to a broad readership.

    1. Reviewer #2 (Public review):

      Summary:

      The authors tested an interesting hypothesis that white flies and planthoppers independently evolved salivary proteins to dampen plant immunity by targeting a receptor-like protein. Unlike previously reported receptor-like proteins with large ligand-binding domains, the NtRLP4 here has a malectin LRR domain. Interestingly, it also associates with the adaptor SOBIR1. While the function of this protein remains to be further explored, the authors provide strong evidence showing it's the target of salivary proteins as the insects' survival strategy.

      Major points:

      The authors mixed the concepts of LRR-RLPs with malectin LRR-RLPs. These are two different type of receptors. While LRR-RLPs are well studied, little is known about malectin LRR-RLPs. The authors should not simply apply the mode of function of LRR-RLPs to RLP4 which is a malectin LRR-RLP. In addition, LRR-RLPs that function as ligand-binding receptors typically possess >20 LRRs, whereas RLP4 in this work has a rather small ectodomain. It remains unclear whether it will function as a PRR.

      I can't agree with the author's logic of testing uninfested plants for proving a PRR's function. The function of a pattern recognition receptor depends on perceiving the corresponding ligand. As shown by the data provided, RLP4-OE plants have altered transcriptional profile indicating activated defense, suggesting it's unlikely a PRR. An alternative explanation is needed.

      More work on BAK1 will also help to clarify the ideas proposed by the authors.

    1. 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 whole-mount 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 have 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-lysosomal pathway localization. The authors also describe a new type of barrier assay using a streptavidin-coated plate upon which barrier-forming cell cultures can be placted, this could be a very useful alternative or complement to other size-selective barrier assays and presumably could work for other barrier forming cells types, likely epithelial cells.

      Weaknesses:

      (1) There are no measures of bacterial burden in peripheral organs, blood, in the LPM or brain in the TLR4 endothelial cKO mice. Lack of TLR4 in endothelial cells could prevent bacterial 'access' into the LPM and brain, essentially preventing meningitis and leading to a lack of inflammatory responses in the LPM-located cells simply because there is no bacteria present. Bacteremia may also be reduced, as might inflammatory responses in peripheral organs with TLR4-deficient peripheral endothelium. Bacterial counts and inflammatory measures in peripheral organs and blood are important to better understand the mechanism(s) underlying the reduced inflammatory profile in LPM cells and no LPM endothelial breakdown in the Tlr4 endothelial cKO mice. In other words, does deleting TLR4 in EC protect against the development of meningitis by somehow blocking bacteria access to the LPM (this would be supported by low or no CFU counts in infected Tlr4 endothelial cKO) or is it what the authors appear to propose in Figure 1J that TLF4 in EC is the only cell responding to the bacteria to trigger the immune cascade in the LPM? More data is needed to resolve this, as this is a major claim of the paper.

      (2) The authors look at the underlying cortical response (cerebral vasculature for ICAM and immune cells) but do not use markers that could identify microglia (Iba1), the primary resident immune cell (CD206 is not useful, at this stage, in perivascular macrophages that are extremely sparse in the postnatal brain). This would be important to better study the impact on CNS resident immune cell morphological activation.

      (3) The authors suggest that Cldn5 junctional localization is selectively disrupted upon bacterial exposure, mediated by TLR4 - they suggest this based on studying PECAM, GLUT-1, ZO-1 and B-catenin (all normally junction or cell surface located in cultured Bend3.1) in relationship to Cldn5 localization (normally high) - it is possibly these are also impact by bacteria exposure (maybe through different mechanisms?) - a better measure would be to use the similar cyto/PM measure they do for Cldn5 in Fig. 4D and to evaluate this or to use intensity measurements.

      (4) The discussion could benefit from delving more into the prior literature on E.coli-mediated breakdown of junctions in cultured human microvascular brain endothelial cell model and critical host-pathogen interactions of the bacteria with ECs (PMID: 14593586), and how this might involve TLR4.

      (5) It would be important to discuss how their results relate to earlier studies on TLR4-/- and TLR2-/- global knockout mice and protection vs vulnerability to development of meningitis (see PMCID: PMC3524395) - this paper showed that TLR4 global KO mice have increased susceptibility to die from meningitis and have much higher CFU counts in the CNS. In this manuscript and their prior work (Wang et al., 2023), this group shown that both global TLR4-/- mutants and their EC-specific KO have reduced barrier permeability, but we don't have any information about CFU or susceptibility to death from meningitis in their models.

    1. Reviewer #2 (Public review):

      Summary:

      The authors aimed to investigate the mechanistic link between a Mediterranean-mimicking diet (MedDiet)-specifically the synergy between high fiber and fish oil-and its ability to suppress tumor growth. They successfully identify that this dietary combination alters the gut microbiome to favor the expansion of Bacteroides thetaiotaomicron. This bacterium metabolizes dietary tryptophan into indole-3-acetic acid (3-IAA), which then acts systemically to prevent CD8+ T-cell exhaustion.

      Strengths:

      The study integrates controlled dietary interventions, microbiome perturbation, metabolite profiling, and immune functional analyses into a coherent and well-organized framework, making the overall logic of the work easy to follow. The dietary design is carefully controlled, allowing clear interpretation of which broad dietary features are associated with the observed antitumor effects. The immune dependence of the phenotype is addressed using appropriate experimental approaches, and the results broadly support a role for gut microbiota-derived metabolites in shaping immune cell function. In addition, analyses of human datasets provide important context and enhance the potential relevance and usefulness of the findings for a broader research community.

      Weaknesses:

      While the manuscript provides strong support for a role of the microbial metabolite indole-3-acetic acid and downstream stress signaling in shaping immune cell function, the upstream mechanism by which this metabolite exerts its effects remains unresolved. In particular, the specific molecular sensor or binding target through which the metabolite acts has not been identified, and this uncertainty limits mechanistic precision. Framing this point more explicitly as an open question would help align the interpretation with the current data.

      In addition, at several points, the presentation may imply that a single microbial species is uniquely responsible for the observed effects. However, the experimental evidence more directly demonstrates sufficiency under the tested conditions rather than necessity. A clearer distinction between "sufficient" and "necessary" claims would help readers better assess the generality of the findings and their applicability to more complex microbial communities.

      The interpretation of the human data also warrants some caution. The diet-associated score applied to human datasets is derived from gene-expression signatures identified in mouse models and therefore represents an indirect proxy rather than a direct measure of dietary intake. Although the score correlates with clinical outcomes, it does not establish that patient survival is driven by consumption of specific dietary components such as fiber and fish oil.

    1. Reviewer #2 (Public review):

      Summary:

      This study demonstrates that METTL5-mediated rRNA m⁶A1832 modification regulates tumor neoantigen generation by maintaining translational fidelity. Loss of METTL5 in tumor cells promotes immune cell infiltration into the tumor microenvironment and enhances the therapeutic efficacy of anti-PD-1 treatment, identifying a novel and potentially important target for cancer immunotherapy.

      Strengths:

      In murine tumor models, the authors found that Mettl5 depletion increases CD8⁺T cell infiltration and T cell receptor (TCR) repertoire diversity, and revealed a novel mechanism by which reduced ribosomal translation fidelity enhances non-canonical translation, thereby promoting the production of tumor neoantigens.

      Weaknesses:

      (1) While Mettl5 knockout enhances T-cell infiltration into tumors, it remains unclear whether loss of Mettl5 affects the expression of chemokines involved in immune cell recruitment.

      (2) Although the authors report a significant reduction in tumor cell growth as well as tumor volume and weight, direct evidence demonstrating T-cell-mediated cytotoxicity is lacking.

    1. Reviewer #2 (Public review):

      In their manuscript "TGF-β drives the conversion of conventional NK cells into uterine tissue-resident NK cells to support murine pregnancy", Yokoyama and colleagues investigate the role of Tgfbr2 expression by NK cells in the formation of tissue-resident uterine NK cells and subsequent importance in murine pregnancy. By transferring congenic splenic conventional NK cells into pregnant mice, they show conversion of circulating NK cells into uterine ivCD45 negative tissue-resident NK cells. When interfering with the formation of uterine trNK cells, spiral artery remodelling was impaired, fetal resorption rates were increased, and litter sizes were reduced.

      Generally, this is a research topic of high interest, yet the manuscript is lacking detailed mechanistic insights, and some questions remain open. At the current state, the data represent an interesting characterisation of the Tgfbr2-fl/fl Ncr1-Cre mice in pregnancy, but considering (a) the recent publication by the group (Reference 17) on the role of Eomes+ cNK cells during pregnancy, (b) the previously described role of Tgfbr2 and autocrine TGFb expression for uterine NK cell differentiation in virgin mice (also cited by the authors), and (c) the well-known relevance of uterine NK cells during pregnancy, additional experiments addressing the specific role of Tgfb during pregnancy would help to improve novelty and significance of the manuscript. To this end, the following aspects should be discussed and, where applicable, experimentally addressed by the authors:

      (1) The authors suggest cNK extravasation and local differentiation into iv- trNK.

      Can it be estimated how much this process contributes to the trNK pool vs. a potential local proliferation of already existing trNK? How do absolute numbers of CD49a+ Eomes+ trNK change during pregnancies? (In Figure 1A, the cell numbers of CD49a+ Eomes+ trNK seem to go down dramatically between gd 6.5 and 14.5). The plot in 1B could also include absolute numbers of ILC1s and trNKs. Would recruited cNK cells compensate for a potential loss of CD49a+ Eomes+ trNK?

      (2) Figure 1C: 2.5

      Mio cNK cells have been transferred, but only very few cells can be detected within the uterus (concatenated FACS plot shown). What may represent the limit to generate uterine trNK out of cNK? Is the niche supporting cNK-trNK differentiation limited? Is it only a specific subset of (splenic) cNK capable of differentiating into trNK? Is gd 0.5 the optimal timepoint for the transfer? Is there continuous recruitment of cNK into the uterus and differentiation into trNK, or is it enhanced at specific timepoints of pregnancy? Could there be local proliferation of cNK-derived trNK? This could be studied by proliferation dye dilution of WT cNK cells in this transfer-setup.

      (3) The authors should consider inducible Tgfbr2 deletion (e.g. with Tamoxifen-inducible Cre) to enable development of the uterine NK compartment in virgin mice and only ablate trNK differentiation during pregnancy. This could help to estimate the turnover of cNK into trNK, or to understand if constant cNK recruitment is required to form the uterine trNK compartment during pregnancy.

      (4) Did the authors consider transfer of Tgfbr2-floxed Ncr1-Cre cNK in the same setup as in Fig. 1C? This experiment could confirm the requirement of Tgfbr-dependent signalling for cNK to trNK conversion during pregnancy versus effects of Tgfb signals on trNK numbers in the uterus at steady state (before pregnancy).

      (5) Figures 2D/E

      The authors should state that ILC1s are reduced in the virgin uterus of female Tgfbr2-floxed or Tgfb1-floxed Ncr1-Cre mice and cite the relevant work (the Ref #29 discussed in this context did not show that?). It would be helpful to include an analysis of all three uterine ILC subsets in steady state. This could help to answer the question if the cNK cell changes are pregnancy-specific or a general phenomenon in Tgfbr2-floxed Ncr1-Cre mice.

      (6) Figure 2E

      Please phrase more carefully about the "concomitant increase" of cNKs, since this increase is much less pronounced compared to the very strong reduction (absence) of trNKs in Tgfbr2-floxed Ncr1-Cre mice. Do the authors suggest that cNKs are halted at this stage and cannot differentiate into trNK, based on these data?

      (7) Figure 3/4

      Can the reduced litter size and the abnormal spiral artery formation be rescued by transfer of WT cNK into Tgfbr2-floxed Ncr1-Cre mice?

    1. Reviewer #2 (Public review):

      Summary

      This study investigates the role of the human posterior inferotemporal cortex (hPIT) in attentional control, proposing that hPIT serves as an attentional priority map that integrates both top-down (endogenous) and bottom-up (exogenous) attentional processes. The authors conducted three types of fMRI experiments and collected resting-state data from 15 participants. In Experiment 1, using three different spatial attention tasks, they identified the hPIT region and demonstrated that this area is modulated by attention across tasks. In Experiment 2, by manipulating the presence or absence of visual stimuli, they showed that hPIT exhibits strong attentional modulation in both conditions, suggesting its involvement in both bottom-up and top-down attention. Experiment 3 examined the sensitivity of hPIT to stimulus features and attentional load, revealing that hPIT is insensitive to stimulus category but responsive to task load - further supporting its role as an attentional priority map. Finally, resting-state functional connectivity analyses showed that hPIT is connected to both dorsal and ventral attention networks, suggesting its potential role as a bridge between the two systems. These findings extend prior work on monkey PITd and provide new insights into the integration of endogenous and exogenous attention.

      Strength

      (1) The study is innovative in its use of specially designed spatial attention tasks to localize and validate hPIT, and in exploring the region's role in integrating both endogenous and exogenous attention, as prior works focus primarily on its involvement in endogenous attention.

      (2) The authors provided very comprehensive experiment designs with clear figures and detailed descriptions.

      (3) A broad range of analyses was conducted to support the hypothesis that hPIT functions as an attentional priority map -- including experiments of attentional modulation under both top-down and bottom-up conditions, sensitivity to stimulus features and task load, and resting-state functional connectivity. These analyses showed consistent results.

      (4) Multiple appropriate statistical analyses - including t-tests, ANOVAs, and post-hoc tests-were conducted, and the results are clearly reported.

      Comments on revisions:

      The authors have addressed our comments in their revised manuscript and in their response to the reviewers. We don't have any further suggestions or comments.

    1. Reviewer #2 (Public review):

      Summary:

      This article presents a neuromusculoskeletal (NMS) model of the Japanese Macaque. This model is added with a neural feedforward controller based on CPG and synergy that allows for reproducing quadrupedal and bipedal gait as well as the transition between quadrupedal and bipedal gait. The model and controller were validated using experimental data. Results were also compared to an inverted pendulum model to show that the transition between quadrupedal and bipedal in macaque is using this kind of representation for transition and stability. Overall, the article is very interesting, but it sometimes lacks clarity.

      Strengths:

      The results of the model present impressive results for quadrupedal, bipedal, and transition, validated by experimental data. NMS controllers based on feedforward controllers are very difficult to fine-tune.

      Weaknesses:

      (1) The movement regulator is not clear and should be better explained. At first, it seems that it is just a new CPG/synergy (feedforward) added, but in the methods, it seems to be a feedback controller.

      (2) It is also not clear what is meant by discretizing the weight for the trigger limb from 0 to 1 (page 8).

      (3) The controller is mainly using a feedforward controller, allowing only anticipatory movement. Animals are also using a reflex-based feedback controller. A controller with feedback/reflex could reduce failed attempts in training and better represent the transition.

      (4) There are small typos throughout the article that should be corrected.

    1. Reviewer #2 (Public review):

      Summary:

      Many fly species exhibit male-specific visual behaviors during courtship, while little is known about the circuit underlying the dimorphic visuomotor transformations. Nicholas et al focus on two types of visual descending neurons (DNs) in hoverflies, a species in which only males exhibit high-speed pursuit of conspecifics. They combined electrophysiology and behavior analysis to identify these DNs and characterize their response to a variety of visual stimuli in both male and female flies. The results show that the neurons in both sexes have similar receptive fields but exhibit speed-dependent dimorphic responses to different optic flow stimuli.

      Strengths:

      Hoverflies, though not a common model system, show very interesting dimorphic behaviors and provide a unique and valuable entry point to explore the brain organization behind sexual dimorphism. The findings here are not only interesting on their own right but will also likely inspire those working in other systems, particularly Drosophila.

      The authors employed rigorous morphology, electrophysiology, and behavior methods to deliver a comprehensive characterization of the neurons in question. The precision of the measurements allowed for identifying a subtle and nuanced neuronal dimorphism and set a standard for future work in this area.

      Weaknesses:

      Cell-typing using receptive field preferred directions (RFPDs): if I understood correctly, this classification method mostly relies on the LPDs near the center of the receptive field (median within the contour in Fig.1). I have two concerns here. First, this method is great if we are certain there are only two types of visual DNs as described in the manuscript. But how certain is this? Given the importance of vision in flight control, I would expect many DNs that transmit optic flow information to the motor center. I'd also like to point out that there are other lobula plate tangential cells (LPTCs) than HS and VS cells, which are much less studied and could potentially contribute to dimorphic behaviors. Second, this method feels somewhat impoverished given the richness of the data. The authors have nicely mapped out the directional tuning for almost the entire visual field. Instead of reducing this measurement to 2 values (center and direction), I was wondering if there is a better method to fully utilize the data at hand to get a better characterization of these DNs. As the authors are aware, local features alone can be ambiguous in characterizing optic flows. What's more, taking into account more global features can be useful for discovering potentially new cell types.

      Line 131, it wasn't clear to me why full-screen stimuli were used for comparison here, instead of the full receptive field maps. Male flies exhibit sexual dimorphic behaviors only during courtship, which would suggest that small-sized visual stimuli (mimicking an intruder or female conspecific) would be better suited to elicit dimorphic neuronal responses. A similar comment applies to the later results as well. Based on the receptive field mapping in Figure 1, I'm under the impression that these 2 DN types are more suited to detect wide-field optic flows, those induced by self-motion as mentioned in the manuscript. The results are still very interesting, but it's good to make this point clear early on to help set appropriate expectations. Conversely, this would also suggest that there are other visual DN types that are responsible for the courtship-related sexually dimorphic behaviors.

    1. Reviewer #2 (Public review):

      Summary:

      Laurent et al. perform in vivo electrophysiological recordings in the retrosplenial cortex of rats foraging in multi-compartment environments with either identical or unique visual features. The authors characterize two types of directional signals in the area that they have previously reported: classic head direction cells anchored to the global allocentric reference frame and multi-direction cells (MDCs), which have a rotationally preserved directional field anchored to local compartments. The primary finding of this work is that MDCs seem sensitive to local environmental geometry rather than visual context. They also show that MDC tuning persists in the absence of hippocampal place field repetition, further dissociating the RSC local directional signal from the broader allocentric representation of space. A novel observation is that RSC non-directional spatial signals are anchored to the local environment, which could and should be explored further. While the data is solid and the analyses are mostly appropriate, the primary findings are incremental, and more interesting novel claims are not explored in detail or not explicitly tested.

      Strengths:

      The environmental manipulations clearly demonstrate that tuning is not modulated by complex visual information.

      The finding that RSC two-dimensional spatial responses are stable and anchored to environmental features is novel and can be further explored in future work.

      Weaknesses:

      The observation that BDCs and MDCs are insensitive to visual context builds upon the author's previous work (and replicates aspects of Zhang et al., 2022) but leaves many open questions that are not addressed with the current set of experiments. Specifically, what exactly are MDCs anchoring to? The primary theory is that they anchor to environmental geometry, but there are no explicit experimental manipulations to test this theory. It is important to note that 2- and 4-compartment environments share many features, including the same cardinal axes, making any differences/similarities in these two conditions difficult to interpret.

      The main finding presented with respect to BDC/MDs tuning is that they are not sensitive to visual context as manipulated by distinct visual patterns on the wall and floor in multicompartment environments. One could argue that the individual rooms are, in actuality, quite similar in low-level visual features - each possesses a large white background square visual feature on a single wall with a fixed relationship to the door(s). How can the authors rule out that i) BDC/MDC responses are modulated by these low-level features rather than geometry and/or ii) that the rats are not paying attention to any visual features at all? There is no task requiring them to indicate which room they are in. Furthermore, the doorways themselves are prominent visual features that are present in each context. It would be interesting to see if MDC/BDC tuning persisted in a square room where the number of doorways was manipulated to rule out this possibility.

      A strong possibility is that the rotational symmetry of both MDCs and non-directional spatial neurons is related to i) door-related firing, 2) stereotyped movement, and 3) stereotyped directional sampling. In Supplemental Figure 8, the authors begin to address this by comparing a 'population ratemap' to a 'population speed map.' I do not think this is sufficient and is difficult to interpret. Instead, the authors should assess whether MDC and BDCs fire more at doorways and what the overlap is with the speed-modulated cells they report. Moreover, they should assess whether the spatial speed profile itself is rotationally symmetric within each session. It would also be useful to look at the confluence of the variables simultaneously using some form of regression analysis. The authors could generate a directional predictor that captures the main response property of these cells and see if it accounts for greater variability in spiking than speed or x,y position. Finally, rotationally symmetric directional sampling biases could arise from the doors being present on the same two walls in each room. The authors should assess whether MDC tuning is still present if directional sampling is randomly downsampled to match directional observations in each compartment.

      Recent work has demonstrated that neurons with egocentric corner or boundary tuning are observed in RSC. The authors do not address whether egocentric tuning contributes to MDC signals. An explicit analysis of the relationship and potential overlap of MDC and egocentric populations is warranted.

      Many of the MDCs presented in the main figures are not especially compelling. This includes alterations to MDC tuning in Figure 2, which is a key datapoint. The authors should show significantly more (if not all) examples of MDCs in each environment. It would similarly be useful to see all/more examples of non-directional spatially tuned neurons with rotationally symmetric firing patterns.

      "One might hypothesize that specific environmental cues, such as door orientation or landmark positioning, drive these tuning shifts. However, our results argue against this interpretation. In four-room environments, each room had multiple entry points, yet MDCs never exhibited multidirectional activity within a single room."

      I do not understand the logic here. Can the authors unpack this? Also, it is clear that some of the example cells have more than one peak in individual compartments. How is this quantified?

    1. Reviewer #2 (Public review):

      Summary:

      The authors describe a tunable Bessel beam two-photon microscope (tBessel-TPFM) designed to overcome a common limitation of Bessel-based volumetric imaging: axial shifts of the effective focus during Bessel beam parameter tuning. Their optical design allows independent control of axial beam length and resolution while keeping the axial center fixed. This is extensively validated through simulations and experiments.

      Strengths:

      A major strength of the work is the breadth of validation combined with the level of technical detail provided. The authors carefully characterize the optical performance of the system and clearly explain the design choices and underlying derivations, which will make it easier for others to understand and implement. The authors demonstrate the utility of the method across several in vivo applications, including neurovascular imaging, blood flow measurements, optogenetic stimulation, and microglial dynamics.

      Weaknesses:

      In the in vivo demonstrations, the authors employ different Bessel beam configurations across experiments, but the beam parameters are not dynamically tuned during live imaging. A video example showing continuous or interactive tuning of the Bessel beam within a single in vivo imaging sequence would further highlight the practical advantages of this platform and strengthen the case for its potential applications. In addition, while excitation powers are reported, the manuscript does not place these values in the broader context of known photodamage thresholds for two-photon microscopy, which would be helpful to the readers. Denoising/image restoration are applied in one of the in vivo examples, but it is unclear why this step was used specifically for this dataset and whether it was necessary to achieve adequate SNR or primarily included as an additional demonstration.

    1. Reviewer #2 (Public review):

      Summary:

      This is a very interesting paper bringing new and important information about the poorly understood rhodopsin 7 photoreceptive molecule. The very ancient origin of the gene is revealed in addition to data supporting a signaling pathway that is different from the one known for the canonical rhodopsins. Precise expression data, particularly in the optic lobe of the fly, as well as clear behavioral phenotypes in responses to light changes, make this study a strong contribution to the understanding of the still-debated function of rhodopsin 7.

      Specific comments

      (1) Title and abstract: Contribution of Rh7 to circadian clock regulation

      (a) It is not that clear to me what rhodopsin does in terms of circadian regulation (even though its function might be circadianly regulated). The clear role in the light/dark distribution of activity might not be circadian per se, but mostly light/dark-driven, and there is no evidence here for a role in the entrainment of the clock.

      (b) The authors should cite Lazopulo, which nicely shows that Rh7 has an important role in peripheral neurons to allow flies to escape from blue light (see below).

      (2) Figure 2 C

      The finding showing that Galphaz but not Galphaq can trigger signaling from light-excited Rh7 is a very intriguing finding to better understand Rh7 function. Since Galphaz is related to Gi/o, it would be interesting to test those, for example, by expressing RNAi with Rh7-gal4 and testing the Light-dark or light-off response behavior.

      (3) Figures 3-4

      The change in the locomotor activity distribution between light and dark in LD conditions provides a nice assay for Rh7 function. Since Lazopulo et al. (2019) have shown that wild-type but not Rh7 mutants do escape from blue light, it would be important to compare and discuss these LD behavior data with the Lazopulo results. Precisely, is this nighttime preference linked to blue light?

      The expression data are really nice and show that Rh7 is mostly a non-retinal photoreceptor. However, the paper would be strongly reinforced by correlating this with the LD behavior. The LD phenotype should be tested in flies with Rh7 expression rescued under Rh7gal4 control (as done for the startle response). This is important to show whether the expression pattern is likely responsible for the described Rh7 function in LD. If L5 and or M11 drivers are available, they should be used to rescue Rh7? Since expression in some clock neurons is shown, the rescue experiment should also be done with a clock neuron driver.

      In the same line, can the LD phenotype (or startle response phenotype of Figure 4) be restored by expressing Rh7 under ppk control, as shown for the blue light avoidance phenotype by Lazopulo et al?

      Finally, the Rh7 "darkfly" rescued flies should be tested in LD.

    1. Reviewer #2 (Public review):

      Summary:

      Binge eating is often preceded by heightened negative affect, but the specific processes underlying this link are not well-understood. The purpose of this manuscript was to examine whether affect state (neutral or negative mood) impacts food choice decision-making processes that may increase likelihood of binge eating in individuals with bulimia nervosa (BN). The researchers used a randomized crossover design in women with BN (n=25) and controls (n=21), in which participants underwent a negative or neutral mood induction prior to completing a food-choice task. The researchers found that despite no differences in food choices in the negative and neutral conditions, women with BN demonstrated a stronger bias toward considering the 'tastiness' before the 'healthiness' of the food after the negative mood induction.

      Strengths:

      The topic is important and clinically relevant and methods are sound. The use of computational modeling to understand nuances in decision-making processes and how that might relate to eating disorder symptom severity is a strength of the study.

      Weaknesses:

      Sample size was relatively small, and participants were all women with BN, which limits generalizability of findings to the larger population of individuals who engage in binge eating. It is likely that the negative affect manipulation was weak and may not have been potent enough to change behavior. These limitations are adequately noted in the discussion.

    1. Reviewer #2 (Public review):

      Summary:

      This manuscript examines the association between atovaquone/proguanil use, zoster vaccination, toxoplasmosis serostatus and Alzheimer's Disease, using 2 databases of claims data. The manuscript is well written and concise. The major concerns about the manuscript center around the indications of atovaquone/proguanil use, which would not typically be active against toxoplasmosis at doses given, and the lack of control for potential confounders in the analysis.

      Strengths:

      (1) Use of 2 databases of claims data.

      (2) Unbiased review of medications associated with AD, which identified zoster vaccination associated with decreased risk of AD, replicating findings from other studies.

      Weaknesses:

      (1) Given that atovaquone/proguanil is likely to be given to a healthy population who is able to travel, concern that there are unmeasured confounders driving the association.

      (2) The dose of atovaquone in atovaquone/proguanil is unlikely to be adequate suppression of toxo (much less for treatment/elimination of toxo), raising questions about the mechanism.

      (3) Unmeasured bias in the small number of people who had toxoplasma serology in the TriNetX cohort.

    1. Reviewer #2 (Public review):

      Summary:

      The manuscript by Lima et al examines the role of Prmt1 and SFPQ in craniofacial development. Specifically, the authors test the idea that Prmt1 directly methylates specific proteins that results in intron retention in matrix proteins. The protein SFPQ is methylated by Prmt1 and functions downstream to mediate Prmt1 activity. The genes with retained introns activate the NMD pathway to reduce the RNA levels. This paper describes an interesting mechanism for the regulation of RNA levels during development.

      Strengths:

      The phenotypes support what the authors claim that Prmt1 is involved in craniofacial development and splicing. They use of state of the art sequencing to determine the specific genes that have intron retention and changes in gene expression is a strength.

      Weaknesses:

      The results now support the conclusions;however, it is still unclear how direct the relationship is between Prmt1 and SFPQ.

    1. Reviewer #3 (Public review):

      Summary:

      In this manuscript, Wang and colleagues explore factors contributing to the diversification of wtf meiotic drivers. wtf genes are autonomous, single-gene poison-antidote meiotic drivers that encode both a spore-killing poison (short isoform) and an antidote to the poison (long isoform) through alternative transcriptional initiation. There are dozens of wtf drivers present in the genomes of various yeast species, yet the evolutionary forces driving their diversification remain largely unknown. This manuscript is written in a straightforward and effective manner, and the analyses and experiments are easy to follow and interpret. While I find the research question interesting and the experiments persuasive, they do not provide any deeper mechanistic understanding of this gene family.

      Revision update:

      Having read the response to the reviewers, I believe the major issues have been addressed. However, I would strongly suggest toning down the claim regarding the chimeric WTF element in the abstract, which currently reads

      "As proof-of-principle, we generate a novel meiotic driver through artificial recombination between wtf drivers, and its encoded poison cannot be detoxified by the antidotes encoded by their parental wtf genes but can be detoxified by its own antidote."

      As the author reports in their response, despite various attempts, it was not possible to show that this chimeric WTF element was indeed capable of meiotic drive in a natural context (not transgenic overexpression experiment). thus the authors should not claim they generated "a novel meiotic driver"

      Strengths:

      (1) The authors present a comprehensive compendium and analysis of the evolutionary relationships among wtf genes across 21 strains of S. pombe

      (2) The authors found that a synthetic chimeric wtf gene, combining exons 1-5 of wtf23 and exon 6 of wtf18, behaves like a meiotic driver that could only be rescued by the chimeric antidote but neither of the parental antidotes. This is a very interesting observation that could account for their inception and diversification.

      Weaknesses:

      (1) Deletion strains

      The authors separately deleted all 25 Wtf genes in the S. pombe ference strain. Next, the authors performed spot assay to evaluate the effect of wtf gene knockout on the yeast growth. They report no difference to the WT and conclude that the wtf genes might be largely neutral to the fitness of their carriers in the asexual life cycle at least in normal growth condition.

      The authors could have conducted additional quantitative growth assays in yeast, such as growth curves or competition assays, which would have allowed them to detect subtle fitness effects that cannot be quantified with a spot assay. Furthermore, the authors do not rule out simpler explanations, such as genetic redundancy. This could have been addressed by crossing mutants of closely related paralogs or editing multiple wtf genes in the same genetic background.

      Another concern is the lack of detailed information about the 25 knockout strains used in the study. There is no information provided on how these strains were generated or, more importantly, validated. Many of these wtf genes have close paralogs and are flanked by repetitive regions, which could complicate the generation of such deletion strains. As currently presented, these results would be difficult to replicate in other labs due to insufficient methodological details

      Revision update:

      The authors measured the fitness of the deletion strains using growth curves (Fig. 2C and D) and no significant differences were found, further supporting their claims. The requested information (details on the generation of the deletion strains) is now available in the methods section.

      (2) Lack of controls

      The authors found that a synthetic chimeric wtf gene, constructed by combining exons 1-5 of wtf23 and exon 6 of wtf18, behaves as a meiotic driver that can be rescued only by its corresponding chimeric antidote, but not by either of the parental antidotes (Figure 4F). In contrast, three other chimeric wtf genes did not display this property (Figure 4C-E). No additional experiments were conducted to explain these differences, and basic control experiments, such as verifying the expression of the chimeric constructs, were not performed to rule out trivial explanations. This should be at the very least discussed. Also, it would have been better to test additional chimeras.

      Revision update:

      The authors report that the expression of the construct was measured. However, they do not make reference to any specific figure or section of the main text. It would be very useful if the authors explicitly referenced where exactly changes were made (this is true for all changed made)

      (3) Statistical analyses

      In line 130 the authors state that: "Given complex phylogenetic mixing observed among wtf genes (Figure 1E), we tested whether recombination occurred. We detected signals of recombination in the 25 wtf genes of the S. pombe reference genome (p = 0) and in the wtf genes of the 21 S. pombe strains (p = 0) using pairwise homoplasy index (HPI) test. "<br /> Reporting a p-value of 0 is not appropriate. Please report exact P-values.

      Revision update:

      This has been addressed.

    1. Reviewer #2 (Public review):

      Summary:

      Tian et al. explore the developmental origins of cortical reorganization in blindness. Previous work has found that a set of regions in the occipital cortex show different functional responses and patterns of functional correlations in blind vs. sighted adults. Here, Tian et al. explore how this organisation arises over development, asking whether the infant brain looks more like the blind adult pattern, or more like the sighted adult pattern. Their analyses reveal that the answer depends on the particular networks investigated. Some functional connections in infants look more like blind than sighted adults; other functional connections look more like sighted than blind adults; and others fall somewhere in the middle, or show an altogether different pattern in infants compared with both sighted and blind adults.

      Strengths:

      The paper addresses very important questions about the "starting state" in the developing visual cortex, and how cortical networks are shaped by experience. Another clear strength lies in the unequivocal nature of many results. Many results have very large effect sizes, critical interactions between regions and groups are tested and found, and infant analyses are replicated in split halves of the data.

      Weaknesses:

      While potential roles of experience (e.g., visual, cross-modal) are discussed in detail, little consideration is given to the role of experience-independent maturation. The infants scanned are extremely young, only 2 weeks old. It is possible that the sighted adult pattern may still emerge later in infancy or childhood, regardless of infant visual experience. If so, the blind adult pattern may depend on blindness-related experience only (which may or may not reflect "visual" experience per se). In short, it is not clear that the age range studied is a clear-cut "starting point" for development, after which all change can be attributed to experience.

    1. Reviewer #2 (Public review):

      Summary:

      Lesser et al. present an atlas of Drosophila wing sensory neurons. They proofread the axons of all sensory neurons in the wing nerve of an existing electron microscopy dataset, the female adult fly nerve cord (FANC) connectome. These reconstructed sensory axons were linked with light microscopy images of full-scale morphology to identify their origin in the periphery of the wing and encoded sensory modalities. The authors described the morphology and postsynaptic targets of proprioceptive neurons as well as previously unknown sensory neurons.

      Strengths:

      The authors present a valuable catalogue of wing sensory neurons, including previously undescribed sensory axons in the Drosophila wing. By providing both connectivity information with linked genetic drive lines, this research facilitates future work on the wing motor-sensory network and applications relating to Drosophila flight. The findings were linked to previous research as well as their putative role in the proprioceptive and nerve cord circuitry, providing testable hypotheses for future studies.

      Weaknesses:

      With future use as an atlas, it should be noted that the evidence is based on sensory neurons on only one side of the nerve cord. Fruit flies have stereotyped left/right hemispheres in the brain and left/right hemisegments in the nerve cord. Comparison of left and right neurons of the nervous system can give a sense of how robust the morphological and connectivity findings are. Unfortunately, this dataset has damage to the right side, making such comparisons unreliable.

    1. Reviewer #3 (Public review):

      This paper addresses, through experiment and simulation, the combined effects of bacterial circular swimming near no-slip surfaces and chemotaxis in simple linear gradients. The authors have constructed a microfluidic device in which a gradient of L-aspartate is established, to which bacteria respond while swimming while confined in channels of different widths. There is a clear effect that the chemotactic drift velocity reaches a maximum in channel widths of about 8 microns, similar in size to the circular orbits that would prevail in the absence of side walls. Numerical studies of simplified models confirm this connection.

      The experimental aspects of this study are well executed. The design of the microfluidic system is clever in that it allows a kind of "multiplexing" in which all the different channel widths are available to a given sample of bacteria.<br /> The authors have included a useful intuitive explanation of their results via a geometric model of the trajectories. In future work it would be interesting to analyze further the voluminous data on the trajectories of cells by formulating the mathematical problem in terms of a suitable Fokker-Planck equation for the probability distribution of swimming directions. In particular, this might help understand how incipient circular trajectories are interrupted by collisions with the walls and how this relates to enhanced chemotaxis.

      The authors argue that these findings may have relevance to a number of physiological and ecological contexts. As these would be characterized by significant heterogeneity in pore sizes and geometries, further work will be necessary to translate the present results to those situations.

    1. Reviewer #2 (Public review):

      The unstructured α- and β-tubulin C-terminal tails (CTTs), which differ between tubulin isoforms, extend from the surface of the microtubule, are post-translationally modified, and help regulate the function of MAPs and motors. Their dynamics and extent of interactions with the microtubule lattice are not well understood. Hotta et al. explore this using a set of three distinct probes that bind to the CTTs of tyrosinated (native) α-tubulin. Under normal cellular conditions, these probes associate with microtubules only to a limited extent, but this binding can be enhanced by various manipulations thought to alter the tubulin lattice conformation (expanded or compact). These include small-molecule treatment (Taxol), changes in nucleotide state, and the binding of microtubule-associated proteins and motors. Overall, the authors conclude that microtubule lattice "expanders" promote probe binding, suggesting that the CTT is generally more accessible under these conditions. Consistent with this, detyrosination is enhanced. Mechanistically, molecular dynamics simulations indicate that the CTT may interact with the microtubule lattice at several sites, and that these interactions are affected by the tubulin nucleotide state.

      Strengths and weaknesses:

      Key strengths of the work include the use of three distinct probes that yield broadly consistent findings, and a wide variety of experimental manipulations (drugs, motors, MAPs) that collectively support the authors' conclusions, alongside a careful quantitative approach.

      The challenges of studying the dynamics of a short, intrinsically disordered protein region within the complex environment of the cellular microtubule lattice, amid numerous other binders and regulators, should not be understated. While it is very plausible that the probes report on CTT accessibility as proposed, the possibility of confounding factors (e.g., effects on MAP or motor binding) cannot be ruled out. Sensitivity to the expression level clearly introduces additional complications. Likewise, for each individual "expander" or "compactor" manipulation, one must consider indirect consequences (e.g., masking of binding sites) in addition to direct effects on the lattice; however, this risk is mitigated by the collective observations all pointing in the same direction.

      The discussion does a good job of placing the findings in context and acknowledging relevant caveats and limitations. Overall, this study introduces an interesting and provocative concept, well supported by experimental data, and provides a strong foundation for future work. This will be a valuable contribution to the field.

    1. Reviewer #2 (Public review):

      Summary:

      In this work, the authors applied a range of computational methods to probe the translocation of cholesterol through the Smoothened receptor. They test whether cholesterol is more likely to enter the receptor straight from the outer leaflet of membrane or via a binding pathway in the inner leaflet first. Their data reveal that both pathways are plausible but that the free energy barriers of pathway 1 is lower suggesting this route is preferable. They also probe the pathway of cholesterol transport from the transmembrane region to the cysteine-rich domain (CRD).

      Strengths:

      A wide range of computational techniques are used, including potential of mean force calculations, adaptative sampling, dimensionality reduction using tICA, and MSM modelling. These are all applied in a rigorous manner and the data are very convincing. The computational work is an exemplar of a well-carried out study.

      Their computational predictions are experimentally supported using mutagenesis, with an excellent agreement between their PMF and mRNA fold change data.

      The data are described clearly and coherently, with excellent use of figures. They combine their findings into a mechanism for cholesterol transport, which on the whole seems sound.

      Their methods are described well, and much of their analysis methods have been made available via GitHub, which is an additional strength.

    1. Reviewer #2 (Public review):

      This is an ambitious and technically powerful study, investigating a long-standing question about the functional organization of area V4. The project combined large-scale single-unit electrophysiology in macaque V4 with deep learning-based activation maximization to characterize neuronal tuning in natural image space. The authors built predictive encoding models for V4 neurons and used these models to synthesize most exciting images (MEIs), which are subsequently validated in vivo using a closed-loop experimental paradigm.

      Overall, the manuscript advances three main claims:

      (1) Individual V4 neurons showed complex and highly structured selectivity for naturalistic visual features, including textures, curvatures, repeating patterns, and apparently eye-like motifs.

      (2) Neurons recorded along the same linear probe penetration tended to have more similar MEIs than neurons recorded at different cortical locations (this similarity was supported by human psychophysics and by distances in a learned, contrastive image embedding space).

      (3) MEIs clustered into a limited number of functional groups that resembled feature visualizations observed in deep convolutional neural networks.

      Strengths:

      (1) The study is important in that it is the first to apply activation maximization to neurons sampled at such fine spatial resolution. The authors used 32-channel linear silicon probes, spanning approximately 2 mm of cortical depth, with inter-contact spacing of roughly 60 µm. This enabled fine sampling across most of the cortical thickness of V4, substantially finer resolution than prior Utah-array or surface-biased approaches.

      (2) A key strength is the direct in vivo validation of model-derived synthetic images by stimulating the same neurons used to build the models, a critical step often absent in other neural network-based encoding studies.

      (3) More broadly, the study highlights the value of probing neuronal selectivity with rich, naturalistic stimulus spaces rather than relying exclusively on oversimplified stimuli such as Gabors.

      Weaknesses:

      (1) A central claim is that neurons sampled within the same penetration shared MEI tuning properties compared to neurons sampled in different penetrations because of functional organization. I am concerned about technical correlations in activity due to technical or methodology-related approaches (for example, shared reference or grounding) instead of functional organization alone. These recordings were obtained with linear silicon probes, and there have been observations that neuronal activity along this type of probe (including neuropixels probes) may be correlated above what prior work showed, using manually advanced single electrodes. For example, Fujita et al. (1992) showed finer micro-domains and systematic changes in selectivity along a cortical penetration, and it is not clear if that is true or detectable here. I think that the manuscript would be strengthened by a more thorough and explicit characterization of lower-level response correlations (at the neuronal electrophysiology level) prior to starting with fitting models. In particular, the authors could examine noise correlations along the electrode shaft (using the repeated test images, for example), as well as signal correlations in tuning, both within and across sessions. It would also be helpful to clarify whether these correlations depended on penetration day, recording chamber hole (how many were used?), or spatial separation between penetrations, and whether repeated use of the same hole yielded stable or changing correlations. Illustrations of the peristimulus time histogram changes across the shaft and across penetrations would also help. All of this would help us understand if the reports of clustering were technically inevitable due to the technique.

      (2) It is difficult to understand a story of visual cortex neurons without more information about their receptive field locations and widths, particularly given that the stimulus was full-screen. I understand that there was a sparse random dot stimulus used to find the population RF, so it should be possible to visualize the individual and population RFs. Also, the investigators inferred the locations of the important patches using a masking algorithm, but where were those masks relative to the retinal image, and how distributed were they as a function of the shaft location? This would help us understand how similar each contact was.

      (3) A major claim is that V4 MEIs formed groups that were comparable to those produced by artificial vision systems, "suggesting potential shared encoding strategies." The issue is that the "shared encoding strategy" might be the authors' use of this same class of models in the first place. It would be useful to know if different functional groups arise as a function of other encoding neural network models, beyond the robust-trained ResNet-50. I am unsure to what extent the reported clustering, depth-wise similarity, and correspondence to artificial features depended on architectural and training bias. It would substantially strengthen the manuscript to test whether a similar organizational structure would emerge using alternative encoding models, such as attention-based vision transformers, self-supervised visual representations, or other non-convolutional architectures. Another important point of contrast would be to examine the functional groups encoded by the ResNet architecture before its activations were fit to V4 neuronal activity: put simply, is ResNet just re-stating what it already knows?

      (4) Several comparisons to prior work are presented largely at a qualitative level, without quantitative support. For example, the authors state that their MEIs are consistent with known tuning properties of macaque V4, such as selectivity for shape, curvature, and texture. However, this claim is not supported by explicit image analyses or metrics that would substantiate these correspondences beyond appeal to visual inspection. Incorporating quantitative analyses, for instance, measures of curvature, texture statistics, or comparisons to established stimulus sets, would strengthen these links to prior literature and clarify the relationship between the synthesized MEIs and previously characterized V4 tuning properties.

    1. Reviewer #2 (Public review):

      Summary:

      This study introduces a novel knowledge-driven approach, miRTarDS, which enables microRNA-Target Interaction (MTI) prediction by leveraging the disease association degree between a miRNA and its target gene. The core hypothesis is that this single feature is sufficient to distinguish experimentally validated functional MTIs from computationally predicted MTIs in a binary classification setting. To quantify the disease association, the authors fine-tuned a Sentence-BERT (SBERT) model to generate embeddings of disease descriptions and compute their semantic similarity. Using only this disease association feature, miRTarDS achieved an F1 score of 0.88 on the test set.

      Strengths:

      The primary strength is the innovative use of the disease association degree as an independent feature for MTI classification. In addition, this study successfully adapts and fine-tunes the Sentence-BERT (SBERT) model to quantify the semantic similarity between biomedical texts (disease descriptions). This approach establishes a critical pathway for integrating powerful language models and the vast growth in clinical/disease data into biochemical discovery, like MTI prediction.

      Weaknesses:

      The main weakness lies in its definition of the ground-truth dataset, which serves as a foundation for methodological evaluation. The study defines the Negative Set as computationally predicted MTIs that lack experimental evidence. However, the absence of experimental validation does not equate to non-functionality. Similarly, the miRAW sets are classified by whether the target and miRNA could form a stable duplex structure according to RNA structure prediction. This definition is biologically irrelevant, as duplex stability does not fully encapsulate the complex in vivo binding of miRNAs within the AGO protein complex.

    1. Reviewer #2 (Public review):

      In this paper, the authors investigate the role of the cerebellum in song production in the zebra finch. First, they replicate prior studies to show that lesions of the lateral deep cerebellar nuclei (latDCN, primarily lobules IV-VII and IX) result in shorter duration syllables and song motifs than sham controls. The authors then record neural activity from the cerebellum during both passive auditory exposure in anesthetized birds and in freely singing animals. The authors claim that across multiple lobules, the cerebellum receives "non-selective" auditory inputs locked to syllable boundaries (based on acute recordings) and that cerebellar neurons display song-locked responses that are unaffected by auditory feedback perturbations (in chronic recordings). Moreover, the authors emphasized the distinct properties of lobule IV, which they argue is tightly locked to the onset and offset of syllables, and conclude that the cerebellum might contribute to the duration of song elements.

      This paper presents novel and useful descriptions of song-related neural activity in the cerebellum. However, there are multiple serious issues. First, there are major issues with the design and presentation of the analysis of the electrophysiological data; based on these, it is unclear whether the authors are justified in some of their conclusions about neural tuning or are entitled to any of their claims about the specific tuning or function of neurons in particular lobules. Second, because the authors' conceptual framework seems to ignore possible non-auditory inputs to the cerebellum, their results on (minimal) effects of auditory manipulation during singing are over-interpreted with respect to providing evidence of a forward model. Third, the paper's central assertion - that the songbird cerebellum may contribute to the duration of vocal events during song - was firmly established by a prior lesion study (Radic et al., 2024). Although the authors do cite this prior study with respect to longer-term postlesion changes after cerebellar lesions, this paper also showed a large change in syllable duration immediately after cerebellar lesion (Figure 5 in Radic et al). The electrophysiological results in the present paper could provide valuable insights into the neural mechanisms underlying this already-described role of the songbird cerebellum; however, given the other concerns above, it is not clear that the authors have done so.

    1. Reviewer #2 (Public review):

      Summary:

      The manuscript describes a combined computational and experimental approach to investigate the ABHD5 binding to and insertion into membranes.

      Strengths:

      Mutational experiments support computational findings obtained on ABHD5 membrane insertion with enhanced-sampling atomistic simulations.

      Weaknesses:

      While the addressed problem is interesting, I have several concerns, which fall into two categories:

      (A) I see statements throughout the manuscript, e.g. on PNPLA activation, that are not supported by the results.

      (B) The presentation of the computational and experimental results lacks in part clarity and detail.

      Comments and questions on (A):

      (1) I think the following statements in the abstract, which go beyond ABHD5 membrane binding, are not supported by the presented data:

      the addition "to control lipolytic activation" in the 3rd sentence of the abstract.

      further below ".... transforming ABHD5 into an active and membrane-localized regulator".

      (2) The authors state in the Introduction (page numbers and line numbers are missing to be more specific):

      "We hypothesize that binding of ABHD5 alters the nanoscale chemical and biophysical properties of the LD monolayer, which, combined with direct protein-protein interactions, enables PNPLA paralogs to access membrane-restricted substrates. This regulatory mechanism represents a paradigm shift from conventional enzyme-substrate interactions to sophisticated allosteric control systems that operate at membrane interfaces."

      This hypothesis and the suggested paradigm shift are not supported by the data. Protein-protein interactions are not considered. What is meant by "sophisticated allosteric control"?

      (3) The authors state in the Results section:

      "We hypothesize that this TAG nanodomain is critical for ABHD5-activated TAG hydrolysis by PNPLA2." In previous pages, the authors state the location of the nanodomain: "TAG nanodomain under ABHD5".

      If the nanodomain is located under ABHD5, how can it be accessible to PNPLA2? To my understanding, ABHD5 then sterically blocks access of PNPLA2 to the TAG nandomain.

      (4) Another statement: "Our findings suggest that ABHD5-mediated membrane remodeling regulates lipolysis in part by regulating PNPLA2 access to its TAG substrate."

      I don't see how the reported results support this statement (see point 3 above).

      Comments and questions on (B):

      (1) The authors state that the GaMD simulations started "from varying conformations observed during CGMD".

      What is missing is a clear description of the CGMD simulation conformations, and the CG simulations as a whole, prior to the results section on GaMD. The authors use standard secondary and tertiary constraints in the Martini CG simulations. Do the authors observe some (constrained) conformational changes of ABHD5 already in the CG simulations (depending on the strength of the constraints)? Or do the conformational changes occur exclusively in the GaMD simulations? Both are fine, but this needs to be described.

      (2) The authors write: "Three replicas of GaMD were performed."

      Do these replicas lead to similar, or statistically identical, membrane-bound ABHD5 conformations? Is this information, i.e. a statistical analysis of differences in the replica runs, already included in the manuscript?

      (3) The authors state on the hydrogen exchange results:

      "HDX-MS provided orthogonal experimental evidence for the dynamics of the lid. In solution, a peptide (residues 200-226) spanning the lid helix displayed a bimodal isotopic distribution (Fig. S4), indicating the coexistence of different conformations. Upon LD binding, this distribution shifted to a single, low-exchange peak, demonstrating stabilization of the membrane-bound conformation with reduced solvent accessibility. These experimental observations corroborate our MD simulations."

      I find this far too short to be understandable. Also, there are no computational results of ABHD5 in solution that show a bimodal conformational distribution of the lid helix, which is observed in the hydrogen exchange experiments. Which aspects of the MD simulations are corroborated?

    1. Reviewer #2 (Public review):

      Summary:

      This manuscript presents the "NoSeMaze", a novel automated platform for studying social behavior and cognitive performance in group-housed male mice. The authors report that mice form robust, transitive dominance hierarchies in this environment and that individual social rank remains largely stable across multiple group compositions. They further demonstrate that social dominance and aggressive behaviors, like chasing, are partially dissociable and that dominance traits are independent of non-social cognitive performance. The study includes a genetic manipulation of oxytocin receptor expression in the anterior olfactory nucleus, which showed only transient effects on social rank.

      Strengths:

      (1) Innovative Methodology:<br /> The NoSeMaze platform is a technically elegant and conceptually well-integrated system that enables fully automated, long-term monitoring of both social and cognitive behaviors in large groups of group-housed mice. It combines tube-test-like dominance contests, voluntary chase-escape interactions, and an embedded operant olfactory discrimination task within a single, ethologically relevant environment. This modular design allows for high-throughput, minimally invasive behavioral assessment without the need for repeated handling or artificial isolation.

      (2) Experimental Scale and Rigor:<br /> The study includes 79 male mice and over 4,000 mouse-days of observation across multiple group reshufflings. The use of RFID-based identification, automated data logging, and longitudinal design enables robust quantification of individual trait stability and group-level social structure.

      (3) Multidimensional Behavioral Profiling:<br /> The integration of social (tube dominance, proactive chasing), physical (body weight), and cognitive (olfactory learning task) measures offers a rich, multi-dimensional profile of each individual mouse. The authors' finding that social dominance traits and non-social cognitive performance are largely uncorrelated reinforces emerging models of orthogonal behavioral trait axes or "animal personalities".

      (4) Clarity and Data Analysis:<br /> The analytical framework is well-suited to the study's complexity, with appropriate use of dominance metrics, mixed-effects models, and permutation tests. The analyses are clearly explained, statistically rigorous, and supported by transparent supplementary materials.

      Weaknesses:

      (1) Conceptual Novelty and Prior Work:<br /> While the study is carefully executed and methodologically innovative, several of its core findings reaffirm concepts already established in the literature. The emergence of stable, transitive social hierarchies, the persistence of individual differences in social behavior, and the presence of non-despotic social structures have all been previously reported in mice, including under semi-naturalistic conditions (e.g., Fan et al., 2019; Forkosh et al., 2019). Although this work extends those findings with greater behavioral resolution and scale, the manuscript would benefit from a clearer articulation of what is genuinely novel at the conceptual level, beyond the technological advance.

      (2) Role of OXTR Deletion:<br /> The inclusion of the OXTR manipulation feels somewhat disconnected from the manuscript's central aims. The effects were minimal and transient, and the authors defer full interpretation to a separate study.

      (3) Scope Limitations (Sex and Age):<br /> The study is limited to male mice, and although this is acknowledged, the title and overall framing imply broader generalizability. This sex-specific focus represents a common but problematic bias. Additionally, results from the older mouse cohort are under-discussed; if age had no effect, this should be explicitly stated.

      (4) Ambiguity of Dominance as a Construct:<br /> While the study robustly quantifies social rank and hierarchy structure, the broader functional meaning of "dominance" remains unclear. As in prior work (e.g., Varholick et al., 2019), dominance rank here shows only weak associations with physical attributes (e.g., body weight), cognitive strategy, or neuromodulatory manipulation (OXTR deletion). This recurring pattern, where rank metrics are reliably established yet poorly predictive of other behavioral or biological traits, raises important questions about what such measures actually capture. In particular, it challenges the assumption that outcomes in paradigms like the tube test or chase frequency necessarily reflect dominance per se, rather than other constructs.

    1. Reviewer #2 (Public review):

      Summary:

      In this study, the authors were testing the hypothesis that hemagglutination inhibition antibody titers, measured later in life, might be higher against influenza viruses that belong to the same hemagglutinin classification group as the influenza virus that a person was likely first exposed to early in life. This is one conceptualization of a phenomenon termed immune imprinting, which may explain previously observed differences in susceptibility to severe influenza infection between cohorts that were likely first exposed to different hemagglutinin groups. The results of the analysis provide some support for this analysis. However, support for the hypothesis is not consistently observed across sensitivity analyses, and a simulation study finds that antibody patterns consistent with immune imprinting may arise due to other factors in the absence of true imprinting effects. Therefore, overall support for the hypothesis is weak. Nonetheless, this study is important in that it provides guidance and has developed an analytic methodology for additional studies in this area of research. These findings and methods may also be useful for other infectious diseases for which patterns consistent with immune imprinting have been observed.

      Strengths:

      The strengths of this study include the relatively large cohort data source with broad age representation, rigorous statistical methods, and the use of sensitivity and simulation analyses to assess the robustness of the results.

      Weaknesses:

      The model outcome includes antibody titers measured against many different viruses, and the imprinting parameter was defined at the subtype level. This may obscure specific imprinting effects related to finer structural similarities between first and subsequent virus exposures. This analysis focuses only on one component of the immune response to influenza; immune imprinting may also involve other immune mechanisms. The analysis was carried out in a Chinese cohort, and vaccination status of the cohort is not discussed; the results may not be generalizable to other populations, particularly if vaccination patterns differ.

    1. Reviewer #2 (Public review):

      Summary:

      Zhao et al investigate how object location and colour are degraded across saccadic eye movements. They employ an eye-tracking task that requires participants to remember two sequentially presented items and subsequently report the colour and position of either one of these. Through counterbalancing of the presence or absence of saccades across items, the authors endeavour to dissect the impact of saccades independently on item location or colour. These behavioural findings form the basis of generative models designed to test competing, nested accounts of how stored information is stored and updated across saccades.

      Strengths:

      The combination of eye-tracking and generative modelling is a strength of the paper, which opens new perspectives into the impact of Alzheimer's and Parkinson's disease on the performance of visuospatial cognitive tests. The finding that the model parameters covary with clinical performance on the ROCF test is a nice example of a "computational assay" of disease.

      Comments on revisions:

      I thank the authors for their detailed responses and revisions arising from my feedback on the original manuscript. The revised manuscript adequately addresses all of my concerns.

    1. Reviewer #3 (Public review):

      Summary:

      Sarkar, Bhandari, Jaiswal and colleagues establish a suite of quantitative and genetic tools to use Drosophila melanogaster as a model metazoan organism to study polyphosphate (polyP) biology. By adapting biochemical approaches for use in D. melanogaster, they identify a window of increased polyP levels during development. Using genetic tools, they find that depleting polyP from the cytoplasm alters the timing of metamorphosis, accelerationg eclosion. By adapting subcellular imaging approaches for D. melanogaster, they observe polyP in the nucleolus of several cell types. They further demonstrate that polyP localizes to cytoplasmic puncta in hemocytes, and further that depleting polyP from the cytoplasm of hemocytes impairs hemolymph clotting. Together, these findings establish D. melanogaster as a tractable system for advancing our understanding of polyP in metazoans.

      Strengths:

      • The FLYX system, combining cell type and compartment-specific expression of ScPpx1, provides a powerful tool for the polyP community.

      • The finding that cytoplasmic polyP levels change during development and affect the timing of metamorphosis is an exciting first step in understanding the role of polyP in metazoan development, and possible polyP-related diseases.

      • Given the significant existing body of work implicating polyP in the human blood clotting cascade, this study provides compelling evidence that polyP has an ancient role in clotting in metazoans.

      Limitations:

      • While the authors demonstrate that HA-ScPpx1 protein localizes to the target organelles in the various FLYX constructs, the capacity of these constructs to deplete polyP from the different cellular compartments is not shown. This is an important control to both demonstrate that the GTS-PPBD labeling protocol works, and also to establish the efficacy of compartment-specific depletion. While not necessary to do for all the constructs, it would be helpful to do this for the cyto-FLYX and nuc-FLYX.

      • The cell biological data in this study clearly indicates that polyP is enriched in the nucleolus in multiple cell types, consistent with recent findings from other labs, and also that polyP affects gene expression during development. Given that the authors also generate the Nuc-FLYX construct to deplete polyP from the nucleus, it is surprising that they test how depleting cytoplasmic but not nuclear polyP affects development. However, providing these tools is a service to the community, and testing the phenotypic consequences of all the FLYX constructs may arguably be beyond the scope of this first study.

      Editors' note: The authors have satisfactorily responded to our most major concerns related to the specificity of PPDB and the physiological levels of polyPs in the clotting experiments. We also recognise the limitations related to the depletion of polyP in other tissues and hope that these data will be made available soon.

    1. Reviewer #2 (Public review):

      Summary:

      The study by Li et al. proposes a dual-path framework that concurrently decodes acoustic and linguistic representations from ECoG recordings. By integrating advanced pre-trained AI models, the approach preserves both acoustic richness and linguistic intelligibility, and achieves a WER of 18.9% with a short (~20-minute) recording.

      Overall, the study offers an advanced and promising framework for speech decoding. The method appears sound, and the results are clear and convincing. My main concerns are the need for additional control analyses and for more comparisons with existing models.

      Strengths:

      • This speech-decoding framework employs several advanced pre-trained DNN models, reaching superior performance (WER of 18.9%) with relatively short (~20-minute) neural recording.

      • The dual-pathway design is elegant, and the study clearly demonstrates its necessity: The acoustic pathway enhances spectral fidelity while the linguistic pathway improves linguistic intelligibility.

      Comments on revisions:

      The authors have thoughtfully addressed my previous concerns about the weaknesses. I have no further concerns.

    1. Reviewer #2 (Public review):

      Summary:

      Calcium ions play a key role in synaptic transmission and plasticity. To improve calcium measurements at synaptic terminals, previous studies have targeted genetically encoded calcium indicators (GECIs) to pre- and postsynaptic locations. Here, Chen et al. improve these constructs by incorporating the latest GCaMP8 sensors and a stable red fluorescent protein to enable ratiometric measurements. Extensive characterization in the Drosophila neuromuscular junction demonstrates favorable performance of these new constructs relative to previous genetically encoded and synthetic calcium indicators in reporting synaptic calcium events. In addition, they develop a new analysis platform, 'CaFire', to facilitate automated quantification. Impressively, by positioning postsynaptic GCaMP8m near glutamate receptors, the authors show that their sensors can report miniature synaptic events with speed and sensitivity approaching that of intracellular electrophysiological recordings. These new sensors and the analysis platform provide a valuable tool for resolving synaptic events using all-optical methods.

      Strength:

      The authors present rigorous characterization of their sensors using well-established assays. They employ immunostaining and super-resolution STED microscopy to confirm correct subcellular targeting. Additionally, they quantify response amplitude, rise and decay kinetics, and provide side-by-side comparisons with earlier-generation GECIs and synthetic dyes. Importantly, they show that the new sensors can reproduce known differences in evoked Ca²⁺ responses between distinct nerve terminals. Finally, they present what appears to be the first simultaneous calcium imaging and intracellular mEPSP recording to directly assess the sensitivity of different sensors in detecting individual miniature synaptic events.

      The revised version contains extensive new data and clarification that fully addressed my previous concerns. In particular, I appreciate the side-by-side comparison with synthetic calcium indicator OGB-1 and the cytosolic version of GCaMP8m (now presented in Figure 3), which compellingly supports the favorable performance of their new sensors.

      Weakness:

      I have only one remaining suggestion about the precision of terminology, which I do think is important. The authors clarified in the revision that they "define SNR operationally as the fractional fluorescence change (ΔF/F).", and basically present ΔF/F values whenever they mentioned about SNR. However, if the intention is to present ΔF/F comparisons, I would strongly suggest replacing all mentions of "SNR" in the manuscript with "ΔF/F" or "fractional/relative fluorescence change".

      SNR and ΔF/F are fundamentally different quantities, each with a well-defined and distinct meaning: SNR measures fluorescence change relative to baseline fluctuations (noise), whereas ΔF/F measures fluorescence change relative to baseline fluorescence (F₀). While larger ΔF/F values often correlate with improved detectability, SNR also depends on additional factors such as indicator brightness, light collection efficiency, camera noise, and the stability of the experimental preparation. Referring to ΔF/F as SNR can therefore be misleading and may cause confusion for readers, particularly those from quantitative imaging backgrounds. Clarifying the terminology by consistently using ΔF/F would improve conceptual accuracy without requiring any reanalysis of the data.

    1. Reviewer #2 (Public review):

      Parkes et al. combined real-time keypoint tracking with transdermal activation of sensory neurons to examine the effects of recruitment of sensory neurons in freely moving mice. This builds on the authors' previous investigations involving transdermal stimulation of sensory neurons in stationary mice. They illustrate multiple scenarios in which their engineering improvements enable more sophisticated behavioral assessments, including 1) stimulation of animals in multiple states in large arenas, 2) multi-animal nociceptive behavior screening through thermal and optogenetic activation, and 3) stimulation of animals running through maze corridors. Overall, the experiments and the methodology, in particular, is written clearly. The revised manuscript nicely demonstrates a state-dependence in the behavioral response to activation of TrpV1 sensory neurons, which is a nice demonstration of how their real-time optogenetic stimulation capabilities can yield new insights into complex sensory processing.

      Comments on revisions:

      I agree that your revisions have substantially improved the clarity and quality of the work.

    1. Reviewer #2 (Public review):

      Summary:

      This is a concise and interesting article on the role of PHD1-mediated proline hydroxylation of proline residue 604 on RepoMan and its impact on RepoMan-PP1 interactions with phosphatase PP2A-B56 complex leading to dephosphorylation of H3T3 on chromosomes during mitosis. Through biochemical and imaging tools, the authors delineate a key mechanism in regulation of progression of the cell cycle. The experiments performed are conclusive with well-designed controls.

      Strengths:

      The authors have utilized cutting edge imaging and colocalization detection technologies to infer the conclusions in the manuscript.

      Weaknesses:

      Lack of in vitro reconstitution and binding data.

      Comments on revisions:

      Thank you, authors, for providing the statistics and siRNA validations. While I maintain that the manuscript's claims can benefit a lot from the in vitro experiments and that a Pro-Ala mutation may not be a good mimic for Pro-hydroxylation, I understand the authors' reservations and restrictions regarding the new experiments. Despite the lacunae, the manuscript is a good advance for the field.

    1. Reviewer #2 (Public review):

      Summary:

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

      Strengths:

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

      Weaknesses:

      The sample size collected (N = 6) is, in my opinion, too small for the statistical approach adopted (group level). It is well known that small sample sizes result in an increased likelihood of false positives; even in the case of true positives, effect sizes are inflated (Button et al., 2013; Tamar and Orban de Xivry, 2019), negatively affecting the replicability of the effect.

      Although the experimental design allows for an accurate characterization of the effects at the single-subject level, conclusions are drawn from group-level aggregated measures. With only six subjects, the estimation of between-subject variability is not reliable. The authors need to acknowledge that the sample size is too small; therefore, results should be interpreted with caution.

      Conclusion:

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

      Bibliography:

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

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

    1. Reviewer #2 (Public review):

      Summary:

      In the manuscript, "An IL-21R hypomorph circumvents functional redundancy to define STAT1 signaling in germinal center responses," Cecile King and colleagues identify a cytoplasmic site of the IL-21 receptor that differentially regulates STAT1 and STAT3 activation upon IL-21 stimulation. They further examine the immunological consequences of this site-specific alteration on Tfh differentiation and Tfh-dependent humoral immunity, raising important questions about how gene-knockout models may obscure nuanced functional roles of signaling molecules.

      Strengths:

      The study convincingly highlights a non-redundant role for STAT1 downstream of IL-21-IL-21R signaling in the Tfh differentiation pathway. This conclusion is supported by in vitro analyses of STAT1 and STAT3 activation in CD4 T cells stimulated with IL-21 or IL-6; by in vivo assessments of Tfh and germinal center B cell responses in WT and IL21R-EINS mutant mice, including bone-marrow chimera systems; and by investigating the expression of Tfh-related molecules in WT versus IL21R-EINS CD4 T cells.

      Weaknesses:

      Although the experiments were carefully executed with appropriate controls, a key question remains unresolved: whether the Tfh differentiation defect in IL21R-EINS mice is directly attributable to reduced STAT1 activation. Rescue experiments that restore STAT1 signaling in IL21R-EINS TCR-transgenic CD4 T cells would provide strong evidence linking the mutation to impaired STAT1 activation and, consequently, defective Tfh differentiation. Without such evidence, it remains formally possible that additional, uncharacterized mutations introduced during ENU mutagenesis contribute to the phenotypes observed, particularly given the discrepancies between IL21R knockout and IL21R-EINS mutant mice.

    1. Reviewer #2 (Public review):

      This study presents a significant advance in the field of in vitro ribosome assembly by demonstrating that the bacterial GTPases EngA and ObgE enable single-step reconstitution of functional 50S ribosomal subunits under near-physiological conditions-specifically at 37 {degree sign}C and with total Mg²⁺ concentrations below 10 mM.

      This achievement directly addresses a long-standing limitation of the traditional two-step in vitro assembly protocol (Nierhaus & Dohme, PNAS 1974), which requires non-physiological temperatures (44-50 {degree sign}C), and high Mg²⁺ concentrations (~20 mM). Inspired by the integrated Synthesis, Assembly, and Translation (iSAT) platform (Jewett et al., Mol Syst Biol 2013), leveraging E. coli S150 crude extract, which supplies essential assembly factors, the authors hypothesize that specific ribosome biogenesis factors-particularly GTPases present in such extracts-may be responsible for enabling assembly under mild conditions. Through systematic screening, they identify EngA and ObgE as the minimal pair sufficient to replace the need for temperature and Mg²⁺ shifts when using phenol-extracted (i.e., mature, modified) rRNA and purified TP70 proteins.

      However, several important concerns remain:

      (1) Dependence on Native rRNA Limits Generalizability

      The current system relies on rRNA extracted from native ribosomes via phenol, which retains natural post-transcriptional modifications. As the authors note (lines 302-304), attempts to assemble active 50S subunits using in vitro transcribed rRNA, even in the presence of EngA and ObgE, failed. This contrasts with iSAT, where in vitro transcribed rRNA can yield functional (though reduced-activity, ~20% of native) ribosomes, presumably due to the presence of rRNA modification enzymes and additional chaperones in the S150 extract. Thus, while this study successfully isolates two key GTPase factors that mimic part of iSAT's functionality, it does not fully recapitulate iSAT's capacity for de novo assembly from unmodified RNA. The manuscript should clarify that the in vitro assembly demonstrated here is contingent on using native rRNA and does not yet achieve true bottom-up reconstruction from synthetic parts. Moreover, given iSAT's success with transcribed rRNA, could a similar systematic omission approach (e.g., adding individual factors) help identify the additional components required to support unmodified rRNA folding?

      (2) Imprecise Use of "Physiological Mg²⁺ Concentration"

      The abstract states that assembly occurs at "physiological Mg²⁺ concentration" (<10 mM). However, while this total Mg²⁺ level aligns with optimized in vitro translation buffers (e.g., in PURE or iSAT systems), it exceeds estimates of free cytosolic [Mg²⁺] in E. coli (~1-2 mM). The authors should clarify that they refer to total Mg²⁺ concentrations compatible with cell-free protein synthesis, not necessarily intracellular free ion levels, to avoid misleading readers about true physiological relevance.

      In summary, this work elegantly bridges the gap between the two-step method and the extract-dependent iSAT system by identifying two defined GTPases that capture a core functionality of cellular extracts: enabling ribosome assembly under translation-compatible conditions. However, the reliance on native rRNA underscores that additional factors - likely present in iSAT's S150 extract - are still needed for full de novo reconstitution from unmodified transcripts. Future work combining the precision of this defined system with the completeness of iSAT may ultimately realize truly autonomous synthetic ribosome biogenesis.

    1. Reviewer #2 (Public review):

      Summary:

      In this manuscript, the authors investigated magnesium isoglycyrrhizinate (MgIG)'s hepatoprotective actions in chronic-binge alcohol-associated liver disease (ALD) mouse models and ethanol/palmitic acid-challenged AML-12 hepatocytes. They found that MgIG markedly attenuated alcohol-induced liver injury, evidenced by ameliorated histological damage, reduced hepatic steatosis, and normalized liver-to-body weight ratios. RNA sequencing identified isopentenyl diphosphate delta isomerase 1 (IDI1) as a key downstream effector. Hepatocyte-specific genetic manipulations confirmed that MgIG modulates the SREBP2-IDI1 axis. The mechanistic studies suggested that MgIG could directly target HSD11B1 and modulate the HSD11B1-SREBP2-IDI1 axis to attenuate ALD. This manuscript is of interest to the research field of ALD.

      Strengths:

      The authors have performed both in vivo and in vitro studies to demonstrate the action of magnesium isoglycyrrhizinate on hepatocytes and an animal model of alcohol-associated liver disease.

      Weaknesses:

      The data were not well-organised, and the paper needs proofreading again, with a focus on the use of scientific language throughout.

      Here are several comments:

      (1) In Supplemental Figure 1A, all the treatment arms (A-control, MgIG-25 mg/kg, MgIG-50 mg/kg) showed body weight loss compared to the untreated controls. However, Figure 1E showed body weight gain in the treatment arms (A-control and MgIG-25 mg/kg), why? In Supplemental Figure 1A, the mice with MgIG (25 mg/kg) showed the lowest body weight, compared to either A-control or MgIG (50 mg/kg) treatment. Can the authors explain why MgIG (25 mg/kg) causes bodyweight loss more than MgIG (50 mg/kg)? What about the other parameters (ALT, ALS, NAS, etc.) for the mice with MgIG (50 mg/kg)?

      (2) IL-6 is a key pro-inflammatory cytokine significantly involved in ALD, acting as a marker of ALD severity. Can the authors explain why MgIG 1.0 mg/ml shows higher IL-6 gene expression than MgIG (0.1-0.5 mg/ml)? Same question for the mRNA levels of lipid metabolic enzymes Acc1 and Scd1.

      (3) For the qPCR results of Hsd11b1 knockdown (siRNA) and Hsd11b1 overexpression (plasmid) in AML-12 cells (Figure 5B), what is the description for the gene expression level (Y axis)? Fold changes versus GAPDH? Hsd11b1 overexpression showed non-efficiency (20-23, units on Y axis), even lower than the Hsd11b1 knockdown (above 50, units on Y axis). The authors need to explain this. For the plasmid-based Hsd11b1 overexpression, why does the scramble control inhibit Hsd11b1 gene expression (less than 2, units on the Y axis)? Again, this needs to be explained.

    1. Reviewer #2 (Public review):

      Summary:

      The authors aimed to dissect the plasticity of circadian outputs by combining evolutionary biology with chronobiology. By utilizing Drosophila strains selected for "Late" and "Early" adult emergence, they sought to investigate whether selection for developmental timing co-evolves with plasticity in daily locomotor activity. Specifically, they examined how these diverse lines respond to complex, desynchronized environmental cues (temperature and light cycles) and investigated the molecular role of the splicing factor Psi and timeless isoforms in mediating this plasticity.

      Major strengths and weaknesses:

      The primary strength of this work is the novel utilization of long-term selection lines to address fundamental questions about how organisms cope with complex environmental cues. The behavioral data are compelling, clearly demonstrating that "Late" and "Early" flies possess distinct capabilities to track temperature cycles when they are desynchronized from light cycles.

      However, a significant weakness lies in the causal links proposed between the molecular findings and these behavioral phenotypes. The molecular insights (Figures 2, 4, 5, and 6) rely on mRNA extracted from whole heads. As head tissue is dominated by photoreceptor cells and glia rather than the specific pacemaker neurons (LNv, LNd) driving these behaviors, this approach introduces a confound. Differential splicing observed here may reflect the state of the compound eye rather than the central clock circuit, a distinction highlighted by recent studies (e.g., Ma et al., PNAS 2023).

      Furthermore, while the authors report that Psi mRNA loses rhythmicity under out-of-sync conditions, this correlation does not definitively prove that Psi oscillation is required for the observed splicing patterns or behavioral plasticity. The amplitude of the reported Psi rhythm is also low (~1.5 fold) and variable, raising questions about its functional significance in the absence of manipulation experiments (such as constitutive expression) to test causality.

      Appraisal of aims and conclusions:

      The authors successfully demonstrate the co-evolution of emergence timing and activity plasticity, achieving their aim on the behavioral level. However, the conclusion that the specific molecular mechanism involves the loss of Psi rhythmicity driving timeless splicing changes is not yet fully supported by the data. The current evidence is correlative, and without spatial resolution (specific clock neurons) or causal manipulation, the mechanistic model remains speculative.

      This study is likely to be of significant interest to the chronobiology and evolutionary biology communities as it highlights the "enhanced plasticity" of circadian clocks as an adaptive trait. The findings suggest that plasticity to phase lags - common in nature where temperature often lags light - may be a key evolutionary adaptation. Addressing the mechanistic gaps would significantly increase the utility of these findings for understanding the molecular basis of circadian plasticity.

    1. Reviewer #2 (Public review):

      Summary:

      In this manuscript, Jiang et al. developed a robust workflow for identifying proline hydroxylation sites in proteins. They identified proline hydroxylation sites in HEK293 and RCC4 cells, respectively. The authors found that the more hydrophilic HILIC fractions were enriched in peptides containing hydroxylated proline residues. These peptides showed differences in charge and mass distribution compared to unmodified or oxidized peptides. The intensity of the diagnostic hydroxyproline iminium ion depended on parameters including MS collision energy, parent peptide concentration, and the sequence of amino acids adjacent to the modified proline residue. Additionally, they demonstrate that a combination of retention time in LC and optimized MS parameter settings reliably identifies proline hydroxylation sites in peptides, even when multiple proline residues are present

      Strengths:

      Overall, the manuscript presents an advanced, standardized protocol for identifying proline hydroxylation. The experiments were well designed, and the developed protocol is straightforward, which may help resolve confusion in the field.

      Comments on revisions:

      All of my concerns have been resolved by the authors. It is ready for publication.

    1. Reviewer #3 (Public review):

      Summary:

      Recently, the off-target activity of antibiotics on human mitoribosome has been paid more attention in the mitochondrial field. Hafner et al applied mitoribosome profilling to study the effect of antibiotics on protein translation in mitochondria as there are similarities between bacterial ribosome and mitoribosome. The authors conclude that some antibiotics act on mitochondrial translation initiation by the same mechanism as in bacteria. On the other hand, the authors showed that chloramphenicol, linezolid and telithromycin trap mitochondrial translation in a context-dependent manner. More interesting, during deep analysis of 5' end of ORF, the authors reported the alternative start codon for ND1 and ND5 proteins instead of previously known one. This is a novel finding in the field and it also provide another application of the technique to further study on mitochondrial translation.

      Strengths:

      This is the first study which applied mitoribosome profiling method to analyze mutiple antibiotics treatment cells. The mitoribosome profiling method had been optimized carefully and has been suggested to be a novel method to study translation events in mitochondria. The manuscript is constructive and well-written.

      Weaknesses:

      This is a novel and interesting study, however, most of conclusion comes from mitoribosome profiling analysis, as the result, the manuscript lacks the cellular biochemical data to provide more evidence and support the findings.

      Comments on revisions:

      The authors addressed most of my concerns and comments, although there is still no biochemical assay which should be performed to support mitoribsome profiling data.

      The author also carefully investigated the structure of complex I, however, I am surprised that the author chose to analyse a low resolution structure (3.7 A). Recently, there are more high resolution structures of mammalian complex I published (7R41, 7V2C, 7QSM, 9I4I). Furthermore, the authors should not only respond to the reviewers but also (somehow) discuss these points in the manuscript.

    1. Reviewer #2 (Public review):

      This paper remarkably reveals the identification of plasma membrane repair proteins, revealing spatiotemporal cellular responses to plasma membrane damage. The study highlights a combination of sodium dodecyl sulfate (SDS) and lase for identifying and characterizing proteins involved in plasma membrane (PM) repair in Saccharomyces cerevisiae. From 80 PM, repair proteins that were identified, 72 of them were novel proteins. The use of both proteomic and microscopy approaches provided a spatiotemporal coordination of exocytosis and clathrin-mediated endocytosis (CME) during repair. Interestingly, the authors were able to demonstrate that exocytosis dominates early and CME later, with CME also playing an essential role in trafficking transmembrane-domain (TMD) containing repair proteins between the bud tip and the damage site.

      Weaknesses/limitations:

      - Still, there is a lack of clarity about mentioning Pkc1 as the best characterized repair protein, or why is Pkc1 mentioned only as it is changing the localization?!

      - The use of a C-terminal GFP-tagged library for the laser damage assay may have limited the identification of proteins whose localization or function depends on an intact N-terminus. N-terminal regions might contain targeting or regulatory elements; therefore, some relevant repair factors may have been missed. Analysis of endogenously N-terminally tagged strains, at least for selected candidates, could help address this limitation.

      - The authors appropriately discuss the limitations of SDS- and laser-induced plasma membrane damage, including the possibility that these approaches may not capture proteins involved in other forms of membrane injury, such as mechanical or osmotic stress.

    1. Reviewer #2 (Public review):

      Summary:

      Feng, Jing-Xin et al. studied the hemogenic capacity of the endothelial cells in the adult mouse bone marrow. Using Cdh5-CreERT2 in vivo inducible system, though rare, they characterized a subset of endothelial cells expressing hematopoietic markers that were transplantable. They suggested that the endothelial cells need the support of stromal cells to acquire blood-forming capacity ex vivo. These endothelial cells were transplantable and contributed to hematopoiesis with ca. 1% chimerism in a stress hematopoiesis condition (5-FU) and recruited to the peritoneal cavity upon Thioglycolate treatment. Ultimately, the authors detailed the blood lineage generation of the adult endothelial cells in a single cell fashion, suggesting a predominant HSPCs-independent blood formation by adult bone marrow endothelial cells, in addition to the discovery of Col1a2+ endothelial cells with blood-forming potential, corresponding to their high Runx1 expressing property.

      The conclusion regarding the characterization of hematopoietic-related endothelial cells in adult bone marrow is well supported by data. However, the paper would be more convincing, if the function of the endothelial cells were characterized more rigorously.

      (1) Ex vivo culture of CD45-VE-Cadherin+ZsGreen EC cells generated CD45+ZsGreen+ hematopoietic cells. However, given that FACS sorting can never achieve 100% purity, there is a concern that hematopoietic cells might arise from the ones that got contaminated into the culture at the time of sorting. The sorting purity and time course analysis of ex vivo culture should be shown to exclude the possibility.

      (2) Although it was mentioned in the text that the experimental mice survived up to 12 weeks after lethal irradiation and transplantation, the time-course kinetics of donor cell repopulation (>12 weeks) would add a precise and convincing evaluation. This would be absolutely needed as the chimerism kinetics can allow us to guess what repopulation they were (HSC versus progenitors). Moreover, data on either bone marrow chimerism assessing phenotypic LT-HSC and/or secondary transplantation would dramatically strengthen the manuscript.

      (3) The conclusion by the authors, which says "Adult EHT is independent of pre-existing hematopoietic cell progenitors", is not fully supported by the experimental evidence provided (Figure 4 and Figure S3). More recipients with ZsGreen+ LSK must be tested.

      Strengths:

      The authors used multiple methods to characterize the blood-forming capacity of the genetically - and phenotypically - defined endothelial cells from several reporter mouse systems. The polylox barcoding method to trace the adult bone marrow endothelial cell contribution to hematopoiesis is a strong insight to estimate the lineage contribution.

      Weaknesses:

      It is unclear what the biological significance of the blood cells de novo generated from the adult bone marrow endothelial cells is. Moreover, since the frequency is very rare (<1% bone marrow and peripheral blood CD45+), more data regarding its identity (function, morphology, and markers) are needed to clearly exclude the possibility of contamination/mosaicism of the reporter mice system used.

    1. Reviewer #2 (Public review):

      Summary:

      The authors investigated the effects of a low-protein diet (LPD) and a high sugar- and fat-rich diet (Western diet, WD) on paternal metabolic and reproductive parameters and feto-placental development and gene expression. They did not observe significant effects on fertility; however, they reported gut microbiota dysbiosis, alterations in testicular morphology, and severe detrimental effects on spermatogenesis. In addition, they examined whether the adverse effects of these diets could be prevented by supplementation with methyl donors. Although LPD and WD showed limited negative effects on paternal reproductive health (with no impairment of reproductive success), the consequences on fetal and placental development were evident and, as reported in many previous studies, were sex-dependent.

      Strengths:

      This study is of high quality and addresses a research question of great global relevance, particularly in light of the growing concern regarding the exponential increase in metabolic disorders, such as obesity and diabetes, worldwide. The work highlights the importance of a balanced paternal diet in regulating the expression of metabolic genes in the offspring at both fetal and placental levels. The identification of genes involved in metabolic pathways that may influence offspring health after birth is highly valuable, strengthening the manuscript and emphasizing the need to further investigate long-term outcomes in adult offspring.

      The histological analyses performed on paternal testes clearly demonstrate diet-induced damage. Moreover, although placental morphometric analyses and detailed histological assessments of the different placental zones did not reveal significant differences between groups, their inclusion is important. These results indicate that even in the absence of overt placental phenotypic changes, placental function may still be altered, with potential consequences for fetal programming.

      Weaknesses:

      Overall, this manuscript presents a rich and comprehensive dataset; however, this has resulted in the analysis of paternal gut dysbiosis remaining largely descriptive. While still valuable, this raises questions regarding why supplementation with methyl donors was unable to restore gut microbial balance in animals receiving the modified diets.

    1. Reviewer #2 (Public review):

      Summary:

      In this manuscript, Raghavan and his colleagues sought to identify cis-acting elements and/or protein factors that limit meiotic crossover at chromosome ends. This is important for avoiding chromosome rearrangements and preventing chromosome missegregation.

      By reanalyzing published ChIP datasets, the researchers identified a correlation between low levels of protein axis binding - which are known to modulate homologous recombination - and the presence of cis-acting elements such as the subtelomeric element Y' and low gene density. Genetic analyses coupled with ChIP experiments revealed that the differential binding of the Red1 protein in subtelomeric regions requires the methyltransferase Dot1. Interestingly, Red1 depletion in subtelomeric regions does not impact DSB formation. Another surprising finding is that deleting DOT1 has no effect on Red1 loading in the absence of the silencing factor Sir3. Unlike Dot1, Sir3 directly impacts DSB formation, probably by limiting promoter access to Spo11. However, this explains only a small part of the low levels of DSBs forming in subtelomeric regions.

      Strengths:

      (1) This work provides intriguing observations, such as the impact of Dot1 and Sir3 on Red1 loading and the uncoupling of Red1 loading and DSB induction in subtelomeric regions.

      (2) The separation of axis protein deposition and DSB induction observed in the absence of Dot1 is interesting because it rules out the possibility that the binding pattern of these proteins is sufficient to explain the low level of DSB in subtelomeric regions.

      (3) The demonstration that Sir3 suppresses the induction of DSBs by limiting the openness of promoters in subtelomeric regions is convincing.

      Weaknesses:

      (1) The impact of the cis-encoded signal is not demonstrated. Y' containing subtelomeres behave differently from X-only, but this is only correlative. No compelling manipulation has been performed to test the impact of these elements on protein axis recruitment or DSB formation.

      (2) The mechanism by which Dot1 and Sir3 impact Red1 loading is missing.

      (3) Sir3's impact on DSB induction is compelling, yet it only accounts for a small proportion of DSB depletion in subtelomeric regions. Thus, the main mechanisms suppressing crossover close to the ends of chromosomes remain to be deciphered.

    1. Reviewer #2 (Public review):

      Summary:

      Nagao and Mochizuki investigated how the germline (MIC) telomere was removed during programmed genome rearrangement in the developing somatic nucleus (MAC). Using an optimized oligo-FISH procedure, the authors demonstrated that MIC telomeres were co-eliminated with a large region of MIC-limited sequences (MLS) demarcated on the opposite side by a sub-telomeric chromosome breakage site (CBS). This conclusion was corroborated by the latest assembly of the Tetrahymena MIC genome. They further employed CRISPR-Cas9 mutagenesis to disrupt a specific sub-telomeric CBS (4R-CBS). In uniparental progeny (mutant X WT), DNA elimination of the sub-telomeric MLS was not affected, but the adjacent MAC-destined sequence (MDS) may be co-eliminated. However, in biparental progeny (mutant X mutant), global DNA elimination was arrested, revealing previously unrecognized connections between chromosome breakage and DNA elimination. It also paves the way for future studies into the underlying molecular mechanisms. The work is rigorous, well-controlled, and offers important insights into how eukaryotic genomes demarcate genic regions (retained DNA) and regions derived from transposable elements (TE; eliminated DNA) during differentiation. The identification of chromosome breakage sequences as barriers preventing the spread of silencing (and ultimately, DNA elimination) from TE-derived regions into functional somatic genes is a key conceptual contribution.

      Strengths:

      New method development: Oligo-FISH in Tetrahymena. This allows high-resolution visualization of critical genome rearrangement events during MIC-to-MAC differentiation. This method will be a very powerful tool in this area of study.

      Integration of cytological and genomic data. The conclusion is strongly supported by both analyses.

      Rigorous genetic analysis of the role played by 4R-CBS in separating the fate of sub-telomeric MLS (elimination) and MDS (retention). DNA elimination in ciliates has long been regarded as an extreme form of gene silencing. Now, chromosome breakage sequences can be viewed as an extreme form of gene insulators.

      Weaknesses:

      The finding of global disruption of DNA elimination in 4R-CBS mutant progeny is highly intriguing, but it's mostly presented as a hypothesis in the Discussion. The authors propose that the failure to separate MLS from MDS allows aberrant heterochromatin spreading from the former into the latter, potentially silencing genes required for DNA elimination itself. While supported by prior literature on heterochromatin feedback loops, the specific targets silenced are not identified. While results from ChIP-seq and small RNA-seq can greatly strengthen the paper, the reviewer understands that direct molecular characterization may be beyond the scope of the current work.

    1. Reviewer #2 (Public review):

      Summary:

      In this manuscript, Azur et al seek to determine the role of Imp1/Igf2bp1 in regulating the temporal generation of cortical neuron types. The authors showed that overexpression of Imp1 changes the laminar distribution of cortical neurons and suggest that Imp1 plays a temporal role in specifying cell fates.

      Strengths:

      The study uniquely used TEMPO to investigate the temporal effects of Imp1/Igf2bp1 in cortical development. The disrupted laminar distribution and delayed fate transition are interesting. The results are presented with proper quantification, they are generally well interpreted, and suggest important roles for Imp1.

      Weaknesses:

      (1) While the results suggest Imp1 is important in regulating cortical neurogenesis, it remains unclear when and where it is expressed to execute such temporal functions. For instance, where is Imp1 expressed in the developing brain? Is it specific to the radial glial cells or ubiquitous in progenitors and neurons? Does it show temporal expression in RGCs?

      (2) The advantage and interpretation of TEMPO need further clarification. TEMPO is an interesting method and appears useful in simultaneously labelling cells and controlling gene expression. Since the reporter, Cas9, and gRNA triggers are all driven by ubiquitous promoters and integrated into the genome using piggyBac, it appears logical that the color transition should happen in all cells over time. The color code appears to track the time when the plasmids got integrated instead of the birthday of neurons. Is this logically true? If the TEMPO system is introduced into postmitotic neurons and the CAG promoter is not silenced, would the tri-color transition happen?

      (3) The accumulation of neurons at the subplate region would benefit from showing larger views of the affected hemisphere. IUE is invasive. The glass pipette may consistently introduce focal damages and truncate RGCs. It is important to examine slices covering the whole IUE region.

    1. Reviewer #2 (Public review):

      Summary

      Zhou et al. utilize longitudinal, intrathecal contrast-enhanced MRI to investigate a novel physiological pathway: the drainage of cerebrospinal fluid (CSF) into the human skull bone marrow. By mapping tracer enrichment across 87 patients at multiple time points, the authors identify regional variations in drainage speed and link these dynamics to systemic factors like aging, hypertension, and diabetes. Most notably, the study suggests that this drainage function serves as a significant mediator between sleep quality and cognitive performance.

      Strengths

      (1) The study provides a significant transition from murine models to human subjects, showing that CSF-to-marrow communication is a broader phenomenon in clinical cohorts.

      (2) The use of four imaging time points (0h to 39h) allows for a precise characterization of tracer kinetics, revealing that the parietal region near the superior sagittal sinus (SSS) is a rapid exit route.

      (3) The statistical finding that skull bone marrow drainage accounts for approximately 38% of the link between sleep and cognition provides a provocative new target for neurodegenerative research.

      Weaknesses

      (1) Figure 1: The figure relies on a single representative brain to illustrate a process that likely varies significantly across different skull anatomies and disease states. In the provided grayscale MRI scans, the tracer enrichment is essentially imperceptible to the naked eye. Without heatmaps or digital subtraction maps (Post-injection minus Baseline) for the entire cohort, it is difficult to substantiate the quantitative "percentage change" data visually.

      Reliance on a single, manually placed circular Region of Interest (ROI) is susceptible to sampling bias. A more robust approach would involve averaging multiple ROIs per region (multi-sampling) to ensure the signal is representative of the whole marrow compartment.

      (2) Methodological Rigor of Sleep Analysis: The study relies exclusively on the self-reported Pittsburgh Sleep Quality Index (PSQI), which is retrospective and highly prone to recall bias, particularly in a cohort with cognitive impairment. There is no objective verification of sleep (e.g., actigraphy or polysomnography). Since waste clearance is physiologically tied to specific stages, such as Slow-Wave Sleep, subjective scores cannot determine whether drainage is linked to sleep physiology or reflects a higher general disease burden. The MRI captures an acute state during hospitalization, whereas the sleep quality reported covers the month preceding admission. This mismatch complicates the claim that the current drainage function directly reflects historical sleep quality.

      Appraisal and Impact

      The authors demonstrate the feasibility of monitoring CSF-to-skull marrow drainage in humans. However, the strength of the associations with sleep and cognition is currently attenuated by a lack of visual "proof" in the raw data and a reliance on subjective behavioral metrics. If these technical gaps are explicitly addressed through the use of population heatmaps and more rigorous multi-ROI sampling, this work will significantly advance our understanding of the brain's waste-clearance systems and their role in systemic health.

    1. Reviewer #2 (Public review):

      Summary:

      Qiu, Jun et. al., developed and validated a computational pipeline aimed at stabilizing α-helical bundles into very stable folds. The computational pipeline is a hierarchical computational methodology tasked to generate and filter a pool of candidates, ultimately producing a manageable number of high-confidence candidates for experimental evaluation. The pipeline is split into two stages. In stage I, a large pool of candidate designs is generated by RFdiffusion and ProteinMPNN, filtered down by a series of filters (hydropathy score, foldability assessed by ESMFold and AlphaFold). The final set is chosen by running a series of steered MD simulations. This stage reached unfolding forces above 100pN. In stage II, targeted tweaks are introduced - such as salt bridges and metal ion coordination - to further enhance the stability of the α-helical bundle. The constructs undergo validation through a series of biophysical experiments. Thermal stability is assessed by CD, chemical stability by chemical denaturation, and mechanical stability by AFM.

      Strengths:

      A hierarchical computational approach that begins with high-throughput generation of candidates, followed by a series of filters based on specific goal-oriented constraints, is a powerful approach for a rapid exploration of the sequence space. This type of approach breaks down the multi-objective optimization into manageable chunks and has been successfully applied for protein design purposes (e.g., the design of protein binders). Here, the authors nicely demonstrate how this design strategy can be applied to successfully redesign a moderately stable α-helical bundle into an ultrastable fold. This approach is highly modular, allowing the filtering methods to be easily swapped based on the specific optimization goals or the desired level of filtering.

      Weaknesses:

      Assessing the change in stability relative to the WT α-helical bundle is challenging because an additional helix has been introduced, resulting in a comparison between a three-helix bundle and a four-helix bundle. Consequently, the appropriate reference point for comparison is unclear. A more direct and informative approach would have been to redesign the original α-helical bundle of the human spectrin repeat R15, allowing for a more straightforward stability comparison.

      While the authors have shown experimentally that stage II constructs have increased the mechanical stability by AFM, they did not show that these same constructs have increased the thermal and chemical stabilities. Since the effects of salt bridges on stability are highly context dependent (orientation, local environment, exposed vs buried, etc.), it is difficult to assess the magnitude of the effect that this change had on other types of stabilities.

      The three constructs chosen are 60-70% identical to each other, either suggesting overconstrained optimization of the sequence or a physical constraint inherent to designing ultrastable α-helical bundles. It would be interesting to explore these possible design principles further.

      While the use of steered MD is an elegant approach to picking the top N most stable designs, its computational cost may become prohibitive as the number of designs increases or as the protein size grows, especially since it requires simulating a water box that can accommodate a fully denatured protein.

    1. Reviewer #2 (Public review):

      Summary:

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

      Strengths:

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

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

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

      Weaknesses:

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

      (1) I do not understand why SNS-seq would create peaks. Replication should originate in one locus, then move outward in both directions until the replication fork moving outward from another origin is encountered. Hence, in an asynchronous population average measurement, I would expect SNS data to be broad regions of + and -, which, taken together, cover the whole genome. Why are there so many regions not covered at all by reads, and why are there such narrow peaks?

      (2) I am concerned that up to 96% percent of all peaks are filtered away. If there is so much noise in the data, how can one be sure that the peaks that remain are real? Specifically, if the authors placed the same number of peaks as was measured randomly in intergenic regions, would 4% of these peaks pass the filtering process by chance?

      (3) There are 3 previous studies that map origins of replication in T. brucei. Devlin et al. 2016, Tiengwe et al. 2012, and Krasiļņikova et al. 2025 (https://doi.org/10.1038/s41467-025-56087-3), all with a different technique: MFA-seq. All three previous studies mostly agree on the locations and number of origins. The authors compared their results to the first two, but not the last study; they found that their results are vastly different from the previous studies (see Supplementary Figure 8A). In their discussion, the authors defend this discrepancy mostly by stating that the discrepancy between these methods has been observed in other organisms. I believe that, given the situation that the other studies precede this manuscript, it is the authors' duty to investigate the differences more than by merely pointing to other organisms. A conclusion should be reached on why the results are different, e.g., by orthogonally validating origins absent in the previous studies.

      (4) Some patterns that were identified to be associated with origins of replication, such as G-quadruplexes and nucleosomes phasing, are known to be biases of SNS-seq (see Foulk et al. Characterizing and controlling intrinsic biases of lambda exonuclease in nascent strand sequencing reveals phasing between nucleosomes and G-quadruplex motifs around a subset of human replication origins. Genome Res. 2015;25(5):725-735. doi:10.1101/gr.183848.114).

      Are the claims well substantiated?:

      My opinion on whether the authors' results support their conclusions depends on whether my concerns about the sites determined from the SNS-seq data can be dismissed. In the case that these concerns can be dismissed, I do think that the claims are compelling.

      Impact:

      If the origins of replication prove to be distributed as claimed, this study has the potential to be important for two fields. Firstly, in research focused on T. brucei as a disease agent, where essential processes that function differently than in mammals are excellent drug targets. Secondly, this study would impact basic research analyzing DNA replication over the evolutionary tree, where T. brucei can be used as an early-divergent eukaryotic model organism.

    1. Reviewer #3 (Public review):

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

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

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

      Strengths

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

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

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

      Weaknesses

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

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

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

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

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

      In summary I agree that any model that fits the data would have to capture the idea that participants don't differentiate between the different environments as much as they should, but I think there are a number of qualitatively different reasons why they might do this - of which the above are only examples - hence I find it problematic that the authors present the behaviour as evidence for one extremely specific model.

      (3) Despite efforts to control confounds in the fMRI study, including two control experiments, I think some confounds remain.

      For example, a network of regions is presented as correlating with the cumulative probability that there has been a regime shift in this block of 10 samples (Pt). However, regardless of the exact samples shown, Pt always increases with sample number (as by the time of later samples, there have been more opportunities for a regime shift)? To control for this the authors include, in a supplementary analysis, an 'intertemporal prior.' I would have preferred to see the results of this better-controlled analysis presented in the main figure. From the tables in the SI it is very difficult to tell how the results change with the includion of the control regressors.

      On the other hand, two additional fMRI experiments are done as control experiments and the effect of Pt in the main study is compared to Pt in these control experiments. Whilst I admire the effort in carrying out control studies, I can't understand how these particular experiment are useful controls. For example, in experiment 3 participants simply type in numbers presented on the screen - how can we even have an estimate of Pt from this task?

      (4) The Discussion is very long, and whilst a lot of related literature is cited, I found it hard to pin down within the discussion, what the key contributions of this study are. In my opinion it would be better to have a short but incisive discussion highlighting the advances in understanding that arise from the current study, rather than reviewing the field so broadly.

    1. Reviewer #2 (Public review):

      The article is very well written, and the new methodology is presented with care. I particularly appreciated the step-by-step rationale for establishing the approach, such as the relationship between K-means centers and the various parameters. This text is conveniently supported by the flow charts and t-SNE plots. Importantly, I thought the choice of state-of-the-art method was appropriate and the choice of dataset adequate, which together convinced me in believing the large improvement reported. I thought that the crossmodal feature-engineering solution proposed was elegant and seems exportable to other fields. Here are a few notes.<br /> While the validation data set was well chosen and of high quality, it remains a single dataset and also remains a non-recurrent network. The authors acknowledge this in the discussion, but I wanted to chime in to say that for the method to be more than convincing, it would need to have been tested on more datasets. It should be acknowledged that the problem becomes more complicated in a recurrent excitatory network, and thus the method may not work as well in the cortex or in CA3.

      While the data is shown to work in this particular dataset (plus the two others at the end), I was left wondering when the method breaks. And it should break if the models are sufficiently mismatched. Such a question can be addressed using synthetic-synthetic models. This was an important intuition that I was missing, and an important check on the general nature of the method that I was missing.

      While the choice of state-of-the-art is good in my opinion, I was looking for comments on the methods prior to that. For instance, methods such based on GLMs have been used by the Pillow, Paninski, and Truccolo groups. I could not find a decent discussion of these methods in the main text and thought that both their acknowledgement and rationale for dismissing were missing.

      While most of the text was very clear, I thought that page 11 was odd and missing much in terms of introductions. Foremost is the introduction of the dataset, which is never really done. Page 11 refers to 'this dataset', while the previous sentence was saying that having such a dataset would be important and is challenging. The dataset needs to be properly described: what's the method for labeling, what's the brain area, what were the spike recording methodologies, what is meant by two labeling methodologies, what do we know about the idiosyncrasies of the particular network the recording came from (like CA1 is non-recurrent, so which connections)? I was surprised to see 'English et al.' cited in text only on page 13 since their data has been hailed from the beginning.

      Further elements that needed definition are the Nsyn and i, which were not defined in the cortex of Equation 2-3: I was not sure if it referred to different samples or different variants of the synthetic model. I also would have preferred having the function f defined earlier, as it is defined for Equation 3, but appears in Equation 2.

      When the loss functions are described, it would be important to define 'data' and 'labels' here. This machine learning jargon has a concrete interpretation in this context, and making this concrete would be very important for the readership.

      While I appreciated that there was a section on robustness, I did not find that the features studied were the most important. In this context, I was surprised that the other datasets were relegated to supplementary, as these appeared more relevant.

      Some of the figures have text that is too small. In particular, Figure 2 has text that is way too small. It seemed to me that the pseudo code could stand alone, and the screenshot of the equations did not need to be repeated in a figure, especially if their size becomes so small that we can't even read them.

    1. Reviewer #2 (Public review):

      This paper introduces "DrosoMating," an integrated hardware and software solution for automating the analysis of male Drosophila courtship. The authors aim to provide a low-cost, accessible alternative to expensive ethological rigs by utilizing a custom acrylic chamber and smartphone-based recording. The system focuses on quantifying key temporal metrics-Courtship Index (CI), Copulation Latency (CL), and Mating Duration (MD)-and is applied to behavioral paradigms involving memory mutants (orb2, rut).

      The development of open-source behavioral tools is a significant contribution to neuroethology, and the authors successfully demonstrate a system that simplifies the setup for large-scale screens. A major strength of the work is the specific focus on automating Copulation Latency and Mating Duration, metrics that are often labor-intensive to score manually.

      However, there are several limitations in the current analysis and validation that affect the strength of the conclusions:

      First, the statistical rigor requires substantial improvement. The analysis of multi-group experiments (e.g., comparing four distinct strains or factorial designs with genotype and training) currently relies on multiple independent Student's t-tests. This approach is statistically invalid for these experimental designs as it inflates the family-wise Type I error rate. To support the claims of strain-specific differences or learning deficits, the data must be analyzed using Analysis of Variance (ANOVA) to properly account for multiple comparisons and to explicitly test for interaction effects between genotype and training conditions.

      Second, the biological validation using w1118 and y1 mutants entails a potential confound. The authors attribute the low Courtship Index in these strains to courtship-specific deficits. However, both strains are known to exhibit general locomotor sluggishness (due to visual or pigmentation/behavioral defects). Since "following" behavior is likely a component of the Courtship Index, a reduction in this metric could reflect a general motor deficit rather than a specific lack of reproductive motivation. Without controlling for general locomotion, the interpretation of these behavioral phenotypes remains ambiguous.

      Third, the benchmarking of the system is currently limited to comparisons against manual scoring. Given that the field has largely adopted sophisticated open-source tracking tools (e.g., Ctrax, FlyTracker, JAABA), the utility of DrosoMating would be better contextualized by comparing its performance - in terms of accuracy, speed, or identity maintenance - against these existing automated standards, rather than solely against human observation.

      Finally, the visual presentation of the data hinders the assessment of the system's temporal precision. While the system is designed to capture time-resolved metrics, the results are presented primarily as aggregate bar plots. The absence of behavioral ethograms or raster plots makes it difficult to verify the software's ability to accurately detect specific transitions, such as the exact onset of copulation.

    1. Reviewer #2 (Public review):

      Summary:

      The manuscript by Chen et al addresses an important aspect of pathogenesis for mycobacterial pathogens, seeking to understand how bacterial effector proteins disrupt the host immune response. To address this question the authors sought to identify bacterial effectors from M. tuberculosis (Mtb) that localize to the host nucleus and disrupt host gene expression as a means of impairing host immune function. Their revised manuscript has strengthened their observations by performing additional experiments with BCG strains expressing tagged MgdE.

      Strengths:

      The researchers conducted a rigorous bioinformatic analysis to identify secreted effectors containing mammalian nuclear localization signal (NLS) sequences, which formed the basis of quantitative microscopy analysis to identify bacterial proteins that had nuclear targeting within human cells. The study used two complementary methods to detect protein-protein interaction: yeast two-hybrid assays and reciprocal immunoprecipitation (IP). The combined use of these techniques provides strong evidence of interactions between MgdE and SET1 components and suggests the interactions are in fact direct. The authors also carried out rigorous analysis of changes in gene expression in macrophages infected with MgdE mutant BCG. They found strong and consistent effects on key cytokines such as IL6 and CSF1/2, suggesting that nuclear-localized MgdE does in fact alter gene expression during infection of macrophages. The revised manuscript contains additional biochemical analyses of BCG strains expressing tagged MgdE that further supports their microscopy findings.

      Weaknesses:

      There are some drawbacks in this study that limit the application of the findings to M. tuberculosis (Mtb) pathogenesis. Much of the study relies on transfected/ overexpressed proteins in non-immune cells (HEK293T) or in yeast using 2-hybrid approaches, and pathogenesis is studied using the BCG vaccine strain rather than virulent Mtb. In addition, the magnitude of some of the changes they observe are quite small. However, overall the key findings of the paper - that MgdE interacts with COMPASS and alters gene expression are well-supported.

      Comments on revisions:

      The authors have performed additional experiments that have addressed several important concerns from the original manuscript and they now include an analysis of BCG strains expressing FLAG-tagged MgdE that supports their model. However here are still a few areas where the data are difficult to interpret or do not support their claims.

    1. Reviewer #2 (Public review):

      Summary:

      AutoMorphoTrack provides an end-to-end workflow for organelle-scale analysis of multichannel live-cell fluorescence microscopy image stacks. The pipeline includes organelle detection/segmentation, extraction of morphological descriptors (e.g., area, eccentricity, "circularity," solidity, aspect ratio), tracking and motility summaries (implemented via nearest-neighbor matching using cKDTree), and pixel-level overlap/colocalization metrics between two channels. The manuscript emphasizes a specific application to live imaging in neurons, demonstrated on iPSC-derived dopaminergic neuronal cultures with mitochondria in channel 0 and lysosomes in channel 1, while asserting adaptability to other organelle pairs.

      The tool is positioned for cell biologists, including users with limited programming experience, primarily through two implemented modes of use: (i) a step-by-step Jupyter notebook and (ii) a modular Python package for scripted or batch execution, alongside an additional "AI-assisted" mode that is described as enabling analyses through natural-language prompts.

      The motivation and general workflow packaging are clear, and the notebook-plus-modules structure is a reasonable engineering choice. However, in its current form, the manuscript reads more like a convenient assembly of standard methods than a validated analytical tool. Key claims about robustness, accuracy, and scope are not supported by quantitative evidence, and the 'AI-assisted' framing is insufficiently defined and attributes to the tool capabilities that are provided by external LLM platforms rather than by AutoMorphoTrack itself. In addition, several figure, metric, and statistical issues-including physically invalid plots and inconsistent metric definitions-directly undermine trust in the quantitative outputs.

      Strengths:

      (1) Clear motivation: lowering the barrier for organelle-scale quantification for users who do not routinely write custom analysis code.

      (2) Multiple entry points: an interactive notebook together with importable modules, emphasizing editable parameters rather than a fully opaque black box.

      (3) End-to-end outputs: automated generation of standardized visualizations and tables that, if trustworthy, could help users obtain quantitative summaries without assembling multiple tools.

      Weaknesses:

      (1) "AI-assisted / natural-language" functionality is overstated.

      The manuscript implies an integrated natural-language interface, but no such interface is implemented in the software. Instead, users are encouraged to use external chatbots to help generate or modify Python code or execute notebook steps. This distinction is not made clearly and risks misleading readers.

      (2) No quantitative validation against trusted ground truth.

      There is no systematic evaluation of segmentation accuracy, tracking fidelity, or interaction/overlap metrics against expert annotations or controlled synthetic data. Without such validation, accuracy, parameter sensitivity, and failure modes cannot be assessed.

      (3) Limited benchmarking and positioning relative to existing tools.

      The manuscript does not adequately compare AutoMorphoTrack to established platforms that already support segmentation, morphometrics, tracking, and colocalization (e.g., CellProfiler) or to mitochondria-focused toolboxes (e.g., MiNA, MitoGraph, Mitochondria Analyzer). This is particularly problematic given the manuscript's implicit novelty claims.

      (4) Core algorithmic components are basic and likely sensitive to imaging conditions.

      Heavy reliance on thresholding and morphological operations raises concerns about robustness across varying SNR, background heterogeneity, bleaching, and organelle density; these issues are not explored.

      (5) Multiple figure, metric, and statistical issues undermine confidence.

      The most concerning include:<br /> (i) "Circularity (4πA/P²)" values far greater than 1 (Figures 2 and 7, and supplementary figures), which is inconsistent with the stated definition and strongly suggests a metric/label mismatch or computational error.

      (ii) A displacement distribution extending to negative values (Figure 3B). This is likely a plotting artifact (e.g., KDE boundary bias), but as shown, it is physically invalid and undermines confidence in the motility analysis.

      (iii) Colocalization/overlap metrics that are inconsistently defined and named, with axis ranges and terminology that can mislead (e.g., Pearson r reported for binary masks without clarification).

      (iv) Figure legends that do not match the displayed panels, and insufficient reporting of Ns, p-values, sampling units, and statistical assumptions.

    1. Reviewer #2 (Public review):

      The application of rabies virus (RabV)-mediated transsynaptic tracing has been widely utilized for mapping cell-type-specific neural connectivities and examining potential modifications in response to biological phenomena or pharmacological interventions. Despite the predominant focus of studies on quantifying and analyzing labeling patterns within individual brain regions based on labeling abundance, such an approach may inadvertently overlook systemic alterations. There exists a considerable opportunity to integrate RabV tracing data with the global connectivity patterns and the transcriptomic signatures of labeled brain regions. In the present study, the authors take an important step towards achieving these objectives.

      Specifically, the authors conducted an intensive reanalysis of a previously generated large dataset of RabV tracing to the ventral tegmental area (VTA) using dimension reduction methods such as PCA and UMPA. This reaffirmed the authors's earlier conclusion that different cell types in the VTA, namely dopamine neurons (DA) and GABAergic neurons, exhibit quantitatively distinct input patterns, and a single dose of addictive drugs, such as cocaine and morphine, induced altered labeling patterns. Additionally, the authors illustrate that distinct axes of PCA can discriminate experimental variations, such as minor differences in the injection site of viral tracers, from bona fide alterations in labeling patterns caused by drugs of abuse. While the specific mechanisms underlying altered labeling in most brain regions remain unclear, whether involving synaptic strength, synaptic numbers, pre-synaptic activities, or other factors, the present study underscores the efficacy of an informatics approach in extracting more comprehensive information from the RabV-based circuit mapping data.

      Moreover, the authors showcased the utility of their previously devised bulk gene expression patterns inferred by the Allen Gene Expression Atlas (AGEA) and "projection portrait" derived from bulk axon mapping data sourced from the Allen Mouse Brain Connectivity Atlas. The utilization of such bulk data rests upon several limitations. For instance, the collection of axon mapping data involves an arbitrary selection of both cell type-specific and non-specific data, which might overlook crucial presynaptic partners, and often includes contamination from neighboring undesired brain regions. Concerns arise regarding the quantitativeness of AGEA, which may also include the potential oversight of key presynaptic partners. Nevertheless, the authors conscientiously acknowledged these potential limitations associated with the dataset.

      Notably, building on the observation of a positive correlation between the basal expression levels of Ca2+ channels and the extent of drug-induced changes in RabV labeling patterns, the authors conducted a CRISPRi-based knockdown of a single Ca2+ channel gene. This intervention resulted in a reduction of RabV labeling, supporting that the observed gene expression patterns have causality in RabV labeling efficiency. While a more nuanced discussion is necessary for interpreting this result (see below), overall I commend the authors for their efforts to leverage the existing dataset in a more meaningful way. This endeavor has the potential to contribute significantly to our understanding of the mechanisms underlying alterations in RabV labeling induced by drugs of abuse.

      Finally, drawing upon the aforementioned reanalysis of previous data, the authors underscored that a single administration of ketamine/xylazine anesthesia could induce enduring modifications in RabV labeling patterns for VTA DA neurons, specifically those projecting to the nucleus accumbens and amygdala. Given the potential impact of such alterations on motivational behaviors at a broader level, I fully agree that prudent consideration is warranted when employing ketamine/xylazine for the investigation of motivational behaviors in mice.

      Comments on revisions:

      In the re-revised version, the authors have addressed all of my previous comments. I no longer have any major concerns.

    1. Reviewer #2 (Public review):

      Summary:

      Essoh and colleagues present a thorough and elegant study identifying the central amygdala and BNST as key sources of CRF input to the dorsal striatum. Using monosynaptic rabies tracing and electrophysiology, they show direct connections to cholinergic interneurons. The study builds on previous findings that CRF increases CIN firing, extending them by measuring acetylcholine levels in slices and applying optogenetic stimulation of CRF+ fibers. It also uncovers a novel interaction between alcohol and CRF signaling in the striatum, likely to spark significant interest and future research.

      Strengths:

      A key strength is the integration of anatomical and functional approaches to demonstrate these projections and assess their impact on target cells, striatal cholinergic interneurons.

      Comments on revisions:

      No further concerns or recommendations.

    1. Reviewer #2 (Public review):

      Summary:

      The authors investigate how dominance hierarchy shapes defensive strategies in mice under two naturalistic threats: a transient visual looming stimulus and a sustained live rat. By comparing single versus paired testing, they report that social presence attenuates fear and that dominant and subordinate mice exhibit different patterns of defensive and social behaviors depending on threat type. The work provides a rich behavioral dataset and a potentially useful framework for studying hierarchical modulation of innate fear.

      Strengths:

      (1) The study uses two ecologically meaningful threat paradigms, allowing comparison across transient and sustained threat contexts.

      (2) Behavioral quantification is detailed, with manual annotation of multiple behavior types and transition-matrix level analysis.

      (3) The comparison of dominant versus subordinate pairs is novel in the context of innate fear.

      (4) The manuscript is well-organized and clearly written.

      (5) Figures are visually informative and support major claims.

      Weaknesses:

      Lack of neural mechanism insights.

    1. Reviewer #2 (Public review):

      Summary:

      Tan et al. examined how multivoxel patterns shift in time windows surrounding event boundaries caused by both prediction errors and prediction uncertainty. They observed that some regions of the brain show earlier pattern shifts than others, followed by periods of increased stability. The authors combine their recent computational model to estimate event boundaries that are based on prediction error vs. uncertainty and use this to examine the moment-to-moment dynamics of pattern changes. I believe this is a meaningful contribution that will be of interest to memory, attention, and complex cognition research.

      Strengths:

      The authors have shown exceptional transparency in terms of sharing their data, code, and stimuli which is beneficial to the field for future examinations and to the reproduction of findings. The manuscript is well written with clear figures. The study starts from a strong theoretical background to understand how the brain represents events and have used a well-curated set of stimuli. Overall, the authors extend the event segmentation theory beyond prediction error to include prediction uncertainty which is an important theoretical shift that has implications in episodic memory encoding, use of semantic and schematic knowledge and to attentional processing.

      Weaknesses:

      (1) I am not fully satisfied with the author's explanation of pattern shifts occurring 11.9s prior to event boundaries. The average length of time for an event was 21.4 seconds. The window around the identified event boundaries was 20 seconds on either side. The earliest identified pattern shift peaks occur at 11.9s prior to the actual event boundary. This would mean on average, a pattern shift is occurring approximately at the midway point of the event (11.9s prior to a boundary of a 21.4s event is approx. the middle of an event). The authors offer up an explanation in which top down regions signal an update that propagates to lower order regions closer to the boundary. To make this interpretation concrete, they added an example: "in a narrative where a goal is reached midway-for instance, a mystery solved before the story formally ends-higher-order regions may update the event representation at that point, and this updated model then cascades down to shape processing in lower-level regions". This might make sense in a one-off case of irregular storytelling, but it is odd to think this would generalize. If an event is occurring and a given collection of regions represent that event, it doesn't follow the accepted convention of multivariate representational analysis that that set of regions would undergo such a large shift in patterns in the middle of an event. The stabilization of these patterns taking so long is also odd to me. I suspect some of these findings may be due to the stimuli used in this experiment and I am not confident this would generalize and invite the authors to disagree and explain. In the case of the exercise routine video, I try to imagine going from the push-up event to the jumping jack event. The actor stops doing pushups, stands up, and moves minimally for 16 seconds (these lulls are not uncommon). At that point they start doing jumping jacks. It is immediately evident from that moment on that jumping jacks will be the kind of event you are perceiving which may explain the long delay in event pattern stabilisation. Then about 11.9s prior to the end of the event, when the person is still performing jumping jacks (at this point they have been performing jumping jacks for 6 seconds), I would expect the brain to still be expecting this " jumping jacks event". For some reason at this point multivariate patterns in higher order regions shift. I do not understand what kind of top down processing is happening here and the reviewers need to be more concrete in their explanation because as of right now it is ill-defined. I also recognize that being specific to jumping jacks is maybe unfair, but this would apply to the push-ups, granola bar eating, or table cleaning events in the same manner. I suspect one possibility is that the participants realize that the stereotyped action of jumping jacks is going to continue and, thus, mindwander to other thoughts while waiting for novel, informative information to be presented. This explanation would challenge the more active top down processing assumed by the authors.

      I had provided a set of concerns to the authors that were not part of the public review and were not addressed. I was unaware of the exact format of the eLife approach, but I think they are worth open discussion so I am adding them here for consideration. Apologies for any confusion.

      (2) Why did the authors not examine event boundary activity magnitude differences from the uncertainty vs error boundaries? I see that the authors have provided the data on the openneuro. However, it seems like the difference in activity maps would not only provide extra contextualization of the findings, but also be fairly trivial. Just by eye-balling the plots, it appears as though there may be activity differences in the mPFC occurring shortly after a boundary between the two. Given this regions role in prediction error and schema, it would be important to understand whether this difference is merely due to thresholding effects or is statistically meaningful.

      (3) Further, the authors omitted all subcortical regions some of which would be especially interesting such as the hippocampus, basal ganglia, ventral tegmental area. These regions have a rich and deep background in event boundary activity, and prediction error. Univariate effects in these regions may provide interesting effects that might contextualize some of the pattern shifts in the cortex.

      (3) I see that field maps were collected, but the fmriprep methods state that susceptibility distortion correction was not performed. Is there a reason to omit this?

      (4) How many events were present in the stimuli?

    1. Reviewer #2 (Public review):

      This study uses monkey single-unit recordings to examine the role of the STN in combining noisy sensory information with reward bias during decision-making between saccade directions. Using multiple linear regressions and k-means clustering approaches, the authors overall show that a highly heterogeneous activity in the STN reflects almost all aspects of the task, including choice direction, stimulus coherence, reward context and expectation, choice evaluation, and their interactions. The authors report in particular how, here too, in a very heterogeneous way, four classes of neurons map to different decision processes evaluated via the fitting of a drift-diffusion model. Overall, the study provides evidence for functionally diverse populations of STN neurons, supporting multiple roles in perceptual and reward-based decision-making.

      This study follows up on work conducted in previous years by the same team and complements it. Extracellular recordings in monkeys trained to perform a complex decision-making task remain a remarkable achievement, particularly in brain structures that are difficult to target, such as the subthalamic nucleus. The authors conducted numerous rigorous and systematic analyses of STN activities, using sophisticated statistical approaches and functional computational modeling.

      One criticism I would make is that the authors sometimes seem to assume that readers are familiar with their previous work. Indeed, the motivation and choices behind some analyses are not clearly explained. It might be interesting to provide a little more context and insight into these methodological choices. The same is true for the description of certain results, such as the behavioral results, which I find insufficiently detailed, especially since the two animals do not perform exactly the same way in the task.

      Another criticism is the difficulty in following and absorbing all the presented results, given their heterogeneity. This heterogeneity stems from analytical choices that include defining multiple time windows over which activities are studied, multiple task-related or monkey behavioral factors that can influence them, multiple parameters underlying the decision-making phenomena to be captured, and all this without any a priori hypotheses. The overall impression is of an exploratory description that is sometimes difficult to digest, from which it is hard to extract precise information beyond the very general message that multiple subpopulations of neurons exist and therefore that the STN is probably involved in multiple roles during decision-making.

      It would also have been interesting to have information regarding the location of the different identified subpopulations of neurons in the STN and their level of segregation within this nucleus. Indeed, since the STN is one of the preferred targets of electrical stimulation aimed at improving the condition of patients suffering from various neurological disorders, it would be interesting to know whether a particular stimulation location could preferentially affect a specific subpopulation of neurons, with the associated specific behavioral consequences.

      Therefore, this paper is interesting because it complements other work from the same team and other studies that demonstrate the likely important role of the STN in decision-making. This will be of interest to the decision-making neuroscience community, but it may leave a sense of incompleteness due to the difficulty in connecting the conclusions of these different studies. For example, in the discussion section, the authors attempt to relate the different neuronal populations identified in their study and describe some relatively consistent results, but others less so.

    1. Reviewer #2 (Public review):

      Summary:

      This study, conducted by Esmaeili and colleagues, investigates the functional connectivity signatures of different auditory, visual, and motor states in 42 ECoG patients. Patients performed three tasks: picture naming, visual word reading, and auditory word repetition. They use an SVM classifier on correlation patterns across electrodes during these tasks, separating speech production from sensory perception, and incorporating baseline silence as another state. They find that it is possible to classify five states (auditory perception, picture viewing, word reading, speech production, and baseline) based on their connectivity patterns alone. Furthermore, they find a sparser set of "discriminative connections" for each state that can be used to predict each of these states. They then relate these connectivity matrices to high-gamma evoked data, and show largely overlapping relationships between the discriminative connections and the active high-gamma electrodes. However, there are still some connectivity nodes that are important in discriminating states, but that do not show high evoked activity, and vice versa. Overall, the study has a large number of patients, and the ability to decode cognitive state is compelling. The main weaknesses of the work are in placing the findings into a wider context for what additional information the connectivity analysis provides about brain processing of speech, since, as it stands, the analysis mostly reidentifies areas already known to be important for speaking, listening, naming, and visual processing.

      Strengths:

      (1) The authors were able to assess their connectivity analysis on a large cohort of patients with wide coverage across speech and language areas.

      (2) The use of controlled tasks for picture naming, visual word reading, and auditory word repetition allows for parcellating specific components of stimulus perception and speech production.

      (3) The authors chose not to restrict their connectivity analysis to previously identified high amplitude responses, which allowed them to find regions that are discriminative between different states in their speech tasks, but not necessarily highly active.

      Weaknesses:

      (1) Although the work identifies some clear connectivity between brain areas during speech perception and production, it is not clear whether this approach allows us to learn anything new about brain systems for speech. The areas that are identified have been shown in other studies and are largely unsurprising - the auditory cortex is involved in hearing words, picture naming involves frontal and visual cortical interactions, and overt movements include the speech motor cortex. The temporal pole is a new area that shows up, but (see below) it is important to show that this region is not affected by artifacts. Overall, it would help if the authors could expand upon the novelty of their approach.

      (2) Because the connectivity is derived from single trials, it is possible that some of the sparse connectivity seen in noncanonical areas is due to a common artifact across channels. The authors do employ a common average reference, which should help to reduce common-mode noise across all channels, but not smaller subsets. Could the authors include more information to show that this is not the case in their dataset? For example, the temporal pole electrodes show strong functional connectivity, but these areas can tend to include more EMG artifact or ocular artifact. Showing single-trial traces for some of these example pairs of electrodes and their FC measures could help in interpreting how robust the findings are.

      (3) The connectivity matrices are defined by taking the correlation between all pairs of electrodes across 500-ms epochs for each cognitive state, presumably for electrodes that are time-aligned. However, it is likely that different areas will interact with different time delays - for example, activity in one area may lead to activity in another. It might be helpful to include some time lags between different brain areas if the authors are interested in dynamics between areas that are not simultaneous.

      (4) In Figure 3, the baseline is most commonly confused with other categories (most notably, speech production, 22% of the time). Is there any intuition for why this might be? Could some of this confusion be due to task-irrelevant speech occurring during the baseline / have the authors verified that all pre-stimulus time periods were indeed silent?

      (5) How similar are discriminative connections across participants? Do they tend to reflect the same sparse anatomical connections? It is not clear how similar the results are across participants.

      (6) The results in Figure 5F are interesting and show that frontal electrodes are often highly functionally connected, but have low evoked activity. What do the authors believe this might reflect? What are these low-evoked activity electrodes potentially doing? Some (even speculative) mention might be helpful.

      (7) One comparison that seems to be missing, if the authors would like to claim the utility of functional connectivity over evoked measures, is to directly compare a classifier based on the high gamma activity patterns alone, rather than the pairwise connectivity. Does the FC metric outperform simply using evoked activity?

    1. Reviewer #2 (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.

      Weaknesses:

      The study is conducted exclusively using Escherichia coli. While E. coli is a standard model organism, the paper claims to evaluate luminescence as a generalizable high-throughput tool. Many of the discrepancies observed are driven by filamentation. However, distinct morphological responses occur in other critical pathogens (e.g., Staphylococcus aureus does not filament in the same way).

      The authors propose that luminescence data can be corrected using microscopy-derived volume data to better align with CFU counts. The primary appeal of luminescence is high-throughput efficiency. If a researcher must perform time-lapse microscopy to calculate cell volume changes to "correct" their luminescence data, the high-throughput advantage is lost.

      The paper argues that for ciprofloxacin, CFU underestimates viability because cells remain intact and impermeable to propidium iodide. While the cells are metabolically active and membrane-intact, if they cannot divide to form a colony (even after drug removal/dilution), their clinical relevance as "living" pathogens is debatable.

      Some other comments:

      The use of a population dynamical model to simulate filamentation effects is excellent. The finding that light intensity tracks volume ($\psi_V$) better than cell number ($\psi_B$) is a key theoretical contribution.

      The model assumes linear elongation. The authors should briefly comment on whether this holds true for the specific drug mechanisms tested (e.g., PBP inhibition vs. DNA gyrase inhibition).

      The use of bootstrapping to estimate rate distributions is appropriate and robust.

      Conclusion:

      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.

    1. Reviewer #2 (Public review):

      Summary:

      Neurons adapt to prolonged or repeated sensory inputs. One function of such adaptation may be to save resources to avoid representing the same inputs over and over again. However, it has been hypothesized that adaptation could additionally help improve the representation of sensory stimuli, especially during difficult recognition scenarios. This study sheds light on this question and provides behavioral evidence for such enhancement. The behavioral results are interesting and compelling. The paper also includes scalp electroencephalographic (EEG) data, which are noisy but point toward similar conclusions. The authors finally implement a deep convolutional neural network (DCNN) with adaptation mechanisms, which nicely capture human behavior.

      Strengths:

      (1) The authors introduce an interesting hypothesis about the role of adaptation in visual recognition.

      (2) The authors present interesting and compelling behavioral data consistent with the hypothesis.

      (3) The authors introduce a computational model that can capture mechanisms that can lead to adaptation, enhancing visual recognition.

      Weaknesses:

      (1) The main weakness is the scalp EEG data. As detailed below, the results are minimal at best and do not contribute to understanding the mechanisms of adaptation. The paper would be stronger without the EEG data.

      (2) I wonder whether the hypothesis also holds with real-world objects in natural scenes, beyond the confines of MNIST digits.

    1. Reviewer #2 (Public review):

      Summary:

      This work presents a reproducible, scalable workflow for spike sorting that leverages parallelization to handle large neural recording datasets. The authors introduce both a processing pipeline and a benchmarking framework that can run across different computing environments (workstations, HPC clusters, cloud). Key findings include demonstrating that Kilosort4 outperforms Kilosort2.5 and that 7× lossy compression has minimal impact on spike sorting performance while substantially reducing storage costs.

      Strengths:

      (1) Extremely high-quality figures with clear captions that effectively communicate complex workflow information.

      (2) Very detailed, well-written methods section providing thorough documentation.

      (3) Strong focus on reproducibility, scalability, modularity, and portability using established technologies (Nextflow, SpikeInterface, Code Ocean).

      (4) Pipeline publicly available on GitHub with documentation.

      (5) Clear cost analysis showing ~$5/hour for AWS processing with transparent breakdown.

      (6) Good overview of previous spike sorting benchmarking attempts in the introduction.

      (7) Practical value for the community by lowering barriers to processing large datasets.

      Weaknesses:

      No significant weaknesses were identified, although it is noted that the limitations section of the discussion could be expanded.

    1. Reviewer #2 (Public review):

      This manuscript presents an impressive and novel investigation of organizational principles governing brain activity at both global and local scales during naturalistic viewing paradigms. The proposed multi-scale nested structure offers valuable new insights into functional brain states and their dynamics. Importantly, investigation of global brain states in the context of a naturalistic viewing context represents an important and timely contribution that addresses unresolved issues about global signals and anticorrelations in resting-state fMRI. This manuscript presents a novel investigation of organizational principles governing brain activity at both global and local scales during naturalistic viewing paradigms. The authors demonstrate that brain activity during naturalistic viewing is dominated by two anti-correlated states that toggle between each other with a third transitional state mediating between them. The successful replication across three independent datasets (StudyForrest, NarrattenTion, and CamCAN) is a particular strength. The successful replication across three independent datasets (StudyForrest, NarrattenTion, and CamCAN) is a particular strength, and I appreciate the authors' careful documentation of both convergent and divergent findings across these samples.

      Overall, this manuscript makes important contributions to our understanding of large-scale brain organization during naturalistic cognition. The multi-scale framework and robust replication across datasets are notable strengths. Addressing the concerns raised below will substantially strengthen the impact and interpretability of this work.

      (1) Network Definition and Specificity

      (a) The authors adopt an overly broad characterization of the Default Mode Network (DMN). The statement that "areas most active in the default mode state... consist of the precuneus, angular gyrus, large parts of the superior and middle temporal cortex, large parts of the somatomotor areas, frontal operculi, insula, parts of the prefrontal cortex and limbic areas" includes regions typically assigned to other networks. The insula is canonically considered a core node of the Salience Network/Ventral Attention Network (VAN), not the DMN. Also, not clear which limbic areas? The DMN findings reported need to be critically reassessed in this context.

      (b) Given the proposed role of state switching in your framework, a detailed analysis of salience network nodes (particularly insula and dorsal ACC) would be highly informative.

      (c) While you report transition-related signals in the visual and auditory cortex, the involvement of insular and frontal control systems in state transitions remains unaddressed.

      (d) My recommendation is to provide a more anatomically precise characterization of network involvement, particularly distinguishing DMN from salience/VAN regions, and analyze the specific role of salience network nodes in mediating state transitions.

      (2) Distinguishing Top-Down from Stimulus-Driven Effects

      (a) The finding that "the superior parietal lobe (SPL) and the frontal eye fields (FEF) show the greatest overlap between their local ROI state switches and the global state switches" raises an important question: To what extent are these effects driven by overt changes in visual gaze or attention shifts triggered by stimulus features versus internally-generated state changes?

      (b) Similarly, the observation that DAN areas show the highest overlap with global state changes in StudyForrest and NarrattenTion, while VAN shows the highest overlap in CamCAN, lacks sufficient anatomical detail regarding which specific nodes are involved. This information would help clarify whether insular regions and other VAN components play distinct roles in state switching.

      (c) It will be important to (i) discuss potential confounds from eye movements and stimulus-driven attention shifts; (ii) provide detailed anatomical breakdowns of network nodes involved in state transitions, particularly for VAN; (iii) if eye-tracking data or any other relevant stimulus-related data are available, include analyses examining relationships between these measures and state transitions.

      (3) Physiological Interpretation of the "Down" State

      The linkage between the "Down" state and the Default Mode State (DMS) is intriguing but requires deeper physiological grounding. Recent work by Epp et al. (Nature Neuroscience, 2025) demonstrates that decreased BOLD signal in DMN regions does not necessarily indicate reduced metabolic activity and can reflect neurovascular coupling modes with specific metabolic profiles. It would be useful to discuss whether your "Down" state might represent a particular neurovascular coupling mode with distinct metabolic demands rather than simply reduced neural activity. Alternatively, your analytical approach might be insensitive to or unconfounded by such neurovascular uncoupling. This discussion would substantially enrich the biological interpretation of the DMS versus TPS dual mechanism framework.

      (4) Statistical Validation of Bimodality Detection

      The method of selecting bimodal timepoints using the Dip test followed by sign-alignment is novel and creative. However, this filter-then-align procedure could potentially introduce circularity by imposing the anticorrelated structure the authors aim to detect. It would be important to implement validation analyses to confirm that anticorrelation is an intrinsic property rather than a methodological artifact. Approaches include leave-one-subject-out cross-validation, unsupervised dimensionality reduction (e.g., PCA) applied independently to verify the anticorrelated structure, and split-half reliability analysis. Such validation would significantly strengthen the statistical foundation of findings.

      (5) Quantifying Hyperalignment Contribution

      The appendix notes that non-hyperaligned data show a coarser structure, but the specific contribution of hyperalignment to your findings requires more thorough quantification. Please provide a systematic comparison of results with and without hyperalignment, demonstrating that similar (even if weaker) anatomical correspondence exists in native subject space. This would establish that the mesoscale organizational principles you identify are not artifacts of the alignment procedure but reflect genuine neurobiological organization. Consider presenting correlation coefficients or overlap metrics quantifying the similarity of state structures before and after hyperalignment.

      (6) Functional Characterization of the Unimodal State

      The observation that the brain spends approximately 34% of its time in a "Unimodal State" is presented primarily as a transition period. This is an interesting observation. However, it would be useful to characterize the functional connectivity profile of the unimodal state. Specifically, investigate whether it represents a distinct functional state with its own characteristic connectivity pattern. More detailed analysis would provide a more complete picture of temporal brain dynamics during naturalistic viewing and could yield new perspectives on how the brain reorganizes between stable states.

    1. Reviewer #2 (Public review):

      Summary:

      Overall, this is an excellent paper, making use of a newly developed system for monitoring the behaviour of chromatophores in the skin of (mostly) free-swimming bobtail squid and European cuttlefish. The manuscript is very well-written, clearly presented and very well-structured. The central finding, that individual chromatophores are connected to multiple motor neurones, is not new. Novelty instead comes from the ability to measure the actuation of chromatophore sections across wide areas of skin in free-swimming animals, showing the diversity of local motor units and reinforcing the notion that individual chromatophores are not necessarily the individual units of colour change, but rather local motor units that cover multiple neighbour and near-neighbour chromatophore muscles. This is an excellent finding and one that will shape our understanding of the neural control of cephalopod skin colour.

      Strengths:

      The methodological approach to collecting large amounts of data about local variations in the expansion of sections of chromatophores is exciting, and the analysis pipeline for clustering sections of chromatophores whose spontaneous activity correlated over time is powerful and exciting.

      Weaknesses:

      Some minor edits and typographical errors need correcting. I also had some concerns that the preparation for the electrophysiological section of the manuscript complies with the journal's ethical requirements, so I would urge that this be carefully checked.

  3. Jan 2026
    1. Reviewer #2 (Public review):

      Summary:

      Griciunaite et al. report on the function of jam2b and hand2 in the formation of the intestinal vasculature derived from late-forming endothelial cells (ECs) within the secondary vascular field (SVF). They generate transgenic lines that allow for the tracking of jam2b-expressing cells, both with fluorescent proteins and through Cre-mediated recombination in reporter lines. They also show that double maternal zygotic mutants in jam2a and jam2b, as well as hand2 mutants, display defects in the formation of the intestinal vasculature.

      Strengths:

      The results are interesting, as they address the important question of how blood vessels form during later developmental time points and potentially identify specific genes regulating this process.

      Weaknesses:

      (1) The authors generate a new tool, a Gal4 knock-in of the jam2b locus, to track EGFP-expressing cells over time and follow the developmental trajectory of jam2b-expressing cells. Figure 1 characterizes the line. However, it lacks quantification, e.g., how many etv2-expressing cells also show EGFP expression or the contribution of EGFP-expressing cells to different types of blood vessels. This type of quantification would be useful, as it would also allow for comparison of their findings to their previous data examining the contribution of SVF cells to different types of blood vessels. All the authors state that at 30 hpf, EGFP-expressing cells can be seen in the vasculature (apparently the PCV).

      It is not clear why the authors do not use a nuclear marker for both ECs (as they did in their previous publication) and for jam2b-expressing cells. UAS:nEGFP and UAS:NLS-mcherry (e.g. pt424tg) transgenic lines are available. This would circumvent the problem the authors encounter with the strong fluorescence visible in the yolk extension. It would also facilitate quantifying the contribution of jam2b cells to different types of blood vessels.

      (2) The time-lapse movie in Figure 2 is not very informative, as it just provides a single example of a dividing cell contributing to the PCV. Also, quantifications are needed. As SVF cells appear to expand significantly after their initial specification, it would be informative to know how many cell divisions and which types of blood vessels jam2b-expressing cells contribute to. Can the authors observe cells that give rise to different types of blood vessels? Jam2b expression in LPM cells apparently precedes expression of etv2. Is etv2 needed for maintenance, or do Jam2b-expressing cells contribute to different types of tissues in etv2 mutant embryos? Comparing time-lapse analysis in wildtype and etv2 mutant embryos would address this question.

      (3) In Figure 3, the authors generate UAS:Cre and UAS:Cre-ERT2 transgenic lines to lineage trace the jam2b-expressing cells. It is again not clear why the authors do not use a responder line containing nuclear-localized fluorescent proteins to circumvent the strong expression of fluorescent proteins in the yolk extension. It is also unclear why the two transgenic lines give very different results regarding the number of cells being labelled. The ERT2 fusions label around 3 cells in the SIA, while the Cre line labels only about 1.5 cells per embryo, with very little contribution of labelled cells to other blood vessels. One would expect the Cre line requiring tamoxifen induction to label fewer cells when compared to the constitutive Cre line. What is the reason for this discrepancy? Are the lines single integration? Is there silencing? This needs to be better characterized, also regarding the reproducibility of the experiments. If the Cre lines were to be multiple copy integrations, outcrossing the line might lead to lower expression levels in future generations.

      It is also not clear how the authors conclude from these findings that "SVF cells show major contribution to the SIA and SIV" when only 1.5 or 3 cells of the SIA are labelled, with even fewer cells labelled in other blood vessels. They speculate that this might be due to low recombination efficiency, a question they then set out to answer using photoconversion of etv2:KAEDE expressing cells, an experiment that they also performed in their 2014 and 2022 publications. To check for low recombination efficiency, the authors could examine the expression of Cre mRNA in their transgenic embryos. Do many more jam2b expressing cells express Cre mRNA than they observe in their switch lines? They could also compare their experiments using Cre recombinase with those using EGFP expression in jam2b cells. EGFP is relatively stable, and the time frames the authors analyze are short. As no quantification of EGFP-expressing cells is provided in Figure 1, this comparison is currently not possible. Do these two different approaches answer different questions here?

      (4) Concerning the etv2:KAEDE photoconversion experiments: The percentages the authors report for SVF cells' contribution to the SIV and SIA differ from their previous study (Dev Cell, 2022). In that publication, SVF cells contributed 28% to the SIA and 48% to the SIV. In the present study, the numbers are close to 80% for both vessels. The difference is that the previous study analyzed 2dpf old embryos and the new one 4dpf old embryos. Do SVF-derived cells proliferate more than PCV-derived cells, or is there another explanation for this change in percentage contribution?

      (5) Single-cell sequencing data: Why do the authors not show jam2b expression in their single-cell sequencing data? They sorted for (presumably) jam2b-expressing cells and hypothesize that jam2b expression in ECs at this time point is important for the generation of intestinal vasculature. Do ECs in cluster 15 express jam2b? Why are no other top marker genes (tal1, etv2, egfl7, npas4l) included in the dot blot in Figure 5b?

      (6) Concerns about cell autonomy of mutant phenotypes: The authors need to perform in situ hybridization to characterize jam2a expression. Can it be seen in SVF cells? The double mutants show a clear phenotype in intestinal vessel development; however, it is unclear whether this is due to a cell-autonomous function of jam2a/b within SVF cells. The authors need to address this issue, as jam2b and potentially also jam2a are expressed within the tissue surrounding the forming SVF. For instance, do transplanted mutant cells contribute to the intestinal vasculature to the same extent as wild-type cells do?

      (7) Finally, the authors analyze the phenotypes of hand2 mutants and their impact on the expression of jam2b and etv2. They observe a reduction in jam2b and etv2 expression in SVF cells. However, they do not show the vascular phenotypes of hand2 mutants. Is the formation of the SIA and SIV disturbed? Is hand2 cell autonomously needed in ECs? The authors suggest that hand2 controls SVF development through the regulation of jam2b. However, they also show that jam2b mutants do not have a phenotype on their own. Clearly, hand2, if it were to be required in ECs, regulates other genes important for SVF development. These might then regulate jam2b expression. The clear linear relationship, as the title suggests, is not convincingly shown by the data.

    1. Reviewer #2 (Public review):

      Summary:

      This manuscript investigates age-related differences in cooperative behavior by comparing adolescents and adults in a repeated Prisoner's Dilemma Game (rPDG). The authors find that adolescents exhibit lower levels of cooperation than adults. Specifically, adolescents reciprocate partners' cooperation to a lesser degree than adults do. Through computational modeling, they show that this relatively low cooperation rate is not due to impaired expectations or mentalizing deficits, but rather a diminished intrinsic reward for reciprocity. A social reinforcement learning model with asymmetric learning rate best captured these dynamics, revealing age-related differences in how positive and negative outcomes drive behavioral updates. These findings contribute to understanding the developmental trajectory of cooperation and highlight adolescence as a period marked by heightened sensitivity to immediate rewards at the expense of long-term prosocial gains.

      Strengths:

      Rigid model comparison and parameter recovery procedure. Conceptually comprehensive model space. Well-powered samples.

      Weaknesses:

      A key conceptual distinction between learning from non-human agents (e.g., bandit machines) and human partners is that the latter are typically assumed to possess stable behavioral dispositions or moral traits. When a non-human source abruptly shifts behavior (e.g., from 80% to 20% reward), learners may simply update their expectations. In contrast, a sudden behavioral shift by a previously cooperative human partner can prompt higher-order inferences about the partner's trustworthiness or the integrity of the experimental setup (e.g., whether the partner is truly interactive or human). The authors may consider whether their modeling framework captures such higher-order social inferences. Specifically, trait-based models-such as those explored in Hackel et al. (2015, Nature Neuroscience)-suggest that learners form enduring beliefs about others' moral dispositions, which then modulate trial-by-trial learning. A learner who believes their partner is inherently cooperative may update less in response to a surprising defection, effectively showing a trait-based dampening of learning rate.

      This asymmetry in belief updating has been observed in prior work (e.g., Siegel et al., 2018, Nature Human Behaviour) and could be captured using a dynamic or belief-weighted learning rate. Models incorporating such mechanisms (e.g., dynamic learning rate models as in Jian Li et al., 2011, Nature Neuroscience) could better account for flexible adjustments in response to surprising behavior, particularly in the social domain.

      Second, the developmental interpretation of the observed effects would be strengthened by considering possible non-linear relationships between age and model parameters. For instance, certain cognitive or affective traits relevant to social learning-such as sensitivity to reciprocity or reward updating-may follow non-monotonic trajectories, peaking in late adolescence or early adulthood. Fitting age as a continuous variable, possibly with quadratic or spline terms, may yield more nuanced developmental insights.

      Finally, the two age groups compared-adolescents (high school students) and adults (university students)-differ not only in age but also in sociocultural and economic backgrounds. High school students are likely more homogenous in regional background (e.g., Beijing locals), while university students may be drawn from a broader geographic and socioeconomic pool. Additionally, differences in financial independence, family structure (e.g., single-child status), and social network complexity may systematically affect cooperative behavior and valuation of rewards. Although these factors are difficult to control fully, the authors should more explicitly address the extent to which their findings reflect biological development versus social and contextual influences.

      Comments on revisions:

      The authors have addressed most of my previous comments adequately. I only have a minor question: The models with some variations of RL seem to have very similar AIC. What were the authors' criteria in deciding which model is the "winning" model when several models have similar AIC? Are there ways of integrating models with similar structures into a "model family"? Alternatively, is it possible that different models fit better for different subgroups of participants (e.g., high schoolers vs. college students)?

    1. Reviewer #2 (Public review):

      Summary:

      This study presents a systematic and well-executed effort to identify and classify bacterial NRP metallophores. The authors curate key chelator biosynthetic genes from previously characterized NRP-metallophore biosynthetic gene clusters (BGCs) and translate these features into an HMM-based detection module integrated within the antiSMASH platform.

      The new algorithm is compared with a transporter-based siderophore prediction approach, demonstrating improved precision and recall. The authors further apply the algorithm to large-scale bacterial genome mining and, through reconciliation of chelator biosynthetic gene trees with the GTDB species tree using eMPRess, infer that several chelating groups may have originated prior to the Great Oxidation Event.<br /> Overall, this work provides a valuable computational framework that will greatly assist future in silico screening and preliminary identification of metallophore-related BGCs across bacterial taxa.

      Strengths:

      (1) The study provides a comprehensive curation of chelator biosynthetic genes involved in NRP-metallophore biosynthesis and translates this knowledge into an HMM-based detection algorithm, which will be highly useful for the initial screening and annotation of metallophore-related BGCs within antiSMASH.

      (2) The genome-wide survey across a large bacterial dataset offers an informative and quantitative overview of the taxonomic distribution of NRP-metallophore biosynthetic chelator groups, thereby expanding our understanding of their phylogenetic prevalence.

      (3) The comparative evolutionary analysis, linking chelator biosynthetic genes to bacterial phylogeny, provides an interesting and valuable perspective on the potential origin and diversification of NRP-metallophore chelating groups.

      Weaknesses:

      (1) Although the rule-based HMM detection performs well in identifying major categories of NRP-metallophore biosynthetic modules, it currently lacks the resolution to discriminate between fine-scale structural or biochemical variations among different metallophore types.

      (2) While the comparison with the transporter-based siderophore prediction approach is convincing overall, more information about the dataset balance and composition would be appreciated. In particular, specifying the BGC identities, source organisms, and Gram-positive versus Gram-negative classification would improve transparency. In the supplementary tables, the "Just TonB" section seems to include only BGCs from Gram-negative bacteria-if so, this should be clearly stated, as Gram type strongly influences siderophore transport systems.

      Comments on revisions:

      The authors have adequately addressed all of my previous comments. I have no further comments on the revised manuscript.

    1. Reviewer #2 (Public review):

      Here, the authors record dopamine release using fast-scan cyclic voltammetry in the nucleus accumbens/ ventromedial striatum (VMS) while rats perform variants of a Go/No Go task. Two versions are self-paced, in that the rat can initiate a trial by nosepoking at the odor port at any time once the ITI has elapsed, whereas the other two require the rat to wait for a cue-light before responding. Two "long" variants also require either more lever-presses on Go trials, or a longer nosepoke time for No Go trials, and also incorporate "free" trials in which the rat is rewarded for just heading straight to the food tray. The authors find that dopamine levels increase more during the response requirement for Go than No Go trials, indicating a role for invigorating to-be-rewarded actions. Dopamine levels also steadily increased as rats approached the site of reward delivery, and the authors demonstrate quite elegantly that this was not due to orientation to the food tray, or time-to-reward, or action initiation, but instead reflects spatial proximity to the rewarded location. Contrary to previous reports, the authors did not discern any differences in dopamine dynamics depending on whether the trials were cue- or self-paced, and dopamine release did not scale with effort requirements.

      The manuscript is well-written, and the authors use figures to great effect to explain what could otherwise be a hard-to-parse set of data. The authors make good use of the richness of their behavioral data to justify or negate potential conclusions. I have the following comments.

      Re: The lack of relationship between effort to acquire reward in the current study and the magnitude of dopamine release, can the authors unpack this a bit more? Why the difference between the Walton and Bouret studies? Were the shifts in effort requirements comparable across the behavioral tasks? What else could be different between the methodologies?

      I would argue that the cue- vs self-initiated distinction was pretty minor, given that there was a fixed ITI of 5s. How does this task modification compare to those used previously to show that dopamine release corresponds to behavioral controllability? It would help the reader if the authors could spend more time discussing these disparate findings and looking for points of methodological divergence/ commonality.

    1. Reviewer #2 (Public review):

      Summary:

      The manuscript by Zeng et al reports the structural and biochemical study of a novel effectors from the bacterial pathogen Legionella pneumophila. The authors continued from results from their earlier screening for L. pneumophila proteins that that affect host F-actin dynamics to show that Llfat1 (Lpg1387) interacts with actin via a novel actin-binding domain (ABD). The authors also determined the structure of the Lfat1 ABD-F-actin complex, which allowed them to develop this ABD as probe for F-actin. Finally, the authors demonstrated that Llfat1 is a lysine fatty acyltransferase that targets several small GTPases in host cells. Overall, this is a very exciting study and should be of great interest to scientists in both bacterial pathogenesis and actin cytoskeleton of eukaryotic cells.

    1. Reviewer #2 (Public review):

      Summary:

      This study explores how signals from all sides of a developing limb, front/back and top/bottom, work together to guide the regrowth of a fully patterned limb in axolotls, a type of salamander known for its impressive ability to regenerate limbs. Using a model called the Accessory Limb Model (ALM), the researchers created early staged limb regenerates (called blastemas) with cells from different sides of the limb. They discovered that successful limb regrowth only happens when the blastema contains cells from both the top (dorsal) and bottom (ventral) of the limb. They also found that a key gene involved in front/back limb patterning, called Shh (Sonic hedgehog), is only turned on when cells from both the dorsal and ventral sides come into contact. The study identified two important molecules, Wnt10B and FGF2, that help activate Shh when dorsal and ventral cells interact. Finally, the authors propose a new model that explains how cells from all four sides of a limb, dorsal, ventral, anterior (front), and posterior (back), contribute at both the cellular and molecular level to rebuilding a properly structured limb during regeneration

      Strengths:

      The techniques used in this study, like delicate surgeries, tissue grafting, and implanting tiny beads soaked with growth factors, are extremely difficult, and only a few research groups in the world can do them successfully. These methods are essential for answering important questions about how animals like axolotls regenerate limbs with the correct structure and orientation. To understand how cells from different sides of the limb communicate during regeneration, the researchers used a technique called in situ hybridization, which lets them see where specific genes are active in the developing limb. They clearly showed that the gene Shh, which helps pattern the front and back of the limb, only turns on when cells from both the top (dorsal) and bottom (ventral) sides are present and interacting. The team also took a broad, unbiased approach to figure out which signaling molecules are unique to dorsal and ventral limb cells. They tested these molecules individually and discovered which could substitute for actual dorsal and ventral cells, providing the same necessary signals for proper limb development. Overall, this study makes a major contribution to our understanding of how complex signals guide limb regeneration, showing how different regions of the limb work together at both the cellular and molecular levels to rebuild a fully patterned structure.

      Weaknesses:

      Because the expressional analyses are performed on thin sections of regenerating tissue, in the original manuscript, they provided only a limited view of the gene expression patterns in their experiments, opening the possibility that they could be missing some expression in other regions of the blastema. Additionally, the quantification method of the expressional phenotypes in most of the experiments did not appear to be based on a rigorous methodology. The authors' inclusion of an alternate expression analysis, qRT-PCR, on the entire blastema helped validate that the authors are not missing something in the revised manuscript.

      Overall, the number of replicates per sample group in the original manuscript was quite low (sometimes as low as 3), which was especially risky with challenging techniques like the ones the authors employ. The authors have improved the rigor of the experiment in the revised manuscript by increasing the number of replicates. The authors have not performed a power analysis to calculate the number of animals used in each experiment that is sufficient to identify possible statistical differences between groups. However, the authors have indicated that there was not sufficient preliminary data to appropriately make these quantifications.

      Likewise, in the original manuscript, the authors used an AI-generated algorithm to quantify symmetry on the dorsal/ventral axis, and my concern was that this approach doesn't appear to account for possible biases due to tissue sectioning angles. They also seem to arbitrarily pick locations in each sample group to compare symmetry measurements. There are other methods, which include using specific muscle groups and nerve bundles as dorsal/ventral landmarks, that would more clearly show differences in symmetry. The authors have now sufficiently addressed this concern by including transverse sections of the limbs annd have explained the limitations of using a landmark-based approach in their quantification strategy.

    1. Reviewer #2 (Public review):

      Summary:

      Membrane transport proteins function by the alternating access model in which a central substrate binding site is alternately exposed to the soluble phase on either side of the membrane. For many members of the ABC transporter family, the transport cycle involves conformational isomerization between an outward-facing V-shaped conformation and an inward-facing Λ-shaped conformation. In the present manuscript, it is hypothesized that the difference in free energy between these conformational states depends on the radius of curvature of the membrane and hence, that transport activity can be modulated by this parameter.

      To test this, BmrA, a multidrug exporter in Bacillus subtilis, was reconstituted into spherical proteoliposomes of different diameters and hence different radii of curvature. By measuring flux through the ATP turnover cycle in an enzymatic assay and conformational isomerization by single-molecule FRET, the authors argue that the activity of BmrA can be experimentally manipulated by altering the radius of curvature of the membrane. Flux through the transport cycle was found to be reduced at high membrane curvature. It is proposed that the potential to modulate transport flux through membrane curvature may allow ABC transporters to act as mechanosensors by analogy to mechanosensitive ion channels such as the Piezo channels and K2P channels.

      Although an interesting methodology is established, additional experimentation and analyses would be required to support the major claims of the manuscript.

      Strengths:

      Mechanosensitivity of proteins is an understudied phenomenon, in part due to a scarcity of methods to study the activity of proteins in response to mechanical stimuli in purified systems. Useful experimental and theoretical frameworks are established to address the hypothesis, which potentially could have implications for a large class of membrane proteins. The tested hypothesis for the mechanosensitivity of the BmrA transporter is intuitive and compelling.

      Weaknesses and comments:

      (1) Although this study may be considered as a purely biophysical investigation of the sensitivity of an ABC transporter to mechanical perturbation of the membrane, the impact would be strengthened if a physiological rationale for this mode of regulation were discussed. Many factors, including temperature, pH, ionic strength, or membrane potential, are likely to affect flux through the transport cycle to some extent, without justifying describing BmrA as a sensor for changes in any of these. Indeed, a much stronger dependence on temperature than on membrane curvature was measured. It is not clear what radii of curvature BmrA would normally be exposed to, and whether this range of curvatures corresponds to the range at which modulation of transport activity could occur. Similarly, it is not clear what biological condition would involve a substantial change to membrane curvature or tension that would necessitate altered BmrA activity.

      (2) The size distributions of vesicles were estimated by cryoEM. However, grid blotting leaves a very thin layer of vitreous ice that could sterically exclude large vesicles, leading to a systematic underestimation of the vesicle size distribution.

      (3) The relative difference in ATP turnover rates for BmrA in small versus large vesicles is modest (~2-fold) and could arise from different success rates of functional reconstitution with the different protocols.

      (4) The conformational state of the NBDs of BmrA was measured by smFRET imaging. Several aspects of these investigations could be improved or clarified. Firstly, the inclusion and exclusion criteria for individual molecules should be more quantitatively described in the methods. Secondly, errors were estimated by bootstrapping. Given the small differences in state occupancies between conditions, true replicates and statistical tests would better establish confidence in their significance. Thirdly, it is concerning that very few convincing dynamic transitions between states were observed. This may in part be due to fast photobleaching compared to the rate of isomerization, but this could be overcome by reducing the imaging frequency and illumination power. Alternatively, several labs have established the ability to exchange solution during imaging to thereby monitor the change in FRET distribution as a ligand is delivered or removed. Visualizing dynamic and reversible responses to ligands would greatly bolster confidence in the condition-dependent changes in FRET distributions. Such pre-steady state experiments would also allow direct comparison of the kinetics of isomerization from the inward-facing to the outward-facing conformation on delivery of ATP between small and large vesicles.

      (5) A key observation is that BmrA was more prone to isomerize ATP- or AMP-PNP-dependently to the outward-facing conformations in large vesicles. Surprisingly, the same was not observed with vanadate-trapping, although the sensitivity of state occupancy to membrane curvature would be predicted to be greatest when state occupancies of both inward- and outward-facing states are close to 50%. It is argued that this was due to irreversibility of vanadate-trapping, but both vanadate and AMP-PNP should work fully reversibly on ABC transporters (see e.g. PMID: 7512348 for vanadate). Further, if trapping were fully irreversible, a quantitative shift to the outward-facing condition would be predicted.

    1. Reviewer #2 (Public review):

      Summary:

      In this manuscript, the authors examine the mechanisms by which stimulation of the infralimbic cortex (IL) facilitates the retention and retrieval of inhibitory memories. Previous work has shown that optogenetic stimulation of the IL suppresses freezing during extinction but does not improve extinction recall when extinction memory is probed one day later. When stimulation occurs during a second extinction session (following a prior stimulation-free extinction session), freezing is suppressed during the second extinction as well as during the tone test the following day. The current study was designed to further explore the facilitatory role of the IL in inhibitory learning and memory recall. The authors conducted a series of experiments to determine whether recruitment of IL extends to other forms of inhibitory learning (e.g., backward conditioning) and to inhibitory learning involving appetitive conditioning. Further, they assessed whether their effects could be explained by stimulus familiarity. The results of their experiments show that backward conditioning, another form of inhibitory learning, also enabled IL stimulation to enhance fear extinction. This phenomenon was not specific to aversive learning as backward appetitive conditioning similarly allowed IL stimulation to facilitate extinction of aversive memories. Finally, the authors ruled out the possibility that IL facilitated extinction merely because of prior experience with the stimulus (e.g., reducing the novelty of the stimulus). These findings significantly advance our understanding of the contribution of IL to inhibitory learning. Namely, they show that the IL is recruited during various forms of inhibitory learning and its involvement is independent of the motivational value associated with the unconditioned stimulus.

      Strengths to highlight:

      (1) Transparency about the inclusion of both sexes and the representation of data from both sexes in figures.

      (2) Very clear representation of groups and experimental design for each figure.

      (3) The authors were very rigorous in determining the neurobehavioral basis for the effects of IL stimulation on extinction. They considered multiple interpretations and designed experiments to address these possible accounts of their data.

      (4) The rationale for and the design of the experiments in this manuscript are clearly based on a wealth of knowledge about learning theory. The authors leveraged this expertise to narrow down how the IL encodes and retrieves inhibitory memories.

    1. Reviewer #2 (Public review):

      Summary:

      Understanding the mechanisms of neural specification is a central question in neurobiology. In Drosophila, the mushroom body (MB), which is the associative learning region in the brain, consists of three major cell types: γ, α'/β' and α/β kenyon cells. These classes can be further subdivided into seven subtypes, together comprising ~2000 KCs per hemi-brain. Remarkably, all of these neurons are derived from just four neuroblasts in each hemisphere. Therefore, a lot of endeavours are put to understand how the neuron is specified in the fly MB.

      Over the past decade, studies have revealed that MB neuroblasts employ a temporal patterning mechanism, producing distinct neuronal types at different developmental stages. Temporal identity is conveyed through transcription factor expression in KCs. High levels of Chinmo, a BTB-zinc finger transcription factor, promote γ-cell fate (Zhu et al., Cell, 2006). Reduced Chinmo levels trigger expression of mamo, a zinc finger transcription factor that specifies α'/β' identity (Liu et al., eLife, 2019). However, the specification of α/β neurons remains poorly understood. Some evidence suggests that microRNAs regulate the transition from α'/β' to α/β fate (Wu et al., Dev Cell, 2012; Kucherenko et al., EMBO J, 2012). One hypothesis even proposes that α/β represents a "default" state of MB neurons, which could explain the difficulty in identifying dedicated regulators.

      The study by Chung et al. challenges this hypothesis. By leveraging previously published RNA-seq datasets (Shih et al., G3, 2019), they systematically screened BAC transgenic lines to selectively label MB subtypes. Using these tools, they analyzed the consequences of manipulating E93 expression and found that E93 is required for α/β specification. Furthermore, loss of E93 impairs MB-dependent behaviors, highlighting its functional importance.

      Strengths:

      The authors conducted a thorough analysis of E93 manipulation phenotypes using LexA tools generated from the Janelia Farm and Bloomington collections. They demonstrated that E93 knockdown reduces expression of Ca-α1T, a calcium channel gene identified as an α/β marker. Supporting this conclusion, one LexA line driven by a DNA fragment near EcR (R44E04) showed consistent results. Conversely, overexpression of E93 in γ and α'/β' Kenyon cells led to downregulation of their respective subtype markers.

      Another notable strength is the authors' effort to dissect the genetic epistasis between E93 and previously known regulators. Through MARCM and reporter analyses, they showed that Chinmo and Mamo suppress E93, while E93 itself suppresses mamo. This work establishes a compelling molecular model for the regulatory network underlying MB cell-type specification.

      Weaknesses:

      The interpretation of E93's role in neuronal specification requires caution. Typically, two criteria are used to establish whether a gene directs neuronal identity:

      (1) gene manipulation shifts the neuronal transcriptome from one subtype to another, and

      (2) gene manipulation alters axonal projection patterns.

      The results presented here only partially satisfy the first criterion. Although markers are affected, it remains possible that the reporter lines and subtype markers used are direct transcriptional targets of E93 in α/β neurons, rather than reflecting broader fate changes. Future studies using transcriptomics would provide a more comprehensive assessment of neuronal identity following E93 perturbation.

      With respect to the second criterion, the evidence is also incomplete. While reporter patterns were altered, the overall morphology of the α/β lobes appeared largely intact after E93 knockdown. Overexpression of E93 in γ neurons produced a small subset of cells with α/β-like projections, but this effect warrants deeper characterization before firm conclusions can be drawn.

      Overall, this study has nicely shown that E93 can regulate α/β neural identities. Further studies on the regulatory network will help to better understand the mechanism of neurogenesis in mushroom body.

    1. Reviewer #2 (Public review):

      Summary:

      In this paper, the authors present a detailed computational model and experimental data concerning over-ground locomotion in rats before and after recovery from spinal cord injury. They are able to manually tune the parameters of this physiologically based, detailed model to reproduce many aspects of the observed animals' locomotion in the naive case and in two distinct injury cases.

      Strengths:

      The strengths are that the model is driven to closely match clean experimental data, and the model itself has detailed correspondence to proposed anatomical reality. As such this makes the model more readily applicable to future experimental work. It can make useful suggestions. The model reproduces are large number of conditions, across frequencies, and with model structure changed by injury and recovery. The model is extensive and is driven by known structures, has links to genetic identities, and has been validated extensively across a number of experiments and manipulations over the years. It models a system of critical importance to the field, and the tight coupling to experimental data is a real strength.

      Weaknesses:

      A downside is that scientifically, here, the only question tackled is one of sufficiency. With manual tuning of parameters in a way that matches what the field believes/knows from experimental work, the detailed model can reproduce the experimental findings. One of the benefits of computational models is that the counter-factual can be tested to provide evidence against alternate hypotheses. That isn't really done here. I'm pretty sure there are competing theories of what happens during recovery from a hemi-section injury and contusion injury. The model could be used to make predictions for some alternate hypothesis, supporting or rejecting theories of recovery. This may be part of future plans. Here, the focus is on showing that the model is capable of reproducing the experimental results at all, for any set of parameters, however tuned.

      Comments on revisions:

      The authors have addressed my prior concerns and clearly discuss the sufficiency of the model, and strengthen the discussion with interesting findings for the role of propriospinal and commissural interneuronal pathways. This is a very nice contribution.

    1. Reviewer #2 (Public review):

      Summary:

      In this manuscript, Monziani et al. identified long noncoding RNAs (lncRNAs) that act in cis and are coregulated with their target genes located in close genomic proximity. The authors mined the GeneHancer database, and this analysis led to the identification of four lncRNA-target pairs. The authors decided to focus on lncRNA EPB41L4A-AS1.

      They thoroughly characterised this lncRNA, demonstrating that it is located in the cytoplasm and the nuclei, and that its expression is altered in response to different stimuli. Furthermore, the authors showed that EPB41L4A-AS1 regulates EPB41L4A transcription, leading to a mild reduction in EPB41L4A protein levels. This was not recapitulated with sirna-mediated depletion of EPB41L4AAS1. RNA-seq in EPB41L4A-AS1 depleted cells with single LNA revealed 2364 DEGs linked to pathways including the cell cycle, cell adhesion, and inflammatory response. To understand the mechanism of action of EPB41L4A-AS1, the authors mined the ENCODE eCLIP data and identified SUB1 as an lncRNA interactor. The authors also found that the loss of EPB41L4A-AS1 and SUB1 leads to the accumulation of snoRNAs, and that SUB1 localisation changes upon the loss of EPB41L4A-AS1. Finally, the authors showed that EPB41L4A-AS1 deficiency did not change the steady-state levels of SNORA13 nor RNA modification driven by this RNA. The phenotype associated with the loss of EPB41L4A-AS1 is linked to increased invasion and EMT gene signature.

      Overall, this is an interesting and nicely done study on the versatile role of EPB41L4A-AS1 and the multifaceted interplay between SUB1 and this lncRNA, but some conclusions and claims need to be supported with additional experiments before publication. My primary concerns are using a single LNA gapmer for critical experiments, increased invasion and nucleolar distribution of SUB1- in EPB41L4A-AS1-depleted cells.

      Strengths:

      The authors used complementary tools to dissect the complex role of lncRNA EPB41L4A-AS1 in regulating EPB41L4A, which is highly commendable. There are few papers in the literature on lncRNAs at this standard. They employed LNA gapmers, siRNAs, CRISPRi/a, and exogenous overexpression of EPB41L4A-AS1 to demonstrate that the transcription of EPB41L4A-AS1 acts in cis to promote the expression of EPB41L4A by ensuring spatial proximity between the TAD boundary and the EPB41L4A promoter. At the same time, this lncRNA binds to SUB1 and regulates snoRNA expression and nucleolar biology. Overall, the manuscript is easy to read, and the figures are well presented. The methods are sound, and the expected standards are met.

      Weaknesses:

      The authors should clarify how many lncRNA-target pairs were included in the initial computational screen for cis-acting lncRNAs and why MCF7 was chosen as the cell line of choice. Most of the data uses a single LNA gapmer targeting EPB41L4A-AS1 lncrna (eg, Fig. 2c, 3B and RNA-seq), and the critical experiments should be using at least 2 LNA gapmers. The specificity of SUB1 CUT&RUN is lacking, as well as direct binding of SUB1 to lncRNA EPB41L4A-AS1, which should be confirmed by CLIP qPCR in MCF7 cells. Finally, the role of EPB41L4A-AS1 in SUB1 distribution (Fig. 5) and cell invasion (Fig. 8) needs to be complemented with additional experiments, which should finally demonstrate the role of this lncRNA in nucleolus and cancer-associated pathways. The use of MCF7 as a single cancer cell line is not ideal.

      Revised version of the manuscript:

      The authors have addressed many of my concerns in their revised manuscript:

      The use of single gapmers has been adequately addressed in the revised version of the manuscript, as well as CUT RUN for SUb1.

      Future studies will address the role of this lncRNA in invasion and migration using more relevant and appropriate cellular assays. In addition, nucleolar fractionation and analysis of rRNA synthesis are recommended in the follow-up studies for EPB41L4A-AS1.

    1. Reviewer #2 (Public review):

      In this manuscript, the authors describe using "in extracto" cryo-EM to obtain high-resolution structures of mammalian ribosomes from concentrated cell extracts without further purification or reconstitution. This approach aims to solve two related problems. The first is that purified ribosomes often lose cellular cofactors, which are often reconstituted in vitro; this precludes the ability to find novel interactions. The second is that while it is possible to perform cryo-EM on cellular lamella, FIB milling is a slow and laborious process, making it unfeasible to collect datasets sufficiently large to allow for high-resolution structure determination. Extracts should contain all cellular cofactors and allow for grid preparation similar to standard single-particle analysis (SPA) approaches. While cryo-EM of cell extracts is not in itself novel, this manuscript uses 2D template matching (2DTM) for particle picking prior to structure determination using more standard SPA pipelines. This should allow for improved picking over other approaches in order to obtain large datasets for high-resolution SPA.

      This manuscript has two main results: novel structures of ribosomes in hibernating states; and a proof-of-principle for in extracto cryo-EM using 2DTM. Overall, I think the results presented here are strong and serve as a proof-of-principle for an approach that may be useful to many others. However, without presenting the logic of how parameters were optimized, this manuscript is limited in its direct utility to readers.

    1. Reviewer #2 (Public review):

      Summary:

      Dong et al. present a thorough investigation into the potential of repurposing citalopram, an SSRI, for hepatocellular carcinoma (HCC) therapy. The study highlights the dual mechanisms by which citalopram exerts anti-tumor effects: reprogramming tumor-associated macrophages (TAMs) toward an anti-tumor phenotype via C5aR1 modulation and suppressing cancer cell metabolism through GLUT1 inhibition, while enhancing CD8+ T cell activation. The findings emphasize the potential of drug repurposing strategies and position C5aR1 as a promising immunotherapeutic target.

      Strength:

      It provides detailed evidence of citalopram's non-canonical action on C5aR1, demonstrating its ability to modulate macrophage behavior and enhance CD8+ T cell cytotoxicity. The use of DARTS assays, in silico docking, and gene signature network analyses offers robust validation of drug-target interactions. Additionally, the dual focus on immune cell reprogramming and metabolic suppression presents a comprehensive strategy for HCC therapy. By highlighting the potential of existing drugs like citalopram for repurposing, the study also underscores the feasibility of translational applications. During revision, the authors experimentally demonstrated that TAM has lower GLUT1 levels, further strengthening their claim of C5aR1 modulation-dependent TAM improvement for tumor therapy.

      Comments on revised version:

      The authors have addressed most of my concerns about the paper.

    1. Reviewer #2 (Public review):

      Summary:

      In this manuscript, the authors describe the production of a high-resolution connectome for the statocyst of a ctenophore nervous system. This study is of particular interest because of the apparent independent evolution of the ctenophore nervous system. The statocyst is a component of the aboral organ, which is used by ctenophores to sense gravity and regulate the activity of the organ's balancer cilia. The EM reconstruction of the aboral organ was carried out on a five-day old larva of the model ctenophore Mnemiopsis leidyi. To place their connectome data in a functional context, the authors used high-speed imaging of ciliary beating in immobilized larvae. With these data, the authors were able to model the circuitry used for gravity sensing in a ctenophore larva.

      Strengths:

      Because of it apparently being the sister phylum to all other metazoans, Ctenophora is a particularly important group for studies of metazoan evolution. Thus, this work has much to tell us about how animals evolved. Added to that is the apparent independent evolution of the ctenophore nervous system. This study provides the first high-resolution connectomic analysis of a portion of a ctenophore nervous system, extending previous studies of the ctenophore nervous system carried out by Sid Tamm. As such it establishes the methodology for high-resolution analysis of the ctenophore nervous system. While the generation of a connectome is in and of itself an important accomplishment, the coupling of the connectome data with analysis of the beating frequency of balancer cell cilia provides a functional context for understanding how the organization of the neural circuitry in the aboral organ carries out gravity sensing. In addition, the authors identified a new type of syncytial neuron in Mnemiopsis. Interestingly, the authors show that the neural circuitry controlling cilia beating in Mnemiopsis shares features with the circuitry that controls ciliary movement in the annelid Platynereis, suggesting convergent evolution of this circuity in the two organisms. The data in this paper are of high quality, and the analyses have been thoroughly and carefully done.

      Weaknesses:

      The paper has no obvious weaknesses.

      Comments on revisions:

      The authors have satisfactorily addressed the minor issues that I brought up in my original review.

    1. Reviewer #2 (Public review):

      Summary:

      The manuscript by Luden et al. investigates the molecular function and DNA-binding modes of AHL15, a transcription factor with pleiotropic effects on plant development. The results contribute to our understanding of AHL15 function in development, specifically, and transcriptional regulation in plants, more broadly.

      Strengths:

      The authors developed a set of genetic tools for high-resolution profiling of AHL15 DNA binding and provided exploratory analyses of chromatin accessibility changes upon AHL15 overexpression. The generated data (CHiP-Seq, ATAC-Seq and RNA-Seq is a valuable resource for further studies. The data suggest that AHL15 does not operate as a pioneer TF, but is likely involved in gene looping.

      Weaknesses:

      While the overall message is conveyed clearly and convincingly, I see one major issue concerning motif discovery and interpretation. The authors state that because HOMER detected highly enriched motifs at frequencies below 1%, they conclude that "a true DNA binding motif would be present in a large portion of the AHL15 peaks (targets) and would be rare in other regions of the genome (background)."

      I agree that the frequency below 1% is unexpectedly low; however, this more likely reflects problems in data preprocessing or motif discovery rather than intrinsic biological properties of the transcriptional factor that possesses a DNA-binding domain and is known to bind AT_rich motifs. As it is, Figure 2 cannot serve as a main figure in the manuscript: it rather suggests that the generated CHiP-Seq peakset is dominated by noise (or motif discovery was done improperly) than that AHL15 binds nonspecifically.

      Since key methodological details on the HOMER workflow are missing in the M&M section, it is not possible to determine what went wrong. Looking at other results, i.e. the reasonably structured peak distribution around TSS/TTS and consistent overlap of the peaks between the replicas, I assume that the motif discovery step was done improperly.

      Therefore, I recommend redoing the motif analysis, for example, by restricting the search to the top-ranked peaks (e.g. TOP1000) and by using an appropriate background set (HOMER can generate good backgrounds, but it was not documented in the manuscript how the authors did it). If HOMER remains unsuccessful, the authors should consider complementary methods such as STREME or MEME, similar to the approach used for GH1-HMGA (https://pmc.ncbi.nlm.nih.gov/articles/PMC8195489). If the peakset is of good quality, I would expect the analysis to identify an AT-rich motif with a frequency substantially higher than 1%-more likely in the range of at least 30%. If such a motif is detected, it should be reported clearly, ideally with positional enrichment information relative to TSS or TTS. It would also be informative to compare the recovered motif with known GH1-HMGA motifs.

      If de novo motif discovery remains inconclusive, the authors should, at a minimum, assess enrichment of known AHL binding motifs using available PWMs (e.g. from JASPAR). As it stands, the claim that "our ChIP-seq data show that AHL15 binds to AT-rich DNA throughout the Arabidopsis genome with limited sequence specificity (Figure 2A, Figure S2-S4)" is not convincingly supported.

      Another point concerns the authors' hypothesis regarding the role of AHL15 in gene looping. While I like this hypothesis and it is good to discuss it in the discussion section, the data presented are not sufficient to support the claim, stated in the abstract, that AHL15 "regulates 3D genome organization," as such a conclusion would require additional, dedicated experiments.

    1. Reviewer #2 (Public review):

      This is an excellent paper. The ability to measure the immune response to multiple viruses in parallel is a major advancement for the field, that will be relevant across pathogens (assuming the assay can be appropriately adapted). I only had a few comments, focused on maximising the information provided by the sera.

      Comments on revisions:

      These concerns were all addressed in the revised paper.

    1. Reviewer #2 (Public review):

      Summary:

      The authors test how sample size and demographic balance of reference cohorts affect the reliability of normative models in ageing and Alzheimer's disease. Using OASIS-3 and replicating in AIBL, they change age and sex distributions and number of samples and show that age alignment is more important than overall sample size. They also demonstrate that models adapted from a large dataset (UK Biobank) can achieve stable performance with fewer samples. The results suggest that moderately sized but demographically well-balanced cohorts can provide robust performance.

      Strengths:

      The study is thorough and systematic, varying sample size, age, and sex distributions in a controlled way. Results are replicated in two independent datasets with relatively large sample sizes, thereby strengthening confidence in the findings. The analyses are clearly presented and use widely applied evaluation metrics. Clinical validation (outlier detection, classification) adds relevance beyond technical benchmarks.The comparison between within-cohort training and adaptation from a large dataset is valuable for real-world applications.

      The work convincingly shows that age alignment is crucial and that adapted models can reach good performance with fewer samples.

    1. Reviewer #2 (Public review):

      The authors sought to answer several questions about the role of the tumor suppressor PTEN in SHH-medulloblastoma formation. Namely, whether Pten loss increases metastasis, understanding why Pten loss accelerates tumor growth, and the effect of single-copy vs double-copy loss on tumorigenesis. Using an elegant mouse model, the authors found that Pten mutations do not increase metastasis in a SmoD2-driven SHH-medullolbastoma mouse model, based on extensive characterization of the presence of spinal cord metastases. Upon examining the cellular phenotype of Pten-null tumors in the cerebellum, the authors made the interesting and puzzling observation that Pten loss increased the differentiation state of the tumor, with less cycling cells, seemingly in contrast to the higher penetrance and decreased latency of tumor growth.

      The authors then examined the rate of cell death in the tumor. Interestingly, Pten-null tumors had less dying cells, as assessed by TUNEL. In addition, the tumors expressed differentiaton markers NeuN and SyP, which are rare in SHH-MB mouse models. This reduction in dying cells is also evident at earlier stages of tumor growth. By looking shortly after Pten-loss induction, the authors found that Pten loss had an immediate impact on increasing the proliferative state of GCPs, followed by enhancing survival of differentiated cells. These two pro-tumor features together account for the increased penetrance and decreased latency of the model. While heterozygous loss of Pten also promoted proliferation, it did not protect against cell death.<br /> Interestingly, loss of Pten alone in GCPs caused an increase in cerebellar size throughout development. The authors suggest that Pten normally constrants GCP proliferation, although they did not check whether reduced cell death is also contributing to cerebellum size.

      Lastly, the authors examined macrophage infiltration and found that there was less macrophage infiltration to the Pten-null tumors. Using scRNA-seq, they suggest that the observed reduction in macrophages might be due to immunosuppressive tumor microenvironment.

      This mouse model will be of high relevance to the medulloblastoma community, as current models do not reflect the heterogeneity of the disease. In addition, the elegant experimentation into Pten function may be relevant to cancer biologists outside of the medulloblastoma field.

      Strengths:

      The in-depth characterisation of the mouse model is a major strength of the study, including multiple time points and quantifications. The single-cell sequencing adds a nice molecular feature, and this dataset may be relevant to other researchers with specific questions of Pten function.

      Weaknesses:

      Adequately addressed in revisions.

    1. Reviewer #2 (Public review):

      Summary

      In this manuscript, the authors combine an automated touchscreen-based trial-unique nonmatching-to-location (TUNL) task with activity-dependent labeling (TRAP/c-Fos) and birth-dating of adult-born dentate granule cells (abDGCs) to examine how cognitive demand modulates dentate gyrus (DG) activity patterns. By varying spatial separation between sample and choice locations, the authors operationally increase task difficulty and show that higher demand is associated with increased mature granule cell (mGC) activity and an amplified suprapyramidal (SB) versus infrapyramidal (IB) blade bias. Using chemogenetic inhibition, they further demonstrate dissociable contributions of abDGCs and mGCs to task performance and DG activation patterns.

      The combination of behavioral manipulation, spatially resolved activity tagging, and temporally defined abDGC perturbations is a strength of the study and provides a novel circuit-level perspective on how adult neurogenesis modulates DG function. In particular, the comparison across different abDGC maturation windows is well designed and narrows the functionally relevant population to neurons within the critical period (~4-7 weeks). The finding that overall mGC activity levels, in addition to spatially biased activation patterns, are required for successful performance under high cognitive demand is intriguing.

      Major Comments

      (1) Individual variability and the relationship between performance and DG activation.

      The manuscript reports substantial inter-animal variability in the number of days required to reach the criterion, particularly during large-separation training. Given this variability, it would be informative to examine whether individual differences in performance correlate with TRAP+ or c-Fos+ density and/or spatial bias metrics. While the authors report no correlation between success and TRAP+ density in some analyses, a more systematic correlation across learning rate, final performance, and DG activation patterns (mGC vs abDGC, SB vs IB) could strengthen the interpretation that DG activity reflects task engagement rather than performance only.

      (2) Operational definition of "cognitive demand".

      The distinction between low (large separation) and high (small separation) cognitive demand is central to the manuscript, yet the definition remains somewhat broad. Reduced spatial separation likely alters multiple behavioral variables beyond cognitive load, including reward expectation, attentional demands, confidence, engagement, and potentially motivation. The authors should more explicitly acknowledge these alternative interpretations and clarify whether "cognitive demand" is intended as a composite construct rather than a strictly defined cognitive operation.

      (3) Potential effects of task engagement on neurogenesis.

      Given the extensive behavioral training and known effects of experience on adult neurogenesis, it remains unclear whether the task itself alters the size or maturation state of the abDGC population. Although the focus is on activity and function rather than cell number, it would be useful to clarify whether neurogenesis rates were assessed or controlled for, or to explicitly state this as a limitation.

      (4) Temporal resolution of activity tagging.

      TRAP and c-Fos labeling provide a snapshot of neural activity integrated over a temporal window, making it difficult to determine which task epochs or trial types drive the observed activation patterns. This limitation is partially acknowledged, but the conclusions occasionally imply trial-specific or demand-specific encoding. The authors should more clearly distinguish between sustained task engagement and moment-to-moment trial processing, and temper interpretations accordingly. While beyond the scope of the current study, this also motivates future experiments using in vivo recording approaches.

      (5) Interpretation of altered spatial patterns following abDGC inhibition.

      In the abDGC inhibition experiments, Cre+ DCZ animals show delayed learning relative to controls. As a result, when animals are sacrificed, they may be at an intermediate learning stage rather than at an equivalent behavioral endpoint. This raises the possibility that altered DG activation patterns reflect the learning stage rather than a direct circuit effect of abDGC inhibition. Additional clarification or analysis controlling for the learning stage would strengthen the causal interpretation.

      (6) Relationship between c-Fos density and behavioral performance.

      The study reports that abDGC inhibition increases c-Fos density while impairing performance, whereas mGC inhibition decreases c-Fos density and also impairs performance. This raises an important conceptual question regarding the relationship between overall activity levels and task success. The authors suggest that both sufficient activity and appropriate spatial patterning are required, but the manuscript would benefit from a more explicit discussion of how different perturbations may shift the identity, composition, or coordination of the active neuronal ensemble rather than simply altering total activity levels.

    1. Reviewer #2 (Public review):

      Summary:

      In this manuscript, Palo et al present a novel role for FRG1 as a multifaceted regulator of nonsense-mediated mRNA decay (NMD). Through a combination of reporter assays, transcriptome-wide analyses, genetic models, protein-protein interaction studies, ubiquitination assays, and ribosome-associated complex analyses, the authors propose that FRG1 acts as a negative regulator of NMD by destabilizing UPF1 and associating with spliceosomal, EJC, and translation-related complexes. Overall, the data, while consistent with the authors' central conclusions, are undermined by several claims-particularly regarding structural roles and mechanistic exclusivity. To really make the claims presented, further experimental evidence would be required.

      Strengths:

      (1) The integration of multiple experimental systems (zebrafish and cell culture).

      (2) Attempts to go into a mechanistic understanding of the relationship between FGR1 and UPF1.

      Weaknesses:

      (1) Overstatement of FRG1 as a structural NMD component.

      Although FRG1 interacts with UPF1, eIF4A3, PRP8, and CWC22, core spliceosomal and EJC interactions (PRP8-CWC22 and eIF4A3-UPF3B) remain intact in FRG1-deficient cells. This suggests that, while FRG1 associates with these complexes, this interaction is not required for their assembly or structural stability. Without further functional or reconstitution experiments, the presented data are more consistent with an interpretation of FRG1 acting as a regulatory or accessory factor rather than a core structural component.

      (2) Causality between UPF1 depletion and NMD inhibition is not fully established.

      While reduced UPF1 levels provide a plausible explanation for decreased NMD efficiency, the manuscript does not conclusively demonstrate that UPF1 depletion drives all observed effects. Given FRG1's known roles in transcription, splicing, and RNA metabolism, alterations in transcript isoform composition and apparent NMD sensitivity may arise from mechanisms independent of UPF1 abundance. To directly link UPF1 depletion to altered NMD efficiency, rescue experiments testing whether UPF1 re-expression restores NMD activity in FRG1-overexpressing cells would be important.

      (3) Mechanism of FRG1-mediated UPF1 ubiquitination requires clarification.

      The ubiquitination assays support a role for FRG1 in promoting UPF1 degradation; however, the mechanism underlying this remains unexplored. The relationship between FRG1-UPF1 what role FRG1 plays in this is unclear (does it function as an adaptor, recruits an E3 ubiquitin ligase, or influences UPF1 ubiquitination indirectly through transcriptional or signaling pathways?).

      (4) Limited transcriptome-wide interpretation of RNA-seq data.

      Although the RNA-seq data analysis relies heavily on a small subset of "top 10" genes. Additionally, the criteria used to define NMD-sensitive isoforms are unclear. A more comprehensive transcriptome-wide summary-indicating how many NMD-sensitive isoforms are detected and how many are significantly altered-would substantially strengthen the analysis.

      (5) Clarification of NMD sensor assay interpretation.

      The logic underlying the NMD sensor assay should be explained more clearly early in the manuscript, as the inverse relationship between luciferase signal and NMD efficiency may be counterintuitive to readers unfamiliar with this reporter system. Inclusion of a schematic or brief explanatory diagram would improve accessibility.

      (6) Potential confounding effects of high MG132 concentration.

      The MG132 concentration used (50 µM) is relatively high and may induce broad cellular stress responses, including inhibition of global translation (its known that proteosome inhibition shuts down translation). Controls addressing these secondary effects would strengthen the conclusion that UPF1 stabilization specifically reflects proteasome-dependent degradation would be essential.

      (7) Interpretation of polysome co-sedimentation data.

      While the co-sedimentation of FRG1 with polysomes is intriguing, this approach does not distinguish between direct ribosomal association and co-migration with ribosome-associated complexes. This limitation should be explicitly acknowledged in the interpretation.

      (8) Limitations of PLA-based interaction evidence.

      The PLA data convincingly demonstrate close spatial proximity between FRG1 and eIF4A3; however, PLA does not provide definitive evidence of direct interaction and is known to be susceptible to artefacts. Moreover, a distance threshold of ~40 nm still allows for proteins to be in proximity without being part of the same complex. These limitations should be clearly acknowledged, and conclusions should be framed accordingly.

    1. Reviewer #2 (Public review):

      Zeng et al. report that Setdb1-/- embryos fail to extinguish the 1- and 2-cell embryo transcriptional program and have permanent expression of MERVL transposable elements. The manuscript is technically sound and well performed, but, in my opinion, the results lack conceptual novelty.

      (1) The manuscript builds on previous observations that: 1, Setbd1 is necessary for early mouse development, with knockout embryos rarely reaching the 8-cell stage; 2, SETB1 mediates H3K9me3 deposition at transposable elements in mouse ESCs; 3, SETB1silences MERVLs to prevent 2CLC-state acquisition in mouse ESCs. The strength of the current work is the demonstration that this is not due to a general transcriptional collapse; but otherwise, the findings are not surprising. The well-known (several Nature papers of years ago) crosstalk between m6A RNA modification and H3K9me3 in preventing 2CLC generation also partly compromises the novelty of this work.

      (2) The conclusions regarding H3K9me3 deposition are inferred based on previously reported datasets, but there is no direct demonstration.

      (3) The detection of chimeric transcripts is somewhat unreliable using short-read sequencing.

    1. Reviewer #2 (Public review):

      Summary:

      This manuscript explores a DNA fluorescent light up aptamer (FLAP) with the specific goal of comparing activity in vitro to that in bacterial cells. In order to achieve expression in bacteria, the authors devise an expression strategy based on retrons and test four different constructs with the aptamer inserted at different points in the retron scaffold.

      The initial version of this manuscript made several claims about the fluorescence activity of the aptamers in cells, and the observed fluorescence signal has now been found to result from cellular auto-fluorescence. Thus, all data regarding the function of the aptamers in cells have been removed.

      Negative data are important to the field, especially when it comes to research tools that may not work as many people think that they will. Thus, there would have been an opportunity here for the authors to dig into why the aptamers don't seem to work in cells.

      In the absence of insight into the negative result, the manuscript is now essentially a method for producing aptamers in cells. If this is the main thrust, then it would be beneficial for the authors to clearly outline why this is superior to other approaches for synthesizing aptamers.

    1. Reviewer #2 (Public review):

      The authors report results from behavioral data, fMRI recordings, and computer simulations during a conceptual navigation task. They report 3-fold symmetry in behavioral and simulated model performance, 3-fold symmetry in hippocampal activity, and 6-fold symmetry in entorhinal activity (all as a function of movement directions in conceptual space). The analyses seem thoroughly done, and the results and simulations are very interesting.

      [Editors' note: this version was assessed by the editors without consulting the reviewers further.]

    1. Reviewer #2 (Public review):

      (1) Summary and overall comments:

      This is an impressive and carefully executed methodological paper developing an SEM framework with substantial potential. The manuscript is generally very well written, and I particularly appreciated the pedagogical approach: the authors guide the reader step by step through a highly complex model, with detailed explanations of the structure and the use of path tracing rules. While this comes at the cost of length, I think the effort is largely justified given the technical audience and the novelty of the contribution.

      The proposed SEM aims to estimate cross-trait indirect genetic effects and assortative mating, using genotype and phenotype data from both parents and one offspring, and builds on the framework introduced by Balbona et al. While I see the potential interest of the model, it is still a bit unclear in which conditions I could use it in practice. However, this paper made a clear argument for the need for cross-traits models, which changed my mind on the topic (I would have accommodated myself with univariate models and only interpreted in the light of likely pleiotropy, but I am now excited by the potential to actually disentangle cross-traits effects).

      The paper is written in a way that makes me trust the authors' thoroughness and care, even when I do not fully understand every step of the model. I want to stress that I am probably not well-positioned to identify technical errors in the implementation. My comments should therefore be interpreted primarily from the perspective of a potential user of the method: I focus on what I understand, what I do not, and where I see (or fail to see) the practical benefits.

      For transparency, here is some context on my background. I have strong familiarity with the theoretical concepts involved (e.g., genetic nurture, gene-environment covariance, dynastic effects), and I have worked on those with PGS regressions and family-based comparison designs. My experience with SEM is limited to relatively simple models, and I have never used OpenMx. Reading this paper was therefore quite demanding for me, although still a better experience than many similarly technical papers, precisely because of the authors' clear effort to explain the model in detail. That said, keeping track of all moving parts in such a complex framework was difficult, and some components remain obscure to me.

      (2) Length, structure, and clarity:

      I do not object in principle to the length of the paper. This is specialized work, aimed at a relatively narrow audience, and the pedagogical effort is valuable. However, I think the manuscript would benefit from a clearer and earlier high-level overview of the model and its requirements. I doubt that most readers can realistically "just skim" the paper, and without an early hook clearly stating what is estimated and what data are required, some readers may disengage.

      In particular, I would suggest clarifying early on:

      • What exactly is estimated?

      For example, in the Discussion, the first two paragraphs seem to suggest slightly different sets of estimands: "estimate the effects of both within- and cross-trait AM, genetic nurture, VT, G-E covariance, and direct genetic effects." versus "model provides unbiased estimates of direct genetic effects (a and δ), VT effects (f), genetic nurture effects (ϕ and ρ), G-E covariance w and v, AM effects (μ), and other parameters when its assumptions are met." A concise and consistent summary of parameters would be helpful.

      • What data are strictly required?

      At several points, I thought that phenotypes for both parents were required, but later in the Discussion, the authors consider scenarios where parental phenotypes are unavailable. I found this confusing and would appreciate a clearer statement of what is required, what is optional, and what changes when data are missing.

      • Which parameters must be fixed by assumption, rather than estimated from the data?

      Relatedly, in the Discussion, the authors mention the possibility of adding an additional latent shared environmental factor across generations. It would help to clearly distinguish: - the baseline model, - the model actually tested in the paper, and - possible extensions.

      Making these distinctions explicit would improve accessibility.

      This connects to a broader concern I had when reading Balbona et al. (2021): at first glance, the model seemed readily applicable to commonly available data, but in practice, this was not the case. I wondered whether something similar applies here. A clear statement of what data structures realistically allow the model to be fitted would be very useful.

      I found the "Suggested approach for fitting the multivariate SEM-PGS model" in the Supplementary Information particularly helpful and interesting. I strongly encourage highlighting this more explicitly in the main manuscript. If the authors want the method to be widely used, a tutorial or at least a detailed README in the GitHub repository would greatly improve accessibility.

      Finally, while the pedagogical repetition can be helpful, there were moments where it felt counterproductive. Some concepts are reintroduced several times with slightly different terminology, which occasionally made me question whether I had misunderstood something earlier. Streamlining some explanations and moving more material to the SI could improve clarity without sacrificing rigor.

      (3) Latent genetic score (LGS) and the a parameter

      I struggled to understand the role of the latent genetic score (LGS), and I think this aspect could be explained more clearly. In particular, why is this latent genetic factor necessary? Is it possible to run the model without it?

      My initial intuition was that the LGS represents the "true" underlying genetic liability, with the PGS being a noisy proxy. Under that interpretation, I expected the i matrix to function as an attenuation factor. However, i is interpreted as assortative-mating-induced correlation, which suggests that my intuition is incorrect. Or should the parameter be interpreted as an attenuation factor?

      Relatedly, in the simulation section, the authors mention simulating both PGS and LGS, which confused me because the LGS is not a measured variable. I did not fully understand the logic behind this simulation setup.

      Finally, I was unsure whether the values simulated for parameter a in Figures 8-9 are higher than what would typically be expected given the current literature, though this uncertainty may reflect my incomplete understanding of a itself. I appreciated the Model assumptions section of the discussion, and I wonder if this should not be discussed earlier.

      (4) Vertical transmission versus genetic nurture

      I am not sure I fully understand the distinction between vertical transmission (VT) and genetic nurture as defined in this paper. From the Introduction, I initially had the impression that these concepts were used almost interchangeably, but Table 3 suggests they are distinct.

      Relatedly:

      • Why are ϕ and ρ not represented in the path diagram?

      • Are these parameters estimated in the model?

      The authors also mention that these parameters target different estimands compared to other approaches. It would be helpful to elaborate on this point. Relatedly, where would the authors expect dynastic effects to appear in this framework?

      (5) Univariate model and misspecification

      In the simulations where a univariate model is fitted to data generated under a true bivariate scenario, I have a few clarification questions.

      What is the univariate model used (e.g., Table 5)? Is it the same as the model described in Balbona et al. (2025)? Does it include an LGS?

      If the genetic correlation in the founder generation is set to zero, does this imply that all pleiotropy arises through assortative mating? If so, is this a realistic mechanism, and does it meaningfully affect the interpretation of the results?

      (6) Simulations

      Overall, I found the simulations satisfying to read; they largely test exactly the kinds of issues I would want them to test, and the rationale for these tests is clear.

      That said, I was confused by the notation Σ and did not fully understand what it represents.

      In the Discussion, the authors mention testing the misspecification of social versus genetic homogamy, but I do not recall this being explicitly described in the simulation section. They also mention this issue in the SI ("Suggested approach for fitting..."). I think it would be very helpful to include an example illustrating this form of misspecification.

      (7) Cross-trait specific limitations

      I am wondering - and I don't think this is addressed - what is the impact of the difference in the noisiness and the heritability of the traits used for this multivariate analysis?

      Using the example, the authors mention of BMI and EA, one could think that these two traits have different levels of noise (maybe BMI is self-reported and EA comes from a registry), and similarly for the GWAS of these traits, let's say one GWAS is less powered than the other ones. Does it matter? Should I select the traits I look at carefully in function of these criteria? Should I interpret the estimates differently if one GWAS is more powered than the other one?

    1. Reviewer #2 (Public review):

      Summary:

      This manuscript by Choubani et al presents a technically strong analysis of A/B compartment dynamics across interphase using cell-cycle-resolved Hi-C. By combining the elegant Fucci-based staging system with in situ Hi-C, the authors achieve unusually fine temporal resolution across G1, S, and G2, particularly within the short G1 phase of mESCs. The central finding that A/B compartment strength increases abruptly at the G1/S transition, stabilizes during S phase, and subsequently weakens toward G2 challenges the prevailing view that compartmentalization strengthens monotonically throughout interphase. The authors further propose that this "compartment maturation" is triggered by S-phase entry but occurs independently of active DNA synthesis, and that it involves a consolidation and large-scale reorganization of A-compartment domains.

      Strengths:

      Overall, this is a thoughtfully executed study that will be of broad interest to the 3D genome community. The data are of high quality, and the analyses are extensive, albeit not completely novel. In particular, previous work (Nagano et al 2017 and Zhang et al 2019) has shown that compartments are re-established after mitosis and strengthened during early interphase, and single-cell Hi-C studies have reported changes in compartment association across S phase. In particular, Nagano et al show that DNA replication correlates with a build-up of compartments, similar to what is presented here, with the authors' conclusion that compartment strength peaks in early S. The idea that it weakens toward G2, rather than continuing to strengthen, appears to be novel and differs from the prevailing framing in the literature.

      Weaknesses:

      That said, several aspects of the conceptual framing and interpretation would also benefit from further clarification, and the mechanistic interpretation of the reported compartment dynamics requires more careful positioning relative to established models of genome organization. Specific concerns are outlined below:

      (1) One of the major conclusions of the study is that compartment maturation does not require ongoing DNA replication. However, the interpretation would benefit from more precise wording. Thymidine arrest still permits licensing, replisome assembly, and other S-phase-associated chromatin changes upstream of bulk DNA synthesis. Therefore, their data, as presented, demonstrate independence from DNA synthesis per se, but not necessarily from the broader replication program. Please clarify this distinction in the text and interpretations throughout the manuscript.

      (2) A major conceptual issue that is not addressed at all is the well-established anti-correlation between cohesin-mediated loop extrusion and A/B compartmentalization. Numerous studies have shown that loss of cohesin or reduced loop extrusion leads to stronger compartment signals, whereas increased cohesin residence or enhanced extrusion weakens compartmentalization. Given this framework, an obvious alternative explanation for the authors' observations is that the abrupt increase in compartment strength at G1/S, and its decline toward G2, could reflect cell-cycle-dependent modulation of cohesin activity rather than a compartment-intrinsic "maturation" program.

      The manuscript does not explicitly consider this possibility, nor does it examine loop extrusion-related features (such as loop strength, insulation, or stripe patterns) across the same cell-cycle stages. Without discussing or analyzing this widely accepted model, it is difficult to distinguish whether the reported compartment dynamics represent a novel architectural mechanism or an indirect consequence of known changes in extrusion behavior during the cell cycle. I strongly encourage the authors to analyze their data to determine if they observe anti-correlated loop changes at the same time they observe compartment changes. Ideally, the authors would remove loop extrusion during interphase using well-established cohesin degrons available in mESCs and determine if the relative differences in compartment dynamics persist.

      (3) The proposed "peninsula-like" A-domain structures are inferred from ensemble Hi-C data and polymer modeling, rather than directly observed physical conformations. That is, single-cell imaging data clearly have shown that Hi-C (especially ensemble Hi-C) cannot uniquely specify physical conformations and that different underlying structures can produce similar contact patterns. The "peninsula" language, as written, risks being interpreted as a literal structural model rather than a conceptual visualization. Instead of risking this as just another nuanced Hi-C feature in the field, the authors could strengthen the manuscript by either (i) explicitly framing the peninsula model as a heuristic description of contact redistribution rather than a definitive physical architecture, or (ii) discussing alternative structural scenarios that could give rise to similar Hi-C patterns. Clarifying this distinction would improve the rigor and help readers better understand what aspects of A-compartment consolidation are directly supported by the data versus model-based extrapolations. For example, it would be useful to clarify whether the observed increase in long-range A-A contacts reflects spatial extension of internal A regions, changes in loop extrusion dynamics, increased compartment mixing within the A state, or population-averaged heterogeneity across alleles.

      (4) The extension of the analysis to additional cell types using HiRES single-cell data is a valuable addition and supports the idea that compartment maturation is not unique to mESCs. However, the limitations of these data, in particular, the limited phase resolution, in addition to the pseudo-bulk aggregation and variable coverage, should be emphasized more clearly in the main text. Framing these results as evidence for conservation in principle, rather than definitive proof of identical dynamics across tissues, would be a more appropriate framing.

    1. Reviewer #2 (Public review):

      Summary:

      This work advances our understanding of how TFIIH coordinates DNA melting and CTD phosphorylation during transcription initiation. The finding that untethered kinase activity becomes "unfocused," phosphorylating the CTD at ser5 throughout the coding sequence rather than being promoter-restricted, suggests that the TFIIH Core-Kinase linkage not only targets the kinase to promoters but also constrains its activity in a spatial and temporal manner.

      Strengths:

      The experiments presented are straightforward, and the models for coupling initiation and CTD phosphorylation and for the evolution of these linked processes are interesting and novel. The results have important implications for the regulation of initiation and CTD phosphorylation.

      Weaknesses:

      Additional data that should be easily obtainable and analysis of existing data would enable an additional test of the models presented and extract additional mechanistic insights.

    1. Reviewer #3 (Public review):

      Summary:

      This manuscript aims to explore how mutations in the PDC-3 3 β-lactamase alter its ability to bind and catalyse reactions of antibiotic compounds. The topic is interesting and the study uses MD simulations and to provide hypotheses about how the size of the binding site is altered by mutations that change the conformation and flexibility of two loops that line the binding pocket. Some greater consideration of the uncertainties and how the method choice affect the ability to compare equilibrium properties would strengthen the quantitative conclusions. While many results appear significant by eye, quantifying this and ensuring convergence would strengthen the conclusions.

      Strengths:

      The significance of the problem is clearly described the relationship to prior literature is discussed extensively.

      Comments on revised version:

      I am concerned that the authors state in the response to reviews that it is not possible to get error bars on values due to the use of the AB-MD protocol that guides the simulations to unexplored basins. Yet the authors want to compare these values between the WT and mutants. This relates to RMSD, RMSF, % H-bond and volume calculations. I don't accept that you cannot calculate an uncertainty on a time averaged property calculated across the entire simulation. In these cases you can either run repeat simulations to get multiple values on which to do statistical analysis, or you can break the simulation into blocks and check both convergence and calculate uncertainties.

      I note that the authors do provide error bars on the volumes, but the statistics given for these need closer scrutiny (I cant test this without the raw data). For example the authors have p<0.0001 for the following pair of volumes 1072 {plus minus} 158 and 1115 {plus minus} 242, or for SASA p<0.0001 is given for 2 identical numbers 155+/- 3.

      I also remain concerned about comparisons between simulations run with the AB-MD scheme. While each simulation is an equilibrium simulation run without biasing forces, new simulations are seeded to expand the conformational sampling of the system. This means that by definition the ensemble of simulations does not represent and equilibrium ensemble. For example, the frequency at which conformations are sampled would not be the same as in a single much longer equilibrium simulation. While you may be able to see trends in the differences between conditions run in this way, I still don't understand how you can compare quantitative information without some method of reweighing the ensemble. It is not clear that such a rewieghting exists for this methods, in which case I advise some more caution in the wording of the comparisons made from this data.

      At this stage I don't feel the revision has directly addressed the main comments I raised in the earlier review, although there is a stronger response to the comments of Reviewer #2.

    1. Reviewer #2 (Public review):

      Tran and colleagues report evidence supporting the expected yet undemonstrated interaction between the Pkd1 and Pkd2 gene products Pc1 and Pc2 and the Bicc1 protein in vitro, in mice, and collaterally, in Xenopus and HEK293T cells. The authors go on to convincingly identify two large and non-overlapping regions of the Bicc1 protein important for each interaction and to perform gene dosage experiments in mice that suggest that Bicc1 loss of function may compound with Pkd1 and Pkd2 decreased function, resulting in PKD-like renal phenotypes of different severity. These results led to examining a cohort of very early onset PKD patients to find three instances of co-existing mutations in PKD1 (or PKD2) and BICC1. Finally, preliminary transcriptomics of edited lines gave variable and subtle differences that align with the theme that Bicc1 may contribute to the PKD defects, yet are mechanistically inconclusive.

      These results are potentially interesting, despite the limitation, also recognized by the authors, that BICC1 mutations seem exceedingly rare in PKD patients and may not "significantly contribute to the mutational load in ADPKD or ARPKD". The manuscript has several intrinsic limitations that must be addressed.

      The manuscript contains factual errors, imprecisions, and language ambiguities. This has the effect of making this reviewer wonder how thorough the research reported and analyses have been.

      Comments on revision:

      My comments have been addressed.

    1. Reviewer #2 (Public review):

      Summary:

      In this study, Liu et al. investigated cortical network dynamics during movie watching using an energy landscape analysis based on a maximum entropy model. They identified perception- and attention-oriented states as the dominant cortical states during movie watching and found that transitions between these states were associated with inter-subject synchronization of regional brain activity. They also showed that distinct thalamic compartments modulated distinct state transitions. They concluded that cortico-thalamo-cortical circuits are key regulators of cortical network dynamics.

      Strengths:

      A mechanistic understanding of cortical network dynamics is an important topic in both experimental and computational neuroscience, and this study represents a step forward in this direction by identifying key cortico-thalamo-cortical circuits. The analytical strategy employed in this study, particularly the LASSO-based analysis, is interesting and would be applicable to other data types, such as task- and resting-state fMRI.

      Weaknesses:

      Due to issues related to data preprocessing, support for the conclusions remains incomplete. I also believe that a more careful interpretation of the "energy" derived from the maximum entropy model would greatly clarify what the analysis actually revealed.

      (1) Major Comment 1:

      I think the method used for binarization of BOLD activity is problematic in multiple ways.

      a) Although the authors appear to avoid using global signal regression (page 4, lines 114-118), the proposed method effectively removes the global signal. According to the description on page 4, lines 117-122, the authors binarized network-wise ROI signals by comparing them with the cross-network BOLD signal (i.e., the global signal): at each time point, network-wise ROI signals above the cross-network signal were set to 1, and the rest were set to −1. If I understand the binarization procedure correctly, this approach forces the cross-network signal to be zero (up to some noise introduced by the binarization of network-wise signals), which is essentially equivalent to removing the global signal. Please clarify what the authors meant by stating that "this approach maintained a diverse range of binarized cortical states in data where the global signal was preserved" (page 4, lines 121-122).

      b) The authors might argue that they maintained a diverse range of cortical states by performing the binarization at each time point (rather than within each network). However, I believe this introduces another problem, because binarizing network-wise signals at each time point distorts the distribution of cortical states. For example, because the cross-network signal is effectively set to zero, the network cannot take certain states, such as all +1 or all −1. Similarly, this binarization biases the system toward states with similar numbers of +1s and −1s, rather than toward unbalanced states such as (+1, −1, −1, −1, −1, −1). These constraints and biases are not biological in origin but are simply artifacts of the binarization procedure. Importantly, the energy landscape and its derivatives (e.g., hard/easy transitions) are likely to be affected by these artifacts. I suggest that the authors try a more conventional binarization procedure (i.e., binarization within each network), which is more robust to such artifacts.

      Related to this point, I have a question regarding Figure S1, in which the authors plotted predicted versus empirical state probabilities. As argued above, some empirical state probabilities should be zero because of the binarization procedure. However, in Figure S1, I do not see data points corresponding to these states (i.e., there should be points on the y-axis). Did the authors plot only a subset of states in Figure S1? I believe that all states should be included. The correlation coefficient between empirical and predicted probabilities (and the accuracy) should also be calculated using all states.

      c) The current binarization procedure likely inflates non-neuronal noise and obscures the relationship between the true BOLD signal and its binarized representation. For example, consider two ROIs (A and B): both (+2%, +1%) and (+0.01%, −0.01%) in BOLD signal changes would be mapped to (+1, −1) after binarization. This suggests that qualitatively different signal magnitudes are treated identically. I believe that this issue could be alleviated if the authors were to binarize the signal within each network, rather than at each time point.

      (2) Major Comment 2:

      As the authors state (page 5, lines 145-148), the "energy" described in the energy landscape is not biological energy but rather a statistical transformation of probability distributions derived from the Boltzmann distribution. If this is the case, I believe that Figure 2A is potentially misleading and should be removed. This type of schematic may give the false impression that cortical state dynamics are governed by the energy landscape derived from the maximum entropy model (which is not validated).

    1. Reviewer #2 (Public review):

      Summary:

      This work explores the phenotypic developmental traits associated with Cu and Cd responses in teosinte parviglumis, a species evolutionary related to extant maize crops. Cu and Cd could serve as a proxy for heavy metals present in the soils. The manuscript explores potential genetic loci associated with heavy metal responses and domestication. This includes heavy metal transporters which are unregulated during stress. To study that, authors compare the plant architecture of maize defective in ZmHMA1 and speculate on the association of heavy metals with domestication.

      Strengths:

      Very few studies covered the responses of teosintes to heavy metal stress. The physiological function of ZmHMA1 in maize is also valuable. The idea and speculation section is interesting and well-implemented.

      Weaknesses:

      Some conclusions are still speculative and future experiment could provide more clues about potential molecular mechanisms for the ideas proposed here.

    1. Reviewer #2 (Public review):

      Summary:

      The current research presents an end-to-end computational workflow for large-scale Imaging Mass Cytometry (IMC) data and applies it to 813 regions of interest (ROIs) comprising over 4 million cells from 63 TNBC patients. The study integrates image preprocessing (IMC-Denoise and CLAHE), cell segmentation (Mesmer), phenotyping (Pixie), spatial neighborhood analysis (SquidPy), collagen feature extraction, and graph neural network (GNN) modeling to identify spatial-molecular determinants of chemotherapy response. The major observations include T-cell exclusion in non-responders, persistent fibroblast-macrophage co-localization post-therapy, and the identification of B7H4, CD11b, CD366, and FOXP3 as predictive markers via GNN explainability analysis. The work has been implemented on a rich dataset and integrated with spatial and molecular information. The manuscript is well written and addresses an important clinical question.

      Strengths:

      (1) The study analyzes 813 ROIs and over 4 million cells, which is an exceptionally large IMC dataset, and allows the authors to investigate spatial determinants of chemotherapy response in TNBC with considerably more statistical power than prior studies. It clearly shows an integrated spatial-proteomic analysis on a large IMC dataset.

      (2) The work reveals robust, conceptually meaningful tissue patterns with CD8+ T-cell exclusion from tumor regions in non-responders and increased fibroblast-macrophage spatial proximity that align with existing biological understanding of immunosuppressive microenvironments in TNBC. These findings highlight spatial organization, rather than simple cell abundance, as a key differentiator of treatment response.

      (3) Novel use of GNNs for chemoresponse prediction in IMC data helps in demonstrating that spatial and molecular features captured simultaneously can provide predictive information about treatment response. The use of GNNExplainer adds interpretability of the selected features, identifying immune-regulatory markers such as B7H4, CD366, FOXP3, and CD11b as contributors to chemoresponse heterogeneity.

      (4) The work complements emerging spatial transcriptomic analyses from the same SMART cohort and provides a scalable computational framework likely to be useful to other IMC and spatial-omics researchers.

      Weaknesses:

      (1) Some analytical components lack quantitative validation, limiting confidence in specific claims, such as CLAHE-based batch correction applied before segmentation are evaluated primarily through qualitative visualization rather than quantitative metrics. Similarly, the cell-type annotations produced via Pixie and manual thresholds lack independent validation, making it harder to assess the accuracy of downstream spatial and predictive analyses.

      (2) Predictive modeling performance is moderate and may be influenced by dataset structure; the GNN achieves AUROC ~0.71, which is meaningful but still limited, and the absence of external validation or multiple cross-validation strategies raises questions about generalizability. The predictive insights are promising but not yet sufficiently strong to support clinical decision-making.

      (3) Pre- and post-treatment comparisons are constrained to non-responders and pathologist-selected ROIs.

    1. Reviewer #3 (Public review):

      The goal of the work is to establish the linkage between the spatial transcription factors (STF's) that function transiently to establish the identities of the individual NBs and the terminal selector genes (typically homeodomain genes) that appear in the new-born post-mitotic neurons. How is the identity of the NB maintained and carried forward after the spatial genes have faded away? Focusing on a single neuroblast (NB 7-1), the authors present evidence that the fork-head transcription factor, fd4, provides a bridge linking the transient spatial cues that initially specified neuroblast identity with the terminal selector genes that establish and maintain the identity of the stem cell's progeny.

      The study is systematic, concise and takes full advantage of 40+ years of work on the molecular players that establish neuronal identities in the Drosophila CNS. In the embryonic VNC, fd4 is expressed only in the NB 7-1 and its lineage. They show that Fd4 appears in the NB while the latter is still expressing the Spatial Transcription Factors and continues after the expression of the latter fades out. Fd4 is maintained through the early life of the neuronal progeny but then declines as the neurons turn on their terminal selector genes. Hence, fd4 expression is compatible with it being a bridging factor between the two sets of genes.

      Experimental support for the "bridging" role of Fd4 comes from set of loss-of-function and gain-of-function manipulations. The loss of function of fd4, and the partially redundant gene fd5, from lineage 7-1 does not affect the size of the lineage, but terminal markers of late-born neuronal phenotypes, like Eve and Dbx, are reduced or missing. By contrast, ectopic expression of fd4, but not fd5, results in ectopic expression of the terminal markers eve and dbx throughout diverse VNC lineages.

      A detailed test of fd4's expression was then carried out using lineages 7-3 and 5-6, two well characterized lineages in Drosophila. Lineage 7-3 is much smaller that 7-1 and continues to be so when subjected to fd4 misexpression. However, under the influence of ectopic fd4 expression, the lineage 7-3 neurons lost their expected serotonin and corazonin expression and showed Eve expression as well as motoneuron phenotypes that partially mimic the U motoneurons of lineage 7-1.

      Ectopic expression of Fd4 also produced changes in the 5-6 lineage. Expression of apterous, a feature of lineage 5-6 was suppressed, and expression of the 7-1 marker, Eve, was evident. Dbx expression was also evident in the transformed 5-6 lineages but extremely restricted as compared to a normal 7-1 lineage. Considering the partial redundancy of fd4 and fd5, it would have been interesting to express both genes in the 5-6 lineage. The anatomical changes that are exhibited by motoneurons in response to fd4 expression confirms that these cells do, indeed, show a shift in their cellular identity.

      Comments on revisions:

      The authors adequately addressed all of the issues that I had with the original submission.

      Their responses to the other reviewers are also well-reasoned

    1. Reviewer #2 (Public review):

      Summary:

      Wang et al. measure from 10 cortical and subcortical brain as mice learn a go/no-go visual discrimination task. They found that during learning, there is a reshaping of inter-areal connections, in which a visual-frontal subnetwork emerges as mice gain expertise. Also visual stimuli decoding became more widespread post-learning. They also perform silencing experiments and find that OFC and V2M are important for the learning process. The conclusion is that learning evoked a brain-wide dynamic interplay between different brain areas that together may promote learning.

      Strengths:

      The manuscript is written well and the logic is rather clear. I found the study interesting and of interest to the field. The recording method is innovative and requires exceptional skills to perform. The outcomes of the study are significant, highlighting that learning evokes a widespread and dynamics modulation between different brain areas, in which specific task-related subnetworks emerge.

      Weaknesses:

      I had some major concerns that make the claims of the study less convincing: Low number of mice, insufficient movement analysis, figure visualization and analytic methods.

      Nevertheless, I had several major concerns:

      (1) The number of mice was small for the ephys recordings. Although the authors start with 7 mice in Figure 1, they then reduce to 5 in panel F. And in their main analysis they minimize their analysis 6/7 sessions from 3 mice only. I couldn't find a rationale for this reduction, but in the methods they do mention that 2 mice were used for fruitless training, which I found no mention in the results. Moreover, in the early case all of the analysis is from 118 CR trials taken from 3 mice. In general, this is a rather low number of mice and trial numbers. I think it is quite essential to add more mice.

      (2) Movement analysis was not sufficient. Mice learning a go/no-go task establish a movement strategy that is developed throughout learning and is also biased towards Hit trials. There is an analysis of movement in Fig. S4 but this is rather superficial. I was not even sure that the 3 mice in Figure S4 are the same 3 mice in the main figure. There should be also an analysis of movement as a function of time to see differences. Also for Hits and FAs. I give some more details below. In general, most of the results can be explained by the fact that as mice gain expertise, they move more (also in CR during specific times) which leads to more activation in frontal cortex and more coordination with visual areas. More needs to be done in terms of analysis, or at least a mention of this in the text.

      (3) Most of the figures are over-detailed and it is hard to understand the take home message. Although the text is written succinctly and rather short, the figures are mostly overwhelming, especially figures 4-7. For example, Figure 4 presents 24 brain plots! For rank input and output rank during early and late stim and response periods, for early and expert and their difference. All in the same colormap. No significance shown at all. The Δrank maps for all cases look essentially identical across conditions. The division into early and late time periods is not properly justified. But the main take home message is positive Δrank in OFC, V2M, V1 and negative Δrank in ThalMD and Str. In my opinion, one trio maps is enough, and the rest could be bumped to the Supp, if at all. In general, the figures in several cases do not convey the main take home messages.

      (4) Analysis is sometimes not intuitive enough. For example, the rank analysis of input and output rank seemed a bit over complex. Figure 3 was hard to follow (although a lot of effort was made by the authors to make it clearer). Was there any difference between output and input analysis? Also time period seem sometimes redundant. Also, there are other network analysis that can be done which are a bit more intuitive. The use of rank within the 10 areas was not the most intuitive. Even a dimensionality reduction along with clustering can be used as an alternative. In my opinion, I don't think the authors should completely redo their analysis, but maybe mention the fact that other analyses exist.

      Reviewer comments to the authors' revision:

      Thank you for the extensive revision. Most of my concerns were answered and the manuscript is much improved. Still, there are some major issues that remain unconvincing:

      (1) The number of learning mice is only 3 which is substantially low as compared to other studies in the field. Thus, statistics are across trials and session pooled from all mice. This is a big limitation in supporting the authors' claims

      (2) There is no measurement of movement during the task. Since there are already several studies showing that movement has a strong effect on brain-wide dynamics, and since it is well known that mice change their body movement during learning (at least some mice) the authors cannot disentangle between learning-related and movement-related dynamics. This issue is properly discussed in the paper and also partially addressed with a control group where movement was measured without neural recordings.

      (3) The authors do not know exactly where they recorded from, with emphasis on subcortical areas. The authors partially address this in a separate cohort where they regenerate the reproducibility rate of penetration locations, but still this is not a complete address to this concern.

      Given the issues above, I strongly recommend including additional mice with body movement measurement in the future. Great job and congratulations on this study!

    1. Reviewer #2 (Public review):

      The study design involves infecting HaCaT cells (immortalised keratinocytes mimicking basal cells of a target tissue) and observing virus localization with and without actin polymerization inhibition by cytochalasin D (cytoD) to analyze virion transfer from the ECM to the cell via filopodial structures, using cellular proteins as markers.

      In the context of the model system, the authors stress in the revised version the importance of using HaCaT cells as a relevant 'polarized' cell model for infection. The term 'polarized' is used in the cell biological literature for epithelial cells to describe a strict apical vs. basolateral demarcation of the plasma membrane with an established diffusion barrier of the tight junction. However, HaCat cells do not form tight junctions. In squamous epithelia, such barriers are only found in granular layers of the epithelium. The published work cited in support of their claims either does not refer to polarity or only in the context of other cells such as CaCo-2 cells.

      Overall, the matter of polarity would be important, if indeed the virus could only access cell-associated HSPGs as primary binding receptor, or the elusive secondary receptor via the ECM in the used model system (HaCaT cells), if they would locate exclusively basolaterally. This is at least not the case for binding, as observed in several previous publications (just two examples: Becker et al, 2018, Smith et al., 2008). With only a rather weak attempt at experimental verification of their model system with regards to polarity of binding, the authors then go on to base their conclusions on this unverified assumption.

      This is one example of several in the manuscript, where claims for foundational premises, observations, and/or conclusions remain undocumented or not supported by experimental data.

      Another such example is the assumption of transfer of the virus from ECM to the tetraspanin CD151. Here, the conclusions are based on the poorly documented inability of the virus to bind to the cell body, which is in stark contrast to several previous publications, and raises questions. Thus, association with CD151 likely occurs both from ECM derived virus AND virus that binds to cells, so that any conclusions on the mode of association is possible only in live cell data (which is not provided). Overall, their proposed model thus remains largely unsubstantiated with regards to receptor switching.

      There are a number of important additional issues with the manuscript:

      First, none of the inhibitors have been tested in their system for efficacy and specificity, but rely on published work in other cell types. This considerably weakens the confidence on the conclusion drawn by the authors.

      Second, the authors aim to study transfer from ECM to the cell body and effects thereof. However, there are still substantial amounts of viruses that bind to the cell body compared to ECM-bound viruses in close vicinity to the cells. This is in part obscured by the small subcellular regions of interest that are imaged by STED microscopy, or by the use of plasma membrane sheets. This remains an issue despite the added Supple. Fig. 1, where also only sub cellular regions are being displayed. As a consequence the obtained data from time point experiments is skewed, and remains for the most part unconvincing, largely because the origin of virions in time and space cannot be taken into account. This is particularly important when interpreting the association with HS, the tetraspanin CD151, and integral alpha 6, as the low degree of association could be originating from cell bound and ECM-transferred virions alike.

      Third, the use of fixed images in a time course series also does not allow to understand the issue of a potential contribution of cell membrane retraction upon cytoD treatment due to destabilisation of cortical actin. Or, of cell spreading upon cytoD washout. The microscopic analysis uses an extension of a plasma membrane stain as marker for ECM bound virions, this may introduce a bias and skew the analysis.

      Fourth, while the use of randomisation during image analysis is highly recommended to establish significance (flipping), it should be done using only ROIs that have a similar density of objects for which correlations are being established. For instance, if one flips an image with half of the image showing the cell body, and half of the image ECM, it is clear that association with cell membrane structures will only be significant in the original. But given the high density of objects on the plasma membrane, I am not convinced that doing the same by flipping only the plasma membrane will not also obtain similar numbers than the original.

    1. Reviewer #2 (Public review):

      Summary:

      The goal of this manuscript was to examine whether neural indicators explain the relationship between cognition and mental health. The authors achieved this aim by showing that the combination of MRI markers better predicted the cognition-mental health covariation. I have reviewed the paper before and the authors addressed my comments very well.

      Strengths:

      Large sample (UK biobank data) and clear description of advanced analyses.

      Weaknesses:

      My main concern in my previous review was that it was not completely clear to me what it means to look at the overlap between cognition and mental health. The authors have addressed this in the current version.

    1. Reviewer #2 (Public review):

      Summary:

      In this study, Tulloch et al. developed two modified massively parallel reporter assays (MPRAs) and applied them to identify cis-regulatory modules (CRMs) - genomic regions that activate gene expression - controlling retinal gene expression. These CRMs usually function at specific developmental stages and in distinct cell types to orchestrate retinal development. Studying them provides insights into how retinal progenitor cells give rise to various retinal cell types.

      The first assay, named locus-specific MPRA (LS-MPRA), tests all genomic regions within 150-300 kb of the gene of interest, rather than relying on previously predicted candidate regulatory elements. This approach reduces potential bias introduced during candidate selection, lowers the cost of synthesizing a library of candidate sequences, and simplifies library preparation. The LS-MPRA libraries were electroporated into mouse retinas in vivo or ex vivo. To benchmark the method, the authors first applied LS-MPRA near stably expressed retinal genes (e.g., Rho, Cabp5, Grm6, and Vsx2), and successfully identified both known and novel CRMs. They then used LS-MPRA to identify CRMs in embryonic mouse retinas, near Olig2 and Ngn2, genes expressed in subsets of retinal progenitor cells. Similar experiments were conducted in chick retinas and postnatal mouse retinas, revealing some CRMs with conserved activity across species and developmental stages.

      Although the study identified CRMs with robust reporter activity in Olig2+ or Ngn2+ cells, the data do not provide sufficient evidence to support the claims that these CRMs regulate Olig2 or Ngn2, rather than other nearby genes, in a cell type-specific manner. For example, the authors propose that three regions (NR1/2/3) regulate Olig2 specifically in retinal progenitor cells based on: 1) the three regions are close to Olig2, 2) increased Olig2 expression and NR1/2/3 activity upon Notch inhibition, and 3) reporter activity observed in Olig2+ cells (though also present in many Olig2- cells). While these are promising findings, they do not directly support the claims.

      The second assay, called degenerate MPRA (d-MPRA), introduces random point mutations into CRMs via error-prone PCR to assess the impact of sequence variations on regulatory activity. This approach was used on NR1/2/3 to identify mutations that alter CRM activity, potentially by influencing transcription factor binding. The authors inferred candidate transcription factors, such as Mybl1 and Otx2, through motif analysis, co-expression with Olig2 (based on single-cell RNA-seq), and CUR&RUN profiling. While some transcription factors identified in this way overlapped with the d-MPRA results, others did not. This raises questions about how well d-MPRA complements other methods for identifying TF binding sites.

      Strengths:

      The study introduces two technically robust MPRA protocols that offer advantages over standard methods, such as avoiding reliance on predefined candidate regions, reducing cost and labor, and minimizing selection bias.

      The identified regulatory elements and transcription factors contribute to our understanding of gene regulation in retinal development and may have translational potential for cell type-specific gene delivery into developing retinas.

      Weakness:

      Like other MPRA-based approaches, LS-MPRA mainly tests whether a sequence can drive expression of a reporter gene in given cell type(s). However, this type of assay generally does not show which endogenous gene the sequence regulates. In this study, the evidence supporting gene-specific CRMs is largely correlative. The evidence for cell-type-specific CRMs is also not fully supported (e.g., reporter expression is observed in the intended cell type as well as additional cell types). If further validation in the native genomic context (e.g., CRISPRi of the candidate element followed by RNA-seq across relevant cell types) is out of scope, the manuscript should avoid wording that implies definitive target gene assignment or cell-type specificity.

    1. Reviewer #2 (Public review):

      This manuscript aims to elucidate the mechanistic basis for the long-standing observation that DNA methylation and the histone variant H2A.Z occupy mutually exclusive genomic regions. The authors test two hypotheses: (i) that DNA methylation intrinsically destabilizes H2A.Z nucleosomes, thereby preventing H2A.Z retention, and (ii) that DNA methylation suppresses H2A.Z deposition by ATP-dependent chromatin-remodelling complexes. However, neither hypothesis is rigorously addressed. There are experimental caveats, issues with data interpretation, and conclusions that are not supported by the data. Substantial revision and additional experiments, including controls, would be required before mechanistic conclusions can be drawn. Major concerns are as follows:

      (1) The cryo-EM structure of methylated H2A.Z nucleosomes is insufficiently resolved to address the central mechanistic question: where the methylated CpGs are located relative to DNA-histone contact points and how these modifications influence H2A.Z nucleosome structure. The structure provides no mechanistic insights into methylation-induced destabilization.

      The experimental system also lacks physiological relevance. The template DNA sequence is artificial, despite the existence of well-characterised native genomic sequences for which DNA methylation is known to inhibit H2A.Z incorporation. Alternatively, there are a number of studies examining the effect of DNA methylation on nucleosome structure, stability, DNA unwrapping, and positioning. Choosing one of these DNA sequences would have at least allowed a direct comparison with a canonical nucleosome. Indeed, a major omission is the absence of a cryo-EM structure of a canonical nucleosome assembled on the same DNA template - this is essential to assess whether the observed effects are H2A.Z-specific.

      Furthermore, the DNA template is methylated at numerous random CpG sites. The authors' argument that only the global methylation level is relevant is inconsistent with the literature, which clearly demonstrates that methylation effects on canonical nucleosomes are position-dependent. Not all CpG sites contribute equally to nucleosome stability or unwrapping, and this critical factor is not considered.

      Finally, and most importantly, the reported increase in accessibility of the methylated H2A.Z nucleosome is negligible compared with the much larger intrinsic DNA accessibility of the unmethylated H2A.Z nucleosome. These data do not support the authors' hypothesis and contradict the manuscript's conclusions. Claims that methylated H2A.Z nucleosomes are "more open and accessible" must therefore be removed, and the title is misleading, given that no meaningful impact of DNA methylation on H2A.Z nucleosome stability is demonstrated.

      (2) The cryo-EM structures of methylated and unmethylated 601L H2A.Z nucleosomes show no detectable differences. As presented, this negative result adds little value. If anything, it reinforces the point that the positional context of CpG methylation is critical, which the manuscript does not consider.

      (3) Very little H3 signal coincides with H2A.Z at TSSs in sperm pronuclei, yet this is neither explained nor discussed (Supplementary Figure 10D). The authors need to clarify this.

      (4) In my view, the most conceptually important finding is that H2A.Z-associated reads in sperm pronuclei show ~43% CpG methylation. This directly contradicts the model of strict mutual exclusivity and suggests that the antagonism is context-dependent. Similarly, the finding that the depletion of SRCAP reduces H2A.Z deposition only on unmethylated templates is also very intriguing. Collectively, these result warrants further investigation (see below).

      (5) Given that H2A.Z is located at diverse genomic elements (e.g., enhancers, repressed gene bodies, promoters), the manuscript requires a more rigorous genomic annotation comparing H2A.Z occupancy in sperm pronuclei versus XTC-2 cells. The authors should stratify H2A.Z-DNA methylation relationships across promoters, 5′UTRs, exons, gene bodies, enhancers, etc., as described in Supplementary Figure 10A.

      (6) Although H2A.Z accumulates less efficiently on exogenous methylated substrates in egg extract, substantial deposition still occurs (~50%). This observation directly challenges the strong antagonistic model described in the manuscript, yet the authors do not acknowledge or discuss it. Moreover, differences between unmethylated and methylated 601 DNA raise further questions about the biological relevance of the cryo-EM 601 structures.

      (7) The SRCAP depletion is insufficiently validated i.e., the antibody-mediated depletion of SRCAP lacks quantitative verification. A minimum of three biological replicates with quantification is required to substantiate the claims.

      (8) It appears that the role of p400-Tip60 has been completely overlooked. This complex is the second major H2A.Z deposition complex. Because p400 exhibits DNA methylation-insensitive binding (Supplementary Figure 14), it may account for the deposition of H2A.Z onto methylated DNA. This possibility is highly significant and must be addressed by repeating the key experiments in Figure 5 following p400-Tip60 depletion.

      (9) The manuscript repeatedly states that H2A.Z nucleosomes are intrinsically unstable; however, this is an oversimplification. Although some DNA unwrapping is observed, multiple studies show that H3/H4 tetramer-H2A.Z/H2B interactions are more stable (important recent studies include the following: DOI: 10.1038/s41594-021-00589-3; 10.1038/s41467-021-22688-x; and reviewed in 10.1038/s41576-024-00759-1).

      In summary, the current manuscript does not present a convincing mechanistic explanation for the antagonism between DNA methylation and H2A.Z. The observation that H2A.Z can substantially coexist with DNA methylation in sperm pronuclei, perhaps, should be the conceptual focus.

    1. Reviewer #2 (Public review):

      Summary:

      This paper investigates putative networks associated with prediction errors in task-based and resting state fMRI. It attempts to test the idea that prediction errors minimisation includes abstract cognitive functions, referred to as global prediction error hypothesis, by establishing a parallel between networks found in task-based fMRI where prediction errors are elicited in a controlled manner and those networks that emerge during "resting state".

      Strengths:

      Clearly a lot of work and data went into this paper, including 2 task-based fMRI experiments and the resting state data for the same participants, as well as a third EEG-fMRI dataset. Overall well written with a couple of exceptions on clarity as per below and the methodology appears overall sound, with a couple of exceptions listed below that require further justification. It does a good job of acknowledging its own weakness.

      Weaknesses:

      The paper does a good job of acknowledging its greatest weakness, the fact that it relies heavily on reverse inference, but cannot quite resolve it. As the authors put, "finding the same networks during a prediction error task and during rest does not mean that the networks engagement during rest reflect prediction error processing". Again, the authors acknowledge the speculative nature of their claims in the discussion, but given that this is the key claim and essence of the paper, it is hard to see how the evidence is compelling to support that claim.

      Given how uncontrolled cognition is during "resting-state" experiments, the parallel made with prediction errors elicited during a task designed to that effect is a little difficult to make. How often are people really surprised when their brains are "at rest", likely replaying a previously experienced event or planning future actions under their control? It seems to be more likely a very low prediction error scenario, if at all surprising.

      The quantitative comparison between networks under task and rest was done on a small subset of the ROIs rather than on the full network - why? Noting how small the correlation between task and rest is (r=0.021) and that's only for part of the networks, the evidence is a little tenuous. Running the analysis for the full networks could strengthen the argument.

      Looking at the results in Figure 2C, the four-quadrant description of the networks labelled for low and high PE appears a little simplistic. The authors state that this four-quadrant description omits some ROIs as motivated by prior knowledge. This would benefit from a more comprehensive justification. Which ROIs are excluded and what is the evidence for exclusion?

      The EEG-fMRI analysis claiming 3-6Hz fluctuations for PE is hard to reconcile with the fact that fMRI captures activity that is a lot slower while some PEs are as fast as 150 ms. The discussion acknowledges this but doesn't seem to resolve it - would benefit from a more comprehensive argument.

      Comments on revisions:

      The authors have done a good job of addressing the issues raised during the review process. There is one issue remaining that still required attention. In R2.4. when referring to "existing knowledge of prominent structural pathways among these quadrants" please cite the relevant literature.

    1. Reviewer #3 (Public review):

      The manuscript provides evidence that mice have a fusome, a conserved structure most well studied in Drosophila that is important for oocyte specification. Overall, a myriad of evidence is presented demonstrating the existence of a mouse fusome. This work is important as it addresses a long-standing question in the field of whether mice have fusomes and sheds light on how oocytes are specified in mammals.

      Comments on revisions:

      Overall, the authors did a good job of responding to reviewer comments that have improved the manuscript by including higher quality microscope images, revising text for clarity and using the term mouse fusome instead of using a new term. However, two of the headings in the results section that didn't correspond to the data presented in that section still have not been revised eventhough the authors stated that they were revised in their response to reviewer comments. The heading of the first section of the results is: "PGCs contain a Golgi-rich structure known as the EMA granule" even though no evidence in that section shows it is Golgi rich. The heading of the fifth section of the results is: "The mouse fusome associates with polarity and microtubule genes including pard3" however, only evidence for pard3 is presented.

    1. Reviewer #2 (Public review):

      In this manuscript, the authors present a model to explain how working memory (WM) encodes both existence and timing simultaneously using transient synaptic augmentation. A simple yet intriguing idea.

      The model presented here has the potential to explain what previous theories like 'active maintenance via attractors' and 'liquid state machine' do not, and describe how novel sequences are immediately stored in WM. Altogether, the topic is of great interest to those studying higher cognitive processes, and the conclusions the authors draw are certainly thought-provoking from an experimental perspective.

      Comments on revisions:

      The authors have done an excellent job of addressing the questions that I raised, and the manuscript is greatly improved - both in content and clarity. It is an insightful advance and I recommend publication.

    1. Reviewer #3 (Public review):

      Summary:

      The authors aimed to investigate how the brain processes different linguistic units (from phonemes to sentences) in challenging listening conditions, such as multi-talker environments, and how this processing differs between individuals with normal hearing and those with hearing impairments. Using a hierarchical language model and EEG data, they sought to understand the neural underpinnings of speech comprehension at various temporal scales and identify specific challenges that hearing-impaired listeners face in noisy settings.

      Strengths:

      Overall, the combination of computational modeling, detailed EEG analysis, and comprehensive experimental design thoroughly investigates the neural mechanisms underlying speech comprehension in complex auditory environments.

      The use of a hierarchical language model (HM-LSTM) offers a data-driven approach to dissect and analyze linguistic information at multiple temporal scales (phoneme, syllable, word, phrase, and sentence). This model allows for a comprehensive neural encoding examination of how different levels of linguistic processing are represented in the brain.

      The study includes both single-talker and multi-talker conditions, as well as participants with normal hearing and those with hearing impairments. This design provides a robust framework for comparing neural processing across different listening scenarios and groups.

      Weaknesses:

      The study tests only a single deep neural network model for extracting linguistic features, which limits the robustness of the conclusions. A lower model fit does not necessarily indicate that a given type of information is absent from the neural signal-it may simply reflect that the model's representation was not optimal for capturing it. That said, this limitation is a common concern for data-driven, correlation-based approaches, and should be viewed as an inherent caveat rather than a critical flaw of the present work.

    1. Reviewer #2 (Public review):

      Summary:

      Tagoe and colleagues present a thorough analysis of the calcium (Ca2+) binding capacity of calreticulin (CRT), an endoplasmic reticulum (ER) Ca2+-buffer protein, using a mutant version (CRT del52) found in myeloproliferative neoplasms (MPNs). The authors use purified human CRT protein variants, CRT-KO cell lines, and an MPN cell line to elucidate the differing Ca2+ dynamics, both on the level of the protein and on cell-wide Ca2+-governed processes. In sum, the authors provide new insights into CRT that can be applied to both normal and malignant cell biology.

      First, the authors purify CRT protein and perform isothermal titration calorimetry to quantify the Ca2+ binding capacity of CRT. They use full-length human CRT, CRT del52, and two truncations of CRT (1-339 and 1-351, the former of which should lead to the entire loss of low-affinity Ca2+ binding). While CRT del52 has previously been shown to lead to a decrease in Ca2+ binding affinity in other models, the ITC data show that this is retained in CRT del52.

      Next, the authors utilize a CRT-KO cell line with subsequent addition of CRT protein variants to validate these findings with flow cytometric analysis. Cells were transfected with a ratiometric ER Ca2+ probe, and fluorescence indicates that CRT del52 is unable to restore basal ER Ca2+ levels to the same extent as CRT wild-type. To translate these findings to MPNs, the authors perform CRT-KO in a megakaryocytic cell line, where reconstitution with either CRT variant did not cause a difference in cytosolic calcium levels. The authors further test store-operated calcium entry (SOCE), an important process for maintaining ER Ca2+ levels, in these cells, and find that CRT-KO cells have lower SOCE activity, and that this can be slightly recovered with CRT addition.

      Finally, the authors ask whether other effects of CRT-KO/reconstitution can affect the cellular Ca2+ signaling pathway and levels. RNASeq analysis revealed that CRT-KO leads to an increase in various chaperone protein expressions, and that reconstitution with CRT del52 is unable to reduce expression to the same extent as reconstitution with CRT wildtype.

      Strengths:

      The authors provide new insights into CRT that can be applied to both normal and malignant cell biology.

      Weaknesses:

      (1) The authors should consider discussing the high-affinity Ca2+ binding site more in the introduction. Can they show a proof-of-concept experiment that validates that incubation of recombinant CRT reduces the function of that high-affinity Ca2+ binding site?

      (2) For Figure 2B, do you have an explanation for why the purified proteins run higher than predicted (48-52kDa) - are these proteins still tagged with pGB1?

      (3) The MEG-01 cell line has the BCR::ABL1 translocation, while CRT mutations are strictly found in BCR::ABL1 negative MPNs. Could these experiments be repeated in these cells treated with imatinib to decrease these effects, or see if basal MEG-01 Ca2+ levels/activity are changed with or without imatinib?

    1. Reviewer #2 (Public review):

      Summary:

      Sullivan and colleagues studied the fast, involuntary, sensorimotor feedback control in interpersonal coordination. Using a cleverly designed joint-reaching experiment that separately manipulated the accuracy demands for a pair of participants, they demonstrated that the rapid visuomotor feedback response of a human participant to a sudden visual perturbation is modulated by his/her partner's control policy and cost. The behavioral results are well-matched with the predictions of the optimal feedback control framework implemented with the dynamic game theory model. Overall, the study provides an important and novel set of results on the fast, involuntary feedback response in human motor control, in the context of interpersonal coordination.

      Review:

      Sullivan and colleagues investigated whether fast, involuntary sensorimotor feedback control is modulated by the partner's state (e.g., cost and control policy) during interpersonal coordination. They asked a pair of participants to make a reaching movement to control a cursor and hit a target, where the cursor's position was a combination of each participant's hand position. To examine fast visuomotor feedback response, the authors applied a sudden shift in either the cursor (experiment 1) or the target (experiment 2) position in the middle of movement. To test the involvement of partner's information in the feedback response, they independently manipulated the accuracy demand for each participant by varying the lateral length of the target (i.e., a wider/narrower target has a lower/higher demand for correction when movement is perturbed). Because participants could also see their partner's target, they could theoretically take this information (e.g., whether their partner would correct, whether their correction would help their partner, etc.) into account when responding to the sudden visual shift. Computationally, the task structure can be handled using dynamic game theory, and the partner's feedback control policy and cost function are integrated into the optimal feedback control framework. As predicted by the model, the authors demonstrated that the rapid visuomotor feedback response to a sudden visual perturbation is modulated by the partner's control policy and cost. When their partner's target was narrow, they made rapid feedback corrections even when their own target was wide (no need for correction), suggesting integration of their partner's cost function. Similarly, they made corrections to a lesser degree when both targets were narrower than when the partner's target was wider, suggesting that the feedback correction takes the partner's correction (i.e., feedback control policy) into account.

      The strength of the current paper lies in the combination of clever behavioral experiments that independently manipulate each participant's accuracy demand and a sophisticated computational approach that integrates optimal feedback control and dynamic game theory. Both the experimental design and data analysis sound good. While the main claim is well-supported by the results, the only current weakness is the lack of discussion of limitations and an alternative explanation. Adding these points will further strengthen the paper.

    1. 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 data alone are valuable, 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. Collectively, the various analyses and rich illustrations provide superficially convincing evidence in favour of the conclusions.

      Weaknesses:

      (1) The work was not pre-registered, and there is no sample size justification, whether for participants or trials/sequences. So a statistical reviewer should assess the sensitivity of the analyses to different approaches.

      (2) Frequentist NHST is used to claim lack of effects, which is inappropriate, see for instance:

      Greenland, S., Senn, S. J., Rothman, K. J., Carlin, J. B., Poole, C., Goodman, S. N., & Altman, D. G. (2016). Statistical tests, P values, confidence intervals, and power: A guide to misinterpretations. European Journal of Epidemiology, 31(4), 337-350. https://doi.org/10.1007/s10654-016-0149-3

      Rouder, J. N., Morey, R. D., Verhagen, J., Province, J. M., & Wagenmakers, E.-J. (2016). Is There a Free Lunch in Inference? Topics in Cognitive Science, 8(3), 520-547. https://doi.org/10.1111/tops.12214

      (3) In the frequentist realm, demonstrating similar effects between groups requires equivalence testing, with bounds (minimum effect sizes of interest) that should be pre-registered:

      Campbell, H., & Gustafson, P. (2024). The Bayes factor, HDI-ROPE, and frequentist equivalence tests can all be reverse engineered-Almost exactly-From one another: Reply to Linde et al. (2021). Psychological Methods, 29(3), 613-623. https://doi.org/10.1037/met0000507

      Riesthuis, P. (2024). Simulation-Based Power Analyses for the Smallest Effect Size of Interest: A Confidence-Interval Approach for Minimum-Effect and Equivalence Testing. Advances in Methods and Practices in Psychological Science, 7(2), 25152459241240722. https://doi.org/10.1177/25152459241240722

      (4) The lack of consideration for sample sizes, the lack of pre-registration, and the lack of a method to support the null (a cornerstone of this project to demonstrate equivalence onsets between areas), suggest that the work is exploratory. This is a strength: we need rich datasets to explore, test tools and generate new hypotheses. I strongly recommend embracing the exploration philosophy, and removing all inferential statistics: instead, provide even more detailed graphical representations (include onset distributions) and share the data immediately with all the pre-processing and analysis code.

      (5) Even if the work was pre-registered, it would be very difficult to calculate p-values conditional on all the uncertainty around the number of participants, the number of contacts and the number of trials, as they are random variables, and sampling distributions of key inferences should be integrated over these unknown sources of variability. The difficulty of calculating/interpreting p-values that are conditional on so many pre-processing stages and sources of uncertainty is traditionally swept under the rug, but nevertheless well documented:

      Kruschke, J.K. (2013) Bayesian estimation supersedes the t test. J Exp Psychol Gen, 142, 573-603. https://pubmed.ncbi.nlm.nih.gov/22774788/

      Wagenmakers, E.-J. (2007). A practical solution to the pervasive problems of p values. Psychonomic Bulletin & Review, 14(5), 779-804. https://doi.org/10.3758/BF03194105<br /> https://link.springer.com/article/10.3758/BF03194105

      (6) Currently, there is no convincing evidence in the article to clearly support the main claims.

      Bootstrap confidence intervals were used to provide measures of uncertainty. However, the bootstrapping did not take the structure of the data into account, collapsing across important dependencies in that nested structure: participants > hemispheres > contacts > conditions > trials.

      Ignoring data dependencies and the uncertainty from trials could lead to a distorted CI. Sampling contacts with replacement is inappropriate because it breaks the structure of the data, mixing degrees of freedom across different levels of analysis. The key rule of the bootstrap is to follow the data acquisition process, and therefore, sampling participants with replacement should come first. In a hierarchical bootstrap, the process can be repeated at nested levels, so that for each resampled participant, then contacts are resampled (if treated as a random variable), then trials/sequences are resampled, keeping paired measurements together (hemispheres, and typically contacts in a standard EEG experiment with fixed montage). The same hierarchical resampling should be applied to all measurements and inferences to capture all sources of variability. Selectivity and timing should be quantified at each contact after resampling of trials/sequences before integrating across hemispheres and participants using appropriate and justified summary measures.

      The authors already recognise part of the problem, as they provide within-participant analyses. This is a very good step, inasmuch as it addresses the issue of mixing-up degrees of freedom across levels, but unfortunately these analyses are plagued with small sample sizes, making claims about the lack of differences even more problematic--classic lack of evidence == evidence of absence fallacy. In addition, there seem to be discrepancies between the mean and CI in some cases: 15 [-20, 20]; 8 [-24, 24].

      (7) Three other issues related to onsets:

      (a) FDR correction typically doesn't allow localisation claims, similarly to cluster inferences:

      Winkler, A. M., Taylor, P. A., Nichols, T. E., & Rorden, C. (2024). False Discovery Rate and Localizing Power (No. arXiv:2401.03554). arXiv. https://doi.org/10.48550/arXiv.2401.03554

      Rousselet, G. A. (2025). Using cluster-based permutation tests to estimate MEG/EEG onsets: How bad is it? European Journal of Neuroscience, 61(1), e16618. https://doi.org/10.1111/ejn.16618

      (b) Percentile bootstrap confidence intervals are inaccurate when applied to means. Alternatively, use a bootstrap-t method, or use the pb in conjunction with a robust measure of central tendency, such as a trimmed mean.

      Rousselet, G. A., Pernet, C. R., & Wilcox, R. R. (2021). The Percentile Bootstrap: A Primer With Step-by-Step Instructions in R. Advances in Methods and Practices in Psychological Science, 4(1), 2515245920911881. https://doi.org/10.1177/2515245920911881

      (c) Defining onsets based on an arbitrary "at least 30 ms" rule is not recommended:

      Piai, V., Dahlslätt, K., & Maris, E. (2015). Statistically comparing EEG/MEG waveforms through successive significant univariate tests: How bad can it be? Psychophysiology, 52(3), 440-443. https://doi.org/10.1111/psyp.12335

      (8) Figure 5 and matching analyses: There are much better tools than correlations to estimate connectivity and directionality. See for instance:

      Ince, R. A. A., Giordano, B. L., Kayser, C., Rousselet, G. A., Gross, J., & Schyns, P. G. (2017). A statistical framework for neuroimaging data analysis based on mutual information estimated via a Gaussian copula. Human Brain Mapping, 38(3), 1541-1573. https://doi.org/10.1002/hbm.23471

      (9) Pearson correlation is sensitive to other features of the data than an association, and is maximally sensitive to linear associations. Interpretation is difficult without seeing matching scatterplots and getting confirmation from alternative robust methods.

    1. Reviewer #2 (Public review):

      Summary:

      This compelling study proposes a framework to implement latent variable models using population level calcium imaging data. The study incorporates autoregressive dynamics and latent Poisson spiking to improve inference of latent states across different model classes including HMMs, Gaussian Process Factor Analysis and nonlinear dynamical systems models. This approach allows for a more seamless integration of existing methods typically used with spiking data to apply on calcium imaging data. The authors test the model on piriform cortex recordings as well as a biophysical simulator to validate their methods. This approach promises to have wide usability for neuroscientists using large population level calcium imaging.

      Strengths:

      The strengths of this study are the flexibility in the choice of models and relatively easy adaptation to user-specific use cases.

      Weaknesses:

      The weakness of the study lies in its limited validation of biological calcium imaging data. Calcium dynamics in a task-specific context in a sensory brain region might be very different from slower dynamics in a region of integration. The biophysical properties of the data would also be dependent on the SNR of the imaging platform and the generation of calcium indicator being used.

    1. Reviewer #2 (Public review):

      Summary:

      Nian and colleagues comprehensively apply metabolomics, molecular, and genetic approaches to demonstrate that CLas hijacks the DA/DcDop2-miR-31a-AKH-JH signaling cascade to enhance lipid metabolism and fecundity in D. citri, while concurrently promoting its own replication.

      Strengths:

      These findings provide solid evidence of a mutualistic interaction between CLas proliferation and ovarian development in the insect host. This insight significantly advances our understanding of the molecular interplay between plant pathogens and vector insects, and offers novel targets and strategies for HLB field management.

      Weaknesses:

      While the article investigates the involvement of dopamine signaling and specific microRNAs in enhancing fecundity and pathogen proliferation, it still needs to provide a detailed mechanistic understanding of these interactions. The precise molecular pathways and feedback mechanisms by which CLas manipulates dopamine signaling in Diaphorina citri remain unclear.

    1. 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.

      Strength:

      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.

    1. Cortisol plays a key role in mobilizing substances needed for cellular metabolism and stimulates gluconeogenesis or the formation of glucose from noncarbohydrate sources, such as amino acids or free fatty acids in the liver. In addition, cortisol enhances the elevation of blood glucose levels that is promoted by other hormones, such as epinephrine, glucagon, and growth hormone. The effects of cortisol are considered to be permissive for the actions of other hormones. Cortisol also inhibits the uptake and oxidation of glucose by many body cells. Overall, the cortisol-induced increase in carbohydrate metabolism serves to energize the body to cope with the stressor.

      A middle-aged female is presented with COPD, respiratory failure, and prediabetes is being treated with systemic corticosteroids for acute bronchitis. Since starting steroid therapy, her blood glucose levels have remained around 190 mg/dL, and she has a slow-healing wound on her arm. She does not normally require insulin. Which pathophysiological mechanism best explains the delayed wound healing in this patient?

      A. Cortisol activation leads to increased insulin sensitivity and enhanced collagen production.

      B. Elevated cortisol levels cause insulin resistance, impaired leukocyte function, and decreased collagen synthesis.

      C. Acute hypoglycemia resulting in reduced tissue perfusion and delayed cellular repair.

      D. Increased parasympathetic nervous system activity causing accelerated tissue regeneration.

    1. Reviewer #2 (Public review):

      Summary:

      In this study, Geurts et al. investigated the effects of the catecholamine reuptake inhibitor methylphenidate (MPH) on value-based decision making using a combination of aversive and appetitive Pavlovian to Instrumental Transfer (PIT) in a human cohort. Using an elegant behavioural design they showed a valence- and action-specific effects of Pavlovian cues on instrumental responses. Initial analyses showed no effect of MPH on these processes. However the authors performed a more in-depth analysis and demonstrated that MPH actually modulates PIT in action-specific manner, depending on individual working memory capacities. The authors interpret that as an effect on cognitive control of Pavlovian biasing of actions and decision-making more than an invigoration of motivational biases.

      Strengths:

      A major strength a this study is its experimental design. The elegant combination of appetitive and aversive Pavlovian learning with approach/avoidance instrumental actions allows the authors to precisely investigate the differential modulation of value-based decision making, depending on the context and environmental stimuli. Importantly, MPH was only administered after Pavlovian and instrumental learning, restricting the effect to PIT performance only. Finally, the use of a placebo-controlled crossover design allows within-comparisons between the PIT effect under placebo and MPH and the investigation of the relationships between working memory abilities, PIT and MPH effects.

      Weaknesses:

      Previous weaknesses regarding the neurobiological circuits underlying such effects and the possible role of dopamine vs noradrenaline have been clearly discussed in the new version of the manuscript.

      Comments on revisions:

      The authors answered my previous points. The changes to the manuscript clearly improve the clarity of the results and the strength of the study.

    1. Reviewer #2 (Public review):

      Summary:

      With this report, I suggest what are in my opinion crucial additions to the otherwise very interesting and credible research manuscript "Cluster size determines morphology of transcription factories in human cells".

      Strengths:

      The manuscript in itself is technically sound, the chosen simulation methods are completely appropriate the figures are well-prepared, the text is mostly well-written spare a few typos. The conclusions are valid and would represent a valuable conceptual contribution to the field of clustering, 3D genome organization and gene regulation related to transcription factories, which continues to be an area of most active investigation.

      Weaknesses:

      However, I find that the connection to concrete biological data is weak. This holds especially given that the data that are needed to critically assess the applicability of the derived cross-over with factory size is, in fact, available for analysis, and the suggested experiments in the Discussion section are actually done and their results can be exploited. In my judgement, unless these additional analysis are added to a level that crucial predictions on TF demixing and transcriptional bursting upon TU clustering can be tested, the paper is more fitted for a theoretical biophysics venue than for a biology journal such as eLife.

      Comments on revisions:

      The authors have addressed my comments with exemplary diligence, which has clarified all my major concerns. In all cases, either the relevant work was added, or it was explained in the form of a convincing argument why the suggested modifications were not implemented or not possible to implement.

      As a discretionary suggestion, the authors might consider using a title that even more directly highlights the, in my opinion, main take-away of this work. This is not because anything is incorrect about the current title, simply an even more to-the-point title might attract more readers. I would suggest something along the lines of

      "Cluster size-dependent demixing drives specialization of transcription factories"

      Overall, I congratulate the authors on their excellent work and appreciate the opportunity to engage with this manuscript during a very insightful review process.

    1. Reviewer #2 (Public review):

      Summary:

      The intracellular pathogen Toxoplasma gondii scavenges metal ions such as iron and zinc to support its replication; however, mechanistic studies of iron and zinc uptake are limited. This study investigates the function of a putative iron and zinc transporter, ZFT. In this paper, the authors provide evidence that ZFT mediates iron and zinc uptake by examining the regulation of ZFT expression by iron and zinc levels, the impact of altered ZFT expression on iron sensitivity, and the effects of ZFT depletion on intracellular iron and zinc levels in the parasite. The effects of ZFT depletion on parasite growth are also investigated, showing the importance of ZFT function for the parasite.

      Strengths:

      A key strength of the study is the use of multiple complementary approaches to demonstrate that ZFT is involved in iron and zinc uptake. The heterologous expression of ZFT in a Xenopus oocyst system where ZFT was shown to transport iron and zinc is an important addition to the study. The authors also build on their finding that loss of ZFT impairs parasite growth by showing that ZFT depletion induces stage conversion and leads to defects in both the apicoplast and mitochondrion.

      Weaknesses:

      The inclusion of the data showing iron and zinc transport when ZFT is expressed in a Xenopus oocyst system alleviated one of the main weaknesses of the original paper - the lack of direct biochemical evidence that ZFT acted as an iron transporter.

    1. Reviewer #2 (Public review):

      Summary:

      The manuscript titled "Activation of the Spx redox sensor counters cysteine-driven Fe(II) depletion under disulfide stress" by Hall and colleagues describes that an active redox switch is required for surviving under the diamide-induced disulfide stress. Furthermore, the SpxC10A mutant exhibits transcriptional dysregulation of genes involved in thiol maintenance and disulfide repair. The authors further demonstrate a role for Spx in regulating the uptake of L-cysteine, which otherwise leads to the chelation of intracellular iron and thus the repression of growth.

      Strengths:

      The authors demonstrate that the SpxC10A mutant accumulates high levels of thiols, leading to the chelation of intracellular iron and subsequent repression of the SpxC10A mutant's growth.

      Weaknesses:

      The authors did not show a direct regulation of L-cysteine uptake through CymR.

    1. Reviewer #2 (Public review):

      Summary:

      This work is important in my view because it complements other single-molecule mechanics approaches, in particular optical trapping, which inevitably exerts off-axis loads. The nanospring method has its own weaknesses (individual steps cannot be seen), but it brings new clarity to our picture of KIF1A and will influence future thinking on the kinesins-3 and on kinesins in general.

      Strengths:

      By tethering single copies of the kinesin-3 dimer under test via a DNA nanospring to a strong binding mutant dimer of kinesin-1, the forces developed and experienced by the motor are constrained into a single axis, parallel to the microtubule axis. The method is imaging-based which should improve accessibility. In principle, at least, several single-motor molecules can be simultaneously tested. The arrangement ensures that only single molecules can contribute. Controls establish that the DNA nanospring is not itself interacting appreciably with the microtubule. Forces are convincingly calibrated and reading the length of the nanospring by fitting to the oblate fluorescent spot is carefully validated. The excursions of the wild type KIF1A leucine zipper-stabilised dimer are compared with those of neuropathic KIF1A mutants. These mutants can walk to a stall plateau, but the force is much reduced. The forces from mutant/WT heterodimers are also reduced.

      Weaknesses:

      The tethered nanospring method has some weaknesses; it only allows the stall force to be measured in the case that a stall plateau is achieved, and the thermal noise means that individual steps are not apparent. The nanospring does not behave like a Hookean spring - instead linearly increasing force is reported by exponentially smaller extensions of the nanospring under tension. The estimated stall force for Kif1A (3.8 pN) is in line with measurements made using 3 bead optical trapping, but those earlier measurements were not of a stall plateau, but rather of limiting termination (detachment) force, without a stall plateau.

      Comments on revisions:

      The authors have successfully addressed my previous criticisms.

    1. Reviewer #2 (Public review):

      Summary:

      In this study, Blanco-Ameijeiras and colleagues present the use of stem cells to create human spinal cord organoids that recapitulate anterior-posterior identity, with a large focus on posterior fates. In particular, the authors show robust transcriptional landscape specification that reflects certain anterior-posterior spinal cord development.

      Recapitulation of spinal cord development is essential to understand the fundamentals of developmental defects in a systematic manner. This work provides a broad approach to test certain aspects of neural tube morphogenesis, particularly posterior and dorsal identities. Perhaps the shorter protocol is an interesting upgrade for current standards, and the mechanical interpretation provides good proof of concept work that aligns with the need to better understand neural tube mechanobiology.

      Strengths:

      The manuscript addresses a major gap by focusing on posterior spinal cord identity and secondary neurulation, a phase that is less well captured by existing neural tube organoid models (although some do recapitulate that). The manuscript situates the approach within vertebrate development and human embryology.

      Morphometric quantifications are well described and provide a dynamic interpretation of cell-level interpretation, and that is a true strength of the work. This is important to develop important metrics that can later be used to compare modulations and pathway disruption.

      The protocols are well described and documented.

      Weaknesses:

      Some key data lacks proper quantification to robustly support the claims. For example, it is not clear how many organoids in total are counted in Figure 1D to derive the % of organoids expressing certain markers (e.g. SOX2 or BRA).

      Some claims are overstated. In the manuscript, the organoids show primarily dorsal and posterior identities under the current conditions, yet the discussion sometimes reads as if a more complete dorsoventral recapitulation is achieved. Therefore, one can either demonstrate ventral patterning (e.g., SHH / FOXA2) or reduce the claims about spinal cord identity, which, given the results, are more specific to a particular region.

      The mention of anterior organoids seems to distract the reader from the important work, which primarily focuses on the posterior identity. Further, it is not understood why SOX2 identity is reduced by Day 7 in Figure 1D. Since SOX2 in the manuscript is considered a neural marker (although also pluripotency along with NANOG, etc.), a further explanation should be provided. The author should also test the presence of PAX6, which is one of the earliest neuroectoderm markers in humans (Zhang X. et al., Cell Stem Cell 2010).

      The authors position the work as a substantial addition to the field. The work is very much welcomed; however, some claims align with an interpretation that leads the readers to understand a novelty that is beyond the work presented here. For example, in certain instances in the intro, the manuscript conveys that this work consists of the first recapitulation of spinal cord fates anterior or posterior, while other works (Rifes P. Nature Cell Biology 2020, Xue X. Nature 2024) recapitulate dorsoventral and anterior-posterior patterning and identity (albeit not of secondary neurulation) through controlled gradients of WNT and RA activity. To clearly position the importance of this work, the intro should focus on secondary neurulation and posterior identities.

      In a similar fashion, the claim that "Importantly though, to our knowledge these are the first neural organoids exhibiting a robust spinal cord transcriptome identity" is not very well understood when other neural tube organoid systems (including spinal cord identities) have been exhaustively profiled at the single cell level (Rifes P. Xue X. Abdel Fattah A.). Further explanation is therefore needed.

      The mechanical angle is important and adds to the large body of research that traces NT morphogenesis to mechanics. However, the YAP localization images can be much improved. Lower magnification images are needed to show the entire organoid to robustly convince the reader of the correct and varying localization of the YAP protein. The authors should also check for YAP-associated genes in their bulk RNA sequencing.

      The quantification of the YAP analysis in a total of 23 and 18 cells in the two conditions and in 7 organoids is by no means enough to draw a conclusion about YAP localization, and an increase in the number of cells is needed. Moreover, the use of dasatinib as an inhibitor for YAP is great, but there is no evidence shown that in this culture system, the inhibitor actually inhibits YAP. As such, IF images are required to confirm cytosolic YAP. Additionally, the authors can try other inhibitors (such as verteporfin) since most inhibitors are broadband.

      Given the mechanically oriented conclusions, other relevant works have shown posteriorized and ventralized neural tube organoids using RA and SHH activation, which were also mechanically stimulated via actuation, such as work done from the Ranga lab (Nature comm. 2021/2023). Although not strictly related to YAP, the therein molecular profiling, mechanical stimulation, lumen measurements, and NTD-like phenotype using PCP-mutated genes make these important relevant mentions since the current work adds important aspects with YAP analysis.

    1. Reviewer #2 (Public review):

      Summary:

      In this study, the authors set out to understand whether the discrete segments of the C.elegans intestine were specialized to carry out distinct functions during an animal's exposure and adaptation to a fast-changing nutrient environment. To achieve this, the authors used a method called Translating ribosome affinity purification (TRAP), which provides a snapshot of what genes are being translated into proteins (and therefore functionally prioritized by the animal) under different fasting and re-feeding conditions. By expressing the TRAP constructs in two distinct segments of the intestine (INT1) and (INT2-9), the authors were able to identify how these segments responded to changing nutrient availability.

      Already under steady state nutrient conditions, the authors found that INT1 and INT2-9 appeared to have different 'tasks', with INT1 expressing more immune- and stress-response related genes. Exposing animals to different regimens of starvation and refeeding also showed marked differences between the intestinal segments, and the gene expression patterns in INT1 were consistent with INT1 cells playing an integrative role in linking nutrient cues to the secretion of insulin molecules that regulate fat metabolism with food intake. In summary, the data presented catalogue, for the first time, gene expression differences between two areas of the intestine, suspected to play different roles, and through clever experiments, links these gene expression changes to responses to nutrient availability.

      Strengths:

      The data presented catalogue - for the first time and in a careful manner - gene expression differences between two areas of the intestine. They strongly support the presence of intriguing differences between two areas of the intestine in immune, metabolic, and stress-response regulation, and link these gene expression changes to the responses of these regions to nutrient availability.

      Weaknesses:

      The conclusions of this paper are mostly well-supported by data, but the relevance of the changing gene expression patterns could be better clarified and extended in the discussion.

    1. Reviewer #2 (Public review):

      Summary:

      The aim of the study by Hall et al. was to establish a generic method for the production of Snake Venom Metalloproteases (SVMPs). These have been difficult to purify in the mg quantities required for mechanistic, biochemical, and structural studies.

      Strengths:

      The authors have successfully applied the MultiBac system and describe with a high level of detail the downstream purification methods applied to purify the SVMP PI, PII, and PIII. The paper carefully presents the non-successful approaches taken (such as expression of mature proteins, the use of protease inhibitors, prodomain segments, and co-expression of disulfide-isomerases) before establishing the construct and expression conditions required. The authors finally convincingly describe various activity assays to demonstrate the activity of the purified enzymes in a variety of established SVMP assays.

      Weaknesses:

      The manuscript suffers from a lack of bottoming out and stringent scientific procedures in the methodology and the characterization of the generated enzymes.

      As an example, a further characterization of the generated protein fragments in Figure 3 by intact mass spectroscopy would have aided in accurate mass determination rather than relying on SEC elution volumes against a standard. Protein shape and charge can affect migration in SEC. Also, the analysis of N-linked glycosylation demonstrates some reactivity of PIII to PNGase F, but fails to conclude whether one or more sites are occupied, or whether other types of glycosylation is present. Again, intact mass experiments would have resolved such issues.

      The activity assays in Figure 4 are not performed consistently with kinetic assays and degradation assays performed for some, but not all, enzymes, and there is no Echis ocellatus comparison in Figure 4h. Overall, whilst not affecting the main conclusion, this leaves the reader with an impression of preliminary data being presented. For consistency, application of the same assays to all enzymes (high-grade purified) would have provided the reader with a fuller picture.

      Overall, the data presented demonstrates a very credible path for the production of active SVMP for further downstream characterization. The generality of the approach to all SVMP from different snakes remains to be demonstrated by the community, but if generally applicable, the method will enable numerous studies with the aim of either utilizing SVMPS as therapeutic agents or to enable the generation of specific anti-venom reagents, such as antibodies or small molecule inhibitors.

    1. Reviewer #2 (Public review):

      Summary:

      The authors' work focuses on studying cell morphological changes during differentiation of hPSCs into neural progenitors in a 2D monolayer setting. The authors use genetic mutations in VANGL2 and patient-derived iPSCs to show that (1) human phenotypes can be captured in the 2D differentiation assay, and (2) VANGL2 in humans is required for neural contraction, which is consistent with previous studies in animal models. The results are solid and convincing, the data are quantitative, and the manuscript is well written. The 2D model they present successfully addresses the questions posed in the manuscript. However, the broad impact of the model may be limited, as it does not contain NNE cells and does not exhibit tissue folding or tube closure, as seen in neural tube formation. Patient-derived lines are derived from amniotic fluid cells, and the experiments are performed before birth, which I find to be a remarkable achievement, showing the future of precision medicine.

      Major comments:

      (1) Figure 1. The authors use F-actin to segment cell areas. Perhaps this could be done more accurately with ZO-1, as F-actin cables can cross the surface of a single cell. In any case, the authors need to show a measure of segmentation precision: segmented image vs. raw image plus a nuclear marker (DAPI, H2B-GFP), so we can check that the number of segmented cells matches the number of nuclei.

      (2) Lines 156-166. The authors claim that changes in gene expression precede morphological changes. I am not convinced this is supported by their data. Fig. 1g (epithelial thickness) and Fig. 1k (PAX6 expression) seem to have similar dynamics. The authors can perform a cross-correlation between the two plots to see which Δt gives maximum correlation. If Δt < 0, then it would suggest that gene expression precedes morphology, as they claim. Fig. 1j shows that NANOG drops before the morphological changes, but loss of NANOG is not specific to neural differentiation and therefore should not be related to the observed morphological changes.

      (3) Figure 2d. The laser ablation experiment in the presence of ROCK inhibitor is clear, as I can easily see the cell outlines before and after the experiment. In the absence of ROCK inhibitor, the cell edges are blurry, and I am not convinced the outline that the authors drew is really the cell boundary. Perhaps the authors can try to ablate a larger cell patch so that the change in area is more defined.

      (4) Figure 2d. Do the cells become thicker after recoil?

      (5) Figure 3. The authors mention their previous study in which they show that Vangl2 is not cell-autonomously required for neural closure. It will be interesting to study whether this also the case in the present human model by using mosaic cultures.

      (6) Lines 403-415. The authors report poor neural induction and neuronal differentiation in GOSB2. As far as I understand, this phenotype does not represent the in vivo situation. Thus, it is not clear to what extent the in vitro 2D model describes the human patient.

      (7) The experimental feat to derive cell lines from amniotic fluid and to perform experiments before birth is, in my view, heroic. However, I do not feel I learned much from the in vitro assays. There are many genetic changes that may cause the in vivo phenotype in the patient. The authors focus on MED24, but there is not enough convincing evidence that this is the key gene. I would like to suggest overexpression of MED24 as a rescue experiment, but I am not sure this is a single-gene phenotype. In addition, the fact that one patient line does not differentiate properly leads me to think that the patient lines do not strengthen the manuscript, and that perhaps additional clean mutations might contribute more.

      Significance:

      This study establishes a quantitative, reproducible 2D human iPSC-to-neural-progenitor platform for analyzing cell-shape dynamics during differentiation. Using VANGL2 mutations and patient-derived iPSCs, the work shows that (1) human phenotypes can be captured in a 2D differentiation assay and (2) VANGL2 is required for neural contraction (apical constriction), consistent with animal studies. The results are solid, the data are quantitative, and the manuscript is well written. Although the planar system lacks non-neural ectoderm and does not exhibit tissue folding or tube closure, it provides a tractable baseline for mechanistic dissection and genotype-phenotype mapping. The derivation of patient lines from amniotic fluid and execution of experiments before birth is a remarkable demonstration that points toward precision-medicine applications, while motivating rescue strategies and additional clean genetic models. However, overall, I did not learn anything substantively new from this manuscript; the conclusions largely corroborate prior observations rather than extend them. In addition, the model was unsuccessful in one of the two patient-derived lines, which limits generalizability and weakens claims of patient-specific predictive value.

    1. Reviewer #2 (Public review):

      Summary:

      Nanodiscs and synthesized EGFR are co-assembled directly in cell-free reactions. Nanodiscs containing membranes with different lipid compositions are obtained by providing liposomes with corresponding lipid mixtures in the reaction. The authors focus on the effects of lipid charge and fluidity on EGFR activity.

      Strengths:

      The authors implement a variety of complementary techniques to analyze data and to verify results. They further provide a new pipeline to study lipid effects on membrane protein function. The manuscript describes a comprehensive study on the analysis of membrane protein function in context of different lipid environments.

      Weaknesses:

      As the implemented strategy is relatively new, some uncertainties in the interpretation of the data consequently remain. However, using state-of-the-art techniques, the authors support their results by appropriate data and sufficient controls in the revised manuscript.

    1. Reviewer #2 (Public review):

      Summary:

      In this manuscript, Khamari and colleagues investigate how HGF-MET signaling and the intracellular trafficking of the MET receptor tyrosine kinase influence invadopodia formation and invasion in triple-negative breast cancer (TNBC) cells. They show that HGF stimulation enhances both the number of invadopodia and their proteolytic activity. Mechanistically, the authors demonstrate that HGF-induced, RAB4- and RCP-RAB14-KIF16B-dependent recycling routes deliver MET to the cell surface specifically at sites where invadopodia form. Moreover, they report that MET physically interacts with MT1-MMP - a key transmembrane metalloproteinase required for invadopodia function- and that these two proteins co-traffic to invadopodia upon HGF stimulation.

      Although the HGF-MET axis has previously been implicated in invadopodia regulation (e.g., by Rajadurai et al., Journal of Cell Science 2012), studies directly linking ligand-induced MET trafficking with the spatial regulation of MT1-MMP localization and activity have been lacking.

      Overall, the manuscript addresses a relevant and timely topic and provides several novel insights. However, some sections require clearer and more concise writing (details below). In addition, the quality, reliability, and robustness of several data sets need to be improved.

      Strengths:

      A key strength of the study is the novel demonstration that HGF-mediated, RAB4- and RAB14-dependent recycling of MET delivers this receptor, together with MT1-MMP, to invadopodia -highlighting a previously unrecognized mechanism, regulating the formation and proteolytic function of these invasive structures. Another strong point is the breadth of experimental approaches used and the substantial amount of supporting data. The authors also include an appropriate number of biological replicates and analyze a sufficiently large number of cells in their imaging experiments, as clearly described in the figure legends.

      Weaknesses:

      (1) Inappropriate stimulation times for endocytosis and recycling assays.

      The experiments examining MET endocytosis and recycling following HGF stimulation appear to use inappropriate incubation times. After ligand binding, RTKs typically undergo endocytosis within minutes and reach maximal endosomal accumulation within 5-15 minutes. Although continuous stimulation allows repeated rounds of internalization, the temporal dynamics of MET trafficking should be examined across shorter time points, ideally up to 1 hour (e.g., 15, 30, and 60 minutes). The authors used 2-, 3-, or 6-hour HGF stimulation, which, in my opinion, is far too long to study ligand-induced RTK trafficking.

      (2) Low efficiency of MET silencing in Figure S1I.

      The very low MET knockdown efficiency shown in Figure S1I raises concerns. Given the potential off-target effects of a single shRNA and the insufficient silencing level, it is difficult to conclude whether the reduction in invadopodia number in Figure 1F is genuinely MET-dependent. The authors later used siRNA-mediated silencing (Figure S5C), which was more effective. Why was this siRNA not used to generate the data in Figure 1F? Why did the authors rely on the inefficient shRNA C#3?

      (3) Missing information on incubation times and inconsistencies in MET protein levels.

      The figure legends do not indicate how long the cells were incubated with HGF or the MET inhibitor PHA665752 prior to immunoblotting. This information is crucial, particularly because both HGF and PHA665752 cause a substantial decrease in the total MET protein level. Notably, such a decrease is absent in MDA-MB-231 cells treated with HGF in the presence of cycloheximide (Figure S2F). The authors should comment on these inconsistencies.

      Additionally, the MET bands in Figure S1J appear different from those in Figure S1C, and MET phosphorylation seems already high under basal conditions, with no further increase upon stimulation (Figure S1J). The authors should address these issues.

      (4) Insufficient representation and randomization of microscopic data.

      For microscopy, only single representative cells are shown, rather than full fields containing multiple cells. This is particularly problematic for invadopodia analysis, as only a subset of cells forms these structures. The authors should explain how they ensured that image acquisition and quantification were randomized and unbiased. The graphs should also include the percentage of cells forming invadopodia, a standard metric in the field. Furthermore, some images include altered cells - for example, multinucleated cells - which do not accurately represent the general cell population.

      (5) Use of a single siRNA/shRNA per target.

      As noted earlier, using only one siRNA or shRNA carries the risk of off-target effects. For every experiment involving gene silencing (MET, RAB4, RAB14, RCP, MT1-MMP), at least two independent siRNAs/shRNAs should be used to validate the phenotype.

      (6) Insufficient controls for antibody specificity.

      The specificity of MET, p-MET, and MT1-MMP staining should be demonstrated in cells with effective gene silencing. This is an essential control for immunofluorescence assays.

      (7) Inadequate demonstration of MET recycling.

      MET recycling should be directly demonstrated using the same approaches applied to study MT1-MMP recycling. The current analysis - based solely on vesicles near the plasma membrane - is insufficient to conclude that MET is recycled back to the cell surface.

      (8) Insufficient evidence for MET-MT1-MMP interaction.

      The interaction between MET and MT1-MMP should be validated by immunoprecipitation of endogenous proteins, particularly since both are endogenously expressed in the studied cell lines.

      (9) Inconsistent use of cell lines and lack of justification.

      The authors use two TNBC cell lines: MDA-MB-231 and BT-549, without providing a rationale for this choice. Some assays are performed in MDA-MB-231 and shown in the main figures, whereas others use BT-549, creating unnecessary inconsistency. A clearer, more coherent strategy is needed (e.g., present all main findings in MDA-MB-231 and confirm key results in BT-549 in supplementary figures).

      (10) Inconsistency in invadopodia numbers under identical conditions.

      The number of invadopodia formed in Figure 1E is markedly lower than in Figure 1C, despite identical conditions. The authors should explain this discrepancy.

      (11) Questionable colocalization in some images.

      In some figures - for example, Figure 2G - the dots indicated by arrows do not convincingly show colocalization. The authors should clarify or reanalyze these data.

      (12) Abstract, Introduction, and Discussion require substantial rewriting.

      (a) The abstract should be accessible to a broader audience and should avoid using abbreviations and protein names without context.

      (b) The introduction should better describe the cellular processes and proteins investigated in this study.

      (c) The discussion currently reads more like an extended summary of results. It lacks deeper interpretation, comparison with existing literature, and consideration of the broader implications of the findings.

    1. Reviewer #2 (Public review):

      Summary

      Briola and co-authors have performed a structural analysis of the human CTF18 clamp loader bound to PCNA. The authors purified the complexes and formed a complex in solution. They used cryo-EM to determine the structure to high resolution. The complex assumed an auto-inhibited conformation, where DNA binding is blocked, which is of regulatory importance and suggests that additional factors could be required to support PCNA loading on DNA. The authors carefully analysed the structure and compared it to RFC and related structures.

      Strength & Weakness

      Their overall analysis is of high quality, and they identified, among other things, a human-specific beta-hairpin in Ctf18 that flexible tethers Ctf18 to Rfc2-5. Indeed, deletion of the beta-hairpin resulted in reduced complex stability and a reduction in the rate of primer extension assay with Pol ε. Moreover, the authors identify that the Ctf18 ATP-binding domain assumes a more flexible organisation.

      The data are discussed accurately and relevantly, which provides an important framework for rationalising the results.

      All in all, this is a high-quality manuscript that identifies a key intermediate in CTF18-dependent clamp loading.

    1. Reviewer #2 (Public review):

      Summary:

      This study examines how activating specific G protein-coupled receptors (GPCRs) affects the microRNA (miRNA) profiles within extracellular vesicles (EVs). The authors seek to identify whether different GPCRs produce unique EV miRNA signatures and what these signatures could indicate about downstream cellular processes and pathology processes.

      Methods:

      Used U2OS human osteosarcoma cells, which naturally express multiple GPCR types.

      Stimulated four distinct GPCRs (ADORA1, HRH1, FZD4, ACKR3) using selective agonists.

      Isolated EVs from culture media and characterized them via size exclusion chromatography, immunoblotting, and microscopy.

      Employed qPCR-based miRNA profiling and bioinformatics analyses (e.g., KEGG, PPI networks) to interpret expression changes.

      Key Findings:

      No significant change in EV quantity or size following GPCR activation.

      Each GPCR triggered a distinct EV miRNA expression profile.

      miRNAs differentially expressed post-stimulation were linked to pathways involved in cancer, insulin resistance, neurodegenerative diseases, and other physiological/pathological processes.

      miRNAs such as miR-550a-5p, miR-502-3p, miR-137, and miR-422a emerged as major regulators following specific receptor activation.

      Conclusions:

      The study offers evidence that GPCR activation can regulate intercellular communication through miRNAs encapsulated within extracellular vesicles (EVs). This finding paves the way for innovative drug-targeting strategies and enhances understanding of drug side effects that are mediated via GPCR-related EV signaling.

      Strengths:

      Innovative concept: The idea of linking GPCR signaling to EV miRNA content is novel and mechanistically important.

      Robust methodology: The use of multiple validation methods (biochemical, biophysical, and statistical) lends credibility to the findings.

      Relevance: GPCRs are major drug targets, and understanding off-target or systemic effects via EVs is highly valuable for pharmacology and medicine.

      Weaknesses:

      Sample Size & Scope: The analysis included only four GPCRs. Expanding to more receptor types or additional cell lines would enhance the study's applicability.

      Exploratory Nature: This study is primarily descriptive and computational. It lacks functional validation, such as assessing phenotypic effects in recipient cells, which is acknowledged as a future step.

      EV heterogeneity: The authors recognize that they did not distinguish EV subpopulations, potentially confounding the origin and function of miRNAs.

      Comments on revisions:

      All the comments have been taken into account. I wish the authors success in their future research.

    1. Reviewer #3 (Public review):

      "Effects of residue substitutions on the cellular abundance of proteins" by Schulze and Lindorff-Larsen revisits the classical concept of structure-aware protein substitution matrices through the scope of modern protein structure modelling approaches and comprehensive phenotypic readouts from multiplex assays of variant effects (MAVEs). The authors explore 6 unique protein MAVE datasets based on protein abundance through the lens of protein structural information (residue solvent accessibility, secondary structure type) to derive combinations of context-specific substitution matrices that predict variant impact on protein abundance. They are clear to outline that the aim of the study is not to produce a new best abundance predictor, but to showcase the degree of prediction afforded simply by utilizing structural information.

      Both the derived matrices and the underlying 'training' data are comprehensively evaluated. The authors convincingly demonstrate that taking structural solvent accessibility contexts into account leads to more accurate performance than either a structure-unaware matrix, secondary structure-based matrix, or matrices combining both solvent accessibility and secondary structure. The capacity for the approach to produce generalizable matrices is explored through training data combinations, highlighting factors such as the variable quality of the experimental MAVE data and the biochemical differences between the protein targets themselves, which can lead to limitations. Despite this, the authors demonstrate their simple matrix approach is generally on par with dedicated protein stability predictors in abundance effect evaluation, and even outperforms them in a niche of solvent accessible surface mutations, revealing their matrices provide orthogonal abundance-specific signal. More importantly, the authors further develop this concept to creatively show their matrices can be used to identify surface residues that have buried-like substitution profiles, which are shown to correspond to protein interface residues, post-translational modification sites, functional residues or putative degrons.

      The paper makes a strong and well-supported main point, demonstrating the widespread utility of the authors' approach, empowered through protein structural information and cutting edge MAVE datasets. This work creatively utilizes a simple concept to produce a highly interpretable tool for protein abundance prediction (and beyond), which is inspiring in the age of impenetrable machine learning models.

    1. Reviewer #2 (Public review):

      Summary:

      The Drosophila executioner caspase Dcp-1 has established roles in cell death, autophagy, and imaginal disc growth. This study reports previously unrecognized factors that work together with Dcp-1. Specifically, the authors performed a turboID-based proximal ligation experiment to identify factors associated Dcp-1 and Drice. Dcp-1-specific interactors were further examined for their genetic interaction. The authors report autophagy-related genes, including Debcl and Buffy, to be required for Dcp-1 activation. In addition, the authors present evidence of an interaction between Bruce and Dcp-1. Bruce-expression blocks the Dcp-1 overexpression phenotype. Inhibition of effector caspases or overexpression of Bruce commonly reduced wing growth, suggesting a relationship between the two proteins.

      Strengths:

      On the positive side, the study identifies new Dcp-1-interacting proteins and provides a functional link between Dcp-1 and Sirt1, Fkbp59, Debcl, Buffy, Atg2, and Atg8a.

      Weaknesses:

      The data supporting the Dcp-1/Bruce interaction are not strong, even though the title of this manuscript highlights Bruce. For example, the authors' turboID data does not support Dcp-1/Bruce interaction. The case for the interaction is based on a single experiment that overexpresses a truncated Bruce transgene in S2 cells.

    1. Reviewer #2 (Public review):

      (1) The photoconversion protocol requires a more detailed and quantitative discussion. The current description ("5 s pulses for 5 min, leading to 2.5 min of total light delivery") is too brief to evaluate whether the chosen illumination parameters maintain the CaMPARI2 signal within its linear dynamic range. Because CaMPARI2 photoconversion reflects the time integral of 405 nm photoconverting light exposure in the presence of intracellular [Ca²⁺], the red/green fluorescence ratio is directly proportional to cumulative illumination time until saturation occurs. Previous characterization (PMID: 30361563) shows that photoconversion is approximately linear over the first 0-80 s of 405 nm exposure, after which red fluorescence plateaus. The total exposure used here (=150 s) may therefore exceed the linear regime, potentially obscuring differences between cells with moderate versus strong Ca²⁺ activity. The authors should (i) justify the selected illumination parameters, (ii) provide evidence that the chosen conditions remain within the linear response range for the specific optical setup, (iii) discuss how overexposure might affect quantitative interpretation of red/green ratios and comparisons between experimental groups. Inclusion of calibration data would substantially strengthen the methodological rigor and reproducibility of the study.

      (2) For Figure 8a (middle panels), the data points for 16G and KCl show overlaps, raising the possibility that at it 16G may already be saturated. The authors should comment on the potential for CaMPARI2 saturation at 16G, and clarify whether this affects the interpretation of the KCl results "At maximal stimulation by KCl, there was no size-function correlation (R = 0.15, p = 0.14)."

      (3) The term "calcium activity" is used throughout the manuscript but remains vague. Pancreatic islets typically display a biphasic Ca²⁺ response to high glucose-an initial sustained peak followed by repetitive oscillations - and these phases differ in both kinetics and physiological meaning. Ca²⁺ responses are usually quantified using parameters such as rise time, amplitude, and duration for the initial peak, and amplitude, frequency, burst duration, and duty cycle for the oscillatory phase. The authors should clarify how "calcium activity" is defined in their analyses and discuss the appropriateness of directly comparing Ca²⁺ signals with distinct temporal patterns.

      (4) The CaMPARI2 red/green ratio reflects the time-integral of 405 nm photoconverting light exposure in the presence of Ca²⁺, two Ca²⁺ responses with the same duty cycle but different amplitudes could, in principle, yield the same red/green ratios. This raises an important question regarding how well the CaMPARI2 signal distinguishes differences in Ca²⁺ amplitude versus time spent above threshold. The authors should directly relate single-cell Ca²⁺ traces to corresponding red/green ratios to demonstrate the extent to which CaMPARI2 photoconversion truly reflects "Ca²⁺ activity." Such validation would clarify whether the metric is sensitive to variations in oscillation amplitude, duty cycle, or both, and would strengthen the interpretation of CaMPARI2-based functional comparisons.

    1. Reviewer #2 (Public review):

      Summary:

      Liu et al. use whole genome sequencing data from several strains of chicken as well as a subspecies of the chicken wild ancestor to study the impact of domestication on the recombination landscape. They analyze these data using several machine-learning/AI based methods, using simulation to partially inform their analysis. The authors claim to find substantial deviations in the fine-scale recombination landscape between breeds, and surprising patterns between recombination and introgression/selection. However, there are substantial inconsistencies between the author's findings and the current understanding in the field, supported by indirect evidence that is hard to interpret at best.

      Strengths:

      The data produced by the authors of this and a previous paper is well-suited to answer the questions that they pose. The authors use simulations to support some decisions made in analyzing this data, which partially alleviates some potential questions, and could be extended to address additional concerns. Should further analysis support the claims currently made regarding hotspot turnover and introgression frequency vs. recombination rate, these findings would indeed be striking observations at odds with current understanding in the field.

      Weaknesses:

      I have several major concerns regarding the ability of the analyses to support the claims in this paper, summarized below.

      Substantial deviations from field-standard benchmarks the estimated recombination landscape appear to have been disregarded, particularly with regard to the WL breed.<br /> o For example, the number of detected hotspots per subspecies ranges from maybe 500 to over 100,000 based on figure 2A. While the mean is indeed comparable to estimates from other species (lines 315-317), this characterization masks that each recombination map has far too few or too many hotspots to be biologically accurate (at least without substantial corroboration from more direct analyses). As such, statements about hotspot overlap between breeds and hotspot conservation cannot be taken at face value. Authors might consider using alternative methods to detect hotspots, assessing their power to detect hotspots in each breed, and evaluating hotspot overlap between breeds with respect to random expectation.<br /> o Furthermore, the authors consider the recombination landscape at promoters (Figure S10) and H3K4me3 sites (Figure 2C) and find that levels are slightly elevated, but the magnitude of the elevation (negligible to ~1.5x) is substantially lower than that of any other species studied to date without PRDM9. The magnitude of elevation for both comparisons is especially small for WL, which suggests that the recombination estimates for this breed are particularly noisy, and yet this breed is the focus of the introgression analysis.

      Introgression and strong selection can both be thought of as changing the local Ne along the genome. Estimating recombination from patterns of LD most directly estimates rho (the population recombination rate, 4*Ne*r), and disentangling local changes in Ne from local changes in r is non-trivial. Furthermore, selective sweeps, particularly easy-to-detect hard sweeps, are often characterized by having very little genetic variation. Estimating recombination rate from patterns of LD in regions with very little variation seems particularly challenging, and could bias results such as in Figure S15. The authors do not discuss the implications of these challenges for their analyses, which seems particularly relevant for their analyses of introgression and selection with recombination, as well as comparisons between WL (which the authors report to have undergone more selection and introgression) with other breeds. Authors should quantify their ability/power to detect recombination rates and hotspots under these conditions using simulation - some of these simulations are already mentioned in the paper, but are not analyzed in this way. Also useful would be quantifying the impact of simulated bottlenecks on estimates of recombination rate.

      In many analyses (e.g. hotspot and coldspot overlap, histone mark analysis), authors appear to use 1000 randomly selected regions of the same length as a control. If this characterization is accurate, authors should match the number of control regions to the number of features that they're comparing to. A more careful analysis might also select random regions from the same chromosome, match for GC content where appropriate, etc.

      Authors provide very little detail about the number/locations of coldspots or selective sweeps- how many were detected in each subspecies? Does the fraction of hotspots and coldspots which overlap selective sweeps vary between species? It is unclear whether the numbers in the text (lines 356-364) represent a single breed or an analysis across breeds.

    1. Reviewer #2 (Public review):

      Summary:

      The manuscript submitted by Koch et al. describes a novel approach to collect budding yeast cells in metaphase I or metaphase II by synthetically activating the spinde checkpoint (SAC). The arrest is transient and reversible. This synchronization strategy will be extremely useful for studying meiosis I and meiosis II, and compare the two divisions. The authors characterized this so named syncSACapproach and could confirm previous observations that the SAC arrest is less efficient in meiosis I than in meiosis II. They found that downregulation of the SAC response through PP1 phosphatase is stronger in meiosis I than in meiosis II. The authors then went on to purify kinetochore-associated proteins from metaphase I and II extracts for proteome and phosphoproteome analysis. Their data will be of significant interest to the cell cycle community (they compared their datasets also to kinetochores purified from cells arrested in prophase I and -with SynSAC in mitosis).

      Significance:

      The technique described here will be of great interest to the cell cycle community. Furthermore, the authors provide data sets on purified kinetochores of different meiotic stages and compare them to mitosis. This paper will thus be highly cited, for the technique, and also for the application of the technique.

    1. Reviewer #2 (Public review):

      This study leverages acute protein degradation of CHD4 to define its role in chromatin and gene regulation. Previous studies have relied on KO and/or RNA interference of this essential protein and as such are hampered by adaptation, cell population heterogeneity, cell proliferation and indirect effects. The authors have established an AID2-based method to rapidly deplete the dMi-2 remodeller to circumvent these problems. CHD4 is gone within an hour, well before any effects on cell cycle or cell viability can manifest. This represents an important technical advance that, for the first time, allows a comprehensive analysis of the immediate and direct effect of CHD4 loss of function on chromatin structure and gene regulation.

      Rapid CHD4 degradation is combined with ATAC-seq, CUT&RUN, (nascent) RNA-seq and single molecule microscopy to comprehensively characterise the impact on chromatin accessibility, histone modification, transcription and transcription factor (NANOG, SOX2, KLF4) binding in mouse ES cells.

      The data support the previously developed model that high levels of CHD4/NuRD maintain a degree of nucleosome density to limit TF binding at open regulatory regions (e.g. enhancers). The authors propose that CHD4 activity at these sites is an important prerequisite for enhancers to respond to novel signals that require an expanded or new set of TFs to bind.

      What I find even more exciting and entirely novel is the finding that CHD4 removes TFs from regions of limited accessibility to repress cryptic enhancers and to suppress spurious transcription. These regions are characterised by low CHD4 binding and have so far never been thoroughly analysed. The authors correctly point out that the general assumption that chromatin regulators act on regions where they seem to be concentrated (i.e. have high ChIP-seq signals) runs the risk of overlooking important functions elsewhere. This insight is highly relevant beyond the CHD4 field and will prompt other chromatin researchers to look into low level binding sites of chromatin regulators.

      The biochemical and genomic data presented in this study is of high quality (I cannot judge single microscopy experiments due to my lack of expertise). This is an important and timely study that is of great interest to the chromatin field.

      Comments on revised version:

      All my comments below have been addressed in the revised version of the manuscript.

      The revised manuscript provides a significant advance of our understanding of how the nucleosome remodeler CHD4 exerts its function. In particular, the findings suggest an intriguing role of CHD4 in TF removal at genomic regions where only low levels of CHD4 can be detected. In the future, it will be interesting to see if this activity is shared by other ATP-dependent nucleosome remodelers.

    1. Reviewer #2 (Public review):

      Summary:

      The authors present Altair-LSFM (Light Sheet Fluorescence Microscope), a high-resolution, open-source light-sheet microscope, that may be relatively easy to align and construct due to a custom-designed mounting plate. The authors developed this microscope to fill a perceived need that current open-source systems are primarily designed for large specimens and lack sub-cellular resolution or achieve high-resolution but are difficult to construct and are unstable. While commercial alternatives exist that offer sub-cellular resolution, they are expensive. The authors manuscript centers around comparisons to the highly successful lattice light-sheet microscope, including the choice of detection and excitation objectives. The authors thus claim that there remains a critical need for a high-resolution, economical and easy to implement LSFM systems and address this need with Altair.

      Strengths:

      The authors succeed in their goals of implementing a relatively low cost (~ USD 150K) open-source microscope that is easy to align. The ease of alignment rests on using custom-designed baseplates with dowel pins for precise positioning of optics based on computer analysis of opto-mechanical tolerances as well as the optical path design. They simplify the excitation optics over Lattice light-sheet microscopes by using a Gaussian beam for illumination while maintaining lateral and axial resolutions of 235 and 350 nm across a 260-um field of view after deconvolution. In doing so they rest on foundational principles of optical microscopy that what matters for lateral resolution is the numerical aperture of the detection objective and proper sampling of the image field on to the detection, and the axial resolution depends on the thickness of the light-sheet when it is thinner than the depth of field of the detection objective. This concept has unfortunately not been completely clear to users of high-resolution light-sheet microscopes and is thus a valuable demonstration. The microscope is controlled by an open-source software, Navigate, developed by the authors, and it is thus foreseeable that different versions of this system could be implemented depending on experimental needs while maintaining easy alignment and low cost. They demonstrate system performance successfully by characterizing their sheet, point-spread function, and visualization of sub-cellular structures in mammalian cells including microtubules, actin filaments, nuclei, and the Golgi apparatus.

      Weaknesses:

      There is still a fixation on comparison to the first-generation lattice light-sheet microscope, which has evolved significantly since then:

      (1) One of the major limitations of the first generation LLSM was the use of a 5 mm coverslip, which was a hinderance for many users. However, the Zeiss system elegantly solves this problem and so does Oblique Plane Microscopy (OPM), while the Altair-LSFM retains this feature which may dissuade widespread adoption. This limitation and how it may be overcome in future iterations is now discussed in the manuscript but remains a limitation in the currently implemented design.

      (2) Further, on the point of sample flexibility, all generations of the LLSM, and by the nature of its design the OPM, can accommodate live-cell imaging with temperature, gas, and humidity control. In the revised manuscript the authors now implement temperature control, but ideal live cell imaging conditions that would include gas and humidity control are not implemented. While, as the authors note, other microscopes that lack full environmental control have achieved widespread adoption, in my view this still limits the use cases of this microscope. There is no discussion on how this limitation of environmental control may be overcome in future iterations.

      (3) While the microscope is well designed and completely open source it will require experience with optics, electronics, and microscopy to implement and align properly. Experience with custom machining or soliciting a machine shop is also necessary. Thus, in my opinion it is unlikely to be implemented by a lab that has zero prior experience with custom optics or can hire someone who does. Altair-LSFM may not be as easily adaptable or implementable as the authors describe or perceive in any lab that is interested even if they can afford it. Claims on how easy it may be to align the system for a "Novice" in supplementary table 5, appear to be unsubstantiated and should be removed unless a Novice was indeed able to assemble and validate the system in 2 weeks. It seems that these numbers were just arbitrarily proposed in the current version without any testing. In our experience it's hard to predict how long an alignment will take for a novice.

      (4) There is no quantification on field uniformity and the tunability of the light sheet parameters (FOV, thickness, PSF, uniformity). There is no quantification on how much improvement is offered by the resonant and how its operation may alter the light-sheet power, uniformity and the measured PSF.

    1. Reviewer #2 (Public review):

      Summary:

      The study elucidates the role of the recently discovered mediator of p53 tumor suppressive activity, ZMAT3. Specifically, the authors find that ZMAT3 negatively regulates HKDC1, a gene involved in the control of mitochondrial respiration and cell proliferation.

      Comments on revisions:

      The authors have mostly addressed to the concerns raised previously by this reviewer. The lack of functional assays made the reported findings mostly mechanistic with no clear biological context.

      The present manuscript is certainly improved compared to the previous version.

    1. Reviewer #3 (Public review):

      Zhao et al. provide new insights into the mechanism by which a high-fat diet (HFD) induces cardiac arrhythmia employing Drosophila as a model. HFD induces cardiac arrhythmia in both mammals and Drosophila. Both glucagon and its functional equivalent in Drosophila Akh are known to induce arrhythmia. The study demonstrates that Akh mRNA levels are increased by HFD and both Akh and its receptor are necessary for high-fat diet-induced cardiac arrhythmia, elucidating a novel link. Notably, Zhao et al. identify a pair of AKH receptor-expressing neurons located at the posterior of the heart tube. Interestingly, these neurons innervate the heart muscle and form synaptic connections, implying their roles in controlling the heart muscle. The study presented by Zhao et al. is intriguing, and the rigorous characterization of the AKH receptor-expressing neurons would significantly enhance our understanding of the molecular mechanism underlying HFD-induced cardiac arrhythmia.

      Many experiments presented in the manuscript are appropriate for supporting the conclusions while additional controls and precise quantifications should help strengthen the authors' arguments. The key results obtained by loss of Akh (or AkhR) and genetic elimination of the identified AkhR-expressing cardiac neurons do not reconcile, complicating the overall interpretation.

      The most exciting result is the identification of AkhR-expressing neurons located at the posterior part of the heart tube (ACNs). The authors attempted to determine the function of ACNs by expressing rpr with AkhR-GAL4, which would induce cell death in all AkhR-expressing cells, including ACNs. The experiments presented in Figure 6 are not straightforward to interpret. Moreover, the conclusion contradicts the main hypothesis that elevated Akh is the basis of HFD-induced arrhythmia. The results suggest the importance of AkhR-expressing cells for normal heartbeat. However, elimination of Akh or AkhR restores normal rhythm in HFD-fed animals, suggesting that Akh and AkhR are not important for maintaining normal rhythms. If Akh signaling in ACNs is key for HFD-induced arrhythmia, genetic elimination of ACNs should unalter rhythm and rescue the HFD-induced arrhythmia. An important caveat is that the experiments do not test the specific role of ACNs. ACNs should be just a small part of the cells expressing AkhR. Specific manipulation of ACNs will significantly improve the study. Moreover, the main hypothesis suggests that HFD may alter the activity of ACNs in a manner dependent on Akh and AkhR. Testing how HFD changes calcium, possibly by CaLexA (Figure 2) and/or GCaMP, in wild-type and AkhR mutant could be a way to connect ACNs to HFD-induced arrhythmia. Moreover, optogenetic manipulation of ACNs may allow for specific manipulation of ACNs.

      Interestingly, expressing rpr with AkhR-GAL4 was insufficient to eliminate both ACNs. It is not clear why it didn't eliminate both ACNs. Given the incomplete penetrance, appropriate quantifications should be helpful. Additionally, the impact on other AhkR-expressing cells should be assessed. Adding more copies of UAS-rpr, AkhR-GAL4, or both may eliminate all ACNs and other AkhR-expressing cells. The authors could also try UAS-hid instead of UAS-rpr.

    1. Reviewer #2 (Public review):

      Summary:

      The authors present an ambitious and large-scale reproducibility analysis of 400 articles on Drosophila immunity published before 2011. They extract major and minor claims from each article, assess their verifiability through literature comparison and, when possible, through targeted experimental re-testing, and synthesize their findings in an openly accessible online database. The goal is to provide clarity to the community regarding claims that have been contradicted, incompletely supported, or insufficiently followed up in the literature, and to foster broader community participation in evaluating historical findings. The manuscript summarizes the major insights emerging from this systematic effort.

      Strengths:

      (1) Novelty and community value: This work represents a rare example of a systematic, transparent, and community-facing reproducibility project in a specific research domain. The creation of a dedicated public platform for disseminating and discussing these assessments is particularly innovative.

      (2) Breadth and depth: The authors analyze an impressive number of publications spanning multiple decades, and they couple literature-based assessments with new experimental data where follow-up is missing.

      (3) Clarity of purpose: The manuscript carefully distinguishes between assessing evidential support for claims and judging the scientific merit of historical work. This helps frame the project as constructive rather than punitive.

      (4) Metascientific relevance: The analysis identifies methodological and contextual factors that commonly underlie irreproducible claims, providing a useful guide for future study design and interpretation.

      (5) Transparency: Supplementary datasets and the public website provide an exceptional degree of openness, which should facilitate community engagement and further refinement.

      Weaknesses:

      (1) Subjectivity in selection: Despite the authors' efforts, the choice of which papers and claims to highlight cannot be entirely objective. This is an inherent limitation of any retrospective curation effort, but it remains important to acknowledge explicitly.

      (2) Emphasis on irreproducible claims: The manuscript focuses primarily on claims that are challenged or found to be weakly supported. While understandable from the perspective of novelty, this emphasis may risk overshadowing the value of claims that are well supported and reproducible.

      (3) Framing and language: Certain passages could benefit from more neutral phrasing and avoidance of binary terms such as "correct" or "incorrect," in keeping with the open-ended and iterative nature of scientific progress.

      (4) Community interaction with the dataset: While the website is an excellent resource, the manuscript could further clarify how the community is expected to contribute, challenge, or refine the annotations, especially given the large volume of supplementary data.

      (5) Minor inconsistency: The manuscript states that papers from 1959-2011 were included, but the Methods section mentions a range beginning in 1940. This should be aligned for clarity.

      Impact and significance:

      This contribution is likely to have a meaningful impact on both the Drosophila immunity community and the broader scientific ecosystem. It highlights methodological pitfalls, encourages transparent post-publication evaluation, and offers a reusable framework that other fields could adopt. The work also has pedagogical value for early-career researchers entering the field, who often struggle to navigate contradictory or outdated claims. By centralizing and contextualizing these discussions, the manuscript should help accelerate more robust and reproducible research.

    1. Reviewer #2 (Public review):

      In this manuscript, Zhang et al describe a method for cryo-EM reconstruction of small (sub-50kDa) complexes using 2D template matching. This presents an alternative, complementary path for high-resolution structure determination when there is a prior atomic model for alignment. Importantly, regions of the atomic model can be deleted to avoid bias in reconstructing the structure of these regions, serving as an important mechanism of validation.

      The manuscript focuses its analysis on a recently published dataset of the 40kDa kinase complex deposited to EMPIAR. The original processing workflow produced a medium resolution structure of the kinase (GSFSC ~4.3A, though features of the map indicate ~6-7A resolution); at this resolution, the binding pocket and ligand were not resolved in the original published map. With 2DTM, the authors produce a much higher resolution structure, showing clear density for the ATP binding pocket and the bound ATP molecule. With careful curation of the particle images using statistically derived 2DTM p-values, a high-resolution 2DTM structure was reconstructed from just 8k particles (2.6A non-gold standard FSC; ligand Q-score of 0.6), in contrast to the 74k particles from the original publication. This aligns with recent trends that fewer, higher-quality particles can produce a higher-quality structure. The authors perform a detailed analysis of some of the design choices of the method (e.g., p-value cutoff for particle filtering; how large a region of the template to delete).

      Overall, the workflow is a conceptually elegant alternative to the traditional bottom-up reconstruction pipeline. The authors demonstrate that the p-values from 2DTM correlations provide a principled way to filter/curate which particle images to extract, and the results are impressive. There are only a few minor recommendations that I could make for improvement.

    1. Her minuteness of detail has also been found fault with ; but even where it produces , at the time , a degree of tediousness , we know not whether that can justly be reckoned a blemish , which is absolutely essential to a very high excellence .

      Whatley is quite the perplexing individual in that he validates the critiques of others while subtly asserts them as blemishes. It is bold and at the same time rather unapologetic in that manner; however, now I wonder what other critics were saying about Jane Austin during her time. It is clear that Whatley holds her works to a high regard and seems to be the apotheosis of literature from his perspective.

      SIDE NOTE: Based on the claim right afterwards, I think while reading Jane Austin's works I will be paying closer attention to characters and how they are utilized.