Reviewer #2 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

(1) Clarification of DL-TBOA concentration.

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

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

(2) Potential contribution of altered intrinsic excitability.

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

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

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

(4) Interpretation of glial versus neuronal EAAT contributions.

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

Reviewer #2 (Public review):

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

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

Strengths

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

Weaknesses

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

Reviewer #2 (Public review):

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

Strengths:

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

Weaknesses:

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

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

Major points

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

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

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

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

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

Minor points:

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

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

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

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

Weaknesses:

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

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

Reviewer #2 (Public review):

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

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

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

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

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

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

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

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

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

Reviewer #2 (Public review):

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

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

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

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

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

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

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

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

Many of the experiments are elegant and well-performed.

Weaknesses:

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

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

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

Reviewer #2 (Public review):

Summary:

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

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

Strengths:

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

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

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

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

Recommendations:

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

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

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

Reviewer #2 (Public review):

Summary:

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

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

Strengths:

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

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

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

Weaknesses:

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

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

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

The productive collision surface area analysis needs more quantitative data.

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

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

DOI: 10.1016/j.celrep.2026.117477

Resource: RRID:ZFIN_ZDB-ALT-151120-2

Curator: @evieth

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

What is this?

Reviewer #3 (Public review):

Summary:

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

Strengths:

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

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

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

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

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

Comments on revised version:

The revised version addressed my comments well.

Reviewer #2 (Public review):

Summary

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

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

Strengths:

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

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

Weaknesses:

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

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

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

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

Reviewer #4 (Public review):

Summary of General Strengths & Weaknesses:

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

Specific Weaknesses - Major:

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

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

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

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

Comments on the revised version.

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

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

Weaknesses:

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

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

Comments on latest version.

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

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

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

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

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

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

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

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

Weaknesses:

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

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

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

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

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

Reviewer #2 (Public review):

Summary and strengths:

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

Comments on revised version:

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

Overall Assessment:

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

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

Weaknesses:

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

Comment on revisions:

The authors thoughtfully addressed the reviewer comments.

Reviewer #2 (Public review):

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

Major comments:

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

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

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

Comments on revised version.

The authors have addressed my prior comments

Reviewer #2 (Public review):

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Reviewer #2 (Public review):

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

Comments on revised version.

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

Reviewer #2 (Public review):

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

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

Major:

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

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

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

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

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

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

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

Reviewer #2 (Public review):

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

Strengths:

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

Comments on revised version.

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

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

Reviewer #2 (Public review):

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

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

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

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

Reviewer Concerns:

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

(2) There are some typos/grammar concerns.

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

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

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

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

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

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

Weaknesses:

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

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

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

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

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

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

Weaknesses:

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

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

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

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

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

Reviewer #2 (Public Review):

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

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

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

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

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

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

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

Reviewer #2 (Public review):

Summary:

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

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

Strengths:

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

Comments on revised version.

I am fine with the revisions.

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

Comments on revised version.

The authors have addressed all of my questions and comments.

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

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

Weaknesses:

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

Reviewer #2 (Public review):

Summary:

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

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

Strengths:

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

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

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

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

Weaknesses:

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

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

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

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

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

Weaknesses:

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

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

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

Reviewer #2 (Public review):

Summary:

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

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

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

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

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

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

Reviewer #2 (Public review):

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

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

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

Reviewer #2 (Public review):

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

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

Comments on revised version:

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

Comments on revised version.

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

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

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

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

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

Weaknesses

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

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

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

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

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

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

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

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

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

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

Weakness:

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

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

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

Comments on the revised manuscript:

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

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

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

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

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

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

Reviewer #2 (Public review):

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

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

Comments on revised version.

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

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

Reviewer #2 (Public review):

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

Reviewer #2 (Public review):

Summary:

In this manuscript, Martins et al. examined the cooperative response of E. faecalis cells to beta-lactams, in both planktonic culture and in biofilm. They found that the competition outcome between the susceptible and resistant strains is frequency dependent; they have also quantified how the competition curves change with inoculation OD and antibiotic concentration. To the authors' surprise, the competition dynamics are not that different in biofilm and in planktonic culture, which the author attributed to the unstructured nature of the thus-grown E. faecalis biofilms, quantified through correlation analysis. Using a well-mixed model capturing growth, death, and drug degradation by the resistant cells, the authors were able to quantitatively capture the experimental observation.

Strengths:

Overall, the data presented are solid. Although there is not much surprise after the understanding that the E. faecalis biofilm is unstructured, the manuscript still provides a useful "null case", so to speak, for researchers in the field when considering antibiotics in the context of biofilm. The theoretical model presented and the procedure of fitting the experimental data are useful to the research community.

Weaknesses:

One clarification the author should make is on the biofilm growth process. Specifically, could staining experiments be performed to demonstrate the secretion of the extracellular matrix? Just by looking at Figure 1b, it is hard to say. It remains a question whether the biofilm culture simply contains unstructured clusters rather than real biofilms (that are usually structured).

Reviewer #2 (Public review):

Astrocytes are highly responsive to their environment and play a range of critical roles in brain function. Lituma et al. theorize that one mediator of that responsiveness is the regulation of RNA stability. They therefore undertake an assessment of astrocytes missing Upf2, a protein required for mRNA degradation via nonsense-mediated decay. This is an interesting study, approaching astrocyte biology from a novel angle. The authors take on an ambitious set of experiments, spanning morphological assessment, synaptic engulfment, electrophysiology, behavior, and calcium imaging.

The authors show convincing data that knocking out Upf2 in astrocytes impairs synaptic plasticity, affects behavior, and changes the complement of astrocytic mRNA. These results, in and of themselves, are intriguing and suggest that NMD is an important biological process in astrocytes, warranting further study.

My primary concern is whether the authors may be largely studying dying cells. The idea that NMD disruption has a dramatic effect on astrocyte morphology is an intriguing idea, but it is not fully established here. The nuclei in the example cKO morphology images appear small and/or fragmented. This raises concerns that the authors did not ensure that they had the full 3D morphology of the astrocyte in the section, and the cell is in part cut off, which would compromise any data on the morphology. The authors state that the tissue was sectioned at 70 um. The diameter of an astrocyte in the adult mouse brain is typically between 50 and 70 um. Unless astrocytes are perfectly positioned in the center of the slice, at this thickness, the majority of astrocytes will almost certainly be partially cut off. More detail on how cells were chosen and what quality control metrics were implemented would alleviate concerns here. An alternative possible explanation for these small/fragmented nuclei is that cKO astrocytes may be unhealthy to the point that they are actively dying. Using the transgenic ZsGreen label, the authors state that they observe a size change (Figure S4); this is not readily apparent and is not quantified in any way. It does appear from these images that there may be a loss of some astrocytes; cell death, which would also be an interesting finding, is a fundamentally different process than morphologic restructuring in living cells. The authors do attempt to count astrocytes (Figure S6B), but do so with GFAP. This is a fundamentally flawed approach. Because GFAP is not readily detectable in most healthy astrocytes in most gray matter regions, GFAP should not be used to quantify astrocyte numbers; this experiment should be repeated with a better marker, such as Aldh1l1, Sox9, etc.

Synaptic engulfment: This is an extraordinarily high degree of engulfment in the control animals compared to many published studies, leading to concern as to the technical approach. Indeed, the overall low level of PSD-95 signal in control conditions in adult mice is concerning as to the technical accuracy of the approach. It is unclear exactly how the investigators labeled the astrocytes; presumably via the ZsGreen label, but it is never stated, and the only images shown are the highly processed Imaris renderings. The small astrocytic processes, or leaflets, that make up the vast majority of the astrocytic arbor are on the order of 100nm in diameter. The processes shown in Figure 2B are, according to the scale bar, at least 20x that size. It is difficult to have much faith in these results as currently presented.

The signal-to-noise ratio of the GCaMP experiments is worryingly low, likely responsible for the abnormally low dF/F in all conditions and the lack of significant change between control and CalEx, when control astrocytes should show a much higher GCaMP signal than any CalEx-expressing astrocyte. That said, the higher Ca++ in Upf2 KO astrocytes is intriguing. Given the roles of elevated calcium in cell death, this may reflect cells that are unhealthy to the point that they are starting to die.

The authors conduct a FACS-based analysis of astrocytic mRNA from control vs Upf2-KO, with intriguing results. An important caveat, though, is that a large amount of astrocytic mRNA is in the processes. If mRNA stability is being actively and rapidly regulated, it seems likely that the mRNA in the processes would be the most relevant population of regulated mRNA. FACS-based approaches to astrocyte purification will, as robustly shown elsewhere, strip off those processes. Particularly given that the authors have shown that the processes may be the most actively changing astrocytic compartment with Upf2 KO, this is a strange choice of technique vs. something like Ribotag that would preserve the mRNA in processes. At least, there should be some discussion regarding using FACS for this analysis and the consequences for profiling mRNA in astrocytic processes.

Minor points:

(1) The use of the Aldh1l1-CreER mouse is a strong choice and has been shown to be highly astrocyte-specific. Combining that transgenic mouse with viruses driven by different forms of the GFAP promoter is quite bizarre in several ways. First, GFAP-dependent AAVs have been shown repeatedly to have significant neuronal leak. Second, these mice are, in all cases, receiving two different viruses, driven by different forms of the GFAP promoter, and the non-Cre virus is not Cre-dependent (vs. a much more standard approach of using a Cre-dependent second virus to ensure that all analyzed cells received both viruses). The authors mention that "this experimental design ensures that phenotypes are not caused by an acute effect of tamoxifen." It is certainly true that tamoxifen is not a biologically neutral molecule. However, the mice still receive tamoxifen, both in these morphology virus experiments and in almost all other experiments. This experimental approach is not inherently bad, nor does it necessarily invalidate the data (although the near-certain neuronal contamination due to the GFAP promoter-driven viruses is a concern). It is, however, convoluted in ways that appear unnecessary. If there is a strong rationale for this approach beyond the tepid explanation already present, it should be explicitly mentioned.

(2) The characterization of the knockout is incomplete. While the authors should be applauded for their attempts to phenotype the cells in which they observe Cre-mediated recombination, there are issues with their technical approach. Most importantly, and an issue that affects other analyses in the paper as well: the vast majority of astrocytes in the healthy cortex do not express GFAP. Therefore, using GFAP to claim high astrocyte specificity and efficiency is a fundamentally flawed approach. Second, MBP is a myelin marker, not a cytoplasmic marker, and would not successfully colocalize with a cytoplasmic marker like ZsGreen even if recombination in oligodendrocytes did occur. Third, recombination at one set of LoxP sites is not a reliable indicator of recombination at other sites. Recombination efficiency is highly dependent on the spacing between the LoxP sites and cannot be reliably extrapolated to other floxed genes without validation. Finally, the most likely culprit for off-target recombination with Aldh1l1-CreERT2 (or other astrocyte-selective Cres, and certainly the GFAP-based viral promoters) is neurons, which the investigators did not test for. Neuronal Aldh1l1-CreERT2 leak is most likely to occur in the hippocampus. With the images shown in Fig S3, it is unclear whether it is possible to convincingly colocalize Upf2 staining with a cytosolic marker of all astrocytes, such as Aldh1l1 or S100b, but such data would be more appropriate. An alternative approach to validation would be in situ hybridization.

(3) Supplementary Table 2 should include gene IDs, not just Ensemble IDs.

(4) It is not fully clear what the investigators are denoting as a spine in Figure 2E; the two images do not appear to have the large degree of difference that the quantification suggests. The oversaturation of the signal complicates assessment.

(4) A more detailed discussion of the rationale behind the timeline would be helpful. What is the half-life of Upf2, and how rapidly do NMD genes build up upon Upf2 disruption? In particular, in the case of virus experiments, the timeline is quite fast: ~2.5 weeks from injection to analysis. ssAAV expression takes over a week to reach appreciable levels.

Reviewer #2 (Public review):

Summary:

This is an interesting paper by the Unsain lab looking at the nanoscale organization of the membrane-associated periodic cytoskeleton in mouse sciatic nerve axons. The precise organization of the structure remains unclear, especially in vivo, and this manuscript significantly adds to our knowledge of this important structure. While some of the findings in the study are somewhat expected (though still valuable to see in an in vivo setting), an interesting observation is the presence of discrete nanoscale clusters that scale up with the size of the axon, which challenges previous assumptions.

Strengths:

Strong, convincing data; clever combination of imaging and analytical tools to make novel points; well written; excellent composition of figures.

Weaknesses:

(1) Figure 2A/3A: The large and small clusters of spectrin, as seen in cross sections, are unexpected and novel. The authors have done a clever job of combining imaging and analyses, but some things are still unclear. First, the authors should be consistent in their language when they talk about the spectrin clusters. Recommend precise language to define the small and large clusters when they first appear in the text, and then use the definitions consistently throughout the text. Second, based on the data shown, one does not get a clear idea of how the small and large clusters are organized along the longitudinal axis of the axon. In that context, are Figure 2B and C from imaging along the longitudinal axis? If not, it's unclear how the authors can conclude that the spectrin assemblies have a distance of ~170 nm along the linear axis. In general, a perceived limitation of this study is that while the authors have done a good job looking at cross sections, there is no information on the longitudinal distribution of spectrin in these axons. Looking at both cross- and longitudinal sections would also clarify details about the large spectrin clusters. For instance, are they small sausage-like structures, or long rods of spectrin running along the length of the axon? One assumes that all the analyses in Figures 3 and 4 are from the small clusters. Can the authors do a similar analyses of the large clusters? Finally, a schematic model showing both cross- and longitudinal- sections would make things clearer, but the authors would need to show the longitudinal data for that.

(2) It is interesting to think that the larger spectrin accumulations may be similar to the condensate-like structures seen by Boyer et al., as the authors mention in the discussion. In that context, it is possible that these focal accumulations are local reservoirs of spectrin that are also seen in mature axons (indeed, these accumulations were also seen in mature axons in the Boyer et al. paper, and they also speculated that these accumulations may be local reservoirs). Can the authors check if actin/adducin is also present in these larger spectrin accumulations?

(3) While talking about the nanoscale clusters, it is important to specify that the authors are talking about circumferential clusters. Though the writing is excellent, one still does not get the precise definition of "clusters" from just reading the abstract, and it would be good if the authors could work on that more (I recognize that this is not easy to do).

Reviewer #2 (Public review):

Summary:

The authors investigate the dependence of phage adsorption rates on host metabolic state, using 5 coliphages that differ in their infection cycles and host receptors. They find that four of the 5 phages showed significantly reduced infection under low metabolic states, with phage that generally have weaker adsorption being more strongly affected by low metabolism. The authors complement their findings with a 2-step infection model where phages can disengage from their hosts after initial adsorption. The paper illustrates the power of standardized experimental protocols for quantitative trait comparisons and highlights the dependence of phage infection success on host physiology.

Strengths:

The paper is well written and clearly structured.

The experiments are well designed and particularly commendable is the diligent use of control scenarios to allow for quantitative comparison between phages. This standardized protocol will be valuable for the entire phage community.

The authors convincingly show the impact of host physiology on phage adsorption success. This dependence has so far mainly been considered for intracellular phage replication and the paper shows that host physiology has to be taken into account at all steps of phage infection.

Reviewer #3 (Public review):

Summary:

The primary objective of this study was to establish a practical and functional framework for propagation of stable transgenic cell lines of Blastocystis, a common animal gut microeukaryote. Although the work focused on Blastocystis ST7-B, a subtype with relatively low prevalence in humans, this choice is justified by its association with more frequent negative health effects. Beyond their relevance to the medical field, the methodological advances described here have the potential to also expand cell biology studies of this anaerobic organism, including its unusual mitochondria and redox metabolism.

Strengths:

Prior to this work, genetic tools for Blastocystis were very limited, relying on a single strong promoter-terminator combination. The authors successfully expanded the available promoter set across a range of expression strengths by testing two dozen variants in luciferase-based assays. Critically, they developed an integrated workflow from a modular transgenic construct design to an expanded inventory of molecular components (promoters, reporters), optimized DNA delivery, stepwise antibiotic resistance-mediated clonal selection and propagation, and to reporter validation. The evaluation of several anaerobiosis-compatible labeling strategies for live (and fixed) cell optical imaging will be particularly useful, with the SNAP-tag system appearing especially promising for Blastocystis.

Weaknesses:

The presented data generally provide a solid support for the conclusions that the work reached, but clarification of reasoning and several inconsistencies, as well as amendments to visual presentation of the data would be highly beneficial, as detailed below.

(1) Episomal persistence of the construct:

The manuscript repeatedly assumes, including in its title, that constructs persist in Blastocystis in their episomal form, but no direct evidence is provided. Although this interpretation is plausible, it should be identified more clearly as provisional. Nuclear genomic integration (e.g., via NHEJ) remains a possible explanation unless supporting evidence or rationale is provided to exclude it. Testing whether the phenotype persists without drug-mediated selection in the generated transgenic cell lines would help strengthen the case for episomal maintenance.

(2) Promoters and terminators:

(2.1) There is a discrepancy between the claimed number of loci (14), from which promoters used to drive luciferase expression were derived, and those detailed as having been actually generated in Table 1 (11). This inconsistency should be corrected or explained, as it creates uncertainty around the accuracy of the dataset.

(2.2) Based on the presented evidence, constructs benchmarked in bioluminescence assays differed only in their promoter composition. Although terminator selection is mentioned in the Methods section, no additional details are provided; for instance, Table 1 and Figure 2 only list 23 promoters in total. Figure 2A likewise shows only promoter-dependent variation. If the terminator was held constant (LeguP1?), this should be stated explicitly. The authors may then consider revising the wording of having tested "23 promoter-terminator pairs" to better reflect that only promoters varied.

(2.3) Promoter benchmarking was done with a plasmid lacking a selection marker, so it is unclear how the maintenance of the luciferase construct was ensured. Without selection, the observed reporter intensity could reflect differential or stochastic plasmid retention rather than promoter strength alone. The luminescence assay was performed 16-18 hours after transfection, but the rationale for this particular timeframe should be explained. In this context, the authors should explicitly state whether the experiments shown in Fig.2A represent biological triplicates or technical triplicates from a single transfection.

(3) Figure 2:

(3.1) Several aspects of the current design may lead to ambiguity for the reader. The boxplots are colour-coded, but it is unclear whether the colours carry meaning or are purely decorative. Because the data are already spatially separated into bins, additional random colouring is redundant and may suggest distinctions that are not intended. In addition, the part A of Figure 2 is split into two panels with the scale for the left panel shown in the right panel and some of the boxplot colours falling in the range of the scale, but not in line with their counterparts in the left panel. Because the colour use is not consistent, it is difficult to tell whether the same scale should be applied to both panels or how it should be interpreted.

(3.2) The left panel of the part A uses a diverging blue-white-red colour scheme, which is most appropriate when the midpoint represents a meaningful central value such as zero. Because the values shown in this graph are only positive, a non-diverging 2-colour scale or a colour palette such as 'viridis' would make the plot easier to interpret.

(3.3) A black background should be avoided: 'B' and 'C' labels are invisible and it draws attention to a distracting design feature rather to the data themselves.

(4) Figure 3:

(4.1) Individual snapshots should be separated more clearly, either by using a white background or by adding visible borders to make the overall composition clearer. As currently displayed, some boundaries between fluorescent channels resemble image artifacts rather than intentional panel divisions.

(4.2) In the parts B-D, the legend should explain more clearly what each image shows and the figure itself would benefit from annotations. There seem to be three sub-panels in each 'condition' of part B (as well as C and D): while the middle and rightmost panel can be easily inferred to represent the fluorescent protein and bright-field image, what the leftmost panels represent is not specified. If DAPI was used to dye DNA, an explanation why mostly multiple labelled regions are visible should be provided.

(4.3) Cell morphology and appearance differ markedly between UnaG/smURFP and SNAP-tag images, which should be explained. A microscope issue is mentioned in the main text, but if that was the cause, the authors should consider replacing the images as the current distortions complicate interpretation.

Comments on revised version.

The revised version provides sufficient clarity and appropriate visual presentation. Some confusion evidently arose due to my misunderstanding, so I thank the authors for their comprehensive clarifications and patience.

Reviewer #3 (Public review):

Summary:

This paper examines the loss and re-evolution of specific organs during the evolution of ants. The authors show that these organs, the ocelli, disappear and are re-evolved in different ant species, and in different ant castes within these species. The Authors show that this is linked to a conserved GRN discovered in Drosophila, that appears to underlie the development of the ocelli, and demonstrate that this GRN appears to remain active in the developing heads of ants that have no ocelli- implying that it is the evolutionary latency of this GRN that allows loss and subsequent evolution.

Strengths:

This manuscript has outstanding imaging of a very difficult developing organ, and the key data, fluorescence in situ hybridisation, is done well and clearly shows what the authors wish to demonstrate. The methods are well described and underpin the whole work.

The authors convincing demonstrate that gene expression patterns imply the conservation of the ocellus gene regulatory network from Drosophila to ants. They further show that this network is present even in ants that don't produce an adult ocellus, but do show that in those species, loss of a developing nascent ocellus (which they identify) occurs at the same time as an interruption in the expression of the key genes in the GRN. All of this data is beautifully presented and explained.

Weaknesses:

There is one key weakness in that there are no functional students that indicate that the GRN actually does make the ocellus, though the expression patterns are convincing. This applies to loss of the ocellus as well. It would be nice to see that transient loss of the ocelli GRN might lead to loss of ocelli in ant species that have them. These are very difficult things to achieve as the key genes have earlier developmental roles, such that CRISPr knockouts would not be interpretable, and transient RNAi in the head capsules of developing pupal ants would be challenging.

As the authors note in their response this is very difficult to achieve. While the addition of this data would raise this manuscript to an outstanding one, I think the data presented is solid, well-presented and provides novel insight.

Reviewer #2 (Public review):

Summary:

Building on earlier studies, the authors report a role for pol kappa in mediated cisplatin resistance. Their data on dispensability of pol kappa catalytic activity for cisplatin resistance is consistent with previous reports. They further demonstrate that the PIP box of pol kappa is critical for cisplatin response. Based on these observations, the study concludes that targeting pol kappa and PCNA interaction can be a viable approach to overcome cisplatin resistance.

Strengths:

Indications that interaction between Pol kappa PIP box and PCNA can be targeted to overcome cisplatin resistance.

Weaknesses:

(1) The study has used a model of cisplatin resistance and found that the phenotype is specifically reliant on upregulation of Pol kappa. They also observe that in this model of cisplatin resistance, there is rapid degradation of multiple repair proteins, including ATM, ATR, HR and NHEJ proteins upon knocking out Pol kappa. However, it is unclear how the resistant model was derived. Also, since the data and almost all experiments in this manuscript were performed with a single model of cisplatin resistance, the conclusions should be taken with caution.

(2) There are also inconsistencies in findings. Increased G2 arrest and no change in origin firing are being observed despite a significant reduction in Chk1 protein levels.

Reviewer #2 (Public review):

Summary:

This study compares theta-burst stimulation (TBS)-induced synaptic plasticity in hippocampal CA1 slices from rats and non-human primates (Macaca fascicularis). The authors report that while TBS induces persistent LTP in both species, only primate hippocampal slices exhibit synaptic tagging and capture (STC) under these conditions. They further show increased BDNF and PKMζ expression following TBS in primates and propose that a redundant BDNF/PKMζ signaling architecture supports persistent plasticity in primates, whereas rodent TBS-LTP depends primarily on BDNF. The work aims to identify species-specific specializations in associative plasticity with implications for translational neuroscience.

Strengths:

The topic is potentially important because direct comparisons of hippocampal plasticity mechanisms between rodents and primates are rare.

Weaknesses:

(1) Limited biological replication in the primate experiments

The manuscript's strongest claims rely on data obtained from 36 slices from 7 monkeys, qPCR analyses with n=3 biological replicates, and Western blot analyses with n=3 biological replicates. The effective sample size for species-level conclusions is therefore not large. The manuscript frequently treats slices as independent observations while drawing conclusions about species differences. This is particularly problematic for electrophysiological experiments because multiple slices appear to originate from the same animals. The statistical unit should be the animal, not the slice, unless nested analyses are performed.

The authors should (1) report the number of animals contributing to each experiment, (2) provide animal-level analyses, (3) use mixed-effects or hierarchical models where appropriate, and (4) clarify whether multiple slices from the same monkey contributed to the same experimental condition. Without these analyses, the evidence for species-specific mechanisms remains weaker than presented.

(2) The central STC conclusion requires stronger controls

The most important result is that TBS supports STC in primates but not rats (Figures 1F-G). However, several alternative explanations are not excluded. For example, only a single interval (30 min) between TBS and WTET is examined. Classical STC studies characterize tag duration, PRP availability window, and temporal asymmetry. The current work does not determine whether primates exhibit longer tag persistence, increased PRP synthesis, altered capture efficiency, or merely a shifted temporal window. A temporal series (e.g., {plus minus}15, {plus minus}30, {plus minus}60, {plus minus}90 min) would substantially strengthen the mechanistic interpretation.

(3) Species differences may reflect tissue quality or preparation differences

The manuscript compares 5-7 week-old rats with 5-7 year-old monkeys. These are very different developmental stages. Moreover, euthanasia methods, extraction procedures, and postmortem handling are different. These factors can affect BDNF expression, protein synthesis, LTP magnitude, and transcriptional responses. The authors should discuss these caveats more explicitly.

(4) Statistical reporting is incomplete

Many comparisons report exactly Wilcoxon p = 0.0313 and U-test p = 0.0022, across numerous experiments. This suggests very small sample sizes and discrete nonparametric distributions. The manuscript should report exact n values for each comparison, effect sizes, and confidence intervals.

Second, many genes and proteins are tested. No correction for multiple testing is described. The authors should state whether corrections were applied, and if not, justify this choice.

(5) Interpretation and significance

The study addresses an important and understudied question: whether associative synaptic plasticity mechanisms differ between rodents and primates. The finding that TBS can support STC in the primate hippocampus is potentially novel and impactful. However, the mechanistic evidence remains incomplete, the molecular analyses are underpowered, and several key controls are missing. At present, the data support the conclusion that under the specific experimental conditions tested, TBS-induced plasticity in primate hippocampal slices exhibits greater associative persistence than in rat slices.

The stronger claims regarding evolutionary specialization, fundamentally distinct plasticity rules, altered STC thresholds, and redundant BDNF/PKMζ architecture require additional experimental support.

Reviewer #2 (Public review):

Summary:

This is an important contribution to science, not only because large-scale replication studies remain rare despite their value, but also because this one focuses on research that was under represented in previous large-scale efforts. The findings reveal concerningly low replicability in this field, pointing to a problem that warrants immediate attention. Particularly noteworthy is the study's sampling strategy: by randomly selecting experiments from a wide range of publications based on methods, rather than filtering by research area, importance, or citation counts, the authors have produced results that are potentially more representative of the broader literature than those of previous large-scale replication projects in this and other fields. Overall, this is a fantastic contribution that I will be recommending and using in all my open science talks, and from which I have learned a great deal. Congratulations to the team!

Strengths:

A study of this scale inevitably requires an enormous amount of work and methodological care, and this one is clearly both robust and thoughtfully designed. I want to particularly acknowledge the considerable efforts the authors have made to ensure the robustness of their findings. The use of multiple approaches to estimate replicability, combined with a substantial battery of sensitivity analyses, including a multiverse approach on top of everything else, clearly reflects the authors' genuine commitment to understanding their results and the limits of their conclusions. The transparency and sharing of all protocols, materials, and challenges and limitations encountered is also outstanding.

Weaknesses:

There were several instances during my reading of the methodology where I felt the authors relied too heavily on the external supplementary materials, at the expense of basic detail in the main manuscript. I appreciate how overwhelming it can feel to integrate more into an already substantial paper, but without some minimum integration, the reading experience and overall comprehension are too often compromised, at times posing more questions than answers. And it is unrealistic to expect most readers to engage with the extensive supplementary materials provided. Please see the comments below for specific suggestions.

Additionally, I found the discussion rather underdeveloped. There is relatively little engagement with the broader literature, not only with replicability studies from other fields, but more generally with relevant meta-research work on publication bias, blinding, risk of bias, citation practices, etc. Some of the most novel and interesting findings in the paper also receive less attention than they deserve, and the discussion at times reads as a repetition of the results section rather than a critical engagement with them. I would encourage the authors to engage more deeply here, as the study clearly has much more to say. Doing so would further highlight why this study is important for the answers it provides and the questions it can spur. Again, please see the comments below for specific suggestions.

Specific suggestions:

Page 1, abstract: "while t values for replications were positively correlated with researcher predictions about replicability, and negatively correlated with the rate of publications by the original article's last author" - I need to address the question: why t values and not effect sizes, p values, or something else? Update after reading the study: although the authors used others, they seem to place more emphasis on t values, which is not well explained. Without a clear explanation, it just left me wonder why, given that effect sizes would, in principle, be more information.

Page 2, paragraph 2: "reproducibility (defined here as reaching the same results when analyzing a set of data)" - In my opinion, this definition is vague enough that it encompasses not only reproducibility (same data, same methods) but also robustness (same data, different methods), and I would therefore recommend providing a more precise definition. The same applies to replicability (different data, same methods), since the definition used does not highlight the importance of using the same methods, and thus also encompasses generalisability (different data, different methods). Explicitly clarifying these distinctions is particularly important as the field grows and the terms become increasingly mixed up and confusing.

Page 2, paragraph 3: "All of these issues raise concerns about the replicability of published results - something that has not been evaluated systematically in the country" - I would suggest providing more information about why those factors may lead to expected lower replicability, ideally with a couple of sentences supported by references. As it stands, less experienced readers may not follow the argumentation and may consider it speculative.

Page 3, paragraph 2: "We then opened a public call for Brazilian labs that could replicate experiments using these methods and models, advertised by email, social media and lectures in conferences and institutions, to which 73 labs initially responded" - Since recruiting is an important component of this study, I would recommend providing additional details so the reader can better assess how comprehensive and unbiased the recruitment process was. AND Page 5, paragraph 2: Please provide more information about this open call: how was it advertised, where, and when? This is needed so that the reader can assess its comprehensiveness and potential biases. Even the link provided is not specific enough to understand the process, as it only states: "Calls were open to participants > 18 years old with current or previous experience in experimental research in any field and were advertised via e-mails, lectures and social media."

Page 3, paragraph 2: "Based on the expertise of respondents and a feasibility analysis by the coordinating team, we selected 3 outcome assessment methods for replication" - Since this choice determined what was ultimately studied and who could participate, I would like to see more information to understand it: was it based on the most common expertise among respondents? How was feasibility defined and estimated?

Page 3, paragraph 3: How was the manual screening performed? Was it done by one or more people? Was there double-screening to ensure reliability of the screening protocol? Did the authors use a specific decision tree or tool? How were conflicts between observers resolved? Were any other validation steps taken to ensure reliability? The same comments apply to the data extraction (who, how many, validation, protocol, etc.).

Page 3, paragraph 3: As a non-expert, I would need more context about the expected average cost of experiments in this field; otherwise, I cannot assess how representative this sample is or whether potential biases may exist (e.g., cheaper experiments perhaps being expected to be less replicable than more expensive ones). Could expected costs also have affected the reduction in geographical coverage eventually observed in this study (Figure S3)?

Page 6, paragraph 2: "(on a scale of 1 to 5)" - Could you clarify whether 1 means no deviations and 5 means everything deviated? Is that how it was phrased to participants? Was there a threshold used by the coordinating team to decide how many deviations were acceptable? (I would briefly clarify all scales mentioned below to allow easier interpretation throughout.)

Page 6, paragraph 4: How were long-text answers (e.g., justifications) reviewed? Was this done manually by one or more members of the coordinating team, or using any text interpretation tool? What steps were taken to ensure the interpretation of these answers was as objective as possible?

Page 8, paragraph 1: "If issues were found, the lab and coordinating team reviewed them via email until the sources of errors were identified and corrected (see https://osf.io/58vsx for details)." - Could you please provide information about how often these disagreements arose and briefly explain their causes? I am struggling to understand why these discrepancies occurred and how frequently. Without more detail, the error rate presented in the next paragraph is a little concerning.

Page 8, paragraph 4: Please provide the version of any package or software used throughout, and make sure to cite R appropriately (R Core Team XXX). In addition, did the authors calculate the log ratio of means (ROM/lnRR) using escalc()? If so, please report this. If not, I would recommend doing so, as escalc() implements recommended small-sample adjustments that produce slightly different values compared to a simple manual calculation of log(mean1/mean2).

Page 10, paragraph 1: "Coefficients of variation from the original study were compared to the mean coefficient of variation of its replications using Wilcoxon's signed rank test" - I wonder how these CVs were calculated - whether simply as SD/mean or using escalc() from the R package metafor, which includes a correction for small-sample size. This may affect the fairness of the comparison, particularly since CVs from original studies are expected to be slightly overestimated given their smaller sample sizes relative to the replications. I also have concerns about using the mean CV of all replications and comparing it to a single CV value, as this ignores the uncertainty around that mean. An additional check could involve calculating the log coefficient of variation ratio (lnCVR; Nakagawa et al. 2015, Methods in Ecology and Evolution; implemented in escalc()) between the original CV and each replication CV, and running a random-effects (or multilevel) meta-analysis that accounts for shared-control non-independence. I believe this would provide a more robust approach, as it does not ignore the uncertainty around the mean CV of the replications - uncertainty that, if neglected, is expected to increase the likelihood of false positive findings. This concern would also apply to the subsequent analysis on absolute means.

Page 10, paragraph 2: The change in geographical distribution shown in Figure S3 appears rather striking, with western states disappearing step by step. Should the reader be concerned about the eventual geographical representability of the sample?

Page 15, Figure 3A: I wonder whether adding 95% CIs calculated from the sampling variance of each ratio would improve interpretation and help readers appreciate the real differences between the dots (i.e., means) - along the lines of a forest plot.

Page 17, section "Predictors of replication success": It is unclear to me how the decision was made about which results from Figure 4 to present in the text. Intuitively, given that correlations were calculated for both t values and lnRR (and other metrics), I would have expected that whenever a result is highlighted in the text, the authors also report how it changes depending on the metric used - for example, the interesting result regarding the 5-year number of publications, whose correlation is notably lower when using lnRR (−0.31 vs. −0.18). Presenting this nuance in the text would reduce the risk of inadvertently giving the impression of cherry-picking.

Page 23, paragraph 1: (this comment should have come during the first % reported, but only in the discussion I realized how important this would be for comparing estimates) I wonder whether the authors should calculate 95% confidence intervals for all their percentages (and those of Errington et al.) using the Wilson method via the function binom.confint() in R, which handles extreme proportions (0% or 100%) more gracefully. This would ensure that uncertainty around these percentages is not neglected and would aid interpretation when comparisons are made. In addition, in the next sentence, the authors are comparing correlation coefficients, at least verbally, these could in principle be transformed into Pearson's r and assigned 95% confidence intervals following meta-analytic workflows, which would better allow us to assess whether these correlations are meaningfully larger or smaller, and help avoid potentially misleading arguments.

Page 24, paragraph 2: The following result is really interesting and I would love for the authors to expand on it a little. There must be other meta-research studies that, despite not studying replicability directly, have explored a similar predictor: "Other features of the original article were generally uncorrelated with replication outcome, although large rates of publications by the last author were associated with lower replicability, suggesting that incentivizing publication volume may be counterproductive for the reliability of results."

Page 25, paragraph 1: I believe the authors could explore if there is evidence for "incorrect labeling of error bars (Cumming et al., 2007; Vaux, 2004)" by plotting log(SD) vs log(mean) across all original studies, and exploring if large outliers (i.e., points largely deviating from the positive regression) exist. That should provide some insights into whether some values reported as SD in the original studies were indeed SE, which I am assuming is what the authors of the study are referring to when they say "incorrect labelling of error bars" here.

Code: I could not engage with the data and code, but I would like to highlight that the organisation and clarity of the GitHub repository is of high quality.

Reviewer #2 (Public review):

Overview:

This study integrates several datasets into a unified modeling framework that incorporates several mechanisms thought to impact the spread of ESBL-resistant bacterial strains. The model accounts for tradeoffs between persistor and colonizer strains, travel rates, antibiotic treatment and strain clearance, direct competitive interactions, and, most importantly, a series of distinct costs associated with the carriage of ESBL resistance. The resulting 75-compartment model is internally consistent and structurally neutral. However, the parameter estimation is flawed in many ways, compromising the interpretations of the model.

On the usage of the Swedish infant data set to estimate colonization and persistence:

First, while other papers have taken similar approaches, the Swedish infant data set is fundamentally inadequate to estimate colonization and persistence rates. This is because very few colonies were typed per sampling event (2 to 6 colonies per event). The original authors themselves argued that strains of indistinguishable morphology would not be able to be differentiated by this method. They also provided data showing that strain identity was not directly related to colony morphology (same strain often displaying distinct morphologies).

The consequence of this is that strains present in low abundance would be missed with a high likelihood. However, if they were to be stochastically sampled, this would count as a "colonization" event, and if they were missed in subsequent samplings, this would count as a "loss" event. In other words, the statistical methods described conflate within-host dynamics (which might lead to distinct within-host abundances) with between-host dynamics (colonization and loss).

Beyond this conceptual issue, some technical aspects aren't particularly sound. The mean of the inferred posterior for the lambda and mu parameters are then used to calculate the beta, gamma, d, and epsilon parameters through a linear regression. The more technically correct way of doing this would be to directly infer these parameters from the data and obtain a full posterior for these parameters.

This highlights another issue: these parameters are passed down to the next statistical model as point estimates, with no associated uncertainty. This artificially inflates the (already low) confidence of the estimates for the cost parameters.

Finally, when this procedure generated parameters that were inconsistent with their expectations (clearance is too high to explain prevalence in France), they adjusted the parameters by discarding and recalculating their beta parameters to artificially enforce neutrality between their strains and enforce the expected prevalence. This is problematic because beta and gamma were jointly estimated, and there is no particular reason why some of them should be discarded. The more natural interpretation would be that parameters inferred from Swedish infants do not translate well to French adults, which should preclude their usage in this context.

On the estimation of costs of ESBL resistance:

The core of the second statistical model is to use prevalence data, travel data, and treatment data in conjunction with the previously inferred colonization and loss parameters to infer the costs of carrying antibiotic resistance. Therefore, the accuracy of this section is contingent on an accurate estimation of the previous parameters. However, these colonization and loss parameters are inherited with no uncertainty (just point estimates are passed down), which, as previously mentioned, generates an artificially precise posterior distribution for the resistance parameters.

However, the most severe issue with the statistics lies in the choice of priors for the cost parameters. All of them are uniform in a positive range that implies a positive cost. Importantly, the average over a positive range will always be positive; therefore, this method will ALWAYS estimate a positive mean for the costs. Note that the posterior distribution of some cost parameters seems to peak around zero and abruptly decays with no mass to the left of zero. This is caused by the choice of prior. Had delta been allowed to be negative (i.e., antibiotic resistance carried a benefit, having the prior be uniform between -1 and 1), the posterior distribution would likely be much more symmetrical, and the confidence interval would have included 0.

Restating, because the prior is a continuous function between 0 and 1, it contains infinitely more mass in the region that represents there being a cost (delta>0) than in the region representing no cost (delta=0). This means that it is a mathematical impossibility for this model to infer the absence of a cost.

Therefore, the main finding of the paper ("We found that resistance is costly") is a mathematical artifact of the prior choice and of the model structure.

Reviewer #2 (Public review):

Summary:

This manuscript challenges the long-standing assumption that Yoda1 and Yoda2 are PIEZO1-selective activators. Using patch-clamp electrophysiology and calcium imaging in HEK293TΔPZ1 cells overexpressing PIEZO2, the authors demonstrate that Yoda1 potentiates PIEZO2 stretch-activated currents to a similar extent as PIEZO1 and slows PIEZO2 poking-current inactivation (albeit with lower efficacy). They further show that the more potent analog Yoda2 affects PIEZO2 at nanomolar concentrations and use mutagenesis and molecular dynamics simulations to propose that Yoda2's benzoic acid group forms a transient salt bridge with R1724 in the putative Yoda binding pocket, explaining its enhanced potency.

Strengths:

The authors are established Piezo/biophysics experts; the study is highly important, technically competent, and carries significant implications for the reinterpretation of prior work that used Yoda compounds as PIEZO1-selective probes.

The core finding that Yoda1 modulates PIEZO2 stretch currents is convincing and important. However, several conceptual, methodological, and presentational issues need to be addressed before acceptance, as detailed below.

Weaknesses:

(1) The abstract states that Yoda1 potentiates PIEZO2 "as efficaciously as PIEZO1." This claim is accurate only for stretch currents and single-channel open probability, but the paper itself demonstrates important asymmetries: i) Yoda molecules slow PIEZO2 poking-current inactivation ~2-fold, versus ~5-10 fold for PIEZO1 (Figure 3b and ref #60). ii) Spontaneous Ca²⁺ entry via PIEZO2 requires non-physiological conditions (high extracellular Ca²⁺, hypertonic solutions) that are unlikely to occur in native cells.

The abstract should be revised to clearly qualify where equivalence holds and where efficacy differences exist. IMO, the current wording risks overcorrecting the historical bias (PIEZO1-only) by going too far in the other direction.

(2) Related concern: the PIEZO2 Ca²⁺ signal in Figure 2 is only detectable using a Ca²⁺-boosted solution (CBS ie 30 mM Ca²⁺). Physiological extracellular Ca²⁺ and cells normally do not experience sustained hypertonicity at these magnitudes. The authors should explicitly clarify that the practical implication of their findings is primarily for electrophysiological (patch-clamp) experiments and that the Ca²⁺ imaging caveat applies only under amplified conditions. Specifically, the authors should state that in standard Ca²⁺ imaging assays with physiological buffers, PIEZO2 is unlikely to confound Yoda1 results.

Related point: Can cytochalasin D (CytoD) restore a Yoda1-dependent Ca²⁺ signal in physiological saline? This would help determine whether the weak PIEZO2 response is primarily a membrane tension issue (cytoskeletal tethering) versus intrinsically lower channel expression or permeability. The authors already have tagged PIEZO1/2 constructs and could, in principle, normalize by surface expression.

(3) The mean inactivation tau values for wild-type PIEZO2 poking currents in both DMSO and Yoda1 conditions (Figure 3b, approximately 15-40 ms range) appear substantially higher than values reported in published literature (typically 5-10 ms; eg, PMID: 20813920). This discrepancy needs to be addressed.

(4) The authors perform all MD simulations on a truncated PIEZO1 model and justify this choice by noting that the Yoda binding region is highly conserved between homologs. This is a reasonable and defensible starting point given the availability of well-validated PIEZO1 simulation set ups in their lab. A few points are nonetheless worth addressing: While PIEZO2 simulations are not strictly required, the authors are encouraged to briefly discuss whether any long-range structural differences between PIEZO1 and PIEZO2 (outside the binding site itself) could influence Yoda2 binding dynamics, particularly in light of the chimera data showing that PIEZO2 sequence in repeat A abolishes Yoda1 sensitivity. This reviewer still doesn't understand the reason behind this discrepancy despite it being acknowledged in the text.

Another MD-related comment is that three simulation replicas (which is impressive for such a big system) show markedly different salt bridge occupancy (82.6%, 49.7%, 99.8%; stated in the text). This wide variation suggests incomplete sampling in at least one replica. The authors should provide RMSD plots for ligand and protein backbone to assess convergence and possibly discuss whether the 49.7% replica represents a genuinely distinct binding mode or incomplete equilibration.

(5) The Discussion proposes that PIEZO2's weaker Ca²⁺ response to Yoda1 could partly reflect lower membrane expression. Since the authors already have fluorescently tagged PIEZO1 and 2 constructs, a simple fluorescence intensity comparison between the two (acknowledging it would reflect total rather than surface expression) could provide at least indirect support for this claim. Alternatively, if such a comparison is not feasible, the authors may consider removing membrane expression from the list of proposed explanations or explicitly acknowledging that this remains unsubstantiated speculation. The max poking currents may somewhat and roughly indicate the level expression difference too, if done exactly side by side.

(6) The abstract or concluding remarks should highlight that Dooku1 is not PIEZO1-selective in its agonist-like action on PIEZO2, and that Cmpd15/Cmpd64 appear to be better PIEZO1-selective tools. This nuance is buried in the Results section.

(7) The authors should not cite PMID 31015490. Clearly, any work on MCC13 is confounded by the overwhelming expression of PIEZO1 (PMID: 42084270). Instead, the authors should also cite the literature from others who have clearly recorded stretch currents from PIEZO2 before the cited studies (eg, PMID: 37590348).

Reviewer #2 (Public review):

Summary:

This study functionally characterizes a single KCNE-like gene, kcne0, from a jawless vertebrate. The authors conducted multiple experiments, including TEVC, VCF, RT-PCR, and RNA-seq to show that KCNQ1 and kcne0 exhibited a broadly overlapping organ distribution in lamprey species, and KCNE0 produced a constitutively active current when co-expressed with lamprey KCNQ1, similar to the effects of human KCNE3 on KCNQ1. This modulation was species-specific, as co-expression of KCNE0 with other species' KCNQ1 was less effective. Moreover, the authors found that truncating the N-terminal had a more significant reduction of the modulatory effects than truncating the C-terminal of KCNE0. Interestingly, the introduction of the tetra-leucine motif from human KCNE4 into KCNE0 conferred KCNE0 with comparable effects of human KCNE4 on KCNQ1.

Strengths:

The authors clearly introduced an early-diverging member of the KCNE family, and convincingly demonstrated the function of this gene, KCNE0. The results are supported by experiments of multiple approaches and are clearly written. The work is significant and will interest readers from the extended research area.

Weaknesses:

No major concerns were identified with the manuscript in general.

Reviewer #3 (Public review):

Summary:

In this manuscript, Boudjerna and Balagé et al. aim to elucidate the spatial origin of centriole amplification and the mechanisms behind the formation of an apical basal body patch in multiciliated cells (MCCs). To this end, they focused on the role of microtubules and developed new tools for spatiotemporal and high-resolution analysis of different stages of centriole amplification, including the centrosome stages, A-stage, G-stage, MCC-stage. Among these tools, the MEF-MCC cells grown on micropatterns stands out for its versatility as it is not tissue-specific and does not require epithelial cell-to-cell contact for differentiation. Additionally, the Cen2-GFP; mRuby-Deup1 knock-in mouse model was used to study different stages of centriole amplification in physiological brain MCCs. This model offers an advantage over the previously described Cen2-GFP model by enabling the resolution of early events in centriole amplification through the visualization of Deup1-positive structures and their dynamics. Finally, the authors leveraged powerful imaging techniques, including super-resolution microscopy, the U-ExM and high-resolution live cell imaging in order to detect and track centriole amplification, elongation, disengagement, and migration.

By combining the MEF-MCC and knock-in mouse model with spatiotemporal imaging in control and nocodazole-treated cells(treated acutely or chronically), the authors define the sequence of events during centriole amplification, revealing the critical roles of microtubules for the first time. Initially, the centrosome-mediated microtubule network forms, organizing a pericentrosomal nest from which procentrioles and deuterosomes emerge. Their findings indicate the importance of microtubules in recruiting and maintaining pericentriolar material clouds that contain DEUP1, PCNT, SAS6, PLK1, PLK4, and tubulins. Following the amplification stage, the procentrioles mature, leading to cells displaying numerous MTOCs, as demonstrated by regrowth experiments. Mature centrioles then disengage from deuterosomes, attach to the nuclear envelope, and migrate to the apical surface facilitated by microtubules.

Strengths:

The manuscript provides new insights into the regulatory function of microtubules and microtubule-based transport in different stages of differentiation in brain MCCs. Addressing the role of microtubules during different stages of centriole amplification required development of new tools to study brain MCCs, which will be useful in future studies of MCCs. A notable strength of this manuscript is the authors' thorough and quantitative spatiotemporal analysis of highly dynamic processes in MCCs. The precision and detail in describing these dynamic events are impressive and are further strengthened in the revised version through additional analysis and adoption of new methods. This comprehensive analysis advances our understanding of MCC biology regarding the involvement of microtubules.

Comments on revised version.

The revised manuscript is substantially improved, and given the scope, it is appropriate that it primarily establishes a detailed spatiotemporal framework. That said, a few points would further strengthen clarity and impact. First, several observations naturally raise follow-up mechanistic questions, for example whether additional cytoskeletal systems such as actin contribute to steps like centriole apical migration. A slightly more detailed framing of these open questions would help guide future work. Second, some terminology introduced to label observed microtubule-based structures (for example "nest") may not be essential. Finally, while the authors have increased quantification, some analyses would benefit from super plot-style displays with replicate-level comparisons, particularly for intensity-based readouts.

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.

Comments on revised version.

The authors have responded constructively to my major conceptual concerns. The distinction between DNA synthesis and replication initiation has been clarified appropriately. The additional insulation analysis substantially strengthens the argument that compartment maturation is not simply a consequence of changing loop extrusion dynamics, although I would encourage slightly more cautious wording regarding "independence" from cohesin-mediated extrusion. The peninsula model is now framed appropriately as a heuristic interpretation and supported by orthogonal imaging data. Finally, the discussion of conservation across cell types has been appropriately tempered. Overall, I believe the manuscript has been significantly improved.

Reviewer #2 (Public review):

Summary:

As a member of DspB subfamily, PRRT2 is predominantly expressed in CNS and has been associated with various paroxysmal neurological disorders. Previous studies have shown that PRRT2 interacts with Nav and Cav channels, modulating channel properties and neuronal excitability.

In this manuscript, Lu et al. demonstrate that PRRT2 is a potent regulator of Nav channel slow inactivation, promoting the development of Nav slow inactivation and impeding the recovery from slow inactivation. This effect is highly conserved in PRRT2s across species as well as among DspB family members (TRARG1 and TMEM233). The authors further confirmed the interaction between Nav channels and PRRT2 in heterologous expression systems as well as in Prrt2-V5 knock-in mice. Prrt2-mutant mice, which lack PRRT2 expression, require lower stimulation thresholds for evoking after-discharges when compared with WT mice.

Overall, this is a well-executed and methodologically comprehensive study. This work offers valuable insight into the physiological functions of PRRT2 and reveals a potential pathogenic mechanism underlying PRRT2-associated neurological disorders.

The revised manuscript has addressed most of the concerns raised by the reviewers and has been substantially strengthened, although I still have several concerns regarding the discussion section.

Strengths:

(1) Overall, this is a well-executed and methodologically comprehensive study. The electrophysiological data strongly support the conclusion that PRRT2 is a potent regulator of Nav channel slow inactivation. The observation that this regulation is conserved in PRRT2 across species and among DspB family members raises the possibility that altered regulation of Nav channels may also contribute to the pathogenesis of TRARG1- or TMEM233-associated disorders.

(2) Co-immunoprecipitation assay performed using brain tissue from genetically modified Prrt2-V5 knock-in mice provides convincing in vivo evidence for the interaction between PRRT2 and Nav1.2 channels.

(3) Prrt2-V5 KI mice show markedly reduced PRRT2 protein expression and display phenotypes similar to those observed in Prrt2-mutant mice, supporting an important role of PRRT2 in regulating neuronal and network excitability.

Weaknesses:

(1) Nav1.6 is also highly expressed in cortical neurons and is widely regarded as a major contributor to action potential initiation and sustained high-frequency firing. Given that PRRT2 similarly regulates the fast and slow inactivation of Nav1.6 and Nav1.2 channels, the potential contribution of Nav1.6 regulation to neuronal and network excitability should be discussed.

(2) Slow inactivation is generally considered to develop over timescales ranging from hundreds of milliseconds to seconds or longer. Therefore, the statement in Discussion (Page 13, line 381-382) that "slow inactivation develops on a timescale of tens of milliseconds to seconds" may not accurately reflect the conventional kinetic definition of slow inactivation and should be clarified.

(3) Page 14, line 417-430: "question about how Nav channel slow inactivation is regulated in cells that do not express PRRT2".<br /> PRRT2 is unlikely to be the sole regulator of Nav channel slow inactivation. Other molecules and signaling pathways may regulate Nav channel and contribute to neuronal excitability. In addition, neuronal excitability can also be regulated through modulating other Nav properties, such as long-term inactivation or slow recovery from inactivation, as well as through modulating the activity of other ion channels, for example, Kv7.2 and Kv7.3 channels. Therefore, PRRT2-negative cells may utilize alternative mechanisms to fine-tune neuronal excitability. In its current form, this paragraph somewhat overstates the role of PRRT2 and would benefit from a more balanced discussion.

(4) Page 50, Figure 7-figure supplement 2: It would be helpful to include representative traces of the 1st and the last (20th) compound APs in panels B and C.

Reviewer #2 (Public review):

The authors explore the sensation of stickiness from the point of view of whisker exploration and encoding in the trigeminal ganglion. In doing so, they develop methods for 3D whisker tracking to describe stick-specific parameters such as stick-slip rates and strain. Overall, the methods are strong, and the authors present the results appropriately. Overall, I think exploration of the sensation of stickiness is a great question.

My main criticism is in relation to the chosen stimuli, and I wonder whether the authors may have room to explore more naturally sticky materials and what this may mean for the animal.

(1) Chosen stimuli for stickiness:

Four different materials are used, with the aim of presenting animals with graded measures of stickiness. The results show that silicone stands out against the others; it's less clear whether the intermediate textures (Delrin and resin) may be truly intermediate in stickiness.

I wonder if the stimuli chosen were truly representative of the aim of providing a gradient of stickiness. Did the materials differ in other features, such as surface temperature, texture, etc., which could explain some results? The authors discuss this in terms of coefficients of friction and how these estimates are not quantified in relation to whiskers themselves.

Measures of stick-slip and strain with silicone vs other materials make intuitive sense. Could the authors add additional naturally sticky stimuli to exemplify the results? For example, adhesive, glue, or a sugary substance.

(2) Tracking methods and quantification:

The 3D tracking methods, which incorporate whisker twists, strain, and other fine features of whisker exploration, present an advance in terms of analysis of how whiskers may explore more complex, natural features of environments. The analyses and quantifications are all solid and robust. The technical approaches are well-prepared to take the work a step further in terms of stimulus choice.

(3) Peripheral coding of stickiness:

The authors report that some units respond preferentially to whisking on silicone and that this has to do with strain on the whisker. Is there a possibility to understand the nature or anatomy of these units and why they might be preferential for the sticky sensation? Can the location in the follicle be assigned? And/or would the methodology allow for assignment of where the specifically sticky-tuned units project centrally?

(4) Relationship to natural stimuli:

A piece missing from the paper is more discussion and exploration of why stickiness may be important for sensory coding, as well as potentially more naturally sticky stimuli. One could imagine that a mouse navigating the world could find stickiness attractive, if it were a source of sweet food, for example, or it could potentially be a sensation the animal prefers to avoid. Stickiness could also indicate contamination or a sticky trap, to be avoided. If the authors are able to add naturally sticky stimuli, the whisker exploration and encoding could potentially provide further cues towards the valence of stickiness for mice.

Reviewer #2 (Public review):

Summary:

This study integrates bulk and single-cell transcriptomic-derived eQTLs from two separate consortia (PRACTICAL and Finngen) to identify immune-cell-specific therapeutic targets in prostate cancer. Mendelian randomization and Bayesian colocalization have been used to produce druggable eGene modules through STRING and DrugBank.

This is an interesting study that is attempting to address risk-associated, immune-specific transcriptomic repertoires in prostate cancer. It is knitting together concepts of drug repurposing and prostate cancer immunogenicity. This is an entirely computational study, which would benefit from some wet lab experimental validation.

It is very tricky to attribute cell-type-specific responses, especially when the majority of genes involved represent cytoskeletal or stress responses, which are ubiquitous throughout the prostate microenvironment. This point is relevant for the drug repurposing section: if these drugs are targeting immune cell-specific repertoires, what would the response be of the entire environment? It would be useful to contextualize the validity of each proposed therapy in a specific prostate cancer context and the involvement of AR antagonism or radiotherapy.

Strengths and limitations of this study:

Strengths:

This is a scientifically interesting and potentially impactful study, particularly in its attempt to integrate immune-cell-specific transcriptomics, causal inference, and drug repurposing in prostate cancer. The methodology is well described, and the data (albeit limited) are well analyzed.

Limitations:

The central weakness is the overstatement of the conclusions regarding immune-cell-specific causality, without sufficiently contextualizing the biological meaning of the findings.

Highlighted genes, such as LMNA, XBP1, histone-related genes, and stress-response markers, are ubiquitous regulators involved in fundamental cellular processes, including ageing, unfolded protein response (UPR), integrated stress response (ISR), chromatin remodeling, proliferation, and metabolism. It is unclear whether these signatures truly represent immune mechanisms, or instead reflect broader inflammatory and age-associated biology expected within an ageing glandular organ such as the prostate.

Immune cell identity alone may not be sufficient to infer biological relevance because immune state characterization (e.g., exhausted versus functional T cells, or distinct macrophage/myeloid phenotypes) is largely absent from the current analysis. The assertion that specific immune populations are correlated with prostate cancer susceptibility is probably an overstatement unless the nature of these cells can also be characterized.

The interpretation of "causal variants" is not always specified, i.e., what phenotype is being associated: prostate cancer susceptibility, recurrence, progression, or treatment response (e.g. is there direct causality from immune-cell variants to prostate cancer?).

Overall, there is a need for stronger biological and translational contextualization: how do the identified pathways relate to ageing-associated inflammation, PIN, microbiome-driven inflammatory changes, and stress-response biology in the prostate gland? While the manuscript identifies network hubs and enriched pathways, it often stops short of explaining what these modules biologically represent or how they may influence prostate cancer development, progression, treatment resistance, or immune evasion.

There are additional publicly available spatial transcriptomic or single-cell datasets which could be used to validate whether the purported immune-cell-specific genes are genuinely enriched in immune populations adjacent to tumour cells. In the drug repurposing analyses, the current study does not explicitly handle prostate cancer subtypes such as HSPC, CRPC, NEPC, or DNPC and co-treatment with androgen receptor antagonism or radiotherapy.

Reviewer #2 (Public review):

In this manuscript, the authors utilize a combination of techniques to show that macrophage endocytic capacity is partially dictated by cell-cycle stage, that Mycobacterium tuberculosis (Mtb) more readily infects macrophages that are in G2/M -phases, and that bacteria that are internalized by macrophages at different stages of the cell-cycle experience different levels of intracellular stress (as reported by the redox state of the bacteria). Furthermore, the authors provide evidence that terminally differentiated macrophages retain memory of the cell-cycle stage that they were in prior to differentiation, at least in the context of endocytic capacity.

This work provides evidence for the growing idea that fundamental heterogeneity in both host and bacterial organisms can alter the host-pathogen relationship in important ways. However, based on the current data, I am not convinced that the manuscript establishes endocytic capacity as the causal link between macrophage cell-cycle stage and bacterial state. The main issue is that fluorescence-based sorting for cell-cycle stage is likely to covary with cell size. Larger cells, including those later in the cell cycle, may be more likely to fall into the "high" fluorescence gate, while smaller cells may be enriched in the "low" population. Therefore, the observed phenotypes may still be cell-cycle-associated, but the causal determinant could be a correlated feature of cell-cycle progression rather than endocytic capacity itself. This is a significant caveat because nearly all the data, including the live-cell imaging following individual cells, rely on 'total' fluorescence, which will scale strongly with cell size.

If the authors' conclusion that endocytic capacity is cell-cycle regulated holds true after appropriate controls, this would significantly advance our understanding of the causal interplay between host cell-cycle state, endocytosis, and Mtb physiology. However, an alternative interpretation is that the observed differences in Mtb uptake and bacterial redox state are associated with cell-cycle stage but are not caused directly by differences in endocytic capacity. For example, they could instead reflect other cell-cycle-linked changes in macrophage physiology, such as cell size, intracellular volume, metabolic state, or some other mechanism important for Mtb pathogenesis. If the authors find that their data are best explained by cell-cycle stage independent of endocytic capacity, this would still represent an important advance. However, in that case, the manuscript should clearly distinguish the association with cell-cycle state from the downstream effector mechanisms, which would remain to be determined.

Strengths:

The authors utilize various macrophage models for their studies, which is important considering the variability in macrophage behavior, as well as the growing evidence that differences between mouse and human macrophages are relevant for Mtb infection.

Weaknesses:

The most important caveat is the covariance between fluorescence-based reporters and cell size. This concern applies to both the sorting experiments, which directly measure total fluorescence, and the time-lapse microscopy experiments, in which the authors show total fluorescence rather than mean, area-normalized fluorescence in Figure 3C. This could be explained by biomass accumulation alone, rather than by a specific cell-cycle-dependent increase in endocytic capacity. Without distinguishing total signal from concentration or activity per unit cell area/volume, it is difficult to conclude that endocytosis itself is regulated by cell-cycle stage rather than simply scaling with cell size.

Although the authors provide some evidence that the mean GFP intensity, which more closely reflects concentration, differs between the sorted populations in Figure 3B, they do not report statistics for this comparison. Moreover, this control is not carried through the rest of the manuscript, including in key experiments such as Figure 2B. As a result, it remains difficult to determine whether the observed differences between "high" and "low" populations reflect cell-cycle state specifically or instead reflect differences in total reporter fluorescence driven entirely by cell size.

The evidence for cell-cycle-dependent effects would be more convincing if the authors included additional controls. For example, they could:

(1) Plot both mean GFP intensity and total GFP intensity in Figure 3B, ideally alongside an unrelated fluorescent reporter that does not vary across the cell cycle. This would help distinguish changes in reporter concentration from changes driven by cell size or total fluorescence.

(2) Sort cells based on an unrelated fluorescent marker and test whether the same phenotypes - infectivity, dextran uptake, bacterial redox state, etc. - differ between high- and low-fluorescence populations. If these phenotypes are specific to the cell-cycle reporter and not observed with an unrelated marker, this would strengthen the conclusion that the effects are linked to cell-cycle state rather than to fluorescence intensity, cell size, or sorting artifacts.

Reviewer #2 (Public review):

Summary:

Elley and colleagues induced a synthetic torpor-like state in rats (a non-hibernating species) by chemogenetically activating neurons in the medial preoptic area of the hypothalamus. They show that this state substantially reduced cardiac infarct size in an ex vivo ischemia-reperfusion model. They further report that protection persisted when ambient temperature was raised to prevent hypothermia, and used exploratory phosphoproteomics to identify candidate cardioprotective signaling pathways.

Strengths:

This is the first demonstration that a torpor-like state is cardioprotective in a species that does not naturally enter torpor, which meaningfully advances the potential clinical utility of synthetic torpor. The experimental design is logical, and the controls are generally appropriate. The characterisation of the responsible neuronal population using ISH against QPLOT markers adds mechanistic depth and supports the cross-species conservation argument. The phosphoproteomic analysis, though exploratory, generates plausible and biologically coherent hypotheses grounded in the hibernation literature.

Weaknesses:

The primary weakness is that the central conclusion - that hypothermia is not necessary for cardioprotection - exceeds the evidence. The thermoneutral groups were not demonstrably normothermic (36.4 vs 37.05{degree sign}C, p=0.44 with n=6), core temperature telemetry was absent in the majority of control animals contributing to the infarct endpoint, and the decisive test, i.e., a correlation between individual nadir temperature and infarct size, was never performed. Additional weaknesses include the absence of sex-stratified analysis despite known estrogenic contributions to torpor

Reviewer #2 (Public review):

Summary:

This manuscript addresses the question of mechanisms underlying the therapeutic effects of electroconvulsive therapy (ECT). Clinical efficacy of ECT in major depression (and other disorders) is well established and has often been assumed to be a direct consequence of seizure activity generated by the current application. However, as the authors point out, this explanation is unsatisfactory. A recent study (Rosenthal et al., 2025) provided evidence that ECT generates a wave of cortical spreading depolarization (CSD) in mice, and initial evidence that similar events were generated in patients undergoing ECT. Based on their observations, Rosenthal et al. proposed that CSD, rather than seizure, may engage plasticity mechanisms that contribute to the brain's clinical response to ECT. The current study adds to that prior work by reporting other consequences of CSD, in addition to sustained Ca2+ elevations. The current study also links EEG characteristics immediately following the ECT with the likelihood of generating a CSD, which can help optimize ECT parameters.

Strengths:

An important research topic, linking a large set of rodent studies with a limited clinical EEG data set.

The data acquisition and analyses appear to be of very high quality, and the main results are well illustrated.

Association between EEG characteristics linked to good clinical outcome matched by mouse EEG data linked to CSD.

Characterization of multiple consequences of CSD following ECT in the mouse brain.

Weaknesses:

The main characterization of CSD propagation comes from GCaMP Ca2+ measurements, as previously reported (Rosenthal et al., 2025). That prior study also provided key electrophysiological evidence of CSD with a DC shift after ECT in mice (supplemental data). Given the prior evidence for ECT-CSD, the additional measures shown in the current manuscript are fully expected. Thus, the 2-photon imaging of Ca2+ elevations following CSD (Figure 4) is consistent with prior 2-photon imaging studies of CSD, and the complex hemodynamic and pH changes are expected to contribute to propagation of EGFP fluorescence changes (Supplemental Figure 5). These data are well presented, but, contrary to the results section here, these results appear confirmatory rather than necessary to build a case that the key event generated by ECT is a CSD.

The authors state that "our conclusion that CSD is the primary driver of plasticity is based on its role in driving Fos expression" (line 472). Related to the point above, there is already a very well-established literature showing that CSD leads to rapid and robust Fos expression in rodent cortex, so this is fully consistent with prior work. The prior work, CSD-fos work, should be summarized and/or cited more clearly in the manuscript. Showing that Fos increases only in the hemisphere where there is a large CSD-Ca2+ wave is a clear demonstration of this. While Fos increases can certainly be well linked to plasticity in some experimental paradigms, the implication that Fos increases underlie CSD-induced plasticity and possibly therapeutic effects of ECT is not appropriate. Fos increases after CSD are a reliable marker of the very strong neuronal activation that occurs, but Fos increases are not specific for plasticity and can be activated by challenges that do not generate synaptic plasticity. A range of other gene expression changes have been identified with CSD and may contribute to adaptive plasticity; these could be mentioned alongside speculation about Fos. To support the main conclusions of this paper about CSD driving plasticity via Fos, Fos knockout or knockdown studies are needed, as has been used in prior plasticity studies.

Reviewer #2 (Public review):

Summary:

The Garbett et al. identified a critical need to begin to understand the interplay between the assembly, maturation, and elimination of excitatory and inhibitory synapses. They also detail the lack of reliable tools to address this gap in knowledge. Here, the authors developed synaptic reporters expressed by lentiviruses (mClover3-Homer1c, HaloTag-Syb2, and tdTomato-Gephyrin). They combined these reporters with resonance scanning confocal imaging to measure synapses over a 15-hour period during neuron development and in mature neurons in primary hippocampal cultures. Using these reporters in the same neuron, the authors compared the ratios of postsynaptic excitatory and inhibitory specializations that co-localize with presynaptic terminals during development and in mature neurons and found that they are stable across time points. Finally, the authors developed CRISPR/Cas9 tools (TKIT) to knock-in endogenous fluorescent tags (GFP/tdTomato-Gephyrin) or epitope tags (HA-Bassoon and HA-Homer1) to begin to study synapse dynamics using endogenous proteins. I believe this paper highlights an important gap in knowledge and begins to offer methodologies to determine the dynamic coordination between excitatory and inhibitory synapses.

Strengths:

(1) The experiments are well-designed and carefully controlled.

(2) The authors carefully validated the reporter and TKIT constructs.

(3) The authors provide strong proof-of-principle for the use of the reporter constructs to track synapse formation, maintenance, and elimination over a 15-hour period.

(4) Ingenious use of technologies (reporters, TKIT, and resonance scanning confocal microscopy) to develop a platform for future studies of synapse dynamics.

(5) Strong evidence supporting that the ratio of excitatory and inhibitory synapses (those that oppose syb2) stays constant through development.

Overall, this is a well-executed study that develops tools to simultaneously image excitatory and inhibitory synapse dynamics and represents an important first step to address the fundamental question regarding the coordination between these two types of synapses.

Comments on revised version:

The authors addressed all my questions and comments. Their edits have made this paper significantly stronger. I believe that this is an important paper for the field.

Reviewer #2 (Public review):

Summary:

This study investigated how the human brain responds to vocalizations from multiple primate species, including humans, chimpanzees, bonobos, and rhesus macaques. The central finding-that subregions of the temporal voice areas (TVA), particularly in the bilateral anterior superior temporal gyrus, show enhanced responses to chimpanzee vocalizations-suggests a potential neural sensitivity to calls form phylogenetically close nonhuman primates.

Strengths:

The authors employed three analytical models to consistently demonstrate activation in the anterior superior temporal gyrus that is specific to chimpanzee calls. The methodology was logical and robust, and the results supporting these findings appear solid.

Weakness:

The authors only tested vocalizations from three non-human primate species other than humans. In this case, the species specificity of the effect does not fully represent the specificity of evolutionary relatedness.

Comments on revised version.

I have no further comments.

Reviewer #3 (Public review):

Summary:

This study investigates the functional differences between barrel and septal columns in the mouse somatosensory cortex, focusing on how local inhibitory dynamics (particularly involving SST⁺ interneurons) may mediate temporal integration of multi-whisker (MW) stimuli in septa. Using a combination of in vivo multi-unit recordings, calcium imaging, and anatomical tracing, the authors propose a model in which Elfn1-dependent synaptic facilitation onto SST⁺ interneurons contribute to the distinct sensory responses to MW input in barrels and septa, enabling functional segregation between these domains.

Strengths:

The study presents a thought-provoking and useful conceptual model for understanding sensory processing in the somatosensory cortex. While barrel columns have been widely studied, septal regions remain relatively understudied in mice. If septa indeed act as selective integrators of distributed sensory input, this would suggest a novel computational role for cortical microcircuits beyond the classical view focused on barrels. Although still hypothetical, the proposed model in which SST⁺ interneurons contribute to domain-specific sensory responses between barrel and septal domains is intriguing and opens new avenues for investigating inhibitory circuit mechanisms.

Weaknesses:

The primary limitation of this study lies in the spatial and cellular specificity of the recording techniques. The physiological data rely predominantly on unsorted multi-unit activity (MUA) recorded with low-channel-count silicon probes. Because MUA aggregates signals from multiple neurons over a radius of approximately 50-100 µm (comparable to or larger than the width of septal domains in mice), it remains difficult to confidently attribute the recorded activity exclusively to septal versus barrel populations. The authors have now addressed this concern more carefully by reframing their interpretation in terms of "septal-enriched" populations and by providing additional threshold-based analyses suggesting that the principal effects are more robust in Layer 4. These additions substantially improve the manuscript and support a more cautious interpretation of the findings. Nevertheless, the proposed Elfn1/SST⁺ mechanism remains supported primarily by indirect evidence. Although the calcium imaging data provide useful support for stimulus-dependent SST⁺ recruitment, these experiments were restricted to L2/3 interneurons and therefore do not directly test the Layer 4 circuit mechanism proposed to underlie the electrophysiological observations. Direct in vivo cell-type-specific recordings and manipulations in Layer 4 would ultimately be required to establish the proposed mechanism more conclusively.

Comments on revised version.

I have read the revised manuscript and overall, I think the authors have addressed my major concerns appropriately. I appreciate the substantially moderated interpretation of the findings and the additional analyses clarifying the limitations of the MUA recordings.

Reviewer #2 (Public review):

Summary:

Dyce et al investigate the modulation of sensory responses in the somatosensory 'barrel' cortex during a novel whisker vibration detection task in head-fixed mice, aiming to find correlates of spatial attention in both the animals' behavior and their neuronal activity.

Strengths:

The authors produced an extensive and parameterized dataset of both behavioral responses and neuronal activity, with >3000 single units of which >1400 were responsive.

Weaknesses:

In my view, the main conclusions of the manuscript are not currently well supported by the data.

The authors effectively define "spatial attention" as a state where an animal responds more to a stimulus that gives more rewards (out of two possible stimuli presented on different sides of the snout, i.e., segregated spatially). If one defines spatial attention purely in these terms, then their findings do show neuronal correlates of spatial attention. However, those neuronal correlates can be explained by known aspects of neuronal responses in the barrel cortex.

This plays out in several different ways:

From the behavioral point of view, greater attention may correlate with an increased hit rate to stimuli on the rewarded side, but in the absence of other supporting measurements, the relationship could well be the opposite: an animal could pay more (rather than less) attention to the stimulus delivered on the unrewarded side, to make sure it suppresses the incorrect response. It is impossible to tell, as the data don't provide an independent measurement of whether the animal is paying greater attention to, or is more aware of, one side than the other, nor do they provide an independent measurement of neuronal tuning on either side. There is no separate measurement of arousal either (e.g., via pupillometry or locomotion).

The experimental design involved two blocks on each daily task session, with the second block reversing the side on which rewarded stimuli were delivered. Reinforcing one's doubts about the behavior and its interpretation, mice had much poorer performance on each day's second block, to the extent that perceptual sensitivity (d') was the same for both sides: d' did not increase after reward reversal for stimuli on the initially unrewarded side. This further emphasizes the lack of a separate demonstration of focused "spatial attention".

Much of the data (both behavioral and neuronal) could be accounted for, e.g., by a strategy where the mouse keeps a token in working memory of what side seems to be driving rewards, while maintaining equally strong sensory drive on both sides, but with no attentional shift at all. The policy would be to respond more whenever the stimulated side matches the token in memory (thus also reinforcing the token, thus enhancing performance next time). This would be easily implemented with a disinhibitory reward-modulation signal such as the one multiple researchers have found carried by VIP neurons (e.g., Szadai et al DOI: 10.7554/eLife.78815).

Similarly, the fact that "attended trials" (Pref > 0) produced greater responses than "unattended trials" appears to be explainable as follows. Here, "attended" trials are those where the contralateral stimulus is presented (and, if responded to, is rewarded), "unattended" trials are those where the stimulus is ipsilateral (and not rewarded). The animal responds more (at least in the first block) to stimuli delivered to the contralateral pad - i.e., rewarded as opposed to unrewarded ones. Beyond the knowledge mentioned above that cortex-wide VIP sensitivity to rewards can drive disinhibition in general, activity modulation dependent on rewards and outcomes (and stimulus value) has been established specifically in the barrel cortex (e.g., Lacefield et al DOI: 10.1016/j.celrep.2019.01.093, Bale et al DOI: 10.1016/j.cub.2020.10.059, Banerjee et al DOI: 10.1038/s41586-020-2704-z, Chereau et al 10.1038/s41467-020-17005-x). The reward- and value-evoked activity demonstrated in those papers would suffice to predict more activity at the contralateral electrode on "attended" trials, along the lines of the findings in Ramamurthy et al (DOI: 10.1038/s41467-025-60592-w) and consistent also with the enhanced "attentional modulation" on hit trials.

Other aspects of the analysis and terminology lead to confusing outcomes. For example, in the analysis in Figure 3, Performance averaged in a set of trials around a given trial is defined as the mean rate of responses to stimulation on either side - regardless of whether those responses are correct (since the stimuli can be on either side, but only one side is correct and gets rewarded and putatively reinforced). Thus, this definition of "Performance" can increase with the rate of incorrect licks to the wrong side and is at odds with the normal use of the word. On trials where this Perf = 1 and the stimuli are balanced on either side, this corresponds to a true performance (and reward rate) of only 0.5 - what one would normally consider random discrimination between the sides. Thus, Perf = 1 trials may still give a low reward rate and, if responses scale with reward, a small effect of reward. Hence, based on known properties of reward dependence, greater correlation of neuronal activity with "Preference" than with "Performance" would be expected, rather than reflecting a new aspect of "spatial attention". A definition of performance more in line with established practice and measuring side-to-side discrimination (corresponding more closely to the authors' "Preference" parameter) would have shown this more clearly.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors aim to assess how the functional organisation of the hippocampus is related to the geometry and neurobiological differences of the hippocampus. In particular, the authors focus on the first three eigenvectors of hippocampal-cortical functional connectivity, based on non-linear dimensionality reduction on resting-state functional MRI data. Furthermore, the work aims to describe changes in these functional axes and their relation to other factors throughout youth and evaluate whether they are predictive of individual variations in cognition.

Strengths:

A major strength of this study is the attempt to replicate key findings across multiple developmental cohorts.

Weaknesses:

The major weaknesses of the manuscript center on gaps in technical transparency and several conceptual inaccuracies. The machine learning methodology used for cognitive prediction is scarce, leaving little means to evaluate whether the behavioral results suffer from data leakage or overfitting. The introduction sets up an oversimplified historical premise regarding the field's understanding and appreciation of hippocampal connectivity, and contains several incorrect references that throw doubt on the argumentation. Additionally, T1w/T2w signal intensity is incorrectly used as synonymous with myelin, despite gold-standard histological validation showing a non-significant correlation between T1w/T2w and myelin staining (Sandrone et al., 2013).

Appraisal of Aims and Conclusions:

The authors partially achieve their aims by illustrating certain age-related changes in hippocampal function; however, the correlative study design is not equipped to examine how these changes are "shaped" by geometry, myelination, or gene expression (especially the latter two). Furthermore, conclusions were often overstated based on small effect sizes.

Context and Field Impact:

This work adds to a growing body of literature focused on gradient-based representations of hippocampal topology. By applying these methods across a wide developmental age bracket, it provides a useful reference point for how the hippocampus and wider cortex interact during maturation. To improve utility to the neuroimaging and cognitive neuroscience communities, the nesting of subfields within the eigenvector topology should be addressed, too.

Reviewer #2 (Public review):

Summary:

This manuscript investigates how Drosophila larvae make foraging decisions in patchy environments with controlled resource density and valence. Using movement tracking in bounded arenas, the authors show that larvae's patch residence time (PRT) differs depending on resource type, environmental context, and prior experience.

The authors vary whether the environment is homogenous (all patches are equal) or heterogenous (mixed patches) and whether a higher density of the resource is appetitive (food) or aversive (salt). The most salient results are that in heterogeneous environments, larvae remain longer on higher-density patches of fructose, while they stay shorter in higher-density salt patches. The study further demonstrates that prior foraging experience influences subsequent patch residence time (PRT).

A drift-diffusion model is used to describe patch-leaving behavior, suggesting that an integration process may underlie stay-leave decisions during foraging. Overall, the work provides a useful behavioral system for studying foraging behaviour and highlights the role of context and experience in shaping larval foraging strategies.

Strengths:

A major strength of the manuscript is the behavioral system. The assay is simple, well-controlled, and suitable for realistic spatial and temporal scale tracking of individual larvae. The use of non-volatile resources and embedded patches minimizes confounds from olfactory navigation and allows the authors to focus on local patch exploitation, return behavior, and experience-dependent decisions.

The results regarding patch resident time (how long larvae stay in patches of different resource density) are convincing. In homogeneous environments, larvae spend more time on patches with a higher density of food (0.1M > 0.01M) and less time in patches with a lower density of salt (0.01M > 0.1M), indicating that their behaviour is sensitive to the valence of the resource. Further, larvae do not simply respond to current circumstances, since PRT in a given patch is sensitive to the quality of the preceding one encountered, showing some kind of memory.

Weaknesses:

(1) The theoretical background of the experiment, as exposed in the Introduction, is somewhat misleading. The experiment is based on patches of sufficient size for the individual larvae not to deplete them through their activity, so that the intake rate is constant while exploiting a given patch. In those circumstances, the theoretical rate-maximizing strategy would be to either reject a patch on encounter or stay in it indefinitely (until pupation). The threshold for rejection or acceptance will depend on travel time, but patch residence time would be either zero (or minimal identification time) or lifelong. In the introduction, it appears as if the system follows the classical Marginal Value Theorem assumptions as used in classical foraging theory. In that case, patch residence time is fundamentally sensitive to a decline in intake rate while in a patch. This raises questions about what factors drive patch-leaving in the present protocol. A better theoretical framework would focus on behavioural variables that can be expected to depend on the circumstances of the experiment, as discussed below.

(2) Rather than make predictions about time in the patch, which as explained above do not reflect the present system, larval behaviour could be modelled and described as a function of observable properties such as: (a) speed of locomotion; (b) tendency to deviate from straight progress (area restricted searching); (c) probability of return after leaving a patch, possibly controlled through rea restricted searching; (d) a response to concentration gradient, since patch boundaries are probably gradual through diffusion. There is a useful literature in this regard in studies of parasitic wasps such as Venturia canescens (formerly Nemeritis canescens, see Waage 1979). Larva may respond directly to local resource concentration (see van Alphen, J. J., Bernstein, C., & Driessen, G., 2003), where higher concentration leads to increased feeding rate, reduced locomotion, and consequently results in longer time in each patch. This could still be a normative model, but based on realistic driving inputs. The dimensions of the system make it unlikely that larvae have the opportunity to adjust to travel time, or patch composition, on which classical foraging models are based. The original versions of the marginal value theorem were thought for cases where birds exploited pine cones, so that each bird had multiple encounters, and also on dung flies that mated in dung patches, which also dried out. A system with heritable optimised parameters could work for other natural systems where the parameters can be heritable, but not here.

(3) The previous argument indicates that patch time, while it is a real quantitative consequence, is not ideal as the major dependent variable for this system. Given that the authors have the full trajectories, they could treat movement in discrete time bins and ask if the tendency to depart from linear progression (i.e. from moving straight ahead) is a function of the density of the resource. It would appear as if all the results, including return to patches (but not memory), could be explained by area-restricted searching (see Dorfman, A., Hills, T. T., & Scharf, I. (2022). A guide to area‐restricted search: a foundational foraging behaviour. Biological Reviews, 97(6), 2076-2089.). Slower movement (perhaps directly caused by eating) and more twisted progress could generate longer times in higher food densities.

(4) The evidence for an effect of prior experience is interesting but could be strengthened. The authors state that PRT on the second patch depends on the concentration in the first patch. However, statistically significant modulation of prior experience was only found when the second food patch was richer, namely 1M fructose (Figure 4C). If the change in patch time is due to a form of learning and contrast, one might expect significantly shorter times in any second patch if the first one was richer, which is not the case. One difficulty is that the 'patchy' nature of the environment may not be evident to the larvae, because they are much smaller than the patches. From a larva's perspective, a patch is an environment, potentially suitable to remain in until pupation (which is what they ought to do in richer food patches).

(5) The modelling section is promising but currently somewhat underdeveloped relative to the strength of the claims. The authors fit a drift-diffusion model to data and report that a drift-only model captures homogeneous environments, whereas adding a leak term improves the fit in heterogeneous environments. This provides a useful quantitative summary of behavior but the biological interpretation of the leak parameter is not clear. In addition, the valence condition was not modelled.

Reviewer #2 (Public review):

In this manuscript, Ritter et al. propose a model of working memory (WM) that combines feedforward and rotational dynamics. The model is discovered by optimizing a linear RNN using a loss function that encourages maximization of signal-to-noise ratio (SNR) and minimization of activation magnitude. The authors argue that the optimized model outperforms other WM models in terms of SNR and energetic efficiency, while also better replicating key features of neural responses recorded in monkey pre-frontal cortex (PFC) during a WM task. The authors also draw connections to state space models (SSM) used for other machine learning applications.

My main issue with this manuscript is that it does not appear to convincingly demonstrate that rotational dynamics offer any advantage over purely feedforward dynamics. The authors adopt three criteria according to which they compare models:<br /> (1) SNR.<br /> (2) Energy efficiency.<br /> (3) Similarity to neural data.

In terms of SNR, purely feedforward models seem to perform similarly to the optimized models (Figure 1). Figure 1 does seem to show that the optimized network produces responses of smaller magnitude when the number of units is large, but the authors do not explain why adding rotational dynamics would produce such a relationship. In fact, the responses that are plotted for the feedforward network in Figures 1B, 2C, and 5E look similar, if not smaller in magnitude than those of the optimized model. Lastly, while the authors claim in the body of the text that the optimized model replicates key features of monkey PFC responses better than the purely feedforward model, this is not apparent to me from the comparisons plotted in Figure 5E-J. The authors thus do not show strong evidence that the model they propose beats what they claim is an established baseline on any of the three criteria.

Another weakness of the manuscript is that the comparison to attractor and feedforward models seems somewhat unfair. In Figure 1, the rotational model is optimized, while the parameters for the attractor and feedforward models seem to have been at least partially chosen by hand. Figure 5C again shows the three models side by side, but the fact that it compares the same network at different stages during training complicates the comparison. Instead, one should compare the rotational solution to the optimal attractor and feedforward models, respectively (obtained by constrained optimization). From looking at the flow-fields, it seems that a feedforward network with an optimized level of amplification may work just as well. On a mechanistic level, it is unclear what computational advantage rotations offer over feedforward dynamics in the WM context.

The choice of baseline models to compare against might be questionable. The simple line attractor model by Seung et al. (1996) was initially designed to explain oculomotor integration. It is true that a line attractor has been suggested as a mechanism for working memory, e.g., in the seminal work by Machens et al (2005). However, it seems fair to say that most studies employing non-linear networks have focused on point attractors as mechanisms of working memory (e.g., Wong & Wang, 2006; Driscoll, Shenoy, Sussillo, 2024). A point attractor arguably does not suffer the SNR issues of a line attractor, because it does not lead to integration of the noise over time. However, non-trivial point attractors cannot be implemented in linear networks of the kind studied by the authors of the present study.

The authors should expand their discussion to include other, potentially closely related work proposing rotation-like dynamics in artificial neural networks during working memory. In particular, the manuscript does not discuss Sharma, Proca, et al, ICML 2026, which describes a rotational solution to a similar WM task obtained by optimizing linear RNNs (Sharma et al., 2026, Fig. 6). Notably, Sharma et al. arrive at a similar rotational (and likely also non-normal) mechanism without using either noisy inputs or a constraint on energy efficiency. The authors of the present manuscript should discuss to what extent this finding contradicts their claim that "normative pressures on noise-robustness and energetic cost shape the complex dynamics of WM circuits." (present manuscript, Introduction). Given the obvious parallels between the two studies, a comparison between the present work and Sharma et al. (2026) would add necessary context to the Discussion.

The authors should also clarify the significance of the "novel method for optimization of continuous-time RNNs driven by noisy inputs" (see Discussion) that the authors propose. This method is mentioned in the first line of the Discussion section but is barely discussed, let alone sufficiently explained, in the previous Sections. The only time a comparison to BPTT with a simple MSE loss is mentioned, it is stated that the two procedures produce the same results. The novel method appears to consist of a loss with two terms, the second of which is a well-known L2-penalty on unit activations (Sussillo et al., 2015). It is not clear that the method is either novel or necessary to obtain the reported results.

Except for the fact that higher-dimensional networks also converge on rotational solutions, Figure 3 does not add much to the reader's understanding of the optimized model (except for panel F). I find the comparison to SSMs too superficial to provide real insight.

Figure 4 claims to show that the optimized model recapitulates "a range of properties observed in prefrontal cortex and other brain areas during WM tasks" (p. 7) but does not show neural data for comparison.

Reviewer #2 (Public review):

Summary:

Sarcomeres, the contractile units of skeletal and cardiac muscle, contract in a concerted fashion to power myofibril and thus muscle fiber contraction.

Muscle fiber contraction depends on the stiffness of the elastic substrate of the cell, yet it is not known how this dependence emerges from the collective dynamics of sarcomeres. Here, the authors analyze contraction time series of individual sarcomeres using live imaging of fluorescently labeled cardiomyocytes cultured on elastic substrates of different stiffness. They find that a reduced collective contractility of muscle fibers on unphysiologically stiff substrates is partially explained by a lack of synchronization in the contraction of individual sarcomeres.

This lack of synchronization is at least partially stochastic, consistent with the notion of a tug-of-war between sarcomeres on stiff sarcomeres. A particular irregularity of sarcomere contraction cycles is 'popping', the extension of sarcomers beyond their rest length. The statistics of 'popping' suggest that this is a purely random process.

Strengths:

This study thus marks an important shift of perspective from whole-cell analysis towards an understanding the collective dynamics of coupled stochastic sarcomeres.

Reviewer #2 (Public review):

Summary:

This study analyzed consequences of Agbl5 mutation on ependymal cells development and function. Authors first characterize their mutant mouse line reporting a reduced lifespan and severe hydrocephalus. Next, they report defect in ependymal cell cilia number and motility. They provide evidence for impaired basal bodies organisation, cilia glutamylation.

Strengths:

Description of a mutant mouse which implicate Cytosolic Carboxypeptidase 5 (the product of Agbl5 gene) for proper ependymal cells.

Weaknesses:

Description of phenotype are incomplete:

Previous comment: Microtubules are involved in the local organization of ciliary basal bodies (see Werner et al., Vladar et al.,2011; Boutin et al., 2014). It would be interesting that the author checks whether the subapical network of microtubule is glutamylated or not during ependymal cells differentiation and how this network is affected in their mutants.

Although authors now provide images of glutamylation in figure S8 their conclusion claiming that GT335 signal is increased in cilia of Agbl5M1/M1 mutant is not supported convincingly by those pictures. Quantification would be needed.

Reviewer #3 (Public review):

Strengths:

It's sort of novel to study the heritability of movie-watching fMRI data. The methodology the authors used in the paper is also supportive of their findings. Figures are nicely organized and plotted. They finally found that sensory processing in the human brain is under genetic control over stable aspects of brain function (here referring to neural timescale and resting state connectivity).

Weaknesses:

What I am worried about most is the sample size and interpretation of heritability.

(1) Figure 1. I assumed that the authors just calculated the ISC within each group (MZ, DZ, and UR). Of course, you can get different variations between each group. Therefore, there is heritability. Why not calculate ISC across the whole sample, then separate MZ, DZ, and UR?

(2) Heritability scores in the paper are sort of small. If the sample size is small, please consider p-values, which will tell more about the trustworthiness of your heritability.

(3) I don't understand the high-frequency signals in fMRI data. It's always regarded as noise, the band 1 here in particular.

(4) The statement "we show that the heritability of brain activity patterns can be partially explained by the heritability of the neural timescale" should come from Figure 5. However, after controlling for NT, the heritability decreased max. 0.025 in temporal areas. I am not sure this change supports the statement. If the visual cortex is outlined, and combining ISC changes in the visual cortex, I think this would somehow be answered. Instead of delta h2, adding a new model h2 would be obvious to the readers.

(5) Figures 7 and 8, when getting the difference of heritability, please also consider the standard errors of the heritability estimates. Then you can compare across networks/regions.

(6) I think movie VS resting state is a really important result in this paper. However, there is almost no discussion. Discussing this part would be more beneficial for understanding the genetic control over the neuron arousal and excitation circuits.

Comments on revised version.

The whole manuscript has been improved a lot, and the concerns have been clarified.

Reviewer #2 (Public review):

Summary:

Inactivating VHL mutations are common in clear cell renal cell carcinoma, and about half of those mutations unfold/destabilize the protein rather than directly interfering with critical protein-protein interactions. The authors identify a compound that can stabilize/refold mutant VHL and seemingly restore its ability to downregulate its major downstream targets.

Strengths:

The authors use a clever combination of virtual and cell-based screens, followed by suitable biophysical and cell-based validation assays, to arrive at a VHL refolder. This compound is suboptimal from an ADME point of view, but could be a starting point for further medicinal chemistry optimization. Success would have implications for other diseases linked to similar loss-of-function mutations.

Weaknesses:

In going from CP4 to CP4.29 the authors screened based on downregulation of HIF. This is logical but also introduces the danger of identifying chemicals that can downregulate HIF in an "off-target" manner i.e. non-specifically. It therefore essential to clearly show that CP4.29 downregulates steady-state levels of HIF and HIF target genes in cells with suitable (hydrophobic core) VHL mutants but not in isogenic cells lacking VHL.

Reviewer #2 (Public review):

Summary:

This study investigates coordinated beak-tongue movements in seed manipulation, biting, and dehusking in songbirds. A comparative analysis of the seed-eating process in two songbird species with different biting forces, the domestic canary and Java sparrow, was conducted using high-speed XROMM with anatomical marker tracking and quantitative behavioral analysis. The authors have done a great job analyzing upper and lower beak rotation and translation, seed orientation and movement speed, and tongue kinematics.

Strengths:

The methodological approach of using high-speed (500 fps) X-ray reconstruction for 3D kinematic tracking in small animals is novel and powerful. It enables high temporal resolution tracking of orofacial movements and could potentially inspire future orofacial research in mammals, including mice and marmosets. Moreover, this study encompasses a wide range of anatomical components involved in seed manipulation behavior, including the upper and lower beak, the tongue, and jaw muscles. The behavioral quantification of these components is solid. The findings that both the upper and lower beaks contribute to seed processing, that the lower beak exhibits greater up-and-down and left-to-right flexibility than the upper beak during seed processing, and that the tongue plays an important role in transporting seeds into the mouth are all solid conclusions consistent with observations of bird feeding behavior. Nevertheless, it is valuable to confirm and quantitatively characterize these observations experimentally. The videos are excellent and very informative.

Weaknesses:

(1) The paper often resorts to qualitative descriptions (e.g., "a high positive correlation of tongue velocity and seed velocity", "Compared to positioning, the measured velocities of both seed and tongue were much lower") instead of providing exact quantitative measurements or statistical results. The authors stated that temporal autocorrelation biases standard statistical analyses (lines 205-210), but this rationale does not justify the absence of statistical validation. Suggestion: use appropriate methods for time-series data, such as a permutation test, to test the significance of correlations between variables and avoid false positives.

(2) (Minor) The marker-tracking image shown in Figure 1B could benefit from the inclusion of a higher-contrast, zoomed-in frame of the head showing the metal markers without the red tracking points, alongside the same frame with the red tracking points overlaid, to provide readers with a clearer view of the X-ray image and the methodology and its precision.

(3) (Minor: possibly soften the mechanistic claim). The proposed mechanism of lingual papillae on the tongue surface may aid food manipulation and food movement towards the posterior region of the mouth is interesting, yet the evidence describing their morphology is not strong enough to support the claim about their functional roles. Furthermore, the claim that papillae orientation affects food transport in lines 294-296 lacks supporting experimental evidence. In addition, the roles of extrinsic and intrinsic tongue muscles in controlling dexterous tongue shape changes and movements are not discussed.

Reviewer #2 (Public review):

Summary:

Bonanno and colleagues combine unilateral pyramidotomy, continuous voluntary complex-wheel running, whole-brain intersectional CSN tracing, and c-Fos mapping to ask whether rehabilitation reorganizes the supraspinal collaterals of the intact corticospinal tract neurons. The study is technically ambitious and competent, the uPyX + complex-wheel + intersectional-tracing + BrainJ combination is smart and interesting, the behavioral effect is convincing, and the blinding and exclusion criteria are explicit. The central anatomical finding - a CSN-specific, whole-brain projectome comparison with subregional LPGi/GiA/MdV granularity - is a legitimate contribution that builds on Asboth 2018. However, the strength of evidence does not support the strongest causal wording in the current abstract, significance statement, and parts of the discussion: the results remain correlational, the MdV-behavior correlation is modest, and its significance is sensitive to the unit of analysis. A major revision is recommended, primarily of framing and quantitative robustness, rather than because the central dataset is unconvincing.

Strengths:

(1) Technically ambitious and technically competent study addressing a relevant gap: brain-wide mapping of intact-CSN reorganization under continuous voluntary rehabilitation.

(2) The combination of uPyX, complex-wheel running, intersectional tracing, and BrainJ whole-brain projection analysis is novel and well integrated.

(3) Behavioral effect is convincing, blinding, and exclusion criteria are explicit.

(4) The central anatomical finding (CSN-specific whole-brain projectome under rehab, with LPGi/GiA/MdV subregional resolution) is a legitimate contribution that builds on Asboth 2018. The closest recent works (Lemieux et al. 2024, Jeleva et al. 2026) study reticulospinal rather than CSN plasticity and are complementary rather than competing.

Weaknesses:

(1) Causal framing extends beyond what the current evidence supports.

The abstract and significance statement present MdV as a potential mediator, or even a central locus, through which rehabilitation re-establishes descending control of the impaired limb. This is stronger than the evidence. What the paper shows is that CSN collateral projection density in MdV has a mild-to-medium correlation with behavioral recovery, and that this region is already known from prior work (Esposito 2014) to be relevant for skilled forelimb function. That is an interesting anatomical correlation, not a demonstration of mediation. No manipulation of MdV or of MdV-projecting CST terminals is performed; there is no silencing, no pathway-specific perturbation during rehabilitation, and no test showing that the identified sprouting is necessary for recovery. The limitations section acknowledges this, but the prominent claims do not.

(2) The behavioral caveat on what is actually novel.

The cleanest way to state what is genuinely new, clearer than the abstract itself, is this: when a CSN population loses part of its spinal target domain (via contralateral uPyX denervating the opposite cord), some CSNs from the opposite cortex appear to redirect growth into brainstem collaterals (LPGi, GiA, MdV). The compensation is plausibly sufficient to restore gross descending drive to the impaired forelimb, but most probably inadequate for the fractionated, cortico-motoneuronal fine-grain control that the direct CST normally provides. That distinction - recovery of drive and even skilled locomotor control vs. recovery of fine precision - is consistent with the ladder-rung improvements the paper reports (footfall counts are an integrated gross-placement metric) and with the skilled-reaching literature (Esposito 2014 and similar), which suggests precision grip and digit individuation would not be fully recovered by an MdV-centered detour. This note is also translationally important when we ask what humans consider fine motor control, which is mostly object manipulation. Relatedly, the ladder task is "skilled" in the operational sense that it requires cortical control, but the motor output measured (gross paw placement, overreach) is not fine motor function in the sense of digit individuation, grip force modulation, or pellet manipulation. "Skilled" here does not even mean *acquired* skill: classical skilled reaching in rodents involves explicit training to acquire a novel motor program, whereas here mice are only habituated. The brainstem-compensation hypothesis is more comfortable with restoring cortex-dependent gross placement than with restoring acquired fine-motor skills.

(3) The anatomy sample is modest for the precision of the claims.

Projection analysis rests on n = 9 pooled controls, n = 5 uPyX−Rehab, and n = 5 uPyX+Rehab. For a whole-brain subregion analysis, this is not a large dataset, even with the sensible restriction to the Wang et al. spinally-projecting set. The three medullary hits are plausible, but some of the most specific conclusions rely on a relatively small number of animals for its most specific claims. This matters especially for the MdV-behavior correlation.

(4) Normalization enforces a zero-sum structure.

Projection density is normalized to the total CST tract signal. This is a reasonable way to control for tracing variability, but it imposes a relative structure on the data: an apparent increase in one region may partly force an apparent decrease elsewhere. This may matter and has to be looked into by the authors, because the manuscript interprets decreased density in some other targets as meaningful redistribution.

(5) The decision to merge PMn and MdV under a single "MdV" label needs more justification.

Since the discussion relies on prior literature assigning skilled forelimb function to MdV proper, the reader needs to know whether the signal truly localizes there or whether it may partly reflect a neighboring region grouped under the same atlas label. Related to this, laterality would be very informative: since the proposed compensatory route is anatomically directional, showing whether the increased signal is preferentially located on the expected side of the medulla would strengthen the interpretation.

(6) The c-Fos / Fig. 3 section goes beyond what the data directly support.

The section "Complex-wheel running recruits intact corticospinal neurons" and the figure title "Rehabilitation functionally recruits intact CSNs" go beyond the actual observation, which is that a higher fraction of CSNs in M1 and M2 are c-Fos+ in runners than in non-runners. "Functionally" is not supported: c-Fos is a transcriptional marker of recent activity, not a functional readout; it does not show that the CSN's output is used to drive behavior. "Rehabilitation" is not supported either: the contrast is runners vs non-runners, applied uniformly across Sham and uPyX groups - healthy Sham+Rehab animals are on wheels for leisure, and the c-Fos effect is present in them too. The finding is difficult to interpret without thinking of the simpler framing ("moving mice have more motor cortex activity than resting mice"), with no control for generic arousal or ambulation. This section is the softest link in the causal chain running - CSN activity - medullary sprouting - recovery.

(7) MdV-recovery correlation: unstated multiple-comparison correction and possible pseudoreplication.

The correlation (R² ≈ 0.33, p ≈ 0.01) is the backbone of the paper's "causal" claim. Panels L/M/N test three correlations (LPGi, GiA, MdV vs forelimb footfall recovery); only MdV is reported as significant. The Figure 5 legend applies Tukey adjustment to the t-tests in A-C but makes no analogous statement for the correlations in L-N. A 3-test Bonferroni (α = 0.017) would not flip the MdV result, but disclosure is warranted, and the three tested regions were pre-selected from the significant group contrasts in A-C, which, to a statistician, would further shrink effective α. More importantly, the figure legend states that closed and open circles represent CFA- and RFA-traced values, respectively, which suggests the correlation treats the two tracer channels per mouse as independent datapoints - doubling the apparent n (≈ 20 from 10 uPyX mice), with the result of a higher significance than one would have at the mouse level.

(8) Reporting issues.

The reader would benefit from judging statistical choices such as those above directly from a data table rather than interpreting the authors' choices. The SciScore rightfully flags multiple missing components of transparent reporting: missing RRIDs, no code availability, limited data availability, and no power calculation, among others.

Almost all these weaknesses can be addressed with a revision of the manuscript, especially in the framing of results.

Conclusion:

The core message - that rehabilitation is associated with a selective pattern of CSN collateral remodeling in the motor medulla, and that MdV projection density covaries with behavioral recovery - is defensible from the data and already a useful result. The current wording in parts of the abstract, significance statement, and discussion goes beyond this and implies a mechanistic conclusion (mediation, central locus, re-establishment of descending control) that the data do not yet establish. The manuscript would better match its evidence with "associated with", "correlates with", or "candidate locus" framing, unless a causal experiment is added.

Reviewer #2 (Public review):

Summary:

The manuscript by Kelman and coauthors investigates how viral communities differ in the genes they encode in healthy and degraded coral reef ecosystems. Across 19 viral metagenomes from Central Pacific reefs, the authors assess the frequency of integration/excision genes as a proxy for viral community temperateness and ask whether genes associated with central carbon metabolism covary with signatures of temperateness. The main finding is that viral communities with more temperate-related genes encode more genes from the Entner-Doudoroff pathway and other reactions interpreted as anaplerotic, whereas more lytic-associated viral communities show greater representation of some pentose phosphate pathway, TCA, and redox-associated genes interpreted as cataplerotic. The authors propose a model based on these patterns in which lytic viral metabolism helps suppress bacterial overgrowth on healthy reefs, while temperate viral metabolism may promote microbialization on degraded reefs. The study addresses an interesting and potentially important concept - that viral auxiliary metabolic genes are important components of microbial communities and can affect ecosystem functioning. Linking viral metabolism to coral reef microbialization is a creative conceptual advance. The manuscript is clearly written, and the reported enrichment of anaplerotic genes in temperate-associated viromes is an interesting pattern that could motivate future work on how viral metabolic potential varies across reef states.

Strengths:

(1) The study connects viral lifestyle, central carbon metabolism, bacterial overgrowth, and reef degradation in a framework that could be useful for future studies of coral reef ecosystems and viral ecology. This is an interesting synthesis that links viral auxiliary metabolism to broader questions about microbialization and reef state.

(2) The manuscript is generally clearly organized around a testable prediction: viral metabolic gene content should vary along a lytic-to-temperate viral community gradient. The reported enrichment of anaplerotic genes in viromes with a larger fraction of temperate viruses is a compelling result.

(3) The authors highlight several virus-encoded metabolic genes that may not have been previously reported in viral datasets or genomes. If supported by further validation, these observations could expand the known repertoire of viral metabolic potential.

(4) The modeling helps clarify the feedbacks the authors propose may connect viral lifestyle, bacterial metabolism, and coral reef degradation. It provides a foundation for generating hypotheses about how viral metabolic genes could influence reef microbial dynamics.

Weaknesses:

(1) The main limitation is that the evidence for several key claims remains indirect. The core analysis is based on correlations between metabolic gene frequencies and integration/excision-related genes. This does not demonstrate that the metabolic genes occur in temperate viral genomes, are physically linked to lysogeny genes, are expressed during infection, or alter host metabolism. Thus, the data support an association between VLP-associated metabolic annotations and a community-level temperateness proxy, but not a direct link between temperate phages and these metabolic functions.

(2) It is important not to equate community-level gene frequencies with genome-level or infection-level metabolic programs. A virome may contain more anaplerotic genes overall, but that does not demonstrate that individual viruses reprogram their hosts in an anaplerotic manner nor that infection produces a net anaplerotic effect. Individual viruses may encode both anaplerotic and cataplerotic genes, and a smaller number of cataplerotic genes could have stronger metabolic consequences depending on expression, enzyme efficiency, pathway position, and host context. This is an important limitation that should be acknowledged and, if possible, addressed with contig- or genome-level analyses.

(3) The ecological interpretation assumes that viral infection is strong enough to influence reef-scale bacterial population dynamics. However, the study does not directly measure infection frequency, lysis rates, viral production, burst size, lysogeny frequency, prophage induction, gene expression, or bacterial mortality. If viral mortality or lysogenic conversion were rare in these systems, the observed gene-frequency patterns could have limited ecosystem-level consequences. This makes claims about viral metabolism suppressing bacterial overgrowth, accelerating microbialization, or acting as a conservation lever more speculative than suggested.

(4) There are statistical limitations related to the use of relative gene frequencies. Because genes are normalized as percentages of known genes, the data are compositional. Apparent increases in some categories may partly reflect decreases in others. Bootstrapped Spearman correlations are useful for assessing the robustness of these associations, but they do not address compositionality or multiple testing.

(5) The anaplerotic/cataplerotic classification is central to the manuscript's conclusions and would benefit from more support. The framework is useful, but it depends on both annotation confidence and biochemical context. Sequence-similarity annotations alone may be vulnerable to misannotation, especially for central metabolic enzymes that share conserved domains across functionally distinct proteins. Stronger evidence that key genes contain key functional domains and/or are phylogenetically related to characterized enzymes would help support the proposed functions. In addition, many central carbon enzymes are reversible or context-dependent, so a clearer rationale for each classification would strengthen the interpretation.

Overall, the manuscript presents a valuable hypothesis and highlights new ecological patterns in coral reef viral metagenomes, but falls short of the evidence needed for the strongest claims. The work would be strengthened by analyses that directly link metabolic genes to viral genomes or lysogeny markers, address compositional effects, validate key annotations, and more clearly distinguish observed gene-frequency associations from hypothesized effects on infection, host metabolism, and reef state.

Reviewer #2 (Public review):

Summary:

This review by Dorrell and Whittington covers a number of aspects related to normative modeling of grid cells. They begin by discussing key experimental insights on grid cell phenomenology. Then, they discuss how grid cells can be used to perform path integration and how they size up as efficient codes of space. These two sections then lead the authors to discuss how combining path integration and efficient coding objectives leads to models of axis-aligned grid cells in a single module. Discussion on non-linear objectives leading to multi-modules is presented. The review ends with several outstanding questions and an optimistic outlook of how normative models (particularly, task-optimized RNNs) can be used as tools for advancing understanding in neuroscience.

Strengths:

(1) The review is timely and covers an area that has seen a lot of recent activity. This discussion around many of the different results (and kinds of models), I think, will be generally helpful for the field.

(2) Although I think the story could be a little more coherently made (see below), in general I enjoyed the author's flow from efficient coding -> efficient coding + path integration -> efficient coding + path integration + non-linear objective. This framing supports the specific conclusion the authors arrive at.

(3) I also really liked the message that the review made of how normative modeling, despite some of its challenges/limitations, can be used effectively in neuroscience. The discussion of cycling between "experimental" modeling (e.g., vanilla RNNs) and theoretically-grounded models was nice, and I think it helps demonstrate the value of this approach.

(4) Showing how the metric loss could be seen as a bandpass filter (Figure 3C) was nice and a contribution of the review.

(5) While the focus of P4 (conjunctive HD-grid cells) felt initially a little cast aside, the discussion around "brain and task-optimised RNNs with standard architectural choices use fundamentally different path-integration mechanism" was nice and I think helpful for steering the community to an interesting open problem.

(6) Identifying how "non-linear functionality" can lead to multi-modules was nice and not something that I have seen as clearly presented before.

Weaknesses:

(1) The authors view the experimental evidence for grid cells being linked to path integration as "specific and strong" and that the " key computational feature that defines entorhinal cortex [is] path-integration". I think experimentalists (at least the ones I work with) would push back on that. First, it's hard to isolate path integration in rodent experiments. So while Gil et al. (2018) did about as good a job as you could do, there are still other interpretations of the results that are not purely path integration dependent. And second, as the authors point out later in the review, there is experimental work finding that grid cells are disrupted in large environments and 3D. Path integration certainly happens (to some extent) in these spaces, which begs the question of how it is achieved with weakened grid coding. Thus, I think reducing the claims about how strongly grid cells are experimentally linked to path integration is called for.

(2) The authors introduce the idea of efficient coding of space and discuss how grid cells are not optimal. It is later clarified (Sec. 5.3) that multi-module codes can be efficient (even if not the most optimal). I was confused reading Section 3, because in Section 2 the multiple modules are discussed, but then in Section 3, they are dropped, and only a single module is being considered. Equation 2 was also a little confusing to me. Alpha is not defined, and I would have thought that it would be x^Tx' - g(x)^T g(x') and not x^Tx' g(x)^T g(x'). Given that there is no page limit here, I think a little more detail in Section 3 would be helpful.

(3) In Section 3, the authors make use of P2 (translation invariance within a module) to rule out (or, at least, question) certain models/approaches. While this is certainly a standard assumption made in theoretical work, it is not very well supported by experimental findings. In particular, Diehl et al. (2017), Ismakov et al. (2017), and Dunn et al. (2017) all found that individual grid fields systematically vary in their peak firing rate. In addition, Redman et al. (2025) found that, within a given module, there was a small but robust diversity of grid orientations and spacings. These suggest that grid cells within a single module may actually be able to encode properties of local space and give some support to normative models that find efficient space coding with grid cells by finding non-axis-aligned grid fields. I think this is all important to mention because: a) it provides more biological nuance to the question about spatial coding; b) it provides more ways in which to test models. For instance, in Redman et al. (2025), the Sorscher et al. (2022) model was shown to produce variability in grid properties that loosely matched what was found in real data. For tests like this (e.g., how much does a model reproduce variability in grid firing field peak rates), I think it is going to be important for continuing to evaluate models.

(4) The focus of the review, I know, is grid cells, but of course, grid cells are part of the MEC and the larger hippocampal network. I totally understand, at some level, you have to make a decision of what to model, but it seems that there are other functional classes of neurons (border cells, head direction cells) that all play an important role in path integration. And while the models the authors consider at the end of the review capture properties of grid cells really well, they do so at the cost of not modeling anything else. The authors mention this in the context of the models not capturing conjunctive grid-head direction cells, but I think the point is a deeper one, and more discussion of at what level it makes sense to consider grid cells only is important.

(5) As I mentioned in the Strengths section, I did enjoy the flow of the paper on how path integration + efficiency is needed to get grid single modules and path integration + efficiency + non-linearity is needed to get multiple grid modules. This creates the story that adding more of these theory-driven constraints helps lead to more "accurate" models of grid cells. But one alternative view is that, if path integration + efficiency is enough to get a single grid module (but only a single grid module), then maybe the utility (or need) of multiple grid modules comes from something else. That is, instead of saying "we need more constraints to get multiple modules", it could be evidence for "we need to re-think whether multiple modules might need a different theory to explain". While I understand this is a big picture question that maybe isn't entirely fair to ask of the authors, I think: 1) the authors do a nice job of positioning their review as a kind of discussion on what normative modeling can provide to neuroscience, so having this discussion on when the failure of a model to capture ALL aspects of the biological features motivates further constraints as opposed to a new approach, would be useful; 2) this question connects with the title of the paper, i.e. "what is the question?"

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. The authors have responded to all my review critiques and suggestions.

Reviewer #2 (Public review):

Summary:

The study examines how Streptococcus pyogenes integrates bacterial and host-derived signals to regulate SpeB, proposing that Vfr acts as a protease-sensitive repressor whose degradation relieves repression of speB. The authors further suggest that neutrophil-derived serine proteases, including those associated with inflammatory conditions, may promote this transition, and thereby counterbalance LL-37/CovRS-associated suppression of speB. The conceptual framework is interesting and potentially important for understanding how host inflammation feeds into bacterial virulence regulation.

Strengths:

The work addresses a biologically significant question and does so using a broad and generally well-integrated experimental approach, including bacterial genetics, reporter assays, recombinant protein analyses, neutrophil-derived material, human blood infection, and mouse infection models. A particular strength is the effort to connect host inflammatory processes to bacterial regulatory behavior, which gives the study conceptual reach beyond a narrow mechanistic observation. The data support the view that Vfr is relevant to speB control and that neutrophil-associated protease activity may influence this pathway.

Weaknesses:

The main limitations are mechanistic. The physiological form, localization, and abundance of Vfr are not sufficiently defined to support the proposed model at full strength, and the evidence that Vfr functions as a SpeB-labile repressor under biologically relevant conditions remains incomplete. The relationship between Vfr and the broader RopB/SIP regulatory framework is also not yet firmly established. In addition, the reporter system is not yet benchmarked closely enough against endogenous SpeB protein output, and its growth-phase dependence is insufficiently resolved, which makes it difficult in some settings to distinguish promoter activity from mature protease production. The neutrophil protease component is likewise not defined beyond a general serine protease signal, and the potentially important LL-37/CovRS/Vfr connection is underdeveloped in the main text. Overall, the conceptual advance is promising, but several of the central mechanistic claims would benefit from more direct experimental support and more cautious framing.

Reviewer #2 (Public review):

Summary:

The authors have made a convincing argument that the current system of in vitro translation using E. coli extracts can be significantly optimized to work with much lesser components, while maintaining activity. They have showcased their improved activity using not only physical but also functional readouts.

Strengths:

The experiments are designed in a very logical and easy to understand manner, which makes it easier not only to follow the paper, but also reproduce the results. Functional assays with the synthesized proteins are a good way to demonstrate functionality and applicability of the system. They also benchmark their system against a commercial kit to show superior performance of their system.

Weaknesses:

The production of the lysate requires special instrumentation, limiting accessibility.

Comments on revised version:

Thank you to the authors for addressing the concerns both textually and experimentally. This work has significant value.

Reviewer #2 (Public review):

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

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

Reviewer #3 (Public review):

Summary:

The manuscript of Mayer and colleagues analyzes the function of WIPI proteins in mammalian cells. The authors identified previously CROP as a complex consisting of WIPI1 and the retromer complex, primarily in yeast cells. In mammalian cells, both WIPI1 and WIPI2 exist, whereas retromer has a homologous complex termed retriever. The now find that WIPI2 can form a complex with retriever subunits. They name this complex CROP2. Their data further indicate that CROP2 and CROP1 have distinct substrate specificities as knock down of CROP2 subunits affect beta1 integrin sorting, whereas knock down of CROP1 affects EGFR and GLUT1. The further identify a similar sequence (FSSS) in both WIPI1 and WIPI2, which is required for their specific binding to retromer and retriever.

Strengths:

CROP1 and CROP2 seem to use similar features for their formation, and have different substrates, which is convincingly shown.

Weaknesses:

The analysis lacks information that this is a complex as claimed. It can be deduced from the immunoprecipitation analysis.

Comments on revised version.

The authors answered my questions and adjusted the text accordingly. Figure 10 was not part of the submitted version. It should be checked by the editor.

Reviewer #2 (Public review):

Summary:

The study aims to show that the early visual cortex is not merely a sensory-perceptual region that encodes stimuli while they are physically present, but also supports the formation and retrieval of long-term episodic memories. Instead, the authors demonstrate that spatially tuned reactivation of early visual cortex after a single encoding event supports memory-guided behavior, such as recalling an object's original location.

Strengths:

The study provides solid evidence that location information for single, trial-unique objects is reinstated in early visual cortex during both recognition and recall, even without explicit spatial demands, and the remembered vs. forgotten analyses link spatial tuning to behavior. The one-shot design and absence of explicit spatial instructions are important strengths that bring the paradigm closer to everyday, incidental episodic experiences and go beyond highly trained cue-target associations.

Weaknesses:

(1) Conceptually, the main findings would appear less surprising without a sharper theoretical contrast. Given basic retinotopic coding, it is natural that object identity and location are jointly encoded when an object is presented at a particular position, so spatially tuned reinstatement in V1-V3 can be interpreted as a reconfirmation of known properties unless more clearly contrasted with theories that emphasize more abstract, position-invariant cortical representations following hippocampal-cortical recoding. As currently framed, the introduction does not fully articulate what existing accounts might predict, or what pattern of results would have challenged those accounts, which somewhat weakens the perceived theoretical payoff.

(2) It also remains somewhat unclear why early visual cortex (V1-V3), specifically, is the critical locus for the spatial information of interest, as opposed to higher-level visual or parietal regions that could also provide a spatial scaffold; clearer rationale and, if possible, control analyses in additional regions would help here.

(3) Since gaze behavior is central to any spatial account, it would be helpful to report basic eye-tracking analyses comparing remembered versus forgotten trials, especially at encoding, to rule out systematic differences in fixation patterns that could contribute to the spatial tuning results.

Reviewer #2 (Public review):

Summary:

Adeno-associated viruses (AAVs) are popular gene therapy vectors, but AAVs can cause toxicity. This is particularly evident following expression of some transgenes, e.g., GFP, in the retinal pigment epithelium (RPE), which leads to loss of RPE cells and photoreceptors. Here, we sought to unravel the toxicity mechanism(s). Several transgenes, self and non-self, were tested for toxicity, with no clear correlation for this variable. RPE RNA-sequencing revealed upregulation of translational processes, cell stress, cytokine release, antiviral responses, and leukocyte infiltration pathways. Toxicity-inducing pathways were explored for causality by injecting toxic AAVs into mice deficient for intrinsic, innate, or adaptive immune pathways. The CHOP KO partially alleviated toxicity for RPE but not photoreceptors, whereas the type I interferon receptor KO partially alleviated toxicity for photoreceptors but not RPE. In situ hybridization of interferon pathway transcripts (IFNB1, IFNAR1) revealed that the RPE and retina can produce and potentially respond to interferon. These data suggest that transgene-induced cell stress responses in the RPE lead to RPE cell death, while interferon signaling contributes to the death of photoreceptors.

Strengths:

This manuscript used numerous KO mouse models to evaluate the interferon pathway, inflammatory cytokine pathways, the complement pathway, toll-like receptor signaling, cytosolic DNA sensing, double-stranded RNA sensing strain, intrinsic cellular stress pathways, as well as strains deficient for B cells and T cells or B cells, T cells, and natural killer cells. This is a robust piece of work with rigorous controls, groups, and timepoints tested. The RNA-sequencing data provided helpful guidance on the pathways that should be assessed when analyzing AAV toxicity to the retina.

Weaknesses:

The main weakness of the study is that it focuses on subretinal administration to neonatal mice, and the canonical TLR9-MyD88 was not found to have an impact on the AAV toxicity measured. More information could have been provided to understand the discrepancy.

Reviewer #2 (Public review):

Aims:

The authors sought to optimize SHARE-seq, a multimodal single-cell method, to improve the simultaneous profiling of gene expression and chromatin accessibility. Their goal was to enhance barcode design for better sequencing efficiency and cost savings, while improving overall data quality. They then applied their optimized method, easySHARE-seq, to study liver sinusoidal endothelial cells (LSECs) to demonstrate its utility in examining gene regulation and spatial zonation.

Strengths:

The improved barcode design is an advance, increasing the proportion of sequencing reads dedicated to biological information rather than barcode identification. This modification offers practical benefits in terms of sequencing costs and read length, potentially reducing alignment errors. The method also demonstrates improved RNA detection compared to the original SHARE-seq protocol. The biological applications showcase how simultaneous measurement of both modalities enables analyses that would be practically impossible with single-modality approaches, particularly in examining how chromatin states change along developmental or spatial trajectories.

Weaknesses:

There is a notable reduction in chromatin accessibility detection compared to the original SHARE-seq method, likely limiting the use of the method in certain situations.

Overall:

The authors achieve their aim of creating an optimized protocol with improved barcode design and enhanced RNA detection. The method represents a useful advance for specific experimental contexts where the trade-offs are appropriate.

Reviewer #2 (Public review):

Summary:

The manuscript by Payne and colleagues examines how cell-autonomous loss of the activity-dependent transcription factor NPAS4 reshapes spatial and temporal coding in CA1 pyramidal neurons of behaving mice. The work builds on the Bloodgood lab's established framework in which NPAS4 reorganizes inhibition along the somatodendritic axis of CA1 pyramidal cells, principally by regulating CCK+ basket cell synapses, and asks whether this transcriptionally driven reconfiguration of inhibition propagates into the spike-train statistics that underlie hippocampal function. The combination of sparse Cre delivery with channelrhodopsin-mediated optotagging in Npas4 fl/fl:Ai32 mice is technically elegant, as it permits within-animal comparisons of intermingled wild-type and knockout pyramidal neurons sharing a common LFP, which is a significant analytical advantage for spike-timing analyses and for controlling network-level confounds. The reported phenotype is internally consistent and converges on a coherent story: knockout neurons exhibit broader and less stable place fields, lower signal-to-noise within fields, increased out-of-field activity, weaker theta-phase coupling, and shallower phase precession slopes, with the temporal deficits at least partly explained by enlargement of the spatial receptive field.

Strengths:

Several aspects of the work deserve explicit recognition. The validation of the optotagging strategy is thorough, including the high-power stimulation control to corroborate WT classification and the post hoc histological alignment of GFP+ density with electrophysiologically identified KO fractions. The decision to test NPAS4 function in adult mice maintained in long-term enriched environments addresses an important gap, since most prior work has focused on juveniles or short-term induction paradigms. The acute slice recordings recapitulating the somatodendritic inhibition phenotype reassure the reader that the in vivo measurements are interpreted against a known synaptic substrate. The analytical framework, especially the difference maps across epochs and the linear regression decomposition of phase precession slope into genotype, field size, and theta modulation strength, is rigorous and goes beyond simple group-level comparisons. The conceptual contribution, namely the demonstration that an activity-dependent transcription factor can be tied to single-neuron coding properties in vivo, is meaningful, although it is fair to note that the direction of the effect, given that the CCK to place cell link and the NPAS4 to CCK link have each been established in prior independent studies, is largely along the lines one would predict.

Weaknesses:

The most consequential concern, in my view, is the experimental context in which the entire study is conducted. Every animal is housed in an enriched environment for two to three months, and Figure 1A itself shows that NPAS4 expression in CA1 is essentially undetectable in standard-environment conditions and only emerges with enrichment. This raises the question of whether the manuscript is in fact describing the function of NPAS4 in general, or the function of NPAS4 specifically as recruited by chronic enrichment. The paper, in its current framing, elides this distinction and presents the EE state as if it were the baseline, which it is not. EE is known to alter hippocampal connectivity, the dynamics of place cell ensembles, and the expression of many activity-dependent genes; the CCK to pyramidal cell connectivity that the authors invoke as the mechanistic anchor is also dense in standard housing, so the absence of detectable NPAS4 in SE conditions raises the further conceptual problem of how NPAS4-negative neurons would normally be innervated by CCK+ basket cells in the first place. A direct comparison of WT and KO neurons in standard-environment animals, even on a smaller scale, would discriminate between two very different interpretations, namely that NPAS4 has a constitutive role in tuning CA1 firing versus that it is specifically engaged by enrichment-driven activity and contributes to an EE-specific reorganization of coding. Recent work, including Chiaruttini and colleagues (2025), reports baseline NPAS4 expression in CA1, so the SE result in Figure 1A may itself underestimate normal expression and deserves further scrutiny. Without an SE comparison, the generality of the conclusions cannot be assessed, and the title and abstract risk overstating the scope of the findings, particularly when one considers that NPAS4 is also induced by contextual fear conditioning and other paradigms, which would predict context-specific effects rather than a uniform refinement function.

A closely related concern is the meaning of the knockout itself. Even under EE, only a few percent of CA1 pyramidal neurons express detectable NPAS4 at any given moment (Figure 1A), yet the AAV strategy deletes the gene in 30 to 60 percent of pyramidal neurons. In effect, the majority of cells classified as KO in this study would not have been expressing the protein under the relevant conditions, so the population that is statistically driving the WT versus KO differences must include a non-trivial fraction of neurons in which the deletion has no protein-level consequence. This dilutes the expected effect and raises a more interesting biological question: are the observed phenotypes carried by the few KO neurons that would have expressed NPAS4, or do they emerge from a constitutive function of the gene that is broader than the IHC signal suggests? An additional, related possibility is that NPAS4 expression segregates non-uniformly across functional classes, for example, concentrating in cells with particular firing-rate or spatial-tuning profiles, in which case the "KO" label is binary at the level of the manipulation but graded at the level of biological consequence. Stratifying the KO population by some proxy of activity history, or relating the magnitude of the phenotype to per-cell measures of recent firing, would help address this. As written, the manuscript treats the KO designation as homogeneous, while the underlying biology is almost certainly not.

A third concern, more conventionally statistical, is the treatment of cells as independent observations. The analyses rely almost uniformly on Kolmogorov-Smirnov tests applied to individual units pooled across animals, but cells recorded in the same animal share not only a common subject but a common network, since WT and KO neurons here are intermingled in the same CA1 microcircuit. Cell numbers per animal range widely, so a mixed-effects framework treating animal as a random factor, or a hierarchical bootstrap, would clarify which effects are robust against animal-level and session-level variability and protect against pseudo-replication. This concern is particularly acute for the smaller effects in Figure 2C-E, where the cumulative distributions overlap substantially, and the differences could plausibly be driven by a small number of mice or sessions. In several figures, the individual dots in supplementary panels are not labeled by animal or session, and that information would be useful for assessing how much of each effect is carried by which subset of the cohort.

The absence of a Cre/ChR2 expression control is a separate gap. The comparison throughout the manuscript pits Cre+ ChR2+ neurons (NPAS4 KO) against neighboring non-transduced neurons (WT). This is internally elegant, but leaves open the possibility that part of the phenotype arises from chronic ChR2 expression or constitutive Cre activity rather than from NPAS4 loss, especially given that most of the readouts are subtle. A small companion cohort of Ai32 mice without the floxed Npas4 allele, injected with the same AAV and processed through identical optotagging and electrophysiology pipelines, would address this definitively and is, in my view, a near-essential addition.

Several of the downstream phenotypes would benefit from stratified comparisons that hold first-order properties constant. Many of the downstream differences (stability across epochs, theta coupling, phase precession) could, in principle, be inherited from the upstream difference in firing rate, since the high-firing and high-spatial-information cells in the WT pool are likely contributing disproportionately to the group statistics. The authors do perform firing-rate-matched controls in Figure S4D-G, which is helpful, but the analysis should be extended in two ways: a parallel stratification by spatial information for the stability analyses in Figure 4, and matched comparisons of theta coupling (Figure 5) and phase precession (Figure 6) on neurons drawn from overlapping firing-rate and spatial-information distributions. The regression decomposition for phase precession is a step in this direction and shows that field size, not genotype, is the dominant predictor of slope; this finding, in my reading, deserves more prominent framing in the discussion than it currently receives, since it implies that the temporal precision phenotype is largely downstream of the spatial one rather than a parallel deficit.

The place field stability analysis is interesting but somewhat under-analyzed. The authors show that KO fields shift toward the field entrance more rapidly than WT fields and propose that this reflects an accelerated or dysregulated Mehta-effect-like dynamic. The framing is attractive, but the analysis does not establish that the shifts are systematic in the same way the classical Mehta effect is. An alternative reading is that the elevated out-of-field firing creates spurious local maxima that the peak-finding procedure occasionally classifies as field shifts, especially when in-field firing is reduced. A control analysis using a fixed reference window around the original peak, rather than re-identifying the peak each epoch, would help distinguish a genuine plasticity-like shift from instability driven by noise. The behavior of the WT population in epoch 4 also raises a question: would the drift intensify over longer recording windows, and to what extent is the apparent drift imposed by the repetitive structure of the task itself, in which animals are effectively running on a constrained linear /circular track that may impose drift-like dynamics across the population independently of genotype?

A final note on mechanism. The manuscript leans on prior work showing that NPAS4 regulates CCK+ basket cell synapses, and uses this as the mechanistic anchor for the coding deficits. The connection is reasonable but remains indirect within this study, since the authors do not measure CCK+ interneuron activity, perisomatic inhibition, or local circuit dynamics in the same animals. The discussion already acknowledges some of this, but the speculative framing of dendritic versus somatic inhibition contributions could be tightened, especially given that competing inhibitory sources (PV+ basket cells, axo-axonic cells, OLM interneurons) also shape the spatial and temporal features measured here. A more cautious mechanistic framing, distinguishing what is demonstrated from what is inferred from prior work, would be appropriate.

In summary, this is an ambitious and technically demanding study that makes a meaningful contribution by linking activity-dependent transcriptional regulation of inhibition to the spatial and temporal organization of CA1 spike trains in awake, behaving mice. The within-animal optotagging design is a real strength, the phenotype is internally consistent across multiple coding metrics, and the conceptual implications for how experience tunes single-neuron coding are significant. The principal concerns, namely the unaddressed enrichment confound that pervades the entire dataset, the conceptual ambiguity around what a KO designation actually means at the cell level when only a small fraction of CA1 neurons express the protein, the statistical treatment of nested observations from a shared microcircuit, the missing transgene control, the absence of stratified comparisons by firing rate and spatial information for the secondary phenotypes, and the somewhat overreaching mechanistic framing of the discussion, are all addressable, and if handled carefully would substantially strengthen the manuscript. With these revisions, the work would be a valuable contribution to the literature on how the molecular memory of activity shapes circuit-level coding.

Reviewer #2 (Public review):

This manuscript addresses an important and timely question in TDP-43 biology by systematically identifying regulators of TDP-43 anisosome formation, with a particular focus on nuclear export via XPO1. Using a combination of unbiased chemical screening, genetic perturbation, and advanced imaging approaches, the authors propose that inhibition of nuclear export modulates the abundance and biophysical properties of TDP-43 anisosomes. They further strengthen their findings by introducing an additional model system, a semi-permeabilized in vitro assay, which provides mechanistic evidence that XPO1 activity prevents anisosome dissolution by retaining nuclear RNAs. The study is conceptually innovative and has potential relevance for neurodegenerative diseases characterized by TDP-43 pathology. Some minor concerns remain, mostly about experimental design of the newly added data.

Strengths:

(1) The study employs an unbiased, hypothesis-free compound screen to identify regulators of TDP-43 anisosome formation, which is a major strength and reduces confirmation bias.

(2) The authors combine chemical and genetic screening approaches, providing orthogonal validation of key pathways and increasing confidence in the biological relevance of top hits.

(3) The focus on biophysical properties of TDP-43 assemblies, assessed through imaging and FRAP, moves beyond simple presence/absence of aggregates and provides mechanistic insight into the biophysical states of TDP-43.

(4) The use of multiple experimental modalities, including live-cell imaging, FRAP, pharmacological perturbation, and transcriptomic analysis, reflects a technically sophisticated and ambitious study design.

(5) The authors attempt to extend findings beyond immortalized cancer cell lines by incorporating organoid models, demonstrating awareness of disease relevance and translational importance.

(6) The authors extend their study by incorporating a semi-permeabilized in vitro system, which provides compelling evidence that inhibition of nuclear export promotes the retention of nuclear anisosomes, an effect driven by the accumulation of nuclear RNAs.

Overall, the manuscript is clearly written and logically structured, making complex experimental workflows accessible and the central hypotheses easy to follow.

Weaknesses:

(1) The manuscript has significantly improved with the revisions. Some experimental procedures and method details, as well has statements remain incompletely described:

a) What is the smear in Figure S1 after VLX treatment?

b) The authors state that "The reduction in TDP-43 signal was not due to protein elimination.", however no data is provided to support that statement.

c) The authors state that "TDP-43 shifts from phase-separated state to a soluble state ...", however no data is provided to support that statement.

d) Why did the authors choose cow lover cytosol for this study?

e) The experimental setup for supplementing with cytosol/ATP/GTP is unclear. A more detailed schematic would be helpful to understand at what stage in the experiment these factors were added. Which step of the protocol was performed at 37 {degree sign}C, which is indicated in the figure schematic but not described in the methods.

f) In the organoid model, the authors mention that they observe similar levels of total TDP-43, however they do not provide quantification. Instead, they provide a graph that shows highly significant changes in nuclear TDP-43, which was not addressed in the text.

Additionally, some questions remain unclear:

(1) The anisosomes induced by ATP/GTP or cytosol are insufficiently characterized. It remains unclear whether these structures correspond to canonical ring-shaped anisosomes, and whether they exhibit dynamic (liquid-like) or more static (gel-like) properties.

(2) The contribution of the cytosol and ATP/GTP supplementation experiments to the overall narrative is unclear. While the findings are intriguing, their interpretation within the context of the study is not well articulated. In particular, the rationale for including cytosol is not sufficiently justified, given that ATP/GTP alone induces a pronounced effect, whereas cytosol alone does not.

(3) The authors should address why endogenous XPO1 does not co-localize with anisosomes, whereas overexpressed XPO1 does. This raises the possibility that the observed co-localization may be an artifact of non-physiological protein levels, which should be discussed.

(4) The iPSC-based model remains insufficiently characterized. While the authors propose that this system recapitulates the accumulation of liquid and solid aggregates resembling anisosomes, it is unclear whether this phenotype is robustly observed and whether KPT treatment effectively modulates it.

(5) The rationale for the selected treatment durations is unclear, and the timing appears inconsistent across experiments (ranging from 3 to 16 hours), including within experiments involving the same compound. This variability should be justified or standardized.

(6) Several figure legends require clarification:

a) In the section stating "Collectively, our results suggest that the stability and dynamics of anisosomes are modulated by XPO1-mediated nuclear export ...", the cited figure appears to be incorrect. This should refer to Figure 5L rather than Figure 5J.

b) Figure 1B: Please specify the number of replicates per concentration, the number of cells analyzed, and the model used for regression analysis. Additionally, the legend indicates a treatment duration of 15 hours, whereas Figure 1A states 24 hours.

c) Figure 2G: The authors state "7 anisosomes per condition," but the graph displays only 4-6 data points. Please clarify what each data point represents.

d) Figures 3B and 3G: Please clarify whether a defined threshold was used to determine a "reduction in anisosome number."

e) Figure 4B: These do not represent biological replicates, as all samples derive from a single cell line; rather, they constitute independent experimental replicates.

f) Figures 5B and 5H: The legend states "n = 3 biological repeats," but the number of data points shown appears higher. Please clarify.<br /> g) Figures 5K, 6C, and 6E: "Mean Fluorescence Intensity (MPI)" should be corrected to "MFI."

h) Figure 6C: Please include the number of cells analyzed and provide relevant statistical measures (e.g., R², p-value).

i) Figure 6D: The experimental timeline is unclear. Please specify the duration of incubation and the timing of each step.

j) Figure 7B: Improved labeling is needed (e.g., clarification of "mean spot volume") to better align with the figure legend.

Reviewer #2 (Public review):

Summary:

The paper addresses an interesting problem. The authors develop a method to assess the probability of insertion of aromatic residues in intrinsically disordered regions of proteins, to insert in the interfacial regions of membranes.

Strengths:

(1) The idea of the article seems very interesting. The problem of membrane association mediated by aromatic residues is definitely worth studying. Aromatic residues, especially Tryptophan (W), but also, albeit to a lesser extent, Phenylalanine (F), and Tyrosine (Y), are well known to partition preferentially to the headgroup region of the lipid bilayer.

(2) The authors propose to decipher the sequence code for insertion of sequences containing aromatic residues in the membrane employing three types of calculation methods with decreasing order of detail and complexity, but increasing order of efficiency. First, all-atom MD simulations; second, the PPM method (protein positioning in membranes) from Lomize et al (2006), Protein Sci 15, 1318; and third, AroMIP, a mathematical model developed by the authors. The results obtained with the different simulations and mathematical methods are internally consistent.

Weaknesses:

(1) Aromatic residues have been shown to partition preferentially to the headgroup region of the lipid bilayer. Most of the papers on this problem were published in the mid 1990s to early 2000s. Some of the most important papers in this regard are the following: von Heijne, Annu. Rev. Biophys. Biomol. Struct. 1994, 23, 167-192; Doyle et al. Science 1998, 280, 69-77; Landolt-Marticorena, et al. J. Mol. Biol. 1993, 229, 602-608; Killian & von Heijne, TIBS 2000, 25, 429-434; Marx & Fleming J. Am. Chem. Soc. 2021, 143, 764-772. Strangely enough, none of these articles is cited.

(2) This is the most important point and the most serious weakness. The authors find that the PPM method is able to reproduce the results from MD simulations, and the AroMIP model is able to perform well in comparison with PPM and MD, after training AroMIP on a large set of IDR sequences (intrinsically disordered protein regions) of the human proteome. The defining feature of the AroMIP calculation is the recognition of the importance of flanking residues in the membrane-insertion propensity of a sequence containing a central aromatic residue. All this sounds good. However, this is all theoretical. There is no connection to experiment or to any method that draws from experiment. The entire approach relies on the assumption that the MD simulations produce the correct results. There is no proof of the correctness of anything. As one of the greatest physicists of our times, Richard Feynman, wrote, "The test of all knowledge is experiment. Experiment is the sole judge of scientific "truth"."

(3) The drawings in Figures 2 and 3 are incorrect and misleading. The size of the Tryptophan side chain is about 5.5 Å, whereas one-half of the bilayer ("a monolayer") thickness is about 15 Å. But in the figures, the lipid length and the Trp side chain seem about the same size. This is incorrect even in a qualitative sense.

Reviewer #2 (Public review):

The manuscript by Forbes, Skafida, Karapidaki et al. concerns the in silico identification of cis-regulatory elements (CREs) in large genomes using chromatin accessibility (ATAC-seq) and sequence conservation (genomic DNA sequencing) data. They exemplify this method by applying it to identify novel CREs in Parhyale hawaiensis, which they validated using reporter constructs.

The results are convincing and are well supported by the data and validations. Identified CREs are valuable for researchers interested in the regulation of the expression of genes they control.

The methodology on the whole is also valid, as suggested by the results and previous publications on various taxa. Sequence conservation, as stated by the authors, was long used as a method to identify regions of non-coding DNA with functional and evolutionary constraints. The same applies to ATAC-seq data, which has also been used as a proxy for functional regions in different animals such as sea urchins and amphioxus. The methodology proposed is likely to be successfully used by researchers working on a variety of experimental organisms.

The authors do not use existing genome assemblies and use short-read sequencing to identify conserved regions, and while it is not conceptually novel, such an approach is becoming more and more viable and useful considering the recent advances in next-generation sequencing technology and the decrease in price of short-read sequencing.

Two major weaknesses are:

(1) The novelty of the approach and its advantages should be more explicitly stated.

(2) The authors do not discuss in depth the strength of using a combination of two methods rather than either of the two, especially considering that previously known CREs do not overlap with conserved sequences.

Reviewer #2 (Public review):

Summary:

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

Strengths:

- Large sample size

- Replication of their own findings

- Well-controlled task with measures of behaviour and mood + precise and well-validated computational modeling

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

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

(2) Reply to reviewer 1 Q2 (Predicting STB):

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

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

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