Reviewer #1 (Public review):

Summary:

Akkad et al. present an MEG study of overt picture naming, designed to identify oscillatory mechanisms underlying spoken language production. Participants named line drawings of common objects or responded "no" to scrambled versions of the same images. The authors focus on the period preceding articulation and report on an increase in theta power associated with picture naming in lingual cortex and left medial prefrontal cortex. Two networks are then identified: a left lingual-seeded network involving right ventral occipito-temporal cortex, interpreted as supporting object recognition. Second, a left medial prefrontal-seeded network involving medial temporal regions (and centres in the brain) supporting semantic-lexical retrieval streams. The authors further report increased theta-gamma phase-amplitude coupling in left fusiform and left inferior frontal regions, with stronger left fusiform PAC associated with slower naming responses.

Strengths:

The paper provides useful insight into the network-level and temporal dynamics associated with picture naming.

Weaknesses:

The results are somewhat over-interpreted, and the paper would benefit from a broader and more cautious discussion. The main concerns relate to the control condition and the interpretation of the theta-band effects. First, it is unclear whether the control condition adequately isolates the spoken-language network. Second, the reported theta-band effect appears broadband, raising the possibility that it reflects slow evoked responses rather than genuine oscillatory activity.

Reviewer #1 (Public review):

Summary:

This study presents a workflow for nanoscale imaging of endogenous synaptic receptors in intact adult brain tissue. By combining live-tissue chemical labeling of native surface AMPA receptors (AMPARs) using the CAM2 probe, two-color 3D super-resolution microscopy, adaptive optics, in situ point spread function retrieval, and chromatic aberration correction, the authors establish a platform for quantitative super-resolution mapping of synaptic architecture deep within brain tissue.

The authors provide convincing evidence that AMPAR organization differs between the hippocampus and cortex and demonstrate that early tauopathy is associated with selective disruption of extrasynaptic and synaptic nanodomain receptor organization in the hippocampus prior to overt neurodegeneration.

Beyond the specific biological findings, the work represents a significant technical advance that enables quantitative investigation of endogenous synaptic receptor architecture in native brain tissue and will be of broad interest to researchers in synaptic biology, super-resolution microscopy, and neurodegeneration.

Strengths:

(1) Introduces and validates a strategy for nanoscale imaging of endogenous surface AMPARs in adult brain slices using CAM2 labeling and two-color 3D super-resolution imaging.

(2) Achieves 10s of nanometers localization precision in thick tissue and validates synaptic structural measurements against previous literature benchmarks.

(3) Reveals regional differences in AMPAR organization, including a larger extrasynaptic receptor pool in hippocampal regions compared with neighboring cortical regions.

(4) Identifies early, region-specific alterations in AMPAR distribution and nanodomain organization in the PS19 tauopathy model.

Weaknesses:

(1) Statistical power is limited by the relatively small number of animals analyzed, although large numbers of synaptic structures were sampled within each mouse.

(2) Synaptic classification relies on PSD-95 cluster detection criteria that may bias analysis toward more strongly enriched synapses, as acknowledged by the authors.

Reviewer #1 (Public review):

Summary:

Hsiung et al. investigated whether the effects of autophagy gene knockdown on the lifespan of long-lived C. elegans mutants depend on experimental conditions. The authors first compiled published data on autophagy-dependent lifespan regulation in daf-2 and wild-type backgrounds, highlighting that prior results are notably inconsistent and likely context-dependent. They then systematically tested the lifespan effects of RNAi knockdown of six autophagy genes (atg-2, atg-4.1, atg-9, atg-13, atg-18, and bec-1) in wild-type (N2), daf-2 (reduced insulin/IGF-1 signalling), and glp-1 (germlineless) animals, while varying temperature, daf-2 allele, FUDR concentration, and bacterial infection status.

The key findings are as follows. In wild-type animals, lifespan suppression by most autophagy gene knockdowns was more pronounced at 20{degree sign}C than at 25{degree sign}C, where little or no effect was observed. In daf-2 mutants, stronger lifespan suppression was seen in the weaker daf-2(e1368) allele at 20{degree sign}C, but not in the stronger daf-2(e1370) allele, and effects were largely absent at 25{degree sign}C. In glp-1 mutants, four of six gene knockdowns suppressed lifespan to a greater extent than in N2, though again in a temperature-dependent manner. FUDR at a high concentration (800 µM) abolished the life-shortening effects of most knockdowns and, in the case of atg-9 and atg-13, led to lifespan extension. Kanamycin treatment to eliminate bacterial proliferation did not fully account for the lifespan effects, suggesting that increased susceptibility to infection is not the primary mechanism. The authors also tested the programmed aging hypothesis that autophagy promotes lifespan reduction through biomass repurposing, but found no changes in vitellogenin levels upon knockdown of any of the six genes.

Altogether, among all genes tested, atg-18 knockdown produced the strongest and most consistent lifespan suppression across nearly all conditions, including both daf-2 and glp-1 backgrounds. The authors probed whether atg-18 acts through the FOXO transcription factor DAF-16 by examining dauer formation and ftn-1 expression, but found no evidence for this, suggesting a DAF-16-independent mechanism.

Strengths:

The primary strength of this work lies in its systematic and comprehensive approach to dissecting how experimental variables influence the outcome of autophagy-lifespan epistasis tests. The compilation of prior data alongside the authors' own multi-condition dataset is a genuinely useful resource for the field. The study raises a timely and important point about condition selection bias in interpreting autophagy lifespan relationships, with broader relevance to C. elegans studies. The finding that atg-18 behaves distinctly from other autophagy genes across a range of experimental conditions is particularly noteworthy and provides an interesting direction for future mechanistic investigation.

Reviewer #1 (Public review):

Summary:

This manuscript asks how the uterine lumen is remodeled across the peri-implantation window and whether this remodeling is functionally linked to embryo attachment and subsequent pregnancy establishment. The authors combine whole-organ three-dimensional imaging of optically cleared mouse uteri with single-cell and spatial transcriptomic profiling, conditional deletion of p38α at the uterine-wide versus epithelial-restricted level, and rescue experiments using progesterone and leukemia inhibitory factor. Based on these datasets, the authors propose that the luminal epithelium undergoes a previously underappreciated phase of organ-scale architectural reorganization before attachment, and that a p38α-dependent stress-responsive program coordinates epithelial remodeling together with epithelial-stromal communication required for implantation competence.

Strengths:

By moving beyond local attachment-site morphology to a horn-level representation of luminal topology, the work provides anatomical context that is difficult to reconstruct from conventional section-based approaches and should be broadly useful to the implantation community. The integration of organ-scale morphology with single-cell and spatial transcriptomic datasets, together with genetic perturbation and rescue experiments, adds breadth and increases the potential long-term utility of the dataset for investigators interested in uterine receptivity and embryo-uterine interactions.

The revision has addressed several important concerns from the original review. The added methodological details and comparison with conventional two-dimensional histology provide greater confidence that the luminal features observed by whole-organ imaging are not artifacts of tissue clearing or reconstruction. The additional measurements of epithelial folding and orientation also provide better quantitative support for luminal remodeling. The mechanistic interpretation of the p38α findings has also been improved.

Weaknesses:

Most of the major concerns raised in the original review have been addressed. I have only a few remaining comments.

First, the authors have appropriately toned down the causal language regarding embryo positioning. However, because different animals were analyzed at different time points, the direction of the relationship between luminal remodeling and embryo position cannot be determined. A few statements still sound somewhat causal, such as luminal movement "contributes to embryo spacing" and persistent epithelial branching "led to randomized embryo positioning." These could be further softened to reflect associations rather than causality.

Second, some mechanistic claims could also be more cautious. For example, the Figure 9 title states that embryo invasion failure occurs "owing to sustained epithelial polarity." The persistence of E-cadherin and β-catenin is consistent with altered epithelial polarity, but does not establish it as the cause of invasion failure. "Associated with sustained epithelial polarity" would be more appropriate.

Third, the added quantitative analyses are helpful, but the individual animal should remain the biological replicate. When multiple sections from the same dam are analyzed, these should not be treated as independent biological replicates.

Finally, the Figure 9c legend refers to β-actin, whereas the Methods and figure indicate β-catenin. This should be corrected.

Reviewer #1 (Public review):

Summary:

In this manuscript by Rezaei F. et al., the authors determine a cryo-EM structure of the human ABCG5/G8 ABC transporter that was expressed in Pichia Pastoris. The structure was nearly identical to previous crystal and cryo-EM structures of ABCG5/G8, and displayed a non-protein density in the central transport pocket between both halves of the transporter. Since the expression host Pichia pastoris natively makes ergosterol rather than cholesterol, and cholesterol hemisuccinate (CHS) was added during protein solubilization and purification, the authors used molecular dynamics simulations to probe the stability of binding for cholesterol, CHS, and ergosterol in the central pocket where the density was identified. These simulations suggested that ergosterol, rather than CHS, occupies the central pocket in the cryo-EM structure.

The authors then went on to investigate the effect of ergosterol on ABCG5/G8 ATPase activity. Interestingly, ergosterol was more potent than cholesterol or CHS in stimulating ABCG5/G8 ATPase activity. It was further demonstrated that the hydroxyl moiety of Y342 in ABCG5 is essential to achieve full stimulation of ATPase activity by ergosterol, but not cholesterol. This assay highlights a key residue (Y342) in ABCG5 that contributes to differential sterol sensitivity of ABCG5/G8.

Overall, this is a compelling story with solid biochemical kinetic data that largely support the interpretation that binding of ergosterol gives rise to the sterol-like density in the transport pocket of ABCG5/G8.

Strengths:

(1) The finding that ABCG5/G8 responds to ergosterol more strongly than cholesterol is very interesting. This suggests a plausible role for ABCG5/G8 in regulating absorption of exogenous sterols from the human diet.

(2) The biochemical kinetics data appear to be quite strong, with appropriate replicates and statistical analyses in most locations.

(3) The cryo-EM density map appears to be of good quality despite an overall resolution of ~3.6 Å.

(4) The manuscript and figures are well prepared and easy to follow.

Weaknesses:

(1) While I agree with the conclusion that the central density is likely not CHS, how can the authors be sure that this is not cholate (which was included throughout solubilization and purification)?

(2) The authors do comment on the role of the hydroxyl on Y432 being important for differential regulation of the transporter by sterols. However, it was not clear to me how the hydroxyl of Y342 could contribute to enhanced activity with ergosterol and not cholesterol. These two molecules are very similar and bind in essentially the exact same location. Could it be that the additional double bond (creating a conjugated double-bond system) in the B-ring of ergosterol interacts with Y342 in a favorable manner that is not possible with cholesterol, which lacks this double bond? It seems like more discussion on the chemical similarities and differences between ergosterol and cholesterol is warranted in order to potentially explain why the Y342 hydroxyl moiety is so critical for stimulation with ergosterol but not cholesterol.

(3) Minor weakness: Enthusiasm for the cryo-EM structure is slightly tempered by the fact that the structure is essentially identical to a previous ABCG5/G8 cryo-EM structure bound to cholesterol.

(4) I am a little confused by Figure 1D. If the RMSD is calculating the ligand position relative to its initial position in the first frame, then shouldn't the RMSD value for all ligands start at zero when the time is zero? Why does RMSD not start at 0 for all ligands and then gradually increase as the simulation progresses? Similarly, why is the starting RMSD at time 0 so different for ergosterol, cholesterol, and CHS?

(5) It would be good to include a "no sterol" control for the experiments in Figure 3B. Is the basal ATPase activity without sterols the same for WT and Y342F constructs?

(6) In Figure 4D and Table 1 (bottom), ATPase activity is measured as a function of sterol concentration, and the data are fit using a Michaelis-Menten equation, with Vmax and Km reported. I do not think that interpreting these parameters as Vmax and Km is appropriate for this experiment. Although a saturating Michaelis-Menten-type equation can be used to describe the dependence of ATPase activity on sterol concentration, sterol is not the substrate being directly measured in the ATPase reaction. Rather, the experiment measures sterol-dependent stimulation of ATP hydrolysis. Thus, these data are more appropriately described as a sterol dose-response or activation curve, and an apparent EC50 would be a more appropriate parameter to report. A true Km for sterol would require measurement of the sterol transport reaction as a function of sterol concentration.

(7) It would be good to include statistical analyses of the interaction energy decompositions from molecular dynamics (Figure 2C) where appropriate. For instance, is the difference between interaction energies for (G5)-Y424 really different for cholesterol and ergosterol? The error bar for ergosterol makes it hard to tell if this difference is statistically significant.

(8) The changes in side-chain orientations noted in the paper (Figure 2B) are really very, very small changes. I am not quite sure that these represent true changes due to ligand binding, versus small changes in model refinement into intermediate resolution range maps (~3.6Å cryoEM and ~4Å crystal structure).

(9) The discussion surrounding an alternative sterol binding pocket, and particularly its involvement in sterol flip-flop (Figure 4B), seems very speculative.

(10) The authors included AMP-PNP and MgCl2 in their sample for cryo-EM, but did not observe a closed state in 3D classification. Any speculation as to why the open conformation was obtained, or, more importantly, why AMP-PNP was included at all?

Reviewer #1 (Public review):

Summary:

The manuscript presents several reinforcement learning (RL) approaches to control activity in small, ring-shaped neural networks. The paradigm is to find temporally and spatially patterned stimuli applied to axons that maximize the length of activity propagation along the network. Several RL versions were compared. Some RL-designed stimulation patterns worked better than others.

Strengths:

The work is technically and statistically very sound, and important controls were done that are missing in some earlier work along this line of research. The statistics and technical solutions seem solid, though I am no specialist in RL. The figures are well done and informative, with matching quality of the captions. The work presented is of value mainly for someone who wants to build a good closed-loop stimulation system to experiment with neuronal networks in-vitro.

Weaknesses:

The manuscript appears undecided about whether it wants to be about RL control, about a technical implementation of long-term stimulation in vitro, or about the properties of neuronal networks and interaction with them. The introduction is well written, comprehensive and insightful, focusing on biological aspects. Methods are then extensively about RL algorithms, without explaining why several were used or why these in particular, but with specialist language hard to understand for neuroscientists. The results then quantitatively compare the performance of the RL but do not really explain what this teaches us about neuroscience or what we learn about the networks beyond that they can be stimulated for longer propagation patterns. Extensive supplementary material almost advertises the hardware built by the team. Some figures suggest, though I'm not 100% certain about this, that different algorithms find different optimal stimulation patterns in the same network - which I find puzzling. What then does this tell us about the stimulation patterns and the variability of the responses? There is some speculative mechanistic reasoning, but no data to support this further. The conclusions hardly address the initial motivation of the manuscript. To me, it is not clear what can be learned that was not, in one way or another, presented previously, with as well as without RL.

Reviewer #1 (Public review):

Summary:

The authors examine the roles of CKAP2 and CKAP2-Like in ciliogenesis. They assess the localization of both proteins in primary and motile cilia of the human male reproductive tract and use hTERT-RPE1 cells to investigate CKAP2 function. They report that CKAP2 localization is associated with cell-cycle progression and that its intrinsically disordered region is required for ciliary localization. Loss of either CKAP2 or CKAP2-Like results in elongated cilia, whereas loss of both proteins reduces ciliogenesis and restores ciliary length to approximately wild-type levels. Based on these findings, the authors propose compensatory interactions between the two paralogs.

Strengths:

The study combines tissue localization, knockout cell lines, quantitative analysis of ciliogenesis and ciliary length, and live imaging of CKAP2 dynamics. The findings extend previous work implicating CKAP2 and CKAP2-Like in microtubule regulation and support roles for both proteins in ciliogenesis and cell-cycle-associated ciliary dynamics. Overall, the study is convincing and should be of interest to readers.

Weaknesses:

The proposed compensation model requires further support. Because cilia are longer in the single-knockout cells, the ciliary fluorescence signals of CKAP2 and CKAP2-Like should be normalized to ciliary length. The same issue applies to the acetylated-tubulin fluorescence measurements. Furthermore, the ciliary-length phenotypes and increased localization of the remaining paralog do not by themselves establish functional compensation. Additional experiments are needed to determine whether acute depletion of the remaining paralog in each single-knockout background reproduces the double-knockout phenotype and whether expression of either paralog can rescue the double-knockout cells.

Reviewer #1 (Public review):

This manuscript by Lin et al. was a pleasure to read, and the results were quite surprising. The first surprise was the strength of the effects of the [MRPL10+] yeast prion on Drosophila locomotory behavior and chill recovery. The second was that this effect is highly polymorphic in different Drosophila lines, allowing the authors to perform a GWAS and implicate a number of genes involved in gut-brain signaling, thereby establishing a clear mechanism for this effect. The third was that many of these GWAS hits were validated by RNAi, giving further support to their involvement. I only have a few minor questions.

(1) Does the evidence really "support a model in which [MRPL10+] yeast promotes cold tolerance by activating serotonin signaling while simultaneously suppressing octopaminergic signaling"? I agree about serotonin, but the role of octopamine seems less clear. Figure 3d shows that mutants for genes involved in octopamine synthesis (Tdh2) and a receptor (Octβ2R) have higher cold tolerance, irrespective of [MRPL10+]. So while this does establish a role for these two genes in cold tolerance, what is the evidence that [MRPL10+] suppresses octopaminergic signaling? These seem to be two different questions. In other words, maybe any mutant with increased cold tolerance would show no response to [MRPL10+], regardless of whether the mutated gene is involved in mediating [MRPL10+]'s effects.

(2) I was also somewhat confused by the results of Supplementary Figure 4. In S4a, inhibition of octopaminergic neurons (TDC2 > TNT) seems to decrease locomotory behavior in response to [MRPL10+], which is the opposite of what I would expect from the cold tolerance experiments in Figure 3d. And then in the S4c legend, it is stated that "Loss of the octopamine biosynthesis gene Tdc2 or its receptors Octβ2R and Octβ3R triggers elevated locomotor activity even in flies fed wild-type yeast, mimicking the [MRPL10+] phenotype." I can see this for the two receptors, where both the red and black lines show high locomotor activity (>1000 passes) near the middle of each 24-hour experiment, but the Tdc2 graph in S4c looks quite different, with the [MRPL10+] activity never going above ~200 passes at any time point and the wt activity showing high variability. So if I understand the data correctly, it seems that Tdc2 mutants have higher cold tolerance (Figure 3d) but not higher locomotory behavior (Figure S4c).

(3) To summarize, I don't see how the data in either Figure 3d or Supplementary Figure 4 support a role of octopamine in the [MRPL10+] mechanism. Even in cases where perturbing a gene/neuron type abolishes the effects of [MRPL10+] on locomotory behavior or cold tolerance, this establishes a role for them in locomotory behavior or cold tolerance, but not for mediating [MRPL10+]'s effects (for the same reason given in #1 above). In contrast, the 5-HT2A results in Figure 3d do establish mechanistic relevance for serotonin, since the mutant affects only the response to [MRPL10+], but not wt.

(4) Finally, I am intrigued by the idea at the end of the paper that this represents a symbiotic adaptation. Have [MRPL10+] yeast ever been found in the wild? If not, perhaps its effects on flies are unlikely to represent anything adaptive? And if the prion is present in the wild, I wonder: if it's to a fly's advantage to have higher cold tolerance or locomotory behavior, why couldn't it evolve that itself, without needing a prion to induce it? Given the incredible adaptability of flies, I would guess that any physiological effects of a yeast prion would more likely push a fly away from its fitness optimum, and only benefit the yeast-- for example, by increasing yeast dispersal at the cost of a fly's fecundity. The main exception to that would be if [MRPL10+] yeast were only present in some specific environments that the flies couldn't adapt to on their own, but that seems unlikely.

Reviewer #1 (Public review):

Summary:

This manuscript calculates a measure of fitness flux for influenza and SARS-CoV-2 viruses, normalising by a generation time go generate comparable measures of viral adaptation over time. Potential correlates with gain in fitness flux, such as the number of mutations in different regions of the virus, are evaluated in terms of their correlation with the measured gain. A count of mutations in the S1 subunit of Spike performs slightly better in explaining observed fitness changes than previous deep-learning models describing SARS-CoV-2 evolution.

Strengths:

I enjoyed reading this manuscript. I liked the characterisation of fitness effects in a way that makes influenza and SARS-CoV-2 directly comparable. This is a neat new result.

I thought the retrospective regression against numbers of variants was a simple and interesting analysis. There is some precedent for examining correlates of fitness in key viral sites, for example in Bush et al., 1999 and Luksza and Lassig 2014: This carried on a useful tradition.

This paper is clearly written and well-constructed. The figures are well produced. There is an absence of hype in presenting results in a simple and straightforward manner.

After posing the question, I came to the conclusion that the comparison between S1 mutations and EVEscape was a fair one. The question here is that the details of the relationship between S1 mutations and fitness is derived in retrospect, from a large quantity of data, whereas PLM-based scores are advertised as having utility on the basis of only a single genome sequence. However, comparison was made with a fine-tuned model, which in some ways levels the playing field. Maybe further discussion could have been added around this point?

Weaknesses:

(1) I wasn't clear about whether the comparison with Fisher's fundamental theorem was a useful check on the analysis, or simply an inevitable consequence of any estimate of fitness scores. The fitness of a strain is measured in relative terms, as the difference in a fitness score relative to the mean of that score for the whole population. More rapid adaptation occurs when the relative difference to the mean is large, which may necessarily correlate with an increased overall variance in the fitness of strains.

(2) I would have valued more discussion on the potential implications of the findings of this manuscript. Two questions I was left with:

a) Thinking about application to a potential future emergent pathogen, to what extent is prior knowledge being leveraged in these methods? While a comparison is made of fitness gain versus statistics of multiple genes, in one sense we 'know' that the more accessible parts of the viral glycoprotein are going to be of higher relevance for viral fitness and evolution, simply from an understanding of the necessary geometry of antibody-viral interactions. Similar knowledge is leveraged in the Luksza and Lassig 2014 study: Characterising fitness by a number of epitope substitutions in that case rests on biological knowledge of which are the important epitope sites. The EVE family of methods use a similar approach where factors such as residue accessibility are combined with outputs from protein language models. But does this work have implications for how we evaluate emerging variants of existing viruses, notably SARS-CoV-2 or influenza? The H3N2/K substrain of influenza makes me want to ask this question: In that case a large number of non-synonymous changes in HA was not accompanied by a noticeable increase in the severity of seasonal influenza.

(b) What is the implication of this work for the use of PLM-based models for understanding virus evolution? One analysis that was not done is evaluating the performance of combined models, encompassing both mutation counts and PLM data. Models such as EVEscape already utilise multiple metrics alongside PLMs. Do PLMs contribute addition knowledge to a 'number of mutations on the outside of the glycoprotein' count?

Reviewer #1 (Public review):

Summary:

The authors examine the role of retinoic acid signaling in the formation of lengthened outer segments in UV cones in a localized region within the ventral temporal zebrafish retina. The authors demonstrate that the formation of this region of increased sensitivity depends on the degradation of retinoic acid by Cyp26, which is expressed in MG. Inhibiting Cyp26 or stimulating RA expression reduces OS length and visual sensitivity.

Strengths:

A key strength is the use of several experimental strategies to support conclusions. For example, the authors localize key enzymes in Müller glia (MG) and, in a separate experiment, to highlight the overall importance of MG, they ablate them. High acuity zones are critical visual specializations, and understanding their formation is important for vision research, retinal disease, and regenerative medicine. The manuscript also addresses a fundamental question in neuroscience: What are the specific signaling mechanisms that occur between neurons and glia during development?

Weaknesses:

The primary weakness is the use of inhibitors, which have systemic effects. This caveat has been appropriately addressed in the discussion.

Reviewer #1 (Public review):

Summary:

This study uses optogenetics to activate CA3 while recordings from CA1 neurons and characterizing the excitation/inhibition (E/I) balance. They observe use-dependent alterations in the E/I balance as a result of STP and they develop a model to describe these observations. This is a very ambitious paper that deals with many issues using both experimental and modeling approaches.

Strengths:

This paper examines important principles regarding the manner in which synaptic circuitry and use-dependent synaptic plasticity can transform inputs and perform computations.

Weaknesses:

(1) I am pleased that the authors revised their section on external calcium They now approach this issue by calculating the effect of low external calcium on plasticity. These calculations are based on studies of numerous types of synapses, which are unlikely to be directly comparable to hippocampal synapses. They focus on PPR rather than the overall response during more sustained activation that is likely to produce more complex responses. Obviously, it would have been preferable to simply measure the responses in the appropriate external calcium.

(2) The illumination intensity and the effect on fiber stimulation is a limitation that will alter apparent plasticity.

Reviewer #2 (Public review):

This study investigates STX, a non-steroidal, CNS-selective estrogenic compound known for its neuroprotective effects in stroke and Alzheimer's disease models. The authors successfully identify VDAC proteins, specifically VDAC1, VDAC2, and VDAC3, as the direct mitochondrial targets of STX. To characterize this interaction, the researchers employ a comprehensive approach combining chemoproteomics, single-cell qPCR, planar lipid membrane electrophysiology, and Seahorse metabolic flux analyses. The manuscript frames the physiological characterization of the STX-VDAC mechanism within POMC neurons, which serve as a metabolically sensitive and estrogen-responsive system, while appropriately positioning its specific role in neurodegeneration as a direction for future research.

A major strength of this study is its innovative methodology, particularly the development of a novel bifunctional STX probe (BF-STX) featuring a photo-crosslinkable diazirine group and an alkyne handle to capture transient STX-protein interactions in living cells. The experimental design is rigorous, incorporating essential controls such as no-UV negative controls and competition assays with excess unlabeled STX. These controls provide convincing evidence that the identified VDAC interactions are genuine rather than nonspecific artifacts. Furthermore, the authors establish a solid physiological rationale for utilizing POMC neurons to investigate these estrogen-sensitive mitochondrial mechanisms. The mechanistic claims are well supported across multiple complementary platforms, offering a clear view of how STX affects VDAC channel properties and mitochondrial bioenergetics. The authors also demonstrate scientific rigor by properly scoping their conclusions and recognizing all three VDAC isoforms as candidate targets without overstating the exclusivity of any single isoform.

The manuscript thoughtfully addresses the current boundaries of the study within the Discussion section. The authors transparently acknowledge their reliance on immortalized cell lines, correctly identifying the need for primary neurons or whole-animal models in future studies to fully establish the physiological significance of these findings. The study also notes that defining the exact structural binding site of STX and performing targeted loss-of-function experiments, such as neuron-specific VDAC manipulation, remain necessary next steps. Finally, the authors address the non-linear dose-response observed at higher STX concentrations by offering a logical, multi-target hypothesis to explain the complex data.

Reviewer #1 (Public review):

Summary:

This study investigates a fundamental question in cognitive science: is our ability to reason about the physical world an abstract mental process, or is it "embodied"-directly rooted in our real-time physical interactions with the environment? The authors compared participants' performance in computerized reasoning games with and without Galvanic Vestibular Stimulation (GVS). They suggest that participants failed more often and utilized suboptimal strategies under GVS compared to a sham stimulation condition. Furthermore, they suggest that this detrimental effect of GVS was reduced when the games were governed by altered gravity (hyper- and hypo-gravity). Consequently, the authors conclude that the physical experience of the body modifies high-level cognitive skills, such as reasoning.

Strengths:

The manuscript is well-written, organized, and easy to follow. Also, combining a specialized physical reasoning task with real-time vestibular disruption (GVS) is an intriguing approach to testing the boundaries of embodied cognition.

Weaknesses:

The empirical evidence supporting the conclusions, as currently stated in the Abstract, remains weak. The overall effect of GVS is limited, and the conclusions regarding its impact on strategy use rely on sophisticated clustering and classification methods whose reliability and validity are not clearly demonstrated in the current manuscript. The differences between Studies 1 and 2, which are critical to establishing the effect of altered gravity, are also not robust overall.

Reviewer #1 (Public review):

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

Summary:

In the manuscript by Winke et al, the authors present evidence that fear-induced analgesia is mediated by somatostatin projection cells from the vlPAG to the RVM. This study uses a mouse model of fear-induced analgesia, and incorporates optogenetic circuit manipulation with behaviour and electrophysiology to gain a meaningful insight into a novel circuit involved in fear-induced analgesia.

Strengths:

(1) This is a well-constructed study with appropriate controls and analyses.

(2) Alternative interpretations of the data are systematically considered and eliminated via rational experiments. The authors are commended for a nice piece of experimental work.

(3) The vlPAG is a known region of pain modulation, and this study adds valuable insight to the circuit involved in fear-associated analgesia.

Weaknesses:

Only male mice are included in this study. [This has been explained and noted as a limitation.]

Reviewer #1 (Public review):

Summary:

Zhang et al. report on an ambitious study that investigates multiple aspects of the neural and behavioral underpinnings of auditory-motor surprisal in the context of an auditory-motor learning paradigm (piano keyboard). Using an intricate design comprising several sub-parts and control procedures, they report that early ERPs (50-100 ms latency) reflect violations of established key-pitch mappings.

Strengths:

The paradigm is quite intricate and at the same time addresses multiple aspects of auditory-motor learning and does so in an experimentally rigorous way.

Weaknesses:

In its current form, the analyses of the ERP data remain a weak point.

Reviewer #1 (Public review):

This study demonstrates sexual selection on spatial cognition via extra-pair paternity in socially monogamous, non-migratory mountain chickadees (Poecile gambeli). Males rely on spatial memory to recover food caches, with abilities linked to survival, longevity, and heritability. In a wild population, authors quantified extra-pair young (EPY) and compared the cognition of extra-pair sires to cuckolded social males using feeder-array assays. Better-performing males sired more EPY and heavier offspring in their nests; extra-pair sires significantly outperformed social males. Results support the good-genes hypothesis: females gain indirect genetic benefits via EPY from cognitively superior mates.

Reviewer #1 (Public review):

Summary:

This study investigates how temporal and spatial discrepancies between an action and its visual feedback are combined when people judge whether an observed movement corresponds to their own action. Using a virtual-reality reaching task and computational modeling, the authors show that both temporal and spatial discrepancies reduce self-attribution and that a Multiplicative model better explains judgments than the prespecified Minimum and Mean alternatives. Importantly, the main model comparison was confirmed in a preregistered replication.

Strengths:

The study addresses an important question about how multiple sources of sensorimotor information contribute to the sense of agency. The factorial manipulation of temporal and spatial discrepancies provides a clear experimental approach to this question, and the distinction between an exploratory study and a preregistered replication is a major strength. The behavioral effects were consistent across the two samples, and the replication provides confirmatory support for the advantage of the Multiplicative model among the prespecified candidate models.

Weaknesses:

The main limitation concerns the strength of the theoretical conclusions drawn from the model comparison. Although the Multiplicative model outperformed the prespecified Minimum and Mean models, this does not uniquely establish multiplication as the underlying computational operation, because other nonlinear integration rules were not tested. The evidence therefore more directly supports cross-domain integration than a specifically multiplicative computation.

Similarly, the behavioral results do not by themselves establish that this integration occurs within a domain-general representation of agency. The binary judgment used in the task is also closely related to judging whether the seen and performed movements match, leaving open whether the observed integration reflects agency computation itself or a later decision process. These considerations do not undermine the main empirical findings, but they suggest that the broader computational and representational claims should be stated more cautiously.

Reviewer #1 (Public review):

This work uses a compelling pairing of controlled task design with rich, naturalistic behavior. It is ambitious, with eight experiments, both correlative and causal demonstrations, delayed assessments, and generalization of the phenomena to a very different domain.

The stated goal of the paper is to understand how learning different curricula "promote successful learning of complex tasks in human adults," which is a very broad scope. The evidence for generalization to a non-spatial task is compelling, but the structure of the two tasks is isomorphic, and it is still difficult to claim likely generalization to all complex tasks. For example, one could wonder to what extent demands of the task or online setting may have explicitly or implicitly encouraged participants to prefer trials that can be completed more quickly, biasing them towards choosing discovery transitions. Is it possible that they believed that the experiment might end more quickly if they chose trials that were faster to complete?

Reviewer #1 (Public review):

Summary:

The authors aim to characterize how executive function (EF) subdomains (shifting/learning, inhibitory control, working memory maintenance, and working memory updating) are organized in NHPs. They train six macaques on four touchscreen tasks per session and derive a battery of behavioral metrics. They use reliability screening, correlation analyses, unsupervised clustering, and latent factor models to argue for separable EF factors and consistent cross-session cognitive phenotypes.

Strengths:

(1) Clear behavioral effects within tasks.

(2) Battery approach with repeated sampling.

(3) Scalable.

Weaknesses:

(1) Fixed task order may be a confound for between-task correlations. Curious about the potential impact of motivational changes, reward satiety, fatigue, etc., especially if later tasks have lower accuracy or higher variance?

(2) The claim about the common EF factor is limited with only 6 animals.

(3) The claim about phenotypes and clustering is limited as one cluster is a single animal (subject F).

(4) Framing of the AS task as such is inappropriate, as it is a manual response task and is not interchangeable with classic oculomotor AS paradigms.

The authors demonstrate with solid evidence that a multi-task battery can yield repeatable performance metrics across multiple EF-relevant tasks in macaques. The data support the idea that multiple separable dimensions can summarize performance in this cohort and that individuals differ consistently across sessions. However, the claims about the three cognitive phenotypes, four-factor EF architecture, and lack of common EF factor in NHPs are only partially supported given the fixed task order, small sample size, and ambiguity about whether factors reflect stable traits or covariance between sessions. These claims would be strengthened if the authors analyze effects of the fixed task order and time since session start.

Reviewer #1 (Public review):

Summary:

This study has a very well-posed question and interesting proposed finding. It proposes that because LC activity has been shown to correlate with arousal, perhaps its activity is related to mobilizing resources for cognition and action. They use chemogenetics to inactivate LC neurons while monkeys perform a foraging task with homogeneous reward options and a working memory component. They use two task conditions, one where the grid of reward wells is visible and one where they are opaque, and the monkey has to open them to retrieve the food inside and remember where he has been. The authors claim that inactivation of LC had a selective effect on the opaque well task by increasing the number of revisits to the same wells without affecting total rewards, response times, or overall motivation, which they interpreted as reduced efficiency rather than disengagement. This is a particularly appealing outcome because it implies that LC suppression, which should lower arousal, does not cause disengagement, and rather affects working memory in some fashion. However, there are many issues with this study that make the abstract misleading, in a concerning way. The abstract and introduction are written well, but the data do not support the overall claims, and there are fundamental flaws that aren't easily resolvable.

Strengths:

The bigger question is very interesting and has broad appeal. The writing of the abstract and introduction sets the paper up clearly.

Weaknesses:

(1) The title and abstract claim effort; the paper repeatedly discusses working memory. It does not appear that any metric of effort was measured or manipulated in this study (no pupillometry, no effort-cost model, no offered choice between effort levels).

(2) The authors cite their previous paper as strong evidence of chemogenetic manipulation of LC neurons. They use that paper to justify the dose they use of DCZ, the activator of the chemogenetic construct. That study recorded only 5 neurons at that dose, and 3 of them had a reduction in rate. The statistical significance of that result is questionable (given that I think the authors averaged % change across 3 neurons and it was 15%). The authors treat that as a robust result in multiple places, for example:

"...induced a reliable 15% decrease in the firing of LC neurons..." The only significance test reported in the source paper for that data is t(5.8) = -3.6, p = 0.01, and that test compares low-dose against high-dose neurons. It establishes dose-dependence. It does not establish that 0.1 mg/kg produced a reliable decrease in firing.

"...the dose of DCZ was chosen based on its known influence on LC activity in monkey Jf, i.e. a 15% decrease in firing lasting over 30 minutes...".

This is misleading to readers with regard to the effectiveness of chemogenetics in LC and for creating a foundation for this paper.

(3) The authors seem to undermine their main argument that the opaque task requires working memory at all, and I am not convinced the monkeys were not just operating like a random agent. The random agent model seems to sample uniformly with replacement and an arbitrary termination rule, which is a straw man argument for a model. It does not allow for testing memoryless vs. memory. A monkey executing a systematic scan with short, coherent moves will avoid revisits without using working memory at all. The correct control is an agent matched to the animal's own movement statistics (step-length and turn-coherence distributions) with no memory of visited wells and with memory of visited wells. There's currently no evidence that the monkeys are using working memory in the opaque well task.

(4) The models used are not described sufficiently for interpretation or replication. The methods are brief, and the models seem pulled out of thin air with no reference to other work in foraging or any mathematical construct. If the authors have used these models before, then they should cite them, but the statements "...performance of a random agent is harder to evaluate intuitively...", "random agents have no reason to stop generating actions...", "...the number of trials was set arbitrarily...", and the qualitative comparison of performance "was intermediate between that of the optimal and average random agent..." raised concern as to whether the models were principled at all. The distance model was strange, although fine, but why not use geometry? It is also not clear why a reach would have this kind of spatial relationship when the monkey eats food between visiting locations and does not go from one box to the other without a reach to his mouth and a reach back to the board in between.

(5) The figures in this paper need work; axes are not labeled properly, or have labels that are undefined. Legends are not labeled clearly or described properly in the figure legends to interpret the figures. In multiple cases, the box and whisker plots have too little data, and the edges of the boxes collapse on themselves because IQR doesn't make sense for only 6-7 data points.

(6) The statistics seem questionable; although they used parametric and non-parametric tests, they report results of tests that assume normality for small sample sizes <10. Other choices regarding the trial number to stop counting data (e.g., on the 20th or 23rd) are suspicious and seem arbitrary, not data-driven. Some choices regarding analysis are stated in the text as arbitrary when they could be derived from hypotheses or rigor. The extremely small p-values for the ANOVA result testing performance made me suspect that this was combining all trials across sessions (given there were only 6 or 7 sessions per animal) and there was no repeated measures or nesting to account for repeated sampling within an animal. Sessions within an animal under matched conditions are the natural paired unit. So a paired or mixed-model treatment would be both more powerful and more appropriate.

(7) Lastly, there is no evidence that chemogenetics actually worked in this experiment in a way that tests their hypothesis. In Figure 7, they show their only effects that passed statistical significance (p=0.03 and p=0.028) for two monkeys, comparing across saline (D) and DCZ (D) sessions, and show a small effect on mean performance. I don't think there were corrections for multiple tests across all their monkeys and performances. But that aside, the monkeys' performances were not different from those of their random agents on mean performance, as shown in Figure 5(A). So if they are performing randomly, what would inactivation be affecting?

(8) There seems to be an ordering confound of weeks 1 and 2 being saline and weeks 3 and 4 being entirely DCZ, and only the last 2 weeks are randomized, so for 20 of the 28 sessions per animal, treatment is confounded with time.

(9) There does not appear to be any group x treatment interaction test for any analyses. Claims rest on statements like "significant in monkey 1 but not in monkey 3," etc.

(10) There are duplicated statistics between pages: "The effect reached significance for monkey Jf (T-tests, Jf: t(10.79) = -2.31, p = 0.042), but only approached significance for monkey Js (t(8.89) = 2.04, p = 0.072)." on page 12, "The number of trials performed after the 23rd reward increased under DCZ for monkey Js (T-test, t(10.79)=-2.31, p=0.042) and Jf only showed a non-significant trend (T-test, t(8.89)=-2.04, p=0.072)." on page 13 for a separate section.

Reviewer #1 (Public review):

Summary:

Drp1 promotes mitochondrial fission, whereas viral sensing can trigger mitochondrial fusion, promoting MAVS aggregation and the type I interferon response. In this manuscript, Fang et al. describe an unexpected role of caspases induced upon Rift Valley fever virus (RVFV) infection in inactivating Drp1. They show that multiple caspases cleave Drp1 in virus-infected cells and propose that this cleavage boosts mitochondrial elongation and type I interferon signaling. Finally, the authors establish the generalisability of the proposed mechanism in the context of cellular infections with H1N1, SeV, and HSV-1. Caspase-dependent and caspase-independent cell death are important components of host defense against viruses. This work suggests an additional antiviral role for caspases through the mitochondrial type I interferon axis. Although the authors have addressed most of the reviewers' concerns in a rigorously revised manuscript, one aspect of the proposed mechanism requires further validation.

The data in Figures 6E and 6F remain difficult to reconcile with the study's central thesis. The authors propose that caspase-mediated cleavage of full-length Drp1 enhances the type I interferon response in virus-infected cells. To test this model, they overexpressed the caspase-resistant mutant Drp1-3DE. Yet RVFV infection reduced Drp1-WT and Drp1-3DE levels to a similar extent (Fig. 6E), while progeny virus yield was higher in cells overexpressing Drp1-3DE (Fig. 6F). This observation contradicts the notion that the abundance of Drp1 in virus-infected cells is primarily regulated by Caspases and also weakens the potential link between Caspases and viral propagation through Drp1. The authors' rebuttal that the transcription-inhibitory function of NSs may have contributed to the reduction of both Drp1-WT and Drp1-3DE is neither persuasive nor helpful in resolving the mechanistic discrepancy. Because this is a very significant point, clarity on this matter will be critical.

Reviewer #1 (Public review):

I thank the authors for a thorough revision. The correction to the QUEEN reporter sign convention resolves what was the central issue in my original review: with the reciprocal (1/488 nm) now plotted in Figure 5, the single-cell reporter data and the LC-MS/MS measurements in Figure 2 are internally consistent, and I appreciate the added metabolomics (Figure S2B) and transcriptomics (Figure S2A, S1-S3) that support reduced de novo purine biosynthesis as the source of the lower baseline ATP in NTT1 cells, as well as the quantified Hog1 phosphorylation data (Figure 4C, Figure S8). However, several points from my original review are not yet fully resolved, and I would like the authors to address them before I can recommend acceptance.

(1) A residual, uncorrected statement about QUEEN signal directionality. The Results section (subsection "Altered intracellular ATP level modulates lifespan") still states: "...only 488 nm excitation was used in these experiments, and the resulting QUEEN fluorescence signal is inversely correlated with intracellular ATP levels (Fig. 5A-C)." This directly contradicts the corrected Methods section ("...plotted the inverse of fluorescence measurements (1/488nm), as an indicator of ATP abundance, in Fig. 5, A-C") and the Figure 5 legend and color scale, both of which now correctly state that the plotted quantity increases with ATP abundance. Given that this exact ambiguity was the source of the original contradiction the reviewers raised, I ask the authors to correct this sentence and re-check the rest of the text for any other place where the old (pre-correction) sign convention may still be described.

(2) AMPK/Snf1 validation remains indirect. I had asked for AMPK-pathway controls alongside the Hog1 quantification. The revision addresses this only through transcriptomic inference - downregulation of Snf1 target genes (MIG1, HXK1, HXK2, HXT3; Figure S7) is used to argue for low Snf1 activity under high ATP. This is a reasonable correlative observation but is not a direct validation of Snf1/AMPK activity (e.g., Snf1 Thr210 phosphorylation status or a kinase activity assay), which is what I intended by "AMPK controls." Please either add a direct biochemical readout of Snf1 activation status analogous to the Hog1 blots or explicitly temper the claims about Snf1-mediated metabolic rewiring to reflect that they rest on transcriptomic inference alone.

(3) Bidirectional-transport hypothesis addressed indirectly, not experimentally. The new metabolomics (ATP/ADP/AMP all reduced in untreated NTT1 cells) and the coordinated downregulation of the purine biosynthesis pathway are a coherent case for "reduced synthesis" as the parsimonious explanation, and I appreciate this analysis. However, this remains a correlative/transcriptomic argument rather than the direct flux experiment I suggested was feasible (e.g., an isotope-labeled ATP efflux/uptake assay to directly test whether NTT1 exports as well as imports ATP). A contraction of the adenylate pool via reduced synthesis and a bidirectional transporter are not mutually exclusive, and the current data cannot fully distinguish them. I would ask the authors to either perform such a direct test or explicitly acknowledge this as a limitation and an alternative that current data do not rule out.

In summary, the revision has substantially improved the manuscript and resolved the central ATP-directionality contradiction, but points 1-3 above should be addressed, particularly point 1, since it re-introduces the same ambiguity, the revision was meant to eliminate, before I can consider my concerns fully resolved.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. All the reviewers' comments have been adequately addressed and taken into account.]

Objectives of the study and impact of the work

The authors of this article primarily aim to reconstruct the evolutionary history of the insect odorant receptor (OR) family, which is responsible for the detection of odorant signals by olfactory neurons. Due to the lack of phylogenetic signal present in the sequences of this multigene family, which evolves very rapidly, phylogenetic analyses have so far never made it possible to precisely retrace how ORs diversified prior to the appearance of present-day insect orders, and what the drivers of this diversification were. For example, one may suspect that the adaptation of ORs to odors emitted by plants constituted a critical step in insect evolution during the "angiosperm terrestrial revolution," which occurred at the end of the Cretaceous, but nothing currently allows this to be asserted.

There are very nice examples, notably in drosophilids, derived from comparisons between closely related species and documenting mechanisms of OR adaptation to certain signals. However, what the authors attempt to do in this work is to produce a macroevolutionary analysis at the scale of insects as a whole, based almost exclusively on bioinformatic analyses. To do this, they annotated OR genes in about one hundred insect species and developed pipelines for analyzing sequence similarity, structural similarity and functional similarity, the latter being estimated through a molecular docking approach. An important element in the evolution of insect ORs is the appearance of a unique co-receptor, called Orco, which appears to be an OR that has lost the ability to bind odorants. In addition to the large-scale bioinformatic analysis, the authors also aim to explore more specifically the factors that favored the emergence of Orco and the selective advantage conferred by the existence of OR-Orco complexes.

Given the importance of odorant receptors in insect biology and in their adaptation to different environments and lifestyles, retracing their evolutionary history is indeed a major question in evolutionary biology. In principle, this type of work therefore has the potential to become a reference in the field and to provide a basis for significant scientific advances.

Major strengths and weaknesses

The sampling chosen for collecting OR sequences is very impressive, with more than 100 insect families represented, covering most of the major orders. This sampling appears appropriate for the question being addressed. The analysis pipeline used to collect the sequences makes sense, relying on homology-based annotation tools coupled with a structure-based filter. Nevertheless, one can note aberrant numbers of ORs for certain species (much lower than reality). A lower number of OR genes is somewhat expected, as the authors chose to apply a fairly stringent filter on sequence quality (based on predicted 3D structure), which reduces the number from 14,000 to 9,000. This choice seems logical given the subsequent use of these data, but it inevitably leads to data loss. However, the low number of genes also results from the fact that the pipeline did not function correctly for all genomes.

In the revised version of the manuscript, the authors included a benchmarking step, which is a good point. They compared their OR gene annotations with previous reports in the same species. Unfortunately, this comparison is irrelevant because the chosen reference OR repertoires are actually a mix of transcriptome and genome annotations. Furthermore, comparisons with entire OR gene repertoires essentially demonstrate that their annotation was of good quality for species in which OR sequences were already present in the query OR database, but poor for species in which they were not. Therefore, these supplementary analyses made by the authors are not particularly in favor of an overall good quality of OR gene repertoires in the >110 species studied. The fact that some OR genes may be missing and that the total number may not be exact for each species is not prohibitive for studying the evolution of the family on a broad scale. However, it does call into question the correlation between the number of ORs and lifestyles and diets.

From the dataset collected, the authors attempted to categorize ORs in several ways, starting with the reconstruction of sequence similarity networks. The approach is interesting, but fails to reveal homology relationships between ORs from species belonging to different insect orders. So, it is unclear what the advantage of this approach is compared with the "classical" phylogenetic approach.

The clustering based on structure also leads to the identification of a majority of "order-specific" clusters, which does not provide major insights into the evolution of ORs. However, the authors highlight a group of ORs in flies that appear to possess an unusual intracellular region, as well as a cluster of OR shared across many insect orders that exhibit a larger binding cavity. This is really interesting, although more relevant to OR structure than to their evolution.

The analysis of structural diversity then leads the authors to focus on the Orco co-receptors, which are characterized by modifications of the binding pocket and the appearance of an extracellular loop that could explain the loss of the ability to bind odorant molecules. This part, which relies on in vitro experiments, is interesting and constitutes the most striking result of this study, which could in itself have been the subject of a separate manuscript.

The rest of the manuscript is based on the prediction of OR response spectra using molecular docking. The work that has been carried out is extremely substantial, and the objective of linking clusters based on sequence similarity or 3D structural similarity with functional categories is entirely relevant. The docking score threshold used was chosen thoughtfully, which is very good, and according to the calculation performed should ensure a true positive rate of more than 20%, which is excellent in such a docking analysis. But in the absence of functional validation, this 20% true positive rate is not sufficient to extrapolate OR function, and docking-derived binding breadth measures used in the remaining of the manuscript have to be taken with caution, as acknowledged by the authors themselves. Consequently, the chance that results of this part of the work will enlighten the evolution of OR on a broad scale is low. For example, the fact that insect lineages that emerged after the Permian-Triassic extinction have more broadly-tuned OR is an interesting observation, yet remains highly speculative.

In summary, despite the large number of analyses performed, the authors do not really succeed in achieving the stated objective of reconstructing the evolutionary history of insect ORs, and the results obtained do not strongly support all the conclusions regarding the links between OR repertoires and environment or lifestyle.

Reviewer #1 (Public review):

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

Summary:

The authors aim to understand, in the context of leaf shape, how the constraints imposed by development inform evolution. Leaf shape is a good place to study the influence of development on evolution because it is a trait that exhibits a lot of diversity, and the developmental mechanisms that give rise to leaf shapes are apparently rather conserved across angiosperms.

As part of the motivation for their work, the authors cite a previous study (Geeta et al), which found that in angiosperm phylogenies, transitions from complex to simple leaf shapes occur through evolution more often than transitions in the opposite direction. Is this due to developmental constraints or adaptation?

The authors undertake two parallel lines of work:

(1) Extending the study of Geeta et al with more data, consisting of both phylogenies and a shape classification dataset. The conclusion from this line of inquiry is that transitions from lobed to unlobed leaves are more common than transitions away from unlobed leaves.

(2) The authors conduct evolution simulations in a computational model of leaf development. Here, they look at {\it neutral} mutations and whether simply neutral evolution is sufficient to drive the observed trend.

The conclusion of the second part of the work is that the driver of the evolution toward simple leaf shape is entropy: there are more ways to make unlobed leaves than to make lobed leaves (at least in terms of gene regulation parameters that will produce the two leaf types). The argument is that random gene regulatory networks are more likely to produce unlobed leaves than lobed leaves; therefore, neutral evolution drives this trend.

Data Analysis:

Roughly $9000$ images of leaves were classified into 4 categories: unlobed, lobed, dissected, and compound. These labels were applied to the tips of 5 phylogenetic trees of angiosperms (3 resolved at the genus level and 2 at the species level). By fitting a continuous-time Markov chain to the labelled trees, the authors claim that there is a significantly higher rate of transition to the unlobed leaf shape compared to transitions to more complex shapes.

Simulation:

First, the authors validate a computational model (Runions et al) for leaf growth on an experimental dataset. By changing parameters in the model, they can recapitulate the morphological changes in the shapes of Arabidopsis leaves engendered by expression of two particular genes.

Then the authors run an evolutionary model (without selection, just random mutations) on top of the computational leaf development model. As the random walk in parameter space reaches a stationary distribution, they look at both the proportions of the leaf categories in the steady state as well as the transition rates between different categories. The result is that transitions to unlobed leaves are more common than from unlobed leaves.

Reviewer #1 (Public review):

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

Summary:

Maigler et al. set out to test the hypothesis that individual differences in taste preferences are (in part) due to individual differences in central taste processing. They first tested rats' preferences for a variety of taste stimuli on multiple days. They then recorded responses of neurons in taste cortex to the same tastes on two consecutive days.

Strengths:

The authors collected high-resolution behavioral data from the same animals across multiple days, allowing for a detailed characterization of individual variation in taste preferences. They then performed recordings from the same set of animals in response to the same stimuli, allowing them to draw parallels between behavioral and neural responses.

Weaknesses:

(1) Recordings were performed only after multiple days of preference testing, and preferences were not tested in between/following recording sessions. This design precludes a direct comparison between neural and behavioral responses.

(2) Similarly, correlations between neural responses and behavioral measures are not analyzed/reported on an animal-by-animal basis.

Reviewer #2 (Public review):

I appreciate the substantial amount of work the authors have invested in revising the manuscript. The response is extensive, and the addition of pooled frequentist and Bayesian analyses represents a considerable and technically sophisticated effort to address the concerns raised during review. The authors have also improved the use and presentation of the continuous pain-rating data and have responded constructively to several methodological points.

Nevertheless, with respect to my original review, I do not think the revisions have yet aligned the manuscript's central claims with the specificity and uncertainty of the evidence. The additional analyses provide some evidence consistent with a contribution of fitness to heat-pain modulation, but they cannot fully resolve the limited internal replication, selected sample or differences in measurement procedures between studies. Nor do they establish that sex has no effect on pain modulation. In my view, the evidence supports a modest, exploratory conclusion that fitness may contribute to variability in heat-pain modulation under specific conditions, rather than the more categorical conclusion that exercise-induced pain modulation depends on fitness but not sex. The manuscript would therefore be strengthened by reflecting this distinction more consistently in the title, abstract, Discussion and Conclusion. My remaining concerns, organised in relation to the original review, are detailed below.

(1) The core interpretation may not be fully supported by the data

(1.1) Lack of baseline condition

I am satisfied with the authors' substantive response to Comment 1.1, however I note that the authors are still attributing their findings to "hypoalgesia" in the Discussion.

(1.2) Lack of internal replication across conditions

The pooled analyses do not resolve the original lack of internal replication. The substantive effect remains largely restricted to heat pain at the highest stimulus intensity and is not clearly reproduced across stimulus intensities or for pressure pain. The authors' response describes the evidence more cautiously, stating that fitness "contributes to variability in exercise-induced pain modulation". However, the title and principal conclusions do not reflect the exploratory, modality-specific and statistically uncertain nature of the evidence.

(1.3) Deviations from the original study and selective use of data

I appreciate the addition of analyses using the continuous pain ratings, which addresses my concern that the richness of the data from the current study was not being fully used. However, the decision to pool the current and previous datasets introduces a related and potentially more consequential comparability problem. The previous study used retrospective post-stimulus ratings, whereas the current study used continuous ratings from which peak values were extracted. Rescaling these measures to a common numerical range does not establish their measurement equivalence. This is particularly important because study membership is closely confounded with the participant characteristics central to the manuscript: the higher-fitness female group was recruited and assessed in the current study, whereas the comparison groups were assessed using the earlier procedure. Consequently, apparent effects of fitness may partly reflect differences in outcome acquisition between studies. Indeed, including study membership improves model fit substantially more than including fitness.

(1.4) Over-reliance on null results regarding sex differences

I do not think the new Bayesian analyses resolve my original concern regarding the interpretation of the null sex effect. The authors state that the analyses provide no evidence for a moderating role of sex, but they do not report a Bayes factor clearly supporting the null hypothesis for the exercise intensity × sex interaction. In fact, Figure 5 clearly shows that the association between fitness and pain modulation is significant in males but not females. Panels D-F indicate uncertainty regarding a differently specified exercise intensity × sex interaction, rather than evidence for its absence. The figure therefore suggests that the role of sex remains unresolved and may qualify the association attributed to fitness. The authors should therefore distinguish absence of evidence from evidence of absence and temper the conclusion that exercise-induced pain modulation depends on fitness "but not sex".

(2) Limited sample and lack of diversity

The manuscript does not acknowledge the limited generalisability of this small, highly selected sample of physically active women recruited primarily from cycling clubs. Although the rebuttal states that the findings should be interpreted within the context of the sample studied, this qualification is absent from the Limitations section. It should be added, and the conclusions restricted accordingly.

(3) Methodological choices limit interpretability of the data

(3.1) The use of a non-standard VAS scale (0-150 with a fixed pain threshold at 50) is unconventional and may influence how participants report pain, while limiting comparability with related literature.<br /> The authors' response explains the rationale for the modified scale but does not fully address its implications for measurement comparability. In particular, setting all ratings below 50 to zero is not merely rescaling: it collapses distinct responses into a single value and may alter the distribution of the outcome. The cited study addresses the relationship between real-time and retrospective ratings, but does not validate this scale or transformation.

Reviewer #1 (Public review):

The idea is super interesting, and the subsequent work is potentially significant because it links peripheral inflammation to remodelling of perinodal adipose tissue and draining lymph nodes. This suggests an antigen-independent manner by which local tissue inflammation can communicate with and reshape immune organ structure and tissue metabolism. However, the evidence is suggestive. For instance, many conclusions rely on correlational weight/cellularity relationships, models with confounders (spontaneous wounding; potentially systemic IMQ), and macrophage dependence inferred from a single pharmacologic approach without definitive depletion/lineage or tracer-based causal link.

Comments on revised version:

Overall, the rebuttal addresses most of the original concerns constructively, with additional data and appropriate moderation of several claims. However, some of the key mechanistic conclusions remain over-stated. In particular, macrophage origin, the contribution of systemic inflammation, and the mechanistic relationship between fat-pad remodelling and lymph-node expansion remain incompletely resolved. The manuscript would nevertheless be acceptable if these limitations are clearly acknowledged and the mechanistic language toned down. That said, I think the rebuttal is broadly satisfactory.

Reviewer #1 (Public review):

Summary:

This theoretical study of a simple system of stem, transient progenitors and fully differentiated cells provides interesting results about how tissues can reach homeostasis with different proportions of these cell types. The key ingredient is the feedback due to pressure, which regulates the proliferation rate. The study shows that by varying the rates at which stem cells switch to progenitor cells, and progenitor cells to differentiated cells, the final composition of the tissue can be tuned. In addition, the model shows that clusters of stem cells can arise in this model due to their effective immobilization and therefore that stem-cell niches can arise even in the absence of specific adhesion between different cell types.

The model is calculated using both cell-based simulations and continuum dynamics, and is thoroughly analyzed in its spatial and temporal characteristics.

Strengths:

The model is simple, yet leads to very rich results. The authors demonstrate the results of the model using both particle-based simulations and a continuum model, thereby enhancing our understanding of this complex system.

Weaknesses:

The origin of the stem cell niche is not so clearly explained.

Reviewer #1 (Public review):

Summary:

The manuscript entitled "NUDT2 loss defines quantitative limits for dinucleoside polyphosphate action on the cGAS-STING-TBK1 axis" investigates whether intracellular levels of dinucleoside polyphosphates can influence signaling through the cGAS-STING pathway. The study was motivated in part by a previous report proposing that Ap4A can bind to STING and inhibit its activity.

In the present work, the authors prepared recombinant human and mouse cGAS, STING, and TBK1 and systematically investigated their interactions with Ap3A, Ap4A, and Ap4G, which represent biologically relevant dinucleoside polyphosphates. To characterize these interactions, they employed a broad range of biochemical and structural approaches, including isothermal titration calorimetry (ITC), HPLC analysis of enzymatic reactions, X-ray crystallography, and a time-resolved fluorescence kinase assay.

First, the authors prepared human and mouse STING in both wild-type form and as specific mutants previously associated with altered binding of the canonical STING ligand cGAMP. ITC measurements showed that, whereas cGAMP binds STING with nanomolar affinity, none of the tested dinucleoside polyphosphates displayed detectable binding to any of the STING variants. The authors then investigated binding of ATP, GTP, and the dinucleoside polyphosphates to a mutant form of cGAS by ITC. Interestingly, all three dinucleoside polyphosphates showed apparent binding in a range similar to that of the tested NTPs. However, subsequent structural analysis did not reveal electron density corresponding to the dinucleoside polyphosphates in the active site.

The authors further examined the effect of Ap4A on TBK1 and found that Ap4A can inhibit TBK1 activity, but only at very high concentrations. Finally, they quantified intracellular ATP, GTP, Ap3A, Ap4A, and Ap4G levels in NUDT2-knockout cells. Although Ap4A and Ap4G concentrations increased substantially upon NUDT2 deletion, the measured intracellular concentrations generally remained below those required to significantly affect components of the cGAS-STING-TBK1 pathway in vitro.

Overall, the manuscript is clearly written and represents a careful and rigorous piece of biochemical work. I particularly appreciate the authors' effort to critically examine and clarify conclusions from previous studies. The experimental work is comprehensive.

Strengths:

A major strength of the study is the breadth and rigor of the experimental strategy. The authors combine binding measurements, enzymatic assays, structural analysis, kinase assays, and direct measurements of intracellular metabolite concentrations. Their data provide convincing evidence that the tested dinucleoside polyphosphates do not bind STING with physiologically relevant affinity and that inhibition of TBK1 by Ap4A occurs only at concentrations substantially higher than those normally reached in cells. Importantly, the authors also quantify the intracellular concentrations of these metabolites in cells lacking NUDT2 and show that, although Ap4A and Ap4G levels increase significantly, they generally remain below the concentrations required to affect the tested signaling proteins in vitro. This quantitative comparison between biochemical effects and intracellular metabolite levels is particularly valuable and strengthens the physiological interpretation of the study.

Weaknesses:

Interpretation of the pppGpA density in the cGAS structure.

Importantly, when Ap4G was used in the crystallographic experiments with cGAS, the authors observed density corresponding only to pppGpA. They interpret this observation as potentially resulting from processing of Ap4G by DNA-bound cGAS to generate a canonical reaction intermediate.

Based on my direct experience with structural studies of an unrelated enzyme using commercially supplied Ap4G from Jena Bioscience, I believe that an alternative explanation should be carefully considered. In our experience, Ap4G preparations can contain small amounts of pppGpA, likely at the per mille level, as a side product of the chemical synthesis. If the studied protein has substantially higher affinity for pppGpA than for Ap4G, even such a minor contaminant can become strongly enriched in the active site during crystallization and consequently dominate the observed electron density.

Indeed, traces of a corresponding contaminant may already be visible in the HPLC profile presented in Figure S2.3C. I therefore strongly suggest repurifying Ap4G by HPLC and repeating, at minimum, the HPLC-based experiments shown in Figure S2.3C using the purified material. Ideally, the purity of the Ap4G preparation used for crystallography should also be carefully documented.

Until this possibility has been excluded experimentally, I would recommend that the authors substantially temper the conclusion that pppGpA observed in the crystal structure originates from cGAS-mediated processing of Ap4G.

Reviewer #1 (Public review):

In this study, Chaudun et al use optogenetics and genetically encoded neuromodulator sensors to test to what extent dopamine neuron stimulation produces striatal serotonin release, and vice versa. The study is timely given growing interest in dopamine/serotonin interactions, but important controls are missing. The authors find that striatal dopamine and serotonin afferents function largely independently, with dopamine neuron stimulation producing no striatal serotonin release and serotonin neuron stimulation (possibly) producing minimal striatal dopamine release.

In the revised manuscript draft, the authors increased sample sizes for some important experiments, removed inconclusive electrophysiology data, reorganized the figures, and added new anatomical tracing experiments. The critical fluorophore-only controls for the optostimulation experiments requested by reviewers were not done.

Unfortunately, with the exception of increased samples sizes, these revisions have done little to substantially improve the strength of the evidence behind the authors' conclusions. These conclusions, as reflected in the new title of the paper, have also slightly changed in a manner that puts them further at odds with the data presented. As a result, my opinion continues to be that the study is interesting and the experiments are useful, but important controls are missing, a more cautious interpretation is warranted, and the organization of the study is confusing. I explain my reasoning below.

(1) A major criticism of the original manuscript was that the electrophysiology experiments were only tangentially related to the question under study. The manuscript has now been reorganized in such a way that the cocaine experiments are similarly irrelevant. In the authors' own words, the central question of the study is "does activity in one [DA or 5-HT] system directly recruit transmitter release from the other, or do DA and 5-HT operate mainly through parallel circuits?". Optogenetically stimulating release of dopamine while recording serotonin activity (or vice versa) begins to answer this question, and in the original draft, cocaine-evoked dopamine and serotonin recordings were presented side by side with the opto-evoked dopamine/serotonin data. In this configuration, the drug-evoked recording data allowed readers to compare the magnitude of dopamine/serotonin release evoked by an artificial optogenetic manipulation to that evoked by a behaviorally relevant pharmacological treatment. This serves a purpose. In the revised manuscript, the cocaine experiments are presented in a standalone first figure. As the authors themselves note in their response to reviewer 2, cocaine independently evokes dopamine and serotonin accumulation is therefore poorly suited on its own to test how activating one neuromodulatory system affects the other. Thus, the cocaine data presented alone in this way neither address the paper's central question nor support the paper's conclusions.

(2 The original manuscript suggested that one way by which striatal serotonin activity could recruit striatal dopamine release would be if the same serotonin neurons project to both VTA and striatum. To test this, the authors use retrobeads to identify DS-, NAc-, and VTA- projecting dorsal raphe neurons. However, they neither identify whether the labeled neurons are serotonergic nor evaluate colocalization between the retrograde tracers as would be required to ascertain whether the same serotonin send axon collaterals to more than one region. Thus, the anatomical data presented do not answer the question of whether the same serotonin neurons innervate both targets.

(3) As noted in the original round of review, applying light stimulation to mice expressing a fluorophore-only construct without opsin is an important control in optostimulation experiments that is widely standard in the field. The omission of such a control is a weakness of the paper. The authors suggest that other results presented - such as the lack of green serotonin sensor activation when red light is applied in the midbrain in Fig 2G-H - argues against cross-talk between the red and green optical channels. This is technically correct, but ruling out cross-talk between optical channels is not the only reason such a control is necessary. The high intensity red light used for optostim travels several millimeters through tissue and can reach the retina. Although mice do not have cones to detect red light (and therefore cannot distinguish the color red from other colors), their rods are sensitive to red light. As a result, bright red intracranial optostim can be perceived by the animal as a flashing light, and this sensory stimulus can produce a neural response. The absence of such a response in the serotonin system in Fig 2G-H does not rule out the possibility that the small response in the dopamine system observed in Fig 3G-H is driven by sensory input rather than a bona fide physiological effect of serotonin neuron activation on striatal dopamine release. Crucially, sensory responses to the stimulating light would also show 2Hz entrainment to the frequency of the stimulating laser trains. In other words, without a fluorophore-only control, the entirety of the authors' results pertaining to serotonin-evoked dopamine release can be explained by artifactual effects of the optostimulation. If this opsin-negative control is absolutely impossible for the authors to perform, at the very least this major limitation should be clearly and explicitly addressed in the discussion because it pertains directly to the study's main conclusions. This brings me to my final point.

(4) Taken together, the authors' data appear to support two primary conclusions. First, optogenetic dopamine stimulation has no effect on striatal serotonin release. Second, synchronous and supra-physiological activation of the serotonin system has a very modest effect on striatal dopamine release that might be entirely explained by artifacts of the optostimulation protocol. The miniscule magnitude of the evoked dopamine response observed following maximally strong (15-20 mW) optogenetic serotonin stimulation also bears consideration here. It argues that even if the observed dopamine release effect is not an artifact of the optostimulation protocol, serotonin-evoked dopamine release is likely to be vanishingly small or absent in other conditions when serotonin neuron firing is neither supraphysiological nor synchronous. The new title strongly implies the existence of significant cross-talk, which is not well supported by the data. Claims throughout the text that call the cross-talk effect reliable or otherwise robust are similarly overstated.

Reviewer #2 (Public review):

Summary:

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

Strengths:

The reconstituted system clearly demonstrated the requirement for each component, as substrate translocation occurred only when all components were present. Based on these findings, the authors proposed a mechanistic role for MPIase in facilitating Tat-mediated membrane translocation.

Previous studies have shown that MPIase is involved in Sec-dependent protein translocation and membrane protein integration, as well as YidC-dependent membrane insertion. The present study further demonstrated that MPIase also plays an essential role in the Tat translocation pathway.

Overall, this work highlights the central importance of MPIase in bacterial membrane protein biogenesis and provides new insights into the molecular mechanism of Tat-dependent protein transport.

Reviewer #1 (Public review):

Summary:

This study uses high-throughput bacterial cell surface display to identify LC3B interacting peptides in the human proteome. The screen is unbiased and this type of assay has not previously been used for selecting LC3B interacting peptides. The screen was done with library of 500,000 peptides and they ended up with 427 peptides that they scored as high-confidence LC3B binders. The experiments performed are solid and data are analyzed using well documented methods and statistics.

The aim for the authors was to isolate LC3B interacting peptides from the human proteome, and the screen succeeded in doing so. The selected set of peptides included several previously reported LIR motifs, but also many novel LC3B binding peptides that either contained or did not contain the canonical core LIR motif [WFY]xx[LVI].

Another aim was to identify binding determinants important for the LC3B interaction, and they made an interesting sequence logo based on selected LIR containing peptides. This study does not really extend our knowledge related to binding determinants essential for LIR motifs in LC3B binding, but it expands the number of exceptions to the canonical core LIR motif.

Strengths:

The approach used here (high throughput bacterial-surface-display) is new. The screen is unbiased and the fact that peptides are directly tested for LC3B binding may facilitate the discovery of non-canonical LIR motifs. The screen appears to be highly selective and manage to distinguish between peptides that interact with LC3B and peptides that do not interact.

Weaknesses:

It is a limitation that no proteins are analyzed in this study. Further work is therefore needed to verify that identified LIR motifs are functional in full-length proteins and in cells.

Comments on revised version.

It remains a weakness that none of the identified LIR motifs are tested in full-length proteins or cells, but all the specific comments in my initial review have been addressed.

Reviewer #1 (Public review):

Summary:

The authors present the most comprehensive phylogenomic study of free-living kinetoplastids to date, including newly generated transcriptomic data from 11 species. This dataset provides a solid foundation for future comparative evolutionary studies of kinetoplastids, a group that includes important human pathogens such as Trypanosoma brucei.

Strengths:

The study is clearly written, and the analyses are thoroughly described, well documented, and reproducible. The phylogenomic dataset comprises 444 proteins, which is larger than those used in many comparable phylogenomic studies. The main strength of the study is the substantially improved taxon sampling of neobodonids, which provides a much stronger framework for resolving evolutionary relationships among free-living kinetoplastids.

Weaknesses:

The phylogenomic analysis is based on a newly assembled dataset comprising 444 single-copy orthogroups. Using an established phylogenomic dataset, expanded to include the newly studied species, to confirm the inferred relationships would provide additional support for the robustness of the recovered topology.

Reviewer #1 (Public review):

Summary:

This study addresses an important question of how recovery from conditioned fear can be characterized beyond the reduction of defensive responses. The authors combine multiple behavioral measures with a theory-guided hidden Markov model to identify recurring behavioral modes and examine how the organization of behavior changes during fear conditioning and extinction. The study provides an interesting and potentially valuable framework for examining recovery from conditioned fear as a broader change in behavioral repertoire rather than simply as a reduction in defensive behavior.

Strengths:

A major strength of the study is the attempt to characterize fear-related behavior as a dynamic organization of multiple behavioral measures rather than relying on a single conventional measure such as freezing. The integration of freezing, ultrasonic vocalizations, and food-reinforced behavior into recurring behavioral modes provides a potentially useful approach for capturing behavioral states that may be missed by analyses of individual responses. The study also presents a theoretically motivated framework for distinguishing defensive, quiescent, exploratory, and goal-directed behavioral modes, which could provide a useful conceptual basis for studying functional recovery following aversive experiences.

Weaknesses:

The main concern is whether the analyses and behavioral definitions provide sufficient support for the interpretation of these behavioral modes and, in particular, for the proposed concept of functional recovery. First, the data-driven model selection indicates substantially better predictive performance for eight states, whereas the authors retain four states primarily to conform to their theoretical framework. A stronger justification for prioritizing the four-state solution would therefore strengthen the interpretation of the results. Second, it is difficult to determine from the current behavioral measures whether the Quiescent state reflects safety and rest or behavioral inhibition associated with residual fear or anxiety. The marked reduction in exploratory and goal-directed behavior could potentially be consistent with either interpretation, making it important to consider alternative explanations for this state.

The definition of functional recovery also warrants further consideration. The authors propose the reinitiation of food-seeking behavior in the previously threatening environment as an important indicator of recovery. From an evolutionary and ethological perspective, however, an animal that has experienced a threat while foraging in a particular location may benefit from shifting its foraging to an alternative location rather than returning to the previously threatening location, even after extinction learning. Thus, the resumption of goal-directed behavior in the previously threatening environment may not necessarily represent a biologically appropriate benchmark for successful fear extinction or functional recovery, as functional recovery may involve substantial changes in motivational processes that cannot be captured by the simple return of a previously suppressed behavior. More broadly, the results may support the value of examining behavioral repertoire during extinction, but they do not yet establish that restoration of the broader repertoire, or specifically the return of goal-directed behavior in the previously threatening environment, is required for functional recovery.

Finally, the use of the no-shock control group could be more informative. The observed reduction in exploratory behavior during conditioning cannot by itself distinguish associative fear learning from habituation to novelty. A direct comparison between shock and no-shock groups would therefore help determine whether the changes in behavioral modes are specifically related to conditioning.

Overall, the study provides a potentially useful framework and an interesting conceptual perspective on recovery from conditioned fear. However, the strength of the evidence supporting the interpretation of the identified behavioral modes and the proposed definition of functional recovery is currently limited. Addressing these interpretational and analytical issues would strengthen the manuscript and help establish the extent to which this framework provides a meaningful advance in the study of fear extinction and recovery.

Reviewer #1 (Public review):

Summary:

The manuscript proposes an architecture and distance-regression-based logic for 3D cell segmentation.

The architecture combines a U-Net backbone with an xLSTM bottleneck layer and two novel components: a Zernike Phase Layer that is used for input normalization and the Scaled Grid Geocaps that link the input and bottleneck, inspired by the Capsule mechanism.

During training, the network predicts foreground vs. background and regresses a distance transform as output. During inference, these predictions are used as input to a watershed procedure to segment cells in 3D.

The method is evaluated by training on four different 3D cell/nucleus segmentation tasks and compared to StarDist3D and CellPoseSAM baselines, which are also trained on the respective datasets using the same train / val / test splits.

The authors report improved segmentation quality compared to the baselines.

Strengths:

The experiments are solid; ablation studies evaluate the main architectural components, and the software appears to be well documented (I did not have time to test it).

Weaknesses:

(1) This is not really a weakness but a general point: the main issue in microscopy segmentation is that a lot of training data is needed if training a network from scratch. This results in a very laborious data annotation process. This is what modern approaches like CellPoseSAM and microSAM address by providing strong pre-trained networks that work well out-of-the-box for many imaging settings and can then be fine-tuned with a few corrected images to achieve state-of-the-art results. Having a better 3D segmentation approach is of course still worthwhile, but does not address the main practical challenge. I would suggest clarifying this in the introduction.

(2) The authors implement a well-known strategy to segmentation in microscopy: regressing the distance transform. They acknowledge some prior work (Scherr et al., Lux and Matula), but this approach is more prevalent than acknowledged, including for 3D cell segmentation. For example, microSAM [1] implements cell instance segmentation by regressing the distance to the cell boundary and centroid, which is applied in 3D by CochleaNet [2]. See also [3] for an overview of different distance- or flow-field-regression-based cell segmentation approaches. I would suggest performing a more thorough literature review and acknowledging more prior work.

(3) The baseline comparisons are not described in any detail, are questionable for CellPoseSAM, and lack current state-of-the-art models:

3.1) The details on training and inference for the baseline methods are missing. This is particularly missing for CellPoseSAM. Here, it would be important to clarify whether the model is initialized randomly or with CellPoseSAM's pretrained weights and which of the two different 3D segmentation modes is used (see next point). It would also make sense to report both CellPoseSAM in zero-shot mode and finetuned for all cases.

3.2) CellPoseSAM supports two different 3D segmentation modes: either a "2.5D" segmentation mode, where the network is applied across all three axes, the resulting flow maps are merged, and then used for segmentation. And an "overlap-based stitching mode", where segmentation is applied only in the XY plane and slices are then merged based on overlap. It is unclear which of these modes is used. Ideally both should be reported; the "2.5D" mode often leads to worse results for anisotropic data, and we almost always prefer the overlap-based stitching in practice.

3.3) Two important state-of-the-art baselines are missing:

i) microSAM [1], which is widely used for cell segmentation based on a pretrained 2D network that is extended to 3D using a similar strategy as CellPoseSAM's overlap-based stitching mode. It would make sense to report both zero-shot and fine-tuned performance.

ii) uSeg3D [4]: this method implements a generalized 3D stitching approach that works independently of the underlying architecture and reports significant improvements.<br /> Improving and extending the baseline experiments would give a much better picture of the practical relevance of this work.

References:

[1] https://www.nature.com/articles/s41592-024-02580-4

[2] https://www.biorxiv.org/content/10.1101/2025.11.16.688700v1.abstract

[3] https://doi.org/10.6084/m9.figshare.32782521

[4] https://www.nature.com/articles/s41592-025-02887-w

Reviewer #1 (Public review):

Summary:

The manuscript authors have used Martini 3-based CG simulations to study how S22 phosphorylation and two catalytic-pocket inhibitors, Nexturastat A and HPOB, regulate HDAC6 condensation.

In isolated IDR1 slabs, phosphorylation lowers the apparent saturation concentration without compacting single chains, and the manuscript attributes this to new contacts between the phospho-S22/D26 region and Arg/Lys-rich patches. The two ligands perturb these contacts differently. In full-length multichain systems, the C-terminal FD3 domain is the most frequent contact partner, and the ligands shift contacts from FD3-FD3 toward pocket-FD3. The manuscript proposes a two-layer mechanism by which pocket-binding ligands regulate multidomain condensates.

Strengths:

The question is well motivated by published experiments, the simulated IDR1 construct matches the experimental one, the phosphorylation contact pattern recurs across independent salt conditions, and the Discussion offers testable predictions. My main reservations are whether the full-length results are robust to the model and to sampling, and whether the evidence reaches the mechanistic and pharmacological conclusions drawn from it.

Weaknesses:

(1) The full-length conclusions rest on FD3-FD3 being the dominant domain contact. The water-interaction correction applies only to the disordered regions, so the folded domains retain standard Martini 3 behavior, which is known to overestimate protein association (e.g., Thomasen et al., J. Chem. Theory Comput. 2022). The contact maps are also normalized per bead, which favors a small domain such as FD3. Please test whether FD3-FD3 dominance survives a folded-domain correction, and show raw contact counts next to the normalized maps. Without this test, and without experimental evidence that this domain self-associates, frame the FD3 result as a model prediction.

(2) The ligand-treated IDR1 slabs are single trajectories with no statistical uncertainty on the saturation concentrations or on the contact-difference maps. The full-length systems have three replicates; contact numbers are still rising at the end of several trajectories (Figure S9), and most differences between Nexturastat A and HPOB overlap within error. The wild-type controls also reverse the ligand ordering (Figs. S12, S14), which suggests that trajectory-to-trajectory variation may drive the domain-level differences. Please add independent replicas for the ligand comparisons, show convergence over consecutive time blocks, and report uncertainties on the difference maps. Claims should then be limited to the differences that are resolved.

(3) The Discussion presents the simulations as explaining why Nexturastat A suppresses HDAC6 condensation more strongly than HPOB. However, every full-length system assembles at a high protein concentration, and total contacts and morphologies are similar across conditions, so the simulations do not show suppression. The IDR-level and domain-level mechanisms are studied in separate systems, and ligand distribution and IDR1 contacts are not analyzed in the full-length assemblies, so the coupling of the two layers named in the title is not tested. Please add an analysis that bears on condensation propensity and on this coupling, or recast "explains" as "is consistent with" and revise the title and abstract accordingly.

(4) For phosphorylation, the IDR1 fragment is strongly basic, so a simple reduction of net charge could lower the saturation concentration without a position-specific contact node. The phosphoserine charge state used is also lower than expected at neutral pH. Moving the same charge to a distal serine, and testing the fully charged phosphoserine, would distinguish these readings. For the ligands, the coarse-grained models show only weak pocket engagement, lack a non-pocket control, have unvalidated nonbonded parameters, and are simulated at millimolar concentrations. The ligand-IDR1 mechanism could therefore reflect nonspecific association. Please add a non-pocket surface control, validate the ligand parameters, and relate the simulated concentrations to those of the motivating experiments.

Reviewer #1 (Public review):

This manuscript describes a multi-modal study of associative learning and memory in humans that combines scalp EEG, pupillometry and behavioral analysis to explore the construct of mnemonic prediction errors (MPEs), in terms of their relationship to attention and cognitive control. Across two pooled studies, participants performed associative memory tasks in which they learned the relationship between a cue word (action verb) and subsequent picture (animate or inanimate) with a strong vs. weak (4 or 1 repetitions) encoding manipulation. At test, participants were encouraged to generate a prediction following the cue word to determine whether the subsequently presented picture was a match or mismatch. The timecourse of pupillary responses during match decisions were decomposed using temporal principal components analysis, which identified 6 distinct and overlapping processes. Some of the components (PC3/PC4) exhibited sensitivity to both the strength and mismatch conditions, as well as behavior (both RT and accuracy) and retrieval success on the subsequent trial. Furthermore, relationships were also observed between pupillary responses (specifically for PC4) and both frontal theta and posterior alpha power measures obtained from scalp EEG in Experiment 2, as well as for frontal theta and subsequent learning from mismatch stimuli (assessed using subsequent memory findings from a surprise recognition test). The authors suggest the findings indicate that MPEs elicit changes in attention, arousal and cognitive control which impact subsequent learning.

Strengths:

This manuscript has many strengths, including a clever study design, thoughtful integration of multiple neurocognitive measures, and a set of rigorous and technically sophisticated analyses, which reveal a large set of relationships among the measures and behavior. The findings demonstrating brain/physiology-behavior relationships are particularly important, in that they point to potential functional consequences of MPEs.\

Reviewer #1 (Public review):

Summary:

The authors aimed to re-analyse two fMRI datasets of studies investigating the effect of cognitive emotional regulation on amygdala response during the viewing of negative images, in order to assess whether such effects might have been missed in previous reports of the results of these studies. In order to accommodate potential non-typical response profiles in the amygdala, they used a modelling approach that is agnostic about the shape of the BOLD response (finite impulse response modelling). Furthermore, the authors sought to differentiate between amygdala subregions using i) two previously published probabilistic atlases of amygdala subnuclei; and ii) a data-driven analysis focusing on temporal response profiles, which identified four clusters that mostly overlapped with anatomical parcellations. The analyses confirmed their previous results insofar as they did not find any impact of emotional regulation on the amygdala response in any subregion. However, their approach revealed differences in temporal response profiles between amygdala subregions: the centromedial amygdala showed sustained activation extending into the post-stimulus rating period, whereas laterobasal and superficial subregions peaked earlier during stimulus presentation. Overall, this study helps to clarify whether cognitive emotional regulation during negative image viewing alters amygdala response, and demonstrates the value of flexible response modelling to differentiate between functional subregions of an important brain structure.

Strengths:

The strengths of this study lie in the amount of data used (a combined N of 358 participants is rather high), the flexibility of the modelling approach (FIR), the exploratory nature of the data-driven clustering based on temporal response profiles, and clarity of the text and of the findings. One weakness would be the fact that no fMRI data acquired at higher field strengths were used for the aim of differentiating responses of amygdala subunits.

In my opinion, the authors achieved their aims of re-analysing these datasets with complementary methods, and helped to discover new aspects of the BOLD response in the amygdala during emotional regulation. The results support their conclusions.

This work is likely to stimulate discussion of the response of amygdala subnuclei during emotional regulation, and might encourage researchers to resort to more flexible analysis methods by demonstrating the information gain achieved with the FIR approach.

Weaknesses:

There are 7T studies of the amygdala response that have looked at differences in BOLD response across subnuclei. While I don't know of any that have investigated emotional regulation, I think these studies should nevertheless be mentioned and discussed in the Discussion, at least to compare the differences observed across subnuclei.

Reviewer #1 (Public review):

Summary:

Wang et al. report that changes in the levels of canonical Wnt signaling in CNS ECs modulate protein expression levels of VEGFR2 and VEGFR1. An increase in Wnt/beta-catenin signaling results in a decrease in VEGFR2 and an increase in the decoy receptor VEGFR1; conversely, reduction of Wnt signaling leads to the opposite changes in VEGF receptors in brain CVOs (less clear in the retina). Next to the solid quantitative immunostaining of VEGFR2 and VEGFR1 in multiple CNS regions using genetic mosaics and loss-of-function mouse mutants, the authors employ HEK293T cells to investigate the effect of activation of Wnt/beta-catenin signaling on multiple RTK signaling systems and on the level of overexpressed VEGFR2. The principal conclusions are that Wnt/beta-catenin regulates VEGF signaling. Two distinct levels of regulation are reported: one acts in vivo on receptor protein expression levels, the other acts in 293T cells, and the precise mechanism remains to be identified.

Strengths:

Strengths of the study include the use of genetic mosaics that allow for quantification of immuno-staining intensity with an internal reference and the significance of understanding the interplay of beta-catenin-dependent and VEGF pathways.

There are also some weaknesses noted:

(1) Experiments to restore the VEGFR2/VEGFR1 ratio in vivo, or to modulate VEGF signaling in vivo, and assess to what extent Wnt/beta-catenin LOF phenotypes can be restored by modulation of VEGF signaling have not been conducted at this point. In addition, it remains to be determined to what degree an experimental recreation of the aberrant VEGFR2/VEGFR1 ratio is sufficient to recreate (partially) some of the phenotypes observed with loss of Wnt/beta-catenin signaling in ECs.

(2) It would be useful to consider and discuss other essential components of the VEGF signaling system, especially Neuropilins. Wang et al. (2012, Figure 2, PMID: 23217714) reported that CNS ECs with loss of Norrin signaling gain Sema3F binding while not displaying VEGF-B binding sites, suggesting changes in VEGF/semaphorin co-receptor biology.

(3) Martowicz et al. (2019) PMID: 31533473  also investigated the influence of Wnt/beta-catenin signaling in CNS ECs on VEGFR2 and VEGFR3 expression and reported findings regarding VEGFR2 regulation that appear to differ from the present study. This should be discussed.

(4) Norrin/beta-catenin and Wnt/beta-catenin signaling have a critical role in CNS angiogenesis, and Wnt surrogates counteract neovascularization in the oxygen-induced retinopathy model. These findings highlight context-dependent roles of Wnt/beta-catenin signaling in normal and pathological ECs. How the modulation of VEGFR2/VEGFR1 may influence developmental and pathological angiogenesis could be discussed.

(5) When looking up the publicly available scRNA-seq datasets from Heng et al. (2019, PMID: 30988181) from Norrin KO mice, it appears that there is transcriptional regulation of VEGFR1/VEGFR2 consistent with the protein regulation reported here. If transcriptional regulation is important, CMV-driven VEGFR2 expression in Fig.5 supplement 2 may not model the regulatory mechanisms observed in vivo. Does CHIR99021 modulate VEGFR2/VEGFR1 transcripts and proteins in HRMVECs?

The Law of Lidia Poet, tv series, season 03 ep. 04<br /> via https://www.facebook.com/groups/TypewriterCollectors/posts/10164207248754678/

Reviewer #1 (Public Review):

Summary:

In this paper, Li and colleagues have found mircoRNAs that affect levels of metamorphosis-regulating genes that can also affect levels of sesquiterpenoids (juvenile hormone and related compounds) and ecdysteriods, which regulate the timing and stages of insects, respectively. They first compared the transcriptomes of Drosophila at the third larval instar and at the white pre-pupa stage. They found thousands of differences in gene transcript levels between males and females, and between the two different stages. Among those genes that were differentially regulated they saw that genes involved in insect hormone biosynthesis were disproportionately represented. Many of the differentially regulated genes were involved in the insect hormone biosynthesis pathway and ascorbate and alderete metabolism. MicroRNAs were also differentially expressed during metamorphosis and were separately identified. The authors then considered genes and whether the differentially expressed microRNAs might regulate transcripts known to be involved in sesquiterpenoid production. In silico analysis of microRNAs predicted a list of 17 microRNAs that can regulate transcripts of sesquiterpenoid biosynthesis genes. The authors then used an in vitro luciferase assay to validate the binding and downregulation of 10 of the microRNAs to genes involved with sesquiterpenoid production in S2 cells.

Li and colleagues then focus on two genes they found were bound by microRNAs that have established roles in metamorphosis. The microRNAs miR-34 and miR-277 bind transcripts of two protein-coding genes that regulate metamorphosis Kr-h1, which encodes a transcription factor that is a JH-inducible transcription factor, and Allatostatin C Receptor 1, (AstC-R1), a G-protein coupled receptor that regulates the corpora allatum, the gland that produces sesquiterpenoids. Using a LAMP assay, one of the microRNAs, miR-277 was shown to bind to both AstC-R1 and Kr-h1 in in vivo whole-animal extracts. There is no mention of binding between either protein-coding transcript and the miR-34 microRNA. Temporal expression of all four transcripts shows that their abundance is anti-correlated; stages of high miR-34 or miR-277 expression correlate with low AstC-R1 or Kr-h1 expression. Homozygous deletions of both mircroRNAs result in 23% lethality, five days after adult eclosion. The authors also generated specific mutants in miR-34 or miR-277 and find differences in the expression of AstC-R1 and Kr-h1 and sex-specific differences in both sesquiterpenoids and ecdysteroids in the knock-out lines. If there were phenotypes associated with the specific knock-outs, those were not mentioned. Next, the authors examined the transcriptomes of the miR-3277 and miR-34 mutants and found several other GO-terms enriched among the differentially expressed genes. However, the sesquiterpenoid pathway and ascorbate and alderete metabolism are not listed.

Strengths:

This is an interesting manuscript that could make an important contribution to our understanding of the roles of micro RNAs at metamorphosis, and potentially of how sex-specific differences arise during metamorphosis. Strengths of the paper include the functional validation of microRNA binding, in vitro and in vivo-, as well as the characterization of sesquiterpenoid and ecdysteroid titers. The authors have also used CRISPR to generate specific knock-outs of miR-34 and miR-277. The transcriptomes will be a resource for future work to mine for differences in gene expression during metamorphosis.

Weaknesses:

(1) Spatial Expression of miR-34 and miR-277. If miR-34 and miR-277 regulate AstC-R1 and Kr-h1, then they must be expressed in the same cells. Although the authors show that the microRNAs do bind to the transcripts of AstC-R1 and Kr-h1 in S2 cells, and miR-277 binds AstC-R1 and Kr-h1 in vivo whole-animal homogenates, we do not know if the microRNAs are ever in the cells where AstC-R1 or Kr-h1 are expressed. AstC-R1 is only expressed in a few cells in the brain, so it is not at all certain that it is co-expressed with either microRNA. The creation of enhancer lines or in situ hybridization in Drosophila is straightforward and would sort this out.

(2) Phenotypes. Although a double deletion was used and specific knock-outs of both miR-34 and miR-277 were generated, the analysis of the mutants is very superficial. For the homozygous deletion of both microRNAs miR-34 and miR-277, only a decrease in survivorship was observed a full six days after adult eclosion - after the end of metamorphosis. No phenotype for either miR-34KO or miR-277-KO was given. The authors cite the work of others who have found specific phenotypes after manipulation of sesquiterpenoids or ecdysteroids, like Riddiford and Ashburner, but do not use any of these many studies to help them characterize the phenotype. If the loss of miR-34 and miR-277 affects so many pathways (including MAPK signaling, TGF-beta signaling, FoxO signaling, and Wnt signaling), as well as global titers of metamorphic hormones, then there shouldn't there be something different in the development to discuss?

(3) I think the reliance on GO term enrichment is getting in the way of biology. For instance, I would not describe Kr-h1 as a sesquiterpenoid biosynthesis pathway gene. Yet the authors say they were motivated to examine microRNA regulation of Kr-h1 because they saw differences in levels of the sesquiterpenoid biosynthesis pathway between WL3 and WPP, a period which also saw differences in expression of some microRNAs. I understand that Kr-h1 expression is regulated by JH, a sesquiterpenoid, but it is not directly involved with JH production, so relying on GO term enrichment has made the decision to focus on Kr-h1 feel arbitrary.

(4) The transcriptomes of miR-34 and miR-277 should have revealed genes encoding members of the sesquiterpenoid biosynthesis pathway as well as AstC-R1 and Kr-h1, but neither was mentioned. The functional tests of miR-34 and miR-277 were performed because they were shown to affect the levels of expression of genes in the sesquiterpenoid biosynthesis pathway. Figure 2 shows a significant decrease in AstC-R1 and Kr-h1 transcripts after the loss of miR-34 and miR-277. However, the results do not mention either (Lines 250-264). Instead, there is a list of 10 different GO terms (like arginine and proline metabolism or fatty acid degradation) that were enriched in miR-34 and miR-277 transcriptomes. If any of those ten types have any relationship to Kr-h1, AstC-R1, or metamorphosis, that has not been explained.

(5) Not enough care was taken in describing the stages. The methods describe wandering larvae (WL3) and white pre-pupa (WPP) for the transcriptomes, but in the text, different terms are used, like "larva", "pupa" and "L3 larvae instars" "early pupae" "late L3". Also, it seems like the small RNA libraries for sequencing were taken from "L3 larvae", but the stage of the L3 larvae was not mentioned. Staging is important, especially during metamorphosis, since differences in expression are expected to exist between different stages of L3, between early vs late wandering, and between WPP and early pupal stages.

Reviewer #1 (Public review):

Summary:

In the manuscript entitled "Gene function and expression profiling in yeast spores, killifish diapause embryos, and their post-dormant offspring cells" the authors analyze dormancy at three levels: functional, transcriptomic and proteomic, using Schizosaccharomyces pombe spores, diapausing killifish embryos and human dormant cancer cells as models. The authors performed a genome-wide Bar-seq screen for gene deletions in fission yeast spores and then compared changes in mRNA and protein expression in young and old and heat-stressed cells in yeast and killifish. The main conclusions of the work include that dormancy is a dynamic not static state. The authors conclude that specific biological processes, rather than particular genes, are conserved across organisms during the dormancy, and that there is a clear disconnect between the mRNA and protein kinetics and behavior, particularly for ribosomal proteins and processes related to autophagy and mitochondrial metabolism.

In general, the manuscript is well structured and written, with carefully designed figures. The authors are also generally aware of the limitations of the work. The manuscript is interesting and valuable, but some interpretations should be moderated.

Major comments:

(1) The data presented provide in general good support for majority of conclusions presented in the manuscript. However, less support is provided for the theories that: there is a universal "core expression signature" of dormancy; the mRNA/ribosome protein uncoupling reflects a specific mechanism of preparation for exiting dormancy; and the observed changes provide evidence for an epigenetic "memory" of dormancy. These elements are currently more interpretive than evidentiary. I would recommend softening the language in these places and clearly labeling them as hypothetical.

(2) The authors propose that spores and post-dormancy cells retain a memory of time spent in dormancy or stress exposure. However, sporulation is also generally expected to reset or remove accumulated damage. Please clarify whether the observed long-term effects reflect classical "memory" of the cell, persistent regulatory state, or selection of cells with different fitness (carry-over effects). I would be careful in interpreting the effects as a form of memory associated mostly with epigenetic control - the statement seems stronger than what the data directly demonstrate.

(3) Validation of a small set of top hits by independent assays would substantially strengthen the conclusions. For example, targeted qPCR and/or biochemical assays for key genes (like ribosomal and autophagy) or pathways would help confirm the most important transcriptomic and proteomic trends. Without this, the suggestion of, for example, translational regulation remains possible but unproven.

(4) Overall, the study appears reproducible, with detailed methods, biological replicates, and appropriate statistical analyses. However, reproducibility could be improved by more clearly describing the limitations of the comparisons (especially with the published datasets) and the data-processing parameters, particularly for correlation and functional enrichment analyses. Some comparative conclusions are based on data from different studies, under different conditions and often with different depths of coverage. It is not always clear to what extent interspecies comparisons are fully methodologically similar.

Significance:

This is an ambitious work that combines a genetic screen with multi-omics analyses and cross-species comparisons. The novelty is less in known roles of autophagy, mitochondria and translation, but rather in integrating them into a comparative framework across S. pombe spores, killifish diapause embryos, and dormant human cancer cells, combined with Bar-seq screening and multi-omics. Its greatest strength is its coherent, broad concept: dormant cells are not passive, and the regulated processes and functions during dormancy are evolutionarily conserved rather than the individual set of genes. The contribution of this work lies more in demonstrating process-level conservation than in identifying a single universal gene. This significantly expands the literature on dormancy, but rather in terms of a framework of biological organization rather than a single mechanism.

The weakness of the manuscript is the tendency to draw broad, sometimes overly strong mechanistic conclusions based primarily on correlational data (sometimes with poor statistical significance) and on relative, rather than absolute, expression. The lack of biochemical validation, in my opinion, lowers the impact of the paper.

Audience: This work will be of interest especially to aging and dormancy specialists and comparative biologists. It is important to note that this is not a purely technical or model-specific work, but it has the potential to impact researchers interested in homeostasis, translation and adaptation to stress.

My expertise: My expertise is mostly in aging, sporulation, cell cycle control and ribosome biogenesis.

Reviewer #1 (Public review):

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

The authors sought to determine how Rif1 contributes to DNA replication timing (RT), transcriptional regulation, and embryonic development using zebrafish. They generated a maternal-zygotic rif1 knockout line and examined developmental phenotypes, genome-wide replication timing profiles, RNA-seq, and nascent transcription (SLAM-seq) during early embryogenesis.

Their major findings in this manuscript are.

(1) Rif1 is not essential for zebrafish viability, unlike its partially essential role in mice.

(2) Rif1 deficiency causes defects in female sex determination, delayed epiboly, and reduced primitive erythropoiesis.

(3) Genome-wide RT is altered by Rif1, but developmental stage has a much larger influence than Rif1 itself.

(4) Rif1 is required for the proper maturation ("sharpening") of the RT program during development rather than for specific developmental RT switches.

(5) Rif1 has a much stronger effect on transcription during zygotic genome activation (ZGA) than on replication timing at these early stages.

(6) Loss of Rif1 leads to increased expression of early zygotic genes, indicating that Rif1 normally suppresses widespread transcription during ZGA.

Overall, the work proposes that Rif1 independently regulates replication timing and transcription, with these two functions becoming most prominent at different developmental stages.

The major strengths of the manuscript are as follows.

(1) the study combines multiple genome-wide approaches including whole-genome RT profiling, RNA-seq, SLAM-seq in combination with gene KO and developmental analyses.

(2) One of the strongest points is that the authors conducted the analyses at multiple developmental stages rather than a single point.

(3) The most important conclusion is that the Rif1 regulates transcription during development in a manner largely independent of its RT function, which was further strengthened by the additional data provided in the revised manuscript.

Comments on revised version:

The authors responded to my comments in a largely satisfactory manner. They have conducted additional analyses and concluded that Rif1 regulates transcription during ZGA largely independently of its classical RT function, which is an important finding.

Although authors did not examine origin firing and replication fork rate in rif1 KO cells, which I suggested in my original review, this can be saved for their future studies.

I think the revised manuscript has been improved and provides important basic information on the functions of the conserved Rif1 protein in RT and transcriptional regulation.

I have no further recommendation for additional experiments or data analyses.

Reviewer #1 (Public review):

Summary:

Desingu et al. show that JEV infection reduces SIRT2 expression. Upon JEV infection, 10-day old SIRT2 KO mice showed increased viral titer, more severe clinical outcomes, and reduced survival. Conversely SIRT2 overexpression reduced viral titer, clinical outcomes and improved survival. Transcriptional profiling show dysregulation of NF-KB and expression of inflammatory cytokines. Pharmacological NF-KB inhibition reduced viral titer. The authors conclude that SIRT2 is a regulator of JEV infection.

Strengths:

This paper is novel because sirtuins have been primarily studied for aging, metabolism, stem cells/regeneration. Their role in infection has not been explored until recently. Indeed, Barthez et al. showed that SIRT2 protects aged mice from SARS-CoV-2 infection (Barthez, Cell Reports 2025). Therefore, this is a timely and novel research topic. Mechanistically, the authors showed that SIRT2 suppresses the NF-KB pathway. Interesting, SIRT2 has also been shown recently to suppress other major inflammatory pathways, such as cGAS-STING (Barthez, Cell Reports 2025) and the NLRP3 inflammasome (He, Cell Metabolism 2020; Luo, Cell Reports 2019). Together, these findings support the emerging concept that SIRT2 is a master regulator of inflammation.

Comments on revised version.

The authors have addressed my comments.

Reviewer #1 (Public review):

This work reports the finding of a dissociable human Mediator complex subunit, MED16, and its recruitment of transcription factors UBP1 and TFCP2 that form a trimeric complex regulating cellular gene transcription and inhibiting HIV promoter activity, thus promoting MED16-targeting inhibitors as HIV latency-reversing agents for anti-HIV therapy. In this revision, the authors provide new data indicating that MED16 action occurs in the holo-Mediator complex, not as a free form, for its functional association with UBP1 and TFCP2.

Summary:

Characterization of a dissociable Mediator subunit implicated in cellular pathways, particularly lung alveolar function, and HIV latency is conceptually interesting.

Strengths:

The strengths of this study are:

(1) Demonstration of MED16 dissociation from the core Mediator complex and formation of a subcomplex containing MED16, upstream-binding protein 1 (UBP1), and transcription factor cellular promoter 2 (TFCP2) by elegant biochemical fractionation and immunoblotting analysis.

(2) Defining nine N-terminal WD-40 repeats (WDRs) of MED16 as a Mediator-incorporating module and the C-terminal ⍺β-domain (157 amino acids) important for interaction with the UBP1-TFCP2 heterodimeric complex.

(3) Illustration of a weak hydrophobic interaction between MED16 and the Mediator core that could be disrupted by 1,6-hexanediol, but not by its 2,5-hexanediol isomer nor by high salt (500 mM NaCl) disruption.

(4) Classification of UBP1-upregulated cellular genes typically containing binding sites flanking the transcription start site (TSS) in contrast to UBP1-downregulated genes often containing a TSS-overlapping UBP1-binding site;

(5) Presenting evidence for Mediator complex-dissociated free MED16-repressed HIV promoter activity through functional association with UBP1 and showing bromodomain-containing protein 4 (BRD4) inhibitor JQ1 that potentially disrupts BRD4-inhibited HIV-1 transcription elongation could lead to reversal of HIV-1 latency.

Weaknesses:

(1) No clear demonstration that MED16-UBP1-TFCP2 indeed form a trimeric core subcomplex in regulating cellular gene transcription and HIV-1 promoter inhibition.

(2) No validation of transcriptomic datasets and pathways identified.

(3) Use of mostly artificial reporter gene constructs and non-HIV host cells (e.g., human 293T embryotic kidney cells, human HeLa cervical cancer cells, and mouse HT pancreatic cancer cells) for examining MED16/UBP1-regulated HIV transcription.

(4) Inconsistent use of 293T and HeLa cells in the characterization of dissociated MED16 interaction with UBP1 and TFCP2.

(5) In vitro transcription using immobilized DNA templates was not performed to a high standard thus failing to convincingly show MED16/UBP1-inhibited HIV-1 transcription preinitiation complex formation.

In this revision, the authors stipulate that the action of MED16-UBP1-TFCP2 is through the holo-Mediator complex, not as a free trimeric complex, since deletion of the N-terminal Mediator-incorporating module abolishes the functional effect of MED16 even though its interaction with UBP1-TFCP2 persists. The authors also show that a predicted UBP1-binding site is indeed present in the promoter region not overlapping with the TSS in each of the UBP1/MED16-upregulated respiratory gaseous exchange genes, such as surfactant protein A1 (SFTPA1), SFTPA2, SFTPB and SFTPC. To demonstrate UBP1/MED16-inhibited HIV transcription in a more biologically relevant system, the authors employ an HIV-1 latency model derived from CD4+ T cells. Additional experiments are also performed to address other issues raised by the reviewers.

Overall, the revised manuscript has been improved by addressing some of the reviewer's comments. Additional issues that came up while reading this revision are: a) The statement, "UBP1 (as known as LBP-1) and TFCP2 (as known as LSF) belong to a subfamily of the TFCP2/Grainyhead transcription factor family" (lines 63-64), is confusing and needs to be clarified. My understanding is that LBP-1 has four family members encoded by two different genes (see Yoon et al., MCB 14: 1776-1785, 1994): LBP-1a and LBP-1b are probably UBP1, and LBP-1c and LBP-1d are likely TFCP2/LSF. If this is correct, the authors should clearly indicate which specific isoforms are analyzed in their UBP1 and TFCP2 proteins and clarify some of the text descriptions seemingly contradictory to the earlier findings.

The use of mostly artificial reporter templates and transfection assays conducted mostly in 293T and HeLa cells remains concerning. It is also unclear why overexpression of MED16 only, but not MED23 or MED24, inhibits HIV promoter activity (Figure 5) if MED16 action is through the holo-Mediator complex and overexpression of MED16 may titrate out key cellular factors, thus diminishing their action through holo-Mediator. Results based on this squelching type of experiment relying on overexpression of a single component needs to be carefully interpreted.

Reviewer #1 (Public review):

Summary:

This is a useful study by Angla et al that investigates the basis of observations made from previous studies where loss of Onecut (OC) transcription factors lead to changes in spinal interneuron populations that do not themselves normally express OC. The authors hypothesize that OC expression in spinal motor neurons has non-cell-autonomous effects on pre-motor interneuron (V1, V2a/b/c) population size and distribution. By knocking out OC in the motor neuron lineage (i.e., downstream of Olig2, a motor neuron progenitor marker gene), they indeed show that motor neuron-specific loss of OC expression decreases V2c interneuron number and alters the spatial distribution of V1, V2a, V2b, V2c populations. Using bulk RNA-sequencing of WT and OC conditional knockout (cKO) motor neurons, the authors identify that neurotrophic factor Ntf3 as another factor that is responsible for the non-cell-autonomous effects on the interneuron population; upon knock out of Ntf3 downstream of Olig2 they show that this leads to increased interneuron numbers and alters their spatial distribution, ultimately leading to dysregulation of spinal motor circuits and motor activity.

Strengths:

The authors use sophisticated genetic tools to precisely remove OC and Ntf3 expression in a lineage-specific manner and comprehensively assess the downstream effects across brachial, thoracic, lumbar levels of the spinal cord, as well as at two developmental timepoints, E12.5 and E14.5.

Weaknesses:

The evidence supporting their claims is incomplete. In figure 2 and 4, the control distributions (despite reporting the same populations in the same regions) look different, suggesting large sample-to-sample variance in distribution. The authors explain that this is due to several technical limitations in their study.

Furthermore, the way the Ntf3 results are framed can be misleading; it reads as though one of the main claims of this study is that OC acts through Ntf3.

Reviewer #2 (Public review):

Summary:

Vertebrate spinal cord receives inputs from many supraspinal regions. The authors used optical backfilling to trace neurons in the zebrafish larval brain sending axons to the spinal cord . With two-photon microscopy, they managed to render a comprehensive 3D map of these neurons and drew homologs with mammalian brain structures.

Strengths:

The main strength lies in the precise 3D mapping. The fact that most of previously reported neuron groups have been confirmed by their approach is a solid endorsement of their methodology.

This study provides a comprehensive alternative anatomical reference framework for studying individual groups of supraspinal neurons with projections to the zebrafish spinal cord.

Weaknesses:

The backfilling approach does not reveal the full trajectories of axons, which is available to some degree by ZExplorer Atlas.

Reviewer #1 (Public review):

Summary:

The study by Fernandes et al used multiple types of experiments to study the increased metastatic activity conferred by p95-HER2 and presented evidence that biased downstream signaling was engaged by p95-HER2. Further studies demonstrated crucial phosphorylation sites and downstream transcription targets. Overall, this study will contribute to increased understanding of HER2 biology and breast cancer metastasis.

Strengths:

Multiple types of experiments to assess the increased invasion property by p95-HER2. Solid evidence was provided that p95-HER2 elicits a different transcription program, enhancing EMT. Convincing results were achieved in knockdown studies on crucial genes such as MRTFA and TGFB1I1.

Weaknesses:

To enhance the quality of this study, several points need to be addressed.

(1) First, as the background to this study, the authors stated in the introduction that different isoforms of HER2 lead to different invasive properties. Is this conclusion based on clinical observation or animal models? This needs to be specified to help readers grasp the importance of the paper.

(2) Second, this study is mostly performed on three cell lines generated from three tumor models, WT, d16, and p95. Were multiple cell lines generated from the same tumor model (e.g., p95), and how similar are these cell lines if they are from the same tumor model?

(3) Third, Figure 2 presented data from a very interesting experiment. However, the overall conclusion of this experiment is hard to grasp from the text.

Reviewer #1 (Public review):

Summary:

The manuscript aims to mechanistically characterize the final step of the Lol lipoprotein trafficking pathway in Gram-negative bacteria, where triacylated lipoproteins are transferred from the periplasmic chaperone protein LolA to the outer membrane receptor LolB for subsequent insertion into the inner leaflet of the outer membrane. The crystal structures of LolA R43L-LolB, LolB L114G-lipoprotein, LolB Q44A (open), and LolB Q44A (closed) are reported. A combination of structural analysis, growth assays, pull-downs, and fluorescence spectroscopy was employed to characterize the behaviour of wild-type and mutant forms of Lol proteins. The authors then used previously published molecular dynamics simulations to propose a six-step model for the transfer and insertion of lipoproteins from LolA to LolB, and finally into the membrane.

The structural work is mostly solid, but the mechanistic conclusions drawn from it rely too much on interpolation between static states and on functional assays with limited dynamic range.

Strengths:

(1) The structure-guided mutagenesis was thorough and well designed. Mutants were tested both in isolation and in combination with one another, utilizing both alanine and charge reversal mutants, to fully tease apart which residues were most important for the interaction.

(2) The dissection of the Hook interactions allowed the authors to identify the importance of the identity of the hook apex residue, as well as the critical hydrogen bond that maintained the Hook geometry.

(3) The structure of the lipoprotein-bound LolB is a valuable addition to the body of knowledge around this pathway, and the way that the complex was produced was very clever.

Weaknesses:

(1) There is no raw data shown for any of the interactions or lipoprotein transfer experiments. All of the quantitative claims about LolA association and lipoprotein transfer rely on SDS-PAGE densitometry, and not a single gel image from those experiments is provided in the main text or supplemental.

(2) Pull-down assays are a fairly poor assay to use for protein interactions when there are so many quantitative alternatives that would be amenable to this experimental system, especially when the association and transfer of lipoprotein are the central claims of the manuscript.

(3) The crystal structures are under-refined for their resolution, with large R-factor gaps and somewhat concerning statistics contained in the wwPDB reports (e.g. >20% RSRZ outliers in 2/4 structures). The data also seem to be cut at strangely high I/sigI for the two Q44A structures with no explanation.

(4) In the LolB L114G structure, the Hook residue L68 is the most poorly fit in the whole structure. The validation report indicates the entire hook is poorly resolved, but without access to the maps and models, we are unable to assess this independently.

(5) There is no rubric for what constitutes a significant result for the DAUDA fluorescence spectroscopy. What level of increase vs wild-type is considered significant? I188G is incredibly close to L144G, but one is treated as a non-result and the other as something that should be further investigated.

(6) The conformational trajectory of the proposed model is on static endpoints.

Reviewer #1 (Public review):

Summary

The authors set out to address a critical gap in olfactory bulb research: the lack of a comprehensive annotation of neuron types and their connectivity in the adult zebrafish. Using a large serial block-face scanning electron microscopy volume, they reconstructed 459 neurons and performed a detailed morphological and ultrastructural classification. They identified 13 major neuron subclasses, including two projection neuron types (mitral cells and ruffed cells) and 11 interneuron types. A key finding is that despite the diffuse appearance of the lateral olfactory bulb neuropil, it is organized into discrete, segregated glomeruli. The authors also performed targeted synapse annotation, revealing systematic and selective connectivity patterns between projection neurons and specific interneuron subnetworks, and discovered distinct microcircuit motifs involving reciprocal and unidirectional connectivity. This work provides a crucial anatomical framework for understanding the circuit basis of olfactory computations.

Strengths

(1) The volumetric EM reconstructions capture fine ultrastructural features (e.g., spine shapes, neurite caliber variations, and varicosity morphology) at nanometer resolution across hundreds of neurons. The descriptive detail and 3D rendering provided for each subclass are remarkably thorough.

(2) The study goes beyond simple morphological descriptions by integrating ultrastructural features, such as spine shape, neurite diameter, and synaptic arrangements, to define neuron classes. This provides a more functionally relevant taxonomy. The classification was also cross-validated by independent neuroscientists.

(3) The targeted synapse annotation translates anatomy into testable circuit hypotheses, revealing distinct connectivity motifs (reciprocal vs. unidirectional, MC-selective vs. RC-selective) that provide structural substrates for computational functions such as normalization.

Weaknesses

(1) It is important to provide an estimate of the total neuronal population of the adult zebrafish OB and justify that their sample size is sufficient to claim a "comprehensive" neuron type classification.

(2) The classification was based on morphology and ultrastructure. If feasible, we recommend an unsupervised clustering analysis using only the synaptic connectivity matrix for fully reconstructed neurons to test whether connectivity patterns recapitulate the 13 morphological subclasses. Besides, cross-validation by independent annotators is great. However, when the annotators disagreed on a neuron's subclass, how was it resolved?

(3) A summarized reference table that includes features for each subclass is highly recommended (the main text cited several tables; however, I did not find them). This would facilitate community adoption of the classification.

(4) The schematic in Figure 20 could be optimized to reflect synaptic connections among 13 subclasses with connection strength annotated.

Reviewer #1 (Public review):

Summary:

The authors sequenced 888 individuals from the 1000 Genomes Project using the Oxford Nanopore long-read sequencing method to achieve highly sensitive, genome-wide detection of structural variants (SVs) at the population level. They conducted solid benchmarking of SV calling and systematically characterized the identified SVs. While short-read sequencing methods, including those used in the 1000 Genomes Project, have been widely applied, they exhibit high accuracy in detecting single nucleotide variants (SNVs) and small insertions and deletions but have limited sensitivity for SV detection. This study significantly enhances SV detection capabilities, establishing it as a valuable resource for human genetic research. Furthermore, the authors constructed an SV imputation panel using the generated data and imputed SVs in 488,130 individuals from the UK Biobank. They then conducted a proof-of-principle genome-wide association study (GWAS) analysis based on the imputed SVs and selected traits within the UK Biobank. Their findings demonstrate that incorporating SV-GWAS analysis provides additional insights beyond conventional GWAS frameworks focusing on SNVs, particularly in improving fine-mapping.

Strengths:

The authors constructed a high-sensitivity reference panel of genome-wide SVs at the population level, addressing a critical gap in the field of human genetics. This resource is expected to significantly advance research in human genetics. They demonstrated the imputation of SVs in individuals from the UK Biobank using this panel and conducted a proof-of-concept SV-based GWAS. Their findings highlight a novel and effective strategy for integrating SVs into GWAS, which will facilitate the analysis of human genetic data from the UK Biobank and other datasets. Their conclusions are supported by comprehensive analyses.

Weaknesses:

The authors have addressed many of my previous comments, and I appreciate their efforts. However, I still have two related concerns.

(1) Shortly after reviewing this manuscript last year, my laboratory obtained access to the UK Biobank (UKB) Tier 3 dataset for an unrelated project. In August 2025, I searched the UKB Research Analysis Platform (UKB-RAP) for the imputed structural variant (SV) dataset described in this manuscript but was unable to locate it. After contacting UKB, I was informed that they were developing the system for releasing the data. To the best of my knowledge, the dataset remains unavailable. A major contribution of this work is the generation of an imputed SV resource for approximately 500,000 UKB participants with extensive phenotypic information. If this resource is not accessible to the research community, even to authorized UKB users, the practical impact and utility of the study are substantially diminished.

(2) Given that the imputed SV dataset is currently unavailable, it becomes even more important for the authors to provide a detailed, ready-to-run SV imputation pipeline for UKB-RAP, even if the "data processing simply consisted of running standard bioinformatics tools with the parameters exactly as described in the manuscript". In particular, the pipeline should include practical information such as computational requirements (e.g., memory and storage), expected running time, and estimated cost. Anyone with experience using UKB-RAP will agree that reproducing large-scale analyses on the platform can be both technically complex and financially expensive. Such pipeline would greatly improve the reproducibility and accessibility of this work.

Because my initial assessment of the manuscript was generally positive, I do not wish to change my overall evaluation, summary, or assessment of its strengths. However, I would view the work even more favorably if either (i) the imputed SV dataset became publicly available to authorized UKB users, or (ii) the authors extended their SV-GWAS analyses to the full range of UKB phenotypes and released the resulting summary statistics, analogous to the Pan UKBB ("https://pan.ukbb.broadinstitute.org/") resource. Although this would require considerable additional effort and computational resources, it would substantially enhance the long-term value and impact of the study.

Finally, I would like to emphasize that these comments are not intended to create unnecessary difficulties for the authors or the editors. Rather, I believe this highlights a broader issue in the use of this kind of large public datasets: reviewers cannot independently verify key results, and readers cannot readily build upon the work if the underlying resources are inaccessible, even after obtaining authorized access to the original dataset. I hope the authors, together with the eLife editors and UK Biobank where appropriate, can help facilitate the timely release of this valuable resource.

Reviewer #1 (Public review):

Summary:

The authors sought to develop a generalisable method for clearing and labelling large, highly complex human organs and tissues while preserving their three-dimensional structure, enabling visualisation at high resolution. The resulting body of work is substantial, encompassing a diverse range of tissues and labelling approaches, and demonstrates an impressive breadth of experimental work.

Strengths:

A major strength of the method is its systematic validation across a diverse range of human tissues, including several understudied tissues, in combination with labelling using multiple antibodies and fluorescent dyes. An additional strength is that the skin was retained on the finger throughout the clearing, labelling, and imaging procedures, allowing the tissue to be analysed in an intact state. This is particularly relevant to sensory neuroscience, where preserving the cutaneous sensory structures may be important. The use of tissue from donors aged 85 years and older is also a strength, as it provides a stringent test of the method in tissues with substantial age-related pigment accumulation and autofluorescence.

Weaknesses:

A major limitation is the lack of evidence that the method can be applied to formalin-fixed, paraffin-embedded (FFPE) tissue, which represents a substantial proportion of archived human tissue and is an important potential application of tissue-clearing approaches. Furthermore, the claim that the method is cost-effective is not sufficiently supported by the data presented, as there is no comparison of the costs of the proposed approach with those of existing methods.

Appraisal:

(1) Overall, I feel that the authors have broadly achieved their stated aims, although several aspects would benefit from further qualification or supporting evidence.

(2) Although magnetic resonance imaging (MRI) was performed on four tissues, the MRI data do not appear to be fully integrated with the microscopy data, and I did not find evidence of precise spatial correlation of structural information between the two modalities.

(3) The term "photoclearing" may be useful to describe the approach, but the underlying concept does not appear to be entirely novel, given that increased optical transparency can occur as a consequence of photobleaching. Furthermore, the evidence presented is not sufficient, in my view, to establish that the observed effects are attributable to photodegradation of pigments.

(4) I question whether the broader claims regarding the scalability of existing tissue-clearing approaches are sufficiently supported. In particular, the claim that aqueous- and hydrogel-based methods have limited scalability may require further evidence, given that perfusion-based approaches can facilitate processing of large tissue volumes. Similarly, the assertion that organic solvent-based approaches are better suited to large tissue volumes does not appear to be fully supported by the data presented, unless this refers specifically to the beneficial effects of tissue shrinkage during dehydration on imaging.

(5) More generally, a direct comparison of the clearing, labelling, and imaging outcomes for the thyroid samples fixed for 48 hours versus 8 years would be valuable for assessing the extent to which fixation duration influences the performance of the method.

Discussion:

The results have potential value for medical education, comparative anatomy, and research requiring the characterisation of human anatomy across spatial scales. The method could have applications across multiple disciplines and may be of interest to researchers who have access to human tissue from sources including archival material, biopsies, surgical resections, tissue banks, autopsy specimens, and donor tissue. However, the length and complexity of the protocol may limit its practical adoption, particularly in settings where throughput is an important consideration.

Context:

The results for the inner ear and ring finger are particularly notable because they demonstrate the ability of the method to clear, label, and image anatomically complex, highly calcified, and densely structured tissues. The successful clearing and immunolabelling of tissue fixed for 15 years is also significant, given the potential challenges associated with antibody penetration and preservation of epitopes following prolonged fixation. More broadly, successful imaging of large organs, such as the heart, is technically important given the challenges that their size and geometry present for light-sheet microscopy, and demonstrates the feasibility of applying the approach to intact human organs.

Technical concern:

The manuscript should acknowledge the hazardous and potentially toxic nature of several reagents used in the protocol, together with the challenges of safely handling and disposing of the relatively large volumes of chemical waste generated. These factors may have practical implications for implementation of the method.

Conceptual concerns:

The role and added value of photogrammetry in the study are not entirely clear. It would be helpful for the authors to clarify how photogrammetry was used beyond its presentation in the figures and what additional information or utility it provides relative to the other imaging modalities employed.

Reviewer #1 (Public review):

Summary:

The authors introduce a foraging task designed to test whether movement and harvesting durations are governed by a common objective combining reward, effort, and time or by separate objectives. Participants generate wrist torque to move a cursor to a rewarding patch and then hold it within the patch while reward accumulates at a diminishing rate. The task allows reach and harvest effort, as well as delays before or between the two phases, to be manipulated separately.

Reach effort strongly affected reach duration but had little effect on harvest duration, whereas a delay imposed after reaching altered harvest duration without affecting the completed reach. Manipulation of harvest effort did not affect either duration. The authors also found consistency across individuals within each type of duration but no reliable association between reach and harvest durations. The separate model fit the behavioral results better than the common-utility model, particularly for the post-reach delay condition. The findings therefore support partly dissociable, but coupled optimization of harvest and movement in this task, while not excluding common optimization in other contexts.

Strengths:

The task provides a controlled way to manipulate the effort and delays associated with reaching and harvesting while measuring both durations. The control experiments alter the timing of delays, allowing the experimenter to test whether their effects depend on when they occur. These manipulations produce clear behavioral dissociations, particularly the selective effect of a post-reach delay on harvest duration. The delay and effort manipulations were verified, and most participants reported noticing the changes in effort and time.

The separate model extends a previous cost-of-time framework to a foraging task involving movement and reward harvesting. Its assumptions have a clear relationship to the experimental design: applied delays and actions enter the time offset for each separate cost function. This provides an intuitive account of why a delay occurring after the reach can affect harvesting without affecting the completed movement. The separate model also provides a better fit than the common utility model in both modeled experiments.

The individual-level behavioral analyses are also useful. Reach durations are correlated across reach conditions, and harvest durations are correlated across harvest conditions, indicating stable individual differences within each measure. The lack of a corresponding relationship between reach and harvest durations raises an important question about whether the two forms of vigor necessarily reflect a common individual tendency in their task.

Weaknesses:

The block design and familiarization made the changes in effort and delay learnable, and most participants reported awareness of these manipulations. The observed dissociation may reflect adaptation to this task structure. This does not weaken the behavioral result, but it limits how directly the findings can be generalized to tasks in which changes in reward, effort, or time are less explicit.

The main modeling limitation is that both models are fitted to ten group-level median observations in each experiment, rather than to individuals' behavior. The separate model has seven fitted parameters compared with three in the common model. Although the reported AIC penalizes additional parameters, the analysis includes no participant-level fitting, resampling, or cross-validation.

Reviewer #1 (Public review):

The study by Luden et al. seeks to elucidate the molecular functions of AHL15, a member of the AT-HOOK MOTIF NUCLEAR LOCALIZED (AHL) protein family, whose overexpression has been shown to extend plant longevity in Arabidopsis. To address this question, the authors conducted genome-wide ChIP-sequencing analyses to identify AHL15 binding sites. They further integrated these data with RNA-sequencing and ATAC-sequencing analyses to compare directly bound AHL15 targets with genes exhibiting altered expression and chromatin accessibility upon ectopic AHL15 overexpression.

The analyses indicate that AHL15 preferentially associates with regions near transcription start sites (TSS) and transcription end sites (TES). Notably, no clear consensus DNA-binding motif was identified, suggesting that AHL15 binding may be mediated through interactions with other regulatory factors rather than through direct sequence recognition. The authors further show that AHL15 predominantly represses its direct target genes; however, this repression appears to be largely independent of detectable changes in chromatin accessibility.

In addition to the AHL protein family, the globular H1 domain-containing high-mobility group A (GH1-HMGA) protein family also harbors AT-hook DNA-binding domains. Recent studies have shown that GH1-HMGA proteins repress FLC, a key regulator of flowering time, by interfering with gene-loop formation. The observed enrichment of AHL15 at both TSS and TES regions, therefore, raises the intriguing possibility that AHL15 may also participate in regulating gene-loop architecture. Consistent with this idea, the authors report that several direct AHL15 target genes are known to form gene loops.

Overall, the conclusions of this study are well supported by the presented data and provide new mechanistic insights into how AHL family proteins may regulate gene expression.

Reviewer #1 (Public review):

Summary:

The manuscript by Sustar et al. takes a methodical approach to document the types of glutamate receptor subunits that reside in Drosophila muscles, examining developmental stages spanning from larvae to adults. Prior work thoroughly documented the subunits operating in Drosophila larval body wall muscles. Most subsequent research focused on the glutamate receptor heterotetramers found in the body wall, composed of GluRIIA/C/D/E or GluRIIB/C/D/E subunits, along with auxiliary subunits like isoforms of Neto.

For the current work, the authors report that the larval muscle glutamate receptor composition is not universal for all Drosophila muscles. They examine the following muscle systems: larval body wall, adult abdomen, adult leg coxa, and adult indirect flight. They also briefly examine adult muscle structures associated with the proboscis, neck, and haltere. The authors find that the receptor subunits in the adult abdomen (mostly) match those in the larval body wall. This makes sense given that the adult abdominal muscles are derived from the larval body wall. Yet not much else matches the larval body wall. For example, all (or most) of the GluRII-type subunits are missing from the adult indirect flight muscles. Leg muscles have GluRII-type subunits, but they do not have all of them expressed prominently, and they are missing GluRIIB. Additionally, leg muscles express a glutamate-gated chloride channel, which could be a source of inhibitory glutamatergic transmission. Interestingly, when it comes to non-abdominal adult muscles, one general theme seems to be an active promoter (GAL4 driver) for the kainate-type glutamate receptor called Clumsy. The authors propose that Clumsy could be key to understanding how functional GluR complexes are assembled in adult insects.

Strengths:

(1) Documenting the types of glutamate receptors that operate in diverse insect muscle systems is important because it uncovers fundamental information.

(2) Much of the prior research focus has been on how the body wall muscle tetramers assemble and operate. It is a strength to demonstrate the other receptor solutions used by adult NMJs.

(3) The work uses GAL4 drivers and immunohistochemistry (when possible) in combination to draw conclusions.

(4) The muscle anatomical analyses are high quality. This allows the research group to reach refined conclusions.

(5) The confocal-level images of synaptic active zones and their apposed glutamate receptor clusters are high quality.

(6) The dataset adds specific detail and complementary context to bulk transcript analysis collections like FlyAtlas.

(7) The Discussion section is insightful. It is not simply a recap of the data in the paper. It is also an integration of that data with prior work, and it suggests direct experiments that the research team or others could attempt downstream.

Weaknesses:

One can draw expression-level conclusions from these data. But genetic tests (e.g., would clumsy losses of function impair leg muscles?) could help the authors and the field draw stronger conclusions about the roles of some of these glutamate receptor gene products.

Overall Assessment and Discussion:

The data in this study are high quality, and the results support the main conclusion: adult muscle glutamate receptor clusters do not recapitulate the "canonical" larval body wall clusters.

Comments on revised version.

The authors have done a serious revision of their manuscript, and they have directly addressed context/interpretation-level concerns that I had from the first round.

Reviewer #1 (Public review):

Summary:

The authors address the lack of validated tools for detection and quantification of proteins associated with amyotrophic lateral sclerosis (ALS) through an extensive screening of 303 commercially available antibodies to 33 protein targets. Their ALS-Reproducible Antibody Platform (ALS-RAP) delivers a validated antibody toolbox for ALS research, which will provide an advantageous starting point for researchers in this field. Ayoubi R. et al. showcase the characterization workflow, presenting as an example the characterization of antibodies targeting Galectin-1, encoded by the LGALS1 gene. A selection of these antibodies was also used to profile protein levels across human induced pluripotent stem cell (iPSC)-derived and primary neurological cell types, and the fundings support that ALS disease mechanism involves both neuronal and glial cells.

Strengths:

The knockout (KO)-based approach is definitively the major strength of this study, providing a high level of confidence in the data collected in human induced pluripotent stem cell (iPSC)-derived and primary neurological cell types. Important is also the focus on renewable reagents (monoclonal and recombinant antibodies). The extensive characterization of this set of antibodies will benefit any scientist interested in any of the 33 targets proteins, even in fields other than neuroscience.

The authors perform an interesting protein profiling study assessing 27 proteins, comparing RNA and protein expression data, and using two independent WB preparations of the same cell types. The conclusions that can be drawn from this first assessment might not be final, but data are compelling, because they have been collected with reliable and validated antibodies.

Another strength of this work is the data dissemination strategy, which includes the Only Good Antibodies (OGA) platform, where YCharOS data are curated and presented in an easy and intuitive manner that facilitates antibody selection by the end user for WB, IP and IF applications.

The authors mentioned the development of single-chain variable fragment (scFv) recombinant antibodies raised by the SGC against the six proteins (ANXA11, OPTN, MATR3, PFN1, UBQLN2 and VCP) that had limited renewable antibodies that are commercially available. The development was optimized to generate antibodies particularly suitable for IP, and the clone selection process was carried out using IP coupled to mass spectrometry. They provide details on the screening process for the SGC-generated scFv antibodies, plus share that scFv sequences.

Weakness:

The protein profiling study is limited to WB data, and the authors did not provide any explanation on why there was no integration with IP and IF data, not even for those targets that have validated antibodies. Also, not all the cell types have been screened by chemiluminescence-based detection and by fluorescence-based WB, and the authors do not elaborate on the reason for such choice. Technical and practical considerations for such decisions could have been briefly described.

Reviewer #1 (Public review):

Summary:

This is a study utilizing several types of analyses (computational modeling, neuronal cultures, rodent epilepsy model, and human intracranial multi-scale recordings) to address a highly relevant conceptual question: Are fast ripples (FRs) distinct pathological entities or largely emergent products of stochastic spike clustering? The results can potentially reshape current approaches to incorporating fast ripples into the epilepsy surgery evaluation.

Strengths:

The conceptualization of fast ripples as potentially arising by chance is highly novel and builds effectively on questions raised in prior studies that have never been satisfactorily resolved. Integration across biological scales and models provides a rigorous approach, now improved by addressing theoretical concerns regarding validity of the shuffling approach and state dependence. The discussion has been updated to provide a more nuanced interpretation of the study's findings.

Weaknesses:

The authors have satisfactorily and thoughtfully addressed the critiques provided in the first review. However, there remain two points that I would like authors to address prior to publication:

(1) Synchronized burst firing is a key feature of an epileptic site generating interictal discharges, and one that could generate either oscillatory or stochastic FRs as documented in multiple prior publications cited in the manuscript and/or in the prior review. Paroxysmal depolarization, for example, has been very well described, and consists of strong, disorganized burst firing (resulting in summated postsynaptic potentials strong enough to generate high gamma signal) in a neuronal population coinciding with a large low-frequency deflection. I would like to see the results described in this context, and to avoid blanket dismissal of stochastic FRs without a clear oscillatory component.

(2) It would be highly useful to add a conclusion paragraph that spells out implications of the study for use of FRs as epileptic biomarkers in clinical invasive EEG recordings.

Comments on revised version.

The author's additions to the discussion are appreciated.

Reviewer #1 (Public Review):

This work revisits a substantial part of the published literature in the field of Drosophila innate immunity from 1959 to 2011. The strategy has been to restrain the analysis to some 400 articles and then to extract a main claim, two to four major claims and up to four minor claims totaling some 2000 claims overall. The consistency of these claims with the current state-of-the-art has been evaluated and reported on a dedicated Web site known as Reprosci and also in the text as well as in the 28 Supplements that report experimental verification, direct or indirect, e.g., using novel null mutants unavailable at the time, of a selected set of claims made in several articles. Of note, this review is mostly limited to the manuscript and its associated supplements and does not integrally cover the Reprosci website.

Strengths:<br /> One major strength of this article is that it tackles the issue of reproducibility/consistency on a large-scale. Indeed, while many investigators have some serious doubts on some results found in the literature, few have the courage, or the means and time, to seriously challenge studies, especially if published by leaders in the field. The Discussion adequately states the major limitations of the Reprosci approach, which should be kept in mind by the reader to form its own opinion.

This study also allows investigators not familiar with the field to have a clearer understanding of the questions at stake and to derive a more coherent global picture that allows them to better frame their own scientific questions. Besides a thorough and up-to-date knowledge of the literature used to assess the consistency of the claims with our current knowledge, a merit of this study is the undertaking of independent experiments to address some puzzling findings and the evidence presented is often convincing, albeit one should keep in mind the inherent limitations as several parameters are difficult to control, especially in the field of infections, as underlined by the authors themselves. Importantly, some work of the lead author has also been re-evaluated (e.g., Supplements S2-S4). Thus, while utmost caution should be exerted, and often is, in challenging claims, even if the challenge eventually proves to be not grounded, it is valuable to point out potential controversial issues to the scientific community.

While this is not a point of this review, it should be acknowledged that the possibility to post comments on the ReproSci website will allow further readjustments by the community in the appreciation of the literature and also of the Reprosci assessments themselves and of its complementary additional experiments. As science is evolving continuously, this site allows the current state of knowledge to be updated as needed, not necessarily by the authors themselves.

Comments on revised version:

The major weaknesses identified in the original version of the manuscript have been adequately addressed by the authors. In a few cases, additional KO mutants have been generated and analyzed thus further strengthening the manuscript.

Reviewer #1 (Public review):

Summary:

The authors set out on the ambitious task of establishing the reproducibility of claims from the Drosophila immunity literature. Starting out from a corpus of 400 articles from 1959 and 2011, the authors sought to determine whether their claims were confirmed or contradicted by previous or subsequent publications. Additionally, they actively sought to replicate a subset of the claims for which no previous replications were available (although this set was not necessarily representative of the whole sample, as the authors focused on suspicious and/or easily testable claims). The focus of the article is on inferential reproducibility; thus, methods don't necessarily map exactly to the original ones.

The article is a large-scale analysis of the individual replication findings, which are presented in a companion article (Westlake et al. doi.org/10.1101/2025.07.07.663442). In their retrospective analysis, the authors find that 61% of the original claims were verified by the literature, 7.5% were partially verified, and only 6.8% was challenged, with 23.8% having no replication available. This is in stark contrast with the result of their prospective replications, in which only 16% of claims were successfully reproduced.

The authors proceed to investigate correlates of replicability, with the most consistent finding being that findings stemming from higher-ranked universities were more likely to be challenged - a finding that is observed in a multivariable model and multiple sensitivity analyses. Other trends observed in the initial descriptive analysis, such as less replicability in findings from "trophy" journals and duration of engagement with the field, seem less consistent and fail to reach significance in the multivariable model, and should thus be considered tentative.

Although this is a major contribution to the field, it is important to note that the high replication rates are mostly based on a retrospective survey of the literature, while prospective replication rates in the subset of articles directly replicated by the authors were much lower. Thus, the possibility of biases relating both to the field's decisions about what to replicate (and what to publish) and to the authors' criteria in evaluating claims should be considered when comparing these results with prospective replicability estimates obtained in other fields of science.

Strengths:

The work presents a large-scale, in-depth analysis of a particular field of science that includes authors with deep domain expertise of the field. This is a rare endeavour to establish the reproducibility of a particular subfield of science, and I'd argue that we need many more of these in different areas.

The project was built on a collaborative basis (https://ReproSci.epfl.ch/), using an online database (https://ReproSci.epfl.ch/), which was used to organize the annotations and comments of the community about the claims. The website remains online and can be a valuable resource to the Drosophila immunity community. A companion article details the individual replication findings (Westlake et al. doi.org/10.1101/2025.07.07.663442).

The revised version of the preprint includes a number of sensitivity analyses as supplementary material, which help to evaluate how the main findings change according to analytical decisions.

Main concerns:

(1) Although a number sensitivity analyses have now been conducted in order to address reviewer comments, these have been relegated to the supplementary material. Their existence is acknowledged in the multivariable model section, but the actual results of the main analysis are not mentioned at all in the main text and not taken into account in the discussion. Thus, the casual reader is not made aware of how particular results are dependent on analysis choices.<br /> Although the main finding of the correlation between replicability and university ranking holds over nearly all the analyses conducted, others are not as consistent. The association of irreplicability with trophy journals, for instance, is not statistically significant in the multivariate model (suggesting that it may have been partially due to confounding of journal tier with institutional ranking). It becomes even weaker when unchallenged claims are removed from the analysis (see point 2 below). Similarly, the association of irreplicability with "exploratory" career style is already weak in the univariate analysis and becomes even more marginal in the multivariable model. The effect of the lead author having been a first author in the field, on the other hand, is stronger than that of journal impact factor or that of the continuity/exploratory style (even though it fails to reach formal significance), but seems to receive less attention in the discussion.<br /> These differences in strength of evidence could be made more clear both in the abstract and in the discussion, which seem to prioritize some trends over others when discussing results. Once more, presenting a brief description of how results are affected by the sensitivity analyses in the results would be important to make these nuances clearer to the reader.

(2) I still do not understand the authors' choice of including unchallenged claims along with verified ones in the multivariate model used to investigate predictors of replicability. In particular, the justification given for this choice in the supplementary material (i.e. the fact that a finding remaining unchallenged is not a random event and might be influenced by variables such as journal tier and institutional ranking) actually seems like an additional reason for not including unchallenged claims along with verified ones: if findings from low-tier journals or less prestigious institutions are more likely to remain unchallenged, this could lead to a spurious claim of "less irreplicability" in these journals and institutions, which could be purely due to receiving less attention. Predictably, both associations are reduced when unchallenged claims are removed (although the reduction is much more marked in the journal case) in the sensitivity analysis (whose results, again, are only mentioned in the supplementary material).<br /> Moreover, multiple other statements by the authors themselves concerning unchallenged claims seem to contradict their own decision. In multiple points in the text, they reiterate that remaining unchallenged is associated with less replicability (as suggested by the fact that replicability rates were lower in prospective replications than in the literature, even for non-suspicious claims). The decision to include unchallenged claims along with verified ones thus seems unjustified - if anything, I'd have expected the opposite approach after reading the discussion. That said, I'd argue that the best decision would be to exclude them from the analysis, as done in Figure S4, and presenting this model as the main one.

Reviewer #1 (Public review):

This manuscript examines EEG activity during face-to-face Diapix conversations and asks whether neural activity preceding a participant's next speaking turn predicts the latency and duration of that turn. The authors report sustained ERP and alpha/beta effects, particularly associated with upcoming response duration, together with temporal-generalization decoding beginning approximately 1-1.3 s before speech onset. They interpret these results as evidence for two stages of conversational speech planning: an early process that activates and maintains the forthcoming response, and a later process related to commitment and motor execution. The naturalistic dyadic EEG setting, relatively large number of conversational turns, trial-level analyses, and convergence across ERP, oscillatory, and multivariate approaches are important strengths.

I nevertheless have substantial concerns about the interpretation. Most importantly, the EEG analyzed during this period is recorded while participants are processing their partner's speech. Therefore, neural activity necessarily includes auditory, linguistic, semantic, pragmatic, and turn-boundary processing, in addition to any potential response-planning activity. Because properties of the incoming utterance are themselves strongly related to what the listener subsequently says, predicting subsequent response duration or latency does not by itself isolate production planning. The authors acknowledge some of these limitations, but the current title, theoretical framing, Figure 8, and conclusions remain considerably stronger than the evidence allows. Indeed, the Discussion itself acknowledges that the signals cannot be determined to reflect linguistic content, general planning demands, or motor preparation.

I therefore think the study could become valuable, but substantial additional analyses and conceptual reframing are required.

Major concerns:

(1) The central problem is dissociating speech planning from listening/comprehension

This is my main concern with the manuscript and also with the claims in the Discussion. The authors repeatedly infer that because EEG during the partner's turn predicts the duration or latency of the participant's subsequent response, this activity reflects speech planning. For example, the manuscript states that examining the period before self-speech onset "isolat[es] preparatory neural activity before articulation." I do not think this inference is justified.

During precisely this interval, the participant is also listening to and comprehending the partner. The incoming utterance is not independent of the forthcoming response; it is what determines the response. A complex statement, several questions, a request for clarification, or an information-rich description will produce different auditory/linguistic/comprehension activity and may also systematically change the length and timing of the subsequent response. Consequently, both partner speech → listening/comprehension EEG and partner speech → subsequent response properties can generate an EEG-response relationship without requiring that the measured EEG activity itself reflect production planning.

The authors control partner-turn duration, which is useful, and they show that self-duration, self-latency, and partner duration are behaviorally related. However, partner duration is only a very coarse property of the input and cannot control for what participants are actually processing. The analysis should consider, at minimum, partner word count/speech rate, acoustic properties, information density or lexical/syntactic complexity, dialogue act, question versus statement, and preferably semantic/discourse content. For example, the number of questions or propositions in the partner's turn may directly determine both comprehension demands and how much the listener subsequently needs to say.

Given that transcripts and word-level timing are already available, the authors should be able to substantially improve this analysis. One particularly useful approach would be to construct an encoding model of the EEG driven by acoustic and linguistic features of the partner's speech and then test whether the residual neural activity continues to predict subsequent response properties. At minimum, richer input-related covariates are necessary.

Without such analyses, I think the main conclusion should be reframed from "neural signatures of speech planning" to something closer to "pre-response neural activity during conversational listening predicts properties of the subsequent turn." The latter is supported by the data; the former requires stronger dissociation.

(2) It is not clear that the analyzed period is actually a "listening interval".

Relatedly, the definition of the analyzed interval needs careful reconsideration. Epochs are aligned to the participant's own speech onset and extend back 2.2 s, whereas a turn transition is accepted whenever self-onset falls between −1 and +1 s relative to partner offset.

Therefore, the interval from −2 to 0 s relative to self-onset is not necessarily an interval during which the partner is continuously speaking. For positive response latencies, part of this interval contains silence following partner offset. If the preceding partner IPU is relatively short, earlier portions of the epoch could potentially contain a different conversational state altogether. Yet the manuscript describes the whole pre-onset period as being "while they are listening to their partner."

This matters particularly for the comparison between the early and late periods. Different response-latency conditions will necessarily place the partner offset at systematically different positions within an epoch aligned to self-onset. The authors already demonstrate this problem for the anterior latency ERP, where its inflection tracks the distribution of partner offsets. This is an important observation, but I do not think the problem is restricted to that single component.

The authors should quantify, separately for TW1 and TW2, how much time is occupied by: active partner speech, silence after partner offset, overlapping speech, and potentially other conversational states.

I would strongly recommend repeating the critical analyses for periods/trials during which the partner is actually speaking, and/or explicitly modeling partner-speech presence and the temporal distance to partner offset. Analyses aligned with both partner offset and self-onset would also help separate responses to the conversational boundary from activity specifically preceding self-production.

(3) The Early-versus-Late Planning hypotheses are not sufficiently differentiated

I was confused by the theoretical contrast (e.g., Lines 53-62). The Early Planning account is described as proposing that response preparation begins once sufficient information is available, whereas the Late Planning account explicitly allows "some aspects of conceptual preparation" during listening but proposes that full articulatory planning is delayed until near the turn boundary.

Under these definitions, both hypotheses allow for early planning. They differ mainly in the level of production planning that occurs early, that is, conceptual/content preparation versus articulatory/motor preparation. This is quite different from a simple early-versus-late timing hypothesis.

This is problematic because the current EEG measures do not determine whether the early activity reflects conceptual planning, lexical formulation, articulatory planning, comprehension, or general cognitive demands. Indeed, the authors explicitly acknowledge this later. Consequently, observing EEG-behavior relationships 1 s before speech cannot adjudicate between the two hypotheses as currently formulated.

The theoretical framework should therefore distinguish explicitly among at least: conceptual/message planning → linguistic formulation → articulatory/motor preparation → initiation.

If the "Late Planning" hypothesis specifically concerns late articulatory planning, then the authors need evidence that distinguishes articulatory planning from earlier conceptual processes. Otherwise, I would describe the findings more conservatively as showing early behavior-related neural activity followed by stronger onset-proximal sensorimotor activity, rather than claiming that Early and Late Planning accounts have been reconciled.

(4) Response duration is not equivalent to the amount or content of a response that has already been planned

The strongest empirical finding concerns upcoming speaking duration. I agree that this is interesting. However, throughout the Discussion, duration is gradually interpreted as the "extent," "scale," or even the amount of content already prepared. For example, the authors argue that longer responses involve maintaining a larger set of propositions, lexical items, or planned sequences. Figure 8 goes even further and explicitly contrasts "High Content" and "Low Content," although no measure of speech content has been analyzed.

I do not think response duration alone supports this inference.

A 2-s utterance is not necessarily twice as much planned content as a 1-s utterance. Duration can vary because of speech rate, hesitations, lexical retrieval, syntactic formulation, repetitions, interactive feedback, or decisions made after speech has already begun. An eventual IPU duration is therefore not necessarily specified before articulation.

This issue is especially important because the manuscript explicitly acknowledges that the analyses cannot establish whether the signals encode lexical or semantic content. It is then inconsistent to conclude later that early activity supports "what and how much to say."

Since transcripts are available, the authors could directly test several alternatives: word count, content-word count, number of propositions, speech rate, syntactic complexity, semantic similarity between partner and self turns, and possibly dialogue-act categories. If the early signal predicts eventual linguistic content/amount rather than merely duration, the claim of maintained response specification would become considerably stronger. If not, the interpretation should remain at the level of response duration.

(5) The ROI/time-window linear mixed-model (LMM) analysis appears circular

I have a methodological concern about the relationship between the cluster analyses and subsequent LMMs. The authors first identify electrodes and time ranges showing significant differences between long versus short responses or fast versus slow responses. They then use those same data-driven clusters to define anterior/posterior ROIs and TW1/TW2 and extract EEG values from the same trials, after which the extracted EEG measures are tested as predictors of the same behavioral variables.

This creates a potentially serious double-dipping/selection bias problem. The continuous LMM outcome is not statistically independent of the median-split outcome used to select the neural features. FDR correction at the LMM stage does not correct for this feature-selection procedure.

I think the confirmatory analyses need independent feature definition, for example, predefined electrodes/time windows from previous literature, split-half analysis, leave-one-participant-out feature selection, or another cross-validated procedure in which the data used to identify the ROI/window are independent from those used to estimate and test the EEG-behavior relationship.

This is particularly important because the LMM results are used as evidence that the effect survives behavioral covariates. That conclusion should come from statistically independent tests.

(6) Several statistical and validation issues need additional attention

There are several related concerns here. First, the trial-level LMMs include only (1 | participant), despite the fact that the observations come from dyadic interactions, multiple 4-min conversations, and temporally adjacent conversational turns. Participants within the same dyad do not generate independent observations because the speech of one participant directly determines the context for the other participant. I would expect the hierarchy to include at least a dyad/conversation block, and random slopes for critical within-participant predictors should be considered. Robustness to conversational autocorrelation should also be examined.

Second, the authors describe response duration as approximately log-normal, but the model description indicates only centering/scaling rather than transformation. The authors should report residual diagnostics and consider modeling log-duration or using an appropriate non-Gaussian mixed model.

Third, the decoding uses stratified 10-fold cross-validation, but it is unclear how conversational dependence is handled. Randomly assigning turns from the same 4-min conversation to training and testing sets may permit classifiers to exploit slow neural states, discourse context, or block-specific characteristics shared by temporally adjacent turns. A more convincing analysis would use blocked cross-validation, such as leave-one-conversation/run-out. The authors should also clarify whether decoding is performed independently within participants and whether median thresholds are participant-specific or global.

These analyses are particularly important because temporal generalisation establishes stable predictive information, but not the functional identity of that information. A stable partner-speech/context signal could also produce a broad temporal-generalisation pattern.

(7) ERP baseline correction and potential speech/muscle contamination require clarification

The ERP preprocessing raises another concern. ERPs were baseline corrected using the entire −2200 to +500 ms epoch. This interval includes the first 500 ms after self-speech onset, the period most vulnerable to speech-related muscular activity. Because the main grouping variable is upcoming response duration, post-onset activity may itself systematically differ between long and short responses. Subtracting a baseline that includes this activity could introduce condition-dependent shifts in the pre-speech ERP.

I therefore think the critical ERP results should be demonstrated without using post-speech activity in baseline estimation, for example, by using an appropriate pre-speech/regression-based baseline strategy, or by analyses demonstrating that the result is insensitive to baseline choice.

There is also an intriguing inconsistency concerning EMG. The participant section states that facial hair was an exclusion criterion to ensure electrode contact for EMG recordings, whereas the Limitations section suggests that combining EEG with EMG would be useful in future work. If EMG was in fact recorded, it should be described and, ideally, analyzed to establish when peripheral speech preparation begins and whether the onset-proximal alpha/beta results remain significant after controlling for muscle activity. This would be particularly valuable for the proposed late "motor commitment" interpretation.

Reviewer #1 (Public review):

In this manuscript, Yadav and coworkers investigate hydrophobicity governing membrane insertion of mitochondria-encoded polypeptides. The basis of their considerations is the question of why mitochondria maintain a co-translational insertion mechanism and what rules allow allotopic expression. The issue if mitochondrial-encoded proteins can be expressed in the cytoplasm and imported into mitochondria is a long-standing topic in the field with broad implications for the treatment of mitochondrial disorders. In the manuscript, Yadav et al. propose that aliphatic-to-threonine substitution (ATS) are a recurrent and convergent adaptation in the transmembrane helices (TMH) of the inner mitochondrial membrane (MIM) proteins, solving the conflict between hydrophobicity required for membrane insertion and the need for soluble cytosolic transit. The study combines structural comparative genomics, MD simulations, and cellular experiments.

This is a well-written and highly interesting study that provides a solid basis for considerations regarding mitochondrial protein insertion. I am sure that the study will represent an important asset for future studies on allotopic protein expression and potentially the development of genetic tools. The study provides solid evidence, from evolutionary correlation to experimental manipulation and molecular-level explanation. The study provides abundant and well-thought-out controls.

Specific points

(1) There are multiple comparisons throughout the manuscript, and not all of them appear to have been explicitly corrected. Numerous Wilcoxon tests, t-tests, and ANOVAs are reported (Figures 2, 3, 4), without a systematic correction for multiple testing or clear mention of FDR/Bonferroni corrections, except for the directional analysis of substitutions, for which the Benjamini-Hochberg procedure was applied. Given the large number of pairwise comparisons in Figures 3 A-C; and Figure 3 Supplement 1, Supplement 2, Supplement 4, and Supplement 5, with dozens of p-values per panel, it would be relevant to clarify whether a multiple-testing correction was also applied in these analyses. If not, the authors should explain the rationale for not applying one.

(2) The authors used experimental structures as one criterion but, in other cases, AlphaFold2 to compare evolutionarily distant pairs. Using non-experimental structures as a base for structural alignment among very divergent proteins is understandable but also prone to errors, especially for membrane proteins. It might wrongly identify which helices are considered "related". To address this, the authors need to clearly indicate which data are based on experimental or computational data - this is not always the case.

(3) The Kyte-Doolittle hydrophobicity scale is standard but relatively raw in comparison with scales based on experimental insertion energy (like Hessa et al., cited in the text or Bothelo et al.). It might be useful to explain why the authors preferred K-D over an experimental membrane insertion scale for the analysis. Particularly, since the Hessa et al. scale was later used in Figure 8G for the thermodynamic analysis.

(4) The phylogenetic tree of ATP6 (Figure 5A) presents low bootstrap values in some internal nodes (43, 40, 55) on which the interpretation of "independent events" of genetic transfer relies. This must be discussed, since a bootstrap of 40-50% provides not too much confidence in the deep topology of the tree, even though the point that the nuclear sequences don't form a monophyletic group with the mitochondrion seems robust (supported by distinct MTS in each clade).

(5) Definition of "core" vs "peripheric" in TMH (11 central positions) seems arbitrary; it would be worth clarifying why that cut was chosen and whether the results are robust when they vary.

(6) There is a notable gap in the literature when describing some of the findings in the Results and Discussion section:

Biophysics of threonine/serine in TMH:<br /> Senes et al., 2004, Dawson et al., 2002. The result described in Figure 8 (Threonine rotamers) is essentially a biophysical refinement of a body of work already established by the Engelman and DeGrado labs about how Ser-Thr, in comparison with other polar residues, promotes specifically the packing and stability of TMH through intra-inter helical hydrogen bonds, without compromising the membrane insertion. Chamberlain & Bowie, 2002 was included (C-H bonds), and Hessa et al. 2005 (energy of insertion), but no reference was included about why Ser/Thr are polar amino acids "tolerated" at the hydrophobic core of TMH, which is the state the authors describe.

In the argument about why TMH hydrophobicity matters for targeting (not only for membrane insertion), there is much more direct and recent mechanistic work that should be included: Botelho et al., 2011 established experimentally the hydrophobicity threshold for the "stop-transfer" pathway of TIM23 with quantitative data in an analogous way as reported in this work. Lee et al., 2020 and Yang et al., 2025 described structurally how hydrophobicity of the substrate modulates the Mgr2-Tim17 interaction to allow precursors to be embedded within the membrane.

It may be helpful to consider previous published work as an important precedent for the discussion of TMH hydrophobicity and TIM23 in allotopic expression. The final observations of incomplete mitochondrial localization despite reduced TMH hydrophobicity could also be discussed in light of previous published studies. These studies suggest that hydrophobicity is an important factor, but not the only determinant of efficient mitochondrial targeting. The role of TMH hydrophobicity in mitochondrial import had already been explored in this context. This would help clarify how the current findings build upon the existing literature.

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

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

Comments on revised version.

I thank the authors for addressing my concerns in the Introduction and Discussion of their paper. I don't require any further edits at this point.

Joint Public Review:

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

Summary:

This manuscript couples a 32-parameter model with simulation-based inference (SBI) to identify parameter changes that can compensate for three canonical hyperexcitability perturbations (interneuron loss, recurrent-excitatory sprouting, and intrinsic depolarisation). The study demonstrates a careful implementation of SBI and offers a practical ranking of "compensatory levers" that could, in principle, guide therapeutic strategies for epilepsy and related network disorders.

Strengths:

(1) By analysing three mechanistically distinct hyper-excitable regimes within the same modelling and inference framework, the work reveals how different perturbations require different compensatory interventions.

(2) The authors adopt posterior estimation to systematically rank the efficiency of different mechanisms in balancing hyperexcitability.

(3) Code and data are available.

Reviewer #1 (Public review):

Summary:

A fundamental technique for the identification of peptide-specific CD8 T cells is the use of fluorophore-conjugated and peptide loaded MHC tetramers. Classically, refolding of specific peptides with MHC monomers can be labour intensive, and not optimal for screening large numbers of different peptides. Hence, UV-exchanged tetramers have been developed to upscale this, however, still has some associated challenges such as UV-mediated damage to peptide complexes. Here, Pothast, C.R. et al demonstrate the efficacy of using temperature exchanged tetramers for the prevalent alleles HLA-A*03:01, A*11:01, B*07:02, and C*07:02. Building upon their previous work with HLA-A*02:01, H-2Kb, and HLA-E. They first demonstrate the complex stability of tetramers with different affinity peptides at high temperature, showing complex destabilisation can be rescued with higher affinity peptides. This is followed by an optimisation of peptide exchange temperatures, tailored for each allele. The authors then demonstrate successful binding to clonal T cell lines, and then a step further with viral peptides against PBMCs from individuals with confirmed infection history. For the latter they compare to conventional tetramers and demonstrate comparable signal.

Due to the prevalence of these 4 alleles, the ease-of-handling, and short time requirements, these tetramers are likely to show high utility.

Strengths:

The manuscript is well-written and results are solid, although more detail may add clarity to some of the results, in particular figure 1 and 2. Other than the points reported below, the study uses accurate controls to demonstrate the specificity of the tetramers, and the data is convincing.

Overall, their interpretation of the results is accurate and the discussion thorough, additional comments may be included to cover potential tetramer batch variability, and differences in the stability of different alleles. Specifically, whether certain alleles require higher affinity peptides to be stable, compared to others.

Comments on revised version.

The authors addressed the weaknesses highlighted in the previous version, specifically addressing that they do not conclude that thermal peptide exchange is not superior to existing technologies, but may be more feasible, as well as including a section on the stability of the different alleles and template peptides. The authors also updated the labelling and description of figures, making them much more interpretable. Addition of the LILRB1 reporter cell line to demonstrate successful peptide exchange and stability adds extra validity to the results.

Reviewer #1 (Public review):

This work evaluates the impact of reproductive history on growth, body weight and body composition in mammals. In mice, somatic growth is stimulated by the first pregnancy while the second pregnancy increases body weight mainly by increasing adiposity. To probe the role of pituitary growth hormone (GH), the key regulator of somatic growth in these processes, this was addressed by comparing the impact of reproduction on growth in normal ("wild type") and genetically GH-deficient females and by detailed characterization of the profile of fluctuations in circulating GH levels in both types of animals. Additional studies addressed the possible role of other endocrine pathways (ghrelin and estrogen) in the pregnancy-related growth. Surprisingly, reproduction-related growth was independent of GH, ghrelin and estrogen. To determine whether these results may apply ("translate") to human physiology, data on various parameters of somatic growth were collected from women with hereditary GH deficiency. The findings indicate that GH-independent stimulation of growth by reproductive events also occurs in women.

Use of multiple animal models, rigorous characterization of GH levels in normal and GH-deficient females, and inclusion of data derived from a unique and well-characterised population of people with hereditary isolated GH deficiency and no GH replacement therapy are important strengths of these elegant and innovative studies. The results address a broader and clinically significant issue of permanent changes in body size, composition and function that result from pregnancy and lactation. This work also provides important background for further studies aimed at the identification of the mechanism involved and the role of specific reproductive events in the regulation of growth.

Reviewer #1 (Public review):

Summary:

Bussey-Sutton, Gray, Wu et al. combine RelB proximity-labeling proteomics (BioID) with a custom, BioID-informed HIV-CRISPR screen to map the chromatin/transcriptional network that links non-canonical NF-κB (RelB/p52) activation by the SMAC mimetic AZD5582 to HIV-1 latency reversal. They identify a broad basal RelB interactome (chromatin remodelers, RNA-binding proteins, transcription machinery) that is partially reshaped, rather than replaced, by AZD5582 treatment. A targeted CRISPR screen against the BioID hit list then functionally separates these interactors into pro-reactivation factors (KAT7/HBO1, NSD2, SIN3A) and restrictive factors (p300, CHD4, USP7, UHRF1, DNMT1).

Pharmacological inhibition of the two acetyltransferase hits (KAT7i and p300i) validates opposing phenotypes predicted by the screen, and a comparative TNF-α (canonical NF-κB) screen argues that at least the p300 and, more selectively, the KAT7 pharmacology are biased toward the ncNF-κB axis. The dataset is a useful resource, and the BioID, CRISPR, pharmacology pipeline is a nice template for functionally triaging proximity-proteomics hits rather than treating them as a static interactome.

Strengths:

This study takes an integrative approach in which proximity proteomics is used to define candidate RelB-associated regulators, a purpose-built targeted CRISPR library tests these candidates directly for a functional phenotype, and pharmacological inhibition cross-validates the two acetyltransferase hits with an orthogonal, catalytic-activity-specific perturbation. This funneling from unbiased proteomic discovery to targeted functional testing to mechanistic pharmacology is an efficient and logical pipeline for converting a large interactome into a smaller set of high-confidence, functionally validated regulators.

The comparison of basal versus AZD5582-stimulated RelB interactomes is conceptually useful, as it shows that RelB engages a largely pre-existing chromatin and transcriptional regulatory scaffold upon ncNF-κB activation, rather than recruiting an entirely new complex. This is a finding with potential implications for non-canonical NF-κB signaling beyond the HIV latency context specifically.

The inclusion of a parallel HIV-CRISPR screen using TNF-α to activate canonical NF-κB signaling is a valuable control, allowing the authors to distinguish regulators that are broadly required for NF-κB-dependent HIV expression from those more selectively linked to AZD5582-driven ncNF-κB signaling. This comparison strengthens the authors' claims of pathway specificity for hits such as KAT7 and p300.

Finally, pharmacological validation of the top acetyltransferase hits was performed across two independent latency models (J-Lat 10.6 and N6), which helps address, at least in part, the concern that phenotypes are specific to a single clonal integration site. Together with the deposited proteomics and screen datasets, this provides a genuinely useful resource for the field.

Weaknesses:

(1) BioID inherently reports both direct and indirect (proximal) interactions, and no individual hits are validated by an orthogonal method (e.g., co-IP, PLA). As a transcription factor, RelB would be expected to reside near transcriptional/chromatin machinery, so this enrichment alone isn't surprising, making it hard to distinguish functionally relevant RelB complexes from bystander proteins in the same active chromatin neighborhood. At least a subset of top hits should be validated independently.

(2) BioID interactome was defined in a single clonal cell line, limiting generalizability across latent cell types. The RelB BioID proteomics, which forms the entire basis for the downstream targeted CRISPR library generation, was performed in one engineered Jurkat N6 clone. Both RelA/RelB pathway dependency and the baseline expression of the chromatin regulators identified as RelB interactors (e.g., DNMT1, UHRF1, SWI/SNF subunits, NSD2) can vary considerably across cell lines, latency clones, and primary CD4+ T cells. Since the CRISPR screen, and thus all functional hits in the paper, is entirely constrained by this single-cell-line interactome, any RelB interactor that is absent or differently regulated elsewhere would never have been tested, regardless of its true biological importance. To support claims of a broadly relevant RelB/ncNF-κB regulatory network, the authors should at least partially validate the basal and AZD5582-induced interactome (e.g., by co-IP/western for key hits) in a second cell line or primary CD4+ T cells, to distinguish clone-specific interactions from generalizable ones.

(3) Is KAT7/HBO1's contribution to reactivation a direct interaction/synergy with AZD5582, or an independent parallel requirement? The data show that KAT7/HBO1 knockout and catalytic inhibition (WM-3835) both reduce AZD5582-induced reactivation, and that KAT7 was detected as AZD5582-enriched in the RelB BioID. However, it remains unclear from the current data whether KAT7/HBO1 acts as a direct downstream effector in the ncNF-κB/RelB signaling axis (i.e., is recruited by or acts together with RelB/p52 at the LTR specifically upon AZD5582 stimulation), or whether it represents a more general/parallel chromatin requirement for HIV reactivation that is simply necessary regardless of the activating stimulus (and happens to also associate with RelB). Distinguishing these possibilities matters for interpretation: the former would support a model in which AZD5582 and KAT7 act synergistically through the same pathway (i.e., acetylation is mechanistically coupled to ncNF-κB activation), whereas the latter would suggest KAT7-mediated acetylation and RelB/p52 signaling are two independent, simultaneously required mechanisms that converge on the same locus without being mechanistically linked. The comparative TNF-α data (Figure 3C), where the genetic screen shows a shared dependency but the pharmacological inhibitor does not phenocopy this for TNF-α, adds to this ambiguity rather than resolving it. Clarifying whether KAT7/HBO1 functions upstream, downstream, or in parallel with RelB/p52 (e.g., via RelB ChIP after KAT7 knockdown, or KAT7 recruitment kinetics relative to RelB/p52 at the LTR) would strengthen the mechanistic claims in this section.

(4) A major limitation of the study is that screen results were validated in only two cell line models, and neither is a primary cell system. Different latency models are known to have distinct dominant transcriptional blocks, not just different genetic backgrounds. J-Lat clones, U1, ACH2, and other transformed lines differ substantially in why the provirus is silent; some are more Tat/P-TEFb-limited, some more chromatin/Polycomb-restricted, some more dependent on transcription factor availability (NF-κB, NFAT, AP-1). A regulator that is rate-limiting in J-Lat 10.6 specifically (a single integration site, clonally selected for a particular chromatin environment around the LTR) may therefore be irrelevant, or could even act in the opposite direction, in a model where the block is elsewhere.

(5) HIV latency and LRA responsiveness are well known to be strongly integration-site and clone-dependent. Pharmacological validation of CRISPR screen hits extends to N6, but the primary screen hits themselves are not confirmed in a second genetic background. This is an important caveat that should be discussed explicitly, and ideally at least the top hits (KAT7, NSD2, SIN3A, p300, CHD4) should be individually knocked out (not just inhibited) in a second model to confirm the genetic phenotype generalizability, not just the pharmacology.

(6) More importantly, no validation was performed in primary CD4+ T cells or ex vivo resting CD4+ T cells from people with HIV, which remain the field's benchmark for confirming that a candidate regulator is relevant to authentic latency rather than to a transformed cell line. Basal chromatin state, NF-κB pathway, and expression of the chromatin regulators identified here (e.g., DNMT1, UHRF1, SWI/SNF subunits) can differ substantially between transformed lines and primary resting T cells. Given this, the current claims of a broadly applicable "chromatin regulator" network should be tempered, and at least the top hits (e.g., KAT7/HBO1, NSD2, SIN3A, p300) should ideally be tested in a primary cell model before being generalized as regulators of HIV latency and reactivation more broadly.

(7) The finding that p300 restricts AZD5582-driven reactivation is framed as consistent with Horvath & Sadowski (ref 36), but p300/CBP is also a well-established Tat/LTR coactivator in many contexts (Kiernan et al., Marzio et al). The Discussion would benefit from a slightly more developed treatment of how these findings can be reconciled rather than citing a single concordant paper.

Reviewer #1 (Public review):

Summary:

Involved in various cellular pathways and processes, Ser/Thr kinase CK1δ is thought to be constitutively active and its tail autophosphorylation is suggested as a putative inhibitory mechanism of CK1δ kinase activity. Here, the authors investigate CK1δ's phosphorylation status, in relation to its location and dynamics throughout the cell cycle. Immunofluorescence and biochemistry studies showed that the subcellular distribution of CK1δ is dynamic and in equilibrium between centrosomal and nuclear pools. The authors argue that CK1δ phosphorylation protects it from degradation. Finally, the authors show differences in CK1δ phosphorylation status and location throughout the cell cycle. Combining their findings with the existing literature, they propose a model of CK1δ phosphorylation status, location and dynamics throughout the cell cycle.

Comments on latest version:

The authors have unfortunately taken a very defensive mode There are two themes that authors resort to: 1) We have published previously with some reagents - therefore these are well-established and we do not need to include controls anymore; 2) Independent biological replicates and statistics are only appropriate in some places, again because certain observations have been previously published (by the same authors) and well-established. In my opinion, this is not how rigorous research should be done. Specially with IF, it is essential in every experiment to have robust negative controls.

Reviewer #1 (Public review):

The study addresses the organisation of synaptic connections from medial to lateral entorhinal cortex. Classic anatomical work has suggested these connections exist but very little is known about their identity or functional impact. The manuscript argues that these projections are mediated by glutamatergic neurons, providing excitatory input from MEC to all layers of LEC, and by SST+ve interneurons sending inhibitory projections to L1 of LEC. This appears the most likely interpretation of the data. Potential concerns about confounds due to spread of virus/tracer from the injection site are addressed in the supplemental figures. My view is that the weight of evidence favours the authors' interpretation although the evidence isn't quite compelling.

Knowing the configuration of projections from MEC to LEC is important for thinking about circuit mechanisms for spatial cognition and episodic memory. This study adds to an emerging view that MEC and LEC can interact directly, indicating that the cell-type level organisation of these interactions is asymmetric and identifying an intriguing long range inhibitory pathway.

Reviewer #1 (Public review):

The authors describe a learning algorithm that is meant to deal with the problem of inference in large, complex environments. They argue that simpler but ensemble learning systems with heterogeneous learning rates often perform better than more complex approaches. They also relate the ideas of their model to a circuit implementation in the mushroom body, an associative learning area in insects.

I found the argument about the value of sublearners remaining simple to be thoughtful and intriguing. I also appreciated the connection to biology and, although there remain details to be worked out, it seems that the proposed approach has what I'd call a "biologically plausible" instantiation.

Comments on the major claims:

The paper claims that algorithms that learn stochasticity and volatility "necessarily result in worse short-term performance than Hetlearn." The results with Autocovariance Least Squares and the model of Piray and Daw are consistent with this statement, but the authors seem to be making a more generic claim. Is there a rigorous justification of this? In particular, I found the section "Competing sublearners should stay simple" to straddle a line between opinion and fact, and I wasn't sure where it intended to be regarding that line.

Relatedly, regarding the statement just before that section: "The exponential convergence of Hetlearn weightings stands in contrast to the slow convergence of stochasticity/volatility estimates (Figures 2A and C), which result in poor initial performance of the Kalman learner." Is the claim here that the Kalman learner doesn't converge exponentially, or that it converges more slowly?

The paper would benefit from a comparison to other models of multiple learning systems with different timescales. The classic one would be the complementary learning systems ideas about hippocampus and neocortex (McClelland, McNaughten, O'Reilly 1995), and the many subsequent follow-ups. Two other relevant ones to consider are Roxin & Fusi 2013 and Lindsey & Litwin-Kumar 2024, which also consider multiple memory systems with different plasticity rates.

Comments on clarity:

(1) Page 2: There could be some more unpacking of the relationship between x and z in equations 1a, 1b. If z_t are time-varying, shouldn't theta, if it represents what is learned about "large-world factors," also depend on time?

The description of second-order conditioning on page 6 is confusing. Second-order conditioning tests whether S2 acquires a positive predicted value after pairing with S1, which had previously been paired with reward. The text makes it seem like the goal of second-order conditioning is to learn S2->S1->no reward.

(2) Page 6: "Representations decay on a slower timescale than stimulus presentation. Hence, the representation x2 after experiencing S2 → S1 holds traces of the S2 representation." I couldn't understand this. Maybe an equation would help?

(3) Page 7: The phrase "unconditioned stimulus" is introduced without being described. Is this a reward or punishment? What does it have to do with valence lower-case v, or value upper-case V? The authors seem to mix notations from different subfields, leading to a rather confusing description of the model.

Comments on relationship to biology:

(1) Page 6: It is assumed that Kenyon cells interact recurrently through plastic weights. This is an unconventional assumption for mushroom body models, and it is made without much discussion. The authors cite papers that argue for changes in the calyx during learning (although these effects are generally much weaker than the well-documented plasticity onto MBONs). However, KC-to-KC interactions are largely in the lobes, not the calyx. The authors should provide more discussion of this assumption. What happens if the recurrence is weak or absent? A relevant reference to consider is Manoim et al. Current Biology 2022, which shows that KC-to-KC interactions are inhibitory.

The model seems to imply that each MBON compartment encodes only one memory, or did I misunderstand? Is this necessary? Typically, it is thought that because of the sparse, decorrelated representations in the KCs, an individual MBON could store multiple associations without too much interference.

Reviewer #2 (Public review):

Summary:

The study by Millard et al. investigates the effects of nicotine on peak alpha frequency and pain using a highly elaborate experimental design. According to the statistical analysis, the authors found a small covariate-corrected effect for prolonged heat pain and a small effect on global peak alpha frequency in response to nicotine treatment. However, the effect on heat pain was not found for pressure pain, was not mediated by peak alpha frequency, and appears mainly based on a worsening in the placebo condition rather than a clear reduction of pain after nicotine.

Strengths:

I very much like the study design and that the authors followed their research line by aiming to provide a complete picture of the pain-related cortical impact of peak alpha frequency. This is important work, even in the absence of clear statistical or mechanistic support for the main hypothesis. I also appreciate the preregistration of the study, the well-written and balanced introduction, and the additional analyses added during revision.

Weaknesses:

The weakness of the study revolves around two main aspects:

(1) Source separation would still have been more appropriate than electrode regions or global peak alpha frequency to extract the alpha signal. The added ICA analysis is appreciated, but in my view, it does not fully solve the problem. Different alpha sources, such as mu rhythm, occipital alpha, and lateralised alpha activity, are still not clearly disentangled. The main peak alpha frequency effect remains a small global, wide-band, sensor-space effect rather than a clearly source-specific sensorimotor effect.

(2) I still think the choice of nicotine is a major weakness of the study. The rationale for using nicotine as an intervention rests partly on previous reports of nicotine effects on experimental pain, but the most relevant cited meta-analysis already suggested that these effects are small and may be affected by publication bias. It is therefore not a clean way to test whether peak alpha frequency has a causal role in pain. The heat-pain result is also difficult to interpret as analgesia. Statistically, the placebo-controlled contrast may be significant, but in practice, the nicotine condition changed very little, and the effect seems mainly driven by worsening in the placebo group. In a real intervention, one gives the drug, not the difference between drug and placebo.

Impact:

The impact of the study could be to show what did not work to answer the authors' research question. The study is valuable because it provides a careful and largely negative mechanistic test: nicotine produced at most small effects, peak alpha frequency did not mediate pain, and pressure pain was not affected. The study would have more impact with a more direct intervention model and an analysis strategy that more clearly untangles the different alpha sources.

Reviewer #1 (Public review):

In the article, the authors set out to characterize in adipocytes an enhancer, ENH5, of the gene EPAS1, a gene that was found to show strong selection in Tibetan populations. They investigate whether this enhancer contributes to adipocyte response to environmental stress. The authors show that ENH5 is active in preadipocytes and that the Tibetan high-altitude allele confers reduced activity. They then use a mouse ENH5 knockout model to show a hypoxia/thermogenesis responsive phenotype of stronger transcriptional downregulation of aerobic respiration, electron transport chain, and adipogenesis pathways. The authors interpret these findings as evidence that ENH5 conditionally regulates adipocyte energetics and thermogenic response, potentially favoring energy conservation in Tibetans exposed to the demands of high-altitude hypoxia and cold. Overall, the paper presents an interesting potential connection between EPAS1-mediated high-altitude tolerance and energy metabolism; however, more work needs to be done to establish this connection.

Major comments:

(1) The authors use mouse ENH5 enhancer knockout (ENH5-KO) as the model of the Tibetan EPAS1 locus because the high-altitude allele of human ENH5 has lower transcriptional activity than the low-altitude allele (Figure 1A) and mouse ENH5 (musENH5) has enhancer activity (Figure 1D) in mouse preadipocytes. However, it is an overstatement to claim the functional role of Tibetan ENH5 haplotype only based on these data because musENH5 is neither identical to human ENH5 nor the murine high-altitude haplotype. The title should also be revised to better reflect the function of ENH5, like "An EPAS1 enhancer mediates hypoxic and cold response in mouse adipocytes". The authors should consider in some way to actually show that the Tibetan haplotype in ENH5-KO leads to expression changes. This could be done by inserting the haplotype into preadipocytes via CRISPR (realize this is a tough one) or if they have available cells from Tibetans or some eQTL or other similar datasets. The more closely they can connect this haplotype to EPAS1 expression, the more beneficial it would be for the article. As it stands, they currently have episomal luciferase assays showing reduction of enhancer activity in mouse preadipocytes of a human allele and a complete knockout of the mouse enhancer that doesn't recapitulate the Tibetan haplotype. A bit more work is needed to connect all of these to the Tibetan adaptation. As it stands now, this is all very circumstantial.

(2) In Figure 2A, the body weight of ENH5-KO normal diet is significantly lower until four weeks in male, and until 11 weeks and 18 and 19 weeks in female than that of WT. These are slight but significant differences between ENH5-KO and WT; therefore, the authors should describe and discuss this and how it could affect their results.

(3) For the mouse work, it is not clear why the authors did not do cold-exposure or some type of hypoxia experiment for the mice themselves. This will be helpful to support their claim, and if not done, or done without significant differences in the results, the authors should add and mention this. The RNA-seq work, while substantial, again provides circumstantial support.

(4) The authors used CL316243 as a β3-AR selective agonist to mimic thermogenesis in vitro. In humans, it is not β3-AR but β2-AR that mainly drives thermogenesis (Blondin et al., Cell Metabolism, 32, 287-300. e7). Therefore, the authors should describe the limitation due to the difference in mechanisms of action of thermogenesis between humans and mice, as they use the mouse cells as a human model.

(5) The authors note in the discussion that Figure 3's CL316243 stimulation intended to simulate a thermogenic reaction to cold temperatures also generated a change in OXPHOS pathways associated with hypoxia, thus making it difficult to separate the contribution of β3-adrenergic/thermogenic effect from an indirect local hypoxia response. The authors could further interrogate this effect by measuring canonical hypoxia-responsive genes, oxygen consumption, or performing an in vivo cold challenge.

(6) Figure 4: The authors mention that reduced aerobic respiration pathways are evidence for reduced thermogenesis, but it does not directly demonstrate altered thermogenesis correlates. They do not measure heat synthesis, oxygen consumption/respiration, uncoupled respiration, UCP1 protein levels or activity, mitochondrial changes, etc. Their evidence for changed thermogenesis stems from transcriptional changes in energy consumption pathways shared with hypoxia changes. They should tone down their findings.

(7) In the Discussion, the authors should interpret and discuss their data carefully. For example, in the GSEA analysis, the authors identified enriched gene sets in ENH5-KO. Therefore, the authors should discuss which genes might contribute to each pathway, since some genes show large logFC changes. In the current discussion, there is little mention of their results, and it mostly focuses on prospects.

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors investigated factors required for neural progenitors to exit cell cycle before the adult stage. They first show that Kr is expressed in pupal stage MBNBs, and depletion of Kr from pupal stage NBs leads to retention of MBNBs into the adult stage. Then they demonstrate that these retained NBs maintain the expression of Imp, and co-depletion of Imp abolishes the extended neurogenesis. Further, they show that co-depletion of kr-h1 significantly reduces the retained MBNBs caused by loss of kr, suggesting antagonistic genetic interactions between these two. In addition, they demonstrate that over-expressing Kr-h1 leads to the striking phenotype of tumor-like neuroblast overgrowth in adult brains. In the revised manuscript, they provide evidence suggesting that Kr does not regulate Kr-h1 expression, but rather Kr and Kr-h1 may regulate the late temporal gene E93 expression in parallel.

Strengths:

(1) The authors leveraged well-controlled powerful genetic tools (including temporal control of RNAi knock down using the Gal80ts system), and provided strong evidence that Kr is required for the Imp to Syp transition and to promote the end of neurogenesis through E93 in mushroom body neuroblasts. Similarly, the experimental result of co-depleting Kr-h1 and Kr, and the striking phenotype upon Kr-h1 mis-expression, support the antagonistic roles played by Kr-h1 and Kr in this process.

(2) The sample sizes, quantification methods and p-values are well documented for all experiments. In most parts, the data presented strongly support their conclusions.

(3) Identification of two transcription factors with opposite roles in controlling cell cycle exit, and their possible interactions with the Imp/Syp axis, is highly significant for the study on how the proliferation of neural progenitors is regulated and limited before the adult stage.

Weaknesses:

(1) In the revised manuscript, Kr immunostaining was done in KrIf-1 mutant brains using tyramide signal amplification (TSA) to enhance the weak endogenous Kr signal, and they conclude that Kr is ectopically detected in MBNBs and their progeny. However, a wildtype control with TSA amplified Kr immunostaining was not provided, so it is not known whether the elevated signal comes from TSA amplification or the mutant condition. If Kr is indeed mis-expressed in MBNBs in the KrIf-1 mutant, the authors should provide a hypothesis to explain why both loss of Kr and mis-expression of Kr in MBNBs lead to the same NB retention phenotype.

Reviewer #2 (Public review):

Summary:

This paper shows that imiquimod, a compound often used to induce a psoriasis-like skin inflammation in mice, has a TLR7-independent effects that induce the unfolded protein response and amplify cytokine expression in dendritic cells. Although these effects of imiquimod have been described in the literature before, this study provides more detailed evidence and different contexts to this observation. These findings add to existing literature that imiquimod has a pleotropic mechanism of action involving changes in mitochondrial functions and cellular stress responses. Specifically, the authors show that imiquimod can induce calcium signaling in immune cells and potentiate two branches of the unfolded protein response in a TLR7-independent and MyD88-independent manner. They also show that some of these effects might be partially mediated by direct binding of imiquimod to Gelsolin. These findings expand our understanding of imiquimod-mediated inflammation and are useful for the field of experimental skin immunology and mouse models of psoriasis. However, molecular and cellular mechanisms connecting Gelsolin to the unfolded protein response and skin inflammation presented in this paper requires further investigation in the context of TLR-mediated inflammation.

Strengths:

(1) TLR7-independent effects of imiquimod to the expression of genes and proteins involved into the unfolded protein response are well demonstrated.

(2) Gelsolin is identified as a new imiquimod-binding protein in mouse cells.

Weaknesses:

(1) Effects of imiquimod on mitochondrial Ca signaling are not clear form the presented data.

(2) The mechanism of action connecting imiquimod to Gelsolin on the unfolded protein response and cytokine production remains not fully explained.

(3) It remains unclear if Gelsolin contributes to regulating TLR7 (or other types of TLR-mediated) inflammation in vivo.

Reviewer #1 (Public review):

Summary:

Garcia-Alcala, Kratz and Cluzel investigate to what extent our understanding of bacterial physiology in bulk experiments can be applied to single-cell observations. They find that intrinsic noise may be powerful enough to even inverse the trends found in the bulk. The authors hypothesize that asymmetric distribution of ribosomes to daughter cells during the cell division plays the dominant role in the intrinsic noise and is able to generate the observed phenomenon. They do not show it directly, but the data and its agreement with the model suffice to support this claim.

Strengths:

The experimental part is convincing: the positive correlation between the elongation rate and promoter activity of unnecessary protein is clear, as well as the negative correlation between the mean values while changing the promoter strength. This was demonstrated in both rich and poor media. The causality between the growth rate and the promoter activity was shown using the negative lag time of the cross-correlation function. A simple, reasonable model accounts well for the data. This paper demonstrates an interesting phenomenon and provides a plausible theory for it, advancing our understanding of bacterial physiology on the single-cell level.

Weaknesses:

(1) Mean-reversion timescales were assumed to be longer than the simulation time and much longer than the cell cycle time. It is not clear whether the results robust in case mean-reversion timescales become of the order of cell cycle or smaller. If not, is there an argument for such practically infinite reversion timescales?

(2) It is not easy to understand the simulation part unless one reads Ref. [14]. Is k(t) assumed to follow Eq. (1) from ref. [14]? Is this crucial that the ribosome noise appears only at the division? The ribosome noise strength \sigma_R=0.06 - is it lower or higher than the naively expected binomial division?<br /> Also, more intuitive explanation of the Simpson paradox would help the reader.

(3) It would be useful for the reader to see the raw data and not only the filtered one to appreciate the measurement noise level.

(4) Negative lag time of the cross-correlation function is visible, but consider adding statistical test for it.

(5) Can you make similar cross-correlation plots using the model? Can you infer using it whether the data agrees better with the assumption that ribosomes noise appear only at division or continuous fluctuations during the cell cycle?

Comments on revised version:

The authors addressed the five comments listed above.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. We appreciate the care with which the authors have addressed the remaining concerns. The additional analyses and the revisions to the framing and interpretation have strengthened the manuscript and clarified several of the issues raised during the previous round of review. In particular, the added analyses in Figure 4 and the more precise treatment of repeated retrieval, learned threat value, and the relationship between neural activity and freezing have improved the paper substantially.]

Summary:

The authors combine discriminative auditory fear conditioning with longitudinal in vivo calcium imaging to ask how prelimbic (PL) representations of learned and generalized threat evolve across recent and remote memory time points. Using two different CS+ frequencies and a no-shock control group, they report that PL population activity tracks graded behavioral generalization, that population similarity is highest for tones eliciting strong threat responding, and that distinct subnetworks can be identified that appear to encode tone-specific sensory features versus learned threat-related response structure.

To my knowledge, this may be the first study to comprehensively examine neural encoding of fear generalization in prelimbic cortex (PL). The manuscript is ambitious and technically interesting, and several aspects are potentially important. In particular, the suggestion that neurons showing graded, learning-related response patterns become selectively stabilized over time is intriguing. The inclusion of two CS+ training conditions and a no-shock control also strengthens the case that at least some of the reported effects are related to associative learning rather than simple sensory differences.

Reviewer #2 (Public review):

Summary:

In this study, the authors developed a human forebrain organoid model that incorporates both iPSC-derived microglia and CD8⁺ T cells, allowing them to recreate and investigate multicellular aspects of AD pathology in a human-relevant system.

Their findings show that microglia help clear amyloid-β deposits, but they also promote inflammatory responses. Activated microglia recruit CD8⁺ T cells by releasing the chemokines CCL4, CCL5, and CXCL10, which signal through the receptors CCR1/CCR5 and CXCR3. Pharmacological inhibition of CCR5 or CXCR3 prevents T-cell recruitment and alters autophagy pathways in a microglia-dependent manner.

Strengths:

The manuscript has several strengths, including its innovative multicellular organoid model, the combination of complementary experimental approaches, and the identification of potentially relevant immune signaling pathways.

Comment on the revised version.

Overall, the revised manuscript is considerably improved, and the major conceptual concerns raised in the initial review have been adequately addressed.

Reviewer #1 (Public review):

Ma et al. use human-chimpanzee tetraploid cells, across different cell types, to identify the genetic causes and then transcriptomic consequences of divergence in DNA methylation. They conclude that the evolution of DNA methylation is driven primarily by cis-regulatory changes, and that the evolution of CpG sites contributes to cis-regulation while transcription factor expression underlies some trans changes. They then argue that divergence in DNA methylation is associated with changes in gene expression and may contribute to human phenotypes.

The tetraploid model is able to provide compelling evidence that most regulatory evolution occurs due to cis-regulatory changes, and that sites that have diverged in DNA methylation level cluster together into DMRs which share similar divergence patterns and genetic architecture. This stands in intriguing contrast to trans-mechanisms which explain most variation within modern human populations. The authors proceed to show that trans-effects can be explained, in part, by nearby TF binding motifs and many cis-regulatory changes are explained by CpG-disrupting variants. While these mechanisms clearly contribution to divergence in DNA methylation, the degree to which they explain cis- and trans-regulatory divergence would be valuable.

Next, the authors seek to show that differences in DNA methylation are functionally relevant. Consistent with previous results, they show that differences in DNA methylation are (weakly) associated with changes in gene expression. They hypothesize that genes with concordant regulatory should exhibit great methylation-expression coupling than other genes and show that cis-expression/cis-methylation pairs are more strongly correlated than trans/trans pairs. I think that looking at cis/trans or trans/cis changes would also be useful. Another limitation is that this analysis is limited to promoter regions. It is not clear how many divergent DMRs that includes and how many of those genes have differences in expression. The key question is whether differences in DNA methylation are functionally important, and the answer provided by these analyses is "sometimes".

Finally, the authors make a case for lineage-specific selection on DNA methylation that is connected to human traits. Using a sign-test, they identify sets of genes which have likely experienced selection in humans and may underlie human phenotypes.

In conclusion, I think this study provides a valuable resource for differences in DNA methylation between humans and chimpanzees across tissues and provides important insight into the relative abundance of cis and trans regulatory divergence. Additional research is necessary to investigate the underlying regulatory mechanisms and more care needs to be taken in exploring the functional consequences.

Reviewer #1 (Public review):

Summary

This computational modelling study investigates the functional role of metaplasticity in a calcium-dependent synaptic plasticity rule, using a biophysically detailed model of a striatal projection neuron. The learning rule is deliberately simple: local calcium signals derived from different sources regulate LTP and LTD through separate plasticity thresholds, while dopamine provides a reward-related signal that determines the direction of synaptic updates. The author uses linear and nonlinear feature-binding problems (FBP and NFBP) as learning tasks to illustrate the mechanics of competing LTP and LTD processes in this rule. The central aim is thus to use these classification tasks to understand what metaplasticity in the two calcium thresholds contributes to learning.

The study identifies complementary roles for metaplasticity in the LTP and LTD thresholds, enabling synapses exposed to competing plasticity processes to converge toward a stable outcome. In reversal-learning tasks, relaxing the conditions for metaplasticity allows previously stabilized synaptic states to become flexible again and permits relearning. Finally, the manuscript investigates whether two separate calcium thresholds are themselves necessary. While a modified rule with a single adaptive calcium threshold can solve the same tasks comparably well, two thresholds allow separate control over synaptic strengthening and weakening.

Strengths

A major strength of the study is the simplicity of the learning rule, which makes it possible to dissect the roles of individual components while retaining a connection to experimentally motivated mechanisms of cortico-striatal plasticity. The use of shared features in the FBP and NFBP is useful for exposing the interaction between competing LTP and LTD processes and for showing how adaptation of one plasticity threshold can indirectly permit expression of the opposite form of plasticity.

The manuscript also provides a much more systematic analysis of the rule than the original version. In particular, the expanded parameter analyses explore both successful and failing regimes for the learning and metaplasticity rates, while the scan over the maximum synaptic weight provides a clear mechanistic motivation for the additional upper LTP threshold.

Importantly, the single-threshold simulations directly address whether two calcium thresholds are computationally necessary. These additional simulations clarify that the principal advantage of two thresholds is not that they uniquely enable nonlinear learning, but that they permit independent regulation of strengthening and weakening. This considerably strengthens the conceptual conclusions of the study.

Weaknesses

The main limitations concern the scope and biological generalizability of the results. The simulations in this paper are based on a particular detailed SPN model and depend on several specific biological and modelling assumptions. Most notably, solving the nonlinear task requires appropriately clustered excitatory inputs, but the learning rule itself does not provide a mechanism for generating these clusters. The manuscript now discusses this limitation explicitly and appropriately identifies structural plasticity as an important direction for future work.

A second important assumption is the upper calcium threshold that prevents LTP once sufficiently strong supralinear responses are reached. This mechanism plays an important functional role in the model but has not been experimentally established for cortico-striatal synapses. The manuscript appropriately identifies this as a major assumption and discusses potential molecular mechanisms that could implement such an effect.

Overall assessment

The revised manuscript is substantially stronger. The conclusions are carefully matched to what is demonstrated by the simulations, and several important alternative explanations and model configurations are tested directly. In particular, the revised framing provides a more specific mechanistic account of what metaplasticity in two separate thresholds contributes within the proposed rule. The work therefore provides a valuable contribution to computational studies of synaptic plasticity and metaplasticity, with convincing evidence supporting its principal conclusions.

Reviewer #1 (Public review):

Summary:

In this study, the authors elegantly combined latent variable models (i.e., HMM, GPFA and dynamical system models) with a calcium imaging observation model (i.e., latent Poisson spiking and autoregressive calcium dynamics (AR)).

Strengths:

Integrating a calcium observation model into existing latent variable models improves significantly the inference of latent neural states compared to existing approaches such as spike deconvolution or Gaussian assumptions.

The authors also provide an open-source access to their method for direct application to calcium imaging data analysis.

Weaknesses:

As acknowledged by the authors, their method is dependent on the quality of calcium traces extraction from fluorescence videos. It should be noted that this limitation applies to alternative strategies.

While the contribution of this study should prove useful for researchers using calcium imaging, the novelty is limited, as it consists of an integration of the calcium imaging model from Ganmor et al. 2016 with existing LVM frameworks.

Comments on revised version.

The authors addressed my comments and I have no further concerns.

Reviewer #1 (Public review):

In this work, Frey and colleagues have carried out a very large study of α-synuclein polymorphism as a function of aggregation conditions and sample preparation. They provide valuable insight into the many critical factors affecting α-synuclein polymorphism, thereby illuminating the need for detailed reporting in the literature as well as both rigorous and detail-oriented protocols when working with this protein. Indeed, their observations are in line with the difficulties of reproducing structural outcomes across different laboratories and experiments. The authors must be complemented on their openness about the difficulties experienced and the thoroughness of their work. Efforts like these are going to be crucial to achieve an understanding of the unparalleled structural plasticity of α-synuclein amyloid fibrils. It is particularly notable that the authors have managed to optimize protocols to form single-polymorph aggregation reactions with high reproducibility.

In this work, the authors focus on the influence of α-synuclein purity in aggregation reactions. They find that using reverse-phase HPLC to purify the protein significantly alters the aggregation behaviour. It is interesting, and rather uncommon in the field, to use reverse-phase HPLC as a final purification step, rather than SEC, which is commonly used in many laboratories. It would be useful to compare this new protocol even more directly and extensively with the commonly used SEC protocol. When mentioning their previously published work, it should be mentioned explicitly how the protein was purified in these previous studies.

On the point of protein purification, the authors lyophilize their protein prior to storage. In their work, they also find that pre-aggregation oligomer formation alters the aggregation pathway of α-synuclein. While they demonstrate that this can be solved by appropriate filtration, it should be discussed why the lyphilizaiton step was not reconsidered/omitted given that this process is known to facilitate oligomer formation. Do the authors have experience with aggregation studies using α-synuclein that has not undergone lyophilisation and are able to comment on the influence of this step in the protocol?

The authors make note of several degradation products affecting their aggregation reactions, which is why they employ a much more thorough purification protocol. However, they also point out that some of the degradation products found at the end of their reaction could form during the reaction itself. Unfortunately, they never investigate this further. In particular, it would be very useful to know if different aggregation conditions (pH, salt, agitation) lead to different and characteristic degradation patterns. HPLS/mass spec of the supernatant at the end of each aggregation reaction would have been a very insightful thing to do.

With respect to degradation products, in this work a NΔ4-variant is produced to mimic a disease-relevant degradation product and indeed it is found to alter the structural outcome even at low relative concentrations (5%). Have the authors investigated the minimal fraction of the NΔ4 variant necessary to still influence the structural outcome of the predominant WT protein? This type of analysis could have significant relevance to disease-related analysis, where several variants (truncations and PTM variants) are present in trace amounts.

While on this topic, the authors note that in several of their type 5 fibrils, they find unresolved peptide fragments in their cryo-EM structures. Can the authors speculate if these fragments are indeed peptide degradation products or residues wrapping around the fibril originating from the fibril-incorporated protein?

In this work, the authors have performed an extensive study of α-synuclein polymorphism. However, despite generating what is likely the largest single data set of fibril structures, they perform very little quantitative analysis of their data. It would be interesting to analyse the relative abundance of fibril polymorphs produced in each reaction. Perhaps from the particle-picking data it could be estimated the relative abundance of each polymorph as well as non-resolved fibrils to generate a more nuanced view of polymorphism beyond overall classifications of the resolved structures. Indeed, from such data it could also be studied if certain protofilaments are more prone to pair in asymmetric fibril structures over others or if fibril asymmetry can be attributed to random pairing of protofilaments in accord with their abundance. This latter point is particularly interesting for the type 1 fibrils. Perhaps, the propensity of α-synuclein to form specific symmetries could also be estimated.

The authors note that pH is a strong factor in determining polymorph selection. This does indeed appear to be the case, but other parameters do not appear to show any clear trend. Have the authors investigated the influence of aggregation parameters (agitation, duration) on structural outcomes systematically or quantitatively, such as with principal component analysis? Indeed, they also find that some fibril types that otherwise are not compatible at the same pH appear to co-exist when the shaking parameter is modified. Are the authors then confident in the claim that pH is a deterministic parameter?

It is evident from this and other work that amyloid aggregation is highly sensitive to kinetic effects. It is therefore curious that the effect of protein concentration and reaction time has not been systematically investigated. The authors have some data studying dilution series (Figure 6A) and different reaction times (reaction 56 & 57). Could the authors comment on the effects of these two parameters, and might there be more information touching upon this that could be highlighted in this work?

The authors state that this work likely underreports fibril polymorphisms in samples due to population size or data quality challenges. Could the authors, based on their extensive experience, try to quantify this statement?

Additionally, the authors point out that the current framework for classifying α-synuclein fibril polymorphism is not sufficient to describe the real complexity of this protein system. However, they do not seem to address some of the recent literature aiming to solve such issues (see Scheres 2026, Connor et al. 2025, Milchberg et al. 2025 & Price et al. 2025).

Was any biophysical/biochemical analysis performed of the many structures produced here, such as CD spectroscopy, Proteinase K digestion, dye binding or FTIR, which could act as low-resolution structure identifiers and might help to retrospectively explain some findings in the older literature? Such data would be very useful for the vast majority of researchers, who do not have access to cryo-EM.

Reviewer #1 (Public review):

Summary:

The authors have assembled the genome of four local chicken breeds from China and analysed their gene content. They come to the conclusion that thousands of genes present in the current reference genome of chicken have become pseudogenized during chicken evolution and domestication. They argue that their study provides strong support for the importance of the "less-is-more" hypothesis for adaptive evolution.

Strengths:

The paper provides medium-quality genome assemblies for four individuals representing four local populations of chickens and analyses their gene content.

Weaknesses:

They have not excluded the possibility that the high rate of putative pseudogenes reflects the presence of errors in gene models, in particular in GC-rich microchromosomes that are challenging to assemble correctly. The paper contains no genotype-phenotype analysis, which means that the adaptive significance of a high rate of pseudogenization, if it exists, is unknown.

Reviewer #1 (Public review):

Summary:

The CATCHR complexes are a family of five multisubunit complexes that act in vesicle tethering in several key transport steps. COG and GARP act at the Golgi, EARP acts on early endosomes, EXOCYST acts in transport to the cell surface, and DSL1 acts on the endoplasmic reticulum (ER). The authors have used in vivo proximity biotinylation and mass spectrometry to look for new neighbours of three of these complexes, COG, GARP, and EARP (despite the title, only two of the three are on the Golgi). The authors then follow up two of the hits, CCDC186 and WWOX, with more directed experiments.

Strengths:

The strength of the paper is that proximity biotinylation is of a high standard. To avoid overexpression, the authors express TurboID-tagged CATCHR subunits in cell lines from which the genes have been deleted. This allows them to confirm that the tagged proteins are functional and correctly located. Mass spectrometry is used to identify the proteins biotinylated in each cell line with four replicates, and the data are clearly presented in figures and supplementary tables. The authors make a good choice of proteins to follow up, as both CCDC186 and WWOX appear potentially interesting.

Weaknesses:

Overall, although the paper is based on a high-quality initial set of data, it seems somewhat incomplete and preliminary. There is undoubted value in presenting a through if descriptive set of in vivo proximity labelling data for a comprehensive overview of proteins or complexes. However, in this case the authors have only addressed three of the five CATCHR complexes, and so it is not a complete overview. It was also somewhat unclear why they examined VPS52 and VPS53, as these are present in both GARP and EARP, which adds some ambiguity, even if they did at least provide useful confirmation of some of the hits with EARP. Of course, a proximity biotinylation analysis does not need to cover all members of a family if it generates substantial biological insight.

However, the investigation of CCDC186 and WWOX does not provide significant insight into either function or mechanism. CCDC186 has already been identified in C. elegans as a protein involved in dense core vesicle biogenesis (CCCP-1, as the authors acknowledge), and work in C. elegans and mammalian cells has already linked it to EARP function. Less has been published on WWOX, but all that is found here are some small changes in Golgi appearance and glycosylation when it is reduced by RNAi. Thus, the paper falls between two stools: it is neither a comprehensive application of proximity biotinylation to the CATCHR family, nor is it the application of proximity biotinylation to reveal new insight into membrane traffic. I feel that for a broad-interest journal such, it should be one or the other of these.

Reviewer #1 (Public review):

Gary, Soret et al., present an interesting and ambitious study investigating the cellular and signaling mechanisms by which GDNF induces enteric neurogenesis in a disease model of HSCR. The manuscript combines scRNA-Seq, pharmacological inhibition, and several lineage-tracing strategies. The lineage tracing experiments in particular are technically impressive and clearly represent a substantial amount of work. The figures are generally beautiful and high quality, and the biological question is an important one.

However, while I found the study interesting, I also think that several of the major conclusions are substantially stronger than what the current data support. In particular, the scRNA-Seq dataset that the study is founded on is difficult to interpret because of the RFP-based enrichment strategy, the lack of WT reference controls, and the very non-stringent FACS gating. Several mechanistic claims are also based primarily on expression patterns or sequencing results.

Major concerns:

(1) The G4-RFP based enrichment strategy raises some concerns. The authors note that 88-90% of SOX10+ glial cells (where did this number come from, it doesn't seem to match the range in the bar graph?) and only 70% of GDNF-induced neurons. They then sort in "yield" mode using a non-stringent gating strategy, but do not provide the flow graphs in the supplements for interpretation. Consistent with this, the initial dataset contains multiple non-ENS populations, including lymphoid, myeloid cells etc, suggesting that their strategy, in addition to missing cell populations, additionally includes potential negative cells based on background fluorescence.

(2) It's not clear to me why the authors did not include a wild-type control for comparison. Due to the RFP-enrichment strategy, it is additionally difficult to compare to integrated with scRNA-seq datasets. The comparison seems important because the central question is not only whether GDNF induces neurons in the mutant colon, but whether the induced cells and associated populations resemble those found in a normal ENS.

(3) The proportional changes in Figure 2 are hard to interpret. The authors write that GDNF treatment leads to an enrichment in enteric neurons, "at the expense of" SCPs. This seems to be a strange conclusion or writing, unless the authors are suggesting that certain cell populations are additionally depleted by GDNF treatment. I think the authors should provide stronger support, or dial down on conclusions based on cluster proportions, given the sorting strategy.

(4) Some of the mechanistic conclusions are far too strong for the evidence. For instance, the claim that GDNF signals through GFRa1/2 based on only expression UMAPs is not justified. The authors should at least confirm some of the major findings via smFISH (HCR or RNA-Scope), and dial down the mechanistic claims. The pharmacological data is more supportive but still indirect. This section would be stronger if the authors validated NCAM1/FAK activation in the specific progenitor populations proposed to respond to GDNF.

(5) The inhibitors are administered during the same P4-8 window as GDNF. Given that the authors report cellular-level responses as early as 6 hours post GDNF treatment, it is important to know whether the inhibitors were already active at the time of GDNF administration. Why were the inhibitors not administered prior to the start time of GDNF treatment?

(6) The authors draw inferences and conclusions based on IHC images, but do not provide any details on the analysis procedures. For example, in Figure 3, the authors interpret changes in NCAM and FAK expression level. However, it does not appear that there are notable differences in intensity between the two timepoints. There are however, differences in signal coverage. Without knowing what was actually measured and quantified, it is not possible to interpret the results. Please provide the necessary information for all experiments in the methods section.

(7) The final results section introduces one of the more surprising claims in the paper, that a non-neural crest-derived progenitor contributes to regeneration, but the section ends quite quickly and abruptly after introducing the observation. The authors should provide additional validation or interpretations of the data.

Reviewer #1 (Public review):

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

Summary:

From a big picture viewpoint, this work aims to provide a method to fit parameters of reduced models for neural dynamics so that the resulting tuned model has a bifurcation diagram that matches that of a more complex, computationally expensive model. The matching of bifurcation diagrams ensures that the model dynamics agree on a region of parameter space, rather than just at specially tuned values, and that the models share properties such as qualitative features of their phase response curves, as the authors demonstrate. A notable point is the inclusion of extracellular potassium concentration dynamics into the reduced model - here, the quadratic integrate-and-fire model; this is straightforward but nonetheless useful for studying certain phenomena.

Strengths:

The paper demonstrates the method specifically on the fitting of the quadratic integrate-and-fire model, with potassium concentration dynamics included, to the Wang-Buzsaki model extended to include the potassium component. The method works very well overall in this instance. The resulting model is thoroughly compared with the original, in terms of bifurcation diagrams, production of various activity patterns, phase response curves, and associated phase-locking and synchronization properties.

Weaknesses:

It is important to note that the proposed method requires that a target bifurcation diagram be known. In practical terms, this means that the method may be well suited to fitting a reduced model to another, more complicated model, but is not likely to be useful for fitting the model to data.

Reviewer #1 (Public review):

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

Summary:

In this study, the authors examine what happens when two facultative endosymbionts, Rickettsiella viridis and Regiella insecticola, are introduced into a novel aphid host, the Russian wheat aphid (Diuraphis noxia). They ask whether these introduced symbionts affect aphid performance, plant damage, alate production, dispersal, plant defense responses, and symbiont dynamics. The main result is that the two symbionts have contrasting effects: Rickettsiella tends to increase plant damage and reduce dispersal-related traits, whereas Regiella tends to reduce plant damage and aphid population growth, with less evidence for an effect on dispersal.

Strengths:

The manuscript presents successful establishment of stable transinfected populations of an agriculturally important aphid species, which is a substantial technical achievement in itself. I also appreciated that the authors examined the system across several experimental contexts, including different host plants, mixed cages at two temperatures, whole-plant assays, and a mesocosm dispersal experiment, rather than relying on a single laboratory setup. Taken together, these experiments provide a useful and reasonably convincing demonstration that novel symbiont associations can generate contrasting phenotypes in this system.

Reviewer #1 (Public review):

[Editors' note: This revised version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have satisfactorily addressed the substantive comments raised in the previous round of review. The qualifications and limitations are now more clearly acknowledged in the revised manuscript.]

Summary:

This work compiles a comprehensive atlas of ncORFs across mammalian tissues and cell types, derived from reanalysis of ~400 public ribosome profiling datasets. The authors then evaluate cross-species conservation and functional signatures, proposing that evolutionarily ancient ncORFs tend to have higher translation potential, stronger expression, and closer relationships with canonical coding sequences.

Strengths:

In general, the study provides a large-scale and timely resource of annotated ncORFs, which could be broadly useful for the community. The authors collected ~400 public ribosome profiling datasets for annotations of ncORFs, which, to my best knowledge, is the largest collection of data for such purpose. The catalog could facilitate future investigations into ncORF biology and broaden understanding of the coding potential of the "non-coding" genome.

Comments on previous version:

The authors have made efforts to address most of the previous concerns, and several points have been clarified or improved in the revision. However, in a number of cases, the responses rely more on acknowledgment and reframing rather than substantive analytical strengthening. Overall, the manuscript is improved, particularly in terms of clarity, transparency, and positioning of claims. I support its publication and look forward to seeing how the field engages with and discusses these claims.

Reviewer #1 (Public review):

Summary:

The manuscript entitled "Autonomic reflex plasticity associates with time-dependent SUDEP susceptibility in a murine model with hyperactive stress circuits" by Dr. Saunders and colleagues combined a traditional mouse model of SUDEP, ventral intrahippocampal kainite (vIHKA) injection, with a genetic model of chronic hyperactivity of central corticotropin-releasing hormone (CRH) neurons (Kcc2/Crh) that further increases the risk of SUDEP in the weeks following seizure.

Strengths:

Their results show during spontaneous seizures Kcc2/Crh mice had more pronounced reflex-like ictal bradycardias compared to WT controls that notably occurred prior (~10 sec) to seizure termination and had greater autonomic disturbances compared to WT controls, including a pronounced serotonin-mediated Bezold Jarisch reflex. These results show chronic hyperactivity of central corticotropin-releasing hormone (CRH) neurons (Kcc2/Crh) increased autonomic disturbances and risk of SUDEP in a kainic acid model of epilepsy.

Weaknesses:

This study could be improved with a more thorough assessment of heart rate, blood pressure and breathing during and following the seizures, and in particular the fatal event. It is unclear if the bradycardias were spontaneous, or a result of preceding central or obstructive apneas, oxygen desaturations, hypercapnia, arrhythmias, or other possible triggers.

Considerable prior work in the literature suggests SUDEP could be mediated, in some patients, by a burst of parasympathetic activity to the heart. Were the heart rate changes in these animals during seizures inhibited or blocked by atropine, or atenolol? The injection of the 5HT agonist phenylbiguanide into the right jugular is not a selective approach for activating the Bezold Jarisch Reflex (BJR) which is caused by increased activity of intracardiac sensory neurons (generally activated with ischemia or a combination of low preload with high contractility). The results should be interpreted more cautiously, as a response to systemic administration of phenylbiguanide only.

Reviewer #1 (Public review):

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

Summary:

This work asks the question of how different organelles and structures in the apicomplexan parasite Toxoplasma gondii are recycled and/or segregated to the daughter cells during cell replication. In particular, they consider an unusual cell structure called the residual body that links replicating cells during the intracellular infection stage of this parasite. The residual body has historically been considered a 'dumping ground' for unnecessary relics of the mother cell during division, but this notion is increasingly being revised. Indeed, cell replication in Toxoplasma is often misinterpreted as cell division (cytokinesis), but in fact, the cell replicates its organelles and structures to multiple 10s of copies in seemingly distinctly formed daughter cells, but cytokinesis is delayed for many such cycles and typically only occurs simultaneously with parasite egress from its host cell. The residual body is, in fact, the connection between these pre-cytokinetic replicated daughters, and effectively, this is still a single cell at this stage. The authors have previously shown that an actin network extends through the residual body between these daughter cells, and ER and mitochondria common to all cells are also linked through this structure. This study examining the fates of organelles during cell replication is timely for continuing our understanding of how this fascinating component of the cell participates in these processes. The authors use Halo-tags as their principal tool to track discrete populations of proteins, labelling their organelle locations, and this provides beautiful insight into these processes.

Strengths:

Using dyes conjugated to Halo tags this work elegantly tracks the fates of proteins synthesised by an original 'mother' cell over several replication cycles of pre-cytokinetic 'daughters'. Using this tool, they show that some organelles are made intact just once and that some of these can be subsequently sorted to the daughters (micronemes and rhoptries) while others are dismantled (IMC) and the daughters must make their own. A third set of organelles (largely synthesis, sorting and metabolic compartments) are divided and inherited, and new daughter-synthesised proteins are added to the preexisting maternal proteins in these structures. A role for actin and myosin is clearly demonstrated for micronemes and rhoptries, and this correlates with their relatively late inheritance into the developing daughters. Overall, this work gives clarity to the behaviours of several cell structures during replication and paves the way to better understanding the mechanisms that drive the differences between structures and the universality of these processes in other apicomplexan parasites. In particular, this study shows that the residue body is a region of the cell syncytium that organelles can be actively transported from. Therefore, it is a space that can actively contribute to the segregation of the late segregating micronemes and rhoptries.

Reviewer #1 (Public review):

Summary:

This study demonstrates that nutrient resorption efficiency (NuRE) in Phragmites australis is genetically canalized rather than plastic to salt stress. Using 110 genotypes in a common garden, the authors show that intraspecific variation in NuRE is explained by phylogeographic lineage, ecotype, and latitude, not by effective salinity. Element specific regulatory strategies further reveal how N, P, and K resorption are differentially controlled. At the population level, this is an important study that fundamentally advances our understanding of plant functional trait evolution and its implications for ecosystem nutrient dynamics under global change.

Strengths:

This study is the first to demonstrate genetic determination of a key nutrient conservation trait under effective salt stress in a widespread macrophyte, directly testing the 'plastic acclimation versus inherent conservatism' paradigm in a non-nutrient stress context. The experimental design is rigorous: each genotype was paired across control and salt treatments, and multilevel stress effectiveness (metabolomics, biomass, Na accumulation) was confirmed before evaluating NuRE. The large sample size of a macrophyte and dual classification (phylogeography + ecotype) allow robust disentangling of genetic versus plastic sources of variation.

The analysis comprehensively tests three resorption control hypotheses using appropriate SMA regression, revealing element specific and condition dependent patterns. The latitudinal gradient and variation partitioning provide strong evidence that genetic origin and geographic context outweigh short term plasticity, with important implications for predicting ecosystem nutrient cycling under global change. This study provides a clear empirical demonstration that a key nutrient conservation trait can remain homeostatic under non nutrient stress, and that intraspecific variation is primarily a product of population differentiation rather than short term plasticity.

Weaknesses:

First, the salinity treatment spanned only one growing season. The conclusion of genetic canalization therefore specifically refers to the absence of plasticity to an acute salt shock. Whether long term, multigenerational chronic salinity could act as a selective agent or induce transgenerational plasticity remains an open and interesting question for further research. Likewise, the physiological mechanisms underlying the observed lack of plastic increase in NuRE (for example, phloem loading or senescence gene expression) are not directly resolved, leaving some inference about trade-offs versus true unresponsiveness. These points do not weaken the study's main conclusion. Instead, they suggest productive future directions, such as longer-term field manipulations and targeted molecular investigations.

Second, the test of nutrient limitation control relies on resorbed N:P and N:K ratios as proxies, an established but indirect approach. Direct nutrient addition experiments would provide stronger causal evidence. Also, the metabolomic analysis is used primarily to validate stress effectiveness; deeper integration of specific metabolites with NuRE variation across genotypes could have offered mechanistic insights but was not pursued. Additionally, the potential collinearity between ecotype and phylogeographic lineage among Chinese populations is not quantitatively addressed. None of these considerations undermine the main finding, which is supported by a robust experimental design and widely accepted analytical approaches.

Comments on revised version.

The author carefully revised the parts that might cause confusion.

Reviewer #1 (Public review):

Summary:

In this study, the authors trained mice to perform a memory-guided navigation task, in which they must navigate to a previously cued arm after a delay period. They optogenetically inhibited the dorsal hippocampus or mPFC (targeting PL) in different task epochs. They found that for both regions, inactivating at the beginning of the navigation epoch impaired performance and induced mice to revert to habitual side biases. Inactivating during other epochs, including a delay period before the navigation phase, had little or no impact on behavior. The relationship between trial duration and behavioral performance was differentially impacted by hippocampal and mPFC inactivation, suggesting that the nature of the deficits was somewhat different.

Strengths:

The effects of perturbations are robust across animals and generally convincing. The lack of effect at some task epochs serves as a nice internal control. The finding that hippocampus and mPFC inactivation produced subtly different effects is interesting.

Weaknesses:

The simplicity of the behavior makes it difficult to resolve how exactly the hippocampus and mPFC contribute to working memory. Also, the language does not always reflect the trends in the data: the authors claim that optogenetic perturbations cause mice to repeat previous choices, but the data show that perturbations increase the likelihood of choosing a preferred side (which is left for most mice). A side bias is not the same as choice repetition. This has implications for interpreting the nature of the behavioral effects.

Reviewer #1 (Public review):

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

Summary:

This manuscript uses sci-L3-Strand-seq to map sister chromatid exchange events following CRISPR/Cas9-induced DNA damage. Because exchanges between identical sister chromatids are largely invisible to conventional sequencing, the study addresses an important blind spot in the assessment of genome editing outcomes. The authors compare single-locus Cas9 cleavage, simultaneous targeting of 237 repetitive genomic sites, and Cas9 nickase variants. They further use reciprocal daughter-cell pair analysis to ask whether Cas9-associated SCEs are copy-neutral or linked to larger structural alterations. Overall, this is a valuable study that introduces an important additional layer to the analysis of CRISPR/Cas9 repair outcomes. The central finding that Cas9-induced DSBs can trigger frequent local SCE is well supported and likely to be of broad interest.

Strengths:

The major strength of the manuscript is the application of a strand-resolved, single-cell method to a question that is difficult to address with standard genome sequencing. The evidence that a single Cas9-induced DSB can trigger strong local SCE is compelling in concept and supported by multiple guide RNAs targeting distinct loci. The reported on-target SCE frequencies, reaching up to 41%, suggest that inter-sister exchange is a substantial and underappreciated outcome of Cas9 cleavage.

Of particular interest is the comparison between single-site and multi-site targeting. The finding that 237 programmed Cas9 targets produce only mild bulk enrichment of on-target SCE but stronger enrichment in a subpopulation of cells with elevated SCE burden is interesting and may have wider biological implications, particularly if the findings extend beyond Cas9-induced SCE to spontaneous SCEs.

The reciprocal daughter-cell pair analysis is another notable feature of the study. The observation that some Cas9-associated SCEs are accompanied by structural alterations could challenge the assumption that SCE after a programmed break reflects error-free homologous recombination.

Reviewer #1 (Public review):

In this manuscript, the authors present ClustIRR, a computational tool that analyzes multiple TCR repertoires together, instead of one at a time. It builds one shared similarity graph across all the repertoires, then finds communities (CJs) on that graph that can be compared across samples. Building one shared graph across repertoires, rather than clustering each repertoire on its own, is a real improvement over existing tools. However, there are a few concerns that need to be addressed.

(1) The Introduction motivates ClustIRR by contrasting it with beta-binomial regression, Fisher's exact test, and scCODA/tascCODA (lines 62-77), but none of these are actually run on the same data in the Results. Could the authors include a direct comparison, e.g., applying a standard beta-binomial or Fisher's exact test to the Dataset 1 CJ occupancy matrix, to show the Bayesian model gives a lower false-positive rate or better-calibrated intervals than the alternatives it's positioned against?

(2) Prior predictive and posterior predictive checks are both reported as "(data not shown)" (lines 644, 728). Since the manuscript's central claim is rigorous, uncertainty-aware inference, it would help to include these diagnostic plots, along with Rhat and ESS values, in the supplement rather than stating they were checked.

(3) With 7,505 CJs tested simultaneously for differential occupancy in Dataset 1 alone (Figure 1 legend), what is the expected false discovery rate under the non-overlapping-HDI criterion used throughout? A short discussion of multiple-comparisons correction, or an argument for why it isn't needed under this framework, would strengthen the statistical claims.

(4) Line 115 states the Dataset 1 joint graph produced 10,301 CJs, of which 3,038 were singletons, leaving 7,263 non-singleton CJs. The Figure 1 legend reports 7,505 CJs used for the β modeling. Could the authors clarify how these two numbers relate - whether some singletons were included in the model, or a filtering step was applied that isn't described in Methods?

(5) The Methods section states that archival pretreatment tumor tissue was available for four patients (Pt4, Pt32, Pt36, Pt38; line 531), but the T+/T- DCJ analysis in Fig. 3B-C is only shown for Pt4. Was this analysis attempted in the other three patients? Extending it, even partially, would substantially strengthen the claim that contracting DCJs are enriched for tumor-infiltrating TCRs, which is currently based on a single patient.

(6) Dataset 1 was generated by deliberately stimulating T cells with EBV or MART1 antigen, so recovering EBV/MART1-annotated CJs from VDJdb is closer to a positive control than a blinded validation. Do the authors have, or could they obtain, any independent confirmation (e.g., tetramer data or an orthogonal cohort) for the CJs with large β that lack VDJdb annotation (orange dots, Figures 1B-C)?

Reviewer #1 (Public review):

This meta-analysis addresses long-standing questions about the reliability and interpretation of choice probability in macaque visual areas, and provides some important findings (e.g., the cross-study consistency of the CP-sensitivity relationship, V1 distinctiveness). However, the evidence for several claims is incomplete: the analysis does not consider the statistical dependence of data points from the same studies and monkeys, and both the bistable-stimulus effect and the stimulus-duration effect rely on interpretive assumptions.

Strengths:

The paper's transparency about its own limitations is a genuine strength. Several sections of the paper and the supplement report null results (task exposure, lapse rate, eccentricity) rather than omitting them. This kind of self-scrutiny is uncommon in meta-analyses and substantially increases confidence in the parts of the analysis that do hold up.

Weaknesses:

(1) No mixed/hierarchical statistical models for nested data. The paper considers 150 data points from 59 studies and treats them as independent samples, though many share monkeys and brain areas. This reduces the confidence in the reported p-values. A standard way of dealing with this would be to use mixed-effect models with random intercepts rather than OLS.

(2) Evidence for one of the main findings in the abstract ("First, CPs were higher in tasks involving bistable percepts, reinforcing the link between CP magnitude and subjective perception.") is weak. This effect relies entirely on studies using bistable rotating cylinder stimuli performed in a single lab (lines 702 - 711). I would suggest making this more explicit in the abstract / discussion and in Figure 8b,c.

(3) The interpretation of main drivers of CP is unclear. The discussion summarizes the 4 main drivers of CP as "four systematic drivers of this variability: neuronal sensi758tivity, brain area, stimulus duration, and task type." The independent contribution of task type is however, questionable. In line 623, it is stated that the difference between coarse and fine discrimination can be entirely explained by the difference in sensitivity (explained possibly by differences in optimizing the stimuli). Again, detection tasks (line 658) show a trend for higher CP because most studies used tailored stimuli from single-recording experiments. Bistable task: see point 2. Thus, all "task effects" can be attributed to confounds, and the claim of the "four drivers of CP" should be revised.

(4) The paper could be improved by a Discussion that synthesizes the results in a concise manner. Now it seems more like a re-iteration of the results. Overall, I appreciate that the paper is thorough and discusses many of the caveats. However, those are somewhat buried in the long subsections, and I fear that the quick reader may walk away with a stronger impression of "four robust independent drivers" than the text, read carefully, actually supports.

(5) Datapoints are not weighted according to their standard error (common practice in meta-analysis is inverse-variance weighting). The concern is that underpowered studies with high variance (e.g., due to a low number of recorded neurons) have the same impact as well-powered studies, and this may change some of the estimates. For example, Supplementary Figure 4 shows that mean CP values decrease with statistical power of the study, consistent with the concern. If SEMs are not available, could the authors show the robustness of the results by weighting by sample size as a partial check?

(6) Interpretation of feed-forward vs. feedback origin of CP [Disclosure: I am an author of Wimmer et al. 2015.]. This paper presents a mechanistic network model of area MT and a decision area that decomposes CP into two components with distinct time courses, and, directly relevant to Section 2.6, shows how a combination of an early feedforward and a late feedback component can produce a roughly time-invariant (flat) CP. This is a specific, quantitative instance of the "sustained plateau" pattern the authors themselves note is inconsistent across studies (lines 480-486) but don't develop further. Engaging with this model in Section 2.1/2.6 would let the authors contrast their duration-effect interpretation against an explicit dynamical model rather than the generic feedforward/feedback dichotomy in Figure 7a.

(7) Reaction-time experiments. I am worried that differences in CP in RT vs. fixed duration tasks (Supplementary Figure 12) could have an influence on the main regression analysis (because RT experiments are mostly from detection tasks, and because RT experiments presumably include less of a post-decision period). Could this factor be included in the main analysis?

Reviewer #1 (Public review):

Summary:

The authors investigated somatosensory processing along the afferent somatosensory pathway (cuneate nucleus, thalamus, S1) in a group of spinal cord injury patients and a group of controls. They propose that reduced motor function in SCI patients would reduce bottom-up activity; thus, recorded activity in SCI patients would reflect top-down modulation of overt or attempted movements.

Strengths:

(1) Strong methods.

(2) Experimental and control groups.

(3) Strong writing.

(4) Results well presented.

(5) Appropriate statistics.

Weaknesses:

Some results (or lack of) cast doubt about the ability of the used technique (3T fMRI) to detect the desired effects (bottom-up vs top-down activity).

Reviewer #1 (Public review):

Summary:

This manuscript uses a valuable dataset of simultaneous LC single-unit recordings and pupillometry in awake monkeys to examine one aspect of the relationship between LC activity and pupil diameter: whether baseline LC activity predicts evoked pupil and whether baseline pupil predicts evoked LC. These relationships are largely absent in the present dataset, and the authors conclude that this type of prediction is not reliable.

Strengths:

This is a valuable dataset of simultaneous LC single-unit recordings and pupillometry in awake monkeys, the within-modal and within-epoch analyses are sound. The new results further caution the use of pupil diameter to infer LC activity.

Weaknesses:

There is an obvious rationale for asking whether baseline LC relates to baseline pupil or evoked LC relates to evoked pupil. It is also obvious to ask about the relationship between baseline and evoked LC activity, and between baseline and pupil responses. However, the rationale for the cross-modal and cross-epoch analysis is not clear. Why should one expect baseline LC to predict evoked pupil, or baseline pupil to predict evoked LC? What is the biological importance of such predictions? These analyses simultaneously change the modality and the temporal domain.

Furthermore, some recent studies, which are not referenced in this manuscript, showed variability in the relationship between pupil and LC within the same epoch, and that tonic and phasic pupil responses could be regulated by different inputs to LC. Given that the pupil-LC coupling is readily imperfect and potentially controlled by different cellular and circuit mechanisms, it is not surprising that their cross-epoch relationship is even more variable.

One main analysis that correlated baseline pupil with evoked LC showed statistically different results between the two monkeys, raising the question of to what extent a general claim for the cross-modal cross-epoch analysis can be made.

Reviewer #1 (Public review):

Summary:

The authors asked whether neurofeedback during competing continuous speech can help to modulate the attention-related N1-component in the temporal response function (TRF), which is an event-related-response-like estimate of the phase-locked EEG activity following the envelope. The research question is relevant because it asks to what degree the strength of attention can be controlled beyond the binary decision to attend or ignore something, and whether this control is beneficial for the behavioral outcome.

Strengths:

(1) Sample size of 56 participants.

(2) Control group with sham feedback.

(3) Novelty: Under-explored field of neurofeedback in selective speech tracking.

(4) Pragmatic and reasonable methodological decisions.

(5) Transparent results not hiding the fact that effect sizes are small.

Weaknesses:

Besides some need for clarification, I could only find one methodological weakness, which the authors discuss anyway:

(1) Overall, speech tracking-based neurofeedback may lead to more robust results, because the N1-extraction does not have to be handcrafted and all components would be taken into account. As the authors state, the P2-component has been related to effort, and this may provide more "room to play" for voluntary modulation.

The following "weaknesses" are related to the impact of the results:

(2) Non-translating effects to post-training trials, neither neurally nor behaviorally.

(3) Neurofeedback-related Modulation of N1

Reviewer #1 (Public review):

This work provides a valuable toolkit for endogenous isolation of projection neuron subtypes. With further validation, it could present a solid method for low-input ribosome affinity purification using a ribosomal RNA (rRNA) antibody. The experimental evidence for the distinct ribosomal complexes is limited to this method and indirect support from complementary analyses of pre-existing data. However, with additional experimental data to support the specificity of ribosomal complex pulldown and confirmation of the putative ribosomal complex proteins of interest, the study would provide compelling evidence for translation regulation of neuronal development through compositional ribosome heterogeneity. This work would be of interest to neuroscientists, developmental biologists, and those studying translational networks underlying gene regulation.

Strengths

(1) This in vivo labeling of specific projection neurons and ribosomal rRNA affinity purification method accommodates a low input of <100K somata per replicate, which is useful for the study of neuronal subtypes with limited input. In principle, this set of techniques could work across different cell types with limited input depending on the molecule used for cell type labeling.

(2) The authors are also able to isolate endogenous neurons with minimal perturbation up to the point of collection, preserving the native state for the neuron in vivo as long as possible prior to processing.

(3) This study identified over a dozen potential non-ribosomal proteins associated with SCPN ribosomal complexes, as well as a ribosomal protein enriched in CPN.

Limitations

(1) In this study, the authors address the advantages of their ribosomal complex isolation method in SCPN and CPN against RPL22-HA affinity purification. While this does show more pull down of the ribosomal RNA by the Y10B rRNA antibody, the authors claim this method identifies cell-type specific ribosomal complex proteins without demonstrating a positive control for the method's specificity. There are very limited experiments to truly delineate how "specific" this method is working and whether there could be contamination from other complexes bound by the antibody. I see this as the major limitation that should be addressed. To boost their claims of capturing cell-type specific ribosomal complexes, the authors could consider applying their rRNA affinity purification pipeline to compare cell-types with well-characterized ribosome-associated proteins, like mouse embryonic stem cells and HELA cells. The reviewer can completely appreciate the elegance in the neural characterization here, but it seems there needs to be a solid foothold on the specificity of the method, perhaps facilitated by cell types that can be more readily scaled up and tested.

(2) The authors followed up on their differentially enriched ribosomal complex proteins by analyzing ribosome association of these proteins in external datasets. While this analysis supports the ribosome-association of these proteins, there is limited experimental validation of physical association with the ribosome, much less any functional characterization. The reciprocal pulldown of PRKCE is promising; however, I would recommend orthogonal validation of several putative ribosomal complex proteins to increase confidence. Specifically, the authors could use sucrose gradient fractionation of SCPN and CPN, followed by western blot to identify the putative interaction with the 80S monosome or polysomes. This would also provide evidence towards the pulldown capturing association with mature ribosome species, which is currently unclear. This experiment would provide substantial evidence for the direct association of these non-ribosomal proteins with subtype-specific ribosomal complexes.

(3) The authors state interest in learning more about the differences underlying translational regulation of projection neuron development. This method only captures neuronal somata, which will only capture ribosomes in the main cell body. There are also ribosomes regulating local translation in the axons, which may also play a critical role in axonal circuit establishment and activity. These ribosomal complex interactions may also be rather transient and difficult to capture at only one developmental stage. Therefore, this method is currently limited to a single developmental snapshot of ribosomal complexes at P3 within the main cell body. It would be exciting to see extended utility of this method to sample neurites and additional developmental stages to gain further resolution on the developmental translation regulation of these projection neurons.

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

The authors introduce a unique pipeline of techniques to identify cell-type specific ribosomal complex compositions. With more validation, there is certainly potential for those studying neuronal translation to leverage this method in limited primary cells as an alternative to existing methods that do not rely on ribosomal protein tagging, such as ARC-MS (Bartsch et al., 2023), RAPIDASH (Susanto and Hung et al., 2024), and RAPPL (Nature Communications, 2025).

Comments on revised version.

We thank the authors for their thorough response to our comments. The revised manuscript satisfactorily addresses most reviewer comments through clarification and expanded discussion, although we believe some important limitations remain. In particular, we continue to view experimental validation of the identified ribosome-associated proteins as an important component of introducing this methodology to the field, rather than work that falls beyond the scope of the study. The authors have acknowledged that these experiments are future directions, and it is clear they plan to pursue additional validation outside of the current manuscript. Given their emphasis that the primary contribution is the development of a methodological framework, we believe the work may be appropriately framed as a Tool and Resource article. Such positioning would better align reader expectations with the manuscript's strengths as a technical advance while recognizing that further validation and functional characterization will be needed in future studies. Despite these limitations, I believe the manuscript makes a valuable methodological contribution.

Reviewer #3 (Public review):

Summary:

This manuscript presents a well-designed study examining human adaptation to room acoustics, building on prior work. The psychophysical results are convincing and add meaningful knowledge to our understanding of reverberation learning. The transcranial magnetic stimulation (TMS) component shows a role of prefrontal cortex in this listening task, targeting dorsolateral prefrontal cortex (dlPFC). Cautious interpretation of the TMS results is warranted, especially given the modest statistical effects, the fact that the main TMS result of interest is a null result, and the limited ability of TMS to precisely target dlPFC in individual subjects. A surprising and interesting finding in the study is that listeners performed the speech recognition task more poorly in anechoic conditions than in those with naturalistic levels of reverberation. This is likely due to contributions of spatial release from masking provided by reverberation acoustics, which may counteract the detrimental effects of reverberation on speech perception itself. Overall, the experiments are well performed and clearly presented, improving our understanding of how the brain copes with reverberant environments.

Strengths:

(1) Well designed acoustical stimuli and psychophysical task.

(2) Comparisons across room combinations is well conducted.

(3) Virtual acoustic environment is impressive and applied well here.

(4) Timely study with interesting behavioural results.

(5) Causal evidence of a role for dlPFC in reverberation learning.

Weaknesses:

(1) Poorer performance in anechoic environments than some reverberant environments suggests and interplay of spatial release from masking and speech intelligibility that are not fully unpicked here. This could be controlled in future experiments, for example by comparing monaural and binaural listening conditions.

(2) Lack of evidence for targeting TMS to dlPFC in individual participants. This is simply a limitation of the technique which the reader should keep in mind.

(3) Most interesting effect of TMS is a null result compared to a weak statistical effect for "meta-adaptation"

Reviewer #2 (Public review):

The authors initial goal was to demonstrate loss of PG during the slow sporulation process of Myxococcus xanthus, with examination of the PG degradation products in order to implicate possible enzymes involved. Upon finding a predominance of LTG products, they examined sporulation in strains lacking each of the 14 candidate LTGs encoded in the genome, leading to the identification of two sporulation-linked LTGs. An extensive characterization of the roles played by these LTGs. One LTG is responsible for the slow sporulation PG degradation, while another is required for the rapid sporulation process. Interestingly, the "slow" LTG seems to provide an important regulatory brake on the rapid enzyme. Single molecule fluorescent tracking of these enzymes was used to develop a model for their interaction with PG that mimics their observed activity. The rate of PG synthesis activity was also shown to impact the rate of PG degradation, suggesting potential interplay between the synthetic and degradative enzymes.

Strengths:

The genetic analysis to identify sporulation-linked LTGs and their effects on growth sporulation, and spore properties was well done and productive. The fluorescence microscopy to track LTG mobility, presumably tied to activity, produced a convincing argument about the mechanism of regulation of one LTG by another. The authors have responded well to all points of the previous reviews.

Reviewer #1 (Public review):

Summary:

The study from Wu and Turrigiano investigates how disruption of taste coding in a mouse model of autism spectrum disorders (ASDs) affects aversive learning in the context of a conditioned taste aversion (CTA) paradigm. The experiments combine 2photon calcium imaging of neurons in the gustatory portion of the anterior insular cortex (i.e., gustatory cortex) with behavioral training and testing. The authors rely on Shank3 knockout mice as a model for ASDs. The authors found that Shank3 mice learn CTA more slowly and extinguish the memory more rapidly than control subjects. Calcium imaging identified impairments in taste evoked activity associated with memory encoding and extinction. During memory encoding, the authors found less suppressed neuronal activity and increased correlated variability in Shank3 mice compared to control. During extinction, they observed a faster loss of taste selectivity and degradation of taste discriminability in mutants compared to controls.

Strengths:

This is a well-written manuscript that presents interesting findings. The results on the learning and extinction deficits in Shank3 mice are of particular interest. Analyses of neural activity are well conducted and provide important information on the type of impaired cortical activity that may correlate with behavioral deficits.

Weaknesses:

The authors did an excellent job addressing the weaknesses highlighted in my first assessment.

Reviewer #1 (Public review):

Summary:

This is a study which used 7T diffusion MRI in subjects from a Human Connectome Project dataset to characterize the zona incerta, an area of gray matter whose involvement has been demonstrated in a broad range of behavioral and physiologic functions. The authors employ tractography to model white matter tracts that involve connections with the ZI and use clustering techniques to segment the ZI into distinct subregions based on similar patterns of connectivity. The authors report a rostral-caudal organization of the ZI's streamlines where rostrally-projecting tracts are rostrally-positioned in the ZI and caudally-projecting tracts are caudally-positioned in the ZI.

Strengths:

The paper presents robust findings that demonstrate subregions of the human ZI that appear to be structurally distinct using a combination of spectral clustering and diffusion map embedding methods. The results of this work can contribute to our understanding of the anatomy and structural connectivity of the ZI, allowing us to further explore its role as a neuromodulatory target for various neurological disorders.

Weaknesses:

There should be further discussion of the clustering methods employed and why they are appropriate for the pertinent data. Additionally, the limitations of analyzing solely the cortical connections of the zona incerta should be addressed, as anatomical studies of the ZI have shown significant involvement of the ZI in tracts projecting to deep brain regions.

Comments on the latest version:

I reviewed the file and am more than satisfied with the authors responses and edits.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have responded critically to all issues raised in the initial round of reviews.]

Lohse et al. describe an open-source system for laser scanning photostimulation (LSPS) in head-fixed animals. Although similar systems have been developed and used by different groups, Zapit provides an open-source solution requiring few custom parts and minimal coding. This tool can clearly facilitate and speed the adoption of LSPS, particularly for the increasingly used purpose of mapping the effects of focal cortical silencing during behavior. Other potential uses include mapping optogenetically evoked movements and selectively activating genetically labeled neuronal subtypes of interest in the cortex. The design is well thought through, and the presentation is mostly clear and well written.

In general, the more modular such a system is, the better, in terms of compatibility with existing hardware and software that potential users may already have purchased - laser, galvo, and camera in particular.

Reviewer #1 (Public review):

Summary:

Yuan and colleagues present a thorough study of gene activation before and during metamorphosis in sponge larvae, combining in depth analyses of staged transcriptomes and chromatin accessibility profiling (ATACseq). Amongst several very interesting findings, the study reveals that the acquisition of settlement competence, which arises in response to decreasing light at sunset, is characterized by changes in chromatin accessibility that anticipate strong transcriptional shifts occurring as metamorphosis starts. Another notable finding is a set transcription factors amongst the genes strongly up-regulated at the onset of metamorphosis. In addition, larvae exposed to constant light, a condition that stalls metamorphosis, were found to activate metabolic pathways that are not normally expressed in swimming larva, Together the findings provide a rare level of understanding into how environmental conditions can promote deployment of alternative developmental programs in planktonic larvae.

Strengths:

This is a comprehensive and rigorous study of a phenomenon of wide interest. It will inspire researchers working on other species to look for similar, environmentally-driven "anticipatory" epigenetic mechanisms. It also provides a wealth of detailed information on genes, notably transcription factors, that are candidates for involvement in regulating specific metamorphosis transitions - and beyond. The data presented here are thus undoubtedly a rich and valuable resource.

Weaknesses:

It is not always straightforward to connect the conclusion statements in the text to the figures, or to grasp the aims and logic of the workflows.

Reviewer #1 (Public review):

Summary:

A well-presented computational work on how post-translational modifications take place from a thermodynamic and mechanistic point of view.